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OPERATIONSMANAGEMENTINTHESUPPLYCHAINDECISIONSCASES8thEdition.pdf
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Operations Management in the Supply Chain Decisions and Cases Eighth Edition
Roger G. Schroeder Susan Meyer Goldstein Carlson School of Management University of Minnesota
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mheducation.com/highered
OPERATIONS MANAGEMENT IN THE SUPPLY CHAIN: DECISION AND CASES, EIGHTH EDTION
Published by McGraw-Hill Education, 2 Penn Plaza, New York, NY 10121. Copyright © 2021 by McGraw-Hill Education. All rights reserved. Printed in the United States of America. Previous editions © 2018, 2013, and 2011. No part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written consent of McGraw-Hill Education, including, but not limited to, in any network or other electronic storage or transmission, or broadcast for distance learning.
Some ancillaries, including electronic and print components, may not be available to customers outside the United States.
This book is printed on acid-free paper.
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ISBN 978-1-260-36810-9 (bound edition) MHID 1-260-36810-6 (bound edition) ISBN 978-1-260-93700-8 (loose-leaf edition) MHID 1-260-93700-3 (loose-leaf edition)
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All credits appearing on page or at the end of the book are considered to be an extension of the copyright page.
Library of Congress Cataloging-in-Publication Data
Names: Schroeder, Roger G., author. | Goldstein, Susan Meyer. Title: Operations management in the supply chain decisions and cases / Roger G. Schroeder, Susan Meyer Goldstein, Carlson School of Management, University of Minnesota. Other titles: Operations management Description: Eighth edition. | New York, NY : McGraw-Hill Education, [2019] | Original edition entitled: Operations management. | Includes index. Identifiers: LCCN 2019018226| ISBN 9781260368109 (acid-free paper) | ISBN 1260368106 (acid-free paper) Subjects: LCSH: Production management. | Production management—Case studies. | Decision making. Classification: LCC TS155 .S334 2019 | DDC 658.5—dc23 LC record available at https://lccn.loc.gov/2019018226
The Internet addresses listed in the text were accurate at the time of publication. The inclusion of a website does not indicate an endorsement by the authors or McGraw-Hill Education, and McGraw-Hill Education does not guarantee the accuracy of the information presented at these sites.
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SUPPLY CHAIN MANAGEMENT Benton Purchasing and Supply Chain Management Third Edition
Bowersox, Closs, Cooper, and Bowersox Supply Chain Logistics Management Fifth Edition
Burt, Petcavage, and Pinkerton Supply Management Eighth Edition
Johnson Purchasing and Supply Management Sixteenth Edition
Simchi-Levi, Kaminsky, and Simchi-Levi Designing and Managing the Supply Chain: Concepts, Strategies, Case Studies Third Edition
Stock and Manrodt Fundamentals of Supply Chain Management
PROJECT MANAGEMENT Brown and Hyer Managing Projects: A Team-Based Approach Larson Project Management: The Managerial Process Eighth Edition
SERVICE OPERATIONS MANAGEMENT Bordoloi, Fitzsimmons, and Fitzsimmons Service Management: Operations, Strategy, Information Technology Ninth Edition
MANAGEMENT SCIENCE Hillier and Hillier Introduction to Management Science: A Modeling and Case Studies Approach with Spreadsheets Sixth Edition
BUSINESS RESEARCH METHODS Schindler Business Research Methods Thirteenth Edition
BUSINESS FORECASTING Keating and Wilson Forecasting and Predictive Analytics Seventh Edition
LINEAR STATISTICS AND REGRESSION Kutner, Nachtsheim, and Neter Applied Linear Regression Models Fourth Edition
BUSINESS SYSTEMS DYNAMICS Sterman Business Dynamics: Systems Thinking and Modeling for a Complex World
OPERATIONS MANAGEMENT Cachon and Terwiesch Operations Management Second Edition
Cachon and Terwiesch Matching Supply with Demand: An Introduction to Operations Management Fourth Edition
Jacobs and Chase Operations and Supply Chain Management Sixteenth Edition
Jacobs and Chase Operations and Supply Chain Management: The Core Fifth Edition
Schroeder and Goldstein Operations Management in the Supply Chain: Decisions and Cases Eighth Edition
Stevenson Operations Management Fourteenth Edition
Swink, Melnyk, and Hartley Managing Operations Across the Supply Chain Fourth Edition
BUSINESS MATH Slater and Wittry Practical Business Math Procedures Thirteenth Edition
Slater and Wittry Math for Business and Finance: An Algebraic Approach Second Edition
BUSINESS STATISTICS Bowerman, Drougas, Duckworth, Froelich, Hummel, Moninger, and Schur Business Statistics in Practice Ninth Edition
Doane and Seward Applied Statistics in Business and Economics Sixth Edition
Doane and Seward Essential Statistics in Business and Economics Third Edition
Lind, Marchal, and Wathen Basic Statistics for Business and Economics Ninth Edition
Lind, Marchal, and Wathen Statistical Techniques in Business and Economics Eighteenth Edition
Jaggia and Kelly Business Statistics: Communicating with Numbers Third Edition
Jaggia and Kelly Essentials of Business Statistics: Communicating with Numbers Second Edition
McGuckian Connect Master: Business Statistics
The McGraw-Hill Education Series Operations and Decision Sciences
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iv
Roger G. Schroeder is the Frank A. Donaldson Chair Emeritus in Supply Chain and Operations Management at the Curtis L. Carlson School of Management, University of Minnesota. He received B.S. and MSIE degrees in Industrial Engineering with high distinction from the Univer- sity of Minnesota, and a Ph.D. from Northwestern University. He held positions in the Carlson School of Management as Director of the Ph.D. program, Chair of the Operations and Management Science Department, and Co-Director of the Joseph M. Juran Center for Leadership in Quality. Professor Schroeder has obtained research grants from the National Science Foundation, the Ford Foundation, and the American Production and Inventory Control Society. His research is in the areas of quality management, operations strategy, and high-performance manufacturing, and he is among the most widely published and cited researchers in the field of operations management. He has been selected as a mem- ber of the University of Minnesota Academy of Distinguished Teachers and is a recipient of the Morse Award for outstanding teaching. Professor Schroeder received the lifetime achievement award in operations management from the Academy of Management, and he is a Fellow of the Decision Sciences Institute and a Fellow of the Production and Opera- tions Management Society. Professor Schroeder has consulted widely with numerous orga- nizations, including 3M, Honeywell, General Mills, Motorola, Golden Valley Foods, and Prudential Life Insurance Company.
Susan Meyer Goldstein is Associate Professor in the Supply Chain and Operations Department at the Curtis L. Carlson School of Management, University of Minnesota. She earned a B.S. degree in Genetics and Cell Biology and an M.B.A. at the University of Minnesota and worked in the health care industry for several years. She later obtained a Ph.D. in operations management from Fisher College of Business at The Ohio State University. She has served on the faculty at the Uni- versity of Minnesota since 1998 and was a Visiting Professor at the Olin Business School at Washington University in St. Louis for two years. Her current research and teaching interests involve service process design and management, as well as operations strategy issues. Her research has been published in Decision Sciences, Journal of Operations Management, Production and Operations Management, and Manufacturing and Service Operations Management, among others. She serves on the editorial boards of many operations and ser- vice journals. She is the recipient of several research awards and research grants, and has received the Carlson School of Management Teaching Award and the Carlson School of Management Service Award.
About the Authors
Dedication To our families, whose encouragement and love we appreciate
—Roger G. Schroeder —Susan Meyer Goldstein
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v
Preface FEATURES
Operations and supply chain management is an exciting and vital field in today’s com- plex business world. Therefore, students in both MBA and undergraduate courses have an urgent need to understand operations—an essential function in every business.
This textbook on Operations Management in the Supply Chain emphasizes decision making in operations with a supply chain orientation. The text provides materials of inter- est to general business students and operations and supply chain management majors. By stressing cross-functional decision making, the text provides a unique and current business perspective for all students. This is the first text to incorporate cross-functional decision making in every chapter, which provides more relevance for non-majors.
The book is organized into five unique sections to help students understand the key types of decisions made by operations and supply chain managers. See the illustration below.
Introduction 1. Process design - How to get work done? 2. Quality - How to satisfy customers? 3. Capacity and scheduling - When and how much work to do? 4. Inventory - How to manage parts and products? 5. Supply chain decisions - How to manage across organizations?
The text provides a balanced treatment of both service and manufacturing firms. Many books give only cursory treatment to service operations.
The most current knowledge is incorporated, including global operations, supply chain management, service blueprinting, competency-based strategy, Six Sigma, lean systems, 3D printing, blockchain technology, artificial intelligence, analytics, sustainability, and sup- ply chain risk. Complete coverage is also provided on traditional topics, including process design, service systems, quality management, ERP, inventory control, and scheduling.
Decision-making framework for operations in the supply chain.
The Firm
Process
Quality
Capacity
Inventory
Supply Chain
Decisions
Human Resources Finance
Marketing
Accounting Information
Systems
Supplier
Process
Quality
Capacity
Inventory
Supply Chain
Decisions Process
Quality
Capacity
Inventory
Supply Chain
Decisions
Distributor
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vi Preface
While covering the concepts of operations and supply chain management in 18 chapters, the book also provides 19 case studies. A key feature of this book is learning how operations issues are tackled in real situations. The cases are intended to strengthen problem formula- tion skills and illustrate the concepts presented in the text. Long and short case studies are included. The cases are not just large problems or examples; rather, they are substantial man- agement case studies, including some from Amazon, 3M, Mayo Clinic, and Polaris Industries.
The softcover edition with fewer pages than most introductory books covers all the essen- tials students need to know about operations management in the supply chain, leaving out only superfluous and tangential topics. By limiting the size of the book, we have condensed the material to the basics. The book is also available in Connect and LearnSmart digital versions.
This book is ideal for regular operations and supply chain management courses and also case courses and modular courses. It is particularly useful for those who desire a cross- functional and decision-making perspective that reaches across the supply chain. Instructors can easily supplement the text with their own cases, readings, or course materials as desired.
The Connect Library and Instructor Resources contain 22 Excel templates designed to assist in solving analytic problems at the end of chapters and the case studies. These resources also contain technical chapters on linear programming, simulation, transportation method, and queuing, which can be assigned by the instructor, if desired. Using these resources covers all the main analytics in operations and supply chain management. The resources also have PowerPoint slides, a solutions manual, and the test bank. Access to these resources can be obtained from your McGraw-Hill sales representative or directly in the Connect Library.
Walkthrough of Key Learning Features
∙ Over forty Operations Leader boxes are included in the chapters to illustrate current practices implemented by leading firms
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68 Part Two Process Design
design of the eyewear by taking a digital photo of the customer and recommending a style of lenses that fits the customer’s face. An optometrist then adjusts the lenses to fit the cus- tomer’s preference. Finally, the customer selects options for nose bridges, hinges, and arms for the frame. The customer receives a photo of the proposed eyewear. Finally, a technician makes the lenses and frames at the store within one hour.
There are three forms of mass customization:
1. Modular production and assemble-to-order (ATO). 2. Fast changeover (nearly zero setup time between orders). 3. Postponement of options.
Modular production can provide a variety of options by using an assemble-to-order process. For example, when Dell receives a computer order, the company assembles stan- dard modules or components rapidly to fulfill the customer’s order. The order is then shipped and the customer receives it in a few days. But this requires modular design, as well as modular production. Dell also uses the same process to make standard computers for stock and shipment to retail stores.
Fast changeover is the form of mass customization used by Paris Miki for its glasses, where moving from one customer order to the next is very quick, with little or no setup between them. In this case, it is critical that each order is uniquely identified by a bar code, or other identifier, that specifies the customer’s options. It is also essential to have nearly zero changeover time on equipment so that a lot size of a single unit can be produced economically.
Postponement is used to defer a portion of the production until the point of delivery. For example, customized T-shirt shops can put a unique design on a T-shirt at the point of purchase. Hewlett-Packard printers receive their final configuration for various volt- ages and power supplies at U.S. or overseas warehouses before delivery. Postponement makes it possible to ship standard units anywhere in the world and customize them at the last minute.
From a manufacturing point of view, mass customization has changed the dynamics of the product-process matrix. Flexible automation makes it possible to make small lot sizes along with large lot sizes without a great cost penalty. Thus, with mass customiza- tion a firm can operate over a wider range of product choices without major changes to its
Shoes with a customized “fit” are significantly more elusive. While there are firms offering custom-fitted shoes, they sell at prices reflecting the significant work to individually size the shoe, most likely performed in a job shop. These shoes are cus- tom, but not mass customized.
Mass customization gives custom- ers many options, as well as the enjoyment of designing and using a product with their own personal stamp on it.
Nike and Nike-owned Converse, among other athletic shoe brands, offer customized shoes that can be ordered online for a reasonable price and delivered within a few weeks. Customers can select from numerous fabric or leather colors and patterns on various pieces of the shoe, as well as the colors of laces, stitching, and soles. These shoes, with their many customizable options, are an example of successful mass customization.
Nike Does It
OPERATIONS LEADER
obsession.24k/Stockimo/Alamy Stock Photo
∙ Every function in every organization touches Operations and the Supply Chain in some manner. This is the first book to add materials in every chapter to show how topics apply to majors in Marketing, Finance, Accounting, Human Resources, and Information Systems. The hand- shake symbol indicates these cross-functional decisions.
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Preface vii
∙ Students can both preview and review the key points and terms. These are found at the end of each chapter.
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132 Part Two Process Design
container is being moved from A to B, two full contain- ers are sitting in the input area of work center B, and one container is being used at B. These eight containers are needed since work center A also produces parts for other work centers, machines at A may break down, and move times from A to B are not always exactly predictable.
Some companies control the movement of containers by using two types of kanban cards: production cards and withdrawal (move) cards. These cards are used to authorize production and to identify the parts in any container. Instead of using cards, production can also be controlled by kanban squares that visually signal the need for work (to fill the kanban square), or by visual control of the empty containers.
Most importantly, the kanban system is visual in nature. As empty containers accumulate, it is a clear signal that the producing work center is falling behind. When all the containers are filled, production is stopped. The production lot size is exactly equal to one container of parts. All parts are neatly placed in containers of a fixed size. All of these are visual indicators of the work that should be done or stopped.
The number of containers needed to operate a work center is a function of the demand
formula:2
n = DT ___ C
where n = total number of containers
D = demand rate of the using work center
C = container size, in number of parts, usually less than 10 percent of daily demand
T = time for a container to complete an entire circuit: filled, wait, moved, used, and returned to be filled again (also called lead time)
2 Safety stock can be added to the numerator to account for uncertainty in demand or time.
KANBAN SQUARE AT HONEYWELL. The dashed rectangle signals the need for the production of a cabinet. Only one cabinet is placed on this square at a time. When the square is emptied by subsequent production, another cabinet is produced. ©Tulasi Ranganathan/Honeywell
Suppose demand at the receiving work center B is 2 parts per minute and a standard con- tainer holds 25 parts. It takes 100 minutes for a container to make a complete circuit from work center A to work center B and back to A again, including all setup, run, move, and wait times. The number of containers needed in this case is:
n = 2(100)
______ 25
= 8
The maximum inventory in the production system, a useful measure of how lean the system is, equal to the container size times the number of containers (200 units = 8 × 25), since the most inventory we can have is all containers filled:
Maximum inventory = nC = DT
Example
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138 Part Two Process Design
LEARNING ENRICHMENT (for self-study or instructor assignments)
Introduction to Lean Thinking—Gemba Academy Video https://youtu.be/a255lkYgIpI 6:35
Routing Out Waste in a Hospital Video https://youtu.be/jZLtbye--sg 8:46
Lean Manufacturing Tour—5S implementation Video https://youtu.be/mqgHUwSaKj8 9:13
The Toyota Production System Video https://youtu.be/P-bDlYWuptM 4:14
Push vs. Pull with Kanban Simulation Video https://youtu.be/a7YvJB0n16I 8:48
SOLVED PROBLEMS
1. Kanban and takt time. A work center uses kanban containers that hold 300 parts. To produce enough parts to fill the container, 90 minutes of setup plus run time are needed. Moving the container to the next workstation, waiting time, processing time at the next workstation, and return of the empty container take 140 minutes. There is an overall demand rate of nine units per minute.
a. Calculate the number of containers needed for the system. b. What is the maximum inventory in the system? c. A quality team has discovered how to reduce setup time by 65 minutes. If these
changes are made, can the number of containers be reduced? d. What is the takt time for this process?
Problem
a. T is the time required for a container to complete an entire circuit, in this case 90 minutes for setup and run time plus 140 minutes to move the container through the rest of the circuit.
n = DT ÷ C = (9 × (90 + 140)) ÷ 300 = 6.9 (round up to 7)
b. Since production will stop when all the containers are full, the maximum inventory is when all containers are full, that is, nC:
nC = 7(300) = 2100
c. n = DT ÷ C = (9 × (25 + 140)) ÷ 300 = 4.95 (round up to 5), so yes, the number of containers can be reduced from 7 to 5.
d. Takt time = 1/9 minute = 60/9 seconds = 6.67 seconds. Since the process produces 9 units per minute, the takt time is 1/9 minute or 6.67 seconds per unit.
Solution
2. Kanban. Work center A produces parts that are then processed by work center B. Kanban containers used by the work centers hold 100 parts. The overall rate of demand is 4.5 parts per minute at work center B. The table below shows setup, run, move, and wait times for parts at each of the work centers.
Problem Revised Pages
Chapter 7 Lean Thinking and Lean Systems 137
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7.7 KEY POINTS AND TERMS
Lean concepts, principles, and tenets can be deployed to reduce waste in manufacturing and service firms. We have seen how the lean tenets create lean production systems with non-value-added activities eliminated and waste minimized. Key points in the chapter include the following:
∙ Lean thinking is a way of thinking about processes that includes five tenets: specify customer value, improve the value stream, flow the product or service, pull from the customer, and strive for perfection.
∙ The five lean tenets seek to eliminate waste by utilizing the full capability of workers and partners in continuous improvement efforts. Lean tools, or methods, are described for each of the five tenets.
∙ In manufacturing, smooth flow is ensured by a stable and level master schedule. This requires consistent daily production within the master schedule and mixed model assembly. Takt time matches the rate of output with the average demand rate in the market.
∙ Reducing lot sizes, setup times, and lead times is the key to decreasing inventories in a lean production system and ensures smooth flow. Service and administrative activities should also work toward a fast changeover from one customer to the next and a reduced lead time.
∙ The plant layout in a lean production system requires much less space and encourages evolution toward cellular or group technology layouts.
∙ A lean system requires cross-trained workers who can perform multiple tasks. A flex- ible workforce will require changing the way workers are selected, trained, evaluated, and rewarded.
∙ A kanban system is used to pull parts through the production system. A fixed number of containers is provided for each part, thus limiting the amount of work-in-process inven- tory. The pull system can also be applied in service operations by providing only what is needed when it is needed by the customer.
∙ New supplier relationships must be established to make lean production successful. Frequent deliveries and reliable quality are required. Often, long-term single-source contracts will be negotiated with suppliers.
∙ Kaizen emphasizes continuous improvement. Kaizen events are used to implement lean thinking improvements quickly in one week or less on a particular process.
∙ Lean concepts, principles, and techniques can be applied to design, manufacturing, dis- tribution, services, and the supply chain.
Key Terms Toyota Production System (TPS) 119
Just-in-Time (JIT) manufacturing 119
Lean production 119 Lean thinking 120 Waste (muda) 121 Value stream 121 Value stream
mapping 121 Gemba 121
Internal setup 128 External setup 128 Cellular manufacturing 129 Preventative maintenance 129 Cross-training 130 Respect for people 130 Kanban 130 Reducing lead time 133 Supplier relationships 133 Co-location 133 Kaizen 135
Push 123 Pull 123 Perfection 124 5 Whys 125 5S 125 Stabilizing the master
schedule 127 Uniform load 127 Takt time 127 Reducing setup time 128 Single setups 128
∙ To help practice calculations, example boxes are included within chapters and solved problems are added at the end of the chapter.
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viii Preface
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Chapter 7 Lean Thinking and Lean Systems 137
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7.7 KEY POINTS AND TERMS
Lean concepts, principles, and tenets can be deployed to reduce waste in manufacturing and service firms. We have seen how the lean tenets create lean production systems with non-value-added activities eliminated and waste minimized. Key points in the chapter include the following:
∙ Lean thinking is a way of thinking about processes that includes five tenets: specify customer value, improve the value stream, flow the product or service, pull from the customer, and strive for perfection.
∙ The five lean tenets seek to eliminate waste by utilizing the full capability of workers and partners in continuous improvement efforts. Lean tools, or methods, are described for each of the five tenets.
∙ In manufacturing, smooth flow is ensured by a stable and level master schedule. This requires consistent daily production within the master schedule and mixed model assembly. Takt time matches the rate of output with the average demand rate in the market.
∙ Reducing lot sizes, setup times, and lead times is the key to decreasing inventories in a lean production system and ensures smooth flow. Service and administrative activities should also work toward a fast changeover from one customer to the next and a reduced lead time.
∙ The plant layout in a lean production system requires much less space and encourages evolution toward cellular or group technology layouts.
∙ A lean system requires cross-trained workers who can perform multiple tasks. A flex- ible workforce will require changing the way workers are selected, trained, evaluated, and rewarded.
∙ A kanban system is used to pull parts through the production system. A fixed number of containers is provided for each part, thus limiting the amount of work-in-process inven-
is needed when it is needed by the customer. ∙ New supplier relationships must be established to make lean production successful.
Frequent deliveries and reliable quality are required. Often, long-term single-source contracts will be negotiated with suppliers.
∙ Kaizen emphasizes continuous improvement. Kaizen events are used to implement lean thinking improvements quickly in one week or less on a particular process.
∙ Lean concepts, principles, and techniques can be applied to design, manufacturing, dis- tribution, services, and the supply chain.
Key Terms Toyota Production System (TPS) 119
Just-in-Time (JIT) manufacturing 119
Lean production 119 Lean thinking 120 Waste (muda) 121 Value stream 121 Value stream
mapping 121 Gemba 121
Internal setup 128 External setup 128 Cellular manufacturing 129 Preventative maintenance 129 Cross-training 130 Respect for people 130 Kanban 130 Reducing lead time 133 Supplier relationships 133 Co-location 133 Kaizen 135
Push 123 Pull 123 Perfection 124 5 Whys 125 5S 125 Stabilizing the master
schedule 127 Uniform load 127 Takt time 127 Reducing setup time 128 Single setups 128
∙ Twenty-two Excel spreadsheets are included for solving problems and analyzing case studies using analytic methods.
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188 Part Three Quality
a. Using this five-day sample, is the process of the fish supplier in control in average and range?
b. How can the supplier more carefully control the pro- cess to provide 100 pounds of fish each day?
11. As cereal boxes are filled in a factory, they are weighed for their contents by an automatic
scale. The target value is to put 10 ounces of cereal in each box. Twenty samples of three boxes each have been weighed for quality control purposes. The fill weight for each box is shown below.
a. Calculate the center line and control limits for the _ x
and R charts from these data. b. Plot each of the 20 samples on the
_ x and R control
charts and determine which samples are out of control.
c. Do you think the process is stable enough to begin to use these data as a basis for calculating x and
_ R
and to begin to take periodic samples of 3 for quality control purposes?
12. A certain process has an upper specification limit of 220 and a lower specification limit of 160. The process standard deviation is 6, and the mean is 170.
a. Calculate Cp and Cpk for this process. b. What could be done to improve the process capabil-
ity Cpk to 1.0? 13. A certain process is under statistical control and
has a mean value of μ = 130 and a standard devia- tion of σ = 8. The specifications for this process are USL = 150, LSL = 100.
a. Calculate Cp and Cpk. b. Which of these indices is a better measure of process
capability? Why? c. Assuming a normal distribution, what percent
of the output can be expected to fall outside the specifications?
14. A customer has specified that they require a process capability of Cp = 1.5 for a certain product. Assume that USL = 1100, LSL = 700, and the process is cen- tered within the specification range.
a. What standard deviation should the process have? b. What is the process mean value? c. What can the company do if it is not capable of
meeting these requirements?
Observation Sample 1 2 3
1 10.01 9.90 10.03 2 9.87 10.20 10.15 3 10.08 9.89 9.76 4 10.17 10.01 9.83 5 10.21 10.13 10.04 6 10.16 10.02 9.85 7 10.14 9.89 9.80 8 9.86 9.91 9.99 9 10.18 10.04 9.96 10 9.91 9.87 10.06 11 10.08 10.14 10.03 12 9.71 9.87 9.92 13 10.14 10.06 9.84 14 10.16 10.17 10.19 15 10.13 9.94 9.92 16 10.16 9.81 9.87 17 10.20 10.10 10.03 18 9.87 9.93 10.06 19 9.84 9.91 9.99 20 10.06 10.19 10.01
∙ Throughout the text, company and industry examples illustrate real use of the ideas.
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a service, rather than volume, is the main characteris- tic that affects the design of the service process and the way the service is delivered.
Self-service by customers is also a consideration in service delivery system design. Customers may serve as labor at key points in a service process, such as bagging their own groceries, or they may complete an entire service process independently, as occurs when they fill their tanks at a self-service gas station. Self-service usually benefits the firm as customers provide “free” labor during service delivery. For self-service to be a successful component of service delivery system design firms must design their service processes carefully for both simplicity and customer satisfaction.
Self-service is possible for any of the types of ser- vices defined in the service delivery system matrix,
from simple standardized services to highly customized services. A key issue for opera- tions managers is designing self-service opportunities that customers are both willing and able to perform. While the relatively simple self-service offered at ATMs appeals to a wide range of customer segments, having to pull one’s retail selections from warehouse shelv- ing (e.g., at IKEA stores) may limit the appeal of the retail service for some segments. An understanding of the needs of a firm’s target customer segments must serve as a guide to the right service delivery system design.
5.4 CUSTOMER CONTACT
We now look at interactions between customers and service organizations in detail to understand how the extent of customer contact relates to service processes. With low- contact services, it is possible to separate a service into two portions: a service creation or production portion and a service consumption or delivery portion. By doing so, the cus- tomer can be removed from the service creation portion. Separating the customer from the service production portion allows for greater standardization of processes and therefore better efficiency. Examples of low-contact services are processing of online orders and ATM transactions. As indicated above, these services are usually designed using a provider-routed approach. See Figure 5.3, in which low-contact services are referred to as buffered core because these services are designed to be buffered or removed from interac- tions with the customer.
At the other end of the contact spectrum, high-contact services involve the customer during the production of the service. Examples are dentistry, haircutting, and consulting. In these services, the customer can introduce uncertainty into the process with a result- ing loss of efficiency. For example, a customer may impose unique requirements on the service provider, resulting in a need for more processing time. In this case, the service delivery system design typically will be customer-routed unless customization has been limited by the provider. These interactions are referred to as reactive in Figure 5.3 because the service delivery system must react to customer requests.
In the middle ground of customer contact, permeable systems have processes that are penetrated by customers in fairly restricted ways, usually via telephone or limited face-to- face contact. Here, limited interaction with customers allows some customer preferences to be met. But such accommodation is restricted to maintain process efficiency.
LO5.4 Describe the effect on the service delivery system of customer contact.
Grocery self-service is a provider-routed service. Syda Productions/Shutterstock
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technology and systems. For example, Southwest Airlines has the most productive employ- ees in the airline industry. As a result of short routes, fast turnaround, and productive employees, Southwest has 40 percent greater aircraft and pilot utilization than its competi- tors. Employee retention and low employee turnover help drive productivity and customer value. Traditionally, the cost of employee turnover considers only the cost of recruiting, hiring, and training replacements. In reality, the greatest cost of turnover is the lost produc- tivity and decreased customer satisfaction associated with new employees. At Southwest Airlines, customer perceptions of service value are high, based on low fares, on-time ser- vice, and friendly and helpful employees.
Employee retention and productivity are driven by having satisfied employees. For example, a study of insurance company employees found that 30 percent of dissatisfied employees intended to leave the company, a potential turnover rate three times that of satis- fied employees. Satisfied employees are the result of internal service quality. This includes the employee selection process, job design, reward systems, and the technology used to support service workers. Focusing management’s attention on improving internal service quality systems to provide support for employees in conducting their work can improve employee satisfaction, productivity, and turnover. Employees will be satisfied with their jobs when they feel that they can act on behalf of customers. This will lead to both employee and customer satisfaction. This is achieved in part by giving front-line employees latitude to use resources to meet customer needs immediately. For example, in Ritz-Carlton Hotels, front-line employees are authorized to spend up to $2000 to satisfy a customer need.
The service-profit chain illustrates the central role of employees in delivering services to customers. During the delivery of services, employees are the “face” of the company and their satisfaction is directly observed by customers, often influencing customer perceptions of the service as well. This differentiates services from manufacturing, since manufacturing employees rarely have direct contact with customers. A manufacturing employee’s effect on customer satisfaction is through the product that the customer may receive days, weeks, or months later. However, the morale, attitude, and satisfaction of service employees is directly—and immediately—related to customer satisfaction and loyalty. There is no buffer zone between service employees and customers in high- or medium-contact services.
The service delivery system design should reflect this direct contact between service employees and customers. This can be done by providing real-time (during the service delivery) tools such as access to customer information to help service employees perform their jobs. For example, bank tellers who can quickly scan relevant portions of a cus- tomer account while the cus- tomer is face-to-face or on the telephone with them can pres- ent banking products that fit the customer profile. Such per- sonalized selling opportunities tend to be more successful than low-contact marketing, such as mail or e-mail. Services can also be improved through so-called “smile training” in which service workers are trained to be nice to customers and seek their satisfaction even in pressure situations. Service workers should be rewarded for
Harrah’s uses superior customer service to increase profits. Leonard Zhukovsky/123RF
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470
The changeover cost of the production line depends on which type of mower is being produced and the next production model planned. For example, it is relatively easy to change over from the 20-inch push mower to the 20-inch self-propelled mower, since the mower frame is the same. The self-propelled mower has a propulsion unit added and a slightly larger engine. The company estimated the changeover costs as shown in Exhibit 2.
Lawn King fabricates the metal frames and metal parts for its lawn mowers in its own machine shop. These fabri- cated parts are sent to the assembly line along with parts purchased directly from vendors. In the past year, approx- imately $8 million in parts and supplies were purchased, including engines, bolts, paint, wheels, and sheet steel. An inventory of $1 million in purchased parts is held to supply the machine shop and the assembly line. When a particular mower is running on the assembly line, only a few days of parts are kept at the plant, since supplies are constantly coming into the factory.
John Conner, marketing manager for Lawn King, looked over the beautiful countryside as he drove to the cor- porate headquarters in Moline, Illinois. John had asked his boss, Kathy Wayne, the general manager of Lawn King, to call a meeting in order to review the latest fore- cast figures for fiscal year 2020.1 When he arrived at the plant, the meeting was ready to begin. Others in attendance at the meeting were James Fairday, plant manager; Joan Peterson, controller; and Harold Pinter, personnel officer.
John started the meeting by reviewing the latest situ- ation: “I’ve just returned from our annual sales meeting, and I think we lost more sales last year than we thought, due to back-order conditions at the factory. We have also reviewed the forecast for next year and feel that sales will be 110,000 units in fiscal year 2020. The marketing department feels this forecast is realistic and could be exceeded if all goes well.”
At this point, James Fairday interrupted by saying, “John, you’ve got to be kidding. Just three months ago we all sat in this same room and you predicted sales of 98,000 units for fiscal 2020. Now you’ve raised the forecast by 12 percent. How can we do a reasonable job of production planning when we have a moving target to shoot at?”
Kathy interjected, “Jim, I appreciate your concern, but we have to be responsive to changing market condi- tions. Here we are in September and we still haven’t got a firm plan for fiscal 2020, which has just started. I want to use the new forecast and develop a Sales and Opera- tions Plan (S&OP) for next year as soon as possible.”
John added, “We’ve been talking to our best custom- ers, and they’re complaining about back orders during the peak selling season. A few have threatened to drop our product line if they don’t get better service next year. We have to produce not only enough product but also the right models to service the customer.”
MANUFACTURING PROCESS Lawn King is a small-sized producer of lawn mower equipment. Last year, sales were $14.5 million and pretax profits were $2 million, as shown in Exhibit 1. The com- pany makes four lines of lawn mowers: an 18-inch push mower, a 20-inch push mower, a 20-inch self-propelled mower, and a 22-inch deluxe self-propelled mower. All these mowers are made on the same assembly line. Dur- ing the year, the line is changed over from one mower to the next to meet the actual and projected demand.
Case Study Lawn King, Inc.: Sales and Operations Planning
EXHIBIT 1 Profit and loss statement ($000).
FY2018 FY2019
Sales $ 11,611 $ 14,462 Cost of goods sold Materials 6,340 8,005 Direct labor 2,100 2,595 Depreciation 743 962 Overhead 256 431 Total CGS 9,439 11,993 G&A expense 270 314 Selling expense 140 197 Total expenses 9,849 12,504 Pretax profit 1,762 1,958
1The Lawn King 2020 fiscal year runs from September 1, 2019, to August 31, 2020.
This case was prepared by Roger G. Schroeder for class discussion. Copyright © by Roger G. Schroeder, 2016, 2019. All rights are reserved. Reprinted with permission.
Pixtal/age fotostock
∙ Case studies provide students practice in formulating and solving unstructured problems.
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Preface ix
∙ At the end of every chapter, Learning Enrichment boxes provide videos and websites where students can extend their knowledge on chapter topics using Internet content.
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50 Part One Introduction
∙ 3D printing, or additive manufacturing is useful for creating product prototypes. The speed and flexibility of this new technology enhances product design opportunities.
∙ Supply chain collaboration in NPD is essential. This should be accomplished by col- laborating with both customers and suppliers in the NPD process.
∙ QFD is used to connect customer attributes to engineering characteristics. This typi- cally is done through a technique called the house of quality that can be used for both manufacturing and services.
∙
considering only the combinations of options that have significant market demand.
Key Terms Market pull 38 Technology push 38 Interfunctional view 39 Concept development 40 Product design 40 Pilot production/testing 40 Process design 40
Quality function deployment 45 House of quality 45 Customer attributes 46 Engineering characteristics 46 Trade-offs 46 Target value 46 Modular design 48
Production prototypes 41 3D printing 41 Additive manufacturing 41 Misalignment 42 Sequential process 42 Concurrent engineering 42 Collaboration 43
LEARNING ENRICHMENT (for self-study or instructor assignments)
What Is the New Product Development Process? Video https://youtu.be/vQZjNIRpuFg 2:49
Tools for Accelerating a Cross-functional Design Process Web Link https://www.mckinsey.com/business-functions/operations/our-insights/ accelerating-product-development-the-tools-you-need-now
Prototyping Video https://youtu.be/5SWt-TSYD08 2:26
3D Printing Prototype Example Video https://youtu.be/RpFTRT8FkP0 3:02
Sustainability in New Product Development Video https://youtu.be/-HS-slU-XTc 3:56
Discussion Questions 1. Why is cross-functional cooperation important for new
product design? What are the symptoms of a possible lack of cooperation?
2. In what circumstances might a market-pull approach or a technology-push approach to new product design be the best approach?
3. Describe the steps that might be required in writing and producing a play. Compare these steps to the three steps for NPD described in Section 3.2. How are they similar?
4. Why has there been an increase in product variety in global markets?
5. How can modular design help to control production variety and at the same time allow product variety?
6. What is the proper role of the operations function in product design?
7. What form does the product specification take for the following firms: a travel agency, a beer company, and a consulting firm?
KEY CHANGES IN THE EIGHTH EDITION This book is known for its decision orientation and case studies. We have strengthened the decision-making framework by adding new material on digital technology, lean systems, sustainability, and global supply chains. We also include new and existing cases to address these decisions. The Eighth Edition features a new 4-color design and the following major changes:
1. Cross-functional. Most books for operations and supply chain core courses are merely summaries for majors in operations and supply chain management. None address the general business student who is interested in Marketing, Finance, Accounting, or Information Systems. We make this book more applicable and interesting to the approximately 80 percent of business students who don’t major in operations and supply chain management. We add cross-functional materials in each chapter to show how the topics apply to non-majors. The handshake symbols in the margin identify the content.
2. Digital Technology. The Eighth Edition has substantial updates and additions on four digital technologies. 3D printing is becoming useful for producing spare parts, custom manufacturing, medical devices, dental implants, and architectural models. Blockchain software is being developed and tested by many global logistics compa- nies. Artificial intelligence is rapidly developing for service applications, automo- biles, and manufacturing plants. Analytics are being applied to both large and small databases. Analytics that are descriptive, predictive, or prescriptive in nature are discussed. These digital technologies are described in detail in several chapters in the book.
3. Supply Chain Sustainability. We introduce the idea of the triple bottom line regarding environmental, social, and economic sustainability. Sustainability is preserving the earth and resources for future generations. Environmental sustainability is related to global warming, clean water, clean air, and environmental protection. Social sustainability means hiring a diverse workforce, ethical practices, providing equal opportunity, and safe working conditions, for example. Economic sustainability is making a sufficient profit for the firm’s survival in the future. Operations and supply chain managers are actively pursuing all three aspects of sustainability of operations and associated supply chains.
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50 Part One Introduction
∙ 3D printing, or additive manufacturing is useful for creating product prototypes. The speed and flexibility of this new technology enhances product design opportunities.
∙ Supply chain collaboration in NPD is essential. This should be accomplished by col- laborating with both customers and suppliers in the NPD process.
∙ QFD is used to connect customer attributes to engineering characteristics. This typi- cally is done through a technique called the house of quality that can be used for both manufacturing and services.
∙ Modular design is used to minimize the number of different parts needed to make a product line of related products. This can be done by designing standard modules and considering only the combinations of options that have significant market demand.
Key Terms Market pull 38 Technology push 38 Interfunctional view 39 Concept development 40 Product design 40 Pilot production/testing 40 Process design 40
Quality function deployment 45 House of quality 45 Customer attributes 46 Engineering characteristics 46 Trade-offs 46 Target value 46 Modular design 48
Production prototypes 41 3D printing 41 Additive manufacturing 41 Misalignment 42 Sequential process 42 Concurrent engineering 42 Collaboration 43
LEARNING ENRICHMENT (for self-study or instructor assignments)
What Is the New Product Development Process? Video https://youtu.be/vQZjNIRpuFg 2:49
Tools for Accelerating a Cross-functional Design Process Web Link https://www.mckinsey.com/business-functions/operations/our-insights/ accelerating-product-development-the-tools-you-need-now
Prototyping Video https://youtu.be/5SWt-TSYD08 2:26
3D Printing Prototype Example Video https://youtu.be/RpFTRT8FkP0 3:02
Sustainability in New Product Development Video https://youtu.be/-HS-slU-XTc 3:56
Discussion Questions 1. Why is cross-functional cooperation important for new
product design? What are the symptoms of a possible lack of cooperation?
2. In what circumstances might a market-pull approach or a technology-push approach to new product design be the best approach?
3. Describe the steps that might be required in writing and producing a play. Compare these steps to the three steps for NPD described in Section 3.2. How are they similar?
4. Why has there been an increase in product variety in global markets?
5. How can modular design help to control production variety and at the same time allow product variety?
6. What is the proper role of the operations function in product design?
7. What form does the product specification take for the following firms: a travel agency, a beer company, and a consulting firm?
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x Preface
4. Global Supply Chains. In this new edition we have increased our attention to global supply chains by adding new sections on global services, global sourcing, and global logistics. The text explains how to make global decisions that balance the lower costs of overseas sourcing and logistics with the risks of quality failures, loss of intellectual property, increased monitoring costs, and exposure to financial and political risks.
5. Lean Systems. Most books discuss up to 15 techniques of lean including reduced setup time, small lot sizes, uniform load, and takt time. We have completely reor- ganized the lean chapter around the five tenets and principles of lean systems to include all of these techniques. This clarifies lean systems in terms of creating value for the customer, eliminating waste, ensuring flow, customer pull, and striv- ing for perfection.
6. Practical Examples. The text contains over 70 practical examples of concepts, ideas, and analytics. Nineteen new Operations Leader boxes have been added for companies including Southwest Airlines, Lego Group, Culver’s, Nike, LG Electronics, and Trader Joe’s. In addition twenty-five existing Operations Leader boxes have been updated in the various chapters.
7. Learning Enrichment boxes. Every chapter ends with a Learning Enrichment box for student self-study or instructor assignments. These boxes have YouTube video links and websites that expand on the coverage in the chapter. They cover ideas from the chapter in more detail or provide examples of the how the ideas are used. This is one of the first books to make extensive use of the Internet to enrich the material covered in the text.
When reviewers of this book were asked how they would describe the text to a col- league, they said:
“I would highly recommend the book to them. While other textbooks either focus on the techniques or concepts, this book does a good job in addressing both equally well.”
“A solid textbook that is well-written. Good coverage of basic operations management material.”
“It is a guide to operations that takes a practical approach with a strong emphasis on case materials to put concepts into practice.”
CHAPTER REVISIONS AND CASES FOR THE EIGHTH EDITION 1. Introduction to Operations. The first part of the chapter is rewritten to clearly define
operations and supply chain management. A new section explains the role of operations in the firm and the economy including productivity calculations. The triple bottom line is defined for environmental, social, and economic sustainability. Internet links are pro- vided in the Learning Enrichment box on sustainability and globalization.
2. Operations and Supply Chain Strategy. A new Operations Leader box on Southwest Airlines is added. Sustainability, as an objective, is added to cost, quality, delivery and flexibility. Emphasis is placed on decision making in operations that is contingent on strategy.
3. Product Design. New content is added on the use of 3D printing for creating proto- types. Concurrent engineering is illustrated using a new example from NASA. New Operations Leader boxes describe how The LEGO Group tackles sustainability chal- lenges and how TPI Composites is developing and manufacturing blades for wind tur- bine energy systems.
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Preface xi
4. Process Selection. There is a new example of focused operations in a service firm, Midwest Orthopedic Specialty Hospital. Two new Operations Leader boxes describe the food production system at Culver’s and mass customization at Nike. We also expand on the role of 3D printing in modern manufacturing, particularly in the medi- cal sector.
5. Service Process Design. The relevance of service operations to non-majors is dis- cussed. A new Operations Leader box on the City of Fort Collins is added. This edition is the first to offer sections on Technology for Services and Globalization of Services.
6. Process-Flow Analysis. Cross-functional material is added to show its importance to systems thinking. A Learning Enrichment box is included with YouTube videos and Internet links on process mapping, Little’s Law, and queueing at Disney.
7. Lean Thinking and Lean Systems. This chapter is completely reorganized around the five lean tenets to clarify the principles and concepts underlying lean thinking. New material is added on cellular manufacturing and the pull system. The chapter is the first to take a principle and conceptual approach to lean systems, rather than a list- ing of techniques and methods used.
8. Managing Quality. YouTube videos are added to the Learning Enrichment box to expand on ISO9000 certification, mistake proofing, and the Baldrige Award for health care. Quality is expanded to include the entire supply chain, not just the focal firm. The highly cross-functional nature of quality is emphasized.
9. Quality Control and Improvement. We explain why all business students should learn about quality control. The difference between special causes and common causes is emphasized. We clarify the differences between statistical process control and pro- cess capability. The section on Six Sigma was rewritten to expand the content.
10. Forecasting. We shift our description of forecasting to “analytics” so that students can understand how the popular focus on analytics is utilized in operations and supply chain. There is a new section on big data and its use in forecasting, along with a new Operations Leader box on how Amazon uses big data in its own forecasting. When and how to use MADt is clarified, in addition to many minor clarifications in using formulas throughout the chapter.
11. Capacity Planning. We expand discussion about how all functions are involved in and impacted by capacity planning. Improvements in the descriptions of Sales and Operations Planning (S&OP) as well as aggregate planning help to clarify the process involved and the challenges faced. Calculations for level and chase strategies are clari- fied. New Operations Leader boxes on Delta Airlines and Hostess Brands make these concepts tangible for students.
12. Scheduling Operations. We add new material on the theory of constraints about how to identify the bottleneck constraint and eliminate it while subordinating everything else. In the Learning Enrichment box interesting YouTube videos are provided on job shop scheduling at Washburn Guitar, round-robin CPU scheduling, and the theory of constraints.
13. Project Planning and Scheduling. The chapter is updated to illustrate the many industry settings in which projects require skilled management—from manufacturing to service firms, nonprofits, and government. A new Operations Leader box on the Carlsbad Desalination Plant in San Diego provides a nice example of a major multi- government project. Other updates include the Project Management Institute’s Body of Knowledge in Table 13.3.
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xii Preface
14. Independent Demand Inventory. The chapter includes additional content on ven- dor managed inventory (VMI), along with a new Operations Leader box illustrating VMI at Procter and Gamble Co. An additional new Operations Leader box on IKEA describes the use of a min/max inventory replenishment system. The Learning Enrich- ment box at the end of the chapter provides video and web sources for additional information.
15. Materials Requirements Planning and ERP. We clarify for students exactly which elements constitute the MRP system. We also describe the use of Oracle’s ERP soft- ware at Cleveland Clinic to help students understand the breadth of these system’s use in industry. A new Operations Leader box on LG Electronics provides a useful illustra- tion of how a global firm benefits from these systems.
16. Supply Chain Management. This is one of the first books to have a separate section on blockchain technology to explain its uses and methods. More details are also pro- vided on the SCOR model. We rewrote the section on measures of throughput time, cash-to-cash cycle time and total delivered cost for analyzing an entire supply chain. We added a new section on the Amazon effect and omni-channel marketing, also a first in textbooks.
17. Sourcing. The chapter includes an entirely new section on Global Sourcing, including discussion of risks and benefits. Presentation of Total Cost Analysis is expanded. A new Operations Leader box on Trader Joe’s sourcing strategy will appeal to students.
18. Global Logistics. A new section on Global Logistics includes a figure to illustrate the multimodal activities in global supply chains. The concepts of intermodal and ship- ping zones have been added and described. A new Operations Leader box on Home Depot provides insight on how online sales are served from stores and warehouses, while an expanded box on Ryder gives students a glimpse of the people and assets needed for this major 3PL provider.
Case Study Revisions A few of the 19 case studies are described below:
Amazon Revolutionizes Supply Chain Management. This new case, written exclusively for this book, describes the evolution of Amazon’s supply chain and its purchase of Whole Foods. It challenges students to think about how Amazon can change the future of Whole Foods to increase its revenues and earnings. The case also contrasts what Walmart is doing to use e-commerce to compete with Amazon. The case asks students to define the effect of the emergent business strategies of Amazon and Walmart on the supply chains of these companies in terms of locations, sourcing, capacity, and inventory.
Operations Strategy at BYD of China, Electrifying the World’s Automotive Market. BYD, the leading electric vehicle company in the world, must develop a strategy for adapt- ing its supply chain in the future. We updated this case from its last update in 2015 and revised the teaching note for this rapidly changing industry.
Early Supplier Integration for John Deere Skid-Steer Loader. Deere and Company must decide how to involve suppliers in the design of its new Skid-Steer Loader. This case is updated and the teaching note revised.
The Evolution of Lean Six Sigma at 3M Inc. Students are asked to evaluate 3M’s use of Six Sigma and lean thinking. We added significant new information since the last update in 2012.
Consolidated Electric: Inventory Control. Management is designing a new inven- tory control system. The student questions are tailored to increase student learning about this system.
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Preface xiii
Altimus Brands: Managing Procurement Risk. Altimus is deciding which of four off- shore suppliers offers the lowest cost and risk for future purchase contracts. We updated the case and wrote a new teaching note.
ShelterBox: A Decade of Disaster Relief. After the Haiti earthquake of 2010, ShelterBox provided immediate relief and is considering what decisions should be made in advance of future disasters. A new teaching note was written for this case.
INSTRUCTOR RESOURCES McGraw-Hill Connect® McGraw-Hill Connect® is an online assignment and assessment solution that connects students with the tools and resources they’ll need to achieve success through faster learn- ing, higher retention, and more efficient studying. It provides instructors with tools to quickly pick content and assignments according to the topics they want to emphasize.
Instructor Library. The Connect Operations Management Instructor Library is your repository for additional resources to improve student engagement in and out of class. You can select and use any asset that enhances your lecture. The Connect Instructor Library includes: ∙ Solutions Manual. Prepared by the authors, this manual contains solutions to all the
end-of-chapter problems and cases. ∙ Test Bank. The Test Bank includes true/false, multiple-choice, and discussion ques-
tions/problems at varying levels of difficulty. All test bank questions are also available in a flexible electronic test generator. The answers to all questions are given, along with a rating of the level of difficulty, chapter learning objective met, Bloom’s taxonomy question type, and the AACSB knowledge category.
∙ PowerPoint Slides. The PowerPoint slides draw on the highlights of each chapter and provide an opportunity for the instructor to emphasize the key concepts in class discussions.
∙ Digital Image Library. All the figures in the book are included for insertion in Power- Point slides or for class discussion.
∙ Excel Spreadsheets. Twenty Excel Spreadsheets are provided for students to solve des- ignated problems at the end of chapters.
∙ Technical Chapters. Additional Operations analytics are available in four inline Tech- nical Chapters. These are available in the Instructor Resource Library through Connect, or by visiting the URL at www.mhhe.com/schroeder8e The instructor and student resources can also be accessed directly at www.mhhe.com/
schroeder8e.
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Educators know that the more students can see, hear, and experience class resources, the better they learn. In fact, studies prove it. With Tegrity Campus, students quickly recall key moments by using Tegrity Campus’s unique search feature. This search helps stu- dents efficiently find what they need, when they need it, across an entire semester of class recordings. Help turn all your students’ study time into learning moments immediately supported by your lecture. To learn more about Tegrity, watch a two-minute Flash demo at http://tegritycampus.mhhe.com.
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xiv Preface
MCGRAW-HILL CUSTOMER CARE CONTACT INFORMATION At McGraw-Hill, we understand that getting the most from new technology can be chal- lenging. That’s why our services don’t stop after you purchase our products. You can e-mail our Product Specialists 24 hours a day to get product-training online. Or you can search our knowledge bank of Frequently Asked Questions on our support website. For Customer Support, call 800-331-5094 or visit www.mhhe.com/support. One of our Technical Sup- port Analysts will be able to assist you in a timely fashion.
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Preface xv
ACKNOWLEDGMENTS The authors would like to acknowledge the many individuals who have assisted with this book. Special thanks go to the reviewers for this edition:
The authors would also like to thank the staff at McGraw-Hill Education who had a direct hand in the editing and production of the text, including Ryan McAndrews, product developer; Noelle Bathurst, portfolio manager; Harper Christopher, executive marketing manager; and Fran Simon and Angela Norris, project managers.
We would like to thank our colleagues at the University of Minnesota who listened to our ideas and provided suggestions for book improvement. Additional thanks go to Doug and Letty Chard, who diligently and carefully prepared the index. We would also like to thank Tom Buchner of the University of Minnesota who carefully prepared the test bank questions. Our thanks to Ed Pappanastos of Troy University for constructing the Connect solutions to problems. Finally, we thank our families for their patience and perseverance during the many months of writing and editing. Without their support and encouragement this textbook would not have been possible.
Roger G. Schroeder
Susan Meyer Goldstein
Abirami Radhakrishnan Morgan State University
Anita Lee-Post University of Kentucky
Canchu Lin Carroll University
Enar Tunc California Polytechnic State University San Luis Obispo
John Wu California State University San Bernardino
Jooh Lee Rowan University
Jose Ablanedo-Rosas University of Texas El Paso
Kathy Schaefer Southwest Minnesota State University
Kimball Bullington Middle Tennessee State University
Kwasi Amoako-Gyampah University of North Carolina Greensboro
Mark Goudreau Johnson & Wales University
Mark Hanna Georgia Southern University
Mark Jacobs University of Dayton
Richard Hopfensperger Marian University of Wisconsin
Ross Fink Bradley University
Steven Dickstein Fisher College- Ohio State University
Therese Gedemer Marian University of Fond du Lac
Todd Henning Indiana University
Veena Adlakha University of Baltimore
Weiyong Zhang Old Dominion University
William Ramshaw Eastern Washington University
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xviii
Brief Table of Contents About the Authors iv Preface v
PART ONE Introduction 1 1 Introduction to Operations 2 2 Operations and Supply Chain
Strategy 20 3 Product Design 37
PART TWO Process Design 53 4 Process Selection 54 5 Service Process Design 76 6 Process-Flow Analysis 97 7 Lean Thinking and Lean
Systems 118
PART THREE Quality 141 8 Managing Quality 142 9 Quality Control and
Improvement 163
PART FOUR Capacity and Scheduling 189 10 Forecasting 190
Supplement: Advanced Methods 215
11 Capacity Planning 220
12 Scheduling Operations 249 13 Project Planning and Scheduling 267
PART FIVE Inventory 291 14 Independent Demand Inventory 292
Supplement: Advanced Models 320 15 Materials Requirements Planning
and ERP 323
PART SIX Supply Chain Decisions 347 16 Supply Chain Management 348 17 Sourcing 376 18 Global Logistics 397
PART SEVEN Case Studies 423
APPENDIXES 507
INDEX 509
ACRONYMS 519 Technical Chapters available in the Instructor’s Resource Library in Connect
Waiting Lines Simulation Transportation Method Linear Programming
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xix
Contents About the Authors iv Preface v
PART ONE INTRODUCTION 1
Chapter 1 Introduction to Operations 2 1.1 Definition of Operations and Supply Chain
Management 3 1.2 The Role of Operations and Supply Chain
Management 4 1.3 Why Study Operations and Supply Chain
Management? 6 1.4 Decisions at Pizza U.S.A. 9 1.5 Operations Decisions in the Supply
Chain—A Framework 10 1.6 Cross-Functional Decision Making 12 1.7 Operations as a Process 13 1.8 Trends in Operations and Supply Chain
Mangement 15 Sustainability 15
Services 15
Digital Technologies 16
Integration of Decisions Internally and
Externally 16
Globalization of Operations and the Supply
Chain 17
1.9 Key Points and Terms 17 Learning Enrichment 18
Discussion Questions 18
Chapter 2 Operations and Supply Chain Strategy 20 2.1 Operations Strategy Model 22
Corporate and Business Strategy 23
Operations Mission 24
Operations Objectives 24
Strategic Decisions 25
Distinctive Competence 26
2.2 Competing with Operations Objectives 27 2.3 Cross-Functional Strategic Decisions 28
2.4 Global Operations and Supply Chains 30 2.5 Supply Chain Strategy 31 2.6 Environment and Sustainable
Operations 33 2.7 Key Points and Terms 34
Learning Enrichment 35
Discussion Questions 36
Chapter 3 Product Design 37 3.1 Strategies for New Product
Introduction 38 3.2 New Product Development Process 39
Concept Development 40
Product Design 40
Pilot Production/ Testing 41
3.3 Cross-Functional Product Design 42 3.4 Supply Chain Collaboration 43 3.5 Quality Function Deployment 45
Customer Attributes 46
Engineering Characteristics 46
3.6 Modular Design 48 3.7 Key Points and Terms 49
Learning Enrichment 50
Discussion Questions 50
PART TWO PROCESS DESIGN 53
Chapter 4 Process Selection 54 4.1 Product-Flow Characteristics 55 4.2 Approaches to Order Fulfillment 60 4.3 Process Selection Decisions 63 4.4 Product-Process Strategy 64 4.5 Focused Operations 66 4.6 Mass Customization 67 4.7 3D Printing and Additive
Manufacturing 69 4.8 Environmental Concerns 70 4.9 Cross-Functional Decision Making 71 4.10 Key Points and Terms 72
Learning Enrichment 74
Discussion Questions 74
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xx Contents
Chapter 5 Service Process Design 76 5.1 Defining Service 78 5.2 Service-Product Bundle 79 5.3 Service Delivery System Matrix 80 5.4 Customer Contact 83 5.5 Service Recovery and Guarantees 86 5.6 Technology for Services 87
Artificial Intelligence 88
5.7 Globalization of Services 90 5.8 Service Profitability and Employees 92 5.9 Key Points and Terms 94
Learning Enrichment 95
Discussion Questions 96
Chapter 6 Process-Flow Analysis 97 6.1 Process Thinking 98 6.2 The Process View of Business 99 6.3 Process Flowcharting 100 6.4 Process-Flow Analysis as Asking
Questions 104 6.5 Process Analytics 106 6.6 Analyzing Process Flows at Pizza
U.S.A. 108 6.7 Process Redesign 110 6.8 Key Points and Terms 112
Learning Enrichment 113
Solved Problems 113
Discussion Questions 115
Problems 115
Chapter 7 Lean Thinking and Lean Systems 118 7.1 Evolution of Lean 119 7.2 Lean Tenets 120
Create Value 120
Value Stream 121
Ensure Flow 122
Customer Pull 123
Strive for Perfection 124
7.3 Ensure Flow 126 Stabilize Master Schedule 127
Reducing Setup Time and Lot Sizes 127
Changing Layout and Maintenance 129
Cross-Training and Engaging
Workers 130
7.4 Customer Pull 130 7.5 Changing Relationships with
Suppliers 133 7.6 Implementation of Lean 135 7.7 Key Points and Terms 137
Learning Enrichment 138
Solved Problems 138
Discussion Questions 139
Problems 140
PART THREE QUALITY 141
Chapter 8 Managing Quality 142 8.1 Quality as Customer Requirements 143 8.2 Product Quality 144 8.3 Service Quality 146 8.4 Quality Planning, Control, and
Improvement 146 8.5 Mistake-Proofing 149 8.6 Ensuring Quality in the Supply
Chain 150 8.7 Quality, Cost of Quality, and Financial
Performance 151 8.8 Quality Pioneers 154
W. Edwards Deming 154
Joseph Juran 154
8.9 ISO 9000 Standards 156 8.10 Malcolm Baldrige Award 158 8.11 Why Some Quality Improvement Efforts
Fail 160 8.12 Key Points and Terms 161
Learning Enrichment 162
Discussion Questions 162
Chapter 9 Quality Control and Improvement 163 9.1 Design of Quality Control
Systems 164 9.2 Process Quality Control 167 9.3 Attribute Control Chart 169 9.4 Variables Control Chart 170 9.5 Using Control Charts 171 9.6 Process Capability 172 9.7 Continuous Improvement 174 9.8 Six Sigma 178
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Contents xxi
9.9 Lean and Six Sigma 180 9.10 Key Points and Terms 182
Learning Enrichment 183
Solved Problems 183
Discussion Questions 186
Problems 186
PART FOUR CAPACITY AND SCHEDULING 189
Chapter 10 Forecasting 190 10.1 Forecasting for Decision Making 192 10.2 Qualitative Forecasting Methods 193 10.3 Time Series Analytics 195 10.4 Moving Average 196 10.5 Exponential Smoothing 198 10.6 Forecast Accuracy 201 10.7 Advanced Time-Series Forecasting 203 10.8 Causal Forecasting Analytics 204 10.9 Selecting a Forecasting Method 206
Big Data 207
10.10 Collaborative Planning, Forecasting, and Replenishment 208
10.11 Key Points and Terms 209 Learning Enrichment 210
Solved Problems 210
Discussion Questions 212
Problems 213
Supplement: Advanced Methods 215
Chapter 11 Capacity Planning 220 11.1 Capacity Defined 221 11.2 Facilities Decisions 223
Amount of Capacity 224
Size of Facilities 225
Timing of Facility Decisions 226
Facility Location 226
Types of Facilities 227
11.3 Sales and Operations Planning 228 11.4 Cross-Functional Nature of S&OP 230 11.5 Planning Options 231 11.6 Basic Aggregate Planning
Strategies 233 11.7 Aggregate Planning Costs 234 11.8 Aggregate Planning Example 235
11.9 Key Points and Terms 239 Learning Enrichment 240
Solved Problems 240
Discussion Questions 245
Problem 246
Chapter 12 Scheduling Operations 249 12.1 Batch Scheduling 250 12.2 Gantt Charts 251 12.3 Finite Capacity Scheduling 254 12.4 Theory of Constraints 256 12.5 Priority Dispatching Rules 258 12.6 Planning and Control Systems 260 12.7 Key Points and Terms 262
Learning Enrichment 263
Solved Problems 263
Discussion Questions 265
Problems 265
Chapter 13 Project Planning and Scheduling 267 13.1 Objectives and Trade-offs 268 13.2 Planning and Control in Projects 269 13.3 Scheduling Methods 272 13.4 Constant-Time Networks 273 13.5 CPM Method 279 13.6 Use of Project Management
Concepts 281 13.7 Key Points and Terms 282
Learning Enrichment 283
Solved Problems 284
Discussion Questions 287
Problems 287
PART FIVE INVENTORY 291
Chapter 14 Independent Demand Inventory 292 14.1 Definition of Inventory 293 14.2 Purpose of Inventories 295 14.3 Costs of Inventory 296 14.4 Independent versus Dependent
Demand 297
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xxii Contents
14.5 Economic Order Quantity 298 14.6 Continuous Review System 302 14.7 Periodic Review System 306 14.8 Using P and Q Systems in Practice 309 14.9 Vendor Managed Inventory 311 14.10 ABC Classification of Inventory 312 14.11 Key Points and Terms 313
Learning Enrichment 314
Solved Problems 315
Discussion Questions 317
Problems 317
Supplement: Advanced Models 320
Chapter 15 Materials Requirements Planning and ERP 323 15.1 The MRP System 324 15.2 MRP versus Order-Point Systems 326 15.3 Parts Explosion: How an MRP System
Works 327 15.4 MRP System Elements 332
Master Scheduling 332
Bill of Materials (BOM) 333
Inventory Records 333
Capacity Planning 334
Purchasing 334
Shop-Floor Control 334
15.5 Operating an MRP System 335 15.6 The Successful MRP System 336 15.7 Enterprise Resource Planning
Systems 337 15.8 Key Points and Terms 340
Learning Enrichment 341
Solved Problem 341
Discussion Questions 343
Problems 344
PART SIX 347 SUPPLY CHAIN DECISIONS 347
Chapter 16 Supply Chain Management 348 16.1 Supply Chain and Supply Chain
Management 349 16.2 Measuring Supply Chain Performance 351
16.3 Supply Chain Dynamics—The Bullwhip Effect 355
16.4 Improving Supply Chain Performance 358
16.5 Supply Chain Structural Improvements 358
16.6 Supply Chain System Improvements 361 16.7 Technology and Supply Chain
Management 362 E-commerce and Omni-channel
Marketing 364
Blockchain Technology 364
16.8 Supply Chain Risk and Resilience 366 Analysis of Supply Chain Risk 367
16.9 Sustainability of the Supply Chain 369 16.10 Key Points and Terms 372
Learning Enrichment 374
Discussion Questions and Problems 374
Chapter 17 Sourcing 376 17.1 Importance of Sourcing 377 17.2 Sourcing Goals 378 17.3 Insource or Outsource? 378
Advantages of Outsourcing 379
Disadvantages of Outsourcing 380
Total Cost Analysis 381
17.4 Offshoring 382 Costs of Offshoring 382
Reshoring 383
17.5 Global Sourcing 384 17.6 Supply Base Optimization 385
Spend Analysis 385
Total Number of Suppliers 385
Single or Multiple Suppliers 386
17.7 The Purchasing Cycle 387 Internal User-Buyer Interface 387
Sourcing Make-Buy Decision 388
Find Suppliers 388
Supplier Selection 388
Supplier Relationship Management 389
17.8 Challenges Facing Purchasing 389 17.9 Key Points and Terms 391
Learning Enrichment 392
Solved Problems 393
Discussion Questions 394
Problems 394
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Contents xxiii
Chapter 18 Global Logistics 397 18.1 Role of Logistics in Supply Chain
Management 398 18.2 Transportation 400
Transportation Economics 400
Modes of Transportation 401
Selecting the Transportation Mode 404
18.3 Distribution Centers and Warehousing 405 18.4 Logistics Networks 408
Location 408
Number of Warehouses (Distribution
Centers) 411
18.5 Global Logistics 412 18.6 Third-Party Logistics Providers 414 18.7 Logistics Strategy 416 18.8 Key Points and Terms 418
Learning Enrichment 419
Solved Problems 419
Discussion Questions 421
Problems 421
PART SEVEN CASE STUDIES Introduction 423
Operations Strategy at BYD of China, Electrifying the World’s Automotive Market 424
Early Supplier Integration for John Deere Skid-Steer Loader 430
Process Design
Eastern Gear, Inc.: Job Shop 432 Sage Hill Inn Above Onion Creek: Focusing
on Service Process and Quality 435 U.S. Stroller: Lean 439 The Westerville Physician Practice: Value
Stream Mapping 445
Quality
Mayo Clinic and the Path to Quality 449 Toledo Custom Manufacturing: Quality
Control 455 The Evolution of Lean Six Sigma at
3M, Inc. 457
Capacity and Scheduling
Best Homes, Inc.: Forecasting 463 Polaris Industries Inc.: Global Plant
Location 465 Lawn King, Inc.: Sales and Operations
Planning 470
Inventory
Consolidated Electric: Inventory Control 474
Southern Toro Distributor, Inc. 479 ToysPlus, Inc.: MRP 485
Supply Chain
Amazon Revolutionizes Supply Chain Management 489
Altimus Brands: Managing Procurement Risk 496
Murphy Warehouse Company: Sustainable Logistics 499
ShelterBox: A Decade of Disaster Relief 503
APPENDIXES A Areas Under the Standard Normal
Probability Distribution 507 B Random Number Table 508
INDEX 509
ACRONYMS 519
Online Technical Chapters Technical Chapters available in the
Instructor’s Resource Library in Connect
Waiting Lines Simulation Transportation Method Linear Programming
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1. Introduction to Operations
2. Operations and Supply Chain Strategy
3. Product Design
The introductory part of this text provides an overview of operations management in the supply chain. In Chapter 1 students gain an appreciation for the importance to the firm of decisions made in the operations function and its associated supply chain. In Chapter 2 the need for strategy to guide all decision making is emphasized. In Chapter 3 new product design is treated as a cross- functional decision responsibil- ity that precedes the production and delivery of goods or services. ■
Pa rt i
Introduction
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2
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The operations and supply chain management field deals with the production of goods and services and management of the associated supply chain. Every day we come in contact with an abundant array of goods and services, all of which are produced by the operations function within the firm. Without management of operations and its associated supply chain, a modern industrialized society cannot exist. The operations function is the engine that creates goods and services for the firm and in aggregate the global economy.
Supply chains are critical in supporting operations within the firm. Supply chains con- sist of a network of organizations outside the firm that supply the materials and services to the firm and distribute the product or service to the ultimate customer. A global supply chain engages in all the activities and processes needed to plan, source, make, deliver, and return or dispose of a set of products or services. Managing the supply chain is essential in addition to managing internal operations of the firm.
1 c h a p t e r
Introduction to Operations
LO1.1 Define operations and supply chain management.
LO1.2 Review the role of operations in the firm and the economy.
LO1.3 Describe the five main decisions made by operations and supply chain managers.
LO1.4 Explain the nature of cross-functional decision making with operations.
LO1.5 Describe typical inputs and outputs of an operations transformation system.
LO1.6 Analyze trends in operations and supply chain management.
After reading this chapter you should be able to:LEARNING OBJECTIVES
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This book deals with operations management in the supply chain. This means we take a supply chain per- spective to traditional operations. We take ideas from operations management within the firm and combine them with a view of the entire supply chain.
At first glance it may appear that service operations have little in common with manufacturing operations. However, the unifying feature of these operations is that both can be viewed as transformation processes inside organizations that are themselves embedded in supply chains. In manufacturing, inputs of materials, energy, labor, and capital are transformed into finished goods for customers. In service operations, the same types of inputs are transformed into services, for example, sur- geries in hospitals. Managing transformation processes in an efficient and effective manner is the task of the operations manager in any organization.
Most Western economies have shifted dramati- cally from the production of goods to the production of services. It may come as a surprise that more than 80 percent of the U.S. workforce is employed in service industries.1 Even though the preponderance of employ- ment is in the service sector, manufacturing remains important to provide goods needed for export and inter- nal consumption. Because of the importance of both service and manufacturing operations, they are treated on an equal basis in this text.
In the past when the field was primarily related to manufacturing, operations management was called pro- duction management. Later, the name was expanded to operations management to include both manufacturing and service industries. Now it has been expanded again
to operations and supply chain management to include not only operations, but also its associated supply chain.
1.1. DEFINITION OF OPERATIONS AND SUPPLY CHAIN MANAGEMENT
Operations management is defined as managing the production of goods and services. The focus is on production within an organization, for example, production within the four walls of a factory or within multiple factories in a company. Similarly, production of services is treated as within individual service locations or across multiple locations within a single company.
Operations management focuses on decisions for the internal production of the firm’s products or services.
1 U.S. Census Bureau, Statistical Abstract of the U.S., Washington, D.C. 2019 ed.
LO1.1 Define operations and supply chain management.
Apple manages a complex supply chain and operations across the globe. Jill Braaten/McGraw-Hill Education
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4 Part One Introduction
Supply chain management deals with managing the flow of materials, information, and money across multiple organizations from the suppliers to operations to distribution to the final customer, along with reverse flows. The entire supply chain is included from the raw materials through suppliers, factories, warehouses, and retailers to the ultimate customer as shown in Figure 1.1. Reverse flows also occur in the supply chain for returned products, recycled products, and information.
Operations and supply chain management deals with the sourcing, production and distribu- tion of the product or service along with managing the relationships with supply chain partners.
This definition expands the notion of operations and reflects the role of operations in the supply chain. It adds sourcing and distribution to the traditional definition of operations, and it adds managing the relationships/interactions with supply chain partners. Sourcing, also called purchasing, works with manufacturing and service suppliers of the firm and is part of the larger definition of operations and supply chain management. Distribution, also called logistics, is concerned with transporting materials into operations and taking the output of operations to the ultimate customer. Operations and supply chain management must be concerned with managing not only the internal operations of the firm, but also the relationships and processes shared with supply chain partners along the supply chain.
This text brings together two previously separate fields of operations management and supply chain management into what is called operations and supply chain management. While operations management is concerned with the internal operations of the firm, sup- ply chain management adds external relationships with other firms.
Moreover, every organization along the supply chain needs to manage its own operations together with the relationship with the rest of the supply chain partners. Thus operations management appears in the suppliers, the factories, the wholesalers, and the retail companies, since each of them is producing a product or service that is passed along the supply chain.
1.2 THE ROLE OF OPERATIONS AND SUPPLY CHAIN MANAGEMENT
All countries are dependent on economic growth as measured by their GDP (Gross Domestic Product). GDP is the monetary value of all the goods and services produced within a country’s borders. GDP growth leads not only to prosperity of the country, but income growth for the population, since income is closely related to GDP per capita.
LO1.2 Review the role of operations in the firm and the economy.
FIGURE 1.1 A typical supply chain.
Suppliers Suppliers Factories Warehouses Retail Customers
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Productivity is the amount of output from a given amount of inputs or vice versa. It is one factor that leads to economic growth and profitability of the firm. More output over time from the same resources increases GDP and allows people to get more of what they want beyond mere survival. Operations and supply chain management plays a central role in achieving GDP growth and productivity not only for individual companies but, in aggre- gate, for the entire economy of a country.
Productivity is output divided by inputs, all in constant dollars. Since price changes should not affect productivity, constant dollars are used.
Productivity = output ____________ capital + labor
If the same output can be achieved by less capital and labor, productivity will improve. Vice versa, more output achieved from the same levels of capital and labor will also improve productivity. Productivity ratios can be calculated at the firm, industry, and national levels.
Henry Ford believed in producing a reliable automobile at the lowest possible cost to be affordable for all Americans. He represented the epitome of productivity improvement by using better production line design and labor training to produce more output at lower costs, illustrating the power of production in improving productivity and profits, and pro- viding higher wages to employees. This story has been repeated thousands of time in many industries, even to the present time. See the Operations Leader box for how Dell drives productivity and value for its customers.
How are productivity growth and firm profitability achieved? It is only through the creativity, imagination, and innovation of operations and supply chain employees,
Orders for products, once taken, are assembled in one of Dell’s factories and often shipped to customers or retail stores within days, with the factories carrying very little finished goods inventory.
In addition to the importance of the operations func- tion at Dell, sourcing and logistics activities are criti- cal. Sourcing managers source the many components required to manufacture Dell products, and logistics managers handle the global movement of components and finished goods to satisfy customer demand. Manag- ing Dell’s fast and rapidly changing supply chain is a chal- lenging task that they perform well.
Dell today is pursuing environmentally friendly best practices: Its global headquarters campus is now pow- ered by 100 percent green energy; its desk computer systems have been designed to reduce carbon dioxide emissions; Dell was the first computer manufacturer to offer free computer recycling to customers worldwide; and its “Plant a Tree for Me” and “Plant a Forest for Me” programs have planted over 600,000 trees.
Source: Adapted from www.dell.com, 2019.
In 1984 Michael Dell founded Dell Computer Corporation with $1000 in start-up capital and a business model to sell custom-configured personal computers directly to cus-
tomers while passing along cost savings to customers by cutting out the middlemen. The company offers a range of products beyond personal desktop and mobile com- puting products; servers, storage, and networking products; print-
ing and imaging products; electronics and accessories; enhanced business and consumer services; and busi- ness solutions. Nearly half of Dell’s revenue comes from outside of the U.S.
A key to Dell’s strategy is its customer-driven approach to innovation. This approach signals a commit- ment to delivering new products and services that are valued by customers and that address customer needs while improving productivity. This approach explains how Dell pioneered the direct-selling system to allow customer orders to be placed over the Internet or over the phone and, since 2007, through select retail outlets.
Dell Delivers Productivity and Value
OPERATIONS LEADER
Pe3k/Shutterstock
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6 Part One Introduction
managers, and executives. This can be done through innovative product or service design, but also through continuous improvement of the production process and supply chain. A large component of this is achieved through automation, but also the imagination of designers and operations managers for both product and process improvements. It is the responsibility of operations and supply chain managers to improve profitability and pro- ductivity for the firm.
Below is a simple example of a computation of labor productivity in a firm.2
2 For simplicity we consider only labor inputs for the partial labor productivity ratio. A total productivity ratio would include both capital and labor, and perhaps energy and materials inputs, as well.
For a firm with the following labor and output numbers, calculate the rate of labor pro- ductivity change assuming annual labor inflation of 3 percent and annual output (sales) inflation of 2 percent.
Year 1 Year 2 Annual Inflation
Output (sales) $million $56.7 $64.8 2%
Labor (payroll) $million $23.4 $26.6 3%
Labor productivity year 1 = Output year 1
___________ Labor year 1
= 56.7
____ 23.4
= 2.42
Labor productivity year 2 = Deflated output year 2
__________________ Deflated labor year 2
= 64.8(.98)
________ 26.6(.97)
= 2.46
Change in productivity = 2.46
____ 2.42
= 1.016 which is a 1.6% increase
Notice, both the output and input in year 2 have been adjusted for inflation between year 1 and year 2. The productivity increase achieved by operations and supply chain managers in one year is 1.6 percent.
Example
Productivity improvement is not the only way to increase GDP and prosperity in a coun- try. Just being more efficient is not enough, if there is no longer demand for the product. Therefore, GDP growth requires innovation and new product development to meet the evolving needs of markets. As a result, productivity improvement and innovation are two of the most important factors that affect GDP growth, firm output, and firm profitability. Operations and supply chain managers have a key role in introducing new products and achieving scale-up of production. They also participate in product design teams consist- ing of design, marketing, and finance managers. In this way they contribute to both new product innovation and productivity improvement for existing products and ultimately the profitability of the firm and GDP growth.
1.3 WHY STUDY OPERATIONS AND SUPPLY CHAIN MANAGEMENT?
For students majoring in operations and supply chain management this will be an intro- ductory course to the subject. This major leads to challenging and interesting jobs both in domestic and international industries ranging from entry level to middle management
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and top management positions. Some of these positions in both service and manufacturing industries are illustrated in the Operations Leader box on careers in operations and supply chain management.
For non-majors this course is important to gain an understanding of what operations does and its interactions with other functions within the firm and its supply chain. Every decision is cross-functional in nature.3 You will be working with operations and need to understand it no matter what career path you choose. The organization in which someone works only with people from his or her own function does not exist. That is why we take a cross-functional perspective in this text, so the content is useful to the majority of students who are not majors.
3 The “handshake” symbol in the margin identifies a point of cross-functional emphasis and is designed to illustrate that the various functions must work together for an organization to be successful and thrive.
all operations functions associated with branches and cen- tral operations. This individual will participate in the devel- opment of strategic implementation plans and related objectives. Candidates must have strong communication skills and acknowledge the important relationship with customer members in supporting the credit union’s vision and mission.
CONTINUOUS IMPROVEMENT PLANT LEAD ConAgra Foods seeks a partner to roll out a system establishing a zero-loss manufacturing culture. Coordi- nating with the Plant Manager, this Plant Lead executes plans for sustainability, develops and maintains training and tracking standards, and coaches sites on improve- ment methodologies. This position serves as a key development role for a future Plant Manager.
MATERIALS SOURCING MANAGER Herbalife, a direct-sales nutrition company, is hiring a senior-level sourcing manager for global spending of $200 million on raw materials. Responsibilities include reducing raw materials costs yearly, analyzing market intelligence for trends in commodity markets, and mak- ing strategic recommendations to senior management for each category of raw materials. This job also requires maintaining appropriate inventory levels and developing strategic supplier relationships.
Source: Abstracted from www.monster.com.
SUPPLY CHAIN ANALYST PayPal, owned by online shopping site eBay, is hiring a supply chain management professional responsible for end-to-end support for PayPal’s new Here product. The
job requires international travel to manufacturing and distribution sites. Responsibilities include product and distribution manage- ment, on time and on budget; reviewing inventory reports with supply partners; arranging freight shipments globally; and coordi-
nating and collaborating with internal groups within Pay- Pal and eBay. The job description also requests “maniacal attention to detail.”
BUSINESS METRICS/ANALYTICS SUPPLY CHAIN ANALYST Cardinal Health is seeking an analyst to develop, quan- tify, and evaluate the transformation of internal and external information into business intelligence. Qualified candidates will demonstrate knowledge of concepts and principles of business metrics and analytical techniques/ tools. The position requires listening to internal/external customers’ needs and proactively providing them a qual- ity experience through effective communication.
VICE PRESIDENT OF OPERATIONS Envista Credit Union is seeking an executive whose responsibilities include organizing, planning, and directing
Careers in Operations and Supply Chain from Monster.com
OPERATIONS LEADER
NetPics/Alamy Stock Photo
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8 Part One Introduction
As you study operations, you will find that many of the ideas, techniques, and prin- ciples can be applied across the business, not just in operations. For example, all work is accomplished through a process (or sequence of steps). The principles of process think- ing found in this text can be applied to all parts of business. Toyota, for example, uses lean thinking to improve processes in human resources, accounting, finance, information systems, and even the legal department. Many students find that the ideas learned in this course can be applied to their own department, career, or functional responsibilities and are useful to non-majors.
Operations and supply chain management is an exciting and challenging field of study. The ideas that you learn are both qualitative and quantitative, and both are essential to good management practice. You are embarking on a journey that is interesting and useful no matter what career you choose!
There are three aspects of operations and supply chain management that require elaboration:
1. Decisions. Since managers make decisions, it is natural to focus on decision mak- ing as a central theme in operations. Within the broader context of supply chain, this decision focus provides a basis for identifying major decision types. In this text, we specify the five major decision responsibilities of operations and supply chain management as process, quality, capacity, inventory, and supply chain. These deci- sions provide the framework for organizing the text and describing what operations and supply chain managers do. We will discuss these decisions in greater detail in subsequent chapters.
2. Function. Operations is a major function in any organization, along with market- ing and finance. In a manufacturing company, the operations function typically is called the manufacturing or production department. In service organizations, the operations function may be called the operations department or some name peculiar to the particular industry (e.g., the policy service department in insurance compa- nies). In general, the generic term “operations” refers to the function that produces and delivers goods or services. While separating operations out in this manner is useful for analyzing decision making and assigning responsibilities, we must also integrate the business by considering the cross-functional nature of decision making in the firm.
3. Process. Operations managers plan and control the transformation process and its interfaces in organizations as well as across the supply chain. This process view is a powerful basis for the design and analysis of operations in an organization and across the supply chain. Using the process (or systems) view, we consider operations and sup- ply chain managers as designers of the conversion process in the firm. But the process view also provides important insights for the management of productive processes in functional areas outside the operations function. For example, a sales office may be viewed as a production process with inputs, transformation, and outputs. The same is true for an accounts payable office and for a loan office in a bank. In terms of the pro- cess view, operations management concepts have applicability beyond the functional area of operations.
Since the field of operations and supply chain management can be defined by deci- sions, function, and processes, we will expand on these three elements in detail in this chapter. But first we provide an example of the decisions that would be made by operations and supply chain management in a typical company that makes and markets pizzas.
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1.4 DECISIONS AT PIZZA U.S.A.
Pizza U.S.A., Inc., produces and markets pizzas on a national basis. The firm consists of 285 company-owned and franchised outlets (each called a store) in the U.S. The opera- tions function in this company exists at two levels: the corporate level and the level of the individual store.
The major operations and supply chain decisions made by Pizza U.S.A. can be described as follows:
Process Corporate staff makes some of the process decisions, since uniformity across different stores is desirable. They have developed a standard facility design that is sized to fit a par- ticular location. Each store incorporates a limited menu with equipment that is designed to produce pizza to customer orders. As pizzas are made, customers can watch the process through a glass window; this provides entertainment for both children and adults as they wait for their orders to be filled. Because this is a service facility, special care is taken to make the layout attractive and convenient for the customers.
Within the design parameters established by the corporate operations staff, the store managers seek to improve the process continually over time. This is done both by addi- tional investment in the process and by the use of better methods and procedures, which often are developed by the employees themselves. For example, a store might re-arrange its layout to speed up the process of producing pizzas.
Quality Certain standards for quality that all stores must follow have been set by the corporate staff. The standards include procedures to maintain service quality and ensure the quality and food safety of the pizzas served. While perceptions of service quality may differ by customer, the quality of the pizzas can be specified more exactly by using criteria such as temperature at serving time and the amount of raw materials used in relation to standards, among others. Service-quality measures include courtesy, cleanliness, speed of service, and a friendly atmosphere. Service quality is monitored by store manager observation, comment cards, and occasional random surveys. Each Pizza U.S.A. store manager must
carefully monitor quality internally and with suppli- ers to make sure that it meets company standards. All employees are responsible for the quality of their work to ensure that service quality and food quality are meet- ing the standards of the company.
Capacity Decisions about capacity determine the maximum level of output of pizzas. The capacity available at any point in time is determined by the availability of equipment and labor inputs for the pizza-making process at that time. First, when the initial location and process deci- sions are made, the corporate staff determines the phys- ical capacity of each facility. Individual store managers then plan for annual, monthly, and daily fluctuations in capacity within the available physical facility. Dur- ing peak periods, they may employ part-time help, and
LO1.3 Describe the five main decisions made by operations and supply chain managers.
Pizza U.S.A. satisfies its customers by carefully managing the four key decision areas in operations. Steve Mason/Getty Images
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10 Part One Introduction
advertising is used in an attempt to raise demand during slack periods. In the short run, individual personnel are scheduled in shifts to meet demand during store hours.
Inventory Each store manager buys the ingredients required to make the recipes provided by corpo- rate staff. The store managers decide how much flour, tomato paste, sausage, and other ingredients to order and when to place orders. Store operators must carefully integrate sourcing and inventory decisions to control the flow of materials in relation to capacity. For example, they do not want to purchase ingredients for more pizzas than they have the capacity to bake. They also do not want to run out of food during peak periods or waste food when demand is low.
Supply Chain The supply chain decisions consist of sourcing and logistics. Sourcing is done by the cor- porate office. They select the specific suppliers for all inputs, negotiate prices, write con- tracts, and issue blanket purchase orders that stores use to order individual ingredients and items as they need them. The orders are then fulfilled by the suppliers, and a logistics provider ensures the orders are delivered on time. Logistics is handled by a third-party provider who secures transportation and uses its distribution centers to make deliveries to Pizza U.S.A. stores.
1.5 OPERATIONS DECISIONS IN THE SUPPLY CHAIN—A FRAMEWORK
The five decision groupings showcased in the Pizza U.S.A. example provide a framework for understanding the various decisions made by operations and supply chain managers. Although many different frameworks are possible, the primary one used here is a conceptual scheme for grouping decisions according to decision respon- sibilities. The five key decision areas—process, quality, capacity, inventory, and sup- ply chain—encompass what operations and supply chain managers do. This novel and useful decision framework is shown in Figure 1.2. Notice how the five decision areas in the figure apply not only to the firm, but to the supplier and the distributor, since all three must make the same types of decisions in managing their own operations and coordinating those decisions across the supply chain. In Table 1.1, examples are given of key decisions in each area.
FIGURE 1.2 Decision-making framework for operations in the supply chain. The Firm
Process
Quality
Capacity
Inventory
Supply Chain
Decisions
Human Resources Finance
Marketing
Accounting Information
Systems
Supplier
Process
Quality
Capacity
Inventory
Supply Chain
Decisions Process
Quality
Capacity
Inventory
Supply Chain
Decisions
Distributor
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TABLE 1.1 Operations and Supply Chain Decisions—A Framework
Decisions Examples of Decisions
1. Process • What type of process should be selected? • How should the service delivery system be designed? • How should material and customer flows be managed? • What principles of lean systems should be deployed? • How should environmental and global goals be met?
2. Quality • What should the quality standards be? • How can quality be controlled and improved? • What statistical approaches should be used (e.g., control charts and
Six Sigma)? • How should the suppliers and customers be involved in quality?
3. Capacity • What is the facility strategy for size, location, and timing? • How should Sales and Operations Planning be implemented? • How should variable demand be handled with capacity adjustments? • What priority rule should be used for scheduling?
4. Inventory • How much inventory should be held? • What should the order size and reorder frequency be? • Who should hold the inventory? • How can the inventories of suppliers and customers be coordinated?
5. Supply Chain • What suppliers should be used for products and services? • How should sourcing be conducted and evaluated? • What form of transportation should be used? • How should warehouses be used to allow economic flow of materials?
Careful attention to the five decision areas in the framework is the key to the successful management of operations and the associated supply chain. Indeed, well-managed opera- tions and its supply chain can be defined in terms of this decision framework. If decisions in each of the five groupings support the strategy of the firm, provide value, and are well integrated with the other functions of the organization, the operations function and its associated supply chain can be considered well managed.
Each major section of this text is devoted to one of the five decision categories.4 The framework thus provides an integrating mechanism for the text that covers both the deci- sions faced by operations and supply chain managers as well as the cross-functional issues that must be considered.
The five decisions areas of operations and supply chain can be compared to the 4 Ps of marketing: product, price, place, and promotion. These four Ps in the marketing mix are the tools or decision types that marketing managers can use to influence demand. In a similar way the five decision types of operations and supply chain can be used to influence supply and must be compatible and consistent with the 4 Ps of marketing. They are just two sides of the same coin, one influencing demand and the other supply.
Analytics is the analysis of data to make better decisions. Analytics uses many tech- niques for the analysis including those from operations research, statistics, data sciences, and computer science. The analysis can use either big data from massive databases or small data depending on the application. Analytics can be descriptive, predictive, or pre- scriptive in nature. A descriptive analysis typically summarizes the present situation from data. The data can be used to go one step further and predict what will happen in the future. Prescriptive analytics typically uses mathematical models to find an optimal or best deci- sion. Analytics are used in operations and supply chains for a variety of decisions, includ- ing quality control, forecasting, capacity, scheduling, inventory, logistics, and sourcing.
4 Students have called these five categories QPICS, Quality, Process, Inventory, Capacity, and Supply chain, pronounced “Q-PICS.”
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12 Part One Introduction
Throughout the text, best practices are presented. Additionally, discussion and examples of firms in which the best practice is not the best for their particular situation are included. These contingencies, situations, or conditions that require different solutions offer a more nuanced view of operations decision making. For example, successful implementation of a new method such as lean or Six Sigma is contingent on top management support. Simi- larly, the “best” forecasting tools and concepts depend on the availability of data. If there was a single best practice that works for all firms, then operations would not be the chal- lenging function to manage that it is. Therefore, by offering insight into specific conditions in which best practices may not be best, the text addresses the various contingencies or prerequisites or situations that need to be considered.
1.6 CROSS-FUNCTIONAL DECISION MAKING
The operations function is a critical element in every business. No business can survive without good decisions being made by operations managers. The operations function is one of the three primary functions in an organization, along with marketing and finance. In addition, an organization has supporting functions that include human resources, infor-
mation systems, and accounting. Some organizations also have separate sourcing and logistics functions that support operations. In others, the operations, sourcing, and logistics functions are joined together to become the supply chain function.
Functional areas are concerned with a particular focus of responsibility or decision making in an organization. The market- ing function is typically responsible for creating demand and gen- erating sales revenue; the operations function is responsible for the production and distribution of goods or services (generating supply); and finance is responsible for the acquisition and alloca- tion of capital. Within for-profit businesses, functional areas tend to be closely associated with organizational departments because businesses typically are organized on a functional basis. Support- ing functions are essential to provide staff support to the three primary functions.
Every function must be concerned not only with its own deci- sion responsibilities but also with integrating decisions with other functions. The five areas of operations and supply chain decisions, for example, cannot be made sepa- rately; they must be carefully integrated with one another and, equally important, with decisions made in marketing, finance, and other parts of the organization. In the Pizza U.S.A. example, if marketing decides to change the price of pizza, this is likely to affect sales and change the capacity needs of operations as well as the amount of ingre- dients (materials) used. Also, if finance cannot raise the necessary capital, operations may have to redesign the process to require less capital or manage pizza-related inven- tories more efficiently. This in turn may affect the response time to serve customers, costs, and so on.
Decision making is therefore highly interactive and systemic in nature. Unfortunately, functional silos have developed in many organizations and impede cross-functional deci- sion making. As a result, the overall organization suffers due to an emphasis on functional prerogatives. In a similar way, the five decisions need to be coordinated externally with supply chain partners. If capacity of the firm is increased, the capacity of suppliers and distributors must also be increased. The same can be said about coordination of decisions about inventory, quality, sourcing, and logistics.
LO1.4 Explain the nature of cross-functional decision making with operations.
Managerial decision making is cross-functional in nature. ammentorp/123RF
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But some companies are different. Texas Instruments, for example, has been a leader in fostering cross-functional integration. Some companies have done a very good job of cross- functional management. They do this by forming cross-functional teams for new product introductions and for day-to-day improvement. Each member of the team is trained in com- mon methodologies, and the team is given responsibility for achieving its own goals. Some of the key cross-functional decision-making relationships are shown in Table 1.2.
1.7 OPERATIONS AS A PROCESS
Operations can be defined as a transformation system (or process) that converts inputs into outputs. Inputs to the system include energy, materials, labor, capital, and information (see Figure 1.3). Process technology is then used to convert inputs into outputs. The pro- cess technology is the methods, procedures, and equipment used to transform materials or inputs into products or services.
Viewing operations as a process is very useful in unifying seemingly different opera- tions from different industries. For example, the transformation process in manufacturing is one of material conversion from raw materials into finished products. When an automo- bile is produced, steel, plastics, aluminum, cloth, and many other materials are transformed into parts that are then assembled into the finished automobile. Labor is required to operate
LO1.5 Describe typical inputs and outputs of an operations transformation system.
TABLE 1.2 Examples of Cross-Functional Decision Making
Key Decision Area Interface with Operations Decisions
Marketing Market segment and needs Quality design and quality management Market size (volume) Type of process selected (assembly line, batch, or project) and capacity required
Distribution channels Inventory levels and logistics Pricing Quality, capacity, and inventory New product introduction Cross-functional teams
Finance and Accounting Availability of capital Inventory levels, degree of automation, process type selected, and capacity Efficiency of conversion process Process type selection, process flows, value-added determination and sourcing
Net present value and cash flow Automation, inventory, and capacity Process costing or job costing Type of process selected Measurement of operations Costing systems used
Human Resources Skill level of employees Process type selected and automation Number of employees and part-time or
full-time employment Capacity and scheduling decisions
Training of employees Quality improvement and skills Job design Process and technology choice Teamwork Cross-functional decisions in operations
Information Systems Determination of user needs Systems should support all users in operations Design of information systems Systems should help streamline operations and support all analytics and
decisions in operations
Software development Software is needed for capacity, quality, inventory, scheduling, and supply chain decisions
Hardware acquisition Hardware is needed to support automation decisions in operations and to run software
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14 Part One Introduction
and maintain the equipment, and energy and information are also required to produce the finished automobile.
In service industries a transformation process is also used to transform inputs into ser- vice outputs. For example, airlines use capital inputs of aircraft and equipment and human inputs of pilots, flight attendants, and support personnel to produce safe, reliable, fast, and efficient transportation. Transformations of many different types occur in all industries, as indicated in Table 1.3. By studying these different types of transformation processes, you can learn a great deal about how to analyze and manage any operation.
Operations as a process provides a basis for seeing an entire business as a system of interconnected processes. This makes it possible to analyze an organization and improve it from a process point of view. All work, whether in finance, marketing, accounting, or other functions, is accomplished by processes. For example, financial analysis of a stock, closing the books at the end of the year, or conducting market research are each conducted by carrying out an appropriate process. Thus, process principles and tools can be applied in every function in a business.
All of these processes and systems interact with their internal and external environments. We have indicated the nature of internal interaction through cross- functional decision making. Interaction with the external environment occurs through the economic, physical, social, and political environment of operations. Examples include
FIGURE 1.3 An operation as a productive system.
OPERATIONS MANAGEMENT OUTPUTSINPUTS
EXTERNAL BUSINESS ENVIRONMENT
NATURAL ENVIRONMENT
Transformation (conversion)
process
Energy
Materials
Labor
Capital
Information
Goods or services
Feedback information for control of process inputs and process technology
TABLE 1.3 Examples of Productive Systems
Operation Inputs Outputs
Bank Tellers, staff, computer equipment, facilities, and energy
Financial services (loans, deposits, safekeeping, etc.)
Restaurant Cooks, waiters, food, equipment, facilities, and energy
Meals, entertainment, and satisfied customers
Hospital Doctors, nurses, staff, equipment, facilities, and energy
Health services and healthy patients
University Faculty, staff, equipment, facilities, energy, and knowledge
Educated students, research, and public service
Manufacturing plant Equipment, facilities, labor, energy, and raw materials
Finished goods
Airline Planes, facilities, pilots, flight atten- dants, maintenance people, labor, and energy
Transportation from one location to another
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economic changes such as rising labor costs, social changes such as customer preference for “green” products, and political changes such as regulations. Each of these can mean that the operations function and associated supply chain will have to change the way it was producing products and services.
Operations is surrounded by both internal and external environments and constantly interacts with them. The interactive nature of these relationships makes it necessary to constantly monitor the environment and make decisions related to corresponding changes in operations and the supply chain when needed. In the fast-changing world of today’s global business, constant change has become essential as a means of survival. Viewing operations as a process or a constantly updating transformation system helps us understand how operations and the supply chain cannot be insulated from changes in the environment but rather must adapt to them.
1.8 TRENDS IN OPERATIONS AND SUPPLY CHAIN MANGEMENT
Operations and supply chain managers face serveral opportunities and trends that will be addressed repeatedly throughout this text. These trends make operations and supply chain management an exciting and interesting career for future leaders.
The focus on sustainability of the natural environment has been heightened in recent years with concerns over global warming, water contamination, air pollution, and so on. Organizations are increasingly being asked to produce and deliver products or services while minimizing the negative impact on the global ecosystem and not endangering the ability to meet the needs of future generations. See the Operations Leader box titled “Sustainability in Interface Inc.’s Operations Transformation Pro- cess” for an example of one firm’s success in facing these issues. Operations and supply chain partners have made tremendous strides in reducing pollution of the envi- ronment from air to ground to water, but there is still a long way to go. Operations and its supply chain are going beyond environmental sustainability to include social and economic sustainability: the so-called triple bottom line. Social sustainability means hiring a diverse workforce, ethical practices, providing equal opportunity, and safe working conditions, for example. Economic sustainability is making a sufficient profit for firm survival into the future. Operations and their supply chains are find- ing they can reduce pollution, conserve resources, recycle products, and be socially responsible to provide a sustainable world for future generations. Sustainability is an opportunity that progressive operations and supply chain organizations are pursuing. For more details, see the sustainability link in the Learning Enrichment box at the end of this chapter.
Operations concepts and ideas have been applied in service operations for years. Yet, service operations lag behind manufacturing in applying the latest ideas in supply chain management, lean operations, and quality improvement. This represents a tremendous opportunity to apply what is learned in this course. Also, service-specific ideas such as service recovery, web-enabled service, and globalization of service still represent imple- mentation challenges. Nevertheless, some leading service businesses do excel in opera- tions including Walmart, Nordstrom, Starbucks, Amazon.com, FedEx, and Delta Airlines, to name only a few. They excel by applying many of the operations concepts that are pre- sented in this text.
LO1.6 Analyze trends in operations and supply chain management.
Sustainability
Services
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16 Part One Introduction
Emerging digital technologies that operations and supply chain managers are implement- ing include artificial intelligence, blockchain, 3D printing, and data analytics. Artificial intelligence is used in manufacturing and services to perform complex tasks that require human learning. Block chain technology is used to secure information that is passed along the supply chain. 3D printing is used to rapidly make prototypes or custom products. All of these technologies and analytics are discussed throughout this text.
A difficult opportunity and challenge facing all managers is cross-functional integration within the organization. Some organizations are managing functions as separate depart- ments with little integration across them. The best operations are now seeking increased integration through the use of cross-functional teams, information systems, management coordination, rotation of employees, and other methods of integration. Most of the imple- mentation problems of new systems or new approaches can be traced to lack of cross- functional internal cooperation. The same thing can be said about interorganizational change in supply chains. Even when companies partner with their suppliers or customers the partnerships are often not successful. Adequate information systems may also be lack- ing for supply chain integration.
Digital Technologies
Integration of Decisions Internally and Externally
With production on four con- tinents and offices in more than 100 countries, Interface Inc. is the global leader in the design, production, and sales of modu- lar carpet squares. Since under- taking the goal of sustainability, Interface Inc. reports more than 133 million pounds of post- consumer carpet waste has been diverted from landfills to serve as raw materials for new carpet squares. They have achieved a series of major milestones at the European manufacturing facility in The Netherlands. As of 2015, the plant is operating with 100 percent renewable energy, using virtually zero water in man- ufacturing processes and has attained zero waste to landfill.
Source: Adapted from Dave Gustashaw and Robert W. Hall, “From Lean to Green: Interface, Inc.,” Target 24, no. 5 (2008), pp. 6–14 and interfaceglobal.com 2019.
The philosophy of sustain- ability is “meeting the needs of the present without com- promising the ability of future generations to meet their own needs.” Over the past 15 years, carpet manufacturer Interface Inc. has shifted its operations toward this philosophy and tri- ple bottom-line impacts: social, environmental, and financial. Or, in their words: People, Planet, and Profit.
Following production, cus- tomers use and then dispose of carpet products. Interface Inc. set out to change this typi- cal supply chain. Creating a closed-loop supply chain, they use their own post-consumer waste (used carpet) as raw material input to their produc- tion system. It is not a perfect system, as it still requires some newly extracted raw materials, but they believe they are moving in the right direction for achieving sustainability.
Sustainability in Interface Inc.’s Operations Transformation Process
OPERATIONS LEADER
Arcaid Images/Alamy
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Finally, the globalization of operations and supply chains is a pervasive theme in business today. One can hardly avoid information on the accelerat- ing nature of global business. Strategies for operations and its supply chain partners should be formulated with global effects in mind. Even many small businesses compete glob- ally, sourcing or selling goods and services in markets with global competitors. Facility location must be considered in view of its global implications. Technology can be transferred rapidly across national borders. All decisions in operations and its associated supply chains are affected by the global nature of business.
1.9 KEY POINTS AND TERMS
This text provides a broad overview of the challenging and dynamic field of operations management and the supply chain. It stresses decision making in operations, its associated supply chain, and the relationship of these decisions to other functions. The five major decision categories—process, quality, capacity, inventory, and supply chain are the orga- nizing framework for each of the five major sections in the text.
Key points emphasized in the chapter are these:
∙ Operations and its associated supply chain produces and delivers goods or services deemed to be of value to customers in a global economy. Operations and supply chain management is responsible for productivity, innovation and GDP growth in aggregate. Without operations and supply chain management a firm, industry, and country can- not prosper.
∙ Operations and supply chain management focuses on decisions for the production, sourcing, and delivery of the firm’s products and services. These decisions are intended to maximize firm profitability and the value inherent in goods or services delivered to customers throughout the entire supply chain.
∙ The supply chain is the network of manufacturing and service operations that supply each other from raw materials through manufacturing to the ultimate customer. The supply chain consists of the physical flow of materials, money, and information along the entire chain of suppliers, production, and distribution and the reverse supply chain of recycled and returned products and information. The supply chain connects many different organizations.
∙ There are five key groupings of decisions in operations and supply chain management: process, quality, capacity, inventory, and supply chain. These decisions need to utilize analytics when appropriate and account for contingencies, or special situations, because a best practice may not be best in all circumstances.
Globalization of Operations and the Supply Chain
Coke is produced and sold globally. StreetVJ/Shutterstock
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18 Part One Introduction
∙ Operations and supply chain decisions are often cross-functional in nature. Decisions may impact or be impacted by activities in other functions such as marketing and finance. Often, cross-functional teams are formed to undertake complex decisions.
∙ We identify several opportunities and trends facing operations and supply chain man- agers that are emerging and will be important in the future. These are sustainability, services, digital technologies, integration of decisions, and globalization of operations and the supply chain.
Key Terms Supply chain 2 Operations management 3 Supply chain management 4 Operations and supply chain
management 4 Gross Domestic Product
(GDP) 4 Productivity 5
Cross-functional decision making 12
Transformation system 13 Internal and external
environments 14 Sustainability 15 Triple bottom line 15 Globalization 17
Five major decision responsibilities 8
Process 8 Quality 8 Capacity 8 Inventory 8 Supply chain 8 Analytics 11
What Is Operations Management? Video https://youtu.be/leMOReAE2hk 5:19
Supply Chain Management: A Force for Good Video https://youtu.be/Bl0UhiOvrdc 5:01
Coca-Cola: Supply Chain Video https://youtu.be/UBSOiHUctrY 2:29
Sustainability Web Link https://www.epa.gov/sustainability/learn-about-sustainability#what
Globalization Web Link http://www.globalization101.org/what-is-globalization/
LEARNING ENRICHMENT (for self-study or instructor assignments)
Discussion Questions 1. Why study operations management in the supply chain? 2. What is the difference between the terms “production
management” and “operations management”? 3. What is the difference between operations management
and supply chain management? 4. How does the work of an operations manager differ
from the work of a marketing manager or a finance manager? How are these functions similar?
5. How is the operations management function related to activities in human resources, information systems, and accounting?
6. Describe the nature of operations management in the following organizations. In doing this, first identify the outputs of the organization and then use the five deci- sion types to identify important operations decisions and responsibilities.
a. A college library b. A hotel c. A small manufacturing firm 7. For the organizations listed in question 6, describe the
inputs, transformation process, and outputs of the pro- duction system.
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Chapter 1 Introduction to Operations 19
8. Describe the decision-making view and the view of operations as a process. Why are both views useful in studying the field of operations management?
9. Write a short paper on some of the challenges facing operations management in the future. Use newspapers, business magazines, or the Internet as your sources.
10. Review job postings from various sources for manage- ment positions that are available for operations manage- ment graduates. Summarize the responsibilities of these positions.
11. Describe how the view of operations as a process can be applied to the following types of work:
a. Acquisition of another company. b. Closing the books at the end of the year. c. Marketing research for a new product. d. Design of an information system. e. Hiring a new employee. 12. What is the role of operations and supply chain manage-
ment in national economic prosperity? How does it con- tribute to GDP, jobs, income, and society in general?
13. What is the role of the operations function? How does it contribute to profitability, return on investment, growth, and other corporate objectives?
14. For the following problem calculate the labor produc- tivity improvement from year 1 to year 2.
Year 1 Year 2 Annual Inflation
Output (sales) $million $103.4 $108.4 2%
Labor (payroll) $million $ 19.6 $ 22.4 3%
15. A company has experienced the following changes in sales, labor, and capital. Calculate the total productivity percentage improvement from year 1 to year 2. Does the total productivity measure make more sense in this problem, since both labor and capital have been used?
Year 1 Year 2 Annual Inflation
Output (sales) $million $260.5 $270.4 2%
Labor (payroll) $million $110.4 $111.5 3%
Capital $ 60.2 $ 61.0 1%
16. The Atlas company makes weight lifting equipment. They are in the process of automating and have added $5 million in capital equipment to their operations and reduced the labor content. Has this resulted in increased productivity based on the following numbers? What is the productivity gain or loss as a percentage?
Year 1 Year 2 Annual Inflation
Output (sales) $million $358.5 $361.4 2%
Labor (payroll) $million $110.4 $100.6 3%
Capital $ 60.2 $ 65.2 0%
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Operations and Supply Chain Strategy
There is an increasing awareness that operations and the supply chain contribute to the global competitive position of a business and are not merely making a firm’s products or services. This can be done by contributing distinctive capability (or competence) to the business and continually improving the products, services, and processes. Operations strategies and deci- sions should fulfill the needs of the business and add competitive advantage to the firm. The Operations Leader box on Southwest Airlines illustrates how operations adds competitive advantage to its firm.
The operations function is a key value creator for the firm. Value is providing products and services that customers want to buy at low cost. All functions of the firm must be well coordinated for value to be created and competitive advantage to occur. The cross- functional coordination of decision making is facilitated by an operations strategy that is developed by a team of managers from across the entire business.
LO2.1 Define operations strategy.
2 c h a p t e r
LO2.1 Define operations strategy.
LO2.2 Describe the elements of operations strategy and alignment with business and other functional strategies.
LO2.3 Differentiate the ways to compete with operations objectives.
LO2.4 Compare product imitator and innovator strategies.
LO2.5 Explain the nature of global operations and supply chains.
LO2.6 Analyze two types of supply chain strategies.
LO2.7 Illustrate how operations and supply chain can become more sustainable.
After reading this chapter, you should be able to:LEARNING OBJECTIVES
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The following definition of operations strategy is a starting point for our discussion:
Operations strategy is a consistent pattern of decisions for operations and the associated supply chain that are linked to the business strategy and other functional strategies, leading to a competitive advantage for the firm.
This definition will be expanded throughout this chapter as a basis for guiding all decisions that occur in operations and its supply chain with decisions in other functions.
We will use McDonald’s as an example in the next several sections to illustrate the elements of an operations strategy. In 1955, Ray Kroc opened his first restaurant in Des Plaines, Illinois, patterned after the McDonald brothers’ hamburger stand in California. The McDonald’s service system was designed on the idea of a very limited menu and fast production of standardized food and service with convenience and a low price. Never before had customers been served food so fast in a clean and courteous environment. Using a standard design for equipment, facilities, and employee training, the McDonald’s system was replicated in many locations and rapidly expanded throughout the U.S. and then the world.
• Flying out of regional secondary airports such as Midway Field in Chicago and Love Field in Dallas where gate fees and operating costs are much lower, and flights are more convenient and accessible for customers.
• Flying only point-to-point routes between pairs of cit- ies avoiding large airport hubs and thus cutting turn- around time between flights to only 15 minutes with very high aircraft utilization. High utilization of very expensive capital investment is a key to their success.
• Achieving high productivity from employees who have significant profit sharing, training, excellent working conditions, and low employee turnover.
• Making flights fun for the aircrews and passengers and giving passengers free bags when all other air- lines charge a bag fee. This improves customer ser- vice and customer satisfaction.
Southwest Airlines has received numerous awards for customer satisfaction including being ranked #1 by the U.S. Department of Transportation, and receiving the Best Customer Service Award by Freddie Awards for frequent flyers. It has withstood fierce competition from global airlines and other low-cost airlines such as JetBlue. Southwest Airlines has achieved its success by implementing a consistent operations strategy that is well integrated with business strategy and market- ing strategy.
Southwest Airlines was founded in 1971 as a regional airline. It has achieved financial success with its 47th consecutive year of profitability. In 2018 it reported $3.5 billion in net income on $21 billion in revenue with an annual return on invested capital of 25.9 percent. It has achieved this amazing record through a consistent business and operations strategy over its history.
The mission of Southwest Airlines is to provide the highest quality customer service at the lowest cost fares. This might have seemed impossible for a start-up regional airline competing against existing large airlines with massive economies of scale and purchasing power. Southwest Airlines accomplished this by using an inno- vative operations strategy from the beginning with the following features:
• Purchasing only Boeing 737 aircraft. Operating a single aircraft saved on maintenance training, spare parts stor- age, and special prices from Boeing for aircraft. Today, Southwest airlines operates 706 aircraft, all 737s.
Southwest Airlines
OPERATIONS LEADER
Markus Mainka/123RF
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22 Part One Introduction
The McDonald’s system is a standardized service system designed to meet stringent speci- fications. Every detail of the system is designed to provide fast and efficient food and service.
McDonald’s has continuously adapted its service system and supply chain over the years. For example, the menu has been expanded to offer many more food and beverage items, but always within the capability of the existing restaurants. They have updated their information systems in operations, and responded to environmental challenges by replac- ing, for example, the foam boxes previously used for sandwiches with biodegradable paper wrappers. In response to healthy food trends, they added salads, apple slices, and grilled chicken. Nevertheless, McDonald’s still has its critics and sometimes is blamed for the obesity of Americans and for having an adverse environmental impact.
McDonald’s is a global service firm. The operations strategy for global expansion has been to replicate the service system design and supply chain in each country with minimum modifications to the menu or processes. However, a few local international options are pro- vided. For example, McDonald’s serves beer in Germany, McRice in Indonesia, soup in Portugal, and salmon burgers in Japan. They have also extended their supply chain forward by developing a franchise system that maintains strong control over the product and service.
Today, McDonald’s is the global leader in food service with more than 37,000 restau- rants in 120 countries serving an average of 68 million customers each day. Next we will describe the elements of operations strategy in detail and use McDonald’s to illustrate how the elements of operations strategy support overall business strategy.
2.1 OPERATIONS STRATEGY MODEL
Operations strategy is a functional strategy along with the firm’s other functional strate- gies such as those of marketing, engineering, information systems, and human resources. Since operations strategy is a functional strategy, it should be guided by the business and corporate strategies shown in Figure 2.1. The four elements inside the dashed box— mission, objectives, strategic decisions, and distinctive competence—are the heart of oper- ations strategy. The other elements in the figure are inputs or outputs from the process of
LO2.2 Describe the elements of operations strategy and alignment with business and other functional strategies.
McDonald’s is a leading global service firm with an operations and supply chain strategy. Christopher Kerrigan/ McGraw-Hill Education
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developing operations strategy. The outcome of using the operations strategy is a consis- tent pattern of operations decisions that are well connected with the other functions in the business and help provide a competitive advantage to the business.
Corporate strategy and business strategy are at the top of Figure 2.1. The corporate strat- egy defines the business that the company is pursuing. For example, Walt Disney Cor- poration considers itself in the business of “making people happy.” Disney Corporation includes not only theme parks but the production of cartoons, movie production, merchan- dising, and a variety of entertainment-related businesses around the world.
Business strategy follows from the corporate strategy and defines how each particular business will compete. Most large corporations have several different businesses, each com- peting in different market segments. Michael Porter describes three generic business strat- egies: differentiation, low cost, and focus. Differentiation is associated with a unique and
Corporate and Business Strategy
FIGURE 2.1 Operations strategy process.
Operations strategy Functional strategies in
marketing, finance,
engineering,
human resources, and
information systems
Strategic decisions (process, quality system, capacity, inventory, and
supply chain)
Mission
Distinctive competence
Objectives (cost, quality, flexibility,
and delivery)
Business strategy
Corporate strategy
Internal analysis
External analysis
Results
Consistent pattern of decisions
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24 Part One Introduction
frequently innovative product or service, while low cost is pursued in commodity markets where the products or services are imitative. Focus refers to the geographical or product portfolio being narrow or broad in nature. Focus can be combined with either a differentiation or a low-cost strategy.
Every operation should have a mission that is connected to the business strategy and is coordinated with the other functional strate- gies. For example, if the business strategy is differentiation through innovative products, the operations mission should emphasize new product introduction and flexibility to adapt products to changing market needs. Other business strategies lead to other operations missions, such as low cost or fast delivery. The operations mission is thus derived from the particular business strat- egy selected by the business unit.
At McDonald’s, the operations mission is to provide food and service quickly to customers with consistent quality and low cost in a clean and friendly environment.
Operations objectives, sometimes called competitive priorities, are the second element of operations strategy. The four common objectives of operations are cost, quality, delivery, and flexibility. In certain situations, other objectives may be added, such as innovation, safety, and sustainable operations. The objectives should be derived from the operations mission, and they constitute a restatement of the mission in quantitative and measurable terms. The objectives should be long-range-oriented (5 to 10 years) to be strategic in nature and should be treated as goals.
Definitions of the four common operations objectives follow:
∙ Cost is a measure of the resources used by operations, typically the unit cost of produc- tion or the cost of goods or services sold.
∙ Quality is the conformance of the product or service to the customers’ requirements. ∙ Delivery is providing the product or service quickly and on time. ∙ Flexibility is the ability to rapidly change operations.
Table 2.1 shows some common measures of objectives that can be used to quantify long-range operations performance. The four common objectives are listed along with a fifth objective, sustainability, that is becoming more important to many firms. The objec- tives for five years into the future are compared to the current year and also to a current world-class competitor. The comparison to a world-class competitor is for benchmarking purposes and may indicate that operations is behind or ahead of the competition. However, the objectives should be suited to the particular business, which will not necessarily exceed the competition in every category.
At McDonald’s, each restaurant has specific objectives with respect to cost, quality, and service times. These objectives are pursued using extensive standards and are frequently
Operations Mission
Operations Objectives
THE MAGIC KINGDOM. Disney Corporation is in the business of “making people happy.” Phelan M. Ebenhack/AP Images
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measured for compliance. McDonald’s tracks the performance of each restaurant and com- pares the results with those of competitors.
Strategic decisions constitute the third element of operations strategy. These decisions determine how the operations objectives will be achieved. A consistent pattern of strategic decisions should be made for each of the major operations decision categories (process, quality, capacity, inventory, and supply chain). These decisions must be well integrated with other functional decisions. This coordination and consistency is one of the most dif- ficult things to achieve in business.
Table 2.2 indicates some important strategic decisions for operations. Note that these decisions may require trade-offs or choices. For example, in the capacity area there is a
Strategic Decisions
TABLE 2.1 Typical Operations Objectives
Current Year
Objective: 5 Years in the Future
Current: World-Class Competitor
Cost
Manufacturing cost as a percentage of sales Inventory turnover
55% 4.1
52% 5.2
50% 5.0
Quality
Customer satisfaction (percentage satisfied with products)
Percentage of scrap and rework Warranty cost as a percentage of sales
85% 3% 1%
99% 1%
0.5%
95% 1% 1%
Delivery
Percentage of orders filled from stock Lead time to fill stock
90% 3 wk
95% 1 wk
95% 3 wk
Flexibility
Number of months to introduce new products Number of months to change capacity by ±20%
10 mo 3 mo
6 mo 3 mo
8 mo 3 mo
Sustainability
Reduce carbon emissions (ppm) Reduce workplace accidents per thousand
workers
400
30
200
15
400
15
TABLE 2.2 Examples of Important Strategic Decisions in Operations
Strategic Decision Decision Type Strategic Choice
Process Span of process Automation
Make or buy Handmade or machine-made
Process flow Job specialization
Project, batch, line, or continuous High or low specialization
Quality Approach Training Suppliers
Prevention or inspection Technical or managerial training Selected on quality or cost
Capacity Facility size Location Investment
One large or several small facilities Near markets, low cost, or foreign Permanent or temporary
Inventory Amount Distribution Control systems
High or low levels of inventory Centralized or decentralized warehouse Control in greater or less detail
Supply Chain Sourcing Logistics
Insource or outsource products National or global distribution
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26 Part One Introduction
choice between one large facility and several smaller ones. While the large facility may require less total investment due to economies of scale, the smaller facilities can be located in their markets and provide better customer service. Thus, the strategic decision depends on what objectives are being pursued in operations, the availability of capital, marketing objectives, and so forth.
McDonald’s illustrates how a consistent pattern of strategic decisions is made in the five operations decisions areas:
Process: Specialized equipment and work flows ensure meals are delivered to customers quickly. For example, the special French fry scoop puts the right amount of fries in each serving with little effort. Also, servers use information technology to instantly communicate orders to food preparers. Quality: More than 2000 quality, food safety, and inspections monitor food as it moves from farms to suppliers to restaurants. McDonald’s requires that 72 safety and quality protocols be conducted at each restaurant every day. Managers are trained at “Hamburger U” in the McDonald’s system to ensure standards for service, speed, food quality, cleanliness, and courtesy are met. Capacity: Restaurant capacity is carefully designed to control customer waiting times. Employees are scheduled to meet the fluctuating demand during the day. Inventory: Just-in-time replenishment ensures food and packaging are available when needed. Food and packaging are highly standardized across restaurants. Supply Chain: Each restaurant is connected to its supply chain for fast replenish- ment. The supply chain is designed for frequent deliveries and to avoid stockouts.
All operations should have a distinctive competence (or operations capability) that differ- entiates it from the competitors. The distinctive competence is something that operations does better than anyone else. It may be based on unique resources (human or capital) that are difficult to imitate. Distinctive competence can also be based on an embedded organi- zational culture, proprietary or patented technology, or any innovation in operations that cannot be copied easily.
The distinctive competence should match the mission of operations. For example, it is a mismatch to have a distinctive competence of superior inventory management systems when the operations mission is to excel at new product introduction. Likewise, the distinc- tive competence must be coordinated with marketing, finance, and the other functions so that it is supported across the entire business as a basis for competitive advantage.
Distinctive competence may be used to define a particular busi- ness strategy in an ongoing business. The business strategy does not always emanate from the market; it may be built instead on match- ing operations’ distinctive competence (current or projected) with a current or potential new market. Both a viable market segment and a unique capability to deliver the product or service offered must be present for the firm to compete.
Walmart has a mission to be the low-cost retailer. To achieve this mission it has developed a distinctive competence in cross-docking aimed at lowering the costs of shipping. Using cross-docking, goods from suppliers’ trucks are transferred across the loading dock to waiting Walmart trucks and delivered to the stores without enter- ing the warehouse. Walmart also has a sophisticated inventory con- trol system and more purchasing power than its competitors and
Distinctive Competence
Walmart has distinctive competencies to support its low-cost strategy. John Flournoy/McGraw-Hill Education
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therefore can minimize inventories and related costs. These distinctive competencies help Walmart compete on the basis of low cost.
McDonald’s early distinctive competence was its unique service and supply chain that it designed. Since other firms have copied this system over time, the distinctive competence has shifted to continuous improvement of the transformation system along with the brand. McDonald’s system and its brand are now its distinctive competence.
2.2 COMPETING WITH OPERATIONS OBJECTIVES
We will now use the four operations objectives discussed above to describe different ways to compete through operations. Most firms choose one or two objectives to focus on, so that the strategic decisions made in operations can be aligned with and support these focused objectives.
Suppose we start with the idea of competing through a quality objective. Delivering quality means satisfying customer requirements. This assumes that marketing has identi- fied a particular target market, and that operations understands these customers’ specific requirements. Operations processes must be capable of meeting those requirements. If competing through quality is the objective, strategic decisions related to product or ser- vice design, operations, and the supply chain must support customers’ expectations for quality. For example, in a manufacturing company quality is improved by taking pre- ventative measures in training workers, design of the process, and eliminating rework and non-value-added activities. Customers who require quality expect a very low level of defects.
Now, suppose we decide to pursue a low-cost objective. Perhaps the best way to achieve low cost is to focus on conforming to customer requirements (quality) in product/service design and operations processes by eliminating rework, scrap, and other non-value-added activities. By preventing errors through continuous improvement, costs can be lowered at the same time as quality improves. A low-cost objective may require more than just an emphasis on conformance quality. Investment in automation and information systems may also be needed to reduce costs.
If we select a delivery objective, strategic decisions should support fast or on-time delivery, depending on the expectations of customers. Industrial (business) customers often want on-time delivery because they schedule loading docks at warehouses or retail stores and do not want several trucks delivering at the same time. Fast delivery may be desir- able for consumers ordering products online (they will order from the company that can deliver the product soonest). When quality improvement efforts reduce non-value-added steps, the time to produce and deliver the product is indirectly reduced. Time can also be directly reduced by improving process changeover times, simplifying complex operations, and redesigning the product or service for fast production.
Finally, we could choose to emphasize a flexibility objective. If we reduce delivery time, flexibility will automatically improve. For example, if it originally took 16 weeks to make a product and we reduce production time to 2 weeks, then it is possible to change the schedule within a 2-week time frame rather than 16 weeks, making operations more flexible to changes in customer requirements. Other types of flexibility can be directly improved by adding capacity, buying more flexible equipment, training workers to per- form a wider variety of tasks, or redesigning the product or service for high variety.
We can see that operations objectives are connected. If we stress a quality objective, we also naturally get some cost reduction, delivery improvement, and more flexibility. Qual- ity is often a good place to start for improving operations. Then other objectives may be tackled by directing strategic decisions to impact them.
LO2.3 Differentiate the ways to compete with operations objectives.
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28 Part One Introduction
While objectives are connected, an operation must still choose its number one or number two strategic objectives to emphasize. For example, McDonald’s excels at low-cost and fast (delivery) service. It does not emphasize flexibility, rather exactly the opposite. Zara, a giant European fashion retailer, is able to achieve fast replenishment (delivery) of hot-selling items within a few weeks by holding spare capacity and supporting rapid supply chain man- agement practices. Zara emphasizes fast fashion, not low cost. Lexus is renowned for high quality in its cars, which results from both its design and its manufacturing process. Chipotle uses a highly flexible serving process that allows each customer to self-customize a meal.
2.3 CROSS-FUNCTIONAL STRATEGIC DECISIONS
Not only should objectives be linked to an operations mission, operations strategic deci- sions should be linked to business strategy and to marketing and financial strategies as well. Table 2.3 illustrates this linkage by showing two diametrically opposite business strategies that can be selected and the resulting functional strategies. The first one is the product imitator (low-cost) business strategy, which is typical of a mature, price- sensitive market with a standardized product (or service). In this case, the operations objective should emphasize cost as the dominant objective, and operations should strive to reduce costs through strategic decisions such as superior process technology, low personnel costs, low inventory levels, a high degree of vertical integration, and quality improvement aimed at saving cost. Marketing and finance also need to pursue and support the product imitator business strategy, as shown in Table 2.3.
The second business strategy shown in the table is one of product innovator and new product introduction (or product/service leadership). This strategy typically is used in emerging and possibly growing markets where advantage can be gained by bringing to
LO2.4 Compare product imitator and innovator strategies.
TABLE 2.3 Strategic Alternatives
Strategy A Strategy B
Business Strategy Product Imitator Product Innovator
Market Conditions Price-sensitive Mature market High volume Standardization
Product-features-sensitive Emerging market Low volume Customized products
Operations Mission and Objectives
Emphasize low cost for mature products
Emphasize flexibility to introduce new products
Operations Strategic Decisions
Superior processes Dedicated automation Slow reaction to changes Economies of scale Workforce involvement
Superior products Flexible automation Fast reaction to changes Economies of scope Use of product development
teams
Distinctive Compe- tence Operations
Low cost through superior process technology and vertical integration
Fast and reliable new product introduction through product teams and flexible automation
Marketing Strategies Mass distribution Repeat sales Maximizing of sales opportunities National sales force
Selective distribution New-market development Product design Sales made through agents
Finance Strategies Low risk Low profit margins
Higher risks Higher profit margins
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market superior-quality products in a short amount of time. Price is not the dominant form of competition, and higher prices are charged, thereby putting a lower emphasis on costs. In this case, the operations and supply chain objective is flexibility to introduce superior new products rapidly and effectively. Operations strategic decisions include the use of new product introduction teams, flexible automation that is adapted to new products, a workforce with flexible skills, and rapidly responding to marketplace changes. Once again, finance and marketing also need to support the business strategy to achieve an integrated whole.
What Table 2.3 indicates is that drastically different types of operations are needed to support different business strategies. Flexibility and superior-quality products may cost more for the product innovator strategy. There is no such thing as an all-purpose operation that is best for all circumstances. Thus, when asked to evaluate operations, one must imme- diately ask, what is the business strategy, mission, and objective of operations? Evaluating operations is contingent on strategy. In other words, operations with different strategies should adopt different best practices and decisions.
Table 2.3 also suggests that all functions must support the business strategy for it to be effective. For example, in the product imitator strategy, marketing should focus on mass distribution, repeat sales, a national sales force, and maximization of sales opportunities. In contrast, in the product innovator strategy, marketing should focus on selective distribu- tion, new-market development, product design, and perhaps sales through agents. It is not enough for just operations to be integrated with the business strategy; all functions must support the business strategy and one another.
Integrating marketing and operations and clearly laying out a particular mission and objective for operations is essential to meet customer preferences for order winners and order qualifiers. An order winner is an objective that will cause customers in a particular segment that marketing has selected as the target market to choose a particular product or service. In the product imitator strategy, the order winner for the customer is price; this implies the need for low cost in operations, marketing, and finance. Other objectives in this case (flexibility, quality, and delivery) are order qualifiers in that the company must have acceptable levels of these three objectives to qualify to get the customer order. Insuf- ficient levels of performance on order qualifiers can cause the business to lose the order, but higher performance on order qualifiers cannot by themselves win the order. Only low price/cost will win the order in this case.
In the product innovator strategy, the order winner is flexibility to introduce superior products rapidly and effectively; the order qualifiers are cost, delivery, and quality. Note how the order winner depends on the particular strategy selected and that all functions must pursue superior levels relative to the competition on the order winner while achieving levels acceptable to the customer on order qualifiers.
What is the order winner at Walmart? It’s low cost, and strategic decisions in operations are made to keep costs down. The same cannot be said about Nordstrom, which competes on upscale merchandise and superior customer service. Since the order winners in these stores are different, so are the operations strategies.
3M corporate strategy is product innovation. Jill Braaten/McGraw-Hill Education
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30 Part One Introduction
2.4 GLOBAL OPERATIONS AND SUPPLY CHAINS
Every day we hear that markets are becoming global in nature. Many products and services are global in nature, including soft drinks, cell phones, TVs, fast food, banking, travel, automobiles, motorcycles, farm equipment, machine tools, and a wide variety of other products. To be sure, there are still market niches that are national or even local but the trend is toward more global markets and products.
When operating in global markets, a company needs to be organized properly to produce and market its products. As a result, the global corporation has emerged with the follow- ing characteristics. Facilities and plants are located on a worldwide basis, not country by country. Products and services can be shifted between countries. Components, parts, and services are sourced on a global basis. The best worldwide suppliers are sought, regard- less of their national origin. The entire supply chain is global in nature. A few well-known manufacturing companies that are global corporations are Ford, 3M, Nestlé, Philips, Deere & Company, Coca-Cola, and Caterpillar.
The global corporation uses global product design and process technology. A basic product or service is designed, whenever possible, to fit global tastes. When a local varia- tion is needed, it is handled as an option rather than as a separate product or service. Process technology is also standardized globally. For example, Black & Decker recently designed worldwide hand tools. Even fast food, clothing, and soft drinks have become global products.
In the global corporation, demand for products or services is considered on a world- wide, not a local, basis. Therefore, the economies of scale are greatly magnified, and costs can be lower. The iPhone came out as a worldwide product and was marketed globally. Its demand and cost were scaled for a global market right from the start.
Logistics and inventory control systems are also global in nature. This makes it possible to coordinate shipments of products and components on a worldwide basis.
Some services have taken on a global scope of operations. For example, consulting firms, fast food, telecommunications, air travel, entertainment, financial services, and soft- ware programming have global operations. Global consolidation has taken the place of these formerly fragmented service industries. Certainly, not all service is global. There remain services that are delivered on a local basis to serve local markets, but the trend toward globalization is undeniable. A few of the service companies that are globally ori- ented are British Airways, Starbucks, Microsoft, and McDonald’s.
Some firms have adopted a hybrid approach with global economies of scale but a local touch. In this case certain functions, for example, product design and manufacturing, are
handled on a local basis, while other functions, such as logistics and inventory control systems, are standardized around the world. See the Under Armour Operations Leader box for a strategy to compete in global markets with local manufacturing.
The implications for operations strategy of this change toward global business are profound. Operations and supply chains must be conceived of as global in nature, including very broad searches for both suppliers and customers. A global distinctive competence should be developed for operations, along with a global mission, objectives, and strategic decisions. Product design, process design, facility location, workforce policies, and virtually all decisions in operations and the supply chain are affected.
LO2.5 Explain the nature of global operations and supply chains.
Pfizer competes globally in 52 locations around the world. Ulrich Baumgarten/Getty Images
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However, not all companies are following a global operations and supply chain strategy with offshore manufacturing. Some companies that have moved some of their manufactur- ing overseas are moving it back to the U.S., called reshoring. This is occurring as compa- nies reconfigure their supply chains based on changing economic conditions, taxes, quality considerations, and other factors that affect strategic operations and international supply chain location decisions.
2.5 SUPPLY CHAIN STRATEGY
In the same way that operations are being expanded to a global context, operations strategy can be expanded to supply chain strategy. Supply chain strategy includes consideration of customers, suppliers, sourcing, and logistics in addition to operations. It requires a focus on flows of inventory, materials, and information throughout the supply chain from the suppliers to the ultimate customer.
Supply chain strategy takes into account not only the operations strategy of the firm but also the strategies and capabilities of the suppliers and customers in the firm’s supply chain. A supply chain strategy allows the supply chain to compete, not just the firm.
Supply chain strategy should be aimed at achieving a sustainable competitive advantage for the entire supply chain. This advantage can be achieved by expanding the concepts already covered in this chapter. For example, a supply chain should have a distinctive com- petence that is valuable and difficult to imitate or replace by competitors. This distinctive competence should be based on what the firm does along with actions of its supply chain partners. In a similar way, the supply chain partners and the firm should be working toward
LO2.6 Analyze two types of supply chain strategies.
Timing is everything in this “fashion industry” for firms like Under Armour.
Engineers and design- ers from around the world will rotate and collabo- rate at headquarters in Baltimore, Maryland, to develop the new manufac- turing processes. Under Armour hopes to improve response times with their “local for local” model, by both producing and selling
within their global markets.
Source: L. Mirabella, “Under Armour Pushes to Localize Manufacturing,” Baltimore Sun, reprinted in Star Tribune, Oct. 26, 2015 and https://about.underarmour.com/investor- relations, 2020.
Under Armour, maker of sports clothing and acces- sories, has an opera- tions mission to develop advanced manufacturing processes with the goal of producing products on a small scale in local markets where they are sold. They plan to manu- facture in the U.S. for U.S. consumers, in Brazil for South American buyers, in Europe for the European market, and in China for the Chinese market.
Under Armour currently manufactures primarily in China, Jordan, and Vietnam. But shipping times to key markets are typically weeks and sometimes longer due to production delays or labor disputes at ports.
Under Armour Goes Local
OPERATIONS LEADER
Justin Sullivan/Getty Images
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32 Part One Introduction
the same mission and objectives in order to have a consistent supply chain strategy. Since no single firm controls the entire supply chain, a coherent supply chain strategy can be dif- ficult to achieve. Nevertheless, it is important to realize that supply chain partners that are working toward differing goals will not be competitive with other supply chains that have achieved a high degree of cooperation and consistency.
Just like we have already discussed for operations, there are two fundamental supply chain strategies: imitation and innovation. Imitators have products or services similar to those of their competitors and are oriented toward efficiency and low cost as a way of com- peting. In contrast, innovators differentiate their product or service as their way of compet- ing and can charge higher prices. For example, Sport Obermeyer is in the fashion skiwear business. Each year up to 95 percent of its ski, snowboard, and outdoor clothes are new or redesigned. The company must plan production and forecast demand well in advance of sales (more than a year), and as a result it often has stockouts or overstock situations that result in markdowns at the end of the season. The problem facing Sport Obermeyer is that its supply chain doesn’t match the nature of its product. The supply chain is oriented toward efficiency and low cost, whereas Sport Obermeyer with its innovative products needs a faster more flexible supply chain with better forecasting that responds to uncertain demand. Sport Obermeyer appears to have the wrong supply chain.
To identify the proper supply chain, companies should first sort their products into two categories: imitative and innovative. Imitative products are like commodities—they have predictable demand and low profit margins. As a result, imitative products should have a very efficient low-cost supply chain. Examples are toothpaste, oil, standard auto- mobiles, and most food. In contrast, innovative products have unpredictable demand and high profit margins. They need a flexible and fast supply chain to deal with uncertainty in demand. Examples are fashion clothing, electric cars, new electronic products, and some toys. The characteristics of these two types of products are shown at the top of Table 2.4. Note that the product life cycle, contribution margin, average forecasting error, stockout
TABLE 2.4 Supply Chain Strategies Source: Adapted from Fisher, M., What is the right supply chain for your product? Harvard Business Review, Mar-Apr, 1967.
Product Differences Imitative Products Innovative Products
Product life cycle Greater than 2 years 3 months to 1 year
Contribution margin 5% to 20% 20% to 60%
Average forecast error when production is planned 10% 40% to 100%
Average stockout rate 1% to 2% 10% to 40%
Average forced end-of-the- year markdown 0% 10% to 25%
Supply Chain Strategy
Objective Predictable supply at low cost
Respond quickly to unpredictable demand.
Manufacturing High utilization and low-cost production
Excess buffer capacity and short throughput time. May have low utilization of capacity.
Inventory High turnover Significant buffers of parts or finished goods. May have low turnover.
Suppliers Selected for cost and quality Selected for speed, flexibility, and quality.
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rate, and forced end-of-the-year markdowns are all dramatically different for imitative and innovative products.
Firms often make the mistake of using one type of supply chain strategy for both types of products. For example, General Mills, a food company, might use an efficient supply chain with high inven- tory turnover and high utilization of its factories since most of its products are imitative in nature. But General Mills needs a differ- ent supply chain that is highly flexible and responsive to meet the uncertain demand for its new and innovative products. When firms face this dilemma, they should not make the mistake of choosing only one supply chain strategy for all products.
The two types of supply chain strategies are summarized in the bottom half of Table 2.4. The objectives of these two strategies are
different. While imitative supply chains should aim at a predictable supply at low cost, inno- vative supply chains should aim for quick response to unpredictable demand to minimize stockouts, lost sales, and markdowns. In innovative supply chains the high margins can absorb the higher costs of buffer capacity and buffer inventories needed to deal with uncertainty.
By using better forecasting, additional capacity, and drastic lead-time reductions for its innovative products, Sport Obermeyer was able to cut the cost of both overproduction and underproduction in half—enough to increase profits by 60 percent. Retailers were very happy that product availability exceeded 99 percent, making Sport Obermeyer the best in the industry for order fulfillment.
2.6 ENVIRONMENT AND SUSTAINABLE OPERATIONS
Sustainable operations has become an increasingly important part of operations and sup- ply chain objectives and strategy. It refers to minimizing or eliminating the environmental impact of operations along with social and financial viability of the firm for future gen- erations. This is often referred to as the triple bottom line—environmental, social, and economic sustainability.
First, we describe the environmental part of the triple bottom line. In greening its sup- ply chain a company should examine all opportunities, including product development, sourcing, manufacturing, packaging, distribution, transportation, services, and end-of-life management. This must be a cross-functional effort that involves all functions in the firm, because it may require, for example, investments in new equipment or changes to product packaging. Since reducing operations’ environmental impact is a strategic task, it must be conceived as part of the business strategy.
Once the strategy has been set, it is usually best to start with a few focused initiatives from the following list. Others can be attacked later.
1. Curtail air, water, and landfill pollution. 2. Reduce energy consumption. 3. Minimize transportation and total carbon footprint. 4. Work with suppliers to use recyclable and biodegradable packaging. 5. Incorporate product reuse, end-of-life return, and recycling.
The first step that most companies take is to measure their environmental impact in any or all of these five areas. Once this is known, cross-functional teams can be formed to develop strategies and action plans to improve the measures. These teams can also include supply chain partners to spread the effort up and down the supply chain. This should be
LO2.7 Illustrate how operations and supply chain can become more sustainable.
Sport Obermeyer needs an innovative supply chain. action sports/Shutterstock
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34 Part One Introduction
done in concert with the operations and supply chain strategy to ensure that environmental impacts are minimized.
A Walmart effort in 1989 to use recyclable and biodegradable packaging ended in fail- ure. Critics and suppliers believed the effort was intended to generate benefits for Walmart at the expense of its suppliers. In 2005, their environmental effort was different. It was launched by forming teams of representatives from suppliers, Walmart management, envi- ronmental groups, government, and academics. The teams set goals, developed measures of environmental impact, and implemented programs to green the supply chain. Some Walmart results from 2018 and goals for 2025 are as follows:
∙ Increase renewable energy sources to 50 percent by 2025 from 28 percent in 2018. ∙ Reduce emissions from Walmart’s supply chain by one gigaton by 2030. ∙ Work toward zero landfill waste with a 78 percent reduction by 2018. ∙ Various goals for employee diversity, engaging associates and communities, provid-
ing disaster relief, and relieving hunger. From 2015 to 2018 Walmart donated over 2.5 billion pounds of food to food pantries.
Sustainability also includes social responsibility by firms. This can take many forms including hiring a diverse workforce, providing equal opportunities for all employees, insuring safe and healthy working conditions, fair handling of employee grievances, ethi- cal practices of every sort, and following all federal and state regulations. Accepting social responsibility need not cost more, and actually can reduce costs and improve productivity. This is achieved through lower employee turnover, lower training costs, and lower costs of finding replacement employees. More highly engaged and satisfied employees can offer better customer service and greater productivity.
The third part of the triple bottom line is economic sustainability. It is achieved by a business and operations strategy that achieves a sustainable competitive advantage. A firm without a competitive advantage can easily lose market share and customers eroding its top line along with increased costs and ultimately low profitability that threaten firm survival.
Sustainable operations is an objective and strategy that firms and operations can achieve with the help of their supply chain partners. This objective need not cost more or reduce profits. In many cases, but not all, through product redesign or process changes, costs can be reduced and profits improved. British retailer Marks & Spencer has met goals to send zero waste to landfills and is the first major retailer to be carbon neutral. Supply chain partners have been an important source of support for this effort.
2.7 KEY POINTS AND TERMS
This chapter emphasizes achieving a competitive advantage through operations by devel- oping an operations and supply chain strategy based on what the customers of the business value. The key points are as follows:
∙ Operations strategy consists of mission, objectives, strategic decisions, and distinctive competence. These four elements must be tightly integrated with one another and with other functions.
∙ The operations mission should be aligned with the business strategy. Possible missions for operations include low cost, fast new product introduction, fast delivery, or best quality.
Marks & Spencer sets high sustainability goals. TEA/123RF
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∙ The objectives of operations are cost, quality, delivery, and flexibility. One of the four objectives should be selected as an order winner; the others are order qualifiers.
∙ Operations strategic decisions indicate how operations objectives will be achieved. Strategic decisions can be developed for each of the major decision areas (process, qual- ity systems, capacity, inventory, and supply chain).
∙ The operations and supply chain strategy must be linked to the business strategy and other functional strategies, leading to a consistent pattern of decisions, unique capabil- ity, and competitive advantage for the firm.
∙ The distinctive competence of operations should support the mission and differentiate operations from its competitors. Possible distinctive competencies include proprietary technology, embedded organization culture, and any innovation in operations that can- not be copied easily.
∙ The scope of operations and supply chain strategy has expanded to a global basis, par- ticularly for businesses pursuing a global business strategy.
∙ In many situations the basis of competition is not the firm but the entire supply chain. Supply chain strategy is an extension of operations strategy that considers not only the firm but also the strategies and capabilities of its supply chain partners.
∙ Sustainable operations has become a critical objective and strategy. It should be approached by forming cross-functional teams that include suppliers. Measuring and reducing the environmental, social, and economic impact in all phases of design, opera- tions, and distribution are the path of action.
∙ There is no one best strategy for all operations and their supply chains. The mission, objectives, strategic decisions, and distinctive competence depend on whether a product imitator, product innovator, or another strategy is being pursued by the business.
Key Terms Operations strategy 21 Functional strategy 22 Corporate strategy 23 Business strategy 23 Mission 24 Operations objectives 24 Benchmarking 24 Strategic decisions 25
Order winners 29 Order qualifiers 29 Global corporation 30 Reshoring 31 Supply chain strategy 31 Sustainable operations 33 Triple bottom line 33
Distinctive competence 26
Quality objective 27 Low-cost objective 27 Delivery objective 27 Flexibility objective 27 Product imitator 28 Product innovator 28
What Is Operations Strategy? Video https://youtu.be/jUKiuE4-aW0 2:05
Developing Supply Chain Strategy Video https://youtu.be/cEyBTEOAZ48 5:06
Introduction to Supply Chain Strategy Website https://www.thebalancesmb.com/strategic-supply-chain-management-
2221231
IKEA, a Leader in Sustainability–TED Talk Video https://youtu.be/buH_vs7LFzw 13:18
LEARNING ENRICHMENT (for self-study or instructor assignments)
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36 Part One Introduction
Discussion Questions 1. What are the reasons for formulating and implementing
an operations and supply chain strategy? 2. Describe a possible operations mission that fits the fol-
lowing business situations: a. Ambulance service. b. Production of hybrid automobile batteries. c. Production of electronics products that have a short
product life cycle. 3. An operations manager was heard complaining, “The
boss never listens to me—all the boss wants from me is to avoid making waves. I rarely get any capital to improve operations.”
a. Does the business have an operations strategy? b. What should be done about the situation? 4. Define the following terms in your own words: opera-
tions mission, order winner, order qualifier, and distinc- tive competence.
5. How would you determine whether a company has an operations and supply chain strategy? What specific questions would you ask, and what information would you gather?
6. Evaluate two local hospitals in terms of their emphasis on the four operations objectives: cost, quality, delivery, and flexibility. Are all departments focused on the same objec- tives? What are the order winners and the order qualifiers?
7. Define some of the strategic decisions that might be required in a grocery store’s operation and its supply chain depending on whether the strategy was emphasiz- ing imitation or innovation.
8. Find examples of operations and supply chain strate- gies. Write a few paragraphs describing the strategies being pursued.
9. Describe an operation where higher quality will cost more. What is your definition of quality? Why does higher quality cost more? If you use a different defini- tion of quality, will higher quality cost less?
10. What is the distinctive competence of the following companies?
a. Starbucks Coffee Company b. Hewlett Packard c. Burger King 11. Explain how a distinctive competence in operations can
be the basis for competition in the company. 12. Give two examples of a distinctive competence that can
be sustained and not easily duplicated. Explain why it is hard to copy these distinctive competencies.
13. Give an example of a global business with which you are familiar. How has globalization affected its opera- tions and its supply chain?
14. What are the practical consequences of a lack of stra- tegic linkage between the business and the operations function?
15. Find a company that emphasizes sustainability. What types of programs, measures, and objectives does this company have?
16. Under what circumstances can a company pursuing a sustainability strategy actually increase its profits and under what circumstances might it not?
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New product development affects every part of a business, including operations and the supply chain. New products provide growth opportunities and a competitive advantage for a firm, so they are very important to the marketing and finance functions. Increasingly, there is a challenge to introduce new products more quickly without sacrificing quality. For example, the world’s automobile makers can now introduce a new model in two years, even with many new technology features being designed and added, whereas it used to take four years or longer. Personal computers have a very short product life cycle, sometimes less than a year.
New product design greatly affects operations by specifying the products that will be made; it is a prerequisite for production to occur. At the same time, existing processes and products can constrain the technology available for new products. Thus, new products must be defined with not only the market in mind but also the production process that will be used to make a product. New product design also affects the supply chain, as suppliers will need to provide the various components that are needed, and sometimes be involved in designing them.
Product Design
c h a p t e r 3
After reading this chapter, you should be able to:LEARNING OBJECTIVES
LO3.1 Compare the three strategies for new product introduction.
LO3.2 Describe the three phases of new product development.
LO3.3 Evaluate how concurrent engineering deals with misalignment.
LO3.4 Describe the criteria for selecting suppliers for collaboration.
LO3.5 Evaluate an example of Quality Function Deployment.
LO3.6 Explain the benefits of modular design.
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38 Part One Introduction
Product design follows from the development of a business strategy. The business strategy includes a value proposition that defines the target market, the differentiation of the product, and why the customer should buy it. This is the starting point for designing a new product. Factors that will be considered are customer preferences, market size, materials available for making the product, and issues concerning sustainability. See the Operations Leader box on The LEGO Group for linkages among sustainability, strategy, and new product development.
3.1 STRATEGIES FOR NEW PRODUCT INTRODUCTION
There are three fundamentally different ways to introduce new products. These approaches are called market pull, technology push, and interfunctional view.
Market pull. According to this view, the market is the primary basis for determining the products a firm should make, with little regard for existing technology. A firm should make what it can sell. Customer needs are determined, and then the firm organizes the technology, resources, and processes needed to design a product and supply the customer. The market will “pull” through the products that are made. Technology push. In this view, technology is the primary determinant of the products the firm should make. The firm pursues a technology-based advantage by developing superior technologies in their materials and components. The products are pushed into the market, and marketing’s job is to create demand for these new products. Since the products have superior technology, they will have a natural advantage in the market.
LO3.1 Compare the three strategies for new product introduction.
They employ more than 250 product designers in the creative core of the company. They also coordinate with educational institutions to carry out research on materials, develop technology, and understand how children play.
While the cost and effort to develop a reliable new raw material are significant, LEGO wants “children, the builders of tomorrow, to inherit a healthy planet.”
Source: www.lego.com, 2020.
The product development process usually results in a new product for the market, but the process is also use- ful for redesigning existing products. The LEGO Group is investing over $100 million and hiring about 100 new workers to redesign its current product. The goal is to eliminate the use of petroleum-based plastics and make the toys entirely from plant or recycled materials by 2030.
In this case, the product development process is not designing a new toy. In fact, LEGO hopes custom- ers will not notice any difference in their manufactured “elements”–the small plastic pieces that kids (and adults) around the world enjoy. Although a new raw material will be used to manufacture the lego pieces, they should have the same “click” together and easy separation as the existing plastic pieces. The pieces also need to be bright in color and stand up to unexpected trips through the laundry!
The LEGO Group is based in Billund, Denmark, where it produces about 100 million lego pieces every day.
The LEGO Group
OPERATIONS LEADER
Milosh Kojadinovich/12RF
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Interfunctional view. This view combines some of the advantages of the first two strategies, with products that fit the market needs (new or existing markets) and have a technical advantage as well. To accomplish this, all functions (e.g., marketing, engi- neering, operations, and finance) should collaborate to design the new products needed by the firm. Often, this is done by forming cross-functional teams that are respon- sible for the development of a new product. This is the most appealing of the three views but also the most difficult to implement. Often cross-functional friction must be overcome to achieve the degree of cooperation required for interfunctional product development to succeed. If it can be implemented, the interfunctional approach usually will produce the best results, and we emphasize it in the remainder of this chapter. A humorous look at a lack of interfunctional cooperation is depicted in Figure 3.1.
3.2 NEW PRODUCT DEVELOPMENT PROCESS
Most firms have an organized new product development (NPD) process that follows spe- cific phases or prescribed steps. These phases may be formally defined in company docu- ments and require sign-offs by senior management between phases. The purpose of this process is to gain control of product development and ensure that all important issues are addressed by the NPD team. ISO 9000 certification requires that a prescribed NPD process be defined and followed by the company in the development of its products.1
LO3.2 Describe the three phases of new product development.
1 ISO stands for the International Organization for Standards. ISO 9000 is a standard that applies to new product development and to production to ensure that quality products are designed and manufactured.
FIGURE 3.1 Lack of cooperation in designing a swing.
As proposed by marketing As specified in the product request As designed by the senior designer
As produced by manufacturing As used by the customer What the customer wanted
The Firm Designs a Swing
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40 Part One Introduction
The typical phases followed by firms in developing new products are concept development, product design, and pilot production/testing. The names of these phases and the number of phases may vary by company. But there is a great deal of similarity among the various approaches used, even across a wide variety of industries.
This phase is concerned with idea generation and the evaluation of alternative ideas for the new product and is sometimes referred to as the fuzzy front end. During this phase, several product concepts usually are generated and evaluated. The physical product is not designed during concept development; rather, different approaches to defining and meeting market needs are considered and the best approach is selected by the company. For example, when a new smartphone is developed, it must start with concept development. What features should the new phone have, including the size of the screen, the amount of memory, the type of cameras, and the features of the software to name only a few? What will appeal to the customers and the market?
Among the several conceptual designs considered and evaluated, one will be selected for the next phase of product development. The decision to proceed to the product design phase ordinarily requires top management approval. At the time of approval, a cross- functional team is established, if one does not exist already, to design the new product.
This phase is concerned with designing the physical new product. At the beginning, the firm has a general idea of what the new product will be but not too many specifics. At the end of the product design phase, the firm has a set of product specifications and digital images (or engineering drawings) specified in sufficient detail that production prototypes can be built and tested.
Product design requires consideration of many different trade-offs between product cost, quality (features), and the schedule for bringing the new product to market. Engineers are assigned to work on the various parts of the project. As they work, they make decisions that ultimately will affect the product’s cost, its quality (features), and the schedule for product introduction. It is easy to see why marketing, operations, and finance/accounting must also be involved with engineering during this phase so that appropriate trade-offs can be made for the greatest benefit of the entire business.
Engineering usually uses software to design the product and simulate its operation before it is made. This will help ensure that the product works when it is produced. Virtual prototypes, designed and tested using specialized software, are frequently used to speed up and simplify the engineering design tasks. Computer-aided design (CAD) systems are also used to design and view the product digitally and, in most cases, eliminate the need for
paper blueprints or drawings. At the end of this phase, the designs are transmitted to production as a basis for pilot production. In the smartphone example above, all of the physical components and the software will have detailed specifications for manufacturing.
Process design consists of planning the resources, tasks, and training needed for manufacturing the new product. It should be taking place simultane- ously with product design. Manufacturing should not wait for the final design to be completed before process design begins. As a matter of fact, it is bet- ter if process design is done in parallel with product design so that changes can be made in the product to facilitate the production process before finalizing the
Concept Development
Product Design
This is a CAD system used for product design. Shutterstock/Gorodenkoff
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product design. It is also a good idea for the product designers to have some manufac- turing experience so that they are aware of the process options available and the pitfalls of designs that can lead to poor production processes. Figure 3.2 shows how process design should proceed in parallel with product design.
In this third phase, products require testing of production prototypes before they are put into production. For example, in the design of a new laptop computer, several laptops would be built as prototypes and tested for their ability to meet the product specifications. This may include performance tests of hardware and software and lifetime tests of reliabil- ity of the laptop. Similar pilot production and testing is done for aircraft, automobiles, new cereals, and many other new products.
During this phase, the process for production is finalized. Since the product design is nearing completion, the process can be designed in great detail and tested for its capability to make the product that has been designed. Process and product modifications should be con- sidered so that the process is optimized before full-scale production and market introduction begin. To facilitate full-scale production, a set of documents should be finalized that contains not only product specifications but also process design specifications, training procedures for operators, and test results. This will facilitate the transition from design to production.
3D printing or additive manufacturing has made physical prototype development faster and easier. Almost any three-dimensional shape can be made by laying down suc- cessive layers of metal, plastic, or ceramics. An inkjet type of printer is used to make suc- cessive and additive layers of the three-dimensional proto- type. Prototypes for testing can be produced in a few hours instead of days or weeks with older technologies.
As 3D printing technology and the related software con- tinue to improve, more com- plex designs become possible. Airbus, for example, is experi- menting with 3D printing metal components for its jets, allow- ing their engineers a variety of
Pilot Production/ Testing
FIGURE 3.2 New product design process.
Pilot production/testing
Concept development
Product design
Final process design
Preliminary process design
Scientists use 3D printing technology to “print” human cells of spinal cord tissue. While these prototypes are still being tested, they will soon be ready for implanting into patients. Robert Clark/Getty Images
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42 Part One Introduction
new options in the design process. One such prototype is 30 percent lighter than the manu- factured component it would replace, a desirable characteristic in their industry. In the medi- cal industry, scientists are experimenting with printing prototypes built of human cells, as well as a variety of other new materials.
The rapid prototyping enabled by 3D printing is revolutionizing new product develop- ment processes in many industries. Helping firms speed up this portion of the design pro- cess will enable them to create more and better product designs.
3.3 CROSS-FUNCTIONAL PRODUCT DESIGN
The new product development process is one of frequent misalignment. No matter how excellent the advanced planning or the technology is, misalignment between marketing, product design, and operations is a common occurrence. Misalignments can occur for a variety of reasons.
Misalignment in marketing occurs when the product does not meet market needs. This can occur because of poor market intelligence or a misinterpretation of market needs. As a result, sales may be low and the product may need to be redesigned or eliminated.
Technology misalignment occurs when the product designed by engineering cannot be made by operations. This happens when technologies are new or unproven or are not well understood. Operations can be misaligned with the new product in terms of materials needed, labor skills, quality assurance, and scheduling. Finally, reward systems through- out the organization may reinforce the use of current technology and production practices rather than the new processes needed.
To overcome these problems in NPD, a concurrent marketing, engineering, and produc- tion approach can be used. The traditional approach proceeds in stages or steps, as shown in part (a) of Figure 3.3. In a sequential process, each function completes its work before the next one starts.
Figure 3.3 (b) illustrates a simultaneous development process, also called concurrent engineering (or simultaneous engineering). All functions are involved from the beginning, frequently by forming an NPD team, as soon as concept development is started. In the first stage, marketing has the major effort, but other functions also have a role. During the prod- uct design phase, marketing reduces its effort, but not to zero, while engineering has the major role. Finally, operations picks up the lead as the new product is tested and launched into the market.
LO3.3 Evaluate how concurrent engineering deals with misalignment.
FIGURE 3.3 Sequential and concurrent approaches.
Ef fo
rt
Sequential approach (a)
Time
Marketing Engineering Operations Ef fo
rt
Concurrent approach (b)
Time
Engineering Operations
Marketing
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The traditional approach is more like a relay race, while the concurrent approach is like rugby. In a relay race, each runner picks up the baton for one portion of the race. In rugby, the entire team runs down the field together, pushing and shoving in a group, to advance the ball toward the goal.
Concurrent engineering is used extensively by NASA (National Aeronautics and Space Administration) to coordinate both internally and externally with customers. At their Integrated Design Center, design teams develop new tools and technologies for a variety of purposes. The cross-functional teams develop tools such as telescopes and hyper- sensitive imagers, along with space flight designs and space architecture. NASA scientists and engineers work side-by-side with other functions as well as customers who may later manufacture the designed products. Their concurrent approach allows them to improve their product designs and to shorten development schedules.
Concurrent engineering is not always effective. It is less likely to be successful in proj- ects with high uncertainty (e.g., unfamiliar product, market, or technology). Concurrent engineering is more likely to improve performance for product extensions or products that serve familiar markets with current technology. Its main advantages, of helping to reduce misalignment and shorten project completion times, make this method useful in a variety of industries.
3.4 SUPPLY CHAIN COLLABORATION
Just as internal collaboration is important, so is external collaboration with supply chain customers and suppliers. While relationships with customers and suppliers often are estab- lished in new product development, collaboration is something different, requiring actual participation in the design process.
Collaboration with customers (either consumers or business customers) means tapping into their knowledge and expertise to design products they are willing to buy. The collabo- ration can take many different forms, including the following:
∙ Asking customers the right questions. What can we do to help you make your lives easier or more productive?
∙ Aligning incentives for customers to share their knowledge with the design team. Incen- tives could include merchandise, monetary rewards, and first access to new designs.
∙ Creating a collaborative technology platform to share information. This can take many forms, including computer networks or software to enable collaboration. For example, National Semiconductor created software that allows customers to design circuits by using National Semiconductor’s products.
∙ Including customers as advisors to the design team.
While collaborating with customers provides benefits, it also requires a change in attitude from “controlling the design” to working in partnership with customers. This requires a different mindset. For example, the designers cannot simply ask the custom- ers what they want or need, since customers don’t always know. A more sophisticated approach is to observe customers using current products to find limitations. The members of the design team should also ask themselves, What do customers do that we can do bet- ter? When they work with customers collaboratively in this way, new product designs are improved.
The second aspect of collaboration in the supply chain is working with suppliers. Since purchased materials and components often account for more than 50 percent of the cost of goods sold, suppliers should collaborate to design the product. This is particularly
LO3.4 Describe the criteria for selecting suppliers for collaboration.
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44 Part One Introduction
important when the product involves new technologies in which the company does not have expertise.
Suppliers can be asked to join the NPD team or to provide input at critical points in the design process. Their role is to offer improvements in the design or alternative approaches that leverage their own expertise. When a supplier is considered a potential collaborator, the following criteria should be considered:
∙ Technical expertise: Does the supplier have technical expertise that the company does not have?
∙ Capability: Can the supplier meet targets for cost, quality, and product performance? ∙ Capacity: Can the supplier meet the product development schedule and the ramp-up to
production? ∙ Low risk: What is the risk that the supplier will not perform as expected?
Supplier collaboration can provide improvements of 10 to 20 percent in cost, time, quality, and product performance. But should all suppliers be considered for collabora- tion? No, it is best to include only those who are critical to the design and have some- thing useful to offer the process. One example of successful supplier collaboration is TPI Composites wind turbine blades, as shown in the Operations Leader box. When there is collaboration with critical suppliers and customers in the supply chain, the design process is greatly improved.
constraints include highway underpass heights limiting the size of wind towers and difficulty transporting longer wind blades. Addressing these challenges through future collaboration will be needed to advance the industry.
Source: www.energy.gov, 2020 and www.tpicomposites .com, 2020.
TPI Composites, the largest U.S. independent manufac- turer of composite wind blades, is a major supplier in the wind energy industry. Their expertise in producing high quality blades makes them an important supplier to other manufacturers of wind turbine systems. Collaboration within their supply chain is extensive.
The U.S. market has grown substantially, with over 60,000 turbines collecting wind energy for conversion to electricity, and then sharing on the power grid (an additional 60,000 turbines are used for local energy consumption). Modern wind turbines are cost effective and reliable, but also complex, with roughly 8000 parts, including blades up to 75 meters (250 feet) in length and towers over 80 meters (262 feet) high, roughly the height of the Statue of Liberty.
Due to the size and complexity of turbine blades, TPI’s manufacturing process is costly and labor intensive. A collaborative partnership with the Department of Energy, Sandia National Laboratories, Iowa State University, and their blade customers helped TPI reduce production times for a single blade by 37 percent (from 38 to 24 hours).
As the demand for renewable energy persists and wind turbines are designed in ever larger sizes, TPI must find ways to overcome infrastructure constraints. These
TPI Composites
OPERATIONS LEADER
GYRO PHOTOGRAPHY/amanaimagesRF/ Getty Images
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3.5 QUALITY FUNCTION DEPLOYMENT
The new product development process is aided by many different tools and techniques, some of which are covered in the remainder of this chapter. Quality function deployment (QFD) is a tool for linking customer requirements to technical product specifications. QFD is very useful in translating the ordinary language obtained from the customers to technical requirements understood by engineers. It also facilitates cooperation and communication between marketing, engineering, and manufacturing.
QFD was first used in 1972 at the Mitsubishi shipyard in Japan. It spread from there to Toyota and to American companies. Now many companies throughout the world are using QFD in industries such as automobiles, electronics, home appliances, and services. QFD is very useful as a communication tool.
When using QFD, the firm begins by identifying various customer attributes. Each of these attributes can be met by one or more engineering characteristics of the product. By using the matrix shown in Figure 3.4, the customer attributes on the left side of the matrix can be related to the engineering characteristics on the top of the matrix. When the matrix is completed, it is called the house of quality.
The house of quality illustrated in Figure 3.4 will be explained in some detail by using a bicycle example. We will work through this example one step at a time, beginning with the customer attributes.
LO3.5 Evaluate an example of Quality Function Deployment.
FIGURE 3.4 Relationship matrix.
Customer attributes
Total 100
R el
at iv
e im
po rt
an ce
N um
be r
of g
ea rs
(# )
Engineering characteristics
Bi cy
cl e
w ei
gh t (
lb s)
St re
ng th
o f f
ra m
e (ft
/lb s)
C ru
isi ng
sp ee
d (m
ph )
C oa
ts o
f p ai
nt (#
)
Customer perceptions
Strong positive
Positive
Negative
Strong negative
Relationships
Etc. 25
Looks nice 10
Low cost 20
Fast acceleration 15
Strong and durable 20
Easy to pedal 10
Our bike Competitor A Competitor B
1 2 3 4 5
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46 Part One Introduction
The customer attributes (CAs) shown on the left side of the matrix in Figure 3.4 repre- sent the voice of the customer. These attributes are determined through market research involving potential customers of the bicycle to define the important attributes of the prod- uct. Therefore, a target market must be defined so that the appropriate types of customers can be contacted. Suppose, in this case, the bicycle is being designed for a very specific market: use by college students on campus. College students would be interviewed to determine what they consider important features or attributes of a bicycle. Suppose that the students would like a bicycle that is easy to pedal, is strong and durable, has fast accelera- tion, has a low cost, and looks nice. Note that these CAs are not very specific at this point and need further definition by means of the QFD process.
A few more things are now added to the house of quality. After the CAs have been listed on the left side of the matrix, they are rated on their relative importance by customers to sum to a total of 100 points. This is shown on the “chimney” column of the house of qual- ity in Figure 3.4. On the right side of the matrix is a comparison of how the company’s current bicycle compares to competitors’ offerings on each of the CAs.
The next step in QFD is to translate the customer attributes into engineering characteristics (ECs). This is done by determining how each of the customer attributes can be met by the new bicycle design. Engineering characteristics must be measurable and specific and are closely related to the final design specifications for the product.
For the bicycle design, some of the ECs might be number of gears, weight of the bicycle in pounds, strength of the frame, cruising speed, and number of coats of paint on the frame. These characteristics are listed across the top of the matrix in Figure 3.4 and then related to each of the customer attributes. For example, the CA “easy to pedal” is strongly related to the number of gears on the bicycle. Generally, the more gears, the easier it is to
pedal the bicycle in different conditions and situations. Also, “easy to pedal” is inversely related to the weight of the bike. Various sym- bols are placed in the matrix (see Figure 3.4 for the key) to indicate the nature of the relationship between each particular CA and the ECs. This can be done by conducting engineering tests or by using generally understood relationships.
Next, we switch to Figure 3.5, which adds a roof to the house of quality. The roof shows how each EC is related to the other ECs. This makes it possible to study any of the trade-offs that may be required between one EC and another. For example, we see that the weight of the bicycle will negatively affect its cruising speed. Also, the number of coats of paint will have a mild positive effect on bicycle weight.
Finally, on the bottom of the matrix in Figure 3.5, we have indi- cated the value of each EC achieved by the competitors’ bicycles. We have also shown a target value that we have set for each EC in our new bicycle design. The target value is determined by design decisions, based on the importance of various customer attributes, the linkages to ECs, and the desired performance of the new bicycle relative to those of the competitors. The ultimate result of the house of quality is a translation of the CAs into target values for ECs on the bottom of the matrix.
The house of quality is very useful in increasing cross-functional communications because it neatly connects the market requirements with the design characteristics that engineers must consider. Thus, a
Customer Attributes
Engineering Characteristics
Her bicycle can be designed by use of QFD. Paul Bradbury/age fotostock
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design can be developed that will meet the needs of the market while still considering all the design trade-offs required. The house of quality is a visual tool that captures a variety of information needed by various business functions during the new product development process.
QFD also can be applied to service industries in much the same way it is applied to manufacturing. To illustrate, suppose a pizza shop is considering adding a take-out deliv- ery service for its pizza.
The CAs for this new service have been determined from customers to be fast, courte- ous, and reliable service. Also, the delivery agent should have a clean-cut appearance and the order should be delivered complete (no missing items) with hot pizza. The CAs are listed on the left side of the QFD matrix in Figure 3.6.
For services it can be difficult to identify the ECs, which are sometimes hard to define and measure. In this case, the ECs are delivery time (minutes), customer satisfaction (from a periodic survey of customers), proportion of orders delivered on time, and the temperature of the pizza when it is delivered. Note that the customer survey will measure intangible CAs such as a clean-cut appearance, courtesy, order completeness, and general satisfaction with the service.
The CAs are now related to each of the ECs in the same way as in the bicycle example. Also, the roof of the house of quality, customer perceptions, competitive evaluations, and targets are added to complete the analysis, as shown in Figure 3.6. While QFD for service may be measured somewhat differently than it is for manufacturing, the same general prin- ciples apply.
FIGURE 3.5 House of quality.
Customer attributes
A
R el
at iv
e im
po rt
an ce
N um
be r
of ge
ar s (
#)
Bi cy
cl e
w ei
gh t
(lb s)
St re
ng th
o f f
ra m
e (ft
/lb s)
C ru
isi ng
sp ee
d (m
ph )
C oa
ts o
f p ai
nt (#
)
Customer perceptions
Strong positive
Positive
Negative
Strong negative
Relationships
Etc. 25
Looks nice 10
Low cost 20
Fast acceleration 15
Strong and durable 20
Easy to pedal 10
Competitive evaluation B Targets
40 50 35
10 10 12
1,000 1,000 1,100
30 25 35
2 2 3
Our bike Competitor A Competitor B
1 2 3 4 5
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48 Part One Introduction
3.6 MODULAR DESIGN
Usually products are designed one at a time without much regard for commonality of parts or modular properties that can aid production and still meet customer needs. Modular design makes it possible to have relatively high product variety and low component variety at the same time. The core idea is to design a series of basic product components, or mod- ules, that can be assembled into a large number of different products. To the customer, it appears there are a great number of different products. To operations and the supply chain, there are only a limited number of basic components and processes.
Controlling the number of different components that go into products is of great importance to operations, since this makes it possible to produce more efficiently by standardization of processes and equipment. In the supply chain, few components means fewer suppliers to manage and fewer parts to be purchased. A large number of product components will greatly increase the complexity and cost of operations and supply chain.
Modular design offers a fundamental way to change thinking about product design. Instead of designing each product separately, the company designs products around stan- dard component modules and standard processes. When this is done, the product line is carefully analyzed and divided into basic modules. Common modules should be developed that can serve more than one product line, and unnecessary product frills should be elimi- nated. This approach will still allow for a great deal of product variety, but the number of unnecessary product variations will be reduced.
LO3.6 Explain the benefits of modular design.
FIGURE 3.6 QFD for Pizza U.S.A. delivery.
Customer attributes
A
R el
at iv
e im
po rt
an ce
D el
iv er
y tim
e in
m in
ut es
C us
to m
er sa
tis fa
ct io
n su
rv ey
ra tin
g
% o
rd er
s d el
iv er
ed on
ti m
e
Te m
pe ra
tu re
o f
pi zz
a
Customer perceptions
Strong positive
Positive
Negative
Strong negative
Relationships
Hot pizza 10
Complete order 15
Clean-cut appearance 10
Reliable (as promised) 25
Courteous service 10
Fast service 30
Competitive evaluation B Targets
5.0 5.5 6.0
20 18 15
80 85 90
150F 140F 150F Competitor B
Competitor A Our position
1 2 3 4 5
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The modular design approach can best be illustrated by an exam- ple. A large manufacturer of beds used modular design ideas, with four basic sizes: twin, double, queen, and king. The inside construction of the mattresses was limited to only a few different spring arrangements and foam padding thicknesses. A moderate variety of mattress covers were used to meet consumer prefer- ences for color and type of design. This approach greatly reduced the number of mattress components while providing substantial variety for the customer. For example, with four bed sizes, three types of spring construction, three types of foam, and eight different covers, a total of 288 different mattress designs were possible.
4 × 3 × 3 × 8 = 288 combinations
Not all combinations were produced, since some might be unacceptable to the customer (e.g., the expensive springs with the thin foam pad). Although there are still many product combinations in this example, the number of components has been limited.
Most automobile manufacturers use modular design for their vehicles. Even MINI Cooper’s most basic model, for example, has many optional choices: four body colors, three wheel designs, eight interior finish options, two engines, and eleven style options. The theoretical number of different cars that can be produced is as follows:
4 × 3 × 8 × 2 × 11 = 2112
Modular design provides an opportunity to streamline production at MINI while offering abundant consumer choices. The company further benefits by using some of these mod- ules in its other car models, saving significant time and cost in the module design process.
3.7 KEY POINTS AND TERMS
New product design has a great impact on operations and supply chain, and other functions as well, since it determines the specifications for future products. Likewise, operations can constrain a firm’s ability to develop new products and make them more costly to produce. As a result, operations should be deeply involved in new product development.
∙ There are three ways to develop new products: market pull, technology push, and inter- functional. The interfunctional approach is usually the best since it includes both market and technological considerations in the new product design.
∙ The NPD process is often specified in companies as having three phases: concept devel- opment, product design, and pilot production/testing.
∙ Products should be designed from the start for manufacturability. This is done by considering design of the production process as part of product design and utilizing a concurrent engineering approach.
∙ Concurrent engineering uses overlapping phases for product design rather than a sequential approach. Typically, an NPD team is formed with representation from all major functions (marketing, engineering, operations, and finance/accounting) to ensure cross-functional integration.
Robert Wilson/123RF
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50 Part One Introduction
∙ 3D printing, or additive manufacturing is useful for creating product prototypes. The speed and flexibility of this new technology enhances product design opportunities.
∙ Supply chain collaboration in NPD is essential. This should be accomplished by col- laborating with both customers and suppliers in the NPD process.
∙ QFD is used to connect customer attributes to engineering characteristics. This typi- cally is done through a technique called the house of quality that can be used for both manufacturing and services.
∙ Modular design is used to minimize the number of different parts needed to make a product line of related products. This can be done by designing standard modules and considering only the combinations of options that have significant market demand.
Key Terms Market pull 38 Technology push 38 Interfunctional view 39 Concept development 40 Product design 40 Pilot production/testing 40 Process design 40
Quality function deployment 45 House of quality 45 Customer attributes 46 Engineering characteristics 46 Trade-offs 46 Target value 46 Modular design 48
Production prototypes 41 3D printing 41 Additive manufacturing 41 Misalignment 42 Sequential process 42 Concurrent engineering 42 Collaboration 43
LEARNING ENRICHMENT (for self-study or instructor assignments)
What Is the New Product Development Process? Video https://youtu.be/vQZjNIRpuFg 2:49
Tools for Accelerating a Cross-functional Design Process Web Link https://www.mckinsey.com/business-functions/operations/our-insights/ accelerating-product-development-the-tools-you-need-now
Prototyping Video https://youtu.be/5SWt-TSYD08 2:26
3D Printing Prototype Example Video https://youtu.be/RpFTRT8FkP0 3:02
Sustainability in New Product Development Video https://youtu.be/-HS-slU-XTc 3:56
Discussion Questions 1. Why is cross-functional cooperation important for new
product design? What are the symptoms of a possible lack of cooperation?
2. In what circumstances might a market-pull approach or a technology-push approach to new product design be the best approach?
3. Describe the steps that might be required in writing and producing a play. Compare these steps to the three steps for NPD described in Section 3.2. How are they similar?
4. Why has there been an increase in product variety in global markets?
5. How can modular design help to control production variety and at the same time allow product variety?
6. What is the proper role of the operations function in product design?
7. What form does the product specification take for the following firms: a travel agency, a beer company, and a consulting firm?
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Chapter 3 Product Design 51
8. Find examples of modular design of products in every- day life.
9. Work with one of your classmates as your customer; you are the supplier. Have your customer select a prod- uct and specify the customer attributes (CAs) that are desirable. Then you specify the engineering charac- teristics (ECs) required to meet the customer’s needs. Complete the house of quality matrix by specifying the relationships in the matrix. Ask your customer if the resulting ECs will meet his or her needs.
10. What are the essential benefits of using a QFD approach to product design? Also, identify any negative effects that might apply to the use of QFD.
11. A student would like to design a backpack for student books and supplies. The CAs are a (1) comfortable backpack that is (2) durable with (3) enough room and (4) not too heavy to carry. Think of some ECs
that can be used to measure these customer attributes. Then construct a QFD matrix showing the positive and negative relationships that you expect to see in this case.
12. An entrepreneur is designing a sub sandwich shop that would be located on campus. Define the CAs that you would like to see for the service (not the product) deliv- ered at this location. Then specify some ECs that can be used for measurement of the service.
13. Suppose a car you want to buy has five choices for inte- rior colors, three types of stereos, three engine choices, two battery types (regular and heavy duty), 10 exterior colors, two transmission choices, and four types of wheel covers. How many possible combinations of the car are possible for the manufacturer? What can be done to limit the number of combinations without limiting customer choice?
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4. Process Selection
5. Service Process Design
6. Process-Flow Analysis
7. Lean Thinking and Lean Systems
Among the most important decisions made by operations managers are those involving the design and improvement of the process for producing goods and services. These decisions include choice of process and technology, analysis of flows through operations, and the associated value added in operations. Two themes underlie and unify Part Two: first, the idea of designing and improving a process to enhance the flows of materials, customers, and information; second, the idea of eliminating waste in processes. These principles can be used to design and manage a process that not only is efficient but provides value for the customer. ■
ii
Pa rt
Process Design
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Process Selection
Process selection decisions determine the type of process used to make a product or service. For example, automobiles are made using an assembly-line type of process, wine making is a batch type of process, and a tailor shop is a job shop type of process. The important con- siderations required for process selection include the volume of the product and whether the product is standard or custom. Generally speaking, high-volume products that are standard will be made on an assembly line, and low-volume custom products will be made using a batch or job shop process.
This chapter describes the various types of processes that can be selected and the corre- sponding product or service characteristics when one process or another is preferred. Two main types of classifications are provided. The first is by the product flow, including con- tinuous flow, assembly line, batch, job shop, and project. The second is by the type of order fulfillment: whether the product is made-to-order, assembled-to-order, or made-to-stock.
4 c h a p t e r
After reading this chapter, you should be able to:LEARNING OBJECTIVES
LO4.1 Contrast and compare the five types of product-flow processes.
LO4.2 Describe the differences among order fulfillment processes.
LO4.3 Explain how companies should make process selection decisions.
LO4.4 Correctly place examples of products on the product-process matrix.
LO4.5 Describe the features of focused operations.
LO4.6 Discuss the uses of mass customization and 3D printing.
LO4.7 Contrast pollution prevention, pollution control and pollution practices.
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After process types and order fulfillment, we discuss focused operations, mass cus- tomization, and 3D printing as process choices. We also discuss environmental concerns and the prominent role process selection plays in determining the impact of a firm on its natural environment.
4.1 PRODUCT-FLOW CHARACTERISTICS
There are five types of product flow: continuous process, assembly line, batch, job shop, and project. In manufacturing, the product flow is the flow of materials, since materials are being converted into the product. In services, there is a work flow, such as a flow of customers or information.
Continuous Processes Continuous process refers to the so-called process industries, such as sugar, paper, oil, and electricity. Here, the output is made in a continuous fashion and tends to be highly standard and with very high volumes of production. Often continuous flow products are liquids or semisolids that can be pumped or that flow from one operation to another. For example, an oil refinery consists of miles of pipes, tanks, and distillation columns through which crude oil is pumped and refined into gasoline, diesel, oil, lubricants, and many other products.
Continuous processes tend to make commodity products. Since it is difficult to differ- entiate the product, low cost becomes the “order winner” for manufacturing to compete in very price-sensitive markets. Therefore, continuous processes tend to be highly automated, operate at nearly full capacity, and minimize inventories and distribution costs to reduce the total cost of manufacturing. While cost per unit of output is low, flexibility to change product mix or product type is very limited in continuous processes.
Assembly Lines Assembly lines are used to make only one or a few different products using inflexible equipment and labor. Later in this chapter, we describe mass customization that allows much more flexible assembly lines. Assembly-line flow is characterized by a linear sequence of operations. The product moves from one step to the next in a sequential man- ner from beginning to end. Unlike continuous processes, in which the products are liquids or semisolids, assembly lines make discrete products such as automobiles, refrigerators, computers, printers, and a vast array of mass-produced consumer products. Products are moved from one operation to the next, usually by a conveyor system.
Figure 4.1 shows how an assembly-line process is used to make a metal bracket. The first step in production is to cut a rectangular metal blank in the required dimensions of the bracket. At the second workstation, two holes are drilled into the metal blank. Then the bracket is bent at a 90-degree angle, and finally, it is painted. Notice how the workstations are placed in the proper sequence needed so that the product moves sequentially from one end of the line to the other. Each workstation likely has a single worker performing a task, so most workers have limited skills.
Like continuous processes, assembly-line operations are very efficient but also very inflexible. The assembly-line operation requires high-volume and standard products. At the same time, it is difficult to make changes in the product itself or the volume of flow, resulting in inflexibility of operations. For example, it takes several weeks to change over a traditional automobile assembly line to a new model. Also, the line runs at a constant speed, and so the volume can be altered only by changing the number of hours worked or redesigning the entire line.
LO4.1 Contrast and compare the five types of product-flow processes.
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56 Part Two Process Design
FIGURE 4.1 Assembly-line flow.
Task or workstation
Product flow
Cut Drill Bend Paint
The Product (a metal bracket)
Assembly-line operations generally require large amounts of capital investment and must have high volume to justify the investment. For example, a modern plant that makes semiconductor wafers costs over $2 billion in initial investment, and an automobile assem- bly plant costs about $1 billion. An automobile assembly plant completes the production of a car every minute, or about 350,000 automobiles a year, if operated on a two-shift basis. Because of the significant amount of capital required, finance is concerned with the choice of an assembly-line process and works closely with operations in making these investments. Also, marketing must be geared toward mass appeal to justify producing in high volume.
Most electronics manufacturing processes are assembly lines. nikitabuida/Shutterstock
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FIGURE 4.2 Batch flow (metal brackets).
Batch A
Product A
Batch B Batch C
Product B Product C
Bend
Cut
Drill
Paint
Task or work center
Batch Flow Batch flow is characterized by production of the product in batches or lots. Each batch of the product travels together from one operation or work center to another. A work center is a group of similar machines or processes used to make the product.
Figure 4.2 shows various low-volume brackets that are made using a batch process. In this simple example, three differently shaped brackets—A, B, and C—flow through the four work centers. Notice how bracket A requires work in all four work centers; bracket B requires only cutting, bending, and painting; and bracket C requires cutting, drilling, and painting. One characteristic of a batch operation is that it can be used to make many dif- ferent types of products, and so more variety is typical than on an assembly line. Batches of each of these products can have a different flow path, and some products actually skip certain work centers. As a result, the flow is jumbled and intermittent. Contrast this to the flow of a line process, which is regular and sequential.
Batch operations often use general-purpose equipment that is not specialized to make just one particular product. This offers flexibility. Labor is more skilled and flexible in its ability to make different products. As a result, a batch operation is configured with both equipment and skilled labor to be more flexible than an assembly-line process. Lot sizes can vary, from hundreds down to as few as one unit. As a result, batch processes can be configured to handle low-volume orders.
The jumbled flow of a batch operation results in considerable production scheduling and inventory challenges. When loaded to nearly full capacity, the batch operation will typically have high inventories as lots wait in line to be processed. High capacity utilization will cause interference between the various lots as they wait for labor or equipment that is assigned to another job at the time. This results in a loss of efficiency in a batch operation.
A batch operation uses a process layout because the machines and labor are orga- nized by process types into work centers. The assembly-line process, however, uses a
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58 Part Two Process Design
product layout because the machines and labor are organized according to the product flow itself. An example of a process layout is the typical high school, where classrooms are organized according to subjects (or processes) such as math, chemistry, and music. The students flow through the facility in batches (classes), going from one process to the next.
Batch operations are used when the volume is not high or there are many different prod- ucts. Examples are furniture, boats, dishware, and other products with large variety and low to moderate volumes. Furniture making, for example, requires many different styles and options. Dining tables may be available in different woods and with different chair styles. Each of these can be produced in a small batch.
Job Shop Job shops make products to customer order by using a process layout. Thus, we consider the job shop a special case of the batch process. In a job shop, the product is made in batches, usually in small lot sizes, but the product must be made to customer order.
Like the batch process, a job shop uses general-purpose equipment and has a jumbled flow. It has high flexibility for product mix and volume of production, but the costs are generally higher since the volume and standardization are low. Typical products produced in a job shop include plastic parts, machine components, electronic parts, and sheet metal parts that are made-to-order.
Project The project form of operations is used for unique or creative products. Examples of proj- ects are concerts, construction of buildings, and production of large aircraft. Technically speaking, the product does not flow in a project since materials and labor are brought to the project site and the project itself is stationary. Projects are characterized by difficult planning and scheduling problems since the product may not have been made before. Also, projects are difficult to automate, though some general-purpose equipment may be used. Labor must be highly skilled because of the unique nature of the product or service being made.
Each unit is made individually and is different from the other units. Projects are used when the customer desires customization and uniqueness. Generally speaking, the cost of production for projects is high and sometimes difficult to control. It can be challenging up front to specify all of the work that will be needed to complete a project.
Boeing makes large aircraft by using a project process. Each airplane is assembled at a fixed site within the factory with materials and labor brought to the site. A complex sched- ule is made that must balance work across all the different aircraft being produced. The con- struction industry uses projects to construct buildings, roads, and bridges. Service industries also use projects for fund-raising events, political campaigns, concerts, and art fairs.
Discussion of Process Types The characteristics of the five processes we have been discussing—continuous, assembly line, batch, job shop, and project—are summarized in Table 4.1. This table makes direct comparisons among the types of processes. Notice that continuous and assembly-line oper- ations have relatively low-skilled operators and high automation, whereas batch, job shop, and project operations are the opposite. Capital varies from high to low across the various process types, and the objectives and process characteristics also vary.
One way to measure the efficiency of a process is the throughput ratio (TR):
TR = Total processing time for the job ___________________________ Total time in operations
× 100%
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In the numerator of the throughput ratio is total processing time for the job, which includes only the time the job actually spends being processed by machines or labor, excluding any waiting time between operations. The denominator includes the total time the job spends in operations, including both processing and waiting time. Most batch and job shop opera- tions have TRs of 10 to 20 percent, rarely higher than 40 percent. This means that a typi- cal job spends most of its time waiting to be processed relative to the actual processing time. In contrast, continuous and assembly-line processes have TRs of 90 to 100 percent. The throughput ratio represents the proportion of time in operations during which value is actively being added to the job.
At this point, examples from the housing industry may help solidify some of the pro- cess choices. At the project end of the continuum is the custom-built house. A unique plan
for it may be drawn by an architect, or existing plans may be modified for each house built. The process is labor-intensive, time-consuming, and costly, but it is very flexible. General-purpose equipment is used to complete the work.
The batch process is characterized by the produc- tion of similar houses in groups. In this case, the cus- tomer can select one of several standard houses with only minor options such as paint colors, light fixtures, and carpets. Such a house is usually less expensive per square foot than a custom-built project house, but there is less flexibility in operations to allow customers to choose among options.
The assembly-line method of house production is characterized by modular or factory operations. Stan- dard houses are produced in sections, in a factory, by
TABLE 4.1 Process Characteristics
Characteristics Continuous and Assembly Line Batch and Job Shop Project
Product
Order type Continuous or very large batch
Batch Single unit
Flow of product Product variety Market type Volume
Sequenced Low Mass High
Jumbled High Custom Medium to low
None Very high Unique Single unit
Labor
Operator Skills Task type Pay
Low Repetitive Medium
High Nonroutine High
High Nonroutine High
Capital
Investment Inventory Equipment
High Low Special purpose
Medium High General purpose
Medium Little General purpose
Objectives
Flexibility Cost (per unit) Quality Delivery
Low Low Conformance On time
Medium Medium Conformance On time
High High Conformance On time
House construction can be completed using various types of processes. Alex Potemkin/Getty Images
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60 Part Two Process Design
relatively cheap labor. The use of expensive plumbers, carpenters, and electricians is largely avoided by installing complete electrical and plumbing systems at the factory. After being built on an assembly line, the house sections are brought to the site and erected in a few days, using a crane. These modular houses are typically the least expensive of all and pro- vide the least flexibility in customer choice.
Obviously, a company faces a major strategic decision in choosing the type of process to use for the construction of houses. Most companies choose only one type of process, unless separate divisions are formed for different processes.
4.2 APPROACHES TO ORDER FULFILLMENT
Another critical decision for operations is how the orders from customers are fulfilled: whether the product is made-to-order, assembled-to-order, or made-to-stock. There are advantages and disadvantages to each of these. A make-to-stock (MTS) process can provide faster service to customers by delivering orders from available stock and at lower costs than a make-to-order (MTO) process. But the MTO process has higher flexibility for product cus- tomization. An assemble-to-order (ATO) process is like a hybrid of these, enabling relatively fast service to customers because there is limited work to complete once the customer order is received. It is also flexible because the customer can specify some types of customization.
In the MTO process, the cycle of production and order fulfillment begins with the cus- tomer order. After the order has been received, the design must be completed, if it is not already done, and materials are ordered that are not already on hand or on order. Once the materials begin to arrive, the order can be processed as materials and labor are added until the order is completed. Then the order is delivered to the customer. Once the customer pays for the order, the cycle is completed.
The key performance measure of an MTO process is the length of time it takes to design, make, and deliver the product. This is often referred to as the lead time. Another measure of performance in an MTO environment is the percentage of orders completed on time. This percentage can be based on the delivery date the customer originally requested or the date that was promised to the customer. The date requested by the customer provides, of course, a stricter criterion.
In contrast, the MTS process has a standard product line specified by the producer, not by the customer (see Figure 4.3). The products are carried in inventory to fulfill customer demand immediately. Operations produces inventory in advance of actual demand in order to have the proper products in stock when the customer order arrives. The critical manage- ment tasks are forecasting, inventory management, and production planning.
The MTS process begins with the producer specifying and producing the product. The customer then requests a product from inventory. If the product is available in inventory, it is delivered to the customer. If it is not available, a back order may be placed or the cus- tomer may cancel the order. A back order allows the firm to fill the order at a future date but requires the customer to wait for the order. Ultimately, once the order is received, the customer pays for the product and the cycle is completed.
In an MTS process customer orders cannot be identified during production. The pro- duction cycle is being operated to replenish stock. What is being produced at any point in time may bear little resemblance to what is being ordered by customers. Production is geared to future orders and replenishment of inventory. See the differences in the produc- tion cycles in Figure 4.3.
The key performance measure for an MTS process is the percentage of orders filled from inventory. This is called the service level or fill rate and is typically targeted in the
LO4.2 Describe the differences among order fulfillment processes.
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range of 90 to 99 percent. This means, for example, that when a customer places an order, it is immediately filled from existing stock 99 percent of the time. Other relevant perfor- mance measures are the length of time it takes to replenish inventory, inventory turnover, capacity utilization, and the time it takes to fill a back order. The objective of an MTS process is to meet the desired service level at minimum cost.
In summary, the MTS process is keyed to replenishment of inventory with order fulfill- ment from inventory, whereas the MTO process is keyed to fulfilling individual customer orders. An MTO process can provide higher levels of product variety and has greater flexi- bility. The performance measures of these two fulfillment options are completely different. The MTS process is measured by service level and efficiency in replenishing inventory, and the MTO process is measured by its response time to customers and the ability to meet promised customer delivery dates.
Assemble-to-order (ATO) processes are a hybrid of MTO and MTS. The subassem- blies are made-to-stock, but the final assembly is made-to-order. The ATO process builds subassemblies in advance of demand. When the customer order is received, the subassem- blies are taken from inventory and assembled together to fill the customer order. Figure 4.3 shows how the subassemblies are built to a forecast and placed in inventory. The product must be designed in a modular fashion for ATO to be used.
FIGURE 4.3 MTS, MTO, and ATO comparison.
Customer
Production of subassemblies
Forecast orders
Order assembly
Holding inventory of
subassemblies
Product
Customer order
Assemble-to-Order
Production
Forecast orders
Finished goods
inventory
Product
Product
Customer order
Make-to-Stock
Product
Customer order
Customer
Production
Make-to-Order
Customer
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62 Part Two Process Design
Some operations are moving toward assemble-to-order and make-to-order processes for standardized products, whenever possible, by reducing production lead times. If the standard product can be made quickly, it need not be produced ahead of time and placed in finished-goods inventory; instead, it can be made or quickly assembled when ordered by the customer. For example, Allen-Bradley Co. can make and ship a motor starter unit in over 300 different configurations in one day from when it is ordered. This product, which previously had been made-to-stock, can be assembled-to-order with large savings in inven- tory and improved customer service. Allen-Bradley assembles the product with a fast and flexible assembly line.
An example of the three types of processes involves the production of diamond rings for the jewelry business. The MTS process is used for rings that are carried in finished-goods inventory by the jewelry store. In this case, the customer buys one of the rings from the jew- eler’s stock. The ATO process is used when the customer selects the stone and then makes a separate selection of a ring setting. The jeweler will then assemble the ring components. The MTO process is illustrated by jewelers who make rings to the customer’s design. The setting and the stone are designed, fabricated, and assembled into a unique ring. See the Operations Leader box on Culver’s to understand how they use these order fulfillment approaches.
From its 1984 beginning in Sauk Center, Wisconsin, there are now more than 700 Culver’s restaurants in the U.S. The restaurant chain, famous for its ButterBurgers and frozen custard desserts, continues to grow. Their menu provides examples of items that are make-to- stock, assemble-to-order, and make-to-order.
Some food items, such as daily soup options and sal- ads are made-to-stock. They are prepared using batch processes, and then held in stock at each restaurant. These items are ready to be served quickly once custom- ers order them.
ButterBurgers, on the other hand, are made-to-order. They are cooked only once a customer has ordered one, and they require some preparation lead time. Customers can specify which toppings to include, so the sandwich is truly custom to their preferences.
Finally, frozen custard desserts are made using an assemble-to-order process. Several flavors of custard, along with a variety of toppings, are in stock and ready for the customer order. Once the customer specifies their custard flavor and topping, the dessert can be quickly assembled and served.
Culver’s uses three different types of processes— MTS, ATO, and MTO—to operate efficiently and effec- tively. The choice of which to use depends on the characteristics of the food item and on Culver’s strategy.
Source: www.culvers.com, 2020.
Culver’s
OPERATIONS LEADER
designs by Jack/Shutterstock
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The type of customer order, whether MTS, MTO, or ATO, determines the order penetration point in the supply chain where the product is linked to a specific customer order.1 There are four possibilities for the placement of the order penetration point, as shown in Figure 4.4. For MTS operations, the order point is after final assembly is completed; there- fore, the customer can only select the product from what is available in inventory. For ATO, the order penetration point is after fabrication and before final assembly. Since the product is assembled after the order is placed, the customer can specify some customization in terms of the modules he or she selects. For MTO operations, the order penetration point is either before fabrication or before ordering materials from the supplier in cases in which unique materials or components are needed. For MTO, many types of customization are possible, but the lead time to the customer can be longer and the product is typically more costly.
4.3 PROCESS SELECTION DECISIONS
We have been discussing two dimensions that can be used for process classification pur- poses: product flow and approaches to order fulfillment. These dimensions are used to construct the six-cell matrix shown in Table 4.2. This matrix contains the six combinations used in practice. Multiple combinations may be used by a single firm, depending on the products and volumes required by the market.
All six combinations are encountered in industry. Although it is common for an assembly-line operation to make-to-stock, it can also assemble-to-order. For example, an automobile assembly line is used to produce a large variety of different automobile options for particular customers, as well as cars that are being made for dealer stock. Similarly, a
1 Sometimes also called the customer order decoupling point.
LO4.3 Explain how companies should make process selection decisions.
FIGURE 4.4 Order penetration point.
MTO MTO ATO MTS
Raw materials Fabrication Assembly Distribution
TABLE 4.2 Process Characteristics Matrix
Make-to-Stock Make-to-Order/Assemble-to-Order
Continuous and Assembly Line
Automobile assembly Oil refining Cannery Cafeteria
Automobile assembly Laptop computers Electronic components Fast food
Batch and Job Shop Machine shop Wine Glassware factory Costume jewelry
Machine shop Restaurant Hospital Custom jewelry
Project Speculation homes Commercial paintings Noncommissioned art
Buildings Movies Ships
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64 Part Two Process Design
project form of process commonly is used to make-to-order. However, a construction com- pany can build a few speculation houses to stock that are sold later.
In discussing the process selection decision, we shall begin with an example and gen- eralize from there. Let us consider the construction company mentioned in Section 4.1, which can choose to build houses using the project, batch, or assembly-line process. With any of these processes, the company can also choose to make the houses to stock or to order. What, then, are the factors that should be considered in making this choice?
First, the company should consider market conditions. The assembly-line approach requires a mass market for inexpensive houses, the batch process requires a lower-volume market for medium-priced houses, and the project process requires a market for expen- sive houses. Which one of these is chosen will require discussions between marketing and operations, which are cross-functional since both market and process are affected. In the end, matching the process to the market will be a key strategic decision.
Second, the company should consider capital requirements. The assembly-line process will require a great deal more capital than will the project or batch flow. The assembly line requires capital for a factory and equipment and to finance the partially completed or finished houses. By contrast, construction of custom project houses requires much less capital since only one house or a few houses are being built at any one time and no fac- tory is needed. The finance function will be intimately involved with operations in making these capital decisions.
The third factor that should be considered is the availability and cost of labor. The project and batch processes require costly skilled labor, such as plumbers, electricians, and carpenters. The factory line approach requires relatively inexpensive, low-skilled labor. Unionization may affect both the supply and the cost of labor. The human resources func- tion will be involved in these decisions with operations because of the employee selection, training, and compensation issues involved.
Finally, the company should consider the state of technology for both process and prod- uct. Are innovations likely to come along that will make a process obsolete before the costs are recovered? Assessment of these conditions is part of risk evaluation for the process.
In summary, four factors appear to influence process selection:
1. Market conditions 2. Capital requirements 3. Labor 4. Technology
4.4 PRODUCT-PROCESS STRATEGY
To this point, we have been treating process decisions as static, as if the organization makes the decision one time and then uses the selected process forever. Actually, process decisions are dynamic, since processes evolve over time. Furthermore, process decisions are closely related to product decisions, and both products and markets change over time.
Hayes and Wheelwright have proposed a product-process matrix that describes the dynamic nature of product and process choices (see Figure 4.5). On the product dimen- sion (horizontal) of the matrix is the life cycle of a typical product, ranging from a unique, one-of-a-kind product to a high-volume, standardized product. A product typically evolves from the left side to the right side of the matrix.
On the process dimension (vertical) of the matrix the various processes are represented, ranging from the project to a continuous process. The process has a life cycle similar to the
LO4.4 Correctly place examples of products on the product-process matrix.
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product life cycle, evolving from a unique project type of production at the top of the matrix to a continuous process at the bottom. Many products have followed the product and process life cycle. Automobiles were made in a job shop environment in the early 1900s before Henry Ford invented the moving assembly line. Electronics often are produced in batches until the volume becomes sufficient to support an assembly-line process. Most product life cycles will not require processes to evolve from project all the way to continuous, but pro- cesses often do need to change one category or more among those listed in Figure 4.5.
Most organizations should position themselves on the diagonal of the matrix. This means that a low-volume product with high variety would be produced by a project or job shop, but a highly standardized product with high volume would be produced by an assembly-line or continuous process. The diagonal of the matrix represents a logical match between the product and the process.
The product-process matrix represents the strategic choices available to firms in both product and process dimensions. Often, strategy is represented as consisting only of prod- uct choice. But the process can provide a unique capability that helps the firm compete in the market. Thus, a position on the matrix represents a strategic combination of both product and process. This type of strategic position requires cross-functional cooperation between marketing and operations to ensure that both product and process choices have been considered. For example, if a firm typically produces standard beverages in high
FIGURE 4.5 Product-process matrix. Source: Adapted from Hayes, Robert H., and Steven C. Wheelwright. “Line Manufacturing Process and Product Life Cycles.” Harvard Business Review, January–February 1979, pp. 133–140.
Job Shop
Project
Unique, one-of-a-kind product
Low volume, low standardization
Low volume, multiple products
Higher volume, few major products
High volume, high standardization, commodity
Batch
Assembly Line
Continuous None
NoneBuilding
Printing
Heavy Equipment
Auto Assembly
Sugar Refinery
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66 Part Two Process Design
volume, moving into a new market that requires small batches in a wide variety of flavors may be at odds with its current production capabilities. The firm may need to invest in new equipment, alter existing equipment, or reconsider whether it is capable of competing in this new market.
A firm might be tempted to move down the diagonal ahead of its competitors and thus gain competitive advantage at lower cost. This can be a good idea if the customer is ready to accept a more standardized product. If the customer prefers more customization, the firm may be forced to move back up the diagonal to remain competitive.
All firms in any particular industry, however, do not occupy the same spot on the diagonal of the product-process matrix. Some firms may choose to stay in the upper left-hand corner of the matrix; others may move down the diagonal. One example of this behavior is the hand- held calculator business. Hewlett-Packard has chosen to stay with low-volume, high- variety, and high-priced calculators while the rest of the industry has moved down the diagonal toward highly standardized, high-volume, and low-priced calculators. The Hewlett-Packard calculators, which are suited to various specialized market niches such as accounting, survey- ing, and electrical engineering, can command high prices at relatively low volumes.
4.5 FOCUSED OPERATIONS
Often a company will have products that are produced in a variety of volumes and with vari- ous levels of standardization. When a company mixes all these products in the same factory, it can lead to disaster. Skinner, who originated the idea of the focused factory, tells the story of an electronic instrument company that made low-volume custom autopilot instruments and high-volume standard fuel gauges in the same plant.2 After years of losing money on the fuel gauges, management decided as a last resort to separate the fuel gauge production from the autopilot production by building a wall down the center of the plant. They also assigned separate quality control and materials management staff to each product as well as separate direct labor, supervision, and equipment. As a result of these changes, the fuel gauges became profitable in four months and the autopilots also improved their profitability.
The problem essentially resulted from two different sets of objectives being mixed in operations: one of low cost for the fuel gauges and one of superior product performance and innovation for the autopilot. The autopilot production needed more stringent requirements in quality, materials, and skills than did the fuel gauges. Before focus, the fuel gauge costs were inflated and efforts were not directed to each product separately. When their production processes were separated, and thus the specific production needs of each product were sepa- rated, each process could better respond to its particular customer and market requirements.
Services can also be focused. An example of a focused factory for services is Midwest Orthopedic Specialty Hospital near Milwaukee, Wisconsin, which specializes in providing medical treatments on bones and joints. Their specialists perform surgeries and provide nonsurgical treatments for problems ranging from arthritis to sports injuries. With their nar- rower range of services, they are a focused factory when compared with a general hospital, which provides more wide-ranging services. By narrowing the types of customers treated, the orthopedic hospital narrows its need for different types of rooms and the equipment needed to treat various illnesses. The needed range of employee skills is also more limited.
Lack of focus in manufacturing plants and service operations has resulted from attempt- ing to accomplish too many different goals with the same facility or operation. In some cases, product proliferation in the markets served by the company has led to incompatible
LO4.5 Describe the features of focused operations.
2 W. Skinner, “The Focused Factory,” Harvard Business Review (May–June 1974), pp. 113–21.
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products being produced together in the same facility. The solution may be to arrange each product as a plant-within-a-plant (PWP), which entails setting up a process for one product or product line separately from other processes within the same facility. This is done by physically separating product flow, using separate work- forces and equipment, and separate management and support staff. The result is two or more small plants within the larger plant, like the Skinner example earlier in this section. The firm may sacrifice some economies of scale but will do a better job of meeting market requirements and improving profitability.
A refrigeration company used the concept of focused operations by organizing two PWPs inside the same building. It separated
compressor production for high-volume, standardized, and mature products from compres- sor production for low-volume and customized products. The two PWPs used many of the same components and shared their shipping department, but separating their processes enabled both to improve their performance. In this case, one factory was divided into two separate focused factories.
Service operations also can be focused by assigning different types of service prod- ucts to different facilities. For example, in an insurance business selling both high-priced, service-intensive policies and low-priced, commodity-style policies, using the same set of workers to serve both could cause trouble. The high-priced policies might get too little ser- vice while the low-priced policies receive too much service. The solution to this problem is to separate the service for these policies into two different facilities or two different PWPs with separate workforces and appropriate expectations for each type of policy.
4.6 MASS CUSTOMIZATION
To this point, we have been discussing traditional forms of production processes. How- ever, with new technologies that enable flexible manufacturing, mass customization is now possible. Mass customization is a strategy to provide high volumes of custom products in lot sizes of one, that is, each production unit is unique. At first blush, mass customiza- tion (custom products and high volume) appears to be an oxymoron, two words that are incompatible, like jumbo shrimp or a deafening silence. But this dichotomy between mass production and customization can be overcome by using modern technologies, includ- ing computers, robotics, modular design, and the Internet. See the Operations Leader box regarding Nike’s mass customized shoes.
Traditional mass production is built on economies of scale by means of a high-volume standardized product with few options. With economies of scale, the more production the lower the average unit cost. By contrast, mass customization depends on economies of scope—that is, a high variety of products from a single process. Economies of scope also reduces the average unit cost due to production of many products by the same process. Consequently, mass customization comes from a different economic basis, a common pro- cess rather than a common product.
Customization refers to making a different product for each customer with the cost of this usually being high. But mass customization is providing customized products at approximately the same cost as mass production. This is a stringent requirement and means that some products cannot be mass customized because the cost would be too high.
One of the early examples of mass customization is Paris Miki, a global retailer of standard and mass customized eyeglasses. The mass customization process begins with
LO4.6 Discuss the uses of mass customization and 3D printing.
Honeywell uses focused factories to compete by using several PWPs within one building. ©Spencer Platt/Getty Images
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68 Part Two Process Design
design of the eyewear by taking a digital photo of the customer and recommending a style of lenses that fits the customer’s face. An optometrist then adjusts the lenses to fit the cus- tomer’s preference. Finally, the customer selects options for nose bridges, hinges, and arms for the frame. The customer receives a photo of the proposed eyewear. Finally, a technician makes the lenses and frames at the store within one hour.
There are three forms of mass customization:
1. Modular production and assemble-to-order (ATO). 2. Fast changeover (nearly zero setup time between orders). 3. Postponement of options.
Modular production can provide a variety of options by using an assemble-to-order process. For example, when Dell receives a computer order, the company assembles stan- dard modules or components rapidly to fulfill the customer’s order. The order is then shipped and the customer receives it in a few days. But this requires modular design, as well as modular production. Dell also uses the same process to make standard computers for stock and shipment to retail stores.
Fast changeover is the form of mass customization used by Paris Miki for its glasses, where moving from one customer order to the next is very quick, with little or no setup between them. In this case, it is critical that each order is uniquely identified by a bar code, or other identifier, that specifies the customer’s options. It is also essential to have nearly zero changeover time on equipment so that a lot size of a single unit can be produced economically.
Postponement is used to defer a portion of the production until the point of delivery. For example, customized T-shirt shops can put a unique design on a T-shirt at the point of purchase. Hewlett-Packard printers receive their final configuration for various volt- ages and power supplies at U.S. or overseas warehouses before delivery. Postponement makes it possible to ship standard units anywhere in the world and customize them at the last minute.
From a manufacturing point of view, mass customization has changed the dynamics of the product-process matrix. Flexible automation makes it possible to make small lot sizes along with large lot sizes without a great cost penalty. Thus, with mass customiza- tion a firm can operate over a wider range of product choices without major changes to its
Shoes with a customized “fit” are significantly more elusive. While there are firms offering custom-fitted shoes, they sell at prices reflecting the significant work to individually size the shoe, most likely performed in a job shop. These shoes are cus- tom, but not mass customized.
Mass customization gives custom- ers many options, as well as the enjoyment of designing and using a product with their own personal stamp on it.
Nike and Nike-owned Converse, among other athletic shoe brands, offer customized shoes that can be ordered online for a reasonable price and delivered within a few weeks. Customers can select from numerous fabric or leather colors and patterns on various pieces of the shoe, as well as the colors of laces, stitching, and soles. These shoes, with their many customizable options, are an example of successful mass customization.
Nike Does It
OPERATIONS LEADER
obsession.24k/Stockimo/Alamy Stock Photo
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process. This amounts to a wider horizontal operating position on the matrix.
There are limits to mass customization, too. As some early mass customizers discontinue their cus- tomized products, there is disagreement on whether mass customization is a viable strategy for most firms. For example, automobile producers have struggled to make mass customization a reality. While they have successfully modularized the design of their cars and reduced changeover times, they have been less suc- cessful in linking customer preferences to the produc- tion process. In most states, manufacturers cannot sell directly to customers, and so the factory must com- municate with customers via the dealership network. Also, customers like to choose the color of the car, but painting occurs early in the production process. Customers like getting a new car right from the dealer
lot and not waiting a few weeks for the car to be made and shipped to them. These issues illustrate the significant challenges to successful mass customization.
Cross-functional integration is a key enabler of mass customization. Modularity and other forms of mass customization create an increased need for information exchange and cooperation among R&D, manufacturing, and marketing functions. Most new practices that involve both cross-functional work and new technologies are successful only in certain situations and conditions.
4.7 3D PRINTING AND ADDITIVE MANUFACTURING
3D printing is rapidly growing as a production technology. Also called additive manufacturing, this technology deposits successive layers of plastic, metal, or ceramic material to build a 3-dimensional solid object. An inkjet type of printer sprays the mate- rial on thin layers until the product is built up to its normal size. It can make complex shapes with holes, interior spaces, irregular contours, or other difficult dimensions. Prior to 3D printing these objects would have been machined from metal or made from expen- sive plastic injection molds. Regarding process type, additive manufacturing fits as a job shop in the product-process matrix.
3D printing has applications in a variety of fields including medical implants, aero- space, apparel, architectural display models, prototypes, and art objects to name only a few. Spare parts are another application since they can be made at the point of use rather than carried in inventory.
In medical science, 3D printing is playing a major role in the industry shift toward per- sonalized medicine. Dental implants are made to fit a particular patient. Orthopedists are testing designs and materials for printing customized joints for joint replacement surgeries. Ophthalmologists are 3D printing semiconductor polymer materials that they use to cre- ate “bionic” eyes for blind patients. And transplant specialists are even developing options to print human cells into entire organs, such as hearts and kidneys, for patients whose own need replacement.
In additive manufacturing the product design is transmitted via a digital 3D model from the design department to the 3D printer. As a result the technology can be used for
Mass customization is not for everyone. Automobile makers have struggled to mass-customize cars. ©Monty Rakusen/Getty Images
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70 Part Two Process Design
distributed manufacturing, as designs can be transmitted to remote locations and produced there instead of shipping the parts or products long distances.
Additive manufacturing is in its infancy. Rather than replacing traditional manufac- turing it will probably complement it in specific situations. The ability to transmit a design around the globe and make it in many different countries is appealing. The price of 3D printers has been dramatically reduced to less than $1000 for the most basic machine to hundreds of thousands for more advanced equipment.
Already, UPS is experimenting with 3D printing. They have purchased 100 indus- trial grade 3D printers for their Louisville, Kentucky, air hub to make everything from airplane parts to iPhone parts. Since 3D printing can shorten supply chains and reduce inventory, UPS wants to understand whether to treat 3D printing as a threat or a service opportunity. FedEx and Amazon have their own studies under way. UPS also has 3D printers at some of its retail shops, where it can make products and prototypes directly from customer designs.
As the price of additive manufacturing is reduced it can support many low volume cus- tomized parts or products. Additive manufacturing will permit relocalization of produc- tion in both developed and developing countries. Countries and industries can build their additive manufacturing around digital technologies. This will result in shifts in investment, labor, and location of manufacturing.
4.8 ENVIRONMENTAL CONCERNS
More than any other area of the firm, operations affects the natural environment. From the selection of inputs into the transformation process to the process outputs and by- products, decisions about the production process can have a significant environmental impact. With increasing regulation and consumer scrutiny, firms are continuously considering how to meet the demands of these stakeholders.
When firms are making process selection decisions, they must consider the environmen- tal impact. We can think about three areas of decisions that affect environmental impact.
First, there are technologies for pollution prevention. These structural investments reduce or eliminate pollutants from the production process. Process choice decisions, for example, using solar power versus coal-based power, determine the types of pollution out- put the process will create. Pollution prevention investments might include designing the
LO4.7 Contrast pollution prevention, pollution control, and pollution practices.
3D printer and printed objects cookelma/Getty Images; Maruna Skoropadska/123RF
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process to waste fewer raw materials, redesigning products or processes to reduce pol- lutants, or investing in equipment that requires less energy input. These are instances of preventing pollution from occurring.
Second, pollution control technologies are also structural investments. They differ from pollution prevention technologies in that they are used to treat or dispose of pollut- ants and harmful by-products that are outputs from the process. These technologies most commonly are added to existing processes that were designed and purchased in the past, perhaps when firms were less concerned. Pollution control extends an existing process by adding another step to deal with the waste by-products from the process.
The third category of process decisions related to environmental impact is pollution practices that affect the way processes are used. Such practices include retraining workers to use the existing process in a new manner and increasing cross-functional coordination to seek creative and innovation improvements in environmental impact. These practices also include monitoring and reporting systems related to the way processes operate. Other practices may involve changes in the supply chain, for example, selecting new suppliers who certify their materials are obtained using sustainable methods.
Many processes have been improved greatly over the years to lessen their impact on the environment. From changes in process inputs—for example, using consumer waste paper rather than trees to manufacture new paper—to innovative use of used materials—for example, making park benches out of recycled plastic bottles—operations plays a major role in managing environmental issues.
Examples of firms employing these process decisions are abundant. Shipping giant Maersk is pursuing a zero emissions goal, General Mills uses significant water saving strategies, and Toyota has a net positive impact plan—environmental performance even beyond zero emissions. For more details see the sustainability link in the Learning Enrich- ment box at the end of this chapter.
Other environmental concerns related to process choice include the following:
1. Recycling outputs—finding uses for process by-products. Example: Public schools send their food waste to pig farms.
2. Recycled inputs—using materials from other processes as inputs into a process. Exam- ple: Andersen Windows uses wood shavings that are by-products of one process as input together with a thermoplastic polymer to form Fibrex, a composite material used to make window frames and other products.
3. Remanufacturing—restoring and reusing some product components in the production of new products. Example: Caterpillar salvages and reuses many parts in its industrial equipment.
4.9 CROSS-FUNCTIONAL DECISION MAKING
There are many cross-functional interactions in process selection decisions. Marketing has a large stake in process selection decisions due to their understanding of the needs and sizes of markets. Process choices require large capital investments and thus make it dif- ficult to change the process quickly. In many cases, the markets the firm faces may be changing faster than the firm can recover the capital investment from process choices. Thus, marketing should work closely with operations in these decisions to ensure that both current and future market demands can be met, along with environmental impacts.
The critical role of marketing in estimating and managing future demand is apparent. Although forecasting is always an inexact science, some scenario planning should be done
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72 Part Two Process Design
to estimate the appropriate product and process response for different levels of demand. This will make it possible to manage the risk inherent in process choices and the associated capital investment. Marketing should also be aware of the process choice implications by managing demand to support the process choices that are made.
Finance has a key role in process selection decisions because of the capital investment required. Process selection choices should be subjected to standard cash-flow and present value analysis. This will ensure that any contemplated process choices will provide the required returns on capital at an acceptable risk. Finance will also be required to raise the capital once the process selection decision is made and to provide capital for future invest- ments as the product, process, and environmental challenges evolve over time.
The human resources function plays a key role in providing the human capital that is consistent with the process selection choices. Different processes require different labor from unskilled to highly skilled and different labor specialties. The human resources func- tion must hire, train, and guide management of the workforce so that it is coordinated with the process choices made by operations.
Information systems and accounting professionals should be aware that different processes have different performance measures and different data requirements. The information and accounting system designed for an MTO process will not work in an MTS operation; a job shop information system will not work in an assembly-line environment, since the infor- mation used for scheduling and inventory control depends on the type of process selected. Because large investments are required in hardware and software, information systems and accounting decisions must be closely coordinated with process selection choices.
We have shown that process selection choices affect all parts of the firm. They are strategic decisions that determine the future capabilities of the firm and thus involve all functional areas along with general management. With proper cross-functional coordina- tion, the processes selected can offer competitive advantage to the firm and will be sup- ported by all functions.
4.10 KEY POINTS AND TERMS
This chapter has emphasized how process design and selection can meet the strategic needs of the business. These key points have been made in the chapter:
∙ There are five types of processes: continuous, assembly line, batch, job shop, and proj- ect. The continuous and assembly-line processes are suited to high-volume standard products that are produced at low cost with limited flexibility. The batch and job shop processes are suited to low- to moderate-volume products that are customized or pro- duced in a high variety. The disadvantage of batch processes is the jumbled flow, which reduces throughput and efficiency. The project process is best for unique or creative products that are made one at a time. It requires intensive planning and scheduling and generally results in costly products or services.
∙ The second dimension of process is the type of order fulfillment: make-to-stock, make- to-order, or the hybrid assemble-to-order. With MTS, the replenishment cycle for inven- tory is separate from the customer order cycle. In contrast, the MTO process is set in motion by customer orders and geared to delivery performance. The MTS process provides standard products, whereas the MTO process is suited to custom orders. The ATO process makes subassemblies in advance for inventory and assembles them into a final product when ordered by the customer.
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∙ The order penetration point determines the point at which the customer order enters the production process. This is related to whether the process is designed to be MTS, ATO, or MTO.
∙ The combination of product flow and type of order fulfillment provides six types of processes. Selection from among these six requires consideration of market conditions, capital requirements, labor, and technology. Taking into account these factors, the pro- cess selection decision is always strategic and cross-functional in nature.
∙ The product-process matrix provides a dynamic view of the process selection decision by considering the life cycle of both products and processes. Strategy is defined by a position on the matrix for the firm’s product and process. The matrix helps provide coordination between marketing decisions about product and operations decisions con- cerning the process.
∙ Focused operations are used to separate products and processes that have differ- ent requirements in terms of the production process or the markets served. Each type of process or product family should be assigned to a different facility or plant-within-a-plant.
∙ Mass customization is the ability to make a customized product at approximately the same cost as a mass-produced product. This can be done for some products by using flexible automation, robotics, modular design, and information systems. There are three types of mass customization: modular production/assemble-to-order, fast changeover, and postponement.
∙ 3D printing and additive manufacturing can rapidly produce prototypes or unique cus- tom products from a 3D digital design. Rather than replace traditional manufacturing it will complement it. Product designs can be transmitted and products can be printed where they are needed.
∙ Environmental concerns are a major challenge related to process design. When mak- ing decisions about processes, firms must consider whether they will develop struc- tural processes to prevent or control pollution or use pollution practices to manage these matters. Process decisions must account for plans to recycle and remanufacture products.
∙ Process selection decisions are highly cross-functional in nature because they affect human resources, capital, information systems, and the ability of the firm to deliver products to the market. Therefore, all functions should be knowledgeable about process choices and the impact of process selection on their particular functional area and the environment.
Key Terms Continuous process 55 Assembly line 55 Batch 57 General-purpose
equipment 57 Jumbled flow 57 Process layout 57 Product layout 58 Job shop 58 Project 58 Throughput ratio 58
Economies of scale 67 Economies of scope 67 Modular production 68 Fast changeover 68 Postponement 68 3D printing 69 Additive manufacturing 69 Pollution prevention 70 Pollution control 71 Pollution practices 71
Make-to-stock 60 Make-to-order 60 Lead time 60 Back order 60 Service level 60 Assemble-to-order 61 Order penetration point 63 Product-process matrix 65 Focused factory 66 Plant-within-a-plant 67 Mass customization 67
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74 Part Two Process Design
LEARNING ENRICHMENT (for self-study or instructor assignments)
Jelly Belly Factory Tour Video https://youtu.be/tSPi2qS4hsQ 5:00
Kroger Bakery Tour Video https://youtu.be/uhBS02j73wk 2:30
Chrysler Virtual Reality Video https://youtu.be/lhNSEIkcpvM 1:44
Project to Build the Icelandic Super Dam Video https://youtu.be/anpbr4mms0E 13:48
Make-to-Stock versus Make-to-Order Video https://youtu.be/k_Pk0h-vxDU 1:25
Factory Home Construction Video https://youtu.be/LDU3s9Kf0HY 4:35
Mass Customization Video https://youtu.be/lxqJdoY5Wfw 4:28
Zero Emissions Factory Video https://youtu.be/0gg7uLln0CU 1:53
Discussion Questions 1. Classify the following types of processes as continuous,
assembly line, batch, job shop, or project: a. Doctor’s office b. Automatic car wash c. College curriculum d. Studying for an exam e. Registration for classes f. Electric utility 2. Why are assembly-line processes usually so much more
efficient but less flexible than batch processes? Give three reasons.
3. The rate of productivity improvement in the service industries has been much lower than in manufacturing. Can this be attributed to process selection decisions? What are the challenges involved in using more efficient processes in service industries?
4. Several industries—including those that produce furniture, houses, sailboats, and fashion clothing— have progressed very little down the diagonal of the product-process matrix toward more standardized and efficient. Why do you think this is so?
5. Compare an expensive restaurant, fast-food restaurant, and cafeteria in terms of process characteristics, such as product type, labor, capital, and operations objectives.
6. A company is in the business of making souvenir spoons to customer order. The customers select the size of the spoons and may specify the design to be embossed on them. One or more spoons may be ordered. The company is considering going into the make-to-stock spoon business for souvenir spoons and everyday tableware as well. What will it have to do differently in terms of planning production? How is the business likely to change?
7. What are the strategies of the following organizations? Is the strategy defined in terms of product or process or both?
a. McDonald’s b. AT&T Inc. c. General Motors d. Harvard Business School 8. Suppose that a firm is considering moving from a
batch process to an assembly-line process to better
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Chapter 4 Process Selection 75
meet evolving market needs. What concerns might the following functions have about this proposed process change: marketing, finance, human resources, account- ing, and information systems?
9. Give an example of mass customization not discussed in the chapter.
10. What techniques or approaches can be used to achieve mass customization in practice?
11. Search the Internet to find applications of 3D printing. What industries and what product examples do you find?
12. What is the difference between economies of scale and economies of scope? How do firms consider these when investing in processes?
13. What are some of the classic signs of an unfocused operation?
14. What are the pros and cons of organizing a plant- within-a-plant?
15. Why should operations be concerned with environmen- tal issues?
16. What are the main ways in which processes are managed to accommodate environmental goals?
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Service Process Design
The service economy accounts for more than 80 percent of jobs in the U.S. and in most industrialized economies in Europe and Asia today. Yet service production often receives little emphasis in many business and operations management courses. Increased empha- sis on service process design is needed to reflect the importance of services in modern economies.
Unlike manufacturing processes, we see service processes every day. As customers, we participate in the process and immediately know whether we are receiving good or bad ser- vice. Unfortunately, world-class service is rare. For example, was your most recent retail
5 C H A P T E R
After reading this chapter, you should be able to:LEARNING OBJECTIVES
LO5.1 Differentiate the characteristics of a service organization from a manufacturing organization.
LO5.2 Explain the elements of a service-product bundle.
LO5.3 Organize a variety of service offerings into the service delivery system matrix.
LO5.4 Describe the effect on the service delivery system of customer contact.
LO5.5 Explain service recovery and service guarantees.
LO5.6 Evaluate the role of technology in service management.
LO5.7 Appraise how globalization has affected services.
LO5.8 Define the attributes of the service-profit chain.
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service pleasant? Do you enjoy waiting in the doctor’s office? And what do you think of most airline service?
Most business graduates will be employed in service industries and work closely with operations and supply chain professionals. It is important to learn about service since it is highly relevant to all students, managers, and consumers.
Services are delivered by a wide variety of organizations—businesses selling services to consumers (restaurants, appliance repair) and to other businesses (consulting, accounting), non-profit services (health care, education), and government services (licensing, police protection). The operations function in these organizations varies widely in the resources used to produce these services, but there are common elements that allow us to study the processes used in service organizations. For an example of world-class service, see the Operations Leader box on Fort Collins, Colorado.
What can be done to improve services? Service process design is an essential ingredi- ent of better service delivery. We take the ideas of process selection and extend them to
Fort Collins has an improvement approach built around 16 processes that advance the goals of the city. It uses public engagement every two years to set the Mission, Vision, and Values (MVV). This is fol- lowed by identifying measurable outcomes and financial plans.
The city adopts its financial plans based on the Bud- geting for Outcomes (BCO) process that involves city staff members at all levels and citizens to discuss priori- ties that support the MVV.
Source: https://www.nist.gov/baldrige/city-fort-collins, 2019.
The city of Fort Collins, Colorado, is a community of 160,000 people in the front range of the Rocky Moun- tains, and it was a winner of a Malcolm Baldrige National Quality Award in 2017. The city has 2400 employees and 2200 volunteers. Its largest employers are Colorado State University, Hewlett Packard, Poudre Valley Health System, Poudre School District, Eastman Kodak, and Avago Technologies.
The city has excellent living conditions, ranking in the top 10 percent of cities nationally on the best place to live, best place to work, quality of culture, air quality, and visual attractiveness.
Fort Collins is financially sound, with a credit rating of Aaa by Moody’s—a rating maintained by only 4 percent of governments. It has a positive ratio of revenue to bud- get, low debt and increasing tax revenues. The city’s tax rates are among the lowest in Colorado.
Fort Collins is a national leader for environmental goals. Community energy usage decreased by 12 percent annually for the past three years, despite a population growth of 7 percent.
Fort Collins has the wide participation of citizens with citizen involvement on 27 advisory boards and commis- sions. Senior leaders use a “co-creation model” to work collaboratively with residents and businesses on solu- tions to urban challenges.
Information is widely available to citizens online. Online sites provide government transparency and accountabil- ity including the Community Dashboard and Scorecard of City’s performance.
City of Fort Collins
OPERATIONS LEADER
Source: City of Fort Collins
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78 Part Two Process Design
services. We expand the discussion into the domains of service product offerings, ser- vice system designs, globalization of services, service guarantees, and the important role played by employees and technology in service organizations.
5.1 DEFINING SERVICE
Most definitions of service stress the intangibility of the offering. Services are indeed intangible; that is, their processes create value for customers by performing transforma- tions that do not result in a physical entity (product). However, services can be difficult to define and cannot be easily quantified; for example, do hospital patients consume one ser- vice or multiple services as they receive tests and treatments—perhaps numerous in quan- tity? Rather than specify a formal definition of a service, it is important to consider the characteristics of such processes and their implications for both managers and customers.
Simultaneous production and consumption is a critical characteristic of services because it means that the customer may be in the production system while production takes place. The customer can introduce uncertainty into the process by placing demands on the service provider at the time of production. Also, the simultaneity of production and con- sumption means that most services cannot be stored; and the service must often be located near the customer so that the customer can travel to the service provider or vice versa. Exceptions are communications such as call centers, TV, Internet services, and electricity services that can be provided over long distances.
It is important to distinguish between service processes that are front office and those that are back office. Processes that require the presence of or interaction with the customer are front office service processes. The importance of simultaneous production and con- sumption therefore applies to front office services because the customer is participating in the process. For example, dental assistants and dentists provide front office services when interacting with customers. This interaction within the service process between providers and customers is critical to service process design but quite foreign to manufacturers.
Back office services, in contrast, can be performed separately from their consumption by the customer and, therefore, do not have to accommodate interaction with the customer. Most transaction processing in banks and testing patient samples in medical offices are back office processes that are not produced and consumed simultaneously but become valuable to the customer some time after the work is performed.
Because characteristics of services vary widely and the extent of interaction between the provider and the customer can also vary greatly, it is difficult to generalize about ser- vices. However, they are clearly different from products that are outputs of manufacturing. Some of the important contrasts between products and services are shown in Table 5.1.
LO5.1 Differentiate the characteristics of a service organization from a manufacturing organization.
TABLE 5.1 Differences Between a Product and a Service
A Product A Service
A product is tangible A service is intangible Production precedes consumption Production and consumption are simultaneous A product can be transported A service cannot be transported (though
producers can be)* A product can be stored in inventory A service cannot be stored Ownership is transferred at the time of purchase Ownership generally is not transferred A product can be resold No resale is possible A product can be demonstrated before purchase A service does not exist before purchase The seller produces The buyer can perform part of the production
*Exceptions are electricity and communications services.
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5.2 SERVICE-PRODUCT BUNDLE
Before the process to deliver a service is designed, the service-product bundle must be defined. The service-product bundle consists of three elements:
1. The service (explicit service). 2. The psychological benefits of the service (implicit service). 3. The physical goods (facilitating goods).
Most services come bundled with explicit services, implicit services, and facilitating goods. For example, when customers go to a fast-food restaurant, they receive both an explicit service, which they hope is fast and accurate, and a facilitating good, the food. In this case, the implicit service is how customers feel about the interaction and the pleasant- ness of the surroundings. Many services have fixed facilitating goods, such as the building and equipment that are used but not consumed during delivery.
In the case of a subway ride, the explicit service is the transportation from one place to another and includes customer perceptions and experiences, such as the sound, sight, smell, and feel of the ride. The implicit service is the sense of well-being and security that the subway ideally provides. Finally, the subway car is the facilitating good. It is important in the design of the service not to overemphasize one piece of the service-product bundle and neglect the other elements.
Most services require a more complex design than a subway ride. Consider the explicit services, implicit services, and facilitating goods for a luxury hotel. The explicit services include both basic services and amenities. These would be provided by the bellhop, con- cierge, restaurant, maid, room service, front desk, and Internet. The implicit service is a sense of safety, a caring staff, and the atmosphere of a luxury hotel. The facilitating goods are the hotel building, the food, the beds, the room, and physical surroundings.
Figure 5.1 provides more examples of a variety of service-product bundles. Notice that some bundles are mostly all service with few goods (e.g., consulting and haircuts) while the automobile industry provides mostly goods with only a little service. Here, we include the automobile as an example of a service-product bundle because the purchase of a new auto includes several service elements that customers recognize and pay for. The auto bun- dle includes not only the physical product but also the ability to test-drive and finance the product at the dealership in addition to the manufacturer warranty that covers the auto.
The combination of these service elements with the product makes up what we consider a service-product (or product-service!) bundle. One might also consider the maintenance and repair service offered by the dealer after the sale.
The task for the operations function, before deliver- ing any services to customers, is to design the service delivery system. That system includes all the processes that will be used to deliver services, including details such as the technology used in the process design, the types of employees needed, and even the appearance of the employees and facilities. While operations can con- trol both the explicit service and the facilitating goods, implicit services are obviously harder to control (and may vary greatly from one customer to another). There- fore, it is important that management use the means it
LO5.2 Explain the elements of a service-product bundle.
Luxury hotel guests expect a full service-product bundle. Jupiterimages/Getty Images
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80 Part Two Process Design
has available (e.g., technology or employees) to design the implicit services into the ser- vice delivery system.
An important point to emphasize is that the design of the service to be delivered and the design of the service delivery system are intertwined and, often, should be designed concurrently. Also, the delivery of a service is a simultaneous marketing and operations act that requires both the right visual cues and well-functioning processes. Therefore, cross- functional cooperation is essential to service design and delivery.
Like products, services have supply chains, although they may be less concerned with the flow of the physical product and more concerned with the flow of work, customer, and information. Services cannot be stored, but they do use inventory, and so they rely on product-based supply chains to provide that inventory. For example, a hospital patient requires service processes for explicit services (surgery, perhaps) and additionally the work flow of outsourced lab tests, information and financial flows from insurers, and coordination of work and information as the patient is discharged from the hospital to a rehabilitation center. Such a complex network of supply chain activities mirrors the activi- ties of product-based supply chains but usually includes both tangible product flows and intangible work and information flows.
5.3 SERVICE DELIVERY SYSTEM MATRIX
There are many ways to think about services, the options they offer customers, and the vari- ety of ways in which they can be delivered. Some services can be delivered in only one standardized way and every customer gets more or less the same service. Other services are highly customized to customer requests, and exactly the same service is virtually never repeated for another customer. The challenge for management is to design the right service process so that the service delivery system is matched to the requirements of its customers.
Both customer preferences and design requirements of the service delivery system are contained in the service delivery system matrix, which is shown in Figure 5.2. On the top of the matrix is the dimension of customer wants and needs, which captures the service package (or service-product bundle) customers are seeking. This dimension incorporates the uniqueness of demands from one customer to another, an indication of the uncertainty
LO5.3 Organize a variety of service offerings into the service delivery system matrix.
FIGURE 5.1 Comparison of various products and services packages. McGraw-Hill Education
Products Services
100% 75% 50% 25% 0% 25% 50% 75% 100%
Self-service groceries
Automobile
Installed carpeting
Fast-food restaurant
Gourmet restaurant Auto maintenance
Haircut
Consulting services
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and variation introduced into operations by individual customers. Customers with basi- cally the same wants and needs can be served by processes that are highly standardized and routinized, whereas customers with unique wants and needs must be served by processes that allow variety and high levels of customization.
The vertical side of the service delivery system matrix represents the operations service system and denotes the number of different pathways that service customers can take in the service process. This can vary from a single pathway or small number of path- ways to a virtually infinite number. A small number of pathways allows few options in how the service is delivered; however, an infinite number of pathways allows the service to be different each time it is delivered.
When both dimensions of the service delivery system matrix are considered, three types of services can be identified. Customer-routed services are those in which cus- tomers want a unique, highly customized experience. Customers have a great deal of
FIGURE 5.2 Service delivery system matrix. Source: Collier, D.A. and Meyer, S.M., A service positioning matrix, International Journal of Operations and Production Management, 18(12): 1223–44.
Customer Wants and Needs in the Service Package
Many process pathways. Jumbled flows, complex work with many exceptions.
Limited number of process pathways. Line flows, low work complexity.
Moderate number of process pathways. Flexible flows with some dominant paths, moderate work complexity.
Se rv
ic e
D el
iv er
y Sy
st em
D es
ig n
Highly customized with unique process sequence. Customer has great decision-making power.
Standard with options, using moderately repeatable sequence. Customer has some decision-making power.
Standardized with highly repeatable process sequence. Customer has low decision-making power.
Customer-routed Estate planning
Co-routed Stock brokerage
Provider-routed ATM
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82 Part Two Process Design
decision-making power to determine the components of the service as well as how and when and the sequence in which they are delivered. For these services, each customer wants a different set of experiences, and the service process must allow a great deal of personal discretion and interaction with the customer. These services are carried out using highly flexible processes and may rely on highly trained workers to deliver the right set of experiences to match customer wants and needs. Personal trainers, Internet shopping, and museums are examples of customer-routed services. Customer-routed services are simi- lar to those delivered by job shops for manufacturing products, in terms of allowance for customization.
In the midranges of both customer wants and needs and service delivery system design, co-routed services offer customers a moderate number of choices, using moderately stan- dardized processes. Medical and stockbroker services fit in this category. A golf course is another example of a co-routed service in which management has designed the course to be played in a standardized sequence (from Hole 1 to Hole 18), but within the service delivery system customers have a reasonable degree of decision-making power in how they choose to play.
Finally, highly standardized services are delivered using a design for provider-routed services. These services are characterized by processes that allow few options during ser- vice delivery and are designed for customers whose needs are very similar to one another. Grocery store self-checkout is a service delivery system with a very limited number of pathways from which customers may choose. It provides a limited set of services, and there is little customer discretion in using it. Customers whose needs are not met by self-checkout must use employee-operated checkout stations. Eating at McDonald’s and getting a blood test are other examples. Provider-routed services are therefore similar in nature to a manu- facturing assembly-line process. We refer to them as provider-routed because the provider, either an individual or an organization, decides how a particular service will be carried out.
The service delivery system matrix is intended not only to classify the different types of services but also to indicate how the operations function task differs among services. For example, provider-routed services may require management attention to automation and capital investment, but customer-routed services may require more attention to manage- ment of human resources and flexible technology issues.
The service delivery system matrix suggests that service firms will generally be located on the diagonal, indicating alignment between the service package and the service process. Both the choice of which customer segments to serve (horizontal dimension) and decisions regarding design of the service delivery system (vertical dimension) are strate- gic in nature. Marketing, operations, and human resources functions must work closely to ensure that external opportunities and internal capabilities have been considered during strategic planning.
The major difference between the service delivery system matrix and the product- process matrix that guides the selection and design of manufacturing processes is that the design of the service delivery system generally does not vary with customer volume. In the product-process matrix, the volume and customization of the product offering are the major factors in determining the most appropriate production process. In contrast, services often are delivered using the same process whether they are produced in small or large volumes. For example, very similar processes are used for a medical service such as setting a broken leg regardless of whether the service is delivered at a large 2000-bed hospital, which has many such patients, or in a smaller 120-bed hospital. Similarly, fast-food res- taurants treat customers the same way regardless of the number of customers they serve and regardless of customer order size. To increase volume, fast-food restaurants simply open more locations, but the service process is the same. The degree of customization of
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a service, rather than volume, is the main characteris- tic that affects the design of the service process and the way the service is delivered.
Self-service by customers is also a consideration in service delivery system design. Customers may serve as labor at key points in a service process, such as bagging their own groceries, or they may complete an entire service process independently, as occurs when they fill their tanks at a self-service gas station. Self-service usually benefits the firm as customers provide “free” labor during service delivery. For self-service to be a successful component of service delivery system design firms must design their service processes carefully for both simplicity and customer satisfaction.
Self-service is possible for any of the types of ser- vices defined in the service delivery system matrix,
from simple standardized services to highly customized services. A key issue for opera- tions managers is designing self-service opportunities that customers are both willing and able to perform. While the relatively simple self-service offered at ATMs appeals to a wide range of customer segments, having to pull one’s retail selections from warehouse shelv- ing (e.g., at IKEA stores) may limit the appeal of the retail service for some segments. An understanding of the needs of a firm’s target customer segments must serve as a guide to the right service delivery system design.
5.4 CUSTOMER CONTACT
We now look at interactions between customers and service organizations in detail to understand how the extent of customer contact relates to service processes. With low- contact services, it is possible to separate a service into two portions: a service creation or production portion and a service consumption or delivery portion. By doing so, the cus- tomer can be removed from the service creation portion. Separating the customer from the service production portion allows for greater standardization of processes and therefore better efficiency. Examples of low-contact services are processing of online orders and ATM transactions. As indicated above, these services are usually designed using a provider-routed approach. See Figure 5.3, in which low-contact services are referred to as buffered core because these services are designed to be buffered or removed from interac- tions with the customer.
At the other end of the contact spectrum, high-contact services involve the customer during the production of the service. Examples are dentistry, haircutting, and consulting. In these services, the customer can introduce uncertainty into the process with a result- ing loss of efficiency. For example, a customer may impose unique requirements on the service provider, resulting in a need for more processing time. In this case, the service delivery system design typically will be customer-routed unless customization has been limited by the provider. These interactions are referred to as reactive in Figure 5.3 because the service delivery system must react to customer requests.
In the middle ground of customer contact, permeable systems have processes that are penetrated by customers in fairly restricted ways, usually via telephone or limited face-to- face contact. Here, limited interaction with customers allows some customer preferences to be met. But such accommodation is restricted to maintain process efficiency.
LO5.4 Describe the effect on the service delivery system of customer contact.
Grocery self-service is a provider-routed service. Syda Productions/Shutterstock
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84 Part Two Process Design
Operations managers must be concerned with the amount of customer contact because higher levels of customer contact can introduce variability into a process. Variability is a challenge for operations managers because it makes capacity planning more difficult and can result in waiting lines. Table 5.2 defines five types of customer-introduced variability. Service firms that try to accommodate all types of customer-introduced uncertainty may find that the cost of delivering the service begins to spiral out of control. Instead, they must learn to manage the uncertainty, either by using creative means to reduce it or by finding low-cost means of accommodating it.
A few examples provide insight into managing variability. Arrival variability results in empty restaurant seats at certain times of day and full seats and a waiting line at other times. Customer arrivals are somewhat random, but usually clustered around standard meal times. A reservation system can help to manage arrival variability by shifting some custom- ers to somewhat earlier and later than peak standard times. Thus, reservation systems can be effective for managing customer arrival uncertainty. Capability variability, on the other hand, is observed in hospital patients’ varying abilities to move about, feed themselves, and take care of their basic needs such as getting a drink or using the bathroom. Hospitals usu- ally hire low-wage staff to assist with these needs to keep costs low while reserving more expensive labor (like nurses) for tasks that require more extensive licensing.
FIGURE 5.3 Customer contact matrix. Source: Adapted from Jacobs, F.R. and Chase, R.B., Operations and Supply Chain Management, McGraw-Hill Education, 15th ed, 2017.
Clerical skills
Sales opportunity
Production efficiency
Paper handling
Office automation
Helping skills
Demand mgmt.
Routing methods
Verbal skills
Scripting calls
Computer databases
Diagnostic skills Client mix
Client/ worker teams
Trade skills
Capacity mgmt. Self- serve
Procedural skills Flow
control Electronic
aids
Worker Requirements
Innovations
Focus of Operations
High
Low
Low
High
Degree of customer/server contact
Buffered core (none)
Permeable system (some)
Reactive system (much)
Face-to-face total
customization
Face-to-face loose specs
Internet and on-site technology
Face-to-face tight specs
Phone contact
Mail contact
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The relationship between customer contact and process efficiency can be stated as follows:
Potential inefficiency = f (degree of customer contact)
The measure of the degree of customer contact is the amount of time it takes for the service to be produced, delivered, and consumed by the customer. As this time increases, the deliv- ery process is increasingly inefficient. High contact may be costly in terms of lost effi- ciency, but it may offer opportunities to increase sales to customers, resulting in increased revenue for the service firm, as shown in Figure 5.3. For example, consultants often have a high degree of contact with clients, and such interactions provide them with opportunities for additional consulting work and therefore additional revenue.
When possible, high-contact and low-contact portions of service delivery systems should be separated to create front office (high contact) and back office (low contact) pro- cesses. Front office operations require intensive customer interactions, whereas the back office can operate more efficiently away from the customer. The separation of high-contact and low-contact services is an application of the principle of focused operations.
There are several characteristics of high-contact and low-contact services:
∙ Low-contact services are used when face-to-face interaction is not required, for example, shipping operations or check processing in banks.
∙ Low-contact services should use employees with technical skills, efficient processing routines, and standardization processes. High-contact services require employees who are flexible, personable, and willing to work with the customer (the smile factor).
∙ Low-contact operations can work at average demand levels and smooth out the peaks and valleys in demand. Providers of high-contact service must respond imme- diately as demand occurs in peak situations.
∙ High-contact services generally require higher prices and more customization due to the variability that customers introduce into the service.
While customer contact is an important ingredient of service delivery system design, it is not the only consid- eration. Contact with customers becomes increasingly challenging to manage with increases in the total dura- tion of interactions and the richness of the information exchanged during interactions. The nature of uncer- tainty introduced by the customer is also of critical
• Arrival variability—uncertainty in when customers will arrive to consume a service. • Request variability—uncertainty in what customers will ask for in the service-product bundle. • Capability variability—uncertainty in the ability of customers to participate in a service. • Effort variability—uncertainty in the willingness of customers to perform appropriate actions. • Subjective-preference variability—uncertainty in the intangible preferences of customers in how
service is carried out.
TABLE 5.2 Types of Customer- Introduced Variability Source: F. Frei, “Breaking the Trade-off Between Efficiency and Service,” Harvard Business Review, November 2006, pp. 92–101.
Airline service is a high-contact service with some customer variability. Ryan McVay/Getty Images
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86 Part Two Process Design
importance. For example, contact can be high, but if the customer interface is standardized or the customer provides self-service, efficiency is still possible. In fast-food restaurants the degree of customer contact is relatively high, but the nature of the contact is highly controlled in contrast to a fine-dining restaurant, where there is more uncertainty in what the customer may request. Thus, high contact by itself is not always inefficient; it becomes inefficient when customers introduce uncertainty or do not provide self-service.
5.5 SERVICE RECOVERY AND GUARANTEES
Service recovery is an important element of service management when there is a service failure—in other words, when something goes wrong during the delivery of a service. Ser- vice recovery consists of the actions necessary to compensate for the failure and restore, if possible, the service requested by the customer. For example, when there is a power fail- ure, service recovery includes the time it takes for the electric company to restore power. In a restaurant, if the waiter spills soup on a customer’s lap, service recovery includes helping to dry the clothes with napkins, an apology, and perhaps an offer to dry-clean the clothes at the restaurant’s expense. Often when the service recovery is swift, properly performed and appropriate in the customer’s eyes, the customer accepts the service failure and recovery and is satisfied with the overall service experience. Because service failure from time to time is nearly inevitable, service firms must design recovery processes to ensure that such actions are taken consistently. See the Operations Leader box on UPS for an example of a satisfying service recovery.
LO5.5 Explain service recovery and service guarantees.
and speaker. She is passionate about helping businesses grow by leveraging social networks.
Source: Adapted from: “A Social Networker’s Story,” BusinessWeek, March 2, 2009, p. 30; www.tarahunt.com, 2019.
A customer who usually received packages at the office ordered a large storage unit and needed it delivered to her house. Tara Hunt, then an Intuit executive, called UPS to check on it and was told that during the holiday rush, some packages are not delivered until as late as 9 p.m.
Agitated, she posted a message on Twitter about waiting for UPS and that she could not walk her dog while she waited, not wanting to miss the delivery. Tony Hsieh, CEO of Zappos, was following her Tweets after having met her previously. He was having dinner with the UPS president and relayed her frustration to him. Five minutes later, the UPS executive called and connected her with an operations manager to arrange delivery for the following morning.
At 9 a.m. sharp, the doorbell rang. Not only was the package delivered, but the UPS employee brought flow- ers and chocolates, along with treats and toys for her dog! Ms. Hunt says she now goes out of her way to use UPS, and she bought shoes at Zappos the very next day.
Tara Hunt has since moved on to a successful career as a digital marketing professional, researcher, author,
UPS Service Recovery
OPERATIONS LEADER
roberto galan/123RF
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Many companies solidify their service recovery processes by offering service guaran- tees as a way to define the service and ensure its satisfactory delivery to the customer. A service guarantee is like a product guarantee, except customers cannot return a service if they do not like it. For example, if you do not like your haircut because it’s too short, you have to live with it until your hair grows out.
A service guarantee has two components: (a) a promise of what service will be deliv- ered and (b) what the payout or service recovery will be if the promise is not fulfilled. The value of the guarantee to the service firm offering it is that the promise defines exactly what service needs to be delivered correctly. The firm must design its processes and train its workers to meet the expected service every time it is delivered.
FedEx Corporation, for example, has a money-back service guarantee for its shipping services within the United States. Packages will be delivered by the published delivery time (or quoted time, as in the case of FedEx SameDay) or the service price will be refunded to the customer. This service guarantee defines exactly what the organization must achieve and what happens when a service failure occurs. Another example is Atlantic Fasteners, a distributor of hardware in Massachusetts, whose service guarantee for on-time delivery is: “We deliver defect-free in-stock fasteners on time as promised or we give you a $100 credit.” Atlantic Fasteners has an incredible 99.96 percent reliability and accuracy rating in meeting its service guarantee. Other companies may offer somewhat less-precise service guarantees. For example, hotels may give you a free night’s stay if you are not satisfied. A restaurant server may give you a free dessert or a free meal if you are not satisfied with the food. These service guarantees are not as precise in guiding operational activities as the FedEx or the Atlantic Fasteners service guarantees, but they are, nonetheless, better than not having a service guarantee at all.
The service guarantee is not an advertising gimmick or simply a way for customers to get their money back if they are not satisfied. It is an assurance that the service provider will perform as promised. And if a customer is not satisfied and requests the payout from the service guarantee, the service provider can use the request as feedback to understand both what customers expect from the service and how the service delivery system must be changed to better match customer expectations.
A carefully crafted service guarantee benefits both customers and the service provider. For the former, a service guarantee reduces the risk in purchasing the service. Customers know exactly what service they are buying, when a service is deemed to have failed, and how they will be compensated. For the latter, a service guarantee clarifies explicitly what is to be achieved by the service. Such clarification of intent helps guide the design of the service delivery system, specifies the extent of service recovery required upon service failure, and presents a clear vision to motivate employees to deliver high service quality. A service guarantee can, moreover, reward the service provider with loyal customers.
5.6 TECHNOLOGY FOR SERVICES
Technology in services takes many forms. First, there is the technology embedded in the service system itself through equipment and automation. Almost all services have been automated, at least to some extent, in industries from medicine to airlines to retail. See Table 5.3 for examples of automation in various industries.
Pushing automation forward for services is not the right design for all types of services. While the resulting service may be more efficient (more customers served for a lower per- customer cost), automation can change the nature of the service and reduce the number of selling opportunities. The market ultimately will determine how much automation is
LO 5.6 Evaluate the role of technology in service management.
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reasonable and how automation is used. For example, with fast food available everywhere, many customers still prefer traditional restaurants with high human touch, better food, and a larger variety of choices.
Some argue that managers should view employees, not automation, as the center of the service delivery system. They suggest that service companies do the following:
∙ Use automation to support front-line employees, not to monitor or replace them. ∙ Value investments in employees, for example, hiring a highly educated workforce. ∙ Make recruitment and training as important for front-line workers as for managers and
staff employees, and link compensation to performance for employees at every level.
This employee-focused approach emphasizes people as the center of service. It would be appropriate for some customized services that have co-routed or customer-routed service delivery systems.
Artificial intelligence is a second type of technology that is rapidly being implemented in services. Artificial intelligence (AI) is software and hardware that is programmed to exhibit aspects of human intelligence. AI mimics human cognitive functions such as prob- lem solving, learning, and creativity. Recently, AI has been providing services that imitate human service employees. Some of these applications are discussed here along with the potential for future use. AI promises to save human effort while reducing the costs of deliv- ering service. When advanced AI is used it may be difficult to tell the difference between a human service provider and an AI agent or AI bot (bot is short for web-enabled robot).
There are four levels of AI development:
∙ Routine: Repetitive tasks ∙ Analytical: Problem solving and learning ∙ Intuitive: Think creatively ∙ Empathetic: Respond emotionally
These four levels are generally hierarchical from routine at the lowest level of AI to empathetic at the highest level.
Routine AI deals with repetitive tasks in service that can be provided with a minimal degree of learning or adaptation. It can rely on observations to act and react
Artificial Intelligence
Technology enables service delivery. Ariel Skelley/Blend Images/Getty Images
TABLE 5.3 Examples of Technologies Supporting Service Delivery
Service Examples of Technology
Medicine Intensive care unit monitoring systems, MRI scanners, electronic medical records, automated diagnostic testing, pacemakers, robotic surgery, telemedicine
Telecommunications Cellular phones, TV, video conferencing, satellite communications, e-mail, Internet, cloud-based storage and computing
Retail Point-of-sale scanners, inventory control systems, radio-frequency identification (RFID), electronic payment systems, self-service checkout
Education Digital libraries, Internet, interactive learning Legal Digital searches, databases for evidence Hotels Fast checkout, keycard security, reservations systems, heating/
ventilation controls, Internet access Airlines Air traffic control system, electronic cockpits, reservation systems,
in-flight technology services
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repetitively as it performs simple, standardized, repetitive, and transactional service tasks. An example is the service provided by a vacuum cleaner robot that replaces the human effort in vacuuming a room or the entire house. The vacuum cleaner follows an embedded program but can make adjustments for obstacles and obstructions. Other examples of rou- tine AI are health care diagnosis assistance to physicians by pre-programmed scripts, AI to flag bank checks outside the norm, and AI to prevent fraud in credit cards. The advantage of routine AI relative to humans is the consistency of service that can be provided by AI agents, although the services are limited to routine types.
A common use of routine AI is customer phone or chat service provided by a con- versational bot that answers. According to the latest figures from IBM, companies spend $1.3 trillion on customer service calls each year.1 They estimate that up to 80 percent of the 265 billion calls or chats have routine questions that can be answered by a conversa- tional bot; the remainder could be handled by customer service agents. This leaves agents available to handle delicate questions and complex calls increasing customer satisfaction and lowering agent workload. These conversational bots will become even more useful in the future as they become more sophisticated. But some customers may prefer talking to a human, so this option must always be available. As a matter of fact, some companies may provide humans answering the phones as part of their marketing and service strategy, even though it is more expensive.
Analytical AI systems learn and adapt systematically based on data. They use rule- based logic to learn using information processing and logical reasoning. Employees who use Analytical AI software require technical training and skills on data and analysis. Big data analytics utilizing very large data sets is part of this type of AI. Often, but not always, a combination of software and human interaction is required for analytical AI. For example, H&R block uses the IBM Watson computer to assist tax preparers. The computer system combs through 74,000 pages of the U.S. tax code along with thousands of yearly tax law changes. By combining the power of tax professionals and Watson’s technology, improved service to the customer is provided uncovering every deduction the customer is entitled to receive. Another example of Analytical AI is IBM’s Deep Blue chess player. In this case, the software analyzes all of the possibilities for a given chess move and provides a sugges- tion for the best move. Deep Blue has beaten some of the best chess masters in the world.
Big data analytics AI is widely used in sports in conjunction with analysts to provide support for decision making including recruiting players for specific positions and deci- sions about the best strategies in particular games. Practically every professional sport has data analytics software and employees who know how to use it. This type of AI is appropriately used when data analysis leads to learning as part of the service provided. Ultimately, analytical AI can be applied to services such as accounting, financial analysis, and engineering.
Intuitive AI learns and adapts intuitively based on understanding. Neural networks are used to provide deep learning. This type of AI is useful for complex, chaotic, and idio- syncratic tasks that cannot be easily completed. Using neural networks, the software can learn things it has not been taught before based on intuition and experience, the same way that humans learn. It must learn based on the context and can extract ideas from similar situations.
Intuitive AI can support professionals who engage in creative thinking or problem solving such as doctors, lawyers, travel agents, and consultants who offer services to customers. The Associated Press reported that it is using AI bots to cover minor league
1 https://www.business.com/articles/future-of-conversation-bots/.
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baseball games. Automatically generated reports are being offered based on statistics from 142 games in 13 leagues. It took a year for baseball experts to monitor the reports for accuracy and intuition being produced by the AI agent. After one year, the AI agents were used to actually report on the games with confidence they were as accurate and intuitive as human reporters.
Empathetic AI is useful in decision making that requires emotions. The AI agent can learn to adapt empathetically based on experience. It is important for high touch service that includes highly interactive social and emotional communications. One example is the humanoid robot Sophia that interacts with a cli- ent using multiple visual and hearing sensors to act as a human would in a conversation including blink- ing eyes, hand and arm motions, and moving lips for speaking. It is reminiscent of C-3PO in Star Wars. Sophia is a platform for general intelligence R&D
intended to evolve to scalable commercial production. Another empathetic bot, named Pepper, can recognize the principal human emotions and adapt its behavior to the mood of the client. To date more than 140 SoftBank Mobile stores in Japan are using Pepper as a new way of welcoming, informing, and amusing their customers. Pleasant and likeable, Pepper represents a humanoid companion or friendly service representative. Pepper can recognize your face, speak, hear you, and move around. Pepper behaves as if it likes to interact with customers.
Artificial intelligence will have amazing advances and applications in the future. To replace or assist humans the customer should believe the response is from a human ser- vice provider. While AI will provide some services more efficiently at an acceptable level of interaction, other services will remain to be provided by humans. Two strategic ques- tions for all service operations are: (1) In what situations will customers accept service by AI agents, and (2) what should be the nature of the interaction between human service providers and AI agents? These questions need to be answered by management in using AI software to provide service.
5.7 GLOBALIZATION OF SERVICES
We turn to the outsourcing and offshoring of services. Outsourcing of services is placing services outside the firm that were previously done inside the firm, such as HR and account- ing. Offshoring, in contrast, is the export of services to other countries. Both of these prac- tices have been enabled largely by advances in information technology and communications. As a result, seamless delivery of services can be provided globally that are transparent to the user. Services include call centers, finance and accounting, IT infrastructure, HR, medical services, and knowledge services such as product support, R&D, and analytics.
Offshoring of services presents many of the same opportunities and challenges as offshoring manufacturing. Potential upsides include lower costs and focusing on core competencies; downsides include coordination costs and loss of direct control. One dif- ference from manufacturing is due to the intangibility of services. While physical prod- ucts can be inspected upon receipt from a supplier, services can be more challenging to inspect and therefore require additional mechanisms to ensure that service performance
LO 5.7 Appraise how globalization has affected services.
Pepper interacts with a customer. VTT Studio/Shutterstock
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standards are met. One possibility is to request customer feedback immediately after the service is performed.
Service offshoring requires attention to both people and processes. The expectations of the target customers are a major factor in selecting processes for offshoring. Management must be sure to link customer wants and needs (refer back to the service delivery system matrix) with the appropriate process. Understanding the desires of the customers will lead to a set of strate- gically linked decisions on the appropriate mix of processes, technology, and service workers.
Services should be offshored with both the advantages and disadvantages in mind. If a service is offshored, it should be done in partnership with the supplier to ensure quality rather than merely seeking the lowest cost. Offshoring requires an expectation that the sup- plier can continue to fulfill the service requirements and provide the quality required, not only the lower cost. It is a lasting relationship that is desired.
Shifting cost and the quality effects due to international borders can be a concern. What appears to be a significant cost advantage could disappear because of trade differences that occur. For example, wages are bound to rise in low-cost countries over time. Also, the cost advantages can be drastically overestimated owing to the need to monitor and support overseas suppliers, or the quality of service can suffer. Thus careful evaluation is neces- sary; otherwise the firm may find itself reshoring services due to cost or quality concerns.
Economists have engaged in heated debates over offshoring, which often overlap with free trade arguments. Theoretically, free trade benefits both the origin and destination country. The origin country benefits from lower cost imports and the destination coun- try benefits from jobs. On the other hand, offshoring has sparked controversy in the ori- gin country due to job losses and wage erosion. Economists who are against offshoring argue that currency manipulation, unfair trade regulations, and tariffs benefit the destina- tion country to the disadvantage of the origin country. Therefore, managers must consider not only the cost advantages of offshoring, but the possible backlash and negative social effects of job loss in the origin country, when trade is not actually free.
There are two types of offshoring for services. Some services such as call centers and accounting have been commoditized and are routinely outsourced. Many of them have been moved to low-cost countries such as India and the Philippines. These are transaction- based services where prices are driven down leading to outsourcing in an offshore location.
The second type of offshoring is professional services that have been outsourced and moved offshore. One example is lawyers in India that were hired by the Tusker Group in Austin, Texas, to review 400,000 documents for $25 per hour. Similar work could cost
more than $125 per hour in the United States. A second example is reading scans by radiologists. When radi- ologists at Altoona Hospital in Altoona, Pennsylvania, could not keep up with reading scans, they hired a group based in Bangalore, India. The Indian radiologists were trained in the U.S. and costs were substantially lower with no loss in quality, plus scans could be read at night due to time differences and be ready the next morning in the U.S.
Globalization of services is ongoing. Many of the same issues as manufacturing outsourcing must be considered but many services, outside of those already mentioned, are inherently immune to offshoring and must be produced in the country of origin. When off- shoring services, both the advantages and disadvan- tages must be considered.
Legal work is being outsourced to India. Mustafa Quarishi/AP Images
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5.8 SERVICE PROFITABILITY AND EMPLOYEES
Service profitability has been linked to focusing on customers and employees as para- mount in importance. Managers should focus in particular on the front-line employees who deliver the service, the technology that supports them, training, and customer satisfaction. When these factors are linked and improved, profits will be improved according to the service-profit chain shown in Figure 5.4.
Customer loyalty is the key to revenue growth and profitability. Although focusing on increasing market share is sometimes touted as the key to profitability, customer loyalty is an additional factor of equal or greater importance. Even a 5 percent increase in loyal customers can increase profits in many industries by 25 to 85 percent.
The service-profit chain shows that customer loyalty is driven by satisfied customers. Nat- urally, if customers are satisfied, they will likely provide repeat business and also tell others about their positive experiences. Customers who report very high levels of satisfaction affect profitability through their loyalty much more than do customers who are merely satisfied.
External service value leads directly to satisfied customers. External service value is the benefit customers receive minus their cost incurred in obtaining the service, which includes not only the price but also the costs of finding the service, traveling to the service location, waiting for the service, and correcting any service problems encountered. For example, Pro- gressive Corporation, an insurance company, has created CAT (catastrophe) teams that fly to the scene of major accidents to quickly provide support services such as transportation, housing, and claims handling. By avoiding legal costs and putting money quickly into the hands of the insured parties, the CAT team more than makes up for the costs of travel and maintaining the team. The CAT team provides value to customers, helping to explain why Progressive has one of the highest margins in the property-and-casualty insurance industry.
Next, we see the important role that front-line, customer-facing employees play in the service-profit chain. Employee productivity, retention, and satisfaction work together to create high service value to customers. Productive employees lower the costs of operations and ensure satisfied customers when supported by management and appropriate
LO5.8 Define the attributes of the service-profit chain.
FIGURE 5.4 The service-profit chain. Source: Heskett, J.L., et al., “Putting the Service-Profit Chain to Work,” Harvard Business Review, March–April 1994, p. 166.
Operating Strategy and Service Delivery System
Employee satisfaction
Employee productivity
External service value
Employee retention
Internal service quality
Customer satisfaction
Customer loyalty
Profitability
Revenue growth
Job design Employee selection and development Employee rewards and recognition Technology for service
Service concept: Results for customers
Retention Repeat business Referral
Service designed and delivered to meet targeted customers’ needs
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technology and systems. For example, Southwest Airlines has the most productive employ- ees in the airline industry. As a result of short routes, fast turnaround, and productive employees, Southwest has 40 percent greater aircraft and pilot utilization than its competi- tors. Employee retention and low employee turnover help drive productivity and customer value. Traditionally, the cost of employee turnover considers only the cost of recruiting, hiring, and training replacements. In reality, the greatest cost of turnover is the lost produc- tivity and decreased customer satisfaction associated with new employees. At Southwest Airlines, customer perceptions of service value are high, based on low fares, on-time ser- vice, and friendly and helpful employees.
Employee retention and productivity are driven by having satisfied employees. For example, a study of insurance company employees found that 30 percent of dissatisfied employees intended to leave the company, a potential turnover rate three times that of satis- fied employees. Satisfied employees are the result of internal service quality. This includes the employee selection process, job design, reward systems, and the technology used to support service workers. Focusing management’s attention on improving internal service quality systems to provide support for employees in conducting their work can improve employee satisfaction, productivity, and turnover. Employees will be satisfied with their jobs when they feel that they can act on behalf of customers. This will lead to both employee and customer satisfaction. This is achieved in part by giving front-line employees latitude to use resources to meet customer needs immediately. For example, in Ritz-Carlton Hotels, front-line employees are authorized to spend up to $2000 to satisfy a customer need.
The service-profit chain illustrates the central role of employees in delivering services to customers. During the delivery of services, employees are the “face” of the company and their satisfaction is directly observed by customers, often influencing customer perceptions of the service as well. This differentiates services from manufacturing, since manufacturing employees rarely have direct contact with customers. A manufacturing employee’s effect on customer satisfaction is through the product that the customer may receive days, weeks, or months later. However, the morale, attitude, and satisfaction of service employees is directly—and immediately—related to customer satisfaction and loyalty. There is no buffer zone between service employees and customers in high- or medium-contact services.
The service delivery system design should reflect this direct contact between service employees and customers. This can be done by providing real-time (during the service delivery) tools such as access to customer information to help service employees perform their jobs. For example, bank tellers who can quickly scan relevant portions of a cus- tomer account while the cus- tomer is face-to-face or on the telephone with them can pres- ent banking products that fit the customer profile. Such per- sonalized selling opportunities tend to be more successful than low-contact marketing, such as mail or e-mail. Services can also be improved through so-called “smile training” in which service workers are trained to be nice to customers and seek their satisfaction even in pressure situations. Service workers should be rewarded for
Harrah’s uses superior customer service to increase profits. Leonard Zhukovsky/123RF
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both productivity and customer satisfaction. The service-profit chain shows that these two measurements are not in conflict; rather, productivity can actually drive customer satis- faction through faster and better service at lower cost. Both satisfaction and productivity can be achieved not by trying harder but by improving the use of people, technology, and service process flows.
An interesting application of the service-profit chain is being made at Harrah’s in Las Vegas, Nevada. Traditionally, the gambling industry catered to high rollers. A former professor at the Harvard Business School, Gary Loveman, Harrah’s then-CEO, revolu- tionized the gaming industry by showing that the key to profitability and growth is not only catering to the high rollers but also providing exceptional service to all customers. “People don’t understand that gaming itself is fundamentally entertainment,” says Love- man. Gamblers from all walks of life like to play the odds again and again . . . and again! This will be done by having satisfied employees provide exceptional service to satisfied and loyal customers.
5.9 KEY POINTS AND TERMS
This chapter emphasizes the design of service delivery systems. The key points are as follows:
∙ A front office service is defined by simultaneous production and consumption. This makes it impossible to store a service for later use, and a service often must be located near customers, with the exception of technology-delivered services such as communi- cation and electricity. The customer is part of the service process during production and may introduce inefficiencies, but at the same time sales opportunities.
∙ Back office services can be buffered from the uncertainty introduced by customers and therefore can be designed for higher efficiency.
∙ Services consist of bundles of services and goods, including explicit services, implicit services, and facilitating goods. It is important to provide the right mix of these three elements and not overlook the psychological (implicit) component of service.
∙ The service delivery system matrix is formed by juxtaposing customer wants and needs in terms of customizing a service against the service delivery system. The combination of service package and service process design elements results in three main service types: customer-routed services, co-routed services, and provider-routed services. Each of these service types has different requirements for operations managers to meet.
∙ Customer contact depends on the duration and degree of interaction between the pro- vider and customer. Generally, high-contact services are performed in the front office; low-contact services are performed away from the customer in the back office. In addi- tion to contact, the degree of uncertainty introduced by the customer will have an impact on efficiency within the service system.
∙ When services are not delivered as promised, the firm should provide quick and helpful service recovery. A service guarantee can be offered to ensure that the customer under- stands what is promised and what constitutes an error in service delivery. The service guarantee provides a way for operations to know exactly what is required.
∙ Technology allows the automation of services for greater efficiency that can result in lower costs and more uniform quality. Artificial intelligence offers the prospect of providing some services that are indistinguishable from human service providers.
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Nevertheless, both AI and service employees will be needed depending on the type of service provided.
∙ Service outsourcing and offshoring are trends that present opportunities and challenges. Offshoring often is used to obtain talent from widespread global locations, particularly for information or communications intensive services. A strategic approach should be taken to offshoring and outsourcing, not just chasing low-cost labor, since changing costs, quality, and reliable suppliers in the long-run should be considered.
∙ The service-profit chain indicates how value provided to the customer drives customer satisfaction and loyalty, which leads to revenue growth and profitability. External cus- tomer value is the result of employees who are productive, satisfied, and retained by the firm. These employees must be appropriately selected, trained, and rewarded. The service-profit chain indicates the crucial role of employees in delivering services and financial results.
Key Terms Intangibility 78 Simultaneous production and
consumption 78 Front office 78 Back office 78 Service-product bundle 79 Explicit services 79 Implicit services 79 Facilitating goods 79 Service delivery system
matrix 80 Operations service system 81
Analytical AI 89 Intuitive AI 89 Empathetic AI 90 Outsourcing of services 90 Offshoring 90 Service-profit chain 92 Customer loyalty 92 External service value 92 Productive employees 93 Employee retention 93 Satisfied employees 93 Internal service quality 93
Customer-routed services 81 Co-routed services 82 Provider-routed services 82 Self-service 83 Customer contact 83 Customer-introduced
variability 84 Service recovery 86 Service guarantee 87 Artificial intelligence
(AI) 88 Routine AI 88
LEARNING ENRICHMENT (for self-study or instructor assignments)
What Is a Service Export? Web Link http://www.tradeready.ca/2016/trade-takeaways/service-exports-
suddenly-important/
What Is Service Recovery in Health Care? Web Link https://www.ahrq.gov/cahps/quality-improvement/improvement-
guide/6-strategies-for-improving/customer-service/strategy6p- service-recovery.html
Machine Learning and AI in Financial Services Video https://youtu.be/xefkx107p6A 6:00
AI Products with User Centered Design – J.P. Morgan Video https://youtu.be/Ku8x1ina_N4 3:20
The Service System Design Matrix Video www.mhhe.com/servicesystem 10:58
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Discussion Questions 1. Classify the following services by their degree of
customer contact (high, medium, or low). Also, determine how much uncertainty the customer introduces into the service delivery system by the ability to make customized service demands (high, medium, or low).
a. Check-clearing in a bank b. Bank teller c. Bank loan officer 2. Locate each of the following services on the service
delivery system matrix: a. Vending machine b. Housecleaning service c. Appliance repair 3. How do the managerial tasks differ among the services
described in question 2? 4. Describe the service-product bundle for each of the
following services: a. Hospital b. Lawyer c. Trucking firm 5. Critique the customer contact model. What are its
strengths and weaknesses? 6. Identify the front office and back office services for
the following organizations. Could these services be improved by increasing or decreasing the degree of customer contact? By separating low- and high-contact services?
a. Hospital
b. Trucking firm c. Grocery store d. Appliance repair firm 7. Define a possible service guarantee for each of the
following services: a. College classes b. A theater performance c. Buying a used car 8. Give an example of the service-profit chain for movie
theaters. Define each of the components in the chain and explain how you would measure each.
9. Why is the service-profit chain important to operations management?
10. Find some service guarantees in everyday life and bring them to class for discussion.
11. What attributes are required of a service guarantee to make it effective?
12. What are the pros and cons of having a service guarantee?
13. How can we use the service delivery system matrix to improve service operations?
14. What does it mean for a service firm to outsource some of its services?
15. What key factors are most firms seeking when they offshore services?
16. In what situations will customers accept service by AI agents?
17. What should be the nature of interaction between human service providers and AI agents?
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A customer walks into a home improvement store, selects a paint color from the multitude of sample options, and gives the selection to the store employee. The employee enters information about the selection into a machine that automatically dispenses the appropriate set and quantities of pigments into a can of white paint. Another machine is used to shake the can, resulting in consistent color throughout the can. The customer walks away with a virtually customized product in a matter of minutes. The simple process used to create the customized paint combines the customer’s preference, employee skills, and automated technology.
Processes are encountered in all parts of a business, not only in operations and supply chain management. Accountants use many processes, including collecting transactions, posting to the ledger, trial balance, adjusting entries, financial statements, and closing entries. Marketing managers also use numerous processes, including strategic planning, marketing research, advertising, selling, and customer relations. All of these processes can be improved by the ideas of process-flow analysis presented here.
Process-Flow Analysis
c h a p t e r 6
After reading this chapter, you should be able to:LEARNING OBJECTIVES
LO6.1 Describe process thinking and system boundaries.
LO6.2 Explain how the process view of business is cross-functional.
LO6.3 Construct a process flowchart for a given process.
LO6.4 Analyze a process by asking a wide variety of questions informed by the process flowchart.
LO6.5 Calculate process-flow capabilities using analytics.
LO6.6 Explain the principles of process redesign.
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This chapter is about understanding processes and how they are used to produce and deliver products and services. It is also about determining what a process is capable of pro- ducing. Process-flow analysis requires viewing and analyzing the transformation process as a sequence of steps connecting inputs to outputs. It is used to discover better methods or proced- ures for producing and delivering a product or a service deemed to be of value to customers.
Measuring process flows is essential to process-flow analysis and to improving trans- formation processes. We describe several process measures, including processing time, throughput time, flow rate, inventory, and capacity. We also define bottlenecks and provide analyltic methods for calculating these measures.
The flowchart (often referred to as a process map) is an essential tool to facilitate process-flow analysis. Flowcharts should consider not only process flows but customers, suppliers, and employee inputs in designing better processes. A flowchart for a high-contact service process, such as consulting, often reflects the customer’s perspective, mapping the activities performed for the customer. In manufacturing, a flowchart often shows the activ- ities performed on materials as they move through the production system.
To truly understand process-flow analysis, we begin this chapter with process thinking. This is a very powerful idea in business education and in practice.
6.1 PROCESS THINKING
Process thinking is the point of view that all work can be seen as a process. It begins by describing the process of interest as a system. A system is defined by its boundaries, inputs, outputs, suppliers, customers, and system flows. System definition is needed before detailed measurement and process flowcharting can begin.
A system is a collection of interrelated elements whose whole is greater than the sum of its parts. The human body, for example, is a system. The heart, lungs, brain, and muscles can- not function without one another. They are interrelated, and the function of one part affects the others. The whole of the body is greater than any of its individual parts or components.
A business organization can also be viewed as a system. Its parts are the functions of mar- keting, operations, finance, accounting, human resources, and information systems. Each of these functions accomplishes nothing by itself. A business cannot sell what it cannot produce, and it does no good to produce a product or service that cannot be sold. The functions in an organization are highly interactive and have value as a system that they do not have separately.
Within operations, the transformation or conversion system is made up of workers, equipment, customers (for services), and the activities that carry out the transformation. The transformation system can be analyzed by first specifying the system boundaries. The boundaries delineate the resources and activities in the system being analyzed from those that are outside of the analysis and decision area. Identification of the system bound- aries is always difficult and somewhat arbitrary, but it must be done to separate the system being analyzed from the larger system or organization in which it operates. In this sense, the boundaries of a firm separate the firm from the larger supply chain in which it resides.
To illustrate these concepts, consider the case of a bank that is installing a new informa- tion system. The new system will replace the current one, with larger capacity, new hard- ware, and new software. Training will be required to operate the new system, and so human resources can be considered part of the system. Operations will be affected by the new soft- ware and must be included within the system boundaries. Each part of the organization that is affected by the new information system should be included within the system boundaries, and functions that are not affected can be excluded as being outside the system boundaries. In this way, the appropriate system boundaries can be identified for purposes of analysis.
LO6.1 Describe process thinking and system boundaries.
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A cross-functional team should be formed, consisting of the functions that are affected by the conversion to the new information system. This team will be responsible for overseeing the conversion from each of their functional perspectives and should handle the interactions between functions. If this is done by a cross-functional team rather than workers from a single function, a systems view of the project will be taken. This sort of process thinking considers all the interacting functions within the system boundaries when making the conversion.
6.2 THE PROCESS VIEW OF BUSINESS
One of the most important contributions of process thinking is that a business can be viewed as a system that consists of a collection of interconnected processes. The process view of a business is horizontal in nature; the functional view is vertical. This is shown graphically in Figure 6.1.
As an illustration of interconnected processes in a business, consider a scenario. A sales team has a process for creating the customer order, while at the same time interacting with operations to ensure adequate capacity is available to fill the order. Other marketing per- sonnel use a process for pricing the customer order. Once operations receives the order, the necessary processes are used to produce enough output to fill the order. The shipping area has a process for securing the order for delivery, and transportation is scheduled to deliver the order to the customer. Finance uses its own processes to bill and receive payment from the customer, while relying on pricing information from marketing and order size and delivery confirmation from operations.
Viewing a business as a collection of processes emphasizes the cross-functional nature of decision making. It illustrates that functions must make handoffs to one another in exe- cuting a process. As a result, time and information can be lost between processes. In some cases, the number of steps in a process is so large that the system cannot function in an efficient and effective manner. See the example in the Operations Leader box of the com- plex and time-consuming process of setting up clinical trials to test newly developed drugs.
Another example comes from an MRI (magnetic resonance imaging) facility, where a backlog of patients had developed. The backlog was difficult to solve because the MRI facility did not control its own schedule. An outside service provider was contracted to schedule patients, and their scheduling caused several problems. The scan indicated on the schedule did not always match with the actual scan that the patient needed, and sometimes not enough scan time was scheduled for certain patients. Further, there was a need to hire
LO6.2 Explain how the process view of business is cross-functional.
FIGURE 6.1 The process view of business. Source: V. Grover and M.K. Malhorta, “Business Process Reengineering: A Tutorial on Concept, Evolution, Method, Technology and Application,” Journal of Operations Manage- ment 15 (1997), p. 200.
Horizontal organization (process)
CEO
Marketing
Order fulfillment
Customer request
Operations Finance
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100 Part Two Process Design
an additional technician to conduct scans, and such technicians were in relatively short supply in the local labor market. Dealing with the backlog of patients waiting for scans is an operations problem, but processes outside of operations interact with processes within operations to cause the problem. Solutions to the backlog problem need to account for the larger system of activities within and outside of operations.
This example illustrates how operations is a part of a larger organization that includes many other functions and outside organizations. Nearly all operations decisions are related to at least one other function in the organization. The process view of business provides a vehicle for understanding the interactions between various organizational functions, and sometimes extending beyond organizational boundaries. These interactions can be stream- lined and improved by process flowcharting, as is described next.
6.3 PROCESS FLOWCHARTING
Process flowcharting is a tool for beginning to understand and improve processes within a larger system. This is a very commonly used tool in a wide variety of industries. It can be useful for almost any type of process, to gain understanding of the activities that must occur for the process to successfully produce a product or service.
Process flowcharting refers to the creation of a visual diagram to describe a trans- formation process. Flowcharting is known by several names: process mapping, flow-process charting, and in a service operations context as service blueprinting. Value
LO6.3 Construct a process flowchart for a given process.
the time taken by these processes reduced the activa- tion time by 28 percent.
Source: D.A. Martinez, A. Tsalatsanis, A. Yalcin, D.J. Zayas- Castro, and B. Djulbegovic, “Activating Clinical Trials: A Process Improvement Approach,” https://doi.org/10.1186/ s13063-016-1227-2, open source, 2016.
The Office of Clinical Research at the University of South Florida (USF) wanted to improve the complex process of starting a clinical trial. A clinical trial is a research study used to conduct a controlled test of a new drug on humans. Patients volunteer to participate in such studies, and the results are used to determine whether the new drug will be approved for use in the marketplace.
USF assembled a team of experts to map and improve the process. The administrative process comprised five sub- processes, 30 activities, 11 decision points, five loops, and eight participants. The mean activation time was 76.6 days. The typical clinical trial goes through these five subprocesses: Initial Preparation, Contract Negotiation, Budget Negotiation, Preparation for Submission, and Trial Activation.
They used flowcharting to create an overview of the administrative process starting from initial preparation and ending with trial activation. Additionally, activity time stamps were used to compute the duration of each sub- process and of the overall process. From the flowchart they identified and reduced the time taken by many activities in the administrative process.
Based on these studies, time-limiting subprocesses were those of contract and budget negotiation. Reducing
Process Analysis to Improve Clinical Drug Trials
OPERATIONS LEADER
Erik Isakson/Blend Images LLC
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stream mapping is yet another approach to process flowcharting popularized by firms that implement lean systems and lean thinking. Creating a visual diagram can be invaluable in documenting what happens within a transformation process. This pictorial documentation, when it includes process measurements, such as time or cost, can help to identify how the transformation process can be improved by changing some or all of the following elements:
1. Raw materials 2. Product or service design 3. Job design 4. Processing steps or activities used 5. Management control information 6. Equipment or tools 7. Suppliers
While there are many different specific forms of the flowchart in use, the most common is the systems flowchart. An example of a systems flowchart for the “selecting a supplier” process is shown in Figure 6.2. In this example, the systems flowchart is drawn from the perspective of the buyer within an organization and shows the discrete steps, along with decision points and flow sequences, in selecting a supplier.
Another example appears in Figure 6.3, which shows the service provided to help a customer select and have altered a suit from a retail store. This systems flowchart depicts a service context with the customer being in the system and interacting with the service provider and is, as such, also called a service blueprint. Moreover, because the service blueprint captures the perspectives of different people—customer, sales associate, and tailor—it is also known generally as a swim lane flowchart. A swim lane flowchart is used to show the responsibilities of groups or individuals in either hori- zontal or vertical columns. It shows who or what is per- forming each step in the flowchart in the form of “swim lanes” in a pool. In Figure 6.3, horizontal swim lanes are drawn to demarcate the various participants involved in the process of buying a suit from a retail store.
The tailor makes alterations on the suit as part of the service blueprint. Pressmaster/Shutterstock
FIGURE 6.2 A flowchart for selecting a supplier.
Start
End
Buyer receives
request to buy
Buyer identifies supplier
Buyer calls
supplier
Buyer selects
supplier
Information correct?
Supplier capable?
No NoYes
Yes
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102 Part Two Process Design
FIGURE 6.3 Service to select and have altered a suit from a retail store.
For any type of flowchart a number of principles should be followed to create a flow- chart that is easy for individuals unfamiliar with the transformation process to understand and that facilitates process-flow analysis. These principles are consistent with process thinking, which views the transformation process as a system with inputs, outputs, custom- ers, suppliers, boundaries, and processing steps and flows. The principles are as follows:
1. Identify and select a relevant transformation process (or system) to study. This can be the entire supply chain for a product or a service, the entire firm, or a part of the firm, for example, the shipping department. Ideally, the selected transformation process is thought to affect performance. 2. Identify an individual or a team of individuals to be responsible for develop- ing the flowchart and for subsequent analyses. This individual or team should have some familiarity with the transformation process and should have process ownership, that is, authority for initiating and/or implementing changes to the process. When a selected transformation process cuts across different functions, a cross-functional team should be involved. When a selected transformation process cuts across the supply chain, interfirm collaboration becomes critical. 3. Specify the boundaries of the transformation process. The boundaries denote where the selected transformation process begins and ends, identify the customer(s) and the supplier(s) of the transformation process, and determine how many processing steps or activities are to be evaluated. In some cases, a function or department within an organiza- tion is the customer or supplier; in other cases, another firm is the customer or supplier.
Customer arrives at the store
Greet customer
Request preferences (size, style, and price)
Salesperson takes customer to racks
Customer begins search
Customer provides information
Customer
Sales Associate
Tailor
Tailor Shop
Line of Visibility
Do we have a suit of interest?
Exit No
Yes
Start Try on suit and look in mirror
Move customer to the tailor
Make alterations
Determine alterations needed
Write up sales ticket
Thank customer
Customer accepts alterations
Customer returns to pick up suit
Customer likes the suit
Line of Visibility
Exit
Yes
No
End
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4. Identify and sequence the operational steps or the activities necessary to com- plete the output for the customer(s). It is important in process flowcharting to depict what is actually happening and not what one thinks is happening. Once the “as it is” flow- chart has been created and the transformation process has been analyzed, creating a “to be” flowchart may help show what the transformation process should look like when improve- ment changes have been implemented. 5. Identify the performance metrics for the operational steps or the activities within the selected transformation process. These metrics should be tied to the per- formance of the overall transformation process. For example, if delivery performance is of interest, it may be useful to track the processing times for each operational step or activity. Alternatively, if quality performance is of interest, it may be useful to track the defect rate for each operational step or activity. 6. Draw the flowchart, defining and using symbols in a consistent manner. Figure 6.4 shows the common symbols in Microsoft Visio for creating a systems flow- chart. These symbols were used in Figures 6.2 and 6.3 and are also consistent with ISO 9000 standards for flowcharting.
When other specific forms of flowcharts are created, the individual or team responsible may choose to use other symbols. This is allowed as long as the symbols are used consist- ently and, more importantly, a symbol key is provided to help interpret the flowchart that
Customer arrives at the store
Greet customer
Request preferences (size, style, and price)
Salesperson takes customer to racks
Customer begins search
Customer provides information
Customer
Sales Associate
Tailor
Tailor Shop
Line of Visibility
Do we have a suit of interest?
Exit No
Yes
Start Try on suit and look in mirror
Move customer to the tailor
Make alterations
Determine alterations needed
Write up sales ticket
Thank customer
Customer accepts alterations
Customer returns to pick up suit
Customer likes the suit
Line of Visibility
Exit
Yes
No
End
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104 Part Two Process Design
FIGURE 6.4 Common flowcharting symbols.
Process
Decision/Evaluation
Flow
Symbol Meaning
This symbol shows the “start” and the “end” of the flowchart, thereby specifying the boundaries of the transformation process to study. The words “START” and “END” should be written inside the symbol for clarity.
This symbol denotes an operational step or an activity to be performed. A short description of the operational step or the activity should be written inside the symbol for clarity.
This symbol denotes the direction of flow within the flowchart; the flow could be that of materials, information, or person (e.g., customer).
This symbol represents a decision, an evaluation, or an “IF-THEN” condition that has multiple potential outcomes (i.e., branches of arrows). The decision, evaluation, or condition should be properly described in writing inside the symbol for clarity. Each branch of arrow should be properly labeled to denote the meaning of the outcome from the decision, evaluation, or condition.
Terminator
is drawn. Figure 6.5, for example, is a flow-process chart of the picking operations at a distribution center that provides produce, dairy, and meat items to grocery stores. In this case, the interest is in tracking the flow of “materials” inside the distribution center. The flow-process chart depicts every step in the process from initial input of the customer order to picking groceries in various aisles, to consolidation, inspection, and shipment of the order. An information processing flowchart can also be drawn to depict the same picking operation, but here the interest is in tracking the flow of “information” for the purpose of management and control of the distribution center.
6.4 PROCESS-FLOW ANALYSIS AS ASKING QUESTIONS
Creating a flowchart of a transformation process is an important first step in process-flow analysis. Once created, the flowchart can be analyzed to yield insights into how the trans- formation process can be improved, given a specific improvement goal. The improvement goal, for example, can be to increase efficiency, reduce throughput time, improve quality, or even boost worker morale.
A systematic approach should be followed to analyze the created flowchart and the underlying transformation process. This approach is epitomized by asking questions about the flowchart and, by extension, the underlying transformation process. Table 6.1 shows typical questions about the performance of a system regarding flow, time, quality, quantity, and cost.
When these questions are asked, opportunities to improve the underlying transforma- tion process can be identified. For example, looking at the flow-process chart in Figure 6.5 and asking questions about the picking operations at the grocery distribution center led to the realization that many activities (transportation, inspection, delays, and storage) do not add value to the service provided and should be reduced or eliminated. Groceries in fact spent a considerable amount of time waiting for the next operation or in transit and very little time in value-added operations (only 57 minutes out of 526 minutes). As a result
LO6.4 Analyze a process by asking a wide variety of questions informed by the process flowchart.
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FIGURE 6.5 Flow-process chart for the picking operations.
FLOW PROCESS CHART
Subject Charted Summary Operations Transports Inspections Delays Storages Time Distance
Pres. Prop. Save
Operation
Charted by
Chart No. Sheet Can I Eliminate? Can I Combine? Can I Change Sequence? Can I Simplify?
of
Date
Dist. in
Feet
Time in
Min.
Present
Proposed Descriptions Notes
Produce, Dairy, Meat Depts.
Picking
RGS
01
90 60
120
3
10
80
4
20
15
25
10
30
60
5
15
4
10
50
526
=
5
To the warehouse
X
On distribution desk
Separated according to work areas
Taken to start points
Wait for order picker
Picker separates them order by order
(Produce) picker fills order
To Dairy aisle
On conveyor waiting for picker
(Dairy) picker fills order
To Meat aisle
On conveyor waiting for picker
(Meat) picker fills order
To inspection
Inspected
Loaded onto carts route-by-route
Waits to be taken to the warehouse
Total Time
Computer prints order sheets
30
30
45
20
1/8/13
11
7
5 1 5 0
215
O pe
r.
Tr an
.
In sp
.
D el
ay s
St or
e
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Operation (a task or work activity)
SYMBOL KEY
Inspection (an inspection of the product for quantity or quality)
Transportation (a movement of material from one point to another)
Storage (an inventory or storage of materials awaiting the next operation)
Delay (a delay in the sequence of operations)
of asking questions, a number of changes were implemented, including relocating aisles (i.e., a process layout change), revising picking methods to reduce bottlenecks and labor time (i.e., changes to work methods and jobs), and designing special carts to make the loading of delivery vans easier and faster (i.e., an equipment change).
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106 Part Two Process Design
Question Category Examples
1. Flow • Is the transformation process balanced or unbalanced? • Where is the bottleneck in the transformation process? • Are all operational steps or activities necessary? • How jumbled is the flow within the transformation process?
2. Time • How long does it take to produce/deliver one unit of output? • Can the length of this time be reduced? • What is the time between successive units of output? • Where is there excessive setup time? • Where is there excessive waiting time?
3. Quantity • How many units theoretically can be produced/delivered in a given period (e.g., a week)?
• How easy is it to change this quantity? • How many units are actually produced/delivered in a specified
period (e.g., a week)?
4. Quality • What is the historical defect rate? • Which operational step or activity contributes to the defect rate? • Where do errors occur?
5. Cost • How much does it cost to produce/deliver one unit of output? • What are the cost buckets that make up the cost to produce/
deliver one unit of output? • Can some cost buckets be reduced/eliminated?
TABLE 6.1 Process-flow questions about performance
Similarly, looking at the service blueprint for the service of helping a customer pur- chase a suit from a retail store and asking questions might lead to suggestions for improve- ment such as the following:
∙ If sales associates can be trained to listen better to customer requests, will customers be more likely to find a suit of interest?
∙ Can customers call ahead and ask to have some suggested suits waiting for examination, reducing their search time?
∙ Is the tailor available while the customer is trying on the suit to provide suggestions on how the suit can be tailored to fit better?
∙ Does the layout of the retail store make it easy for customers to search and find what they want?
In summary, process-flow analysis begins with a good flowchart of the transformation process used to convert inputs into outputs. This can be facilitated by creating a flow- chart that shows materials flows, information flows, or service flows. Once a flowchart is created, appropriate questions should be asked to highlight improvement opportunities in flow, time, quantity, quality, and cost.
6.5 PROCESS ANALYTICS
Once a process flowchart aimed at improving a transformation process has been created, some basic measures of a transformation process can be described. Process analytics uses these measures to yield insights into the structure and performance of a transformation process.
Let’s study the airport security process during check-in at a major airport. There is a line of passengers waiting to clear security and a number of security scanners for examin- ing passengers and their carry-on luggage. We can measure the total time it takes from
LO6.5 Calculate process-flow capabilities using analytics.
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entering the security line until passengers are cleared to catch their flights. It turns out that the following three observations are related: the average number of passengers in the line, the average rate at which secur- ity can process passengers, and the average time it takes passengers to get through the line. This relation- ship is called Little’s Law, named after the operations researcher who discovered it.
Little’s Law shows that the average number of items in a system (I) is the product of the average arrival rate to the system (R) and the average time an item stays in the system (T). This average time in the system is throughput time, the time from when the processing begins until the product or service is completely fin- ished. It includes both active processing time and any waiting time that occurs during processing. In math- ematical terms Little’s Law is stated as follows:
I = T × R
where I = average number of things in the system (or “inventory”) T = average throughput time (processing time + waiting time) R = average flow rate in the system
In the case of airport security, if the security screeners can process an average of five pas- sengers per minute (R = 5) and it takes an average of 20 minutes to get through the security line (T = 20), the average number of passengers in line (I) will be 100 (R × T = 100). An assumption is that the process is in a steady state in which the average output rate equals the average input rate to the process.
Little’s Law is very powerful and is widely used in practice. It applies to manufacturing and service transformation processes. Little’s Law can be used in a variety of settings and situations.
Average waiting time in line at airport security follows Little’s Law. Philippe Merle/AFP/Getty Images
Suppose a factory can produce an average of 100 units of product per day. The throughput time, including all processing and waiting time for the product, is an average of 10 days.
T = 10 days R = 100 units per day
Then the average inventory (partly finished product) in the factory will be
I = 10 × 100 = 1000 units
For another example, the amount of money in accounts receivable can be considered as inventory, or the stock of money. Using Little’s Law, if there is $2 million in accounts receiv- able (I) and $20,000 per day is added to and subtracted from (flows through) accounts receivable (R), the throughput time is
100 days (T = I /R = 2,000,000/20,000)
Therefore, accounts receivable has 100 days of outstanding receivables.
Example
Little’s Law applies to any steady-state transformation process including manufactur- ing, people waiting in lines, invoice processing, transactions in a legal office, and even accounts receivable processing. Little’s Law is useful when any two of the three variables
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108 Part Two Process Design
in the formula are known, then the third can be calculated. The examples above show how this is done to calculate I and T. We can also calculate R if we know I and T (R = I/T).
Next, we extend process analytics to include capacity, supply, and demand. Capacity is the maximum rate of output from a transformation process or the maximum flow rate that can be sustained over a period of time. In the airport security example, the average flow rate was five passengers per minute, but the capacity of the security checkpoint may have been greater, say, eight passengers per minute. With random arrivals (such as passengers arriving to enter the line) it is necessary to have capacity that exceeds the average arrival rate. If the arrival rate is greater than the capacity, the line will build up to an infinite length due to the randomness of the arrivals. This occurs because there are periods when the arrivals are less than the average and the full capacity cannot be used during those times. Queuing (or waiting line) theory, which is covered in a technical chapter,1 explains these phenomena in detail.
Most processes are composed of several activities that require certain resources. In the airport screening example resources include the workers who check each passenger’s iden- tification and boarding pass, operators who run the scanning equipment, and the equip- ment itself. In general, if there are n resources that process each transaction, then
Capacity = Minimum (capacity of resource1,…, capacity of resourcen)
Note that the capacity of the entire process cannot be greater than the capacity of the most constraining (the smallest capacity) resource, which is called the bottleneck.
The amount of output a transformation process actually produces will depend on its capacity as well as the supply and demand of the process. The flow rate is as follows:
Flow rate = Minimum (supply, demand, capacity)
In the factory example above, assume that capacity is 200 units per day, demand is 75 units per day, and supply is 100 units per day. The flow rate would be 75 units per day (the min- imum of the three variables) assuming they can produce only what is demanded. If they were able to increase demand to 150 units per day, the flow rate would be only 100 units per day unless supply could also be increased.
6.6 ANALYZING PROCESS FLOWS AT PIZZA U.S.A.
To cement our understanding of the concepts of process analytics, let us look at a Pizza U.S.A. example. Suppose that one of the pizza stores produces fresh pizza with seven differ- ent topping choices, including the most popular “everything dump” pizza. The store is staffed by two employees: a pizza chef and an assistant. It has an oven that can bake up to four pizzas at a time. The transformation process (sequence of steps) followed at the store is as follows:
1 Technical chapters are available from Instructor Resources on McGraw-Hill Connect.
Minutes Who
Take the order 1 Assistant Make the crust 3 Chef Prepare and add ingredients 2 Chef Bake the pizza 24 Oven Cut pizza and box the order 1 Assistant Take payment 1 Assistant
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1. What is the capacity of this process?
Looking at the three resources, we have:
∙ The assistant takes 3 minutes per order (1 + 1 + 1) and thus can process 20 orders per hour.
∙ The chef takes 5 minutes per order (3 + 2) and can process 12 orders per hour. ∙ The oven takes an average of 6 minutes per order (24 ÷ 4, because the oven holds
4 pizzas at a time), or 10 orders per hour. For simplicity, we assume that each order is for one pizza and that pizzas can be added to the oven any time during the cooking cycle. The minimum of the three resource capacities is 10 orders per hour, and so the sys- tem can produce 10 orders per hour.
2. What is the bottleneck in this process?
The bottleneck in this case is the oven. The assistant is busy only half the time, and the chef has 1 minute of idle capacity out of every 6 minutes of average bak- ing time. Reallocating jobs between the chef and the assistant to balance the workload may make the chef happy but will not increase the flow rate of the process. If Pizza U.S.A. wants to make more pizzas, something must be done to accelerate the flow of pizzas through the oven, or another oven must be added. The lesson here is that the process cannot produce more than the bottleneck can process.
3. What is the throughput time?
If we assume there is no waiting time in this system, we simply add the times of all the steps to fill an order:
1 + 3 + 2 + 24 + 1 + 1 = 32 minutes
It takes 32 minutes to complete all the steps and make one pizza. Note that adding an oven will increase the capacity and move the bottleneck to the chef, but it will not change the throughput time. Changes would have to be made in the actual process of cooking, prepar- ation, or other flow times to reduce throughput time.
4. What is the flow rate?
Assuming that demand and supply exceed capacity, the flow rate is determined by the bottleneck capacity of 10 orders per hour. However, this is the maximum flow rate; the actual flow rate could be much less. If either demand or supply is less than capacity, then the smaller of the two will determine the flow rate. In the following question, we assume demand is only 60 percent of capacity, for a flow rate of six pizzas per hour.
5. What does it cost to make a pizza if the average demand is 60 percent of capacity?
Assume the chef gets paid $15 per hour, the assistant gets paid $11 per hour, and over- head cost is 50 percent of direct labor cost. At 60 percent of capacity, the average flow rate is six pizzas per hour. The cost per hour of operations is $15 + $11 = $26 for labor plus 50 percent added for overhead = $39 per hour, or $39 ÷ 6 = $6.50 per pizza. Assume
The oven is one of the resources that determines the process capacity. BananaStock/Getty Images
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110 Part Two Process Design
the cost of ingredients is $2.00 per pizza. Therefore, the total cost is $6.50 + $2.00 = $8.50 per pizza.
6. How can the unit cost of pizzas be reduced?
Three possibilities are:
∙ Increase demand through pricing, advertising, or other means. ∙ If demand increases to exceed capacity, increase the flow rate of the entire trans-
formation process by means of automation or process improvements. ∙ Reduce the unit cost of labor, materials, or overhead.
As you can see, these three approaches are interconnected because increasing demand will also require an increase in capacity at some point, and increasing the flow rate does no good unless demand is increased to sell the additional product.
6.7 PROCESS REDESIGN
Process redesign usually starts with identifying critical processes required to meet the customers’ needs. Then the critical processes, many of which cut across organization boundaries, are analyzed in detail using the methods described in this chapter. Changes are often made to these processes as a result of the insight from process-flow analysis. These changes might include eliminating some steps and combining others, or could be as extreme as a complete reconfiguration of process steps. As a result, business processes are redesigned and integrated to better serve the customer. The term business process reengi- neering (BPR) has also been used to label extensive process redesign activities. See the Operations Leader box titled “Crédit Suisse: A Successful Process Redesign” for an example of how BPR is being deployed to aid in improving processes.
In their famous book Reengineering the Corporation, Michael Hammer and James Champy argue that most business processes are antiquated and need to be completely redesigned. Many existing processes have been designed within the confines of individual functions, such as marketing, operations, and finance and also do not make use of complete information systems. As a result, these processes take far too long to provide customer service and are inefficient and wasteful.
Consider a major insurance company that had just this problem. When the customer called about an insurance problem, the call was taken by the call center. The problem was entered into a computer and passed electronically to one of several departments: under- writing, policy service, accounting, or another department. The problem then waited in the queue, often for several days, until a worker had time to investigate it. In some cases, the customer’s problem had been routed to the wrong department and had to be routed to another department, again spending several days in the queue. If the problem required more than one department to answer the question, the process of waiting was repeated. Finally, someone in customer service would get back to the customer after several weeks. In many cases, the original question was not answered completely or was answered incorrectly.
This process was redesigned by completely reorganizing the entire insurance operation around customer service representatives who would attempt to handle customer requests on the phone, if possible, using detailed protocols and standard scripts. If additional work was required, the customer service representative checked with other specialists and got back to the customer with an answer. The customer service representatives had been cross- trained in all the various disciplines required and were supported by the other depart- ments. Although this required more training of customer service representatives, it greatly improved the speed and accuracy of the service while saving many millions of dollars. It also provided a single point of contact and less hassle for the customer.
LO6.6 Explain the principles of process redesign.
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and corporate banking customers. In the past, the steps of closing a customer account involved many manual steps and a variety of banking personnel. The original accounts closing process, shown here, was prone to errors, slow to respond, and not very efficient.
After the process was analyzed, an important insight came to light. Most requests for account closing could be handled in a standardized manner and therefore could be automated. A new software application was devel- oped to allow the relationship manager to initiate all the activities that would close a customer account. Other bank personnel did not need to be involved, except in a small number of unusual cases. As a result, the time to close an account was reduced by 50 percent and the error rate was reduced to just 0.01 percent.
Headquartered in Zurich, Switzerland, Crédit Suisse is a global financial services institution with more than two million customers in 50 countries and a global workforce of more than 50,000 employees. Process redesign has been applied to many of its major service processes. The “accounts closing” process is described here.
Customers’ rising expectations for faster service, along with increasing regulations, created a need for a faster and less error- prone process. Daily, hundreds of accounts are closed by retail
Crédit Suisse: A Successful Process Redesign
OPERATIONS LEADER
send inquiries
send inquiries
Customer Relationship Manager
Administrator Accounting Clerk
Original process
Redesigned process
Payments database
speak to or write
fill form or send e-mail
send instructions
Pending tasks
database
Customer Relationship Manager
New software application
Payments database
speak to or write
enter data
Personnel
Key Work flow
Data flow
Pending tasks
database
Source: Peter Küng and Claus Hagen, “The Fruits of Business Process Management: An Experience Report from a Swiss Bank,” Business Process Management Journal 13, no. 4 (2007), pp. 477–87; www.credit-suisse.com, 2019.
DSGNSR1/Shutterstock
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112 Part Two Process Design
Process redesign is radical redesign when processes simply cannot be improved in small steps and require a complete rethinking and rearrangement of process activities to improve them in a major way, as was the case for the insurance company described above. Often radical redesign is supported by new technology, in the form of either production technology or information technology.
To pursue a successful radical redesign requires four principles:
1. Organize around outcomes, not tasks. The insurance company was originally organized according to tasks, using the classic division of labor. When the company reor- ganized around the outcome, which was customer service, dramatic improvements were made. A customer service representative handled all activities associated with the desired outcome. Although it is not always possible to have one person do everything, jobs can be broadened and handoffs between departments can be minimized. 2. Have the people who do the work process their own information. When bedside or portable information system access is available, nurses can update patient electronic medical records as they are dispensing medications to the patient. By doing so, nurses avoid delaying the record update and also do not “hand off” the information for input by someone else, thus reducing the likelihood of inadvertent errors. This principle can be applied in many situations in which information is passed from one department to another. 3. Put the decision point where the work is performed, and build control into the process. It is better to push decision making to the lowest possible level. This will elimi- nate layers of bureaucracy and speed up the decision-making process. In the insurance example, the customer service representative had greater latitude to make decisions di- rectly for the customer rather than referring decisions to other departments. To accomplish this, however, information and controls must be built into the process itself. 4. Eliminate unnecessary steps in the process. Simplifying the processes frequently means that unnecessary steps and paperwork are eliminated. Every step is examined by using the flowcharting techniques discussed earlier, and only those that add value for the customer should be retained. Process redesign can be used to streamline and implify work flows.
Process redesign is just one of many methods that can be used to improve operations. It uses a process view of the organization as a way of improving process flows. As a result of process redesign, processes will be simplified, process flows improved, and non-value- added work eliminated.
6.8 KEY POINTS AND TERMS
This chapter has emphasized process-flow analysis by building on the ideas of systems, measurement, flowcharting, analytics and process redesign. The key points are:
∙ A prerequisite to process-flow analysis is definition of the system to be analyzed. Sys- tems definition requires isolation of the system of interest from its environment by defining a boundary, customers, outputs, inputs, suppliers, and process flows.
∙ The process view is the idea that a business is a set of horizontal processes that are interconnected with the objective of meeting customer needs.
∙ Process flowcharting creates a pictorial description of a transformation process. The aim is to create flowcharts, or visual diagrams of a transformation process, that are easy to understand by people who may not be familiar with the underlying transformation process.
∙ Process flowcharting can be applied to materials flow, information flow, and customer flow. In manufacturing, a flow-process chart is created to show materials flow. In services, a service blueprint is created to show how customers interact with service providers.
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∙ Process-flow analysis takes the flowchart and the measurements of a transformation process and seeks answers to relevant questions. These questions help highlight oppor- tunities that can be implemented to improve the transformation process.
∙ Process analytics is essential to process improvement. Little’s Law relates inventory to throughput time and flow rate of a stable system. The bottleneck resource determines the capacity of the entire process.
∙ Process redesign is used for changing how a process is carried out. It is often cross- functional in nature and may require a complete overhaul of work methods, flows, and information systems.
Key Terms Process-flow analysis 98 Process thinking 98 System 98 System boundaries 98 Process view of a business 99 Process flowcharting 100 Process mapping 100
Capacity 108 Bottleneck 108 Flow rate 108 Process redesign 110 Business process
reengineering 110 Radical redesign 112
Flow-process charting 100 Service blueprinting 100 Systems flowchart 101 Process ownership 102 Process analytics 106 Little’s Law 107 Throughput time 107
How to Draw a Simple Process Map https://youtu.be/DXuPeDj4TsE
Video 6.41
Little’s Law Worked Problem https://youtu.be/h-1Q-uuuQkQ
Video 6.07
Little’s Law and Lead Time https://youtu.be/JUszeJViSjU
Video 5:07
Business Process Reengineering–Definition https://youtu.be/Wi-BmxkA7YU
Video 3:12
Disney World Queuing and Waiting Time www.mhhe.com/disney
Video 9:26
LEARNING ENRICHMENT (for self-study or instructor assignments)
SOLVED PROBLEMS
1. A ticket line for a Minnesota Vikings football game has an average of 100 fans waiting to buy tickets and an average flow rate of 5 fans per minute. What is the average time that a ticket buyer can expect to wait in line?
Using Little’s Law I = T × R, solve for T:
T = I ÷ R = 100 ÷ 5 = 20
A ticket buyer can expect to spend an average of 20 minutes in line. 2. Joe’s commercial laundry has contracts to wash bedsheets for hotels. Joe intakes each
batch of sheets, which takes 1 minute, and then the sheets are washed, taking 20 minutes, and dried, taking 30 minutes. The batch of sheets is ironed, taking 10 minutes for one
Problem
Solution
Problem
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114 Part Two Process Design
employee to complete each batch, and there are two employees ironing sheets. Finally, Joe packages the sheets and bills the customer, taking 2 minutes. Joe has five washing machines and seven dryers that can process one batch of sheets each.
a. What is the capacity of the laundry system, and what is the bottleneck? b. What is the average throughput time of a batch of sheets? c. If the flow rate is 10 batches per hour, what is the average number of batches of
sheets in the system (inventory)?
a. The capacity of each resource is as follows: ∙ Joe takes 3 minutes for each batch and can thus handle 20 batches per hour.
∙ Ironing takes 10 minutes, and so each employee can handle 6 batches per hour and the total capacity for two employees is 12 batches per hour.
∙ Washing machines take 20 minutes per batch or three loads per hour for each machine, and there are five machines, for a total capacity of 15 batches per hour.
∙ Dryers take 30 minutes per batch or two loads per hour from each machine × seven machines for a capacity of 14 batches per hour.
The most constraining (minimum capacity) resource is the ironing, and so the system capacity is 12 batches per hour and ironing is the bottleneck.
b. The average throughput time (assuming no waiting time) of the system for each batch of sheets is:
T = 1 + 20 + 30 + 10 + 2 = 63 minutes
c. I = T × R = (63 ÷ 60) × 10 = 10.5 batches (note that the 63 minutes must be con- verted to hours using 60 minutes in an hour).
3. A restaurant has 30 tables. When the guests arrive, the manager seats them, servers serve them, and the cashier assists them when they pay the bill. The process is shown with processing times above the process steps and waiting times that occur between operations below the steps. One manager, one cashier, and four servers are available.
Solution
Problem
Oper. time Manager 1 minute
Server 2 minutes
Server 3 minutes
Server 4 minutes
Server 1 minute
Cashier 2 minutes
Find table Serve drinks
& order food
Serve food Bring check Pay cashier
Time between Oper. (minutes)
5 510 20 30
Bring menu &
order drinks
a. What is the capacity of the system and the bottleneck resource? b. What is the throughput time for each customer? c. If there are 20 arrivals per hour, what is the average number of tables filled?
a. The capacity of each resource is as follows: ∙ The manager takes 1 minute each and can handle 60 customers (or tables) per hour. ∙ The cashier takes 2 minutes each and can handle 30 customers per hour. ∙ Each server takes 10 minutes per table and can handle 6 tables per hour. There are
four servers, and so the total capacity for servers is 24 tables per hour. ∙ There are 30 tables available.
Solution
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Chapter 6 Process-Flow Analysis 115
The resource with the minimum capacity is the servers, and so the system capacity is 24 tables per hour and the bottleneck is the servers.
b. The throughput time (including both processing time and waiting time) of the system for each customer is
1 + 2 + 3 + 4 + 1 + 2 + 5 + 10 + 20 + 30 + 5 = 83 minutes
c. If there are 20 arrivals per hour, there will be an average of
I = T × R = (83 ÷ 60) × 20 = 27.7 tables being used
Ship checks to the check
clearinghouse
Sort checks by bank
Receive checks
Discussion Questions 1. In the following operations, isolate a system for analysis
and define customers, services produced, suppliers, and the primary process flows.
a. A college b. A fast-food restaurant c. A library 2. Explain how the process view of an organization is
likely to uncover the need for greater cross-functional cooperation.
3. Explain Little’s Law in your own words. How can it be used, and what are its limitations?
4. Provide a definition of a bottleneck. Why is it important to find the bottleneck?
5. Explain the differences between capacity, flow rate, and demand.
6. What kinds of problems are presented by the redesign of existing processes that are not encountered in the design of a new process?
7. Why is it important to define the system of interest before embarking on improvement? Give three reasons.
8. Find examples of flowcharts and study their details. Describe how the flowcharts might be used to make improvements.
9. Describe service blueprinting in your own words, including examples of when it should be used.
Problems 1. In a company that processes insurance claims, the aver-
age flow rate is 10 claims per hour and the average throughput time is 6 hours.
a. How many claims are in the system on average? b. If the demand for claims to be processed is seven per
hour and the capacity is eight per hour, what is the flow rate?
c. What assumptions have you made in your answers? 2. Suppose a bank clears checks drawn on customers’
checking accounts by using the following process:
c. What could be done to decrease the throughput time?
3. The Stylish Hair Salon has three stylists who provide services to women. After checking in with the recep- tionist, which takes an average of 1 minute, the custom- er’s hair is washed, dried, and styled, taking an average of 25 minutes. The payment takes 3 minutes and is also performed by the receptionist.
a. What is the capacity of the process, and what is the bottleneck?
b. What is the average throughput time? If the aver- age flow rate is five customers per hour, what is the average number of customers in the system?
c. If the input to the system is random, what will hap- pen as the flow rate approaches the capacity of the system?
4. Judy’s Cake Shop makes fresh cakes to customer orders. After receiving the order by Judy’s assistant, which takes 2 minutes, Judy then takes 8 minutes to mix the ingredients for the cake and loads a cake pan for baking. Then the cake is put into the oven for 30 minutes. The oven can hold three cakes at one time.
a. If the capacity for receiving checks is 1000 checks per hour, for sorting checks is 800 checks per hour, and for shipping checks is 1200 per hour, what is the capacity of the system to process checks?
b. If the flow rate is an average of 600 checks per hour and there are an average of 200 checks in the sys- tem, what is the average throughput time of checks?
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116 Part Two Process Design
When the cake is taken out of the oven, it is cooled for 1 hour. The assistant then takes 2 minutes to pack the cake for pickup and bills the customer, which takes 3 minutes.
a. What is the capacity of the process, and what is the bottleneck?
b. What is the throughput time for a typical cake? c. If on average five orders are taken per hour, how
many cakes are there in the process (on average)? 5. The Swanky Hotel provides room service for its guests.
The process for room service begins with a room ser- vice manager who takes orders by phone at an average of 2 minutes per order. The manager then sends the order to the kitchen, where it takes a cook an average of 16 minutes to prepare the food for each order. There are four cooks in the kitchen. If the customer orders a beverage, the room service manager sends the order to the bar at the same time the order is sent to the kitchen. It takes 3 minutes for a bartender to fill the order, and 80 percent of the orders require a beverage. When the kitchen and bar orders are both ready, a waiter takes them to the room and bills the guest. There are six waiters to provide the service, and each order takes 20 minutes for the waiter to complete.
a. What is the capacity of the process, and what is the bottleneck?
b. What is the throughput time of a typical order? c. Assume that on Friday evenings an average of
10 room-service orders per hour are placed. How many orders are in the system on average on Friday nights?
d. Assume the following pay rates for the employees. Waiters are paid $9 per hour (not including tips), cooks are paid $15 per hour, the bartender is paid $10 per hour, and the room service manager is paid $18 per hour. Also, assume that 60 percent overhead is added to direct labor and that the cost of food and beverages averages $6 per order.
Setup Time, Minutes
Run Time per Piece, Minutes
Capacity, Pieces per Hour
Wood cutting 30 5 15
Make four legs 60 10 10
Make tops 60 12 8
Finish the wood 20 8 12
Assemble and ship 20 17 14
∙ What is the average cost of an order when oper- ating at 10 orders per hour?
∙ What is the minimum cost per order that the sys- tem can achieve?
e. What assumptions have you made in these calcula- tions that may not be reasonable?
6. A furniture factory makes two types of wooden tables, large and small. See the flowchart below.
Small tables are made in batches of 100, and large tables are made in batches of 50. A batch includes a fixed setup time for the entire batch at each process step and a run time for each piece in the batch. Both large and small tables have the same processing times. The capacities of each process step are given, and apply to production of either type of table, as shown in the flowchart.
a. What is the capacity of the system, and what is the bottleneck?
b. What are the throughput times for batches of large and small tables?
c. When producing at a rate of six small tables per hour on average, how many tables will be in the system?
7. Draw a flowchart of the following processes: a. The procedure used to pay your bills b. College registration c. Checking out a book from the library
Make tops
Make legs
Finish furniture
Assemble and shipCut wood
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Chapter 6 Process-Flow Analysis 117
8. Review your answers in problem 7 to be sure that you are correctly using the flowchart symbols described in this chapter.
9. Use the key questions of what, who, where, when, and how for problem 7 to suggest improvements in the processes.
10. Using the correct symbols, draw a flowchart of the fol- lowing processes:
a. Preparing yourself for a job interview b. Going to the library to study and returning to your room
11. Use the what, who, where, when, and how questions to make improvements in problem 10.
12. Draw a service blueprint for the following: a. Pizza delivery b. Automobile repair 13. Analyze the service blueprints in problem 12 for pos-
sible improvements. Use the flow, time, quantity, qual- ity, and cost questions.
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Lean is a way to reduce waste and non-value-added activities in organizational processes. For example, most emergency departments in hospitals are not lean. The average patient spends three hours in the emergency department even for a relatively minor medical visit. Non-value-added activities for patients such as waiting for a blood test, then waiting for an x-ray, then waiting for a nurse, and finally waiting for a doctor accumulate to more than two hours of waiting time for a three-hour visit. Less than one hour of the visit adds value for the patient. Lean concepts and principles can improve the flow of patients and take out much of the non-value-added waiting times.
Lean thinking and lean systems are applied in a wide variety of industries and settings. They are used to improve operations processes in manufacturing and services. Lean ideas
Lean Thinking and Lean Systems
c h a p t e r 7
LO7.1 Describe the origins and evolution of lean thinking.
LO7.2 Describe the five tenets of lean thinking and the seven forms of waste in a lean system.
LO7.3 Explain why a stabilized master schedule is required for smooth flow.
LO7.4 Explain how setup time, lot size, layout, and maintenance are related to lean thinking.
LO7.5 Differentiate how employees are unique in lean systems.
LO7.6 Design a kanban system to achieve customer pull.
LO7.7 Compare lean suppliers to traditional manufacturing suppliers.
LO7.8 Explain how to implement a lean system.
After reading this chapter, you should be able to:LEARNING OBJECTIVES
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are also used to improve processes outside of operations, including software development and maintenance, annual budgeting, and even for collecting on delinquent accounts! What is lean and how do firms use lean ideas to improve their business?
In this chapter we introduce the lean concepts, principles, and techniques that organiza- tions adopt for performance improvement. These concepts, principles, and techniques can be deployed to reform not only manufacturing systems but also administrative systems, service systems, and entire supply chains. We begin by looking at the evolution of lean before presenting lean thinking as a set of five tenets.
7.1 EVOLUTION OF LEAN
After World War II the U.S. system of mass production was the envy of the world. Mass production—the production of standardized discrete products in high volume—was the norm. Materials were produced in large batches, and machines were made to run faster to reduce unit costs. In some cases this resulted in sacrificing quality in the name of effi- ciency and creating narrow jobs that led to worker dissatisfaction, but still the world bought products manufactured in the U.S.
In the 1960s a “Japanese miracle” started at the Toyota manufacturing company. After visiting U.S. manufacturing companies, Toyota determined that it could not copy their sys- tem of mass production. Not only was demand for Toyota automobiles low at that time, there was a severe lack of resources. Because of the lack of resources, Toyota developed a strong aversion to waste. Scrap and rework were deemed wasteful, and so was inventory that tied up storage space and valuable resources. Toyota realized that it needed to produce automobiles in much smaller batches, with much lower inventory, using simple but high- quality processes and involving workers as much as possible. This realization became the foundation for what is known today as the Toyota Production System (TPS) and Just-In- Time (JIT) manufacturing. This production system is now used around the world. See the Operations Leader box titled “TPS at the Toyota Plant in Georgetown, Kentucky, USA.”
JIT manufacturing first came to the U.S. in 1981 at the Kawasaki motorcycle plant in Nebraska, which used some of the TPS ideas. However, instead of transforming the entire system, JIT manufacturing focused primarily on inventory reduction but ignored other aspects of Toyota’s complete system. As a result, many U.S. companies that attempted to copy the TPS ideas achieved only partial improvement.
In 1990 Womack, Jones, and Roos studied JIT auto- mobile manufacturing in Japan, the U.S., and Europe and popularized the term lean production in their famous book The Machine That Changed the World: The Story of Lean Production. Lean production was defined as sys- tematically eliminating waste in all production processes by providing exactly what the customer needs and no more. They reported that the best plants using lean pro- duction had a big edge in automobile assembly perfor- mance anywhere in the world. Labor productivity in the best plants exceeded that in the worst plants in all three regions by a factor of 2 to 1, defects were reduced by half, and inventory was reduced from two weeks’ worth to only enough to maintain production for two hours. The best U.S.-owned plants, indeed, had labor produc- tivity (vehicle assembly hours) and quality comparable
LO7.1 Describe the origins and evolution of lean thinking.
Lean thinking can be applied in hospital emergency rooms to speed patient treatment. Paul Bradbury/Getty Images
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120 Part Two Process Design
to the best Japanese-owned plants in the U.S., while European plants lagged behind. This showed that the best U.S. plants could adopt the TPS and compete with Japanese plants, but average U.S. plants were still far behind, particularly behind plants located in Japan.
Today, the concepts, principles, and techniques that encompass lean production are often referred to as lean thinking and are being deployed across a broad spectrum of global firms, including 3M, Black & Decker, Deere & Company, Delta Airlines, Ford, General Electric, Hewlett-Packard, IBM, Starbucks, Taco Bell, United Health Care, and Wells Fargo. In virtually all instances, benefits such as increased inventory turnover (50 to 100 times per year), superior quality, greatly reduced customer waiting time, and substan- tial costs savings (15 to 20 percent) have been reported.
7.2 LEAN TENETS
Lean thinking, as the name signals, is a way of thinking about processes at work in all types of organizations. Lean thinking is built around five tenets that subsume specific con- cepts, principles, and techniques. The five tenets guide organizations in delivering value to customers efficiently.
The first tenet in lean thinking is to specify precisely what about a product or service cre- ates value from the customer’s perspective. Value is defined by the customer and provided in the product or service the customer needs at a place, time, and price the customer is willing to pay. Value is not what the firm thinks but what the customer says, the “voice of
LO7.2 Describe the five tenets of lean thinking and the seven forms of waste in a lean system.
Create Value
frequently, allowing TMMK to hold inside its facility, on average, enough inventory to last for just four hours of production.
Source: A. Harris, “Automotive Special Report—Made in the USA,” Manufacturing Engineer 86, no. 1 (2007), pp. 14–19 www.toyotaky.com, 2019.
Toyota Motor Manufacturing Kentucky, Inc. (TMMK), is Toyota’s flagship manufacturing facility in the United States, currently producing 550,000 vehicles annually. Established in 1986, TMMK occupies 1,300 acres in Georgetown, Kentucky, is over 8.1 million square feet in size, and employs 8,000 workers to build the Camry, Avalon, and Lexus models.
At TMMK, employees are trained not only in required job skills but also in problem-solving and continuous improvement methods. Job tasks have been standard- ized to minimize waste and assure quality. Employees can stop and are strongly encouraged to stop the pro- duction line when a quality problem is detected. Employ- ees are, moreover, actively involved in suggesting ways to improve their work and work environments, with an astounding 100,000 suggestions on average per year.
Toyota has done more than transfer the Toyota Pro- duction System (TPS) to TMMK. Realizing that the perfor- mance of TMMK depends on its suppliers, it has worked aggressively to help its 350 U.S.-based suppliers to implement the TPS. TMMK created the Toyota Supplier Support Center in Erlanger, Kentucky, to provide con- sulting services to suppliers. Suppliers deliver to TMMK
TPS at the Toyota Plant in Georgetown, Kentucky, USA
OPERATIONS LEADER
Walter Cicchetti/123RF
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the customer.” Value is often a solution to a problem a customer is facing or improvements in the quality of life that the customer is willing to pay for. Value, as such, is dynamic in nature and changes over time as customer preferences change. Firms should design and deliver product and service features that customers value and stop doing activities that are not valued by customers (unless required for other reasons, for example, legal). This may mean removing unvalued product features or reducing waiting times in service systems.
Waste, in lean thinking, is anything that does not contribute value to the product or service being produced and delivered to the customer; waste adds costs that are greater than the customer-perceived value. The Japanese term for waste is muda. In many manu- facturing, administrative, and service processes only 5 to 10 percent of total throughput time adds value for the customer. Firms want to eliminate obvious waste, but many forms of waste are hidden. For example, the value-added time to produce a product may be only three hours, but it takes a week to complete it. The muda or non-value-adding time might include waiting for machines or labor to become available, dealing with backlogs, search- ing for materials, or correcting processing errors.
Table 7.1 defines the seven forms of waste originally identified by Taiichi Ohno, Toyota’s former chief engineer, who is considered the father of the TPS. Womack and Jones in their book, Lean Thinking, introduced an eighth form of waste: underutilization of workers. This stems from not recognizing, developing, and utilizing the mental, creative, and physical abilities of employees. Contributing to this waste are factors such as poor hiring and training practices, high employee turnover, and an organization culture that does not respect people.
The second tenet in lean thinking is to identify, study, and improve the value stream of the process for each product or service. The value stream identifies all the processing steps and tasks undertaken to complete a product or deliver a service from beginning to end. A typical value stream thus can include both value-added and non-value-added processing steps and tasks. The goal in studying the value stream is to eliminate the non-value-adding processing steps and tasks.
One technique supporting this tenet is value stream mapping, which creates a visual representation of the value stream of a process, much like process flowcharting. Value stream mapping requires direct observation of work and the flow of work within a process so that opportunities for improvement can be identified. The Japanese refer to such direct observation of work as gemba.1 Using a gemba approach, the analyst walks through the
Value Stream
1 A Japanese term meaning “the real place.”
TABLE 7.1 The Seven Forms of Waste Source: Adapted from Taiichi Ohno, Toyota Production System: Beyond Large-Scale Production (New York: Productivity Press, 1988).
• Overproduction: Producing more than the demand of customers, resulting in unnecessary inventory, handling, paperwork, and warehouse space.
• Waiting time: Operators and machines waiting for parts or work to arrive from suppliers or other operations; customers waiting in line.
• Unnecessary transportation: Double or triple movement of materials due to poor layouts, lack of coordination, and poor workplace organization.
• Excess processing: Poor design or inadequate maintenance of processes, requiring additional labor or machine time.
• Too much inventory: Excess inventory due to large lot sizes, obsolete items, poor forecasts, or improper production planning.
• Unnecessary motion: Wasted movements of people or extra walking to get materials. • Defects: Use of material, labor, and capacity for production of defects, sorting out bad parts, or
warranty costs with customers.
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122 Part Two Process Design
entire process from start to finish while observing and documenting each step where the work is actually happening. The resulting value stream map shows the beginning and end- ing points of the process, the steps and tasks between those points, and relevant perfor- mance information about the process. Figure 7.1 is a simplified value stream map showing how patients flow through a clinic. Improvements to the process come from studying the value stream map and then asking and answering the question, “Is this step or task neces- sary in creating value for the customer?” Processing steps and tasks that are not neces- sary or are non-value-adding, such as the numerous waiting times in the figure, should be reduced or removed to improve performance and ultimately enhance value in the product or service provided to the customer. In Figure 7.1 the total throughput time is 160 minutes, but 120 minutes of it is waiting time. Much of the waiting time (non-value-added) can, no doubt, be eliminated by revising the process.
The third tenet in lean thinking is to ensure that flow within a process is simple, smooth, and error-free, thereby avoiding waste. To appreciate this tenet, look at Figure 7.2, where production is viewed as a stream and the water level as the inventory of raw materials, work-in-progress, and finished goods. At the bottom of the stream are rocks, which rep- resent problems related to quality, suppliers, delivery, machine breakdowns, and so forth. The traditional approach is to hold inventory high enough to cover up the rocks (problems) and thus keep the stream flowing. Lean thinking calls for the opposite: lowering the water (inventory) level to expose the rocks (problems). When the rocks have been pulverized (i.e., the problems have been solved), the water is lowered again to expose more rocks. This sequence is iterated until all rocks are turned into pebbles and the stream (production sys- tem) flows smoothly and simply at the true market demand rate while only needing a low
Ensure Flow
FIGURE 7.1 Health care value stream map. Source: Adapted from Bushell, Mobley & Shelest, “Discovering Lean Thinking at Progressive Health Care,” Journal of Quality & Participation 25, no. 2, pp. 161–191.
Information Flow
Patient OutPatient In
Pharmacy
120 minutes
40 minutes
160 minutes
Visit Doctor Blood Test
Visit PrepCheck-in
Wait Time
Processing Time
Total Throughput
Time
15 minutes
Wait Wait Wait Wait
40 minutes 20 minutes 45 minutes
5 minutes
Check-in
8 minutes
Visit Prep
16 minutes 11 minutes
Visit Doctor Pharmacy, Blood Test
Doctor Visit
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level of inventory at any given time. Inventory in this analogy is a form of waste that hides problems that contribute to other forms of waste besides inventory.
The idea of simple, smooth, and error-free flow means that production flows are sim- ple and direct, and do not change from one production run or one customer to another. To accomplish this, small batches will be needed to match market demand, rather than building up inventory with large batches of production. Such predictable flows ensure that the exact appropriate resources, including labor and equipment, can be devoted to each production step. It also means that workers should understand the connection of their own work to work performed upstream (before them in the production process) as well as work that follows their own. These direct and unambiguous links in the pro- cess provide complete certainty about exactly who has performed what work within the process. As a result, workers themselves are actively engaged in controlling the smooth and error-free flow of production. This is done by simply limiting the inventory buildup between operations, limiting defective products and keeping the flow of production mov- ing. As mentioned earlier, problems are exposed—not hidden and covered by inventory. The problems are fixed by the production workers themselves who keep the flow moving. There are many techniques used to accomplish smooth production flow. They are covered later in the chapter.
The goal of ensuring simple, smooth, error-free flow can be extended up the supply chain to suppliers. They need to fill orders just-in-time to meet production schedules of the customer. This means that suppliers may have to deliver goods to factories on a daily basis or perhaps multiple times within a day. Ultimately, suppliers will also have to convert to lean operations in their factories to produce products in small batches only when needed and when pulled by the customer’s manufacturing plant.
In service operations smooth and error-free flow is achieved by reducing waiting time for customers and providing exactly what the customer needs. Customers should flow from one stage to the next in a service encounter. Value stream mapping is used to reduce or eliminate waiting time. In a similar way to manufacturing, service employees should be in charge of ensuring quality outcomes for customers and smooth flow as the service is delivered in a timely manner.
The fourth tenet in lean thinking is to produce only what is pulled by the customer. Com- plying with this tenet requires replacing the push system typical in traditional mass pro- duction with the pull system of lean production. A push system aims to produce goods or
Customer Pull
FIGURE 7.2 Simple, smooth, and nonwasteful flow: A stream analogy.
Water flows smoothly (once problems are solved)
W at
er le
ve l
Prob
Prob
Problems
Problems
W at
er le
ve l
Original situation (inventory covers problems)
Prob Problems
Water level lowered (problems are exposed)
W at
er le
ve l
Problems
Prob
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124 Part Two Process Design
ensure delivery of services well in advance of demand, often according to a schedule or plan created from potentially inaccurate forecasts. Large batches of materials are pushed from one process or machine to the next regardless of whether the inventory is needed. This allows machines and processes to be utilized at full capacity, but builds up excess inventory. See Figure 7.3 for an illustration of push vs. pull systems.
A pull system, on the contrary, waits for the downstream process customer to signal a need for a good or service before producing it to fulfill that need. The signal from the customer is then sent visually upstream in the various stages of production—and even the supply chain—to signal what and when production and delivery are needed. No upstream process is authorized to produce a good or service until a downstream customer asks for it, thus minimizing inventory throughout the production system. An example of a push system is the “hub and spoke” system used by many of the major airlines. Flying point- to-point by some airlines is a pull system based on what the customer wants. No customer wants to connect through a hub to get to their destination but the system is designed this way for airline efficiency. However, by flying point-to-point Southwest Airlines developed a pull system approach that revolutionized the airline industry.
The fifth tenet in lean thinking is to strive for perfection. Striving for perfection requires continuous improvement of all processes as well as radical redesign when necessary. When continuous improvement is undertaken, more value is provided by the firm in its quest for ultimate perfection for the customer. The definition of perfection used here is an afford- able good or service, delivered rapidly and on time, that meets the needs of the customer. When customer needs change, the definition of value changes and so does the definition of what constitutes perfection. There is, therefore, no end to the improvements that can be sought and made.
In lean thinking, the process changes necessary in seeking perfection must be made using scientific methods, including designing experiments and testing hypotheses. Employ- ees are discouraged from changing a process based on intuition alone. Rather, lean thinking promotes decision making based on scientifically derived evidence.
Quality is absolutely essential in a lean production system, because defective goods or services are a major form of waste. Internally, wasted parts and labor add unneces- sary costs, while externally, poor quality does not meet customer expectations of value. But a lean system does not create quality. Quality must be an input into a lean system for processes to create value for the customer, as needed to fulfill the first lean tenet and sub- sequent tenets.
Strive for Perfection
FIGURE 7.3 Push vs. pull system illustration. Source: https://www.panview .nl/lean-productie-theorie/ het-pull-principe-productie- op-kantoor-het-leven
PULL
PUSH
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Defective goods and services are clearly waste. More importantly, they can bring the production process to a halt since workers often inspect their own work and do not pass defects on to the next work center. In a lean system, quality problems rapidly gain atten- tion as the production line or service process stops when problems occur. For example, in fast-food restaurants, if the food is not at the required temperature, it cannot be delivered to customers and may cause a backup at the drive-through window. Now customers must wait longer for food, and the value of the food and service declines.
A lean production system is designed to expose errors and get them corrected at their source rather than covering them up with inventory or other means. To cover a quality, or maintenance, or worker training problem with inventory means to use excess inventory to keep a production process moving when it should be stopped and fixed. The excess inventory is waste and prevents quality problems from being quickly detected by the next process. Because a lean system does not have excess inventory to cover up mistakes, striv- ing for perfection is required. When the lean tenets and techniques are used consistently, continuous improvement moves the process toward perfection.
One simple and relatively powerful technique used to strive for perfection is the 5 Whys technique. This problem-solving technique systematically explores the cause-and-effect relationships that underlie an observed problem (e.g., a product defect or late delivery). By asking why at least five times, this technique is used to deliver insights into the root cause of an observed problem so that proper corrective action can be taken to prevent the root cause from re-creating the observed problem. Here is an example: A defective part is produced. Why? The machine is out of tolerance. Why? The machine was not adjusted properly. Why? The operator was not trained. Why? Standard procedures were not followed by the supervisor for training a new operator. Why? The supervisor was too busy solving other problems. Once the root cause is discovered the problem can be fixed, hopefully per- manently for all operators and supervisors.
Another well-known technique supporting lean thinking is 5S. This is a technique for organizing a workspace (e.g., production shop floor, office space, hospital station, tool shop) to improve employee morale, environmental safety, and process efficiency. The name of this technique comes from five Japanese terms, all of which when transliterated and translated begin with the letter S. These terms are defined in Table 7.2. Underlying the 5S technique is the belief that when a workspace is well organized, time will not be wasted looking for “things” (e.g., a tool or paperwork); misplaced items also will be read- ily noticed. By having employees decide which items should be kept where as well as how they should be stored, 5S can instill in employees a sense of ownership, help standardize work, assure a safe work environment, and keep processes from becoming overly complex. See the Operations Leader box titled “5S + Safety = 6S!”
TABLE 7.2 5S: Japanese terms and English translations
Term Translation Meaning
Seiri To sort Decide what things to keep and what things to discard so that only the essential things remain.
Seiton To straighten or set in order
Arrange essential things in a manner that supports an efficient flow of work.
Seiso To shine, sweep, or clean
Assure cleanliness by returning things to their storage locations and removing things that do not belong.
Seiketsu To standardize Standardize work and adopt seiri-seiton-seiso throughout so that all employees know what their responsibilities are.
Shitsuke To sustain Maintain seiri-seiton-seiso-seikutsu as a habit of work and a way to operate.
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126 Part Two Process Design
7.3 ENSURE FLOW
As you can see, the five tenets of lean thinking have many techniques and concepts associ- ated with them. We have already covered a fair amount of detail on all tenets except tenet 3 (ensure flow) and tenet 4 (customer pull). In the remainder of this chapter we focus on these remaining two tenets to provide more detail and techniques on how they are actually implemented in manufacturing and service settings.
The third tenet of lean is to ensure smooth and error-free flow by avoiding all of the seven wastes and non-value-adding activities. Among others, this includes waste in over- production, excess inventory, unnecessary transportation, and defects. This is a complex tenet and requires several techniques, principles, and concepts. To ensure smooth flow requires changes from traditional production in four ways: a stabilized master schedule, reducing setup time and lot sizes, changing layout and maintenance, and cross-training and engaging workers. These four changes and how they are related to ensure flow are described next.
restocked as needed. “A helpful rule of thumb is that anyone should be able to find any item in 30 seconds or less.”
The sixth S for safety is integrated with standard 5S methods. To promote safe use and storage of chemi- cals, 6S training helps businesses develop appropri- ate visual warnings in areas near chemicals, and clear the space around storage cabinets to avoid tripping hazards.
Lean concepts like 5S, as seen in this example, can be customized to the particular needs of an organi- zation or situation. Safety is integrated here with 5S, a logical connection when hazardous chemicals are being used.
Source: Adapted, with photos, from www.epa.gov, 2020.
The U.S. Environmental Protection Agency provides train- ing materials to businesses for safe storage of hazardous chemicals, calling the program 6S, for 5S + Safety. The training uses standard 5S methods on removing unused chemicals that are lingering in storage areas, decentral- izing chemicals by moving them to where they are used in work processes, and organizing and labeling storage areas so that the chemicals are easy to find and their absence is easily noticed. As a result, errors in using the wrong chemical are minimized.
The photos show an example from one manufactur- ing plant where, before 5S activities were conducted, chemicals were disorganized and difficult to locate. Following 5S, the storage cabinet contains only chemi- cals that are needed nearby, in quantities that last only a few days, and labeled shelves can be easily
5S + Safety = 6S!
OPERATIONS LEADER
Before After Source: The Lean & Chemicals Toolkit/U.S. Environmental Protection Agency
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One of the ways that firms can move toward achieving the lean tenet of simple, smooth, and error-free flow is to level the amount of work that is performed each day. For a service, this might mean scheduling a certain number of customers each day or using methods such as advertising or pricing to even out the number of customers who want the service each day. This practice is referred to as stabilizing the master schedule. Although this termi- nology is generally not used in services, the concept still applies. The process of produc- tion planning for manufacturing starts with a long-range production plan, which then is broken down into annual, monthly, and daily plans.
Master scheduling for products is done to achieve a uniform load, the assignment of approximately equal amounts of work to each machine or worker. Assume that one month of production is scheduled in advance. Also assume that the monthly schedule calls for 10,000 units of product A, 5000 units of product B, and 5000 units of product C. If there are 20 days of production in the month, the daily schedule will call for 1/20 of each model produced in each day: 500A, 250B, and 250C. Furthermore, the individual units will be mixed as they go down the production line. The sequence will be /AABC/AABC/AABC/. Note how two units of A are produced for every unit of B and C. Due to long changeover (or setup) times in traditional manufacturing, large batches of final product are scheduled to avoid changing the production process from one product to another. In traditional pro- duction with long changeover times, products A, B, and C might each be scheduled in weekly batches sizes of 2500 units of A, 1250 units of B and 1250 units of C, assuming one-fourth of monthly production is made before changing over.
Matching supply to demand is illustrated by the concept of takt time. Takt is the German word for the baton that an orchestra director uses to regulate the speed of the music. In lean production systems takt time is the time between successive units of production; this represents the speed of output. For example, a takt time of 2 minutes means that one unit is completed every 2 minutes, or 30 units are produced in an hour (60/2). In lean production systems the takt time of production should be set equal to the average demand rate of the market to match production with demand and thus mini- mize inventories.
To establish the beat of the market, takt time can be computed by dividing the time available for production (being sure to subtract for nonproductive time such as holidays and lunch breaks) by the demand over the same period. For example, if market demand is 1000 units of a product per day and there are 7 hours of production time available in the day (or 420 minutes), the takt time is then (420 ÷ 1000) = 0.42 minute per unit. So, given the available production time, production of one unit will have to be completed every 0.42 minute (about 25 seconds) to meet market demand. Producing at rates less than the takt time will result in shortages in meeting the demand, and producing at rates greater than takt time will result in building up inventory. The idea of takt time is to produce at a constant rate that equals average demand of the market.
The objective of the lean production system is to produce the right quantity each day— no more and no less. This minimizes finished-goods inventory since the production output is closely matched to demand. This also helps reduce work-in-process and raw-materials inventories, since stabilizing the master schedule provides nearly constant demands on all work centers and outside suppliers. Contrast this with traditional mass-production pro- cesses in which lot sizes are large, and are not matched to market demand, resulting in large inventories of finished goods, work in process, and raw materials.
To achieve a uniform daily master schedule and smooth flow requires small lot sizes throughout each step of the production process. The lots produced are much smaller than traditional manufacturing, which has long setup times between lots. Setup time is the
Stabilize Master Schedule
LO 7.3 Explain why a stabilized master schedule is required for smooth flow.
Reducing Setup Time and Lot Sizes
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128 Part Two Process Design
nonproductive time when machines are being adjusted before beginning work on a new batch of parts. In a service setting, it might include readying a customer for service, for example, guiding a customer from the waiting room to an exam chair, and adjusting the chair position for a dental exam.
Reducing setup time, also referred to as changeover, is the key to small lot sizes. Shorter setup times allow manufacturing and service processes to more closely match the rate of demand. Then, the takt time can represent both the demand rate and the production rate.
Traditional manufacturing managers have focused on reducing production run times per unit and gave too little attention to setup times. When long runs of thousands of units are anticipated, run times naturally are more important than setup times. Since setup time has received so little attention, phenomenal reductions are possible. For example, at General Motors the time required to change a die in a large punch press was reduced from six hours to 18 minutes. This allowed dramatic reductions in inventory at this work center from $1 million to $100,000, and much smaller lot sizes. Hospitals focus on surgical suite turnaround, or setup time between one patient departing and the next patient’s surgery beginning. Some hospitals using lean concepts report as much as 30-minute reductions in turnaround, reducing this non-value added time, and essentially increasing capacity for surgeries.
Single setups, sought in many companies, refer to setup times that are completed in single digit minutes—less than 10 minutes per setup. This is often referred to as SMED (single minute exchange of die). These low setup times can be achieved by designing a two- step setup process. First, external and internal setups are separated. Internal setup refers to actions that require the machine to be stopped, whereas an external setup is preparation that can be done while the machine is operating. The external setup is analogous to the on- deck batter in baseball; the player is warmed up and ready to move into position as soon as the prior batter is finished. After internal and external setups are separated, as much of the setup as possible is converted from internal to external. This is done, for example, by using two sets of dies, one inside the machine and one outside; having quick change adjust- ments; and employing cleverly designed tools and fixtures. Once the machine is stopped, it can be quickly readied for a new product since internal setup has been minimized. Much improvement in setup time can be accomplished once people realize the importance of it
in stabilizing the master schedule and producing only what is pulled by the next process.
Workers can practice setups to reduce the time. For example, hospital personnel practice moving patients from the emergency room to surgery so they can resolve (before a real patient arrives) problems such as slow elevators that might cause a delay. A good example of quick changeover comes from the racetrack. Race cars are quickly fueled, tires are changed, and the windshield is washed in short pit stops, the racing equivalent of a setup, by highly coordinated and trained pit crews using specialized tools and equipment. Southwest Airlines is renowned for its quick turnaround (setup) times with its planes, utilizing the techniques discussed here. Much of its success has been attributed to its ability to keep planes productive in the air while minimizing time spent on the ground.
LO7.4 Explain how setup time, lot size, layout, and maintenance are related to lean thinking.
Pit crews make quick changeovers of race cars in amazingly short times. Source: U.S. Air Force photo by Master Sgt Michael A. Kaplan
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Ensuring flow (tenet 3) has a natural effect on layout and equipment. The manufacturing or service facility evolves toward a more streamlined flow because lot sizes are reduced, inventory is held close to where it is used, and problems are resolved with standardized solutions so that the problems do not arise again in the future. Moreover, since inventory is typically kept low—only a few hours or days of supply—work spaces can be much smaller because of the reduced storage space needed. One comparison of manufacturing plants showed that lean plants need only one-third of the space of non-lean plants.
The effect of lean thinking on layout in a manufacturing plant is dramatic. In a non- lean layout suppliers deliver to stockrooms and parts are returned to the stockrooms after certain stages of production are completed. In a lean production system all stockrooms have been eliminated as stock is kept on the shop floor very close to where it is used. This eliminates the wasted space of the stockroom and the wasted transportation moving materials in and out of it. Work centers can eventually be organized into a group technol- ogy, or cellular manufacturing, layout. Cellular manufacturing is often arranged in a U-shaped cell, and ensures flow from one machine or task to the next without interrup- tion; see Figure 7.4. Parts (customers in service settings) flow smoothly between machines
and tasks within the cell. Most of the inventory buffers, which are next to each machine, have been eliminated. It is a natural consequence of lean thinking to evolve toward cellular manufacturing.
With a lean production system, preventative main- tenance of equipment is extremely important. This is the regular checking of and caring for equipment, much like oil changes and regular inspection of your own car, so that it does not break down or fail. Since inventories have been cut to minimal levels as workers strictly adhere to the daily plan for production, it is crit- ical to avoid unplanned equipment failures. A lean sys- tem requires the right amounts of capacity, inventory, workers, and everything operating as planned—each and every day. Workers take responsibility for most of their own equipment and workspace maintenance, and
Changing Layout and Maintenance
FIGURE 7.4 Cellular manufacturing in a U-shaped cell. Equipment and workstations are arranged to facilitate a continuous production flow in small lots or single units.
INPUT Components
and Materials
OUTPUT Finished Goods
Station 2Station 1
Station 4Station 5
Station 3
In a lean system, stock is held on the shop floor. SolStock/Getty Images
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130 Part Two Process Design
this gives them more control over their work and work environment. Repairs by mainte- nance personnel are performed between shifts so that it does not disrupt the regular daily work schedule.
A final element in ensuring flow is cross-training and engaging workers who have a much broader set of skills than their counterparts in traditional environments. Cross-training of workers is therefore a critical human resources responsibility. Workers are trained and experienced to operate several machines in a manufacturing setting or perform a variety of tasks in a service setting. In manufacturing, the worker can shut down one work center when there is no work to do there and move to another work center where parts are needed. The worker should be trained for several different work areas to set up machines, do rou- tine maintenance, and inspect the parts. The main benefit of cross-trained workers is that they provide flexibility to the production system. Nurses who can be moved to different hospital units and production workers who can be shifted to different production areas place labor resources just where they are needed at any given time. This reduces the need to have excess labor in specific work areas just in case capacity is needed on short notice.
Moving toward a flexible workforce may require changing the way workers are paid and rewarded. Traditional pay systems are often based on seniority and level of job skills. New pay systems in a lean system reward workers on the basis of the number of different jobs they can perform. This will encourage workers to learn more skills and become more flex- ible. Labor unions often are organized along skill lines, and they do not tend to encourage flexibility in the workforce. As a result, management needs to work closely with unions to develop trusting relationships so they can work together to build the kind of workforce needed for lean systems.
Lean is built on the idea of “respect for people.” It is respect for every person’s ideas, desire to do a better job, and commitment to improve. This is an essential principle of the Toyota Production System that engages employees to accomplish lean objectives. Manag- ers must earn respect by trusting workers and staff to improve the system and encourage them to participate in decision making. Respect also extends to customers and suppli- ers throughout the supply chain. Without an emphasis on “respect for people,” efforts to implement lean systems will fail.
In lean systems, quality teams and suggestion systems are used to actively engage work- ers and engineers in problem-solving activities. Since inventory is not available to cover up problems, an environment of participation, respect, and teamwork must be created to get all employees to contribute individually and collaboratively toward production requirements and problem solving. Lean production systems cannot be implemented without worker understanding and cooperation. Management in all organization functions must ensure that the workers understand their new roles and accept the lean approach.
7.4 CUSTOMER PULL
It is not enough to arrange for smooth flow; the flow must be controlled. Lean thinking in tenet 4 uses a pull system to control the flow of production. Production is only authorized when the downstream work center requires it. A pull system is achieved in manufacturing by kanban.
Kanban is the method of production authorization and materials movement in the lean production system that supports the tenet of producing only what is pulled by the customer. Kanban in the Japanese language means a marker (card, sign, plaque, or other device) used to control the timing and movement of parts through a sequential process. The kanban
Cross-Training and Engaging Workers
LO7.5 Differentiate how employees are unique in lean systems.
LO7.6 Design a kanban system to achieve customer pull.
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system is a simple and visual “parts withdrawal system” involving cards and containers to pull parts from one work center to the next just in time. In services, a kanban system might be used to control inventory levels (by limiting items to fixed-quantity bins), or to pull many types of work such as paperwork, or even the customer, through the process! Since kanbans are mostly associated with manufacturing, we discuss how they are used to pull inventory through a production system.
The purpose of the kanban system is to signal the need for more parts and ensure that those parts are produced just in time to support subsequent work centers. Parts are kept in small containers, and only a specific number of those containers are provided. When all the containers are filled, production is stopped, and no more parts are produced at that work center until the subsequent (receiving) work center provides an empty container. Thus, work-in-process inventory is limited to available containers.
The final assembly schedule is used to pull parts from one work center to the next just in time to support production needs, which are aligned with market demand. Only the final assembly line receives a schedule from the dispatching office, and this schedule is nearly the same from day to day. All machine operators and suppliers receive production orders (kanban cards) from the subsequent (receiving) work centers. If production stops for a time in the receiving work centers, the supplying work centers also stop soon because their parts containers become full since their output is not being pulled by the receiving work centers. The kanban system can be extended to suppliers so that the suppliers also respond (deliver) only when parts are pulled by the factory.
To see how the kanban system works as a physical control system, assume that eight containers are used between work centers A and B (A supplies B) and that each container holds exactly 20 parts. The maximum inventory that can exist between these two work centers is 160 units (8 × 20) since production at work center A will stop when all the con- tainers are filled.
In the normal course of a day, the eight containers might be distributed as shown in Figure 7.5. Three containers filled with parts are located at work center A in the output area. One container is currently being filled by the machine at work center A. One full
FIGURE 7.5 Kanban system.
Input area
Output area
Withdrawal card
In transit
Work center A
Work center B
Input area
Withdrawal kanban post
Production kanban post
Production card
Output area
A B
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container is being moved from A to B, two full contain- ers are sitting in the input area of work center B, and one container is being used at B. These eight containers are needed since work center A also produces parts for other work centers, machines at A may break down, and move times from A to B are not always exactly predictable.
Some companies control the movement of containers by using two types of kanban cards: production cards and withdrawal (move) cards. These cards are used to authorize production and to identify the parts in any container. Instead of using cards, production can also be controlled by kanban squares that visually signal the need for work (to fill the kanban square), or by visual control of the empty containers.
Most importantly, the kanban system is visual in nature. As empty containers accumulate, it is a clear signal that the producing work center is falling behind. When all the containers are filled, production is stopped. The production lot size is exactly equal to one container of parts. All parts are neatly placed in containers of a fixed size. All of these are visual indicators of the work that should be done or stopped.
The number of containers needed to operate a work center is a function of the demand rate, container size, and the lead time for a container. This is illustrated by the following formula:2
n = DT ___ C
where n = total number of containers
D = demand rate of the using work center
C = container size, in number of parts, usually less than 10 percent of daily demand
T = time for a container to complete an entire circuit: filled, wait, moved, used, and returned to be filled again (also called lead time)
2 Safety stock can be added to the numerator to account for uncertainty in demand or time.
KANBAN SQUARE AT HONEYWELL. The dashed rectangle signals the need for the production of a cabinet. Only one cabinet is placed on this square at a time. When the square is emptied by subsequent production, another cabinet is produced. ©Tulasi Ranganathan/Honeywell
Suppose demand at the receiving work center B is 2 parts per minute and a standard con- tainer holds 25 parts. It takes 100 minutes for a container to make a complete circuit from work center A to work center B and back to A again, including all setup, run, move, and wait times. The number of containers needed in this case is:
n = 2(100)
______ 25
= 8
The maximum inventory in the production system, a useful measure of how lean the system is, equal to the container size times the number of containers (200 units = 8 × 25), since the most inventory we can have is all containers filled:
Maximum inventory = nC = DT
Example
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Inventory can be decreased by reducing the size of the containers or the number of con- tainers used. This is done by reducing the lead time, the time required to circulate a container. When any of these times have been reduced, management can remove kanban cards from the system and remove a corresponding number of containers. It is the responsibility of managers and workers in a lean system to reduce inventory by means of a continuous cycle of improve- ment. Reducing lead time by reducing the fill, wait, move, use, or return times is the key.
A complete kanban system can link all work centers in a production facility. It can, moreover, link the production facility to its suppliers. With such a kanban system, all mate- rial is pulled through the production system by the final assembly schedule, using a highly visible shop-floor and supplier control system.
A pull system also works in a service environment where the flow is of customers and information, not materials. When customers are pushed through a system, they tend to wait in lines for services as bottlenecks occur and queues develop. A pull system signals custom- ers to move when they can be served by the next process. Likewise, in offices where paper- work, or electronic information, is being processed from one employee to the next, a pull system will limit the amount of work that can develop between employees. There is no need to continue processing information when the next process does not pull it through. The supplier should stop and work on something else, which, of course, requires cross-training.
At this point, the reader should recognize these characteristics of a pull system in either manufacturing or service.
∙ Visibility of a queue of customers, information, or inventory (for manufacturing). ∙ Limits are defined for the length of the queue, or amount of inventory. ∙ Work stops when the queue is filled at that location and employees move to other tasks. ∙ The employees manage the flow through the system.
This completes our discussion of the techniques and concepts used to create a pull system.
7.5 CHANGING RELATIONSHIPS WITH SUPPLIERS
It’s not enough to institute a lean system internally in a firm; the company’s supplier rela- tionships must also radically change. In a lean production system, suppliers are treated the same way internal work centers are treated. Suppliers may receive kanban cards and special containers, and they are expected to make frequent deliveries just in time for the processes using those supplies. Suppliers are viewed as the external factory and as part of the produc-
tion team, in line with modern supply chain manage- ment in which key suppliers are considered partners.
Several deliveries may be made each day if the sup- plier is located in the same vicinity; this is referred to as co-location. Suppliers located at a distance may have local warehouses where they receive bulk ship- ments and then break them down for frequent deliveries to the customer. This is not desirable, however, since too much inventory builds up in the pipeline and lead times from the factory to the warehouse can be long. Local suppliers with short lead times are preferred. Nevertheless, in some cases implementing lean produc- tion systems has simply shifted some of the inventory from the customer to the suppliers when long distances are involved or suppliers still have long setup times and large batch sizes.
LO 7.7 Compare lean suppliers to traditional manufacturing suppliers.
Lean supplier partnerships may require frequent deliveries in small lots. Mario Tama/Getty Images
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134 Part Two Process Design
Suppliers are given specific delivery times rather than shipment dates. For example, a supplier may be required to deliver parts that will last for two hours of production at 8 a.m., 10 a.m., 12 noon, and 2 p.m. On each delivery, the supplier picks up empty containers and associated withdrawal kanban cards, which lists the part number, the part name, and the quantity required. Only that number of empty containers is filled for the next delivery. Deliveries are made directly to the production line location where the supplies will be used, bypassing incoming inspection. In a retail setting, this may mean the supplier putting inventory directly onto the grocery store shelf. This requires the receiving customer to have complete confidence in the supplier’s quality. It also greatly reduces paperwork, lead time, inventory, the number of receiving areas, and required storage space.
For cases in which it is too expensive to make several deliveries each day, several suppliers may coordinate to make round-robin deliveries. For example, one supplier goes to three other suppliers plus his or her own for the 8 a.m. delivery. Another supplier will make the 10 a.m. run, and so on. This method can save on transportation expenses for small-lot deliveries.
Lean production systems tend to use fewer suppliers. This is done to establish long-term relationships with the suppliers and to work together to ensure the quality of the items needed. A complete reversal of thinking is needed here since we ordinarily assume that fewer suppliers might price-gouge the customer, and that more sources are needed to keep prices low. Supplier prices, however, can be managed with long-term contracts that include negotiated price stability. This requires a totally different type of supplier–customer rela- tionship from what was typical in the past.
Many companies develop an “integrated supplier program” to move toward a lean pro- duction system. The features of this type of program are as follows:
1. Early supplier selection. Suppliers are selected before the parts reach final design, and so the design can be worked out completely with the suppliers.
2. Family-of-parts sourcing. A supplier takes responsibility for an entire family of parts, allowing the supplier to establish economic volumes and reduce the number of separate deliveries.
3. Long-term strategic relationship. An exclusive contract for the life of the part can be given to a supplier in exchange for a specific price schedule. In other cases two or more suppliers of the same part may be used to ensure reliable supply, but nevertheless, long- term strategic relationships are established.
4. Paperwork reduction in receiving and inspection. Reducing the work associated with each order and delivery results in a direct savings to the customer and supplier.
Changing supplier relations is one of the most important aspects of creating a lean produc- tion system. As firms move toward leaner supply chains with fewer suppliers, they reduce inventory across the entire supply chain. These supply chain partners then work to improve flow across the entire supply chain.
Is it possible for a supply chain to be too lean? When inventory is significantly reduced, a supply chain may be at increased risk of shutting down. Typically, inventory serves as a buffer between supply chain firms so that if one firm slows or stops production, inventory can keep the rest of the supply chain flowing. Production slowdowns can be due to natu- ral (weather) or man-made (worker strikes) disruptions. Having fewer suppliers, a natural characteristic of lean systems, can also increase the risk of supply chain disruption. Fewer suppliers means fewer redundancies, or back-up arrangements, and maintaining production flows across lean system suppliers becomes even more important. Being too lean naturally increases some risks of supply chain disruption. There is a point at which a supply chain can be too lean and upstream or downstream disruptions can grind the supply chain to a halt.
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7.6 IMPLEMENTATION OF LEAN
Implementing lean thinking may sound simple but it is, in reality, very challenging. Manage- ment will be most effective if they clearly communicate a sustained commitment to lean think- ing with all workers. Lean requires a change in philosophy and culture along with changes in practices. New practices could include a reward system focused on creating flexible capacity, engaging workers in problem solving, providing time and resources to root out waste, and creating closer relationships with key suppliers. Table 7.3 provides a summary of the five lean tenets and the practices associated with each one. Not all these tenets and practices must be implemented in every situation. The approach should be customized to the situation.
Deploying lean thinking often starts and is maintained through kaizen events.3 A kaizen event can take between two days and one week and is focused on creating significant improvement in performance (quality, speed and cost) in one particular area of operations, for example, the shipping area or an area that has experienced a recent increase in quality problems. Kaizen is about fixing the process, not planning to fix it.
Kaizen events have helped Dr Pepper Snapple Group Inc. increase profits during indus- trywide declining sales in the U.S. soda market. Nearly all employees participated in teams that used gemba (observation of the production process) to find waste and then eliminate it. Improvements have included reducing average setup times between batches of differ- ent fountain syrup flavors from 32 to 13 minutes, reducing inventory holding space by 1.5 million square feet, and simplifying packaging to reduce printing costs. In five years, kaizen events have totaled $270 million in savings.
To facilitate implementation of kaizen the following approach is suggested:
1. Establish a team of employees that will study the process that needs improvement. These employees should come from different functions and levels of the organization to represent all stakeholders involved with the process.
2. Have the team determine what the customer values. The customer can be internal (the next process) or external to the organization. Only the customer can specify what is valued in the good or service.
LO7.8 Explain how to implement a lean system.
3 Kaizen is a Japanese word that means continuous improvement.
TABLE 7.3 Lean Tenets, Techniques, and Concepts
Lean Tenets Techniques and Concepts
Create product or service value from customer’s perspective
Understand customer-defined value Muda (waste)—work to eliminate
Identify, study, and improve the value stream Value stream mapping Gemba (observation)—work to improve flow
Ensure simple, smooth, and error-free flow Stabilizing master schedule Uniform load and Takt time Cross-training workers Reducing setup time and lot size Cellular manufacturing Preventative maintenance
Produce only what is pulled by customer Kanban (signal)—visual control system Supplier relationships/Co-location
Strive for perfection 5S—organize the work space 5 Whys—find root causes of problems Kaizen (continuous improvement)
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136 Part Two Process Design
3. Construct a value stream map of all process steps and the associated times or value that is added. Then analyze the value stream map and eliminate non-value- adding activities by searching for the seven forms of waste. The 5S and 5 Whys tech- niques may be applied at this step to identify and reduce wasted time, space, effort and resources.
4. Ensure flow to be smooth, steady, and error free to meet customer demand as it occurs. Stabilize the master schedule to match market demand, produce in small lots, change the layout, and cross-train workers.
5. Use customer demand to pull the flow of work through the process. Do not produce until output is required by the customer. Let the customer signal when work from the process is needed.
6. Implement the necessary changes identified by the team to achieve lasting improve- ment. Then repeat the cycle on another internal process or to the processes of upstream suppliers and downstream customers.
Lean concepts, principles, and techniques are increasingly being deployed in diverse settings. For example, the seven forms of waste can be observed in health care deliv- ery, as shown in Table 7.4. In health care, overproduction may be seen in excessive or unnecessary lab tests or surgery for a patient who may have been treated more easily and inexpensively with physical therapy. Unnecessary transportation may involve moving a patient among hospital departments for X-rays and other tests, when it may be possible to complete such tests in the patient’s own room. Nurses often walk miles per day to com- plete their work, a form of unnecessary motion. Even government services can benefit from lean thinking. Implementation of lean systems is also becoming common in many administrative processes.
Lean tenets once were believed to be applicable only to mass production. This is no longer true as the impact and benefits of lean are demonstrated again and again in diverse manufacturing and service settings and across the supply chain. Lean think- ing’s major impact in changing firm practices worldwide is being compared to the Ford moving assembly line as one of the great innovations in operations and supply chain management.
TABLE 7.4 Waste in Health Care
Waste Health Care Examples
Overproduction • Multiple forms asking for the same information • Multiple copies of reports • Multiple lab tests
Waiting time • Patient waiting • Waiting for lab test results
Unnecessary transportation • Patients being transported within and between hospitals
Excess processing • Re-entering patient information into system
Too much inventory • Overstocking of medication • Overstocking of supplies
Unnecessary motion • Walking to and from storage room • Searching for missing patient information and charts
Defects • Medical and surgical errors • Order-entry errors • Incomplete forms
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7.7 KEY POINTS AND TERMS
Lean concepts, principles, and tenets can be deployed to reduce waste in manufacturing and service firms. We have seen how the lean tenets create lean production systems with non-value-added activities eliminated and waste minimized. Key points in the chapter include the following:
∙ Lean thinking is a way of thinking about processes that includes five tenets: specify customer value, improve the value stream, flow the product or service, pull from the customer, and strive for perfection.
∙ The five lean tenets seek to eliminate waste by utilizing the full capability of workers and partners in continuous improvement efforts. Lean tools, or methods, are described for each of the five tenets.
∙ In manufacturing, smooth flow is ensured by a stable and level master schedule. This requires consistent daily production within the master schedule and mixed model assembly. Takt time matches the rate of output with the average demand rate in the market.
∙ Reducing lot sizes, setup times, and lead times is the key to decreasing inventories in a lean production system and ensures smooth flow. Service and administrative activities should also work toward a fast changeover from one customer to the next and a reduced lead time.
∙ The plant layout in a lean production system requires much less space and encourages evolution toward cellular or group technology layouts.
∙ A lean system requires cross-trained workers who can perform multiple tasks. A flex- ible workforce will require changing the way workers are selected, trained, evaluated, and rewarded.
∙ A kanban system is used to pull parts through the production system. A fixed number of containers is provided for each part, thus limiting the amount of work-in-process inven- tory. The pull system can also be applied in service operations by providing only what is needed when it is needed by the customer.
∙ New supplier relationships must be established to make lean production successful. Frequent deliveries and reliable quality are required. Often, long-term single-source contracts will be negotiated with suppliers.
∙ Kaizen emphasizes continuous improvement. Kaizen events are used to implement lean thinking improvements quickly in one week or less on a particular process.
∙ Lean concepts, principles, and techniques can be applied to design, manufacturing, dis- tribution, services, and the supply chain.
Key Terms Toyota Production System (TPS) 119
Just-in-Time (JIT) manufacturing 119
Lean production 119 Lean thinking 120 Waste (muda) 121 Value stream 121 Value stream
mapping 121 Gemba 121
Internal setup 128 External setup 128 Cellular manufacturing 129 Preventative maintenance 129 Cross-training 130 Respect for people 130 Kanban 130 Reducing lead time 133 Supplier relationships 133 Co-location 133 Kaizen 135
Push 123 Pull 123 Perfection 124 5 Whys 125 5S 125 Stabilizing the master
schedule 127 Uniform load 127 Takt time 127 Reducing setup time 128 Single setups 128
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138 Part Two Process Design
LEARNING ENRICHMENT (for self-study or instructor assignments)
Introduction to Lean Thinking—Gemba Academy Video https://youtu.be/a255lkYgIpI 6:35
Routing Out Waste in a Hospital Video https://youtu.be/jZLtbye--sg 8:46
Lean Manufacturing Tour—5S implementation Video https://youtu.be/mqgHUwSaKj8 9:13
The Toyota Production System Video https://youtu.be/P-bDlYWuptM 4:14
Push vs. Pull with Kanban Simulation Video https://youtu.be/a7YvJB0n16I 8:48
SOLVED PROBLEMS
1. Kanban and takt time. A work center uses kanban containers that hold 300 parts. To produce enough parts to fill the container, 90 minutes of setup plus run time are needed. Moving the container to the next workstation, waiting time, processing time at the next workstation, and return of the empty container take 140 minutes. There is an overall demand rate of nine units per minute.
a. Calculate the number of containers needed for the system. b. What is the maximum inventory in the system? c. A quality team has discovered how to reduce setup time by 65 minutes. If these
changes are made, can the number of containers be reduced? d. What is the takt time for this process?
Problem
a. T is the time required for a container to complete an entire circuit, in this case 90 minutes for setup and run time plus 140 minutes to move the container through the rest of the circuit.
n = DT ÷ C = (9 × (90 + 140)) ÷ 300 = 6.9 (round up to 7)
b. Since production will stop when all the containers are full, the maximum inventory is when all containers are full, that is, nC:
nC = 7(300) = 2100
c. n = DT ÷ C = (9 × (25 + 140)) ÷ 300 = 4.95 (round up to 5), so yes, the number of containers can be reduced from 7 to 5.
d. Takt time = 1/9 minute = 60/9 seconds = 6.67 seconds. Since the process produces 9 units per minute, the takt time is 1/9 minute or 6.67 seconds per unit.
Solution
2. Kanban. Work center A produces parts that are then processed by work center B. Kanban containers used by the work centers hold 100 parts. The overall rate of demand is 4.5 parts per minute at work center B. The table below shows setup, run, move, and wait times for parts at each of the work centers.
Problem
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Chapter 7 Lean Thinking and Lean Systems 139
Work Center
A B
Setup 4 3 Run time per unit 0.1 0.4 Move time 2 6 Wait time 10 20
a. What is the minimum number of containers needed between these two work centers? b. Assume that two extra containers are available (at no extra cost). If these work cen-
ters use the two containers, what is the maximum parts per minute that could be expected to flow through these two work centers? Could the work centers handle a demand of 8.5 parts per minute?
a. T is the time required for a container to go through both work centers and back to its starting point. Therefore, T = 4 + 3 = 7 minutes of setup time, 100 × (0.1 + 0.4) = 50 minutes of run time, 2 + 6 = 8 minutes of move time, and 10 + 20 = 30 minutes of wait time. Thus, T = 7 + 50 + 8 + 30 = 95 minutes.
n = DT ÷ C = (4.5 × (95)) ÷ 100 = 4.275 (round up to 5 containers)
b. Assume two extra containers are available.
n
=
DT ÷ C
5 + 2 = (D × (95)) ÷ 100 D
=
7 × (100 ÷ 95) = 7.37 parts per minute
Since 7.37 < 8.50, the work centers cannot handle a demand rate of 8.5 units per minute if they have seven containers.
Solution
Discussion Questions 1. Visit a manufacturing facility in your area. What are
the major causes of inventory? Be sure to ask about lot sizes and setup times. Would a lean production system work in this facility? Why or why not?
2. Why did the concepts, principles, and techniques of lean emerge and evolve in Japan, not in the Western countries?
3. State the lean tenets in your own words. 4. Why is a stable master schedule desirable for a lean
production system? What is the effect if it is not stable? 5. How can lot sizes and inventories be reduced in a lean
production system? Discuss specific approaches. 6. Describe typical supplier relations before and after
embracing lean tenets. 7. How do workers and managers in a lean production
system differ from their counterparts in traditional non- lean environments?
8. Discuss how lean thinking can lead to a reduction of costs (material, labor, overhead), other than inventory. Be specific.
9. Are there manufacturing firms that should not use lean? Why?
10. Find an example from the Internet of the application of lean thinking to a service operation. Describe how the lean tenets are applied in this setting.
11. How can lean thinking be applied to accounting, finance, human resources, and marketing processes?
12. Identify some of the seven forms of waste in the follow- ing situations.
a. Restaurant b. Doctor’s office 13. Construct a value stream map for the following
processes. a. Cafeteria b. Grocery store 14. What does it mean to say that a supply chain can be too
lean? Give examples why this may be a problem.
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140 Part Two Process Design
Problems 1. Calculate the daily production quantities and sequences
from the following monthly requirements for product models A, B, and C. Assume the month has 20 produc- tion days.
a. 5000 A, 2500 B, and 3000 C b. 2000 A, 3000 B, and 6000 C 2. Suppose a lean work center is being operated with
a container size of 25 units and a demand rate of 100 units per hour. Also assume it takes 180 minutes for a container to circulate.
a. How many containers are required to operate this system?
b. What is the maximum inventory that can accumulate? c. How many kanban cards are needed? 3. For a particular operation, the setup time is 10 minutes
and the run time is 50 minutes to produce a standard lot of 40 parts. It takes three additional hours to circu- late a container of parts after production is completed. The demand rate is 20,000 parts per month. There are 160 production hours in a month.
a. How many standard containers are needed? b. What is the takt time of this process? 4. Assume that a plant operates 2000 hours per year and
the demand rate for parts is 100,000 units per year. The circulation time for each kanban container is 24 hours.
a. How many kanban containers are needed for a container size of 100 parts?
b. What would be the effect of reducing the container size to 60 parts?
c. What is the takt time for this process? d. What takt time is needed for 80,000 units per year? 5. Suppose a work center has a setup plus run time of
30 minutes to make 50 parts. Also assume it takes 10 minutes to move a standard container of 50 parts to the next work center and the demand rate is one part per minute throughout the day.
a. Schedule this situation by drawing a picture of when work center A should be producing and idle and when movements of containers take place from A to B, the using work center.
b. How many standard containers are needed for this part to circulate from the picture in part a?
c. Use the formula n = DT ÷ C to calculate the number of containers.
6. A company is in the business of machining parts that go through various work centers. Suppose work center A feeds work center B with parts. The following times (in minutes) are given for each work center.
Work Center
A B
Setup time 3 2 Run time (per part) 0.5 0.1 Move time 6 8
A standard kanban container holds 50 parts that are transferred from work center A to work center B. The demand rate at work center B is four parts per minute.
a. How many kanban containers are needed for this situation?
b. If move time is cut in half, what does this do to the number of containers needed? How much will this change reduce inventory?
7. Suppose that a lean work center is being operated with a lot size of 50 units. Assume that 200 parts are demanded per hour and it takes three hours to circu- late a container, including all setup, run, move, and idle time.
a. Calculate the number of kanban containers required. b. What is the maximum inventory that will accumulate? c. What can be done to reduce the inventory level?
Suggest alternatives. 8. A supplier provides parts to a manufacturing com-
pany that demands frequent deliveries. At the present time it takes six hours to make a round trip between the supplier’s warehouse and the customer, including loading, travel, and unloading time. The lot size is 12 pallet loads on a truck, and the manufacturer uses 2 pallets per hour.
a. How many trucks are needed to ship the pallets to the manufacturer?
b. What is likely to happen if the truck breaks down? c. How can the supplier ensure that the customer does
not run out of parts even in the face of delivery problems or other uncertainties?
d. What will happen to the supplier if the manufacturer runs into trouble and shuts down for a period of six hours?
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8. Managing Quality
9. Quality Control and Improvement
Quality is one of the four objectives of operations, along with cost, delivery, and flexibility. To meet the quality objective, it is important to manage and control all aspects of the quality system. Chapter 8 begins this part with a discussion of managing quality, and Chapter 9 addresses quality control and improvement.
The main contribution of Part Three is a broad treatment of quality, which includes management, planning, and policy concerns in addition to the more traditional statistical topics. In practice, quality is primarily a management problem, and statistical methods are used to first stabilize a system and to then achieve continuous improvement of a stable system. ■
Pa rt iii
Quality
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Quality is one of the four key objectives of operations, along with cost, flexibility, and delivery. While quality management is cross-functional in nature and involves the entire organization, operations has a special responsibility to produce a quality product or service for the customer. This requires the cooperation of the entire organization and careful atten- tion to the management and control of quality.
Quality management has had many different meanings over the years. In the early 1900s, managing quality meant inspection, which was the primary method used to ensure quality
8 c h a p t e r
Managing Quality
LO8.1 Explain quality, from a customer perspective.
LO8.2 Characterize product quality based on four dimensions.
LO8.3 Distinguish service quality from product quality based on its distinct measurement.
LO8.4 Apply the quality cycle to a product or service.
LO8.5 Explain how mistake-proofing and the supply chain are integrated with quality management planning.
LO8.6 Attribute how cost of quality is related to financial performance.
LO8.7 Recall the two key quality pioneers and their main ideas.
LO8.8 Compare and contrast ISO 9000 standards and the Baldrige Award criteria.
LO8.9 Articulate some key barriers to successful quality improvement efforts.
After reading this chapter, you should be able to:LEARNING OBJECTIVES
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products (services were rarely inspected). In the 1940s, managing quality took on a statistical connotation as statistical methods began to be used to control quality within the natural varia- tion of the transformation process. Statistics pioneer Walter Shewhart developed statistical con- trol charts to learn to maintain a production process within a state of statistical control and thus reduce the amount of inspection required. In the 1960s, the meaning of quality management was expanded to include activities across the entire organization as all functions contributed to designing and producing quality. Quality was seen not as just an act of production; rather, it was something the entire organization should strive to provide for the customer. Now, qual- ity management is taking on a broader meaning, including continuous improvement, com- petitive advantage, and a customer focus together with quality along the entire supply chain. The Operations Leader box shows how Ritz-Carlton Hotel, a two-time winner of the Malcolm Baldrige National Quality Award, is implementing modern quality management principles.
8.1 QUALITY AS CUSTOMER REQUIREMENTS
Quality is defined as “meeting, or exceeding, customer requirements now and in the future.” This means that the product or service is fit for the customer’s use. Fitness for use is related to the benefits received by the customer. Benefits are based on the totality of features and characteristics that determine the ability of a product or service to satisfy given needs. Only the customer, not the producer, can determine if the product or service has the right benefits.
LO8.1. Explain quality, from a customer perspective.
Employees respond to a customer’s requirements at both the team and individual levels. They provide highly personal, individual service. Customer likes and dislikes are captured and entered into a guest history that pro- vides information on the personal preferences of hun- dreds of thousands of repeat Ritz-Carlton guests. When a customer stays at any of their hotels the information is provided to the employees serving that customer.
If an employee detects a problem, the employee is empowered to do whatever it takes to make the cus- tomer happy immediately, or the employee can call on any other employee to assist. Such a system depends on well-trained, perceptive, and motivated employees along with a well-defined service delivery system. With more than a million customer contacts on a busy day, Ritz- Carlton understands that its customer and qual- ity requirements must be driven by each individual employee at the lowest level of the organization.
Results indicate that Ritz-Carlton hotels are doing an exceptional job of translating customer requirements into employee behavior and excellent systems. Ninety- seven percent of Ritz-Carlton’s customers report having a “ memorable experience” while staying in one of their hotels.
Source: www.ritzcarlton.com, 2020.
The Ritz-Carlton Hotel Company, L.L.C., is a five-star hotel management company that develops and oper-
ates 91 luxury hotels and resorts in 30 countries. The com- pany targets primarily industry executives, meeting planners, and prestigious trav- elers. It employs 40,000 people who are highly trained and motivated to provide quality ser- vice. The Ritz-Carlton Hotel Company is the only hotel company
to win two Malcolm Baldrige awards. Ritz-Carlton translates customer requirements into
employee requirements through its Gold Standards and its strategic planning process. They have taken what their customers want most and designed the simplest ways to provide them. Ritz-Carlton’s data show that its employees’ understanding of the Gold Standards is directly correlated with guest satisfaction.
The Ritz-Carlton Hotel Company, L.L.C.
OPERATIONS LEADER
Leonard Zhukovsky/Shutterstock
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144 Part Three Quality
Customer satisfaction is related to quality. It means that the quality of the product or service meets the customers’ expectations. For exam- ple, the car functions as the customer expects, or a service is delivered in a manner that meets customer expectations. The customer may receive great benefits, but relative to expectations the customer is not satisfied. Customer satisfaction is therefore a relative measure of quality.
Customer expectations can depend on many things. Advertising can determine the customer’s expectations. Another factor is: Does the customer know how to properly use the product or service? The prod- uct can be more difficult or easier to use than the customer expected. Also, the customer’s expectations may change over time as the cus- tomer becomes familiar with different products and services available. The expectations of customers of the Ritz-Carlton, for example, are certainly much different from those of a lower priced hotel.
Producers certainly attempt to meet customer requirements and expectations through both design and production of the product or ser-
vice. The producer specifies the quality attributes of the product or the service as carefully as possible and then strives to meet those specifications while improving the production and delivery process over time. Whether the resulting product or service meets the customer’s requirements and expectations will be judged ultimately by the customer.
8.2 PRODUCT QUALITY
For a manufactured good, the following dimensions of quality can be useful in understand- ing product quality: ∙ Quality of design ∙ Quality of conformance ∙ The “abilities” ∙ Field service
Quality of design is determined before a product is produced. This determination is usually the responsibility of a cross-functional product design team, including members from marketing, engineering, operations, and other functions.
Quality of design is determined by market research, the design concept, and product specifications. Market research is aimed at assessing customer needs. Since there are dif- ferent ways to meet those needs, a particular design concept must be developed. For exam- ple, the customer may need inexpensive and energy-efficient transportation—a need that can be met by a large number of different automobiles, each representing a different design concept. The design concept then is translated into a very detailed set of specifications for the product, for example, a digital blueprint and bill of materials.
Quality of conformance means producing a product to meet the specifications. When the product conforms to specifications, operations considers it a quality product regardless of the quality of the design specifications. For example, inexpensive shoes will have high quality of conformance if they are made according to specifications and low quality of conformance if they do not meet specifications. Quality of design and quality of confor- mance thus represent two different uses of the term quality.
Another aspect of quality involves the so-called abilities: availability, reliability, and maintainability. Each of these terms has a time dimension and thus extends the meaning of quality over some time horizon. The addition of time to the definition of quality is, of course, necessary to reflect continued satisfaction by the customer.
LO8.2. Characterize product quality based on four dimensions.
RITZ-CARLTON. Any of the employees of the Ritz-Carlton can spend up to $2000 to immediately correct a guest’s problem or handle a complaint. Its employees are the key factor in Ritz-Carlton’s receipt of two Malcolm Baldrige National Quality awards. Sylvain Grandadam/age Fotostock
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Availability defines the continuity of usability to the customer. A product is available if it is in an operational state and not down for repairs or maintenance. Availability can be measured quantitatively as follows:
Availability = Uptime _________________ Uptime + Downtime
Reliability refers to the length of time a product can be used before it fails. Reliability is measured as mean time between failure (MTBF), which is the average time the product functions from one failure to the next. The longer the MTBF, the more reliable the product. For a cell phone, reliability is a measure of its expected lifespan until it fails.
Maintainability refers to the restoration of a product or service once it has failed. All cus- tomers consider maintenance or repairs a nuisance. Thus, a high degree of maintainability is desired so that a product can be restored to use quickly. Maintainability can be measured by the mean time to repair (MTTR) the product. For example, Caterpillar Inc. supports excellent main- tainability by supplying spare parts for its equipment anywhere in the world within 48 hours.
Availability, then, is a combination of reliability and maintainability. If a product is good in both reliability and maintainability, it will be high in availability. The above rela- tionship for availability can be restated in terms of MTBF and MTTR:
Availability = MTBF ______________ MTBF + MTTR
For example, if a product has an MTBF of eight hours and an MTTR of two hours, its availability will be 80 percent.
Field service, the last dimension of quality, represents maintenance, repair or replace- ment of the product after it has been sold. Field service is also called customer service, sales service, or just service. Field service is related to variables such as promptness, com- petence, and integrity. The customer expects that problems will be corrected quickly, in a satisfactory manner, and with a high degree of honesty and courtesy.
The four different dimensions of quality are summarized in Figure 8.1. As can be seen there, quality is more than just good product design; it extends to quality control of produc- tion, quality over the life of the product, and quality of field service after the sale.
FIGURE 8.1 Different types of quality.
Customer satisfaction Fitness for use
Quality of design
Quality of conformance
Availability
Field service
Quality of market research
Quality of concept
Quality of specification
Technology
Employees
Management
Reliability
Maintainability
Logistical support
Promptness
Competence
Integrity
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146 Part Three Quality
8.3 SERVICE QUALITY
The definition and measurement of service quality is quite different from product quality. Service quality has dimensions of the facilitating good, explicit service, and implicit service. While the facilitating-good quality can be measured by using the dimensions of manufacturing, explicit (visible) service and implicit (psychological) service require different measurements.
Product measurements can be largely objective while many service measures are per- ceptual or subjective. For example, product design quality can be measured by the product features offered, such as the speed of acceleration of an automobile and its normal braking distance. The conformance quality can be measured by the cost of scrap and rework in the factory. Services can also have some objective quality features, such as the time to get your meal at a drive-thru window, or if you can walk without pain after foot surgery. But subjec- tive measures of how the customer perceives the service quality are also common.
The most popular approach to evaluating service quality is called SERVQUAL.1 SERVQUAL assesses customer perceptions about five dimensions of a service:
1. Tangibles. The appearance of the physical facilities, equipment, facilitating goods, and personnel from the service firm. For example, if a restaurant is dirty, the food does not look nice, and the employees are disheveled, the tangible quality will be low.
2. Dependability. The ability of the service firm to perform the promised service depend- ably and accurately without errors. For example, if a restaurant takes a reservation for 7:00 p.m. and the customer is not seated promptly or the waiters bring the wrong meal, the dependability will be low.
3. Responsiveness. The ability of the service firm to provide service that is prompt and helpful to the customer. In the restaurant, for example, the meal should be provided in a timely fashion and customers’ questions about the menu answered.
4. Assurance. The knowledge and courtesy exhibited by employees of the service firm and their ability to convey trust and confidence. In the restaurant example, does the server know the menu and is he or she courteous in providing the service?
5. Empathy. The caring, individualized attention that the service firm provides to its custom- ers. The server should show individualized concern for customers and their particular needs.
As can be seen, service quality dimensions are very different from product quality dimensions and reflect the close interaction the employees have with the customer in service delivery.
SERVQUAL uses a questionnaire to measure these five dimensions. Service quality is measured as the gap (or mathematical difference) between what the customer expects on each dimension and what is provided. For example, if the customer does not expect a lot of empathy, service quality can be perceived to be high even though not much empathy is provided. The use of gaps as a measure of service quality has been debated vigorously. While some argue that the perceived level of service provided should measure service quality, others claim that the gap between what is provided and what is expected is a better measure of service quality.
8.4 QUALITY PLANNING, CONTROL, AND IMPROVEMENT
The dimensions of product or service quality can be part of a process to manage quality. The process of quality planning, control, and improvement requires continual interaction between the customer, the operations function, and other parts of a business. Figure 8.2
LO8.3. Distinguish service quality from product quality based on its distinct measurement.
1 A. Parasuraman, V. A. Zeithaml, and L. L. Berry, “SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality,” Journal of Retailing, 64(1), 1988.
LO8.4. Apply the quality cycle to a product or service.
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illustrates how these interactions occur through a quality cycle. The customer needs are determined, usually through marketing as part of a cross-functional team. These needs are either expressed directly by the customer or discovered through a process of market research. Engineering, in conjunction with other functions, designs a product or service to meet those needs. Quality function deployment is a useful technique for aligning the voice of the customer (customer needs) with the engineering specifications.
Once the design concept and specifications have been completed, the quality of design has been established. Operations, as part of the quality team, then produces the product or service as specified. Operations must continually ensure that production occurs as speci- fied by insisting on quality of conformance. This ordinarily is done through proper train- ing, supervision, machine maintenance, and operator inspections. The quality cycle must be a never-ending process of gathering current customer needs, and then designing and producing to meet those needs. In this way continuous improvement occurs.
Figure 8.3 is a description of the quality cycle for a mass transit system. In this case, an agency, in place of marketing, interprets customer needs. A planner, working in greater detail, then determines the design concept and the specifications for service. The operations function delivers the service, and the quality cycle begins again as the public then restates its needs or confirms that the present service is satisfactory. The quality cycle should exist in every organization to ensure that all aspects of quality are planned, controlled, and continually improved. Feedback from the customer is essential to produce quality products and services.
The implementation of planning, control, and improvement of quality through the qual- ity cycle requires this sequence of steps:
1. Define quality attributes on the basis of customer needs. 2. Decide how to measure each attribute.
FIGURE 8.2 The quality cycle.
Needs
Interpretation of needs
Product
Specifications
CUSTOMER Quality needs
Interprets customer needs
Works with customer to design product
MARKETING
Defines design concept Prepares specifications Defines quality
characteristics
ENGINEERING Produces the product
or service
OPERATIONS
Plans and monitors quality
QUALITY CONTROL
Cross-functional Team
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148 Part Three Quality
3. Set quality standards. 4. Establish appropriate tests for each standard. 5. Find and correct causes of poor quality. 6. Continue to make improvements.
Planning for quality must always start with the product attributes. The quality team determines which attributes are important to customer satisfaction and which are not. For example, the manufacturer of L’eggs panty hose has determined three important quality attributes for its product: (1) a comfortable fit, (2) an attractive appearance, and (3) a wear life that is considered reasonable by the customer. It has determined that fit and appearance depend on the materials used, while wear life depends on materials and stitch patterns.
A method must then be devised to test and measure quality for each of the product attributes. For example, the manufacturer of L’eggs has developed a special cross-stretcher that can test the strength of its product. L’eggs are also inspected visually for fabric defects, seaming defects, and shade variations.
After deciding on the measurement techniques to use, the quality team sets standards and tolerances that describe the amount of quality required on each attri- bute. Standards are set as desired targets. For example, a standard on L’eggs panty hose is the amount of pressure that the garment must withstand on the cross-stretcher. Tolerances are stated as (± quantities), or minimum and maximum acceptable limits around the standard.
After standards have been set, a testing process should be established. In the case of L’eggs, this process is based on sampling procedures since it would be far too costly to test and inspect each of the millions of pairs of panty hose produced each year.
It is not enough simply to inspect the products for defects. As the saying goes, “You cannot inspect quality into a product, you must build it in.” Upon discovering defects, workers should find the underlying causes and correct them. Causes of poor quality can include improper raw materials, lack of training, unclear procedures, a faulty machine, and so on. When the causes of poor quality are found and corrected, the production system will be in control and continuous improvement will be possible.
FIGURE 8.3 The quality cycle in a mass transit system.
County planning Regional planning State transportation agency
Planner Scheduler
Operations office
Routes Schedules Budgets
Method Facilities Equipment
Evaluation Inspections Audits Surveys Hearings
Public
Riders' needs
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8.5 MISTAKE-PROOFING
Planning, controlling, and improving quality can be augmented by focusing on preventing errors from occurring in the first place. This requires designing products, services, and internal procedures that are mistake-proof, working with suppliers to prevent errors, train- ing employees before problems occur, and performing preventive machine maintenance. Nevertheless, when errors do occur, they need to be corrected quickly and the system itself changed to prevent errors of the same type from recurring.
The concept of mistake-proofing was developed in the 1960s by Shigeo Shingo, who worked for Toyota Motors in Japan. It is called poka-yoke (pronounced poe-ka-yoke), which means “mistake-proofing” in Japanese. The idea of poka-yoke is to design the product and pro- cess so that it is impossible for humans to make mistakes when producing, delivering, or using a product or a service or for mistakes to be easily detected by humans when they do occur.
For example, your microwave will not start if the door is open, and your car will not start unless your foot is on the brake pedal. These are examples of poka-yokes that prevent con- sumers from using products in unsafe or unintended ways. In the manufacturing process, parts should be designed that cannot be assembled backward or left off the product by mistake.
Services should also be designed to avoid errors by both the producer and the customer. For example, many rides in amusement parks have height requirements. To prevent a child who does not meet the height requirement from getting on a ride, riders have to walk past a measuring post at the entrance to the ride, with the height requirement clearly marked. A ride operator can quickly gauge whether a child meets the height requirement before allowing the child to get on the ride.
If the error cannot be prevented from occurring, it should be made easy to detect. For example, all of the warning lights on car dashboards try to get drivers to fix little problems before they become catastrophes! For more examples of mistake-proofing, see Figure 8.4.
LO8.5. Explain how mistake-proofing and the supply chain are integrated with quality management planning.
FIGURE 8.4 Examples of mistake proofing (poka-yoke). Courtesy of John Grout’s Mistake- Proofing Center (www .mistakeproofing.com)
Medical gas outlets are designed so proper valves fit in only one outlet.
Scald protectors close water flow if the water temperature becomes too hot.
A car cannot start in gear. It must either be in park or neutral.
These school buses have a wire loop on the bumper that swings out to ensure no children are hidden under the hood.
Pa ve
lS to
ck /S
hu tte
rs to
ck
©John Grout’s Mistake-Proofing Center (www.mistakeproofing.com)
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150 Part Three Quality
8.6 ENSURING QUALITY IN THE SUPPLY CHAIN
Recall that product quality and service quality are defined by the customer and that the cycle of quality planning, control, and improvement is driven by customer needs. There- fore, the customer input is important not only to the firm but also the entire supply chain in driving quality performance.
For many products and services, more than 50 percent of the product or service inputs (materials and other work) are purchased from suppliers. Indeed, with outsourcing, 100 percent of the product or service can be sourced from suppliers. For example, the iPhone is completely outsourced by Apple, Inc., except for the design, which is done in-house.
In working with suppliers there are several principles that should be followed. First, the supplier should be involved in the design of the product or service to maximize the preven- tion of design defects from the start (poka-yoke). Suppliers often can recommend new or different materials or services that can improve quality or prevent defects from occurring within production processes that suppliers have responsibility for and control over.
When a product or service is complex, it is important that suppliers maintain very high levels of quality to ensure that the final product has the required quality. A concept called rolled yield accounts for the cumulative defect rate observed by the final customer. For example, suppose a product or service has 100 components or parts and each part has a yield of 99 percent (1 percent defective). Then the overall yield of the final product is obtained by multiplying the yields of all the individual parts. Since there are 100 parts with the same yield (.99), in this case the rolled yield is .99 × .99 × .99 . . . × .99 (100 times):
Rolled yield = (.99) 100 = .366
As can be seen, the rolled yield is only 36.6 percent for the final product. Therefore, the quality provided by the suppliers must be much higher to ensure a rolled yield of, say, 99 percent in the final product or service. For a 99 percent rolled yield, supplier quality must be 99.99 percent for each of the 100 parts.
Supplier management requires more than simply selecting suppliers and measuring quality compliance. Operations must also manage risk and ensure ongoing process control by suppliers. Many product recalls in the U.S. are due to suppliers’ quality failures and not by the selling firm itself. One case was Mattel’s toy recalls in 2007 due to lead paint con- tamination. These toys were all manufactured by a supplier in China. Yet, the selling firm is often legally responsible for the costs of the recall. The financial and reputational losses to Mattel were devastating from this recall of 19 million toys.
Supplier quality management thus requires a system not only to select suppliers but to man- age them on an ongoing basis. Managing suppliers is more than a matter of ensuring compliance to standards through incoming inspection. Oversight of the outsourced process is also required. Certifying the supplier can help to accomplish this. Supplier certification means the supplier has control over its processes and can pass an audit by the customer or an independent agency, at the very least. The audit ensures that there is a quality system in place, including documented pro- cedures, training, and ongoing statistical control of the process to prevent defects from occurring.
In selecting a supplier, the price and the product samples may look good, but is this enough? A typical item sourced from an overseas supplier encountered the following issues:
∙ The samples submitted to the buyer were “jewelry,” that is, carefully selected items that were not being produced by a reliable production process. The samples were actually carefully handmade and inspected to ensure their quality.
∙ In the production process, quality was actually being inspected into the product with only a 60 percent yield at final inspection. Only the good products were included
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in the sample. This means the production process was not capable of producing consis- tently good quality.
∙ Small lots were not feasible since production equipment had been set up for long runs, with questionable quality discovered later, after production.
∙ The production cycle time was long and variable, resulting in large inventories.
This example indicates why certified suppliers are necessary to ensure that suppliers have a good quality system in place for ongoing production of products or services. Without this, suppliers may merely provide good samples at a low price, only to produce low qual- ity later. Read the Operations Leader box about Boeing Company and how its supplier rating system ensures quality from suppliers.
8.7 QUALITY, COST OF QUALITY, AND FINANCIAL PERFORMANCE
Quality and financial performance are intimately related. First, we consider the relation- ship between quality and cost. A powerful idea in the area of quality is to calculate the cost of quality, which includes prevention, appraisal, internal failure, and external failure categories. All these, except prevention, are costs of not doing things right the first time. When a cost is assigned to poor quality, it can be managed and controlled like any other cost. Since managers speak the language of money, putting quality in cost terms provides a powerful means of motivation, communication, and control.
LO8.6. Attribute how cost of quality is related to financial performance.
supplier receives: Red (Unsat- isfactory), Yellow (Improvement Needed), Bronze (Satisfactory), Silver (Very Good), and Gold (Exceptional).
The supplier ratings are available at three levels of visibility: the site level, the business-group level, and the
company level. Consistent with the concept of 360-degree feedback, suppliers get to see their performance rat- ings and learn from them. Suppliers can access detailed reports at the incident level (e.g., an incident involving a nonconforming shipment of supplier products).
Boeing uses its supplier rating performance system not only to encourage and help its suppliers improve but also to help various Boeing units select and partner with capable suppliers. Exceptionally performing suppliers are eligible for the Supplier of the Year award from Boeing.
Source: Kirsten Parks and Timothy Connor, “The Way to Engage,” Quality Progress 44, no. 1 (April 2011), pp. 20–27; www.boeing.mediaroom.com, 2019.
In 2017, Boeing, the world’s largest aerospace company, spent $60 billion on more than 13,000 suppliers located in 58 countries to support the manufacture of complex, advanced-technology prod- ucts ranging from commercial and military aircraft to satel- lites to weaponry systems to electronic and defense systems. Suppliers play a critical role in helping Boeing meet customer product requirements and delivery mandates. With so many suppliers involved, how does Boeing manage to keep track of supplier performance, especially those who may not be performing as well as they should and are in need of help? The answer lies with its enterprise-wide supplier performance rating system.
Boeing grades its suppliers in three performance categories—quality performance, delivery performance, and general performance. Supplier performance in each category is tracked on a monthly basis and compared to thresholds that then determine which of five colors a
Boeing’s Supplier Rating System
OPERATIONS LEADER
funlovingvolvo/123RF
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152 Part Three Quality
Most companies have no idea how much they spend to manage quality. Those that have found that the cost of quality is about 30 percent of sales, and typically ranges from 20 to 40 percent. Since these figures are two or three times greater than profit margins in many companies, a reduction in the cost of quality can lead to a significant improvement in profit. The best-managed companies have been able to reduce their costs of quality from 30 percent of sales to as little as 5 percent in a few years. This has been done while improv- ing the quality of their products or services.
The cost of quality may be divided into two components: control costs and failure costs. A full listing of these costs is given in Table 8.1.
Control costs are related to activities that remove defects from the production stream. This can be done in two ways: by prevention and by appraisal. Prevention costs include activities such as quality planning, new-product reviews, training, and engineering analysis.
TABLE 8.1 Costs of Quality Source: Adapted from J. M. Juran and A. B. Godfrey, eds., Juran’s Quality Handbook, 5th ed. (New York: McGraw-Hill, 1999).
Control Costs
Prevention Costs
Quality planning Costs of preparing an overall plan, numerous specialized plans, quality manuals, procedures.
New product review Review or prepare quality specifications for new products, evaluation of new designs, preparation of tests and experimental programs, evaluation of vendors, marketing studies to determine customers’ quality requirements.
Training Developing and conducting training programs. Process planning Designing and developing process control devices. Quality data Collecting data, data analysis, reporting. Improvement projects Planned failure investigations aimed at chronic
quality problems.
Appraisal Costs
Incoming materials inspection
The cost of determining quality of incoming raw materials.
Process inspection All tests, sampling procedures, and inspections done while the product is being made.
Final goods inspection All inspections or tests conducted on the finished product in the plant or the field.
Quality laboratories The cost of operating laboratories to inspect materials at all stages of production.
Failure Costs
Internal Failure Costs
Scrap The cost of labor and materials for product that cannot be used or sold.
Rework The cost of redoing product that can be made to conform.
Downgrading Product that must be sold at less than full value due to quality problems.
Retest Cost of inspection and tests after rework. Downtime Idle facilities and people due to quality failures.
External Failure Costs
Warranty The cost of refunds, repairing, or replacing products on warranty.
Returned merchandise Merchandise that is returned to the seller. Complaints The cost of settling customer complaints due to
poor quality. Allowances The cost of concessions made to customers due
to substandard quality.
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FIGURE 8.5 Cost of quality categories and trade-offs.
Cost/unit
100% defective
100% good
Internal failure + External failure costs
Prevention & appraisal costs
Cost of Quality Categories and Trade-offs
These activities mostly occur before production and are aimed at preventing defects before they occur. The other category of control costs includes appraisal or inspection aimed at eliminating defects after they occur but before the products or services reach the customer.
Failure costs are incurred either during the production process (internal) or after the product is shipped (external). Internal failure costs include items such as scrap, rework, quality downgrading, and machine downtime. External failure costs include warranty charges, returned goods, and allowances. The potential loss of customers’ confidence in the product or service is perhaps the greatest external cost.
The cost of quality can be a confusing term. Three of the four costs can be called the cost of nonconformance or the costs of poor quality (appraisal, internal failure, or exter- nal failure). Prevention is the cost of achieving good quality. Figure 8.5 reveals how the four cost of quality categories relate to one another. As prevention costs and appraisal costs increase, internal failure and external failure decreases. A trade-off, therefore, exists between the control costs categories (i.e., prevention and appraisal) and the failure costs categories (i.e., internal failure and external failure). Figure 8.5 appears to suggest that there is an optimal quality level where control and failure costs meet that is not 100 per- cent good quality. However, management stresses continuous improvement by finding ways to shift the curve for prevention and appraisal costs to the right over time, allowing quality to improve through more efficient prevention and appraisal activities.
Many companies find that by investing in prevention activities such as training, process planning, and new-product review, they avoid costs that occur later in production (appraisal, internal failure) or after production (external failure). Prevention is a tremendous leverage fac- tor. Investing one dollar in prevention activities generates more than one dollar in appraisal, internal failure, and external cost savings. Those savings flow directly to the bottom line, which in many companies will more than double profits.
A construction company investigated its cost of poor quality and found a total of 72 instances of nonconformance on one highway construction project. Those instances could be classified into the following types of preventable errors.
∙ Design problems that caused the reworking of a portion of the highway several times. ∙ Noncompliance by a cement contractor that required repair of the poured concrete. ∙ Subcontractor problems that resulted in failure to deliver by some subcontractors.
The company found that it could save considerable costs in future projects by seeking to prevent these errors before they occurred.
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154 Part Three Quality
The cost of quality can be a powerful incentive for quality improvement when it is used properly. It focuses management attention on waste due to excess failures or high control costs. It also provides a quantitative basis for monitoring progress in reducing quality costs.
Quality improvement can also dramatically increase revenues through either a more consistent product or new products or services that better meet customer needs. Improving customer satisfaction can be a powerful driver of revenue and market share when custom- ers receive a product or service that they really like.
Improving quality effects profitability and return on investment through both increasing revenues and reducing costs. Quality has a powerful effect on the top line, margins, and ultimately the bottom line.
8.8 QUALITY PIONEERS
Many approaches to managing quality have been advocated. Deming, Juran, Crosby, Feigenbaum, Shewhart, and Ishikawa, to name only a few, are pioneers who have shaped modern approaches to quality management. Of these, Deming and Juran are most noted for teaching quality to the Japanese and restoring attention to quality by American and European companies.
W. Edwards Deming emphasized the role that management should take in quality improve- ment. Deming defined quality as continuous improvement of a stable system. This defini- tion emphasizes two things. First, all systems (administrative, design, production, and sales) must be stable in a statistical sense. This requires that measurements be taken of quality attributes and monitored over time. If these measurements have a constant variance around a constant average, the system is stable. The second aspect of Deming’s definition is continu- ous improvement of the various systems to reduce variation and better meet customer needs.
Deming expressed his philosophy of quality in his famous 14 points, which are listed in Table 8.2. He stressed that top executives should manage for the long run and not sacrifice quality for short-run profits. Deming argued that excessive attention to quarterly profit reports and short-run objectives distracts top management from focusing on customer ser- vice and long-run quality improvement. He also argued, as others do, that management should cease its dependence on mass inspection to achieve quality and stress prevention of defects instead. Deming suggested that this should be accomplished by training of all employees, good supervision, and use of statistical procedures.
Deming went on to exhort management to break down barriers between departments and encourage people to work together to produce quality products and services. He thought that many of the work standards, individual performance pay systems, and quotas that companies use get in the way of cooperation among individuals and departments and thus impede quality improvement.
Deming was a strong advocate of applying statistics to stabilize and improve processes. Quality cannot be improved by trying harder. Workers and managers must have the proper tools to identify causes of variation, to control variation, and to reduce variation in the product.
Deming and the other quality pioneers are advocates of the idea that most quality prob- lems are caused by poor systems, not by the workers. They argue that quality problems should not be blamed on the workers; rather, management must change the system to improve quality. All levels of management must accept responsibility for quality.
Juran originated the idea of the quality trilogy: planning, control, and improvement of quality. In the planning area he suggested that companies should identify the major
LO8.7. Recall the two key quality pioneers and their main ideas.
W. Edwards Deming
Joseph Juran
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business goals, customers, and products required. New products should be intro- duced only after they are carefully tested and when they meet a verified customer need. He also suggested that much of qual- ity improvement requires careful planning to ensure that the most important quality problems are attacked first—“the vital few.”
Juran stressed control of quality through use of the statistical methods covered in the next chapter. He argued that management should institute the procedures and methods needed to ensure quality and then work to
keep the system continuously in control. Like Deming, Juran believed strongly in the sta- tistical approach to quality as a way of achieving process control.
The third leg of the quality trilogy is improvement. Juran suggested both breakthrough improvement and continuous improvement of processes. He argued that this could be done once the system was brought under statistical control. Juran also believed that training and involvement of all employees was necessary to ensure continuous quality improvement.
While the specific details of quality improvement may vary between Deming and Juran, they have much in common. Some of their common ideas and those of other quality pio- neers are shown in Table 8.3. As can be seen from the table, there is a common thread running through quality thinking.
TABLE 8.2 Deming’s 14 Management Principles Source: Adapted from W. Edwards Deming, Out of the Crisis (Cambridge, MA: MIT Center for Advanced Engineering Study, 1986).
Requirements for a business whose management plans to remain competitive in providing goods and services that will have a market.
1. Create constancy of purpose toward improvement of products and services with the aim of being competitive and staying in business for long-run, rather than short-run, profits.
2. Adopt the new philosophy by refusing to allow commonly accepted levels of mistakes, defects, delays, and errors. Accept the need for change.
3. Cease dependence on mass inspec- tion. Rely instead on building quality into the product in the first place and on statistical means for controlling and improving quality.
4. End the practice of awarding business on the basis of price tag alone. Instead, minimize total cost. Reduce the number of suppliers by eliminating those who cannot provide evidence of statistical control of processes.
5. Improve constantly, and forever, systems of production to improve qual- ity and productivity and thus constantly reduce costs.
6. Institute training and retraining for all employees.
7. Focus management and supervisors on leadership of their employees to help them do a better job.
8. Drive out fear. Don’t blame employees for “systems problems.” Encourage effective two-way communications. Eliminate management by control.
9. Break down barriers between depart- ments. Encourage teamwork among different areas such as research, design, manufacturing, and sales.
10. Eliminate programs, exhortations, and slogans that ask for new levels of produc- tivity without providing better methods.
11. Eliminate arbitrary quotas, work standards, and objectives that interfere with quality. Instead, substitute leader- ship and continuous improvement of work processes.
12. Remove barriers (poor systems and poor management) that rob people of pride in their work.
13. Encourage lifelong education and self-improvement of all employees.
14. Put everyone to work on implement- ing these 14 points.
Textbook author Schroeder (left) learns from Joseph Juran at a conference. ©Roger Schroeder
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156 Part Three Quality
8.9 ISO 9000 STANDARDS
ISO 9000, established in 1987, is one of the major approaches that companies are using to ensure quality today. ISO 9000 is one of several sets of standards developed by ISO (Inter- national Organization for Standardization). ISO, an international body consisting of mem- bers from 162 countries, is the largest developer of international standards. Besides ISO 9000, other standards have been developed for environmental management (ISO 14000), social responsibility (ISO 26000), supply chain security (ISO 28000), and risk manage- ment (ISO 31000).
ISO 9000 was originally oriented toward compliance, or what we have termed confor- mance quality. Customer needs were not included in the original ISO 9000 standard—you could make any product you liked, even if it did not sell, as long as the company had a quality system to ensure that it could make what it said it could. The ISO 9000 standard has been revised to include customer requirements, continuous improvement, and management leadership to ensure that quality meets customer needs, not just conformance to specifica- tions. The standard continues to be updated.
The ISO 9000 standards are meant to describe how a company should develop a system and processes for ensuring quality, but the benefits go beyond quality. Firms adopting the ISO 9000 standards, compared to those that have not adopted ISO 9000 standards, are more likely to survive, to experience greater growth in sales and employment, to pay employ- ees better wages, and to have fewer employment-related injuries. The ISO 9000 standards ideally apply to large and small companies and to simple and complex products. ISO 9000 standards also apply to services and to software development. Read the Operations Leader box on Physicians’ Clinic of Iowa and its efforts to become ISO certified.
The ISO 9000 standards specify that a company must have a quality system in place, including procedures, policies, and training, to provide quality that consistently meets customer requirements. A quality manual and careful record keeping are usually required as part of the documentation. ISO 9000 requires that the company have process flow- charts, operator instructions, inspection and testing methods, job descriptions, organiza- tion charts, measures of customer satisfaction, and continuous improvement processes.
LO8.8. Compare and contrast ISO 9000 standards and the Baldrige Award criteria.
TABLE 8.3 Changing Quality Assumptions
From To
Reactive Proactive Inspection Prevention Meet the specifications Continuous improvement Product-oriented Process-oriented Blame placing Problem solving Quality versus schedule Quality and schedule Cost or quality Cost and quality Operations only Marketing, engineering, and operations Predominantly blue-collar caused Predominantly white-collar caused Defects should be hidden Defects should be highlighted Quality department has quality problems Purchasing, R&D, marketing, and operations
have quality problems Subordinated to management team Part of management team General managers not evaluated on quality Quality performance part of general-
manager review Quality costs more Quality costs less Quality is technical Quality is managerial Schedule first Quality first
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to support medical professionals in their practices while improving their efficiencies and delivery of care. As a consequence, PCI identified how to exert better con- trol over documents, records, and nonconformity; how to audit and review key processes with an eye toward improvement; and how to initiate corrective and preven- tive actions. PCI is convinced that it is not unique. The health care sector, private or public, domestic or interna- tional, can benefit from ISO 9000 certification.
Source: Robert Burney, James Levett, and Paula Dolan, “ISO-Lating the Problem,” Quality Progress 42, no. 1 (January 2009), pp. 36–40; www.pcofiowa.com, 2020.
Physicians’ Clinic of Iowa (PCI), one of the largest private, multispecialty physician groups in Iowa, provides medi-
cal and surgical care in approximately 20 different specialties and subspecialties. Founded in 1997 in
Cedar Rapids, lowa, PCI currently has more than 80 board-certified physicians, surgeons, and other providers.
On November 10, 2003, PCI became ISO 9000 certi- fied. Certification did not happen overnight. The journey from when PCI leadership decided to seek certification to becoming certified took approximately 2.5 years, while consuming about $108,000 in training and auditing. In the first year following certification, PCI recouped more than its initial investment with cost savings of over $200,000. Since then, PCI has continued to seek recertification.
What motivated PCI to pursue ISO 9000 certifica- tion was the recognition that it needed to operate as a single organization, despite the diversity of specialties and being in five different locations. A single organiza- tion would allow PCI to have common goals, processes, and procedures that would be compliant with mandatory requirements by government agencies, as well as volun- tary requirements of accreditation organizations.
ISO 9000 offered PCI the answer to creating a com- prehensive, patient-centric quality management system
Physicians’ Clinic of Iowa Gets ISO Certified
OPERATIONS LEADER
McGraw-Hill Education/Mark Dierker
It is also expected that employees will be trained in the procedures and actually follow them in practice. To ensure compliance, certified ISO 9000 registrars audit the organiza- tion and determine whether the system in use conforms to the formal system description in their documentation. If no discrepancies are found, the registrar, who is external to the company, certifies the company’s plant or facility. The product itself is not certified as having high quality; only the process for making the product is certified. The ISO 9000 certification must be renewed periodically via return audits by a registrar.
ISO 9000 has had a major impact on worldwide quality practice. Many companies are requiring ISO 9000 certification of suppliers as a condition for doing business. The European Community has adopted ISO 9000 as a standard for selling in its markets and compliance with ISO 9000 is required by some European customers. ISO 9000 certifica- tion has caught on around the world, and many countries and companies are also requiring ISO 9000 certification of their suppliers.
ISO 9000 does not provide a complete quality system, because it does not address com- petitive strategy, information systems, and business results. A company can be making a product that satisfies the customer for a shrinking market and going out of business and still be ISO 9000 certified. Nevertheless, ISO 9000 is a good first step that addresses the funda- mental processes needed to ensure a quality product and high levels of customer satisfaction.
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8.10 MALCOLM BALDRIGE AWARD
The U.S. Congress established the Malcolm Baldrige National Quality Award in 1987 to promote better quality management practices and improved quality results by American industry. The criteria for the award have gained wide acceptance and are a de facto stan-
dard for “best quality practice” in the United States. Baldrige has require- ments similar to those of ISO 9000, but strategy, information systems, and business results are also required.
Each year the Baldrige Award is given to at most three organizations in each of six categories: manufacturing, service, small business, health care, education, and nonprofit. A few of the past winners are Milliken & Co., Federal Express, Sunny Fresh Foods, Ritz-Carlton, 3M, IBM, the University of Wisconsin at Stout, the Pearl River School District, and the city of Irving, Texas. To win this award these organizations exhibited high levels of quality management practice and performance excellence as indicated by the Baldrige criteria. During the first twenty years, Baldrige winners were mostly large manufacturing and service companies. Since then, many of the winners have been nonprofits, health care, education, and small businesses.
The Baldrige criteria recognize quality efforts that have senior manage- ment leadership, business results, employee involvement, control of internal processes, strong customer satisfaction, and so on. The specific categories of quality evaluated by the Baldrige examiners are listed in Table 8.4. These seven Baldrige categories are judged from a self-evaluation report prepared by each applicant for the award and a site visit by Baldrige examiners for applicants that pass an initial screening of the self-evaluation report.
The Baldrige criteria have 1000 points total, which are allocated among the seven categories shown in Table 8.4. These criteria have evolved from quality management to the more general “performance excellence” due to a
realization that the criteria are about achieving success of any enterprise. The first category, leadership, is based on senior management commitment, vision,
active involvement by all managers in the business, and the extent to which quality values have permeated the entire organization. It also includes societal responsibilities, ethical behavior, and community involvement.
The second category addresses strategy. A company cannot provide quality products and services unless it has a coherent business strategy that defines the target markets, com- petition, and how the company plans to compete (e.g., low cost or differentiation). Suc- cessful applicants have established high-level goals and strategic plans that are specific and have been implemented.
Category three is customers. Winning companies collect customer data from a variety of sources, including focus groups, market research surveys, and one-on-one contacts. The information should be acted on and used to direct the company toward customer needs and satisfied customers. Baldrige winners strive to delight their customers, not just minimally satisfy them. They often exceed customer expectations and anticipate customer needs.
Category four is measurement, analysis, and knowledge management. This category includes decision making based on hard data, sometimes called “management by fact.” The company’s database should be accessible to employees and should have comprehen- sive information on suppliers, internal processes, and customers. The information system must be integrated with processes and used for decision making in the company.
Malcolm Baldrige National Quality Award. Source: United States Department of Commerce
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The fifth category is workforce, a very broad area. This category includes employee involvement, continuous education and training, teamwork, and decision making by the workers. There is also an evaluation of motivation, rewards, recognition, and leadership development. Past Baldrige winners have been strong advocates of their workforce as the basis for all improvement efforts.
Operations, the sixth category, includes process definition, documentation, statistical process control, and the tools of process improvement. The best companies have in-depth understanding of their processes, and have integrated processes across functions, depart- ments, and the supply chain.
The seventh Baldrige category is results, and it accounts for the greatest number of points. This category includes product and process outcomes, customer-focused outcomes, financial and market outcomes, workforce outcomes, and leadership and governance outcomes. Stan- dard quality measures such as percent defective product, customer returns, and on-time deliver- ies are considered, along with profitability, return on investment, and market share. Successful companies can demonstrate improvement trends over time, not stellar results in one year only.
These seven categories represent a comprehensive framework for quality manage- ment and performance excellence in general. No standard approach is required to win the Baldrige Award. Each organization is free to choose its own specific techniques and approaches within the overall goals and criteria described above, and there is enormous
TABLE 8.4 Baldrige Execellence Framework, 2017–2018 Source: U.S. Department of Commerce, 2018.
Categories and Items
1 Leadership 120
1.1 Senior Leadership 1.2 Governance and Social Responsibilities
2 Strategy 85
2.1 Strategy Development 2.2 Strategy Implementation
3 Customers 85
3.1 Voice of the Customer 3.2 Customer Engagement
4 Measurement, Analysis, and Knowledge Management 90
4.1 Measurement, Analysis, and Improvement of Organizational Performance
4.2 Information and Knowledge Management
5 Workforce 85
5.1 Workforce Environment 5.2 Workforce Engagement
6 Operations 85
6.1 Work Processes 6.2 Operational Effectiveness
7 Results 450
7.1 Product and Process Results 7.2 Customer Results 7.3 Workforce Results 7.4 Leadership and Governance Results 7.5 Financial and Market Results
TOTAL POINTS 1000
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variety among the past winners. This is a strength of the Baldrige Award: It allows flexibility in defining performance excellence by individual companies and nonprofit organizations.
Many companies use the Baldrige criteria as a vehicle for internal assessment of their quality and performance improvement systems. They train their own managers to make Baldrige assessments of other divisions. The objective is not to win an award but to diag- nose strengths and weaknesses of their management system.
8.11 WHY SOME QUALITY IMPROVEMENT EFFORTS FAIL
Quality improvement is a proven strategy that has yielded significant financial benefits for many companies. Yet quality efforts have also failed or yielded marginal results in other companies. Some studies have indicated that only one-third of companies had obtained significant results from their quality improvement programs, one-third had achieved mod- erate results, and one-third were dissatisfied with the results. Why has this happened, and why have results been so inconsistent?
It may matter little which approach a company uses to improve quality that makes the difference; it’s the implementation process. To improve quality, a company must change its values, culture, and management philosophy, which is not easy.
One of the main reasons for quality implementation failure is the lack of leadership by middle and top management. Management should do much more than pay lip service to quality improvement efforts. They have the responsibility to institute a known system for quality improvement such as ISO 9000 or Baldridge. They must provide the resources for training, improvement specialists, and time for employees to participate in improvement. They need to track progress themselves and offer rewards for improvement. It is only with the full attention of management that quality will improve.
Some managers instinctively blame the employees when there is a quality failure. It doesn’t occur to them to look at the system and rules that employees work within. Only man- agers can change the underlying system causes of the quality problem, not the employees.
Managers who believe in trade-offs can also take quality improvement efforts off track. To them, consistent quality cannot be achieved without sacrificing the schedule or cost. When they must decide to ship the product or fix a quality problem, these managers will ship the product and fix the problem later. They also believe that it is too expensive to pro- duce good quality. These managers don’t realize that consistent quality and prevention can save money and drive better results in schedule, flexibility, and delivery.
Managers sometimes interfere with teamwork, which is often essential to achiev- ing good quality. Either they do not really delegate decision making to the team or they continue to reward individual performance over team performance. The reward system is ingrained in the organization and is one of the most difficult things to change.
Finally, many quality efforts fail because suppliers are not certified for a functioning quality system. Suppliers attempt to inspect quality into the product rather than develop a preventive approach to quality system design. As a result, the customer cannot rely on consistent quality.
Thus, producing quality requires a systems approach to management, which must be driven by customer needs. This approach conflicts with the philosophies and values of some companies. Quality improvement therefore requires deep cultural change. Executives have to lead by example to make the transformation.
The only way to institute successful quality improvement is through extensive education of all employees and constant leadership at all levels of management. With this approach, a quality system can be introduced into any service or manufacturing organization along with its supply chain, and the financial, human, and market results will be impressive.
LO8.9. Articulate some key barriers to successful quality improvement efforts.
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8.12 KEY POINTS AND TERMS
This chapter concerns the management for quality. The key points include:
∙ Quality is defined as meeting or exceeding customer requirements now and in the future. The four dimensions of product quality are quality of design, quality of confor- mance, the “abilities,” and field service.
∙ Five dimensions define service quality: tangibles, dependabililty, responsiveness, assur- ance, and empathy. These measures can be obtained by surveying customers.
∙ There is a cycle of product or service quality—from understanding customer needs through quality of design, production, and use by the customer. This cycle is controlled by specifying quality attributes, determining how to measure each attribute, setting quality standards, establishing a testing program, and finding and correcting causes of poor quality. Continuous improvement of the system through prevention of defects is the preferred approach.
∙ Supplier certification is a good way to ensure that suppliers have a quality system in place to prevent defects from occurring.
∙ Quality can both improve revenues and reduce costs. The cost of quality measures the lack of conformance to customer requirements. Quality costs can be divided into con- trol costs and failure costs. Control costs are due to prevention or appraisal. Failure costs may be due to internal or external failures.
∙ Two quality pioneers, Deming and Juran, have taken somewhat different approaches to quality but also have much in common. Deming argued that management needs to change for quality to improve. He also advocated the aggressive use of statisti- cal quality control techniques. Juran advocated the quality trilogy: planning, control, and improvement.
∙ ISO 9000 process certification is based on a set of standards that address meeting customer requirements and continuous improvement. It requires well-defined and documented procedures along with trained operators who implement them to ensure a quality process, a consistent quality product, and improvement.
∙ The Baldrige Award recognizes companies that achieve a total quality system as defined and measured by the Baldrige criteria. The criteria have become the common definition for excellence in quality and performance excellence for U.S. organizations.
∙ Quality improvement efforts fail when management does not lead by example and does not take a systems approach driven by customer needs.
Key Terms Quality management 143 Fitness for use 143 Customer satisfaction 143 Quality of design 144 Quality of conformance 144 Availability 145 Reliability 145 Maintainability 145 Field service 145 Service quality 146
Poka-yoke 149 Supplier certification 150 Cost of quality 151 Control costs 152 Failure costs 152 Deming 154 Juran 154 Quality trilogy 154 ISO 9000 156 Baldrige Award 158
SERVQUAL 146 Tangibles 146 Dependability 146 Responsiveness 146 Assurance 146 Empathy 146 Quality cycle 147 Standards 148 Tolerances 148 Mistake-proofing 149
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162 Part Three Quality
LEARNING ENRICHMENT (for self-study or instructor assignments)
ISO 9001 and ISO 9000 Certification Video https://youtu.be/lILXyEWOl8w 2:14
MidwayUSA Baldrige Award Winner Video https://youtu.be/DMRDpm7dGeg 5:26
How Health Care Uses Baldrige Video https://youtu.be/vz5xdfIfO9w 4:08
Cost of Quality: What Is It? Video https://youtu.be/vkeoBeGEDyw 2:48
Mistake Proofing (Poka-yoke) Website http://asq.org/learn-about-quality/process-analysis-tools/
overview/mistake-proofing.html
Discussion Questions 1. How can quality be measured for the following? a. Phone service b. Automobile repair c. Ballpoint pens 2. What are the differences between quality of design and
quality of conformance? 3. Product A has an MTBF of 30 hours and an MTTR of
5 hours. Product B has an MTBF of 40 hours and an MTTR of 2 hours.
a. Which product has higher reliability? b. Which product has better maintainability? c. Which product has greater availability? 4. Recall a bad service experience that you recently had.
What led to the service failure? Consider such dimen- sions as tangibles, reliability, responsiveness, assurance, or empathy.
5. Suppose you manufacture 10,000 wooden pencils per day. What would be an appropriate quality planning and control system for this product? Consider such factors as product attributes, measures of quality, tests, and so forth.
6. Can you name products and services that, in your opinion, have relatively poor quality? Relatively high quality? Are companies that provide better quality more successful? How can you tell?
7. How can supplier certification contribute to quality products or services? Should all suppliers be certified? Why or why not?
8. What products have recently been recalled? Why? Check the U.S. Consumer Product Safety Commission website.
9. Which of the four manufacturing quality dimensions are most likely to improve revenue? Which ones are related more to cost reduction or to both revenue and cost?
10. The following costs have been recorded: Incoming materials inspection $20,000 Training of personnel 40,000 Warranty 45,000 Process planning 15,000 Scrap 13,000 Quality laboratory 30,000 Rework 25,000 Allowances 10,000 Complaints 14,000 What are the costs of prevention, appraisal, external failure, and internal failure?
11. Which of Deming’s 14 points do you agree with and which ones do you disagree with?
12. Contrast and compare the Deming and Juran approaches to quality improvement. How different are these two approaches?
13. Why is ISO 9000 considered a first step or a basic approach to quality?
14. Critique the seven categories used by the Baldrige Award. Are there some items that you think are missing?
15. Compare the Baldrige-based approach to the use of ISO 9000.
16. What are some of the barriers to a successful quality implementation effort?
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C H A P T E R 9
Quality Control and Improvement
In 1924, Walter A. Shewhart of the Bell Telephone Labs developed a statistical quality control chart. Two others from the Bell Labs, H. F. Dodge and H. G. Romig, further devel- oped the theory of statistical quality control in the 1930s. But little was done in industry until World War II in the early 1940s. The war created demand for huge quantities of mili- tary goods from industry. The military required that industry adopt the new methods of statistical quality control to help ensure that the goods it ordered would meet government standards. As a result, statistical methods for control of quality were widely adopted by industry. In later years, however, these methods were abandoned, only to be rediscovered in the 1980s as a valid way to ensure quality products and services.
Service industries have been slower to adopt the methods of statistical quality con- trol. As a result, there is a tremendous opportunity to use these methods in service firms. Organizations in banking, health care services, airlines, and government offices find that quality control tools are useful for controlling and improving quality.
After reading this chapter, you should be able to:LEARNING OBJECTIVES
LO9.1 Describe the steps in designing a quality control system.
LO9.2 Design a process control system using control charts.
LO9.3 Define and calculate process capability.
LO9.4 Apply continuous improvement concepts using the seven quality tools.
LO9.5 Explain Six Sigma and the DMAIC process.
LO9.6 Differentiate lean and Six Sigma.
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164 Part Three Quality
The American Society for Quality (ASQ) serves as a society for quality professionals across all industries. While the initial emphasis was on statistical quality control methods, the focus has broadened to include understanding customer needs, quality management systems, and continuous improvement. ASQ helps quality professionals stay up-to-date on tools, techniques, and most importantly, current thinking about the importance of quality in industry. Read the Operations Leader box on Milliken & Company and how it uses sta- tistical methods for quality control.
In applying quality control and improvement methods, we recognize that an organi- zation consists of many interrelated processes that need to be controlled to produce qual- ity products and services. It follows that quality control and continuous improvement are highly cross-functional in nature and require the participation and support of the entire organization.
All business students are likely to encounter quality control and improvement in their career. Accounting will find that quality-related costs are reduced by 20 to 30 percent of sales when quality in production processes is well-controlled. In human resources, imple- mentation of quality programs requires in-depth workforce training on managing improve- ment projects, statistical training, and learning to inspect their own output. Marketing will see a reduction in the number of defects produced, fewer customer complaints, and increased sales. Finally, finance will see the results of these efforts on the bottom line.
9.1 DESIGN OF QUALITY CONTROL SYSTEMS
The goal of quality control is to stabilize and maintain transformation processes (or more generally “processes”) to produce consistent output. All organizations consist of many interrelated processes that need to be controlled to produce quality outputs. Continuous improvement can occur only after a process is stabilized and under statistical control. Therefore, we treat quality control in the first part of this chapter before discussing con- tinuous improvement.
The design of quality control systems begins with process definition. Process definition requires a clear understanding of the transformation process. This can be a manufacturing process, a service delivery process, or an administrative process. Questions to answer in defining the transformation process include: what are the outcomes of the process, what are the process steps (or activities) to produce this outcome, and which process steps are associated with product or service quality attributes?
Of course, a process is typically composed of many subprocesses, each having its own intermediate product or service. A process can therefore be an individual machine, a group of machines, or any of the many clerical and administrative processes that exist in the organization. Each of these processes has its own internal customers and its own prod- ucts or services that are produced. The internal customer is the next process (or processes) downstream that receives the work output. For example, the customer of the design depart- ment is the machine shop that makes the parts. The customer of the machine shop is the assembly department that uses the parts. When a large production system is broken down into many smaller systems or processes, quality can be defined and controlled at each point along the way.
After identifying the processes that need to be controlled, critical control points can be chosen where inspection or measurement should take place. The types of measure- ment or tests required and the amount of inspection required at each of these points should be determined. Finally, management should decide who will do the inspection, the workforce itself or separate inspectors. Usually operator inspection by the worker
LO9.1 Describe the steps in designing a quality control system.
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at that point in the process is preferred because it places responsibility on those who make the product or service. Once these decisions are made, it is possible to design a complete system of quality control, which allows continuous improvement of a stable system.
1. The first step in designing a quality control system is to identify the critical points in each process where inspection and testing are needed. The guidelines for doing this are as follows:
∙ Ensure that incoming raw materials or purchased services meet specifications. Ide- ally, incoming inspection can be eliminated, or reduced to sampling, by certifying the supplier. Supplier certification is normally granted to suppliers that have dem- onstrated they use statistical process control (SPC) and other methods to achieve consistent quality performance. In this case, the products or services of the supplier can be used with confidence by the customer.
∙ Inspect products or services during the production process. As a general rule, the product or service should be inspected by operators before irreversible operations take place or before a great deal of value is added to the product. In these cases, the cost of inspection is less than the cost of adding more value to the product. A precise determination of where in the process the product or service should be inspected should be made from the process flowchart.
∙ The third critical inspection point is the finished product or service. In manu- facturing, final products are frequently inspected or tested before shipping or
Milliken & Company has won the Malcolm Baldrige National Quality Award and many other quality awards. The focus on quality helps Milliken & Company compete successfully against lower-cost global suppliers.
Source: www.milliken.com, 2020.
Milliken & Company, headquartered in Spartanburg, South Carolina, is a global leader in textiles, car- pets, and fire retardant fabric. An innovator at heart,
Milliken & Company has long led the way for “ knowledge-based” investment, employ-
ing over 100 PhDs, and has accumulated more than 5,000 patents worldwide. Today, Milliken & Company has 39 manufacturing facilities located in the United States, Europe, and China and employs approximately 7,000 associates globally.
Milliken & Company has a long history of deploying statistical process control (SPC) to help monitor process quality performance. In one example, SPC was used for an out-of-control process. To solve this problem, several people from different departments joined together. After analysis by the team, the process was brought under control and the process capability improved to where the process could consistently meet specifications.
Implementing SPC at Milliken & Company
OPERATIONS LEADER
Source: Photo by Charlie Rahm, USDA Natural Resources Conservation Service
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166 Part Three Quality
before the product is placed in inventory. At an automobile assembly plant, for example, a random sample of cars is taken directly off the assembly line and thor- oughly inspected for appearance and function. The defects are noted and fed back to assembly-line personnel so that they can correct the underlying causes. The defects are also used to compute a quality score for comparison among assembly plants.
It is usually far better to prevent defects from occurring than to inspect and correct defects after production. Nevertheless, some measurement via sampling inspection is necessary to maintain processes in a continuous state of statistical control and to facil- itate improvement. Thus, inspection cannot be eliminated, but it can be reduced by a vigorous process of prevention.
2. The second step in designing a quality control system is to decide on the type of mea- surement to be used at each inspection point. There are generally two options: measure- ment based on variables or attributes.
Variables measurement utilizes a continuous scale for product and service charac- teristics such as time, length, height, and weight. Examples of variables measurement are the dimensions of parts, the viscosity of liquids, and the time it takes to answer a customer service call.
Attribute measurement uses a discrete scale by counting the number of defective units or the number of defects per unit. When the quality specifications are complex, it usually is necessary to use attribute measurements. For example, a laptop may be clas- sified as defective if it fails any of a number of functional tests or if the appearance of the display is not satisfactory. In inspection of cloth, a defect can be defined as a flaw in the material and the number of defects per 100 yards can be counted during inspection. Determining the type of measurement to use also involves the specification of measur- ing equipment.
3. The third step in defining the quality control system is to decide on the amount of inspection to use. Generally, a production process that is in statistical process control minimizes the amount of inspection needed. Exceptions to this might be when process variables are difficult to define or when the consequences of failure are very high. For example, when human lives are at stake, both process control and inspection of every production unit may be used.
4. The final step in designing a quality control system is deciding who will do the inspec- tion. Usually, it is best to have workers inspect their own output and be responsible for the quality of their work (called quality at the source). A prevention program, along with worker responsibility for quality, will be less expensive than an extensive inspec- tion program. In high-contact services there is no choice but to have quality at the source, since the customer immediately perceives defects.
In some cases, the customer will be involved in inspecting the product or service. Some business customers station inspectors at suppliers’ plants to examine and accept or reject shipments before they are sent on to the customer. The government has inspec- tors in a variety of industries to ensure quality in the interest of public health and safety, for example, in the food supply chain.
A well-designed quality control system requires a series of management judgments and the participation of all functions. The control principles themselves are elemen- tary, requiring performance standards, measurement, and feedback of results to correct the process. The application of these principles in any specific situation is often com- plex. The guiding principle is to first control the system and then aim for continuous improvement of the resulting stable system.
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9.2 PROCESS QUALITY CONTROL
Statistical process control (SPC) utilizes inspection (or testing) of the product or service while it is being produced. Periodic samples of the product or service are taken. When inspection reveals that there is reason to believe that the product or service quality charac- teristics have changed, the production process is stopped. A search is carried out to deter- mine an assignable cause of the change in the product or service. This could be a change in the operator, machine, or material. When the cause is found and corrected, the process is started again. A process can be brought into a state of statistical control and maintained in that state through the use of quality control charts (also called control charts).
Process control is based on two key principles. The first is that random variability is pres- ent in any production process. No matter how perfectly a process is designed, there will be some random variability in quality characteristics from one unit to the next. For example, a machine filling cereal boxes will not deposit exactly the same weight in each box; the amount filled will vary around some average figure. The aim of process control is to find the range of natural random variation of the process and ensure that production stays within that range.
The second principle of process control is that production processes are not usually found in a state of statistical control when SPC is not being used. Due to lax procedures, untrained operators, improper machine maintenance, and so on, the variation being produced is usu- ally much greater than necessary. The first job of process control managers is to seek out these sources of unnecessary variation, the assignable cause variation, and bring the pro- cess into statistical control so that the remaining variation is due only to random causes.
Administrative processes in accounting, human resources, sales, marketing, and finance in most organizations are also not usually under statistical control. These processes can also be controlled using SPC. The same principles used to control production processes can be used to control administrative processes.
SPC is carried out using quality control charts. In the control chart shown in Figure 9.1, the y axis represents the quality variable or attribute characteristic that is being controlled and the x axis represents time or a particular sample taken from the process. The center line of the chart is the average of the quality characteristic being measured. The upper control limit represents the maximum acceptable random variation, and the lower control limit indicates the minimum acceptable random variation when the production process is
LO9.2 Design a process control system using control charts.
FIGURE 9.1 Quality control chart.
Average +
deviations
Upper control limit (UCL)
Center line (CL)
Lower control limit (LCL)
x
y
Time
Quality measurement
average
Average – 3 standard deviations
3 standard
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168 Part Three Quality
in a state of control. Generally speaking, the upper and lower control limits are set at ± three standard deviations from the mean. If a normal probability distribution is assumed, these control limits will include 99.74 percent of the random variation observed.
To understand this last point, take a look at the right side of Figure 9.1 showing a normal probability distribution rotated on its side. It indicates that the distribution mean (average) is located on the center line of the control chart and the tails of the distribution are outside the control limits by just a small amount. Thus, 99.74 percent of the sample observations that are taken and plotted on the graph in Figure 9.1 will fall inside the con- trol limits, as long as the process is in a state of control.
A state of statistical control is defined as a process with a constant mean and variance that is not changing over time. As long as these two measures of a process do not change, the only variation that occurs is due to random causes and not due to a change in the under- lying process. The purpose of a control chart is to determine when the process itself has, in a very high degree of likelihood, shifted or changed and is therefore out of control.
In using a control chart to ensure steady-state operation, periodic samples are taken and plotted on the control chart (see Figure 9.2). When the average of the variable or attribute measurement falls within the control limits, the production process is allowed to continue operating. From time to time, sample measurements signal that the process is no longer in a state of statistical control. One such signal is when measurements fall outside of the control limits. Other signals include measurements that, when plotted on the control chart, reveal a trend upwards or downwards; an oscillation where measurements alternate in a highly volatile up-down manner, or a pattern with many measurements being within one standard deviation of the center line. When this occurs, the process is not in a state of con- trol, and a search should be made to determine the assignable causes.
Assignable causes have also been termed special causes, those that cause points, for exam- ple, to fall outside of the control limits. Special causes are changes in materials, operator, or machine that can be corrected and control restored. In contrast, common causes of variation are those that randomly occur when the process is under statistical control. Common causes cannot be removed without changing the design of the process itself. Through use of control charts, the process can be maintained in a constant state of statistical control in which there is only natural random variation (common causes) in the output from the transformation process.
Quality can be monitored using slightly different control charts for attributes or for vari- ables. We cover each of these cases below.
FIGURE 9.2 Quality control chart example.
UCL
Sample 1 2 3 4 5 6
Q ua
lit y
M ea
su re
m en
t
CL
LCL
Stop the process; look for assignable cause
Stop the process; look for assignable cause
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9.3 ATTRIBUTE CONTROL CHART
A quality characteristic can be measured on a discrete scale (e.g., an item is either good or defective) rather than a continuous scale. An example of quality as an attribute is the per- centage of defectives occurring in a sample. Other examples of attribute measurements are the percentage of phone calls not answered within three rings, the percentage of customers who are dissatisfied, and the percentage of parts from a supplier that are defective.
When the quality characteristic is an attribute, the appropriate type of control chart to use is an attribute control chart. One particularly useful attribute control chart is the p chart for the percentage of defectives in the sample, corresponding to the quality characteristic of interest. For example, percentage defective is estimated by taking random samples of n units each from a process at specified time intervals. For each sample, the observed percent defective (p) is computed. These observed values of p are plotted on the p control chart, one for each sample.
To determine the center line and control limits of the p chart, we take a large number of samples of n units each. The p value is computed for each sample and then averaged over all samples to yield a value
_ p . This value of
_ p is used as the center line since it represents
Suppose 200 records are taken from a data entry operation at two-hour intervals to moni- tor the data entry process. If we collect 200 records every two hours for 11 times, we would have 11 samples, each with 200 records. The percentage of records in error for the past 11 samples is found to be .5, 1.0, 1.5, 2.0, 1.5, 1.0, 1.5, .5, 1.0, 1.5, and 2.0 percent. The average of these 11 sample percentages yields a
_ p = 1.27 percent, which is the cen-
ter line of the control chart. The upper and lower control limits are
UCL
=
.0127 + 3 √ ___________
.0127(.9873)
___________ 200
=
.0364
LCL
=
.0127 − 3 √ ___________
.0127(.9873)
___________ 200
=
− .0110
When the LCL is negative, it is rounded up to 0 because a negative percentage is impos- sible. The percent defective in each sample is then plotted on the p chart. Thus, we have the following p chart:
UCL3.64
1.27
0
Percent defective
Sample number
CL
LCL
Since all points are found to be in control, these 11 samples can be used to establish the center line and control limits. New samples of 200 records can now be taken, plotted on the p chart with data points moving toward the right over time, and interpreted to deter- mine whether or not the process is still in control. Note, the formulas use the number of items in each sample, 200, not the 11 samples taken. The 11 samples are immaterial to the calculations except to determine the process average,
_ p .
Attribute Control Chart: A p Chart Example
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170 Part Three Quality
the best available estimate of the true average percent defective of the process. We also use the value of
_ p to compute upper and lower control limits as follows:
UCL
=
_
p + 3 √ ________
_
p (1 − _
p ) _______ n
LCL
=
_
p − 3 √ ________
_
p (1 − _
p ) _______ n
In this case, the standard deviation of the process is the quantity under the square root sign. We are adding and subtracting three standard deviations from the mean to get the control limits. See the example of this computation for controlling computer data entry operations.
After the p chart is constructed with its center line and upper and lower control limits, new samples of the process are inspected, and the proportion defective in each sample is plotted on the chart as an individual point. If the percentage falls within the control limits, no action is taken. If the percentage falls outside the control limits (below the lower or above the upper), the process is stopped and a search for an assignable cause (material, operator, or machine) is made. After the assignable cause is found and corrected—or, in very rare cases, no assignable cause is found—the process is restored to operating condition and production is resumed.
9.4 VARIABLES CONTROL CHART
Control charts are also used for measurements of variables. In this case, a measurement of a continuous variable is made when each unit in the sample is inspected. As a result, two values are computed from the sample: a measure of central tendency (usually the aver- age) and a measure of variability (the range or standard deviation). With these values, two control charts are developed: one for the central tendency and one for the variability of the process. When the process is found to be out of control on either of these charts, it is stopped and a search for an assignable cause is made.
When variable measurement is used, two control charts are needed because the normal distribution is assumed and it has two parameters (mean and variance). Either the mean of the distribution can change or the variance (as measured by range) can change. As a result, we monitor both the average and the range of a process for control purposes.
Suppose that the average ( _ x ) and range (R) are computed each time a sample is taken. Then
a control chart for average and a chart for range will be used. The center line and control limits for the average chart (often referred to as the x chart or x-bar chart) are computed as follows:
CL
=
x
UCL = x + A 2 _
R LCL
=
x − A 2
_ R
where x (x-double bar) is the grand average of several past sample _ x averages and
_ R is the
average of several past sample R values. Recall that the range (R) is simply the largest value minus the smallest value in a sample. In the above formulas, A2 is a constant that includes three standard deviations from the average in terms of the range. Table 9.1 provides values of A2 for various sample sizes for the normal distribution. The center line and control limits for the range chart are computed as follows:
CL
=
_
R
UCL = D 4 _
R LCL
=
D 3
_ R
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Sample Size n A2 D3 D4 2 1.880 3.267 3 1.023 0 2.575 4 0.729 0 2.282 5 .577 0 2.115 6 .483 0 2.004 7 .419 .076 1.924 8 .373 .136 1.864 9 .337 .184 1.816 10 .308 .223 1.777 12 .266 .284 1.716 14 .235 .329 1.671 16 .212 .364 1.636 18 .194 .392 1.608 20 .180 .414 1.586 22 .167 .434 1.566 24 .157 .452 1.548
TABLE 9.1 Control Chart Constants Source: Factors reproduced from 1950 ASTM Manual on Quality Control of Materials by American Society for Testing and Materials, Philadelphia.
The Midwest Bolt Company would like to control the quality of the bolts produced. Each machine produces 100 bolts per hour and is controlled by a separate control chart. Every hour, a random sample of six bolts is selected from the output of the machine and the diam- eter of each sample bolt is measured. From the six diameters, an average and range are computed. For example, one sample produced the following six diameter measurements: .536, .507, .530, .525, .530, and .520. The average of these measurements is
_ x = .525,
and the range is R = .029. We also know that the grand average of all past samples is x = .513 and the grand average range is
_ R = 0.20. From these, the control chart param-
eters are computed as follows (see Table 9.1 for control chart constants with n = 6).
_ x Chart R Chart
CL
=
.513
UCL = .513 + .483(.020) = .523
LCL
=
.513 − .483(.020)
=
.503
CL
=
.020
UCL = 2.004(.020) = .040 LCL
=
0(.020) = 0
Once each sample point is plotted on the two control charts, the process is found to be out of control on average measurement and in control on range. (Note:
_ x = .525 is outside
the upper control limit on the _ x chart, also the value of R = .029 is within its control limits).
We should therefore stop the process and look for an assignable cause that is making the process produce bolts that are too large in diameter.
Variables Control Chart: The
_ x & R
Charts Example
9.5 USING CONTROL CHARTS
There are two issues of concern in using control charts. First, the problem of sample size must be faced. For an attribute control chart, samples should be fairly large, frequently in the range of 50 to 300 observations. As a general rule, the sample must be large enough to allow for the detection of at least one defective unit. For example, if the process being controlled produces 1 percent defective units, a sample size of at least 100 should be used to detect one defective unit on average. Control charts for variables require much smaller sample sizes, usually in the range of 5 to 10 units because each unit provides much more information.
The constants D3 and D4 in Table 9.1 provide three standard deviation limits for the range. The purpose of these constants is to help calculate the upper and lower control limits of the range chart as a function of sample size. A given sample size can be used in Table 9.1 to look up the appropriate values of A2, D3, and D4 for average and range charts.
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172 Part Three Quality
The second issue is how frequently to sample. This issue often is decided on the basis of the rate of production and the cost of producing defects in relation to the cost of inspection. A high- volume production process should be sampled frequently since a large number of defective units could be produced between samples. When the cost of producing defective units is high in relation to the cost of inspection, the process should also be sampled frequently. An example of a costly situation is one in which the entire production output must be screened when the process is found to be out of control. Another example is when raw materials costs are high, and produced units must be scrapped when inspection reveals a quality problem. In these cases, samples should be taken frequently, provided that the cost of sampling is not too high.
Control charts are widely used in industry for both products and services. In manu- facturing companies, control charts are frequently located on each machine to control the quality output of that machine. Quality measurements are taken periodically and plotted on the chart to ensure that the machine is still producing at its required tolerances and the average and range haven’t changed.
In service industries control charts are used to control the time or the percentage of defects from various processes—for example, the time it takes to answer a phone, the time it takes to serve a customer, or the time it takes to collect accounts receivable. Ser vice industries also use control charts to monitor and control the percentage of dissatisfied cus- tomers or the percentage of late payments, for example.
9.6 PROCESS CAPABILITY
Once a process has been brought under statistical control, process capability can be assessed. Process capability is simply the ability of the process to meet or exceed the tech- nical specifications obtained from customers. A process that is not capable of meeting specifications means that defective outputs are being produced. Moreover, it is important to remember that whether or not a process is in a state of statistical control and whether or not a process is capable are two separate issues. Just because a process is in a state of sta- tistical control does not mean that it is capable.
Whether or not a process is capable of meeting specifications can be determined by computing the process capability index Cp—the ratio of the specification (spec) width to the process width:
C p = Spec width ____________
Process width
If the process is centered within the specification range, as shown in both charts in Figure 9.3, Cp ≥ 1 will be a good indicator of the ability of the process to meet its speci- fications. Notice that the difference in the two charts, representing two processes, is the process standard deviation, or the variability in measures produced by the process.
In practical use, the specification width is computed as the difference between the upper specification limit (USL) and the lower specification limit (LSL). The process width is computed by using six standard deviations of the measurement being monitored (6σ). The standard deviation (σ) refers to variation in measurement in the individual items being produced. The logic for 6σ is that most of the variation of a measurement is included within ±3 standard deviations of the mean, or a total of 6 standard deviations. Thus we have
C p = Spec width ____________
Process width = USL − LSL _________
6σ
If the process is centered in the specification range and Cp = 1, the process is considered to be minimally capable of meeting the specifications. A process with Cp < 1 is not capable
LO9.3 Define and calculate process capability.
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FIGURE 9.3 Process capability index examples.
LSL USL
USL = 160 LSL = 100
Cp = 1
Cp =
σ = 10
100 160
Spec width Process width
USL – LSL 6σ
LSL USL
USL = 160 LSL = 100
Cp = σ =
100 160
=
Process width
Specification width
5 2
Fr eq
ue nc
y
Individual measure
Individual measure Fr
eq ue
nc y
If 99.9 percent quality standards were in effect, the following would happen:
• 114,500 mismatched pairs of shoes will be shipped this year. • 12 babies will be given to the wrong parents every day. • 2 million documents will be lost by the IRS this year. • 2.5 million books will be shipped next year with the wrong cover. • 5.5 million cases of soft drinks produced next year will be flat.
TABLE 9.2 When 99.9 Percent Quality Is Not Enough Source: http://www.math.psu .edu/tseng/class/99percent .html, 2018
and must be improved by reducing the standard deviation or increasing the specification width, if possible, to become capable.
For the normal distribution, if Cp = 1 and the process is centered within the specifications and under statistical control, 99.74 percent of the product or service produced will lie within the specifications, corresponding to a defect rate of 2600 parts per million (ppm).1 The figure of 99.74 percent can be obtained by using the normal probability distribution tables from Appendix A. If Cp = 1.33, then 99.9967 percent of the product will lie within the specifica- tions, corresponding to 33 ppm defective. Thus a slight increase in Cp causes a dramatic drop in the defective rate of the process. Customers often specify Cp values from 1 to 1.5 or even as high as 2.0, depending on their particular quality requirements. Table 9.2 shows why very high process capability and extremely low rates of defects may be required in some cases.
One problem with the Cp measure is that it requires the process to be centered in the specification range for an accurate measure of process capability. Because of this problem, a more widely used measure (Cpk) has been devised:
C pk = Min ( USL − μ
_ 3σ
, μ − LSL _ 3σ
)
where μ = the process mean value and σ = the process standard deviation.
1Note that 99.74 percent good product corresponds to (100 − 99.74) = .26 percent bad. The .26 percent can be converted to 2600 ppm by multiplying .0026 by 1,000,000.
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174 Part Three Quality
This slightly more complicated measure of process capability overcomes the centering problem by calculating the process capability for each half of the normal distribution and then taking the minimum of the two calculations. The result is shown in Figure 9.4a, where the value of Cpk = 0, while Cp = 1. This figure illustrates that the use of the Cp index when the process is not centered gives the wrong answer, since the process is not capable of meeting the specifications, whereas Cpk gives the correct answer with Cpk = 0. A further example is given in Figure 9.4b, where Cpk = 1, even though the distribution is not centered. In this case, the process is capable of meeting the specifications but could be improved by shifting the mean closer to the center of the specification range. Because Cpk more accurately reflects the actual process capability, it is the measure commonly used by industry.
At this point, notice that Figures 9.3 and 9.4 are capability charts of the distribution of individual measurements, not averages. In contrast, quality control charts are based on plotting the sample averages of the individual measures to determine if a process is in control. Thus, control charts and capability calculations serve two different purposes, one to control the process and the other to determine capability. Capability charts use individ- ual measures, not averages, because each individual item that is measured must be within specifications.
9.7 CONTINUOUS IMPROVEMENT
Continuous improvement is an ongoing effort to improve the process, product, or ser- vice. In the remainder of this chapter we deal with continuous improvement of processes that are already under statistical control. Continuous improvement is needed if a process is unable to meet customer specifications or other improvement is needed, perhaps to offer a better product with fewer defects. If a process is not under statistical control, it must be brought under control before continuous improvement begins. Assignable causes (machine, operator, or material) that are often quite easily found are eliminated to bring the process under control. When that has been done, then efforts can be made to eliminate common causes to improve the process further. Correcting common causes will require engineering efforts to redesign the process, not just finding special causes that can be easily corrected. Redesign can include specifying different input materials, buying a more capable machine,
LO9.4 Apply continuous improvement concepts using the seven quality tools.
FIGURE 9.4 Computation of Cpk.
LSL
100 130 160 100 115 130 160
USL USL = 160 LSL = 100
σ = μ = 100
Cp = Cpk =
LSL USL USL = 160 LSL = 100
σ = μ = 115
Cp = Cpk =
10
1 0
5
2 1Fr
eq ue
nc y
Individual measure (a)
Individual measure (b)
Fr eq
ue nc
y
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FIGURE 9.5 The seven quality tools. Source: Gitlow et al., Tools and Methods for Quality Improve- ment, 2d ed. (Burr Ridge, IL: Irwin, 1994).
Cause-and-Effect
Pareto Chart
Type
Fr eq
ue nc
y
Histogram
Measurement
Fr eq
ue nc
y Scatter Diagram
· · ·· ·
·· · · ·
· · ·
Variable 1
Va ri
ab le
2
· · ·
Check Sheet
observation
1
2
3
4
5
data
Flowchart
Control Chart
Time
UCL
LCL
x Pr
oc es
s M ea
su re
instituting a new training program for operators, or making a process design change. Con- tinuous improvement occurs only by correcting common causes.
Common causes are much more difficult to eliminate than special causes and thus require the use of the seven quality tools shown in Figure 9.5. When finding common causes to eliminate, teams of workers and engineers are often utilized. Table 9.3 summa- rizes the purpose of each of these tools for controlling and improving processes.
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176 Part Three Quality
The search for common causes and continuous improvement starts with flowcharting. Flowcharts describe the flow of work and the relationships among steps in the process, and reveal any unnecessary steps and waste that can be eliminated. A flowchart also identifies possible quality problems that need to be investigated via further data collection and analysis.
Data collection is done using check sheets, which are a tabular list used to collect data on the process. For example, a check sheet could contain critical process measurements taken at periodic intervals during the day and tabulated by the time taken. It can also be used to tabulate the frequency of certain defects or other quality-related events.
The next step in process improvement and problem solving is to display the data using a histogram. A histogram is a frequency count using data from the check sheet to show the form and shape of the distribution of the data. A histogram can indicate that some data points are outliers, or there may be odd shapes to the distribution that indicate skewness or possibly more than one mode or peak in the distribution.
A Pareto chart can be constructed to show the most important problems. In 1906, Vil- fredo Pareto observed that a few items in any population constitute a significant percentage of the entire group—the vital few. According to Pareto’s law, a few of the failure modes account for most of the observed defects.
Consider the following example of a Pareto chart. Table 9.4 provides a count of pos- sible reasons for hydraulic leaks found in assembling front-end tractor loaders in a factory. As is noted in the table, the most common reason for a leak (defect) is loose connections, followed by cracked connectors, and so on. These data are transferred to the Pareto chart in Figure 9.6 by first calculating the percentage of all defects belonging to each cause, and then arranging the causes from most to least frequent. Because it graphs the reasons for leaks in decreasing order of occurrence, the Pareto chart readily shows the importance of the various types of defects that have been found.
The Pareto chart shows which defects we should try to eliminate first. We see that we should investigate loose connections first because they occur most frequently. Of course, cracked connectors is a close second and should be investigated too, since these two causes account for 78.6 percent of all defects. Pareto analysis is very helpful when one is first studying a quality problem because it helps to focus problem-solving effort where it can have the most impact.
Tool Purpose
Flowcharts Understanding the process and identifying possible problem areas Check sheets Tabulating data on the problem area Histograms Illustrating the frequency of occurrence of measures Pareto charts Identifying the most important problems Cause-and-effect diagrams Showing possible causes of the problem Scatter diagrams Investigating relationships between two variables Control charts Holding the gains from process improvement
TABLE 9.3 Purpose of the Seven Quality Tools
Number Inspected (N) = 2347
Defective Items Number of Defectives Percent Defective
O-rings missing 16 3.9% Improper torque 25 6.1 Loose connections 193 46.8 Fitting burrs 47 11.4 Cracked connectors 131 31.8 Total 412 100.0%
TABLE 9.4 Defectives in Front-End Loader Hydraulics
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FIGURE 9.7 Cause-and-effect diagram for loose connections.
Workers
InexperienceContent
Training
Hose Fatigue
Method
Material
Type
Large Size
Small
Nuts
Stripped
ThreadsWrong sizeSurface
defect
Size
Torque
Errors Measurement
Experience
Inspector
Training Air pressure
Adjustment
Wear Measuring tools
Judgment
Judgment method
Material connectors
Loose connections
ToolsInspection
FIGURE 9.6 Pareto diagram.
400 100
75
50
25
Loose connections
Cracked connectors
Fitting burrs
Improper torque
O-rings missing
300
200
100N um
be r
of D
ef ec
tiv es
Pe rc
en ta
ge
The next step in the analysis is to take one of these failure modes, say, loose connec- tions, and generate ideas for the causes of failure. This is done by using the cause-and- effect diagram, also called an Ishikawa diagram, after Dr. Kaoru Ishikawa, who first used these diagrams in Japan.
A cause-and-effect (CE) diagram is shown in Figure 9.7 for the loose connections. The problem itself, the effect, is placed on the right side of the diagram. The various poten- tial causes of this problem are shown along the spine of the diagram and categorized, for example, as materials, workers, inspection, and tools. The appearance of this diagram sug- gests a fishbone analogy. The bones of the fish are the probable causes of the problem, but
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178 Part Three Quality
any cause can be listed. Each of the major causes is then broken down into more detailed causes, giving rise to more bones on the fish. For example, the worker cause is split into three possibilities: inexperience, fatigue, and training. Training in turn is divided into con- tent and method.
CE diagrams frequently are constructed by quality improvement teams that include the workers who produce the product or service. Through brainstorming, the team will iden- tify a wide variety of possible causes for a problem. Then the team or an individual can collect data to narrow down the potential causes before taking corrective action.
Additional data can be analyzed via a scatter diagram, which shows the relationship between two variables. If a particular cause and effect are suspected to be related, the rela- tionship will be apparent as a linear or curved pattern on the scatter diagram.
Using the seven quality tools makes it possible to reduce defects and thus improve qual- ity, not just control it. For example, in the case of hydraulic leaks, the quality improvement team may find that the loose connections are caused by the torque adjustment of the tools and the type of threads used that would require redesign of the connection. After these causes are corrected, the number of defects will be reduced. It is then possible to move to the second most frequent problem, which is cracked connectors. Perhaps new materials are needed in a revised design that are not so easily cracked. In this way, continuous improve- ment is achieved.
Once improvements have been made, the new process should be stabilized to hold the gains by using a new control chart. The original control chart from before process improvement will no longer be appropriate following the improvements. New charts with new center lines and upper and lower limits can be created, based on data from the improved process.
9.8 SIX SIGMA
Motorola invented the term Six Sigma quality in the 1980s to reflect a desire for very high levels of consistent quality in all its processes. At the time they realized that Japanese elec- tronics competitors were capable of beating them on quality and cost. Six Sigma equates to a defect rate of 3.4 parts per million (ppm), much better than they were capable of produc- ing at the time. Getting there would require removing common causes from their processes.
Six Sigma quality is related to the normal probability distribution, with sigma (σ) denot- ing the standard deviation of the processes. Most quality control charts are created for pro- cesses that are at three sigma. Six Sigma refers to a stretch goal for process performance, as well as the new DMAIC method for process improvement.
Six Sigma is a systematic method for process improvement that often uses the five steps defined by the acronym DMAIC:
1. Define: The process is selected for improvement, and the project charter is specified. 2. Measure: Quality variables valued by the customer are measured, and goals are set for
improvement. 3. Analyze: The root causes of the current defect levels are identified, and alternatives are
considered for process changes. The analyze step uses some or all of the seven quality tools.
4. Improve: The process is changed and checked for improvement. 5. Control: This step uses a control chart or measurements to ensure that the process
improvement is not lost over time.
LO9.5 Explain Six Sigma and the DMAIC process.
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The Six Sigma approach can be applied to processes in manufacturing, service, or admin- istrative areas.
A simple application of Six Sigma occurred when a Motorola component supplier had a quality problem. A Motorola quality professional with Six Sigma training used the DMAIC approach to define, measure, and collect data on the problem. Using simple his- tograms and normal probability plots she found the data had a bimodal distribution. She discovered that two machine operators were interpreting Motorola’s supplier requirements differently. The supplier followed up with retraining the operators and validating the mea- surement technique.
Motorola has also applied Six Sigma in the finance and accounting department to improve the cycle time to close books at the end of the month. It reduced this time from a couple of weeks to a couple of days by removing both special and common causes. The department also now measures how many errors were made in closing by tracking the sigma level each month.2
Rather than improving one process at a time, management should make a strategic choice of which processes to improve. Senior management should choose critical pro- cesses that are essential to implement the strategy of the firm. For example, top manage- ment may determine that the sales processes, the processes for hiring new employees, or a particular manufacturing process should be selected for improvement.
Once a process is selected for improvement a cross-functional team is formed since most processes cut across functional lines. A full-time trained process improvement spe- cialist, usually called a “black-belt,” is chosen to lead the improvement team. The team then sets out to make improvements by using the DMAIC approach.
2www.supplychaindigital.com, 2019; www.isixsigma.com, 2019.
Wine Enthusiast Magazine critic said, “This is the best tempranillo wine in this critic’s experience.” Tempranillo is a full-bodied red wine native to Spain.
Source: http://sixsigmaranch.com, 2019.
Six Sigma Ranch & Winery brings the science of Six Sigma methods to the craftsmanship of winemaking. Owner Kaj Ahlmann, with a background in math and sta- tistics, applied Six Sigma techniques in previous work at General Electric. He became convinced the techniques could be applied to winemaking as well. He was so confi- dent that he named a winery after the Six Sigma process.
Six Sigma Ranch and Winery works toward accom- plishing one goal: making wine of extraordinary quality at an affordable price. Specifically, Six Sigma methods have been used for:
• Vineyard site selection • Selecting grapevine root stocks • Vineyard pruning • Grape harvest • Fermentation management
Six Sigma Ranch & Winery is located an hour north of the well-known wine region of Napa Valley, California. A
Six Sigma Ranch & Winery
OPERATIONS LEADER
Pixtal/AGE Fotostock
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180 Part Three Quality
The team begins improvement by flowcharting the process and defining process defects, using measures that are critical to the customer. Data are collected on these measures to establish a current process baseline and goals for improvement. For example, if the process is currently producing 1 defect in 100 opportunities (1 percent defective), a goal might be to improve the process to 1 defect in 1000 opportunities, a 10 times (10X) improvement factor. This kind of aggressive improvement approach is undertaken by Six Sigma teams to ensure that significant change is achieved. Of course, the improvement goal must not be set arbitrarily; rather, it is set on the basis of the economic benefit of improvement and the time available for the team to accomplish its goal, with three to six months being the typical project length.
Once the goal has been set, the team seeks the root causes of the current defect levels. The team must be careful to go beyond symptoms and find the real causes. This is often done by brainstorming and careful collection of data to analyze the situation. A variety of tools such as CE diagrams, scatter diagrams, and Pareto charts are used at this stage.
After root causes are found, alternatives for improvement are considered and improve- ments are made. Then, further data are collected to ensure that improvements have occurred, savings have been generated, and a control plan is put in place to ensure that the changes are permanent. Quality control charts can be used at this point to maintain the new process in a state of statistical control.
While the use of the Six Sigma approach is well established in manufacturing, Six Sigma is also being deployed to improve service or administrative processes. The context may be different but the DMAIC steps are equally applicable, as are the underlying prin- ciples. For an interesting application, read the Operations Leader box about Six Sigma applied to winemaking.
Six Sigma has produced dramatic results in companies such as Motorola, General Elec- tric, Citigroup, 3M, American Express, and Honeywell. These results are possible only through aggressive senior management leadership, widespread training in Six Sigma, use of full-time improvement specialists, and careful tracking of financial results. Six Sigma is not merely a quality improvement approach but also a way to improve the net income of the company. It is estimated that Six Sigma efforts have saved Fortune 500 companies in the U.S. well over $400 billion in the past 20 years.3
9.9 LEAN AND SIX SIGMA
Companies often combine lean and Six Sigma programs. While these approaches are com- plementary in nature, they also have several important differences in objectives, organiza- tion, methods, and type of projects. Table 9.5 compares differences between lean and Six Sigma. These differences are based on typical implementations of lean and Six Sigma, but definitions and usage vary widely in practice.
Objectives of Projects. Lean systems have the objective of eliminating waste defined as non-value-adding activities. Six Sigma efforts, by contrast, are aimed at reducing defects in the product or service. Thus, the objectives of these efforts are different, but at the same time they can be overlapping. For example, lean can attack defects as one of the seven wastes. Six Sigma can attack waste when it is causing a defect in the customers’ eyes, but would not normally attack internal waste such as excessive inventory, wasted motions, or
3https://www.sixsigma.com/why-six-sigma/.
LO9.6 Differentiate lean and Six Sigma.
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unnecessary movement of materials—typical lean activities. While Six Sigma tends to be used to reduce variance in processes, lean improves process flow.
Organization of Projects. Another difference is in the way these programs are organized. Six Sigma typically relies on full-time black belts as project leaders and vice president champions who select and oversee the projects. In contrast, lean systems rely on part-time project leaders and a more informal hierarchy. Lean improvements often involve the entire workforce, while Six Sigma projects are more selective in workforce involvement. Six Sigma black belt training is extensive and usually requires four weeks of training plus suc- cessful completion of one or more projects. Lean training is more informal and typically lasts only a week. Six Sigma programs are therefore different in how they are organized.
Methods Used. A third difference is in the methods employed. Lean thinking relies on a process that starts with the customer need. While Six Sigma also starts with a customer need, the highly structured DMAIC sequence of steps differs from those used in lean think- ing. Also, lean systems do not stress the use of data or statistical analysis to the same extent as Six Sigma. As noted in Table 9.5, value stream mapping is used in lean while Six Sigma does not use a particular type of flowcharting. Another important difference is that only lean uses the concept of pulling demand from the customer to flow the product or service. Finally, lean does not formally track project cost savings or revenue improvements, while Six Sigma insists on careful tracking by the finance function.
Types of Projects. The last area of difference is the type of projects undertaken. Lean proj- ects are usually simple and are often based on employee suggestions, but Six Sigma is used for complex and difficult process improvement projects. A typical Six Sigma project takes three to six months and is aimed at a large impact, often $200,000 in savings or more. Lean projects can last as little as one week using kaizen events and often have much less impact from each project. Lean programs will attack many more small improvement projects than Six Sigma and may not select projects for strategic importance.
Differences Lean Six Sigma
Objectives Reduce waste (non-value- added activities); waste can include, in part, defects
Reduce defects. Defects can include, in part, some non-value-added activities
Organization: Team leadership Part-time leaders (usually) Full-time leaders (usually) Use of champions Champions not used Vice president champions Workforce involvement Everyone is involved Only selected employees Training One week of training Four weeks for a black belt
Method used: Steps followed Five-step lean thinking DMAIC steps Data emphasis Less data-driven Statistical emphasis Flowcharting Value stream mapping Any flowchart method Use of pull systems Yes, pull from the customer Not part of Six Sigma Tracking financial impact Not typically done Closely tracked
Type of projects: Project complexity Simple projects Complex projects Time for completion One week or less Typically 3 to 6 months Number of projects Many small projects Fewer large projects Project selection Employee suggestions Strategic project selection
TABLE 9.5 Comparison of Lean and Six Sigma
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182 Part Three Quality
Both Six Sigma and lean are aimed at improvement, but in different ways. Thus, an organization already using lean can benefit from using Six Sigma to attack larger com- plex projects with a more formalized data-driven approach, using full-time project leaders to reduce defects and variance. Conversely, an organization using Six Sigma can benefit from the fast-hitting small-scale kaizen approach of lean, aimed at eliminating waste and improving process flow. Similarities are that both approaches start with identifying a true customer need that is not being met, and both are focused on process improvement.
Some companies are developing an integrated lean and Six Sigma approach. For example, they might use the DMAIC methodology and full-time project leaders from Six Sigma, and then incorporate the value stream mapping, pull systems, and waste reduction focus of lean. This approach would attack waste, improve flow, and reduce defects (vari- ance). For more detail view the video on Lean Six Sigma in the Learning Enrichment box below.
9.10 KEY POINTS AND TERMS
This chapter introduces methods for controlling and improving quality. The major points include the following:
∙ Quality control is defined as the stabilization and maintenance of a process to produce consistent output. Continuous improvement can occur once a stable process is achieved.
∙ Operations consists of a sequence of interconnected processes, each with its own inter- nal customers. Critical points must be defined for inspection and measurement to con- trol and improve these processes.
∙ Process control charts should be considered for critical points in the inputs (by the sup- pliers), as part of the process, and for the outputs. The critical control points are best identified in a flowchart of the process.
∙ Using process quality control, periodic samples are taken from a production process. As long as the sample measurements fall within the control limits, production is continued. When the sample measurements fall outside the control limits, the process is stopped and a search is made for an assignable cause—operator, machine, or material. With this procedure, a production or service process is maintained in a continuous state of statistical control.
∙ It is preferable to use statistical process control instead of inspection whenever possible, because SPC is prevention-oriented. SPC can be used for internal quality control and achieving a certified-supplier status, which requires a stable production process.
∙ A process is capable when it can consistently meet its specifications with high prob- ability. This requires that the specification width (USL-LSL) is greater than the process variation width (6σ) for a process that is centered.
∙ Six Sigma is an organized and systematic approach to process improvement. It utilizes the five DMAIC steps: define, measure, analyze, improve, and control. Careful analysis using statistical tools is needed to identify the root causes of defects perceived by cus- tomers, analyze changes, and control the improved process.
∙ Companies are now combining lean and Six Sigma process improvement approaches. While these approaches both start with current customer needs, they are different in their objectives, organization, methods, and types of projects. However, they are com- plementary in seeking process improvement and can be used in an integrated fashion.
∙ There are seven quality tools that can be used to monitor quality, identify quality prob- lems, and conduct root cause analysis when quality problems occur.
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∙ Every function in the company can benefit from the application of quality control and improvement. Other functions outside operations, and suppliers and customers outside the company, will also benefit when quality control and improvement principles are used.
Key Terms Walter A. Shewhart 163 Internal customers 164 Critical control points 164 Operator inspection 165 Supplier certification 165 Variables measurement 166 Attribute measurement 166 Statistical process control 167 Assignable cause 167
Flowchart 176 Check sheet 176 Histogram 176 Pareto chart 176 Cause-and-effect diagram 177 Scatter diagram 178 Control chart 178 Six Sigma 178 DMAIC 178
Center line 167 Upper control limit 167 Lower control limit 167 State of statistical control 168 Special cause 168 Common cause 168 Process capability 172 Continuous improvement 174 Seven quality tools 175
LEARNING ENRICHMENT (for self-study or instructor assignments)
Introduction to LEAN Six Sigma Video https://youtu.be/DBKfGlP_NAg 3:14
DMAIC Example Video https://youtu.be/Pe4NKVEifxI 4:59
Honda Statistical Process Control Video https://youtu.be/Sdj-8ZBYYmo 6:48
How to Calculate an X-bar Chart Video https://youtu.be/RiKUZqW41UM 3:47
Cpk Explained by Professor Cleary Video https://youtu.be/ewHGNNzKjdU 6:35
Statistical Process Control Slide Share Website https://www.slideshare.net/anubijis/statistical- process-control-16017031
SOLVED PROBLEMS
1. p Control Chart A company that makes golf tees controls its production process by periodically taking a sample of 100 tees from the production line. Each tee is inspected for defective characteristics. Control limits are developed using three standard devia- tions from the mean. During the last 16 samples taken, the proportion of defective items per sample was recorded as follows:
.01 .02 .01 .03 .02 .01 .00 .02
.00 .01 .03 .02 .03 .02 .01 .00
Problem
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184 Part Three Quality
a. Determine the mean proportion defective, the UCL, and the LCL. b. Draw a control chart and plot each of the sample measurements on it. c. Does it appear that the process for making tees is in statistical control?
a. The mean proportion defective (center line) is
CL
=
(
.01 + .02 + .01 + .03 + .02 + .01 + .00 + .02 + .00 + .01 + .03 + .02 + .03 + .02 + .01 + .00 ) _________________________________________________________________________ 16
=
.015
UCL
=
.015 + 3 √
_________
.015(.985) _________ 100
= .015 + .0365
=
.0515
LCL
=
.015 − 3 √ _________
.015(.985) _________ 100
=
.015 − .0365
=
− .0215, which is negative
Therefore, the LCL = 0. b.
c. All the points are within the control limits. We can conclude that the process is in statis- tical control.
Solution
UCL
CL
LCL
.0515
.0150
0
.060
.050
.040
.030
.020
.010
0
p Control Chart
Sample Number
Pr op
or tio
n D
ef ec
tiv e
2 4 6 8 10 12 14 16
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Chapter 9 Quality Control and Improvement 185
Problem 2. _ x and R Control Charts A cereal manufacturer fills cereal boxes to an average weight
of 20 ounces and has an average range of 2 ounces when the filling process is in control. A sample size of 10 boxes is used in evaluating the process.
a. What are the CL, UCL, and LCL for the _ x and R charts?
b. A sample with the following 10 measurements was just taken: 20, 21, 19, 18, 19, 21, 22, 20, 20, 19. Is the process still in control?
Solution a. _ x Chart R Chart
CL = 20 CL = 2 UCL = 20 + .308(2) UCL = 1.777(2) = 20.616 = 3.554 LCL = 20 − .308(2) LCL = 0.223(2) = 19.384 = 0.446
Note: Table 9.1 is used to get the control chart constants. b. Process control charts need to be checked for both mean and range. The sample
mean is 199/10 = 19.9, and the sample range is 22 − 18 = 4. The range is out of control, above the upper control limit, but the mean is in control. They should stop the process and look for an assignable cause.
Problem 3. Process Capability (Cpk and Cp) The operations manager of an insurance claims- processing department wants to determine the claims-processing capability. Claims usually take a minimum of four days to handle. The company has a commitment to handle all claims within 10 days. On average, claims are processed in eight days and processing has a standard deviation of one day.
a. Compute Cp and Cpk for the claims-processing department. Based on these computa- tions, should the claims department improve its process?
b. Using the same data, recompute Cpk, but use an average claims-processing time of seven days instead of eight days.
c. Using the original data, recompute Cpk, but use a standard deviation of 2/3 of a day. Which change made the most improvement—the change in mean in part b or the change in standard deviation? Can you explain the results?
Solution a.
C p
=
10 − 4 _____ 6(1 )
= 1.000
C pk
=
Min {
10 − 8 _ 3(1 )
, 8 − 4 _ 3(1 )
}
=
Min { 0.667, 1.333 } = 0.667
The Cp calculation seems to indicate that the process is capable of performing within specification; however, since Cpk is less than 1.0, the process needs improvement if it is to become even minimally capable of meeting the customer service specifications.
b. If a reduced mean claim-processing time of seven days per claim is used,
C pk
= Min {
10 − 7 _ 3(1 )
, 7 − 4 _ 3(1 )
} =
Min { 1.0, 1.0 } = 1.0
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186 Part Three Quality
c. If a reduced standard deviation of claim-processing time of .667 day per claim is used,
C pk
= Min {
10 − 8 _ 3(.667)
, 8 − 4 _ 3(.667)
} =
Min { 1.0, 2.0 } = 1.0
Either change would result in the process being capable of meeting specifications. Since the mean processing time was not centered within the specification limits to begin with, shifting the mean processing time toward the center of the specification limits has exactly the same effect as decreasing the variation in claims-processing time. Ideally, the manager should strive for a reduction in both the mean and the variation of claims-processing time to enhance process capability.
Discussion Questions 1. Why did statistical quality control ideas catch on in the
1940s? 2. Suppose you make electronic calculators that contain
a chip purchased from a local vendor. How would you decide how much inspection to perform on the chips supplied to you?
3. For the following situations, comment on whether inspection by variables or by attributes might be more appropriate:
a. Filling packaged food containers to the proper weight.
b. Inspecting for defects in cloth. c. Inspecting appliances for surface imperfections. d. Determining the sugar content of candy bars. 4. Workers should be given more control over the inspec-
tion of their own work. Discuss the pros and cons of this proposition.
5. Why are most processes not in statistical control when they are first sampled for control chart purposes?
6. Define the purpose of continuous improvement of quality.
7. How is a Pareto chart used to improve quality? 8. Which technique would be useful for each of the fol-
lowing situations? a. To rank-order the causes of a quality problem.
b. To brainstorm the reasons why a product might have failed.
c. To find an assignable cause. d. To determine if a process range is under control. e. To reduce the variability of failures found in the
field under actual use of the product. f. To achieve the smallest possible variance in the time
it takes to wait on tables in a restaurant. 9. A cause-and-effect diagram is used to identify the pos-
sible causes of defects. Draw a CE diagram for the fol- lowing situations:
a. Your car doesn’t start in the morning. b. You received a low grade on your last exam. c. A student fails to graduate from college. 10. It has been said that Six Sigma is a metric, a process for
improvement, and a philosophy for managing a busi- ness. Explain these different perspectives.
11. Use the DMAIC steps to describe and improve the pro- cess of ordering a book from an Internet retailer. From the perspective of the retailer, what would be done in each of the steps?
12. How can lean and Six Sigma approaches work together in making process improvements?
13. If an organization was using neither lean nor Six Sigma, how would you decide which approach to use first?
Problems Two Excel spreadsheets are provided on Connect for assistance in solving the chapter problems. 1. Golden Gopher Airline issues thousands of aircraft board-
ing passes to passengers each day. In some cases a board- ing pass is spoiled for various reasons and discarded by the airline agent before the final boarding pass is issued to a customer. To control the process for issuing boarding passes, the airline has sampled the process for 100 days
and determined the average proportion of defective passes is .006 (6 in every 1000 passes are spoiled and discarded). In the future, the airline plans to take a sample of 500 passes that are issued each day and calculate the proportion of spoiled passes in that sample for control chart purposes. a. What is the sample size (n) for this problem? Explain
the significance of the 100 days used to determine the average proportion defective.
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Chapter 9 Quality Control and Improvement 187
b. Calculate the center line and the upper and lower con- trol limits, using three standard deviations for control purposes.
2. We have taken 12 samples of 400 book pages and found the following proportions of defective pages: .01, .02, .02, .00, .01, .03, .02, .01, .00, .04, .03, and .02. A page is con- sidered defective when one or more errors are detected.
a. Calculate the control limits for a p control chart. b. A new sample of 400 pages is taken, and 6 pages are
defective. Is the process still in control? 3. Each day 500 inventory control records are cycle-counted for errors. These counts have been
made over a period of 20 days and have resulted in the fol- lowing proportion of records found in error each day:
.0025 .0075 .0050 .0150 .0125 .0100 .0050 .0025 .0175 .0200
.0150 .0050 .0150 .0125 .0075 .0150 .0250 .0125 .0075 .0100 a. Calculate the center line, upper control limit, and
lower control limit for a p control chart. b. Plot the 20 points on the chart and determine which
ones are in control. c. Is the process stable enough to begin using these
data for quality control purposes? 4. A process for producing electronic circuits has achieved
very high yield levels. An average of only 8 defective parts per million is currently produced.
a. What are the upper and lower control limits for a sample size of 100?
b. Recompute the upper and lower control limits for a sample size of 10,000.
c. Which of these two sample sizes would you recom- mend? Explain.
5. Widgets are made in a two-shift operation. Management is wondering if there is any difference in the proportion of defectives produced by these two shifts.
a. How would you use the p control chart to determine if there is a difference between the two shifts? Explain.
b. On the first shift, samples of 200 units have been used and
_ p = .06. Calculate CL, UCL, LCL for the first shift.
c. On the second shift, six samples of 200 units have been taken with the proportion of defectives .04, .06, .10, .02, .05, and .03. Using the samples from the second shift, has the process mean shifted upward or downward? Explain.
6. In a control chart application, we have found that the grand average over all past samples of 6 units is x = 30 and
_ R = 5.
a. Set up _ x and R control charts.
b. The following measurements are taken from a new sample: 38, 35, 27, 30, 33, and 32. Is the process still in control?
7. The producer of electronic circuits in problem 4 has reconsidered the method of quality control and has decided to use process control by variables instead of attributes. For variables control, a circuit voltage will be measured using a sample of five circuits. The past aver- age voltage for samples of 5 units has been 3.4 volts, and the range has been 1.3 volts.
a. What would the upper and lower control limits be for the resulting control charts (average and range)?
b. Five samples of voltage are taken with the following results:
Sample 1 2 3 4 5
_ x 3.6 3.3 2.6 3.9 3.4
R 2.0 2.6 0.7 2.1 2.3
What action should be taken, if any? c. Discuss the pros and cons of using the variables
control chart versus the control chart described in problem 4. Which do you prefer?
8. A machining operation requires close tolerances on a certain part for automobile engines. The current specifi- cation for this measurement is 3.0 cm ± .001. The qual- ity control procedure is to take a sample of 4 units and measure each of the parts. On the basis of past samples of size 4, x = 3.0 and
_ R = .0020.
a. Construct average and range charts for this part. b. On the basis of the following data, is the process in
control?
Sample 1 2 3 4 5
_ x 3.0005 2.9904 3.0010 3.0015 3.0008
R 0.0024 0.0031 0.0010 0.0040 0.0010
c. Is the process creating output outside of its specifications?
9. The Robin Hood Bank has noticed a decline in daily deposits. The average daily deposit has been running at $109 million with an average range of $15 million over the past year. The deposits for the past six days have been 110, 102, 96, 87, 115, and 106.
a. What are the CL, UCL, and LCL for the _ x and R
charts based on a sample size of six days? b. Compute an average and range for the sample that
consists of the past six days. Do the figures for the past six days suggest a change in the average or range from the past year?
10. A grocery store purchases fresh fish every day from its supplier. It has ordered 100 pounds of fish each day, but the weight actually received varies from day to day with an average range of 6 pounds. Over the past five days it received the following weights of fish: 106, 94, 102, 100, and 97 pounds.
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188 Part Three Quality
a. Using this five-day sample, is the process of the fish supplier in control in average and range?
b. How can the supplier more carefully control the pro- cess to provide 100 pounds of fish each day?
11. As cereal boxes are filled in a factory, they are weighed for their contents by an automatic
scale. The target value is to put 10 ounces of cereal in each box. Twenty samples of three boxes each have been weighed for quality control purposes. The fill weight for each box is shown below.
a. Calculate the center line and control limits for the _ x
and R charts from these data. b. Plot each of the 20 samples on the
_ x and R control
charts and determine which samples are out of control.
c. Do you think the process is stable enough to begin to use these data as a basis for calculating x and
_ R
and to begin to take periodic samples of 3 for quality control purposes?
12. A certain process has an upper specification limit of 220 and a lower specification limit of 160. The process standard deviation is 6, and the mean is 170.
a. Calculate Cp and Cpk for this process. b. What could be done to improve the process capabil-
ity Cpk to 1.0? 13. A certain process is under statistical control and
has a mean value of μ = 130 and a standard devia- tion of σ = 8. The specifications for this process are USL = 150, LSL = 100.
a. Calculate Cp and Cpk. b. Which of these indices is a better measure of process
capability? Why? c. Assuming a normal distribution, what percent
of the output can be expected to fall outside the specifications?
14. A customer has specified that they require a process capability of Cp = 1.5 for a certain product. Assume that USL = 1100, LSL = 700, and the process is cen- tered within the specification range.
a. What standard deviation should the process have? b. What is the process mean value? c. What can the company do if it is not capable of
meeting these requirements?
Observation Sample 1 2 3
1 10.01 9.90 10.03 2 9.87 10.20 10.15 3 10.08 9.89 9.76 4 10.17 10.01 9.83 5 10.21 10.13 10.04 6 10.16 10.02 9.85 7 10.14 9.89 9.80 8 9.86 9.91 9.99 9 10.18 10.04 9.96 10 9.91 9.87 10.06 11 10.08 10.14 10.03 12 9.71 9.87 9.92 13 10.14 10.06 9.84 14 10.16 10.17 10.19 15 10.13 9.94 9.92 16 10.16 9.81 9.87 17 10.20 10.10 10.03 18 9.87 9.93 10.06 19 9.84 9.91 9.99 20 10.06 10.19 10.01
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iv
Pa rt
10. Forecasting
11. Capacity Planning
12. Scheduling Operations
13. Project Planning and Scheduling
Operations managers are responsible for providing sufficient capacity to meet their firms’ needs. Forecasting is a prerequisite for any capacity or scheduling decisions. The forecasting chapter is followed by long-, medium-, and short-range capacity and scheduling decisions. ■
Capacity and Scheduling
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Forecasting
C H A P T E R 10
LO10.1 Describe why forecasting is important.
LO10.2 Describe the four common methods of qualitative forecasting.
LO10.3 Use forecast analytics to calculate a moving average and exponential smoothed average.
LO10.4 Evaluate forecast accuracy using a variety of methods.
LO10.5 Carry out forecast analytics for a causal model.
LO10.6 Evaluate factors that impact forecasting method selection.
LO10.7 Describe how big data analytics are used to forecast.
LO10.8 Explain the benefits and costs of CPFR.
LO10.9 Solve advanced forecasting problems.
After reading this chapter, you should be able to:LEARNING OBJECTIVES
Forecasting is the art and science of predicting future events. In organizations, managers are usually most interested in predicting future demand. Before appropriate software was available, forecasting was largely an art, but it has more recently developed into a science as well. Although managerial judgment is still required for forecasting, managers today are aided by both simple and sophisticated analytical tools and methods, as well as significant amounts of data from a wide variety of sources. For example, airlines forecast future capacity needs by analyzing their own historical demand data as well as data on the pricing and capacity of their competitors.
LO10.1 Describe why forecasting is important.
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Many different methods of forecasting and their uses are described here. Selecting the most appropriate forecasting analytics for a given situation must be done carefully for the par- ticular use it is intended to serve. There is no universal forecasting method for all situations.
Forecasts are almost always wrong! It is rare for sales to exactly match the amount fore- cast. A little variation from the forecast can often be absorbed by extra capacity, inventory, or rescheduling of orders. But large variations can wreak havoc in the business. For example, suppose 100,000 cases of a product are forecast to be sold in a particular year, but only 80,000 cases are actually sold. The extra 20,000 cases can end up in inventory, or workers might be cut to reduce production levels. It is equally painful if the forecast is too low. Then capacity is strained, overtime or extra workers may be added in a rush, or sales may be lost due to stockouts. Consumers often see the results of under- or over-forecasting in retail stores in the form of stockouts or clearance of leftover inventory. From these examples it is clear that forecasting has a strong impact on operations and, indeed, all functions in the business.
In recognition of inherent forecasting error, all forecasts should have at least two num- bers: one for the best estimate of demand (e.g., mean, median, or mode) and the other for forecast error (standard deviation, absolute deviation, or range). To produce forecasts with only an average is to ignore error, but this is a common occurrence in practice.
Given the challenge of getting the forecast “right,” there are three main ways for manag- ers to accommodate forecast errors. One is to try to reduce the error through better forecast- ing. The second is to build more flexibility into operations and the supply chain. The third is to reduce the lead time over which forecasts are required. This is because forecasting error usually increases as the forecasting time horizon increases, so next week’s forecast
have helped the hotel achieve an annual occupancy rate of 98.6 percent. How do they do it?
Cherokee first determines true customer demand, based on past demand and reservation requests that were denied (because facilities were full). Custom- ers provide their casino membership number when requesting reservations, making it easy for Chero- kee to track both accepted and denied reservation requests.
Next, Cherokee develops its daily forecast based on historical data. For example, the forecast for a particular Saturday might be based on demand for recent Satur- days as well as similar dates in previous years. The fore- cast model accounts for day of week, seasonality, trends, and other special-event factors.
Based on its forecast and knowledge about the price each customer segment is willing to pay, Chero- kee sets a room price for each customer segment on each day.
Source: Metters et al., “The ‘Killer Application’ of Revenue Management: Harrah’s Cherokee Casino & Hotel,” Interfaces, May—June 2008; and www.caesars.com/ harrahs-cherokee, 2020.
Harrah’s Cherokee Casino Resort, located in the town of Cherokee, North Carolina, draws about four million visitors each year. Its facilities include over 1100 hotel rooms. The Eastern Band of Cherokee Indians contracts with Harrah’s, the world’s largest gaming company, to manage the casino and hotel.
Sophisticated segmentation of customers, analysis of past demand patterns, and focused pricing strategies
A Winning Forecast for Harrah’s Cherokee Casino Resort
OPERATIONS LEADER
Steve Allen/Brand X Pictures/Jupiterimages
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192 Part Four Capacity and Scheduling
will usually have less error than next month’s forecast. Even good forecasts will have some error, but the smallest possible error along with reasonable forecasting costs is the goal.
Forecasting occupies a central role in the firm, and throughout the supply chain, because of its complexity and its impact on the business. Harrah’s Cherokee Casino Resort per- forms complex forecasting, as described in the Operations Leader box.
10.1 FORECASTING FOR DECISION MAKING
Although there are many types of forecasting, this chapter focuses on forecasting demand for output from the operations function. Demand and sales, however, are not always the same thing. Past sales data may not reflect real customer demand when stockouts occur. In this case, customer demand is greater than past sales and cannot be accurately forecast from historical sales data. Sales data must be adjusted, if possible, for lost sales.
We should also clarify the difference between forecasting and planning. Forecasting deals with what we think will happen in the future. Planning deals with what we think should hap- pen in the future. Thus, through planning, we consciously attempt to alter future events, while we use forecasting only to predict them. Good planning utilizes a forecast as an input. If the forecast is not acceptable, sometimes a plan can be devised to change the course of events.
Forecasting is one input to all types of business planning and control, both inside and outside the operations function. Marketing uses forecasts for planning products and ser- vices, promotion, and pricing. Finance uses forecasts as an input to financial planning. Human resources requires forecasts to anticipate hiring decisions and personnel budgets. Forecasting is an input for operations decisions on process design, capacity planning, and inventory. Forecasting is done by firms all along the supply chain.
For process design purposes, forecasting is needed to decide on the type of process and the degree of automation to be used. For example, a low forecast of future demand may indicate that little automation is needed and the process should be kept as simple as pos- sible. If, on the other hand, the forecast shows that demand is growing, management may decide that it is a good time to investment in automation.
Capacity decisions utilize forecasts for different planning horizons. For planning facilities, a long-range forecast several years into the future is needed. For medium-range capacity deci- sions, a more detailed forecast by product line or service will be needed to determine hiring plans, subcontracting, and equipment decisions. Short-range capacity decisions, including the assignment of available workers and machines to jobs, require a highly accurate forecast.
Inventory decisions resulting in purchasing actions tend to be short range in nature and deal with specific products. The fore- casts that lead to these decisions must meet the same require- ments as short-range scheduling forecasts: They must have a high degree of accuracy and individ- ual product specificity.
There are different types of decisions in operations with dif- ferent forecasting requirements,
Operations, Marketing, Finance, and Human Resources collaborate to both create and use forecasts. mediaphotos/Getty Images
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as shown in Table 10.1. The table also shows some of the uses of forecasts in marketing, finance/accounting, and human resources. And it indicates the three types of forecasting methods associated with these decisions: qualitative, time series, and causal.
In general terms, qualitative forecasting methods rely on managerial judgment; they do not use specific quantitative models. Qualitative methods are useful when there is a lack of data or when past data are not reliable predictors of the future.
There are two general types of quantitative forecasting analytics: time series and causal forecasting. Quantitative methods utilize an analytical model to arrive at a forecast. The basic assumption for all quantitative forecasting methods is that past data and data patterns are reliable predictors of the future. Forecasting relies on predictive analytics, con- structing a useful forecasting model from past demand and other relevant data.
In the remainder of this chapter, we refer to long, medium, and short time ranges. “Long range” will mean two years or more into the future, a common horizon for the planning of facilities and processes. “Medium range” is between six months and two years, the normal time frame for aggregate planning decisions, budgeting, and other resource acquisition and allocation decisions. “Short range” refers to less than six months, where the decisions involve procurement of materials and scheduling of particular jobs and activities.
10.2 QUALITATIVE FORECASTING METHODS
Qualitative forecasting methods utilize managerial judgment, experience, and relevant data, if available. Because judgment is used, two different managers using qualitative methods may arrive at widely different forecasts.
Some people think that qualitative forecasts should be used only as a last resort. This is not strictly true. Qualitative forecasts should be used when past data are not reliable indicators of future demand, for example, when changes in styles or technologies alter customer preferences. Qualitative forecasting must also be used for new product and new service introductions for which historical demand data are not available. In these cases, qualitative methods can be used to develop a forecast by life-cycle analogy or by the use
LO10.2 Describe the four common methods of qualitative forecasting.
TABLE 10.1 Forecasting Uses and Methods
Time Horizon
Accuracy Required
Number of Forecasts
Management Level
Forecasting Method
Uses of Forecasting for Operations Decisions
Process design Long Medium Single or few Top Qualitative or causal Capacity planning facilities Long Medium Single or few Top Qualitative and causal Aggregate planning Medium High Few Middle Causal and time series Scheduling Short Highest Many Lower Time series Inventory management Short Highest Many Lower Time series
Uses of Forecasting in Marketing, Finance/Accounting, and Human Resources
Long-range marketing programs Long Medium Single or few Top Qualitative Pricing decisions Short High Many Middle Time series New product introduction Medium Medium Single Top Qualitative and causal Cost estimating Short High Many Lower Time series Capital budgeting Medium High Few Top Causal and time series Labor planning Medium Medium Few Lower Qualitative and time series
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194 Part Four Capacity and Scheduling
Accuracy
Qualitative Methods Description of Method Uses
Short Term
Medium Term Long Term
Relative Cost
1. Delphi Forecast developed by a panel of experts answer- ing a series of questions on successive rounds. Anonymous responses are fed back on each round to all participants. Three to six rounds may be used to obtain convergence.
Capacity or facil- ity planning. To assess when technological changes might occur.
Fair to very good
Fair to very good
Fair to very good
Medium to high
2. Market surveys
Panels, questionnaires, test markets, or surveys used to gather data on market conditions.
Total company sales, major product groups, or individual products.
Very good
Good Fair High
3. Life-cycles analogy
Prediction based on the introduction, growth, and maturity phases of simi- lar products. Uses the S-shaped sales growth curve.
Long-range sales for capacity or facility planning.
Poor Fair to good
Fair to good
Medium
4. Informed judgment
Forecast by a group or an individual on the basis of experience, hunches, or facts about the situa- tion. No rigorous method is used.
Total sales and individual products.
Poor to fair
Poor to fair
Poor to fair
Low
Source: Exhibit adapted from David M. Georgoff and Robert Murdick, “Manager’s Guide to Forecasting,” Harvard Business Review, January–February 1986, pp. 110–120.
TABLE 10.2 Qualitative Forecasting Methods
of market research data. Note, a systematic approach to qualitative forecasting is possible even though judgment and experience is used.
Table 10.2 describes four of the best-known qualitative methods. Qualitative methods typically are used for medium- and long-range forecasts for planning process design or the capacity of facilities.
Both informed judgment and the Delphi method use expert opinion to arrive at a fore- cast. When informed judgment is used, a panel will discuss the forecast and arrive at a consensus. The danger of this method is that sometimes not all members of the panel are heard, and one person can dominate the panel in terms of the final forecast.
The Delphi method was developed to correct this situation. It consists of several rounds of anonymous data collection before reaching a forecast. In the first round, each member of the panel anonymously provides a forecast. Then the forecast information from all panel members is fed back to each panel member, again anonymously, along with any reasons or comments about their forecasts. In the second and subsequent rounds members can review the forecasts of the other panel members and then revise their forecasts if they find new information. After three or four rounds of data collection, there is a tendency for the fore- cast to converge to a range of forecast values, and members no longer adjust their forecasts on the basis of panel feedback. As a result, the Delphi panel arrives not only at a most
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likely forecast (e.g., mean, median, or mode) but also an estimate of forecast error (e.g., standard deviation, absolute deviation, or range).
Market surveys are commonly used to get information from potential customers about willingness to buy a product or service. A variety of methods can be used, including cus- tomer responses via phone, mail, or Internet. Also, test markets are an effective way to gauge customer demand.
The life-cycle analogy method is based on the idea that product or service demand has well-defined life stages (introduction, growth, and maturity) that follow an S-shaped curve. To gauge the shape of the curve, an analogy with a similar product or service is used. For example, an estimate of demand for a new website is based on the actual growth curve of similar websites.
Although we are not describing qualitative methods in detail, we note their usefulness in certain situations. Next, we turn to the first type of quantitative model: time-series ana- lytics, which are well suited to creating forecasts of a short-range nature.
10.3 TIME SERIES ANALYTICS
Time series analytics make detailed analyses of past demand patterns to predict demand in the future. One of the basic assumptions of all time series analytics is that demand can be decomposed into components such as average level, trend, seasonality, cycle, and
random error. A sample of these components for a rep- resentative time series is shown in Figure 10.1. When the components are added together (or in some cases multiplied), they will equal the original time series data pattern.
The level is the relatively constant average demand during a time interval. The trend is an increase or decrease in the average demand over time. Seasonality is a regularly repeated pattern of increasing and decreas- ing demand. It can be yearly (such as peak demand at a campus bookstore at the start of each semester), but can also apply to shorter time frames, weekly or daily. For example, a 24-hour call center experiences a seasonal demand pattern on a daily basis. Peak demand occurs during the day, moderate demand in the evening, and very little demand during the night. The cycle is increas- ing or decreasing demand over long time periods, often
FIGURE 10.1 Decomposition of time-series data.
Time
D em
an d
Original Time Series (Real Demand)
Time
D em
an d
Cycle
Seasonality
Level
Random error
Trend
Snow boarding is an industry that exhibits several demand patterns. It is primarily a seasonal industry, and over many years the industry has experienced a growth trend. Random factors like snowfall cause abrupt variations in demand. Adie Bush/Getty Images
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196 Part Four Capacity and Scheduling
many years. Cyclical changes in demand may be due to changes in the overall economy or changes in product or service life cycles, among other reasons. Random error reflects short-term fluctuations in demand that cannot be forecast.
The basic strategy used in time series forecasting is to identify the magnitude and form of each component on the basis of available past data. These components, except the ran- dom error component, are then used to estimate future demand in the form of a forecast.
In discussions of time series forecasting, the following symbols and terminology are used:
Observed Demands Forecasts at Time t
Data D1 D2 Dt–2 Dt–1 Dt Ft+1 Ft+2 Ft+3
Period 1 2 . . . t – 2 t – 1 t t + 1 t + 2 t + 3 . . .
↑ Present Time
Dt = demand during period t Ft +1 = forecast demand for period t + 1 et = Dt − Ft = forecast error in period t At = average computed through period t
We are at the end of period t, having just observed actual demand that defines the value of Dt and are making forecasts for future periods t + 1, t + 2, t + 3, and so on.
10.4 MOVING AVERAGE
The simplest analytics method of time series forecasting is the moving average. For this method, it is assumed that the time series has only a level component plus a random error component. No seasonal pattern, trend, or cycle components are assumed to be present in the demand data. More advanced versions of the moving average can, however, include these additional components.
When the moving average is used, a given number of periods (N) is selected for the computations. Then the average demand, At, for the past N periods at time t is computed as follows:
A t = D t + D t−1 + ⋯ + D t − N +1 __________________
N (10.1)
Since we are assuming that the time series is level (or horizontal), the best forecast for period t + 1 is simply the average demand observed through period t. Thus, we have
F t +1 = A t
Each time Ft+1 is computed, the most recent period of demand is included in the calculation of the average and the oldest period of demand is dropped. This procedure maintains N periods of demand in the forecast and lets the average move along as new demand data are observed.
In Table 10.3, a three-period moving average is used for forecasting purposes. Notice how the moving average is offset by one period to obtain the moving forecast. The forecast error is also shown in the table as the difference between actual and forecast demand. Always use the forecast for period t (Ft) in computing forecast errors, not the average for period t (At).
LO10.3 Use forecast analytics to calculate a moving average and exponential smoothed average.
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FIGURE 10.2 Time-series data.
Period Dt
(demand)
At (3-period moving
average)
Ft (3-period forecast)
Dt – Ft (error)
1 10 2 18 3 29 19.0 4 15 20.7 19.0 –4.0 5 30 24.7 20.7 +9.3 6 12 19.0 24.7 –12.7 7 16 19.3 19.0 –3.0 8 8 12.0 19.3 –11.3 9 22 15.3 12.0 10.0 10 14 14.7 15.3 –1.3 11 15 17.0 14.7 0.3 12 27 18.7 17.0 10.0 13 30 24.0 18.7 11.3 14 23 26.7 24.0 –1.0 15 15 22.7 26.7 –11.7
TABLE 10.3 Moving-Average Forecasts
} }
Using the numbers in Table 10.3 calculate a three-period moving average. The average for period 3, A3 is just the sum of demands from periods 3, 2, and 1 averaged over these three periods:
A 3 = (29 + 18 + 10) /3 = 19
The forecast for period 4 is equal to the moving average through period 3; therefore, F4 = 19. Once we know the actual demand in period 4, which is D4 = 15, we can calculate a forecast error as follows:
e t = D t − F t
The forecast error in period 4 is 15 − 19 = −4. Calculate the three-period moving average, forecast, and error for the remaining periods, for practice.
Example
2 4 6 8 100
10
20
30
40
12 14 Time period
D em
an d
Demand data Three-period moving average
Six-period moving average
The graph in Figure 10.2 shows the demand data from the example, the three-period moving average, and a six-period moving average. The six-period moving averages are: A6 = 19.0, A7 = 20.0, A8 = 18.3, A9 = 17.2, and so forth. It is a good idea to plot the data and forecasts when making comparisons. Notice how the six-period moving average responds
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198 Part Four Capacity and Scheduling
more slowly to demand changes than the three-period moving average. As a general rule, the greater the averaging periods, the slower the response to demand changes. A longer period thus has the advantage of providing stability in the forecast but the disadvantage of responding more slowly to real changes in the demand level. The forecasting analyst must select the appro- priate trade-off between stability and response time when selecting the number of periods in N.
One way to make the moving average respond more rapidly to changes in demand is to place relatively more weight on recent demands than on earlier ones. Any desired weights can be specified so long as they add up to 1. This is called a weighted moving average, which is computed as follows:
F t +1 = A t = W 1 D t + W 2 D t −1 + ⋯ + W N D t −N+1 (10.2)
with the condition
∑ i=1
N
W i = 1
If we have demands D1 = 10, D2 = 18, and D3 = 29, and weights of W1 = .5, W2 = .3, and W3 = .2, the three-period weighted moving average is:
A 3 = (.5)(29) + (.3)(18) = (.2)(10) = 21.9
According to the formula, the weight W1 is applied to the most recent demand in the third period (29), W2 to the second period (18), and W3 to the first period (10). Notice how the weighted moving average responds more rapidly than the ordinary moving average to the increased demand of 29 in the third period.
Example
One of the disadvantages of a weighted moving average is that the entire demand his- tory for N periods must be used in the computation. Furthermore, the responsiveness of a weighted moving average cannot be changed without changing each of the weights. To overcome these difficulties, the method of exponential smoothing has been developed.
10.5 EXPONENTIAL SMOOTHING
The second predictive analytics method for forecasting is useful for reducing the amount of past demand data that must be carried forward. Exponential smoothing is based on the sim- ple idea that a new average can be computed from an old average along with the most recent observed demand. Suppose, for example, we have an old average of 20 and we have just observed a demand of 24. The new average will be between 20 and 24, depending on how much weight we want to assign to the newest demand versus the weight on the old average.
To formalize this logic, we can write
A t = α D t + (1 − α) A t−1 (10.3)
In this case, At−1 is the old average (20), Dt the newest demand (24), and α the proportion of weight placed on the new demand (0 ⩽ α ⩽ 1).
To illustrate, suppose we use the values α = .1, Dt = 24, and At − 1 = 20. Then, from Equation (10.3), we have At = 20.4. If α = .5, we have At = 22, and if α = .9, we have At = 23.6. Thus At varies between the old average of 20 and the newest demand of 24, depending on the value of α used.
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If we want At to be very responsive to recent demand, we should choose a large value of α. If we want At to remain close to the old average, α should be small. Usually, α is given a value between .1 and .3 to maintain reasonable stability.
In simple exponential smoothing, just as in the case of moving averages, we assume that the time series is level with no cycles and that there are no seasonal or trend compo- nents. Then the exponentially smoothed forecast for the next period is simply the average obtained through the current period, offset one period from the smoothed average. That is,
F t +1 = A t
We can substitute the preceding relationship into Equation (10.3) to obtain the follow- ing equation:
F t +1 = α D t + (1 − α) F t (10.4)
Sometimes this alternative form of simple, or first-order, exponential smoothing is more convenient to use than Equation (10.3) because it uses forecasts instead of averages.
Another way to view exponential smoothing is to rearrange the terms on the right-hand side of Equation (10.4) to yield
F t +1 = F t + α( D t − F t )
This form indicates that the new forecast is the old forecast plus a proportion of the error between the observed demand and the old forecast. The proportion of error in the new forecast can be controlled by the choice of α.
Suppose we forecasted for period 5, F5 = 100, and observe the demand for period 5, D5 = 120. In this case we have an error of D5 − F5 = 20. If α = .1, then we add only 10 per- cent of this error to the old forecast to make the adjustment for the fact that demand has exceeded the forecast. Therefore, the forecast for period 6 is:
F 6 = 100 + (.1)(20) = 102
Note that in using a smoothing constant of .1 we are not overreacting to the fact that demand exceeded our forecast. However, if we want to react more quickly to demand increases, we could increase the value of α. For example, what is the forecast for period 6 if α = .5 or α = .7? (Answers: For α = .5, F6 = 110 and for α = .7, F6 = 114.)
Example
Students often ask why the name “exponential smoothing” has been given to this method. It can be mathematically shown that the weights on each preceding demand data point decrease exponentially, by a factor of (1 − α), until the demand from the first period and the initial forecast F1 is reached. Since the weights on the previous demands decrease exponentially over time and all the weights add up to 1, exponential smoothing is just a special form of the weighted moving average.
In Table 10.4, two exponentially smoothed forecasts are computed for α = .1 and α = .3, using the same demand data as in Table 10.3. These data are shown graphically in Figure 10.3. As can be seen, the α = .3 forecasts respond more rapidly to demand changes but are less stable than α = .1. Which of these forecasts is better?
Before answering this question, we’ll look at a few rows in Table 10.4. In row 1 the initial forecast for period 1, F1 = 15, is given as a starting value. The demand for period 1 is only 10 units, and so the forecast for period 2 will decrease. For α = .1 the new forecast F2 will be 14.5, and for α = .3 the new forecast will be 13.5. (Practice calculating these numbers yourself.)
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200 Part Four Capacity and Scheduling
FIGURE 10.3 Time-series data.
0
10
20
30
40
D em
an d
Demand data
α = .3
α = .1
2 4 6 8 10 12 14 Time period
α = .1 α = .3
Period Dt
(demand) Ft
(forecast) Dt − Ft (error)
Ft (forecast)
Dt − Ft (error)
MADt (α = .3)
TS (tracking signal)
1 10 15 −5.0 15 −5.0 6.4 −.8 2 18 14.5 3.5 13.5 4.5 5.8 −.1 3 29 14.85 14.15 14.85 14.15 8.3 1.6 4 15 16.26 −1.26 19.09 −4.09 7.1 1.3 5 30 16.14 13.86 17.86 12.14 8.6 2.5 6 12 17.52 −5.52 21.50 −9.50 8.8 1.4 7 16 16.97 −.97 18.65 −2.65 7.0 1.4 8 8 16.87 −8.87 17.85 −9.85 7.9 −.1 9 22 15.98 6.02 14.90 7.10 7.6 .9 10 14 16.58 −2.58 17.03 −3.03 6.2 .6 11 15 16.33 −1.33 16.12 −1.12 4.7 .6 12 27 16.19 10.81 15.78 11.22 6.7 2.1 13 30 17.27 12.73 19.15 10.85 7.9 3.1 14 23 18.54 4.46 22.40 0.60 5.7 4.4 15 15 18.99 −3.99 22.58 −7.58 6.4 2.8
∑(Dt − Ft) Bias 36.01 17.74 ∑|Dt − Ft| Absolute Deviation 95.05 103.38
*Assume F1 = 15 as a starting point. Also assume MAD0 = 7. See the text for definitions of MAD and tracking signal.
TABLE 10.4 Exponential Smoothing*
That is why we say that the forecast reacts more quickly to demand changes for higher values of α but is less stable, since we do not know if the underlying long-term average has changed or whether we are just seeing random fluctuation in the first period.
To answer the question of which is the best forecast, we need to look at forecast errors over many periods. Two measures of forecast accuracy are computed in Table 10.4 for 15 periods. One measure is simply the arithmetic sum of all errors, which reflects the bias in the forecasting method. Ideally, this sum should be zero, since the positive and negative errors should cancel out over time. In Table 10.4, both methods have a positive bias, with α = .1 producing more bias than α = .3.
The second measure of forecast error is the absolute deviation. In this case the absolute values of the errors are summed, so that negative errors do not cancel positive errors. The result is a measure of variance in the forecasting method. The total absolute deviation for α = .1 is less than for α = .3.
Thus, we have the interesting result that the α = .1 forecast has more bias but less abso- lute deviation than the α = .3 forecast. In this case, there is no clear preference between the two forecasting models; it depends on the manager’s evaluation of the importance of bias
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and deviation. However, if a forecast has both lower deviation and lower bias, it is clearly preferred.
To determine a good value for α, forecasts should be computed for several values of α. If one value of α produces a forecast with less bias and less deviation than the others, this value is preferred. If no clear preference exists, trade-offs between bias and deviation must be considered in choosing the preferred value of α.
The exponential smoothing method has the advantage that only one period of demand and forecast data must be carried forward. Simple exponential smoothing cannot always be used in practice because of trends or seasonal effects in the data. When these effects are present, higher-order smoothing, trend-corrected smoothing, or seasonal smoothing may be used. Some of these more advanced methods are presented in the chapter supplement.
10.6 FORECAST ACCURACY
An estimate of forecast accuracy should be computed along with the forecast average. This accuracy estimate might be used for several purposes:
1. To monitor erratic demand observations or outliers, which should be carefully evalu- ated and perhaps excluded from data analysis.
2. To determine when the forecasting method is no longer tracking actual demand and needs to be reset.
3. To determine the parameter values (e.g., N and α) that provide the forecast with the best accuracy.
There are four ways to measure long-run forecast accuracy over several periods. (Recall that et = Dt − Ft is the forecast error for period t.)
Note that n is the number of past periods used to compute the cumulative error measurements. We have already referred to the value of CFE as the bias in the forecast. Ideally, the bias
will be zero, which occurs if positive errors are offset by negative errors. However, if the forecast is always low, for example, the error will be positive in each period and the CFE will be a large positive number, indicating a biased forecast. In this case the forecasting method should be adjusted.
MSE and MAD measure the variance in the forecast error. The square root of MSE is the well-known standard deviation σ. MSE uses the square of each error term so that
LO10.4 Evaluate forecast accuracy using a variety of methods.
Cumulative sum of forecast errors
CFE = ∑ t=1
n
e t
Mean square error MSE = ∑ t=1
n
e t 2 _____
n
Mean absolute deviation of forecast errors MAD =
∑ t=1
n
∣ e t ∣ _____
n
Mean absolute percentage errors MAPE =
∑ t=1
n
| e t ___ D t | 100 __________ n
(expressed as a percentage)
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202 Part Four Capacity and Scheduling
positive and negative errors do not cancel each other out. MAD is computed from the abso- lute values of the error in each period instead of the squared errors. MAD is just the aver- age error over n periods without regard to the positive or negative sign of the error in each period. In practice, MAD is widely used because it is easy to understand and easy to use.
MAPE normalizes the error by computing a percentage error. This will make it possible to compare forecast errors for different time series data. For example, if one time series has low demand values and another has much higher demand values, MAPE will be an accu- rate way of comparing the errors for these two time series.
When exponential smoothing is used, it is common to calculate the smoothed mean absolute deviation period by period. MADt is the mean absolute deviation in time period t, which is defined as follows:
MAD t = α | D t − F t | + (1 − α) MAD t −1 In this case, the current MADt is simply a fraction α of the current absolute deviation plus (1 − α) times the old MADt−1. This is analogous to Equation (10.3), since the MADt is being smoothed in the same way as the forecast average. MADt is an exponentially weighted average of absolute error terms.
The current MADt should be computed for each period along with the forecast aver- age. The MADt can then be used to detect an outlier in demand by comparing the absolute value of the single period error (et) with the MADt. If the absolute error is greater than 3.75 × MADt, we suspect that the demand in period t may be an outlier. The multiplier 3.75 is used here because this is comparable to determining whether an observed value lies outside three standard deviations (σ) for the normal distribution. In Table 10.4, MADt was computed for α = .3. As can be seen, none of the demand errors fall outside 3.75 × MADt and so no outliers are suspected in the demand data.
The second use of MADt is to determine whether the forecast is tracking with the actual time series values. To determine this, a tracking signal is computed, as follows:
Tracking signal = TS = CFE ____ MAD t
The tracking signal is a ratio of bias (cumulative forecast error) in the numerator divided by the most recent estimate of MADt. If demand variations are random, control limits of ±6 on the tracking signal should ensure only a 3 percent probability that the limits will be exceeded by chance.1 Thus, when the tracking signal exceeds ±6, the forecasting method should be adjusted to more nearly match observed demand. In Table 10.4, the tracking signal does not exceed ±6 in any period. Therefore, the forecast is considered to be track- ing sufficiently close to actual demand.
As an example of these computations, refer to Table 10.4. In the last two columns of the table we have computed smoothed MADt and tracking signal. Starting with the arbitrary assumption that MAD0 = 7, we can compute MAD1 using α = .3:
MAD 1 = .3 | 10 − 15 | + .7(7) = 6.4 The tracking signal for period 1 is the cumulative error divided by MAD1:
TS = − 5/6.4 = − .8
As an exercise, compute MAD2 and the tracking signal for period 2 and compare your results to Table 10.4.
1The control limits and probability are based on the normal probability distribution and a value of α = .1.
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In computerized forecasting systems, it is extremely important to incorporate error controls of the type dis- cussed above. This will ensure that the forecast system does not run out of control. Instead, the user is notified when outliers in demand are detected or when the track- ing signal becomes too large.
10.7 ADVANCED TIME-SERIES FORECASTING
A variation of exponential smoothing is adaptive exponential smoothing. In one form, simple exponen- tial smoothing is used but the smoothing coefficient is varied at each forecast by ±.05 to determine which of the three forecasts has the lowest forecast error. The resulting value of α is used for the next-period forecast.
Another type of adaptive smoothing is to continually adjust α on the basis of current forecast error. If there is a large error, α will be large until the forecast comes back on track. When the error is smaller, α will also be small and a stable forecast will result. This method appears to work quite well for inventory forecasting situations.
Table 10.5 summarizes four time series forecasting methods. We have already discussed two of them, mov- ing average and exponential smoothing. The remaining two are described briefly below.
At Kellogg USA, demand for cereal is translated into forecasts, useful for inventory planning and meeting supply chain goals. Rick Souders/Getty Images
Accuracy
Time Series Methods
Description of Method Uses
Short Term
Medium Term
Long Term
Relative Cost
1. Moving averages
Forecast is based on arith- metic average or weighted average of a given number of past data points.
Short- to medium- range planning for inventories, production levels, and scheduling.
Poor to good
Poor Very poor Low
2. Exponential smoothing
Similar to moving average, with exponentially more weight placed on recent data. Well adapted to large number of items to be forecast.
Same as moving average.
Fair to very good
Poor to good
Very poor Low
3. Analytical models
A linear or nonlinear model fit- ted to time series data, usually by regression methods.
Limited, due to expense, to a few products.
Very good Fair to good
Very poor Medium
4. Box-Jenkins Autocorrelation methods are used to identify underlying time series and to fit the “best” model. Requires about 60 past data points.
Limited, due to expense, to products requiring very accurate short-range forecasts.
Very good to excellent
Fair to good
Very poor Medium to high
Source: Exhibit adapted from David M. Georgoff and Robert Murdick, “Manager’s Guide to Forecasting,” Harvard Business Review, January–February 1986, pp. 110–120.
TABLE 10.5 Time Series Forecasting Methods
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204 Part Four Capacity and Scheduling
A customized analytical model can be fitted to a time series with level, trend, and sea- sonal components. For example, a linear regression model or nonlinear methods can be used. In some cases, the resulting model may provide a more accurate forecast than expo- nential smoothing. However, a custom-fitted model is more expensive because an indi- vidual with advanced skills will be needed to develop it, and so the trade-off between accuracy and model cost must be considered.
Another option, the sophisticated Box-Jenkins method, has been developed for time-series forecasting. This technique permits more precise analysis of proposed models than is pos- sible with the other methods. The Box-Jenkins method requires about 60 periods of past data. For a special forecast involving a costly decision, the use of Box-Jenkins may be warranted.
In summary, time series methods are useful for short- or medium-range forecasts when the demand pattern is expected to remain relatively stable. Time series forecasts are often inputs to decisions concerning aggregate output planning, budgeting, resource allocation, inventory, and scheduling.
10.8 CAUSAL FORECASTING ANALYTICS
The second type of quantitative forecasting, causal forecasting analytics, develop a cause- and-effect model between demand and other variables. For example, the demand for ice cream may be related to population, the average summer temperature, and time. Data can be collected on these variables and analysis conducted to determine the validity of the pro- posed model. One of the best-known causal methods is regression, which is usually taught in statistics courses.
For regression methods, a model must be specified before the data are collected and the analysis is conducted. The simplest case is the following single-variable linear model:
y ^ = a + bx
where
y ^ = estimated demand x = independent variable (hypothesized to cause y ^ ) a = y intercept b = slope
Data are collected for x and y in this model, and the parameters a and b are estimated. Then estimates of future demand can be made from the above equation. Of course, more compli- cated models with multiple x’s can be developed.
We illustrate linear regression forecasting with a simple example. Suppose we are inter- ested in estimating the demand for bicycles on the basis of local population. The demand for bicycles over the past eight years (yi) and the corresponding population in a small city (xi) are shown in Table 10.6. We first com- pute the values of a and b for the regression line using one of many statistics packages, such as Excel Minitab, SPSS, JMP, or SAS. The result is a = −1.34 and b = 2.01. The best (least squares) equation for predicting demand for bicycles is thus y = −1.34 + 2.01x. From
LO10.5 Carry out forecast analytics for a causal model.
i yi xi
1 3.0 2.0 2 3.5 2.4 3 4.1 2.8 4 4.4 3.0 5 5.0 3.2 6 5.7 3.6 7 6.4 3.8 8 7.0 4.0
39.1 24.8
*The demand for bicycles, yi, is expressed in thousands. The population, xi, is expressed in ten thousands of people.
TABLE 10.6 Regression Example*
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this equation we can see that the rate of increase in bicycles is 2.01 (thousands) for each 10,000-person increase in population. This rate of increase, or trend, allows us to project bicycle demand in future years from population estimates, assuming that a linear equation continues to be a good fit with population as a predictor variable.
Other forms of causal forecasting—econometric models, input-output models, and sim- ulation models—are described in Table 10.7. In general, these models are more complex and more costly to develop than regression models. However, in situations in which it is necessary to model a segment of the economy in detail, an econometric or input-output model may be appropriate.
Simulation models are especially useful when a supply chain or logistics system is modeled for forecasting purposes. For example, suppose you want to estimate the demand for TVs. A simulation model can be built representing the distribution pipeline from the screen manufacturer, to the assembler, and finally to wholesale and retail distribution; all imports, inventories, and exports from the supply chain would be included. Using this model, a reasonable forecast for TVs several years into the future is obtained.
One of the most important features of causal models is that they are used to predict turn- ing points in the demand function. Because of this ability causal models are usually more accurate for medium- to long-range forecasts than time-series models that only predict trends. Causal models therefore are more widely useful for facility and process planning in operations.
Accuracy
Causal Methods Description of Method Uses Short Term
Medium Term
Long Term
Relative Cost
1. Regression This method relates demand to other external or internal variables that tend to cause demand changes. Uses least squares to obtain a best fit among the variables.
Short- to medium-range planning for aggregate production or inven- tory involving a few products. Useful where strong causal relation- ships exist.
Good to very good
Good to very good
Good Medium
2. Econometric model
A system of interdepen- dent regression equa- tions that describes some sector of economic sales or profit activity.
Forecast of sales by product classes for short- to medium-range planning.
Very good to excellent
Very good Good High
3. Input-output model
A method of forecasting that describes the flows from one sector of the economy to another. Pre- dicts the inputs required to produce required out- puts in another sector.
Forecasts of company- or country-wide sales by industrial sectors.
Not available
Good to very good
Good to very good
Very high
4. Simulation model
Simulation of the distribu- tion system describing the changes in sales and flows of product over time. Reflects effects of the distribution pipeline.
Forecasts of compa- nywide sales by major product groups.
Very good Good to very good
Good High
Source: Exhibit adapted from David M. Georgoff and Robert Murdick, “Manager’s Guide to Forecasting,” Harvard Business Review, January–February 1986, pp. 110–120.
TABLE 10.7 Causal Forecasting Methods
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206 Part Four Capacity and Scheduling
10.9 SELECTING A FORECASTING METHOD
In this section, we present a set of factors to consider for selecting a forecasting analytics method.
1. Use or decision characteristics. The forecasting method must be related to the use or decisions required. The use, in turn, is closely related to characteristics such as accuracy required, time horizon of the forecast, and number of items to be forecast. For example, inventory, scheduling, and pricing decisions by a big box retailer require highly accurate short-range forecasts for a large number of items. Time-series methods are ideally suited to these requirements. By contrast, decisions by an auto manufacturer involving process, facility planning, and marketing programs are long range in nature and require less accu- racy. Qualitative or causal methods tend to be more appropriate for those decisions. In the middle time range are aggregate planning, capital budgeting, and new product and new service introduction decisions, which often utilize time series or causal methods.
2. Data availability. The choice of forecasting method is often constrained by available data. An econometric model may require data that are simply not available in the short run; therefore, another method must be selected. The Box-Jenkins time series method requires about 60 data points (five years of monthly data). In some cases, data can be collected, but then time and resources must also be considered relative to the importance of the forecast. The quality of the data available is also a concern. Poor data lead to poor forecasts. Data should be checked for outliers.
3. Data pattern. The pattern in the data will affect the type of forecasting method selected. If the time series is level, as we have assumed in most of this chapter, a fairly simple method can be used. However, if the data show trends or seasonal patterns, more advanced methods will be needed. The pattern in the data will also determine whether a time series method will suffice or whether causal models are needed. If the data pattern is unstable over time, a qualitative method may be selected. One way to detect the pattern is to plot the data on a graph as the first step in forecasting.
An issue concerning the selection of forecasting methods is the difference between fit and prediction. When different models are tested, it is often thought that the model with the best fit to historical data (least error) is also the best predictive model. This is not true. For example, sup- pose demand observations are obtained for the last eight time periods and we want to fit the best time series model to these data. A polynomial model of degree seven can be made to fit exactly
through each of the past eight data points.2 However, this model is not necessarily the best predictor of the future.
The best predictive model is one that describes the underlying time series but is not force-fitted to the data. The correct way to fit models based on past data is to sep- arate model fit and model prediction. First, the data set is divided into two subsets, one for building the forecasting model and the other hold-out set for testing the predictive ability of the model. Several models based on reason- able assumptions about seasonality, trend, and cycle are then fitted to the first data set. These models are used to predict values for the second data set, and the one with the lowest error on the second set is the best model. This approach utilizes fit on the first data set and prediction on the second as a basis for model selection.
LO10.6 Evaluate factors that impact forecasting method selection.
2The model would be Y = a1 + a2t + a3t2 + . . . + a8t7, where t = time.
Retailers like Walmart use Google Analytics to understand changing consumer preferences. Montgomery Martin/Alamy Stock Photo
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Big data analytics are increasingly used in demand forecasting. Several surveys show that a majority of supply chain executives consider big data analytics to be one of the most important disruptive technologies in supply chain management today. Big data come from sources both inside and outside the firm. Internal data useful for forecasting can include, for example, sales and loyalty programs. In addition to internal data, useful external data might come from social media, or in the case of Walmart, from Google Analytics. Walmart monitored preholiday food searches to guide forecasting for ingredients to stock in their stores. When searches showed spikes in “tachos”—nachos with tater tots in place of chips—Walmart increased its stock of tater tots and highlighted the dish in ads. Service producers like Netflix also analyze big data, in their case to plan future shows that will attract large audiences.
There are three types of resources needed to carry out big data analytics for forecasting. First, firms need data, either collecting their own or acquiring it from other sources. Detailed data as to the quantity and timing of past demand for particular products may be useful for developing the types of quantitative models studied earlier in the chapter. Walmart, for exam- ple, collects data on more than one million customer transactions every hour. In addition, less structured data such as call center recordings might be studied, coded, and analyzed for insight into customer needs. This insight can be used to inform forecast models.
Second, firms need tools—hardware and software—to store and analyze the data. Cer- tain data sets may require significant computing capacity, and firms may need to outsource or acquire such capacity. And third, firms need experts with the capabilities to conduct the analysis. Such skills are not currently widespread in most industries. But as more data scientists, statisticians, and analysts are trained in methods including data mining and machine learning, more rapid forecasting cycles will become common. See the Operations Leader box on how Amazon is using big data to automate the forecasting processes.
LO10.7 Describe how big data analytics are used to forecast.
Big Data
customers. Those data are now used to develop and refine sophisticated forecasting analytics, enabling the entire forecasting effort to be automated.
Under a program called “hands off the wheel” the company is shifting tasks such as forecasting demand for millions of products to algorithms. Initially, workers could override the automated forecasts if they felt that they should. More recently, Amazon is discouraging such tinkering, and anyone overriding the automated forecast has to justify their reason.
Amazon is automating interaction with suppliers as well. An Amazon portal includes information on whether it is interested in buying a supplier’s product, the quan- tity (based on the automated forecast), and the price they will pay. Suppliers can simply check the portal for up-to- date information.
Source: “Amazon’s clever machines are moving from the warehouse to the headquarters,” by Spencer Soper, Bloomberg, June 13, 2018, and www.amazon.com, 2020.
Amazon.com, Inc. is famous for replacing warehouse workers with robots that carry out a variety of duties. Using big data analytics, automation is also replacing the humans who forecast demand and negotiate orders from suppliers.
Since it was founded in 1994 in Seattle, Washington, Amazon has collected data on the behaviors of online
Amazon’s Big Data
OPERATIONS LEADER
Lisa Werner/Getty Images
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208 Part Four Capacity and Scheduling
West Marine, the largest boating-supply retail chain in the U.S. opened its first store in Palo Alto, California, in 1975. Today, they have sales of more than $700 million from over 250 stores and an active website carrying products from kayaks and anchors to life jackets and wetsuits.
During planning processes, retail stores have primary responsibility for creating the demand forecasts for each item. Retailers base their forecasts on data such as sea- sonal forecasts, planned promotions, and future product assortment changes. These forecasts are then integrated with planning at the company’s distribution centers and its suppliers.
West Marine gains supplier buy-in for using CPFR by working closely with them to accommodate their materi- als planning schedules. Suppliers will know about special promotions well in advance so that lead times (often inter- national) can be managed.
Source: Larry Smith. “West Marine: A CPFR Success Story,” Supply Chain Management Review, March 1, 2006; and www.westmarine.com, 2020.
After 10 years of using collaborative planning, forecast- ing, and replenishment (CPFR) with 200 of its major sup- pliers, West Marine has seen forecast accuracy rise 85 percent, and 96 percent of products are in-stock in retail stores during their peak season.
CPFR Creates Waves for West Marine
OPERATIONS LEADER
Thorsten Henn/Getty Images
Large or small data sets can be helpful for improving forecasts, in most instances. How- ever, managers must balance the insights gained from forecast analytics with the time and cost of obtaining them. They should prevent detailed data analysis from slowing their deci- sion making, while similarly avoiding so-called “analysis paralysis”—a freeze and lack of action when facing unfamiliar and massive amounts of data.
10.10 COLLABORATIVE PLANNING, FORECASTING, AND REPLENISHMENT
Collaborative planning, forecasting, and replenishment (CPFR) is sharing information between business customers and suppliers in the supply chain during the planning and forecasting process. CPFR is a valuable way in which information systems are critical to daily operations and to supply chain performance. For example, a customer (e.g., retailer) may have information on planned sales promotions that are not known to the supplier. In this case a supplier’s forecast based on time series data alone would be inaccurate, but it could be adjusted if the retailer information is shared upstream with suppliers.
Using CPFR, the customer and supplier exchange information on their respective fore- casted demands. When there is a discrepancy in the forecasts, a discussion ensues to discover the basis for the difference. After discussion, an agreed forecast is developed that becomes the basis for replenishment planning. Note, this is a forecast and not an actual order from the customer that would typically be placed at a later time. The collaborative forecast gives vis- ibility into the replenishment planning processes beyond the usual ordering cycle.
LO10.8 Explain the benefits and costs of CPFR.
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CPFR works best in B2B relationships. Target stores, for example, share forecasted demand with suppliers. As a result the suppliers gain visibility into expected demand shifts and special sales promotions that Target is planning. CPFR helps coordinate the Target supply chain. See the Operations Leader box about West Marine for another example of the use of CPFR.
The important points to remember about CPFR are:
1. All parties must be willing to share sensitive information about demand, future sales promotions, new products, lead times, and so forth. Assurances must be provided that competitors will not have access to this proprietary information.
2. A long-term collaborative relationship that is mutually beneficial is needed. This will require an atmosphere of trust and ongoing management attention.
3. Sufficient time and resources must be provided for CPFR to succeed. In other words, there is a cost to receive the benefits of CPFR.
10.11 KEY POINTS AND TERMS
Demand forecasting analytics are crucial inputs to planning decisions within operations and other parts of business. In this chapter, we have highlighted several important uses and methods of forecasting. Some of the chapter’s main points are the following:
∙ Different decisions require different forecasting methods, including the following in operations: process design, capacity planning, aggregate planning, scheduling, and inventory management. Some of the decisions outside of operations that require fore- casts are long-range marketing programs, pricing, new product and new service intro- duction, cost estimating, and capital budgeting. The available methods may be classified as qualitative, time series, and causal methods.
∙ Four of the most important qualitative methods are Delphi, market surveys, life-cycle analogy, and informed judgment. These methods are most useful when historical data are not available or are not reliable in predicting the future. Qualitative methods are used primarily for long- or medium-range forecasting involving process design, facili- ties planning, and marketing programs.
∙ Time series forecasting is used to decompose demand data into their underlying compo- nents and to project the historical pattern forward in time. The primary uses are short- to medium-term forecasting for inventory, scheduling, pricing, and costing decisions. Some time series techniques are the moving average, exponential smoothing, math- ematical models, and the Box-Jenkins method.
∙ Causal forecasting analytics include regression, econometric models, input-output models, and simulation models. These methods are used in an attempt to establish a cause-and-effect relationship between demand and other variables. Causal methods can help in predicting turning points in time-series data and are therefore most useful for medium- to long-range forecasting.
∙ Two measures of accuracy in forecasting are bias and deviation. Both should be monitored routinely to control the accuracy of the forecasts obtained. For forecasting applications, tracking signal and MAD are two methods used to determine if bias and deviation, respectively, are well controlled.
∙ A forecasting method should be selected on the basis of five factors: user and system sophistication, time and resources available, use or decision characteristics, data avail- ability, and data pattern.
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210 Part Four Capacity and Scheduling
∙ Big data analytics are allowing firms to develop more sophisticated forecasts, using both internal and external data. Big data analytics requires data, computing capabilities, and expertise.
∙ CPFR is a method used to share and improve forecasts between customers and suppliers along the supply chain and thereby reduce forecasting errors.
Key Terms Qualitative forecasting methods 193
Quantitative forecasting analytics 193
Time series analytics 195 Level 195 Trend 195 Seasonality 195 Cycle 195
Forecast accuracy 201 Adaptive exponential
smoothing 203 Causal forecasting
analytics 204 Fit 206 Prediction 206 Big data analytics 207 CPFR 208
Random error 195 Moving average 196 Forecast error 197 Weighted moving average 198 Exponential smoothing 198 Simple exponential
smoothing 199 Bias 200 Absolute deviation 200
LEARNING ENRICHMENT (for self-study or instructor assignments)
Time Series Forecasting in Excel Video https://youtu.be/BveOFQhSUXU 6:21
Delphi Technique Video https://youtu.be/bHwohMjG9OA 3:02
How Forecasting Helps Your Business Website https://www.tradegecko.com/blog/ what-is-demand-forecasting-and-how-can-it-help-your-business
Top-Rated Forecasting Software Website https://www.capterra.com/sales-forecasting-software/
Big Data Analytics at Walmart Website https://blog.walmart.com/innovation/20170807/ 5-ways-walmart-uses-big-data-to-help-customers
More about CPFR Video https://youtu.be/cBM2g1j9q0s 2:12
SOLVED PROBLEMS
1. Moving Average, Weighted Moving Average, and Exponential Smoothing The weekly demand for chicken wings at a local restaurant during the past six weeks has been
Week 1 2 3 4 5 6
Demand 650 521 563 735 514 596
a. Forecast the demand for week 7 using a five-period moving average. b. Forecast the demand for week 7 using a three-period weighted moving average. Use
the following weights: W1 = .5, W2 = .3, W3 = .2.
Problem
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Chapter 10 Forecasting 211
a. Solution
Problem
Solution
F 7
=
A 6 =
D 6 + D 5 + D 4 + D 3 + D 2 _________________ n
=
596 + 514 + 735 + 563 + 521 _____________________
5
=
585.8
b. F 7
=
A 6 = ( W 1 × D 6 ) + ( W 2 × D 5 ) + ( W 3 × D 4 )
= (.5 × 596) + (.3 × 514) + (.2 × 735) =
599.2
c. F 7
=
A 6 = [(α) × D 6 ] + [ (1 − α) × F 6 ]
= [(.1) × 596 ] + [(1 − .1) × 600 ] =
599.6
d. We assumed the following: Future demand will be like past demand. No trend, sea- sonality, or cyclical effects are present. In the weighted-moving-average model, the more recent demand is considered more important than older demand. In the expo- nential smoothing model, an α value of .1 puts very little weight on current demand (10 percent), while most of the weight is put on past demand (90 percent).
2. Exponential Smoothing, Exponentially Smoothed MAD, and Tracking Signal The XYZ Company was flooded by a thunderstorm and lost part of its forecasting data. Positions in the table that are marked [a], [b], [c], [d], [e], and [ f ] must be recalculated from the remaining data.
Period Dt
(demand) Ft(α = .3) (forecast)
et = Dt = Ft (error)
α = .3 (MADt)
Tracking Signal
0 10.0 1 120 100.0 20.0 [a] 1.5 2 140 106.0 34.0 19.3 [b] 3 160 [c] [d ] [e] [f ]
a.
b.
TS t
=
CFE ______ MAD t
TS 2 = ( D 1 − F 1 ) + ( D 2 − F 2 ) ________________
MAD 2
=
20.0 + 34.0 _________ 19.3
=
2.8
MAD t
=
(α × | D t − F t | ) + [(1 − α) × MAD t −1 ] MAD 1 = (α × | D 1 − F 1 | ) + [ (1 − α) × MAD 0 ]
=
(.3 × | 120 − 100 | ) + [(1 − .3) × 10.0 ]
=
13.0
c. Forecast the demand for week 7 using exponential smoothing. Use an α value of .1 and assume the forecast for week 6 was 600 units.
d. What assumptions are made in each of the above forecasts?
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212 Part Four Capacity and Scheduling
e.
MAD t
=
(α × | D t − F t | ) + [(1 − α) × MAD t −1 ] MAD 3 = (α × | D 3 − F 3 | ) + [(1 − α) × MAD 2 ]
=
(.3 × | 160 − 116.2 | ) + [(1 − .3) × 19.3 ]
=
26.7
f.
TS t
=
CFE ______ MAD t
TS 3 = ( D 1 − F 1 ) + ( D 2 − F 2 ) + ( D 3 − F 3 ) ________________________
MAD 3
=
20.0 + 34.0 + 43.8 ______________ 26.7
=
3.7
Discussion Questions 1. Is there a difference between forecasting demand and
forecasting sales? Can demand be forecast from histori- cal sales data?
2. What is the distinction between forecasting and planning? 3. Qualitative forecasting methods should be used only as
a last resort. Agree or disagree? Comment. 4. Describe the uses of qualitative, time-series, and causal
forecasts. 5. Qualitative forecasts and causal forecasts are not par-
ticularly useful as inputs to inventory and scheduling decisions. Why is this statement true?
6. What type of time series components would you expect for the following products and services?
a. Monthly sales of natural gas (for heating and cooking).
b. Weekly sales of milk in a supermarket. c. Daily demand in a call center. 7. What are the advantages of exponential smoothing over
the moving average and the weighted moving average?
8. How should the choice of α be made for exponential smoothing?
9. Describe the difference between fit and prediction for forecasting models.
10. In the Stokely Appliance Company, marketing makes a forecast based on market surveys. Meanwhile, opera- tions makes a forecast based on past data, trends, and seasonal components. The operations forecast usually turns out to be 20 percent less than the forecast of the marketing department. How should forecasting in this company be done?
11. What types of big data sources might be useful for forecasting
a. Pajamas sold on a retail website? b. A new urgent care clinic? 12. Explain how CPFR can be used to reduce forecasting
error. 13. Under what circumstances might CPFR be useful, and
when is it not useful?
d.
e t
=
D t − F t
e 3 = D 3 − F 3 =
160 − 116.2
=
43.8
c.
F t+1
=
(α × D t ) + [(1 − α) × F t ]
F 3 = (α × D 2 ) + [(1 − α) × F 2 ] =
(.3 × 140) + [(1 − .3) × 106.0 ]
=
116.2
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Chapter 10 Forecasting 213
Problems Four Excel spreadsheets are provided on Connect for assis- tance in solving the chapter problems and supplement. 1. Daily demand for marigold flowers at a large garden
store is shown below. Compute: a. A three-period moving average for each period. b. A five-period moving average for each period.
Period Demand
1 85 2 92 3 71 4 97 5 93 6 82 7 89
2. The number of daily calls for the repair of Speedy copy machines has been recorded as follows:
October Calls
1 92 2 127 3 106 4 165 5 125 6 111 7 178 8 97
a. Prepare three-period moving-average forecasts for the data. What is the error on each day?
b. Prepare three-period weighted-moving-average fore- casts using weights of W1 = .5, W2 = .3, W3 = .2.
c. Which of the two forecasts is better? 3. The ABC Floral Shop sold the following number of gera-
niums during the last two weeks:
Day Demand Day Demand
1 200 8 154 2 134 9 182 3 147 10 197 4 165 11 132 5 183 12 163 6 125 13 157 7 146 14 169
Develop a spreadsheet for the following. a. Calculate forecasts using a three- and five-period
moving average.
b. Graph these forecasts and the original data using Excel. What does the graph show?
c. Which of the above forecasts is best? Why? 4. The Handy-Dandy Department Store had forecast sales
of $110,000 for the previous week. The actual sales were $130,000. a. What is the forecast for this week, using exponential
smoothing and α = .1? b. If sales this week turn out to be $120,000, what is the
forecast for next week? 5. The Yummy Ice Cream Company uses the exponential
smoothing method. Last week the forecast was 100,000 gallons of ice cream, and 90,000 gallons was actually sold. a. Using α = .1, prepare a forecast for next week. b. Calculate the forecast using α = .2 and α = .3. Which
value of α gives the best forecast, assuming actual demand is 95,000 gallons?
6. Using the data in problem 2, prepare exponentially smoothed forecasts for the following cases: a. α = .1 and F1 = 90 b. α = .3 and F1 = 90
7. Compute the errors of bias and absolute deviation for the forecasts in problem 6. Which of the forecasting models is the best?
8. At the ABC Floral Shop, an argument developed between two of the owners, Maya and Henry, over the accuracy of forecasting
methods. Maya argued that exponential smoothing with α = .1 would be the best method. Henry argued that the shop would get a better forecast with α = .3.
a. Using F1 = 100 and the data from problem 3, which of the two managers is right?
b. Graph the two forecasts and the original data using Excel. What does the graph reveal?
c. Maybe forecast accuracy could be improved. Try addi- tional values of α = .2, .4, and .5 to see if better accu- racy is achieved.
9. Only a portion of the following table for exponential smoothing has been completed. Complete the missing entries using α = .1.
Period Dt Ft et MADt
Tracking Signal
0 20 1 300 290 2 280 3 309
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214 Part Four Capacity and Scheduling
10. A candy store has sold the following number of pounds of candy for the past three days. Assuming α = .4, com- plete the following table.
Period Dt At Ft et MADt
Tracking Signal
0 16 1 1 20 2 26 3 14
11. A grocery store sells the following num- ber of frozen turkeys during the week prior to Thanksgiving:
Turkeys Sold
Monday 80 Tuesday 53 Wednesday 65 Thursday 43 Friday 85 Saturday 101
a. Prepare a forecast of sales for each day, starting with F1 = 85 and α = .2.
b. Compute the MAD and the tracking signal in each period. Use MAD0 = 0.
c. On the basis of the criteria given in the text, are the MAD and tracking signal within tolerances?
d. Recompute parts a and b using α = .1, .3, and .4. Which value of α provides the best forecast?
12. The famous Widget Company uses simple exponential smoothing to forecast the demand for its best-selling widgets. The company is considering whether it should use α = .1 or α = .3 for forecasting purposes. Use the following data for daily sales to arrive at a recommendation:
Day Demand Day Demand
1 35 8 39 2 47 9 24 3 46 10 26 4 39 11 36 5 26 12 43 6 33 13 46 7 24 14 29
Develop an Excel spreadsheet to answer the following questions.
a. For the first seven days of data compare the absolute deviation for forecasts using α = .1 and α = .3. Start with A0 = 33. Which method is best?
b. Use the second week of data to make the same com- parison. Use A7 = 32. Which method is best now?
c. What does this example illustrate? 13. The Easyfit tire store had demand for tires shown
below. Assume F1 = 198. a. Develop a spreadsheet using the first seven days of
demand to determine the best exponential smoothing model for values of α = .2, α = .3, and α = .4. Select the model with the smallest absolute deviation for seven periods.
b. Develop another spreadsheet using the second seven days to compare the best exponential smoothing model found in part a with a three-period moving- average model. Compare the predictions on the basis of the total absolute deviation.
c. What principles does this problem illustrate?
Day Demand Day Demand
1 200 8 208 2 209 9 186 3 215 10 193 4 180 11 197 5 190 12 188 6 195 13 191 7 200 14 196
14. The ABC Floral Shop from problem 3 is considering fitting various forecasting models on the first seven days of demand and using the second seven days as a hold-out sample for comparing the prediction accuracy of the models. They have decided to use α = .25, but aren’t sure what starting value of forecast, F1, to use.
a. Try values of F1 = 160, F2 = 170, and F3 = 180 to determine the best exponential model for the first seven days using the minimum total absolute devia- tion as the criterion. You may modify the spread- sheet from problem 8 for the calculations.
b. Compare the best model from part a to a three-period moving average model on the second set of data. Which one has the smallest sum of absolute errors?
c. What principles does this problem illustrate?
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Supplement
Advanced Methods This supplement describes three additional methods for time series forecasting that have trend and seasonal components. These methods are extensions of the techniques described in the chapter.
When the time series model has a trend component, an exponential smoothing model can be developed that is based on updating two variables in each time period: an average level and a trend. The average level is computed as an expanded version of the first-order equation to include trend, as follows:
A t = α D t + (1 − α)( A t−1 + T t−1 )
This average is then, in turn, used to update the estimate of trend by taking the difference in averages and smoothing this difference with the old trend. The updated trend is thus
T t = β( A t − A t −1 ) + (1 − β) T t −1
In this case, the smoothing constant β, which can be the same as or different from the con- stant α used for level, is used for trend. The model requires initial estimates of A0 and T0 to get started. These estimates can be based either on judgment or on past data.
Using the above values, we can compute forecasts for the future. The procedure is now slightly different from the first-order case, because a constant trend is assumed in the time series. The forecast for period t + K in the future is therefore
F t+K = A t + K T t K = 1, 2, 3, …
One unit of trend is added for each period into the future. An example using these formulas is shown in Table S10.1.
Time series that have both trend and seasonal components can be forecast. In this case, three variables—average, trend, and a seasonal factor—are updated for each time period.
The average is computed for period t as follows:
A t = α ( D t _
R t−L ) + (1 − α)( A t −1 + T t −1 )
In this case, the demand is adjusted by the seasonal ratio and smoothed with the old aver- age and old trend. The trend for period t is
T t = β( A t − A t−1 ) + (1 − β) T t−1
The seasonal ratio for period t is
R t = γ ( D t _ A t
) + (1 − γ) R t−L
LO10.9 Solve advanced forecasting problems.
t Dt (demand) At (average) Tt (trend) Ft (forecast) Dt – Ft (error)
1 85 85 15 85 0 2 105 100.5 15.05 100 5.00 3 112 115.2 15.01 115.55 –3.55 4 132 130.4 15.03 130.21 1.79 5 145 145.4 15.03 145.43 –.43
*Assume A0 = 70, T0 = 15, α =.1, β =.1.
TABLE S10.1 Trend-Adjusted Exponential Smoothing*
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216 Part Four Capacity and Scheduling
In this case, we are assuming that the seasonal cycle is L periods. There are L seasonal ratios, one for each period. If the demand is monthly and the seasonal cycle repeats on an annual basis, L = 12. Each month, one of the seasonal ratios will be updated to a new value, along with the trend and average.
The model requires initial estimates of A0, T0 and R0, R−1, . . . , R−L + 1. These initial esti- mates can be based on judgment or data if available.
According to the updated values, the forecast for future periods in period t is
F t + K = ( A t + K T t )( R t −L + K )
An example of this method is shown in Table S10.2. If there is no trend, this method can be used with seasonal factors alone. In this case, the
above trend equation and Tt values are simply dropped. One of the techniques used frequently in time series forecasting is classical decompo-
sition. This involves decomposing a time series into level, trend, seasonal, and possibly cyclic components. Decomposition is illustrated by an example with three years of quar- terly data from a store that sells children’s toys. It is assumed that the seasonal pattern is quarterly in nature, and there may be trend and level components in the data as well. Since only three years of data are available, no cycle component will be estimated.
The quarterly data on the sales of toys are shown in Table S10.3. The biggest sales of toys, by far, are in the fourth quarter. Visual inspection of the data indicates an upward trend—but how can this trend be disentangled from the seasonality of the data? This is done by first computing a four-quarter moving average. Decomposition requires the same number of periods in the moving average as the seasonality of the data (i.e., 4 periods for quarterly seasonality and 12 periods for monthly seasonality). This is done to average out the high periods and the low periods of demand over the seasonal cycle. The four-period moving average is shown in the third column of Table S10.3. These moving averages are centered between periods, because a four-period average should represent a point with two periods on each side. From column 3, the upward trend is clear, because the seasonality has been removed from the data.
To calculate seasonal ratios, we need an average for each period. This is done in column 4 of Table S10.3 by constructing a two-period moving average of column 3. These new aver- ages are then once again centered on the periods of data instead of between periods. Column 4 then represents the best average of the data for estimating the trend. It is also used to cal- culate seasonal ratios directly by dividing sales by column 4 to produce the seasonal ratios in column 5. Interpretation of these ratios is as follows: Demand in the third quarter is 95.8 per- cent of the annual average, demand in the fourth quarter is 170.9 percent of the yearly aver- age, and so on. To obtain a best estimate of the seasonal ratios, we simply average the ratios for corresponding quarters. This calculation is shown on the bottom of Table S10.3. Note that the seasonal ratios are quite stable in this example, but we have a minimal amount of data to work with. Ordinarily, at least four years of data should be used to establish seasonal ratios.
t Dt (demand)
At (average)
Tt (trend)
Rt (seasonal
ratio)
Ft (forecast)
Dt – Ft (error)
1 66 80.5 10.1 .804 64 2.0 2 106 90.1 10.0 1.195 108.7 –2.7 3 78 99.5 9.9 .799 80.4 –2.4 4 135 110.1 10.0 1.201 130.7 4.3
*Assume A0 = 70, T0 = 10, L = 2, R–1 = .8, R0 = 1.2, α = .2, β = .2, γ = .2.
TABLE S10.2 Seasonal Exponential Smoothing Method*
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Quarter Sales* Four-Period
Moving Average Two-Period
Moving Average Seasonal Ratio
1 30 2 42 3 55 57.4 .958 4 100 58.5 1.709 5 35 59.5 .588 6 46 62.5 .736 7 59 66.0 .894 8 120 68.4 1.754 9 43 71.3 .603 10 57 75.5 .755 11 71 12 142
Average
*Sales are in thousands of dollars.
TABLE S10.3 Classical Decomposition Method
Seasonal Ratios Quarter
1 2 3 4
.958 1.709 .588 .736 .894 1.754 .603 .755 .596 .746 .926 1.732
} }
} }
56.75 58 59 60 65 67 69.75 72.75 78.25
The original sales data and the de-seasonalized moving average, from column 4, are plotted in Figure S10.1. The moving average indicates an upward trend line. Actually, the trend might be slightly nonlinear, but let us assume for this example a linear trend line. Then a regression line can be fitted to the eight moving-average points shown on the graph. The result is
Y(t ) = 47.8 + 2.63t
where γ(t) = sales and t = time. A trend line could also be fitted to the original sales data, but it is customary in classical
decomposition to use moving averages before fitting the trend line. This seems to give a slightly more stable forecast.
FIGURE S10.1 Seasonal toy sales.
Quarter
Q ua
rt er
ly sa
le s
1 2
160
140
120
100
80
60
40
20
0 3 4 1 2 3 4 1 2 3 4
Sales Moving average Trend (regression)
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218 Part Four Capacity and Scheduling
To forecast sales for the coming year, the following method is used. First, use the trend- line equation to predict the average for quarters 13, 14, 15, and 16 by inserting these values of time into the above regression equation. This yields column 2 in Table S10.4. Then mul- tiply the seasonal ratio for each quarter by the predicted average. The result is a forecast for each quarter of the next year, as shown in Table S10.4.
Quarter Predicted Average × Seasonal Factor = Forecast
13 82.0 .596 48.8
14 84.6 .746 63.1
15 87.2 .926 80.7
16 89.9 1.732 155.7
TABLE S10.4 Seasonal Forecast Calculations
Supplement Problems 1. Ace Hardware sells spare parts for lawn mowers. The
following data were collected for one week in May when replacement lawn-mower blades were in high demand:
Day Demand
1 10 2 12 3 13 4 15 5 17 6 20 7 21
a. Simulate a forecast for the week, starting with F1 = 10, T0 = 2, α = .2, and β = .4. Use the trend model given in the chapter supplement.
b. Compute the MAD and tracking signal for the data. Use MAD0 = 0.
c. Are the MAD and tracking signal within tolerances? d. Simulate a forecast using simple smoothing for the
week, starting with F1 = 10 and α = .2. Plot the fore- cast and the demand on a graph. Note how the forecast lags behind demand.
2. The daily demand for chocolate donuts from the Donut-Hole Shop has been recorded for a two-week period.
Day Demand Day Demand
1 80 8 85 2 95 9 99 3 120 10 110 4 110 11 90 5 75 12 80 6 60 13 65 7 50 14 50
a. Simulate a forecast of the demand using trend- adjusted exponential smoothing. Use values of A0 = 90, T0 = 25, and α = β = .2.
b. Plot the data and the forecast on a graph. c. Does this appear to be a good model for the data?
3. The SureGrip Tire Company produces tires of various sizes and shapes. The demand for tires tends to follow a quarterly seasonal pattern with a trend. For a particular type of tire the company’s current estimates are as fol- lows: A0 = 10,000, T0 = 1,000, R0 = .8, R−1 = 1.2, R−2 = 1.5, and R−3 = .75. a. The company has just observed the first quarter
of demand D1 = 6000 and would like to update its forecast for each of the next four quarters using α = β = γ = .4.
b. When demand is observed for the second quarter, it is D2 = 15,000. How much error is there in the forecast?
c. Update the forecasts again for the coming year, using the second-quarter demand data.
4. Management believes there is a seasonal pattern in the above data for the Donut-Hole
Shop (see problem 2), with the first two days of a week representing one level; the third and fourth days repre- senting a second level; and the fifth, sixth, and seventh days a third level. Thus, three seasonal factors have been suggested: R0 = .9, R−1 = 1.3, and R−2 = .8.
a. Simulate a forecast of demand for days 1 to 7 using A0 = 85, T0 = 0, and α = β = γ = .1.
b. Comment on the appropriateness of the forecasts developed.
5. Management of the ABC Floral Shop believes that its sales are seasonal in nature with a monthly seasonal pat- tern and no trend. The demand data and seasonal ratios for the past three years are given as follows.
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Chapter 10 Forecasting 219
Month Year 1
Demand Year 2
Demand Year 3
Demand Seasonal
Ratio
Jan. $12,400 $11,800 $13,600 0.8 Feb. 23,000 24,111 21,800 1.8 Mar. 15,800 16,500 14,900 0.9 Apr. 20,500 21,000 19,400 1.6 May 25,100 24,300 26,000 2.0 June 16,200 15,800 16,500 1.0 July 12,000 11,500 12,400 0.7 Aug. 10,300 10,100 10,800 0.6 Sept. 11,800 11,000 12,500 0.7 Oct. 14,000 14,300 13,800 1.2 Nov. 10,700 10,900 10,600 0.9 Dec. 7,600 7,200 8,100 0.6
a. Calculate a forecast for Year 3 using A0 = 15,000, α = γ = .3, and the seasonal ratios shown above. For each period, calculate the forecast and the updated seasonal ratio.
b. Plot the original data and the forecast on a graph. c. Calculate the tracking signals for the past year using
MAD0 = 0. Are they within tolerances? d. Using the classical decomposition method described
in the chapter supplement, calculate the seasonal ratios from the data and determine the trend and aver- age levels. Use these ratios and estimates of trend and level to make a forecast for the next year.
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Capacity Planning
C H A P T E R 11
LO11.1 Define capacity and utilization.
LO11.2 Illustrate with an example a facilities strategy that considers: amount, size, timing, location, and type.
LO11.3 Explain how S&OP is done.
LO11.4 Identify the demand and supply options that are available for S&OP.
LO11.5 Contrast and compare the chase and level strategies.
LO11.6 Define the various costs associated with aggregate planning.
LO11.7 Create an alternative strategy for the Hefty Beer Company example.
After reading this chapter, you should be able to:LEARNING OBJECTIVES
In this chapter, we discuss capacity decisions related to carrying out the production of goods and services. Firms make capacity planning decisions that are long range, medium range, and short range in nature. Long-range decisions are concerned with facilities that typically extend one or more years into the future. The first part of this chapter describes facilities decisions and a strategic approach to making them. In this chapter we also deal with medium-range aggregate planning, which extends from six to eighteen months into the future. The next chapter discusses short-range capacity decisions of less than six months regarding the scheduling of available resources to meet demand.
Facilities, aggregate planning, and scheduling form a hierarchy of capacity decisions about the planning of operations extending from long, to medium, to short range in nature. First, facility planning decisions are long term in nature, made to obtain physical capacity that must be planned, developed, and constructed before its intended use. Then, aggregate
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planning determines the workforce level and production output level for the medium term within the facility capacity available. Finally, scheduling consists of short-term decisions that are constrained by aggregate planning and allocates the available capacity by assign- ing it to specific activities.
This hierarchy of capacity decisions is shown in Figure 11.1. Notice that the decisions proceed from the top down and that there are feedback loops from the bottom up. Thus, scheduling decisions often indicate a need for revised aggregate planning, and aggregate planning also may uncover needs to update facility decisions.
Capacity planning requires involvement of all functional areas. Long-range planning is closely tied with budgeting and the finance function, while medium-range capacity deci- sions require input from marketing and human resources. Even accounting and information systems closely interact with capacity during planning phases and on an ongoing basis. We discuss this cross-functional involvement in more detail later in the chapter.
11.1 CAPACITY DEFINED
We define capacity (sometimes referred to as peak capacity) as the maximum output that can be produced over a specific period of time, such as a day, week, or year. Capacity can be measured in terms of output such as number of units produced, tons produced, or num- ber of customers served over a specified period. It also can be measured by physical asset availability, such as the number of hotel rooms available, or labor availability, for example, the labor hours available for consulting or accounting services.
Estimating capacity depends on reasonable assumptions about facilities, equipment, and workforce availability for one, two, or three shifts as well as the operating days per week or per year. If we assume two eight-hour shifts are available for five days per week all year, the capacity of a facility is 16 × 5 = 80 hours per week and 80 × 52 = 4160 hours per year. However, if the facility is staffed for only one shift, these capacity estimates must be halved. Facility capacity is not available unless there is a workforce in place to operate it.
Utilization is the relationship between actual output and capacity and is defined by the following formula:
Utilization = Actual output ____________ Capacity
× 100%
LO11.1 Define capacity and utilization.
FIGURE 11.1 Hierarchy of capacity decisions.
Facilities decisions
Months Planning Horizon
0 6 12 18 24
Facilities decisions
Aggregate planning
Aggregate planning
Scheduling
Scheduling
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222 Part Four Capacity and Scheduling
The utilization of capacity is a useful measure for estimating how busy a facility is or the proportion of total capacity being used. It is almost never reasonable to plan for 100 percent utilization since spare (slack) capacity is needed for planned and unplanned events. Planned events may include required maintenance or equipment replacement, and unplanned events could be a late delivery from a supplier or unexpected demand.
Utilization rates vary widely by industry and firm. Continuous flow processes may have utilization near 100 percent. Facilities with assembly-line processes may set planned uti- lization at 80 percent to allow for flexibility to meet unexpected demand. Batch and job shop processes generally have even lower utilization. Emergency services such as police, fire, and emergency medical care often have fairly low utilization, in part so that they can meet the demands placed on them during catastrophic events. The Operations Leader box describes capacity measurement and utilization at Delta Airlines.
It is possible in the short term for some firms to operate above 100 percent utilization. Overtime or an increased work-flow rate can be used in the short term to meet highly vari- able or seasonal demand. Mail and package delivery services often use these means to increase work output before major holidays. However, firms cannot sustain this rapid rate of work for more than a short period. Worker burnout, delayed equipment maintenance, and increased costs make it undesirable to operate at very high utilization over the medium or long term for most firms.
In addition to the theoretical peak capacity, there is an effective capacity that is obtained by subtracting downtime for maintenance, shift breaks, schedule changes, absen- teeism, and other activities that decrease the capacity available. The effective capacity is the amount of capacity that can be used in planning for actual output over a period of time. To estimate effective capacity for the previously described two-shift facility, we must sub- tract hours for planned and unforeseen events when capacity is not being utilized.
75 percent 10 years ago and a spacious 65 percent 20 years ago.
Industry leader Delta Air Lines, flying 180 million passengers each year, serves as a useful example. Headquartered in Atlanta, GA, they fly to 304 destina- tions in 52 countries, including flights by their alliance partners. Delta owns a fleet of more than 800 planes which take off about 3000 times every day. With an 86.2 percent passenger load, their capacity utilization rate continues a slow upward climb that is similar to the industry average.
In the airline industry, passenger capacity is measured in terms of the number of seats that can be sold. Those seats have gotten smaller and closer together in recent years, as any flyer can attest! Each unit of sellable capac- ity is valuable, and airlines will sell as many as they can.
So, if you are feeling crowded on your next flight, that is capacity management in action.
Source: www.delta.com, 2020.
It is not your imagination. Air travelers are feeling pinched these days.
Over the last decade, the proportion of airline seats occupied by passengers is way up. Airlines today fill, on average, more than 85 percent of their seats, and the most popular flight times and routes are completely full. This contrasts with average seat utilization rates of about
Delta Airlines
OPERATIONS LEADER
sattapapan tratong/123RF
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11.2 FACILITIES DECISIONS
Facilities decisions, the longest-term capacity planning decisions, are of great importance to a firm. These decisions place physical constraints on the amount of goods or services that can be produced, and they often require significant capital investment. Therefore, facilities decisions involve input from all organizational functions and often are made at the highest corporate level, including top management and the board of directors.
Firms must decide whether to expand existing facilities or build new ones. As we discuss the facilities strategy below, we will see there are trade-offs that must be considered. Expand- ing current facilities may provide location conveniences for current employees but may not be the best location in the long-run. Alternatively, new facilities can be located near a larger potential workforce but require duplication of activities such as maintenance and training.
When construction is required, the lead time for many facilities decisions ranges from one to five years. The one-year time frame generally involves buildings and equipment that can be constructed quickly or leased. The five-year time frame involves large and complex facilities such as oil refineries, paper mills, steel mills, and electricity generating plants.
In facilities decisions, there are five crucial questions:
1. How much capacity is needed? 2. How large should each facility be? 3. When is the capacity needed? 4. Where should the facilities be located? 5. What types of facilities/capacity are needed?
These questions can be separated conceptually but are often intertwined in practice. As a result, facilities decisions are exceedingly complex and difficult to analyze.
Facilities strategy is one of the critical parts of an operations strategy. Since major facil- ities decisions affect competitive success, they need to be considered as part of the total operations strategy, not simply as a series of incremental capital budgeting decisions.
A facilities strategy considers the amount of capacity, the size of facilities, the tim- ing of capacity changes, facilities locations, and the types of facilities needed for the long run. It must be coordinated with other functional areas due to the necessary investments (finance), market sizes that determine the amount of capacity needed (marketing), work- force issues related to staffing new facilities (human resources), estimating costs in new facilities (accounting), and technology decisions regarding equipment investments (infor- mation systems and engineering). The facilities strategy needs to be considered in an inte- grated fashion with these functional areas and will be affected by the following factors:
1. Predicted demand. The expected demand for future years is a key factor in adding or reducing capacity.
2. Cost of facilities. Cost is driven by the amount of capacity added or subtracted at one time, the timing, and the location of capacity.
3. Likely behavior of competitors. An expected slow competitive response may lead the firm to add capacity to grab the market before competitors become strong. In con- trast, an expected fast competitive response may cause the firm to be more cautious in expanding capacity.
4. Business strategy. The business strategy may dictate that a company put more empha- sis on cost, service, or flexibility in facilities choices. For example, a business strategy to provide the best service can lead to facilities with some excess capacity or several market locations for fast service. Other business strategies can lead to cost minimization or attempts to maximize future flexibility.
LO11.2 Illustrate with an example a facilities strategy that considers amount, size, timing, location, and type.
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224 Part Four Capacity and Scheduling
5. Global considerations. As markets and supply chains continue to become more global in nature, facilities often are located globally. This involves not merely chasing cheap labor but locating facilities for the best strategic advantage, sometimes to access new markets or to obtain desired expertise in the workforce.
One part of a facilities strategy is the amount of capacity needed. This is determined both by forecasted demand and by a strategic decision by the firm about how much capacity to provide in relation to expected demand. This can best be described by the notion of a capacity cushion, which is defined as follows:
Capacity cushion = 100% – Utilization
The capacity cushion is the difference between the output that a firm could achieve and the actual output that it produces to meet demand. Since capacity utilization reflects the output required to satisfy demand, a positive cushion means that there is more capacity available than is required to satisfy demand. Zero cushion means that the average demand equals the capacity available.
The decision regarding a planned amount of cushion is strategic in nature. Three strate- gies can be adopted with respect to the amount of capacity cushion:
1. Large cushion. In this strategy, a large positive capacity cushion, with capacity in excess of average demand, is planned. The firm intentionally has more capacity than the average demand forecast. This type of strategy is appropriate when there is an expand- ing market or when the cost of building and operating capacity is inexpensive relative to the cost of running out of capacity. Electric utilities adopt this approach, since blackouts and brownouts are generally not acceptable. Firms in growing markets may adopt a positive capacity cushion to enable them to capture market share ahead of their com- petitors. Also, a large cushion can help a firm meet unpredictable customer demand, for example, for new technologies that very quickly become popular.
2. Moderate cushion. In this strategy, the firm is more conservative with respect to capac- ity. Capacity is built to meet the average forecasted demand comfortably, with enough excess capacity to satisfy unexpected changes in demand as long as the changes are not hugely different from the forecast. This strategy is used when the cost (or consequences)
Amount of Capacity
FACILITIES STRATEGY. This Bacardi Rum factory supplies the entire North American market from a single modern automated distillery in Puerto Rico. Irina Moskalev/123RF
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of running out is approximately in balance with the cost of excess capacity. An appli- ance manufacturer, with fairly predictable demand, might use a moderate cushion.
3. Small cushion. In this strategy, a small or nearly zero capacity cushion is planned to maximize utilization. This strategy is appropriate when capacity is very expensive rela- tive to stockouts, as in the case of oil refineries, paper mills, and other capital intensive industries. These facilities operate profitably only at very high utilization rates between 90 and 100 percent.
When planning the capacity cushion, firms assess the probability of various levels of demand based on their forecast and then use those estimates to make decisions about planned increases or decreases in capacity. For example, suppose a firm has capacity to produce 1200 units. It also has a 50 percent probability of 1000 units of demand, and 50 percent probability of 800 units of demand. Then average demand is estimated to be (.5 × 1000) + (.5 × 800) = 900 units. Producing 900 units results in a (900/1200) × 100% = 75% utilization rate. Based on existing capacity, the cushion is (100% − 75%) = 25%.
The solved problems section at the end of the chapter provides an example of how to compute the capacity cushion by using probabilities of demand, existing levels of capacity, and costs of building capacity. This method provides an analytic basis for estimating the amount of capacity cushion that may be required.
After deciding on the amount of capacity, a facilities strategy must address how large each unit of capacity should be. This is a question involving economies of scale, based on the notion that large facilities are generally more economical because fixed costs can be spread over more units of production. Economies of scale occur for two reasons. First, the cost of building and operating large production equipment does not increase linearly with volume. A machine with twice the output rate generally costs less than twice as much to buy and operate. Also, in larger facilities the overhead related to managers and staff can be spread over more units of production. As a result, the unit cost of production falls as facility size increases when scale economies are present, as shown in Figure 11.2.
This is a good news–bad news story, for along with economies of scale come disecon- omies of scale. As a facility gets larger, diseconomies can occur for several reasons. First, logistics diseconomies are present. For example, in a manufacturing firm, one large facility incurs more transportation costs to deliver goods to markets than do two smaller facilities that are closer to their markets. In a service firm, a larger facility may require more move- ment of customers or materials, for example, moving patients around a large hospital or moving mail through a regional sorting center. Diseconomies of scale also occur because coordination costs increase in large facilities. As more layers of staff and management are added to manage large facilities, costs can increase faster than output. Furthermore, costs
Size of Facilities
FIGURE 11.2 Optimal facility size.
Unit Cost
Facility Size (units produced per year)
Economies of scale
Diseconomies of scale
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226 Part Four Capacity and Scheduling
related to complexity and confusion rise as more products or services are added to a single facility. For these reasons, the curve in Figure 11.2 rises on the right- hand side due to diseconomies of scale.
As Figure 11.2 indicates, there is a minimum unit cost for a certain facil- ity size. This optimal facility size will depend on how high the fixed costs are and how rapidly diseconomies of scale occur. For example, in the wood furni- ture industry there are plants with over a thousand employees and other plants with only a few employees. Each firm seems to have an optimal facility size, depending on its demand volume, cost structure, product/service mix, and par- ticular operations strategy, which may emphasize cost, delivery flexibility, or service. Cost is, after all, not the only factor that affects facility size.
Another element of facilities strategy is the timing of capacity additions. There are basically two opposite strategies here.
1. Preemptive Strategy. In this strategy, the firm leads by build- ing capacity in advance of the needs of the market. This strat- egy provides a positive capacity cushion and may actually stimulate the market while at the same time preventing competition from coming in for a while. Apple Inc. used this strategy in the early days of the personal computer market. Apple built capacity in advance of demand and had a large share of the market before com- petitors moved in. Apple still uses this strategy today in building massive capac- ity and inventories in advance of new product launches for the iPad and iPhone.
2. Wait-and-see Strategy. In this strategy, the firm waits to add capacity until demand develops and the need for more capacity is clear. As a result, the company lags mar- ket demand, using a lower-risk strategy. A small or negative capacity cushion can develop, and a loss of potential market share may result. However, this strategy can be effective because superior marketing channels or technology can allow the follower to capture market share. For example, in the smartphone market Android phones (e.g., Samsung and others) have been able to take away market share from the leader, Apple, through pricing, advertising, and new products. In contrast, U.S. automobile companies followed the wait-and-see strategy, to their chagrin, for small autos. While U.S. auto- makers waited to see how demand for small cars would develop, Japanese manufactur- ers grabbed a dominant position in the U.S. small-car market.
Facility location decisions have become more complex as globalization has expanded the options for locating capacity and developing new markets. For example, Starbucks may choose to build facilities in regions with heavy coffee drinkers, competing for customers there. Alternatively, it may choose to locate facilities in regions where people typically do not
Timing of Facility Decisions
Facility Location
Starbucks uses a preemptive strategy to grow in new markets. John Flournoy/McGraw-Hill Education
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consume coffee and attempt to create demand for their product and service. Starbucks’s U.S. competitor Caribou Coffee tries to find facilities locations on the right-hand side of the road of morning traffic, because customers are more likely to stop frequently when they can pull over on the right but are less willing to make cumbersome left-hand turns in heavy traffic!
Location decisions are made by considering both quantitative and qualitative factors. Quantitative factors that affect the location decision may include return on investment, net present value, transportation costs, taxes, and lead times for delivering goods and services. Qualitative factors can include language and norms, attitudes among workers and custom- ers, and proximity to customers, suppliers, and competitors. Front office services in par- ticular must often locate near customers for the customers’ convenience, and so this factor may outweigh most others in determining where to locate new facilities. Examples include clinics, grocery stores, and restaurants.
Firms often compare potential locations by weighting the importance of each factor that is relevant to the decision and then scoring each potential location on those factors. Then, multiplying the factor weight by the location score allows calculation of a weighted-average score for each site. This score provides insight on how well each potential site meets the needs of the firm and may be used to make the final facility location decision.
The final element in facility strategy considers the question of what the firm plans to accomplish in each facility. There are four different types of facilities:
1. Product-focused (55 percent) 2. Market-focused (30 percent) 3. Process-focused (10 percent) 4. General-purpose (5 percent)
The figures in parentheses indicate the approximate percentages of companies in the For- tune 500 using each type of facility.
Product-focused facilities produce one family or type of product or service, usually for a large market. An example is the Andersen Corporation main facility, which produces various types of windows for the entire U.S. Product-focused plants often are used when transportation costs are low or economies of scale are high. This tends to centralize facili- ties into one location or a few locations. Other examples of product-focused facilities are large credit card processing operations and auto leasing companies that process leases for cars throughout the U.S. from a single site.
Market-focused facilities are located in the markets they serve. Many service facilities fall into this category since services generally cannot be transported. Plants that require quick customer response or customized products or that have high transportation costs tend to be market focused. For example, due to the bulky nature and high shipping costs of mat- tresses, most production plants are located in regional markets. Some international facilities are market focused because of tariffs, trade barriers, and potential currency fluctuations.
Process-focused facilities have one technology or at most two. These facilities fre- quently produce components or subassemblies that are supplied to other facilities for further processing. This is common in the auto industry, in which engine plants and trans- mission plants feed the final assembly plants. Process-focused plants such as oil refineries can make a limited variety of products within the given process technology.
General-purpose facilities may produce several types of products and services, using several different processes. For example, general-purpose facilities are used to manufac- ture furniture and to provide consumer banking and investment services. Most hospitals are general-purpose facilities. General-purpose facilities usually offer a great deal of flex- ibility in terms of the mix of products or services that are produced there. They sometimes are used by firms that do not have sufficient volume to justify more than one facility.
Types of Facilities
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228 Part Four Capacity and Scheduling
We have shown how a facilities strategy can be developed by considering questions of capacity, size of facilities, timing, location, and types of facilities. Analytics using mathematical optimization models can often be helpful in answering these five strategic questions as discussed in the BMW Operations Leader box. We now shift from long-term facilities decisions to medium-term decisions regarding how capacity, once built, is used.
11.3 SALES AND OPERATIONS PLANNING
Sales and operations planning (S&OP) is a term used by many firms to describe the aggregate planning process. Aggregate planning is the activity of matching supply of output (production) with demand (market) over the medium time range. The time frame is between six and eighteen months into the future, or an average of about one year.
The term aggregate implies that the planning is done for a single overall measure of out- put or at most a few aggregated product or service categories. Products can be grouped, for planning purposes, into a product family of items with similar production needs and serving similar markets. The product family might include all refrigerators for an appliance producer or all surgical procedures for planning at a hospital. The aim of S&OP is to set overall output levels in the medium-term future in the face of fluctuating or uncertain demand.
S&OP, or aggregage planning, includes the following characteristics and assumptions:
1. A time horizon of about 12 months, with updating of the plan on a periodic basis, per- haps monthly.
LO11.3 Explain how S&OP is done.
the typical development and production life cycle for new BMW designs. The mathematical model calculates the supply of finished products that should be produced by each plant to meet the forecasts in all global markets.
As a result, the model determines how much of each product should be produced in each plant over the next 12 years. All possible locations, amounts, and types of BMWs are considered by the mathematical model in arriving at the minimum cost plan.
This type of analysis is very helpful in setting over- all capacity strategies for how much, how large, where, when, and what type. For example, the resulting strat- egy might be to use distributed production to produce in each national market the amount sold there or a more centralized production and export strategy. Due to the many assumptions made, the models do not determine the final capacity strategy; however, they are very helpful in evaluating many different possibilities.
Source: B. Fleischmann, S. Ferber, and P. Henrich, “Strategic Planning of BMW’s Global Production Network,” Interfaces 36(3), 2006; and www.bmwgroup-plants.com/en.html, 2020.
Analytics using mathematical optimization models (e.g., mixed linear programming) can be helpful in evaluating various capacity strategies. Given a forecast of demand over the next several years, the models will determine the minimum cost plan for meeting the demand.
An example from BMW helps explain this process. BMW uses a 12-year future planning horizon to represent
Strategic Capacity Planning at BMW
OPERATIONS LEADER
Goran Jakuš/123RF
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2. An aggregate level of demand for one or a few categories of product or service. The demand is assumed to be fluctuating, uncertain, or seasonal.
3. The possibility of changing both supply and demand variables. 4. A variety of management objectives, which might include low inventories, good labor
relations, low costs, flexibility to increase future output levels, and good customer service.
5. Facilities that are considered fixed and cannot be expanded or reduced.
As a result of S&OP, decisions related to the workforce are made concerning hiring, laying off, overtime, and subcontracting. Decisions regarding production output and inven- tory levels are also made. S&OP is used not only to plan production output levels but also to determine the appropriate resource input mix to use. Since facilities are assumed to be fixed and cannot be expanded or contracted, management must consider how to use exist- ing facilities and resources to best match market demand.
S&OP can involve plans to influence demand as well as supply. Factors such as pricing, advertising, and product mix may be considered in planning for the medium term. We will discuss these tactics later in this chapter.
S&OP generally is done by product family, including the equipment and workforce needed to produce output. Usually no more than a few product families are used for S&OP to limit the complexity of the planning process. Inconsistencies between supply and demand are resolved by revising the plan as conditions change.
S&OP matches supply and demand by using a cross-functional team approach. The cross- functional team consisting of marketing, sales, engineering, human resources, operations,
Hostess knew it needed to manage costs closely. Retailers, such as gas stations and grocers, now play a bigger role in both production planning and delivery. The new model required retailers to forecast demand, order goods, receive goods at their own distribution cen- ters, deliver to their stores, and stock their own shelves. Retailers signed on to this new approach because their customers wanted Hostess products. Hostess became the first in its segment to use this forecast, planning, and delivery model.
Under their faster S&OP processes, Hostess turned their attention toward new product offerings, which are up 80 percent. They tapped customer interest in holiday- themed Twinkies, DingDongs, and HoHos. Even pumpkin spice Twinkies! With limited shelf life, product turnover must be quick, and Hostess Brands’ new business model is making that happen.
Source: Abe Eshkenazi, “Sweetening the Deal: How Hostess Improved Its Supply Chain,” January 15, 2016, www.apics.org; and www.hostessbrands.com, 2020.
Hearts were broken in 2012 when Hostess announced they were stopping production of such favorites as Twinkies and HoHos. But under new ownership, the company relaunched in 2013 as Hostess Brands LLC and moved quickly to rebuild the brand, with new S&OP processes and a new supply chain design.
S&OP at Hostess Brands
OPERATIONS LEADER
bhofack2/Getty Images
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230 Part Four Capacity and Scheduling
and finance meets with the general manager to agree on the sales forecast, the supply plan, and any steps needed to modify supply or demand. During the S&OP process, demand is decoupled from supply. For each product family, the cross-functional team must decide whether to produce inventory, manage customer demand, or provide additional capacity (internal or external). Once plans to manage demand and supply are in balance, however, the current plan may not agree with previous financial plans or human resources plans or budgets, which also may need to be modified.
The resulting sales and operations plan is updated approximately monthly, using a 12-month or longer rolling planning horizon. At its best, S&OP reduces misalignment among functions by requiring a common plan to be implemented by all parties. Strong general manager leadership may be required to resolve any conflicts that arise. Read the Operations Leader box to learn how Hostess Brands is using S&OP to revive their business.
Syngenta is a world leader in agribusiness products such as seeds and fertilizer, with 28,000 employees in 90 countries. The highly seasonal agricultural market is difficult to forecast and experiences large demand shifts. Syngenta uses S&OP to create collaboration across functions and with its supply chain partners. Managers across several countries use the S&OP process and the supporting software to gain better agreement on forecasts, sales promotions, inventory levels, sales plans, and aggregate production plans.
Since S&OP is a form of aggregate planning, it precedes detailed scheduling, which is covered in the next chapter. Scheduling serves to allocate the capacity made available by aggregate planning to specific jobs, activities, or orders.
11.4 CROSS-FUNCTIONAL NATURE OF S&OP
Aggregate planning for how capacity will be used in the medium-term future is the respon- sibility of the operations function. However, the planning process requires cross-functional coordination and cooperation with all functions in the firm, including accounting, finance, human resources, and marketing.
S&OP or aggregate planning is closely related to other business decisions involving, for example, budgeting, personnel, and marketing. The relationship to budgeting is par- ticularly strong. Most budgets are based on assumptions about aggregate output, personnel levels, inventory levels, purchasing levels, and so forth. An aggregate plan thus should be the basis for initial budget development and for budget revisions as conditions warrant.
Personnel, or human resource planning, is also greatly affected by S&OP because such planning for future production can result in hiring, layoffs, and overtime decisions. In ser- vice industries, which cannot use inventory as a buffer against changing demand, aggregate planning is sometimes synonymous with budgeting and personnel planning, particularly in labor-intensive services that rely heavily on the workforce to deliver services.
Marketing must always be closely involved in S&OP because the future supply of out- put, and thus customer service, is being determined. Marketing, through pricing, promo- tion, and other activities, will impact demand. Therefore, it is essential that such sales plans and their timing be accounted for in the planning process.
S&OP is not a stand-alone system. It is a key input into the enterprise resource plan- ning (ERP) system, which is discussed later. ERP tracks all detailed transactions from orders to shipments to payments, but requires a high-level aggregate plan for future sales and operations as an input. The ERP system accepts as input the S&OP plan and projects the detailed transactions (shop orders, purchase orders, inventories, and payments) that are required to support the agreed plan. Figure 11.3 captures these inputs and outputs from an S&OP process.
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In some firms, the S&OP process is broken or missing. Top management does not actively support or participate in the process. Accountability for S&OP is inadequate or in conflict across functions. The firm’s information system may not support S&OP, and so the firm is not able to conduct important “what if ” analysis. Also, S&OP plans may not be executed by all organizational functions as has been agreed. Therefore, to be successful, the S&OP system may require changes in the organization, reporting and accountability, and the information systems.
11.5 PLANNING OPTIONS
Operations and marketing must work closely to plan for matching supply and demand over the medium-term time frame. They do this during aggregate planning when they coordi- nate their decisions to develop enough demand for products and services without over- shooting available facility capacity.
The S&OP process includes discussion of the various decision options available. These include two categories of decisions: (1) those modifying demand and (2) those modifying supply.
Demand management entails modifying or influencing demand in several ways: 1. Pricing. Differential pricing often is used to reduce peak demand or to build up demand
in off-peak periods. Some examples are matinee movie prices, off-season hotel rates, factory discounts for early- or late-season purchases, and off-peak specials at restau- rants. The purpose of these pricing schemes is to level demand through the day, week, month, or year.
LO11.4 Identify the demand and supply options that are available for S&OP.
FIGURE 11.3 Relationship of S&OP with other functions.
Operations - Forecast
- Inventory levels - Capacity
- Current orders
Finance - Investment
Accounting - Cost analysis
Marketing - Forecast
- Sales plan
Human Resources - Personnel planning
S&OP Process
ERP System - Production
plan
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232 Part Four Capacity and Scheduling
2. Advertising and promotion. These methods are used to stimulate or in some cases smooth out demand. Advertising can be timed to promote demand during slow periods and shift demand from peak periods to slack times. For example, golf courses advertise to lengthen their season and turkey growers advertise to stimulate demand outside the peak holiday seasons.
3. Backlogs or reservations. In some cases, demand is influenced by asking customers to wait for their orders (backlog) or by reserving capacity in advance (reservations). Gener- ally, this has the effect of shifting demand from peak periods to periods with slack capac- ity. However, backlogs may have the undesirable effect of losing customers or profit.
4. Development of complementary offerings. Firms with highly seasonal demands may try to develop products that have countercyclic seasonal trends. For example, Toro produces both lawn mowers and snowblowers, seasonally complementary products. In fast-food restaurants, breakfast has been added in many cases to utilize previously idle capacity.
The service industries, using all the mechanisms described above, have gone much further than most of their manufacturing counterparts in influencing demand. Because they are unable to inventory their output—their services—they use these mechanisms to improve their utilization of fixed facility capacity.
Supply management includes a variety of ways to increase or decrease supply through aggregate planning. These include the following: 1. Hiring and laying off employees. Some firms will do almost anything before reduc-
ing the size of the workforce through layoffs. Other companies routinely increase and decrease the workforce as demand changes. These practices, which vary widely by firm and industry, affect not only costs but also labor relations, productivity, and worker morale. As a result, company hiring and layoff practices may be restricted by union contracts or company policies. These effects must be factored into decisions about whether to change the size of the workforce to match demand more closely.
2. Using overtime and undertime. Overtime sometimes is used for short- or medium- range labor adjustments in lieu of hiring and layoffs, especially if the change in demand is considered temporary. Overtime labor usually costs 150 percent of regular time, with double time on weekends and holidays. Because of its high cost, managers are some- times reluctant to use overtime. Furthermore, workers may be reluctant to work more than 20 percent weekly overtime for an extended period. Undertime refers to planned underutilization of the workforce rather than layoffs, perhaps by using a shortened work- week. Undertime, in the form of furloughs, is common in many industries, including manufacturing, education, and government during recessions or periods of low demand.
3. Using part-time or temporary labor. In some cases, it is possible to hire part-time or temporary employees to meet peak or seasonal demand. This option is particularly attractive when part-time employees are paid significantly less in wages and benefits. Unions frequently frown on the use of part-time employees because they often do not pay union dues and may weaken union influence. Part-time and temporary labor is used extensively in many service operations, such as restaurants, hospitals, supermar- kets, and department stores. Temporary labor is also common in agriculture-related industries.
4. Carrying inventory. In manufacturing firms, inventory can be used as a buffer between supply and demand. Inventories for later use can be built up during periods of low demand. Inventory thus decouples supply from demand in manufacturing operations, allowing for smoother operations with more even use of capacity throughout a time period. Inventory is a way to store expended capacity and labor for future consumption.
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This option is generally not available for service operations; this results in greater chal- lenges for service industries in matching supply and demand.
5. Subcontracting. Subcontracting is the outsourcing of work (either manufacturing or service activities) to other firms. This option can be very effective for increasing or decreasing supply. The subcontractor may supply the entire product or service or only some of the components. For example, a manufacturer of toys may utilize subcontrac- tors to make plastic parts during periods of high demand. Service operations may sub- contract call center operations or catering services during peak periods.
6. Cooperative arrangements. These arrangements are similar to subcontracting in that other sources of supply are used, but cooperative arrangements often involve partner firms that are typically competitors. The firms choose to share their capacity, thus pre- venting either firm from building capacity that would be used only during brief periods. Examples include electric utilities that link their capacity through power-sharing net- works, hospitals that send patients to other hospitals during demand peaks, and hotels or airlines that shift customers among one another when they are fully booked.
In considering all these options, it is clear that S&OP and the aggregate planning decisions are extremely broad and affect most parts of the firm. The decisions that are made are therefore strategic and cross-functional, and should reflect all of the firm’s objectives. If aggregate planning is considered narrowly, it may not bring to light the trade-offs that can occur. Some of the multiple trade-offs that should be considered are customer service level (through back orders or lost demand), inventory levels, stability of the labor force, and costs. The conflicting objectives and trade-offs among these ele- ments sometimes are combined into a single cost function. A method for doing this is described next.
11.6 BASIC AGGREGATE PLANNING STRATEGIES
For most firms, demand for their product or service changes over time. For example, demand for lawn fertilizer is very seasonal in nature, but the firm may prefer to keep full-time workers all year. Demand for services can also fluctuate, such as resorts, which
depend on good weather and consumer interest. Resort owners may prefer to frequently hire and lay off work- ers to closely match demand. In this section, we discuss the aggregate planning strategies used in each of these instances and explain how firms decide which strategy is best for them.
Two basic planning strategies can be used, as well as combinations of them, to meet medium-term aggregate demand. One strategy is to maintain a level workforce; the other is to chase demand with the workforce.
With a level strategy, the size of the workforce and the rate of regular-time output are constant. Any varia- tions in demand must be absorbed by using inventories, overtime, temporary workers, subcontracting, coopera- tive arrangements, or any of the demand-influencing options discussed above. The level strategy essentially holds the regular workforce at a fixed number, and so the rate of workforce output is fixed over the aggregate
LO11.5 Contrast and compare the chase and level strategies.
Using a level strategy often results in holding inventory during low demand periods. Andersen Ross/Getty Images
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234 Part Four Capacity and Scheduling
planning period. However, a firm using a level strategy can respond to fluctuations in demand by using the demand and supply planning options discussed in the previous section.
With a chase strategy, the size of the workforce is changed to meet, or chase, demand. With this strategy, it is not necessary to carry inventory or use the demand and supply planning options available for aggregate planning; the workforce absorbs all changes in demand. The chase strategy generally results in a fair amount of hiring and laying off of workers as demand is chased.
These two strategies are extremes; one strategy makes no change in the workforce, and the other varies the workforce directly with demand changes. In practice, many firms use a combination of these two strategies. Read the Operations Leader box to see how Travelers Insurance successfully uses a level strategy even though demand for its service can vary significantly.
11.7 AGGREGATE PLANNING COSTS
Most aggregate planning methods include a plan that minimizes costs. These methods assume that demand is given (based on forecasts) but varies over time; therefore, strategies for modifying demand are not considered. If both demand and supply are modified simul- taneously, it may be more appropriate to develop a model to maximize profit rather than minimize costs, since demand changes affect revenues along with costs.
LO11.6 Define the various costs associated with aggregate planning.
In September 2017, Hurricane Irma became the most powerful storm to hit the continental U.S. in more than a decade. Before Irma slammed the Florida coast, Travelers claims employees from around the country were moving toward the affected areas so that they would be immedi- ately available to serve affected customers. Even before the storm made landfall, teams of trained and equipped claims professionals were ready.
Travelers uses a level strategy, with workers from many regions pitching in during large-scale disasters and workers being diverted to training and catch-up activities during slow times when it might appear to be overstaffed. The strategy seems to pay off in terms of maintaining high levels of customer service during a peak demand period. Travelers was able to contact most of its Hurri- cane Irma-affected customers within 48 hours of their reporting a claim and to inspect, provide payment, and close more than 90 percent of claims within 30 days.
Source: www.travelers.com, 2020.
Travelers offers a wide variety of insurance products and services, covering customers in more than 90 countries. It sells insurance for auto owners, renters, home owners, and businesses. Travelers is an example of a service firm that uses a level strategy to manage its workforce and capacity.
Travelers Meets Demand
OPERATIONS LEADER
FotoKina/Shutterstock
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When demand is given, the following costs should be included: 1. Hiring and layoff costs. Hiring costs consist of the recruiting, screening, and training
costs required to bring a new employee up to full productive skill. For some jobs, this cost may be only a few hundred dollars; for more highly skilled jobs, it may be thou- sands of dollars. Layoff costs include employee benefits, severance pay, and other asso- ciated costs. This cost may also range from a few hundred to several thousand dollars per worker.
2. Overtime and undertime costs. Overtime costs consist of regular wages plus an over- time premium, typically an additional 50 to 100 percent. Undertime costs reflect the use of employees at less than full productivity.
3. Inventory carrying costs. Inventory carrying costs are associated with maintaining goods in inventory, including the cost of capital, the variable cost of storage, obsoles- cence, and deterioration. These costs often are expressed as a percentage of the dollar value of inventory, ranging from 15 to 35 percent per year. This cost can be thought of as an interest charge assessed against the dollar value of inventory held in stock. Thus, if the carrying cost is 20 percent and each unit costs $10 to produce, it will cost $2 to carry one unit in inventory for a year.
4. Subcontracting costs. The cost of subcontracting is the price paid to another firm to produce the units. Subcontracting costs can be either greater or less than the cost of producing units in-house but typically would be greater than in-house costs.
5. Part-time labor costs. Due to differences in benefits and hourly rates, the cost of part- time or temporary labor is often less than that of regular labor. Although part-time workers often receive no benefits, a maximum percentage of part-time labor may be specified by operational considerations or by union contract. Otherwise, there might be a tendency to use all part-time or temporary labor. However, the regular labor force is generally essential for operations continuity as well as to utilize and train part-time and temporary workers effectively.
6. Cost of stockout or back order. The cost of taking a back order or the cost of a stock- out should reflect the effect of reduced customer service. This cost is extremely difficult to estimate, but it should capture the loss of customer goodwill, the loss of profit from the order, and the possible loss of future sales. Some or all of these costs may be relevant in any aggregate planning problem. The
applicable costs can be used to “price out” alternative decisions and strategies. In the example below, the total costs related to three alternative strategies are estimated. When this type of analysis is conducted on a spreadsheet, a very large number of alternative strat- egies can be considered.
11.8 AGGREGATE PLANNING EXAMPLE
The Hefty Beer Company is constructing an aggregate plan for the next 12 months. Although several types of beers are brewed at the Hefty plant and several container sizes are bottled, management has decided to use gallons of beer as the aggregate measure of capacity.
The demand for beer over the next 12 months is forecast to follow the pattern shown in Figure 11.4. Notice that demand peaks during the summer months and is decidedly lower in the winter.
LO11.7 Create an alternative strategy for the Hefty Beer Company example.
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236 Part Four Capacity and Scheduling
The management of the Hefty brewery would like to consider three aggregate plans:
1. Level workforce. Use inventory to meet peak demands. 2. Level workforce plus overtime. Use 20 percent overtime along with inventory in June,
July, and August to meet peak demands. 3. Chase strategy. Hire and lay off workers each month as necessary to meet demand.
To evaluate these strategies, management has collected the following cost and resource data:
∙ Assume the starting workforce is 40 workers. Each worker can produce 10,000 gallons of beer per month on regular time. On overtime, the same production rate is assumed, but overtime can be used for only three months during the year.
∙ Each worker is paid $4,000 per month on regular time. Overtime is paid at 150 percent of regular time. A maximum of 20 percent overtime can be used.
∙ Hiring a worker costs $5,000, including screening, paperwork, and training costs. Lay- ing off a worker costs $4,000, including all severance and benefit costs.
∙ For inventory valuation purposes, beer costs $4 per gallon to produce. The cost of car- rying inventory is estimated to be 3 percent per month (or 12 cents per gallon of beer per month).
∙ Assume the starting inventory is 50,000 gallons. The desired ending inventory a year from now is also 50,000 gallons. All forecast demand must be met; no stockouts are allowed.
The next task is to evaluate each of the three strategies in terms of the costs given. The first step in this process is to construct spreadsheets like those shown in Tables 11.1 through 11.3, which show all relevant costs: regular workforce, overtime, hiring/layoff, and inventory carrying. Notice that subcontracting, part-time labor, and back orders/stock- outs have not been used as variables in this example.
To evaluate the level strategy, we calculate the size of the workforce required to meet the demand and inventory goals. Since ending and beginning inventories are assumed to be equal, the workforce must be just large enough to meet total demand during the year. When the monthly demands from Figure 11.4 are summed, the annual demand is 5,400,000 gal- lons. Since each worker can produce 10,000(12) = 120,000 gallons per year, a level work- force of 5,400,000 ÷ 120,000 = 45 workers is needed to meet the total demand. This means that five new workers must be hired. The inventories for each month and the resulting costs have been calculated in Table 11.1.
FIGURE 11.4 Hefty Beer Company—demand forecast.
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238 Part Four Capacity and Scheduling
Consider the calculations for January. With 45 regular workers entered at the top of the table, 450,000 gallons of beer can be produced, since each worker produces 10,000 gallons in a month. The production exceeds the sales forecast by 150,000 (450,000 − 300,000) gallons, which is added to the beginning inventory of 50,000 gallons to yield an inventory level of 200,000 gallons at the end of January.
Next the costs in Table 11.1 are calculated as follows: Regular time costs are $180,000 in January (45 workers × $4,000 each). There is no overtime cost, but 5 workers have been hired, since the starting workforce level was 40 workers. The cost of hiring these five work- ers is $25,000. Finally, it cost 12 cents to carry a gallon of beer in inventory for a month, and Hefty is carrying 200,000 gallons at the end of the month, which costs $24,000.1 These costs total $229,000 for January. The calculations are continued for each month and then summed for the year to yield the total cost of $2,548,000 for the level strategy.
The second strategy, level workforce plus overtime, is a bit more complicated. If X is the workforce size for option 2, we calculate based on nine months without overtime and three months with 20 percent overtime, as allowed in the example assumptions.
9(10,000X) + 3[(1.2)(10,000X)] = 5,400,000 gallons
For nine months Hefty will produce 10,000X gallons per month, and for three months it will produce 120 percent of 10,000X, including overtime. When the above equation is solved for X, we round off to X = 43 workers. The 43 workers each produce 10,000 gal- lons per month during nine months. Working 20 percent overtime during the summer, each produces 12,000 gallons per month during those three months. In Table 11.2 we have calculated the inventories and resulting costs for this option.
The third strategy, the chase strategy, varies the workforce each month by hiring and laying off workers to meet monthly demand exactly. When this strategy is used, a con- stant level of 50,000 gallons in inventory is maintained as the minimum inventory level, as shown in Table 11.3. The number of workers in January starts at only 30 that are needed to meet the demand of 300 units. In April, the number of workers is increased to 40 to pro- duce the demand of 400 units. A peak of 65 workers is reached in August, and so on, until the number of workers is finally reduced to 45 in December.
The annual costs of the three strategies are summarized in Table 11.4. On the basis of the given costs and assumptions, the chase strategy is the lowest-cost strategy. However,
1For convenience, we use the end-of-month inventory to calculate inventory carrying costs rather than the average monthly
Strategy 1—Level Regular-time payroll $2,160,000 Hire/layoff 25,000 Inventory carrying 363,000 Total $2,548,000 Strategy 2—Level with overtime Regular-time payroll $2,064,000 Hire/layoff 15,000 Overtime 154,800 Inventory carrying 361,600 Total $2,595,400 Strategy 3—Chase Regular-time payroll $2,160,000 Hire/layoff 295,000 Inventory carrying 72,600 Total $2,527,600
TABLE 11.4 Cost Summary
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Chapter 11 Capacity Planning 239
sch68106_ch11_220-248.indd 239 06/17/19 12:28 PM
cost is not the only consideration. For example, the chase strategy requires building from a minimum workforce of 30 to a peak of 65 workers, and then layoffs are used to reduce the number back to 45 workers. Will the labor climate and availability permit this amount of hiring and laying off each year, or will this lead to unionization and potentially higher labor costs, or even shortages in production? Maybe a two-shift policy or the use of part- time or temporary workers should be considered for peak demand portions of the year. These alternatives, along with others, should be considered in attempting to evaluate and possibly improve on the chase strategy. Alternatively, the firm may decide to use the level strategy in view of the small additional cost with no labor disruption.
We have shown how to compare costs in a very simple case of aggregate planning by using three potential strategies. Advanced analytic methods have been developed to consider many more strategies and more complex aggregate planning problems. These methods, which can be quite complex, include linear programming, simulation, and various decision rules.
11.9 KEY POINTS AND TERMS
The following key points are discussed in the chapter:
∙ Facilities decisions are long-range in the hierarchy of capacity decisions. A facility strategy should be implemented rather than a series of incremental facility decisions. A facilities strategy answers the questions of how much, how large, where, when, and what type of capacity is needed.
∙ The amount of capacity planned should be based on the desired risk of meeting fore- cast demand. The capacity cushion is a decision that firms must consider, determining whether they will use a large cushion and not run out of capacity or a small cushion with the possibility of a capacity shortage.
∙ When timing capacity expansion, a firm can choose to be preemptive by building capac- ity sooner or wait and see how much capacity is needed.
∙ Both economies and diseconomies of scale should be considered in setting an optimal facility size. The type of facility selected is focused on product, market, process, or general-purpose needs.
∙ Sales and operations planning (S&OP), or aggregate planning, serves as the link between facilities decisions and scheduling. S&OP decisions set output levels for the medium time range. As a result, decisions regarding workforce size, subcontracting, hiring, and inventory levels are also made. These decisions must fit within the facilities capacity available and are constrained by the resources available.
∙ Aggregate planning is concerned with matching supply and demand over the medium time range. There are many options or factors for managing or changing supply and demand.
∙ Supply factors that can be changed by aggregate planning are hiring, layoffs, overtime, undertime, inventory, subcontracting, part-time labor, and cooperative arrangements. Factors that influence demand are pricing, promotion, backlog or reservations, and complementary products.
∙ There are two basic strategies for adjusting supply: the chase strategy and the level strat- egy. Firms can also use a combination of these two main strategies. A choice of strategy can be analyzed by estimating the total cost of each of the available strategies. Factors, other than costs, to consider are customer service levels, possible demand changes, the labor force, and forecasting accuracy.
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240 Part Four Capacity and Scheduling
Key Terms Hierarchy of capacity decisions 220
Capacity 221 Utilization 221 Effective capacity 222 Facilities decisions 223 Facilities strategy 223 Capacity cushion 224
Sales and operations planning 228
Aggregate planning 228 Product family 228 Demand management 231 Supply management 232 Level strategy 233 Chase strategy 234
Economies of scale 225 Diseconomies of scale 225 Preemptive strategy 226 Wait-and-see strategy 226 Product-focused facilities 227 Market-focused facilities 227 Process-focused facilities 227 General-purpose facilities 227
LEARNING ENRICHMENT (for self-study or instructor assignments)
Overview of Capacity Planning Video https://youtu.be/i-pzxlCRJR0 4:47
How to Measure Capacity Website https://www.allaboutlean.com/production-capacity/
Capacity Planning for Surgical Suites Video https://youtu.be/CBDfMETpaH4 9:48
Choosing Global Locations for Capacity Website https://www.strategy-business.com/article/10403?gko=e029a
Steps for S&OP Process Website http://www.apics.org/apics-for-individuals/
apics-magazine-home/magazine-detail-page/2013/09/09/s-op-step-by-step
Aggregate Planning Supply and Demand Options Video
https://youtu.be/HOtai_3EdNY 1:59
SOLVED PROBLEMS
1. Probabilistic Capacity Planning The XYZ Chemical Company estimates the annual demand for a certain product as follows:
Thousands of Gallons 100 110 120 130 140
Probability .10 .20 .30 .30 .10
a. If capacity is 130,000 gallons, how much of a capacity cushion is there? b. What is the probability of idle capacity? c. What is the average utilization of the plant? d. If lost business (stockout) costs $100,000 per thousand gallons and it costs $5,000 to
build 1000 gallons of capacity, how much capacity should be built to minimize total costs?
Problem
a. Solution
Capacity cushion
=
100% − utilization
= 130 − [(.1 × 100) + (.2 × 110) + (.3 × 120)
+ (.3 × 130) + (.1 × 140)]
9 thousand gallons, or 9 / 130 = 6.9% of capacity
=
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Chapter 11 Capacity Planning 241
b. Probability of idle capacity
=
probability of demand < 130
= .1 + .2 + .3
= .6 (or 60%)
c. Average utilization
=
(.1 × 100 / 130) + (.2 × 110 / 130) + (.3 × 120 / 130)
+ (.3 × 130 / 130) + (.1 × 140 / 130)
= 93.1%
d. To determine the amount of capacity that minimizes total costs, we must determine the cost of capacity and then add on the penalty cost for not supplying the quantity demanded. This is done for each amount of possible capacity.
To build 100,000 gallons of capacity:
Total cost
=
Capacity cost + Penalty cost
= (100 × $5,000) + { $100,000 × [0 × .1) + (10 × .2)
+ (20 × .3) + (30 × .3) + (40 × .1)] }
=
$2,600,600
To build 110,000 gallons of capacity:
Total cost
=
Capacity cost + Penalty cost
= (110 × $5,000) + { $100,000 × [(0 × .1) + (0 × .2)
+ (10 × .3) + (20 × .3) + (30 × .1)] }
=
$1,750,000
To build 120,000 gallons of capacity:
Total cost
=
Capacity cost + Penalty cost
= (120 × $5,000) + { $100,000 × [(0 × .1) + (0 × .2) + (0 × .3)
+ (10 × .3) + (20 × .1)] }
=
$1,100,000
To build 130,000 gallons of capacity:
Total cost
=
Capacity cost + Penalty cost
= (130 × $5,000) + { $100,000 × [(0 × .1) + (0 × .2) + (0 × .3)
+ (0 × .3) + (10 × .1)] }
=
$750,000
To build 140,000 gallons of capacity:
Total cost
=
Capacity cost + Penalty cost
= (140 × $5,000) + { $100,000 × [(0 × .1) + (0 × .2) + (0 × .3)
+ (0 × .3) + (0 × .1)] }
=
$700,000
The choice that minimizes total costs is to build 140,000 gallons of capacity, which has an estimated total cost of $700,000.
2. Services Aggregate Planning Ace Accounting Associates (AAA) provides income tax filing services for individuals. Customers pay for the service according to the type of form they file. Customers with complex forms (i.e., 1040) are charged $200. Custom- ers with simpler forms are charged $50. Five permanent accountants work for AAA at
Problem
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242 Part Four Capacity and Scheduling
a rate of $600 per week. During the busy season—the five weeks before the due date for tax filing—temporary accountants can be hired for $600 per week. A one-time fee of $200 is paid to an employment service each time the company hires a temporary accountant. All accountants (permanent and temporary) access a computerized expert system, which costs the company $175 per accountant per week. On the average, any accountant (permanent or temporary) can process 4 complex forms per week or 20 simple forms per week. Demand for simple and complex forms for the upcoming tax season is given in the table below. All demand must be met (serviced) by the end of the fifth week.
Week 1 2 3 4 5
Demand (simple) 40 60 80 100 100 Demand (complex) 10 17 21 30 20
a. Determine the total profit that would result from having enough accountants to meet demand each week.
b. Find a more profitable arrangement in which all forms will be completed by the end of the fifth week (demand does not have to be met during the week it occurs).
c. If one or more permanent accountants will work up to an additional 40 hours over- time per week at 1.5 times the regular pay rate for the overtime hours worked, how will that change your solution to part b?
d. Are there any limitations or assumptions in your answers to parts a, b, and c that might affect the decisions regarding whom and when to hire or lay off?
The revenue and permanent employee costs are the same for all the solutions, and so they are shown here once:
Week 1 2 3 4 5
Revenue Simple forms 2000 3000 4000 5000 5000 Complex forms 2000 3400 4200 6000 4000 Total revenues 4000 6400 8200 11,000 9000
Costs of 5 permanent employees: Accountants 3000 3000 3000 3000 3000 Computer system 875 875 875 875 875 Permanent costs 3875 3875 3875 3875 3875
a. First, the number of total accountants needed is computed as follows:
Number of accountants: Simple forms 2.00 3.00 4.00 5.00 5.00 Complex forms 2.50 4.25 5.25 7.50 5.00
4.50 7.25 9.25 12.50 10.00 Round-up total 5 8 10 13 10
To determine the number of temporary accountants, subtract five permanent accoun- tants from the round-up total.
Solution
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Chapter 11 Capacity Planning 243
Costs of Temporary Accountants
Number of Temps 0 3 5 8 5
Hiring fees 0 600 400 600 0 Accountants (pay) 0 1800 3000 4800 3000 Computer system 0 525 875 1400 875 Temporary costs 0 2925 4275 6800 3875 Permanent costs 3875 3875 3875 3875 3875 Total costs 3875 6800 8150 10,675 7750 Total revenue 4000 6400 8200 11,000 9000
Profit (loss) 125 (400) 50 325 1250
Five-week profit (loss) = $1350
b. In this case we do not need to round up the number of accountants to meet demand in each period.
Costs of Temporary Accountants
Number of Temps 0 2 4 8 5
Hiring fees 0 400 400 800 0 Accountants 0 1200 2400 4800 3000 Computer system 0 350 700 1400 875 Temporary costs 0 1950 3500 7000 3875 Permanent costs 3875 3875 3875 3875 3875 Total costs 3875 5825 7375 10,875 7750 Total revenue 4000 6400 8200 11,000 9000
Profit (loss) 125 575 825 125 1250
Five-week profit (loss) = $2900
c. Suppose we use only the five temporary accountants in week 4 and meet total demand in that week by using overtime.
Costs of Temporary Accountants
Number of Temps 0 2 4 5 5
Hiring fees 0 400 400 200 0 Temp. accountants 0 1200 2400 3000 3000 Overtime (perm. accts.) 0 0 0 2700 0 Computer system 0 350 700 875 875 Temporary costs 0 1950 3500 6775 3875 Permanent costs 3875 3875 3875 3875 3875 Total costs 3875 5825 7375 10,650 7750 Total revenue 4000 6400 8200 11,000 9000
Profit (loss) 125 575 825 350 1250
Five-week profit (loss) = $3125
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244 Part Four Capacity and Scheduling
d. Aggregate planning is rarely as simple as this sample problem. For example, in this problem, the costs of termination are not considered. It is doubtful that the customers of this imaginary firm would allow their filings to be put off until it was convenient for the firm to file them—especially if they were expecting a refund!
3. Manufacturing Aggregate Planning Manufacturers Inc. (MI) currently has a labor force of 10, which can produce 500 units per period (50 units per worker per period). The cost of labor is now $2400 per period per employee. The company has a long- standing rule that does not allow overtime. In addition, the product cannot be subcon- tracted due to the specialized machinery that MI uses to produce it. As a result, MI can increase or decrease production only by hiring or laying off employees. The cost is $5000 to hire an employee and $5000 to lay off an employee. Inventory carrying costs are $100 per unit remaining at the end of each period. The inventory level at the beginning of period 1 is 300 units and ending inventory should be similar. The forecast demand in each of six periods is given in the table below.
Period 1 2 3 4 5 6
Aggregate demand 630 520 410 270 410 520
a. Compute the costs of a chase strategy using only full-time workers. b. Compute the costs of a level strategy, again with full-time workers. c. Compare the two strategies.
Problem
a. First, decide on the workforce level to be used for the chase strategy so that produc- tion meets demand in each period. For example, in period 1, demand is 630 units, which requires 12.6 workers (each worker can make 50 units). The answer is rounded up to 13 workers. The tables for number of units produced and for cost calculations are as follows:
Period 1 2 3 4 5 6
Units: Aggregate demand 630 520 410 270 410 520 Number of workers 13 10 8 5 8 10 Units produced 650 500 400 250 400 500 Ending inventory 320 300 290 270 260 240 Costs: Cost of labor 31,200 24,000 19,200 12,000 19,200 24,000 Hiring/layoff cost 15,000 15,000 10,000 15,000 15,000 10,000 Inventory carrying cost 32,000 30,000 29,000 27,000 26,000 24,000 Cost per period 78,200 69,000 58,200 54,000 60,200 58,000
Total costs $377,600
b. For the level strategy, decide first on the workforce level. To make a fair comparison between the costs of the chase and level strategies and because we round off to whole numbers of workers, we must produce the same number of total units over six peri- ods. The total units produced in part a are
650 + 500 + 400 + 250 + 400 + 500 = 2700 units
Solution
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Chapter 11 Capacity Planning 245
A level strategy produces an equal number of units each period, or 2700/6 = 450 units per period. This requires exactly nine workers (450/50) each period. The resulting number of units and cost calculations are
Period 1 2 3 4 5 6
Units: Aggregate demand 630 520 410 270 410 520 Number of workers 9 9 9 9 9 9 Units produced 450 450 450 450 450 450 Ending inventory 120 50 90 270 310 240 Costs: Cost of labor 21,600 21,600 21,600 21,600 21,600 21,600 Hiring/layoff cost 5,000 0 0 0 0 0 Inventory carrying cost 12,000 5,000 9,000 27,000 31,000 24,000 Cost per period 38,600 26,600 30,600 48,600 52,600 45,600
Total costs $242,600
c. The level strategy is much less costly. This is the case because it is fairly expensive to hire and lay off workers.
Discussion Questions 1. Approximately how far ahead would one need to plan
for the following types of facilities? a. Restaurant b. Hospital c. Oil refinery d. Toy factory e. Electric power plant f. Public school g. Private school 2. What problems are created by simultaneously consid-
ering the capacity questions of how much, how large, where, when, and what type?
3. A school district has forecast student enrollment for several years into the future and predicts excess capac- ity for 2000 students. The school board has said that the only alternative is to close a school. Evaluate.
4. Why are facilities decisions often made by top manage- ment? What is the role in these decisions of operations, marketing, finance, accounting, information systems, engineering, and human resources?
5. In what ways does corporate strategy affect capacity decisions?
6. S&OP or aggregate planning sometimes is confused with scheduling. What is the difference?
7. The XYZ Company manufactures a seasonal product. At the present time, the company uses a level labor
force as a matter of company policy. The company is afraid that if it lays off workers, it will not be able to rehire them or find qualified replacements. Does this company have an aggregate planning problem? Discuss.
8. It has been said that aggregate planning is related to personnel planning, budgeting, and market planning. Describe the nature of the relationship among these types of planning.
9. Firms often have multiple objectives such as good labor relations, low operating costs, high inventory turnover, and good customer service. What are the pros and cons of treating these objectives separately in an aggregate planning problem versus combining them all into a single measure of cost?
10. What factors are important in choosing the length of the planning horizon for aggregate planning?
11. A barbershop has been using a level workforce of bar- bers five days per week, Tuesday through Saturday. The barbers have considerable idle time on Tuesday through Friday, with certain peak periods during the lunch hours and after 4 p.m. each day. On Friday afternoon and all day Saturday, all the barbers are very busy, with cus- tomers waiting a substantial amount of time and some customers being turned away. What options should this barbershop consider for aggregate planning? How would you analyze these options? What data should be collected, and how should the options be compared?
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246 Part Four Capacity and Scheduling
Problems Three Excel spreadsheets are provided on Connect for assistance in solving the chapter problems. 1. Suppose we are considering the question of how much
capacity to build in the face of uncertain demand. Assume that the cost is $20 per unit of lost sales due to insufficient capacity. Also assume that there is a cost of $7 for each unit of capacity built. The probability of various demand levels is as follows:
Demand—X Units Probability of X
0 .05 1 .10 2 .15 3 .20 4 .20 5 .15 6 .10 7 .05
a. How many units of capacity should be built to mini- mize the total cost of providing capacity plus lost sales?
b. State a general rule regarding the amount of capacity to build.
c. What principle does this problem illustrate? 2. The Ace Steel Mill estimates the demand for steel in
millions of tons per year as follows:
Millions of Tons Probability
10 .10 12 .25 14 .30 16 .20 18 .15
a. If capacity is set at 18 million tons, how much of a capacity cushion is there?
b. What is the probability of idle capacity, and what is the average utilization of the plant at 18 million tons of capacity?
c. If it costs $8 million per million tons of lost business and $80 million to build a million tons of capacity, how much capacity should be built to minimize total costs?
3. A barbershop has the following demand for haircuts on Saturday, which is its busiest day of the week.
Number of Haircuts Probability
20 .1 25 .3 30 .4 35 .1 40 .1
a. What is the average demand for haircuts on Saturday? b. If the capacity is 35 haircuts, what is the average uti-
lization of the shop? c. If capacity is 35 haircuts, how much of a capacity
cushion does it have? d. If it costs $50 per lost haircut due to customer dis-
satisfaction and $100 for each unit of capacity provided, how much capacity should be built to minimize costs?
4. Assume a restaurant operates from 11 a.m. to 11 p.m. seven days per week.
a. How much capacity does the restaurant have on a weekly basis and an annual basis, in hours?
b. If the restaurant can serve a maximum of 40 custom- ers per hour, how much weekly capacity does the restaurant have in terms of customers?
c. What implicit assumptions are made in your calcula- tion for part b?
5. An urgent care clinic is staffed by two physicians who can each see four patients per hour. The clinic is open 6 p.m. until midnight, seven days per week. The clinic tracked the average number of patients arriving by hour for a month and observed the following:
Time Demand
6–7 8 7–8 10 8–9 10 9–10 4 10–11 4 11–12 2
a. Sketch a graph with one line showing capacity and another line showing demand.
b. What observations do you make from the graph in part a?
c. What suggestions would you make to the clinic for managing its capacity?
6. The Chewy Candy Company would like to determine an aggregate production plan for the
next six months. The company makes many different types of candy but feels it can plan its total production in pounds provided that the mix of candy sold does not change too drastically. At the present time, the Chewy Company has 70 workers and 9000 pounds of candy in inventory. Each worker can produce 100 pounds of candy per month and is paid $19 per hour (use 160 hours of regular time per month). Overtime, at a pay rate of 150 percent of regular time, can be used up to a maximum of 20 percent in addition to regular time in
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Chapter 11 Capacity Planning 247
any month. It costs 80 cents to store a pound of candy for a year, $1,200 to hire a worker, and $1,500 to lay off a worker. The forecast for the next six months are 8000, 10,000, 12,000, 8000, 6000, and 5000 pounds of candy.
a. Determine the costs of a level production strategy for the next six months, with an ending inventory of 8000 pounds.
b. Determine the costs of a chase strategy for the next six months.
c. Calculate the costs of using the maximum overtime for the two months of highest demand.
7. A company has seasonal demand, with the forecast for the next 12 months as given below. The current labor force can produce 500 units per month. Each employee can produce 20 units per month and is paid $2,000 per month. The inventory carrying cost is $50 per unit per year. Changes in the production quantity cost $100 per unit (in months when production volumes change) due to hiring or layoffs, line changeover costs, and so forth. Assume 200 units of initial inventory.
a. What is the cost of carrying inventory for the month of January for the level strategy?
b. What is the total cost of the level strategy including regular time, inventory carrying cost, and changes in production level?
c. What is the total cost of the chase strategy?
Month J F M A M J J A S O N D
Demand 651 700 850 702 650 500 600 850 803 900 703 600
8. Approximately 40 percent of a medical clinic’s weekly incoming calls for appointments occur on Monday. Due to this large workload, 20 percent of the callers receive a busy signal and have to call back later. The clinic has one clerk for each two departments to handle incoming calls. Each clerk handles calls for the same departments all week and thus is familiar with the doctors’ hours, scheduling practices, and idiosyncrasies. Consider the following alternatives to solve this problem:
∙ Continue the present system, which results in some customer inconvenience, loss of business, and perceived poor service. About 1000 patients attempt to call the clinic on Mondays. The clinic has 50,000 patients in all.
∙ Expand the phone lines and add more people to handle the peak load. The estimated cost for adding two more lines and two clerks is $60,000 per year.
∙ Install new software to speed up making appointments. In this case, the peak load could be handled with the current personnel. The estimated cost to lease and maintain the software is $50,000 per year.
∙ Expand the phone lines and ask people to call back later in the week for an appointment. Add two lines and two phone-answering clerks part time at $30,000 per year.
a. Analyze these options from the standpoint of an aggre- gate planning problem. What are the pros and cons of each option?
b. Which option do you recommend? Why? c. How does this problem differ from the other aggregate
planning problems above? 9. The Restwell Motel in Orlando, Florida, is preparing
an aggregate plan for the upcoming 12 days. The motel has a maximum of 200 rooms, but demand varies dur- ing the week. Demand is listed in terms of rooms rented each day. The motel requires one employee, paid $105 per day for each 12 rooms rented. It can utilize up to 20 percent overtime at 150 percent pay and also can hire part-time workers at $120 per day. Each part-time worker can also clean 12 rooms per day. There is no hiring and layoff cost for the part-time workers. A frac- tional number of part-time workers (e.g., 3.4 workers) can be employed since less than a full day of employ- ment is possible for each worker.
Day M T W Th F S Su M T W Th F
Demand 185 190 170 160 110 100 100 160 180 170 150 100
a. Assume a steady regular workforce of 10 employees, 20 percent overtime when needed, and the balance of demand met by part-time workers. How much does this strategy cost over the 12-day planning horizon? When needed to meet demand, assume maximum overtime is used before part-time workers are hired.
b. What is the total cost over the 12-day planning horizon if the regular workforce of 10 employees and only part-time workers are used? No overtime is used?
10. The Bango Toy Company produces sev- eral types of toys. The forecast for the next six
months in thousands of dollars is given below:
July Aug. Sept. Oct. Nov. Dec.
Forecast $1000 $1500 $2000 $1800 $1500 $1000
A regular employee can produce $10,000 worth of toys per month, and the company has 80 regular employees at the end of June. Regular-time employees are paid $3800 per month, including benefits. An employee on overtime produces at the same rate as on regular time but is paid at 150 percent of the regular pay. Up to 20 percent overtime can be used in any one month. A worker can be hired for $1000, and it costs $2000 to lay off an employee. Inventory carrying costs are 30 per- cent per year. The company wishes to end the year with 80 employees. Beginning inventory of toys is $900,000.
a. Calculate the cost of a chase strategy. b. Calculate the cost of a level strategy.
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248 Part Four Capacity and Scheduling
c. Using the Excel template, simulate several other strategies.
d. Determine the effect on the chase strategy, in part a, of changing the hiring cost to $1500, $2000, and $2500. What do these changes suggest the relation- ship is between hiring cost and total cost?
e. Use the Excel template to study the effect of demand changes on the total cost of the chase strategy. Assume various percentage increases and decreases in demand (110 percent, 120 percent, 210 percent, 220 percent, etc.).
11. A small textile company makes several types of sweat- ers. Demand is very seasonal, as shown by the follow- ing quarterly demand estimates. Demand is estimated in terms of standard hours of production required.
Fall Winter Spring Summer
Forecast 10,000 15,000 8000 5000
An hour of regular time costs the company $12. Employees are paid $18 per hour on overtime, and labor can be subcontracted at $14 per hour. A maximum of 1000 overtime hours is available in any month. A change in the regular level of production (increase or decrease) incurs a one-time cost of $5 per hour for add- ing or subtracting an hour of labor. It costs 2 percent per month to carry an hour of finished work in inventory. Materials and overhead costs in inventory are equal to the direct labor costs. At the beginning of the fall quar- ter, there are 5000 standard hours in inventory and the workforce level is equivalent to 10,000 standard hours.
a. Suppose management sets the level of regular work- ers for the year equal to the average demand and subcontracts out the rest. What is the cost of this strategy?
b. What is the cost of a chase strategy? 12. Beth’s Broasted Chicken shop offers a variety of fast-food items. Beth uses regular
and part-time workers to meet demand. The demand for the next 12 months has been forecast in thousands of dollars, as follows:
J F M A M J J A S O N D
Demand 25 33 40 57 50 58 50 48 37 33 28 32
Assume that each employee can produce $5000 worth of demand in a month. The company pays regular workers $10 per hour, including benefits, and part-time workers $7 per hour. There are 167 working hours in a month. Management would like to use as many part- time workers as possible but must limit the ratio to one
regular worker to no more than one part-time worker to provide adequate supervision and continuity of the workforce. A fractional number of part-time workers (e.g., 2.6 workers) can be employed since less than a full day of employment is possible for each worker. For example, if 10.6 total workers are needed, 6 regular workers and 4.6 part-time workers is a feasible combi- nation, but 5 regular workers and 5.6 part-time workers is not, because the part-time workers exceed the full- time workers. Demand must be met on a month-by- month basis. It costs $500 to hire and $200 to lay off a regular worker. No costs are associated with hiring and laying off part-time workers.
a. Develop a strategy for this problem by using the minimum integer number of regular workers along with the maximum amount of part-time workers in each month. What is the total cost of this strategy including regular-time labor, part-time labor and hir- ing/firing cost?
b. What is the total cost of a strategy with a constant level of 6 full-time workers used in each month? Excess labor is allowed when demand is less than six full-time workers.
13. Valley View Hospital faces somewhat seasonal demand. As a result, the forecast of patient days of demand is as follows (a patient day is one patient staying for one day in the hospital):
Fall Winter Spring Summer
Forecast 90,000 70,000 85,000 65,000
The hospital uses regular nurses, part-time nurses (when the hospital can get them), and contract nurses (who are not employees). Contract nurses work a num- ber of hours, which varies depending on their contract established with the hospital. Regular nurses are paid a sum of $15,500 per quarter for 60 days of work; part- time nurses are paid $6500 per quarter for 30 days of work. Contract nurses get an average of $17,200 per quarter for 60 days of work. It costs $1000 to hire or lay off any of these three types of nurses.
Suppose that regular nurses are set at a level of 800 nurses for the year. Each regular nurse works the equivalent of 60 days per quarter. The remainder of the demand is made up by 50 percent part-time and 50 percent contract nurses on a quarter-by-quarter basis. What is the cost of this plan starting at the beginning of fall with 800 regular nurses, 200 part- time nurses, and 200 contract nurses? Assume it takes 0.8 nurse day to provide around-the-clock care for each patient day.
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c h a p t e r 12
A teaching hospital must create a schedule for physicians in resident training that assigns them to overnight call shifts across three hospitals over a 365-day planning horizon. The work shifts must meet constraints such as assigning residents to six consecutive weeks at a particu- lar hospital and not assigning them to be on call more than once every four days. A manu- facturing manager in a bottling plant must schedule a variety of beverages to allow intensive cleaning setups between batches while also considering how much inventory to hold.
Organizations in every industry must schedule work to meet demand for products and ser- vices while supporting longer-term strategies. Scheduling decisions allocate available capac- ity or resources (equipment, labor, and space) to jobs, activities, tasks, or customers over time. Since scheduling involves allocation decisions, it uses the resources made available by facilities decisions and aggregate planning. Therefore, scheduling consists of short-term deci- sions that are constrained by previous decisions regarding facilities and aggregate planning.
In practice, scheduling results in a time-phased plan of activities, indicating what is to be done, when, by whom, and with what equipment. Scheduling should be clearly differentiated
Scheduling Operations
LO12.1 Describe the concept of batch scheduling.
LO12.2 Construct a Gantt chart.
LO12.3 Create work schedules using forward and backward scheduling.
LO12.4 Explain the implications of the theory of constraints for scheduling.
LO12.5 Compare various dispatching rules.
LO12.5 Describe the important factors to consider when designing a scheduling system.
After reading this chapter, you should be able to:LEARNING OBJECTIVES
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250 Part Four Capacity and Scheduling
from aggregate planning. Aggregate planning seeks to determine the resources needed, while scheduling allocates the resources made available through aggregate planning in the best manner to meet operations objectives. Aggregate planning is done on a time frame of about one year; scheduling is done on a time frame of a few months, weeks, or hours.
Scheduling seeks to achieve potentially conflicting objectives: high efficiency, low inventories, and good customer service. Efficiency is achieved by a schedule that main- tains high utilization of labor, equipment, and space. Of course, the schedule should also seek to maintain low inventories; unfortunately, this may lead to low efficiency due to lack of available material or high setup times. Thus, a trade-off decision in scheduling between efficiency and inventory levels is required in the short run. In the long run, how- ever, efficiency can be increased, customer service improved, and inventory simultane- ously reduced by changing the production process itself through cycle time reduction and quality improvement efforts. Scheduling, then, is primarily an activity that involves poten- tial trade-offs between conflicting objectives in the short run.
Because of the conflicting objectives, all functional areas are interested in scheduling. Marketing wants to make sure the most important customers are scheduled first. Finance and accounting want to be sure that the schedule is cost-efficient and makes the best use of available resources. Operations is often at the intersection of a cross-functional scheduling challenge that requires coordination across all the business functions.
12.1 BATCH SCHEDULING
For scheduling batch operations, much of the terminology (“shop,” “job,” and “work cen- ter”) comes from manufacturing job shops. The concepts, however, apply to batch opera- tions of all types, including factories, hospitals, offices, and schools. For service operations, “job” can be replaced by “customer,” “patient,” “client,” “paperwork,” or whatever type of work flows through the process. Furthermore, “work center” can be replaced by “room,” “office,” “facility,” “skill specialty,” or whatever the processing centers are. In this way, the concepts can be generalized to all types of operations.
A few examples of batch scheduling might be helpful. In a university students are processed in batches, with the batch size equal to the number of students in a class. Batch scheduling consists of assigning classes to classrooms and instructors. For manufacturing Louisville Slug- ger aluminum bats, batch sizes of 100 are used to make a variety of models. Different models require processing at different work centers. For example, some bats have a metal end produced by heating and rotating the bat while others receive a plastic end-cap that is snapped into place.
Batch scheduling, the plan for assigning work to the necessary resources, is a very complex management problem. First, each batch flowing through a batch process typically moves along with many starts and stops, not smoothly. This irregular flow is due to the layout of the batch pro- cess by machine group or skills into work centers. As a result, jobs or customers wait in line as each batch is transferred from one work center to the next, and work-in-process (WIP) builds up.
The batch scheduling problem can be thought of as a network of queues. A queue of WIP inventory is formed at each work center as jobs wait for resources to become avail- able. These queues are interconnected through a network of material or customer flows. The problem in scheduling batch processes is how to manage these queues.
One of the characteristics of a batch operation is that jobs or customers spend most of their time waiting in line. The amount of time spent waiting will, of course, vary with the load on the process. If the process is highly loaded (high utilization rate), a job may spend as much as 95 percent of its total production time waiting in queues. Under these circum- stances, if it takes one week to actually process an order, it will take 20 weeks on average to move completely through production. However, if the process is lightly loaded, the waiting
LO12.1 Describe the concept of batch scheduling.
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time will be reduced since all the jobs will flow through the process more rapidly. Regard- less of process load, the challenge is to develop scheduling procedures that will effectively manage the flow of jobs, customers, and work.
We continue this chapter with a discussion of Gantt charts, a simple form of scheduling. This is extended to more complex and realistic settings with discussions of finite capacity schedul- ing and the theory of constraints. The chapter is completed with dispatching rules and examples of scheduling systems used in actual practice. The Operations Leader box on the scheduling of games in a soccer league provides an interesting example of scheduling in practice.
12.2 GANTT CHARTS
One of the oldest scheduling methods is the Gantt chart. Although there are many varia- tions of the Gantt chart, we restrict its use in this chapter to the batch scheduling problem.
The Gantt chart is a table with time across the horizontal dimension and a limited resource, such as machines, people, or machine hours, along the vertical dimension. In the example below, we assume that machines are the limited resource to be scheduled.
LO12.2 Construct a Gantt chart.
that met all constraints while allowing nonconflicting TV broadcasts of the most attractive games, particularly important for revenue purposes. However, since league rules prohibit repeating a previously used schedule, every year’s tournament requires a new schedule!
Source: Adapted from Celso C. Ribeiro and Sebastian Urrutia, “Soccer Scheduling Goaaaaal,” OM/MS Today, April 2010, pp. 52–57; and https://www.capterra.com/sports- league-software/, 2019.
Soccer is far and away the most popular sport in Brazil. Each year, the Brazilian Football Confederation faces the challenge of scheduling its 20 teams in an eight-month tournament to determine a champion. A fair and bal- anced schedule is important, both to maximize revenue and to instill confidence in the tournament outcome.
The goal is to schedule all teams in the tournament while meeting more than 30 different constraints. Exam- ples of constraints are:
• Each team faces each other team twice, playing once at home and once away.
• Every pair of teams plays once in the first half of the tournament and once in the second half.
• Elite teams must play as often as possible on week- ends rather than weekdays.
• Teams with the same home city must have comple- mentary patterns (i.e., when one plays at home, the other plays away).
• No team plays more than two consecutive home games or two consecutive away games.
Numerous other constraints include the rights of certain players, league officials, media sponsors, and city admin- istrators to approve or reject a proposed schedule.
Recently, the league began using software to assist with scheduling. Formulating the scheduling problem while including all constraints was computationally impossible, but solving for some constraints first and then using feasible solutions to resolve other constraints proved fruitful. The league is able to identify a schedule
Soccer Scheduling Goal!
OPERATIONS LEADER
Koji Aoki/Aflo/Getty Images
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252 Part Four Capacity and Scheduling
FIGURE 12.1 Job data for scheduling.
A/2, B/3, C/4 C/6, A/4 B/3, C/2, A/1 C/4, B/3, A/3 A/5, B/3
Due date
3 2 4 4 2
Job
1 2 3 4 5
Work center/ Machine hours
FIGURE 12.2 Gantt chart. Jobs are scheduled in sequence 1, 4, 5, 2, 3.
M ac
hi ne
A
B
C
Time
2 7 8 11 15 19 20
2 85 11 14
4 95 15 17
1
1 4 5 3
4 1 2 3
5 4 2 3
Suppose we have three work centers (A, B, C) consisting of one machine each and five jobs (1, 2, 3, 4, 5) to be scheduled. The processing time of each job in each work center is shown in Figure 12.1 along with sequencing of the jobs through the work centers. For example, job 2 is processed in work center C for six hours followed by four hours in work center A. This is denoted by C/6, A/4 in Figure 12.1.
The jobs are scheduled forward in time within the finite capacity of one machine of each type (A, B, and C). We assume, arbitrarily, that the jobs should be scheduled in the sequence 1, 4, 5, 2, 3.
The Gantt chart resulting from these assumptions is shown in Figure 12.2. This chart is constructed by first scheduling job 1 on all three machines. Job 1 starts on machine A for two hours; then it is placed on machine B for three hours (time 2 to 5); finally, it is processed on machine C for four hours (time 5 to 9). There is no waiting time for the first job sched- uled, since there can be no job interference or waiting. Next, according to the assumed sequence, job 4 is scheduled on the Gantt chart for machines C, B, and then A. Job 4 can begin immediately on machine C, since the machine is open until time 5 and only four hours is needed. After a waiting time of one hour, job 4 can start on machine B. Job 4 can then be scheduled on machine A from time 8 to 11. Next, job 5 is scheduled on the Gantt chart. Job 5 is processed on machine A first, but machine A is already scheduled until time 2. So job 5 starts at time 2 and is completed by time 7. After completion on machine A, job 5 is moved to machine B, which is busy until time 8. Job 5 is then scheduled from time 8 to 11 on machine B. Jobs 2 and 3 are then scheduled.
Example
FIGURE 12.3 Machine idle and job waiting times.
Machine idle (hr)
A 5 B 8 C 4 17
Makespan = 20 hr
Job waiting Delivery Job time (hr) time (hr)
1 0 9 2 9 19 3 14 20 4 1 11 5 3 11
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After the Gantt chart has been constructed, it should be evaluated with respect to both job and machine per- formance. One way to evaluate machine performance is on the basis of the time it takes to complete all work, the makespan. In Figure 12.2, the makespan is 20 hours, since it takes 20 hours to complete all five jobs.
Another measure of Gantt chart performance is machine utilization. In the five jobs, a total of 43 hours of process- ing time is required (simply add machine times for all jobs from Figure 12.1). Utilization is 43/60 = 71.7 percent, because a total of 60 hours of machine time is available (makespan 20 × 3 machines). The 43 hours of processing time is a constant regardless of the schedule used. Notice also that idle time = 3 × (makespan) − 43. Therefore, mini- mizing makespan will also minimize machine idle time.
A measure of job performance is the sum of the wait- ing times for all jobs. In Figure 12.3, the delivery times and job-waiting times are listed for each job. These quantities are obtained directly from the Gantt chart. The delivery time and waiting times will, of course, depend greatly on the job sequence used. Since job 1 was scheduled first, it has no waiting time and is completed ahead of the due date. Jobs 2 and 3, which were scheduled last, have considerable waiting time.
In general, the waiting times of jobs and machine utilization are highly dependent on the sequence of the jobs scheduled. In this case, we have five jobs to schedule and 5! (five factorial) = 120 possible sequences of jobs. If we construct 120 Gantt charts, one for each possible sequence, we could determine the job sequence with the minimum makespan, or the one with the minimum total job waiting time. In general, for n jobs there will be n! possible sequences to evaluate to find the optimal sequence by complete enumeration of all the possibilities. Complete enumeration is often cumbersome or impossible in practical situations in which there may be several hundred or more jobs.
Optimal job-sequencing algorithms attempt to find an optimal solution without enumer- ation of all possible job sequences. One particular problem is called the m × n machine- scheduling problem, where m is the number of machines and n is the number of jobs. Optimal solutions can be found for only relatively small values of m and n. Fairly good heuristics are available to develop good solutions for any values of m and n.
In summary, the following conclusions about batch scheduling can be drawn from Gantt chart scheduling:
1. Schedule performance (makespan, job waiting times, job delivery times, machine utili- zation, and inventory level) is highly sequence dependent (which job is scheduled first, second, third, etc.).
2. The waiting time of a job depends on the job interference encountered in the schedule and the capacity available on machines.
3. Finding the optimal schedule is computationally intensive and cannot be done for most practical size applications. However, good heuristic procedures are available that closely approximate the optimal schedule.
Batch scheduling methods have many applications in both manufacturing and service industries. A service example is the scheduling of patients in a hospital. Patients flow through the hospital and require the services of multiple resources (people and equipment). At one cancer treatment unit, for example, waiting time for appointments for radiology
VISIBLE SCHEDULES. A good schedule must be available for all employees to see. Ingram Publishing
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254 Part Four Capacity and Scheduling
treatments was reduced from 40 days to 16 days despite a 14 percent increase in workload. The new scheduling system allowed the radiology staff to schedule all sequential treat- ments and other linked appointments. This also meant that patients could see the full extent of their treatment plan at the outset.1
12.3 FINITE CAPACITY SCHEDULING
Finite capacity scheduling (FCS) is an extension of Gantt charts. It establishes a work schedule to be produced in a certain time period, considering relevant limitations of resources. Software is often used to determine a good schedule with efficient flow, while accounting for trade-offs of inventory levels and customer service.
FCS schedules jobs through a number of work centers, each with one or more machines that perform the same function. Jobs can pass each other, or change their sequence, as they are processed, depending on their priority. A job can be split if this will facilitate schedul- ing. For example, if the job consists of making 100 parts, the job could be split into two lots of 50 parts each to help the schedule. Alternate routings of a job through the work centers may also be allowed. In FCS, attention is paid to scarce resources to facilitate job flow and improve the performance of the shop. Let’s take a look at a simple example which is an extension to FCS of Figure 12.1. See the highlighted example box below.
This addition of capacity in the form of additional machines substantially improves the completion dates of jobs and reduces their waiting times. The makespan is now 11 hours instead of 20 as before. This type of forward scheduling provides a feasible estimate of a completion date for current orders. Alternatively, backward scheduling can be used to assign orders to machines or other resources, working backward from a due date to determine when work must be started in order to be completed by the due date. Backward scheduling is used when meeting due dates is more important than machine efficiency.
Aside from forward or backward scheduling, it is important to understand the effect of bottlenecks on scheduling. The formal definition of a bottleneck is a work center whose capacity is less than the demand placed on it and less than the capacities of all other resources. A bottleneck resource will constrain the capacity of the entire shop, and an hour added to a bottleneck will add an hour of capacity to the entire plant. An hour added to a non-bottleneck work center will not help the schedule at all, since excess capacity already exists there.
1 N. Huber, “Scheduling System Slashes Radiotherapy Waiting Times by 60% at Wirral Cancer Unit,” Computer Weekly, May 4, 2004, pp. 39–40.
LO12.3 Create work schedules using forward and backward scheduling.
Assume the same situation as in Figure 12.1 that was used for Gantt charting, except now there are two machines of each type in each work center. In other words, there are two machines of type A, two of type B, and two of type C.
We can now construct a Gantt chart with this new information, as shown in Figure 12.4. In this figure, the two machines of type A are labeled A1 and A2. We use the same sequence of scheduling as before, with jobs scheduled in the sequence 1, 4, 5, 2, 3. The Gantt chart will not change for job 1, since this job was scheduled without job interference and no job waiting time. Next, job 4 can be completed one hour earlier by the additional machine added to each work center and is scheduled on machine C1, followed by B2 and A1. Previ- ously job 5 could not start immediately because machine A was already scheduled. Now that we have two machines, job 5 is scheduled on machine A2 followed by B1. Next we schedule job 2, which is benefited substantially by the addition of a second machine of type C; it can be scheduled to start immediately. Also job 3 can start earlier than before.
Example
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In the example in Figure 12.4, work center C is a bottleneck from time 3 to time 6 since job 3 is waiting to be processed.2 Demand exceeds capacity, and no other work center provides a constraint at that time. Work center A is a bottleneck from time 8 to time 10 for similar reasons, and job 3 is again waiting to be processed. Note, the bottleneck is not constant; it shifts from one work center to another.
Scheduling can be improved by adding capacity at the bottleneck work center. If this were done in the example in Figure 12.4, the makespan could be further reduced from 11 hours to 10 hours, the minimum makespan because job 2 has 10 hours of processing time. Capacity can be added in many ways: by adding machine time, reducing setup time, adding overtime, and subcontracting, to name a few. An important principle in scheduling is to find the bottlenecks and work to remove them by improving flow through the bottle- neck resources. FCS can be used to identify the bottlenecks at any point in time.
One way that managers can improve throughput at the bottleneck is to increase the flex- ibility of capacity resources; for example, using equipment that can complete a variety of tasks or cross-training workers so they can work where they are needed most at any given time. The burden on the bottleneck can be eased by shifting its workload to other machines or workers. The resources targeted for increased flexibility must be closely coordinated with the job schedule. 2 We assume for this example that job 3 cannot be split into two or more lots for processing.
FIGURE 12.4 Work center Gantt chart (jobs are sequenced in order 1, 4, 5, 2, 3).
M ac
hi ne
A1
A2
B1
B2
C1
C2
Time
2 7 10 11
2
3 4
4 5
6 8
9
7
5 8
105 6
1
5
1
3 4
4
2 3
1
5
2
34
Machine center idle (hr)
A 7 B 10 C 6 23
Makespan = 11 hr
Job waiting Delivery Job time (hr) time (hr)
1 0 9 2 0 10 3 5 11 4 0 10 5 0 8
M ac
hi ne
A1
A2
B1
B2
C1
C2
Time
2 7 10 11
2
3 4
4 5
6 8
9
7
5 8
105 6
1
5
1
3 4
4
2 3
1
5
2
34
Machine center idle (hr)
A 7 B 10 C 6 23
Makespan = 11 hr
Job waiting Delivery Job time (hr) time (hr)
1 0 9 2 0 10 3 5 11 4 0 10 5 0 8
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256 Part Four Capacity and Scheduling
12.4 THEORY OF CONSTRAINTS
In his popular book The Goal,3 Eliyahu Goldratt argues that making money from operations can be broken down into three measurable quantities: throughput, inventory, and operating expenses. He defines these terms in rather nontraditional ways. Throughput is defined as the sales of the plant minus the cost of raw materials used to produce those sales. It is not enough just to make a product; it must be sold to the customer in order to make money. So, if opera- tions has excess capacity, the task of operations is to help the sales department increase sales (and thus throughput). In contrast, if the plant is operating at capacity, it must push orders through the plant faster to increase throughput. This is done by identifying the bottleneck operations in the plant and increasing the capacity of bottlenecks, often without buying more equipment but through more creative scheduling, overtime, better workforce policies, and so forth. Goldratt calls this the theory of constraints (TOC) since the most important constraint, either sales or the production bottleneck, is being relieved in order to increase throughput.
A plant must also reduce inventory to make money. Goldratt defines inventory as only the raw-material value of any goods being held in inventory, a rather unconventional defi- nition. He puts all labor and overhead costs into the operating expense category not into inventory. Operating expense is the cost of turning raw materials into throughput. His logic is that true costs are distorted by putting labor and overhead into inventory on the assump- tion that the inventory will be sold, when in fact no money is made for the company until the inventory actually is sold.
TOC is based on several principles observed in organizations:
∙ Companies, departments, and teams have unbalanced capacities. Annual budgets attempt to provide resources to balance capacities, but rarely succeed.
∙ There is always a constraint in the system somewhere in the plant, human resources, purchasing, or sales that prevents the company from making more money.
∙ One hour of capacity lost at the constraint (bottleneck) is an hour lost to the whole orga- nization and can never be recovered.
∙ An hour gained at a nonconstraint does not add to the output or profit of the organization. ∙ Constraints must be managed differently than nonconstraints.
TOC has many implications for scheduling. First, the bottleneck is the critical resource and constraint that should be scheduled to achieve maximum throughput. As was noted above, each hour of capacity gained at the bottleneck is an hour gained for the entire plant. All non-bottleneck resources should be scheduled so that the bottleneck is not starved (waiting) for materials and is kept busy processing orders needed for sale. Also, a queue of jobs should be formed in front of the bottleneck resource to ensure that it stays busy. Non-bottleneck resources do not need to operate at full capacity provided that they process enough to keep the bottleneck busy. Thus, some of the non-bottleneck work centers may have idle time in their schedule. Non-bottleneck resources should not produce inventory just to increase resource utilization. They should be idle when their capacity is not needed to supply the bottleneck. See Figure 12.5 for an illustration of the bottleneck constraint and non-bottleneck resources.
Many steps can be taken at the bottleneck resource to increase capacity. These steps include reduction of setup time so that the work center can be quickly changed from one job to the next. Another step is to be sure that the bottleneck resource is used as much as possible and is not shut down for breaks, lunch, or even maintenance that can be deferred. Resources should
LO12.4 Explain the implications of the theory of constraints for scheduling.
3 Eliyahu M. Goldratt and Jeff Cox, The Goal: A Process of Ongoing Improvement, 3rd ed. (Great Barrington, MA: North River Press, 2014).
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be added to the bottleneck work center via additional labor or machines on a temporary basis if possible. When this is done, the operation will progress toward its goal of making money.
In summary, there are four steps to eliminate constraints:
1. Identify the system constraint that prevents the company from making more money. 2. Decide how to reduce the system’s constraint, so it is no longer a constraint. 3. Subordinate everything else (other tasks, work centers, sales, purchasing or other
departments) to reducing the constraint. 4. Once the constraint is eliminated, find the next constraint and start over.
An example might be helpful here. Delta Airlines’ maintenance, repair, and overhaul (MRO) operations used TOC to improve the scheduling of jobs based on their capacity constraint—the repair and support shops. Based on the rate of work done in the repair and support shops, both upstream and downstream work processes were paced to match the bottleneck rate. This helped to reduce inventory in all related work centers. Using TOC, Delta MRO increased throughput by 18 percent and decreased inventory by 50 percent.
Traditional cost accounting attempts to maximize the utilization of all resources and work centers even if they build inventory that is not needed and even if the work centers are not bottlenecks. TOC argues that non-bottleneck resources can remain idle some of the time, pro- vided that they do not constrain the bottleneck. Maximizing the efficiency of each resource, or reducing their standard cost variances to zero, does not make more money for the company.
Firms should consider the following ways to reduce bottlenecks: ∙ Can more capacity be added at the bottleneck, even if it is less efficient, or uses anti-
quated equipment or expensive overtime, or is outsourced to a vendor? ∙ Can the work that does not absolutely need to go through the bottleneck be diverted to
another non-bottleneck resource? ∙ Can work that has poor quality and will be scrapped later be prevented from reaching
the bottleneck? ∙ Can the output of the bottleneck be increased by running larger batches or reducing the
setup time?
FIGURE 12.5 The bottleneck constrains the flow of the entire system.
Bottleneck
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258 Part Four Capacity and Scheduling
The theory of constraints has had a major impact on scheduling software design and practice. Software using finite capacity scheduling can identify bottlenecks and make it possible to configure schedules that achieve the goal of making more money.
TOC can also be applied to service operations. The Odessa, Texas, police department used TOC to improve its process for hiring new police officers.4 The old pro- cess consisted of eight steps: application, written exam, background investigation, oral interview, polygraph exam, medical exam, psychological exam, and drug screening. The entire hiring process took 117 days from initial application to successful hiring of a candidate. While most of the steps were completed in a few days, the background investigation took 104 days and became the constraint or the bottleneck in the process. Of the
60 applicants each year, only 10 were able to complete the entire process and were hired. Because of the long waiting time, many applicants became discouraged and found jobs elsewhere. As a result, the Odessa Police Department had a shortage of qualified police officers.
To relieve the bottleneck, it was decided that the background check should be divided into two parts, a cursory initial background check followed by a complete background check. The cursory initial check could be done in one day and would eliminate some appli- cants immediately. The complete background check would be done only after an applicant passed most of the other steps. As it turned out, it took only 3 days of processing to com- plete the entire background check and most of the 104 days was waiting time. As a result of reducing the workload on the bottleneck, the total throughput time was reduced from 117 days to 16 days, and the yield of the process improved to provide the badly needed 20 officers per year.
12.5 PRIORITY DISPATCHING RULES
Dispatching is a technique used during scheduling to determine the job priority at any particular work center. The priority of a job may change from one work center to another, depending on the particular dispatch rules chosen. In finite capacity scheduling, the dis- patch rule is used to select the particular job to schedule next in a work center when more than one job is waiting in line to be processed.
In practice, schedules are difficult, if not impossible, to maintain because conditions often change: A machine breaks down, a qualified operator is ill, materials do not arrive on time, and so on. Real-time adjustments to the schedule are made by use of dispatch rules to determine which job to process next.
A dispatch rule specifies which job should be selected for processing next from among a queue of jobs. When a machine or worker becomes available, the dispatch rule is applied and the next job is selected. A dispatch rule is thus dynamic in nature and continually sets the priority on the basis of changing conditions.
4 L. J. Taylor, III, B. J. Moersch, and G. M. Franklin, “Applying the Theory of Constraints to a Public Safety Hiring Process,” Public Personnel Management 32, no. 3 (2003), pp. 367–382.
LO12.5 Compare various dispatching rules.
The police department in Odessa, Texas, used TOC to improve the hiring process. Blend Images/Alamy Stock Photo
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In practice, several types of dispatch rules are used. For services three types of rules are common: 1. First come, first served (FCFS) is very common and gives customers a feeling of fair-
ness. Using this rule, customers are served in the exact sequence in which they enter the waiting line. FCFS is rarely used in manufacturing since it performs poorly in meeting due dates and minimizing makespan.
2. Priority rule assigns some customers to be served before others. The priority can be based on the price the customer paid (for example, flying using a first-class ticket), the expected time to service their needs (for example, the “10 items or less” lane at the gro- cery store), or other factors.
3. Preemptive rule is used to interrupt service for one customer and shift capacity to a customer with more urgent needs. Hospitals, police, and fire services often use a pre- emptive rule to shift resources to a customer in a life-or-death situation. For manufacturing, two types of dispatch rules are commonly used:
1. Critical ratio (CR) is computed as
CR = remaining time until due date _______________________ remaining processing time
The job with the minimum value of CR is scheduled first, the job with the next smallest value of CR is scheduled next, and so on. When the ratio exceeds a value of 1, there is sufficient time available to complete the job if the queue times are managed properly. If the ratio is less than 1, the job will be late unless processing times can be compressed. The CR rule has a precise meaning; for example, a ratio of 2 means there is twice as much time remaining until the due date as the processing time.
2. Shortest processing time (SPT) means the job with the least time needed on the machine (or resource) is selected. This rule is based on the idea that when a job is fin- ished quickly due to its short processing time, other machines downstream will receive work, resulting in a high flow rate and high utilization. While the SPT rule is good at achieving efficiency and high throughput, it is poor at
meeting due dates, primarily because due dates are not considered in its calculation. How- ever, due dates are very critical in practice. The CR does a much better job of meeting due dates since it explicitly considers them in its calculation.
Lead times can vary depending on how managers set them and how work is scheduled. If a job is given a very tight due date, perhaps just a little greater than total processing time, a rule such as CR will speed the job through the shop because of its high priority. Depending on the dispatching rules used, lead time can be expanded or contracted to a great extent.
It comes as a surprise to some people that lead times can be managed. The common view is that lead time is relatively fixed or a statistical phenomenon. There is lit- tle realization that lead time is a function of both priority and capacity. If an operation is producing at near capac- ity, average lead times will be extended. Even though the average lead time is long, an individual job can be quickly delivered if its priority is high. Thus, lead time is a function of both capacity and priority decisions.
This dispatcher determines the priorities of work being done. Rick Brady/McGraw-Hill Education
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260 Part Four Capacity and Scheduling
In summary, dispatching rules are used to determine the priority of a job during sched- uling and in real time during processing. The priority of a job can be changed dynamically as it is processed through the shop. See the Operations Leader box for an example of using a priority rule for scheduling golf tee times.
12.6 PLANNING AND CONTROL SYSTEMS
When scheduling operations, a planning and control system is needed. This system should facilitate the development of good schedules (planning) and ensure that schedules are implemented and corrected as needed (control). These scheduling systems incorporate the methods described above. But without managers’ attention to the overall system, the meth- ods are useless.
Every scheduling system should answer several questions:
1. What delivery date do we promise? The promised delivery date should be based on both marketing and operations considerations, including available capacity and cus- tomer requirements. We have seen how the promised date can be derived through Gantt chart scheduling or FCS. Marketing needs to input appropriate customer priorities into the scheduling process. Finance needs to make the capital available in time. All functions need to work together for the best interests of customers and the bottom line of the business.
2. Where is the bottleneck? Capacity of the entire facility will be limited by the bot- tleneck work center. The scheduling method must therefore find the bottleneck and work to remove it by adding more capacity with approaches such as reducing the setup time, adding equipment, overtime, subcontracting, and reassigning work at the bottleneck.
LO12.6 Describe the important factors to consider when designing a scheduling system.
the first choice of golf course and requested tee times, since they have recently played the least. Golfers that play the most and have high point totals are given the lowest priority for their requested times when sched- uling. The assignment process is continued until all 7000 golfers are scheduled by the reservation system or the courses run out of capacity.
This point system helps avoid wasting golf course capacity by encouraging players to use their scheduled tee times and also provides fair and equal access to the courses for all residents. Since executive golf courses can be played free of charge, the point system prevents individual golfers from overusing the courses. This golf community is successful in using priority rules to allocate tee times to residents.
The Villages is a retirement com- munity in Florida with 666 holes of golf consisting of 12 championship courses with 27 holes each and 38 nine-hole executive courses. Sched- uling over 7000 golfers per day on these courses presents a tremen- dous challenge. The Villages accom- plishes this by utilizing an online reservation system that uses a prior- ity dispatching rule.
Each time a resident schedules a round of golf, he/ she is assigned one point. If the reservation is canceled prior to play, the player is assigned another point, and if the player does not show up for the scheduled tee time, a third point is assigned. A rolling total count of points is kept for the most recent seven days. When requesting tee times, players with the lowest point totals are given
Scheduling Golf at The Villages in Florida
OPERATIONS LEADER
linda nolan/Alamy Stock Photo
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3. When should we start each job, activity or task? This question is answered by using dispatching rules or a Gantt chart/FCS schedule.
4. How do we ensure that the job is completed on time? Dispatching helps answer this question partially, but the answer also requires constant activity monitoring. Correc- tive action can be taken as needed to make sure that jobs are finished on time.
Advanced planning and scheduling (APS) is a process and software that includes scheduling methods such as finite capacity scheduling, constraint-based bottleneck sched- uling, and dispatching at the plant-floor level. APS systems consider materials require- ments and plant capacity when generating a daily production schedule, helping to achieve goals such as maximum throughput with minimum inventory while meeting customer due dates.
To illustrate the principles of a scheduling planning and control system, an example is discussed.
Courtroom Scheduling Courtroom scheduling requires scheduling planning and control systems. Sometimes court calendars are overloaded, with the result that police officers, witnesses, lawyers, and defendants spend long times waiting. After a day of waiting without being heard, some witnesses will not return.
At the same time, the court may suffer from case underload, with judges kept waiting and inefficient use of courtrooms. This condition occurs when cases finish earlier than expected or cases scheduled to appear are delayed.
In an attempt to correct these problems, a court-scheduling system was developed for the New York City Criminal Court to achieve the following objectives: (1) high probability that judges will be kept busy, (2) high probability that cases will be heard when scheduled, (3) several cases for a police officer should be batched on the same day, (4) high-priority cases should be scheduled as soon as possible, and (5) a maximum waiting-time limit should be set for all cases.
The heart of the system was a priority dispatching rule. Cases are not scheduled until they meet the priority rule based on factors such as seriousness of the charge, whether
the defendant was in jail, and elapsed time since arraign- ment. When the priority of a case reaches a certain thresh- old, it is inserted into the court calendar; otherwise it remains unscheduled.
When a case was scheduled, the capacity reserved for it was predicted by a multiple regression equation that utilized causal variables such as the plea of the defendant, seriousness of the offense, number of witnesses, and presiding judge. The pre- dicted time was then scheduled for the first available spot on the calendar. Some slots, however, were kept open for emergen- cies and future rescheduling.
Each day the planning and control system allows priorities to be revised on the basis of the current conditions. Any new cases with a high enough priority are added to the schedule.
This example illustrates how a service operation can use a dispatching rule as part of a planning and control system, and how the system answers the crucial questions above. Schedul- ing embedded in an information system helps answer the crucial questions required to develop and implement the schedule.
Courtrooms can be scheduled with better systems. Guy Cali/Corbis/Getty Images
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262 Part Four Capacity and Scheduling
12.7 KEY POINTS AND TERMS
In this chapter, we have treated scheduling decisions for batch operations. The chapter’s theme is that all scheduling decisions deal with the allocation of limited resources to jobs, activities, tasks, or customers. We assume, for scheduling purposes, that resources are fixed as a result of aggregate planning and facilities decisions.
The following are among this chapter’s key points:
∙ Within the available resources, scheduling seeks to satisfy the conflicting objectives of low inventories, high efficiency, and good customer service. Thus, trade-offs may be implicitly or explicitly made whenever a schedule is developed. Because of the poten- tial for conflicting objectives, cross-functional coordination is required for effective scheduling.
∙ Gantt charting is the simplest form of scheduling. It is used to schedule jobs one at a time according to the resources available. Gantt charting will determine the waiting time of each job, job completion dates, resource (machine) utilization, and the make- span of all jobs.
∙ Finite capacity scheduling is used to schedule multiple jobs through a number of differ- ent work centers. The jobs are scheduled in a manner similar to Gantt charting except that each work center may have multiple machines (or resources). In finite scheduling, efforts are made to improve job flow through bottlenecks by splitting jobs, alternative routings, overtime, and other methods.
∙ The theory of constraints (TOC) is aimed at making money by managing throughput, inventory, and operating expenses. The bottleneck resource is scheduled to increase throughput, while non-bottleneck resources are scheduled to keep the bottleneck busy.
∙ Dispatching is used to decide on the priority of jobs as they pass through the factory or service process. Various dispatching rules can be used to decide which job or activity to process next at each work center.
∙ Scheduling systems should answer the following questions: (1) What delivery date do we promise? (2) Where is the bottleneck? (3) When should we start each job, activity, or task? (4) How do we ensure that the job is completed on time? To handle constantly changing situations, these systems are usually part of an information system and they operate as a daily planning and control system.
∙ Lead time for completion of a job is not a statistical phenomenon. Lead time is a func- tion of both capacity and priority decisions.
Key Terms Time-phased plan 249 Trade-off decision 250 Batch scheduling 250 Network of queues 250 Gantt chart 251 Makespan 253 Machine utilization 253 Machine-scheduling
problem 253
Dispatch rule 258 First come, first served 259 Priority rule 259 Preemptive rule 259 Critical ratio 259 Shortest processing
time 259 Advanced planning and
scheduling 261
Finite capacity scheduling 254 Forward scheduling 254 Backward scheduling 254 Bottleneck 254 Throughput 256 Inventory 256 Operating expenses 256 Theory of constraints 256 Dispatching 258
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LEARNING ENRICHMENT (for self-study or instructor assignments)
Theory of Constraints—Introduction Video https://youtu.be/1UqWejurWwU 3:36
Round Robin CPU Scheduling Algorithm Video https://youtu.be/aWlQYllBZDs 4:23
Linear Programming for Staff Scheduling Video https://youtu.be/3I8B21M-ob8 3:58
nMetric—Smart Job Scheduling Priority Video https://youtu.be/y9DqLj9MGzU 1:59
Job Shop Scheduling Video Scheduling: Washburn Guitar 10:40
SOLVED PROBLEMS
1. Gantt Charting The table below includes information about four jobs and three work centers. Assume that six hours is required to transfer a job from one work center to another (move time not including waiting time for busy machines). Sequence the jobs with a Gantt chart. Use the following priority order: 1, 2, 3, 4. Can you tell if any jobs will be late? Which ones? Can a simple reordering of job priorities alleviate the problem?
Job Work Center/Machine Hours Due Date (days)
1 A/2, B/1, C/4 3 2 C/4, A/2 2 3 B/4, A/2 2 4 B/4, A/2, C/3 3
Work center Time (in hours)
A
B
C
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
1 3
2
4 1 2 3 4
1 4
Job 4 will be one day late, since it is due at the end of day 3, and it will still need one hour of processing on day 4 to be completed. But moving job 4 in front of job 3 in the schedule priority would allow job 4 to be completed one hour before it is due. Job 3 would still be done on time.
2. Priority Dispatching Rules The five jobs listed below are waiting for their final oper- ation at a work center. Determine the order of processing for the jobs by using the fol- lowing rules: SPT, FCFS, and CR.
Job Processing Time Due Date Order of Arrival
A 5 10 3 B 7 18 1 C 6 29 2 D 2 12 5 E 10 19 4
Problem
Solution
Problem
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264 Part Four Capacity and Scheduling
The order of processing for each rule is given below. The SPT rule assigns jobs with the smallest amount of processing time first. The job with the next smallest amount of process- ing time is assigned to be produced next, and so on. According to this rule, the following sequence is used:
D−A−C−B−E
The CR rule assigns the jobs on the basis of the minimum ratio of total time remaining to total processing time remaining. In this case we take the ratio of due date to processing times in the table and arrange the jobs in sequence from the minimum to the maximum CR ratio, resulting in the following sequence:
E−A−B−C−D
The FCFS rule assigns the job that arrived first to be processed first, and so on. Accord- ing to this rule, the following sequence is used:
B−C−A−E−D
3. Finite Capacity Scheduling A medical clinic has three departments (A, B, and C) that can process patients. Each department has one clinician, except Department C, which has two. Currently there are four patients who must be scheduled through the three departments on a first come, first served basis in the sequence patient 1, 2, 3, and 4. The times required to process each patient in each department are shown below.
Patient Department/Time
1 B/2, C/2, A/3 2 A/2, C/3, A/1 3 B/3, C/1, A/2 4 C/2, B/3
Using finite capacity scheduling, draw a Gantt chart for the schedule.
a. What is the makespan? b. Which department is the bottleneck? c. If capacity is added to relieve the bottleneck, what is the new makespan?
The Gantt chart is shown below.
A B
C
C
0 1
1
1
2 2
2
2 3
3
3
3
4
4 4
5 1
6 7 8 9 10
a. The makespan is 10. b. Department A is the bottleneck. Patients 2 and 3 could be completed earlier if capac-
ity were added to the bottleneck. Department A constrains the output (makespan) of the entire facility.
c. The new makespan is 8 if one more clinician is added to Department A.
Solution
Problem
Solution
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Chapter 12 Scheduling Operations 265
Discussion Questions 1. What types of scheduling decisions are manage-
ment likely to encounter in the following operations? Describe the scheduling decisions in terms of the types of resources to be scheduled and the associated custom- ers or jobs scheduled.
a. Hospital b. University c. Moviemaking d. Make-to-order factory 2. Specify the kinds of objectives that might be appropri-
ate for each of the situations listed in question 1. 3. Why is it important to view a batch-process operation
as a network of interconnected queues? 4. How is the scheduling of patients in a doctor’s clinic simi-
lar to and different from the scheduling of jobs in a factory?
5. Describe the differences between Gantt charting, FCS, and the theory of constraints.
6. Why are m × n machine-scheduling algorithms not widely used in practice?
7. What is the purpose of a planning and control system related to scheduling?
8. What is the goal as stated by the theory of constraints (TOC), and how is that goal achieved?
9. What is the definition of a bottleneck according to TOC?
10. What scheduling rule should be applied to bottleneck work centers, and what scheduling rule should be applied to non-bottleneck work centers?
11. What measures can be taken to provide more capacity at a bottleneck work center?
Problems 1. Students must complete two activities to register for class:
registration and payment of fees. Because of individual dif- ferences, the processing time (in minutes) for each of these two activities for five students varies, as shown below:
Minutes
Student Registration Pay Fees
A 12 5 B 7 2 C 5 9 D 3 8 E 4 6
a. Construct a Gantt chart to determine the total time required to process all five students. Use the follow- ing sequence of students: D, E, B, C, A.
b. Can you construct a better sequence to reduce the total time required?
c. What problems might be encountered in using this approach to registration in colleges?
2. Six jobs must be processed through machine A and then machine B as shown below. The processing time for each job is also shown.
Machine (minutes)
Job A B
1 10 6 2 6 12 3 7 7 4 8 4 5 3 9 6 6 8
a. Develop a Gantt chart to determine the total time required to process all six jobs. Use the following sequence of jobs: 1, 2, 3, 4, 5, 6.
b. Can you develop a better sequence to reduce the total time required for processing?
3. Sequence the jobs shown below by using a Gantt chart. Assume that the move time between machines is one hour. Sequence the jobs in priority order 1, 2, 3, 4.
Job Work Center/Machine Hours Due Date (days)
1 A/3, B/2, C/2 3 2 C/2, A/4 2 3 B/6, A/1, C/3 4 4 C/4, A/1, B/2 3
a. What is the makespan? b. How much machine idle time is there? c. When is each job delivered compared with its due
date? d. How much idle time (waiting time) is there for each
job? e. Devise a better job sequence for processing. 4. In problem 3, assume there are two machines of type A,
two of type B, and two of type C. a. Prepare a finite capacity schedule. b. Compare the FCS to the Gantt chart in problem 3. 5. In problem 2, assume there are two machines of type A
and two of type B. a. Prepare a finite capacity schedule. b. How does your FCS compare to the performance of
the Gantt chart in problem 2?
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266 Part Four Capacity and Scheduling
6. The Security Life Insurance Company processes all new life insurance policies through three departments: incom- ing mail (I), underwriting (U), and policy control (P). The incoming mail department receives applications and customer payments and then routes the files to the under- writing department. After checking on the applicants’ qual- ifications for life insurance, the underwriting department forwards the file to policy control for the issue of the policy. At the present time, the company has five new policy applications waiting to be processed. The time required for processing in each department is shown below.
Policy Department/Hours
1 I/3, U/6, P/8 2 I/2, P/10 3 I/1, U/3, P/4 4 I/2, U/8, P/6 5 I/1, P/6
a. Prepare a Gantt chart schedule for these policies. 7. At the University Hospital, five blood samples must
be scheduled through a blood-testing laboratory. Each sample goes through up to four different testing sta- tions. The times for each test and the due dates for each sample are as follows:
Sample Test Station/Hours Due Date (hours)
1 A/1, B/2, C/3, D/1 6 2 B/2, C/3, A/1, D/4 10 3 C/2, A/3, D/1, C/2 8 4 A/2, D/2, C/3, B/1 14 5 D/2, C/1, A/2, B/4 12
a. Using a Gantt chart, schedule these five samples in priority order of earliest due date first.
b. Assume that the capacity of each test station (A, B, C, and D) is doubled. Prepare an FCS for this situation.
c. What are the bottleneck work centers in part a of the problem? Suggest capacity additions that might be needed.
8. A secretary is considering three dispatching rules for typing term papers. The following information is given on jobs that are waiting to be typed:
Total Processing Hours Remaining Time Order until Due Processing (typing of Paper Date Time* (hours) hours) Arrival
A 20 12 10 4th B 19 15 12 3d C 16 11 6 2d D 10 5 5 1st E 18 11 7 5th
*Includes typing, corrections, and copying.
Use the following dispatching rules to determine the sequence for term paper processing. a. SPT b. FCFS c. CR 9. Suppose you are in charge of dispatching for the
University Hospital laboratory described in problem 7. Use the following dispatching rules for the first station (A) to determine which job should be processed first through station A. Hint: Decide between jobs 1 and 4.
a. SPT b. CR 10. Using the Gantt charts developed in the following prob-
lems, which is the bottleneck work center? a. Problem 2 b. Problem 3 c. Problem 6 11. How would the theory of constraints be used to improve
output for the operations in the following problems? a. Problem 2 b. Problem 3 c. Problem 6
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Project Planning and Scheduling
13 c h a p t e r
After reading this chapter, you should be able to:LEARNING OBJECTIVES
LO13.1 Explain the nature of trade-offs among the three objectives of project management.
LO13.2 Describe the four activities included in project management.
LO13.3 Distinguish the advantages and disadvantages of a network over a Gantt chart for project scheduling.
LO13.4 Calculate the ES, EF, LS, LF for an example network.
LO13.5 Explain the significance of the critical path and slack.
LO13.6 Calculate the cost of crashing a network by one or two days.
LO13.7 Contrast and compare the use of constant-time and CPM networks.
A significant amount of the work that is carried out by firms, nonprofit organizations, and governments is managed as projects. Projects undertaken by business firms include set- ting up new production facilities, putting on concerts at large stadiums, as well as nearly all consulting projects. Nonprofit organizations use projects to tackle problems, such as the Gates Foundation goal to eradicate malaria, which is approached through multiple and often overlapping projects. Government projects are many, including managing the imple- mentation of a new electronic health record for the Veterans Administration.
While projects have varying degrees of complexity, most will benefit from specific tools and techniques designed to help manage projects. Large projects, in particular, can be very unwieldy without such tools for scheduling and managing the many different elements of the project. Here, we introduce helpful ways to manage the project type of operation, which produces a unique product or service.
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268 Part Four Capacity and Scheduling
In this chapter, you will learn how to manage both small and large projects. A project is an operation or process undertaken to create a unique product, service, or outcome. It should be noted that projects have a spec- ified beginning and end; they are not ongoing activities. Because of this, the management of a project differs considerably from that of an ongoing operation.
Although many decisions in projects differ from those in ongoing operations, our main concern in this chapter is with project planning and scheduling decisions. In the first part of the chapter, a broad framework for project planning is established; this includes the project objec- tives and the planning and control activities they require. In the second part of the chapter, specific scheduling methods are described in detail.
Projects include a wide range of manufacturing and service activities. Large objects such as ships, passenger airplanes, and satellite launchers are manufactured on a project basis. Each unit is made as a unique item, and the manufac- turing process is often stationary, so that materials and labor must be brought to the proj- ect site. The construction of buildings typically is organized on a project basis. Services such as making movies and fund-raising campaigns are also produced on a project basis. Table 13.1 lists a wide range of manufacturing and service activities that are managed as projects.
13.1 OBJECTIVES AND TRADE-OFFS
In projects, there are usually three distinct project objectives: cost, schedule, and perfor- mance. The project cost is the sum of direct and allocated costs assigned to the project. The project manager and project team’s job is to control those costs that are directly control- lable by the project organization. These costs typically cover labor, materials, and some support services. Ordinarily, the project will have its own budget, which includes the costs assigned to the project.
The second objective in managing projects is schedule. A project completion date and intermediate milestones frequently are established at the outset. Just as the project team and manager must control the project costs within budget, they must also control the schedule to meet established dates. Frequently, the budget and schedule conflict. For exam- ple, if the project is behind schedule, overtime may be needed to bring it back on schedule. But there may be insufficient funds in the budget to support the overtime costs. Therefore, a trade-off decision between time and cost must be made. Management must determine whether the schedule objective is of sufficient importance to justify an increased cost.
LO13.1 Explain the nature of trade-offs among the three objectives of project management.
TABLE 13.1 Examples of Projects Building construction Movie making
New product introduction Teaching a course Research and development Designing an advertising campaign Computer system design Start-up or shutdown of a plant Installation of equipment Manufacture of aircraft, ships, and large machines NASA mission Auditing accounts Fund-raising campaign Planning a military invasion
Planning for a large fund-raising gala is managed as a project. HIZIR KAYA/123RF
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The third objective in project management is performance, that is, the performance characteristics of the product or service being produced by the project. For constructing a building, performance can be meeting the specifications and blueprints for the building. If the project is a movie, performance refers to the quality of the movie produced. In this case, performance may be specified by a variety of movie standards regarding casting, sound, filming, and editing. Generally speaking, performance is meeting some measures of outcome success for the project.
Performance may also require trade-offs with both schedule and cost. In a movie, for example, if the picture is not meeting performance expectations, additional shots or script revisions may be required. These performance requirements may, in turn, cause cost and schedule changes. Since it is rarely possible to predict performance, schedule, and cost requirements accurately before a project begins, numerous trade-offs may be required while the project is under way.
13.2 PLANNING AND CONTROL IN PROJECTS
A general sequence of management decisions required in all projects is planning, schedul- ing, control, and closing. Details of some of the activities involved in each of these project stages are shown in Table 13.2.
Project planning refers to those decisions required in the beginning of a project that establish its general character and direction. Project planning establishes the major proj- ect objectives, the resources required, the type of organization used, and the key people who will manage and implement the project. Project planning is usually a function of top and middle managers, with a cross-functional team often making all major decisions. When completed, project planning should be documented by a project authorization form or letter, which is used to initiate further project activities. The project authorization form should specify all the planning decisions listed in part A of Table 13.2.
In the project scheduling phase of project management, the cross-functional team specifies the project plan in more detail. This phase begins with the construction of a detailed list of project activities, called a work breakdown structure. A detailed time
LO13.2 Describe the four activities included in project management.
TABLE 13.2 Project Management Activities and Decisions
A. Planning Identify the project customer Establish the end product or service Set project objectives Estimate total resources and time required Decide on the form of project organization Make key personnel appointments (project manager, etc.) Define major tasks required Establish a budget
B. Scheduling Develop a detailed work breakdown structure Estimate time required for each task Sequence the tasks in the proper order Develop a start/stop time for each task Develop a detailed budget for each task Assign people to tasks
C. Control Monitor actual time, cost, and performance Compare planned to actual figures Determine whether corrective action is needed Evaluate alternative corrective actions Take appropriate corrective action
D. Closing Finish all work Close contracts Pay all accounts payable Turn over project to owners Reassign personnel and equipment
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270 Part Four Capacity and Scheduling
schedule for each activity in the work breakdown structure is then established using the methods described later in this chapter. When the time schedule is completed, a time- phased budget, which is keyed to the start and completion times of each of the project activities, can be developed. Finally, the project personnel can be assigned to individual project activities.
A work breakdown structure (WBS) is a hierarchical listing of all the tasks needed to complete a project. It is constructed by organizing the project into activities and subactivi- ties, as shown in Figure 13.1 for a banquet. Note how Level 2 consists of all the activities needed to complete the banquet, including planning and supervision, dinner, the room and equipment, guests, staff, and speakers. Each of these activities, in turn, is broken down into Level 3 subactivities that have to be completed. From the WBS, a schedule can be
prepared and a budget and personnel can be assigned to each activity. This makes it possible to assign responsi- bilities for each part of the project and even subcontract portions of the project if desired. The WBS becomes the basis for planning, scheduling, budgeting, and con- trolling the project.
Project control is maintained by the cross- functional team, which monitors each activity as the work is per- formed on the project. Activities should be monitored for time, cost, and performance in accordance with the project plan. When a significant discrepancy exists between actual results and the plan, corrective action should be taken. These corrective actions might include revision of the plan, reallocation of funds, personnel changes, and other changes in resources. Such correc- tive actions should make the plan feasible and realistic once again.
FIGURE 13.1 Work breakdown structure example—Banquet. Source: Reprinted from www.hyperthot.com/pm_ wbs.htm
Banquet
Planning & Supervision Dinner
1.0“Level 1” =>
1.2 1.3 1.4 1.5 1.61.1
Planning
Budget
Disbursements/ Reconciliation
Coordination
Menu
Shopping List
Shopping
Cooking
Serving
Site/Room
Tables/Chairs
Setting/ Utensils
Decorations
Equipment, Pots, etc.
Guest List
RSVPs
Name Tags
Special Needs
Shoppers
Cooks
Servers
Hosts
Cleanup
Invite
Transport
Coordinate Topics
Backup for No-Shows
Thank-yous
Guests Staff SpeakersRoom &Equipment
“Level 2”
“Level 3” =>
BOEING PRODUCTION. Large aircraft are produced by using project management methods. © Larry W. Smith/Getty Images
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Project closing is concerned with formally ending a project. It includes finishing all work, closing all subcontracts, paying all bills, the turnover of the project to its “own- ers,” and reassignment of the personnel and equipment used on the project. It is important to close a project so that a specific ending is defined. In road construction the closing phase is often ended with the “ribbon cutting.” All the phases of a typical project at Churchill Downs are shown in the Operations Leader box.
Project management is a profession. As such, it has a body of knowledge, a profes- sional organization—the Project Management Institute (PMI), and a variety of recognized certifications. The body of knowledge is extensive and forms the basis for certification as a project manager. See Table 13.3 for the topics in the body of knowledge defined by the PMI.
We have already discussed some of the subjects in the body of knowledge. Owing to space limitations, the remainder of this chapter will be restricted primarily to project scheduling methods and related concepts such as the critical path and slack.
with a budget and a designated project manager. Then at the next gatepost, the charter and work breakdown structure are developed. This is followed by monitoring progress and risk assessment as the project progresses around the racetrack until it reaches the finish line. Since this approach was so successful for an initial IT project, it was expanded to other projects at Churchill Downs.
Source: PM Network, July 2009, pp. 40–45 and Churchilldowns.com, 2020.
Churchill Downs is famous for the annual Kentucky Derby horse race—“the most exciting two minutes in sports.” Prior to establishing a project management office (PMO), they managed projects in an informal way. Churchill Downs then hired a project director and established a PMO to formalize the process of project management. To ease the organization into the new process, a racetrack analogy was developed as shown below. The starting gate consists of initial approval and prioritization along
Churchill Downs Embraces Project Management
OPERATIONS LEADER
Paddock
Starting Gate
1 Investment Request Worksheet
2 Approval & Prioritization
3 Charter 4 Work Breakdown Structure
5 Risk & Issues Logs 6 Scope Change Control (Requests/Logs) 7 Testing/Defect Tracking
8 IT Approval (as applicable) 9 Production Turn/Implementation
10 Sponsor Approval
11 Lessons Learned 12 Benefit Measurement
3/4 mile1/2 mile
1/4 mile FinishWinner’s Circle
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272 Part Four Capacity and Scheduling
13.3 SCHEDULING METHODS
Several types of scheduling methods are in use. These may be generally classified as Gantt chart or network methods. Gantt chart methods utilize a bar chart, as shown in Figure 13.2. The network methods use a graph or network to show precedence relationships.
The Gantt chart method of scheduling has a great deal in common with Gantt chart scheduling for batch processes as described in the previous chapter. In each case, the activ- ity durations are shown on the chart by a bar or line. These charts also show when each activity is scheduled to begin and when it will be completed.
LO13.3 Distinguish the advantages and disadvantages of a network over a Gantt chart for project scheduling.
TABLE 13.3 Project Management Institute Body of Knowledge
1. Integration Management Develop project charter Project planning Project execution Monitor and control
2. Scope Management Scope planning Work breakdown structure Scope verification Scope control
3. Schedule Management Sequencing of activities Resource estimating Activity duration estimating Schedule control
4. Cost Management Cost estimating Cost budgeting Cost control
5. Quality Management Quality planning Quality assurance Quality control
6. Resource Management Organize project team Lead project team Manage project team
7. Communications Management
Communications planning Information distribution Performance reporting
8. Risk Management Risk management planning Risk resource planning Risk monitoring and control
9. Procurement Management
Contracting Select sellers Contract administration Contract closure
10. Stakeholder Management
Identify stakeholders Analyze expectations Analyze impact Engage stakeholders
Figure 13.2 is a simplified Gantt chart for establishing a new office location for a business. Time is shown across the top, and activities are shown down the side. Each activity in the project is depicted as a bar on the chart over the period of time for which the particular activity is scheduled.
The first activity in the chart is to decide on the location and lease the office space, which is started and completed in Week 1. After this is decided, the company can begin to hire workers and arrange for furnishings and phones. Thus, activities 2, 3, and 5 occur after activity 1. The chart also shows that arranging for furnishings, hiring, and arranging for phones occur in parallel during the same time frame. The Gantt chart therefore shows not only how much time is required for each activity but also when each activity takes place.
Example
Gantt charts are commonly used in project scheduling because they are easy to use and quite widely understood. In complex projects, however, a Gantt chart becomes inadequate because it does not show the interdependencies and relationships between activities. For complex projects, it is difficult to schedule the project initially and even more difficult to reschedule it when changes occur. The network method of project scheduling overcomes these difficulties.
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The advantage of the network method over the Gantt chart is that the precedence rela- tionships in network scheduling are shown explicitly on the network. This permits the development of scheduling algorithms that account for all precedence relationships when the schedule is developed. With Gantt charts, the precedence relationships must be kept in the scheduler’s head. On complex projects, this cannot be done easily, and Gantt charts become unwieldy. Furthermore, when a single activity time changes on the Gantt chart, the entire chart must be rescheduled by hand. Rescheduling can be done automatically by a network algorithm. In contrast, networks are more complex, more difficult to under- stand, and more costly to use than Gantt charts. Thus, networks should be used in complex projects that have many different interrelated activities. However, when using scheduling software even very simple projects can take advantage of network methods.
Network scheduling methods involve the use of some important scheduling concepts, such as critical path and slack. These network scheduling concepts will be described next by means of the constant-time network. More complicated networks using time-cost trade- offs will be discussed later in the chapter.
13.4 CONSTANT-TIME NETWORKS
In constant-time networks, the time for each activity is assumed to be a constant. This is the simplest case from the standpoint of scheduling. Other, more complicated methods are then derived from these constant-time network methods.
First, we illustrate the construction of a simple network. Table 13.4 shows the activities required to write a typical business report. The first activity, A, is to decide on the topic and scope of the report. Then two activities, B (collect data) and C (search the Internet), proceed in parallel or at the same time. Once B and C are completed, the report can be written (activity D). Table 13.4 indicates the immediate predecessors of the activities we
LO13.4 Calculate the ES, EF, LS, LF for an example network.
FIGURE 13.2 Gantt chart project example.
No. Activity Description 2 3 4 5 6 71 8 Week
Hire the workers
Arrange for the furnishings
Install the furnishings
Arrange for the phones
Install the phones
Move into the office
1
2
3
4
5
6
7
Lease the site
TABLE 13.4 Write a Business Report
Activity Description Immediate
Predecessors Duration in
Days
A Decide topic and scope None 1 B Collect data A 2 C Search the Internet A 3 D Write the report B and C 5
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274 Part Four Capacity and Scheduling
have just described. Activity A has no immediate predecessor, since it is the first thing that must be done. Activities B and C each have activity A as the immediate predecessor. Activity D has B and C as immediate predecessors, because the final report cannot be writ- ten until the data are collected and the Internet is searched. The duration times for each activity are also shown in Table 13.4.
The above information can be put into a network representation. The activity-on-node (AON) network representation is shown in Figure 13.3.1 Here, each of the four activities is shown as a node (circle) in the diagram and the arrows indicate the precedence relation- ships between the activities. In each circle the duration of the activity is shown below its label. Activities B and C cannot start until activity A is completed, and activity D cannot start until both activities B and C are completed. The convention is that all preceding activities must be completed before a successor activity can start.
We use the business report example from Table 13.4 and Figure 13.3 to illustrate constant-time network scheduling. Once the network (precedence of relationships) has been defined, the scheduling calculations can be made. To calculate activity start and fin- ish times the following notation and definitions are needed:
ES(a) = early start time of activity A based on the early finish times of all immediate predecessors.
EF(a) = early finish time of activity A, which is constrained by its early start time. LS(a) = late start time of activity A, which is constrained by its late finish time. LF(a) = late finish time of activity A without delaying the late start time of all
immediate successors.
Each activity has four scheduled times, as defined above. For convenience we abbreviate them as ES, EF, LS, and LF. These times may be calculated by a forward pass and a back- ward pass through the network.
First, a forward pass is made to calculate the early start (ES) and early finish (EF) times directly from the network diagram. This is done by starting at the beginning of the network and proceeding through to the end of the network in precedence order. We illustrate this cal- culation by using the example from Figure 13.3. A convention is that we place the ES and EF times on top of the nodes, as shown in Figure 13.4. Starting at node A, we assign an ES time of zero since it is the first activity (ES = 0 on node A). The EF of activity A is the ES plus the activity duration (from Table 13.4), which is 0 + 1 = 1. The earliest any activity can pos- sibly finish is just the time it takes to conduct the activity (its duration) added to its ES time.
1 There is also an activity-on-arrow convention for drawing networks. We use the AON convention here because it is easier to understand and is the basis for most scheduling software (e.g., Microsoft Project).
FIGURE 13.3 Network for writing a business report.
A 1—
B 2—
C 3—
D 5—
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The ES of activities B and C, the successors of activity A, is the EF of activity A because B and C cannot start until A is finished. It follows that the EF of activity B is its ES time (1) plus the activity duration of B, which is 2 days, or EF(B) = 3. Likewise, the EF(C) is its ES time (1) plus the activity duration of C, which is 3 days, EF(C) = 4.
Now we can schedule the ES of activity D, which cannot begin until both activities B and C are completed. Therefore, the earliest start time of activity D is determined by the maximum of the EF of both B and C. In this case, ES(D) = Max (3, 4) = 4. The meaning of precedence is that both the preceding activities have to be finished before activity D can start, therefore taking the maximum of EF times of these predecessor will yield the earliest time that D can start. The earliest finish of activity D is its ES plus the activity D duration time [EF(D) = 4 + 5 = 9]. We have now completed the forward pass for this network. The project completion time is 9 days, which is the EF of the last activity.
The logic we have been using in these calculations can be expressed by the following formulas:
ES(a) = 0 for starting activities EF(a) = ES(a) + t(a), where t(a) denotes the duration of activity a ES(a) = Max [EF (all predecessors of a)] Project completion time = Max [EF (all ending activities)]
To summarize, the reason we take the maximum EF of all predecessors to each activity for its early start time is that an activity cannot start until all its predecessors are finished. Even one predecessor that is not finished can hold up the early start of the next activity, which leads to the maximum EF of all predecessors. Once the ES of an activity has been determined the early finish (EF) of that activity is just its ES + the activity duration time, t(a). So the activity cannot finish until its duration has passed from the early start time.
A backward pass is needed to calculate the late start (LS) and late finish (LF) times. This is done to determine the latest that activities can be started and completed, without affecting other activities. The backward pass is based on the following calculations:
LF(a) = Min [LS (all successors of a)] LS(a) = LF(a) − t(a)
These late times are computed starting with the last activity in the network and proceed- ing backward through the entire network. As shown, LS and LF are positioned below the node. The LF time for activity D in Figure 13.5 is the same as the EF since this is the last
FIGURE 13.4 Forward pass for writing a business report. 0 1
1 3
1 4
4 9
ES EF
A 1—
B 2—
C 3—
D 5—
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276 Part Four Capacity and Scheduling
activity, which is 9. Also, the LS for activity D is the same as the ES, which is 4. The LF for activities B and C is equal to the LS of activity D since it is the only successor. The LS for activities B and C is obtained by subtracting their activity duration times from their LF. For activity A there are two successors, B and C, so the LF for activity A should be the minimum of the LS for the successors, Min (1, 2) = 1. The reason we use the minimum is that activity A must finish in time for both B and C to achieve their late start times or the project completion will be delayed. Since the late start of either activity B or C could delay the project completion, we take the minimum of their LS times to ensure the late finish of activity a is finished on time. The LS for activity A is its LF minus the activity time, 1 − 1 = 0.
On the backward pass, the same logic is applied as the forward pass except we have to consider now the minimum LS time of all successors. As we work backwards through the network, the LF of each preceding activity must be completed in time to not delay any of the LS of the successors. That leads to the formula LF(a) = Min [LS (all successors of a)]. Once the LF(a) has been determined, the LS(a) is just the LF(a) minus the duration time of activity (a).
As a check on your computations, determine whether the ES = LS and EF = LF for activity A, the first one in the network. After the backward pass, you should always end up with the same ES and EF times that you started with when going forward.2
We can now identify the critical path as the longest path in the network from start to finish. It consists of all activities where ES = LS and EF = LF. In this case the critical path of activities is A–C–D. For these activities the earliest they can start is also the latest they can start. There is no slack in the activities on the critical path. The critical path constrains the completion time of the project since it is the longest path of activity times from the start to the end of the project. In the example in Figure 13.5 there are only two paths through the network: A–B–D and A–C–D. The length of these paths is 8 and 9, respectively. These lengths are obtained by adding the times of activities along each path. It is apparent from these calculations that path A–C–D is the longer of the two and is therefore the critical path. Notice that the length of the critical path is the project completion time we have just computed.
In large examples it is not possible to enumerate all paths, as we have just done to find the longest path, because there are simply too many. Therefore, the forward and backward
2This assumes that the project starts with a single activity.
LO13.5 Explain the significance of the critical path and slack.
FIGURE 13.5 Forward and backward pass for writing a business report. 0 1
0 1
1 3
2 4
1 4
1 4
4 9
4 9
ES EF
LS LF
A 1—
B 2—
C 3—
D 5—
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passes are used to find the critical path by noting those activities where ES = LS or equiva- lently EF = LF. In other words, the critical activities comprise the longest chain because the earliest they can start is also the latest they can start and the earliest they can finish is also the latest they can finish.
Slack is defined as the mathematical difference between LS and ES, or equivalently LF–EF. In Figure 13.5 there is only one activity with slack—activity B with one unit of slack. This means the duration of activity B can slip by one day and still not affect the proj- ect completion date. In this case it is easy to see that once activity B has slipped by one day, it also is on a critical path and the project has two critical paths at that point.
In managing a project, all activities on the critical path must be carefully monitored. If any of the critical activities slips (takes more time than planned), the completion date of the project will slip by a like amount. In a typical project, with a few hundred activities, only 5 to 10 percent of all activities are on the critical path. Therefore, the focus of monitoring on critical activities provides a significant reduction in managerial effort. This is basically management by exception, paying more attention to those activities that are going to affect the completion date of the project. For activities not on the critical path, they can slip by the amount of slack in the activity before affecting the final project completion date.
It is now apparent that network calculations have several advantages over the Gantt chart. Networks allow precise determination of the critical path and slack, and they allow the rapid evaluation of proposed schedule changes.
We take the example of opening a new office used in the Gantt chart (Figure 13.2) and schedule it using a network representation. First, we need to specify the precedence rela- tionships and the activity times. These are shown in Table 13.5. It’s logical that we can’t install the furnishings before we arrange for them, and we can’t install the phones before we make the phone arrangements. Assuming we are using hard-wired phones, we have also specified that the furnishings be installed before the phones are installed in order to know where to place the phone jacks, and of course, everything must be completed before we can move into the office. These precedence relationships are shown in the network in Figure 13.6.
A forward and backward pass was made on Figure 13.6 to determine the ES, EF, LS, and LF for each activity. When making the forward pass, activity 6 cannot start until activi- ties 5 and 4 both are finished. Activity 7 cannot start until activities 2, 6, and 4 are finished; therefore, ES(7) = Max[EF(2), EF(6) and EF(4)] = Max[6,5,4] = 6. When making the backward pass, we start with the LF of activity 7 and work backward. Take a close look at the LF for activity 4. It is the Min[LS(6), LS(7)] = Min (5,6) = 5. The remaining backward calculations are straightforward. As a check on our math, we note for activity 1 that ES = LS and EF = LF.
Example
TABLE 13.5 Precedence and Times for Opening a New Office
Activity Description Immediate
Predecessors Activity
Time Computed
Slack
1 Lease the site None 1 0 2 Hire the workers 1 5 0 3 Arrange for the furnishings 1 1 1 4 Install the furnishings 3 2 1 5 Arrange for the phones 1 1 3 6 Install the phones 4,5 1 1 7 Move into the office 2,6,4 2 0
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278 Part Four Capacity and Scheduling
The critical path consists of those activities where ES = LS and EF = LF, that is, path 1–2–7. To check our logic, there are four paths in this network with the following lengths obtained by adding the times along each path.
Activities Total time
1–2–7 8 1–5–6–7 5 1–3–4–6–7 7 1–3–4–7 6
As we can see, path 1–2–7 is the longest path through the network and thus the critical path. Those activities not on the critical path have some slack, as shown in Table 13.5. These figures are obtained by simply subtracting LS – ES or LF – EF for each activity. Slack is the amount of time an activity can slip before affecting the project completion date.
It is possible to put the results from the critical path calculations into a Gantt chart format. In this case we start each activity at its early start time and follow it with a dashed line to show the slack in each activity. This provides a useful display of the critical path along with the slack; see Figure 13.7. Next, we expand on the constant-time network to consider CPM.
FIGURE 13.6 Network for opening a new office.
0 1
0 1
6 8
6 85 6
2 4
4 5
3 5
1 6
1 6
1 2
2 3
1 2
4 5
ES EF
LS LF
2 5—
5 1—
6 1—
7 2—
3 1—
4 2—
1 1—
FIGURE 13.7 Gantt chart project example.
No. Activity Description 1 2 3 4 5 6 7 8 Week
Slack
Lease the site
Hire the workers
Arrange for the furnishings
Install the furnishings
Arrange for the phones
Install the phones
Move into the office
1
2
3
4
5
6
7
Critical path
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13.5 CPM METHOD
The critical path method (CPM) was developed by E.I. du Pont de Nemours & Co. as a way to schedule the start-up and shutdown of major plants. Since these plant activities were repeated frequently, the times were fairly well known. However, the time of any activ- ity could be compressed by expending more money. Thus, CPM uses a time–cost trade-off rather than a constant time.
The CPM method of project scheduling uses a time–cost function of the type shown in Figure 13.8 for each activity. The activity can be completed in proportionally less time if more money is spent. To express this assumed linear time–cost relationship, four figures are given for each activity: normal time, normal cost, crash time, and crash cost.
The following definitions are provided.
Normal time: the planned activity duration. Normal cost: the budgeted cost for the normal time. Crash time: the minimum activity duration for additional cost. Crash cost: the cost needed to achieve the crash time.
The project network is solved initially by using normal times and normal costs for all activities. If the resulting project completion time and cost are satisfactory, all activities will be scheduled at their normal times. If the project completion time is too long, the project can be completed in less time at greater cost by crashing (using less time) for certain activities.
For any given project completion time that is less than the normal time, a great number of network possibilities exist, each at a different total cost. This occurs because a variety of different activity times can be decreased to meet any specified project completion time. All these possibilities can be evaluated by means of a linear programming (LP) problem. The LP problem is used to find the solution representing the minimum total project cost for any given project completion time.
To illustrate the principles involved, an example is given below. The example shows how to calculate normal times and normal costs and how to determine the best way to reduce project completion by one day. Although this simple example is easily evaluated,
LO13.6 Calculate the cost of crashing a network by one or two days.
FIGURE 13.8 Time–cost relationship in CPM.
C ra
sh co
st N
or m
al co
st
C os
t
Normal time
Crash time
Time
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280 Part Four Capacity and Scheduling
it will, as the network becomes more complex, be necessary to use linear programming to evaluate all combinations.
Note from this example that the project completion time can be decreased one unit at a time by incurring more cost. This can be continued until all activities on the critical path are “crashed” to their minimum times or until other paths become critical. Remaining activities can have some slack in them. Management can determine how much it will cost to obtain any given project completion time between the normal time and the minimum full-crash time by simply decreasing project completion time one unit at a time until full crash times are reached.
A project network—along with activity times and costs—is given below. Calculate the normal project time and normal cost. Also, calculate the least-cost way to reduce the normal proj- ect completion time by one day.
Start End
A 3—
B 2—
C 6—
D 4—
E 3—
Note that when there is more than one beginning node (in this case A, B, and C), a start node is added to the network. Also, when there is more than one ending node (in this case D, C, and E), an end node is added to the network.
Activity Normal
Time Normal
Cost Crash Time
Crash Cost
A 3 40 1 80 B 2 50 1 120 C 6 100 4 140 D 4 80 2 130 E 3 60 1 140
The normal project completion time is computed by setting all activities at their normal times and making a forward pass. The resulting normal project completion time = 7. See the ES, EF time calculations below.
Solution
Example
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Start End
0 0 0 6
0 3
0 2 52
7 7
3 7
A 3—
B 2—
C 6—
D 4—
E 3—
The normal project cost is the sum of normal costs for all activities, which equals $330. Crashing one or more activities on the critical path can reduce the project completion
time by one day. Therefore, we calculate the activity cost per day for each activity on the critical path that can be crashed by at least one day and then choose the least cost per day of those activities. The following formula is used:
Activity cost/day = Crash $ − Normal $
______________________ Normal days − Crash days
The project completion time can be reduced from seven to six days by crashing either activity A or activity D, the only two on the critical path, by one day. It costs $20 per day = (80 − 40)/ (3 − 1) to crash activity A and $25 per day = (130 − 80)/(4 − 2) to crash activity D by one day. Therefore, it is less costly to crash activity A by one day in order to achieve an overall project completion time of six days at a cost of $350. This process can be continued, crash- ing the least-cost activity on the critical path (which may itself change) one day at a time until the minimum project completion time is reached.
13.6 USE OF PROJECT MANAGEMENT CONCEPTS
Project management requires a great deal more than scheduling. Planning for the project is required before the scheduling begins, and control is required after the schedule is developed. Project management requires a blend of behavioral and analytic skills, often involving the use of cross-functional teams. Thus, scheduling methods should be seen as only one part of a complete approach to project management. See an example of project complexity in the Operations Leader box for a major infrastructure project in California.
In selecting project scheduling methods, we should make a conscious trade-off between sophisticated methods and cost. Gantt chart methods should not be seen as outdated or naive. Rather, Gantt charts are justified for projects in which the activities are not highly intercon- nected or for small projects. In these cases when the Gantt chart is warranted, a network method may not provide enough additional benefits in relation to its costs. When using sched- uling software, a Gantt chart will normally be provided in the output similar to Figure 13.7.
If a network method is justified, a choice must be made between constant-time, CPM, or more advanced methods. The constant-time method is adequate for cases when activity
LO13.7 Contrast and compare the use of constant-time and CPM networks.
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282 Part Four Capacity and Scheduling
times are constant or nearly so. CPM methods, by contrast, should be used when activity times are fairly constant but can be reduced by spending more money. CPM might apply in cases such as construction projects, installation of equipment, and plant start-up and shutdown. More advanced network methods include PERT (probabilist times), generalized networks, resource-constrained networks, and project management based on the theory of constraints. These methods are beyond the scope of this textbook.
Computerized network scheduling methods are used in practice. A large number of different standard software packages are available to cover the entire range of scheduling methods. These packages also assist in project accounting and in controlling progress.
Chevron Corporation, a multinational energy firm, manages much of its work as proj- ects. For its major construction projects, from Kazakhstan to Australia, the use of sophis- ticated project management scheduling systems is crucial. In contrast, personal wedding planners also use some of the tools discussed in this chapter, so that everything is ready for the big day! Keeping activities on time and on budget is important in all industries, and there is tremendous demand for professional project management skills.
13.7 KEY POINTS AND TERMS
This chapter is concerned with the planning and scheduling of projects. The major points include the following:
∙ A project is a production activity geared toward the creation of a unique product, ser- vice, or result.
needs for the San Diego region. With a paltry 3.3 inches of rain at the city’s official weather station in 2018, this investment in water supply helps to sustain the region’s 3.3 million people.
Source: https://www.carlsbaddesal.com, 2020.
The Claude “Bud” Lewis Carlsbad Desalination Plant opened ahead of schedule in 2015 to provide a fresh water supply to the San Diego County Water Authority. Referred to as the nation’s largest, most advanced and energy-efficient seawater desalination plant, the project cost about $1 billion for the plant, pipelines, and upgrades to existing facilities. Ongoing California droughts created urgency for completing the project ahead of its original 2016 planned completion.
Named for the former mayor of Carlsbad, California, the total project time line was 17 years, including plan- ning, permitting, construction, and six months of final testing. The project involved construction and exper- tise from numerous global engineering firms. A variety of project management tools were necessary to man- age the long and detailed schedule. In total, 1.5 million hours of work were involved, and the project employed 2500 workers.
This complex project resulted in a plant that uses reverse osmosis to produce 50 million gallons of fresh water output per day, about 7 percent of the water
Carlsbad Desalination Plant
OPERATIONS LEADER
Reed Kaestner/Getty Images
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∙ The three objectives in projects are time, cost, and performance. Because these objectives are conflicting, trade-offs among them must be made in the course of managing projects.
∙ All projects go through four phases: planning, scheduling, control, and closing. The planning phase establishes the objectives, organization, and resources for the project. The scheduling phase establishes the time schedule, cost, and personnel assignments. The control phase monitors the progress of the project in cost, time, and performance; it also corrects the plan and schedule as necessary to achieve project objectives. The clos- ing phase shuts down the project and turns it over to the owners.
∙ Project management is a profession that includes a body of knowledge and certification as a project manager.
∙ The Gantt chart is a scheduling method for displaying project activities in a bar-chart form. The Gantt chart is useful for small projects or projects in which activities are not highly interrelated.
∙ Two network scheduling methods are covered in this book: constant-time and CPM. Both methods rely on a network or graph to represent the precedence relationship between activities.
∙ A network allows us to identify the critical path, slack, and activities that need to be rescheduled. The critical path is the longest time path of activities from the beginning to the end of the network. Activities on the critical path have zero slack—they must be com- pleted on time to prevent slippage of the project completion date. Slack is the amount of time an activity can be extended while still allowing the project to be completed on time.
∙ The early start, late start, early finish, and late finish times for each activity can be com- puted by means of a forward pass and a backward pass through the network.
∙ CPM is a network-based method that uses a linear time–cost trade-off. Each activity can be completed in less than its normal time by crashing the activity for a given cost. Thus, if the normal project completion time is not satisfactory, certain activities can be crashed to complete the project in less time at greater cost.
Key Terms Project 268 Project objectives 268 Project planning 269 Project scheduling 269 Work breakdown
structure 269
Late start 275 Late finish 275 Critical path 276 Slack 277 Critical path method
(CPM) 279
Project control 270 Project closing 271 Constant-time networks 273 Activity-on-node 274 Early start 274 Early finish 274
LEARNING ENRICHMENT (for self-study or instructor assignments)
Gantt Chart Excel Tutorial Video https://youtu.be/xsxi4qaEnOg 2:35
30 Global Megaprojects Website https://www.popularmechanics.com/technology/g2121/the-worlds-
25-most-impressive-megaprojects/
Review of Forward and Backward Pass Video https://youtu.be/4oDLMs11Exs 7:25
Project Crashing in Microsoft Project Video https://youtu.be/TCNSYur2o00 6:03
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284 Part Four Capacity and Scheduling
SOLVED PROBLEMS
Problem 1. Constant-Time Network A list of activities, precedence relations, and activity times for a project is given below:
Activity Name Predecessor Activities
A — 5 B A 4 C B 2 D A, C 6 E D 8 F E 5 G C 4 H D, E, G, I 13 I C 2 J G, H 1 K F, H, J 6
a. Draw an activity-on-node network diagram. b. Compute the early start (ES), late start (LS), early finish (EF), and late finish (LF)
times for each activity in the network. c. What is the critical path? What is the expected completion time for the project?
a.
A 5—
B 4—
C 2—
D 6— E
8—
F 5—
G 4—
I 2—
J 1 —
K 6—
H 13—
b. Activity
Name ES LS EF LF Slack
A 0 0 5 5 0 B 5 5 9 9 0 C 9 9 11 11 0 D 11 11 17 17 0 E 17 17 25 25 0 F 25 34 30 39 9 G 11 21 15 25 10 H 25 25 38 38 0 I 11 23 13 25 12 J 38 38 39 39 0 K 39 39 45 45 0
Solution
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Chapter 13 Project Planning and Scheduling 285
c. The critical path is the activities that have no slack:
A–B–C–D–E–H–J–K
2. Constant-Time Network The times are shown below for each activity.
B 4—
F 6—
D 9—
E 7—
C 6—
A 3—
a. What is the critical path for the project? b. What is the expected completion time of the project? c. What is the slack in each activity?
The forward and backward passes are shown on the figure below with early start, early finish, late start, and late finish times.
3, 7
14, 18
ES EF
LS LF
0, 3
0, 3
9, 18
9, 18
18, 24
18, 24
3, 9
3, 9
9, 16
11, 18
D 9—
A 3—
C 6—
E 7—
F 6—
B 4—
Problem
Solution
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286 Part Four Capacity and Scheduling
a. The critical path is A–C–D–F. This is the longest path in the network and ES = LS, EF = LF for all activities on the critical path.
b. Expected completion time is 24, which is the LF of the last activity. c. Activity B has a slack of 11 and E has a slack of 2. For all other activities slack is
zero.
3. CPM Network The following information is given for a CPM network.
Activity Predecessor Successor Normal
Time Normal
Cost Crash Time
Crash Cost
A — B, C 4 $50 2 $100 B A D, C 3 60 2 80 C A, B D 5 70 3 140 D B, C — 2 30 1 60
a. Draw the network showing the normal times. b. Make a forward and backward pass to calculate ES, LS, EF, LF for each activity. c. What are the normal project completion time and the normal cost? d. What should be done to crash the network by one day? By two days?
Problem
a. Solution B 3—
D 2—
C 5—
A 4—
b. Activity ES EF LS LF A 0 4 0 4 B 4 7 6 9 C 4 9 4 9 D 9 11 9 11
c. Normal project completion time = 11, normal cost = $210. d. To crash by one day, any of the activities on the critical path (A, C, or D) can be
crashed. The cost of crashing per day is (A = $25, C = $35, D = $30). The low- est cost of crashing one day is therefore activity A. In this case project cost is $210 + $25 = $235 for 10-day project completion.
To crash 2 days, also consider the critical path, since no other path is longer than 10 days. Activity A can be crashed for another day, and so the next lowest cost is to crash activity A by one more day. The total cost for 9-day project completion is $210 + $25 + $25 = $260.
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Chapter 13 Project Planning and Scheduling 287
Discussion Questions 1. How does project scheduling differ from the scheduling
of ongoing operations? 2. How would you, after the fact, audit a project to deter-
mine whether it was successful? 3. Give three examples of projects not given in the text. Are
these projects unique, or are they repeated in some way? 4. Contrast and compare CPM and constant-time network
as project-scheduling techniques. 5. Define the term critical path. 6. What is the management significance of the critical
path through a network?
7. How is the Gantt chart used as a scheduling tool? When should the Gantt chart be used in preference to network- based methods?
8. What is meant by the need to make trade-offs between cost, performance, and schedule? Give examples.
9. Why are a forward pass and a backward pass needed to produce a project schedule?
10. What is the definition of the early and late start times of an activity and the early and late finish times of an activity?
Problems 1. A public accounting firm requires the following activi-
ties for an audit:
Immediate Activity Activity Predecessor Time
A — 3 B A 2 C — 5 D B, C 2 E A 4 F B, C 6 G E, D 5
a. Draw a network for this project. b. Make a forward pass and a backward pass to deter-
mine ES, LS, EF, and LF. c. What are the critical path and the project completion
time? d. If the project completion must be reduced by two
days, which activities might be affected? 2. The following activities are required in starting up a
new plant:
Immediate Activity Activity Predecessor Time
A — 3 B — 2 C A 2 D B 5 E B 4 F C, D 2 G E, C, D 3
a. Draw a network for this project. b. Make a forward and backward pass to determine
ES, LS, EF, and LF. c. Calculate slack. d. Prepare a Gantt chart for this project. 3. A construction project has the following network and
activity times: a. Make a forward pass and a backward pass on the
activity times. b. Find the slack for each activity. c. Prepare a Gantt chart for this project. d. Activity D will be delayed by one day. What effect
will this have on the project?
Start End
A 2—
B 5—
D 3—
E 1—
F 2—
H 5—
C 3—
G 3—
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288 Part Four Capacity and Scheduling
4. A clinic start-up is based on the following network:
Immediate Activity Activity Predecessor Time
A — 4 B — 8 C — 3 D A 3 E A 6 F C 5 G B, D 6
a. Draw a network for this project. b. What is the project completion time? c. Identify the critical path. 5. An entrepreneur is starting a new business. The activi-
ties and times required are given below:
Start End
A 2—
B 4—
D 5—
E 3—
F 5—
C 4—
G 3—
a. Find the critical path and the project completion time. b. What are the ES, LS, EF, and LF for each activity? c. How much slack is there in activity D? 6. In preparing to teach a new course, the professor has
estimated the following activity times.
Start End
3
A 3—
B 2—
D 3—
E 6—
F 4—
C 4—
G 4—
a. Find the completion time of the project. b. What is the critical path? 7. Construction of a building is based on the following
CPM network:
Normal Normal Crash Crash Activity Predecessor Successor Time Cost Time Cost
A — B, C, D 6 $100 2 $150
B A E 8 80 2 140
C B, A F 2 40 1 60
D A F, G 3 80 2 120
E B G 5 80 3 140
F C, D G 5 60 1 100
G E, F, D — 6 120 2 160
a. Draw the network for this project and label the activities.
b. What are the normal project completion time and normal cost?
c. Identify the critical path. d. How much will it cost to crash the project comple-
tion by one day? by two days? e. What is the minimum time for project completion? 8. The professor from problem 6 is considering reducing
the time for completion of the project. He can hire a teaching assistant (TA) to help with the new course, but this will cost additional money. The TA can help reduce the times only for activities A, D, and C. In each case the TA can reduce the time required by one day for $150 and two days for $300.
a. Which activity should the TA perform to reduce the project completion time by one day?
b. Can the network be crashed by two days in total? Explain why or why not.
9. A software development project is based on the following:
Activity Predecessor Successor Normal
Time Normal
Cost Crash Time
Crash Cost
A — C 8 $200 7 $300 B — D 10 300 6 400 C A E 2 800 1 1000 D B E 4 200 2 300 E C, D — 15 500 11 800
a. Draw the network for this software development project.
b. What are the normal project completion time and normal cost?
c. What is the critical path? d. Teams of software engineers working on activities
A and B agree to combine their efforts and to label their new activity as “F.” They believe that, by work- ing together, they can complete their combined work in nine periods. Draw the new network.
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Chapter 13 Project Planning and Scheduling 289
e. What is the new project completion time and the new critical path?
10. Using the original information in problem 9, the proj- ect manager determines it is necessary to shorten the completion time for the project.
a. If she decides to crash the project by one day, what activity should be crashed?
b. What is the total project cost after crashing by one day?
c. If she decides to crash by two days, what activity should be crashed next?
d. What is the total project cost after crashing by two days?
11. The project manager for making an action movie involving a very highly paid star is very concerned about managing the project well. The following infor- mation is provided.
Activity Predecessor Successor Normal
Time Normal
Cost Crash Time
Crash Cost
A — 4 $2000 Not available
—
B A 2 3000 1 $7000 C B 3 1000 1 2000 D B 4 2000 2 3000 E C, D 5 2000 4 6000 F E 3 1000 Not
available —
G E 2 4000 1 5000 H F, G 3 2000 2 4000 I H 4 1000 2 4000 J I — 3 1000 2 3000
a. Complete the successor column. b. What are the normal project completion time and
normal cost? c. What is the critical path? 12. Using the project information provided in problem 11,
answer the following: a. To shorten the project by one day, what activity
should be crashed? b. What is the total project cost after crashing by one
day?
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14. Independent Demand Inventory
15. Materials Requirements Planning and ERP
Part Five addresses decisions and tools for managing inventory in organizations. The discussion is organized so that inventory with independent demand is handled in Chapter 14. Independent demand refers to the market forces that drive demand for these items (e.g., finished goods and spare parts). Chapter 15 covers inventory with dependent demand, which is derived from the demand for another item or component (e.g., demand for car engines is dependent on demand for complete cars). MRP and ERP systems are used to manage dependent demand inventories. ■
Inventory
Pa rt V
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Independent Demand Inventory
14 c h a p t e r
LO14.1 Define inventory types and the purpose of inventory.
LO14.2 Explain the costs incurred by inventory.
LO14.3 Differentiate between independent and dependent demand.
LO14.4 Calculate the economic order quantity and identify the underlying assumptions.
LO14.5 Compute the parameters for a continuous review and periodic review inventory control system.
LO14.6 Explain how continuous and periodic review systems are used in practice.
LO14.7 Describe how inventory and service level are related.
LO14.8 Define vendor managed inventory (VMI) and the ABC system.
LO14.9 Solve advanced inventory problems.
After reading this chapter, you should be able to:LEARNING OBJECTIVES
Inventory may be the most visible sign of supply chain management for end consumers. A case in point is that college students expect their favorite foods to be available when they are picking up groceries. Few things disappoint consumers more than advertised products that are out of stock when a customer shops in a retail store or online. If the supply chain works well, goods are available when and where people need them.
Inventory management is among the most important operations management responsi- bilities because inventory requires a great deal of capital and affects the delivery of goods
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to customers. Inventory management affects all business functions, including operations; marketing, which needs inventory for sales; accounting and information systems, which track inventory; and finance, which provides necessary funds. Decisions related to manag- ing inventory can be improved significantly through the use of the basic tools presented in this chapter.
Many technologies are used to help manage inventory. Bar coding, for example, is ubiquitous in most organizations (components are scanned in the production process; nurses scan drugs before administering them to patients) and has reduced hand counting and recording of inventory data significantly. Bar coding enables the use of point of sale data, which are collected as items are scanned and sold, by firms and their supply chains. Radio-frequency identification (RFID) is a technology for tracking the movement of goods. The ability to locate inventory is valuable for both accounting and loss prevention. Technologies such as these help to track and manage inventories in complex global supply chains. See the Learning Enrichment feature at the end of the chapter for a video on how Walmart uses robots to monitor store inventory.
14.1 DEFINITION OF INVENTORY
Inventory is a stock of materials used to facilitate production or satisfy customer demands. Typical inventories include raw materials, work in process, and finished goods. In Figure 14.1, an operation is shown as a materials-flow process with raw materials inventories waiting to enter the production process, work-in-process inventories in an intermediate stage of transformation, and finished goods inventories that have been transformed completely by the production process.
Inventory stocks are located at various points in the production process, with flows of materials connecting one stock point to another. The rate at which stock is replenished is the supply, and the rate of stock depletion is demand. Inventory acts as a buffer between the supply rate and the demand rate.
The water tank shown in Figure 14.2 is a good analogy for these concepts of flows and stocks. In this figure, the level of water in the tank corresponds to inventory. The rate of flow into the tank is analogous to the supply rate, and the rate of flow out of the tank cor- responds to the demand rate. The water level (inventory) is the buffer between supply and demand. If the demand rate exceeds the supply rate, the water level drops until the supply
LO14.1 Define inventory types and the purpose of inventory.
FIGURE 14.1 A materials-flow process.
Raw materials
Work in process
Finished goods
Work in process
Work in process
Suppliers Customer
Productive Process
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294 Part Five Inventory
and demand rates come back into balance or until the water (inventory) is depleted. If the supply rate exceeds the demand rate, the water (inventory) level rises.
Imagine a series of these tanks connected to one another, all with varying rates of inputs and outputs. This situation, which is illustrated in Figure 14.3, is analogous to the chal- lenge of inventory management. Here, one tank represents raw materials, there are two tanks for work in process, and there is one tank for finished goods. The tanks serve as buf- fers to absorb variations in flow rates within this pseudo-production system.
Inventories in the supply chain serve the same purpose as inventories in the factory—to buffer the difference in flows between supply and demand. However, in a supply chain, typically, one firm does not control all inventories; rather, inventory must be coordinated across the supply chain partners. Many of the concepts covered in this chapter apply to the broader context of the supply chain, in which coordination between parties with different interests and objectives must also be considered.
Inventory is often described as a “necessary evil” and a form of waste. This perspec- tive has led many firms to strive relentlessly to reduce their inventory levels of items that they manage, often without careful consideration of items themselves (e.g., uncertainty, stockouts, etc.).
Two points deserve emphasis. First, reducing excessive inventory is a laudable goal; eliminating inventory completely is not wise. Inventory is needed as a buffer to prevent stockouts whenever the demand rate is not equal to the supply rate. Second, within a sup- ply chain there will be demand and supply variation seen by each member of the supply chain. One member of the supply chain cannot reduce inventory without effecting the other members, possibly to carry more inventory. Thus, inventory changes will be felt across the supply chain.
FIGURE 14.2 A water tank analogy for inventory.
Supply rate
Demand rate
Inventory level
FIGURE 14.3 Water tanks as pseudo-production system.
Raw materialsSupplier
supply rate
Customer demand rate
Raw- material
usage rate First
work-in- process
stage
First-stage output rate
Second- stage
output rate Finished goods
Low- quality
materials
Scrap Scrap Scrap
Second work-in- process
stage
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14.2 PURPOSE OF INVENTORIES
The primary purpose of inventories is to uncouple the various phases of operations and the supply chain. Raw materials inventory uncouples a manufacturer from its suppliers, mean- ing that the supplier can produce parts at a convenient time within its own schedule and the manufacturer can later use those materials at the appropriate time for its transformation process. Similarly, work-in-process inventory uncouples the various stages of manufactur- ing, and finished goods inventory uncouples a manufacturer from its customers.
There are four primary reasons for firms to carry inventory:
1. To protect against uncertainties. In inventory systems, there are uncertainties in sup- ply, demand, and lead time. Safety stock is inventory that is maintained to protect against these uncertainties. If customer demand is known, it is feasible—although not necessarily economical—to produce at the same rate as consumption. In this case, no finished goods inventory would be needed; however, every change in demand would cause the production system also to change, resulting in a very uneven workload. Instead of such tight coupling, safety stocks of finished goods are maintained to absorb changes in demand so that production can maintain a separate, more even pace. In a similar way, safety stocks of raw materials are maintained to absorb uncertainties in delivery by suppliers in terms of both the quantity and the timing of delivery. Safety stocks of work-in-process inventories are maintained to allow for unexpected breakdowns, unreliable workers, and schedule changes. Most safety stocks can be reduced by improving coordination with suppliers and customers in the supply chain. 2. To allow economic production and purchase. It is often economical to produce inventory in lots (batches) as it allows production at one point in time, and then no further production of the same item is done until the lot is nearly depleted. This makes it possible to spread the setup cost of production over a large number of items. Producing or ordering in lots also permits the use of the same production equipment for different products. A similar benefit holds for the purchase of raw materials. Owing to ordering costs, quantity discounts, and transportation costs, it is sometimes economical to purchase in large lots even though part of a lot is held in inventory for later use. The inventory resulting from the purchase or production of material in lots is called cycle inventory, since the lots are produced or pur- chased on a cyclic basis. Most firms are working to reduce setup times and costs by altering the product or process. This effort can result in smaller lot sizes and much lower inventories. 3. To cover anticipated changes in demand or supply. There are several situations in which changes in demand or supply are expected, causing firms to hold anticipation inventory. Expected changes in the price or availability of raw materials may cause stock- piling of raw materials; for example, firms often stockpile steel before an expected strike in the steel industry. Another source of anticipation is a planned market promotion in which a large amount of finished goods may be stocked before a sale. Firms in seasonal businesses often hold anticipation inventory in order to smooth employment. For example, a producer of air conditioners may use a level production strategy even though most air conditioners are sold during the summer. 4. To provide for transit. Inventories that are moving from one point to another in the supply chain are called pipeline inventory or transit inventory. These inventories are affected by production location decisions and by the choice of carrier. These inventories can be significant in size when ships rather than planes are used to transport goods across the world. Obviously, firms compare the cost and time factors in evaluating various trans- portation options. Time-sensitive goods may be more profitable when transported by using costly but rapid air freight because they reach the market so quickly.
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296 Part Five Inventory
Overall, it is easy to see that there are many good reasons for firms to hold inventories. Inventory helps firms satisfy customer demand while also allowing a firm and its supply chain partners to schedule production economically.
14.3 COSTS OF INVENTORY
Many inventory decisions can be made by using economic criteria. One of the most impor- tant prerequisites, however, is an understanding of the relevant costs. Inventory cost struc- tures incorporate the following four types of costs:
1. Item cost. This is the cost of buying or producing the individual inventory items. The item cost usually is expressed as a cost per unit multiplied by the quantity procured or produced. Item cost may be discounted if enough units are purchased at one time. 2. Ordering (or setup) cost. The ordering cost is incurred when ordering a lot (batch) of items and generally does not depend on the lot size ordered; it is assigned to the entire batch. This cost includes creating the purchase order, expediting the order, transportation costs, receiving costs, and so on. When the item is produced within the firm, there are also costs associated with placing an order that are independent of the number of items produced. This is called the setup cost, and it includes the costs to set up the production equipment for a run as well as record-keeping costs. In some cases, setup costs can be thousands of dollars, leading to significant economies for large batches. Setup cost often is considered fixed when, in fact, it can be reduced by changing the way operations are designed and managed. Reducing setup time is an important way to align the production rate with the demand rate, and thereby reduce inventory. 3. Carrying (or holding) cost. The carrying or holding cost is associated with keeping items in inventory for a period of time. Typically, the carrying cost is charged as a percent- age of dollar value per unit time. For example, a 15 percent annual holding cost means that it costs 15 cents to hold $1 of inventory for a year. In practice, holding costs often range from 15 to 30 percent per year. The carrying cost usually consists of three components:
∙ Cost of capital. When items are carried in inventory, the capital invested in them is not available for other purposes. This represents a cost of forgone opportunities for other investments, which is assigned to inventory as an opportunity cost.
∙ Cost of storage. This cost includes variable space cost, insurance, and taxes. ∙ Costs of obsolescence, deterioration, and loss. Obsolescence costs are assigned
to items that have a high risk of becoming obsolete, for example, fashion and tech- nology items that quickly lose their appeal in the market. Perishable products are charged with deterioration costs when they deteriorate over time, for example, food and blood. Many products have an expiration date printed on them and become obso- lete at that time. The costs of loss include pilferage and breakage costs associated with holding items in inventory.
4. Stockout cost. Stockout cost reflects the economic consequences of running out of stock. As a result, the current sale can be lost if the customer will not accept a backorder and/or a dissatisfied customer may be less likely to buy in the future.
In light of these costs, it should be apparent why firms do not want to hold more inven- tory than is necessary to serve their customers. Also, it is easy to see why inventory management is a cross-functional challenge. Marketing may be particularly interested in minimizing the stockout costs associated with lost sales. Accounting and finance may be
LO14.2 Explain the costs incurred by inventory.
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interested in minimizing the amount of inventory that has to be financed and held. Opera- tions may want a sufficient level of inventory to assure smooth scheduling and production control. Since these objectives may be at odds, it is important that the total cost minimiza- tion approach be taken of the four costs described above.
The minimum cost principle also applies when supply chain partners attempt to mini- mize the total cost across the entire supply chain. However, it may be difficult to achieve a minimum when lower costs to one party incur higher costs for another. Nevertheless, market forces, financial incentives, and negotiations among parties can be used to seek the minimum cost across the supply chain. The Operations Leader box explains how Target Corporation manages inventory in its complex supply chain.
14.4 INDEPENDENT VERSUS DEPENDENT DEMAND
A crucial distinction in inventory management is whether demand is independent or dependent. Independent demand is influenced by market conditions outside the firm; it is therefore independent of demand for any other inventory items. Finished goods inventories and spare parts for replacement usually have independent demand. Dependent demand items have demand that is related to another item and is not independently determined by the market. When final products are assembled from components, the demand for those components is dependent on the demand for the final product.
A toy wagon illustrates the difference between independent demand and dependent demand. Demand for wagons is independent because it is influenced by the market and must be forecast. Demand for wagon wheels is dependent because it has a direct mathemati- cal relationship to the demand for wagons; it takes four wheels to complete each wagon. Likewise, demand for wagon handles is dependent on the demand for finished wagons.
LO14.3 Differentiate between independent and dependent demand.
Target manages the flow of finished goods inven- tory from the factory to the end consumer in more than 1800 stores in all 50 states, and via online sales with ship-to-home or -store options. Its supply chain begins in thousands of factories around the world.
Target has more than 40 distribution centers. Some suppliers ship to distribution centers while others ship directly to stores. It is all about getting the right inventory to the right place at the right time.
In-store inventory management is technology driven. Point of sale (POS) data are used to derive a list of sold items every hour so that shelves can be restocked imme- diately. Orders are triggered by either stock levels or percentages of stock sold. Workers use hand-held tech- nology to provide customers with immediate information on inventory availability in other stores or online.
Source: www.target.com, 2020.
With inventory valued at more than $5 million in each retail store, Target Corporation stands out as one of the most advanced retailing firms in managing inventory in the United States.
Target Sets the Standard for Inventory Management
OPERATIONS LEADER
artzenter/Shutterstock
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298 Part Five Inventory
Independent and dependent demand items exhibit very different usage or demand pat- terns. Since independent demand is subject to market forces, it often exhibits both a fixed pattern and random influences stemming from customer preferences. In contrast, depen- dent demand exhibits a lumpy on-again, off-again pattern because production is scheduled in lots. A quantity of parts is required when a lot is made; then no parts are required until the next lot is produced. These demand patterns are shown in Figure 14.4.
Different demand patterns call for different approaches to inventory management. For independent demand, a replenishment philosophy is appropriate. As the stock is used, it is replenished so that products are always on hand for customers. Thus, as inventory begins to run out, an order is triggered for more material, either by ordering from a supplier or by producing more, and the inventory is replenished.
For dependent demand, a requirements philosophy is used. The amount of stock ordered is based on requirements for higher-level items. As dependent demand items or materials are used, additional inventory is not ordered. More items or materials are ordered only as required by the scheduled production for the higher-level or end items they are used to produce.
The nature of demand therefore leads to two different philosophies of inventory man- agement, and those philosophies generate different sets of methods and software. In this chapter, decisions related to independent demand items are covered, including the follow- ing types of inventories:
1. Finished goods inventories and spare parts in manufacturing firms. 2. Maintenance, repair, and operating supplies (MRO) inventories. 3. Retail and wholesale finished goods. 4. Service industry (e.g., hospitals and schools) inventory.
14.5 ECONOMIC ORDER QUANTITY
The economic order quantity (EOQ) and its variations are still widely used in industry for independent demand inventory management. The EOQ helps to determine a logical order size or batch size for a single inventory item. It does this by balancing cost trade-offs.
The EOQ model is based on the following assumptions:
1. The demand rate is constant, recurring, and known. For example, demand (or usage) is 100 units per day with no random variation, and demand is assumed to continue into the indefinite future.
2. The lead time is constant and known. The lead time, from order placement to order delivery, is therefore always a fixed number of days.
LO14.4 Calculate the economic order quantity and identify the underlying assumptions.
FIGURE 14.4 Demand patterns.
D em
an d
U sa
ge
D em
an d
U sa
ge
Time Time
Independent demand Finished goods Spare parts
Dependent demand Work in process Raw materials
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3. No stockouts are allowed. Since demand and lead time are constant, one can determine exactly when to order inventory to avoid stockouts.
4. Items or materials are ordered or produced in a lot or batch, and the lot is placed into inventory all at one time.
5. The unit item cost is constant, and no discounts are given for large purchases. The car- rying cost is linearly related to the average inventory level. The ordering or setup cost for each lot is fixed and is independent of the number of items in that lot.
6. The item is an independent item, without interactions with other inventory items.
Under these assumptions, the inventory level over time is as shown in Figure 14.5, where the dark line represents the amount of inventory on hand over time. Notice that the figure shows a perfect sawtooth pattern, because demand is assumed to be constant and items are ordered in fixed lot sizes.
In choosing the lot size, there is a trade-off between ordering frequency and inventory level. Small lots will lead to frequent reorders and a low average inventory level. If larger lots are ordered, the ordering frequency will decrease but more inventory will be carried. This trade-off between ordering frequency and inventory level can be represented by a mathematical equation using the following symbols:
D = demand rate, units per year S = cost per order placed or setup cost, dollars per order C = unit cost, dollars per unit i = carrying rate, percentage of dollar value per year Q = lot size, units TC = total of ordering cost plus carrying cost, dollars per year
The annual ordering cost is
Ordering cost per year = (cost per order) × (orders per year) = SD / Q
In the above equation, D is the total demand for a year, and the item is ordered Q units at a time; thus, D/Q orders are placed in a year. This is multiplied by S, the cost per order placed.
The annual carrying cost is:
Carrying cost per year
=
(annual carrying rate) × (unit cost)
× (average inventory) = iCQ / 2
In this equation, the average inventory is Q/2. A maximum of Q units is carried in inven- tory (when a new batch arrives); the minimum amount carried is zero units. Since the stock is depleted at a constant rate, the average inventory is Q/2. The carrying rate per year (i)
FIGURE 14.5 EOQ inventory levels.
O n
H an
d Time
Order interval
Lot size = Q– Average inventory level = Q/2
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300 Part Five Inventory
multiplied by the unit cost (C) gives the cost of holding one unit in inventory per year. This unit charge multiplied by the average inventory level gives the total annual carrying cost.
Given the annual ordering and carrying costs above, the total cost of an inventory item is
TC = SD / Q + iCQ / 2 (14.1)
Figure 14.6 is a plot of TC versus Q, showing the carrying and ordering costs along with the total, which is the sum of the other two lines. As Q increases, the annual ordering cost decreases because fewer orders are placed per year; at the same time, however, the annual carrying cost increases because more inventory is held. Ordering costs and carrying costs, therefore, offset one another; one decreases while the other increases. Because of this trade-off, the function TC has a minimum.
Finding the value of Q that minimizes TC is a classic problem in calculus. We take the derivative of TC, set it equal to zero, and then solve for the resulting value of Q:
TC′
=
− SD ___ Q 2
+ iC __ 2 = 0
SD ___ Q 2
=
iC __ 2
Q 2 =
2SD ____ iC
Q
=
√ ____
2SD ____ iC
(14.2)
Equation (14.2) is the economic order quantity (EOQ), which minimizes the cost of man- aging an item in inventory. Although we have minimized cost on an annual basis, any unit of time can be used provided that the demand rate and carrying rate are compatible. For example, if demand is expressed on a monthly basis, the carrying rate also must be expressed on a monthly basis.
Although the EOQ formula is based on rather restrictive assumptions, it is a useful approximation in practice. The formula provides a ballpark figure as long as the assump- tions are reasonably accurate. Furthermore, the total cost curve is rather flat in the region
FIGURE 14.6 Total cost curve.*
A nn
ua l C
os t (
$ / ye
ar , T
C ) Total Cost
(SD/Q + iCQ/2)
Carrying Cost (iCQ/2)
Ordering cost (SD/Q)
EOQ Q (units)
M in
im um
C os
t
*Notice that the item cost of procurement is the constant CD, which is independent of Q and therefore can be removed from further consideration. It will not affect the minimum of TC.
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of the minimum; thus, the order quantity can be adjusted somewhat based on circum- stances without greatly affecting total costs.
It is very important that inventory decisions be made by considering total cost. Regardless of the situation, if one can identify the relevant total cost equation, an eco- nomic lot size can be found. The idea of minimizing the total cost equation is basic to all lot-sizing formulas. For example, the supplement to this chapter shows the total cost equation and associated minimization procedure when price discounts are available for large orders.
Hewlett-Packard has extended the total cost concept to its entire supply chain. In producing personal computers (PCs), it identifies four relevant costs:
∙ Component devaluation costs. ∙ Price protection costs (lowest price guarantees given to retailers). ∙ Product return costs. ∙ Obsolescence costs (end-of-life write-off).
All these costs are associated with the declining value of a PC once it is placed in inventory due to the risk of not selling the product before a new model is introduced to the market. We referred to these costs pre- viously as the cost of obsolescence and deterioration that are included as part of holding cost. These costs often exceed the profit margin on a prod- uct and must be considered in establishing the EOQ amount.
To illustrate the use of the EOQ formula, suppose we are managing a carpet store and want to determine how many yards of a certain type of carpet to buy. The carpet has the follow- ing characteristics:
D
=
360 yards per year
S
=
$10 per order
i = 25 percent per year
C
=
$18 per yard
Thus:
Q = √ _________
2(10)(360)
_________ .25(18)
= √ _____
1600 = 40 yards
The manager should order 40 yards of carpet at a time. This will result in D/Q = 360/40 = 9 orders per year, or one order every 1.33 months.
The minimum cost of managing this inventory will be $180 per year, as follows:
TC = 10(360 / 40) + .25(18)(40 / 2) = 90 + 90 = 180
Notice that the minimum cost occurs when the annual ordering cost component equals the annual carrying cost component.
The total cost curve for inventory is very flat in the neighborhood of the minimum. For example, if 50 units of carpet are ordered instead of the EOQ of 40 units, a 25% increase, the change in total cost is small, about a 2.5 percent increase. Thus, while calculating the EOQ provides a good estimate for planning order size, the inventory manager can adjust the order quantity if necessary, with a limited effect on the total cost of maintaining an inventory item.
Example
Poorly managed inventory may result in the need to discount prices. TY Lim/Shutterstock
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302 Part Five Inventory
The EOQ is used frequently in manufacturing to calculate appropriate order sizes (from suppliers) and lot sizes (for production), and it also is used in many service industry supply chains. Restaurants use EOQ for estimating order sizes for food and other supplies, larger firms use EOQ to manage their office supply stocks, and pharmaceutical mail order firms use EOQ to estimate order sizes to replenish their warehouses. Below, we describe two inventory management systems that are based on the EOQ model.
14.6 CONTINUOUS REVIEW SYSTEM
In practice, one of the most serious limitations of the EOQ model is the assumption of con- stant demand. This assumption can be relaxed to design a practical system for managing inventory that allows for random demand. We build a system based on the EOQ that is suf- ficiently flexible to use in practice for independent demand items. All EOQ assumptions except constant demand and no stockouts remain in effect.
In managing inventory, decisions about when to reorder stock are based on the total of on-hand inventory plus inventory that is on order. On-order inventory is counted the same as on-hand inventory for reorder decisions because the on-order inventory is scheduled and expected to arrive. The total of on-hand inventory and on-order inventory is called the stock position. Be careful on this point! A common mistake in inventory calculations is failure to consider amounts already on order.
In a continuous review system (also known as a fixed order quantity system or the Q system), the stock position is monitored after each transaction, or continuously. When the stock position drops to a predetermined level, or reorder point, an order is placed for a fixed quantity. Since the order quantity is fixed, the time between orders varies in accordance with the random nature of demand. See the Operations Leader box on Cantaloupe Sys- tems, a provider of hardware and software to monitor vending machine inventory levels.
A formal definition of the decision rule embedded in the Q system is as follows:
Continually review the stock position (on hand plus on order). When the stock position drops to the reorder point R, the fixed quantity Q is ordered.
A graph of this system is shown in Figure 14.7. The stock position drops as inventory is used to fulfill irregular demand until it reaches the reorder point, R, when an order for Q units is placed. The order arrives later, after a lead time, L, and the cycle of usage, reorder, and order arrival is repeated.
The Q system is completely determined by two parameters, Q and R. In practice, these parameters are set by using certain simplifying assumptions. First, Q is set equal to the EOQ value from Equation (14.2). In more complex models, Q and R must be determined
LO14.5 Compute the parameters for a continuous review and periodic review inventory control system.
FIGURE 14.7 A continuous review system (or Q system).
St oc
k Po
sit io
n
R
Time
Q
Q
Q
LLL
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simultaneously. However, using the EOQ to estimate Q is a reasonable approximation pro- vided that demand is not highly uncertain.
The value of R is based on either the stockout cost or the stockout probability. Formula- tions that utilize the stockout cost become quite difficult to estimate, and so the stockout probability is commonly used to determine R.
To calculate R, management must determine a desired service level, which is the per- centage of customer demand satisfied from inventory. The service level also is called the fill rate. A 100 percent service level means that all customer demand is satisfied from inventory, but as we will see shortly, this is nearly impossible to achieve. The stockout percentage is equal to 100 minus the service level.
There are three ways to express service level:
1. Service level is the probability that all orders are filled from stock during the replenish- ment lead time of one reorder cycle.
2. Service level is the percentage of demand filled from stock during a particular period of time (e.g., one year).
3. Service level is the percentage of time the system has stock on hand.
Each of these definitions of service level leads to slightly different reorder points. Fur- thermore, one must determine whether to count customers, units, or orders when applying these definitions. In this text, for the sake of simplicity, only the first definition of service level will be used.
The reorder point is based on the notion of a probability distribution of demand during the lead time. As inventory is used (depleted), eventually the inventory manager places
Cantaloupe Systems builds and installs a device that sits inside a vending machine. This device, called a seed device, monitors all transactions on an ongoing basis and transmits the data wirelessly to servers hosted by Cantaloupe Systems.
The seed device acts essentially like a continuous review system for monitoring inventory of snacks and beverages sold through vending machines. When an item nearly sells out, the device notifies the owner of the vending machine. Cantaloupe Systems expects owners of vending machines with its seed devices to save an average of $35,000 annually per route. Think of a route as comprising a number of vending machine locations that a replenishment truck has to traverse. The seed devices from Cantaloupe Systems can, moreover, help to reduce fuel consumption by approximately 40 percent since replenishment trucks can avoid making unneces- sary stops and to be able to refill 80 percent more vend- ing machines per week.
Source: www.cantaloupesys.com, 2019.
Owners of vending machines make money when cus- tomers find what they want to buy. Keeping track of items that are in stock and replenishing items that have sold out are therefore activities crucial to making money from owning vending machines.
Are Your Vending Machines Full or Empty? Ask Cantaloupe Systems
OPERATIONS LEADER
McGraw-Hill Education
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304 Part Five Inventory
an order. But until the order arrives, the inventory system is exposed to the potential for a stockout. Therefore, the only risk of a stockout is during the replenishment lead time.
Figure 14.8 shows a typical probability distribution of independent demand during the lead time. We must know the statistical demand distribution during the lead time to esti- mate R (we use a reasonable assumption of a normal distribution here). The reorder point R in the figure can be set to any desired service level.
The reorder point is defined as follows:
R = m + s (14.3)
where R = reorder point m = mean (average) demand during the lead time s = safety stock (or buffer stock)
We can express safety stock as:
s = zσ
where z = safety factor σ = standard deviation of demand during the lead time = √
________ leadtime × ( σ single period )
Then we have:
R = m + zσ
Thus, the reorder point is set equal to the average demand during the lead time (m) plus a specified number (z) of standard deviations (σ) to protect against stockouts. By deciding z, the number of standard deviations, the firm is setting both the reorder point and the service level. A high value of z results in a high reorder point and a high service level.
The values in Table 14.1 are from the normal distribution. These service levels represent the probability that the demand during the lead time will be satisfied by using safety stock. That is the same as saying that demand during the lead time will fall within the specified number of standard deviations (z) from the mean. When a firm decides what the service level should be, the corresponding z from Table 14.1 is used to calculate the reorder point.
FIGURE 14.8 Probability distribution of demand during lead time.
Fr eq
ue nc
y
Demand during Lead Time
Service-level probability
Stockout probability
m R s
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TABLE 14.1 Normal Demand Percentages
z Service Level (%) Stockout (%)
0 50.0 50.0 .5 69.1 30.9
1.0 84.1 15.9 1.1 86.4 13.6 1.2 88.5 11.5 1.3 90.3 9.7 1.4 91.9 8.1 1.5 93.3 6.7 1.6 94.5 5.5 1.7 95.5 4.5 1.8 96.4 3.6 1.9 97.1 2.9 2.0 97.7 2.3 2.1 98.2 1.8 2.2 98.6 1.4 2.3 98.9 1.1 2.4 99.2 .8 2.5 99.4 .6 2.6 99.5 .5 2.7 99.6 .4 2.8 99.7 .3 2.9 99.8 .2 3.0 99.9 .1
An example will help cement these ideas. Suppose we are managing a warehouse that distrib- utes a particular breakfast food to retailers. The breakfast food has the following characteristics:
Average demand
=
200 cases per day
Lead time
=
4 days to receive the order form the supplier
Standard deviation of daily demand
=
150 cases
Desired service level = 95% S
=
$20 per order
i
=
20 % per year
C
=
$10 per case
Assume that a continuous review system is used and that the warehouse is open 5 days per week, 50 weeks per year, or 250 days per year. Then average annual demand = 250(200) = 50,000 cases per year.
The economic order quantity is calculated by using Equation (14.2):
Q = √ ____________
2(20)(50,000 )
____________ .2(10)
= √ _________
1,000,000 = 1000 cases
The average demand during the lead time is 200 cases per day for four days; therefore, m = 4(200) = 800 cases. The standard deviation of daily demand is 150 cases, but we need to calculate the standard deviation over the four-day lead time. This is done with a simple conversion:
σ = √ ________
leadtime × ( σ single period ) = √ __
4 × (150) = 300 units
The 95 percent level requires a safety factor of z = 1.65 (see Table 14.1). Thus, we can calculate the reorder point by using Equation (14.3):
R = m + zσ = 800 + 1.65(300) = 1295
Recall that in a Q system, there are just two things we need to know: when to order (R) and how much to order (Q). The Q system we have designed here includes placing an order for 1000 cases whenever the stock position drops to 1295 cases. On average, 50 orders
Example
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306 Part Five Inventory
will be placed per year, and there will be an average of five working days between orders. The actual time between orders will vary, however, with demand.
To complete this example, Table 14.2 simulates the operation of the Q system decision rule. A series of random demands were generated on the basis of an average of 200 cases per day and a standard deviation of 150 cases per day. It is assumed that 1100 units are on hand at the beginning of the simulation and none are on order. An order for 1000 cases is placed whenever the stock position reaches 1295 units, and so an order must be placed immediately on day 1. The stock position is reviewed each day as demands occur. The result is that orders are placed on days 1, 7, 10, and 15. The lowest inventory level is 285 units at the beginning of day 10. Check some of the numbers in Table 14.2 to see if you can verify them.
TABLE 14.2 Q-System Example*
Day Demand
Beginning Period on
Hand
Beginning Period on
Order
Beginning Period Stock
Position Amount Ordered
Amount Received
1 111 1100 — 1100 1000 2 217 989 1000 1989 3 334 772 1000 1772 4 124 438 1000 1438 5 0 1314 — 1314 — 1000 6 371 1314 — 1314 7 135 943 — 943 1000 8 208 808 1000 1808 9 315 600 1000 1600 10 0 285 1000 1285 1000 11 440 1285 1000 2285 — 1000 12 127 845 1000 1845 13 315 718 1000 1718 14 114 1403 — 1403 — 1000 15 241 1289 — 1289 1000 16 140 1048 1000 2048
*For this table, we have used Q = 1000 and R = 1295.
14.7 PERIODIC REVIEW SYSTEM
Instead of reviewing the stock position on a continuous basis, an inventory management system can be designed to review stock position periodically. Suppose a supplier makes deliveries only at periodic intervals, for example, every two weeks. In this case, the stock position is reviewed every two weeks and an order is placed if inventory is needed.
This inventory management system, like the Q system, is based on the EOQ model. In this section, we assume that the stock position is reviewed periodically (on a fixed schedule) and that the demand is random. All EOQ assumptions in Section 14.5 except constant demand and no stockouts remain in effect.
In a periodic review system (also known as the fixed order period system, or the P system), the stock position is reviewed at fixed intervals. When the review is performed, the stock position is “ordered up” to a target inventory level. The target level is set to cover demand until the next periodic review plus the delivery lead time. The order quantity depends on how much is needed to bring the stock position up to the target level.
A formal definition of the decision rule embedded in the P system is as follows:
Review the stock position (on hand plus on order) at fixed periodic intervals P. An amount equal to target inventory T minus the stock position is ordered at each review.
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A graph of this system is shown in Figure 14.9. The stock on hand drops on an irregular basis as it is used to meet demand, until the end of the fixed periodic interval is reached. At that time, a quantity is ordered to bring the stock position up to the target level. The order arrives later, after lead time L, and then the cycle of usage, reorder, and order arrival repeats.
The P system is different from the Q system in several ways: (1) It does not have a reor- der point but instead a target inventory level; (2) it does not have an EOQ since the order quantity varies according to demand; and (3) in the P system, the order interval is fixed; in a Q system, an order can be placed whenever inventory is needed.
The P system is determined by two parameters, P and T. Since P is the time between orders, it is related to the EOQ as follows:
P = Q / D (14 .4)
where
Q = EOQ
Equation (14.4) provides an approximately optimal review interval P. We note that if demand is highly uncertain, the approximation of P may be poor.
The target inventory level is set by specifying a service level. In this case, the target level is set high enough to cover demand during the lead time (L) plus the periodic review inter- val (P). This coverage time (P + L), known also as the protection interval, is needed because an order cannot be placed again until the end of the next review interval, and that order will take the lead time to arrive. To achieve the specified service level, average demand must be covered over the time P + L and the safety stock also must cover P + L. Thus, we have
T = m′+s′ (14.5)
where T = target inventory level m′ = average demand over P + L s′ = safety stock to cover P + L
For safety stock, we have
s′= zσ′
where z = safety factor σ′ = the standard deviation of demand over P + L
Just as in the Q system, z reflects the desired service level (see Table 14.1).
FIGURE 14.9 A periodic review system (P System).
St oc
k Po
sit io
n
Time
T
PPP
Q1
Q1 Q2
Q2
Q3
Q3
L L L
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308 Part Five Inventory
To illustrate, we will use the breakfast food example from the previous section. Recall that the EOQ was 1000 cases and the daily demand was 200 cases. The optimal review interval is then
P = Q / D = 1000 / 200 = 5 days
In this case, m′ is the average demand over P + L = 5 + 4 = 9 days. Thus, we have m′ = 9(200) = 1800. The standard deviation is for the P + L period, or 9 days. Thus, with the daily standard deviation = 150 and the coverage period of 9 days,
σ′ = √ __
9 × (150) = 450 cases
Therefore, with a 95 percent service level (z = 1.65):
T = m′ + zσ′ = 1800 + 1.65(450) = 2542 cases
The P system is summarized as the following: The stock position is reviewed every five days, and the order quantity is set to order up to a target of 2542 cases.
It is interesting to note that the P system requires 1.65(450) = 742 units of safety stock, whereas the same service level is provided by the Q system with only 1.65(300) = 495 units of safety stock. The P system always requires more safety stock than the Q system for the same service level. This occurs because the P system must provide coverage over a time of P + L, whereas the Q system must protect against stockout only over the lead time L.
This example is completed by an example in Table 14.3, which uses the same demand figures as Table 14.2. Here, however, the review is periodic instead of continuous. A review is made in periods 1, 6, 11, and 16—that is, every five periods. The amounts ordered are 1442, 786, 1029, and 1237. While the review period is fixed, the amount ordered is allowed to vary. It is a good idea to practice calculating some of the numbers in the table to see if you can verify them.
Example
TABLE 14.3 P-System Example*
Day Demand
Beginning Period on
Hand
Beginning Period on
Order
Beginning Period Stock
Position Amount Ordered
Amount Received
1 111 1100 — 1100 1442 2 217 989 1442 2431 3 334 772 1442 2214 4 124 438 1442 1880 5 0 1756 — 1756 — 1442 6 371 1756 — 1756 786 7 135 1385 786 2171 8 208 1250 786 2036 9 315 1042 786 1828
10 0 1513 — 1513 — 786 11 440 1513 — 1513 1029 12 127 1073 1029 2102 13 315 946 1029 1975 14 114 631 1029 1660 15 241 1546 — 1546 — 1029 16 140 1305 — 1305 1237
*For this table, we have used P = 5 and T = 2542.
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14.8 USING P AND Q SYSTEMS IN PRACTICE
In industry, both Q and P systems, as well as modifications of them, are used widely for independent demand inventory management. Examples of independent demand invento- ries are in wholesale, retail, restaurants, hospitals, factory finished goods, and MRO (main- tenance, repair, and operations) inventories. The choice between Q and P systems is not a simple one and may be dictated by management practices as well as economics. However, there are some conditions under which the P system may be preferred to the Q system:
1. The P system should be used when orders must be placed or delivered at specified inter- vals, for example, weekly or daily deliveries of food to grocery stores.
2. The P system should be used when multiple items are ordered from the same supplier and delivered in the same shipment. In this case, the supplier prefers to consolidate the items into a single order. For example, a large supplier such as Dole may consolidate orders for a number of products when delivering to grocery warehouses.
3. The P system should be used for inexpensive items whose inventory level is monitored only at specific intervals, not continuously. An example is the nuts or bolts used in a manufacturing process. In this case, the bin size determines the target inventory level, and the bin is filled at fixed intervals.
In sum, the P system provides the advantage of scheduled replenishment and less record keeping. However, it requires a larger safety stock than does the Q system, as the previ- ous example illustrates. Because of this larger safety stock, the Q system often is used for expensive items where it is desirable to hold down the investment in safety stock inventory. The choice between the Q and P systems should be made, therefore, on the basis of timing of replenishment, the type of record-keeping system in use, and the cost of the item.
In practice, one can find hybrid systems that are mixtures of P and Q systems. One of these systems is characterized by Min/Max decision rules and periodic review. In this case, the system has both a reorder point (Min) and a target (Max). When the periodic review is performed, no order is placed if the stock position is above the Min. If the stock position is below the Min, an order is placed to raise the stock position to the Max level. See the Operations Leader box for a successful example of a Min/Max inventory system at IKEA.
Service Level and Inventory Level There is an important trade-off between the service level and the inventory level. In man- aging independent demand inventories, one of the key considerations is the level of cus- tomer service the firm wishes to maintain. High customer service levels are clearly good for customers (and perhaps for relationship- building purposes), but they must be balanced against the required investment in inventory, since higher customer service levels generally require higher inventory investments. The aver- age inventory level I is given by
I = Q / 2 + zσ
Q/2 units are carried on average when ordering in lots of size Q, and zσ units are
LO14.6 Explain how continuous and periodic review systems are used in practice.
LO14.7 Describe how inventory and service level are related.
The P system is often used when multiple items are ordered from a single supplier. Stockbyte/Getty Images
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310 Part Five Inventory
carried on average in safety stock. (For the P system, use σ′ in place of σ.) Thus, the inven- tory level is the sum cycle stock (Q/2) and safety stock (zσ).
If we fix Q, the inventory level is a function of z, which represents the service level. Thus, we can vary z and plot the service level versus the average inventory required, as shown in Figure 14.10.
The figure shows the increasing inventory level required to achieve higher service lev- els. Recall that the service level is the probability of being able to satisfy demand from stock, thus avoiding lost sales or backorders. In order to achieve a service level close to 100 percent, very large inventories are required. This happens because, assuming normally distributed demand during the lead time, the safety stock must be very large to cover very unlikely events as the service level approaches 100 percent.
Due to the highly nonlinear relationship between service level and inventory level, it is crucial for management to estimate the costs of a reasonable service level. The selection of an arbitrary service level (“Let’s just set it at 99 percent!”) may be very costly since the difference of a few percentage points in service level could increase the required inventory level substantially. For example, in Figure 14.10 an increase in the service level from 95 to 99 percent requires a 32 percent increase in inventory. Thus, although there is often pressure from marketing to set service levels very high, it is the inventory manager’s job to make sure that the firm recognizes and fully accounts for the cost of the chosen service level.
The selection of the service level (and thus the related inventory level) helps deter- mine the number of inventory turnovers. Inventory turnover indicates the number of times (during a year) the inventory in stock is completely renewed, that is, the relation- ship between the average inventory on hand and the annual usage of inventory. Inventory
its in-store restaurants maintain both the thrifty and the Swedish themes.
Store managers use a “minimum/maximum” inven- tory replenishment system for stocking stores. The minimum is set to signal the need to order, with reorder points set at the store level. The maximum is the most of a particular product to order at one time. The logic is to balance inventory stock within the fixed order period, and this target is based on the number of items that will fit in each product’s designated bin. This com- bined continuous and periodic review system enables IKEA to meet customer demand and lower the likeli- hood of lost sales.
Point-of-sale data help managers determine how much inventory to order each day. Automation in ware- houses further reduces manual counting and moving of inventory. Their successful management of inventory has made IKEA the world’s largest furniture retailer.
Source: www.tradegecko.com/blog, July 2, 2018.
IKEA was founded in Sweden in 1943 and continues to expand its global reach today. With 424 stores in 52 countries, it is still growing. Stores are stocked with nearly 10,000 functional and reasonably priced products. And
IKEA Uses Hybrid P and Q System
OPERATIONS LEADER
Tooykrub/Shutterstock
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turnover (or inventory turns) can be calculated for single items or for the overall stock of inventory:
Inventory turnover = Annual cost of goods sold / Average inventory level
In practice, firms have inventory turnover anywhere between 1 and 50 turns per year. Spe- cialty shops may have turnover as low as one to two turns per year. Summit Brewery, a regional brewer, has 12 to 18 turns per year, and it is quite rare for a firm to have more than 50 turns per year. To assess whether inventory is being well managed, it is often best to compare the inventory turnover of the firm against the inventory turnover of the best firms in the same industry. If inventory turnover is low, it could be explained by either higher service levels or different ordering and holding costs. Management should look beyond inventory turnover to the service level policy or the cost structure inherent in the inventory system. Management may accept a lower inventory turnover than the industry norm in favor of a higher service level.
Alternatively, management might focus on reducing Q or σ, thereby reducing the inventory required for a given service level. The lot size Q can be reduced by reducing setup time or order- ing costs. The standard deviation of demand during the lead time can be reduced by decreasing the daily variation in demand or by decreasing the lead time. Daily variation in demand can be reduced by working with customers to smooth out demand and reduce uncertainty in their ordering patterns. Lead time can be reduced by decreasing throughput times in the production and distribution process. Another possible cause of low inventory turnover is that the firm has too much inventory of slow moving items that should be reduced and written off.
14.9 VENDOR MANAGED INVENTORY
Many firms have adopted vendor managed inventory (VMI). VMI is a supply chain management initiative that passes the responsibility for managing inventory stocks to ven- dors (or suppliers). To make this work, a vendor under VMI is given access to the firm’s demand forecast and inventory records. The vendor is contractually tasked with maintain- ing the correct inventory level at the firm’s location. VMI requires collaboration between the supplier (vendor) and the customer (firm) in terms of sharing data as well as access to the firm and its stocking locations. For example, VMI is used in grocery stores for some food items, with the supplier stocking the shelves in the store, and is used for some supplier deliveries to manufacturing plants. As the payoff for the effort expended to collaborate, both supply chain partners can benefit from greatly reduced ordering costs and often a
LO14.8 Define vendor managed inventory (VMI) and the ABC system.
FIGURE 14.10 Service level versus inventory level. (Q = 100; σ = 100.)
Se rv
ic e
Le ve
l ( pe
rc en
t) 100
95
90
85
150 200 250 300
z = 1.0
z = 1.2 z = 1.3
z = 1.5 z = 1.7
z = 1.9 z = 2.1 z = 2.4
Average Inventory Level
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312 Part Five Inventory
higher level of customer service. Check the Operations Leader box to see how P&G uses VMI to hold down its investment in inventory.
Cloud-based VMI platforms can allow vendors and their business customers to safely connect and share inventory data. Information systems are increasingly able to commu- nicate with one another, making VMI more easily implemented. Most VMI partnerships result in reduced inventory in the supply chain, on average about 30 percent.
14.10 ABC CLASSIFICATION OF INVENTORY
Pareto’s law states that, for many events, roughly 80 percent of the effects come from 20 percent of the causes. It is also true that a few products in a firm account for most of the sales. The law of the significant few can be applied to inventory management as well.
With inventories, a few items usually account for most of the inventory value as mea- sured by dollar usage (demand × cost). Thus, one can manage these few items intensively and control most of the inventory value. In inventory management, items usually are divided into three classes: A, B, and C. Class A typically contains about 20 percent of the items and 80 percent of the dollar usage. It therefore represents the most significant few. At the other extreme, class C contains 50 percent of the items and only 5 percent of the dollar usage. These items account for very little of the dollar value of inventory. In the middle is class B, with 30 percent of the items and 15 percent of the dollar usage. The classification of inventory in this way is called ABC analysis or the 80–20 rule.
Table 14.4 shows an example of an inventory with 10 items. For each item (row), we have multiplied the annual usage in units by the unit cost to determine the dollar usage of that item. We also have calculated the percentage of total dollar usage by comparing each item’s dollar usage to the entire inventory usage ($254,725). We see that items 3 and
software flags critical inventory levels, so that an analyst can step in when needed.
Source: consumergoods.com, 2020; us.pg.com, 2020.
Manufacturer P&G, renowned for its sophisticated supply chain, uses vendor managed inventory (VMI) practices to manage inventory levels for its retailers and distributors. P&G makes leading consumer brands in many product segments, including Tide, Bounce, Gillette, Dawn, and Crest, among many others. Used primarily to fulfill the inventory needs of its largest retail customers, P&G is expanding VMI to provide broader opportunities for col- laboration with its customers around the world.
P&G’s experience shows that VMI improves perfor- mance in a variety of ways. Retail stockouts of P&G prod- ucts are less frequent, even while lowering inventory levels by about one-third. On-time delivery is better, and delivery truck fill rates improved at least 5 percent with VMI, wasting less truck space and, thus, less fuel.
P&G helps its retailers quickly grasp VMI best prac- tices, while improved technology interfaces allow them to increase their collaboration with both suppliers and customers. VMI is relatively “auto-pilot,” but the system
The Procter and Gamble Company (P&G)
OPERATIONS LEADER
Roberto Machado Noa/Contributor/Getty Images
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6 account for a great deal of the dollar usage (73.2 percent) and are classified as A items. Items 1, 5, 7, 8, and 10 are low in dollar usage (10.5 percent) and are considered C items. The other items are considered B items.
The designation of three classes is arbitrary; there could be any number of classes. Also, the exact percentage of items in each class will vary from one set of inventory to another. The important factors are the two extremes: a few items that are significant and a large number of items that are relatively insignificant.
Most of the dollar usage in inventory (80 percent) can be controlled by closely monitor- ing the A items (20 percent). For these items, a tight control system should be used, includ- ing continuous review of stock levels, less safety stock, and frequent resupply. Looser control might be used for C items. A periodic review system probably would be used with longer ordering cycles and lower reorder and transportation costs. The B items require an intermediate level of attention and management control.
With computerized systems, a uniform level of control sometimes is used for all items. Nevertheless, managing inventories still requires setting priorities, and ABC analysis is useful in doing this. A items usually deserve additional attention and effort.
14.11 KEY POINTS AND TERMS
This chapter provides an overview of inventory management and specific methods for the management of independent demand inventories. The major points include the following:
∙ Inventory management is a key operations management responsibility. Inventory man- agement affects capital requirements, costs, and customer service.
∙ Inventory is a stock of materials used to facilitate production or satisfy customer demands. Inventories include raw materials, work in process, and finished goods.
∙ Inventories are held for many purposes, including cycle inventory, safety stock, antici- pation inventory, and pipeline inventory.
∙ Inventory decisions should account for several costs. There are four inventory costs to consider: item cost, ordering (or setup) cost, carrying (or holding) cost, and stockout cost.
∙ The economic order quantity (EOQ) is a simple but powerful calculation for estimating the best order size while balancing ordering and holding costs. It includes assumptions of a constant demand rate, constant lead time, fixed setup time, no stockouts, lot order- ing, no discounts, and a single independent product.
∙ A continuous review (Q) system provides one way to handle random demand. When the stock position drops to reorder point R, a fixed quantity Q is ordered. The time between
TABLE 14.4 Annual Usage of Items by Dollar Value
Item Annual Usage
in Units Unit Cost Dollar Usage Percentage of Total
Dollar Usage
1 5,000 $ 1.50 $ 7,500 2.9% 2 1,500 8.00 12,000 4.7 3 10,000 10.50 105,000 41.2 4 6,000 2.00 12,000 4.7 5 7,500 .50 3,750 1.5 6 6,000 13.60 81,600 32.0 7 5,000 .75 3,750 1.5 8 4,500 1.25 5,625 2.2 9 7,000 2.50 17,500 6.9
10 3,000 2.00 6,000 2.4 Total $254,725 100.0%
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314 Part Five Inventory
orders varies depending on actual demand. The value of Q is set equal to the EOQ. The value of R is based on the service level desired.
∙ A periodic review (P) system provides another way to handle random demand. The stock position is reviewed at fixed intervals P, and an amount is ordered equal to target inventory T minus the stock position. The amount ordered at each review period varies depending on actual demand. The value of P is determined by using the EOQ, and the value of T is based on the service level desired.
∙ The choice between P and Q systems should be based on the timing of replenishment, type of record keeping, and cost of the item. The P system should be used when inven- tory orders must be on a regular schedule.
∙ High service levels require high investment levels for a given order quantity (Q) and standard deviation (σ). Management should analyze the investment required for a set of service levels before setting the desired level. Looking at inventory turnover alone does not provide an adequate basis for decisions on inventory levels.
∙ VMI, vendor managed inventory, passes the responsibility for monitoring and replen- ishing inventory stocks from the buying firm to its vendors. Vendors must have access to demand forecast and inventory levels. Collaboration between vendors and the buying firm is crucial.
∙ ABC analysis classifies inventory items into A, B, and C categories. ABC analysis is based on the law of the significant few and the insignificant many. A items should be closely managed. Less effort and cost should be expended on B and C items.
Key Terms Bar coding 293 Point of sale data 293 Radio-frequency
identification 293 Inventory 293 Safety stock 295 Cycle inventory 295 Anticipation inventory 295 Pipeline inventory 295 Item cost 296 Ordering (setup) cost 296
Continuous review system 302 Reorder point 302 Stockout probability 303 Service level 303 Periodic review system 306 Target level 306 Inventory turnover 310 Vendor managed
inventory 311 ABC analysis 312
Carrying (holding) cost 296 Stockout cost 296 Independent demand 297 Dependent demand 297 Replenishment
philosophy 298 Requirements philosophy 298 Economic order quantity 298 Lead time 298 Total cost 300 Stock position 302
LEARNING ENRICHMENT (for self-study or instructor assignments)
Variety of Inventory Topics Website www.effectiveinventory.com/articles
Inventory Management Software Website www.cissltd.com
Using Inventory Technology in Small Business Video https://youtu.be/1d0O8MAMyAM 5:03
ABC and Inventory Turnover Video https://youtu.be/-l9rIMekpfs 3:33
Inventory Technology at Walmart Video https://youtu.be/KRJV1SPYpIE 6:20
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Chapter 14 Independent Demand Inventory 315
SOLVED PROBLEMS
1. EOQ In a hardware warehouse, the independent demand for a commonly used bolt is 500 units per month. The ordering cost is $30 per order placed. The carrying cost is 25 percent per year, and each unit costs $.50. a. According to the EOQ formula, what lot size should this product have? b. How often should this product be purchased? c. A quality team has found a way to reduce ordering costs to $5. How will that change
the lot size and the frequency of purchasing for this product?
First, convert demand to the same time units as the carrying cost. In this case, the carrying cost is in years and demand is in months. The annual demand is 500 × 12 = 6000 units.
Q
=
√ ____
2SD ____ iC
= √ ___________
2 × 30 × 6000 ____________ .25 × .50
=
√ ________
360,000 _______ .125
=
1697.06 → 1697 units
b. The annual frequency of procurement = D/Q or 6000/1697 = 3.54 times per year. To convert to months, divide 12 months per year by the annual frequency of procurement.
12 ____ 3.54
= Every 3.39 months
52 ____
3.54 = Every 14.69 weeks
365 ____ 3.54
= Every 103.11 days
c.
Q
=
√ ____
2SD ____ iC
= √ ___________
2 × 5 × 6000 ___________ 25 × .50
=
√ _______
60, 000 ______ .125
=
692.8 → 693 units
The frequency of procurement = DQ or 6000/693 = 8.66 times per year.
2. Q System Part number XB-2001 is a spare part with annual independent demand of 4000 units, a setup cost of $100, a carrying cost of 30 percent per year, and an item cost of $266.67. The production facility is open 5 days per week and 50 weeks per year, making a total of 250 productive days per year. The lead time for this product is nine days, and the standard deviation of demand is two units per day. The firm wants to have a 95 percent service level for this spare part.
Problem
Solution
a.
Problem
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316 Part Five Inventory
a. Compute Q, using the EOQ formula. b. Compute R. c. If the firm is using a Q system of inventory control (continuous review), interpret the
results of your computations.
Q
=
EOQ
=
√ ____
2SD ____ iC
= √
_____________
2 × 100 × 4000 _____________ .3 × 266.67
=
√ ______
10, 000
=
100
b. Solving this part of the problem correctly requires two steps. First, the daily demand must be calculated. This is done by dividing the annual rate of demand by the num- ber of working days per year—4000/250 = 16 units per day. Thus, the average de- mand during lead time is 16 units per day for 9 days, or 9 × 16 = 144 units. Second, the standard deviation of demand during the lead time must be calculated. This is determined by taking the standard deviation of daily demand (two units) and multi- plying by the square root of the number of days of lead time (the square root of 9).
R
=
m + zσ
= (9 × 16) + 1.65 × (2 × √
__ 9 )
= 144 + 9.9
=
153.9 → 154 units
c. Order 100 units when inventory (on hand plus on order) gets down to 154 units. On the average, 9.9 units of safety stock will be on hand when the order arrives. In 5 percent of the cycles, there will be a stockout before the order arrives.
3. P System Consider the product described in solved problem 2 when answering the following questions: a. How often should orders be placed for this product if they are placed at regular inter-
vals using a periodic review system? b. Compute the target inventory level. c. State the specific decision rule for this product by using the information you have
calculated so far. d. Assume it is time for a periodic review. A check of the inventory level for this prod-
uct reveals that there are 60 units on hand and 110 units on order. What should be done?
P
=
Q __ D
(use Q and D from the previous problem )
= 100 _____ 4000
= .025 year
=
1.25 working weeks (.025 year × 50 working weeks per year)
=
6.25 days (.025 year × 250 woring days per year)
=
6 days (round off)
Solution a.
Problem
Solution a.
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Chapter 14 Independent Demand Inventory 317
Discussion Questions 1. Identify the different types of inventories (raw materi-
als, work in process, and finished goods) carried in the following organizations: gas station, hamburger stand, clothing store, and machine shop. What functions (purposes) do these inventories perform?
2. Why are stockout costs difficult to determine? Suggest an approach that might be used to estimate them.
3. What is the difference between a requirements philoso- phy and a replenishment philosophy of inventory management? Why is this difference important?
4. Compare and contrast the management of finished goods inventory in a manufacturing firm with that in a retail or wholesale firm.
5. For a given service level, why does a P system require a larger inventory investment than a Q system? What factors affect the magnitude of the difference?
6. Suppose you are managing the Speedy Hardware Store. Give examples of items that might be managed by a P system and other items for which a Q system might be used. How do these items differ?
7. How should a manager decide the appropriate service level for finished goods items? Should some items have a 100 percent service level?
8. What is the appropriate role of inventory turnover as a measure for evaluating the management of inventory? Under what circumstances is high turnover detrimental to a firm?
9. Suppose you are managing a chain of retail department stores. As a top manager, how would you measure the overall inventory management performance of each store? How would you use this information in your relationship with the individual store managers?
Problems Five Excel spreadsheets are provided on Connect for assistance in solving the chapter problems. 1. The Always Fresh Grocery Store carries a particular
brand of tea that has the following characteristics: Sales = 8 cases per week Ordering cost = $10 per order Carrying charge = 20 percent per year Item cost = $80 per case
a. How many cases should be ordered at a time? b. How often will tea be ordered? c. What is the annual cost of ordering and carrying
tea? d. What factors might cause the firm to order a larger
or smaller amount than the EOQ?
2. The Grinell Machine Shop makes a line of metal tables. Some of these tables are carried in finished goods inventory. A particular table has the following characteristics:
Sales = 300 per year Setup cost = $1200 per setup (this includes machine
setup for all the different parts in the table) Carrying cost = 20 percent per year Item cost = $25
a. How many of these tables should be made in a production lot?
b. How often will production be scheduled? c. What factors might cause the firm to schedule a lot
size different from the one you have computed?
T
=
m′ + s′
=
m′ + z σ′
= (average demand over P + L) + z(s.d of demand during P + L)
= 16 × (6 + 9) + 1.65 × (2 × √
____ 9 + 6 )
=
240 + 12.8
=
252.8 → 253
c. Review stock (on hand and on order) every six days and order up to a target level of 253 units.
d. Order up to the target level. The target level is 253 units. The amount of inventory on hand and on order is 60 + 110 units, or 170 units total. The difference between the target level and the inventory on hand and on order is the quantity which should be ordered for delivery in nine days, 253 − (60 + 110) = 83. Order 83 units for delivery in nine days.
b.
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318 Part Five Inventory
3. The local Toyota dealer has to decide how many spare shock absorbers of a particular type to order for repair- ing Toyota automobiles. This shock absorber has a demand of four units per month and costs $25 each. The carrying charge is 30 percent per year, and the ordering cost is $15 per order.
a. What is the EOQ for this item? b. How often will the dealer reorder this part? c. What is the annual cost of ordering and carrying
this part? 4. What is the effect on EOQ and total cost of the following types of changes for the data in
problem 1? a. A 40 percent increase in demand. b. A 20 percent increase in carrying charge. c. Use a spreadsheet to study the relationship between
lot size and carrying cost. 5. The famous Widget Company sells widgets at the rate
of 80,000 units per year. Each widget sells for $100, and it costs 30 percent to carry widgets in inventory for a year. The process of widget production has been auto- mated over the years, and it now costs $1000 to change over the widget production line to other products that are made on the same line.
a. What is the economical lot size for the production of widgets?
b. How many lots will be produced each year? c. What are the annual cost of carrying widgets and the
annual cost of changeover? d. What factors or changes in assumptions might cause
the Widget Company to produce a larger lot than the economic lot size calculated in part a?
6. The Harvard Co-op orders sweatshirts with the Harvard University emblem on them and sells them for $50 each. During a typical month, 900 sweatshirts are sold (this includes all styles and sizes ordered from a particular supplier). It costs $25 to place an order (for multiple sizes and styles) and 25 percent to carry sweatshirts in inventory for a year.
a. How many sweatshirts should the Co-op order at one time?
b. The supplier would like to deliver sweatshirts once a week. How much will this cost the Co-op per year? Under what conditions would you agree to the supplier’s proposal?
c. Suppose that sales increase to 1500 sweatshirts per month but you decide to keep the lot size the same as in part a. How much will this decision cost the Co-op per year?
7. The Co-op in problem 6 has discovered that it should establish a safety stock for its sweatshirts. It wants
to use a reorder point system with a two-week lead time. The demand over a two-week interval has an average of 450 units and a standard deviation of 250 units.
a. What reorder point should the Co-op establish to ensure a 95 percent service level?
b. What reorder point should be established to ensure that no more than one stockout occurs in the course of a year?
c. How much average inventory will the Co-op carry for part b? Include both cycle inventory and safety stock in your answer.
d. How often will the Co-op turn over its inventory, using the results from part c?
8. An electronics retailer carries a particular cell phone with the following characteristics:
Average monthly sales = 120 units Ordering cost = $25 per order Carrying cost = 35 percent per year Item cost = $300 per unit Lead time = 4 days Standard deviation of daily demand = .2 unit Working days per year = 250
a. Determine the EOQ. b. Calculate the reorder point for a 92 percent service
level, assuming normally distributed demand. c. Design a Q system for this item. d. What happens to the reorder point when the lead
time changes? What happens to the reorder point when the standard deviation of demand changes?
9. For the data given in problem 8: a. Design a P system for this phone with a
92 percent service level. b. Compare the inventory investments required for the
P and Q systems (from problem 8) for a 92 percent service level and other various values of service level.
c. Why does the P system require a higher inventory investment?
10. The Toyota dealer from problem 3 is considering installing either a Q or a P system for inventory control. The standard deviation of demand has been 4 units per month, and the replenishment lead time is two months. A 95 percent service level is desired.
a. If a continuous review system is used, what is the value of Q and R that should be used?
b. If a periodic review system is used, what is the value of P and T that would be applicable?
c. What are the pros and cons of using the P system compared with using the Q system for this part?
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11. The Suregrip Tire Company carries a certain type of tire with the following characteristics:
Average annual sales = 600 tires Ordering cost = $40 per order Carrying cost = 25 percent per year Item cost = $50 per tire Lead time = 4 days Standard deviation of daily demand = 1 tire a. Calculate the EOQ. b. For a Q system of inventory control, calculate the
safety stock required for service levels of 85, 90, 95, 97, and 99 percent.
c. Construct a plot of total inventory investment versus service level.
d. What service level would you establish on the basis of the graph in part c? Discuss.
12. For the data in problem 11: a. Calculate the annual turnover as a function of ser-
vice level. b. If sales were to increase by 50 percent, what would
happen to the turnover at a 95 percent service level? 13. The Cover-up Drapery Company carries four types of fabric with the following
characteristics:
Type Annual Demand (yards) Item Cost per Yard
1 300 $20 2 250 $18 3 100 $12 4 200 $ 8
Assume that the items are to be ordered together from the same supplier at an ordering cost of $20 per order and an annual carrying cost of 20 percent. Also assume 300 working days in a year.
a. If a P system is used, what is the optimal ordering interval in days?
b. How much of each type of fabric would be ordered when a combined order is placed?
c. What is the effect on the ordering interval of changing the carrying cost to 25, 30, and 35 percent?
d. Can these fabrics be ordered by using a Q system? Explain.
e. Classify the four items above as A, B, or C inventory items.
14. Suppose you are the supplier of the Cover-up Drapery Company described in problem 13. It costs $2000 each time you change over your fabric-producing machine from one type to another (1, 2, 3, or 4). Assume that your carrying cost is 30 percent and the other data are as given in problem 13.
a. What lot sizes would the supplier of fabric prefer to make for items 1, 2, 3, and 4?
b. How would you reconcile the lot sizes that the supplier would like to produce and those that the Cover-up Drapery Company would like to buy? Describe several ways in which these two differing lot sizes can be reconciled.
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320 Part Five Inventory
Supplement
Advanced Models This supplement presents two additional models that are useful for managing independent demand inventory. The first model applies to outside procurement in which price discounts are given; the second applies to a gradual fill of inventory when the lot arrives uniformly over time rather than all at once.
PRICE BREAKS Outside suppliers often offer price discounts for large purchases. These discounts may be given at different procurement levels, and they may apply either to the whole order or to only the increment purchased. In this supplement, we assume that the price discounts apply to the entire order. For example, the procurement price may be $2 per unit for 1 to 99 units and $1.50 per unit for 100 units and up. The cost of the units thus exhibits a jump or discontinuity at 100 units. For 99 units, the cost of the procurement order is $198, and for 100 units the cost is $150.
To solve for the EOQ, the procedure is to first calculate the EOQ for each different procurement price. Some of these EOQs may not be feasible because the EOQ falls outside the range of the price used to compute it. The infeasible EOQs are eliminated from further consideration. The total procurement and inventory operating cost for each feasible EOQ and each price-break quantity is then computed. The feasible EOQ or price break that results in the lowest total cost then is selected as the order quantity.
Consider the following example:
D = 1000 units per year i = 20 percent per year S = $10 per order C1 = $5 per unit for 1 to 199 units C2 = $4.50 per unit for 200 to 499 units C3 = $4.25 per unit for 500 units or more
First, we calculate the three EOQs corresponding to the three values of Ci. We obtain Q1 = 141, Q2 = 149, and Q3 = 153. In this case, Q2 and Q3 are infeasible, and they are eliminated from further consideration. We then compute the total cost of procurement and inventory at the remaining EOQ and at the two price breaks. These total costs are as follows:*
TC
=
S ( D
_ Q
) + iC ( Q
_ 2 ) + CD
TC(141) = 10 ( 1000 ⁄ 141 ) + .2(5) ( 141 ⁄ 2 ) + 5(1000) = $5141 TC(200)
=
10 ( 1000 ⁄ 200 ) + .2(4.5) ( 200 ⁄ 2 ) + 4.5(1000) = $4640
TC(500)
=
10 ( 1000 ⁄ 500 ) + .2(4.25) ( 500 ⁄ 2 ) + 4.25(1000) = $4482
Since TC(500) is the lowest annual cost, 500 units should be ordered.
S-LO14.9 Solve advanced inventory problems.
* Note that the annual cost CD of buying the units is included in the total cost equation since this cost is affected by the discount.
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The cost behavior for the example is shown in Figure S14.1. Notice that at each price break, the total cost is reduced. Therefore, in this example, the quantity at the highest price break is selected.
It is not always necessary to calculate all the EOQs and the cost at each price break. A more efficient procedure follows:
1. Calculate the EOQ for the lowest cost per unit (the largest price-break quantity). If this EOQ is feasible, that is, above the price break, then this is the most economic order quantity.
2. If the EOQ is not feasible, use the next lowest price and continue calculating EOQs until a feasible EOQ is found or until all prices have been used.
3. Next, calculate the total cost of the EOQ and the total cost at all the higher price breaks. 4. The minimum of these total costs indicates the most economic order quantity.
In the above example, this procedure yields the same result as in the calculations earlier. By coincidence, both methods require the same number of calculations for this particular example.
UNIFORM LOT DELIVERY In some cases, the entire lot is not placed in inventory at one time but is delivered gradu- ally. An example is a manufacturer that builds inventory at a constant production rate. Another example is a retailer that accepts delivery of an order in several shipments over a period of time.
The effect of this delivery condition on inventory is shown in Figure S14.2. The inven- tory level builds up gradually as both production and consumption occur. Then the inven- tory level is depleted as only consumption takes place.
The effect of gradual delivery is to reduce the maximum and average inventory level over that obtained in the simple EOQ case when the entire lot is accepted at one time. Sup- pose units are produced at a rate of p units per year and consumed at a rate of D units per year (where p > D). Then the average inventory level is
Q __ 2 ( 1 − D _ p )
This formula can be derived with the use of geometry by reference to Figure S14.2.
FIGURE S14.1 Inventory cost with price breaks.
TC
200 500 Q
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322 Part Five Inventory
The above expression for average inventory is used in place of Q/2 in Equation (14.1). When the resulting expression for TC is minimized, the following EOQ formula is obtained:
Q = √ __________
2SD _________ iC(1 − D / p)
The EOQ in this case is always somewhat larger than the ordinary EOQ because the fac- tor (1 − D/p) is less than 1. As p approaches D, the EOQ becomes very large, which means that production is continuous. When p is very large, the above EOQ formula approaches the ordinary EOQ. In deriving the ordinary EOQ, we assumed that the entire lot arrived in inventory at once, which is equivalent to an infinite production rate p.
FIGURE S14.2 Uniform lot delivery.
In ve
nt or
y Le
ve l (
1 –
D /p
)Q
Q/D
Time
Rate = p – D
Rate = D
Supplement Problems 1. Suppose that for problem 1 in the chapter, the Always Fresh Grocery Store is offered
a discount by its supplier if more than 50 cases of tea are ordered at one time. The unit item costs are $80 per case for 0 to 49 cases and $76 per case for 50 cases or more. This price of $76 applies to the entire order.
a. Should the grocery store take the discount offer? b. What discount is required for the store to be indif-
ferent between taking the discount and ordering the EOQ?
2. A supplier has come to you and offered the following deal. If you buy 29 or fewer cases of cleaning solution, the cost will be $25 for each case. If you buy 30 or more cases, the cost will be $20 per case. Assume your cost of carrying inventory is 15 percent a year, it costs $20 for you to order the material, and you use 50 cases per year.
a. How many cases should you order? b. Would you negotiate with this supplier for a further
discount? Explain the quantities and prices that you
would negotiate for and why those quantities and prices are selected.
3. For problem 2 in the chapter, suppose the Grinell Machine Shop produces its tables at a rate of two per day (250 working days per year).
a. What is the optimal lot size? b. Draw a graph of on-hand inventory versus time. c. What is the maximum value of inventory? 4. A producer of electronic parts wants to take account
of both production rate and demand rate in deciding on its lot sizes. A particular $50 part can be produced at a rate of 1000 units per month, and the demand rate is 200 units per month. The firm uses a carrying charge of 24 percent a year, and the setup cost is $200 each time the part is produced.
a. What lot size should be produced? b. If the production rate is ignored, what would the lot
size be? How much does this smaller lot size cost the firm on an annual basis?
c. Draw a graph of on-hand inventory versus time.
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The typical manufacturing firm has thousands of products and parts to manage, constantly shifting priorities, and unpredictable demand. It is possible to manage this complex situ- ation through the use of a computerized planning and control system called materials requirements planning (MRP).
Consider a company that is making several different types of skateboards. Each skate- board requires a deck (top), four wheels, and two axle units to attach the wheels. The com- pany assembles the skateboards from parts that are purchased. For each skateboard type, the company needs to plan ahead to order enough decks, wheels, and axle units to arrive in time for final assembly. Assuming there is already some inventory of these parts on hand or scheduled to arrive and the lead times for ordering new parts are known, how does the company plan the orders and assembly so all the parts arrive just when needed to make
Materials Requirements Planning and ERP
c h a p t e r 15
After reading this chapter, you should be able to:LEARNING OBJECTIVES
LO15.1 Define the elements, inputs, and outputs of an MRP system.
LO15.2 Contrast and compare MRP vs. order-point systems.
LO15.3 Construct a materials plan given the gross requirements.
LO15.4 Describe in detail each element of an MRP system.
LO15.5 Discuss DRP and different ways to deal with uncertain demand.
LO15.6 Explain the five requirements for a successful MRP system.
LO15.7 Describe what an ERP system does.
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324 Part Five Inventory
a batch of, say 100, new finished skateboards three weeks from now? This planning and scheduling can be done by an MRP system.
Service organizations also can benefit from the use of MRP systems. Services such as restaurants, hospitals, and electric-power companies need facilitating goods to support their service delivery systems. Delivery of these goods can also be scheduled by an MRP system to arrive just when they are needed to support the scheduled service offerings.
An MRP system is driven by the master schedule, which specifies the production timing of final products (often referred to as end items) or output of the production function. All future demands for purchased parts or shop orders to make the parts are dependent on the master schedule and derived mathematically by the MRP system from the master schedule. Remember it takes exactly one deck, four wheels, and two axle units to make a skateboard. Given the num- ber of skateboards in the master schedule, the number of decks, wheels, and axle units needed to meet the master schedule is then known. Since conditions are usually changing, the master schedule is a far better basis than past demand for planning future material requirements.
MRP software “explodes” the master schedule into purchase orders and shop orders for scheduling the factory. For example, if the product in the master schedule is a hand-held cal- culator, the process of parts explosion will determine all the parts and components needed to make a specified number of calculator units. This process of parts explosion requires a detailed bill of materials that lists each of the parts needed to manufacture any particular end item in the master schedule. The required parts may include assemblies, subassemblies, manufactured parts, and purchased parts. Parts explosion thus results in a complete list of the parts that must be ordered and the shop schedule that is required for internal production.
In the process of parts explosion, it is necessary to consider inventories of parts that are already on hand or on order. For example, an order for 100 end items may require a new order of only 20 units of a particular part because 50 units are already in stock and 30 units are on order.
Another adjustment made during parts explosion is for production and purchasing lead times. Starting from the master schedule, each manufactured or purchased part is offset (i.e., ordered earlier) by the amount of time it takes to get the part (the lead time). This procedure ensures that each component will be available in time to support the master schedule. If sufficient manufacturing and supplier capacity is available to meet the orders resulting from parts explosion, the MRP system will produce a valid plan for procurement and manufacturing actions. If sufficient capacity is not available, it will be necessary to replan the master schedule or change the capacity.
15.1 THE MRP SYSTEM
A typical MRP system, along with inputs and outputs, is illustrated in Figure 15.1. The MRP system begins with the master schedule, which is determined by customers’ orders, aggregate production planning, and forecasts of future demand. The parts-explosion pro- cess, at the center of the system, is driven by three types of information: master schedule, bill of materials, and inventory records. The result of the parts-explosion process is two types of output: purchase orders that go to suppliers and shop orders that go to the factory.
Before shop orders are sent to the factory, however, materials planners check on whether sufficient capacity is available to produce the parts required. If capacity is available, the shop orders are placed under control of the shop-floor control system. If capacity is not available, a change must be made by the planners in the capacity or in the master schedule through the feedback loop shown. Once the shop orders are under the shop-floor control system, the progress of these orders is managed through the shop to make sure that they are completed on time.
LO15.1 Define the elements, inputs, and outputs of an MRP system.
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FIGURE 15.1 A closed-loop MRP system.
S&OP (aggregate production
plan)
Master schedule
Parts explosion
Bill of
materials
Engineering design
changes
Inventory transactions
Inventory records
Shop orders
Capacity planning
Shop-floor control
Operations
Firm orders from customers
or from finished- goods inventory
Forecast of
demand
Purchase orders
Suppliers
Raw Materials
Product
PRODUCTION CONTROL. This production control employee uses a computer to track the flow of materials as part of an MRP system. Cultura Exclusive/Getty Images
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326 Part Five Inventory
Figure 15.1 represents MRP as an information system used to plan and control inventories and capacity. Information is processed through the various parts of the system to support man- agement decisions. If the information is accurate and timely, management can use the system to control inventories, deliver customer orders on time, and control costs for the firm. In this way, the materials are managed continually in a dynamic and changing environment.
15.2 MRP VERSUS ORDER-POINT SYSTEMS
An MRP system calls into question many of the traditional concepts used to manage inven- tories. Order-point systems do not work well for the management of inventories subject to dependent demand. Dependent demand is determined by demand for another item and not by the market. When a product is manufactured, all demand for components, assem- blies and parts is dependent on demand for the final product in the master schedule.
Some of the key distinctions between MRP and order-point systems are summarized in Table 15.1. One distinction is the requirements philosophy used in MRP systems versus a replenishment philosophy used in order-point systems. A replenishment philosophy indicates that material should be replenished when it runs low. An MRP system does not do this. More
LO15.2 Contrast and compare MRP vs. order-point systems.
also could consider capacity and frequently reschedule its factories.
Using JDA Company (formerly i2) software, 3M inte- grated collaborative forecasting, material planning, and shop-floor execution with complete visibility across the supply chain. 3M implemented two applications, JDA Factory Planner and JDA Supply Chain Planner, across all factories in Canada. 3M could replan every day on the basis of data from the previous shifts and new cus- tomer orders. Supply Chain Planner created optimized purchase requirements and manufacturing orders. The previous system could plan only on the basis of material availability, but Factory Planner also considered machine capacity and other resources. As a result, 3M Canada was able to grow sales through better on-time delivery, reduce inventories by 23 percent, and improve cash flow.
Source: www.3m.com, 2020.
3M Canada is one of the first subsidiaries established by 3M in 1951. Headquartered in London, Ontario, 3M Canada now has sales offices in the provinces of Alberta, British Columbia, Ontario, and Quebec, as well as five man- ufacturing facilities—four in Ontario and one in Manitoba.
3M Canada Uses JDA Software
OPERATIONS LEADER
3M Canada used to operate a legacy MRP system that considered only material availability. By incorporating finite capacity scheduling and constraint management, it
MRP Order Point
Demand Dependent Independent Order philosophy Requirements Replenishment Forecast Based on master schedule Based on past demand Control concept Control all items ABC Objectives Meet manufacturing needs Meet customer needs Lot sizing Discrete EOQ Demand pattern Lumpy but predictable Random Types of inventory Work-in-process and raw materials Finished goods and spare parts
TABLE 15.1 Comparison of MRP and Order-Point Systems
Pa ul
B rig
ha m
/1 2
3 R
F
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material is ordered only when it is needed to meet pro- duction specified on the master schedule. If there are no future manufacturing requirements for a particular part, it will not be replenished even though the inventory level is low. This requirements concept is particularly impor- tant in manufacturing because demand for component parts is “lumpy.” When a lot is scheduled, the component parts are needed for that lot, but demand is then zero until another lot is scheduled. If order-point systems are used for this type of lumpy demand pattern, material will be carried on hand during long periods of zero demand.
Another distinction between the two systems is the use of forecasting. For order-point systems, future demand is forecast on the basis of the past history of demand. These forecasts are used to replenish the stock levels to serve customers. In MRP systems, past demand for component parts is irrelevant for forecasting future needs. Future needs are derived mathematically from the master production schedule.
The ABC classification of inventory also does not work well for MRP systems. In manufacturing a product,
components that are C items are just as important as A items. For example, an automobile cannot be shipped if it lacks a fuel line or radiator cap even though these items are relatively inexpensive C items. A meal cannot be served by a restaurant if a key ingredient is missing. Therefore, it is necessary to control all parts, even the C items.
The traditional EOQ is not useful in MRP systems, although modified lot-sizing formu- las are available. The assumptions used to derive the traditional EOQ are badly violated by the lumpy demand patterns for component parts. Lot sizing in MRP systems should be based on discrete requirements. For example, suppose that the demand for a particular part by week over the next six weeks is 0, 30, 10, 0, 0, and 15. Further assume that the EOQ is calculated to be 25 parts. With the EOQ or multiples of the EOQ, we could not match the requirements exactly and therefore would end up with remnants in inventory. These rem- nants from the EOQ cause unnecessary inventory carrying costs. It would be far better to base lot sizes on the discrete demand observed. For example, with a lot-for-lot policy, we could order 30 units for the second week, 10 for the third week, and 15 for the sixth week, resulting in three orders and no carrying costs. We could also order 40 units for the second and third weeks combined, thereby saving one order but incurring a small carrying cost. With MRP systems, various discrete lot sizes need to be examined.
The objective in managing independent demand inventories with reorder-point rules is to provide a high customer service level at low inventory operating costs. This objective is oriented toward the customer. In contrast, the objective in managing dependent demand inventories with MRP is to support the master production schedule. This objective is man- ufacturing oriented; it focuses inward rather than outward.
15.3 PARTS EXPLOSION: HOW AN MRP SYSTEM WORKS
The easiest way to understand MRP is to focus on the parts-explosion process itself. Sup- pose that tables of the type shown in Figure 15.2 are being manufactured. The finished table consists of a top and a leg assembly. The leg assembly in turn consists of four legs, two short rails, and two long rails. In this particular example, leg assemblies are built in
LO15.3 Construct a materials plan given the gross requirements.
These auto parts are subject to dependent demand. Barry Willis/Getty Images
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328 Part Five Inventory
advance and stored in inventory. This procedure permits the table to be produced faster, as orders are received, than it could be if the table were completely assembled from individ- ual parts. It is common practice in manufacturing firms to build assemblies for inventory to reduce total production lead time and save setup costs.
The bill of materials (BOM) for this table is shown schematically in Figure 15.3. The finished table is at the first level of the bill, and is called the end item or finished product. The leg assembly and tabletop are at the second level, since these parts are assembled together to produce a finished table. The pieces that go into the leg assembly are all listed at the third level. We are assuming that the parts for this table are purchased from outside; otherwise there would be a fourth level in the BOM for the wood used to make the legs, rails, and top.
Another piece of information needed before parts explosion is the planned lead times for manufactured and purchased parts, as shown in Table 15.2. For planning purposes, it takes one week to assemble the finished table from the leg assembly and top. This planned lead time includes average waiting time due to interference from other jobs, which is usu- ally much longer than the actual working time. Similarly, Table 15.2 shows that two weeks are planned for purchase of a tabletop from the time the order is placed until the tabletop is in the factory. One week of lead time is required to purchase the table legs and rails, and one week needed for leg assembly.
It is now possible, using parts explosion, to construct a materials plan for the finished tables and all parts. The resulting materials plan is shown in Table 15.3. Now, we will walk through the line-by-line calculations for finished tables shown in the first panel at the top of Table 15.3.
FIGURE 15.3 Bill of materials (quantity per unit shown in parentheses).
Table
Top (1)
Leg assembly (1)
Long rails (2)
Legs (4)
Short rails (2)
FIGURE 15.2 Table example. Top
Leg assembly
Leg
Long railShort rail
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Weeks
Assemble table* 1 Finished leg assembly† 1 Purchase legs 1 Purchase short rails 1 Purchase long rails 1 Purchase top 2
*Assume the tabletop and complete leg assembly are available. † Assume the legs, short rails, and long rails are available.
Line 1: Gross requirement is the demand for finished tables: 200 in week 4, 150 in week 5, and 100 in week 6. Line 2: The scheduled receipts for tables are zero for all weeks in this case. Scheduled receipts consist of tables currently being made and expected to be completed from past shop orders. Line 3: There are currently 50 tables on hand. Projected Ending Inventory is 50 for each of the first three weeks, since we are not planning to use any inventory during these weeks. Line 4: Net requirement is just the gross requirement minus the projected ending inventory at the end of the previous week. In this case in week 4 the net requirement is 200 − 50 = 150. We use the on-hand inventory from week 3 to meet some of the gross requirement in week 4; the rest of the gross requirement is now listed as a net require- ment. Since there is no on-hand inventory carried over for week 5 or 6, the net require- ment equals the gross requirement in those two weeks. Line 5: Planned order receipt for 150 tables is entered in week 4 and is the same as the net requirement in that week since we are assuming lot-for-lot (L4L) production. L4L means every net requirement is met by a planned order receipt of the same amount in that period. Likewise, the planned order receipts for week 5 are 150 and for week 6 are 100, the same as the net requirements in those weeks. Line 6: Planned order releases are offset by one period for the table lead time (from Table 15.2). This means we will release the order so it arrives one week later as a planned order receipt. In this case, orders are planned to be released using the one week offset for 150 tables in week 3, 150 in week 4, and 100 in week 5.
The weeks in the materials plan are such that the current week (in other words, today) is always within week 1. This means that after the current week has passed, what is currently listed as week 2 will become week 1, and a new planning week is added at the far end of the schedule. Note, all quantities are assumed to occur at the beginning of each week, except projected ending inventory that occurs at the end of the week.
Now, step back and look at the first panel in Table 15.3. You can see that the 200 tables required in week 4 are translated into a net requirement of 150 tables, since there are 50 finished tables in inventory. Using L4L logic, the planned order receipts in week 4 are also 150 tables. Using the one-week offset in lead time we get a planned order release of 150 tables in week 3. In a similar way, the gross requirements for weeks 5 and 6 are netted for zero projected inventory and then entered as planned order receipts and offset by a one- week lead time to ultimately get planned order releases of 150 in week 4 and 100 in week 5. This is the logic of MRP.
Next, the planned order releases for tables are used to calculate gross requirements for tops and leg assemblies at the next level down in the BOM. The planned order releases for
TABLE 15.2 Planned Lead Times
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330 Part Five Inventory
tables (level 1) are transferred to gross requirements for tops and leg assemblies (both at level 2) on a one-for-one basis, since it takes one tabletop and one leg assembly to make a table (see arrows in Table 15.3). The projected ending inventory and scheduled receipts for table tops and leg assemblies are subtracted from the gross requirements to arrive at net requirements. The net requirements are then entered as the same planned order receipts using L4L logic. The planned order receipts are offset by lead time to arrive at planned order releases for tabletops and leg assemblies. Notice that in Table 15.3, 50 tabletops are currently on hand and 50 are scheduled to arrive in week 2. These arrivals increase the projected ending inventory in week 2 to 100 units total. Since we have 100 tops available in inventory, we only have a net requirement of 50 more tops to meet the gross requirement of 150 tops in week 3. Using L4L logic and a two-week offset (for the lead time) leads to a planned order release of 50 tops in week 1.
Week
1 2 3 4 5 6
Tables On hand = 50 Gross requirement 200 150 100 LT = 1 wk Scheduled receipts Lot size: L4L Projected ending inventory 50 50 50 Safety stock = 0 Net requirement 150 150 100
Planned order receipts 150 150 100 Planned order releases 150 150 100
Tops On hand = 50 Gross requirement 150 150 100 LT = 2 wk Scheduled receipts 50 Lot size: L4L Projected ending inventory 50 100 Safety stock = 0 Net requirement 50 150 100
Planned order receipts 50 150 100 Planned order releases 50 150 100
Leg assembly On hand = 100 Gross requirement 150 150 100 LT = 1 wk Scheduled receipts Lot size: L4L Projected ending inventory 100 100 Safety stock = 0 Net requirement 50 150 100
Planned order receipts 50 150 100 Planned order releases 50 150 100
Leg X4 On hand = 150 Gross requirement 200 600 400 LT = 1 wk Scheduled receipts 100 Lot size: L4L Projected ending inventory 150 50 Safety stock = 0 Net requirement 550 400
Planned order receipts 550 400 Planned order releases 550 400
Short rail X2 On hand = 50 Gross requirement 100 300 200 LT = 1 wk Scheduled receipts Lot size: L4L Projected ending inventory 50 Safety stock = 0 Net requirement 50 300 200
Planned order receipts 50 300 200 Planned order releases 50 300 200
Long rail X2 On hand = 0 Gross requirement 100 300 200 LT = 1 wk Scheduled receipts Lot size: L4L Projected ending inventory Safety stock = 0 Net requirement 100 300 200
Planned order receipts 100 300 200 Planned order releases 100 300 200
TABLE 15.3 Materials Plan— Parts Explosion
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Once we have completed the calculations in Table 15.3 for tops and leg assemblies, we are ready to finish the material plan. The planned order releases for leg assemblies are used to compute gross requirements for legs, short rails, and long rails. The planned orders for leg assemblies are multiplied by 4 for legs, by 2 for short rails, and by 2 for long rails to arrive at gross requirements. A gross requirement at any level is the amount of material required to support planned order releases at the next-highest level. The gross-to-net calcu- lation and the offset for lead time are then performed for each of the three remaining parts to arrive at planned order releases. This completes the parts explosion.
Table 15.3 has been constructed from the master schedule down, one level at a time, through the BOM. The materials plan for each level in the BOM was completed before moving down to the next level. For each part, the gross requirements have been reduced by projected ending inventory and scheduled receipts to arrive at net requirements. The net requirements have been entered as planned order receipts and then offset (planned earlier) by the lead time to arrive at planned order releases. By the process of netting and offset- ting, the master schedule is converted to planned order releases for each part required.
What does the materials plan in Table 15.3 tell us? While most of the plan helps with record keeping, the planned order releases will require action. Currently, only orders in week 1 must be dealt with. First, we should immediately release purchase orders to our sup- pliers for 50 tops, 50 short rails, and 100 long rails since these are the planned order releases at the beginning of week 1. The materials plan also gives us the planned order releases for each week in the future. If the master schedule and all other conditions remain constant, the planned orders will be released when the time comes. For example, in week 2 we plan to release an order to the shop to complete 50 leg assemblies. If the materials arrive as planned, we will have on hand the legs and rails needed for this shop order: 200 legs, 100 short rails, and 100 long rails. In addition to the shop order for 50 leg assemblies, we plan to release, in week 2, purchase orders for 150 tops, 550 legs, 300 short rails, and 300 long rails. These mate- rials will be needed to support future leg-assembly and table-assembly shop orders.
This example illustrates the construction of a time-phased materials plan. All purchase orders and shop orders are interrelated to provide materials when needed. If the actual lead times can be managed to meet the planned lead times, there will be no unnecessary inventory accumulations or wasted time waiting for materials in the shop, and the orders for delivery of finished tables will be shipped on time.
As a matter of fact, once any initial inventories are depleted, no finished goods invento- ries will be planned by the MRP system using the L4L approach. This is the case because we have planned production to just equal final demand, after adjusting for available inventories. Likewise, no purchased-parts inventories are planned after initial inventories and sched- uled receipts are depleted. Unless safety stocks are added for uncertainties or economic lot sizes are used to smooth out production levels, no inventory will be planned except work in process required for assembly or fabrication. The logic embedded into the MRP system assumes parts are available exactly when they are needed to support the production plan.
Lot sizing is very important in MRP to achieve economical production lots and purchas- ing orders. As a result, a fixed or calculated lot size may be used for each level in the mate- rial plan rather than an L4L approach. For illustration purposes, Table 15.4 shows a fixed lot size for the finished tables and table tops. We assume the economic lot size for finished tables is 200 tables and the economic lot size for ordering tops is 300 tops. We also assume that a safety stock of 50 units is planned for the table tops, but it won’t be used until needed. This safety stock provides protection for late deliveries by the table top supplier.
The revised material plan is shown in Table 15.4. In period 4 we have a gross require- ment of 200 tables and a net requirement of 150 tables, as before. However, the lot size is 200 tables, so the planned order receipts to assemble tables will be 200, leaving a projected
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332 Part Five Inventory
ending inventory of 50 tables at the end of period 4. In period 5 the gross requirement is for 150 tables, leaving a net requirement of 100 tables after using the 50 tables in inven- tory. Using the lot size of 200 we must assemble 200 tables, which leaves a projected end- ing inventory of 100 tables at the end of period 5. This inventory of 100 tables just meets the gross requirement for period 6, so there are no additional planned order receipts. The planned order receipts are now offset by a one-period lead time to yield planned order releases of 200 in period 3 and 200 in period 4. These planned order releases now become gross requirements for the tops (see arrow in Table 15.4).
This changes the gross requirements for tops from the prior L4L calculations. Proceed- ing ahead, we subtract the safety stock of 50 tops from the on-hand inventory, to give a projected ending inventory of zero tops in period 1. This simply takes safety stock out of the calculations going forward. Then 50 tops are scheduled receipts in period 2 leaving a projected ending inventory of 50 at the end of period 2. We then complete the calculations for purchasing tops in Table 15.4 by netting and offsetting. Notice, by ordering the fixed quantity of 300 units at a time, we end up with planned order releases of 300 tables in peri- ods 1 and 2 instead of the smaller planned orders we had with L4L lot sizing.
15.4 MRP SYSTEM ELEMENTS
Although parts explosion is the heart of the MRP system, it takes a good deal more to make an MRP system work. An MRP system needs several elements to be successful. We describe these elements more formally next.
Master scheduling drives the entire materials planning process. The master schedule has been described as “top management’s handle on the business.” By controlling the master schedule, top management can control customer service, inventory levels, and manufacturing costs. Top managers cannot perform the master scheduling task by themselves because there are too many details; therefore, they often delegate the task to a cross-functional team. However, top manag- ers can set master scheduling policy, thereby controlling the materials planning function.
Top management’s primary interface with manufacturing is through the aggregate pro- duction plan (or S&OP) shown at the top of Figure 15.1. The aggregate production plan deals with families of products or product lines, not specific products, models, or options that are
LO15.4 Describe in detail each element of an MRP system.
Master Scheduling
Week
1 2 3 4 5 6
Tables On hand = 50 Gross requirement 200 150 100 LT = 1 wk Scheduled receipts Lot size = 200 Projected ending inventory 50 50 50 50 100 Safety stock = 0 Net requirement 150 100
Planned order receipts 200 200 Planned order releases 200 200
Tops On hand = 50 Gross requirement 200 200 LT = 2 wk Scheduled receipts 50 Lot size = 300 Projected ending inventory 50 150 250 250 250 Safety stock = 50 Net requirement 150 50
Planned order receipts 300 300 Planned order releases 300 300
TABLE 15.4 Material Plan with Lot Sizing
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in the master schedule. For example, if a manufacturer such as John Deere makes a variety of tractors, the aggregate production plan might contain various types of tractors but not the particular size of engine, hydraulics options, or other features that the customer can select. Thus, the master scheduling process accounts for the overall aggregate production plan, which has already been established, or seeks to modify this plan if it is discovered, for example, that capacity is not available.
The master schedule might extend into the future for a year or more. It must extend at least beyond the longest cumulative production lead time to ensure that sufficient time is available to order all parts and make the finished product. Gen- erally speaking, the master schedule should be frozen inside the cumulative pro- duction lead time to prevent unnecessary scrap and expediting due to changes during the production cycle.
Rarely is the master schedule a reflection of future demand forecasts. Rather, the master schedule is a forecast of what will be produced. It is a “build” sched-
ule. Finished goods inventory is a buffer between the master schedule and final customer demand, smoothing out workloads and providing fast customer service.
The BOM is a structured list of all the materials or parts needed to produce a particu- lar finished product, assembly, subassembly, manufactured part, or purchased part. The BOM serves the same function as a recipe used for cooking: It lists all the ingredients. It would be foolish to allow errors to creep into your favorite cooking recipes. The same is true for a BOM. If there are errors in the BOM, the proper materials will not be ordered and the product cannot be assembled and shipped on time. As a result, the other parts that are available will wait in inventory while the missing parts are expedited. Man- agement must therefore insist that all BOMs are 100 percent accurate. Experience has shown that it is not too costly to have 100 percent accuracy; rather, it is too costly to tolerate imperfect BOMs.
Some firms have several BOMs for the same product. Engineering has one BOM, man- ufacturing has a different version, and cost accounting has still another. An MRP system requires a single BOM for each product to be used by all individuals in the firm. The BOM in the MRP system must be the correct one, and it must represent how the product is manufactured. In firms where the BOM has been used as a reference document and not a materials-planning tool, this concept of a single bill is very difficult to implement.
BOMs are constantly undergoing change as products are redesigned. Thus, an effective engineering-change-order (ECO) system is needed to keep the BOMs up to date. Usually an ECO coordinator must be appointed and charged with the responsibility for coordinat- ing all engineering changes with the various departments involved.
A typical computerized inventory record includes the following data segments. The item master data segment contains the part number, which is the unique item identifier, and other information: lead time, standard cost, and so on. The inventory status segment con- tains a complete materials plan for each item over time. Finally, the subsidiary data seg- ment contains information concerning outstanding orders, requested changes, detailed demand history, and the like.
In practice, constant effort is required to keep inventory records accurate. Traditionally, inventory accuracy has been ensured by an annual physical inventory count, where the plant is shut down for a day or two and everything is counted from wall to wall. Because inexperienced people are often doing the counting, as many errors are introduced by this procedure as are corrected. After the inventory is taken, the total inventory in dollars is accurate for financial purposes because the plus and minus errors cancel out. But the
Bill of Materials (BOM)
Inventory Records
Cloud computing facilitates MRP systems. ImageFlow/Shutterstock
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334 Part Five Inventory
counts of individual items are usually not accurate enough for mate- rial planning. As a result, cycle counting has been developed as a substitute for the annual physical inventory.
With cycle counting, a small percentage of the items are counted each day by storeroom personnel. Errors are corrected in the records, and an attempt is made to find and correct the procedure that caused them. By developing a high regard for accuracy and adopting daily cycle counting, firms can eliminate most errors in inventory records. The result is so reliable that many auditors no longer require an annual physical inventory when an effective cycle-counting system is in place.1
The purpose of capacity planning is to aid management in checking on the validity of the master schedule. There are two ways this can
be done: shop loading or finite capacity scheduling. When shop loading is used, a full parts explosion is run before capacity planning. The resulting shop orders are then loaded against work centers through the use of detailed parts-routing data. As a result, workforce and machine hours for each work center are projected into the future. If sufficient capacity is not available, management should adjust either capacity or the master schedule until it is feasible. At this point, a valid materials plan is available.
An alternative to shop loading is scheduling to finite capacity. Finite capacity schedul- ing establishes a work schedule to be produced in a certain time period, considering rele- vant limitations of resources. Software has been developed to implement methods for forward scheduling to finite capacity. An MRP system can, therefore, be modified to start with a feasible finite capacity schedule, and materials are planned to arrive in time to sup- port the feasible schedule.
The purchasing function in the firm is helped by the use of an MRP system. Past-due orders are largely eliminated because an MRP system generates valid due dates and keeps them up to date.
By developing and executing a valid materials plan, management can eliminate much of the order expediting that usually is done by purchasing. This allows the purchasing manag- ers to concentrate on their primary function: qualifying suppliers, looking for alternative sources of supply, and working with suppliers to ensure delivery of quality parts, on time, at low cost.
With an MRP system, it is possible to provide suppliers with reports of planned future orders. This gives them time to plan capacity before actual orders are placed. The practice of giving suppliers planned orders interlocks them more closely with the firm’s own materials plan and helps to coordinate the supply chain. Many firms have gone so far as to insist that their suppliers also install MRP systems so that their delivery reliability can be more readily ensured. Also, electronic data interchange (EDI) and cloud-based systems are being used to transmit planned order releases by an MRP system directly to suppliers.
The purpose of the shop-floor control subsystem is to release orders to the shop floor and manage the orders on their way through the factory to make sure they are completed on
1 Accounting students should take note of this concept, since they are likely to encounter cycle counting in practice.
Capacity Planning
Purchasing
Shop-Floor Control
Cycle counting ensures accuracy of inventory records. Alistair Berg/Digital Vision/Getty Images
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time. The shop-floor control system helps management adjust to all the day-to-day things that go wrong in manufacturing: absenteeism among workers, machine breakdowns, loss of materials, and so on. When these unplanned complications arise, decisions must be made about what to do next. Good decision making requires information on job priorities from the shop-floor control system, also called a manufacturing execution system (MES).
Job priorities are calculated by dispatching rules that determine the sequence of work to be performed. Dispatching rules (e.g., first come, first served) are particularly useful when there is more than one job waiting to be processed by a resource. When these dispatching rules are used as part of the shop-floor control system, it is possible to adjust to changing conditions and still get the work out on time. Through the use of dispatching rules, a job’s production lead time can be drastically cut or increased as it goes through the shop. This is possible because a job normally spends as much as 90 percent of its time waiting in queues. If a job is behind schedule, its priority can be increased until it gets back on schedule. Similarly, a job can be slowed down if it is ahead of schedule. It is the function of the shop-floor control system to provide information to managers so that they can manage production lead time dynamically.
Lead times can be managed by expanding or contracting them on the basis of priority. This concept has been popularized by the old saying, “Lead time is what you say it is.” This is a very difficult concept to accept when managers are used to thinking in terms of fixed lead time or lead times as random variables.
It is possible through a shop-floor control system to de-expedite orders—that is, to slow them down. This is not done in normal manufacturing, where orders are expedited but never de-expedited. Orders should be slowed down when the master schedule is changed or when other parts will not be available on time. This results in the minimum inventory consistent with MRP timing requirements.
15.5 OPERATING AN MRP SYSTEM
There is much more to the MRP system than just installing the proper software modules. Management must operate the system in an intelligent and effective way.
One of the decisions management should make is how much safety stock to carry. To the surprise of many managers, little safety stock is needed if the MRP system is properly used. This is due to the concept of lead time management, where both purchasing and shop lead times are effectively controlled within small variances. In purchasing, this is done by developing relationships with suppliers who provide reliable deliveries. In the shop, lead times can be managed by a shop-floor control system as described above. Once the uncer- tainty in lead time is reduced, there is much less need for safety stock.
If safety stock were carried at the component-part level, a great deal of it would be needed to be effective. Suppose, for example, that 10 parts are required to make an assem- bly and each part has a 90 percent service level. The probability of having all 10 parts on hand when needed is only 35 percent.2 It is much better, therefore, to plan and control the timing of the 10 parts than to cover all contingencies with safety stock. When safety stock is carried, it often is added at the master schedule level. This ensures that matched sets of components, not simply an assortment of various parts, are available for final products. The purpose of safety stock at the master schedule level is to provide flexibility to meet changing customer requirements.
Safety lead time is a concept that should be considered for component parts. If a sup- plier is unreliable and the situation cannot be remedied, the planned lead time can be
LO15.5 Discuss DRP and different ways to deal with uncertain demand.
2 Probability = (.9)10 = .35, assuming parts availabilities are independent events.
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336 Part Five Inventory
lengthened by adding safety lead time. This will add to overall inventory levels, however, when the supplier delivers within the original lead time.
A third way of handling uncertainty is to plan for safety capacity. This approach means planning production levels below the actual capacity. The extra capacity is used to respond to uncertainties such as late supplier delivery or incorrect production order size. The prob- lem with safety stock is that it is frequently available for the wrong parts—too much of one part and too little of another. Thus, serious consideration should be given to safety capacity as an alternative to safety stock; this has not been widely done in industry. Rather, safety stock (inventory) has been considered an asset, even if it is never used, and high capacity utilization is a desirable goal, even if excess inventories result.
Management must also decide on the scope of its MRP application. MRP can be extended in the supply chain through distribution all the way to the final customer. In this case the application is called distribution requirements planning (DRP). When DRP is implemented, for example in retail, it can start with the retailer who makes a forecast of future demand and then does a time-phased plan by netting inventory and offsetting lead times to pass planned orders on to the wholesaler. The wholesaler in turn aggregates all planned orders from various retailers as its gross requirement and then constructs a time- phased plan by netting inventory and offsetting lead times to arrive at planned orders for the manufacturer. In this way the entire downstream supply chain is linked together.
The same logic can be applied to upstream suppliers. The manufacturer can provide time- phased planned orders to its first tier suppliers to give them visibility about future demands. The first tier supplier can use these planned orders as gross requirements together with planned orders from other customers in its MRP system. The first tier supplier then constructs a time- phased material plan by netting inventory and offsetting lead time to provide planned orders to second tier suppliers and so on. This links the manufacturer to the upstream supply chain.
There must be sufficient safety stock in the system to prevent a tightly linked system from becoming “nervous.” Every small change in future downstream planned orders should not trigger an immediate change in the master schedules of the suppliers. This would cause too many small changes in the supply chain, only to be adjusted later when conditions change once again.
15.6 THE SUCCESSFUL MRP SYSTEM
The logic embedded in an MRP system is relatively simple and straightforward. But, some firms have tried to implement and deploy an MRP system without success. For the MRP system to be successfully implemented and consequently deployed, at least five issues must be addressed.
Implementation planning must, first and foremost, be a prerequisite to any effort to implement and deploy an MRP system. Unfortunately, too many firms jump in and start implementing MRP without adequate preparation. Advanced planning and problem- prevention efforts can help smooth out implementation efforts.
Second, there must be appropriate and adequate IT support available. An adequate com- puter system is probably one of the easiest elements of MRP to implement. Today, there are approximately 100 MRP software packages on the market. Most firms use these stan- dard packages rather than writing their own software.
Third, an MRP system requires accurate data. Some firms are accustomed to lax record keeping in manufacturing because they have always been managed by informal systems. But accurate data are required when decisions are made from information supplied by the MRP system. Accurate data include inventory records, bills of materials, and the master schedule.
LO15.6 Explain the five requirements for a successful MRP system.
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Fourth, the importance of management support to the successful MRP system cannot be overemphasized. But management support requires more than lip service and passive sup- port on the managers’ part. “Management participation” or “leadership” would be a better phrase. The ultimate change required by management at all levels is to use the system, not to override it by management edicts and arbitrary decisions.
The fifth and final requirement for the successful MRP system is user knowledge at all levels of the firm. An MRP system requires an entirely new approach to manufac- turing. All employees must understand how they will be affected and grasp their new roles and responsibilities. All supervisors, middle managers, and top managers need to understand the MRP system including those inside and outside of manufacturing. As the MRP system is broadened in scope, the extent of training within the firm must be broadened too.
There is tremendous room for the application of MRP system elements in the service industry. If the bill of materials is replaced by a bill of labor or a bill of activities, one can explode the master schedule of output into all the activities and personnel required to deliver a particular mix of services. Some service operations will also require a bill of materials when materials are an important part of the goods-services bundle.
As an example, one electric utility has been using an MRP system for several years in the electric hookup part of its business. When a new customer requests electrical ser- vice, a planner enters the request into a computer system for the type of service required. The computer then explodes this service request into detailed labor, material, and work activities. Each of these requirements is time-phased and accumulated over all jobs to determine whether sufficient capacity is available. When the time comes, the utility hookup crews are given work orders from the system output, and completed work is entered back to the system. The MRP system then drives billing, labor-reporting, and other accounting systems.
15.7 ENTERPRISE RESOURCE PLANNING SYSTEMS
So far, we have been discussing the use of MRP systems in manufacturing and ser- vice operations. While MRP is the base for operations planning and control, it can also be extended into all other business functions through the use of an enterprise resource planning (ERP) system. For example, MRP transactions can be fed directly to the accounting and finance system. Accounting transactions can be seen as putting MRP transactions into
LO15.7 Describe what an ERP system does.
MRP systems can be used for services too. In renovating hotel rooms, Marriott develops a bill of materials and a bill of labor for each room type and then “explodes” the bill throughout the hotel facility to summarize its furniture and decorating needs. Onoky/SuperStock
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338 Part Five Inventory
dollars-and-cents terms. Accounting control in dollars is closely related to control of the physical units and the physical flow of inventory in operations.
Likewise, an ERP system is useful for linking marketing to operations. Marketing and sales transactions should be closely integrated as inputs to the MRP through order entry. Often, marketing and sales systems are developed and designed as separate systems that are not fully integrated with the MRP system in operations. As a result, the functions of marketing and operations are isolated from an information systems point of view.
Finally, transactions in a manufacturing or service firm should be integrated with its human resource system. This takes place not only through payroll transactions but also through recruiting and selection activities as well. For example, when operations makes a decision to expand capacity by hiring more people, this decision should be fed directly to the HR system and the hiring process should be tracked through to completion. The payroll system should pick up the new people hired by operations, and these employees should be followed through their lifetime of employment.
When operations, finance/accounting, marketing/sales, and HR systems are integrated through a common database, the ERP system is completed. The ERP system will track transactions from their origin at the customer, to order entry, through operations and accounting until the transaction is completed. Also, all decisions made in one function will be apparent to other functions and reflected in their information systems. No longer will the various functional information systems be isolated; rather, they will be integrated through a common database.
For example, the type of ERP system we have been discussing has been developed by SAP, a German firm. SAP has hundreds of thousands of customers across 180 coun- tries and serves numerous industries with software and cloud services. One advantage of the SAP system is that it can be tailored to different firms and industries. Standard processes, including order entry, payroll, MRP, inventory management, accounts pay- able, and accounts receivable, have been designed into the SAP system. Each firm can select those processes that fit its needs and customize them to its particular business (see Table 15.5).
An ERP system integrates data across functions in the firm. This list shows some of the many functions supported by SAP’s ERP package.
Financial Systems Operations and Logistics Accounts receivable and payable Inventory management Asset accounting Materials requirements planning Cash management and forecasting Materials management Cost-element and cost-centered accounting Plant management Executive information system Production planning Financial consolidation Project management General ledger Purchasing Product-cost accounting Quality management Profitability analysis Routing management Profit-center accounting Shipping Standard and period-related costing Vendor evaluation
Human Resources Sales and Marketing Human resources accounting Order management Payroll Pricing Personnel planning Sales management Travel expenses Sales planning
TABLE 15.5 ERP: Cross- Functional Integration Through Data Sharing
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LG continues to expand their system, as needed. Build- ing a single centralized system that integrates available modules for uniform use at a global level replaces their previous dependency on local systems.
Source: www.lg.com/us, 2020.
Global giant LG Electronics, based in Korea, has 114 subsidiaries and more than 82,000 employees across 40 countries. In the past, data management challenges made it difficult for LG to operate as a global company. They continue to develop and expand their ERP system to meet their needs.
LG’s past challenges included local information sys- tems leading to unclear reporting, local processes lack- ing transparency and automation, limited sharing of best practices, difficulties with decision making, and disen- gaged employees.
Their ERP solution has supported the following benefits: centrally managed system with minimal maintenance costs, transparency in processes, easy sharing of best practices across locations, and real-time reporting for upper man- agement for informed decision making. Employee morale, productivity, and engagement have improved.
Their ERP system enables LG to mitigate the chal- lenges posed by their numerous global locations. Today,
LG Electronics Inc.
Operations Leader
Oracle is another ERP software vendor. Cleveland Clinic, a leader in health care deliv- ery, uses Oracle systems in their domestic and international locations. Systems developed specifically for the health care industry are designed to benefit back-office personnel, medical professionals, and patients. The systems are used to enhance financial forecast- ing, revenue management, and data integration across functions. For operations, the Ora- cle modules support supply procurement and inventory management. See the Operations Leader box about use of ERP at LG Electronics.
ERP systems are the basis for cross-functional integration. When all functions share information through a common database the functional silos are minimized and functions can communicate effectively with each other. Once ERP systems are fully operating inside a firm they can be integrated with suppliers and customers. A variety of information can be exchanged to help coordinate decisions along the supply chain. Supply chain coordination can take the form of Collaborative Planning and Forecasting and also planning for new product introductions with suppliers and customers.
Many firms have determined that their existing information systems, which have grown up separately, can no longer meet the needs of the business and must be inte- grated through an ERP system. ERP system implementation, however, is expensive, time-consuming, risky, and nontrivial. ERP system implementation failures are not uncommon. For example, Avon abandoned its ERP implementation in 2013 after having spent over $125 million, and Waste Management ended up in court while suing (and being counter-sued by) SAP from a failed implementation. ERP implementation is a worthwhile endeavor with great benefits; realizing these benefits requires careful planning, signifi- cant resources, and patience in execution.
Kobby Dagan/123RF
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340 Part Five Inventory
15.8 KEY POINTS AND TERMS
This chapter describes MRP and ERP systems for managing dependent demand inventory. The major points include the following:
∙ An MRP system is an information system used to plan and control manufacturing of dependent demand inventory items.
∙ The parts-explosion process has three principal inputs: master schedule, bill of materi- als (BOM), and inventory records. There are two principal outputs: purchase orders and shop orders. Parts explosion is the heart of the MRP system.
∙ An MRP system follows a requirements philosophy—parts are ordered only as required by the master schedule. Past demand for parts is irrelevant, and component inventories are not replenished when they reach a low level.
∙ Master schedules should be based on both marketing and production considerations. They should represent a realistic build plan within factory capacity. Management should use the S&OP and master schedule to plan and control the business through a cross-functional planning team.
∙ The BOM contains the list of parts used to make the product. To maintain the accuracy of the BOM, an engineering-change-order system is needed.
∙ The accuracy of the inventory record system should be maintained through cycle count- ing. Daily cycle counting can be used in place of annual physical inventory count.
∙ Shop-floor control is used to control the flow of materials through the factory. This is done by managing lead times dynamically as the product is manufactured. If lead times are properly managed, much safety stock can be eliminated.
∙ A successful MRP system requires (1) implementation planning, (2) adequate IT support, (3) accurate data, (4) management support, and (5) user knowledge. Both system and people problems must be solved to use MRP successfully. When this is done, benefits include reduced inventory, increased customer service, and improved efficiency.
∙ Enterprise resource planning systems integrate a basic MRP system with informa- tion from marketing, sales, finance/accounting, and human resources through a com- mon database. ERP systems can be the basis for cross-functional and supply chain integration.
Key Terms Materials requirements planning (MRP) 323
Master schedule 324 Parts explosion 324 Dependent demand 326 Bill of materials 328 Planned lead times 328 Materials plan 328 Gross requirements 329 Net requirement 329
Cycle counting 334 Shop loading 334 Manufacturing execution
system 335 Safety lead time 335 Safety capacity 336 Distribution requirements
planning (DRP) 336 Enterprise resource planning
(ERP) 337
Planned order receipt 329 Lot-for-lot (L4L)
production 329 Planned order releases 329 Time-phased materials
plan 331 Purchase orders 331 Shop orders 331 Engineering-change-
order 333
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Chapter 15 Materials Requirements Planning and ERP 341
1. MRP a. Using the information given below, develop a complete MRP material plan.
A (1) End item (lead time = 1)
B (1) Component B (lead time = 2)
C (2) Component C (lead time = 1)
It takes one unit of B and two units of C to make one unit of A. At the beginning of time period 1, the following information is available:
Item ID Quantity on Hand Lead Time
A 100 1
B 150 2
C 80 1
The gross requirements of item A are 200 units for period 4 and 250 units for period 5. Use L4L lot size planning.
b. If the lead time for item A increases by one week and the lead time for item C also increases by one week, what will the revised materials plan look like? Are there any problems that need immediate attention?
c. Returning to the material plan for part a, what is the effect of using lot sizes of 200 for all items A, B, and C? You many use multiples of 200 when needed to satisfy planned order receipts.
SOLVED PROBLEM
LEARNING ENRICHMENT (for self-study or instructor assignments)
SAP ERP System Website https://www.sap.com/products/enterprise-management-erp.html
Oracle ERP System Website https://www.oracle.com/applications/erp/what-is-erp.html
Example of Using an MRP System Video https://youtu.be/BItcIuapE6g 6:57
Elements in a Bill of Materials Website https://www.thebalancesmb.com/bill-of-materials-2221363
ERP Solutions for Manufacturing Video https://youtu.be/YA68olpZbk8 2:09
Problem
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342 Part Five Inventory
a. The MRP materials plan is as follows:
Week
1 2 3 4 5
Item A On hand = 100 Gross Requirement 200 250 LT = 1 wk Scheduled Receipts Lot size: L4L Projected Ending Inventory 100 100 100 Safety Stock = 0 Net Requirement 100 250
Planned order receipts 100 250 Planned order releases 100 250
Item B On hand = 150 Gross Requirement 100 250 LT = 2 wk Scheduled Receipts Lot size: L4L Projected Ending Inventory 150 150 50 Safety Stock = 0 Net Requirement 200
Planned order receipts 200 Planned order releases 200
Item C On hand = 80 Gross Requirement 200 500 LT = 1 wk Scheduled Receipts Lot size: L4L Projected Ending Inventory 80 80 Safety Stock = 0 Net Requirement 120 500
Planned order receipts 120 500 Planned order releases 120 500
b. The revised MRP materials plan is as follows:
Week
1 2 3 4 5
Item A On hand = 100 Gross Requirement 200 250 LT = 2 wk Scheduled Receipts Lot size: L4L Projected Ending Inventory 100 100 100 Safety Stock = 0 Net Requirement 100 250
Planned order receipts 100 250 Planned order releases 100 250
Item B On hand = 150 Gross Requirement 100 250 LT = 2 wk Scheduled Receipts Lot size: L4L Projected Ending Inventory 150 50 Safety Stock = 0 Net Requirement 200
Planned order receipts 200 Planned order releases 200
Item C On hand = 80 Gross Requirement 200 500 LT = 2 wk Scheduled Receipts Lot size: L4L Projected Ending Inventory 80 Safety Stock = 0 Net Requirement 120 500
Planned order receipts 120 500 Planned order releases 500
Solution
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Chapter 15 Materials Requirements Planning and ERP 343
Yes, there is a problem that needs immediate attention. Item C is behind schedule and will need to be expedited immediately to ensure that 120 units of C are avail- able in week 2. Alternatively, the master schedule could be revised to accommo- date the availability of item C. Combinations of these two alternatives could also be considered. c. The revised materials plan is as follows. Note, although the lot size is 200, we need
to order two lots for item C of 200 each to exceed net requirements for this product.
Week
1 2 3 4 5
Item A On hand = 100 Gross Requirement 200 250 LT = 1 wk Scheduled Receipts Lot size = 200 Projected Ending Inventory 100 100 100 100 50 Safety Stock = 0 Net Requirement 100 150
Planned order receipts 200 200 Planned order releases 200 200
Item B On hand = 150 Gross Requirement 200 200 LT = 2 wk Scheduled Receipts Lot size = 200 Projected Ending Inventory 150 150 150 150 150 Safety Stock = 0 Net Requirement 50 50
Planned order receipts 200 200 Planned order releases 200 200
Item C On hand = 80 Gross Requirement 400 400 LT = 1 wk Scheduled Receipts Lot size = 200 × 2 Projected Ending Inventory 80 80 80 80 80 Safety Stock = 0 Net Requirement 320 320
Planned order receipts 400 400 Planned order releases 400 400
Discussion Questions 1. In what ways do independent demand inventories differ
from dependent demand inventories? 2. Why is demand history irrelevant for the management
of raw materials and work-in-process inventories? 3. With regard to inventory management, discuss the
difference between a replenishment philosophy and a requirements philosophy.
4. Can ABC inventory classification be applied to manu- facturing component inventories? Discuss.
5. How much safety stock should be carried in an MRP system? What is the role of safety stock in MRP sys- tems? Where should safety stock be carried?
6. Describe the advantages of cycle counting over an annual physical inventory count.
7. Is it possible to control financial totals without physical control of materials in manufacturing?
8. A company president said his firm is too small to afford an MRP system. Discuss.
9. A materials manager said that her firm needs only a replenishment inventory management system. What would you tell her about the additional capabilities of an MRP system?
10. Describe how MRP concepts could be used for the fol- lowing service operations:
a. Hotel b. Legal office 11. How are MRP and ERP related?
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344 Part Five Inventory
Three Excel spreadsheets are provided on Connect for assistance in solving the chapter problems 1. The following information is given for a particular part.
Using a lead time of two weeks, complete the table. Use L4L with On hand = 80 and SS = 0.
Week
1 2 3 4 5
Gross requirement 100 400 300 Scheduled receipts 50 Projected ending inventory 80 Net requirement Planned order receipts Planned order releases
2. Using the original information in problem 1, complete the table again, but this time assuming that the supplier requires a fixed lot size of 500 units.
3. Again using the original information in problem 1 and L4L, complete the table with a requirement of safety stock of 100 units.
4. The Old Hickory Furniture Company manufactures chairs on the basis of the BOM
shown below. At the present time, the inventories of parts and lead times are as follows:
Chair
SeatLeg assembly
Legs (4)
Rails (4)
Back assembly
Spindles (4)
Top
On Hand Weeks of Lead Time
Chairs 100 1 Leg assembly 50 2 Back assembly 25 1 Seat 40 3 Rails 100 1 Legs 150 1 Top 30 2 Spindles 80 2
The firm would like to produce 600 chairs in week 5 and 300 chairs in week 6.
a. Develop a materials plan for all the parts using L4L. b. What actions should be taken now? c. Assume it takes one hour to assemble backs, one
hour to assemble legs, and two hours to finish com- pleted chairs. Total assembly time for all three types of assembly is limited to 1000 hours per week. Will this capacity constraint cause a bottleneck in assem- bly? If it does, what can be done?
d. What is the effect of changing the master schedule to 300 chairs in week 5 and 400 chairs in week 6?
5. Product A consists of subassemblies B and C. Subas- sembly B requires two parts of D and one part of E. Subassembly C requires one part of D and one part of F.
a. Draw a product structure tree (BOM) for this product.
b. How many parts are needed to make 300 units of finished product?
6. The BOM for product A is given below:
Part On Hand Weeks of Lead Time
A 75 1 B 150 2 C 50 1 D 100 2
A
C(2)
D D(2) B
Assume the master schedule calls for 200 units of product A in week 5 and 250 units in week 6. Use L4L.
a. Develop a materials plan for this product. b. What actions should be taken immediately? c. Project the inventory ahead for each part. d. If you were suddenly notified that part D will take
three weeks to get instead of two weeks, what actions would you take?
7. The master scheduler in the ABC Widget Company is in the process of revising the master schedule. At the present time, he has scheduled 400 widgets for week 5 and is considering changing this to 500 widgets.
a. What information would you need to decide whether you should make this change?
Problems
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b. Suppose that each widget takes one hour of press time and three hours of assembly time three weeks before delivery. Can the additional 100 widgets be made in view of the following shop loadings?
Press Hours Maximum available500
Pr es
s S ho
p H
ou rs
b y
W ee
k
400
300
200
100
0 1 2 3 4 5
Week
Assembly Hours Maximum available
A ss
em bl
y H
ou rs
b y
W ee
k
800
600
400
200
0 1 2 3 4 5
Week
c. If the additional widgets cannot be made in part b above, what actions might be taken to make it pos- sible to produce the required widgets?
8. A firm makes a basic scissors consisting of three parts: the left side, the right side, and the screw that holds the sides together. At the present time, the firm has the fol- lowing numbers of parts on hand and on order. The lead times for reorder of each part are also shown along with a BOM and a sketch of the scissors.
Scissors
ScrewLeft side
Right side
On Hand Weeks of
Lead Time Scheduled Receipts
Scissors 100 1 Left side 50 2 100 in week 2 Right side 75 2 200 in week 2 Screw 300 1 200 in week 1
a. Assume the master schedule calls for 200 scissors to be shipped in week 4 and 500 in week 5; work out a complete materials plan using L4L.
b. Suppose the supplier of right-hand sides calls to say that deliveries of the 200 parts on order will be one week late. What effect will this have on the materi- als plan?
c. If demand for scissors is uncertain and has a stan- dard deviation of 50 units, what would you recom- mend the firm do to maintain a 95 percent service level for scissors?
d. If the delivery of the scissors parts is unreliable and the standard deviation of delivery lead time is one week for each of the parts, what would you recommend the firm do to maintain its production schedule?
9. A lamp consists of a frame assembly and a shade, as shown below in the sketch and
the bill of materials. The frame is made from a neck, a socket, and a base, which are assembled together from purchased parts. A shade is added to the frame assem- bly to make the finished lamp. The number of parts on hand, the parts scheduled to arrive, and the lead times to obtain more parts are shown below.
Lamp
FrameShade
Neck BaseSocket
On Hand Weeks of
Lead Time Scheduled Receipts
Lamp 200 1 — Frame 100 2 — Neck 0 1 — Socket 300 1 — Base 200 1 — Shade 400 3 —
a. Assuming 1000 finished lamps are required in week 5 and 1500 in week 6, construct a complete materials plan for the lamp using L4L. What actions should be taken immediately to implement the plan?
b. If it takes 15 minutes of assembly time to assemble the parts into the frame and 5 minutes to assemble the shade and frame into a finished lamp, how much total assembly time is required in each week? What can be done if insufficient time is available in any given week?
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c. If the lead time for assembly of lamps is extended from one week to two weeks, what changes will be needed in the materials plan to adjust for this change?
10. A telephone is assembled from a handset and a base. The handset in turn is assembled from a handle and a cord, and the base is assembled from a case, a circuit board, and a face plate. A BOM and a sketch of the phone, along with the numbers of parts on hand and lead times, are shown as follows.
Phone
BaseHandset
CordHandle Face plate
Case Circuit board
On Hand Weeks of Lead Time
Phone 200 1 Handset 300 1 Handle 250 2 Cord 75 2 Base 250 1 Case 225 2 Circuit board 150 1 Face plate 300 2
a. Management would like to start assembling phones as soon as possible. How many phones can be made from the available parts, and when can they be delivered? Construct a materials plan to show your answer.
b. For the materials plan constructed in part a, develop an inventory projection of parts and finished goods on a week-by-week basis using L4L.
c. Suppose another 100 circuit boards can be obtained within one week. What effect will this have on your answer for part a?
11. A small toy robot is assembled from six parts: a body, a head, two arms, and two legs. The firm uses a one-level bill of materials to assemble this product. The number of parts on hand and the lead times (weeks) to obtain more parts are shown below. There are no parts on order.
Toy robot
On Hand Lead Time
Body 25 2 Head 50 1 Arm 60 2 Leg 80 1
a. Assume that an order for 200 robots is received now for delivery at the beginning of week 4 and that it takes one week to assemble the parts once they are all available. Construct a complete materials plan for the robots using L4L. What actions should be taken immediately to implement the plan?
b. The customer has called and asked if he could receive a portion of the 200 robots as soon as possible. How many robots can be assembled and delivered to him ASAP, and when would they arrive? What are the implications of this action?
c. The supplier of heads has just sent an e-mail that said it will take two weeks to deliver the heads instead of one week. What effect will this have on your materials plan from part a?
12. Using the information from problem 11, complete the plan for the robot parts assuming that a fixed lot size of 400 units is required for all parts.
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16. Supply Chain Management
17. Sourcing
18. Global Logistics
This part deals with external supply chain decisions that connect operations to its suppliers and customers. The first chapter addresses general supply chain issues, followed by sourcing and global logistics chapters. Sourcing connects operations with its service and manufacturing suppliers. Logistics deals with moving materials, either from operations to customers or suppliers to operations. ■
vi
Pa rt
Supply Chain Decisions
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Supply Chain Management
16 c h a p t e r
After reading this chapter, you should be able to:LEARNING OBJECTIVES
LO16.1 Define supply chain and supply chain management.
LO16.2 Review key measures of supply chain performance.
LO16.3 Explain the bullwhip effect and how it can be reduced.
LO16.4 Contrast structural and systems improvements.
LO16.5 Evaluate the effect of technology on the supply chain.
LO16.6 Discuss supply chain risk, resilience, and how risk can be managed.
LO16.7 Describe supply chain sustainability.
You probably never thought about the everyday impact and importance of supply chains. Americans eat an average of five pounds of food every day. A small city of 100,000 people requires 500,000 pounds of food shipped every day, assuming no inventory buildup or reduction. This is a huge amount of food that must be transported from the farm all the way to restaurants or tables in homes. The fresh fruit, meats, and vegetables are refrigerated and have a short shelf life. They require special and fast transportation from the farm to packaging plants, to deconsolidation warehouses and then finally to the retail stores. Other products, such as packaged foods, travel by train, ocean, and truck through manufacturing, distribution centers, and retail stores until they reach your table. The global food supply chain must be reliable, low cost, and resilient to disruptions (e.g., natural and human disas- ters). This is no small task and supply chain managers make it happen every day.
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In this chapter, we introduce the subject of supply chain management, which has gener- ated a great deal of interest recently in industry and academia. There are several reasons for this sudden interest. First, the total time for materials to travel through the entire supply chain can be six months to a year or more. Since the materials spend so much time waiting in inventory, there is a great opportunity to reduce the total supply chain cycle time, leading to a corresponding reduction in inventory, increased flexibility, reduced costs, and better deliv- eries. Also, many companies have improved their internal operations dramatically and now find it necessary to consider relations with external customers and suppliers in the supply chain to gain further improvements in operations. Finally, supply chain thinking is an appli- cation of systems thinking and provides a basis for understanding processes that cut across a company’s internal departments and processes that extend outside the company as well.
16.1 SUPPLY CHAIN AND SUPPLY CHAIN MANAGEMENT
Supply chain management is an essential aspect of business today. To understand what sup- ply chain management entails, we first provide a formal description of a supply chain. Although a supply chain generally can be depicted without specifying a vantage point, it is often more useful to show a supply chain from the perspective of a firm, a factory, a service delivery unit for a firm, a product family (e.g., automobiles), or even a type of service (e.g., outpatient surgeries). Figure 16.1, for example, shows the entire supply chain for an organiza- tion called F, the focal entity. The organization F, in this case, can be the entire firm or a specific factory or hotel property. The various nodes or ovals represent other facilities through which materials and requisite information flow for the product that F sells to end customers.
The flow of materials from upstream nodes into the focal entity generally is referred to as physical supply and the flow of materials from F through downstream nodes toward
LO16.1 Define supply chain and supply chain management.
FIGURE 16.1 A typical supply chain from the perspective of a focal entity, F.
Upstream or Backward Materials and Information Flow
2nd-Tier Suppliers
1st-Tier Suppliers
Distribution Centers and Warehouses
Retailers
Downstream or Forward Materials and Information Flow
Physical Supply Physical Distribution
F Focal entity
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350 Part Six Supply Chain Decisions
the end customers is referred to as physical distribution. Distribution channel, a term frequently used in marketing, is a specific route from a producer (in this case, F) forward through the various nodes (e.g., distributors and wholesalers) to the end customer and is therefore only part of the supply chain for F. Notice also that the physical supply for the focal entity can be segmented further into tiers such that 1st-tier suppliers have a direct linkage (represented by an arrow) to F, 2nd-tier suppliers have a linkage to F through 1st- tier suppliers, and so on. Similarly, the focal entity has linkages to downstream entities (distributors and wholesalers) as part of its physical distribution. Each entity in Figure 16.1 ideally plays a value-added role in transforming materials and services into the desired final product for the customer while passing along relevant information. The Operations Leader box titled “Apple’s iPhone” describes the integrative roles that different players assume in bringing forth today’s increasingly complex products.
A large company will have several supply chains. For example, large companies such as Procter & Gamble and General Electric may use 20 to 40 different supply chains to bring their products to market. Some of these supply chains use distribution through company- owned warehouses, some use direct distribution, some use outside manufacturing, and some use in-house manufacturing sites. The elements in a supply chain can be arranged in many different ways.
A company can identify its supply chains by first selecting a particular product group or product family. Then it should trace the flow of materials and information from the final customer (end user) backward through the distribution system to the manufacturer and then to the suppliers and the sources of raw materials. This entire chain of activities and processes constitutes the supply chain for that product group.
Armed with this understanding of a supply chain, a useful definition of supply chain management (SCM) taken from the Institute for Supply Management is as follows:
Supply chain management is the design and management of seamless, value-added processes across organizational boundaries to meet the real needs of the end customer.
Many high-tech consumer products are not manufactured by the companies whose brands they carry, but instead are manufac- tured by a host of other companies that act as 1st-tier, 2nd-tier, and 3rd-tier suppliers. The iPhone design, software develop- ment, chip design, and marketing are done in the U.S. by Apple. The manufacturing is outsourced to Taiwan, China, Korea, Japan, and Singapore along with other countries. The iPhone is being assembled by the millions of units in China by FoxConn, a huge Taiwan-based electronics company. Taiwan Semiconductor Man- ufacturing Company (TSMC), provides Apple’s custom-designed chip—the most important hardware component of the phone. The digital camera modules, internal circuitry, Bluetooth chip- sets, screen controllers, and other components are provided by 2nd- and 3rd-tier suppliers. This illustrates the complex and global supply chain used by Apple.
Sources: “The Global Supply Chain behind the iPhone,” Beta News, 2015; and Apple A12 processor, wikipedia.com, 2020.
Apple’s iPhone
OPERATIONS LEADER
adrianhancu/123RF
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SCM, by this definition, involves a sequence of value-added processes that not only cut across organizational boundaries but also must be tightly integrated. To be integrated, the processes must be appropriately designed and systematically managed to allow informa- tion to flow and be deployed within and across them. The design and management of these processes therefore require that decisions be made to implement strategies and solve problems to ensure an effective and efficient flow of materials and requisite information across the entire supply chain. These strategies and problem resolutions are intended to reduce uncertainty across the entire supply chain. Taking a systems perspective is therefore paramount so that strategies and problem resolutions to reduce uncertainty at one node do not end up negatively affecting another node. In Section 16.3, we demonstrate more clearly the system dynamics inherent in supply chains and explain why supply chains and their management must be viewed in a holistic fashion.
The SCOR or Supply Chain Operations Reference model is described in the Operations Leader box. This model defines the processes of plan, source, make, deliver and return that apply to each organization in the supply chain. By providing a common reference model, supply chain designers in each organization can refer to the processes needed in a uniform manner that allows for integration of the supply chain. The SCOR model is an essential tool used for supply chain design across organizations.
Besides defining SCM from a process or decision-making orientation, many schol- ars and managers define SCM as the integration of three traditionally separate functions: sourcing (purchasing), operations, and logistics. With respect to our example, sourcing is the function that deals with the physical supply to ensure the flow of materials and infor- mation into the focal entity, operations is the function that produces the product or service, and logistics is the function that designs and manages the physical transportation of mate- rials both inbound into the focal entity and outbound from it.
What has to be emphasized is that in recent years the three functions of sourcing, opera- tions, and logistics have evolved and taken on responsibilities for materials and informa- tion flow. As a result, there has been a blurring of what duties, decisions, and problems belong to sourcing or operations or logistics. For example, what used to be known as the Council of Logistics Management has been renamed the Council of Supply Chain Man- agement Professionals to reflect a broadened definition of logistics management that is identical to that of SCM. Similarly, the National Association of Purchasing Managers has changed its name to the Institute for Supply Management (ISM).
16.2 MEASURING SUPPLY CHAIN PERFORMANCE
While it is useful to think of a supply chain when one is considering the set of activities needed to manufacture a product or deliver a service, measuring its performance cannot be done in isolation from the various entities that make up the supply chain for a particular product or service. Measuring the performance of a supply chain therefore must be done one company at a time from each company’s individual perspective, along with a few mea- sures that are applicable to the entire supply chain. From the standpoint of supply chain measurement, each company can derive its own performance measures, which in turn are affected by its supply chain partners. Finally, the performance of a company within a sup- ply chain can affect the performance of the other companies as well.
For example, suppose a manufacturing company has three kinds of inventory: raw materials, work in process, and finished goods. The level of raw-materials inventory is a function of the suppliers’ lead times and the safety stock needed to handle variance in lead times and demand. Therefore, raw-materials inventory depends on the suppliers in the
LO16.2 Review key measures of supply chain performance.
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352 Part Six Supply Chain Decisions
supply chain. Similarly, finished-goods inventory is a function of the logistics lead time in shipping the product to the customer, the producer’s lead time in refilling inventory, and the customer’s variance in demand. Both the company and the customer influence the level of finished-goods inventory. Work-in-process inventory, however, is the most control- lable component of inventory by the manufacturing company itself and is a function of
materials into a finished product. The Deliver process is the set of activities involved in order entry, materi- als handling, and transporting of goods and services to
meet demand. The Return process is the set of activi- ties for handling returns of goods. Level 1 of the SCOR model also establishes performance objectives and targets for performance.
Level 2 (Configuration Level) establishes 26 core supply chain process categories that can be deployed to configure the actual or an ideal operational structure of a firm’s supply chain. Level 3 (Process Element Level) provides information at the process level (e.g., inputs/ outputs, process metrics) to help firms compete in the marketplace. Finally, Level 4 (Implementation Level) helps firms identify and implement specific supply chain management practices.
A major advantage of the SCOR model is that it pro- vides a common framework and lexicon for interorgani- zational communication and efforts aimed at improving performance of the entire supply chain.
Source: Adapted from www.aims.education/study-online/ supply-chain-operations-reference-model-scor/, 2020.
The SCOR, or “Supply Chain Operations Reference,” model represents a cross-industry process framework and standard for defining what SCM entails. In this
respect, it seeks to play the same role that ISO 9000 or the Baldrige Award plays with respect to total quality management.
SCOR was introduced in November 1996 by the Supply- Chain Council consisting of 69 firms. The 69 member firms worked for six months to define common supply chain management processes, best practices for those processes, and benchmark performance data.
The current version of the SCOR model is rep- resented as a four-level pyramid, with Level 1 (Top Level) defining SCM to encompass management of five distinct processes—Plan, Source, Make, Deliver, and Return. The Plan process refers to the develop- ment of a course of action (i.e., strategy) for balancing demand and supply while meeting the requirements of sourcing, production, and delivery. The Source pro- cess refers to the set of activities involved in procur- ing materials and services to meet planned or actual demand. Make refers to processes that transform
SCOR Model
OPERATIONS LEADER
Plan
Suppliers’ Supplier
Customer’s Customer
Supplier Customer
Your Company
Internal or External Internal or External
Plan
Source Make Deliver Deliver Source Make Deliver
Return Return Return
DeliverSource SourceMake
Return Return Return
Return Return
Plan Plan Plan
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the company’s throughput time to convert raw materials into finished goods. Therefore, in measuring supply chain performance, we must remember that each member of the supply chain should measure its own performance but that performance is highly influenced by other supply chain members.
While there are many metrics for measuring supply chain performance, they generally correspond to delivery, quality, flexibility, and cost measures of operations discussed pre- viously. These measures are made by each individual firm, but as noted are influenced by the other firms in the supply chain. There are, however, three measures that stretch across the entire supply chain: throughput time, cash-to-cash, and total delivered cost. These mea- sures reflect the performance of the entire supply chain as a whole.
1. Throughput time can be measured not only for an individual company but also for the entire supply chain. The total supply chain throughput time is just the sum of the throughput times (also called cycle times) of each of the entities in the supply chain. For example, if the throughput time of the supplier is 5 weeks, the throughput time of the producer is 10 weeks, and the delivery time to the customer is 2 weeks, the total sup- ply chain throughput time is 17 weeks. If there is a constant usage rate from inventory, the throughput time is the inventory level divided by the usage rate (an application of Little’s Law). For example, if the inventory level is $10 million and we sell (or with- draw) $100,000 per day, we have 100 days of throughput time. The throughput time in each part of the supply chain (supplier, manufacturer, wholesaler, and retailer) is added to get the supply chain total throughput time.
2. Cash-to-cash cycle time.1 However, it is also important to consider the time it takes to get paid for the product once it is sold. It is not enough to have low inventories; the company must also get the cash from sales so that it can use the money to make and sell more products. Cash-to-cash cycle time is a frequently used measure to gauge how quickly a firm is paid by its customers relative to how quickly it has to pay its suppliers. Cash-to-cash cycle time can be computed as follows:
Cash-to-cash cycle time = Days in inventory + Days in accounts receivable – Days in accounts payable
For example, suppose a firm has 35 days of inventory, 40 days in accounts pay- able and only 10 days in receivables. Then the cash-to-cash cycle time is only 5 days (35 + 10 − 40). They receive the cash very quickly from customers (low receivables), while delaying payments to suppliers (high payables).
3. Total delivered cost. Cost, from an operations point of view, generally refers to the unit cost of the product or service. Unit cost is defined as the total manufacturing cost, including materials, labor, and overhead, divided by the number of units produced. Sup- pliers heavily influence the unit cost, since often more than 50 percent of costs are accounted for by purchased materials.
Cost is a measure that also can be analyzed for the supply chain as a whole. Each entity adds cost as the product is moved along the supply chain. There are costs of materials and components from suppliers. The producer adds a certain amount of cost to fabricate and assemble the product. Cost is added by logistics to ship materials and work-in-progress between firms in the supply chain and ship the finished-goods inven- tory to the customer. The sum of all of these costs is the total delivered cost.
1 Also called the cash conversion cycle (CCC)
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354 Part Six Supply Chain Decisions
A supply chain has the following information.
Notice in this example that the sourcing cost to the factory is the supplier sales unit price ($18), the sourcing cost to the wholesaler is the sales unit price from the factory ($82), and the sourcing cost to the retailer is the sales unit price from the wholesaler ($107). Therefore, each entity passes its costs plus a profit down the supply chain.
a. Calculate the total supply chain throughput time for all entities from beginning to end. b. Compute the cash-to-cash cycle time for each of the four entities separately. Based on
this calculation, who is benefiting the most? c. Compute the total delivered cost in the supply chain from beginning to end. How much
profit is there in the supply chain?
ANSWER:
a. Total supply chain throughput time = 20 + 60 + 30 + 20 = 130 days b. Supplier cash-to-cash time = 20 + 30 − 45 = 5 days Factory cash-to-cash time = 60 + 45 − 30 = 75 days Wholesale cash-to-cash time = 30 + 30 − 60 = 0 days Retail cash-to-cash = 20 + 40 − 47 = 13 days The wholesaler is benefiting the most with 0 days cash-to-cash c. Total delivered cost = $10 + 5 + 50 + 15 + 40 = $120 Total profit = $3 + 14 + 10 + 14 = $41
Note, to get total delivered cost we start with the sourcing cost (unit + added) and then just sum the added cost at each stage. This calculation takes out all the profit at each stage. Adding total profit ($41) back into total delivered cost ($120) equals the retail selling price ($161), as it should.
Example
Supplier Factory Wholesale Retail
Inventory in days 20 60 30 20
Accounts receivable in days 30 45 30 40
Accounts payable in days 45 30 60 47
Sourcing unit cost $10 $18 $82 $107
Added unit cost $5 $50 $15 $40
Sales unit price $18 $82 $107 $161
The information from this example can be used for analysis of the supply chain.
1. How can the length (throughput) time of the supply chain be shortened? What will be the impact of reducing throughput time by each of the entities?
2. Who is benefiting the most in the supply chain from the cash-to-cash time? What can be done in terms of inventory, payables, and receivables times to improve the cash-to-cash for various entities?
3. Who is profiting the most from the supply chain and where are costs too high? Is it possible to change contracts or even vertically integrate to make the supply chain more efficient and profitable for certain entities?
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Calculating these measures is the first step in conduct- ing an analysis, along with collecting the cost, quality, flexibility, and delivery measures of each individual entity.
It is important for a company to set goals for the four separate measurement areas (cost, quality, delivery, and flexibility) with respect to improving its own perfor- mance. A company should also meet with its suppliers and customers to set supply chain improvement goals as a group. It is important that the whole supply chain be improved, not just one portion. Also, improvement in the company’s part of the supply chain could work to the detriment of other parts and needs to be coordinated for overall system benefit. For example, if a company unilaterally cuts its finished-goods inventory, it could reduce its cost but increase stockouts, affecting its abil- ity to supply its customers. Alternatively, a company
could reduce its inventory by reducing its throughput time and also working with suppliers and logistics to reduce their throughput times. This could benefit the entire supply chain.
16.3 SUPPLY CHAIN DYNAMICS—THE BULLWHIP EFFECT
The entities in a supply chain are interrelated by the very fact that they send materials and information up and down the supply chain. The decisions they make and the actions they take can have a substantial impact on each other. These interrelationships define the dynamics that we often observe in any supply chain, with one specific manifestation of supply chain dynamics being the bullwhip effect.
The bullwhip effect describes the increasing variability in orders that are received by entities upstream in a supply chain, which in turn affects the amount of inventory that those entities hold. The bullwhip effect (also called the accelerator effect) has been observed in numerous industries ranging from consumer products to pharmaceuticals to electronics. The bullwhip effect takes its name from Procter & Gamble executives who first saw the effect on ordering baby diapers, a relatively fixed-demand item. Yet, orders at the factories, whole- sale, and retail levels exhibited much more variance than final consumer demand. Hewlett- Packard also observed an upstream increase in variance of orders and inventories for printers.
To illustrate the bullwhip effect, consider the four-tier supply chain shown in Figure 16.2. The retailer, which is closest to the market demand, observes the demand and places orders to its 1st-tier supplier. The retailer orders correspond to the demand for the 1st-tier supplier. The 1st-tier supplier in turn orders from the 2nd-tier supplier, and so on. At the same time, because there is the replenishment lead time involved in producing and delivering products, each entity in this four-tier supply chain also holds inventory. By doing so, each entity is aiming to fulfill demand quickly (i.e., the orders an entity receives) from inventory since orders do not have to wait to be produced.
In Figure 16.2, we see that the retailer suddenly creates a spike in orders to the 1st-tier sup- plier typically due to increased demand at the retail level. When we compare the magnitude of the variability of the orders placed by the retailer with those placed by the 1st-tier supplier, with those placed by the 2nd-tier supplier, and with those placed by the 3rd-tier supplier, an interesting pattern emerges. As we move farther and farther back from the market or up the supply chain, the variability of orders placed by upstream entities becomes magnified.
LO16.3 Explain the bullwhip effect and how it can be reduced.
Dell computer has one of the smallest cash-to-cash cycles in its industry due to low inventories, low receivables, and high payables. Norasit Kaewsai/123RF
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356 Part Six Supply Chain Decisions
The farther away a supply chain entity is, the greater is the variability of orders it places. The same pattern of upstream magnification of order variability also describes inventory levels and stockouts across the four entities in this supply chain. Because the entities in the supply chain are not synchronized to match the market demand observed by the retailer, the varying order sizes received by the various entities result in an accumulation of inven- tory at times and in shortages and delivery delays at other times. The bullwhip effect thus affects not only the performance of the individual entities in a supply chain but also that of the supply chain in its entirety.
FIGURE 16.2 The bullwhip effect. Source: Adapted from J. Nien- haus, A. Ziegenbein, and P. Schoensleben, “How Human Behaviour Amplifies the Bull- whip Effect. A Study Based on the Beer Distribution Game Online,” Production Planning and Control 17, no. 6 (2006), pp. 547–557.
Orders Placed Inventory Levels
Time 0
5 10 15 20
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2nd-Tier Supplier
3rd-Tier Supplier
Time –60 –70
–50 –40 –30 –20 –10
0 10 20 30 40 50 60 70 80
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5 10 15 20
Retailer
1st-Tier Supplier
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Why is the bullwhip effect so common across indus- tries? One reason is that supply chain entities farther upstream may not have or be granted access to actual market demand. Instead, they use forecasts to guide their initial decisions and actions and use actual orders received to make adjustments to those decisions and actions. When forecasts are inaccurate, the initial decisions and actions do not match actual market demand, creating situations of feast or famine. Another reason is the replenishment lead time (i.e., the time between when an order is placed and when an order is received) that each entity faces. When a supply chain entity faces substantial replenishment lead time, it may have no choice but to hold safety stock as a buffer against unexpected large orders. A third reason is the delay in sharing information up and down the supply chain. However, even if the retailer in Figure 16.2 is very
willing to share market demand data up the supply chain this will not solve the problem as long as there are lead times in filling orders. When demand increases at the retailer, for exam- ple, the 1st-tier supplier not only must fill the larger order but also must replenish its inventory, leading to larger orders passed on to the 2nd-tier supplier and so on up the supply chain. This explains the order amplification seen upstream in the supply chain.
To summarize, the supply chain example depicted in Figure 16.2 illustrates five key points about supply chain dynamics:
1. The supply chain is a highly interactive system. Decisions in each part of the supply chain affect the other parts.
2. A bullwhip (or accelerator) effect often is observed in supply chains. Upstream enti- ties in the supply chain (e.g., warehouses and the factory) react to inflated orders from downstream entities that are closer to the market by placing even larger orders upstream and carrying inventory. These inflated orders distort the true demand information (quantity change, timing of change, etc.) observed in the market.
3. Even with perfect information available to all levels, the bullwhip effect can be observed in a supply chain because of long replenishment lead times between the entities in the sup- ply chain and potentially long lags in sharing information up and down the supply chain.
4. The best way to improve the supply chain is to reduce the total replenishment lead time and feed back actual demand information to all levels as quickly as possible. The physi- cal and information time lags in the supply chain only serve to create fluctuations in orders and inventories.
5. Marketing can reduce demand spikes by using everyday low pricing instead of sales and discounts that create temporary spikes in retail demand. Alternatively, forecasts for spe- cial planned retail promotions and discounts could be sent in advance to upstream entities.
Research results of simulation studies with over 4000 participants shows how human behavior also amplifies the bullwhip effect.2 Managers tend to over compensate due to chang- ing orders and inventory. Two human strategies caused amplification in the supply chain.
1. Safe harbor: When orders increase, managers order more than necessary to increase safety stocks because they are afraid of running out of inventory. This forces suppliers to also
2 J. Nienhaus, et.al, op. cit.
Retail supply chains are exposed to the bullwhip effect. Jonathan Nackstrand/AFP/Getty Images
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order more inventory and may cause upstream stockouts temporarily. Thus, a safe harbor causes increased orders and inventory magnification upstream on the whole supply chain.
2. Inventory panic: When orders decrease, managers reduce inventories thinking they are too high and costly. Subsequently, when downstream demand increases, the effect is to order more due to low safety stock. As a result, upstream tiers often run out of inventory and are unable to fill orders for some days. This also magnifies the effect of demand changes. As noted above, there are several ways to reduce the bullwhip effect by sharing informa-
tion, or reducing replenishment lead times or changing retail pricing behavior. By doing this the bullwhip will be reduced but not eliminated, since managerial behavior for a safe harbor or inventory panic is still present. The role of human behavior in causing the bull- whip must also be considered.
16.4 IMPROVING SUPPLY CHAIN PERFORMANCE
To improve supply chain performance, greater coordination must be attained not only within firms but also across firms. The typical firm is organized into functional silos, with different departments managing different aspects of the supply chain. For example, sourcing takes care of the suppliers and raw-materials inventory, operations takes care of manufacturing and work-in-progress inventory, and marketing manages demand and finished-goods inventory. When these departments lack coordination, as they often do, there are dramatic effects on the supply chain within the firm as well as beyond the firm.
Within-firm and across-firm coordination can be increased by changing and improving either the structure or the systems used to manage supply chains. Changes in supply chain structure relate to the products and services offered, the types and locations of facilities, process technology and layouts, and vertical integration. These are changes in the physi- cal elements of the supply chain and often require major investments. Changes in supply chain systems are changes in people and processes such as the use of teams and partner- ships, lean systems, and information systems used to plan and improve the supply chain.
Whether the intended improvement is in supply chain structure or supply chain systems, the goal of any improvement initiative should be to facilitate increased coordination to reduce either uncertainty or total replenishment lead time and the total cost of supplying the market. Only when uncertainty in demand or in supply times can be reduced along the chain is the need for inventory also reduced. For example, in the extreme case in which demand uncertainty is zero and resupply is completely reliable, no inventory is needed except for that in transit. The material can be scheduled to arrive just as it is needed by the next entity in the supply chain. Likewise, when the total replenishment lead time in the supply chain is reduced, the supply chain as whole can react more flexibly and rapidly to real demand changes, again reducing the investment that the supply chain needs to make in inventory.
16.5 SUPPLY CHAIN STRUCTURAL IMPROVEMENTS
Changes in supply chain structure rearrange the elements of the supply chain, usually with a major and dramatic effect. These changes are frequently long-range in nature and require considerable capital. Changing and improving supply chain structure can be accomplished in a number of different ways, including the following: 1. Forward and backward integration 2. Major process simplification 3. The configuration of factories, warehouses, or retail locations 4. Major product redesign
LO16.4 Contrast structural and system improvements.
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Forward integration and backward integration refer to ownership within the supply chain. If a manu- facturer, for example, decides to buy a wholesale firm and distribute its products only through that wholesaler, the integration is forward toward the market. If the manufacturer buys a supplier company, the integration is backward in the supply chain. If one firm owns the entire supply chain, there is total vertical integration.
Zara is a global clothing retail chain based in Spain that has engaged aggressively and successfully in verti- cal integration in support of its more than 2200 cloth- ing stores in over 96 countries. By integrating across design, production, distribution, and retailing, Zara is a rebel in an industry in which the norm is to outsource all production activities to countries with the lowest labor costs. By owning its own production facilities, Zara is able to dictate 85 percent of what is made while in-season, often with small batch runs. Because that is coupled with IT investments in capturing and transmit- ting demand information across its supply chain, Zara
can respond quickly to changing market trends, with the design-to-store-delivery cycle time being as fast as just two weeks.
In addition to the substantial time-to-market benefits, vertical integration reaps the profits of suppliers or distributors provided that there is an attractive return on investment. Vertical integration also has drawbacks, however, such as loss of flexibility to changing technology and possible loss of economies of scale. Nevertheless, forward and backward integration decisions can be evaluated like any other investment choice of the firm and may be the key to improving supply chain performance.
Major process simplification is used to improve supply chains when the processes are so complex or out of date that a major change is required. In this case, a clean-slate approach is used in which the processes are designed from scratch without regard for the existing processes. This could include using the SCOR model to make major con- ceptual changes in how business is conducted and major changes in information systems. For example, consider the changes 3M made in its Post-it Notes supply chain. The plant implemented a pull system driven by customer demand, which utilized quick changeovers, daily replenishment of branch stock, and responsive production scheduling based on daily customer demand. This resulted in a 99 percent fill rate, work-in-process inventory of less than one day, a reduction in machine changeovers from two hours to 13 minutes, and a reduction in new product introductions from 80 days to less than 30 days.
The third way to restructure supply chains is to change the number and configuration of suppliers, factories, warehouses, or retail sites. Sometimes the distribution system is no longer configured in the right way. For example, many companies have determined that they have too many suppliers and are reducing the number of suppliers by one-half or more (supply base reduction). This is being done to partner with the best suppliers to ensure JIT deliveries and certified sources of material. Another structural change of this type has occurred in Europe as it became a more unified market. As a result, companies found that they needed fewer plants and warehouses in different locations. A complete reconfigura- tion of the production and distribution facilities has occurred at many companies.
Changing the configuration of a supply chain often involves practices such as outsourcing and off-shoring. Off-shoring occurs when a firm moves work performed internally to another facility belonging to the same firm but in another country. Outsourcing occurs
Zara vertically integrates to respond quickly to changing market needs. TonyV3112/Shutterstock
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when work that traditionally has been performed internally is delegated to another firm, whether that firm is in the same country or in another country. When an activity is trans- ferred from a domestic facility to the facility of another firm in another country, the label “off-shore outsourcing” is most appropriate. U.S. manufacturers today are engaged in off- shore outsourcing, with major subsystems of complex products being designed and manu- factured by a global cadre of firms. While labor cost is a major motivating factor, it is by no means the only reason firms outsource. See the Operations Leader box titled “Boeing 787 Dreamliner” for Boeing’s approach to developing and manufacturing the 787 aircraft.
Major product redesign is often another initiative needed to make improvements in the supply chain. Some companies have found that they have too many different product varia- tions and types, some with extremely low sales. As a result, product lines are trimmed and redesigned to be more modular in nature. For example, Hewlett-Packard found that it had to make many different models of laser printers because of the different power require- ments in different countries. To get around the problem, the company decided to have a laser printer design with a swappable power supply module that could be inserted at the last minute to configure the printer for the particular country where it would be used. Except for the swappable power supply module, all other parts of the laser printer remained com- mon across countries. This postponement strategy saved the company millions of dollars.
Boeing 787 Dreamliner unique in that the design of the airplane involved cooperation from an international cast of top-tier strategic supply partners who are supplying approximately 50 percent of the parts making up the air- plane with the other 50 percent made in the U.S.A. and assembled in Everett, Washington, and its South Carolina factory with non-USA parts transported to the plants by road, rail, sea, and plane for final assembly.
The list of offshore outsourcing companies and associated parts includes such venerable partners as Messier-Dowty (France) for electric brakes, Rolls-Royce (United Kingdom) and General Electric (USA) for engines, Alenia Aeronautica (Italy) for the horizontal stabilizers, Mitsubishi Heavy Industries (Japan) for the wing box, and Chengdu Aircraft Group (China) for the rudder. The decision to involve these strategic partners was moti- vated not so much by design and production cost as by technological expertise and the promise of new business from airlines in the respective countries of these major suppliers. Air Nippon Airways was the first to take deliv- ery of the Boeing 787, with at least another 1150 air- plane orders having been received from 60 other airlines around the world.
Source: Adapted from aerospaceweb.org/aircraft/jetliner/ b787 and www.businessinsider.com, 2020.
The 787 Dreamliner is Boeing’s super-efficient commer- cial airplane. The 787 Dreamliner has three models—the 787-8, 787-9 (larger), and the 787-10 (largest). After three years of delays, the aircraft finally started flying customers in December 2011. By 2018 more than 781 787’s were delivered.
There are several aspects that make the Boeing 787 Dreamliner impressive besides its fuel-efficient perfor- mance. For one, the airplane is manufactured using 50 percent composite material. By comparison the 777 uses only 10 to 12 percent. The product development process and the global supply chain also make this
Boeing 787 Dreamliner
OPERATIONS LEADER
Jordan Tan/123RF
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Other global firms have followed in Hewlett-Packard’s footsteps by incorporating mod- ularity into the designs of their products. Modular product designs have catalyzed the pur- suit of mass customization and allowed those firms to realize many operational benefits, including simpler process flows, less process complexity, lower inventory investments, and lower unit cost. In addition, these firms have been able to reconfigure their supply chains since the type of modularity incorporated has implications for the selection of suppliers, the way they are managed, the contracts to pursue with suppliers, and their proximity.
16.6 SUPPLY CHAIN SYSTEM IMPROVEMENTS
Changes to improve the supply chain system are made within a specific structure or con- figuration of the supply chain. These changes are considered to be on the “soft” side of the supply chain regarding people, processes or information systems. They involve changing the way the supply chain operates within the structural arrangements. This means that decisions about issues such as vertical integration, the number and type of factories and warehouses, and major product and/or process designs have already been made.
This, however, does not mean that initiatives to improve the supply chain system cannot have a major impact. The objective of supply chain system improvement initiatives is the same: to remove sources of uncertainty, time, and cost from the supply chain. Improve- ments in the supply chain system can be just as dramatic and just as important as improve- ments that effect supply chain structural change. While numerous initiatives to improve supply chain systems are available, we focus on the following three:
1. Cross-functional teams and partnerships with suppliers and customers. 2. Lean systems 3. Information systems
The use of cross-functional teams is pervasive in many businesses today. Their purpose is to provide coordination that is lacking across the various departments and functions of a business. For example, a cross-functional team often is used to conduct Sales and Operations Planning (S&OP). The team consists of representatives from marketing/sales, production, human resources, and accounting/finance. The team develops a forecast of future expected orders, and plans the aggregate production and inventory levels. Everyone then agrees to work toward executing this plan. Without a cross-functional team of this type, marketing makes a forecast, production uses a different forecast to plan production, and the capital is not made available to provide the capacity needed. Without a cross-functional team, the functional silos are very effective in destroying any semblance of a plan that everyone can implement.
Partnerships with suppliers and customers provide coordination across businesses the same way cross-functional teams provide coordination within the business. Partnerships start with a commitment by both firms to establish a long-term business relationship that will be mutually beneficial. The partners must develop trust in each other to make this work. Also, the partners probably will establish teams of employees from the two different firms to work together on important improvement projects. For example, a new product was developed over several months by a team of engineers from an appliance company and its key customer’s site. This team worked very effectively and made a final presentation to the senior executives from both firms. One executive turned to the other and said, “Which employees are yours and which ones are ours?” The team had become so integrated that it was difficult to tell the members apart.
Another example comes from the grocery industry. Demand at the retailer level typ- ically varies by about 5 percent from week to week, yet demand at the wholesale and
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supplier levels varies by factors of two to four times that amount. This again reflects the bullwhip effect. To combat the bullwhip effect, the grocery industry has formed a partner- ship of retailers, wholesalers, and manufacturers to implement what is called efficient con- sumer response (ECR). The basic elements of ECR are aimed at managing both demand and the supply chain to serve customers efficiently.
In supply chain improvement it is often necessary to deploy lean tenets and techniques to pursue setup time reduction across entities within the supply chain. A McKinsey report in fact identified lean as one of the key management practices that differentiate firms with good supply chain performance from those with poor supply chain performance. As part of lean systems, setup time reduction can take many days out of the supply chain, reduc- ing the total replenishment lead time and the total supply chain throughput time. In addi- tion, reduced setup times allow smaller lots of materials and the product to be produced and transferred across the supply chain economically. Once lot sizes are reduced, inven- tory in the supply chain can also be reduced; the inventory can turn over more quickly, more closely meeting the market need. Other aspects of lean such as 5S and stabilizing the master schedule can also be employed to reduce the cycle time and inventories in the supply chain.
Changes to information systems are important in supply chains. A flow of information is needed both downstream from suppliers to customers but upstream as well. Downstream information includes usage instructions, inventory levels, invoices, and order shipment sta- tus. At the same time, information must also flow upstream from customers to suppliers on demand forecasts and future planned orders to facilitate planning and reduce the bullwhip effect. Also flowing upstream are monetary payments along with payment status. Any returns from customers and recycled materials will also be accompanied by information flowing upstream. Information flow in both directions is essential to make supply chain partnerships effective.
16.7 TECHNOLOGY AND SUPPLY CHAIN MANAGEMENT
Structural and system improvements in the supply chain can help reduce cost, uncertainty, and time. These improvements often take advantage of advanced technology to facilitate increased coordination among supply chain entities.
The Internet is a disruptive technology that is changing not only how business transac- tions occur among firms or between firms and customers but also how the supply chain can be made more efficient. Because of the Internet, electronic commerce (e-commerce) is thriving. B2B (business-to-business) connections in forms such as e-procurement, order entry, and Internet auctions are facilitating interfirm exchanges of goods and services. Similarly, B2C (business-to-consumer) connections are allowing traditional brick-and- mortar firms to create an alternative distribution channel to offer merchandise and services for sale. Examples include Walmart.com, Target.com, and BestBuy.com.
At the same time, Internet retailers have emerged to sell goods and services over the Internet; Amazon.com, eBay.com (auction), eBags.com (luggage), and Expedia.com (travel) are examples of this type of business.
In terms of the supply chain, the Internet is rapidly allowing businesses to be connected to each other and to the end consumer. These interconnections are providing integration and facilitating more rapid and accurate information exchange across the supply chain, result- ing in better coordination between companies. Information that was once not readily avail- able can now be made visible to many layers of the supply chain. The Internet, as a result, is enabling companies to speed up their supply chains and reduce costs at the same time.
LO16.5 Evaluate the effect of technology on the supply chain.
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See the Operations Leaders box titled “The Cisco Story” to see how Cisco is using the Internet to manage its supply chain.
In all supply chains, two fundamental processes are being affected dramatically by the Internet:
1. Order placement 2. Order fulfillment
The process of order placement includes not only the actual entry of an order from the customer but also information supplied before the order is entered. For example, a customer might like to know before ordering a particular item whether it is in stock and how long it will take to be delivered. When this information is available on the supplier’s website, the customer can access it quickly.
The Internet can facilitate faster order placement and increased accuracy of an order. As the order is taken online, it can be checked for missing information, and selection menus can be provided to ensure that the customer makes correct choices. When the customer makes a special order, the specifications can be provided to the supplier and then checked for consistency when the order is filled. After the order is entered, the Internet can provide the customer with manufacturing and shipment status. With the Internet, the order place- ment process can be streamlined and made more efficient and less error-prone.
In the same way, the Internet can enhance order fulfillment. Today, advancements in planning technologies allow orders taken by the producer to be shared seamlessly within a firm to schedule production of the order or replenishment of inventory. Such orders can be transmitted directly to control internal manufacturing of supporting parts and external pro- curement of materials as needed. These advanced planning technologies even allow place- ment of procurement orders directly to suppliers, with suppliers having visibility of current as well as future planned orders. In this way the entire supply chain is linked electronically.
Transaction information systems for order placement and order fulfillment now provide the opportunity to use analytics to improve decision making. Data on customer demand from order placement can be analyzed to provide forecasts of future demand. These fore- casts can be entered into an S&OP process to plan future production levels. The resulting
• 82 percent of support calls now resolved over the Internet.
• Customer satisfaction has increased significantly.
Cisco’s former CEO, John Chambers, says, “Cisco’s success and our increased productivity gains are due largely to the implementation of Internet applications to run our business. The ability to harness the power of the Internet to create a New World business model is driving survival and competition in today’s fast-paced economy.”
Source: Cisco website: www.cisco.com, 2015 and 2019.
Cisco Systems, Inc., is the worldwide leader in network- ing for the Internet. Cisco’s Internet Protocol–based (IP)
networking solutions are the foun- dation of the Internet and most cor- porate, education, and government networks around the world; Cisco employs 74,000 people worldwide.
Cisco has set the standard for business transformation by using Internet technology to integrate its core processes and culture. The results have been phenomenal:
• 90 percent of orders taken online. • Monthly online sales exceed $3.5 billion.
The Cisco Story
OPERATIONS LEADER
Cisco Systems, Inc.
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master schedule can be used to place orders with suppliers thereby linking the supply chain to the predicted customer demand. Other analytics methods can be used to simulate production schedules and project the human resources and equipment needed.
Better information and analytics allows firms to reduce their inventory levels to meet customer demand. When orders can be shipped more quickly and cycle times reduced then inventory can also be reduced. Information can speed up and shorten the entire
supply chain. Therefore, information and analytics are not only necessary for a supply chain to function; they have allowed firms to partially replace inventory with information.
What has been called the “Amazon Effect” is the biggest change in e-commerce in the last 25 years. This “effect” is the ongoing revolution and disruption of the retail industry by online sales. What is often not recognized is that Amazon and other e-commerce firms are supply chain companies and have created massive disruptions in supply chains around the world.
In 1964 Jeff Bezos started Amazon as an online bookstore company in Seattle, Wash- ington. It is now the largest e-commerce, cloud computing platform and supply chain company in the world measured by revenue and market capitalization. Soon after start- ing, Amazon diversified into selling toys, cosmetics, consumer electronics, clothing, and sports equipment, and it now has 10,000 categories of goods. In 2017 Amazon bought Whole Foods Market to enter into the grocery business and provide 470 retail outlets for its products.
The importance of supply chain management to Amazon cannot be overemphasized. They have built massive distribution centers around the world to serve local markets. In the U.S. Amazon has 386 distribution centers and is still expanding its footprint. Some of these centers cover one million square feet. In Canada, Mexico, Brazil, the U.K., and many other countries they operate 461 distribution centers. Amazon engages in the SCOR (supply chain operations reference) model tasks of planning, sourcing, delivering, and returning.
Amazon and other e-commerce companies are causing traditional retailers to go online with their products. Walmart, Target, and other retailers have made massive investments in online sites and use their stores for fast delivery. Groceries and other items can be ordered online and picked up at curbside. In some cases, deliveries are made by these retailers to your front door. Thus, many e-commerce firms and traditional retailers are pursuing a hybrid strategy of both online and physical stores.
This transformation of the supply chain enables omni-channel marketing, which means to interact with customers through multiple channels such as a physical store, online website, physical and virtual catalogs, and social media. Customers interact with brands and companies using smartphones, tablets, desktop computers, and laptops. The challenge for retailers is to make all these interactions as seamless, consistent, and error-free as pos- sible. Organizations employ omni-channel marketing and associated supply chains to meet customers where they are in an efficient, transparent way.
Blockchain is the latest technology to impact supply chains. It is a secure ledger (or data- base) that is distributed and shared by all parties in the supply chain. What makes block- chain unique is the level of security that makes it almost impossible to be hacked or altered. It also does not require a central authority to manage or protect the data. Each block in the chain can represent a transaction such as a purchase order, receipt of a shipment, or a payment made. When it is entered, the data in the block is encrypted with a 60-character
E-commerce and Omni- channel Marketing
Blockchain Technology
Amazon is an e-commerce, retail, and supply chain company. rvlsoft/Shutterstock
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personal key, along with a public key that is coded (or hashed) and linked to the keys in subsequent blocks. This linkage ensures that a block cannot be altered unless all subsequent blocks agree to the change. As a result of sharing their data, each party in the chain has a complete database of all transactions in the chain that cannot be easily hacked or altered.
Blockchain technology is used for crypto currency, like Bitcoin, but that is an entirely different application. Blockchain is ideal for supply chain security and transactions. It reduces errors and the time for all parties to process transactions, since the required data, paperwork, and legal documents are all available at each point in the supply chain.
Let’s take an example of shipping a 40-foot container from China to the U.S. It is a complex process that includes exporters, importers, freight forwarders, ocean shipping lines, freight companies, intermodal operators, banks, and insurance companies. These companies are collectively responsible for processing more than 50 documents that include invoices, packing lists, certificates of origin, bills of lading, custom clearance documents, freight invoices, receiving documents, and payments. These documents need to be acces- sible and accurate to quickly move the container along the supply chain. Currently, the documents are sent by e-mail or EDI between parties and are frequently missing authoriza- tions or information that is needed. A study indicates that 10 percent of all freight invoices have inaccurate data that cause disputes and process inefficiencies, and this is only one document in the chain.
Using blockchain technology, supply chain parties can create their own blockchain for shipment of the container to greatly reduce the amount of labor needed while improving accuracy. For example, a clothing manufacturer in China wishes to fill an order from the U.S. for a container shipment. The manufacturer, a pre-verified participant in the digital ledger, uploads the commercial invoice, packing list, and certificate of origin to start the blockchain using a unique 60-character encryption code that identifies its transaction and the first block. Then a Chinese customs official, also a pre-verified participant, provides export approval using another 60-character encryption code creating the second block that is linked to the first block. Next, the preapproved importer will upload its import license, delivery instructions, and necessary clearances to create the encrypted third block that is linked to the first two blocks and so on. As a result of this, a complete secure database of all transactions will be available to each party in the chain as the shipment progresses. The Learning Enrichment box at the end of this chapter has a video that explains how block- chain works for a diamond supply chain.
Blockchain is an emerging technology that is being pilot tested, but not yet widely used for supply chains. Some of the early movers are Starbucks to make its coffee supply chain transparent, Coca-Cola to prevent use of forced labor in sugar cane fields by creating a reg- ister of workers and their contracts, and Cargill to track turkeys from farms to Cargill’s pro- cessing lines and eventually to the grocery store. Logistics and transportation companies such as Maersk, FedEx, BNSF Railway, C.H. Robinson, and YRC Worldwide are early testers of the use of blockchain. The BiTA (Blockchain in Transport Alliance) has over 200 companies that are using, studying, or considering using this technology.
Despite the enthusiasm in industry, there are significant obstacles to overcome. National, local, and international laws could be an impediment. Moving a 40-foot container across international borders and within countries encounters significant regulatory and legal hur- dles that specify responsibility for freight moving through various jurisdictions. Revising the laws and regulations, as needed, could impose difficulties in implementation.
Scalability is also an issue. When a transaction occurs, every block in the chain must be updated with the new information. Because of the complex and secure linkages between blocks, computing cost and time are extremely high for long blockchains. Even the most powerful computer networks slow down and become very expensive to operate.
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16.8 SUPPLY CHAIN RISK AND RESILIENCE
Modern supply chains span across multiple countries and have numerous suppliers and cus- tomers. As a result of this complexity, they are subject to higher risk from supply and demand disruptions that are unexpected. There has been a tendency to reduce the cost and inventories in supply chains by a variety of approaches including lean systems and other inventory reduc- tion approaches. As a result, supply chains tend to be less resilient to disruptions and have higher risk exposure. We define supply chain resilience as the ability to quickly respond to unexpected disruptions in supply or demand than can be either natural or manmade.
In March 2011, the worst earthquake, tsunami, and nuclear disaster in history hit Japan. Toyota’s supply chain was devastated by this disaster. Lean manufacturing pioneered by Toyota was based on relative certainty of supply and demand together with minimal inven- tories. Automobile parts in high demand and short supply reached 500 parts after the disas- ter, thereby severely limiting production. The shortage was reduced to only 30 parts four months later when Toyota production finally was restored to 90 percent of its capacity. As a result, in 2011, Toyota sales and production dropped 21 percent over the previous year.
However, some manufacturing firms in Japan had more resilient supply chains. Apple’s iPad2, which had just been launched, suffered little production loss because Apple had multiple suppliers inside Japan and in other countries. Fujitsu had major semiconductor factories near the heart of the earthquake zone, yet recovered more quickly than other semiconductor suppliers. While the March 2011 disaster was extreme, it raises the ques- tion of how much supply chain resilience should be planned. There must be a balance between efficiency, low inventories, and supply chain resilience for unexpected events.
The level of resilience is determined by the ability to plan for disruptions, detect them early, and act quickly. This is illustrated in Figure 16.3, where company B is more resilient than company A. Company A has no risk mitigation system and subsequently incurs more loss of revenue, profitability, and market share than company B, which mitigated supply
LO16.6 Discuss supply chain risk, resilience, and how risk can be managed.
FIGURE 16.3 Supply chain mitigation framework. Source: APICS Magazine 22, no. 1 (January/February 2012).
Resilience— Proactive supply chain risk mitigation
Agility— Early detection and quick response to minimize damage
Effect of visibility systems
T Discovery B1 Discovery A1
Company A
Company B
Recovery B2 Recovery A2
Effect of swift action plus effect of capacity and inventory buffers
Impact of supply chain disruption on organization A, which has no risk mitigation system Impact on organization B, which has mitigated supply chain risk and is continuously monitoring for disruptions
Stage 1: Business as usual
Stage 3: Business as usual
Stage 2: Recovering from a supply chain disruption
Recovery— Damage control through last line of defense: insurance cover
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chain risk and is continuously monitoring possible disruptions. At point T in Figure 16.3 the disruption occurs. Company B discovers the problem more quickly at point B1, while company A discovers it at point A1. Also, company B acts more quickly to respond to the crisis than company A. When a disruption occurs, rapid actions to maintain business con- tinuity are needed. The business continuity plan needs to be implemented and risk mitiga- tion actions taken immediately.
There are many factors that lead to unexpected disruptions in supply chains. These include strikes, recessions, sudden pricing changes, natural disasters, manufacturing failures, and unexpected demands. All of these must be considered when planning for supply chain resil- iency. Ensuring that a supply chain is resilient helps to bring a supply chain back up to normal operational capabilities once disruptive events occur. Even then it is impossible to plan for all possible disruptive events, especially those that are unavoidable acts of nature (force majeure). So the question is how is risk mitigated in a supply chain?
There are three stages to risk mitigation. In Stage 1, a proactive plan is needed before dis- ruption occurs. Stage 2 is oriented to minimize damage to the supply chain during disruption. Then, Stage 3 is concerned with post-disruption recovery. The actions that should be taken in each of these stages are shown in Table 16.1, at both the strategic and operational levels.
The important point is that supply chains can be made more resilient by advance planning, early detection, and speedy action during disruptions. Since additional capacity, alternative sources of supply, or more inventories can be required, this may reduce the efficiency of the supply chain. Supply chains can be too fat or too lean; either condition should be avoided.
In Table 16.1, the first stage of a resilient supply chain is development of a proactive plan to prevent disruption. Most companies have no idea how resilient their supply chain is to risk of failure. They don’t have a methodology to understand their risk exposure. Yet, sup- ply chain disruption can be very serious. It can result in a loss of business continuity and a failure to deliver products to the market. This will negatively affect the brand of the com- pany and can lead to a loss in brand equity and stockholder equity. Thus supply chain risk should be carefully evaluated and mitigated when possible.
Supply chain risk is the probability of loss due to disruption of the supply chain. Both the chances of the occurrence of a disruption and the magnitude of the loss must be con- sidered. The loss can range all the way from a minor cost to airfreight some parts to meet a deadline to the failure of the entire supply chain for a long period of time.
Supply chain risk can be decreased at each node in the supply chain. A node is a sup- plier, warehouse, or a point where inventory can be held. For simplicity let’s just consider reducing risk from the supplier side of the network. Risk is reduced as follows:
∙ Add inventory at a supplier node or at the firm location itself. ∙ Have two suppliers and be able to shift production from one to another. The suppliers
will need to be dispersed geographically or they could suffer from the same natural disaster such as a flood, hurricane, tornado, or tsunami.
∙ For a sole source, have two separate locations for supplying the product or a second sup- plier that can be quickly brought online.
All risks cannot be reduced to zero without excessive cost. So the question is how much risk does the supply chain have, and is this level of risk acceptable in view of the cost?
Most companies that evaluate risk do so at their highest spend suppliers. Suppliers tend to obey the 80-20 rule. Eighty percent of the cost is incurred by 20 percent of the sup- pliers. So, firms look at the 20 percent first or the largest suppliers. This is not a good approach because even a low-cost part can cause a production stoppage. For example, a
Analysis of Supply Chain Risk
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coat manufacturer cannot ship a coat because of a missing button. All the parts in a product are important to have and it is relatively cheap to be sure you have enough inventory of the low-cost parts. What is needed is a methodology for evaluating the risk of all suppliers.
A risk evaluation analysis was developed at the Ford Motor company and has been deployed to other companies, as well.3 It is as follows:
1. For each supplier calculate TR = time to recover from a disaster. This is the time it will take for the supplier to get up and running again. Of course, the severity of the disaster must be assumed for TR to be calculated.
2. Calculate PI = the performance impact that occurs during TR. This would normally be the lost profit during the time of disruption. The longer TR the greater the loss.
3 David Simchi-Levi webinar, Oct. 21, 2015.
TABLE 16.1 Framework for Building a Resilient Supply Chain Source: APICS Magazine 22, no. 1 (January/February 2012).
Proactive: plan for disruption
Reactive: minimize damage
Post-recovery
O pe
ra tio
na l
• Conduct enterprise- level supply chain risk assessment
• Make risk adjustments to total cost of sourcing equations
• Design actionable busi- ness continuity plans covering all failure scenarios
• Identify authorities for decision making during disruptions
• Invest in improving capacity and inventory visibility
• Paradigm shift with less emphasis on efficiency and more emphasis on business continuity
• Sanction supplies from reliable alternative sources and employ alternate transport nodes and manufactur- ing facilities in case the preferred options fail (risks associated with the alternate sources should be divorced from those borne by primary sources)
• Reevaluation of the supply chain to assess the following parameters:
° effectiveness of the business continuity plan
° effectiveness of early disruption detection systems
° validity of total cost of ownership/sourcing equations
° resilience of the supply chain to future disruptions
St ra
te gi
c
• Supplier selection based on
° risk-adjusted total cost to source
° supplier’s business con- tinuity plan strength
• Identify alternate suppliers with different operating conditions
• Maintain higher buffer lev- els for critical components
• Continuous monitor- ing of supply chain for disruptions
• Backup of information systems
• Diagnose all the impacts to the supply chain once a disruption has been identified
• Invoke the business con- tinuity plan to ensure safety of employees and continuity of operations
• Take swift action to em- ploy available capacities within the organization and supplier network
• Constantly monitor the situation
• Prepare a disruption report that covers failure points as a result of disruption, cause and effect anal- ysis, and comparative analysis of disruption performance through industry peers
• Systematic loss report- ing to mitigate issues through insurance coverage as a last line of defense
Before the disruption During the disruption After the disruption
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3. For each supplier also calculate TS = maximum time that the supplier can match supply and demand after a disaster. This would depend on the amount of inventory and how long it would take to bring in an alternate supplier.
Ideally, a supply chain should have TS > TR for each supplier node. In that case the sup- ply chain could survive while each supplier is recovering. See Figure 16.4 for examples of survival and non-survival of a supply chain.
Through an analytic network method, Ford was able to calculate TS, TR, and PI for each node in their network of more than 2100 Tier 1, 2, and 3 suppliers. They found the profit impact during recovery was $2.5 billion for the entire network. For Tier 1 suppliers TR, the time to recover from a disaster, varied from one to two weeks. That was acceptable if the TS was long enough, in this case more than one or two weeks. However, the TS varied widely across these suppliers from less than one week for over 600 sites to TS over 50 weeks for 150 sites. For the 600 suppliers with TS less than one week they would not recover in time for the network to survive. This meant the network had too little inventory and alternative supplier options at these nodes and too much at others. They were able to shift inventory and add alternate suppliers to the sites with small TS. As a result the network became more resilient with TS > TR.
It can cost more to have a more resilient network. The application of lean think- ing has reduced inventories in some cases to levels that are too low to prevent supply chain disruptions. In other cases, a decision to have fewer or single source suppliers has resulted in networks that are less resilient. Therefore, the level of resilience, and pos- sible associated costs, needs to be carefully evaluated as part of the proactive plan for business continuity.
16.9 SUSTAINABILITY OF THE SUPPLY CHAIN
Sustainability is meeting present needs without sacrificing the needs of future genera- tions. It usually refers to going green to conserve natural resources (air, water, land, and energy) for current and future generations. Sustainability also has social and economic components. The social component is related to safe working conditions, community involvement, and progressive human resources practices. The economic part is one of financial responsibility to the stockholders. Sustainability means environmental conserva- tion with social and financial responsibility for all stakeholders. This is often called the triple bottom line, referring to the environmental, social, and financial performance of the firm and its supply chain.
LO16.7 Describe supply chain sustainability.
FIGURE 16.4 Time lines for two suppliers
Supplier A 0 |
|
|
|
Survival not possible TS < TR TS TR
Supplier B 0 Survival is possible TS > TR TR TS
Disaster occurs at time 0
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The triple bottom line rests on the concept of stakeholders including all those who have a stake in the business, not just the stockholders. Stakeholders are the stockholders, com- munity, government, employees, suppliers, and customers. The triple bottom line attempts to benefit all stakeholders without exploiting any of them. Triple bottom line accounting expands the notion of traditional accounting to include the three P’s: people (social), profit, and planet (environment). Thus, companies not only commit to the triple bottom line, but also measure the results by accounting.
To some firms sustainability goals increase their costs and progress is only made through government regulation. Fortunately, there are also many ways to pursue sustain- ability of the firm and its supply chain by innovations in products and processes with- out incurring regulation or additional costs. For example, green practices can lower costs through use of recycled materials, refurbishment and repair of products, and less landfill waste. The “By the Yard” company makes outdoor furniture entirely from recycled plastic milk jugs. Social practices can also result in lower costs through increased productivity and motivation of the workforce. See the Operations Leader box: “Unpackaged: The Eco- Friendly London Grocery Store.”
obeyed, bringing with them bottles, glass jars, paper bags, plastic bags, and old boxes to carry their produce home. Inside this London store, organic grocery items are stored in barrels, buckets and bins, and matte black tubs. Customers scoop their purchases into the contain- ers they bring. The store has been profiled in videos on their website.
Asked to describe the store’s philosophy, Conway responded as follows:
We source Fair Trade products where possible; we don’t sell products that are shipped by air; we give preference to suppliers who are part of cooperatives; and we apply the same three basic principles of the “waste hierarchy”: reduce, reuse and recycle. Unnecessary packaging increases the price of the goods because you’re effec- tively being charged twice: First, when you buy over- packaged goods, and then through your taxes, which are spent getting rid of the leftover rubbish. Packaging is usually disposed of either in a landfill or by incinera- tion, both of which are major pollutants. Of course, some packaging can be recycled, but only some. Despite our best efforts, most of what we bring into the home ends up in a landfill. (from C. Dowdy, “On the Loose,” Hemi- sphere, May 2009, p. 92)
Source: Adapted from C. Dowdy, “On the Loose,” Hemisphere, May 2009, pp. 90–92; http://beunpackaged .com/, 2020.
Unpackaged is not your typical grocery store. An organic grocery store founded in 2006 by its proprietor, Cath- erine Conway, Unpackaged tells its customers to bring their own containers when they shop. Customers have
Unpackaged: The Eco-Friendly London Grocery Store
OPERATIONS LEADER
Cate Gillon/Getty Images
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Sustainable supply chains refer not only to a firm’s practices but those of the suppli- ers and customers throughout the supply chain. Suppliers use as much as 80 percent of resources consumed in making a product; and social practices of suppliers in developing countries have been subject to human rights and worker safety concerns. This includes loss of life due to fires and building collapse in supplier’s factories, the use of underage labor, and unsafe working conditions. Therefore, the entire supply chain is a concern for the triple bottom line. One example is the initiative taken by General Mills, a global packaged food manufacturer, to pursue environmental and social practices from “farm to fork.” They plan to cut greenhouse gas emissions by 28 percent by 2025 from their supply chain and invest over $100 million to accomplish this. Their plan extends upstream in the supply chain to sustainable agriculture by adding 250,000 acres of organic food production.
Sustainability is accomplished primarily through innovation in products and processes throughout the supply chain. Products can be designed to be more environmentally friendly and safer to produce. Processes can also be redesigned to accomplish the same purposes. When this is done in connection with suppliers, the entire supply chain becomes more sus- tainable at lower costs. Even the selection of suppliers who help pursue the triple bottom line is essential.
To increase supply chain sustainability, a company typically takes a three-phase approach:
1. Set environmental, social, and financial goals. 2. Develop long-range plans to meet those goals with the suppliers. 3. Implement the plans throughout the firm and its supply chain.
Some examples of how this can be done are as follows:
Goals ∙ Reduce carbon emissions by the firm and its supply chain by 20 percent in five years. ∙ Reduce the consumption of water by the firm and its supply chain by 30 percent in three
years. ∙ Increase the use of recycled materials by the firm and its supply chain by 40 percent in
four years. ∙ Reduce accidents by the firm and its supply chain workforce to nearly zero in three
years. ∙ Eliminate the use of child labor and unsafe working conditions in its suppliers to zero in
one year.
Plans to Achieve the Goals ∙ Carbon emissions will be decreased by greater use of renewable energy, improved mile-
age of transportation, and redesigned products and processes that have a smaller carbon footprint in both the firm and its supply chain.
∙ The consumption of water will be achieved by using recycled water and redesigning products and processes to use less water by the firm and its supply chain.
∙ Use of recycled materials will be achieved by redesigning the firm’s products and engaging suppliers to do the same.
∙ The firm and its suppliers will institute safety programs and accident prevention efforts throughout its facilities.
∙ Engage only 1st-, 2nd-, and 3rd-tier suppliers that do not use child labor and unsafe working conditions. Use inspectors to ensure that these working conditions are met.
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Implementation A firm will need to mobilize its entire organization and its supply chain to achieve these goals. It cannot be done by a centralized environmental office. A small centralized office may be needed to track the results and provide training. But, the majority of the efforts will be made in the various divisions and facilities of the company and its supply chain partners. This is clearly a cross-functional effort that touches all parts of the organization and its suppliers and customers.
Perhaps some suppliers cannot assist in achieving the triple bottom line, or after an audit they are not in compliance with the firm’s requirements to meet environmental, social, or financial goals. Then the supplier will need to make changes or another supplier will be secured.
See the Operations Leader box on Cargill for an example of a company’s goals and plans to implement sustainability. It’s clear that the time has come for companies to be more environmentally and social conscious, and the result can be financially rewarding.
16.10 KEY POINTS AND TERMS
Every firm must manage one or more supply chains. An understanding of supply chain management is essential to improving performance in all parts of the supply chain. This chapter’s key points include the following:
∙ A supply chain is the set of entities and relationships that cumulatively define the way materials and information flow downstream and upstream from the customer. The
percent, reduced greenhouse gases by 9 percent, and increased fresh water efficiency by 12 percent. Cargill has continued to excel in achieving environmental and social goals.
Cargill instituted many programs. For example, in a poultry facility, they used recovered vegetable oils and animal fats to displace fossil fuels. At their wheat pro- cessing facility in the Netherlands, half of the biogas produced in wastewater treatment is used to power the facility saving 1000 metric tons of CO2 per year. They reduced water use in a facility in Texas by 25 percent over six years. Cargill was named a sector leader in tack- ling deforestation. They are committed to sustainable, deforestation-free, and socially responsible palm oil pro- duction in developing countries.
These efforts were undertaken in over 100 facilities and supply chains around the world. Only a small corpo- rate staff is engaged in goal setting, measurement, and training.
Source: Cargill.com 2015 and 2019.
Cargill is the largest privately held company in the U.S. with $114 billion in annual revenue. For 150 years they have engaged in food processing, grain trading,
and food transportation and storage. Cargill believes it is good for the planet and the company to seek sus- tainable practices throughout its supply chain. As part of their commitment they set new goals every five years. They set their first environmental goals in 2000. By 2015 they had increased energy efficiency by 16
Cargill
OPERATIONS LEADER
Ken Wolter/Shutterstock
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downstream flow facilitates transformation of materials and services into units of the final product sold to consumers and information related to the product. The upstream flow facilitates return of defective units, recyclables, and information for planning purposes.
∙ Supply chain management is concerned with the design and management of value- added processes that not only cut across organizational boundaries but must be tightly integrated to allow information and materials to flow and be deployed within and across them.
∙ Measurement of supply chain performance should be made in four areas: delivery, qual- ity, flexibility, and cost for each firm along with throughput time, cash-to-cash, and total delivered cost for the entire supply chain.
∙ The bullwhip, or accelerator, effect entails market demand being magnified through orders placed to upstream supply chain entities, such that the farther upstream an entity is, the greater is the variability in the orders received and inventory held. Information time lags, retail pricing practices, human behavior, and long replenishment lead time account for the dynamics observed.
∙ Structural improvements in supply chains can be achieved by vertical integration; major process simplification; changing warehouse, factory, and retail configurations; and major product redesign.
∙ The supply chain practices of outsourcing and off-shoring change a firm’s supply chain configuration by allocating work performed internally to other firms within the supply chain either domestically or in other countries.
∙ Systems improvements in supply chains can be accomplished by cross-functional teams, partnerships, lean systems, and information systems.
∙ The Internet is creating new types of businesses that facilitate transactions between firms (B2B) or between a firm and its customers (B2C). The Internet is also improving supply chain performance by speeding up and reducing costs in order placement and order fulfillment processes. E-commerce and blockchain digital technologies are trans- forming supply chains.
∙ Supply chain resilience is the capability to quickly respond to unexpected disruptions in the supply chain, either natural or man-made. Resilience is achieved by advanced plan- ning, early detection, and swift actions.
∙ Sustainability is meeting present needs without sacrificing the needs of future genera- tions. The triple bottom line refers to environmental, social, and financial responsibility.
Key Terms Supply chain 349 Physical supply 349 Physical distribution 350 Supply chain
management 351 SCOR model 351 Throughput time 353 Cash-to-cash cycle time 353 Total delivered cost 353 Bullwhip effect 355
B2B 362 B2C 362 Analytics 363 e-commerce 364 Omni-channel marketing 364 Blockchain 364 Supply chain resilience 366 Supply chain risk 367 Sustainability 369 Triple bottom line 369
Supply chain structure 358 Supply chain systems 358 Forward integration 359 Backward integration 359 Process simplification 359 Supply base reduction 359 Outsourcing 359 Off-shoring 359 Postponement strategy 360 Partnerships 361
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Discussion Questions and Problems
LEARNING ENRICHMENT (for self-study or instructor assignments)
What Is Supply Chain Management? Video https://youtu.be/Mi1QBxVjZAw 8:05
Supply Chain Sustainability: A Force for Good Video https://youtu.be/Bl0UhiOvrdc 5:02
The Bullwhip Effect 101 Video https://youtu.be/2nlmkTYZG5s 5:30
IBM and Maersk Demo: Cross-border Solution on Blockchain Video https://youtu.be/tdhpYQCWnCw 3:10
How It works: Blockchain for Diamonds Video https://youtu.be/lD9KAnkZUjU 3:35
The Amazon Effect: Launching Businesses Faster Video https://youtu.be/9H3dL0CO1bw 2.55
Rethinking Relationships in the Global Garment Supply Chain, Video Susan Goldstein, University of Minnesota 2:11 https://youtu.be/2bVbZwyK6zE
1. Using the SCOR model give an example of a supply chain that you are familiar with from plan, source, make, deliver, and return.
2. Define the supply chains for the following products from the first source of raw materials to the final customer:
a. Big Mac b. Gasoline c. Automobile repair d. A textbook 3. How do lead times and forecast errors affect supply
chain performance? 4. How can coordination be increased both internally
within the firm and externally with customers and suppliers?
5. A supply chain has the following information:
Supplier Factory Wholesale Retailer
Inventory in days*
30 90 40 20
Accounts receivable in days
20 45 30 40
Accounts payable in days
30 45 60 37
Sourcing unit cost
$ 5 $20 $55 $ 70
Added unit cost $10 $25 $10 $ 30
Sales unit price $20 $55 $70 $110
On-time delivery (%)
85 95 75 95
* This is also the throughput time in days.
a. Compute the total supply chain throughput time for all the entities from beginning to end.
b. Compute the cash-to-cash cycle time for each of the four entities separately. Based on this calculation, who is benefiting the most?
c. Compute the total delivered unit cost in the supply chain from beginning to end. How much profit is there in the supply chain?
6. Considering the data and calculations from question 5: a. Which entities in the supply chain have the worst
performance in terms of throughput time, cash-to- cash, added unit cost, and on-time delivery?
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b. Where should improvements be made to benefit the supply chain as a whole?
7. Consider the following information from a supply chain:
a. Compute the number of days in inventory for each of the entities.
b. What is the throughput time for the entire supply chain?
c. Calculate the cash-to-cash cycle time. d. Who is benefiting the least in the supply chain?
e. What would you do to improve the throughput time or the cash-to-cash cycle time?
8. How would you decide whether a supply chain needs improvement in supply chain structure, supply chain systems, or both?
9. Relate off-shoring to outsourcing to global sourcing. 10. Explain how lean operations can have a powerful posi-
tive or negative effect on the entire supply chain. 11. Why are cross-functional teams so widely used for sup-
ply chain improvement? 12. Explain how companies use order placement and order
fulfillment. 13. Discuss how e-commerce has affected retail supply
chains. 14. To what extent can blockchain technology influence
global supply chains? 15. What are the advantages and disadvantages of a decen-
tralized blockchain approach to global shipping com- pared to a database that is centrally managed without blockchain?
16. How can a company ensure that its supply chain is resil- ient to unexpected events?
17. Give some examples of sustainability goals and plans.
Tier 1 Supplier
Tier 2 Supplier Manufacturer
Average inventory $000
2000 1500 5000
Cost of goods sold $000/day
125 75 100
Accounts payable in days
15 25 45
Accounts receivable in days
30 60 30
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Dell has a well-known supply chain for making its products. It makes extensive use of sourcing, which includes the activities to identify suppliers of the components and parts needed to make its computers. Components and parts are outsourced to global suppliers, including Intel for semiconductors, LG for displays, Samsung for hard drives, and Microsoft for software. Dell has a very lean supply chain with most of the parts inventory held by its suppliers. Suppliers also submit sustainability reports to Dell. Most final assembly is done in Dell factories to control the quality and delivery schedules of the final product. The final assembly, the design of computers, and the brand are considered core competencies and are not usually outsourced.
Sourcing
17 c h a p t e r
LO17.1 Calculate the profit leverage effect of sourcing and explain its importance.
LO17.2 Explain the goals of sourcing.
LO17.3 Contrast the advantages and disadvantages of outsourcing and offshoring.
LO17.4 Calculate the total cost of outsourcing and offshoring.
LO17.5 Describe supply base optimization.
LO17.6 Explain the elements of the purchasing cycle.
LO17.7 Analyze an example of the weighted scoring method of supplier selection.
LO17.8 Discuss the challenges facing purchasing.
After reading this chapter, you should be able to:LEARNING OBJECTIVES
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Sourcing is deciding if a product, part, or service should be outsourced or insourced by the firm. It estab- lishes the inputs the firm will use in making its products or services. Sourcing makes the following strategic decisions.
1. Which products and services, if any, should be out- sourced in whole or part?
2. Which of these should be supplied from offshore? 3. How should the supply base be optimized?
Once the strategic sourcing decisions have been made, purchasing makes tactical decisions with specific suppli- ers. Purchasing deals with choosing suppliers, negotiating contracts, and managing the buyer–supplier relationship. Purchasing makes the following decisions.
1. Which supplier(s) should be selected to make the outsourced products and services?
2. How should suppliers and associated contracts be managed on an ongoing basis?
The sourcing decisions are discussed in the first part of the chapter, and the purchasing process in the second part.
17.1 IMPORTANCE OF SOURCING
In many firms a large percentage of the products and services are outsourced. Over time there has been a trend toward more outsourcing and less vertical integration. In its early years, Ford Motor made nearly everything for its cars. Now, all automobile companies pri- marily engage in engine production and assembly of the final product while sourcing thou- sands of other parts from outside suppliers. Many service functions are also outsourced in part or entirely such as call centers, human resources, logistics, and information systems.
Purchasing has been an important part of business since the late 19th century. In 1866 the Pennsylvania Railroad established a supplying department. It was so important that it was given top management status. Sourcing and purchasing today report to top manage- ment in many companies, since a large part of firms’ costs are purchased from outside suppliers.
Sourcing is an important way to improve profitability. Target Corp. had the following financial results in 2018 (in millions of dollars):
Sales $71,880
Cost of Goods Sold (COGS) 50,870 All Other Costs 17,300 Pretax Earnings $ 3,710
Using these figures, Target had a profit margin of 5.2 percent (earnings/sales). Every dollar saved in purchasing goods that Target sells lowers COGS by one dollar.
In contrast, with the current Pretax Earnings ratio, Target would have to increase sales by 1/5.2% = 19 dollars to have the same effect on earnings. This ratio is called the profit leverage effect. It happens because savings in the cost of goods sold drop directly to the
LO17.1 Calculate the profit leverage effect of sourcing and explain its importance.
Dell sources components and completes final assembly. Jeff Chiu/AP Images
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378 Part Six Supply Chain Decisions
bottom line, while additional sales do not increase earnings directly. Leverage is particu- larity high in retail where the profit margins are thin and all of the products sold are pur- chased from outside the firm.
17.2 SOURCING GOALS
Goals are needed before any sourcing decisions are made. The usual goals of sourcing are:
Access Technology and Innovation. This goal is critical in new product or service design. The firm may not have all the technologies needed, so products, parts, or services are designed to be outsourced from the beginning. A partnership may be established with one or more suppliers to develop the design. At a minimum, firms will insource tech- nologies that are considered to be core to their business. Other technologies should be considered for outsourcing when there is a cost, quality or other advantage. Decrease Total Costs. A primary goal in outsourcing is to lower total costs. Parts or services are prime candidates for outsourcing when there are suppliers with econo- mies of scale, since these suppliers’ total costs can be lower. Also good candidates are standard products or services provided by multiple companies and therefore subject to market forces. When outsourcing, the total cost must be considered, not just the price of purchasing. Some additional costs incurred are for finding suppliers, negotiating and maintaining contracts with suppliers, additional inventory, and transportation costs. For foreign procurement, currency effects, tariffs, and monitoring costs are added. Minimize the Risk of Quality and Delivery Problems. Late deliveries and quality problems from suppliers need to be minimized. Some potential problems are hidden from the buyer. Suppliers that screen out the bad items from the sample can deliver quality sample parts. What is needed from the supplier is a certified process for quality that is controlled. Similar risk holds for delivery promises that cannot be met, either because of capacity issues or tier 2 or tier 3 supplier problems. Require Social Responsibility and Ethical Behavior. Firms often require social responsibility from their suppliers. This can range from environmental protection and employee safety to community involvement. Firms may also require minority hiring, ethical responsibility, and protection of human rights. Purchasing officers need to be aware of ethics. In some countries, it is common practice for suppliers to provide payoffs or bribes to obtain a supply contract. This can be done covertly through third parties in order to hide the payoffs, which are illegal. Also paid vacations, expensive gifts, lavish meals, and free entertainment are prohibited by most companies. Purchasing officers must deal with these practices in an ethical way as part of their responsibilities.
17.3 INSOURCE OR OUTSOURCE?
The first strategic decision we consider is whether to insource or outsource an entire prod- uct, part, or service. Outsourcing is defined as obtaining products from an outside sup- plier instead of producing them internally. The same can be said about internal service functions that are outsourced to another company, but formerly provided inside the firm.
The first question a firm must answer is the rationale for insourcing or outsourcing. This begins with the notion of core competence. Core competence provides a competitive advantage to the firm and therefore will not be outsourced. Core competence is what makes a company competitive in the market and profitable. It includes, for example, proprietary
LO17.2 Explain the goals of sourcing.
LO17.3 Contrast the advantages and disadvantages of outsourcing and offshoring.
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technology, skilled personnel, knowledge, the brand, or anything that affects the competi- tive ability of the company. The core competence is valuable, difficult to imitate, and hard to replace with a substitute. As a result, the company has an advantage that can be sus- tained for the foreseeable future. Everything else the company does is a candidate for out- sourcing if the advantages outweigh the disadvantages of outsourcing. The Operations Leader box explains sourcing at Trader Joe’s.
∙ Access to technology that is not core and may be changing over time. If the technology is changing and can be obtained from suppliers, the investment made in-house may not be recovered in time. This is particularly true in fast-changing technologies such as electronics, information systems, and communications.
∙ Scale economies. Scale economies can be a factor for outsourcing especially for com- modities or other products where a standard product is sold to many different compa- nies and the scale for any one company is insufficient to lower costs. Examples of this are standard parts, commodity inputs, computer equipment, chemicals, basic materials, and service functions such as information systems, logistics, and call centers.
∙ Lower costs and investment. Lower total costs when purchasing from a supplier com- pared to internal costs are always a consideration for outsourcing. Outsourcing can also require less investment and allows resources to be used for important internal needs. For example, we already noted that Dell outsources parts and materials to suppliers. Dell supports $79 billion in revenues with only $5.3 billion in fixed assets. They do this by investing only in fixed assets for final assembly.
Advantages of Outsourcing
Trader Joe’s has specific requirements for all sup- pliers. Some of these include selling whole products or packaged food, no recipes or concepts, because Trader Joe’s wants to stay squarely in the retail business. Regardless of whether the supplier is a manufacturer or farmer, they must deal directly with the company, with no distributors or middlemen. Food products must be manu- factured in FDA or USDA licensed facilities. Trader Joe’s branded products have strict requirements for no artifi- cial colors, flavors, preservatives, MSG, or genetically modified ingredients.
Part of Trader Joe’s sourcing process includes third parties as well. Suppliers must provide third party nutri- tional analysis for food items, and all items must have third party shelf life analysis. Finally, all suppliers must carry their own product liability insurance. In total, Trader Joe’s sourcing strategy allows a sharp focus on retail while guiding them in finding the types of products their customers want to buy.
Source: www.traderjoes.com, 2020.
From its 1950s start to nearly 500 grocery stores today, Trader Joe’s has always made sourcing an important part of its business strategy. Customers know the stores for great quality and prices, not to mention staff wearing Hawaiian shirts! How do they deliver on their reputation for high quality and affordable products, many of which are labeled with Trader Joe’s brand name?
Who Makes Trader Joe’s Food?
OPERATIONS LEADER
QualityHD/Shutterstock
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In addition to the advantages gained from outsourcing, there are risks incurred by out- sourcing that can ultimately lead to a number of problems.
∙ Risk of supply chain disruption. This is especially risky if only one supplier is used and inventories are very low in a lean system. When a natural or man-made disruption occurs there may not be enough inventory for the supplier to recover in time thereby stopping production or closing service operations. This is particularly true when there is a single supplier and no other source is readily available. Recently, for example, there was a bird flu epidemic in the U.S. that decimated egg production for several months. As a result, all commercial users of eggs had to scramble to find alternative sources, pay higher prices, and find substitute recipes. This was exacerbated by packaged food manufactur- ers that had a sole source supplier for eggs. It wasn’t just a pricing problem, there was actually a shortage of supply, and buyers found new sources of eggs from overseas.
∙ Risk of potential quality or delivery failures. Supplier certification by ISO 9000, or other means, is a way to ensure that the supplier has a quality control system in place. Delivery delays can occur because the supplier’s supply chain is not managed properly or a tier 2 supplier has quality problems. Quality risks can be severe as occurred when Mattel had to recall millions of Chinese-made toys because a second tier supplier in China used lead paint. This risk was unknown to Mattel, which damaged its brand and almost caused its bankruptcy.
∙ Risk of losing the knowledge or capability to make the product. After the product has been outsourced and eventually brought in-house later, it will be difficult and expensive to restart everything. As technology advances, the company will also miss generations of technology development. Outsourced products can result in the theft of intellectual property and the associated loss of knowledge or capability advantage.
∙ Risk of price increases. A supplier may underbid a contract and subsequently raise its prices after the contract is completed. When buying military equipment or in construc- tion, it is common to have engineering change orders (ECOs). These ECOs, which are not anticipated in the beginning, bring the opportunity for the supplier to make pric- ing changes that are advantageous to the supplier. Even without ECOs, suppliers can increase their prices especially when there is little competition.
Economists use transaction costs as a basis for understanding outsourcing. Transac- tion costs are the costs of drafting and negotiating contracts, buying specialized assets, and monitoring and enforcing agreements. According to economists outsourcing should be done whenever transactions costs are low, otherwise the product should be kept in-house. Transaction costs are generally low for commodities, mature products, and slowly chang- ing technologies when multiple suppliers compete. In this case markets work well and are efficient in keeping the prices down. Transaction costs are high for nonstandard products; when specialized assets are used, there is little competition in the market, or suppliers can- not be trusted to keep their promises. In this case products should be made in-house. The advantage and disadvantages of outsourcing are summarized in Table 17.1.
Disadvantages of Outsourcing
Advantages Disadvantages
Access to new or changing technology Risk of supply chain disruptions Lower total costs Possible quality or delivery failures Less investment/free-up resources Risk of price increases Scale economies in the supplier Loss of knowledge and technology related to the
outsourced work
TABLE 17.1 Advantages and Disadvantages of Outsourcing
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Outsourcing service functions, called business process outsourcing (BPO) is quite prevalent. This is being fueled by information technology. Outsourced service functions include human resources, in whole or in part, information systems, and logistics. Transac- tion costs are incurred if outsourcing causes legal issues, high contracting costs, the use of specialized assets, or transparency in what is being provided by the contractor. If the ser- vices are commodities and there are many providers, then market forces may make out- sourcing more efficient than insourcing provided the function is not a core competence. Outsourcing services to offshore locations is a big business. The BPO industry in the Philip- pines employs 1.2 million workers, primarily in call centers, with $25 billion in revenues.
If firms look only at price, outsourcing will often appear to be a very good deal. However, there are other costs that add to the total cost of outsourcing that must also be considered. These include transportation costs, inventory carrying costs, and costs of administering contracts, among others. Total cost analysis means calculating the total cost of outsourc- ing, not just the price.
Notice in the example below that the outsourcing total cost is substantially higher than insourcing ($8.37 vs $7.68). This is an ordinary part made on common machinery where outsourcing is often less costly. There are many reasons why the in-house total cost might be lower. It could be that in-house manufacturing has the scale for lower costs and it may have lower costs of labor and materials, plus the company doesn’t pay for the supplier’s profits along with the costs of inventory carrying, transportation, and administration of the contract. In other words, the transaction costs are quite high in this case.
Total Cost Analysis
The Widget Company is considering either making a new molded plastic part in-house or outsourcing it to a local supplier. An outside supplier has bid on the part and will provide it for $7.50 each based on production of 100,000 units each year with a three-year contract. In addition the part will be transported to Widget facilities at a cost of $.45 each, inventory car- rying costs will be $.30 per unit, and contract administrative costs will be $1000 per month.
The molded part can be produced in-house if a new machine is purchased. The cost will be $400,000 to buy the new machine that is amortized over the three years of the contract. The direct labor cost is $2.10 each including benefits, the indirect labor is $0.75 each, and the materials cost $1.40 each. Overhead is equal to the direct labor cost. See Table 17.2 below for the calculations.
Example Domestic Outsourcing
Outsourcing
Purchase price $7.50 • Administrative cost is $1000 per month × 36 months = $36,000 divided by 300,000 units = $0.12 per unitTransportation cost .45
Inventory carrying cost .30 Administrative cost .12 Total per unit $8.37
Insourcing
Manufacturing Costs
Direct labor $2.10 • Depreciation is $400,000 divided by 300,000 units = $1.33 per unitMaterials 1.40
Indirect labor .75 Depreciation 1.33 Overhead 2.10 Total per unit $7.68
TABLE 17.2 Total Cost Analysis at the Widget Company
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Qualitative Costs of Outsourcing
There are some costs of outsourcing that are difficult to quantify.
∙ Potential costs of quality, rework, warranty and legal costs of product failures ∙ Cost of work stoppages and supply chain disruptions ∙ Possible loss of intellectual property
To summarize, decisions to insource or outsource must consider a variety of important issues. Price and total cost are important, but also a variety of other factors. Firms should consider how their core competence is related to these decisions.
17.4 OFFSHORING
Offshoring and outsourcing are two different things. Offshoring is just moving production of products or services to an offshore location, whether a firm has made it before or not. In contrast, outsourcing is moving something you have made to an outside supplier whether domestically or offshore. This gives rise to four possibilities.
Offshore is a term that refers to a product made in a foreign country. It may not literally be made offshore (e.g., products made in Mexico for export to the U.S.). A product that was made in-house before it was outsourced to China is both outsourced and offshored at the same time. There also are offshored products made from the start in a foreign location, and thus never outsourced. For example, a U.S. manufacturer opens a new plant in Asia to serve Asian markets (lower left-hand corner in Table 17.3). See Table 17.3 for all four possibilities.
The main reason and argument for offshoring is lower total costs. While wages may be much lower in foreign countries, the productivity must also be taken into account. What matters is the unit cost of production including both wages and the quantity produced by workers per hour of labor.
When evaluating total costs of offshoring the following costs are taken into account. These costs will be added to obtain the total cost of the product or service.
Price paid for the product Shipping costs Carrying cost of inventory Tariffs and taxes Travel for auditing, negotiations, and product support Pre-evaluation, supplier selection, and regulatory compliance Cost of preparing and administrating contracts with a foreign supplier
LO17.4 Calculate the total cost of outsourcing and offshoring.
Costs of Offshoring
Outsource
No Yes
Offshore
No Domestic Domestic In-house Outsource
Yes Offshore Offshore In-house Outsource
TABLE 17.3 Offshoring and Outsourcing
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Based on this analysis the cost of offshoring the part is $7.39 versus making it in-house for $7.68. Even though the price of the product manufactured in China is only $5.22 or 68 percent of U.S. manufacturing costs, the added costs increase the total to 96 percent of U.S. costs. Considering the risks and qualitative factors involved, is it worth it to offshore this product in China—probably not!
Qualitative Factors in Offshoring Aside from costs, qualitative factors also need to be considered in offshoring. These are factors that could cost the company money, but are very difficult to estimate.
Costs of currency changes over time Potential costs of quality, rework, warranty and legal costs of product failures Airfreight costs to overcome delivery or quality problems Wage inflation over time Loss of intellectual property Costs due to work stoppage or supply chain disruption
While these costs are difficult to estimate, they are not zero. They could tip the balance in specific cases. Below, we discuss a weighted scoring model that considers costs and quali- tative factors, as well.
Reshoring is bringing services or products back to the home country after moving them earlier to offshore. This happens when the economic benefits of producing offshore are no longer advantageous. Typically, wages increase much faster in the offshore location than the home country. As the wage rates become more equal, production will be either
Reshoring
The Widget Company, previously discussed, has the opportunity to secure an offshore source in China for its plastic molded part. A commitment is needed to order 100,000 units at a time, which is a one-year supply. It is typical for foreign producers to ask for large orders in order to justify buying the molds, setting up the equipment, and arranging for facilities and labor.
The following costs are provided. The parts will be shipped in 40-foot containers from the factory in China to a port, then loaded on a ship and sent to the U.S. The containers will then be moved by truck to the Widget Company factory. The total shipping cost of the one-year supply is $60,000. The inventory carrying cost is 20 percent of the aver- age inventory in stock. The pre-evaluation, product support, and auditing cost is based on expenses of $100,000 per year for trips to China and associated salaries of engineers and auditors for this product. A contract administration cost of $5,000 is incurred in the U.S. assigned to this contract. See Table 17.4 for the calculations of offshore costs.
Example Offshoring Total Costs
Total Cost of Offshoring
Unit price in China $5.22 • Shipping costs are $60,000 for 100,000 units or $.60 each.
• Inventory carrying costs. On average each unit is carried in inventory for 6 months of the one-year supply. The carrying cost is $5.22 × .20/2 = $.52
• Contract administration cost is $5,000 for 100,000 units or $.05 each.
Shipping costs .60 Tariffs 0 Inventory carrying costs .52 Product support and auditing 1.00 Administration of contract .05
Total costs $7.39
TABLE 17.4 Total Costs of Offshoring
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moved to another lower wage country or back to the home country. Currency differences, tariffs, and transportation costs can also cause a company to reshore its products or ser- vices. Reshoring is occurring in some cases because of increases in the supply chain risks associated with quality or delivery. Some companies seek to shorten their supply chain by moving production back onshore or closer to the home market (i.e., near shoring), thereby reducing stock in transit and risks associated with a long supply chain.
There has been a progression of industries moving offshore. An early example is the textile industry moving from England to the U.S. in the 1800s. In the 1900s, textile produc- tion moved from the U.S. to Japan, and then from Japan to other Asian countries. Similar migration has occurred for television and electronics production. The latest migration is products and services moving from China to other Asian countries and in some cases back to the U.S or European countries.
17.5 GLOBAL SOURCING
Global sourcing is the practice of sourcing products and services from the broad global marketplace, across national boundaries. The goal is for buying firms to find the best effi- ciencies or access to the needed products and services. Firms source globally to obtain efficiencies such as low cost labor, low cost raw materials, or tax breaks. Firms might also be seeking access to particular types of skilled labor, new technologies, specialized materi- als, or even to gain access to new customers.
There are many examples of global sourcing. Clothing retailers often look to suppliers in Asia for low cost goods, as well as high volume and high quality manufacturing capa- bilities. Software coding may be sourced from companies in India due to its considerable supply of software engineers. U.S. call centers are frequently sourced from the Philippines for workers’ low cost English speaking skills. Specialized instruments requiring advanced capabilities may be sourced from German suppliers.
Globally sourcing products and services has both advantages and disadvantages over domestic sourcing. The advantages go well beyond low cost labor to include factors such as
learning about potential foreign markets, accessing regional capabilities, locat- ing sources of particular skills and resources, reducing risks associated with the current supply base, and increasing total capacity. Some disadvantages include potential loss of intellectual property, increased monitoring costs, exposure to financial and political risks, and other uncertainties such as cultural differ- ences. Lead times are often longer, and complexities are often increased when sourcing across country borders. These downsides must be weighed against the potential for significantly lower costs or other potential gains.
For an example, we can look at Ashley Furniture Industries, the world’s largest furniture manufacturer and retailer, headquartered in Arcadia, Wis- consin. Fifteen manufacturing and distribution centers provide products for 800 Ashley HomeStores and thousands of retail partners, with distribution reaching into 123 countries.
Ashley’s in-house designers and engineers travel the world to under- stand the latest trends, discover emerging materials, and react quickly to consumer tastes. They manufacture more than 7000 product stock keeping units (SKUs) in 22 product categories (sofas, tables, desks, etc.). From their U.S. facilities, production output is over 50,000 units per day. Ashley uses state-of-the art equipment often designed and built in-house, propri- etary methods, lean systems, and strict quality control.Ken Wolter/123RF
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Many U.S. furniture manufacturers outsourced and offshored either components or full assembly in recent years to reduce labor costs and avoid environmental regulations. Ashley keeps production in-house at both domestic and offshore locations. They have manufacturing facilities in Wisconsin, Mississippi, North Carolina, and Pennsylvania, as well as China and Vietnam. Factory and warehouse locations are chosen strategically to serve regional markets, and this helps to hold down shipping costs and carrying costs in the markets they serve.
We can see that Ashley’s hybrid local and foreign in-house production strategy helps them gain certain advantages and avoid some common downsides of global sourcing. Advantages of Ashley’s foreign locations are close proximity to serving their markets, lower cost production, and access to regional skills and capabilities. While labor costs are much higher in the U.S., Ashley’s domestic factories are able to protect proprietary equip- ment, save importing and transportation costs, and more quickly serve the U.S. market.
17.6 SUPPLY BASE OPTIMIZATION
Supply base optimization is the streamlining of a firm’s suppliers, and removing any unnecessary ones. This is done to make sure that the firm has the right number of suppliers for their needs, and that they are getting the right capabilities from their suppliers. The overall goal is for the firm to manage its suppliers as efficiently as possible and to maintain the right number of suppliers—not too few or too many. Spend analysis and reviewing the number of suppliers are essential activities, as outlined below.
Spend analysis is the first part of supply base optimization. It is analyzing what the firm is buying, from whom, in what quantities, and at what price. In a large firm purchasing is typi- cally very dispersed. There may be a central purchasing office at corporate headquarters, purchasing at various divisions or facilities, and purchasing located internationally. A spend analysis takes data from all of these locations and consolidates spending by product type, supplier, prices, and amounts. As a result, some unusual patterns may be found. One possi- bility is that a particular supplier is being used by several different locations and provides several different types of products. Price concessions may be obtained from that supplier for volume purchasing. Another example is the many different models of laptops bought at multiple locations from the same supplier, but no special pricing has been negotiated.
The second part of supply base optimization is deciding on the number of different sup- pliers. Using too many suppliers can make communications and control complex. Using too few suppliers increases the risk of shortages and supply chain disruptions, and can increase prices. Nevertheless, firms are decreasing their number of suppliers in three ways: consolidating similar suppliers, purchasing families of parts, or using modular production.
Consolidating similar suppliers can be done using spend analysis. It will be possible to determine if the same product, or a similar product, is being purchased from different suppliers. As a result some consolidation may be possible by reviewing past supplier per- formance and pricing, then selecting those suppliers that have the best performance record.
It may be possible to gain economies by purchasing a family of parts, products, or ser- vices from one supplier. For example, an automobile company may be buying its alterna- tors from several different suppliers and electrical components from yet other suppliers. If a family of electrical parts can be identified, then it is possible to source the entire family of parts from only a few suppliers.
Modular production uses common modules in many combinations to produce variety in the final product. A limited number of modules can be assembled in various ways to make
LO17.5 Describe supply base optimization.
Spend Analysis
Total Number of Suppliers
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many different final products. For example, computers use a limited number of processors, screens, and memories to provide a large number of different computers. When modular production is used, the number of suppliers will be limited.
A company can use too few suppliers, as well as too many. When too few suppliers are used, supply chain risk increases. This is particularly true when lean operations are imple- mented with very limited inventory. Production stops or service stops when a disruption occurs, and there is no alternative supplier or enough inventory for the supplier to recover before the inventory runs out.
A firm needs to develop a policy or strategy on when it will use single suppliers and when to use multiple suppliers. A case for a single supplier, known as sole sourcing, can usually be made in the following situations:
1. The single supplier provides the product or service from two or more different loca- tions. These locations are separated geographically to minimize the disruption risk from natural disasters such as floods, hurricanes, tsunamis, or tornadoes. The separate loca- tions should have the capacity to provide additional product to make up for the loss of a single facility.
2. The single supplier carries enough inventory to provide sufficient time for recovery from man-made or natural disasters. The required inventory level is negotiated as part of the purchasing contract and not stored on-site at the supplier.
Aside from business continuity concerns, a single supplier raises the prospect of future price opportunism. Some firms have multiple suppliers for critical products to bring price competition into play. If there is only one supplier, however, market analysis can be done if the supplier proposes price changes.
An advantage of a single supplier is better quality and economies of scale. A supplier that has a particularly good process and is certified for quality could be considered as a preferred supplier. In this case, if the supplier is given all the business for a product or ser- vice, the lower price of scale economies and volume purchasing can be expected. Another opportunity from sole sourcing is developing a partnership with a trusted supplier. Col- laborative work becomes a win-win for both parties, providing value beyond just pricing, and may improve the buying firm’s competitiveness. Still, the above steps must be taken to reduce the risk of supply chain disruptions from the single supplier.
Another option is cross-sourcing, when a firm uses one supplier for one part of the business and another supplier with similar capabilities in another part of the business. For example, an automobile company may have one supplier make transmissions for one model and another supplier make transmissions for another model. This provides some flexibility when one supplier has problems, because they can fill in for one another.
Dual sourcing is when two suppliers are used for the same product. In this case, a majority of the business may be given to one supplier and the other is treated as a back- up supplier. The firm needs to form a strategy for which products and services use single sourcing, dual sourcing, and cross-sourcing. This strategy will help guide individual pur- chasing decisions when the need arises to issue a sourcing contract.
Preferred suppliers are designated based on past performance. A preferred supplier meets criteria such as proven quality, on-time deliveries, competitive pricing, agreeable payment terms, ethical business practices, and social and community support. Just because a supplier is preferred doesn’t mean that it will be the sole supplier. A preferred supplier may be part of a bidding process or one of multiple suppliers depending on the amount of the spending and type of product.
Single or Multiple Suppliers
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