Chapter summary & Homework

OPERATIONS MANAGEMENT

THIRD CANADIAN EDITION

JAY HEIZER Texas Lutheran University

BARRY RENDER Graduate School of Business, Rollins College

CHUCK MUNSON Carson College of Business, Washington State University

PAUL GRIFFIN Humber Institute of Technology and Advanced Learning

SUSTAINABILITY AND SUPPLY CHAIN MANAGEMENT

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To Kathryn Ann Heizer —JH

To Donna, Charlie, Jesse, and Reva and to Howard G. Kornacki, the teacher who taught

me to love math —BR

To Suzanne, Alexandra, Kenna, Ryan, and Robert Kathleen

—PG

Pearson Canada Inc., 26 Prince Andrew Place, North York, Ontario M3C 2H4.

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ISBN 978-0-13-483807-6

1 20

Library and Archives Canada Cataloguing in Publication

Heizer, Jay, author Operations management : sustainability and supply chain management / Jay Heizer, Barry Render, Chuck Munson, Paul Griffin. -- Third Canadian edition.

Includes bibliographical references and indexes. ISBN 978-0-13-483807-6 (softcover)

1. Production management--Textbooks. 2. Textbooks. I. Render, Barry, author II. Munson, Chuck, author III. Griffin, Paul, 1961-, author IV. Title.

TS155.H3726 2018 658.5 C2018-904040-8

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About the Authors

iii

Jay Heizer Professor Emeritus, the Jesse H. Jones Chair of Business Administration, Texas Lutheran University, Seguin, Texas. He received his B.B.A. and M.B.A. from the University of North Texas and his Ph.D. in Management and Statistics from Arizona State University. He was previously a member of the faculty at the University of Memphis, the University of Oklahoma, Virginia Commonwealth University, and the University of Richmond. He has also held visiting positions at Boston University, George Mason University, the Czech Management Center, and the Otto-Von-Guericke University, Magdeburg.

Dr. Heizer’s industrial experience is extensive. He learned the practical side of operations manage- ment as a machinist apprentice at Foringer and Company, as a production planner for Westinghouse Airbrake, and at General Dynamics, where he worked in engineering administration. In addition, he has been actively involved in consulting in the OM and MIS areas for a variety of organizations, including Philip Morris, Firestone, Dixie Container Corporation, Columbia Industries, and Tenneco. He holds the CPIM certification from APICS—the Association for Operations Management.

Professor Heizer has co-authored five books and has published more than 30 articles on a variety of management topics. His papers have appeared in the Academy of Management Journal, Journal of Purchasing, Personnel Psychology, Production & Inventory Control Management, APICS— The Performance Advantage, Journal of Management History, IIE Solutions, and Engineering Management, among others. He has taught operations management courses in undergraduate, graduate, and executive programs.

Barry Render Professor Emeritus, the Charles Harwood Professor of Operations Management, Crummer Graduate School of Business, Rollins College, Winter Park, Florida. He received his B.S. in Mathematics and Physics at Roosevelt University, and his M.S. in Operations Research and Ph.D. in Quantitative Analysis at the University of Cincinnati. He previously taught at George Washington University, University of New Orleans, Boston University, and George Mason University, where he held the Mason Foundation Professorship in Decision Sciences and was Chair of the Decision Sciences Department. Dr. Render has also worked in the aerospace industry for General Electric, McDonnell Douglas, and NASA.

Professor Render has co-authored 10 textbooks for Prentice Hall, including Managerial Decision Modeling with Spreadsheets, Quantitative Analysis for Management, Service Management, Introduction to Management Science, and Cases and Readings in Management Science. Quantitative Analysis for Management, now in its 11th edition, is a leading text in that discipline in the United States and globally. Dr. Render’s more than 100 articles on a variety of management topics have appeared in Decision Sciences, Production and Operations Management, Interfaces, Information and Management, Journal of Management Information Systems, Socio-Economic Planning Sciences, IIE Solutions, and Operations Management Review, among others.

Dr. Render has been honoured as an AACSB Fellow and was twice named a Senior Fulbright Scholar. He was Vice President of the Decision Science Institute Southeast Region and served as Software Review Editor for Decision Line for six years and as Editor of the New York Times Operations Management special issues for five years. From 1984 to 1993, Dr. Render was President of Management Service Associates of Virginia, Inc., whose technology clients included the FBI, the U.S. Navy, Fairfax County, Virginia, and C&P Telephone. He is currently Consulting Editor to Financial Times Press.

Dr. Render has taught operations management courses in Rollins College’s MBA and Executive MBA programs. He has received that school’s Welsh Award as leading Professor and was selected by Roosevelt University as the 1996 recipient of the St. Claire Drake Award for Outstanding Scholarship. In 2005, Dr. Render received the Rollins College MBA Student Award for Best Overall Course, and in 2009 was named Professor of the Year by full-time MBA students.

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iv About the Authors

Chuck Munson Professor of Operations Management, Carson College of Business, Washington State University, Pullman, Washington. He received his BSBA summa cum laude in finance, along with his MSBA and Ph.D. in operations management, from Washington University in St. Louis. For two years, he served as Associate Dean for Graduate Programs in Business at Washington State. He also worked for three years as a financial analyst for Contel Telephone Corporation.

Professor Munson serves as a senior editor for Production and Operations Management, and he serves on the editorial review board of four other journals. He has published more than 25 articles in such journals as Production and Operations Management, IIE Transactions, Decision Sciences, Naval Research Logistics, European Journal of Operational Research, Journal of the Operational Research Society, and Annals of Operations Research. He is editor of the book The Supply Chain Management Casebook: Comprehensive Coverage and Best Practices in SCM, and he has co-authored the research monograph Quantity Discounts: An Overview and Practical Guide for Buyers and Sellers. He is also coauthor of Managerial Decision Modeling with Spreadsheets (4th edition), published by Pearson.

Dr. Munson has taught operations management core and elective courses at the undergraduate, MBA, and Ph.D. levels at Washington State University. He has also conducted several teaching workshops at international conferences and for Ph.D. students at Washington State University. His major awards include being a Founding Board Member of the Washington State University President’s Teaching Academy (2004); winning the WSU College of Business Outstanding Teaching Award (2001 and 2015), Research Award (2004), and Service Award (2009 and 2013); and being named the WSU MBA Professor of the Year (2000 and 2008).

Paul Griffin Associate Dean, Business Degrees, Humber Institute of Technology & Advanced Learning, Toronto, Ontario, Canada. He received his Ph.D. in Management from the University of Bradford in the United Kingdom and has also achieved 18 professional designations, including Chartered Professional Accountant (CPA), Certified Management Accountant (CMA), Certified General Accountant (CGA), Certified Financial Planner (CFP), Fellow of the Canadian Securities Institute (FCSI), and several others.

Before joining academia, Dr. Griffin was engaged in the financial services sector for over 20 years and was most recently the National Director of Operations and Compliance at ING Canada. He remains an active member of several boards and committees, most notably the Insurance Institute of Canada’s Ethics Advisory Board and the Financial Services Commission of Ontario’s Advisory Board, and he serves as Chair of the Education Committee and Board of Directors for the Canadian Institute of Financial Planning. Before becoming Associate Dean at Humber, Dr. Griffin was a Professor and taught operations management, accounting, finance, and marketing. During that time, he received the Award of Excellence for Outstanding Academic Contribution.

Dr. Griffin continues to write for practitioner-targeted publications and develops a continuous stream of technical manuals, materials, and courses for both the academic and industrial sectors. He remains an active member of the Editorial Advisory Board for the Journal of Financial Planning.

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Brief Table of Contents

v

PART ONE Introduction to Operations Management 1 1 Operations and Productivity 1 2 Operations Strategy in a Global

Environment 26

3 Project Management 58 4 Forecasting 103

PART TWO Designing Operations 151 5 Design of Goods and Services 151 Supplement 5: Sustainability in the

Supply Chain 183

6 Managing Quality 203 Supplement 6: Statistical

Process Control 233

7 Process Strategy 264 Supplement 7: Capacity and

Constraint Management 293

8 Location Strategies 322 9 Layout Strategies 349 10 Human Resources, Job Design,

and Work Measurement 387

PART THREE Managing Operations 421 11 Supply Chain Management 421 Supplement 11: Supply Chain

Management Analytics 453

12 Inventory Management 468

13 Aggregate Planning and Sales and Operations Planning 512

14 Material Requirements Planning (MRP) and ERP 543

15 Short-Term Scheduling 580 16 Lean Operations 617 17 Maintenance and Reliability 643

PART FOUR Business Analytics Modules 661 A Decision-Making Tools 661 B Linear Programming 681 C Transportation Models 711 D Waiting-Line Models 731 E Learning Curves 761 F Simulation 775 Appendix A1

Bibliography B1

Indices I1

Online Tutorials 1 Statistical Tools for Managers T1-1 2 Acceptance Sampling T2-1 3 The Simplex Method of Linear

Programming T3-1

4 The MODI and VAM Methods of Solving Transportation Problems T4-1

5 Vehicle Routing and Scheduling T5-1

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About the Authors

vi

About the Authors iii Preface xvi

PART ONE Introduction to Operations Management 1

1 Operations and Productivity 1 What Is Operations Management? 2 Organizing to Produce Goods and Services 3

The Supply Chain 4 Why Study Operations Management? 4 What Operations Managers Do 5

Where Are the OM Jobs? 6 The Heritage of Operations Management 6 Operations in the Service Sector 9

Differences Between Goods and Services 9 Growth of Services 9 Service Pay 10

New Challenges in Operations Management 11 The Productivity Challenge 11

Productivity Measurement 12 Productivity Variables 14 Productivity and the Service Sector 16

Ethics, Social Responsibility, and Sustainability 17 Chapter Summary 18 • Ethical Dilemma 18 • Discussion Questions 19 • Solved Problems 19 • Problems 20 • Case Studies: National Air Express 21 • Video Case Studies: Frito- Lay: Operations Management in Manufacturing 22 • Hard Rock Cafe: Operations Management in Services 22 • Rapid Review 23 • Self-Test 25

2 Operations Strategy in a Global Environment 26 A Global View of Operations and Supply Chains 28

Reduce Costs 29 Improve the Supply Chain 30 Provide Better Goods and Services 30 Understand Markets 30 Learn to Improve Operations 31 Attract and Retain Global Talent 31

Cultural and Ethical Issues 31 Developing Missions and Strategies 32

Mission 32 Strategy 32

Achieving Competitive Advantage Through Operations 33

Competing on Differentiation 34 Competing on Cost 34 Competing on Response 35

10 Strategic OM Decisions 36 Issues in Operations Strategy 39 Strategy Development and Implementation 40

Key Success Factors and Core Competencies 41 Build and Staff the Organization 42 Integrate OM with Other Activities 42

Strategic Planning, Core Competencies, and Outsourcing 43

The Theory of Comparative Advantage 44 Risks of Outsourcing 44 Rating Outsource Providers 45

Global Operations Strategy Options 47 International Strategy 47 Multidomestic Strategy 48 Global Strategy 48 Transnational Strategy 48 Chapter Summary 49 • Ethical Dilemma 49 • Discussion Questions 50 • Solved Problems 50 • Problems 51 • Case Studies: Mr. Lube 53 • Video Case Studies: Operations Strategy at Regal Marine 53 • Hard Rock Cafe’s Global Strategy 53 • Rapid Review 54 • Self-Test 56

3 Project Management 58 The Importance of Project Management 59 Project Planning 60

The Project Manager 61 Work Breakdown Structure 61

Project Scheduling 62 Project Controlling 64 Project Management Techniques: PERT and CPM 65

The Framework of PERT and CPM 65 Network Diagrams and Approaches 66 Activity-on-Node Example 67 Activity-on-Arrow Example 69

Determining the Project Schedule 70 Forward Pass 70 Backward Pass 72

Table of Contents

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Table of Contents vii

Calculating Slack Time and Identifying the Critical Path(s) 73

Variability in Activity Times 75 Three Time Estimates in PERT 76 Probability of Project Completion 77

Cost–Time Trade-Offs and Project Crashing 81 A Critique of PERT and CPM 83

Advantages 83 Limitations 84

Using Microsoft Project to Manage Projects 84 Entering Data 84 Viewing the Project Schedule 85 PERT Analysis 86 Tracking the Time Status of a Project 86 Chapter Summary 87 • Ethical Dilemma 87 • Discussion Questions 87 • Using Software to Solve Project Management Problems 88 • Solved Problems 88 • Problems 91 • Case Studies: Fast Creek Lightning: (A) 96 • Video Case Studies: Project Management at Arnold Palmer Hospital 97 • Managing Hard Rock’s Rockfest 98 • Rapid Review 100 • Self-Test 102

4 Forecasting 103 What Is Forecasting? 104

Forecasting Time Horizons 105 The Influence of Product Life Cycle 105 Types of Forecasts 106

The Strategic Importance of Forecasting 106 Supply Chain Management 106 Human Resources 106 Capacity 106

Seven Steps in the Forecasting System 107 Forecasting Approaches 107

Overview of Qualitative Methods 107 Overview of Quantitative Methods 108

Time-Series Forecasting 108 Decomposition of a Time Series 108 Naive Approach 109 Moving Averages 109 Exponential Smoothing 112 Measuring Forecast Error 113 Exponential Smoothing with Trend Adjustment 116 Trend Projections 119 Seasonal Variations in Data 122 Cyclical Variations in Data 126

Associative Forecasting Methods: Regression and Correlation Analysis 126

Using Regression Analysis for Forecasting 126 Standard Error of the Estimate 128

Correlation Coefficients for Regression Lines 129 Multiple-Regression Analysis 131

Monitoring and Controlling Forecasts 132 Adaptive Smoothing 133 Focus Forecasting 133

Forecasting in the Service Sector 134 Specialty Retail Shops 134 Fast-Food Restaurants 134 Chapter Summary 135 • Ethical Dilemma 135 • Discussion Questions 136 • Using Software in Forecasting 136 • Solved Problems 138 • Problems 139 • Case Studies: Fast Creek Lightning: (B) 146 • Video Case Studies: Forecasting at Hard Rock Cafe 146 • Rapid Review 147 • Self-Test 150

PART TWO Designing Operations 151

5 Design of Goods and Services 151 Goods and Services Selection 152

Product Strategy Options Support Competitive Advantage 153 Product Life Cycles 154 Life Cycle and Strategy 154 Product-by-Value Analysis 155

Generating New Products 155 New Product Opportunities 155 Importance of New Products 155

Product Development 156 Product Development System 156 Quality Function Deployment (QFD) 157 Organizing for Product Development 160 Manufacturability and Value Engineering 161

Issues for Product Design 162 Robust Design 162 Modular Design 162 Computer-Aided Design (CAD) 162 Computer-Aided Manufacturing (CAM) 163 Virtual Reality Technology 164 Value Analysis 164 Sustainability and Life Cycle Assessment (LCA) 164

Time-Based Competition 164 Purchasing Technology by Acquiring a Firm 166 Joint Ventures 166 Alliances 166

Defining a Product 166 Make-or-Buy Decisions 167 Group Technology 168

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viii Table of Contents

Documents for Production 169 Product Life Cycle Management (PLM) 169

Service Design 170 Process–Chain–Network (PCN) Analysis 170 Adding Service Efficiency 172 Documents for Services 172

Application of Decision Trees to Product Design 173 Transition to Production 175

Chapter Summary 175 • Ethical Dilemma 176 • Discussion Questions 176 • Solved Problem 176 • Problems 177 • Case Studies: StackTeck 179 • Video Case Studies: Product Strategy at Regal Marine 179 • Rapid Review 180 • Self-Test 182

5 Supplement: Sustainability in the Supply Chain 183 Corporate Social Responsibility 184 Sustainability 185

Systems View 185 Commons 185 Triple Bottom Line 185

Design and Production for Sustainability 188 Product Design 188 Production Process 190 Logistics 190 End-of-Life Phase 193

Regulations and Industry Standards 193 International Environmental Policies and Standards 194 Supplement Summary 195 • Discussion Questions 195 • Solved Problems 196 • Problems 197 • Video Case Studies: Building Sustainability at the Orlando Magic’s Amway Center 199 • Green Manufacturing and Sustainability at Frito-Lay 199 • Rapid Review 200 • Self-Test 202

6 Managing Quality 203 Quality and Strategy 204 Defining Quality 205

Implications of Quality 206 National Quality Awards 206 ISO 9000 International Quality Standards 206 ISO 14000 206 Cost of Quality (COQ) 207 Ethics and Quality Management 208

Total Quality Management 208 Continuous Improvement 209 Six Sigma 210 Employee Empowerment 211 Benchmarking 211

Just-in-Time (JIT) 213 Taguchi Concepts 213 Knowledge of TQM Tools 214

Tools of TQM 214 Check Sheets 214 Scatter Diagrams 214 Cause-and-Effect Diagrams 214 Pareto Charts 215 Flowcharts 217 Histograms 218 Statistical Process Control (SPC) 218

The Role of Inspection 219 When and Where to Inspect 219 Source Inspection 220 Service Industry Inspection 220 Inspection of Attributes versus Variables 220

TQM in Services 221 Chapter Summary 223 • Ethical Dilemma 224 • Discussion Questions 224 • Problems 224 • Case Studies: Fast Creek Lightning: (C) 226 • Video Case Studies: The Culture of Quality at Arnold Palmer Hospital 227 • Quality Counts at Alaska Airlines 228 • TQM at Ritz-Carlton Hotels 229 • Rapid Review 230 • Self-Test 232

6 Supplement: Statistical Process Control 233 Statistical Process Control (SPC) 233

Natural Variations 233 Assignable Variations 234 Samples 234 Control Charts 235 Control Charts for Variables 235 The Central Limit Theorem 235 Setting Mean Chart Limits (X -Charts) 237 Setting Range Chart Limits (R-Charts) 240 Using Mean and Range Charts 240 Control Charts for Attributes 242 Managerial Issues and Control Charts 245

Process Capability 246 Process Capability Ratio (Cp) 246 Process Capability Index (Cpk) 247

Acceptance Sampling 248 Operating Characteristic Curve 248 Average Outgoing Quality 250 Supplement Summary 251 • Discussion Questions 251 • Using Software for SPC 252 • Solved Problems 253 • Problems 254 • Case Studies: PEI Potato Purveyors 258 • Video Case Studies: Frito-Lay’s Quality-Controlled Potato Chips 260 • Farm to Fork: Quality at Darden Restaurants 260 • Rapid Review 261 • Self-Test 263

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Table of Contents ix

7 Process Strategy 264 Four Process Strategies 266

Process Focus 266 Repetitive Focus 267 Product Focus 267 Mass Customization Focus 268 Comparison of Process Choices 270

Selection of Equipment and Technology 272 Process Analysis and Design 273

Flowchart 274 Time-Function Mapping 274 Value-Stream Mapping 274 Process Charts 275 Service Blueprinting 276

Special Considerations for Service Process Design 277

Customer Interaction and Process Design 277 More Opportunities to Improve Service Processes 279

Production Technology 279 Machine Technology 279 Automatic Identification Systems (AISs) and RFID 280 Process Control 280 Vision Systems 281 Robots 281 Automated Storage and Retrieval Systems (ASRSs) 281 Automated Guided Vehicles (AGVs) 281 Flexible Manufacturing Systems (FMSs) 281 Computer-Integrated Manufacturing (CIM) 282

Technology in Services 283 Process Redesign 284

Chapter Summary 285 • Ethical Dilemma 285 • Discussion Questions 285 • Solved Problem 286 • Problems 286 • Case Studies: Regina Manufacturing’s Process Decision 287 • Environmental Sustainability at Walmart 287 • Video Case Studies: Process Strategy at Wheeled Coach Ambulance 288 • Process Analysis at Arnold Palmer Hospital 288 • Alaska Airlines: 20-Minute Baggage Process—Guaranteed! 289 • Rapid Review 290 • Self-Test 292

7 Supplement: Capacity and Constraint Management 293 Capacity 293

Design and Effective Capacity 293 Capacity and Strategy 296 Capacity Considerations 296

Managing Demand 297 Demand and Capacity Management in the Service Sector 299

Bottleneck Analysis and the Theory of Constraints 299 Theory of Constraints 302 Bottleneck Management 302

Break-Even Analysis 304 Assumptions 304 Graphic Approach 304 Algebraic Approach 305 Single-Product Case 305 Multiproduct Case 306

Reducing Risk with Incremental Changes 308 Applying Expected Monetary Value (EMV) to Capacity Decisions 309 Applying Investment Analysis to Strategy-Driven Investments 309

Investment, Variable Cost, and Cash Flow 309 Net Present Value 309 Supplement Summary 312 • Discussion Questions 312 • Using Software for Break-Even Analysis 312 • Solved Problems 313 • Problems 315 • Video Case Study: Capacity Planning at Arnold Palmer Hospital 318 • Rapid Review 319 • Self-Test 321

8 Location Strategies 322 The Strategic Importance of Location 323

Location and Costs 324 Factors that Affect Location Decisions 324

Labour Productivity 326 Exchange Rates and Currency Risk 326 Costs 327 Political Risk, Values, and Culture 327 Proximity to Markets 327 Proximity to Suppliers 328 Proximity to Competitors (Clustering) 329

Methods of Evaluating Location Alternatives 329 The Factor Rating Method 329 Locational Break-Even Analysis 330 Centre-of-Gravity Method 332 Transportation Model 333

Service Location Strategy 334 Geographic Information Systems 334 Chapter Summary 336 • Ethical Dilemma 336 • Discussion Questions 336 • Using Software to Solve Location Problems 337 • Solved Problems 337 • Problems 339 • Case Studies: Atlantic Assembly Services 344 • Video Case Studies: Locating the Next Red Lobster Restaurant 344 • Hard Rock’s Location Selection 345 • Rapid Review 346 • Self-Test 348

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x Table of Contents

9 Layout Strategies 349 The Strategic Importance of Layout Decisions 350 Types of Layout 351 Office Layout 352 Retail Layout 353

Servicescapes 355 Warehousing and Storage Layouts 356

Cross-Docking 356 Random Stocking 357 Customizing 358

Fixed-Position Layout 358 Process-Oriented Layout 359

Computer Software for Process-Oriented Layouts 363

Work Cells 364 Requirements of Work Cells 364 Staffing and Balancing Work Cells 365 The Focused Work Centre and the Focused Factory 367

Repetitive and Product-Oriented Layout 367 Assembly-Line Balancing 368 Chapter Summary 373 • Ethical Dilemma 373 • Discussion Questions 373 • Using Software to Solve Layout Problems 373 • Solved Problems 374 • Problems 377 • Case Studies: Automobile Licence Renewals 382 • Video Case Studies: Layout at Arnold Palmer Hospital 383 • Facility Layout at Wheeled Coach Ambulance 384 • Rapid Review 385 • Self-Test 386

10 Human Resources, Job Design, and Work Measurement 387 Human Resource Strategy for Competitive Advantage 389

Constraints on Human Resource Strategy 389 Labour Planning 390

Employment-Stability Policies 390 Work Schedules 390 Job Classifications and Work Rules 391

Job Design 391 Labour Specialization 391 Job Expansion 392 Psychological Components of Job Design 392 Self-Directed Teams 393 Motivation and Incentive Systems 393

Ergonomics and the Work Environment 395 Ergonomics 395 Operator Input to Machines 395 Feedback to Operators 395 The Work Environment 396

Methods Analysis 397 The Visual Workplace 399 Labour Standards 400

Historical Experience 400 Time Studies 400 Predetermined Time Standards 405 Work Sampling 407

Ethics 409 Chapter Summary 410 • Ethical Dilemma 410 • Discussion Questions 410 • Solved Problems 411 • Problems 413 • Case Studies: Jackson Manufacturing Company 416 • Video Case Studies: The “People” Focus: Human Resources at Alaska Airlines 416 • Human Resources at Hard Rock Cafe 417 • Rapid Review 418 • Self-Test 420

PART THREE Managing Operations 421

11 Supply Chain Management 421 The Supply Chain’s Strategic Importance 422

Supply Chain Risk 424 Ethics and Sustainability 425

Personal Ethics 425 Ethics within the Supply Chain 425 Ethical Behaviour Regarding the Environment 425

Supply Chain Economics 426 Make-or-Buy Decisions 427 Outsourcing 427

Supply Chain Strategies 427 Many Suppliers 428 Few Suppliers 428 Vertical Integration 428 Joint Ventures 429 Keiretsu Networks 429 Virtual Companies 429

Managing the Supply Chain 430 Mutual Agreement on Goals 430 Trust 430 Compatible Organizational Cultures 430 Issues in an Integrated Supply Chain 431 Opportunities in an Integrated Supply Chain 431

Eprocurement 433 Electronic Ordering and Funds Transfer 434 Online Catalogues 434 Auctions 434

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Table of Contents xi

RFQs 434 Real-Time Inventory Tracking 434

Vendor Selection 435 Vendor Evaluation 435 Vendor Development 436 Negotiations 436 Contracting 437 Centralized Purchasing 437 E-Procurement 437

Logistics Management 438 Distribution Systems 438 Warehousing 439 Third-Party Logistics 440 Cost of Shipping Alternatives 440 Security and JIT 441

Measuring Supply Chain Performance 442 Supply Chain Performance 442 Assets Committed to Inventory 442 The SCOR Model 444 Chapter Summary 445 • Ethical Dilemma 445 • Discussion Questions 445 • Solved Problems 445 • Problems 446 • Case Studies: Dell ’s Value Chain 447 • Video Case Studies: Darden’s Global Supply Chain 448 • Supply Chain Management at Regal Marine 449 • Arnold Palmer Hospital ’s Supply Chain 449 • Rapid Review 450 • Self-Test 452

11 Supplement: Supply Chain Management Analytics 453 Techniques for Evaluating Supply Chains 453 Evaluating Disaster Risk in the Supply Chain 453 Managing the Bullwhip Effect 455

A Bullwhip Effect Measure 456 Supplier Selection Analysis 457 Transportation Mode Analysis 458 Warehouse Storage 459

Supplement Summary 460 • Discussion Questions 460 • Solved Problems 460 • Problems 462 • Rapid Review 465 • Self-Test 467

12 Inventory Management 468 The Importance of Inventory 470

Functions of Inventory 471 Types of Inventory 471

Managing Inventory 472 ABC Analysis 472 Record Accuracy 474 Cycle Counting 474 Control of Service Inventories 476

Inventory Models 478

Independent versus Dependent Demand 478 Holding, Ordering, and Setup Costs 478

Inventory Models for Independent Demand 478 The Basic Economic Order Quantity (EOQ) Model 479 Minimizing Costs 479 Reorder Points 483 Production Order Quantity Model 485 Quantity Discount Models 487

Probabilistic Models and Safety Stock 490 Other Probabilistic Models 493

Single-Period Model 495 Fixed-Period (P) Systems 496

Chapter Summary 497 • Ethical Dilemma 497 • Discussion Questions 497 • Using Software to Solve Inventory Problems 498 • Solved Problem 499 • Problems 502 • Case Studies: Zhou Bicycle Company 507 • Video Case Studies: Managing Inventory at Frito-Lay 507 • Inventory Control at Wheeled Coach Ambulance 508 • Rapid Review 508 • Self-Test 510

13 Aggregate Planning and Sales and Operations Planning 512 The Planning Process 513

Sales and Operations Planning 513 The Nature of Aggregate Planning 515 Aggregate Planning Strategies 516

Capacity Options 517 Demand Options 517 Mixing Options to Develop a Plan 518

Methods for Aggregate Planning 519 Graphical Methods 519 Mathematical Approaches 523 Comparison of Aggregate Planning Methods 525

Aggregate Planning in Services 526 Restaurants 526 Hospitals 527 National Chains of Small Service Firms 527 Miscellaneous Services 527 Airline Industry 528

Yield Management 528 Chapter Summary 531 • Ethical Dilemma 531 • Discussion Questions 532 • Using Software for Aggregate Planning 532 • Solved Problems 533 • Problems 534 • Case Studies: Fast Creek Lightning (G) 538 • Andrew-Carter, Inc. 539 • Video Case Studies: Using Revenue Management to Set Orlando Magic Ticket Prices 540 • Rapid Review 540 • Self-Test 542

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xii Table of Contents

14 Material Requirements Planning (MRP) and ERP 543 Dependent Demand 544 Dependent Inventory Model Requirements 545

Master Production Schedule 545 Bills of Material 547 Accurate Inventory Records 549 Purchase Orders Outstanding 549 Lead Times for Components 549

MRP Structure 550 MRP Management 554

MRP Dynamics 554 MRP and JIT 554

Lot-Sizing Techniques 555 Lot-for-Lot 555 Economic Order Quantity (EOQ) 556 Periodic Order Quantity 557 Lot-Sizing Summary 558

Extensions of MRP 559 Material Requirements Planning II (MRP II) 559 Closed-Loop MRP 560 Capacity Planning 560

MRP in Services 561 Restaurants 562 Hospitals 562 Hotels 562 Distribution Resource Planning (DRP) 563

Enterprise Resource Planning (ERP) 563 ERP in the Service Sector 565 Chapter Summary 566 • Ethical Dilemma 566 • Discussion Questions 566 • Using Software to Solve MRP Problems 566 • Solved Problems 568 • Problems 571 • Case Studies: Hill ’s Automotive, Inc. 575 • Video Case Studies: When 18 500 Orlando Magic Fans Come to Dinner 575 • MRP at Wheeled Coach Ambulance 576 • Rapid Review 577 • Self-Test 579

15 Short-Term Scheduling 580 The Importance of Short-Term Scheduling 581 Scheduling Issues 582

Forward and Backward Scheduling 583 Finite and Infinite Loading 584 Scheduling Criteria 585

Scheduling Process-Focused Facilities 586 Loading Jobs 586

Input–Output Control 586 Gantt Charts 588 Assignment Method 588

Sequencing Jobs 592 Priority Rules for Dispatching Jobs 592 Critical Ratio 595 Sequencing N Jobs on Two Machines: Johnson’s Rule 595 Limitations of Rule-Based Dispatching Systems 597

Finite Capacity Scheduling (FCS) 597 Scheduling Repetitive Facilities 599 Scheduling Services 599

Hospitals 599 Banks 599 Retail Stores 600 Airlines 600 24/7 Operations 600 Scheduling Service Employees with Cyclical Scheduling 601 Cyclical Scheduling 601 Chapter Summary 603 • Ethical Dilemma 603 • Discussion Questions 603 • Using Software for Short-Term Scheduling 603 • Solved Problems 605 • Problems 608 • Case Studies: Old Muskoka Wood Store 611 • Video Case Studies: From the Eagles to the Magic: Converting the Amway Center 612 • Scheduling at Hard Rock Cafe 614 • Rapid Review 614 • Self-Test 616

16 Lean Operations 617 Lean Operations 619

Eliminate Waste 619 Remove Variability 621 Improve Throughput 621

Lean and Just-in-Time 621 Supplier Partnerships 621

Lean Layout 624 Distance Reduction 624 Increased Flexibility 624 Impact on Employees 624 Reduced Space and Inventory 625

Lean Inventory 625 Reduce Inventory and Variability 625 Reduce Lot Sizes 626 Reduce Setup Costs 627

Lean Scheduling 628 Level Schedules 628 Kanban 629

Lean Quality 631 Toyota Production System 632

Continuous Improvement 632 Respect for People 633 Processes and Standard Work Practice 633

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Lean Organizations 633 Building a Lean Organization 633 Lean Sustainability 634

Lean Operations in Services 635 Suppliers 635 Layouts 635 Inventory 635 Scheduling 635 Chapter Summary 635 • Ethical Dilemma 636 • Discussion Questions 636 • Solved Problems 636 • Problems 637 • Case Studies: Saskatchewan Mutual Insurance Company 638 • Video Case Studies: Lean Operations at Alaska Airline 638 • JIT at Arnold Palmer Hospital 640 • Rapid Review 640 • Self-Test 642

17 Maintenance and Reliability 643 The Strategic Importance of Maintenance and Reliability 644 Reliability 645

Improving Individual Components 645 Providing Redundancy 647

Maintenance 649 Implementing Preventive Maintenance 649 Increasing Repair Capabilities 652 Autonomous Maintenance 653

Total Productive Maintenance 653 Techniques for Enhancing Maintenance 653

Simulation 653 Expert Systems 654 Automated Sensors 654 Chapter Summary 654 • Ethical Dilemma 654 • Discussion Questions 654 • Using Software to Solve Reliability Problems 655 • Solved Problems 655 • Problems 655 • Video Case Study: Maintenance Drives Profits at Frito-Lay 657 • Rapid Review 658 • Self-Test 659

PART FOUR Business Analytics Modules 661

A Decision-Making Tools 661 The Decision Process in Operations 661 Fundamentals of Decision Making 662 Decision Tables 663 Types of Decision-Making Environments 664

Decision Making Under Uncertainty 664

Decision Making Under Risk 665 Decision Making Under Certainty 665 Expected Value of Perfect Information (EVPI) 666

Decision Trees 667 A More Complex Decision Tree 668

Using Decision Trees in Ethical Decision Making 670

The Poker Decision Process 671 Module Summary 671 • Discussion Questions 671 • Using Software for Decision Models 672 • Solved Problems 673 • Problems 674 • Case Study: Tom Tucker’s Liver Transplant 678 • Rapid Review 678 • Self-Test 680

B Linear Programming 681 Why Use Linear Programming? 681 Requirements of a Linear Programming Problem 682 Formulating Linear Programming Problems 682

Glickman Electronics Example 682 Graphical Solution to a Linear Programming Problem 683

Graphical Representation of Constraints 683 Iso-Profit Line Solution Method 684 Corner-Point Solution Method 687

Sensitivity Analysis 688 Sensitivity Report 689 Changes in the Resources or Right-Hand-Side Values 689 Changes in the Objective Function Coefficient 690

Solving Minimization Problems 690 Linear Programming Applications 692

Production-Mix Example 692 Diet Problem Example 693 Labour Scheduling Example 694

The Simplex Method of LP 695 Integer and Binary Variables 696

Creating Integer and Binary Variables 696 Linear Programming Applications with Binary Variables 696 A Fixed-Charge Integer Programming Problem 697 Module Summary 698 • Discussion Questions 698 • Using Software to Solve LP Problems 699 • Solved Problems 700 • Problems 702 • Case Study: Golding Landscaping and Plants Inc. 708 • Rapid Review 708 • Self-Test 710

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xiv Table of Contents

C Transportation Models 711 Transportation Modelling 711 Developing an Initial Solution 713

The Northwest-Corner Rule 713 The Intuitive Lowest-Cost Method 714

The Stepping-Stone Method 715 Special Issues in Modelling 718

Demand Not Equal to Supply 718 Degeneracy 719 Module Summary 720 • Discussion Questions 720 • Using Software to Solve Transportation Problems 721 • Solved Problems 722 • Problems 724 • Case Study: Custom Vans Inc. 727 • Rapid Review 728 • Self-Test 730

D Waiting-Line Models 731 Queuing Theory 731 Characteristics of a Waiting-Line System 732

Arrival Characteristics 732 Waiting-Line Characteristics 734 Service Characteristics 734 Measuring a Queue’s Performance 736

Queuing Costs 736 The Variety of Queuing Models 737

Model A (M/M/1): Single-Channel Queuing Model with Poisson Arrivals and Exponential Service Times 738 Model B (M/M/S): Multiple-Channel Queuing Model 741 Model C (M/D/1): Constant-Service-Time Model 745 Little’s Law 746 Model D: Limited-Population Model 746

Other Queuing Approaches 749 Module Summary 750 • Discussion Questions 750 • Using Software to Solve Queuing Problems 750 • Solved Problems 751 • Problems 753 • Case Studies: Labrador Foundry Inc. 756 • The Winter Park Hotel 757 • Rapid Review 758 • Self-Test 759

E Learning Curves 761 What Is a Learning Curve? 761 Learning Curves in Services and Manufacturing 762 Applying the Learning Curve 763

Arithmetic Approach 763 Logarithmic Approach 763 Learning-Curve Coefficient Approach 764

Strategic Implications of Learning Curves 766

Limitations of Learning Curves 767 Module Summary 767 • Discussion Questions 767 • Using Software for Learning Curves 767 • Solved Problems 768 • Problems 769 • Case Study: SMT’s Negotiation with IBM 771 • Rapid Review 772 • Self-Test 774

F Simulation 775 What Is Simulation? 775 Advantages and Disadvantages of Simulation 776 Monte Carlo Simulation 777

Step 1. Establishing Probability Distributions 777 Step 2. Building a Cumulative Probability Distribution for Each Variable 778 Step 3. Setting Random-Number Intervals 778 Step 4. Generating Random Numbers 779 Step 5. Simulating the Experiment 779

Simulation of a Queuing Problem 780 Simulation and Inventory Analysis 783

Module Summary 786 • Discussion Questions 786 • Using Software in Simulation 786 • Solved Problems 788 • Problems 789 • Case Study: Canadian Shield Airlines Call Centre 793 • Rapid Review 794 • Self-Test 796

Appendix A1 Bibliography B1 Indices I1

Online Tutorials

1 Statistical Tools for Managers T1-1 Discrete Probability Distributions T1-2

Expected Value of a Discrete Probability Distribution T1-3 Variance of a Discrete Probability Distribution T1-3

Continuous Probability Distributions T1-4 The Normal Distribution T1-4 Summary T1-7 • Key Terms T1-7 • Discussion Questions T1-7 • Problems T1-7 • Bibliography T1-8

2 Acceptance Sampling T2-1 Sampling Plans T2-2

Single Sampling T2-2 Double Sampling T2-2 Sequential Sampling T2-2

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Table of Contents xv

Operating Characteristic (OC) Curves T2-2 Producer’s and Consumer’s Risk T2-3 Average Outgoing Quality T2-5

Summary T2-6 • Key Terms T2-6 • Solved Problem T2-7 • Discussion Questions T2-7 • Problems T2-7

3 The Simplex Method of Linear Programming T3-1 Converting the Constraints to Equations T3-2 Setting Up the First Simplex Tableau T3-2 Simplex Solution Procedures T3-4 Summary of Simplex Steps for Maximization Problems T3-6 Artificial and Surplus Variables T3-7 Solving Minimization Problems T3-7

Summary T3-8 • Key Terms T3-8 • Solved Problem T3-8 • Discussion Questions T3-8 • Problems T3-9

4 The MODI and VAM Methods of Solving Transportation Problems T4-1 MODI Method T4-2

How to Use the MODI Method T4-2 Solving the Arizona Plumbing Problem with MODI T4-2

Vogel’s Approximation Method: Another Way to Find an Initial Solution T4-4

Discussion Questions T4-8 • Problems T4-8

5 Vehicle Routing and Scheduling T5-1 Introduction T5-2

Service Delivery Example: Meals-for-ME T5-2 Objectives of Routing and Scheduling Problems T5-2 Characteristics of Routing and Scheduling Problems T5-3

Classifying Routing and Scheduling Problems T5-3 Solving Routing and Scheduling Problems T5-4

Routing Service Vehicles T5-5 The Traveling Salesman Problem T5-5 Multiple Traveling Salesman Problem T5-8 The Vehicle Routing Problem T5-9 Cluster First, Route Second Approach T5-10

Scheduling Service Vehicles T5-11 The Concurrent Scheduler Approach T5-13

Other Routing and Scheduling Problems T5-13 Summary T5-14 • Key Terms T5-15 • Discussion Questions T5-15 • Problems T5-15 • Case Study: Routing and Scheduling of Phlebotomists T5-17 • Bibliography T5-17

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Preface

Welcome to your operations management (OM) course and to the third Canadian edition of this textbook. This text presents a state-of-the-art view of the activities of the operations function from a Canadian perspective. Operations is an exciting and dynamic area of management that has a profound effect on the productivity of both services and manufacturing. Indeed, few other activities have so much impact on the quality of your life. The goal of this book is to present a broad introduction to the field of operations in a realistic, meaningful, and practical manner. OM includes a blend of subject areas, including accounting, industrial engineering, management, management science, and statistics. Whether you are pursuing a career in the operations field or not, you will likely be working with people in operations. Therefore, having a solid understanding of the role of operations in an organization is of substantial benefit to you. This text will also help you understand how OM affects society and your life. Certainly, you will better understand what goes on behind the scenes when you buy a coffee at Tim Hortons, take a flight from Edmonton to Vancouver, place an order with Amazon.ca, or enter a Canadian hospital for medical care.

Although many readers of this book are not OM majors, students studying marketing, finance, accounting, and MIS will hopefully find the material both interesting and useful as they develop a fundamental working knowledge of the operations side of the firm.

ABOUT THE THIRD CANADIAN EDITION The goal of this third Canadian edition is to retain the features and strengths that have made this book so successful over the years while bringing a new Canadian perspective to the text. Readers will find examples of Canadian companies and success stories woven throughout the book with cases drawn from the manufacturing and service industry taken from both the private and public sectors. The text describes many Canadian locations and uses Canadian data when available. Readers can follow the story of the construction of a hockey arena as a recurring case study that touches upon many aspects of OM in a familiar setting. It is also important to acknowledge the global nature of today’s business environment. Operations management is a discipline that encompasses both the local and the international, with global considerations affecting everything from location strategies to scheduling and transportation. This third Canadian edition therefore retains many of the best and most familiar U.S. and international examples.

NEW TO THIS EDITION We’ve made significant revisions to this edition, and we want to share some of the changes with you.

Five New Video Case Studies Featuring Alaska Airlines In this edition we take you behind the scenes of Alaska Airlines, consistently rated as one of the top carriers in North America. This fascinating organization opened its doors—and planes—so we could examine leading-edge OM in the airline industry. We observe the quality program at Alaska Air (Chapter 6), the process analysis behind the airline’s 20-minute baggage retrieval guarantee (Chapter 7), how Alaska empowers its employees (Chapter 10), the airline’s use of Lean, 5s, kaizen, and Gemba walks (Chapter 16), and the complexities of scheduling (Module B). These videos, and other video case studies that feature real companies, can be found in MyLab Operations Management.

New Sustainability in the Supply Chain Supplement 5 We have enhanced the cov- erage of sustainability in this edition with the inclusion of a brand-new supplement that covers the topics of corporate social responsibility, design and production for sustainability, and regula- tions and industry standards.

Creating Your Own Excel Spreadsheets We continue to provide two free decision support software programs, Excel OM for Windows and Mac and POM for Windows, to help

xvi

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Preface xvii

you and your students solve homework problems and case studies. These excellent packages are found in MyLab Operations Management’s Download Center.

Many instructors also encourage students to develop their own Excel spreadsheet models to tackle OM issues. With this edition we provide numerous examples at chapter end on how to do so. “Creating Your Own Excel Spreadsheets” examples now appear in Chapters 2, 4, 8, 12, and Supplement 6, Supplement 7, and Modules A, and F. We hope these 8 samples will help expand students’ spreadsheet capabilities.

Expanding and Reordering Our Set of Homework Problems We believe that a vast selection of quality homework problems, ranging from easy to challenging (denoted by one to four dots), is critical for both instructors and students. Instructors need a broad selection of problems to choose from for homework, quizzes, and exams—without reusing the same set from semester to semester. We take pride in having more problems than any other OM text. We added dozens of new problems this edition.

Further, with the majority of our adopters now using the MyLab Operations Management learning system in their classes, we have reorganized all the homework problems—both those appearing in the printed text and the additional homework problems that are available in MyLab Operations Management—by topic heading. We identify all problems by topic.

The list of all problems by topic also appears at the end of each boxed example as well as in the Rapid Review that closes each chapter. These handy references should make it easier to assign problems for homework, quizzes, and exams. A rich set of assignable problems and cases makes the learning experience more complete and pedagogically sound.

Lean Operations In previous editions we sought to explicitly differentiate the concepts of just-in-time, Lean, and the Toyota Production System in Chapter 16. However, there is signifi- cant overlap and interchangeability among those three concepts, so we have revised Chapter 16 to incorporate the three concepts into an overall concept of “Lean”. The chapter suggests that students view Lean as a comprehensive integrated operations strategy that sustains competitive advantage and results in increased returns to all stakeholders.

In addition, the following changes have been made for the third Canadian edition: • New section on strategic planning, core competencies, and outsourcing added to Chapter 2. • Coverage of agile and waterfall approaches to project management have been revised in

Chapter 3. • New section on supply chain management in Chapter 4. • Added coverage of sustainability and life cycle assessment (LCA) to Chapter 5. • New section on ISO 9000 International Quality Standards in Chapter 6. • Coverage of bottleneck analysis in Supplement 7 has been completely revised. • Added coverage of supplier certification, contracting, and centralized purchasing to

Chapter 11. • Added section on warehouse storage to Supplement 11. • Coverage of economic order quantity enhanced with new section on period order quantity in

Chapter 14. • Added coverage of finite and infinite loading to Chapter 15. • Added coverage of Lean sustainability to Chapter 16. • Added coverage of parallel redundancy to Chapter 17. • New examples and case studies throughout the text.

MyLab Operations Management Resources In addition to our video case studies and our Excel OM and POM for Windows software, we provide the following resources in MyLab Operations Management: • Excel OM data files: Prepared for specific examples, these files allow users to solve all the

marked text examples without reentering data. • Active Models: These are Excel-based OM simulations, designed to help students under-

stand the quantitative methods shown in the textbook examples. Students may change the

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xviii Preface

ACKNOWLEDGMENTS We wish to acknowledge the contributions of the following reviewers who provided feedback during the development of the manuscript.

Farid Albehadili, University of Prince Edward Island

Gary Llewellyn Evans, University of Prince Edward Island

Scott Hadley, Sheridan College

Elkafi Hassini, McMaster University

Sam Lampropoulos, George Brown College

David Roberts, Southern Alberta Institute of Technology

Publishing a textbook requires the work of many talented individuals to handle the specialized tasks of development, photography, graphic design, illustration, editing, and production, to name only a few. I would like to thank Scott Hardie, Portfolio Manager; and Jennifer Murray, Content Developer, for her editorial guidance throughout the writing stage. I also thank the rest of the talented team: John Polanszky, Content Manager; Pippa Kennard and Christine Selvan, Project Managers; Sally Glover, Copy Editor; the team at Pearson CSC, and, finally, Spencer Snell, Marketing Manager.

But most of all, I thank my wife, Suzanne, and my children, Alexandra and Kathleen; my granddaughter, Kenna; plus Ryan and Robert, family and extended family, friends, and col- leagues. I couldn’t have done it without all of their support.

data to see how the changes affect the answers. These files are available in the Download Center.

• Online Tutorial Chapters: “Statistical Tools for Managers,” “Acceptance Sampling,” “The Simplex Method of Linear Programming,” “The MODI and VAM Methods of Solving Transportation Problems,” and “Vehicle Routing and Scheduling” are provided as additional material.

• Additional case studies: These case studies supplement the ones in the text. • Virtual office hours videos: Professors Heizer, Render, and Munson walk students through

the Solved Problems in a series of 5- to 20-minute explanations.

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Operations and Productivity

PART ONE Introduction to Operations Management (Chapters 1–4)

Learning Objectives LO1 Define operations

management 2

LO2 Explain the distinction between goods and services 9

LO3 Explain the difference between production and productivity 11

LO4 Compute single-factor productivity 12

LO5 Compute multifactor productivity 13

LO6 Identify the critical variables in enhancing productivity 14

Operations Management at Hard Rock Cafe Operations managers throughout the world are producing products daily

to provide for the well-being of society. These products take on a mul-

titude of forms, including auto parts at Magna International, motion pic-

tures at DreamWorks Studios, rides at Disney World, and food at Hard

Rock Cafe. These firms produce thousands of complex products every

day—to be delivered as the customer ordered them, when the customer

wants them, and where the customer wants them. Hard Rock does this

for over 35 million guests worldwide every year. This is a challenging

task, and the operations manager’s job—whether at Magna Internation-

al, DreamWorks, Disney, or Hard Rock—is demanding.

Orlando-based Hard Rock Cafe opened its first restaurant in London in

1971, making it over four decades old and the granddaddy of theme restau-

rants. Although other theme restaurants have come and gone, Hard Rock is

still going strong, with 150 restaurants in 53 countries—and new restaurants

opening each year. Hard Rock made its name with rock music memorabilia,

having started when Eric Clapton, a regular customer, marked his favourite

bar stool by hanging his guitar on the wall in the London cafe. Now Hard

1

1

Global Company Profile Hard Rock Cafe

Ruffer/Agencja Fotograficzna Caro/Alamy Stock Photo

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2 PART 1 Introduction to Operations Management

Rock has 70 000 items and millions of dollars invest-

ed in memorabilia. To keep customers coming back

time and again, Hard Rock creates value in the form

of good food and entertainment.

The operations managers at Hard Rock Cafe at

Universal Studios in Orlando provide more than 3500

custom products—in this case, meals—every day.

These products are designed, tested, and then ana-

lyzed for cost of ingredients, labour requirements, and

customer satisfaction. On approval, menu items are

put into production—and then only if the ingredients

are available from qualified suppliers. The production

process—from receiving, to cold storage, to grilling or

baking or frying, and a dozen other steps—is designed

and maintained to yield a quality meal. Operations

managers, using the best people they can recruit and

train, also prepare effective employee schedules and

design efficient layouts.

Managers who successfully design and deliver

goods and services throughout the world understand

operations. In this textbook, we look not only at how

Hard Rock’s managers create value but also at how

operations managers in other services, as well as in

manufacturing, do so. Operations management is de-

manding, challenging, and exciting. It affects our lives

every day. Ultimately, operations managers determine

how well we live.

What Is Operations Management? Operations management (OM) is a discipline that applies to restaurants like Hard Rock Cafe as well as to factories like Ford and Whirlpool. The techniques of OM apply throughout the world to virtually all productive enterprises. It doesn’t matter if the application is in an office, a hospi- tal, a restaurant, a department store, or a factory—the production of goods and services requires operations management. And the efficient production of goods and services requires effective application of the concepts, tools, and techniques of OM that we introduce in this book.

As we progress through this text, we will discover how to manage operations in a changing global economy. An array of informative examples, charts, text discussions, and pictures illus- trate concepts and provide information. We will see how operations managers create the goods and services that enrich our lives.

In this chapter, we first define operations management, explaining its heritage and exploring the exciting role operations managers play in a huge variety of organizations. Then we discuss production and productivity in both goods- and service-producing firms. This is followed by a discussion of operations in the service sector and the challenge of managing an effective and efficient production system.

Production is the creation of goods and services. Operations management (OM) is the set of activities that creates value in the form of goods and services by transforming inputs into outputs. Activities creating goods and services take place in all organizations. In manufacturing firms, the production activities that create goods are usually quite obvious. In them, we can see the creation of a tangible product such as a Sony TV or a Harley-Davidson motorcycle.

In an organization that does not create a tangible good or product, the production function may be less obvious. We often call these activities services. The services may be “hidden” from the public and even from the customer. The product may take such forms as the transfer of funds from a savings account to a chequing account, the transplant of a human organ, the filling of an empty seat on an airplane, or the education of a student. Regardless of whether the end product is a good or service, the production activities that go on in the organization are often referred to as operations, or operations management.

LO1 Define operations management

VIDEO 1.1 Operations Management

at Hard Rock

VIDEO 1.2 Operations Management

at Frito-Lay

Production The creation of goods and services.

Operations management (OM) Activities that relate to the crea- tion of goods and services through the transformation of inputs to outputs.

Hard Rock Cafe in Orlando, Florida, prepares over 3500 meals each day. Seating more than 1500 people, it is one of the largest restaurants in the world. But Hard Rock’s operations managers serve the hot food hot and the cold food cold.

An dr

e Je

nn y/

Al am

y St

oc k

Ph ot

o

Operations management is one of the three functions that every organization performs.

STUDENT TIP

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Chapter 1 Operations and Productivity 3

Organizing to Produce Goods and Services To create goods and services, all organizations perform three functions (see Figure 1.1). These functions are the necessary ingredients not only for production but also for an organization’s survival. They are:

1. Marketing, which generates the demand, or at least takes the order for a product or service (nothing happens until there is a sale).

Let’s begin by defining what this course is about.

STUDENT TIP

Manufacturing

Operations Facilities

Construction; maintenance

Production and inventory control Scheduling; materials control

Quality assurance and control

Manufacturing Tooling; fabrication; assembly

Supply chain management

Design Product development and design Detailed product specifications

Industrial engineering Efficient use of machines, space, and personnel

Process analysis Development and installation of production tools and equipment

Finance/accounting Disbursements/credits

Accounts receivable Accounts payable General ledger

Funds management Money market International exchange

Capital requirements Stock issue Bond issue and recall

Marketing Sales promotion

Market research Sales Advertising

(C)

Commercial Bank

Operations Teller scheduling Cheque clearing Collection Transaction processing Facilities design/layout Vault operations Maintenance Security

Finance Investments

Real estate Securities

Accounting

Loans Commercial Industrial Financial Personal Mortgage

Trust department

(A)

Auditing

Airline

Operations Ground support equipment

Maintenance

Ground operations Facility maintenance Catering

Flight operations Crew scheduling Flying Communications Dispatching

Management science

Finance/accounting Accounting

Accounts payable Accounts receivable General ledger

Finance Cash control International

exchange

Marketing

Marketing

Traffic administration Reservations Schedules Tariffs (pricing)

Advertising

Sales

(B)

FIGURE 1.1

Organization Charts for Two Service Organizations and One Manufacturing Organization (A) A bank, (B) an airline, and (C) a manufacturing organiza- tion. The blue areas are OM activities.

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4 PART 1 Introduction to Operations Management

2. Production/operations, which creates, produces, and delivers the product. 3. Finance/accounting, which tracks how well the organization is doing, pays the bills, and

collects the money.

Universities, places of worship, and businesses all perform these functions. Even a volunteer group such as Scouts Canada is organized to perform these three basic functions. Figure 1.1 shows how a bank, an airline, and a manufacturing firm organize themselves to perform these functions. The blue-shaded areas of Figure 1.1 show the operations functions in these firms.

THE SUPPLY CHAIN Through the three functions—marketing, operations, and finance—value for the customer is created. However, firms seldom create this value by themselves. Instead, they rely on a variety of suppliers who provide everything from raw materials to accounting services. These suppliers, when taken together, can be thought of as a supply chain. A supply chain (see Figure 1.2) is a global network of organizations and activities that supply a firm with goods and services.

As our society becomes more technologically oriented, we see increasing specialization. Specialized expert knowledge, instant communication, and cheaper transportation also fos- ter specialization and worldwide supply chains. It just does not pay for a firm to try to do everything itself. The expertise that comes with specialization exists up and down the supply chain, adding value at each step. When members of the supply chain collaborate to achieve high levels of customer satisfaction, we have a tremendous force for efficiency and competi- tive advantage. Competition in the 21st century is no longer between companies; it is between supply chains.

Why Study Operations Management? We study OM for four reasons:

1. OM is one of the three major functions of any organization, and it is integrally related to all the other business functions. All organizations market (sell), finance (account), and produce (operate), and it is important to know how the OM activity functions. Therefore, we study how people organize themselves for productive enterprise.

2. We study OM because we want to know how goods and services are produced. The produc- tion function is the segment of our society that creates the products and services we use.

3. We study OM to understand what operations managers do. Regardless of your job in an organization, you can perform better if you understand what operations managers do. In addition, understanding OM will help you explore the numerous and lucrative career oppor- tunities in the field.

4. We study OM because it is such a costly part of an organization. A large percentage of the revenue of most firms is spent in the OM function. Indeed, OM provides a major opportunity for an organization to improve its profitability and enhance its service to society. Example 1 considers how a firm might increase its profitability via the production function.

Supply chain A global network of organizations and activities that supplies a firm with goods and services.

Farmer Syrup producer

Bottler Distributor Retailer

FIGURE 1.2 Soft Drink Supply Chain A supply chain for a bottle of Coke requires a beet or sugar cane farmer, a syrup producer, a bottler, a distributor, and a retailer, each adding value to satisfy a customer. Only with collaborations between all members of the supply chain can efficiency and customer satisfaction be maximized. The supply chain, in general, starts with the provider of basic raw materials and continues all the way to the final customer at the retail store.

Good operations managers are scarce, and as a result, career opportunities and pay are excellent.

STUDENT TIP

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Chapter 1 Operations and Productivity 5

1 Fisher Technologies is a small firm that must double its dollar contribution to fixed cost and profit in order to be profitable enough to purchase the next generation of production equipment. Management has determined that if the firm fails to increase its contribution, its bank will not make the loan and the equipment cannot be purchased. If the firm cannot purchase the equipment, the limitations of the old equipment will force Fisher to go out of business and, in doing so, put its employees out of work and discontinue producing goods and services for its customers.

APPROACH c  Table 1.1 shows a simple profit-and-loss statement and three strategic options (mar- keting, finance/accounting, and operations) for the firm. The first option is a marketing option, where good marketing management may increase sales by 50%. By increasing sales by 50%, contribution will in turn increase 71%. But increasing sales 50% may be difficult; it may even be impossible.

EXAMPLE

Examining the Options for Increasing Contribution

Marketing Optiona

Finance/ Accounting

Optionb OM Optionc

Current Increase Sales Revenue 50%

Reduce Finance Costs 50%

Reduce Production Costs 20%

Sales $100 000 $ 150 000 $100 000 $100 000

Costs of goods 280 000 2120 000 280 000 264 000

Gross margin 20 000 30 000 20 000 36 000

Finance costs 26 000 26 000 23 000 26 000

Subtotal 14 000 24 000 17 000 30 000

Taxes at 25% 23 500 26 000 24 250 27 500

Contributiond $ 10 500 $ 18 000 $ 12 750 $ 22 500

a Increasing sales 50% increases contribution by $7500, or 71% (5 7500/10 500). b Reducing finance costs 50% increases contribution by $2250, or 21% (5 2250/10 500). c Reducing production costs 20% increases contribution by $12 000, or 114% (5 12 000/10 500). d Contribution to fixed costs (excluding finance costs) and profit.

Table 1.1 Options for Increasing Contribution

The second option is a finance/accounting option, where finance costs are cut in half through good financial management. But even a reduction of 50% is still inadequate for generating the necessary increase in contribution. Contribution is increased by only 21%.

The third option is an OM option, where management reduces production costs by 20% and increases contribution by 114%.

SOLUTION c  Given the conditions of our brief example, Fisher Technologies has increased contri- bution from $10 500 to $22 500. It may now have a bank willing to lend it additional funds.

INSIGHT c  The OM option not only yields the greatest improvement in contribution but also may be the only feasible option. Increasing sales by 50% and decreasing finance costs by 50% may both be virtually impossible. Reducing operations costs by 20% may be difficult but feasible.

LEARNING EXERCISE c  What is the impact of only a 15% decrease in costs in the OM option? [Answer: A $19 500 contribution; approximately an 86% increase.]

Example 1 underscores the importance of an effective operations activity of a firm. Development of increasingly effective operations is the approach taken by many companies as they face growing global competition.

What Operations Managers Do All good managers perform the basic functions of the management process. The management process consists of planning, organizing, staffing, leading, and controlling. Operations man- agers apply this management process to the decisions they make in the OM function. The 10 major decisions of OM are shown in Table 1.2. Successfully addressing each of these decisions requires planning, organizing, staffing, leading, and controlling. Typical issues relevant to these decisions and the chapter in which each is discussed are also shown.

Management process The application of planning, organiz- ing, staffing, leading, and controlling to the achievement of objectives.

An operations manager must successfully address the 10 decisions around which this text is organized.

STUDENT TIP

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6 PART 1 Introduction to Operations Management

WHERE ARE THE OM JOBS? How does one get started on a career in operations? The 10 OM decisions identified in Table 1.2 are made by individuals who work in the disciplines shown in the blue areas of Figure 1.1. Competent business students who know their accounting, statistics, finance, and OM have an opportunity to assume entry-level positions in all of these areas. As you read this text, identify disciplines that can assist you in making these decisions, then take courses in those areas. The more background an OM student has in accounting, statistics, information systems, and mathematics, the more job opportunities will be available. About 40% of all jobs are in OM.

The following professional organizations provide various certifications that may enhance your education and be of help in your career:

• APICS, the Association for Operations Management (www.apics.org) • Standards Council of Canada (www.scc.ca) • Institute for Supply Management (ISM) (www.instituteforsupplymanagement.org) • Project Management Institute (PMI) (www.pmi.org) • Council of Supply Chain Management Professionals (www.cscmp.org)

Figure 1.3 shows some possible job opportunities.

The Heritage of Operations Management The field of OM is relatively young, but its history is rich and interesting. Our lives and the OM discipline have been enhanced by the innovations and contributions of numerous individuals. We now introduce a few of these people, and we provide a summary of significant events in operations management in Figure 1.4.

Eli Whitney (1800) is credited for the early popularization of interchangeable parts, which was achieved through standardization and quality control. Through a contract he signed with the

Table 1.2 10 Critical Decisions of Operations Management

10 Decision Areas Issues Chapter(s)

1. Design of goods and services What good or service should we offer? How should we design these products?

5

2. Managing quality How do we define the quality? Who is responsible for quality?

6, Supplement 6

3. Process and capacity design What process and what capacity will these products require? What equipment and technology are necessary for these processes?

7, Supplement 7

4. Location strategy Where should we put the facility? On what criteria should we base the location decision?

8

5. Layout strategy How should we arrange the facility? How large must the facility be to meet our plan?

9

6. Human resources and job design

How do we provide a reasonable work environment? How much can we expect our employees to produce?

10

7. Supply chain management Should we make or buy this component? Who should be our suppliers, and how can we integrate them into our strategy?

11, Supplement 11

8. Inventory, material requirements planning, and JIT (just-in-time)

How much inventory of each item should we have? When do we reorder?

12, 14, 16

9. Intermediate and short-term scheduling

Are we better off keeping people on the payroll during slowdowns? Which job do we perform next?

13, 15

10. Maintenance Who is responsible for maintenance? 17

Current OM emphasis on quality and supply chain has increased job opportunities in these 10 areas.

STUDENT TIP

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Chapter 1 Operations and Productivity 7

Plant Manager Division of Fortune 1000 company seeks plant manager for plant located in the Vancouver area. This plant manufactures loading dock equipment for commercial markets. The candidate must be experienced in plant management including expertise in production planning, purchasing, and inventory management. Good written and oral communication skills are a must, along with excellent application of skills in managing people. Operations Analyst Expanding national coffee shop: top 10 “Best Places to Work” wants junior-level systems analyst to join our excellent store improvement team. Business or I.E. degree, work methods, labour standards, ergonomics, cost accounting knowledge a plus. This is a hands-on job and excellent opportunity for a team player with good people skills. West coast location. Some travel required. Quality Manager Several openings exist in our small package processing facilities in Montreal and Winnipeg for quality managers. These highly visible positions require extensive use of statistical tools to monitor all aspects of service, timeliness, and workload measurement. The work involves (1) a combination of hands-on applications and detailed analysis using databases and spreadsheets, (2) process audits to identify areas for improvement, and (3) management of implementation of changes. Positions involve night hours and weekends. Send résumé. Supply Chain Manager and Planner Responsibilities entail negotiating contracts and establishing long-term relationships with suppliers. We will rely on the selected candidate to maintain accuracy in the purchasing system, invoices, and product returns. A bachelor’s degree and up to two years’ related experience are required. Working knowledge of MRP, ability to use feedback to master scheduling and suppliers and consolidate orders for best price and delivery are necessary. Proficiency in all PC Windows applications, particularly Excel and Word, is essential. Knowledge of Oracle business systems is a plus. Effective verbal and written communication skills are essential. Process Improvement Consultants An expanding consulting firm is seeking consultants to design and implement lean production and cycle time reduction plans in both service and manufacturing processes. Our firm is currently working with an international bank to improve its back office operations, as well as with several manufacturing firms. A business degree required; APICS certification a plus.

1/15

2/23

3/18

4/6

5/14

FIGURE 1.3 Many Opportunities Exist for Operations Managers

Early Concepts

Cost Focus Quality Focus

1776–1880 Labour Specialization (Smith, Babbage) Standardized Parts (Whitney)

Scientific Management Era 1880–1910 Gantt Charts (Gantt) Motion & Time Studies (Gilbreth) Process Analysis (Taylor) Queuing Theory (Erlang)

Mass Production Era 1910–1980 Moving Assembly Line (Ford/Sorensen) Statistical Sampling (Shewhart) Economic Order Quantity (Harris) Linear Programming PERT/CPM (DuPont) Material Requirements Planning (MRP)

Mass Customization Era 1995–2015 Globalization Internet/Ecommerce Enterprise Resource Planning International Quality Standards (ISO) Finite Scheduling Supply Chain Management Mass Customization Build-to-Order Sustainability

Lean Production Era 1980–1995 Just-in-Time (JIT) Computer-Aided Design (CAD) Electronic Data Interchange (EDI) Total Quality Management (TQM) Baldrige Award Empowerment Kanbans

Customization Focus

FIGURE 1.4 Significant Events in Operations Management

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8 PART 1 Introduction to Operations Management

U.S. government for 10 000 muskets, he was able to command a premium price because of their interchangeable parts.

Frederick W. Taylor (1881), known as the father of scientific management, contributed to personnel selection, planning and scheduling, motion study, and the now popular field of ergo- nomics. One of his major contributions was his belief that management should be much more resourceful and aggressive in the improvement of work methods. Taylor and his colleagues, Henry L. Gantt and Frank and Lillian Gilbreth, were among the first to systematically seek the best way to produce.

Another of Taylor’s contributions was the belief that management should assume more responsibility for:

1. Matching employees to the right job. 2. Providing the proper training. 3. Providing proper work methods and tools. 4. Establishing legitimate incentives for work to be accomplished.

By 1913, Henry Ford and Charles Sorensen combined what they knew about standardized parts with the quasi-assembly lines of the meatpacking and mail-order industries and added the revolutionary concept of the assembly line, where men stood still and material moved.

Quality control is another historically significant contribution to the field of OM. Walter Shewhart (1924) combined his knowledge of statistics with the need for quality control and provided the foundations for statistical sampling in quality control. W. Edwards Deming (1950) believed, as did Frederick Taylor, that management must do more to improve the work environ- ment and processes so that quality can be improved.

Operations management will continue to progress with contributions from other disciplines, including industrial engineering and management science. These disciplines, along with statis- tics, management, and economics, contribute to improved models and decision making.

Innovations from the physical sciences (biology, anatomy, chemistry, and physics) have also contributed to advances in OM. These innovations include new adhesives, faster inte- grated circuits, gamma rays to sanitize food products, and higher-quality glass for LCD and plasma TVs. Innovation in products and processes often depends on advances in the physical sciences.

Especially important contributions to OM have come from information technology, which we define as the systematic processing of data to yield information. Information tech- nology—with wireless links, internet, and ecommerce—is reducing costs and accelerating communication.

Decisions in operations management require individuals who are well versed in manage- ment science, in information technology, and often in one of the biological or physical sciences. In this textbook, we look at the diverse ways a student can prepare for a career in operations management.

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Chapter 1 Operations and Productivity 9

Operations in the Service Sector Manufacturers produce a tangible product, while service products are often intangible. But many products are a combination of a good and a service, which complicates the definition of a ser- vice. Even the Canadian government has trouble generating a consistent definition. Because definitions vary, much of the data and statistics generated about the service sector are incon- sistent. However, we define services as including repair and maintenance, government, food and lodging, transportation, insurance, trade, financial, real estate, education, law, medicine, entertainment, and other professional occupations.

DIFFERENCES BETWEEN GOODS AND SERVICES Let’s examine some of the differences between goods and services:

• Services are usually intangible (for example, your purchase of a ride in an empty airline seat between two cities) as opposed to a tangible good.

• Services are often produced and consumed simultaneously; there is no stored inventory. For instance, the beauty salon produces a haircut that is “consumed” simultaneously, or the doctor produces an operation that is “consumed” as it is produced. We have not yet figured out how to inventory haircuts or appendectomies.

• Services are often unique. Your mix of financial coverage, such as investments and insurance policies, may not be the same as anyone else’s, just as the medical procedure or a haircut produced for you is not exactly like anyone else’s.

• Services have high customer interaction. Services are often difficult to standardize, automate, and make as efficient as we would like because customer interaction demands uniqueness. In fact, in many cases this uniqueness is what the customer is paying for; therefore, the oper- ations manager must ensure that the product is designed (i.e., customized) so that it can be delivered in the required unique manner.

• Services have inconsistent product definition. Product definition may be rigorous, as in the case of an auto insurance policy, but inconsistent because policyholders change cars and pol- icies mature.

• Services are often knowledge based, as in the case of educational, medical, and legal services, and therefore hard to automate.

• Services are frequently dispersed. Dispersion occurs because services are frequently brought to the client/customer via a local office, a retail outlet, or even a house call.

The activities of the operations function are often very similar for both goods and services. For instance, both goods and services must have quality standards established, and both must be designed and processed on a schedule in a facility where human resources are employed.

Having made the distinction between goods and services, we should point out that, in many cases, the distinction is not clear-cut. In reality, almost all services and almost all goods are a mixture of a service and a tangible product. Even services such as consulting may require a tangible report. Similarly, the sale of most goods includes a service. For instance, many prod- ucts have the service components of financing and delivery (e.g., automobile sales). Many also require after-sale training and maintenance (e.g., office copiers and machinery). “Service” activ- ities may also be an integral part of production. Human resource activities, logistics, accounting, training, field service, and repair are all service activities, but they take place within a manufac- turing organization. Very few services are “pure,” meaning they have no tangible component. Counselling may be one of the exceptions.

GROWTH OF SERVICES Services constitute the largest economic sector in postindustrial societies. Until about 1900, many Canadians were employed in agriculture. Increased agricultural productivity allowed peo- ple to leave the farm and seek employment in the city. Similarly, manufacturing employment has decreased in North America in the past 30 years. The Canadian market tends to follow U.S. trends, as can be seen in the following comparison. The changes in U.S. agriculture, man- ufacturing, and service employment are shown in Figure 1.5. Although the number of people employed in manufacturing has decreased since 1950, each person is now producing almost 20 times more than in 1950. Services became the dominant employer in the early 1920s, with manufacturing employment peaking at about 32% in 1950. The huge productivity increases in

Services Economic activities that typically produce an intangible product (such as education, entertain- ment, lodging, government, financial, and health services).

LO2 Explain the distinction between goods and services

Services are especially important because almost 80% of all jobs are in service firms.

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10 PART 1 Introduction to Operations Management

agriculture and manufacturing have allowed more of our economic resources to be devoted to services. Consequently, much of the world can now enjoy the pleasures of education, health services, entertainment, and myriad other things that we call services. Examples of firms and percentage of employment in the Canadian service sector are shown in Table 1.3. The table also provides employment percentages for the nonservice sectors of manufacturing, construction, utilities, agriculture, and mining on the bottom five lines.

SERVICE PAY Although there is a common perception that service industries are low paying, in fact, many service jobs pay very well. Operations managers in the maintenance facility of an airline are very

Service sector The segment of the economy that includes trade, financial, lodging, education, legal, medical, and other professional occupations.

Table 1.3 Examples of Organizations in Each Sector

Sector Example Percent of All Jobs

Service-Producing Sector

Trade Hudson Bay Company; Real Canadian Superstore

15%

Transportation and warehousing WestJet; Maritime–Ontario Freight Lines Limited

5%

Finance, insurance, real estate, and leasing

Royal Bank; Manulife 6%

Professional, scientific, and technical services

Borden Ladner Gervais Law Firm 8%

Business, building, and other support services1

Edmonton Waste Management Centre; Carlson Wagonlit Travel

4%

Educational services McGill University 7% Health care and social assistance SickKids Hospital 12% Information, culture, and recreation Calgary Flames; Princess of Wales Theatre 5% Accommodation and food services Tim Hortons; Royal York Hotel 6%

Other Services Joe’s Barber Shop; ABC Landscaping 4% Public administration Province of Manitoba; City of Hamilton 6%

Goods-Producing Sector 22% Agriculture Farming Operations 2% Forestry, fishing, mining, quarrying, oil, and gas2

Canadian Mining Company Inc.; Dome Pacific Logging Ltd.

2%

Utilities Ontario Power Generation 1% Construction PCL Construction Management Inc. 7% Manufacturing Magna International Inc. 10% 1 Formerly “Management of companies, administrative, and other support services.” 2 Also referred to as “Natural resources.”

Source: Statistics Canada, CANSIM, table 282-0008 and Catalogue no. 71F0004XCB.

FIGURE 1.5 U.S. Agriculture, Manufactur- ing, and Service Employment Source: U.S. Bureau of Labor Statistics.

1800

0

20

40

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60

80

100

1825 1850

1875

U.S. Agriculture, Manufacturing, and Service Employment

1900 1925

1950 1975

2000 2025 (est.)

Agriculture

Services

Manufacturing

Service jobs with their operations component are growing as a percentage of all jobs.

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Chapter 1 Operations and Productivity 11

well paid, as are the operations managers who supervise computer services to the financial com- munity. However, the accommodation and food services sectors followed by the arts, recreation, and entertainment sectors offer the lowest average weekly pay levels in Canada.

New Challenges in Operations Management Operations managers work in an exciting and dynamic environment that is the result of a variety of challenging forces, from globalization of world trade to the transfer of ideas, products, and money at electronic speeds. Let’s look at some of these challenges:

• Global focus: The rapid decline in communication and transportation costs has made markets global. Similarly, resources in the form of capital, materials, talent, and labour are also now global. As a result, countries throughout the world are contributing to globalization as they vie for economic growth. Operations managers are rapidly seeking creative designs, efficient production, and high-quality goods via international collaboration.

• Supply chain partnering: Shorter product life cycles, demanding customers, and fast changes in technology, materials, and processes require supply chain partners to be in tune with the needs of end users. And because suppliers may be able to contribute unique expertise, oper- ations managers are outsourcing and building long-term partnerships with critical players in the supply chain.

• Sustainability: Operations managers’ continuing battle to improve productivity is concerned with designing products and processes that are ecologically sustainable. This means design- ing green products and packaging that minimize resource use, can be recycled or reused, and are generally environmentally friendly.

• Rapid product development: Technology combined with rapid international communication of news, entertainment, and lifestyles is dramatically chopping away at the lifespan of prod- ucts. OM is answering with new management structures, enhanced collaboration, digital tech- nology, and creative alliances that are more responsive and effective.

• Mass customization: Once managers recognize the world as the marketplace, the cultural and individual differences become quite obvious. In a world where consumers are increas- ingly aware of innovation and options, substantial pressure is placed on firms to respond in a creative way. And OM must rapidly respond with product designs and flexible production processes that cater to the individual whims of consumers. The goal is to produce customized products, whenever and wherever needed.

• Lean operations: Lean is the management model sweeping the world and providing the stand- ard against which operations managers must compete. Lean can be thought of as the driving force in a well-run operation, where the customer is satisfied, employees are respected, and waste does not exist. The theme of this text is to build organizations that are more efficient, where management creates enriched jobs that help employees engage in continuous improve- ment and where goods and services are produced and delivered when and where the customer desires them. These ideas are captured in the phrase Lean.

These trends are part of the exciting OM challenges currently facing operations managers.

The Productivity Challenge The creation of goods and services requires changing resources into goods and services. The more efficiently we make this change, the more productive we are and the more value is added to the good or service provided. Productivity is the ratio of outputs (goods and services) divided by the inputs (resources, such as labour and capital) (see Figure 1.6). The operations manager’s job is to enhance (improve) this ratio of outputs to inputs. Improving productivity means improv- ing efficiency. Efficiency means doing the job well—with a minimum of resources and waste. Note the distinction between being efficient, which implies doing the job well, and being effec- tive, which means doing the right thing. A job well done—say, by applying the 10 decisions of operations management—helps us be efficient; developing and using the correct strategy helps us be effective.

Productivity The ratio of outputs (goods and services) divided by one or more inputs (such as labour, capital, or management).

LO3 Explain the difference between production and productivity

Why is productivity important? Because it determines our standard of living.

One of the reasons OM is such an exciting discipline is that an operations manager is confronted with ever-changing issues, from technology, to global supply chains, to sustainability.

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12 PART 1 Introduction to Operations Management

This improvement can be achieved in two ways: reducing inputs while keeping output con- stant, or increasing output while keeping inputs constant. Both represent an improvement in productivity. In an economic sense, inputs are labour, capital, and management, which are inte- grated into a production system. Management creates this production system, which provides the conversion of inputs to outputs. Outputs are goods and services, including such diverse items as guns, butter, education, improved judicial systems, and ski resorts. Production is the making of goods and services. High production may imply only that more people are working and that employment levels are high (low unemployment), but it does not imply high productivity.

Measurement of productivity is an excellent way to evaluate a country’s ability to provide an improving standard of living for its people. Only through increases in productivity can the standard of living improve. Moreover, only through increases in productivity can labour, capital, and management receive additional payments. If returns to labour, capital, or management are increased without increased productivity, prices rise. On the other hand, downward pressure is placed on prices when productivity increases, because more is being produced with the same resources.

The benefits of increased productivity are illustrated in the OM in Action box “Improving Productivity at Starbucks”. Since 1973, labour productivity in Canada has experienced an annual rate of growth averaging approximately 1.25%, down considerably from the previous level of 3.00% during the period between 1961 and 1973. An increase of one percentage point in this performance would almost double the annual growth rate to 2.25%. Such a growth rate in labour productivity would mean that the average level of labour productivity in Canada would double every 32 years, not every 58 years as it will with a 1.25% growth rate. Moreover, if our labour productivity level were to double every 32 years, then (in the absence of major demographic effects) so would Canada’s standard of living.

PRODUCTIVITY MEASUREMENT In this text, we examine how to improve productivity through operations management. Productivity is a significant issue for the world and one that the operations manager is uniquely qualified to address.

The measurement of productivity can be quite direct. Such is the case when productivity is measured by labour-hours per tonne of a specific type of steel. Although labour-hours are a common measure of input, other measures such as capital (dollars invested), materials (tonnes of ore), or energy (kilowatts of electricity) can be used.1 An example of this can be summarized in the following equation:

Productivity = Units produced

Input used (1-1)

Inputs Transformation Outputs

Feedback loop

Goods and services

The Canadian economic system transforms inputs

to outputs at about an annual 2.2% increase in

productivity per year. The productivity increase is

the result of a mix of capital (38% of 2.2%), labour (10% of 2.2%),

and management (52% of 2.2%).

Labour, capital, management

FIGURE 1.6

The Economic System Adds Value by Transforming Inputs to Outputs An effective feedback loop evaluates performance against a strategy or standard. It also evaluates customer satisfaction and sends signals to manag- ers controlling the inputs and transformation process.

1 The quality and time period are assumed to remain constant.

LO4 Compute single-factor productivity

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Chapter 1 Operations and Productivity 13

For example, if units produced = 1000 and labour-hours used is 250, then:

Single@factor productivity = Units produced

Labour@hours used =

1000 250

= 4 units per labour@hour

The use of just one resource input to measure productivity, as shown in Equation (1-1), is known as single-factor productivity. However, a broader view of productivity is multifac- tor productivity, which includes all inputs (e.g., capital, labour, material, energy). Multifactor productivity is also known as total factor productivity. Multifactor productivity is calculated by combining the input units as shown here:

Multifactor productivity = Output

Labour + Material + Energy + Capital + Miscellaneous (1-2)

To aid in the computation of multifactor productivity, the individual inputs (the denominator) can be expressed in dollars and summed as shown in Example 2.

LO5 Compute multifactor productivity

Single-factor productivity Indicates the ratio of the goods and services produced (outputs) to one resource (input).

Multifactor productivity Indicates the ratio of the goods and services produced (outputs) to many or all resources (inputs).

“This is a game of seconds . . .” says Silva Peterson, whom Starbucks has put in charge of saving seconds. Her team of 10 analysts is constantly asking themselves: “How can we shave time off this?”

Peterson’s analysis suggested that there were some obvious opportunities. First, stop requiring signatures on credit card purchases under $25. This sliced 8 seconds off the transaction time at the cash register.

Then analysts noticed that Starbucks’s largest cold beverage, the Venti size, required two bending and dig- ging motions to scoop up enough ice. The scoop was too small. Redesign of the scoop provided the proper amount in one motion and cut 14 seconds off the average time of one minute.

Third were new espresso machines; with the push of a button, the machines grind coffee beans and brew. This allowed the server, called a “barista” in Starbucks’s vocabulary, to do other things. The savings: about 12 seconds per espresso shot.

As a result, operations improvements at Starbucks outlets have increased the average yearly volume by nearly $200 000, to about $940 000 in the past six years. This is a 27% improvement in productivity—about 4.5% per year. In the service industry, a 4.5% per year increase is very tasty.

Sources: Based on The Wall Street Journal (August 4, 2009): A1, A10 and (April 12, 2005): B2:B7; Industrial Engineer (January 2006): 66; and www.finfacts.com, October 6, 2005.

Improving Productivity at StarbucksOM in Action

2 Collins Title wants to evaluate its labour and multifactor productivity with a new computerized title- search system. The company has a staff of four, each working eight hours per day (for a payroll cost of $640/day) and overhead expenses of $400 per day. Collins processes and closes on eight titles each day. The new computerized title-search system will allow the processing of 14 titles per day. Although the staff, their work hours, and pay are the same, the overhead expenses are now $800 per day.

APPROACH c  Collins uses Equation (1-1) to compute labour productivity and Equation (1-2) to compute multifactor productivity.

SOLUTION c  

Labour productivity with the old system: 8 titles per day

32 labour@hours = 0.25 titles per labour@hour

Labour productivity with the new system: 14 titles per day

32 labour@hours = 0.4375 titles per labour@hour

Multifactor productivity with the old system: 8 titles per day

$640 + 400 = 0.0077 titles per dollar

Multifactor productivity with the new system: 14 titles per day

$640 + 800 = 0.0097 titles per dollar

EXAMPLE

Computing Single- Factor and Multifactor Gains in Productivity

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14 PART 1 Introduction to Operations Management

Use of productivity measures aids managers in determining how well they are doing. But results from the two measures can be expected to vary. If labour productivity growth is entirely the result of capital spending, measuring just labour distorts the results. Multifactor productivity is usually better but more complicated. Labour productivity is the more popular measure. The multifactor-productivity measures provide better information about the trade-offs among factors, but substantial measurement problems remain. Some of these measurement problems are:

1. Quality may change while the quantity of inputs and outputs remains constant. Compare an HDTV of this decade with a black-and-white TV of the 1950s. Both are TVs, but few people would deny that the quality has improved. The unit of measure—a TV—is the same, but the quality has changed.

2. External elements may cause an increase or a decrease in productivity for which the system under study may not be directly responsible. A more reliable electric power service may greatly improve production, thereby improving the firm’s productivity because of this sup- port system rather than because of managerial decisions made within the firm.

3. Precise units of measure may be lacking. Not all automobiles require the same inputs: Some cars are subcompacts; others are 911 Turbo Porsches.

Productivity measurement is particularly difficult in the service sector, where the end prod- uct can be hard to define. For example, economic statistics ignore the quality of your haircut, the outcome of a court case, or service at a retail store. In some cases, adjustments are made for the quality of the product sold but not for the quality of the sales presentation or the advantage of a broader product selection. Productivity measurements require specific inputs and outputs, but a free economy is producing worth—what people want—which includes con- venience, speed, and safety. Traditional measures of outputs may be a very poor measure of these other measures of worth. Note the quality-measurement problems in a law office, where each case is different, altering the accuracy of the measure “cases per labour-hour” or “cases per employee”.

PRODUCTIVITY VARIABLES As we saw in Figure 1.6, productivity increases are dependent on three productivity variables:

1. Labour, which contributes about 10% of the annual increase. 2. Capital, which contributes about 38% of the annual increase. 3. Management, which contributes about 52% of the annual increase.

These three factors are critical to improved productivity. They represent the broad areas in which managers can take action to improve productivity.

LABOUR Improvement in the contribution of labour to productivity is the result of a healthier, better-educated, and better-nourished labour force. Some increase may also be attributed to a shorter work week. Historically, about 10% of the annual improvement in productivity is attributed to improvement in the quality of labour. Three key variables for improved labour productivity are:

1. Basic education appropriate for an effective labour force. 2. Diet of the labour force. 3. Social overhead that makes labour available, such as transportation and sanitation.

Productivity variables The three factors critical to pro- ductivity improvement—labour, capital and management.

LO6 Identify the critical variables in enhancing productivity

Labour productivity has increased from 0.25 to 0.4375. The change is (0.4375 2 0.25)/0.25 5 0.75, or a 75% increase in labour productivity. Multifactor productivity has increased from 0.0077 to 0.0097. This change is (0.0097 2 0.0077)/0.0077 5 0.26, or a 26% increase in multifactor productivity.

INSIGHT c  Both the labour (single-factor) and multifactor productivity measures show an increase in productivity. However, the multifactor measure provides a better picture of the increase because it includes all the costs connected with the increase in output.

LEARNING EXERCISE c  If the overhead goes to $960 (rather than $800), what is the multifactor productivity? [Answer: 0.00875.]

RELATED PROBLEMS c  1.1, 1.2, 1.5, 1.6, 1.7, 1.8, 1.9, 1.11, 1.12, 1.14, 1.15

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Chapter 1 Operations and Productivity 15

Illiteracy and poor diets are major impediments to productivity, costing countries up to 20% of their productivity. Infrastructure that yields clean drinking water and sanitation is also an opportunity for improved productivity, as well as an opportunity for better health, in much of the world.

In developed nations, the challenge becomes maintaining and enhancing the skills of labour in the midst of rapidly expanding technology and knowledge. Recent data suggest that the average American 17-year-old knows significantly less mathematics than the average Japanese person of the same age, and about half cannot answer the questions in Figure 1.7. Moreover, more than 38% of U.S. job applicants tested for basic skills were deficient in reading, writing, or math.2

Overcoming shortcomings in the quality of labour while other countries have a better labour force is a major challenge. Perhaps improvements can be found not only through increasing competence of labour but also via better utilized labour with a stronger commitment. Training, motivation, team building, and the human resource strategies discussed in Chapter 10, as well as improved education, may be among the many techniques that will contribute to increased labour productivity. Improvements in labour productivity are possible; however, they can be expected to be increasingly difficult and expensive.

CAPITAL Human beings are tool-using animals. Capital investment provides those tools. Capital investment has increased in Canada most years except during a few very severe recession peri- ods. Accumulated capital investment has increased in Canada at a compound annual growth rate of 4.5%.

Inflation and taxes increase the cost of capital, making capital investment increasingly expen- sive. When the capital invested per employee drops, we can expect a drop in productivity. Using labour rather than capital may reduce unemployment in the short run, but it also makes econ- omies less productive and therefore lowers wages in the long run. Capital investment is often necessary but seldom sufficient in the battle for increased productivity.

The trade-off between capital and labour is continually in flux. The higher the cost of capital, the more projects requiring capital are “squeezed out”: they are not pursued because the potential return on investment for a given risk has been reduced. Managers adjust their investment plans to changes in capital cost.

MANAGEMENT Management is a factor of production and an economic resource. Management is responsible for ensuring that labour and capital are effectively used to increase productivity. Management accounts for over half of the annual increase in productivity. This increase includes improvements made through the use of knowledge and the application of technology.

Using knowledge and technology is critical in postindustrial societies. Consequently, postin- dustrial societies are also known as knowledge societies. A knowledge society is one in which much of the labour force has migrated from manual work to technical and information-pro- cessing tasks requiring ongoing education. The required education and training are important high-cost items that are the responsibility of operations managers as they build organizations and workforces. The expanding knowledge base of contemporary society requires that managers use technology and knowledge effectively.

Knowledge society A society in which much of the labour force has migrated from manual work to work based on knowledge.

2 “Can’t Read, Can’t Count,” Scientific American (October 2001): 24; and “Economic Time Bomb: U.S. Teens Are among Worst at Math,” The Wall Street Journal (December 7, 2004): B1.

Which of the following is true about 84% of 100?

It is greater than 100

It is less than 100

It is equal to 100

What is the area of this rectangle?

6 yds

4 yds

4 square yds

6 square yds

10 square yds

20 square yds

24 square yds

If 9y + 3 = 6y + 15 then y =

1

2

4

6

FIGURE 1.7

About Half of the 17-Year-Olds in the United States Cannot Correctly Answer Questions of This Type

Perhaps as many as 25% of North American workers lack the basic skills needed for their current job.

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16 PART 1 Introduction to Operations Management

More effective use of capital also contributes to productivity. It falls to the operations man- ager, as a productivity catalyst, to select the best new capital investments as well as to improve the productivity of existing investments.

The productivity challenge is difficult. A country cannot be a world-class competitor with second-class inputs. Poorly educated labour, inadequate capital, and dated technology are sec- ond-class inputs. High productivity and high-quality outputs require high-quality inputs, includ- ing good operations managers.

PRODUCTIVITY AND THE SERVICE SECTOR The service sector provides a special challenge to the accurate measurement of productivity and productivity improvement. The traditional analytical framework of economic theory is based primarily on goods-producing activities. Consequently, most published economic data relate to goods production. But the data do indicate that, as our contemporary service economy has increased in size, we have had slower growth in productivity.

Productivity of the service sector has proven difficult to improve because service sector work is:

1. Typically labour intensive (e.g., counselling, teaching). 2. Frequently focused on unique individual attributes or desires (e.g., investment advice). 3. Often an intellectual task performed by professionals (e.g., medical diagnosis). 4. Often difficult to mechanize and automate (e.g., a haircut). 5. Often difficult to evaluate for quality (e.g., performance of a law firm).

The effective use of capital often means finding the proper trade-off between investment in capital assets (automation, left) and human assets (a manual process, right). While there are risks connected with any investment, the cost of capital and physical investments is fairly clear-cut, but the cost of employees has many hidden costs, including fringe benefits, social insurance, and legal constraints on hiring, employment, and termination.

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Siemens, the multibillion-dollar German conglomer- ate, has long been known for its apprentice programs in its home country. Because education is often the key to efficient operations in a technological society, Siemens has spread its apprentice-training programs to its international plants. These programs are laying the foundation for the highly skilled workforce that is essential for global competitiveness.

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Chapter 1 Operations and Productivity 17

The more intellectual and personal the task, the more difficult it is to achieve increases in pro- ductivity. Low-productivity improvement in the service sector is also attributable to the growth of low-productivity activities in the service sector. These include activities not previously a part of the measured economy, such as child care, food preparation, house cleaning, and laundry service. These activities have moved out of the home and into the measured economy as more and more women have joined the workforce. Inclusion of these activities has probably resulted in lower measured productivity for the service sector, although, in fact, actual productivity has probably increased because these activities are now more efficiently produced than previously.

However, in spite of the difficulty of improving productivity in the service sector, improve- ments are being made, and there are a multitude of ways to make these improvements. Indeed, what can be done when management pays attention to how work actually gets done is astonishing!

Although the evidence indicates that all industrialized countries have the same problem with service productivity, the United States remains the world leader in overall productivity and ser- vice productivity. Retailing is twice as productive in the United States as in Japan, where laws protect shopkeepers from discount chains. The U.S. telephone industry is at least twice as pro- ductive as Germany’s. However, because productivity is central to the operations manager’s job and because the service sector is so large, we take special note in this text of how to improve productivity in the service sector. (See, for instance, the OM in Action box “Taco Bell Improves Productivity and Goes Green to Lower Costs.”)

Ethics, Social Responsibility, and Sustainability Operations managers are subjected to constant changes and challenges. The systems they build to convert resources into goods and services are complex. The physical and social environments change, as do laws and values. These changes present a variety of challenges that come from the conflicting perspectives of stakeholders such as customers, distributors, suppliers, owners, lenders, and employees. These stakeholders, as well as government agencies at various levels, require constant monitoring and thoughtful responses.

Identifying ethical and socially responsible responses while building productive systems is not always clear-cut. Among the many ethical challenges facing operations managers are:

• Efficiently developing and producing safe, quality products. • Maintaining a sustainable environment. • Providing a safe workplace. • Honouring stakeholder commitments.

Founded in 1962 by Glenn Bell, Taco Bell seeks compet- itive advantage via low cost. Like many other services, Taco Bell relies on its operations management to improve productivity and reduce cost.

Its menu and meals are designed to be easy to pre- pare. Taco Bell has shifted a substantial portion of food preparation to suppliers who can perform food processing more efficiently than a stand-alone restaurant. Ground beef is precooked prior to arrival and then reheated, as are many dishes that arrive in plastic boil bags for easy sanitary reheating. Similarly, tortillas arrive already fried and onions arrive prediced. Efficient layout and automa- tion has cut to eight seconds the time needed to prepare tacos and burritos and has cut time in the drive-through lines by one minute. These advances have been combined with training and empowerment to increase the span of management from one supervisor for five restaurants to one supervisor for 30 or more.

Operations managers at Taco Bell believe they have cut in-store labour by 15 hours per day and reduced floor space by more than 50%. The result is a store that can handle twice the volume with half the labour.

In 2010, Taco Bell completed the rollout of its new Grill- to-Order kitchens by installing water- and energy-saving grills that conserve over a billion litres of water and 200 million kWh of electricity each year. This “green”-inspired cooking method also saves the company’s 5600 restau- rants $17 million per year.

Effective operations management has resulted in productivity increases that support Taco Bell’s low-cost strategy. Taco Bell is now the fast-food low-cost leader with a 73% share of the Mexican fast-food market.

Sources: Based on Energy Business Journal (May 12, 2008): 111; Harvard Business Review (July/August 2008): 118; and J. Hueter and W. Swart, Interfaces (January–February 1998): 75–91.

Taco Bell Improves Productivity and Goes Green to Lower CostsOM in Action

Ethics must drive all of a manager’s decisions.

STUDENT TIP

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18 PART 1 Introduction to Operations Management

Managers must do all of this in an ethical and socially responsible way while meeting the demands of the marketplace. If operations managers have a moral awareness and focus on increasing productivity in a system where all stakeholders have a voice, then many of the eth- ical challenges will be successfully addressed (for example, see the OM in Action box “Magna International”). The organization will use fewer resources, the employees will be committed, the market will be satisfied, and the ethical climate will be enhanced. Throughout this text, we note ways in which operations managers can take ethical and socially responsible actions while successfully addressing these challenges of the market. We also conclude each chapter with an Ethical Dilemma exercise.

Operations, marketing, and finance/accounting are the three functions basic to all organizations. The operations function creates goods and services. Much of the progress of oper- ations management has been made in the 20th century, but since the beginning of time, humankind has been attempting to improve its material well-being. Operations managers are key players in the battle to improve productivity.

As societies become increasingly affluent, more of their resources are devoted to services. In Canada, more than three-quarters of the workforce is employed in the service sector. Productivity improvements are difficult to achieve, but operations managers are the primary vehicle for making improvements.

CHAPTER SUMMARY

Major corporations with overseas subcontractors (such as IKEA in Bangladesh, Unilever in India, and Nike in China) have been crit- icized, often with substantial negative publicity, when children as young as 10 have been found working in the subcontractor’s facili- ties. The standard response is to perform an audit and then enhance controls so it does not happen again. In one such case, a 10-year-old

was terminated. Shortly thereafter, the family, without the 10-year- old’s contribution to the family income, lost its modest home, and the 10-year-old was left to scrounge in the local dump for scraps of metal. Was the decision to hire the 10-year-old ethical? Was the decision to terminate the 10-year-old ethical?

ETHICAL DILEMMA

In operations management, balancing the interests of the various stakeholders associated with a company can be challenging at the best of times. To add to the challenge, progressive organizations are now placing the needs of society high on the priority list and have de- clared their corporate social responsibility. Automotive parts manufacturer Magna International is an example of one of these companies.

Magna has publicly stated that it is committed to supporting the basic fabric of society through a number of programs, volunteer work, and charitable activities. Magna’s “Corporate Constitution” allocates a maximum of 2% of its pretax profits to support charitable and nonprofit organizations, and it has pledged support to many pro- grams dealing with health, culture, education, sports, and politics. Magna’s executive officers have expressed their desire to continuously improve the quality of life in each of the communities in which their employees work and live.

Magna International’s “Corporate Constitution” publicly declares and defines the rights of its employees and investors to participate in its profits and growth, while also imposing specified disciplines on management. This con- stitution strikes a balance between employees, investors,

society, and management. This business philosophy was introduced by the company’s founder, Frank Stronach, in 1971—it is known as “Fair Enterprise” and is at the heart of Magna’s operating structure.

Magna InternationalOM in Action

Magna International actively supports the concept of corporate social responsibility.

Source: Based on www.magna.com/about-magna/our-culture /corporate-constitution.

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Chapter 1 Operations and Productivity 19

Discussion Questions

1. Why should one study operations management? 2. Identify four people who have contributed to the theory and

techniques of operations management. 3. Briefly describe the contributions of the four individuals identi-

fied in the preceding question. 4. Figure 1.1 outlines the operations, finance/accounting, and

marketing functions of three organizations. Prepare a chart sim- ilar to Figure 1.1 outlining the same functions for one of the following:

a. newspaper b. drugstore c. college library d. summer camp e. small costume-jewellery factory 5. Answer Question 4 for some other organization, perhaps an

organization where you have worked. 6. What are the three basic functions of a firm? 7. Name the 10 decision areas of operations management.

8. Name four areas that are significant to improving labour productivity.

9. Canada, and indeed much of the world, has been described as a knowledge society. How does this affect productivity measure- ment and the comparison of productivity between Canada and other countries?

10. What are the measurement problems that occur when one attempts to measure productivity?

11. Mass customization and rapid product development were iden- tified as current trends in modern manufacturing operations. What is the relationship, if any, between these trends? Can you cite any examples?

12. What are the five reasons productivity is difficult to improve in the service sector?

13. Describe some of the actions taken by Taco Bell to increase productivity that have resulted in Taco Bell’s ability to serve “twice the volume with half the labour”.

Solved Problems Virtual Office Hours help is available at MyLab Operations Management.

Productivity can be measured in a variety of ways, such as by labour, capital, energy, material usage, and so on. At Modern Lumber, Inc., Art Binley, president and producer of apple crates sold to growers, has been able, with his current equipment, to produce 240 crates per 100 logs. He currently purchases 100 logs per day, and each log requires three labour-hours to process. He

believes that he can hire a professional buyer who can buy a bet- ter-quality log at the same cost. If this is the case, he can increase his production to 260 crates per 100 logs. His labour-hours will increase by eight hours per day.

What will be the impact on productivity (measured in crates per labour-hour) if the buyer is hired?

. SOLUTION

(a) Current labour productivity = 240 crates

100 logs * 3 hours/log

= 240 300

5 0.8 crate per labour-hour

(b) Labour productivity with buyer

= 260 crates

100 logs * 3 hours/log + 8 hours

= 260 308

5 0.844 crates per labour-hour

Using current productivity (0.80 from part [a]) as a base, the increase will be 5.5% (5 0.844/0.8 5 1.055, or a 5.5% increase).

Art Binley has decided to look at his productivity from a multi- factor (total factor productivity) perspective (refer to Solved Problem 1.1). To do so, he has determined his labour, capital, energy, and material usage and decided to use dollars as the com- mon denominator. His total labour-hours are now 300 per day and

will increase to 308 per day. His capital and energy costs will remain constant at $350 and $150 per day, respectively. Material costs for the 100 logs per day are $1000 and will remain the same. Because he pays an average of $10 per hour (with fringes), Binley deter- mines his productivity increase as follows:

. SOLVED PROBLEM 1.2

. SOLVED PROBLEM 1.1

. SOLUTION

Current System

Labour: 300 h @ $10/h 5 $3000

Material: 100 logs/day 1000

Capital: 350

Energy: 150

Total Cost: $4500

Multifactor productivity of current system:

5 240 crates/$4500 5 0.0533 crates/dollar

System with Professional Buyer

308 h @ $10/h 5 $3080

1000

350

150

$4580

Multifactor productivity of proposed system:

5 260 crates/$4580 5 0.0568 crates/dollar

Using current productivity (0.0533) as a base, the increase will be 0.066. That is, 0.0568/0.0533 5 1.066, or a 6.6% increase.

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20 PART 1 Introduction to Operations Management

Problems* • • 1.1 John Lucy makes wooden boxes in which to ship motorcycles. John and his three employees invest a total of 40 hours per day making 120 boxes. a) What is their productivity? b) John and his employees have discussed redesigning the process

to improve efficiency. If they can increase the rate to 125 boxes per day, what will be their new productivity?

c) What will be their unit increase in productivity per hour? d) What will be their percentage change in productivity? PX

• • 1.2 Riverside Metal Works produces cast bronze valves on a 10-person assembly line. On a recent day, 160 valves were pro- duced during an eight-hour shift. a) Calculate the labour productivity of the line. b) The manager at Riverside changed the layout and was able to

increase production to 180 units per eight-hour shift. What is the new labour productivity per labour-hour?

c) What is the percentage of productivity increase? PX

• • 1.3 This year, Benson, Inc., will produce 57 600 hot water heaters at its plant in Saskatoon, Saskatchewan, in order to meet expected global demand. To accomplish this, each labourer at the Saskatoon plant will work 160 hours per month. If the labour pro- ductivity at the plant is 0.15 hot water heaters per labour-hour, how many labourers are employed at the plant?

• • 1.4 As a library or internet assignment, find the U.S. pro- ductivity rate (increase) last year for the (a) national economy, (b) manufacturing sector, and (c) service sector.

• • 1.5 Aditi produces “Final Exam Care Packages” for resale. She is currently working a total of five hours per day to produce 100 care packages. a) What is Aditi’s productivity? b) Aditi thinks that by redesigning the package, she can increase

her total productivity to 133 care packages per day. What will be her new productivity?

c) What will be the percentage increase in productivity if Aditi makes the change? PX

• • 1.6 Eric Lafleur makes billiard balls in his New Brunswick plant. With recent increases in his costs, he has a newfound interest in efficiency. Eric is interested in determining the productivity of his organization. He would like to know if his organization is main- taining the manufacturing average of 3% increase in productivity. He has the following data representing a month from last year and an equivalent month this year:

Last Year Now

Units produced 1 000 1 000

Labour (hours) 300 275

Resin (kilograms) 50 45

Capital invested ($) 10 000 11 000

Energy (BTU) 3 000 2 850

Show the productivity percentage change for each category, and then determine the improvement for labour-hours, the typical stand- ard for comparison. PX

• • 1.7 Eric Lafleur (using data from Problem 1.6) determines his costs to be as follows: • Labour: $10 per hour • Resin: $5 per kilogram • Capital expense: 1% per month of investment • Energy: $0.50 per BTU Show the percentage change in productivity for one month last year versus one month this year, on a multifactor basis with dollars as the common denominator. PX

• • 1.8 Kleen Karpet cleaned 65 rugs in October, consuming the following resources:

Labour: 520 hours at $13 per hour

Solvent: 100 gallons at $5 per gallon

Machine rental: 20 days at $50 per day

a) What is the labour productivity per dollar? b) What is the multifactor productivity? PX

• • 1.9 David Upton is president of Upton Manufacturing, a producer of Go-Kart tires. Upton makes 1000 tires per day with the following resources:

Labour: 400 hours per day @ $12.50 per hour

Raw material: 20 000 pounds per day @ $1 per pound

Energy: $5000 per day

Capital costs: $10 000 per day

a) What is the labour productivity per labour-hour for these tires at Upton Manufacturing?

b) What is the multifactor productivity for these tires at Upton Manufacturing?

c) What is the percent change in multifactor productivity if Upton can reduce the energy bill by $1000 per day without cutting pro- duction or changing any other inputs? PX

• • 1.10 Sawyer’s, a local bakery, is worried about increased costs—particularly energy. Last year’s records provide a fairly good estimate of the parameters for this year. Judy Sawyer, the owner, does not believe things have changed much, but she did invest an additional $3000 for modifications to the bakery’s ovens to make them more energy efficient. The modifications were supposed to make the ovens at least 15% more efficient. Sawyer has asked you to check the energy savings of the new ovens and also to look over other measures of the bakery’s productivity to see if the modifica- tions were beneficial. You have the following data to work with:

Last Year Now

Production (dozen) 1 500 1 500

Labour (hours) 350 325

Capital investment ($) 15 000 18 000

Energy (BTU) 3 000 2 750

• • 1.11 Cunningham Performance Auto, Inc., modifies 375 autos per year. The manager, Peter Cunningham, is interested in obtaining a measure of overall performance. He has asked you to provide him with a multifactor measure of last year’s performance as a benchmark for future comparison. You have assembled the follow- ing data. Resource inputs were: labour, 10 000 hours; 500 suspension and engine modification kits; and energy, 100 000 kilowatt-hours.

PX

* Note: PX means the problem may be solved with POM for Windows and/or Excel OM.

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Chapter 1 Operations and Productivity 21

Average labour cost last year was $20 per hour, kits cost $1000 each, and energy costs were $3 per kilowatt-hour. What do you tell Cunningham? PX

• • 1.12 Halifax Seafood makes 500 wooden packing boxes for fresh seafood per day, working in two 10-hour shifts. Due to increased demand, plant managers have decided to operate three eight-hour shifts instead. The plant is now able to produce 650 boxes per day. a) Calculate the company’s productivity before the change in work

rules and after the change. b) What is the percentage increase in productivity? c) If production is increased to 700 boxes per day, what is the new

productivity? PX

• • 1.13 Marjatta Viitasalo operates a bakery in Thunder Bay, Ontario. Because of its excellent product and excellent location, demand has increased by 25% in the last year. On far too many occasions, customers have not been able to purchase the bread of their choice. Because of the size of the store, no new ovens can be added. At a staff meeting, one employee suggested ways to load the ovens differently so that more loaves of bread can be baked at one time. This new process will require that the ovens be loaded by hand, requiring additional manpower. This is the only thing to be changed. If the bakery makes 1500 loaves per month with a labour productivity of 2.344 loaves per labour-hour, how many workers will Viitasalo need to add? (Hint: Each employee works 160 hours per month.)

• • 1.14 Refer to Problem 1.13. The pay will be $8 per hour for employees. Marjatta Viitasalo can also improve the yield by purchasing a new blender. The new blender will mean an increase in her investment. This added investment has a cost of $100 per month, but she will achieve the same output (an increase to 1875) as the change in labour-hours. Which is the better decision?

a) Show the productivity change, in loaves per dollar, with an increase in labour cost (from 640 to 800 hours).

b) Show the new productivity, in loaves per dollar, with only an increase in investment ($100 per month more).

c) Show the percent productivity change for labour and investment.

• • 1.15 Refer to Problems 1.13 and 1.14. If Marjatta Viitasalo’s utility costs remain constant at $500 per month, labour at $8 per hour, and cost of ingredients at $0.35 per loaf, but Viitasalo does not purchase the blender suggested in Problem 1.14, what will the productivity of the bakery be? What will be the percent increase or decrease?

• • 1.16 In December, General Motors produced 6600 custom- ized vans at its plant in Windsor. The labour productivity at this plant is known to have been 0.10 vans per labour-hour during that month; 300 labourers were employed at the plant that month. a) How many hours did the average labourer work that month? b) If productivity can be increased to 0.11 vans per hour, how many

hours would the average labourer work that month?

• • 1.17 Natalie Attired runs a small job shop where garments are made. The job shop employs eight workers. Each worker is paid $10 per hour. During the first week of March, each worker worked 45 hours. Together, they produced a batch of 132 garments. Of these garments, 52 were “seconds” (meaning that they were flawed). The seconds were sold for $90 each at a factory outlet store. The remain- ing 80 garments were sold to retail outlets at a price of $198 per gar- ment. What was the labour productivity, in dollars per labour-hour, at this job shop during the first week of March?

National Air Express

National Air Express is a competitive air-express firm with offices around the country. Mohammed Chaudry, the Ottawa station manager, is preparing his quarterly budget report, which will be presented at the Eastern regional meeting next week. He is very concerned about adding capital expense to the operation when busi- ness has not increased appreciably. This has been the worst first quarter he can remember, with snowstorms, freezing rain, and bitter cold. He has asked Martha Lewis, field services supervisor, to help him review the available data and offer possible solutions.

Service Methods National Air offers door-to-door overnight air-express delivery within Canada. Chaudry and Lewis manage a fleet of 24 trucks to handle freight in the Ottawa area. Routes are assigned by area, usu- ally delineated by postal codes, major streets, or key geographical features, such as the Ottawa River. Pickups are generally handled between 3:00 p.m. and 6:00 p.m., Monday through Friday. Driver routes are a combination of regularly scheduled daily stops and pickups that the customer calls in as needed. These call-in pickups are dispatched by radio to the driver. Most call-in customers want as late a pickup as possible, just before closing (usually at 5:00 p.m.).

When the driver arrives at each pickup location, he or she pro- vides supplies as necessary (an envelope or box if requested) and must receive a completed air waybill for each package. Because the industry is extremely competitive, a professional, courteous driver is essential to retaining customers. Therefore, Chaudry has always been concerned that drivers not rush a customer to complete his or her package and paperwork.

Budget Considerations Chaudry and Lewis have found that they have been unable to meet their customers’ requests for a scheduled pickup on many occasions in the past quarter. Although, on average, drivers are not handling any more business, they are unable on some days to arrive at each location on time. Chaudry does not think he can justify increasing costs by $1200 per week for additional trucks and drivers while productivity (measured in shipments per truck/day) has remained flat. The company has established itself as the low-cost operator in the industry but has at the same time committed itself to offering quality service and value for its customers.

CASE STUDIES

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22 PART 1 Introduction to Operations Management

Discussion Questions 1. Is the productivity measure of shipments per day per truck still

useful? Are there alternatives that might be more effective? 2. What, if anything, can be done to reduce the daily variability in

pickup call-ins? Can the driver be expected to be at several loca- tions at once at 5:00 p.m.?

3. How should package pickup performance be measured? Are standards useful in an environment that is affected by the weather, traffic, and other random variables? Are other compa- nies having similar problems?

Source: Adapted from a case by Phil Pugliese under the supervision of Professor Marilyn M. Helms, University of Tennessee at Chattanooga. Reprinted by permission.

Frito-Lay, the massive Dallas, Texas-based subsidiary of PepsiCo, has 38 plants and 48 000 employees in North America. Seven of Frito-Lay’s 41 brands exceed $1 billion in sales: Fritos, Lay’s Cheetos, Ruffles, Tostitos, Doritos, and Walker’s Potato Chips. Operations are the focus of the firm—from designing products for new markets, to meeting changing consumer preferences, to adjust- ing to rising commodity costs, to subtle issues involving flavours and preservatives—OM is under constant cost, time, quality, and market pressure. Here is a look at how the 10 decisions of OM are applied at this food processor.

In the food industry, product development kitchens experiment with new products, submit them to focus groups, and perform test marketing. Once the product specifications have been set, processes capable of meeting those specifications and the necessary quality standards are created. At Frito-Lay, quality begins at the farm, with onsite inspection of the potatoes used in Ruffles and the corn used in Fritos. Quality continues throughout the manufacturing process, with visual inspections and with statistical process control of prod- uct variables such as oil, moisture, seasoning, salt, thickness, and weight. Additional quality evaluations are conducted throughout shipment, receipt, production, packaging, and delivery.

The production process at Frito-Lay is designed for large vol- umes and small variety, using expensive special-purpose equip- ment, and with swift movement of material through the facility. Product-focused facilities, such as Frito-Lay’s, typically have high capital costs, tight schedules, and rapid processing. Frito-Lay’s facilities are located regionally to aid in the rapid delivery of prod- ucts because freshness is a critical issue. Sanitary issues and nec- essarily fast processing of products put a premium on an efficient layout. Production lines are designed for balanced throughput and high utilization. Cross-trained workers, who handle a variety of pro- duction lines, have promotion paths identified for their particular skill set. The company rewards employees with medical, retire- ment, and education plans. Its turnover is very low.

The supply chain is integral to success in the food industry; vendors must be chosen with great care. Moreover, the finished food product is highly dependent on perishable raw materials. Consequently, the supply chain brings raw material (potatoes, corn, etc.) to the plant securely and rapidly to meet tight produc- tion schedules. For instance, potatoes are picked in St. Augustine, Florida, unloaded at the Orlando plant, processed, packaged, and shipped from the plant, all in under 12 hours. The requirement for fresh product requires on-time, just-in-time deliveries combined with both low raw material and finished goods inventories. The continuous-flow nature of the specialized equipment in the produc- tion process permits little work-in-process inventory. The plants usually run 24/7. This means that there are four shifts of employees each week.

Tight scheduling to ensure the proper mix of fresh finished goods on automated equipment requires reliable systems and effec- tive maintenance. Frito-Lay’s workforce is trained to recognize problems early, and professional maintenance personnel are avail- able on every shift. Downtime is very costly and can lead to late deliveries, making maintenance a high priority.

Discussion Questions* 1. From your knowledge of production processes and from the case

and the video, identify how each of the 10 decisions of OM is applied at Frito-Lay.

2. How would you determine the productivity of the production process at Frito-Lay?

3. How are the 10 decisions of OM different when applied by the operations manager of a production process such as Frito-Lay versus a service organization such as Hard Rock Cafe? (See the Hard Rock Cafe video case below.)

Frito-Lay: Operations Management in ManufacturingVideo Case

* You may wish to view the video that accompanies this case before addressing these questions.

Sources: Professors Beverly Amer (Northern Arizona University), Barry Render (Rollins College), and Jay Heizer (Texas Lutheran University).

Since its inception in 1971, Hard Rock has grown from a mod- est London pub to a global power managing 150 cafes, 13 hotels/ casinos, live music venues, and a huge annual Rockfest concert. This puts Hard Rock firmly in the service industry—a sector that employs over 75% of the people in the United States. Hard Rock moved its world headquarters to Orlando, Florida, in 1988 and has expanded to more than 40 locations throughout the United States, serving over 100 000 meals each day. Hard Rock chefs are modifying the menu from classic American—burgers and chicken wings—to include

higher-end items such as stuffed veal chops and lobster tails. Just as taste in music changes over time, so does Hard Rock Cafe, with new menus, layouts, memorabilia, services, and strategies.

At Orlando’s Universal Studios, a traditional tourist destina- tion, Hard Rock Cafe serves over 3500 meals each day. The cafe employs about 400 people. Most are employed in the restaurant, but some work in the retail shop. Retail is now a standard and increas- ingly prominent feature in Hard Rock Cafes (since close to 48% of revenue comes from this source). Cafe employees include kitchen

Hard Rock Cafe: Operations Management in ServicesVideo Case

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Chapter 1 Operations and Productivity 23

and wait staff, hostesses, and bartenders. Hard Rock employees are not only competent in their job skills but are also passionate about music and have engaging personalities. Cafe staff is scheduled down to 15-minute intervals to meet seasonal and daily demand changes in the tourist environment of Orlando. Surveys are done on a regular basis to evaluate quality of food and service at the cafe. Scores are rated on a 1 to 7 scale, and if the score is not a 7, the food or service is considered a failure.

Hard Rock is adding a new emphasis on live music and is rede- signing its restaurants to accommodate the changing tastes. Since Eric Clapton hung his guitar on the wall to mark his favourite bar stool, Hard Rock has become the world’s leading collector and exhibitor of rock ‘n’ roll memorabilia, with changing exhibits at its cafes through- out the world. The collection includes thousands of pieces, valued at $40 million. In keeping with the times, Hard Rock also maintains a website, www.hardrock.com, which receives over 100 000 hits per

week, and a weekly cable television program on VH-1. Hard Rock’s brand recognition, at 92%, is one of the highest in the world.

Discussion Questions* 1. From your knowledge of restaurants, the video, the Global

Company Profile that opens this chapter, and the case itself, identify how each of the 10 decisions of operations management is applied at Hard Rock Cafe.

2. How would you determine the productivity of the kitchen staff and wait staff at Hard Rock?

3. How are the 10 decisions of OM different when applied to the operations manager of a service operation such as Hard Rock versus an automobile company such as Ford Motor Company?

* You may wish to view the video that accompanies this case before addressing these questions.

Main Heading Review Material

MyLab Operations Management

WHAT IS OPERATIONS MANAGEMENT? (p. 2)

• Production—The creation of goods and services. • Operations management (OM)—Activities that relate to the creation of

goods and services through the transformation of inputs to outputs.

VIDEO 1.1

Operations Management at Hard Rock

VIDEO 1.2 Operations Management at Frito-Lay

ORGANIZING TO PRODUCE GOODS AND SERVICES (pp. 3–4)

All organizations perform three functions to create goods and services: 1. Marketing, which generates demand 2. Production/operations, which creates the product 3. Finance/accounting, which tracks how well the organization is doing,

pays the bills, and collects the money

THE SUPPLY CHAIN (p. 4)

• Supply chain—A global network of organizations and activities that supplies a firm with goods and services.

WHY STUDY OPERATIONS MANAGEMENT? (pp. 4–5)

We study OM for four reasons: 1. To learn how people organize themselves for productive enterprise 2. To learn how goods and services are produced 3. To understand what operations managers do 4. Because OM is a costly part of an organization

WHAT OPERATIONS MANAGERS DO (pp.5–6)

• Management process—The application of planning, organizing, staffing, leading, and controlling to achieve objectives.Ten major decisions are required of operations managers:

1. Design of goods and services 2. Managing quality 3. Process strategy 4. Location strategy 5. Layout strategy 6. Human resources 7. Supply chain management 8. Inventory management 9. Scheduling 10. Maintenance About 40% of all jobs are in OM. Operations managers possess job titles such as plant manager, quality manager, process-improvement consultant, and operations analyst.

CHAPTER 1 RAPID REVIEW

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24 PART 1 Introduction to Operations Management

Main Heading Review Material

MyLab Operations Management

THE HERITAGE OF OPERATIONS MANAGEMENT (pp. 6–8)

Significant events in modern OM can be classified into five eras:

1. Early concepts (1776–1880)—Labour specialization (Smith, Babbage), standardized parts (Whitney)

2. Scientific management (1880–1910)—Gantt charts (Gantt), motion and time studies (Gilbreth), process analysis (Taylor), queuing theory (Erlang)

3. Mass production (1910–1980)—Assembly line (Ford/Sorensen), sta- tistical sampling (Shewhart), economic order quantity (Harris), linear programming (Dantzig), PERT/CPM (DuPont), material requirements planning

4. Lean production (1980–1995)—Just-in-time, computer-aided design, electronic data interchange, total quality management, Baldrige Award, empowerment, kanbans

5. Mass customization (1995–2005)—Globalization, internet/ecommerce, enterprise resource planning, international quality standards, finite sched- uling, supply chain management, mass customization, build-to-order, sustainability

6. Globalization era (2005–2020)—Global supply chains, growth of trans- national organizations, instant communications, sustainability, ethics in a global work force, logistics and shipping

OPERATIONS IN THE SERVICE SECTOR (pp. 9–11)

• Services—Economic activities that typically produce an intangible product (such as education, entertainment, lodging, government, financial, and health services). Almost all services and almost all goods are a mixture of a service and a tangible product.

• Service sector—The segment of the economy that includes trade, finance, lodging, education, law, medicine, and other professional occupations. Services now constitute the largest economic sector in postindustrial so- cieties. The huge productivity increases in agriculture and manufacturing have allowed more of our economic resources to be devoted to services. Many service jobs pay very well.

NEW CHALLENGES IN OPERATIONS MANAGEMENT (p. 11)

Some of the current challenges for operations managers include: • Global focus; international collaboration • Rapid product development; design collaboration • Environmentally sensitive production; green manufacturing; sustainability • Mass customization • Supply chain partnering; joint ventures; alliances • Lean operations; continuous improvement and elimination of waste

THE PRODUCTIVITY CHALLENGE (pp. 11–17)

• Productivity—The ratio of outputs (goods and services) divided by one or more inputs (such as labour, capital, or management).

High production means producing many units, while high productivity means producing units efficiently.

Only through increases in productivity can the standard of living of a coun- try improve. Canadian productivity has averaged over 3% for the past half century.

Productivity = Units produced

Input used (1-1)

• Single-factor productivity—Indicates the ratio of one resource (input) to the goods and services produced (outputs).

• Multifactor productivity—Indicates the ratio of many or all resources (inputs) to the goods and services produced (outputs). Also called total factor productivity.

Multifactor Productivity

= Output

Labour + Material + Energy + Capital + Miscellaneous (1-2)

Problems: 1.1–1.17

Virtual Office Hours for Solved Problems: 1.1, 1.2

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Chapter 1 Operations and Productivity 25

Main Heading Review Material

MyLab Operations Management

Measurement problems with productivity include: (1) the quality may change, (2) external elements may interfere, and (3) precise units of measure may be lacking.

• Productivity variables—The three factors critical to productivity im- provement are labour (10%), capital (38%), and management (52%).

• Knowledge society—A society in which much of the labour force has migrated from manual work to work based on knowledge.

ETHICS, SOCIAL RESPONSIBILITY, AND SUSTAINABILITY (pp. 17–18)

Among the many ethical challenges facing operations managers are (1) efficiently developing and producing safe, quality products; (2) maintaining a clean environment; (3) providing a safe workplace; and (4) honouring stakeholder commitments.

LO1 Productivity increases when: a) inputs increase while outputs remain the same. b) inputs decrease while outputs remain the same. c) outputs decrease while inputs remain the same. d) inputs and outputs increase proportionately. e) inputs increase at the same rate as outputs.

LO2 Services often: a) are tangible. b) are standardized. c) are knowledge based. d) are low in customer interaction. e) have consistent product definition.

LO3 Productivity: a) can use many factors as the numerator. b) is the same thing as production. c) increases at about 0.5% per year. d) is dependent upon labour, management, and capital. e) is the same thing as effectiveness.

LO4 Single-factor productivity: a) remains constant. b) is never constant.

c) usually uses labour as a factor. d) seldom uses labour as a factor. e) uses management as a factor.

LO5 Multifactor productivity: a) remains constant. b) is never constant. c) usually uses substitutes as common variables for the factors of

production. d) seldom uses labour as a factor. e) always uses management as a factor.

LO6 Productivity increases each year in Canada are a result of three factors:

a) labour, capital, management b) engineering, labour, capital c) engineering, capital, quality control d) engineering, labour, data processing e) engineering, capital, data processing

Self-Test  Before taking the self-test, refer to the learning objectives listed at the beginning of the chapter and the key terms listed at the end of the chapter.

Answers: LO1. b; LO2. c; LO3. d; LO4. c; LO5. c; LO6. a

Most of these questions can be found in MyLab Operations Management. Visit MyLab Operations Management to access cases, videos, downloadable software, and much more. MyLab Operations Management Management also features a personalized Study Plan that helps you identify which chapter concepts you’ve mastered and guides you towards study tools for additional practice.

MyLab Operations Management

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26

Global Company

Profile Boeing

Boeing’s Global Strategy Yields Competitive Advantage Boeing’s strategy for its 787 Dreamliner is unique from both an

engineering and a global perspective.

The Dreamliner incorporates the latest in a wide range of aerospace

technologies, from airframe and engine design to super-lightweight

titanium-graphite laminate, carbon-fibre and epoxy, and composites.

Another innovation is the electronic monitoring system that allows the

airplane to report maintenance requirements to ground-based computer

systems. Boeing has also worked with General Electric and Rolls-Royce

to develop more efficient engines. The advances in engine technology

contribute as much as 8% of the increased fuel/payload efficiency of the

new airplane, representing a nearly two-generation jump in technology.

This state-of-the-art Boeing 787 is also global. Led by Boeing at its

Everett, Washington, facility, an international team of aerospace companies

developed the airplane. New technologies, new design, new manufacturing

processes, and committed international suppliers are helping Boeing and its

Operations Strategy in a Global Environment

Learning Objectives LO1 Define mission and strategy 32

LO2 Identify and explain three strategic approaches to competitive advantage 32

LO3 Identify and define the 10 decisions of operations management 36

LO4 Understand the significance of key success factors and core competencies 41

LO5 Identify and explain four global operations strategy options 47

2 Peter Carey/Alamy Stock Photo

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Chapter 2 Operations Strategy in a Global Environment 27

partners achieve unprecedented levels of performance

in design, manufacture, and operation.

The 787 is global not only because it has a range

of 13 800 km but also because it is built all over the

world—with a huge financial risk of over US $5 bil-

lion, Boeing needed partners. The global nature of

both technology and the aircraft market meant finding

exceptional developers and suppliers, wherever they

might be. It also meant finding firms willing to step

up to the risk associated with a very expensive new

product. These partners not only spread the risk but also

bring commitment to the table. Countries that have a

stake in the 787 are more likely to buy from Boeing than

from the European competitor Airbus Industrie.

Boeing teamed with more than 20 international

systems suppliers to develop technologies and design

concepts for the 787. Boeing found its 787 partners

in over a dozen countries; a few of them are shown in

the table.

Some of the International Suppliers of Boeing 787 Components

Latecoere France Passenger doors

Labinal France Wiring

Dassault France Design and PLM software

Messier-Bugatti France Electric brakes

Thales France Electrical power conversion system and integrated standby flight display

Messier-Dowty France Landing gear structure

Diehl Germany Interior lighting

Cobham United Kingdom Fuel pumps and valves

Rolls-Royce United Kingdom Engines

Smiths Aerospace United Kingdom Central computer system

BAE Systems United Kingdom Electronics

Alenia Aeronautica Italy Upper centre fuselage and horizontal stabilizer

Toray Industries Japan Carbon fibre for wing and tail units

Fuji Heavy Industries Japan Centre wing box

Kawasaki Heavy Industries Japan Forward fuselage, fixed sections of wing, landing gear wheel well

Teijin Seiki Japan Hydraulic actuators

Mitsubishi Heavy Industries Japan Wing box

Chengdu Aircraft Group China Rudder

Hafei Aviation China Parts

Korean Airlines South Korea Wingtips

Saab Sweden Cargo and access doors

State-of-the-art composite sections of the 787 are built around the world and shipped to Boeing for final assembly.

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28 PART 1 Introduction to Operations Management

A Global View of Operations and Supply Chains Today’s operations manager must have a global view of operations strategy. Since the early 1990s, nearly 3 billion people in developing countries have overcome the cultural, religious, ethnic, and political barriers that constrain productivity and are now players on the global eco- nomic stage. As these barriers disappear, simultaneous advances are being made in technology, reliable shipping, and cheap communication. The unsurprising result is the growth of world trade (see Figure 2.1), global capital markets, and the international movement of people. This means increasing economic integration and interdependence of countries—in a word, globalization. In response, organizations are hastily extending their operations globally with innovative strategies. For instance:

• Boeing is competitive because both its sales and production are worldwide. • Italy’s Benetton moves inventory to stores around the world faster than its competition by

building flexibility into design, production, and distribution. • Sony purchases components from suppliers in Thailand, Malaysia, and elsewhere around the

world for assembly in its electronic products. • Volvo, considered a Swedish company, was recently controlled by a U.S. company (Ford)

and has been subsequently acquired by Geely of China. But the current Volvo S40 is built in Belgium on a platform shared with the Mazda 3 (built in Japan) and the Ford Focus (built in Europe.)

Globalization means that domestic production and exporting may no longer be a viable business model; local production and exporting no longer guarantee success or even survival. There are new standards of global competitiveness that impact quality, variety, customiza- tion, convenience, timeliness, and cost. The globalization of strategy contributes efficiency and adds value to products and services, but it also complicates the operations manager’s job. Complexity, risk, and competition are intensified; companies must carefully account for them.

The Japanese companies Toray, Teijin Seiki, Fuji,

Kawasaki, and Mitsubishi are producing over 35%

of the project, providing whole composite fuselage

sections. Italy’s Alenia Aeronautica is building an

additional 10% of the plane.

Many North American companies—including Crane

Aerospace, Fairchild Controls, Goodrich, General

Dynamics, Hamilton Sundstrand, Honeywell, Moog,

Parker Hannifin, Rockwell Collins, and Triumph Group—

are also suppliers. Boeing has 70% to 80% of the

Dreamliner built by other companies. And even some of

the portion built by Boeing is produced at Boeing facilities

outside the United States, in Australia and Canada.

The Dreamliner is efficient, has a global range,

and is made from components produced around the

world. The result: a state-of-the-art airplane reflecting

the global nature of business in the 21st century and

one of the fastest-selling commercial jets in history.

As Prof. Thomas Sewell observed, “No great civilization has developed in isolation.”

Source: Thomas Sowell, Race, Culture, and Equality, Hoover Press, 1998.

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Growth of World Trade as a Percent of World GDP

Source: World Bank; World Trade Organization; and IMF.

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Chapter 2 Operations Strategy in a Global Environment 29

We have identified six reasons why domestic business operations decide to change to some form of international operation. They are:

1. Reduce costs (labour, taxes, tariffs, etc.). 2. Improve the supply chain. 3. Provide better goods and services. 4. Understand markets. 5. Learn to improve operations. 6. Attract and retain global talent.

Let us examine, in turn, each of the six reasons.

REDUCE COSTS Many international operations seek to take advantage of the tangible opportunities to reduce their costs. Foreign locations with lower wages can help lower both direct and indirect costs. (See the OM in Action box “Cartoon Production at Home in Manila.”) Less stringent government regulations on a wide variety of operations practices (e.g., environmental control, health and safety, etc.) reduce costs. Opportunities to cut the cost of taxes and tariffs also encourage foreign operations. In Mexico, the creation of maquiladoras (free-trade zones) allows manufacturers to cut their costs of taxation by paying only on the value added by Mexican workers. If a Canadian manufacturer brings a $500 machine to a maquiladora operation for assembly work costing $25, tariff duties will be charged only on the $25 of work performed in Mexico.

Shifting low-skilled jobs to another country has several potential advantages. First, and most obviously, the firm may reduce costs. Second, moving the lower-skilled jobs to a lower-cost location frees higher-cost workers for more valuable tasks. Third, reducing wage costs allows the savings to be invested in improved products and facilities (and the retraining of existing workers, if necessary) at the home location. The impact of this approach is shown in the OM in Action box, “Going Global to Compete”.

Trade agreements have also helped reduce tariffs and thereby reduce the cost of operating facilities in foreign countries. The World Trade Organization (WTO) has helped reduce tariffs from 40% in 1940 to less than 3% today. Another important trade agreement is the United States, Mexico, Canada Agreement (USMCA). USMCA seeks to phase out all trade and tariff barri- ers among Canada, Mexico, and the United States. Other trade agreements that are accelerating global trade include APEC (the Pacific Rim countries), SEATO (Australia, New Zealand, Japan, Hong Kong, South Korea, New Guinea, and Chile), MERCOSUR (Argentina, Brazil, Paraguay, and Uruguay), and CAFTA (Central America, Dominican Republic, and the United States).

Another trading group is the European Union (EU).1 The European Union has reduced trade barriers among the participating European nations through standardization and a common

Maquiladoras Mexican factories located along the U.S.–Mexico border that receive preferential tariff treatment.

World Trade Organization (WTO) An international organization that promotes world trade by lowering barriers to the free flow of goods across borders.

United States, Mexico, Canada Agreement (USMCA) A free trade agreement between Canada, Mexico, and the United States.

European Union (EU) A European trade group that has 28 member states as of 2015.

1 The 28 members of the European Union (EU) as of 2015 were Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, and the United Kingdom. Not all have adopted the euro. In addition, Albania, Montenegro, Serbia, Macedonia, and Turkey are candidates for entry into the EU.

Fred Flintstone is not from Bedrock. He is actually from Manila, capital of the Philippines. So are Tom and Jerry, Aladdin, and Donald Duck. More than 90% of North American television cartoons are produced in Asia and India, with the Philippines leading the way. With their competitive advantage of English as an official language and a strong familiarity with North American culture, animation companies in Manila now employ more than 1700 people. Filipinos understand Western culture, and “You need to have a group of artists that can under- stand the humour that goes with it,” says Bill Dennis, a Hanna-Barbera executive.

Major studios like Disney, Marvel, Warner Brothers, and Hanna-Barbera send storyboards—cartoon action outlines—and voice tracks to the Philippines. Artists there draw, paint, and film about 20 000 sketches for a 30-minute episode. The cost of $130 000 to produce an episode in the Philippines compares with $160 000 in Korea and $500 000 in the United States.

Sources: Journal of Global Information Technology Management (2007): 1–6; The New York Times (February 26, 2004): A29; and The Wall Street Journal (August 9, 2005): D8.

Cartoon Production at Home in ManilaOM in Action

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30 PART 1 Introduction to Operations Management

currency, the euro. However, this major Canadian trading partner, with 503 million people, is also placing some of the world’s most restrictive conditions on products sold in the EU. Everything from recycling standards to automobile bumpers to hormone-free farm products must meet EU standards, complicating international trade.

IMPROVE THE SUPPLY CHAIN The supply chain can often be improved by locating facilities in countries where unique resources are available. These resources may be expertise, labour, or raw material. For example, a trend is evident in which precious metals companies are relocating to the mining regions of northern Ontario. Auto-styling studios from throughout the world are migrating to the auto Mecca of southern California to ensure the necessary expertise in contemporary auto design. Similarly, world athletic shoe production has migrated from South Korea to Guangzhou, China: this loca- tion takes advantage of the low-cost labour and production competence in a city where 40 000 people work making athletic shoes for the world. And a perfume essence manufacturer wants a presence in Grasse, France, where much of the world’s perfume essences are prepared from the flowers of the Mediterranean.

PROVIDE BETTER GOODS AND SERVICES Although the characteristics of goods and services can be objective and measurable (e.g., num- ber of on-time deliveries), they can also be subjective and less measurable (e.g., sensitivity to culture). We need an ever better understanding of differences in culture and of the way business is handled in different countries. Improved understanding as the result of a local presence per- mits firms to customize products and services to meet unique cultural needs in foreign markets.

Another reason to have international operations is to reduce response time to meet customers’ changing product and service requirements. Customers who purchase goods and services from Canadian firms are increasingly located in foreign countries. Providing them with quick and adequate service is often improved by locating facilities in their home countries.

UNDERSTAND MARKETS Because international operations require interaction with foreign customers, suppliers, and other competitive businesses, international firms inevitably learn about opportunities for new products and services. Europe led the way with cell phone innovations, and now the Japanese lead with the latest cell phone fads. Knowledge of these markets helps firms not only under- stand where the market is going but also diversify their customer base, add production flexibil- ity, and smooth the business cycle.

Another reason to go into foreign markets is the opportunity to expand the life cycle (i.e., stages a product goes through; see Chapter 5) of an existing product. While some products in

Headquartered in Montreal and founded in 1880, Bell Canada is one of Canada’s prominent players in wire- less telecommunications, controlling about 30% of the domestic market. Approximately 50% of Bell Canada’s revenue stems from its wireless initiatives. It is active in contracting suitable vendors as part of outsourcing key voice-based projects for its satellite TV, Bell Mobility, Solo Mobility, and internet divisions. Bell Canada intends to outsource these particular projects via fixed payouts as part of a deal worth roughly between $25 million and $30 million per year. India is the beneficiary of these outsourced contracts, and the projects include inbound customer contact. Bell remains watchful for outsourcing partners with strong competen- cies in managing this type of front-end work.

In a similar fashion, the Canadian Bar Association reported through its in-house magazine about the “com- moditization” of legal services, and noted a trend toward outsourcing certain aspects of legal work. Although the concept is fairly new to Canadian lawyers, firms that do engage in it suggest they provide hourly savings of up to 75%.

Resourceful organizations, such as Bell Canada and these law firms, use a global perspective to become more efficient, which allows them to develop new products, retrain employees, and invest in new plant and equipment.

Sources: Ottawa Citizen (2006); and www.bell.ca.

Going Global to CompeteOM in Action

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Chapter 2 Operations Strategy in a Global Environment 31

Canada are in a “mature” stage of their product life cycle, they may represent state-of-the-art products in less-developed countries. For example, the market for personal computers could be characterized as “mature” in Canada but as in the “introductory” stage in many developing coun- tries, such as Vietnam and Myanmar (Burma).

LEARN TO IMPROVE OPERATIONS Learning does not take place in isolation. Firms serve themselves and their customers well when they remain open to the free flow of ideas. For example, General Motors found that it could improve operations by jointly building and running, with the Japanese, an auto assembly plant in San Jose, California. This strategy allowed GM to contribute its capital and knowledge of North American labour and environmental laws while the Japanese contributed production and inven- tory ideas. Similarly, operations managers have improved equipment and layout by learning from the ergonomic competence of the Scandinavians.

ATTRACT AND RETAIN GLOBAL TALENT Global organizations can attract and retain better employees by offering more employment opportunities. They need people in all functional areas and areas of expertise worldwide. Global firms can recruit and retain good employees because they provide both greater growth oppor- tunities and insulation against unemployment during times of economic downturn. During eco- nomic downturns in one country or continent, a global firm has the means to relocate unneeded personnel to more prosperous locations.

So, to recap, successfully achieving a competitive advantage in our shrinking world means maximizing all of the possible opportunities, from tangible to intangible, that international oper- ations can offer.

Cultural and Ethical Issues While there are great forces driving firms towards globalization, many challenges remain. One of these challenges is reconciling differences in social and cultural behaviour. With issues rang- ing from bribery, to child labour, to the environment, managers sometimes do not know how to respond when operating in a different culture. What one country’s culture deems acceptable may be considered unacceptable or illegal in another. It is not by chance that there are fewer female managers in the Middle East than in India.

In the last decade, changes in international laws, agreements, and codes of conduct have been applied to define ethical behaviour among managers around the world. The WTO, for example, helps to make uniform the protection of both governments and industries from foreign firms that engage in unethical conduct. Even on issues where significant differences between cultures exist, as in the area of bribery or the protection of intellectual property, global uniformity is slowly being accepted by most nations.

As the owner of a Guatemala plant said, “The ethics of the world markets is very clear: Manufacturers will move wherever it is cheapest or most convenient to their interests.”

A worldwide strategy places added burdens on operations management. Because of regional differences, designers and manufacturers must adapt their products to suit their various markets. A common example of the market differences involves automobiles and the need to place the driver on either the right or the left due to the local roadways and infrastructure.

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32 PART 1 Introduction to Operations Management

In spite of cultural and ethical differences, we live in a period of extraordinary mobility of capital, information, goods, and even people. We can expect this to continue. The financial sec- tor, the telecommunications sector, and the logistics infrastructure of the world are healthy insti- tutions that foster efficient and effective use of capital, information, and goods. Globalization, with all its opportunities and risks, is here and will continue. It must be embraced as managers develop their missions and strategies.

Developing Missions and Strategies An effective operations management effort must have a mission so it knows where it is going and a strategy so it knows how to get there. This is the case for a small domestic organization as well as a large international organization.

MISSION Economic success, indeed survival, is the result of identifying missions to satisfy a customer’s needs and wants. We define the organization’s mission as its purpose—what it will contribute to society. Mission statements provide boundaries and focus for organizations and the concept around which the firm can rally. The mission states the rationale for the organization’s existence. Developing a good strategy is difficult, but it is much easier if the mission has been well defined. Figure 2.2 provides examples of mission statements.

Once an organization’s mission has been decided, each functional area within the firm deter- mines its supporting mission. By functional area, we mean the major disciplines required by the firm, such as marketing, finance/accounting, and production/operations. Missions for each func- tion are developed to support the firm’s overall mission. Then within that function, lower-level supporting missions are established for the OM functions. Figure 2.3 provides such a hierarchy of sample missions.

STRATEGY With the mission established, strategy and its implementation can begin. Strategy is an organ- ization’s action plan to achieve the mission. Each functional area has a strategy for achieving its mission and for helping the organization reach the overall mission. These strategies exploit opportunities and strengths, neutralize threats, and avoid weaknesses. In the following sections, we will describe how strategies are developed and implemented.

Firms achieve missions in three conceptual ways: (1) differentiation, (2) cost leadership, and (3) response. This means operations managers are called on to deliver goods and services that are (1) better, or at least different, (2) cheaper, and (3) more responsive. Operations managers trans- late these strategic concepts into tangible tasks to be accomplished. Any one or combination of

LO1 Define mission and strategy

Mission The purpose or rationale for an organization’s existence.

Strategy How an organization expects to achieve its missions and goals.

LO2 Identify and explain three strategic approaches to competitive advantage

Getting an education and managing an organization both require a mission and a strategy.

Royal Canadian Mounted Police

Hard Rock Cafe

Arnold Palmer Hospital

The RCMP is Canada’s national police service. Proud of our traditions and confident in meeting future challenges, we commit to preserve the peace, uphold the law and provide quality service in partnership with our communities.

Our Mission: To spread the spirit of rock ’n roll by creating authentic experiences that rock.

Arnold Palmer Hospital for Children provides state of the art, family-centered healthcare focused on restoring the joy of childhood in an environment of compassion, healing and hope.

Source: Mission Statement for Royal Canadian Mounted Police. Reprinted with permission.

Source: Mission Statement for Hard Rock Café, Hard Rock Café International (USA), Inc. Reprinted with permission.

Source: Mission Statement from Arnold Palmer Hospital for Children. Copyright © by Orlando Health. Reprinted with permission.

FIGURE 2.2

Mission Statements for Three Organizations

VIDEO 2.1 Operations Strategy at Regal Marine

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Chapter 2 Operations Strategy in a Global Environment 33

these three strategic concepts can generate a system that has a unique advantage over competi- tors. For example, Hunter Fan has differentiated itself as a premier maker of quality ceiling fans that lower heating and cooling costs for its customers. Nucor Steel, on the other hand, satisfies customers by being the lowest-cost steel producer in the world. And Dell achieves rapid response by building personal computers with each customer’s requested software in a matter of hours.

Clearly, strategies differ. And each strategy puts different demands on operations manage- ment. Hunter Fan’s strategy is one of differentiating itself via quality from others in the industry. Nucor focuses on value at low cost, and Dell’s dominant strategy is quick, reliable response.

Achieving Competitive Advantage Through Operations Each of the three strategies provides an opportunity for operations managers to achieve com- petitive advantage. Competitive advantage implies the creation of a system that has a unique advantage over competitors. The idea is to create customer value in an efficient and sustainable

Competitive advantage The creation of a unique advantage over competitors.

Sample Company Mission

Sample OM Department Missions

Sample Operations Management Mission

Process design To determine, design, and produce the production process and equipment that will be compatible with low-cost product, high quality, and a good quality of work life at economical cost.

Location To locate, design, and build efficient and economical facilities that will yield high value to the company, its employees, and the community.

Product design To design and produce products and services with outstanding quality and inherent customer value.

Quality management To attain the exceptional value that is consistent with our company mission and marketing objectives by close attention to design, procurement, production, and field service opportunities.

Layout design To achieve, through skill, imagination, and resourcefulness in layout and work methods, production effectiveness and efficiency while supporting a high quality of work life.

Human resources To provide a good quality of work life, with well-designed, safe, rewarding jobs, stable employment, and equitable pay, in exchange for outstanding individual contribution from employees at all levels.

Supply chain management To collaborate with suppliers to develop innovative products from stable, effective, and efficient sources of supply.

Inventory To achieve low investment in inventory consistent with high customer service levels and high facility utilization.

Scheduling To achieve high levels of throughput and timely customer delivery through effective scheduling.

Maintenance To achieve high utilization of facilities and equipment by effective preventive maintenance and prompt repair of facilities and equipment.

To manufacture and service an innovative, growing, and profitable worldwide microwave communications business that exceeds our customers’ expectations.

To produce products consistent with the company’s mission as the worldwide low-cost manufacturer.

FIGURE 2.3

Sample Missions for a Company, the Operations Function, and Major OM Departments

For many organizations, the operations function provides the competitive advantage.

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34 PART 1 Introduction to Operations Management

way. Pure forms of these strategies may exist, but operations managers will more likely be called on to implement some combination of them. Let us briefly look at how managers achieve com- petitive advantage via differentiation, low cost, and response.

COMPETING ON DIFFERENTIATION Safeskin Corporation is number one in latex exam gloves because it has differentiated itself and its products. It did so by producing gloves that were designed to prevent allergic reactions about which doctors were complaining. When other glove makers caught up, Safeskin devel- oped hypoallergenic gloves. Then it added texture to its gloves. Then it developed a synthetic disposable glove for those allergic to latex—always staying ahead of the competition. Safeskin’s strategy is to develop a reputation for designing and producing reliable state-of-the-art gloves, thereby differentiating itself.

Differentiation is concerned with providing uniqueness. A firm’s opportunities for creat- ing uniqueness are not located within a particular function or activity but can arise in virtu- ally everything the firm does. Moreover, because most products include some service, and most services include some product, the opportunities for creating this uniqueness are limited only by imagination. Indeed, differentiation should be thought of as going beyond both physical characteristics and service attributes to encompass everything about the product or service that influences the value that the customers derive from it. Therefore, effective operations managers assist in defining everything about a product or service that will influence the potential value to the customer. This may be the convenience of a broad product line, product features, or a service related to the product. Such services can manifest themselves through convenience (location of distribution centres, stores, or branches), training, product delivery and installation, or repair and maintenance services.

In the service sector, one option for extending product differentiation is through an experi- ence. Differentiation by experience in services is a manifestation of the growing “experience economy”. The idea of experience differentiation is to engage the customer—to use people’s five senses so they become immersed, or even an active participant, in the product. Disney does this with the Magic Kingdom. People no longer just go on a ride; they are immersed in the Magic Kingdom—surrounded by a dynamic visual and sound experience that complements the phys- ical ride. Some rides further engage the customer by having them steer the ride or shoot targets or villains.

Theme restaurants, such as Hard Rock Cafe, likewise differentiate themselves by providing an “experience”. Hard Rock engages the customer with classic rock music, big-screen rock vid- eos, memorabilia, and staff who can tell stories. In many instances, a full-time guide is available to explain the displays, and there is always a convenient retail store so the guest can take home a tangible part of the experience. The result is a “dining experience” rather than just a meal. In a less dramatic way, both Tim Hortons and your local supermarket deliver an experience when they provide music and the aroma of brewing coffee or freshly baked bread.

COMPETING ON COST Porter Airlines has been a consistent success while other North American airlines have lost bil- lions of dollars. Porter has done this by fulfilling a need for low-cost and short-hop flights. Its operations strategy has included use of secondary airports and terminals, few fare options, smaller crews, and no expensive ticket offices.

Additionally, and less obviously, Porter has very effectively matched capacity to demand and effectively utilized this capacity. It has done this by designing a route structure that matches the capacity of its Bombardier Q400, the only plane in its fleet. Second, it achieves more air miles than other airlines through faster turnarounds—its planes are on the ground less.

One driver of a low-cost strategy is a facility that is effectively utilized. Porter and others with low-cost strategies understand this and utilize resources effectively. Identifying the opti- mum size (and investment) allows firms to spread overhead costs, providing a cost advantage. For instance, Walmart continues to pursue its low-cost strategy with superstores that are open 24 hours a day. For more than 50 years, it has successfully grabbed market share. Walmart has driven down store overhead costs, shrinkage, and distribution costs. Its rapid transportation of goods, reduced warehousing costs, and direct shipment from manufacturers have resulted in high inventory turnover and made it a low-cost leader.

Differentiation Distinguishing the offerings of an organization in a way that the customer perceives as adding value.

Experience differentiation Engaging a customer with a prod- uct through imaginative use of the five senses, so the customer “experiences” the product.

VIDEO 2.2 Hard Rock’s Global Strategy

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Chapter 2 Operations Strategy in a Global Environment 35

Low-cost leadership entails achieving maximum value, as defined by your customer. It requires examining each of the 10 OM decisions in a relentless effort to drive down costs while meeting customer expectations of value. A low-cost strategy does not imply low value or low quality.

COMPETING ON RESPONSE The third strategy option is response. Response is often thought of as flexible response, but it also refers to reliable and quick response. Indeed, we define response as including the entire range of values related to timely product development and delivery, as well as reliable scheduling and flexible performance.

Flexible response may be thought of as the ability to match changes in a marketplace where design innovations and volumes fluctuate substantially.

Hewlett-Packard is an exceptional example of a firm that has demonstrated flexibility in both design and volume changes in the volatile world of personal computers. HP’s products often have a life cycle of months, and volume and cost changes during that brief life cycle are dra- matic. However, HP has been successful at institutionalizing the ability to change products and volume to respond to dramatic changes in product design and costs—thus building a sustainable competitive advantage.

The second aspect of response is the reliability of scheduling. One way the German machine industry has maintained its competitiveness despite having the world’s highest labour costs is through reliable response. This response manifests itself in reliable schedul- ing. German machine firms have meaningful schedules—and they perform to these schedules. Moreover, the results of these schedules are communicated to the customer, and the cus- tomer can, in turn, rely on them. Consequently, the competitive advantage generated through reliable response has value to the end customer. This is also true for organizations such as grocerygateway.com, where reliability in scheduling and adhering to these schedules is an expectation of customers.

The third aspect of response is quickness. Whether it is a production system at a Toyota plant, a pizza delivered in five minutes by Pizza Hut, or customized phone products delivered in three days from Motorola, the operations manager who develops systems that respond quickly can have a competitive advantage.

In practice, differentiation, low cost, and response can increase productivity and generate a sustainable competitive advantage (see Figure 2.4). Proper implementation of the following decisions by operations managers will allow these advantages to be achieved.

Low-cost leadership Achieving maximum value, as perceived by the customer.

Response A set of values related to rapid, flexible, and reliable performance.

Whether it is because of a busy lifestyle or other reasons, customers can shop at home for groceries by placing an order with grocerygateway.com and arranging for a delivery time within a 90-minute window. Reliability is vital for this type of service.

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36 PART 1 Introduction to Operations Management

10 Strategic OM Decisions Differentiation, low cost, and response can be achieved when managers make effective decisions in 10 areas of OM. These are collectively known as operations decisions. The 10 decisions of OM that support missions and implement strategies are:

1. Goods and service design: Designing goods and services defines much of the transfor- mation process. Costs, quality, and human resource decisions are often determined by design decisions. Designs usually determine the lower limits of cost and the upper limits of quality.

2. Quality: The customer’s quality expectations must be determined and policies and proce- dures established to identify and achieve that quality.

3. Process and capacity design: Process options are available for products and services. Process decisions commit management to specific technology, quality, human resource use, and maintenance. These expenses and capital commitments determine much of the firm’s basic cost structure.

4. Location selection: Facility location decisions for both manufacturing and service organi- zations may determine the firm’s ultimate success. Errors made at this juncture may over- whelm other efficiencies.

5. Layout design: Material flows, capacity needs, personnel levels, technology decisions, and inventory requirements influence layout.

6. Human resources and job design: People are an integral and expensive part of the total sys- tem design. Therefore, the quality of work life provided, the talent and skills required, and their costs must be determined.

7. Supply chain management: These decisions determine what is to be made and what is to be purchased. Consideration is also given to quality, delivery, and innovation, all at a satisfactory price. Mutual trust between buyer and supplier is necessary for effective purchasing.

8. Inventory: Inventory decisions can be optimized only when customer satisfaction, suppliers, production schedules, and human resource planning are considered.

9. Scheduling: Feasible and efficient schedules of production must be developed; the demands on human resources and facilities must be determined and controlled.

10. Maintenance: Decisions must be made regarding desired levels of reliability and stability, and systems must be established to maintain that reliability and stability.

Operations decisions The strategic decisions of OM are goods and service design, quality, process and capacity design, location selection, layout design, human resources and job design, supply chain management, inventory, scheduling, and maintenance.

10 Operations Decisions Approach Example

Competitive Advantage

Product

Quality

Process

Location

Layout

Human resource

Supply chain

Inventory

Scheduling

Maintenance

Innovative design . . . . . . . . . . . . . . . . . . . . . . . Safeskin’s innovative gloves Broad product line . . . . . . . . . . . . . . . . . . . . .Fidelity Security’s mutual funds After-sales service . . . . . . . . . . . . . . . . Caterpillar’s heavy equipment service Experience . . . . . . . . . . . . . . . . . . . . . . . . . Hard Rock Cafe’s dining experience

COST LEADERSHIP: Low overhead . . . . . . . . . . . . . . . . . . . . . Franz-Colruyt’s warehouse-type stores

Effective capacity use . . . . . . . . . . . . Porter Airlines’s high aircraft utilization Inventory management . . . . . . . . . . Walmart’s sophisticated distribution system

RESPONSE: Flexibility . . . . . . . . . . . . . Hewlett-Packard’s response to volatile world market

Reliability . . . . . . . . . . . . . . . . . . . . . . . FedEx’s “absolutely, positively on time” Quickness . . . . . . . . . . . . . Pizza Hut’s five-minute guarantee at lunchtime

DIFFERENTIATION:

Differentiation (better)

Cost leadership (cheaper)

Response (faster)

FIGURE 2.4 Achieving Competitive Advantage Through Operations

This text is structured around these 10 decisions.

These 10 decisions are used to implement a specific strategy and yield a competitive advantage.

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LO3 Identify and define the 10 decisions of operations management

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Chapter 2 Operations Strategy in a Global Environment 37

Operations managers implement these 10 decisions by identifying key tasks and the staff- ing needed to achieve them. However, the implementation of decisions is influenced by a variety of issues, including a product’s proportion of goods and services (see Table 2.1). Few products are either all goods or all services. Although the 10 decisions remain the same for both goods and services, their relative importance and method of implementation depend on this ratio of goods and services. Throughout this text, we discuss how strategy is selected and implemented for both goods and services through these 10 operations management decisions.

Let’s look at an example of strategy development through one of the 10 decisions.

Table 2.1 The Differences Between Goods and Services Influence How the 10 Operations Management Decisions Are Applied

Operations Decisions Goods Services

Goods and services design Product is usually tangible (a computer). Product is not tangible. A new range of product attributes (a smile).

Quality Many objective quality standards (battery life). Many subjective quality standards (nice colour).

Process and capacity design Customer is not involved in most of the process (auto assembly).

Customer may be directly involved in the process (a haircut).

    Capacity must match demand to avoid lost sales (customers often avoid waiting).

Location selection May need to be near raw materials or labour force (steel plant near ore).

May need to be near customer (car rental).

Layout design Layout can enhance production efficiency (assembly line).

Can enhance product as well as production (layout of a classroom or a fine-dining restaurant).

Human resources and job design

Workforce focused on technical skills (stonemason). Labour standards can be consistent (assembly line employee). Output- based wage system possible (garment sewing).

Direct workforce usually needs to be able to interact well with customer (bank teller); labour standards vary depending on customer requirements (legal cases).

Supply chain management Supply chain relationships critical to final product. Supply chain relationships important but may not be critical.

Inventory Raw materials, work-in-process, and finished goods may be inventoried (beer).

Most services cannot be stored; so other ways must be found to accommodate fluctuations in demand (can’t store haircuts, but even the hair salon has an inventory of supplies).

Scheduling Ability to inventory may allow levelling of production rates (lawn mowers).

Often concerned with meeting the customer’s immediate schedule with human resources.

Maintenance Maintenance is often preventive and takes place at the production site.

Maintenance is often “repair” and takes place at the customer’s site.

The production of both goods and services requires execution of the 10 OM decisions.

1 Pierre Alexander has just completed culinary school and is ready to open his own restaurant. After examining both the external environment and his prospective strengths and weaknesses, he makes a decision on the mission for his restaurant, which he defines as, “To provide outstanding French fine dining for the people of Calgary.”

APPROACH c  Alexander’s supporting operations strategy is to ignore the options of cost leadership and quick response and focus on differentiation. Consequently, his operations strategy requires him to evaluate product designs (menus and meals) and selection of process, layout, and location. He must also evaluate the human resources, suppliers, inventory, scheduling, and maintenance that will support his mission as well as a differentiation strategy.

EXAMPLE

Strategy Development

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38 PART 1 Introduction to Operations Management

SOLUTION c   Examining just one of these 10 decisions, process design, requires that Alexander consider the issues presented in the following figure.

Notice how the 10 decisions are altered to build two distinct strategies in the same industry.

The first option is to operate in the lower right corner of the figure above, where he could produce high volumes of food with a limited variety, much as in an institutional kitchen. Such a process could produce large volumes of standard items such as baked goods and mashed potatoes prepared with state-of-the-art automated equipment. Alexander concludes that this is not an acceptable process option.

Alternatively, he can move to the middle of the figure, where he could produce more variety and lower volumes. Here, he would have less automation and use prepared modular components for meals, much as a fast-food restaurant does. Again, he deems such process designs inappropriate for his mission.

Another option is to move to the upper right corner and produce a high volume of customized meals, but neither Alexander nor anyone else knows how to do this with gourmet meals.

Finally, Alexander can design a process that operates in the upper left corner of the figure, which requires little automation but lends itself to high variety. This process option suggests that he build an extremely flexible kitchen suitable for a wide variety of custom meals catering to the whims of each customer. With little automation, such a process would be suitable for a huge variety. This process strategy will support his mission and desired product differentiation. Only with a process such as this can he provide the fine French-style gourmet dining that he has in mind.

INSIGHT c  By considering the options inherent in each of the 10 OM decisions, managers— Alexander, in this case—can make decisions that support the mission.

LEARNING EXERCISE c If Alexander’s mission were to offer less expensive meals and reduce the variety offered but still do so with a French flair, what might his process strategy be? [Answer: Alexander might try a repetitive (modular) strategy and mimic the La Madeleine cafeteria-style restau- rants. The La Madeleine chain has more than 60 locations and would be a good model for Alexander to mirror. It has the approach, atmosphere, style, and menu he is seeking.]

The 10 decisions of operations management are implemented in ways that provide competi- tive advantage, not just for fine-dining restaurants, but for all the goods and services that enrich our lives. How this might be done for two drug companies—one seeking a competitive advan- tage via differentiation, and the other via low cost—is shown in Table 2.2.

STUDENT TIP

V a ri

e ty

o f

p ro

d u

c ts

Moderate

Moderate

Volume

Low

Low

High

High

(Print shop, emergency room, machine shop,

fine-dining restaurant)

JOB SHOPS

Process Focused

(Cars, appliances, TVs, fast-food restaurants)

ASSEMBLY LINE

Repetitive (Modular) Focus

(Steel, beer, paper, bread, institutional kitchen)

CONTINUOUS

Product Focused

CUSTOMIZATION AT HIGH VOLUME

(Dell Computer’s PC, cafeteria)

Mass Customization

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Chapter 2 Operations Strategy in a Global Environment 39

Issues in Operations Strategy Whether the OM strategy is differentiation, cost, or response (as shown earlier in Figure 2.4), OM is a critical player. Therefore, prior to establishing and attempting to implement a strategy, some alternative perspectives may be helpful. One perspective is to take a resources view. This means thinking in terms of the financial, physical, human, and technological resources available and ensuring that the potential strategy is compatible with those resources. Another perspective is Porter’s value chain analysis.2 Value chain analysis is used to identify activities that represent strengths, or potential strengths, and may be opportunities for developing competitive advan- tage. These are areas where the firm adds its unique value through product research, design, human resources, supply chain management, process innovation, or quality management. Porter also suggests analysis of competitors via what he calls his five forces model.3 These potential competing forces are immediate rivals, potential entrants, customers, suppliers, and substitute products.

In addition to the competitive environment, the operations manager needs to understand that the firm is operating in a system with many other external factors. These factors range from political, to legal, to cultural. They influence strategy development and execution and require constant scanning of the environment.

The firm itself is also undergoing constant change. Everything from resources, to technology, to product life cycles is in flux. Consider the significant changes required within the firm as its products move from introduction, to growth, to maturity, and to decline (see Figure 2.5). These internal changes, combined with external changes, require strategies that are dynamic.

In this chapter’s Global Company Profile, Boeing provides an example of how strategy must change as technology and the environment change. Boeing can now build planes from carbon fibre, using a global supply chain. Like many other OM strategies, Boeing’s strategy has changed with technology and globalization. Microsoft has also had to adapt quickly to a changing

Resources view A method managers use to evalu- ate the resources at their disposal and manage or alter them to achieve competitive advantage.

Value chain analysis A way to identify those elements in the product/service chain that uniquely add value.

Five forces model A method of analyzing the five forces in the competitive environment.

Table 2.2 Operations Strategies of Two Drug Companies

  Brand Name Drugs, Inc. Generic Drug Corp.

Competitive Advantage Product Differentiation Low Cost

Product Selection and Design

Heavy R&D investment; extensive labs; focus on development in a broad range of drug categories

Low R&D investment; focus on development of generic drugs

Quality Quality is major priority; standards exceed regulatory requirements

Meets regulatory requirements on a country-by-country basis, as necessary

Process Product and modular production process; tries to have long product runs in specialized facilities; builds capacity ahead of demand

Process focused; general production processes; “job shop” approach, short-run production; focus on high utilization

Location Still located in city where it was founded Recently moved to low-tax, low-labour-cost environment

Layout Layout supports automated product-focused production

Layout supports process-focused “job shop” practices

Human Resources Hire the best; nationwide searches Very experienced top executives provide direction; other personnel paid below industry average

Supply Chain Long-term supplier relationships Tends to purchase competitively to find bargains

Inventory Maintains high finished goods inventory primarily to ensure all demands are met

Process focus drives up work-in-process inventory; finished goods inventory tends to be low

Scheduling Centralized production planning Many short-run products complicate scheduling

Maintenance Highly trained staff; extensive parts inventory Highly trained staff to meet changing demands

An effective strategy finds the optimum fit for the firm’s resources in the dynamic environment.

2 M. E. Porter, Competitive Advantage: Creating and Sustaining Superior Performance. New York, NY: The Free Press, 1985. 3 Michael E. Porter, Competitive Strategy: Techniques for Analyzing Industries and Competitors. New York, NY: The Free Press, 1980, 1998.

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40 PART 1 Introduction to Operations Management

environment. Faster processors, new computer languages, changing customer preferences, increased security issues, the internet, the cloud, and Google have all driven changes at Microsoft. These forces have moved Microsoft’s product strategy from operating systems to office products, to internet service provider, and now to integrator of computers, cell phones, games, and television via the cloud.

The more thorough the analysis and understanding of both the external and internal factors, the more likely that a firm can find the optimum use of its resources. Once a firm understands itself and the environment, a SWOT analysis, which we discuss next, is in order.

Strategy Development and Implementation A SWOT analysis is a formal review of the internal strengths and weaknesses and the external opportunities and threats. Beginning with SWOT analyses, organizations position themselves, through their strategy, to have a competitive advantage. A firm may have excellent design skills or great talent at identifying outstanding locations. However, it may recognize limitations of its manufacturing process or in finding good suppliers. The idea is to maximize opportunities and minimize threats in the environment while maximizing the advantages of the organiza- tion’s strengths and minimizing the weaknesses. Any preconceived ideas about mission are then re-evaluated to ensure they are consistent with the SWOT analysis. Subsequently, a strategy for achieving the mission is developed. This strategy is continually evaluated against the value provided to customers and competitive realities. The process is shown in Figure 2.6. From this process, key success factors are identified.

SWOT analysis A method of determining internal strengths and weaknesses and external opportunities and threats.

Product design and development critical

Frequent product and process design changes

Short production runs High production costs

Limited models

Attention to quality

Practical to change price or quality image

Strengthen niche

Poor time to change image, price, or quality

Competitive costs become critical

Defend market position

Cost control critical

Forecasting critical

Product and process reliability

Competitive product improvements and options

Increase capacity

Shift towards product focus

Enhance distribution

Standardization

Fewer rapid product changes, more minor changes

Optimum capacity

Increasing stability of process

Long production runs

Product improvement and cost cutting

Little product differentiation

Cost minimization

Overcapacity in the industry

Prune line to eliminate items not returning good margin

Reduce capacity

Best period to increase market share

R&D engineering is critical

Introduction Growth DeclineMaturity

O M

S tr

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g y / I s s u

e s

C o

m p

a n

y S

tr a te

g y / I s s u

e s

Sales

Drive-through restaurantsInternet search engines

Analog TVs

CD-ROMs

Avatars

Boeing 787

Twitter

LCD & plasma TVs iPods

Xbox 360

FIGURE 2.5 Strategy and Issues During a Product’s Life

A SWOT analysis provides an excellent model for evaluating a strategy.

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Chapter 2 Operations Strategy in a Global Environment 41

KEY SUCCESS FACTORS AND CORE COMPETENCIES Because no firm does everything exceptionally well, a successful strategy requires determin- ing the firm’s critical success factors and core competencies. Key success factors (KSFs) are those activities that are necessary for a firm to achieve its goals. Key success factors can be so significant that a firm must get them right to survive in the industry. A KSF for McDonald’s, for example, is layout. Without a play area, an effective drive-through, and an efficient kitchen, McDonald’s cannot be successful. KSFs are often necessary, but not sufficient for competitive advantage. On the other hand, core competencies are the set of unique skills, talents, and capa- bilities that a firm does at a world-class standard. They allow a firm to set itself apart and develop a competitive advantage. Organizations that prosper identify their core competencies and nurture them. While McDonald’s KSFs may include layout, its core competency may be consistency and quality. Honda Motors’s core competency is gas-powered engines—engines for automobiles, motorcycles, lawn mowers, generators, snow blowers, and more. The idea is to build KSFs and core competencies that provide a competitive advantage and support a successful strategy and mission. A core competency may be a subset of KSFs or a combination of KSFs. The operations manager begins this inquiry by asking:

• “What tasks must be done particularly well for a given strategy to succeed?” • “Which activities will help the OM function provide a competitive advantage?” • “Which elements contain the highest likelihood of failure, and which require additional com-

mitment of managerial, monetary, technological, and human resources?”

Only by identifying and strengthening key success factors and core competencies can an organization achieve sustainable competitive advantage.

In this text-book, we focus on the 10 OM decisions that typically include the KSFs. Potential KSFs for marketing, finance, and operations are shown in Figure 2.7. The 10 OM decisions we develop in this text provide an excellent initial checklist for determining KSFs and identifying core com- petencies within the operations function. For instance, the 10 decisions, related KSFs, and core

LO4 Understand the significance of key success factors and core competencies

Key success factors (KSFs) Activities or factors that are key to achieving competitive advantage.

Core competencies A set of skills, talents, and activities in which a firm is particularly strong.

Analyze the Environment

Determine the Corporate Mission

State the reason for the firm’s existence, and identify the value it wishes to create.

Form a Strategy

Build a competitive advantage, such as low price, design or volume flexibility, quality, quick delivery, dependability, after-sale services, or broad product lines.

Identify the strengths, weaknesses, opportunities, and threats. Understand the environment, customers, industry, and competitors.

FIGURE 2.6

Strategy Development Process

Honda’s core competency is the design and manufacture of gas-powered engines. This competency has allowed Honda to become a leader in the design and manufacture of a wide range of gas-powered products. Tens of millions of these products are shipped around the world.

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42 PART 1 Introduction to Operations Management

competencies can allow a firm to differentiate its product or service. That differentiation may be via a core competency of innovation and new products, where the KSFs are product design and speed to market, as is the case for 3M and Rubbermaid. Similarly, differentiation may be via quality, where the core competency is institutionalizing quality, as at Toyota. Differentiation may also be via mainte- nance, where the KSFs are product reliability and after-sale service, as is the case at IBM and Canon.

Whatever the KSFs and core competencies, they must be supported by the related activities. One approach to identifying the activities is an activity map, which links competitive advantage, KSFs, and supporting activities. For example, Figure 2.8 shows how Porter Airlines, whose core compe- tency is operations, built a set of integrated activities to support its low-cost competitive advantage. Notice how the KSFs support operations and in turn are supported by other activities. The activities fit together and reinforce each other. And the better they fit and reinforce each other, the more sus- tainable the competitive advantage. By focusing on enhancing its core competency and KSFs with a supporting set of activities, Porter Airlines has become one of the great airline success stories.

BUILD AND STAFF THE ORGANIZATION The operations manager’s job is a three-step process. Once a strategy and key success factors have been identified, the second step is to group the necessary activities into an organizational structure. The third step is to staff it with personnel who will get the job done. The manager works with subordinate managers to build plans, budgets, and programs that will successfully implement strategies that achieve missions. Firms tackle this organization of the operations function in a variety of ways. The organization charts shown in Chapter 1 (Figure 1.1) indicate the way some firms have organized to perform the required activities.

INTEGRATE OM WITH OTHER ACTIVITIES The organization of the operations function and its relationship to other parts of the organiza- tion vary with the OM mission. Moreover, the operations function is most likely to be success- ful when the operations strategy is integrated with other functional areas of the firm, such as marketing, finance, information technology, and human resources. In this way, all of the areas support the company’s objectives. For example, short-term scheduling in the airline industry is dominated by volatile customer travel patterns. Day-of-week preference, holidays, seasonality, school schedules, and so on all play a role in changing flight schedules. Consequently, airline

Activity map A graphical link of competitive advantage, KSFs, and supporting activities.

Service Distribution Promotion Price Channels of distribution Product positioning (image, functions)

Leverage Cost of capital Working capital Receivables Payables Financial control Lines of credit

Product Quality

Process Location Layout Human resource Supply chain Inventory Schedule Maintenance

Marketing Finance/Accounting Operations

Decisions Sample Options Chapter

Customized or standardized Define customer expectations and how to achieve them Facility design, capacity Near supplier or near customer Work cells or assembly line Specialized or enriched jobs Single or multiple suppliers When to reorder; how much to keep on hand Stable or fluctuating production rate Repair as required or preventive maintenance

5 6,S6

7,S7 8 9 10

11, S11 12,14,16

13,15 17

Support a Core Competency and Implement Strategy by Identifying and Executing the Key Success Factors in the Functional Areas

FIGURE 2.7

Implement Strategy by Identifying and Executing Key Success Factors That Support Core Competencies

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Chapter 2 Operations Strategy in a Global Environment 43

scheduling, although an OM activity, can be a part of marketing. Effective scheduling in the trucking industry is reflected in the amount of time trucks travel loaded. However, scheduling of trucks requires information from delivery and pickup points, drivers, and other parts of the organization. When the OM function results in effective scheduling in the air passenger and commercial trucking industries, a competitive advantage can exist.

The operations manager transforms inputs into outputs. The transformations may be in terms of storage, transportation, manufacturing, dissemination of information, and utility of the prod- uct or service. The operations manager’s job is to implement an OM strategy, provide competi- tive advantage, and increase productivity.

Strategic Planning, Core Competencies, and Outsourcing As organizations develop missions, goals, and strategies, they identify their strengths—what they do as well as or better than their competitors—as their core competencies. By contrast, noncore activities, which can be a sizable portion of an organization’s total business, are good candidates for outsourcing. Outsourcing is transferring activities that have traditionally been internal to external suppliers.

Outsourcing is not a new concept, but it does add complexity and risk to the supply chain. Because of its potential, outsourcing continues to expand. The expansion is accelerating due to three global trends: (1) increased technological expertise, (2) more reliable and cheaper transporta- tion, and (3) the rapid development and deployment of advancements in telecommunications and computers. This rich combination of economic advances is contributing to both lower cost and more specialization. As a result more firms are candidates for outsourcing of noncore activities.

Outsourcing implies an agreement (typically a legally binding contract) with an external organization. The classic make-or-buy decision, concerning which products to make and which to buy, is the basis of outsourcing. When firms such as Apple find that their core competency is in creativity, innovation, and product design, they may want to outsource manufacturing.

Outsourcing manufacturing is an extension of the long-standing practice of subcontracting produc- tion activities, which when done on a continuing basis is known as contract manufacturing. Contract manufacturing is becoming standard practice in many industries, from computers to automobiles. For instance, Johnson & Johnson, like many other big drug companies whose core competency is research and development, often farms out manufacturing to contractors. On the other hand, Sony’s core competency is electromechanical design of chips. This is its core competency, but Sony is also one of the best in the world when it comes to rapid response and specialized production of these

Outsourcing Transferring a firm’s activities that have traditionally been internal to external suppliers.

Lean, Productive Staffing Policy

Standardized Fleet of Bombardier Q400

Short-haul Flights

Frequent, Reliable Schedules

High Aircraft Utilization

Reduced Costs (e.g., wages,

maintenance, etc.)

Flexible, Adaptable, Adjustable

Maximization of Revenue

FIGURE 2.8

Activity Mapping of Porter Airlines’s Low-Cost Competitive Advantage To achieve a low-cost compet- itive advantage, Porter Airlines addresses a number of key success factors. As the figure illustrates, a low-cost advantage is highly dependent on a very well-run operations function.

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44 PART 1 Introduction to Operations Management

chips. Therefore, Sony finds that it wants to be its own manufacturer, while specialized providers come up with major innovations in such areas as software, human resources, and distribution. These areas are the providers’ business, not Sony’s, and the provider may very well be better at it than Sony.

Other examples of outsourcing noncore activities include:

• DuPont’s legal services routed to the Philippines • IBM’s handing of travel services and payroll and Hewlett-Packard’s provision of IT services

to P&G • Production of the Audi A4 convertible and Mercedes CLK convertible by Wilhelm Karmann

in Osnabruck, Germany • Blue Cross sending hip resurfacing surgery patients to India

Managers evaluate their strategies and core competencies and ask themselves how to use the assets entrusted to them. Do they want to be the company that does low-margin work at 3%–4% or the inno- vative firm that makes a 30%–40% margin? PC and iPad contract manufacturers in China and Taiwan earn 3%–4%, but Apple, which innovates, designs, and sells, has a margin 10 times as large.

THE THEORY OF COMPARATIVE ADVANTAGE The motivation for international outsourcing comes from the theory of comparative advantage.  This theory focuses on the economic concept of relative advantage. According to the theory, if an external provider, regardless of its geographic location, can perform activities more productively than the purchasing firm, then the external provider should do the work. This allows the purchasing firm to focus on what it does best—its core competencies. Consistent with the theory of comparative advantage, outsourcing continues to grow. But outsourcing the wrong activities can be a disaster. And even outsourcing noncore activities has risks.

RISKS OF OUTSOURCING Risk management starts with a realistic analysis of uncertainty and results in a strategy that minimizes the impact of these uncertainties. Indeed, outsourcing is risky, with roughly half of all outsourcing agreements failing because of inadequate planning and analysis. Timely deliv- ery and quality standards can be major problems, as can underestimating increases in inventory and logistics costs. Some potential advantages and disadvantages of outsourcing are shown in Table 2.3. A survey of North American companies found that, as a group, those that outsourced customer service saw a drop in their score on the American Consumer Satisfaction Index. The declines were roughly the same whether companies outsourced domestically or overseas.4

Theory of comparative advantage A theory which states that countries benefit from specializing in (and export- ing) goods and services in which they have relative advantage, and they benefit from importing goods and services in which they have a relative disadvantage.

Contract manufacturers such as Flextronics provide outsourcing service to IBM, Cisco Systems, HP, Microsoft, Sony, Nortel, Ericsson, and Sun, among many others. Flextronics is a high- quality producer that has won over 450 awards, including the Malcolm Baldrige Award. One of the side benefits of outsourcing is that client firms such as IBM can actually improve their performance by using the competencies of an outstanding firm like Flextronics. But there are risks involved in outsourcing.Ke

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STUDENT TIP

4 J. Whitaker, M. S. Krishnan, and C. Fornell. “How Offshore Outsourcing Affects Customer Satisfaction.” The Wall Street Journal (July 7, 2008): R4.

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Chapter 2 Operations Strategy in a Global Environment 45

However, when outsourcing is overseas, additional issues must be considered. These issues  include financial attractiveness, people skills and availability, and the general business environment. Another risk of outsourcing overseas is the political backlash that results from mov- ing jobs to foreign countries. The perceived loss of jobs has fuelled anti-outsourcing rhetoric. This rhetoric is contributing to a process known as reshoring, the return of business activity to the orig- inating country. (See the OM in Action box “Reshoring to Smaller Towns in North America ”.)

In addition to the external risks, operations managers must deal with other issues that out- sourcing brings. These include: (1) reduced employment levels, (2) changes in facility require- ments, (3) potential adjustments to quality control systems and manufacturing processes, and (4) expanded logistics issues, including insurance, tariffs, customs, and timing.

To summarize, managers can find substantial efficiencies in outsourcing noncore activities, but they must be cautious in outsourcing those elements of the product or service that provide a competitive advantage. The next section provides a methodology that helps analyze the out- sourcing decision process.

RATING OUTSOURCE PROVIDERS Research indicates that the most common reason for the failure of outsourcing agreements is that the decisions are made without sufficient analysis. The factor rating method provides an objective way to evaluate outsource providers. We assign points for each factor to each provider and then importance weights to each of the factors. We now apply the technique in Example 2 to compare outsourcing providers being considered by a firm.

Table 2.3 Potential Advantages and Disadvantages of Outsourcing

Advantages Disadvantages

Cost savings Increased logistics and inventory costs

Gaining outside expertise that comes with specialization Loss of control (quality, delivery, etc.)

Improving operations and service Potential creation of future competition

Maintaining a focus on core competencies Negative impact on employees

Accessing outside technology Risks may not manifest themselves for years

North American companies continue their global search for efficiency by outsourcing call centres and back- office operations, but many find they need to look no farther than a place like Dubuque, Iowa.

To North American firms facing quality problems with their outsourcing operations overseas and bad publicity at home, small-town America is emerging as a pleasant alternative. Dubuque (population 57,313), Nacogdoches, Texas (population 29,914), or Twin Falls, Idaho (popu- lation 34,469), may be the perfect call centre location. Even though the pay is low, the jobs are some of the best available to small-town residents.

By moving out of big cities to the cheaper labour and real estate of small towns, companies can save millions and still increase productivity. A call centre in a town that just lost its major manufacturing plant finds the jobs easy to fill.

IBM, which has been criticized in the past for moving jobs to India and other offshore locations, picked Dubuque for its new remote computer-services centre with 1300 jobs.

Taking advantage of even cheaper wages in other countries will not stop soon, though. Is India the unstoppable

overseas call centre capital that people think it is? Not at all. Despite its popu- lation of 1.3 billion, only a small percent- age of its workers have the language skills and technical education to work in Western-style indus- tries. Already, India has been warned that if call centres can’t recruit at reasonable wages, its jobs will move to the Philippines, South Africa, and Ghana. And indeed, Dell, Apple, and Britain’s Powergen are reshoring from Indian call centres, claiming their costs had become too high.

Sources: Industry Week (August 5, 2014) and The Wall Street Journal, (November 27, 2013).

Reshoring to Smaller Towns in North AmericaOM in Action

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46 PART 1 Introduction to Operations Management

Most North American toy companies now outsource their production to Chinese manufacturers. Cost savings are significant, but there are several downsides, including loss of control over such issues as quality. A few years ago, Mattel had to recall 10.5 million Elmos, Big Birds, and SpongeBobs. These made-in-China toys contained excessive levels of lead in their paint. More recently, quality issues have dealt with poisonous pet food, tainted milk products, and contaminated sheetrock. A.

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National Architects, Inc., a Vancouver-based designer of high-rise office buildings, has decided to outsource its information technology (IT) function. Three outsourcing providers are being actively considered: one in Canada, one in India, and one in Israel.

APPROACH c    National’s VP–Operations, Susan Cholette, has made a list of seven criteria she considers critical. After putting together a committee of four other VPs, she has rated each firm (boldface type, on a 1–5 scale, with 5 being highest) and has also placed an importance weight on each of the factors, as shown in Table 2.4.

2EXAMPLE

Rating Provider Selection Criteria

Table 2.4 Factor Ratings Applied to National Architects’s Potential IT Outsourcing Providers

FACTOR (CRITERION)* IMPORTANCE

WEIGHT

OUTSOURCE PROVIDERS

BIM (CANADA) S.P.C. (INDIA)

TELCO (ISRAEL)

1. Can reduce operating costs

.2 .2 × 3 = .6 .2 × 3 = .6 .2 × 5 = 1.0

2. Can reduce capital investment

.2 .2 × 4 = .8 .2 × 3 = .6 .2 × 3 = .6

3. Skilled personnel .2 .2 × 5 = 1.0 .2 × 4 = 8 .2 × 3 = .6

4. Can improve quality .1 .1 × 4 = .4 .1 × 5 = .5 .1 × 2 = .2

5. Can gain access to tech- nology not in company

.1 .1 × 5 = .5 .1 × 3 = .3 .1 × 5 = .5

6. Can create additional capacity

.1 .1 × 4 = .4 .1 × 2 = .2 .1 × 4 = .4

7. Aligns with policy/ philosophy/culture

.1 .1 × 2 = .2 .1 × 3 = .3 .1 × 5 = .5

Total Weighted Score 3.9 3.3 3.8

*These seven major criteria are based on a survey of 165 procurement executives, as reported in J. Schildhouse, Inside Supply Management (December 2005): 22–29.

SOLUTION c  Susan multiplies each rating by the weight and sums the products in each column to generate a total score for each outsourcing provider. She selects BIM, which has the highest overall rating.

INSIGHT c When the total scores are as close (3.9 vs. 3.8) as they are in this case, it is important to ex- amine the sensitivity of the results to inputs. For example, if one of the importance weights or factor scores changes even marginally, the final selection may change. Management preference may also play a role here.

LEARNING EXERCISE c  Susan decides that “Skilled personnel” should instead get a weight of 0.1 and “Aligns with policy/philosophy/culture” should increase to 0.2. How do the total scores change? [Answer: BIM = 3.6, S.P.C. = 3.2, and Telco = 4.0, so Telco would be selected.]

RELATED PROBLEMS c 2.8–2.12

EXCEL OM Data File Ch02Ex2.xlsx can be found in MyLab Operations Management.

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Chapter 2 Operations Strategy in a Global Environment 47

Global Operations Strategy Options As we suggested earlier in this chapter, many operations strategies now require an international dimension. We tend to call a firm with an international dimension an international business or a multinational corporation. An international business is any firm that engages in international trade or investment. This is a broad category and is the opposite of a domestic, or local, firm.

A multinational corporation (MNC) is a firm with extensive international business involve- ment. MNCs buy resources, create goods or services, and sell goods or services in a variety of countries. The term multinational corporation applies to most of the world’s large, well-known businesses. Bombardier is a good example of an MNC. It has a presence in 60 countries world- wide, including 76 production and engineering sites. Bombardier acquires parts and raw materi- als from around the world, and ships its finished products (including planes, trains, and buses) to its customers wherever they may be.

Operations managers of international and multinational firms approach global opportunities with one of four operations strategies: international, multidomestic, global, or transnational (see Figure 2.9). The matrix of Figure 2.9 has a vertical axis of cost reduction and a horizontal axis of local responsiveness. Local responsiveness implies quick response and/or the differentia- tion necessary for the local market. The operations manager must know how to position the firm in this matrix. Let us briefly examine each of the four strategies.

INTERNATIONAL STRATEGY An international strategy uses exports and licences to penetrate the global arena. As Figure 2.9 suggests, the international strategy is the least advantageous, with little local responsiveness and little cost advantage. There is little responsiveness because we are exporting or licensing goods from the home country. And the cost advantages may be few because we are using the existing production process at some distance from the new market. However, an international strategy is

International business A firm that engages in cross-border transactions.

Multinational corporation (MNC) A firm that has extensive involvement in international business, owning or controlling facilities in more than one country.

LO5 Identify and explain four global operations strategy options

International strategy A strategy in which global markets are penetrated using exports and licences.

Firms that ignore the global economy will not survive.

STUDENT TIP

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HighLow

High

Local Responsiveness (Quick Response and/or Differentiation)

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• Use existing domestic model globally • Franchise, joint ventures, subsidiaries

Examples: Heinz McDonald’s The Body Shop Hard Rock Cafe

Multidomestic strategy

• Import/export or license existing product

Examples: U.S. Steel Harley-Davidson

International strategy

Global strategy

• Standardized product • Economies of scale • Cross-cultural learning

Examples: Texas Instruments Caterpillar Otis Elevator

Transnational strategy

Movement of material, people, or ideas across national boundaries Economies of scale Cross-cultural learning

Examples: Coca-Cola Nestlé

•

• •

FIGURE 2.9

Four International Operations Strategies

Source: Based on M. Hitt, R. D. Ireland, and R. E. Hoskisson, Strategic Management, Competitiveness and Globalization, 7th ed. (Cincinnati: Southwestern College Publishing, 2009).

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48 PART 1 Introduction to Operations Management

often the easiest, as exports can require little change in existing operations, and licensing agree- ments often leave much of the risk to the licensee.

MULTIDOMESTIC STRATEGY The multidomestic strategy has decentralized authority with substantial autonomy at each business. Organizationally, these are typically subsidiaries, franchises, or joint ventures with substantial independence. The advantage of this strategy is maximizing a competitive response for the local market; however, the strategy has little or no cost advantage. Many food produc- ers, such as Heinz, use a multidomestic strategy to accommodate local tastes because global integration of the production process is not critical. The concept is one of “We were success- ful in the home market; let’s export the management talent and processes, not necessarily the product, to accommodate another market.” McDonald’s is operating primarily as a multido- mestic, which gives it the local responsiveness needed to modify its menu country by coun- try. McDonald’s can then serve beer in Germany, wine in France, McHuevo (poached egg hamburger) in Uruguay, and hamburgers without beef in India. With over 2000 restaurants in Japan and a presence for more than a generation, McDonald’s is thought to have been invented in Japan, according to the average Japanese family. Interestingly, McDonald’s prefers to call itself multilocal.5

GLOBAL STRATEGY A global strategy has a high degree of centralization, with headquarters coordinating the organ- ization to seek out standardization and learning between plants, thus generating economies of scale. This strategy is appropriate when the strategic focus is cost reduction but has little to recommend it when the demand for local responsiveness is high. Caterpillar, the world leader in earth moving equipment, and Texas Instruments, a world leader in semiconductors, pursue global strategies. Caterpillar and Texas Instruments find this strategy advantageous because the end products are similar throughout the world. Earth moving equipment is the same in Nigeria as in Prince Edward Island, which allows Caterpillar to have individual factories focus on a limited line of products to be shipped worldwide. This results in economies of scale and learn- ing within each facility. A global strategy also allows Texas Instruments to build optimum-size plants with similar processes and to then maximize learning by aggressive communication between plants. The result is an effective cost reduction advantage for Texas Instruments.

TRANSNATIONAL STRATEGY A transnational strategy exploits the economies of scale and learning, as well as pressure for responsiveness, by recognizing that core competence does not reside in just the “home” country but can exist anywhere in the organization. Transnational describes a condition in which material, people, and ideas cross—or transgress—national boundaries. These firms have the potential to pursue all three operations strategies (i.e., differentiation, low cost, and response). Such firms can be thought of as “world companies” whose country identity is not as important as its interde- pendent network of worldwide operations. Key activities in a transnational company are neither centralized in the parent company nor decentralized so that each subsidiary can carry out its own tasks on a local basis. Instead, the resources and activities are dispersed, but specialized, so as to be both efficient and flexible in an interdependent network. Nestlé is a good example of such a com- pany. Although it is legally Swiss, 95% of its assets are held and 98% of its sales are made out- side Switzerland. Fewer than 10% of its workers are Swiss. Similarly, service firms such as Asea Brown Boveri (an engineering firm that is Swedish but headquartered in Switzerland), Reuters (a news agency), Bertelsmann (a publisher), and Citicorp (a banking corporation) can be viewed as transnationals. We can expect the national identities of these transnationals to continue to fade.

Multidomestic strategy A strategy in which operating decisions are decentralized to each country to enhance local responsiveness.

Global strategy A strategy in which operating decisions are centralized and headquarters coordinates the standardization and learning between facilities.

Transnational strategy A strategy that combines the benefits of global-scale efficien- cies with the benefits of local responsiveness.

5 James L. Watson, ed., Golden Arches East: McDonald’s in East Asia (Stanford University Press, 1997): 12. Note: McDonald’s also operates with some of the advantages of a global organization. By using very similar product lines throughout the world, McDonald’s obtains some of the standardization advantages of a global strategy. However, it manages to retain the advantages of a multidomestic strategy.

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Chapter 2 Operations Strategy in a Global Environment 49

In a continuing fierce worldwide battle, both Komatsu and Caterpillar seek global advantage in the heavy equipment market. As Komatsu (left) moved west to the United Kingdom, Caterpillar (right) moved east, with 13 facilities and joint ventures in China. Both firms are building equipment throughout the world as cost and logistics dictate. Their global strategies allow production to move as markets, risk, and exchange rates dictate.

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Global operations provide an increase in both the chal- lenges and opportunities for operations managers. Although the task is challenging, operations managers can and do improve productivity. They can build and manage OM functions that contribute in a significant way to competi- tiveness. Organizations identify their strengths and weak- nesses. They then develop effective missions and strategies that account for these strengths and weaknesses and com- plement the opportunities and threats in the environment. If this procedure is performed well, the organization can

have competitive advantage through some combination of product differentiation, low cost, and response. This com- petitive advantage is often achieved via a move to inter- national, multidomestic, global, or transnational strategies.

Effective use of resources, whether domestic or interna- tional, is the responsibility of the professional manager, and professional managers are among the few in our society who can achieve this performance. The challenge is great, and the rewards to the manager and to society substantial.

CHAPTER SUMMARY

As a manufacturer of athletic shoes whose image, indeed perfor- mance, is widely regarded as socially responsible, you find your costs increasing. Traditionally, your athletic shoes have been made in Indonesia and South Korea. Although the ease of doing business in those countries has been improving, wage rates have also been increasing. The labour-cost differential between your present sup- pliers and a contractor who will get the shoes made in China now exceeds $1 per pair. Your sales next year are projected to be 10 mil- lion pairs, and your analysis suggests that this cost differential is not

offset by any other tangible costs; you face only the political risk and potential damage to your commitment to social responsibility. Thus, this $1 per pair savings should flow directly to your bottom line. There is no doubt that the Chinese government engages in cen- sorship, remains repressive, and is a long way from a democracy. Moreover, you will have little or no control over working conditions, sexual harassment, and pollution. What do you do, and on what basis do you make your decision?

ETHICAL DILEMMA

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50 PART 1 Introduction to Operations Management

Discussion Questions

1. Based on the descriptions and analyses in this chapter, would Boeing be better described as a global firm or a transnational firm? Discuss.

2. List six reasons to internationalize operations. 3. Coca-Cola is called a global product. Does this mean that it is

formulated in the same way throughout the world? Discuss. 4. Define mission. 5. Define strategy. 6. Describe how an organization’s mission and strategy have dif-

ferent purposes. 7. Identify the mission and strategy of your automobile repair

garage. What are the manifestations of the 10 OM decisions at the garage? That is, how is each of the 10 decisions accomplished?

8. As a library or internet assignment, identify the mission of a firm and the strategy that supports that mission.

9. How does an OM strategy change during a product’s life cycle?

10. There are three primary ways to achieve competitive advan- tage. Provide an example, not included in the text, of each. Support your choices.

11. Given the discussion of Porter Airlines in the text, define an operations strategy for that firm.

12. How must an operations strategy integrate with marketing and accounting?

13. How would you summarize outsourcing trends? 14. What potential cost-saving advantages might firms experience

by using outsourcing? 15. What internal issues must managers address when outsourcing? 16. How should a company select an outsourcing provider? 17. What are some of the possible consequences of poor outsourcing? 18. What global operations strategy is most descriptive of

McDonald’s?

. SOLVED PROBLEM 2.1 The global tire industry continues to consolidate. Michelin buys Goodrich and Uniroyal and builds plants throughout the world. Bridgestone buys Firestone, expands its research budget, and focuses on world markets. Goodyear spends almost 4% of its sales revenue on research. These three aggressive firms have come to dominate the world tire market, with total market share approaching 60%. And the German tire maker Continental AG has strengthened its position as fourth in the world, with a dominant presence in Germany. Against this formidable array, the old-line Italian tire company Pirelli SpA found it difficult to respond effectively. Although Pirelli still had 5% of the market, it was losing millions of dollars per year while the competi- tion was getting stronger. Tires are a tough, competitive business that rewards companies having strong market shares and long production runs. Pirelli has some strengths: an outstanding reputation for excel- lent high-performance tires and an innovative manufacturing function.

Use a SWOT analysis to establish a feasible strategy for Pirelli.

. SOLUTION First, find an opportunity in the world tire market that avoids the threat of the mass-market onslaught by the big three tire makers. Second, utilize the internal marketing strength represented by Pirelli’s strong brand name and history of winning World Rally Championships. Third, maximize the internal innovative capabili- ties of the operations function.

Solved Problems Virtual Office Hours help is available at MyLab Operations Management.

To achieve these goals, Pirelli made a strategic shift out of low-margin standard tires and into higher-margin performance tires. Pirelli established deals with luxury brands Jaguar, BMW, Maserati, Ferrari, Bentley, and Lotus Elise and established itself as a provider of a large share of tires on new Porsches, S-class Mercedes, and Saabs. As a result, more than 70% of the company’s tire production is now high-performance tires. People are willing to pay a premium for Pirellis.

The operations function continued to focus its design efforts on performance tires and developing a system of modular tire man- ufacture that allows much faster switching between models. This modular system, combined with investments in new manufacturing flexibility, has driven batch sizes down to as small as 150 to 200, making small-lot performance tires economically feasible. Manufacturing innovations at Pirelli have streamlined the produc- tion process, moving it from a 14-step process to a three-step pro- cess. A threat from the Big Three going after the performance market remains, but Pirelli has bypassed its weakness of having a small mar- ket share. The firm now has 24 plants in 12 countries and a presence in more than 160 countries, with sales exceeding $4.5 billion.

Sources: Just Auto (February 2009): 14–15 and (December 2008): 14–15; Hoover’s Company Records (October 15, 2005): 41369; and www.pirelli .com/corporate/en/investors/pirelli_at_glance/default.html.

Using Software to Solve Outsourcing Problems Excel, Excel OM, and POM for Windows may be used to solve many of the problems in this chapter.

CREATING YOUR OWN EXCEL SPREADSHEETS Program 2.1 illustrates how to build an Excel spreadsheet for the data in Example 2. In this example the factor rating method is used to compare National Architects’s three potential out- sourcing providers.

This program provides the data inputs for seven important factors, including their weights (0.0–1.0) and ratings (1–5 scale where 5 is the highest rating) for each country. As we

see, BIM is most highly rated, with a 3.9 score, versus 3.3 for S.P.C. and 3.8 for Telco.

X USING EXCEL OM Excel OM (free with your text and also found in MyLab Operations Management) may be used to solve Example 2 (with the Factor Rating module).

P USING POM FOR WINDOWS POM for Windows also includes a factor rating module. For details, refer to Appendix IV. POM for Windows is also found in MyLab Operations Management and can solve all problems labeled with a P.

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Chapter 2 Operations Strategy in a Global Environment 51

Problems Note: PX means the problem may be solved with POM for Windows and/or Excel OM. Problems 2.1–2.3 relate to A Global View of Operations and Supply Chains

•• 2.1 Match the product with the proper parent company and country in the table below:

Product Parent Company Country

Arrow Shirts Volkswagen 1. France

Braun Household Appliances

Bidermann International

2. Great Britain

Volvo Autos Bridgestone 3. Germany

Firestone Tires Campbell Soup 4. Japan

Godiva Chocolate Credit Lyonnais 5. United States

Häagen-Dazs Ice Cream (USA)

Tata 6. Switzerland

Jaguar Autos Procter & Gamble 7. China

MGM Movies Michelin 8. India

Lamborghini Autos

Nestlé

Goodrich Tires Geely

Alpo Pet Foods

•• 2.2 Based on the corruption perception index developed by Transparency International (www.transparency.org), rank the fol- lowing countries from most corrupt to least: Venezuela, Denmark, the United States, Switzerland, and China.

•• 2.3 Based on the competitiveness ranking developed by the Global Competitiveness Index (www.weforum.org), rank the following countries from most competitive to least: Mexico, Switzerland, the United States, and China.

Problems 2.4 and 2.5 relate to Achieving Competitive Advantage Through Operations

• 2.4 The text provides three primary strategic approaches (differentiation, cost, and response) for achieving competitive advantage. Provide an example of each not given in the text. Support your choices. (Hint: Note the examples provided in the text.)

•• 2.5 Within the food service industry (restaurants that serve meals to customers, but not just fast food), find examples of firms that have sustained competitive advantage by competing on the basis of (1) cost leadership, (2) response, and (3) differentiation. Cite one example in each category; provide a sentence or two in support of each choice. Do not use fast-food chains for all catego- ries. (Hint: A “99¢ menu” is very easily copied and is not a good source of sustained advantage.)

Problem 2.6 relates to Issues in Operations Strategy

••• 2.6 Identify how changes within an organization affect the OM strategy for a company. For instance, discuss what impact the following internal factors might have on OM strategy: a) Maturing of a product. b) Technology innovation in the manufacturing process. c) Changes in laptop computer design that builds in wireless

technology.

Problem 2.7 relates to Strategy Development and Implementation

••• 2.7 Identify how changes in the external environment affect the OM strategy for a company. For instance, discuss what impact the following external factors might have on OM strategy: a) Major increases in oil prices. b) Water- and air-quality legislation. c) Fewer young prospective employees entering the labour market. d) Inflation versus stable prices. e) Legislation moving health insurance from a pretax benefit to

taxable income.

Compute the weighted scores as the sum of the product of the weights and the scores for each option using the SUMPRODUCT function.

=SUMPRODUCT($B$6:$B$12,C6:C12)

Enter factor names and weights in columns A and B.

Enter scores (that come from manager ratings) for BIM, S.P.C., and Telco on each factor in columns C, D, and E.

Actions Copy C14 to D14 and E14

PROGRAM 2.1

Using Excel to Develop a Factor Rating Analysis, With Data from Example 2.

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52 PART 1 Introduction to Operations Management

Problems 2.8–2.12 relate to Strategic Planning, Core Competencies, and Outsourcing

•• 2.8 Claudia Pragram Technologies, Inc., has nar- rowed its choice of outsourcing provider to two firms located in different countries. Pragram wants to decide which one of the two countries is the better choice, based on risk-avoidance criteria. She has polled her executives and established four criteria. The resulting ratings for the two countries are presented in the table below, where 1 is a lower risk and 3 is a higher risk.

Selection Criterion England Mexico

Price of service from outsourcer 2 3

Nearness of facilities to client 3 1

Level of technology 1 3

History of successful outsourcing 1 2

The executives have determined four criteria weightings: Price, with a weight of 0.1; Nearness, with 0.6; Technology, with 0.2; and History, with 0.1. a) Using the factor rating method, which country would you select? b) Double each of the weights used in part (a) (to 0.2, 1.2, 0.4, and

0.2, respectively). What effect does this have on your answer? Why? PX

•• 2.9 Ranga Ramasesh is the operations manager for a firm that is trying to decide which one of four countries it should research for possible outsourcing providers. The first step is to select a country based on cultural risk factors, which are criti- cal to eventual business success with the provider. Ranga has reviewed outsourcing provider directories and found that the four countries in the table that follows have an ample number of pro- viders from which they can choose. To aid in the country selec- tion step, he has enlisted the aid of a cultural expert, John Wang, who has provided ratings of the various criteria in the table. The resulting ratings are on a 1 to 10 scale, where 1 is a low risk and 10 is a high risk.

John has also determined six criteria weightings: Trust, with a weight of 0.4; Quality, with 0.2; Religious, with 0.1; Individualism, with 0.1; Time, with 0.1; and Uncertainty, with 0.1. Using the factor rating method, which country should Ranga select? PX

Culture Selection Criterion Mexico Panama

Costa Rica Peru

Trust 1 2 2 1

Society value of quality work

7 10 9 10

Religious attitudes 3 3 3 5

Individualism attitudes 5 2 4 8

Time orientation attitudes

4 6 7 3

Uncertainty avoidance attitudes

3 2 4 2

•• 2.10 Fernando Garza’s firm wishes to use factor rating to help select an outsourcing provider of logistics services. a) With weights from 1–5 (5 highest) and ratings 1–100 (100

highest), use the following table to help Garza make his decision:

Criterion

Rating of Logistics Providers

Weight Overnight Shipping

Worldwide Delivery

United Freight

Quality 5 90 80 75 Delivery 3 70 85 70 Cost 2 70 80 95

b) Garza decides to increase the weights for quality, delivery, and cost to 10, 6, and 4, respectively. How does this change your conclusions? Why?

c) If Overnight Shipping’s ratings for each of the factors increase by 10%, what are the new results? PX

••• 2.11 Walker Accounting Software is marketed to small accounting firms throughout the United States and Canada. Owner George Walker has decided to outsource the company’s help desk and is considering three providers: Manila Call Center (Philippines), Delhi Services (India), and Moscow Bell (Russia). The following table summarizes the data Walker has assembled. Which outsourcing firm has the best rating? (Higher weights imply higher importance and higher ratings imply more desirable providers.) PX

Criterion

Provider Ratings

Importance Weight Manila Delhi Moscow

Flexibility 0.5 5 1 9 Trustworthiness 0.1 5 5 2 Price 0.2 4 3 6 Delivery 0.2 5 6 6

•••• 2.12 Rao Technologies, a Quebec-based high-tech manufac- turer, is considering outsourcing some of its electronics production. Four firms have responded to its request for bids, and CEO Mohan Rao has started to perform an analysis on the scores his OM team has entered in the table below.

Factor

Ratings of Outsource Providers

Weight A B C D

Labour w 5 4 3 5 Quality procedures 30 2 3 5 1 Logistics system 5 3 4 3 5 Price 25 5 3 4 4 Trustworthiness 5 3 2 3 5 Technology in place 15 2 5 4 4 Management team 15 5 4 2 1

Weights are on a scale from 1 through 30, and the outsourcing pro- vider scores are on a scale of 1 through 5. The weight for the labour factor is shown as a w because Rao’s OM team cannot agree on a value for this weight. For what range of values of w, if any, is company C a recommended outsourcing provider, according to the factor rating method?

Problem 2.13 relates to Global Operations Strategy Options

•• 2.13 Does Boeing practice a multinational operations strat- egy, a global operations strategy, or a transnational operations strategy? Support your choice with specific references to Boeing’s operations and the characteristics of each type of organization.

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Chapter 2 Operations Strategy in a Global Environment 53

Mr. Lube

A substantial market exists for automobile tune-ups, oil changes, and lubrication service for the more than 12 million cars on Canadian roads. Some of this demand is filled by full-service auto dealerships, some by Canadian Tire, and some by other tire/service dealers. However, Mr. Lube, Great Canadian Oil Change, Jiffy Lube, and others have also developed strategies to accommodate this opportunity.

Mr. Lube stations perform oil changes, lubrication, and interior cleaning in a spotless environment. The buildings are clean, freshly painted, and often surrounded by neatly trimmed landscaping and clean parking areas. To facilitate fast service, cars can be driven though the facility. At Mr. Lube, the customer is greeted by service representatives who take their order, which typically includes fluid checks (oil, water, brake fluid, transmission fluid, and differential grease) and the necessary lubrication, as well as filter changes for air and oil. Service personnel in neat uniforms then move into action. The standard team has one person checking fluid levels under the

hood, another in the garage pit removing the oil filter, draining the oil, checking the differential and transmission, and lubricating as necessary. Precise task assignments and good training are designed to move the car into and out of the bay in minutes. The idea is to charge no more, and hopefully less, than gas stations, automotive repair chains, and auto dealers. While doing so, Mr. Lube strives to provide better service than its competitors.

Discussion Questions 1. What constitutes the mission of Mr. Lube? 2. How does the Mr. Lube operations strategy provide competitive

advantage? (Hint: Evaluate how Mr. Lube’s traditional compet- itors perform the 10 decisions of operations management com- pared to how Mr. Lube performs them.)

3. Is it likely that Mr. Lube has increased productivity over its more traditional competitors? Why? How would we measure productivity in this industry?

CASE STUDIES

Regal Marine, one of the United States’s 10 largest power-boat manufacturers, achieves its mission—providing luxury perfor- mance boats to customers worldwide—using the strategy of differ- entiation. It differentiates its products through constant innovation, unique features, and high quality. Increasing sales at the Orlando, Florida, family-owned firm suggest that the strategy is working.

As a quality boat manufacturer, Regal Marine starts with con- tinuous innovation, as reflected in computer-aided design (CAD), high-quality moulds, and close tolerances that are controlled through both defect charts and rigorous visual inspection. In-house quality is not enough, however. Because a product is only as good as the parts put into it, Regal has established close ties with a large number of its suppliers to ensure both flexibility and perfect parts. With the help of these suppliers, Regal can profitably produce a product line of 22 boats, ranging from the $14 000 19-foot boat to the $500 000 44-foot Commodore yacht.

“We build boats,” says VP Tim Kuck, “but we’re really in the ‘fun’ business. Our competition includes not only 300 other boat, canoe, and yacht manufacturers in our $17 billion industry, but home theatres, the internet, and all kinds of alternative family

entertainment.” Fortunately, Regal has been paying down debt and increasing market share.

Regal has also joined with scores of other independent boat makers in the American Boatbuilders Association. Through econ- omies of scale in procurement, Regal is able to navigate against billion-dollar competitor Brunswick (maker of the Sea Ray and Bayliner brands). The Global Company Profile featuring Regal Marine (which opens Chapter 5) provides further background on Regal and its strategy.

Discussion Questions* 1. State Regal Marine’s mission in your own words. 2. Identify the strengths, weaknesses, opportunities, and threats that

are relevant to the strategy of Regal Marine. 3. How would you define Regal’s strategy? 4. How would each of the 10 operations management decisions

apply to operations decision making at Regal Marine?

* You may wish to view the video that accompanies this case before addressing these questions.

Operations Strategy at Regal MarineVideo Case

Hard Rock brings the concept of the “experience economy” to its cafe operation. The strategy incorporates a unique “experience” into its operations. This innovation is somewhat akin to mass cus- tomization in manufacturing. At Hard Rock, the experience con- cept is to provide not only a custom meal from the menu but also a dining event that includes a unique visual and sound experience not duplicated anywhere else in the world. This strategy is suc- ceeding. Other theme restaurants have come and gone while Hard Rock continues to grow. As Professor Constantinos Markides of the London Business School says, “The trick is not to play the game better than the competition, but to develop and play an

altogether different game.”* At Hard Rock, the different game is the experience game.

From the opening of its first cafe in London in 1971, during the British rock music explosion, Hard Rock has been serving food and rock music with equal enthusiasm. Hard Rock Cafe has two Canadian outlets, more than 40 U.S. locations, about a dozen in Europe, and the remainder scattered throughout the world, from Bangkok and Beijing to Beirut. New construction, leases, and investment in remodelling are long term; a global strategy means special consideration of political risk, currency risk, and social norms in a context of a brand fit. Although Hard Rock is one of the

Hard Rock Cafe’s Global StrategyVideo Case

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54 PART 1 Introduction to Operations Management

most recognized brands in the world, this does not mean its cafe is a natural everywhere. Special consideration must be given to the sup- ply chain for the restaurant and its accompanying retail store. About 48% of a typical cafe’s sales are from merchandise.

The Hard Rock Cafe business model is well defined, but because of various risk factors and differences in business prac- tices and employment law, Hard Rock elects to franchise about half of its cafes. Social norms and preferences often suggest some tweaking of menus for local taste. For instance, Hard Rock focuses less on hamburgers and beef and more on fish and lobster in its British cafes.

Because 70% of Hard Rock’s guests are tourists, recent years have found it expanding to “destination” cities. While this has been a winning strategy for decades, allowing the firm to grow from one London cafe to 145 facilities in 60 countries, it has made Hard Rock susceptible to economic fluctuations that hit the tourist business hardest. So Hard Rock is signing a long-term lease for a new location in Nottingham, England, to join recently opened

cafes in Manchester and Birmingham—cities that are not standard tourist destinations. At the same time, menus are being upgraded. Hopefully, repeat business from locals in these cities will smooth demand and make Hard Rock less dependent on tourists.

Discussion Questions†

1. Identify the strategy changes that have taken place at Hard Rock Cafe since its founding in 1971.

2. As Hard Rock Cafe has changed its strategy, how have its responses to some of the 10 decisions of OM changed?

3. Where does Hard Rock fit within the four international opera- tions strategies outlined in Figure 2.9? Explain your answer.

* Constantinos Markides, “Strategic Innovation,” MIT Sloan Management Review 38, no. 3 (spring 1997): 9. † You may wish to view the video that accompanies the case before addressing these questions.

cAdditional Case Study: Visit MyLab Operations Management for this free case study: Motorola’s Global Strategy: Focuses on Motorola’s international strategy.

Main Heading Review Material

MyLab Operations Management

A GLOBAL VIEW OF OPERATIONS AND SUPPLY CHAINS (pp. 28–31)

Domestic business operations decide to change to some form of international operations for six main reasons: 1. Reduce costs (labour, taxes, tariffs, etc.) 2. Improve supply chain 3. Provide better goods and services 4. Understand markets 5. Learn to improve operations 6. Attract and retain global talent • Maquiladoras—Mexican factories located along the U.S.–Mexico border

that receive preferential tariff treatment. • World Trade Organization (WTO)—An international organization that

promotes world trade by lowering barriers to the free flow of goods across borders.

• United States, Mexico, Canada Agreement (USMCA)—A free trade agreement between Canada, Mexico, and the United States.

• European Union (EU)—A European trade group that has 28 member states as of 2015.

Other trade agreements include APEC (the Pacific Rim countries), SEATO (Australia, New Zealand, Japan, Hong Kong, South Korea, New Guinea, and Chile), MERCOSUR (Argentina, Brazil, Paraguay, and Uruguay), and CAFTA (Central America, the Dominican Republic, and the United States).

The World Trade Organization helps to make uniform the protection of both governments and industries from foreign firms that engage in unethical conduct.

CULTURAL AND ETHICAL ISSUES (pp. 31–32)

Globalization involves many challenges, including reconciling differences in social and cultural behaviour.

CHAPTER 2 RAPID REVIEW

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Chapter 2 Operations Strategy in a Global Environment 55

Main Heading Review Material

MyLab Operations Management

DEVELOPING MISSIONS AND STRATEGIES (pp. 32–33)

An effective operations management effort must have a mission so it knows where it is going and a strategy so it knows how to get there. • Mission—The purpose or rationale for an organization’s existence. • Strategy—How an organization expects to achieve its missions and goals. The three strategic approaches to competitive advantage are: 1. Differentiation 2. Cost leadership 3. Response

VIDEO 2.1

Operations Strategy at Regal Marine

ACHIEVING COMPETITIVE ADVANTAGE THROUGH OPERATIONS (pp. 33–36)

• Competitive advantage—The creation of a unique advantage over competitors.

• Differentiation—Distinguishing the offerings of an organization in a way that the customer perceives as adding value.

• Experience differentiation—Engaging a customer with a product through imaginative use of the five senses, so the customer “experiences” the product.

• Low-cost leadership—Achieving maximum value, as perceived by the customer.

• Response—A set of values related to rapid, flexible, and reliable performance.

Differentiation can be attained, for example, through innovative design, by providing a broad product line, by offering excellent after-sale service, or through adding a sensory experience to the product or service offering. Cost leadership can be attained, for example, via low overhead, effective capacity use, or efficient inventory management. Response can be attained, for example, by offering a flexible product line, reliable scheduling, or speedy delivery.

VIDEO 2.2

Hard Rock’s Global Strategy

10 STRATEGIC OM DECISIONS (pp. 36–39)

• Operations decisions—The strategic decisions of OM are goods and service design, quality, process and capacity design, location selection, layout design, human resources and job design, supply chain management, inventory, sched- uling, and maintenance.

ISSUES IN OPERATIONS STRATEGY (pp. 39–40)

• Resources view—A method managers use to evaluate the resources at their disposal and manage or alter them to achieve competitive advantage.

• Value chain analysis—A way to identify the elements in the product/ service chain that uniquely add value.

• Five forces model—A method of analyzing the five forces in the compet- itive environment.

The potential competing forces in Porter’s five forces model are (1) immediate rivals, (2) potential entrants, (3) customers, (4) suppliers, and (5) substitute products. Different issues are emphasized during different stages of the product life cycle: • Introduction—Company strategy: Best period to increase market

share, R&D engineering is critical. OM strategy: Product design and development critical, frequent product and process design changes, short production runs, high production costs, limited models, attention to quality.

• Growth—Company strategy: Practical to change price or quality image, strengthen niche. OM strategy: Forecasting critical, product and process re- liability, competitive product improvements and options, increase capacity, shift towards product focus, enhance distribution.

• Maturity—Company strategy: Poor time to change image or price or quality, competitive costs become critical, defend market position. OM strategy: Standardization, less rapid product changes (more minor chang- es), optimum capacity, increasing stability of process, long production runs, product improvement, and cost cutting.

• Decline—Company strategy: Cost control critical. OM strategy: Little product differentiation, cost minimization, overcapacity in the industry, prune line to eliminate items not returning good margin, reduce capacity.

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56 PART 1 Introduction to Operations Management

Main Heading Review Material

MyLab Operations Management

STRATEGY DEVELOPMENT AND IMPLEMENTATION (pp. 40–43)

• SWOT analysis—A method of determining internal strengths and weak- nesses and external opportunities and threats.

The strategy development process first involves performing environmental analysis, followed by determining the corporate mission, and finally forming a strategy. • Key success factors (KSFs)—Activities or factors that are key to achiev-

ing competitive advantage. • Core competencies—A set of skills, talents, and activities in which a firm

is particularly strong. A core competency may be a subset of, or a combination of, KSFs. • Activity map—A graphical link of competitive advantage, KSFs, and

supporting activities. An operations manager’s job is to implement an OM strategy, provide com- petitive advantage, and increase productivity.

Virtual Office Hours for Solved Problem: 2.1

STRATEGIC PLANNING, CORE COMPETENCIES, AND OUTSOURCING (pp. 43–46)

• Outsourcing—Transferring a firm’s activities that have traditionally been internal to external suppliers

• Theory of comparative advantage—A theory which states that countries benefit from specializing in (and exporting) goods and services in which they have relative advantage, and they benefit from importing goods and services in which they have a relative disadvantage.

GLOBAL OPERATIONS STRATEGY OPTIONS (pp. 47–49)

• International business—A firm that engages in cross-border transactions.

• Multinational corporation (MNC)—A firm that has extensive involve- ment in international business, owning or controlling facilities in more than one country.

• International strategy—A strategy in which global markets are penetrated using exports and licences.

• Multidomestic strategy—A strategy in which operating decisions are decentralized to each country to enhance local responsiveness.

• Global strategy—A strategy in which operating decisions are centralized and headquarters coordinates the standardization and learning between facilities.

• Transnational strategy—A strategy that combines the benefits of global-scale efficiencies with the benefits of local responsiveness. These firms transgress national boundaries.

The four operations strategies for approaching global opportunities can be classified according to local responsiveness and cost reduction:

1. International—Little local responsiveness and little cost advantage

2. Multidomestic—Significant local responsiveness but little cost advantage

3. Global—Little local responsiveness but significant cost advantage

4. Transnational—Significant local responsiveness and significant cost advantage

Self-Test  Before taking the self-test, refer to the learning objectives listed at the beginning of the chapter.

LO1 A mission statement is beneficial to an organization because it: a) is a statement of the organization’s purpose. b) provides a basis for the organization’s culture. c) identifies important constituencies. d) details specific income goals. e) ensures profitability.

LO2 The three strategic approaches to competitive advantage are _______, _________, and _________.

LO3 Core competencies are those strengths in a firm that include: a) specialized skills. b) unique production methods. c) proprietary information/knowledge. d) things a company does better than others. e) all of the above.

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Chapter 2 Operations Strategy in a Global Environment 57

Most of these questions can be found in MyLab Operations Management. Visit MyLab Operations Management to access cases, videos, downloadable software, and much more. MyLab Operations Management Management also features a personalized Study Plan that helps you identify which chapter concepts you’ve mastered and guides you towards study tools for additional practice.

MyLab Operations Management

LO4 Evaluating outsourcing providers by comparing their weighted aver- age scores involves:

a) factor rating analysis. b) cost-volume analysis. c) transportation model analysis. d) linear regression analysis. e) crossover analysis.

LO5 A company that is organized across international boundaries, with decentralized authority and substantial autonomy at each business via subsidiaries, franchises, or joint ventures, has:

a) a global strategy. b) a transnational strategy. c) an international strategy. d) a multidomestic strategy.

Answers: LO1. a; LO2. differentiation, cost leadership, response; LO3. e; LO4. a; LO5. c.

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58

Global Company

Profile EllisDon

Project Management Is a Core Strength for EllisDon Doing a good job is commendable, but in the construction industry it is

imperative that it is also done on time, every time, and at each step dur-

ing the process. Excellence in project management is a defining factor

in successful companies.

EllisDon is a Canadian leader in engineering and construction project

management. It is self-described as a project management service that takes

a “hands-on” approach. The company’s belief is that by becoming deeply

involved in a project, it can ensure that the job is completed as the owner

intended. This level of commitment and involvement aids in foreseeing

issues, thus allowing challenges to be faced head-on and resolved faster.

EllisDon works with clients to keep its projects on track from project

conception through to the selection of consultants, planning, tendering, and

finally completion, closeout, and commissioning. In instances where EllisDon

is not the builder of the project, it oversees all the work, manages the con-

sultants, and reports the progress to the owner.

Project Management

Learning Objectives LO1 Use a Gantt chart for

scheduling 62

LO2 Draw AOA and AON networks 67

LO3 Complete forward and backward passes for a project 70

LO4 Determine a critical path 74

LO5 Calculate the variance of activity times 77

LO6 Crash a project 81

AboutLife/Shutterstock

3

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Chapter 3 Project Management 59

The company has a wealth of experience and

knowledge, having worked on projects of all sizes and

complexities in a wide variety of locations around the

world. It has also built solid relationships with archi-

tects, engineers, and subcontractors. This network of

expertise is a valuable resource for project manage-

ment in this industry.

On the global scene, EllisDon is the project man-

ager for the Palm Jumeirah in Dubai, United Arab

Emirates. This is a property development project

using land reclamation to create an artificial archi-

pelago so large that it can be seen from space; upon

completion, it is anticipated it will be visible from the

moon. It contains apartment buildings, town houses,

plus food and retail outlets.

The following is a list of some of the company’s

other more notable current projects, both those that

are completed and ongoing:

• Increased expansion at the Calgary Airport.

• Union Station (Toronto) renovation and expansion.

• Design-builder for the Halifax 4-Pad Arena.

• General contractor for additions to the Hamilton

Community Centre for the City of Richmond, British

Columbia.

• Construction manager for George Brown College’s

Waterfront Campus.

• Construction of the SickKids (Hospital) Research

Tower.

• Construction management contract for the

Ritz-Carlton, Toronto, and the Residences at the

Ritz-Carlton.

• Construction work on the Saskatoon Police Head-

quarters.

• Engineer-procure-construct contract for an ethanol

plant for Terra Grain Fuels, Inc., of Regina,

Saskatchewan.

EllisDon’s excellence in project management con-

tinues to provide a competitive advantage. Due to the

company’s reputation and experience in project man-

agement, it is not difficult to understand why EllisDon

is a Canadian success story.

Source: www.ellisdon.com.

The Importance of Project Management When EllisDon, the subject of the opening Global Company Profile, received confirmation that it was awarded the contract to be the project manager for the Palm Jumeirah in Dubai, United Arab Emirates, it had to mobilize a large force of subcontractors, workers, construction pro- fessionals, and engineers. The project management team was also required to ensure ongoing access to physical resources and an uninterrupted flow of supplies. Similarly, when Hard Rock Cafe sponsors Rockfest, hosting more than 100 000 fans at its annual concert, the project man- ager begins planning some nine months earlier. Using the software package Microsoft Project, described in this chapter, each of the hundreds of details can be monitored and controlled. When a band can’t reach the Rockfest site by bus because of massive traffic jams, Hard Rock’s project manager is ready with a helicopter backup.

EllisDon and Hard Rock Cafe are just two examples of firms that face modern phenomena: growing project complexity and collapsing product/service life cycles. This change stems from awareness of the strategic value of time-based competition and a quality mandate for continuous improvement. Each new product/service introduction is a unique event—a project. In addition, projects are a common part of our everyday life, whether we are planning a wedding or a surprise birthday party, remodelling a house, or preparing a semester-long class project.

VIDEO 3.1 Project Management at Hard Rock’s Rockfest

Construction of the SickKids (Hospital) Research Tower.

Si ck

Ki ds

F ou

nd at

io n/

N ew

sc om

Wherever your career takes you, one of the most useful tools you can have, as a manager, is the ability to manage a project.

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60 PART 1 Introduction to Operations Management

Scheduling projects is a difficult challenge for operations managers. The stakes in project management are high, and cost overruns and unnecessary delays occur due to poor scheduling and poor controls.

Projects that take months or years to complete are usually developed outside the normal pro- duction system. Project organizations within the firm may be set up to handle such jobs and are often disbanded when the project is complete. On other occasions, managers find projects just a part of their job. The management of projects involves three phases (see Figure 3.1):

1. Planning: This phase includes goal setting, defining the project, and team organization. 2. Scheduling: This phase relates people, money, and supplies to specific activities and relates

activities to each other. 3. Controlling: Here, the firm monitors resources, costs, quality, and budgets. It also revises or

changes plans and shifts resources to meet time and cost demands.

We begin this chapter with a brief overview of these functions. We also describe three pop- ular techniques to allow managers to plan, schedule, and control—Gantt charts, the program evaluation and review technique (PERT), and the critical path method (CPM).

Project Planning Projects can be defined as a series of related tasks directed towards a major output. In some firms, a project organization is developed to make sure existing programs continue to run smoothly on a day-to-day basis while new projects are successfully completed.

For companies with multiple large projects, such as a construction firm, a project organiza- tion is an effective way of assigning the people and physical resources needed. It is a temporary

Project organization An organization formed to ensure that programs (projects) receive the proper management and attention.

Planning the Project

Scheduling the Project

Controlling the Project

Set the goals Performance

1.1 1.2 2.0 2.1

2.11

Define the project

Develop work breakdown

structure Identify team/

resources

Sequence activities Assign people

Schedule deliverables Schedule resources

T im

e Cost

1.1 1.2 2.0 2.1

2.11

Monitor resources, costs, quality

Adams Smith Jones

Shift resources

Revise and change plans

Adams Smith Jones

Before project

Start of project During project

Timeline

FIGURE 3.1 Project Planning, Scheduling, and Controlling

Managers must “plan the work and then work the plan”. Project planning helps you do that.

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Chapter 3 Project Management 61

organization structure designed to achieve results by using specialists from throughout the firm. NASA and many other organizations use the project approach. You may recall Project Gemini and Project Apollo, terms used to describe teams that NASA organized to reach space explora- tion objectives.

The project organization works best when:

1. Work can be defined with a specific goal and deadline. 2. The job is unique or somewhat unfamiliar to the existing organization. 3. The work contains complex interrelated tasks requiring specialized skills. 4. The project is temporary but critical to the organization. 5. The project cuts across organizational lines.

THE PROJECT MANAGER An example of a project organization is shown in Figure 3.2. Project team members are tempo- rarily assigned to a project and report to the project manager. The manager heading the project coordinates activities with other departments and reports directly to top management. Project managers receive high visibility in a firm and are responsible for making sure that (1) all nec- essary activities are finished in proper sequence and on time; (2) the project comes in within budget; (3) the project meets its quality goals; and (4) the people assigned to the project receive the motivation, direction, and information needed to do their jobs. This means that project man- agers should be good coaches and communicators, and be able to organize activities from a variety of disciplines.

ETHICAL ISSUES FACED IN PROJECT MANAGEMENT Project managers not only have high visibility but also face ethical decisions on a daily basis. How they act establishes the code of conduct for the project. Project managers often deal with (1) offers of gifts from contractors, (2) pressure to alter status reports to mask the reality of delays, (3) false reports for charges of time and expenses, and (4) pressures to compromise quality to meet bonus or penalty schedules.

Using the Project Management Institute’s (www.pmi.org) ethical codes is one means of try- ing to establish standards. Research has shown that without good leadership and a strong organi- zational culture, most people follow their own sets of ethical standards and values.1

WORK BREAKDOWN STRUCTURE The project management team begins its task well in advance of project execution so that a plan can be developed. One of its first steps is to carefully establish the project’s objectives, then break the project down into manageable parts. This work breakdown structure (WBS) defines the project by dividing it into its major subcomponents (or tasks), which are then subdivided into

Work breakdown structure (WBS) A hierarchical description of a project into more and more detailed components.

Project No.1

Project No. 2

Mechanical Engineer

Test Engineer

Production

Project Manager

Technician Electrical Engineer

Computer Engineer

Project Manager

Technician

Quality Mgt.

Human Resources Marketing Finance Design

President FIGURE 3.2

A Sample Project Organization

1 See Hilder Helgadottir, “The Ethical Dimension of Project Management,” International Journal of Project Management 26, no. 7 (October 2008): 743–748.

Project organizations can be temporary or permanent. A permanent organization is usually called a “matrix organization”.

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62 PART 1 Introduction to Operations Management

more detailed components, and finally into a set of activities and their related costs. The division of the project into smaller and smaller tasks can be difficult but is critical to managing the pro- ject and to scheduling success. Gross requirements for people, supplies, and equipment are also estimated in this planning phase.

The work breakdown structure typically decreases in size from top to bottom and is indented like this:

Level

1 Project

2 Major tasks in the project

3 Subtasks in major tasks

4 Activities (or “work packages”) to be completed

This hierarchical framework can be illustrated with the development of Microsoft’s operating system Windows 8. As we see in Figure 3.3, the project, creating a new operating system, is labelled 1.0. The first step is to identify the major tasks in the project (level 2). Three examples would be software design (1.1), project management (1.2), and system testing (1.3). Two major subtasks for 1.1 are development of graphical user interfaces (GUIs) (1.1.1) and creating com- patibility with previous versions of Windows (1.1.2). The major subtasks for 1.1.2 are level 4 activities, such as creating a team to handle compatibility with Windows 7 (1.1.2.1), creating a team for Windows Vista (1.1.2.2), and creating a team for Windows XP (1.1.2.3). There are usually many level 4 activities.

Project Scheduling Project scheduling involves sequencing and allotting time to all project activities. At this stage, managers decide how long each activity will take and compute how many people and what materials will be needed at each stage of production. Managers also chart separate schedules for personnel needs by type of skill (management, engineering, or pouring concrete, for example). Charts also can be developed for scheduling materials.

One popular project scheduling approach is the Gantt chart. Gantt charts are low-cost means of helping managers make sure that (1) activities are planned, (2) order of performance is documented, (3) activity time estimates are recorded, and (4) overall project time is developed. As Figure 3.4 shows, Gantt charts are easy to understand. Horizontal bars are drawn for each project activity along a timeline. This illustration of a routine servicing of a Delta jetliner during a 40-minute lay-

Gantt charts Planning charts used to schedule resources and allocate time.

LO1 Use a Gantt chart for scheduling

Level 2

Level 3

Level 4

Level 1 Develop Windows 8 Operating System

Software Design

Project Management

System Testing

Develop GUIs

Planning

1.0

1.1 1.2 1.3

1.1.1

1.1.2

1.1.2.1

1.1.2.2

1.1.2.3

1.2.2 1.3.2

1.2.1 1.3.1 Module Testing

Ensure Compatibility with Earlier Versions

Defect Tracking

Cost/Schedule Management

Compatible with Windows 7(Work packages)

Compatible with Windows Vista

Compatible with Windows XP

FIGURE 3.3

Work Breakdown Structure

Gantt charts are simple and visual, making them widely used.

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Chapter 3 Project Management 63

over shows that Gantt charts also can be used for scheduling repetitive operations. In this case, the chart helps point out potential delays. The OM in Action box on Delta provides additional insights.

On simple projects, scheduling charts such as these permit managers to observe the progress of each activity and to spot and tackle problem areas. Gantt charts do not adequately illustrate the interrelationships between the activities and the resources, however.

PERT and CPM, the two widely used network techniques that we shall discuss shortly, do have the ability to consider precedence relationships and interdependency of activities. On com- plex projects, the scheduling of which is almost always computerized, PERT and CPM thus have an edge over the simpler Gantt charts. Even on huge projects, though, Gantt charts can be used as summaries of project status and may complement the other network approaches.

To summarize, whatever the approach taken by a project manager, project scheduling serves several purposes:

1. It shows the relationship of each activity to others and to the whole project. 2. It identifies the precedence relationships among activities. 3. It encourages the setting of realistic time and cost estimates for each activity. 4. It helps make better use of people, money, and material resources by identifying critical

bottlenecks in the project.

0 10 20 30 40

Time, minutes

Passengers

Baggage

Fuelling

Lavatory servicing

Galley servicing

Cargo and mail

Drinking water

Flight service

Cabin cleaning

Cargo and mail

Operating crew Baggage Passengers

Baggage claim Deplaning

Container offload

Engine injection water Pumping

Container offload Main cabin door Aft cabin door

Loading Aft, centre, forward

Economy section First-class section

Container/bulk loading

Galley/cabin check

Aircraft check Receive passengers

Loading Boarding

FIGURE 3.4

Gantt Chart of Service Activities for a Delta Jet during a 40-Minute Layover Delta hopes to save U.S. $50 million a year with this turnaround time, which is a reduction from its traditional 60-minute routine.

Flight 574’s engines screech its arrival as the jet lumbers down Richmond’s taxiway with 140 passengers arriving from Atlanta. In 40 minutes, the plane is to be airborne again.

However, before this jet can depart, there is business to attend to: passengers, luggage, and cargo to unload and load; thousands of gallons of jet fuel and countless drinks to restock; cabin and restrooms to clean; toilet holding tanks to drain; and engines, wings, and landing gear to inspect.

The 10-person ground crew knows that a miscue any- where—a broken cargo loader, lost baggage, misdirected passengers—can mean a late departure and trigger a chain reaction of headaches from Richmond to Atlanta to every destination of a connecting flight.

Carla Sutera, the operations manager for Delta’s Rich- mond International Airport, views the turnaround opera- tion like a pit boss awaiting a race car. Trained crews are in place for Flight 574, with baggage carts and tractors, hydraulic cargo loaders, a truck to load food and drinks, another to lift the cleanup crew, another to put fuel on, and a fourth to take water off. The “pit crew” usually per- forms so smoothly that most passengers never suspect the proportions of the effort. Gantt charts, such as the one in Figure 3.4, aid Delta and other airlines with the staffing and scheduling that are needed for this task.

Sources: Knight Ridder Tribune Business News (July 16, 2005): 1 and (November 21, 2002): 1.

Delta’s Ground Crew Orchestrates a Smooth TakeoffOM in Action

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64 PART 1 Introduction to Operations Management

Project Controlling The control of projects, like the control of any management system, involves close monitoring of resources, costs, quality, and budgets. Control also means using a feedback loop to revise the pro- ject plan and having the ability to shift resources to where they are needed most. Computerized PERT/CPM reports and charts are widely available today on personal computers. Some of the more popular of these programs are Oracle Primavera (by Oracle), MindView (by Match Ware), HP Project (by Hewlett-Packard), Fast Track (by AEC Software), and Microsoft Project (by Microsoft Corp.), which we illustrate in this chapter.

These programs produce a broad variety of reports, including (1) detailed cost breakdowns for each task, (2) total program labour curves, (3) cost distribution tables, (4) functional cost and hour summaries, (5) raw material and expenditure forecasts, (6) variance reports, (7) time analy- sis reports, and (8) work status reports.

Controlling projects can be difficult. The stakes are high; cost overruns and unnecessary delays can occur due to poor planning, scheduling, and controls. Some projects are “well-defined,” whereas others may be “ill-defined”. Projects typically only become well-defined after detailed extensive initial planning and careful definition of required inputs, resources, processes, and outputs. Well-established projects where constraints are known (e.g., buildings and roads) and engineered products (e.g., airplanes and cars) with well-defined specifications and drawings may

VIDEO 3.2 Project Management at Arnold

Palmer Hospital

Construction of the new 11-storey building at Arnold Palmer Hospital in Orlando, Florida, was an enormous project for the hospital administration. The photo on the left shows the first six floors under construction. The photo on the right shows the building as completed two years later. Prior to beginning actual construction, regulatory and funding issues added, as they do with most projects, substantial time to the overall project. Cities have zoning and parking issues; the U.S. Environmental Protection Agency has drain- age and waste issues; and regulatory authorities have their own requirements, as do issuers of bonds. The $100 million, four-year project at Arnold Palmer Hospital is discussed in the Video Case Study at the end of this chapter.

Co ur

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A rn

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Pa lm

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ed ic

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r

Co ur

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A rn

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Pa lm

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ed ic

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en te

r

Agile project management has changed the way that Mastek Corp., in Mumbai, India, develops its educational software products. On a traditional well-defined project, managers are actively involved in directing work and telling their team what needs to be done—a style often referred to as a step-by-step waterfall style of project management.

Agile project management is different. In the early stages, the project manager creates a high-level plan, based on outline requirements and a high-level view of the solution. From that point, the end project is created iteratively and incrementally, with each increment building on the output of steps preceding it.

The principles of agile are essentially communication and transparency. Instead of waiting for something to be

delivered, with limited understanding of the desired end result, there are numerous checkpoints and feedback loops to track progress.

Agile provides Mastek the ability to keep costs under control. Without agile, the cost of quality increases. “It’s much harder to correct mistakes when a software product is nearing its final phase of development,” says a company executive. “It’s much better to develop it as you go along. I think agile project management would help any software developer.”

Sources: AMPG International (2015) and www.cprime.com (2012).

Agile Project Management at MastekOM in Action

Software has revolutionized project control.

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Chapter 3 Project Management 65

fall into this category. Well-defined projects are assumed to have changes small enough to be managed without substantially revising plans. They use what is called a waterfall approach, where the project progresses smoothly, in a step-by-step manner, through each phase to completion.

But many projects, such as software development (e.g., 3-D games) and new technology (e.g., landing the Mars land rover) are ill-defined. These projects require what is known as an agile style of management with collaboration and constant feedback to adjust to the many unknowns of the evolving technology and project specifications. The OM in Action box “Agile Project Management at Mastek” provides such an example. Most projects fall somewhere between waterfall and agile.

Project Management Techniques: PERT and CPM Program evaluation and review technique (PERT) and the critical path method (CPM) were both developed in the 1950s to help managers schedule, monitor, and control large and complex projects. CPM arrived first, in 1957, as a tool developed by J. E. Kelly of Remington Rand and M. R. Walker of DuPont to assist in the building and maintenance of chemical plants at DuPont. Independently, PERT was developed in 1958 for the U.S. Navy.

THE FRAMEWORK OF PERT AND CPM PERT and CPM both follow six basic steps:

1. Define the project and prepare the work breakdown structure. 2. Develop the relationships among the activities. Decide which activities must precede and

which must follow others. 3. Draw the network connecting all the activities. 4. Assign time and/or cost estimates to each activity. 5. Compute the longest time path through the network. This is called the critical path. 6. Use the network to help plan, schedule, monitor, and control the project.

Step 5, finding the critical path, is a major part of controlling a project. The activities on the critical path represent tasks that will delay the entire project if they are not completed on time. Managers can gain the flexibility needed to complete critical tasks by identifying noncritical activities and replanning, rescheduling, and reallocating labour and financial resources.

Although PERT and CPM differ to some extent in terminology and in the construction of the network, their objectives are the same. Furthermore, the analysis used in both techniques is very similar. The major difference is that PERT employs three time estimates for each activity. These time estimates are used to compute expected values and standard deviations for the activity. CPM makes the assumption that activity times are known with certainty and hence requires only one time factor for each activity. For an example of large project that put these principles into action see the OM in Action box “Rebuilding the Electricity Grid in China”.

For purposes of illustration, the rest of this section concentrates on a discussion of PERT. Most of the comments and procedures described, however, apply just as well to CPM.

PERT and CPM are important because they can help answer questions such as the following about projects with thousands of activities:

1. When will the entire project be completed? 2. What are the critical activities or tasks in the project—that is, which activities will delay the

entire project if they are late? 3. Which are the noncritical activities—the ones that can run late without delaying the whole

project’s completion? 4. What is the probability that the project will be completed by a specific date? 5. At any particular date, is the project on schedule, behind schedule, or ahead of schedule? 6. On any given date, is the money spent equal to, less than, or greater than the budgeted

amount? 7. Are there enough resources available to finish the project on time? 8. If the project is to be finished in a shorter amount of time, what is the best way to accom-

plish this goal at the least cost?

Program evaluation and review technique (PERT) A project management technique that employs three time estimates for each activity.

Critical path method (CPM) A project management technique that uses only one time factor per activity.

Critical path The computed longest time path(s) through a network.

To use project management software, you first need to understand the next two sections in this chapter.

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66 PART 1 Introduction to Operations Management

B C

A

B

C A

B

C

A

B

C

B

C

A B CA

B DA

C

CA

DB

A

B D

A C

B

C

DA

CA

DB

CA

DB

A comes before B, which comes before C.

A and B must both be completed before C can start.

B and C cannot begin until A is completed.

C and D cannot begin until both A and B are completed.

C cannot begin until both A and B are completed; D cannot begin until B is completed. A dummy activity is introduced in AOA.

B and C cannot begin until A is completed. D cannot begin until both B and C are completed. A dummy activity is again introduced in AOA.

Dummy activity

Dummy activity

Activity-on-Node (AON) Activity Meaning Activity-on-Arrow (AOA)

(a)

(b)

(c)

(d)

(e)

(f)

FIGURE 3.5 A Comparison of AON and AOA Network Conventions

NETWORK DIAGRAMS AND APPROACHES The first step in a PERT or CPM network is to divide the entire project into significant activities in accordance with the work breakdown structure. There are two approaches for drawing a project network: activity on node (AON) and activity on arrow (AOA). Under the AON convention, nodes designate activities. Under AOA, arrows represent activities. Activities consume time and resources. The basic difference between AON and AOA is that the nodes in an AON diagram represent activities. In an AOA network, the nodes represent the starting and finishing times of an activity and are also called events. So nodes in AOA consume neither time nor resources.

Figure 3.5 illustrates both conventions for a small portion of the airline turnaround Gantt chart (in Figure 3.4). The examples provide some background for understanding six common activity relationships in networks. In Figure 3.5(a), activity A must be finished before activity B is started, and B must, in turn, be completed before C begins. Activity A might represent “deplaning passengers,” while B is “cabin cleaning,” and C is “boarding new passengers”.

Figures 3.5(e) and 3.5(f) illustrate that the AOA approach sometimes needs the addition of a dummy activity to clarify relationships. A dummy activity consumes no time or resources but is required when a network has two activities with identical starting and ending events, or when two or more follow some, but not all, “preceding” activities. The use of dummy activities is also

Activity-on-node (AON) A network diagram in which nodes designate activities.

Activity-on-arrow (AOA) A network diagram in which arrows designate activities.

Dummy activity An activity having no time that is inserted into a network to maintain the logic of the network.

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Chapter 3 Project Management 67

ACTIVITY-ON-NODE EXAMPLE

Hamilton Paper Manufacturing, Inc., located near downtown Hamilton, has long been delaying the expense of installing air pollution control equipment in its facility. The province has recently given the manufacturer 16 weeks to install a complex air filter system. Hamilton Paper has been warned that it may be forced to close the facility unless the device is installed in the allotted time. Joni Steinberg, the plant manager, wants to make sure that installation of the filtering system progresses smoothly and on time.

Given the following information, develop a table showing activity precedence relationships.

APPROACH c  Hamilton Paper has identified the eight activities that need to be performed in order for the project to be completed. When the project begins, two activities can be simultaneously started: building the internal components for the device (activity A) and making the modifications necessary for the floor and roof (activity B). The construction of the collection stack (activity C) can begin when the in- ternal components are completed. Pouring the concrete floor and installation of the frame (activity D) can be started as soon as the internal components are completed and the roof and floor have been modified.

After the collection stack has been constructed, two activities can begin: building the high- temperature burner (activity E) and installing the pollution control system (activity F). The air pollution device can be installed (activity G) after the concrete floor has been poured, the frame has been installed, and the high-temperature burner has been built. Finally, after the control system and pollution device have been installed, the system can be inspected and tested (activity H).

SOLUTION c  Activities and precedence relationships may seem rather confusing when they are pre- sented in this descriptive form. It is therefore convenient to list all the activity information in a table, as shown in Table 3.1. We see in the table that activity A is listed as an immediate predecessor of activity C. Likewise, both activities D and E must be performed prior to starting activity G.

LO2 Draw AOA and AON networks

EXAMPLE 1

Activity-on-Node for Environmental Problem at Hamilton Paper

Table 3.1 Hamilton Paper Manufacturing’s Activities and Predecessors

Activity Description Immediate Predecessors

A Build internal components —

B Modify roof and floor —

C Construct collection stack A

D Pour concrete and install frame A, B

E Build high-temperature burner C

F Install pollution control system C

G Install air pollution device D, E

H Inspect and test F, G

INSIGHT c  To complete a network, all predecessors must be clearly defined.

LEARNING EXERCISE c  What is the impact on the sequence of activities if provincial approval is required after Inspect and test? [Answer: The immediate predecessor for the new activity would be H, Inspect and test, with Provincial approval as the last activity, I.]

Note that in Example 1, it is enough to list just the immediate predecessors for each activity. For instance, in Table 3.1, since activity A precedes activity C, and activity C precedes activity E, the fact that activity A precedes activity E is implicit. This relationship need not be explicitly shown in the activity precedence relationships.

When there are many activities in a project with fairly complicated precedence relationships, it is difficult for an individual to comprehend the complexity of the project from just the tabular information. In such cases, a visual representation of the project, using a project network, is con- venient and useful. A project network is a diagram of all the activities and the precedence rela- tionships that exist between these activities in a project. Example 2 illustrates how to construct a project network for Hamilton Paper Manufacturing.

important when computer software is employed to determine project completion time. A dummy activity has a completion time of zero and is shown graphically with a dashed line.

Although both AON and AOA are popular in practice, many of the project management soft- ware packages, including Microsoft Project, use AON networks. For this reason, although we illustrate both types of networks in the next examples, we focus on AON networks in subsequent discussions in this chapter.

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68 PART 1 Introduction to Operations Management

We now show the precedence relationships using lines with arrow symbols. For example, an arrow from activity Start to activity A indicates that Start is a predecessor for activity A. In a similar fashion, we draw an arrow from Start to B.

Next, we add a new node for activity C. Since activity A precedes activity C, we draw an arrow from node A to node C. Likewise, we first draw a node to represent activity D. Then, since activities A and B both precede activity D, we draw arrows from A to D and from B to D (see Figure 3.7).

D

C

Activity A Precedes Activity C

Activities A and B Precede Activity D

Start

B

A

FIGURE 3.7

Intermediate AON Network for Hamilton Paper

We proceed in this fashion, adding a separate node for each activity and a separate line for each precedence relationship that exists. The complete AON project network for the Hamilton Paper Manufacturing project is shown in Figure 3.8.

D G

H

Arrows Show Precedence

Relationships

Start

B

A

F

E

C

FIGURE 3.8

Complete AON Network for Hamilton Paper

INSIGHT c  Drawing a project network properly takes some time and experience. We would like the lines to be straight and arrows to move to the right when possible.

LEARNING EXERCISE c  If Provincial approval occurs after Inspect and test, what is the impact on the graph? [Answer: A straight line is extended to the right beyond H to reflect the additional activity.]

RELATED PROBLEMS c  3.3, 3.6, 3.7, 3.9a, 3.10, 3.12, 3.15a

2 Draw the AON network for Hamilton Paper, using the data in Example 1.

APPROACH c  In the AON approach, we denote each activity by a node. The lines, or arrows, rep- resent the precedence relationships between the activities.

SOLUTION c  In this example, there are two activities (A and B) that do not have any predecessors. We draw separate nodes for each of these activities, as shown in Figure 3.6. Although not required, it is usually convenient to have a unique starting activity for a project. We have therefore included a dummy activity called Start in Figure 3.6. This dummy activity does not really exist and takes up zero time and resources. Activity Start is an immediate predecessor for both activities A and B, and serves as the unique starting activity for the entire project.

EXAMPLE

AON Graph for Hamilton Paper

A

B

Activity A (Build Internal Components)

Activity B (Modify Roof and Floor)

Start

Start Activity

FIGURE 3.6

Beginning AON Network for Hamilton Paper

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Chapter 3 Project Management 69

When we first draw a project network, it is not unusual that we place our nodes (activi- ties) in the network in such a fashion that the arrows (precedence relationships) are not straight lines. That is, the lines could be intersecting each other, and even facing in opposite directions. For example, if we had switched the location of the nodes for activities E and F in Figure 3.8, the lines from F to H and E to G would have intersected. Although such a project network is perfectly valid, it is good practice to have a well-drawn network. One rule that we especially recommend is to place the nodes in such a fashion that all arrows point in the same direction. To achieve this, we suggest that you first draw a rough draft of the network, making sure all the relationships are shown. Then you can redraw the network to make appropriate changes in the location of the nodes.

As with the unique starting node, it is convenient to have the project network finish with a unique ending node. In the Hamilton Paper example, it turns out that a unique activity, H, is the last activity in the project. We therefore automatically have a unique ending node.

In situations in which a project has multiple ending activities, we include a “dummy” ending activity. This dummy activity has all the multiple ending activities in the project as immediate predecessors. We illustrate this type of situation in Solved Problem 3.2 at the end of this chapter.

ACTIVITY-ON-ARROW EXAMPLE We saw earlier that in an AOA project network we can represent activities by arrows. A node represents an event, which marks the start or completion time of an activity. We usually identify an event (node) by a number.

3Draw the complete AOA project network for Hamilton Paper’s problem.

APPROACH c    Using the data from Table 3.1 in Example 1, draw one activity at a time, starting with A.

SOLUTION c  We see that activity A starts at event 1 and ends at event 2. Likewise, activity B starts at event 1 and ends at event 3. Activity C, whose only immediate predecessor is activity A, starts at node 2 and ends at node 4. Activity D, however, has two predecessors (i.e., A and B). Hence, we need both activities A and B to end at event 3, so that activity D can start at that event. However, we cannot have multiple activities with common starting and ending nodes in an AOA network. To overcome this diffi- culty, in such cases, we may need to add a dummy line (activity) to enforce the precedence relationship. The dummy activity, shown in Figure 3.9 as a dashed line, is inserted between events 2 and 3 to make the diagram reflect the precedence between A and D. The remainder of the AOA project network for Hamilton Paper’s example is also shown.

EXAMPLE

Activity-on-Arrow for Hamilton Paper

C

(Construct Stack)

(Pour Concrete/Install Frame)

D

(B u ild

B u rn

e r)

E

A

(B uil

d In

te rn

al

Co m

po ne

nt s)

B (M

odify Roof/Floor)

(Install Controls)

F

G

(In st

al l P

ol lu

tio n

De vic

e)

(Inspect/Test)

HDummy Activity

2 4

5

6 7

3

1

FIGURE 3.9

Complete AOA Network (With Dummy Activity) for Hamilton Paper

INSIGHT c  Dummy activities are common in AOA networks. They do not really exist in the project and take zero time.

LEARNING EXERCISE c    A new activity, Provincial approval, follows activity H. Add it to Figure 3.9. [Answer: Insert an arrowed line from node 7, which ends at a new node 8, and is labelled I (Provincial Approval).]

RELATED PROBLEMS c  3.4, 3.5, 3.9b

The dummy activity consumes no time, but note how it changes precedence. Now activity D cannot begin until both B and the dummy are complete.

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70 PART 1 Introduction to Operations Management

As mentioned earlier, the critical path is the longest time path through the network. To find the critical path, we calculate two distinct starting and ending times for each activity. These are defined as follows:

Earliest start (ES) 5 earliest time at which an activity can start, assuming all predecessors have been completed

Earliest finish (EF) 5 earliest time at which an activity can be finished Latest start (LS) 5 latest time at which an activity can start so as not to delay the

completion time of the entire project Latest finish (LF) 5 latest time by which an activity has to finish so as not to delay the

completion time of the entire project

We use a two-pass process, consisting of a forward pass and a backward pass, to determine these time schedules for each activity. The early start and finish times (ES and EF) are deter- mined during the forward pass. The late start and finish times (LS and LF) are determined during the backward pass.

FORWARD PASS To clearly show the activity schedules on the project network, we use the notation shown in Figure 3.10. The ES of an activity is shown in the top left corner of the node denoting that activ- ity. The EF is shown in the top right corner. The latest times, LS and LF, are shown in the bottom left and bottom right corners, respectively.

EARLIEST START TIME RULE Before an activity can start, all of its immediate predecessors must be finished:

• If an activity has only a single immediate predecessor, its ES equals the EF of the predecessor. • If an activity has multiple immediate predecessors, its ES is the maximum of all EF values of

its predecessors. That is,

ES 5 Max {EF of all immediate predecessors} (3-1)

LO3 Complete forward and backward passes for a project

Forward pass A process that identifies all the early start and early finish times.

Table 3.2 Time Estimates for Hamilton Paper Manufacturing

Activity Description Time (weeks)

A Build internal components 2

B Modify roof and floor 3

C Construct collection stack 2

D Pour concrete and install frame 4

E Build high-temperature burner 4

F Install pollution control system 3

G Install air pollution device 5

H Inspect and test 2

  Total time (weeks) 25

Determining the Project Schedule Look back at Figure 3.8 (in Example 2) for a moment to see Hamilton Paper’s completed AON project network. Once this project network has been drawn to show all the activities and their precedence relationships, the next step is to determine the project schedule. That is, we need to identify the planned starting and ending time for each activity.

Let us assume Hamilton Paper estimates the time required for each activity, in weeks, as shown in Table 3.2. The table indicates that the total time for all eight of the company’s activities is 25 weeks. However, since several activities can take place simultaneously, it is clear that the total project completion time may be less than 25 weeks. To find out just how long the project will take, we perform the critical path analysis for the network.

Critical path analysis A process to find the most effective sequence of activities that helps determine a project schedule.

We now add times to complete each activity. This lets us find the critical path.

STUDENT TIP

Does this mean the project will take 25 weeks to complete? No. Don’t forget that several of the activities are being performed at the same time. It would take 25 weeks if they were done sequentially.

STUDENT TIP

All predecessor activities must be completed before an activity can begin.

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Chapter 3 Project Management 71

EARLIEST FINISH RULE The earliest finish time (EF) of an activity is the sum of its earliest start time (ES) and its activity time. That is,

EF 5 ES 1 Activity time (3-2)

ES

Earliest Start

Earliest Finish

Activity Name or Symbol

Activity Duration

Latest Start

Latest Finish

A

2

LS

EF

LF

FIGURE 3.10

Notation Used in Nodes for Forward and Backward Passes

4 Calculate the earliest start and finish times for the activities in the Hamilton Paper Manufacturing project.

APPROACH c  Use Table 3.2, which contains the activity times. Complete the project network for the company’s project, along with the ES and EF values for all activities.

SOLUTION c  With the help of Figure 3.11, we describe how these values are calculated. Since activity Start has no predecessors, we begin by setting its ES to 0. That is, activity Start can

begin at time 0, which is the same as the beginning of week 1. If activity Start has an ES of 0, its EF is also 0, since its activity time is 0.

Next, we consider activities A and B, both of which have only Start as an immediate predecessor. Using the earliest start time rule, the ES for both activities A and B equals 0, which is the EF of activity Start. Now, using the earliest finish time rule, the EF for A is 2 (5 0 1 2), and the EF for B is 3 (5 0 1 3).

Since activity A precedes activity C, the ES of C equals the EF of A (5 2). The EF of C is therefore 4 (5 2 1 2).

We now come to activity D. Both activities A and B are immediate predecessors for B. Whereas A has an EF of 2, activity B has an EF of 3. Using the earliest start time rule, we compute the ES of activity D as follows:

ES of D 5 Max(EF of A, EF of B) 5 Max(2, 3) 5 3

The EF of D equals 7 (5 3 1 4). Next, both activities E and F have activity C as their only immedi- ate predecessor. Therefore, the ES for both E and F equals 4 (5 EF of C). The EF of E is 8 (5 4 1 4), and the EF of F is 7 (5 4 1 3).

Activity G has both activities D and E as predecessors. Using the earliest start time rule, its ES is therefore the maximum of the EF of D and the EF of E. Hence, the ES of activity G equals 8 (5 maxi- mum of 7 and 8), and its EF equals 13 (5 8 1 5).

Finally, we come to activity H. Since it also has two predecessors, F and G, the ES of H is the maxi- mum EF of these two activities. That is, the ES of H equals 13 (5 maximum of 13 and 7). This implies that the EF of H is 15 (5 13 1 2). Since H is the last activity in the project, this also implies that the earliest time in which the entire project can be completed is 15 weeks.

INSIGHT c  The ES of an activity that has only one predecessor is simply the EF of that predecessor. For an activity with more than one predecessor, we must carefully examine the EFs of all immediate predecessors and choose the largest one.

LEARNING EXERCISE c  A new activity I, Provincial Approval, takes one week. Its predecessor is activity H. What are I’s ES and EF? [Answer: 15, 16.]

RELATED PROBLEMS c  3.11, 3.14c

EXCEL OM Data File Ch03Ex4.xlsx can be found at MyLab Operations Management.

EXAMPLE

Computing Earliest Start and Finish Times for Hamilton Paper

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72 PART 1 Introduction to Operations Management

Although the forward pass allows us to determine the earliest project completion time, it does not identify the critical path. To identify this path, we need to now conduct the backward pass to determine the LS and LF values for all activities.

BACKWARD PASS Just as the forward pass began with the first activity in the project, the backward pass begins with the last activity in the project. For each activity, we first determine its LF value, followed by its LS value. The following two rules are used in this process.

LATEST FINISH TIME RULE This rule is again based on the fact that before an activity can start, all of its immediate predecessors must be finished:

• If an activity is an immediate predecessor for just a single activity, its LF equals the LS of the activity that immediately follows it.

• If an activity is an immediate predecessor to more than one activity, its LF is the minimum of all LS values of all activities that immediately follow it. That is:

LF 5 Min{LS of all immediate following activities} (3-3)

LATEST START TIME RULE The latest start time (LS) of an activity is the difference of its latest finish time (LF) and its activity time. That is:

LS 5 LF 2 Activity time (3-4)

Backward pass A process that identifies all the late start and late finish times.

0 A

ES of A

ES EF = Max(2,3)

LS LF

Activity Name

Activity Duration

ES = Max(EF of D, EF of E) = Max(7, 8) = 8

EF of A = ES of A + 2

ES of C = EF of A

2

2

0 B

3

3 8 G

5

13

13 H

2

15

4 F

3

7

2 C

2

4

3 D

4

7

4 E

4

80 Start

0

0

FIGURE 3.11 Earliest Start and Earliest Finish Times for Hamilton Paper

Calculate the latest start and finish times for each activity in Hamilton Paper’s pollution project.

APPROACH c  Figure 3.12 shows the complete project network for Hamilton Paper, along with LS and LF values for all activities. In what follows, we see how these values were calculated.

SOLUTION c  We begin by assigning an LF value of 15 weeks for activity H. That is, we specify that the latest finish time for the entire project is the same as its earliest finish time. Using the latest start time rule, the LS of activity H is equal to 13 (5 15 2 2).

Since activity H is the lone succeeding activity for both activities F and G, the LF for both F and G equals 13. This implies that the LS of G is 8 (5 13 2 5), and the LS of F is 10 (5 13 2 3).

EXAMPLE 5

Computing Latest Start and Finish Times for Hamilton Paper

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Chapter 3 Project Management 73

CALCULATING SLACK TIME AND IDENTIFYING THE CRITICAL PATH(S) After we have computed the earliest and latest times for all activities, it is a simple matter to find the amount of slack time2 that each activity has. Slack is the length of time an activity can be delayed without delaying the entire project. Mathematically:

Slack 5 LS 2 ES or Slack 5 LF 2 EF (3-5)

Slack time Free time for an activity.

We now consider activity A. We compute its LF as 2 (5 minimum of LS of C and LS of D). Hence, the LS of activity A is 0 (5 2 2 2). Finally, both the LF and LS of activity Start are equal to 0.

INSIGHT c  The LF of an activity that is the predecessor of only one activity is just the LS of that following activity. If the activity is the predecessor to more than one activity, its LF is the smallest LS value of all activities that follow immediately.

LEARNING EXERCISE c  A new activity I, Provincial approval, takes one week. Its predecessor is activity H. What are I’s LS and LF? [Answer: 15, 16.]

RELATED PROBLEMS c  3.11, 3.14c.

0 A

2

2

0 B

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2

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3

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80 Start

0

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0 0

0 2 LS

LF = Min(2,4) = 2

2 4

10 13

LF = Min(LS of E, LS of F) = Min(4,10) = 4

4 8

1 4 4 8

LS = LF – 4

8 13

LF = EF of Project

13 15

FIGURE 3.12

Latest Start and Finish Times Are Now Added

2 Slack time may also be referred to as free time, free float, or free slack.

6 Calculate the slack for the activities in the Hamilton Paper project.

APPROACH c  Start with the data in Figure 3.12 in Example 5 and develop Table 3.3 one line at a time.

SOLUTION c  Table 3.3 summarizes the ES, EF, LS, LF, and slack time for all of the firm’s activities. Activity B, for example, has one week of slack time since its LS is 1 and its ES is 0 (alternatively, its

EXAMPLE

Calculating Slack Times for Hamilton Paper

Proceeding in this fashion, we see that the LF of E is 8 (5 LS of G) and its LS is 4 (5 8 2 4). Likewise, the LF of D is 8 (5 LS of G) and its LS is 4 (5 8 2 4).

We now consider activity C, which is an immediate predecessor to two activities: E and F. Using the latest finish time rule, we compute the LF of activity C as follows:

LF of C 5 Min(LS of E, LS of F) 5 Min(4, 10) 5 4

The LS of C is computed as 2 (5 4 2 2). Next, we compute the LF of B as 4 (5 LS of D), and its LS as 1 (5 4 2 3).

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74 PART 1 Introduction to Operations Management

The activities with zero slack are called critical activities and are said to be on the critical path. The critical path is a continuous path through the project network that:

• Starts at the first activity in the project (Start in our example). • Terminates at the last activity in the project (H in our example). • Includes only critical activities (i.e., activities with no slack time).

LF is 4 and its EF is 3). This means that activity B can be delayed by up to one week, and the whole project can still be finished in 15 weeks.

On the other hand, activities A, C, E, G, and H have no slack time. This means that none of them can be delayed without delaying the entire project. Conversely, if plant manager Joni Steinberg wants to reduce the total project times, she will have to reduce the length of one of these activities.

Figure 3.13 shows the slack computed for each activity.

0 A

2

2

0 B

3

3 8 G

5

13

13 H

2

15

4 F

3

7

2 C

2

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4

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4 E

4

80 Start

0

0

0 0

0 2 2 4

10 13

4 8

1 4 4 8 8 13

13 15

Slack = 0

Slack = 0

Slack = 6

Slack = 1 Slack = 1

Slack = 0Slack = 0

Slack = 0

FIGURE 3.13

Slack Times Are Now Computed and Added

INSIGHT c  Slack may be computed from either early/late starts or early/late finishes. The key is to find which activities have zero slack.

LEARNING EXERCISE c  A new activity I, Provincial approval, follows activity H and takes one week. Is it on the critical path? [Answer: Yes, its LS 2 ES 5 0.]

RELATED PROBLEMS c  3.6, 3.11, 3.27

ACTIVE MODEL 3.1 This example is further illustrated in Active Model 3.1 at MyLab Operations Management.LO4 Determine a critical path

Table 3.3 Hamilton Paper’s Schedule and Slack Times

Activity Earliest Start ES

Earliest Finish EF

Latest Start LS

Latest Finish

Slack LS – ES

On Critical Path

A 0 2 0 2 0 Yes B 0 3 1 4 1 No C 2 4 2 4 0 Yes D 3 7 4 8 1 No E 4 8 4 8 0 Yes F 4 7 10 13 6 No G 8 13 8 13 0 Yes H 13 15 13 15 0 Yes

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Chapter 3 Project Management 75

TOTAL SLACK TIME Look again at the project network in Figure 3.14. Consider activities B and D, which have slack of one week each. Does it mean that we can delay each activity by one week, and still complete the project in 15 weeks? The answer is no.

Let’s assume that activity B is delayed by one week. It has used up its slack of one week and now has an EF of 4. This implies that activity D now has an ES of 4 and an EF of 8. Note that these are also its LS and LF values, respectively. That is, activity D also has no slack time now. Essentially, the slack of one week that activities B and D had is, for that path, shared between them. Delaying either activity by one week causes not only that activity, but also the other activ- ity, to lose its slack. This type of a slack time is referred to as total slack. Typically, when two or more noncritical activities appear successively in a path, they share total slack.

Variability in Activity Times In identifying all earliest and latest times so far, and the associated critical path(s), we have adopted the CPM approach of assuming that all activity times are known and fixed constants. That is, there is no variability in activity times. However, in practice, it is likely that activity completion times vary depending on various factors.

For example, building internal components (activity A) for Hamilton Paper Manufacturing is estimated to finish in two weeks. Clearly, factors such as late arrival of raw materials, absence of key personnel, and so on, could delay this activity. Suppose activity A actually ends up taking three weeks. Since A is on the critical path, the entire project will now be delayed by one week to 16 weeks. If we had anticipated completion of this project in 15 weeks, we would obviously miss our deadline.

Although some activities may be relatively less prone to delays, others could be extremely susceptible to delays. For example, activity B (modify roof and floor) could be heavily depend- ent on weather conditions. A spell of bad weather could significantly affect its completion time.

This means that we cannot ignore the impact of variability in activity times when deciding the schedule for a project. PERT addresses this issue.

Total slack Time shared among more than one activity.

Show Hamilton Paper’s critical path and find the project completion time.

APPROACH c  We use Table 3.3 and Figure 3.14. Figure 3.14 indicates that the total project com- pletion time of 15 weeks corresponds to the longest path in the network. That path is Start-A-C-E-G-H in network form. It is shown with thick blue arrows.

INSIGHT c  The critical path follows the activities with slack 5 0. This is considered the longest path through the network.

LEARNING EXERCISE c  Why are activities B, D, and F not on the path with the thick blue line? [Answer: They are not critical and have slack values of 1, 1, and 6 weeks, respectively.]

EXAMPLE 7

Showing Critical Path With Blue Arrows

RELATED PROBLEMS c  3.3, 3.4, 3.5, 3.6, 3.7, 3.12, 3.14b, 3.15, 3.17, 3.20a, 3.22a, 3.23, 3.26

0 A

2

2

0 B

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80 Start

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0 0

0 2 2 4

10 13

4 8

1 4 4 8 8 13

13 15

FIGURE 3.14

The Critical Path Is Now Shown in Five Thick Blue Lines

PERT’s ability to handle three time estimates for each activity enables us to compute the probability that we can complete the project by a target date.

STUDENT TIP

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76 PART 1 Introduction to Operations Management

THREE TIME ESTIMATES IN PERT In PERT, we employ a probability distribution based on three time estimates for each activity, as follows:

Optimistic time (a) 5 time an activity will take if everything goes as planned. In estimating this value, there should be only a small probability (say, 1/100) that the activity time will be less than a.

Pessimistic time (b) 5 time an activity will take assuming very unfavourable conditions. In estimating this value, there should also be only a small probability (also, 1/100) that the activity time will be greater than b.

Most likely time (m) 5 most realistic estimate of the time required to complete an activity.

When using PERT, we often assume that activity time estimates follow the beta probability distribution (see Figure 3.15). This continuous distribution is often appropriate for determining the expected value and variance for activity completion times.

To find the expected activity time, t, the beta distribution weights the three time estimates as follows:

t 5 (a 1 4m 1 b)>6 (3-6) That is, the most likely time (m) is given four times the weight as the optimistic time (a) and

pessimistic time (b). The time estimate t computed using Equation 3-6 for each activity is used in the project network to compute all earliest and latest times.

Optimistic time The “best” activity completion time that could be obtained in a PERT network.

Pessimistic time The “worst” activity time that could be expected in a PERT network.

Most likely time The most probable time to complete an activity in a PERT network.

Optimistic Time (a)

Most Likely Time (m)

Pessimistic Time (b)

Activity Time

P ro

b a b ili

ty

Probability of 1 in 100 of occurring< a

Probability of 1 in 100 of occurring> b

FIGURE 3.15

Beta Probability Distribution With Three Time Estimates

To plan, monitor, and control the huge number of details involved in sponsoring a rock festival attended by more than 100 000 fans, man- agers use Microsoft Project and the tools discussed in this chapter. The Video Case Study “Managing Hard Rock’s Rockfest,” at the end of the chapter, provides more details of the management task.

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Chapter 3 Project Management 77

PROBABILITY OF PROJECT COMPLETION The critical path analysis helped us determine that Hamilton Paper’s expected project comple- tion time is 15 weeks. Joni Steinberg knows, however, that there is significant variation in the time estimates for several activities. Variation in activities that are on the critical path can affect the overall project completion time—possibly delaying it. This is one occurrence that worries the plant manager considerably.

PERT uses the variance of critical path activities to help determine the variance of the overall project. Project variance is computed by summing variances of critical activities:

s2p = Project variance = a (variances of activities on critical path) (3-8)

3 This formula is based on the statistical concept that from one end of the beta distribution to the other is 6 standard deviations (63 standard deviations from the mean). Since (b 2 a) is 6 standard deviations, the variance is [(b 2 a)/6]2.

8 Joni Steinberg and the project management team at Hamilton Paper want an expected time and vari- ance for activity F (Installing the pollution control system) where:

a 5 1 week, m 5 2 weeks, b 5 9 weeks

APPROACH c  Use Equations 3-6 and 3-7 to compute the expected time and variance for F.

SOLUTION c  The expected time for activity F is:

t = a + 4m + b

6 =

1 + 4 ( 2) + 9 6

= 18 6

= 3 weeks

The variance for activity F is:

Variance = c ( b - a) 6

d 2

= c ( 9 - 1) 6

d 2

= a 8 6 b

2

= 64 36

= 1.78

INSIGHT c    Steinberg now has information that allows her to understand and manage activity F. The expected time is, in fact, the activity time used in our earlier computation and identification of the critical path.

LEARNING EXERCISE c  Review the expected times and variances for all of the other activities in the project. These are shown in Table 3.4.

LO5 Calculate the variance of activity times

EXAMPLE

Expected Times and Variances for Hamilton Paper

Table 3.4 Time Estimates (in Weeks) for Hamilton Paper’s Project

Activity Optimistic

a

Most Likely

m Pessimistic

b Expected Time

t 5 (a 1 4m 1 b)/6 Variance

[(b 2 a)/6]2

A 1 2 3 2 [(3 2 1)/6]2 5 4/36 5 0.11

B 2 3 4 3 [(4 2 2)/6]2 5 4/36 5 0.11

C 1 2 3 2 [(3 2 1)/6]2 5 4/36 5 0.11

D 2 4 6 4 [(6 2 2)/6]2 5 16/36 5 0.44

E 1 4 7 4 [(7 2 1)/6]2 5 36/36 5 1.00

F 1 2 9 3 [(9 2 1)/6]2 5 64/36 5 1.78

G 3 4 11 5 [(11 2 3)/6]2 5 64/36 5 1.78

H 1 2 3 2 [(3 2 1)/6]2 5 4/36 5 0.11

RELATED PROBLEMS c  3.13, 3.14a, 3.17ab, 3.21a

EXCEL OM Data File Ch03Ex8.xlsx can be found at MyLab Operations Management.

To compute the dispersion or variance of activity completion time, we use the formula:3

Variance [(b 2 a)>6]2 (3-7)

Can you see why the variance is higher in some activities than in others? Note the spread between the optimistic and pessimistic times.

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78 PART 1 Introduction to Operations Management

Hamilton Paper’s managers now wish to know the project’s variance and standard deviation.

APPROACH c  Because the activities are independent, we can add the variances of the activities on the critical path and then take the square root to determine the project’s standard deviation.

SOLUTION c    From Example 8 (Table 3.4), we have the variances of all of the activities on the critical path. Specifically, we know that the variance of activity A is 0.11, variance of activity C is 0.11, variance of activity E is 1.00, variance of activity G is 1.78, and variance of activity H is 0.11.

Compute the total project variance and project standard deviation:

Project variance s2p = 0.11 + 0.11 + 1.00 + 1.78 + 0.11 = 3.11

which implies:

Project standard deviation ( sP ) = 2Project variance = 23.11 = 1.76 weeks INSIGHT c  Management now has an estimate not only of expected completion time for the project but also of the standard deviation of that estimate.

LEARNING EXERCISE c  If the variance for activity A is actually 0.30 (instead of 0.11), what is the new project standard deviation? [Answer: 1.817.]

RELATED PROBLEM c  3.17e

EXAMPLE 9

Computing Project Variance and Standard Deviation for Hamilton Paper

How can this information be used to help answer questions regarding the probability of fin- ishing the project on time? PERT makes two more assumptions: (1) total project completion times follow a normal probability distribution, and (2) activity times are statistically independ- ent. With these assumptions, the bell-shaped normal curve shown in Figure 3.16 can be used to

Standard Deviation = 1.76 Weeks

15 Weeks

(Expected Completion Time)

FIGURE 3.16

Probability Distribution for Project Completion Times at Hamilton Paper

This ship is being built at the Hyundai shipyard, Asia’s largest shipbuilder, in Korea. Managing this project uses the same techniques as managing the remodelling of a store or installing a new production line.

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Chapter 3 Project Management 79

represent project completion dates. This normal curve implies that there is a 50% chance that the manufacturer’s project completion time will be less than 15 weeks and a 50% chance that it will exceed 15 weeks.

10 Joni Steinberg would like to find the probability that her project will be finished on or before the 16-week provincial deadline.

APPROACH c  To do so, she needs to determine the appropriate area under the normal curve. This is the area to the left of the 16th week.

SOLUTION c  The standard normal equation can be applied as follows:

Z = ( Due date - Expected date of completion) >sp (3-9) = ( 16 weeks - 15 weeks ) >1.76 weeks = 0.57

where Z is the number of standard deviations the due date or target date lies from the mean or expected date.

Referring to the Normal Table in Appendix I, we find a Z-value of 0.57 to the right of the mean indicates a probability of 0.7157. Thus, there is a 71.57% chance that the pollution control equipment can be put in place in 16 weeks or less. This is shown in Figure 3.17.

EXAMPLE

Probability of Completing a Project on Time

15 Weeks

16 Weeks

0.57 Standard Deviations

Time

Probability (T ≤ 16 Weeks) is 71.57%

FIGURE 3.17

Probability That Hamilton Paper Will Meet the 16-Week Deadline

INSIGHT c  The shaded area to the left of the 16th week (71.57%) represents the probability that the project will be completed in less than 16 weeks.

LEARNING EXERCISE c  What is the probability that the project will be completed on or before the 17th week? [Answer: About 87.2%.]

RELATED PROBLEMS c  3.14d, 3.17f, 3.21de, 3.22b, 3.24

DETERMINING PROJECT COMPLETION TIME FOR A GIVEN CONFIDENCE LEVEL Let’s say Joni Steinberg is worried that there is only a 71.57% chance that the pollution control equipment can be put in place in 16 weeks or less. She thinks that it may be possible to plead with the environ- mental group for more time. However, before she approaches the group, she wants to arm herself with sufficient information about the project. Specifically, she wants to find the deadline by which she has a 99% chance of completing the project. She hopes to use her analysis to convince the group to agree to this extended deadline.

Clearly, this due date would be greater than 16 weeks. However, what is the exact value of this new due date? To answer this question, we again use the assumption that Hamilton Paper’s project completion time follows a normal probability distribution with a mean of 15 weeks and a standard deviation of 1.76 weeks.

11 Joni Steinberg wants to find the due date that gives her company’s project a 99% chance of on-time completion.

APPROACH c    She first needs to compute the Z-value corresponding to 99%, as shown in Figure 3.18. Mathematically, this is similar to Example 10, except the unknown is now Z rather than the due date.

EXAMPLE

Computing Probability for Any Completion Date

Here is a chance to review your statistical skills and use of a normal distribution table (Appendix I).

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80 PART 1 Introduction to Operations Management

VARIABILITY IN COMPLETION TIME OF NONCRITICAL PATHS In our discussion so far, we have focused exclusively on the variability in the completion times of activities on the critical path. This seems logical since these activities are, by definition, the more important activities in a project network. However, when there is variability in activity times, it is important that we also investigate the variability in the completion times of activities on noncritical paths.

Consider, for example, activity D in Hamilton Paper’s project. Recall from Figure 3.14 in Example 7 that this is a noncritical activity, with a slack time of one week. We have therefore not considered the variability in D’s time in computing the probabilities of project completion times. We observe, however, that D has a variance of 0.44 (see Table 3.4 in Example 8). In fact, the pessimistic completion time for D is six weeks. This means that if D ends up taking its pessimis- tic time to finish, the project will not finish in 15 weeks, even though D is not a critical activity.

For this reason, when we find probabilities of project completion times, it may be necessary for us not to focus only on the critical path(s). Indeed, some research has suggested that expend- ing project resources to reduce the variability of activities not on the critical path can be an effective element in project management.4 We may need also to compute these probabilities for noncritical paths, especially those that have relatively large variances. It is possible for a non- critical path to have a smaller probability of completion within a due date, when compared with the critical path. Determining the variance and probability of completion for a noncritical path is done in the same manner as Examples 9 and 10.

WHAT PROJECT MANAGEMENT HAS PROVIDED SO FAR Project management techniques have thus far been able to provide Joni Steinberg with several valuable pieces of management information:

1. The project’s expected completion date is 15 weeks. 2. There is a 71.57% chance that the equipment will be in place within the 16-week deadline.

PERT analysis can easily find the probability of finishing by any date Steinberg is interested in.

SOLUTION c  Referring again to the Normal Table in Appendix I, we identify a Z-value of 2.33 as being closest to the probability of 0.99. That is, Steinberg’s due date should be 2.33 standard deviations above the mean project completion time. Starting with the standard normal equation (see Equation 3-9), we can solve for the due date and rewrite the equation as:

Due date = Expected completion time + ( Z * sp ) = 15 + ( 2.33 * 1.76) = 19.1 weeks

(3-10)

INSIGHT c    If Steinberg can get the environmental group to agree to give her a new deadline of 19.1 weeks (or more), she can be 99% sure of finishing the project on time.

LEARNING EXERCISE c  What due date gives the project a 95% chance of on-time completion? [Answer: About 17.9 weeks.]

RELATED PROBLEMS c  3.22c, 3.24e

0 2.33 Z2.33 Standard

Deviations

Probability of 0.99

Probability of 0.01

FIGURE 3.18

Z-Value for 99% Probability of Project Completion at Hamilton Paper

4 F. M. Pokladnik, T. F. Anthony, R. R. Hill, and G. Ulrich, “A Fresh Look at Estimated Project Duration: Noncritical Path Activity Contribution to Project Variance in PERT/CPM,” Proceedings of the 2003 Southwest Decision Science Conference, Houston.

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Chapter 3 Project Management 81

3. Five activities (A, C, E, G, and H) are on the critical path. If any one of these is delayed for any reason, the entire project will be delayed.

4. Three activities (B, D, and F) are not critical and have some slack time built in. This means that Steinberg can borrow from their resources, and, if necessary, she may be able to speed up the whole project.

5. A detailed schedule of activity starting and ending dates, slack, and critical path activities has been made available (see Table 3.3 in Example 6).

Cost–Time Trade-Offs and Project Crashing While managing a project, it is not uncommon for a project manager to be faced with either (or both) of the following situations: (1) the project is behind schedule, and (2) the scheduled project completion time has been moved forward. In either situation, some or all of the remaining activ- ities need to be speeded up (usually by adding resources) to finish the project by the desired due date. The process by which we shorten the duration of a project in the cheapest manner possible is called project crashing.

The critical path method (CPM) is a technique in which each activity has a normal or stand- ard time that we use in our computations. Associated with this normal time is the normal cost of the activity. However, another time in project management is the crash time, which is defined as the shortest duration required to complete an activity. Associated with this crash time is the crash cost of the activity. Usually, we can shorten an activity by adding extra resources (e.g., equipment, people) to it. Hence, it is logical for the crash cost of an activity to be higher than its normal cost.

The amount by which an activity can be shortened (i.e., the difference between its normal time and crash time) depends on the activity in question. We may not be able to shorten some activities at all. For example, if a casting needs to be heat-treated in the furnace for 48 hours, adding more resources does not help shorten the time. In contrast, we may be able to shorten some activities significantly (e.g., frame a house in three days instead of 10 days by using three times as many workers).

Likewise, the cost of crashing (or shortening) an activity depends on the nature of the activity. Managers are usually interested in speeding up a project at the least additional cost. Hence, when choosing which activities to crash, and by how much, we need to ensure the following:

• The amount by which an activity is crashed is, in fact, permissible. • Taken together, the shortened activity durations will enable us to finish the project by the due

date. • The total cost of crashing is as small as possible.

Crashing a project involves four steps:

STEP 1: Compute the crash cost per week (or other time period) for each activity in the net- work. If crash costs are linear over time, the following formula can be used:

Crash cost per period = (Crash cost - Normal cost) (Normal time - Crash time)

(3-11)

STEP 2: Using the current activity times, find the critical path(s) in the project network. Identify the critical activities.

STEP 3: If there is only one critical path, then select the activity on this critical path that (a) can still be crashed and (b) has the smallest crash cost per period. Crash this activity by one period.

If there is more than one critical path, then select one activity from each critical path such that (a) each selected activity can still be crashed and (b) the total crash cost per period of all selected activities is the smallest. Crash each activity by one period. Note that the same activity may be common to more than one critical path.

STEP 4: Update all activity times. If the desired due date has been reached, stop. If not, return to Step 2.

Crashing Shortening activity time in a network to reduce time on the critical path so total completion time is reduced.

LO6 Crash a project

When a project needs to be shortened, we want to find the most economical way of “crashing” it.

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82 PART 1 Introduction to Operations Management

We illustrate project crashing in Example 12.

Suppose that Hamilton Paper Manufacturing has been given only 13 weeks (instead of 16 weeks) to install the new pollution control equipment or face a court-ordered shutdown. As you recall, the length of Joni Steinberg’s critical path was 15 weeks, but she must now complete the project in 13 weeks.

APPROACH c  Steinberg needs to determine which activities to crash, and by how much, to meet this 13-week due date. Naturally, Steinberg is interested in speeding up the project by two weeks, at the least additional cost.

SOLUTION c  The company’s normal and crash times, and normal and crash costs, are shown in Table 3.5. Note, for example, that activity B’s normal time is three weeks (the estimate used in com- puting the critical path), and its crash time is one week. This means that activity B can be shortened by up to two weeks if extra resources are provided. The cost of these additional resources is $4000 (5 difference between the crash cost of $34 000 and the normal cost of $30 000). If we assume that the crashing cost is linear over time (i.e., the cost is the same each week), activity B’s crash cost per week is $2000 (5 $4000/2).

EXAMPLE 12

Project Crashing to Meet a Deadline at Hamilton Paper

Table 3.5 Normal and Crash Data for Hamilton Paper Manufacturing

  Time (Weeks) Cost ($)    

Activity Normal Crash Normal Crash Crash Cost

per Week ($) Critical Path?

A 2 1 22 000 22 750 750 Yes

B 3 1 30 000 34 000 2 000 No

C 2 1 26 000 27 000 1 000 Yes

D 4 3 48 000 49 000 1 000 No

E 4 2 56 000 58 000 1 000 Yes

F 3 2 30 000 30 500 500 No

G 5 2 80 000 84 500 1 500 Yes

H 2 1 16 000 19 000 3 000 Yes

This calculation for activity B is shown in Figure 3.19. Crash costs for all other activities can be computed in a similar fashion.

1

$30 000

Activity Cost

$31 000

$32 000

$33 000

$34 000

2 3

Crash

Normal

Crash Cost/Week = Crash Cost – Normal Cost Normal Time – Crash Time

= $34 000 – $30 000 3 – 1

= $4000 2 Weeks

= $2000/Week

Time (Weeks)

Crash Time Normal Time

Normal Cost

Crash Cost

FIGURE 3.19

Crash and Normal Times and Costs for Activity B

Steps 2, 3, and 4 can now be applied to reduce Hamilton Paper’s project completion time at a mini- mum cost. We show the project network for Hamilton Paper again in Figure 3.20.

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Chapter 3 Project Management 83

The current critical path (using normal times) is Start-A-C-E-G-H, in which Start is just a dummy starting activity. Of these critical activities, activity A has the lowest crash cost per week of $750. Joni Steinberg should therefore crash activity A by one week to reduce the project completion time to 14 weeks. The cost is an additional $750. Note that activity A cannot be crashed any further, since it has reached its crash limit of one week.

At this stage, the original path Start-A-C-E-G-H remains critical with a completion time of 14 weeks. However, a new path Start-B-D-G-H is also critical now, with a completion time of 14 weeks. Hence, any further crashing must be done to both critical paths.

On each of these critical paths, we need to identify one activity that can still be crashed. We also want the total cost of crashing an activity on each path to be the smallest. We might be tempted to simply pick the activities with the smallest crash cost per period in each path. If we did this, we would select activity C from the first path and activity D from the second path. The total crash cost would then be $2000 (5 $1000 1 $1000).

But we spot that activity G is common to both paths. That is, by crashing activity G, we will simul- taneously reduce the completion time of both paths. Even though the $1500 crash cost for activity G is higher than that for activities C and D, we would still prefer crashing G, since the total crashing cost will now be only $1500 (compared with the $2000 if we crash C and D).

INSIGHT c  To crash the project down to 13 weeks, Steinberg should crash activity A by one week, and activity G by one week. The total additional cost will be $2250 (5 $750 1 $1500). This is impor- tant because many contracts for projects include bonuses or penalties for early or late finishes.

LEARNING EXERCISE c  Say the crash cost for activity B is $31 000 instead of $34 000. How does this change the answer? [Answer: No change.]

RELATED PROBLEMS c  3.16, 3.18, 3.19, 3.20, 3.25

EXCEL OM Data File Ch03Ex12.xlsx can be found at MyLab Operations Management.

0 A

Activity Name

2

2

0 B

3

3 8 G

5

13

4 E

4

8 13 H

2

15

4 F

3

7

2 C

2

4

3 D

4

7

0 2

EFES

2 4

10 13

4 8

1 4 4 8 8 13

13 15

LS

Slack = 0 LF

Slack = 0

Slack = 6

Activity Duration

Slack = 1 Slack = 1 Slack = 0

Slack = 0 Slack = 0

0 Start

0

0

0 0

FIGURE 3.20

Critical Path and Slack Times for Hamilton Paper

A Critique of PERT and CPM As a critique of our discussions of PERT, here are some of its features about which operations managers need to be aware:

ADVANTAGES

1. Especially useful when scheduling and controlling large projects. 2. Straightforward concept and not mathematically complex. 3. Graphical networks help highlight relationships among project activities.

Every technique has shortfalls as well as strengths. It is important to know both.

STUDENT TIP

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84 PART 1 Introduction to Operations Management

4. Critical path and slack time analyses help pinpoint activities that need to be closely watched. 5. Project documentation and graphs point out who is responsible for various activities. 6. Applicable to a wide variety of projects. 7. Useful in monitoring not only schedules but costs as well.

LIMITATIONS 1. Project activities have to be clearly defined, independent, and stable in their relationships. 2. Precedence relationships must be specified and networked together. 3. Time estimates tend to be subjective and are subject to fudging by managers who fear the

dangers of being overly optimistic or not pessimistic enough. 4. There is the inherent danger of placing too much emphasis on the longest, or critical, path.

Near-critical paths need to be monitored closely as well.

Using Microsoft Project to Manage Projects The approaches discussed so far are effective for managing small projects. However, for large or complex projects, specialized project management software is much preferred. In this section, we provide a brief introduction to the most popular example of such specialized software, Microsoft Project. A time-limited version of Microsoft Project may be requested directly from Microsoft.

Microsoft Project is extremely useful in drawing project networks, identifying the project schedule, and managing project costs and other resources.

ENTERING DATA Let us again consider the Hamilton Paper Manufacturing project. Recall that this project has eight activities (repeated in the margin). The first step is to define the activities and their prec- edence relationships. To do so, we select File|New to open a blank project. We type the project start date (as July 1), then enter all activity information (see Program 3.1). For each activity (or task, as Microsoft Project calls it), we fill in the name and duration. The description of the activ- ity is also placed in the Task Name column in Program 3.1. As we enter activities and durations, the software automatically inserts start and finish dates.

Due to its rapidly expanding economy and steady growth, China has been striving to rebuild its infrastruc- ture and utilities. Among these many needs is a require- ment for a robust and stable electricity grid. To meet the demand for electricity, China contracted Atomic Energy of Canada Limited (AECL) in order to construct two 728 megawatt CANDU reactors at Qinshan in the eastern part of the country (roughly 125 km south of Shanghai). The project was mutually beneficial to both countries. In particular, China was able to secure a contract with an organization with a proven track record, while Canada was fortunate to export human and physical resources for a high-profile project and derive significant revenue and goodwill.

Largely thanks to excellent project management, the project was completed four months ahead of schedule and under budget. Currently, the project has the record for the shortest construction schedule ever completed

for a nuclear power plant in that country. In fact, several significant milestones were achieved and records were set. These include:

• The first CANDU unit (Unit 1) was operating commer- cially 43 days ahead of schedule and was the first of its kind ever built in China.

• Unit 1 also boasted the shortest construction period for a nuclear plant in the country (54 months).

• Unit 2 was launched into commercial operation 112 days ahead of plan.

• The entire project was completed 10% below budget.

The foregoing demonstrates the value of good planning and solid project management. The benefits are tangible to all stakeholders.

Source: www.cna.ca.

Rebuilding the Electricity Grid in ChinaOM in Action

Hamilton Paper Co. Activities

Activity Time

(weeks) Prede- cessors

A 2 — B 3 — C 2 A D 4 A, B E 4 C F 3 C G 5 D, E H 2 F, G

Now that you understand the workings of PERT and CPM, you are ready to master this useful program. Knowing such software gives you an edge over others in the job market.

STUDENT TIP

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Chapter 3 Project Management 85

The next step is to define precedence relationships between these activities. To do so, we enter the relevant activity numbers (e.g., 1, 2) in the Predecessors column.

VIEWING THE PROJECT SCHEDULE When all links have been defined, the complete project schedule can be viewed as a Gantt chart. We can also select View|Network Diagram to view the schedule as a project network (shown in Program 3.2). The critical path is shown in red on the screen in the network diagram. We can click on any of the activities in the project network to view details of the activities. Likewise, we can easily add or remove activities from the project network. Each time we do so, Microsoft

Project will finish on Friday, 10/14.

View has been zoomed out to show weeks.

Click here to select different views.

Gantt chart view.

PROGRAM 3.1 Gantt Chart in Microsoft Project for Hamilton Paper Manufacturing

Source: Courtesy of Microsoft Corporation.

Critical path and activities (A, C, E, G, and H) are shown in red.

Click activity to see details regarding the activity.

Project network view.

PROGRAM 3.2 Project Network in Microsoft Project for Hamilton Paper Manufacturing

Source: Courtesy of Microsoft Corporation.

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86 PART 1 Introduction to Operations Management

Project automatically updates all start dates, finish dates, and the critical path(s). If desired, we can manually change the layout of the network (e.g., reposition activities) by changing the options in Format|Layout.

Programs 3.1 and 3.2 show that if Hamilton Paper’s project starts July 1, it can be finished on October 14. The start and finish dates for all activities are also clearly identified. Project management software, we see, can greatly simplify the scheduling procedures discussed earlier in this chapter.

PERT ANALYSIS Microsoft Project does not perform the PERT probability calculations discussed in Examples 10 and 11. However, by clicking View|Toolbars|PERT Analysis, we can get Microsoft Project to allow us to enter optimistic, most likely, and pessimistic times for each activity. We can then choose to view Gantt charts based on any of these three times for each activity.

TRACKING THE TIME STATUS OF A PROJECT Perhaps the biggest advantage of using software to manage projects is that it can track the pro- gress of the project. In this regard, Microsoft Project has many features available to track indi- vidual activities in terms of time, cost, resource usage, and so on.

An easy way to track the time progress of tasks is to enter the percent of work completed for each task. One way to do so is to double-click on any activity in the Task Name column in Program 3.1. A window is displayed that allows us to enter the percent of work completed for each task.

The table in the margin provides data regarding the percent of each of Hamilton Paper’s activities as of today. (Assume that today is Friday, August 12, that is, the end of the sixth week of the project schedule.)

Pollution Project Percentage Completed

on Aug. 12

Activity Completed

A 100

B 100

C 100

D 10

E 20

F 20

G 0

H 0

Activity F is behind schedule, as are activities D and E.

Check mark indicates activity is 100% complete.

This is the indicator for today’s date (Aug. 12).

Bar indicates activity process.

PROGRAM 3.3 Tracking Project Progress in Microsoft Project

Source: Courtesy of Microsoft Corporation.

As shown in Program 3.3, the Gantt chart immediately reflects this updated information by drawing a thick line within each activity’s bar. The length of this line is proportional to the per- cent of that activity’s work that has been completed.

How do we know if we are on schedule? Notice that there is a vertical line shown on the Gantt chart corresponding to today’s date. Microsoft Project will automatically move this line to correspond with the current date. If the project is on schedule, we should see all bars to the left of today’s line indicate that they have been completed. For example, Program 3.3 shows that activities A, B, and C are on schedule. In contrast, activities D, E, and F appear to be behind schedule. These activities need to be investigated further to determine the reason for the delay. This type of easy visual information is what makes such software so useful in practice for project management.

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Chapter 3 Project Management 87

PERT, CPM, and other scheduling techniques have proven to be valuable tools in controlling large and complex projects. Managers use such techniques to segment projects into dis- crete activities (work breakdown structures), identifying spe- cific resources and time requirements for each. With PERT and CPM, managers can understand the status of each activ- ity, including its earliest start, latest start, earliest finish, and latest finish (ES, LS, EF, and LF) times. By controlling the trade-off between ES and LS, managers can identify the activ- ities that have slack and can address resource allocation, per- haps by smoothing resources. Effective project management also allows managers to focus on the activities that are critical to timely project completion. By understanding the project’s

critical path, they know where crashing makes the most eco- nomic sense.

Good project management also allows firms to effi- ciently create products and services for global markets and to respond effectively to global competition. Microsoft Project, illustrated in this chapter, is one of a wide variety of software packages available to help managers handle network model- ling problems.

The models described in this chapter require good man- agement practices, detailed work breakdown structures, clear responsibilities assigned to activities, and straightforward and timely reporting systems. All are critical parts of project man- agement.

CHAPTER SUMMARY

Two examples of massively mismanaged projects are TAURUS and the Canadian federal government long-gun registry. The first, for- mally called the London Stock Exchange Automation Project, cost U.S. $575 million before it was finally abandoned. Although most IT projects have a reputation for cost overruns, delays, and underper- formance, TAURUS set a new standard.

As unfortunate as the TAURUS case may be, the Canadian fed- eral government’s long-gun registry was worse. In addition to the registry being a divisive issue and its value being questioned, the

costs of implementing and maintaining the system mushroomed out of control. Taxpayers were initially expected to contribute $2 million of the budget while registration fees were expected to cover the remaining costs. By the time the registry was scrapped in 2012, esti- mates of the cost of the program exceeded $1 billion.

Read about one of these two projects (or another of your choice) and explain why it faced such problems. How and why do project managers allow such massive endeavours to fall into such a state? What do you think are the causes?

ETHICAL DILEMMA

Discussion Questions

1. Give an example of a situation in which project management is needed.

2. Explain the purpose of project organization. 3. What are the three phases involved in the management of a

large project? 4. What are some of the questions that can be answered with

PERT and CPM? 5. Define work breakdown structure. How is it used? 6. What is the use of Gantt charts in project management? 7. What is the difference between an activity-on-arrow (AOA)

network and an activity-on-node (AON) network? Which is primarily used in this chapter?

8. What is the significance of the critical path? 9. What would a project manager have to do to crash an activity? 10. Describe how expected activity times and variances can be

computed in a PERT network. 11. Define early start, early finish, late finish, and late start

times.

12. Students are sometimes confused by the concept of critical path and want to believe that it is the shortest path through a net- work. Convincingly explain why this is not so.

13. What are dummy activities? Why are they used in activity- on-arrow (AOA) project networks?

14. What are the three time estimates used with PERT? 15. Would a project manager ever consider crashing a noncritical

activity in a project network? Explain convincingly. 16. How is the variance of the total project computed in PERT? 17. Describe the meaning of slack, and discuss how it can be deter-

mined. 18. How can we determine the probability that a project will be

completed by a certain date? What assumptions are made in this computation?

19. Name some of the widely used project management software programs.

20. What is the difference between the waterfall approach and agile project management?

We encourage you to download a time-limited version of Microsoft Project directly from Microsoft and to create a project network for work you are currently doing.

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88 PART 1 Introduction to Operations Management

Using Software to Solve Project Management Problems

In addition to the Microsoft Project software just illustrated, both Excel OM and POM for Windows are available to readers of this text as project management tools.

X USING EXCEL OM Excel OM has a Project Scheduling module. Program 3.4 uses the data from the Hamilton Paper Manufacturing example in this chapter (see Examples 4 and 5). The PERT/CPM analysis also handles activities with three time estimates.

P USING POM FOR WINDOWS The POM for Windows Project Scheduling module can also find the expected project completion time for a CPM and PERT network with either one or three time estimates. POM for Windows also performs project crashing. For further details, refer to Appendix IV.

Early start is the maximum of the computations below.

Late finishes depend on the tasks that precede the given task. The late finish is the earliest of the dependencies.

Enter the task names, times, and the names of the precedences. Be careful that the precedence names match the task names.

Hamilton Paper

EF = ES + task time.

Late start is the late finish (from below) minus the task time.

PROGRAM 3.4 Excel OM’s Use of Hamilton Paper Manufacturing’s Data from Examples 4 and 5

Source: Courtesy of Microsoft Corporation.

Solved Problems Virtual Office Hours help is available at MyLab Operations Management.

. SOLVED PROBLEM 3.1 Construct an AON network based on the following:

Activity Immediate

Predecessor(s)

A —

B —

C —

D A, B

E C

. SOLUTION

End

D

E

B

A

C

Start

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Chapter 3 Project Management 89

. SOLVED PROBLEM 3.2 Insert a dummy activity and event to correct the following AOA network:

. SOLUTION Since we cannot have two activities starting and ending at the same node, we add the following dummy activity and dummy event to obtain the correct AOA network:

3 days

5 days

2

3

4

51

5 Dummy activity

2 3

4

1

Dummy event

(0 days)

3 d ays

5 days

. SOLVED PROBLEM 3.3 Calculate the critical path, project completion time T, and project variance s2p based on the following AON network information:

. SOLUTION We conclude that the critical path is Start–A–C–E–G–End:

Total project time 5 T 5 2 1 2 1 4 1 5 5 13

andActivity Time Variance ES EF LS LF Slack

A 2 2 6

0 2 0 2 0

B 3 2 6

0 3 1 4 1

C 2 4 6

2 4 2 4 0

D 4 4 6

3 7 4 8 1

E 4 2 6

4 8 4 8 0

F 3 1 6

4 7 10 13 6

G 5 1 6

8 13 8 13 0

Start End E G

A

B

FC

D

s2p = a Variances on the critical path = 26 + 4 6

+ 2 6

+ 1 6 =

9 6 = 1.5

. SOLVED PROBLEM 3.4 To complete the wing assembly for an experimental aircraft, Jim Gilbert has laid out the seven major activities involved. These activities have been labelled A through G in the following table, which also shows their estimated completion times (in weeks) and immediate predecessors. Determine the expected time and vari- ance for each activity:

. SOLUTION Expected times and variances can be computed using Equations (3-6) and (3-7). The results are summarized in the following table:

Activity a m b Immediate

Predecessors

A 1 2 3 — B 2 3 4 — C 4 5 6 A D 8 9 10 B E 2 5 8 C, D F 4 5 6 D G 1 2 3 E

Activity Expected Time

(in weeks) Variance

A 2 1 9

B 3 1 9

C 5 1 9

D 9 1 9

E 5 1

F 5 1 9

G 2 1 9

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90 PART 1 Introduction to Operations Management

. SOLVED PROBLEM 3.5 Referring to Solved Problem 3.4, now Jim Gilbert would like to determine the critical path for the entire wing assembly project as well as the expected completion time for the total project. In addi- tion, he would like to determine the earliest and latest start and finish times for all activities.

. SOLUTION The AON network for Gilbert’s project is shown in Figure 3.21. Note that this project has multiple activities (A and B) with no immediate predecessors, and multiple activities (F and G) with no successors. Hence, in addition to a unique starting activity (Start), we have included a unique finishing activity (End) for the project.

Figure 3.21 shows the earliest and latest times for all activi- ties. The results are also summarized in the following table:

The activities along the critical path are B, D, E, and G. These activities have zero slack as shown in the table.

. SOLVED PROBLEM 3.6 The following information has been computed from a project:

Expected total project time = T = 62 weeks Project variance ( s2p ) = 81

What is the probability that the project will be completed 18 weeks before its expected completion date?

. SOLUTION The desired completion date is 18 weeks before the expected completion date, 62 weeks. The desired completion date is 44 (or 62 – 18) weeks:

sp = 2Project variance Z =

Due date - Expected completion date sp

= 44 - 62

9 =

- 18 9

= - 2.0

The normal curve appears as follows:

Activity Time

Activity ES EF LS LF Slack

A 0 2 5 7 5

B 0 3 0 3 0

C 2 7 7 12 5

D 3 12 3 12 0

E 12 17 12 17 0

F 12 17 14 19 2

G 17 19 17 19 0

Expected project length 5 19 weeks Variance of the critical path 5 1.333

Standard deviation of the critical path 5 1.155 weeks

Activity Duration

Dummy Ending Activity

17 G

2

19

17 190 Start

0

0

0 A

Activity Name

2

2

0 B

3

3 12 F

5

17

19 End

0

19

12 E

5

172 C

5

7

3 D

9

12

0 0

5 7 7 12 12 17

0 3 3 12 14 19

19 19 Dummy Starting Activity

ES EF

LS LF

FIGURE 3.21

Critical Path for Solved Problem 3.5

T = 62Due date = 44

Because the normal curve is symmetrical and table values are cal- culated for positive values of Z, the area desired is equal to 1 2 (table value). For Z = + 2.0, the area from the table is 0.97725. Thus, the area corresponding to a Z-value of 22.0 is 0.02275 (or 1 2 0.97725). Hence, the probability of completing the project 18 weeks before the expected completion date is approximately 0.023, or 2.3%.

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Chapter 3 Project Management 91

. SOLVED PROBLEM 3.7 Determine the least cost of reducing the project completion date by three months based on the following information:

The critical path consists of activities B, D, and E. Next, crash cost/month must be computed for each activity:

Start

B

C

D E

End

A

Activity

Normal Time

(months) Crash Time

(months) Normal

Cost Crash Cost

A 6 4 $2000 $2400

B 7 5 3000 3500

C 7 6 1000 1300

D 6 4 2000 2600

E 9 8 8800 9000

Activity ES EF LS LF Slack

A 0 6 9 15 9

B 0 7 0 7 0

C 6 13 15 22 9

D 7 13 7 13 0

E 13 22 13 22 0

. SOLUTION The first step in this problem is to compute ES, EF, LS, LF, and slack for each activity:

Activity

Normal Time –

Crash Time

Crash Cost – Normal

Cost

Crash Cost/

Month Critical Path?

A 2 $400 $200/month No

B 2 500 250/month Yes

C 1 300 300/month No

D 2 600 300/month Yes

E 1 200 200/month Yes

Finally, we will select that activity on the critical path with the smallest crash cost/month. This is activity E. Thus, we can reduce the total project completion date by one month for an additional cost of $200. We still need to reduce the project com- pletion date by two more months. This reduction can be achieved at least cost along the critical path by reducing activity B by two months for an additional cost of $500. Neither reduction has an effect on noncritical activities. This solution is summarized in the following table:

Activity Months Reduced Cost

E 1 $200

B 2 500

    Total: $700

Problems* • 3.1 The work breakdown structure for building a house (levels 1 and 2) is shown below:

Site Preparation Masonry Carpentry Plumbing Finishing

House

Level 2

Level 1

a) Add two level 3 activities to each of the level 2 activities to pro- vide more detail to the WBS.

b) Select one of your level 3 activities and add two level 4 activities below it.

• • 3.2 Robert Mefford has been nominated as a candidate to run for a seat as a member of Parliament representing Bonavista South. He views his eight-month campaign for office as a major project and wishes to create a work breakdown structure (WBS) to

* Note: PX means the problem may be solved with POM for Windows and/or Excel OM.

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92 PART 1 Introduction to Operations Management

help control the detailed scheduling. So far, he has developed the following pieces of the WBS:

Activity Immediate Predecessor(s) Time (days)

A — 5 B A 2 C A 4 D B 5 E B 5 F C 5 G E, F 2 H D 3 I G, H 5

• 3.5 Using AOA, diagram the network described below for Roni Zuckerman’s construction project. Calculate its critical path. How long is the minimum duration of this network?

Activity Nodes Time

(weeks) Activity Nodes Time

(weeks)

J 1–2 10 N 3–4 2 K 1–3 8 O 4–5 7 L 2–4 6 P 3–5 5 M 2–3 3      

• 3.6 Anju Chaudhary is developing a program in leader- ship training for middle-level managers. She has listed a number of activities that must be completed before a training program of this nature could be conducted. The activities, immediate predecessors, and times appear in the accompanying table:

Activity Immediate Predecessor(s) Time (days)

A — 2 B — 5 C — 1 D B 10 E A, D 3 F C 6 G E, F 8

a) Develop an AON network for this problem. b) What is the critical path? c) What is the total project completion time? d) What is the slack time for each individual activity?

• • 3.7 Task time estimates for a production line setup project at Robert Klassen’s Ontario factory are as follows:

Activity Time (in hours) Immediate Predecessors

A 6.0 —

B 7.2 —

C 5.0 A

D 6.0 B, C

E 4.5 B, C

F 7.7 D

G 4.0 E, F

a) Draw the project network using AON. b) Identify the critical path. c) What is the expected project length? d) Draw a Gantt chart for the project.

Level Level ID No. Activity

1 1.0 Develop political campaign

2 1.1 Fund-raising plan

3 1.11 ____________________________

3 1.12 ____________________________

3 1.13 ____________________________

2 1.2 Develop a position on major issues

3 1.21 ____________________________

3 1.22 ____________________________

3 1.23 ____________________________

2 1.3 Staffing for campaign

3 1.31 ____________________________

3 1.32 ____________________________

3 1.33 ____________________________

3 1.34 ____________________________

2 1.4 Paperwork compliance for candidacy

3 1.41 ____________________________

3 1.42 ____________________________

2 1.5 Ethical plan/issues

3 1.51 ____________________________

Help Mr. Mefford by providing details where the blank lines appear. Are there any other major (level 2) activities to create? If so, add an ID number 1.6 and insert them.

• 3.3 Draw the activity-on-node (AON) project network associated with the following activities for Dave Carhart’s consult- ing company project. How long should it take Dave and his team to complete this project? What are the critical path activities?

Activity Immediate

Predecessor(s) Time (days)

A — 3

B A 4

C A 6

D B 6

E B 4

F C 4

G D 6

H E, F 8

• 3.4 Given the activities whose sequence is described by the following table, draw the appropriate activity-on-arrow (AOA) net- work diagram. a) Which activities are on the critical path? b) What is the length of the critical path?

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Chapter 3 Project Management 93

• • 3.9 Refer to the table in Problem 3.8. a) Draw the AON network for the construction activity. b) Draw the AOA network for the construction activity.

• 3.10 The activities needed to build an experimental chemical contaminant tracking machine at Charlie Cook Corp. are listed in the following table. Construct an AON network for these activities.

Activity Immediate

Predecessor(s) Activity Immediate

Predecessor(s)

A — E B B — F B C A G C, E D A H D, F

• 3.11 Charlie Cook (see Problem 3.10) was able to determine the activity times for constructing his chemical contaminant track- ing machine. Cook would like to determine ES, EF, LS, LF, and slack for each activity. The total project completion time and the critical path should also be determined. Here are the activity times:

Activity Time

(weeks) Activity Time

(weeks)

A 6 E 4 B 7 F 6 C 3 G 10 D 2 H 7

• 3.12 The activities described by the following table are given for the Duplaga Corporation:

Activity Immediate Predecessor(s) Time A — 9 B A 7 C A 3 D B 6 E B 9 F C 4 G E, F 6 H D 5 I G, H 3

• • 3.8 The City of Lethbridge has decided to build a botani- cal garden and picnic area in the heart of the city for the recreation of its citizens. The precedence table for all the activities required to

a) Draw the appropriate AON PERT diagram for Annelise Duplaga’s management team.

b) Find the critical path. c) What is the project completion time?

• 3.13 A small renovation of a Hard Rock Cafe gift shop has six activities (in hours). For the following estimates of a, m, and b, calcu- late the expected time and the standard deviation for each activity:

Activity a m b

A 11 15 19

B 27 31 41

C 18 18 18

D 8 13 19

E 17 18 20

F 16 19 22

• • 3.14 McGee Carpet and Trim installs carpet in commercial offices. Andrea McGee has been very concerned with the amount of time it took to complete several recent jobs. Some of her workers are very unreliable. A list of activities and their optimistic completion time, the most likely completion time, and the pessimistic completion time (all in days) for a new contract are given in the following table:

  Time (days) Immediate Predecessor(s) Activity a m b

A 3 6 8 —

B 2 4 4 —

C 1 2 3 —

D 6 7 8 C

E 2 4 6 B, D

F 6 10 14 A, E

G 1 2 4 A, E

H 3 6 9 F

I 10 11 12 G

J 14 16 20 C

K 2 8 10 H, I

a) Determine the expected completion time and variance for each activity.

b) Determine the total project completion time and the critical path for the project.

Code Activity Description Time

(in hours) Immediate Predecessor(s)

A Planning Find location; determine resource requirements 20 None B Purchasing Requisition of lumber and sand 60 Planning C Excavation Dig and grade 100 Planning D Sawing Saw lumber into appropriate sizes 30 Purchasing E Placement Position lumber in correct locations 20 Sawing, excavation F Assembly Nail lumber together 10 Placement G Infill Put sand in and under the equipment 20 Assembly H Outfill Put dirt around the equipment 10 Assembly I Decoration Put grass all over the garden, landscape, paint 30 Infill, outfill

construct this area successfully is given below. Draw the Gantt chart for the whole construction activity.

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94 PART 1 Introduction to Operations Management

c) Determine ES, EF, LS, LF, and slack for each activity. d) What is the probability that McGee Carpet and Trim will finish

the project in 40 days or less?

• • 3.15 The following is a table of activities associated with a project at Bill Figg Enterprises, their durations, and what activities each must precede:

Activity Duration (weeks) Precedes

A (start) 1 B, C

B 1 E

C 4 F

E 2 F

F (end) 2 —

a) Draw an AON diagram of the project, including activity durations. b) Define the critical path, listing all critical activities in chronolog-

ical order. c) What is the project duration (in weeks)? d) What is the slack (in weeks) associated with any and all noncrit-

ical paths through the project?

• • 3.16 Assume that the activities in Problem 3.15 have the following costs to shorten: A, $300/week; B, $100/week; C, $200/ week; E, $100/week; and F, $400/week. Assume also that you can crash an activity down to zero weeks in duration and that every week you can shorten the project is worth $250 to you. What activ- ities would you crash? What is the total crashing cost?

• • • 3.17 Thabo Mbeki, president of Mbeki Construction, has developed the tasks, durations, and predecessor relationships in the following table for building new motels. Draw the AON network and answer the questions that follow.

Immediate Predecessor(s) 

Time Estimates (in weeks)

Activity Optimistic Most

Likely Pessimistic

A — 4 8 10

B A 2 8 24

C A 8 12 16

D A 4 6 10

E B 1 2 3

F E, C 6 8 20

G E, C 2 3 4

H F 2 2 2

I F 6 6 6

J D, G, H 4 6 12

K I, J 2 2 3

a) What is the expected (estimated) time for activity C? b) What is the variance for activity C? c) Based on the calculation of estimated times, what is the critical

path? d) What is the estimated time of the critical path? e) What is the activity variance along the critical path? f) What is the probability of completion of the project before week

36?

• • • 3.18 What is the minimum cost of crashing by four days the following project that James Walters manages at Athabasca University?

Activity

Normal Time (days)

Crash Time (days)

Normal Cost

Crash Cost

Immediate Predecessor(s)

A 6 5 $ 900 $1000 —

B 8 6 300 400 —

C 4 3 500 600 —

D 5 3 900 1200 A

E 8 5 1000 1600 C

• • 3.19 Three activities are candidates for crashing on a project network for a large computer installation (all are, of course, criti- cal). Activity details are in the following table:

Activity Predecessor Normal

Time Normal

Cost Crash Time

Crash Cost

A — 7 days $6000 6 days $6600

B A 4 days 1200 2 days 3000

C B 11 days 4000 9 days 6000

a) What action would you take to reduce the critical path by one day?

b) Assuming no other paths become critical, what action would you take to reduce the critical path one additional day?

c) What is the total cost of the two-day reduction?

• • • 3.20 Development of a new deluxe version of a particular software product is being considered by Ravi Behara’s software house. The activities necessary for the completion of this project are listed in the following table:

Activity

Normal Time

(weeks)

Crash Time

(weeks) Normal

Cost Crash Cost

Immediate Predecessor(s)

A 4 3 $2000 $2600 —

B 2 1 2200 2800 —

C 3 3 500 500 —

D 8 4 2300 2600 A

E 6 3 900 1200 B

F 3 2 3000 4200 C

G 4 2 1400 2000 D, E

a) What is the project completion date? b) What is the total cost required for completing this project on

normal time? c) If you wish to reduce the time required to complete this project

by one week, which activity should be crashed, and how much will this increase the total cost?

d) What is the maximum time that can be crashed? How much would costs increase?

• • • 3.21 The estimated times and immediate predecessors for the activities in a project at Caesar Douglas’s retinal scanning com- pany are given in the following table. Assume that the activity times are independent.

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Chapter 3 Project Management 95

  Immediate Predecessor 

Time (weeks)

Activity a m b

A — 9 10 11

B — 4 10 16

C A 9 10 11

D B 5 8 11

a) Calculate the expected time and variance for each activity. b) What is the expected completion time of the critical path?

What is the expected completion time of the other path in the network?

c) What is the variance of the critical path? What is the variance of the other path in the network?

d) If the time to complete path A–C is normally distributed, what is the probability that this path will be finished in 22 weeks or less?

e) If the time to complete path B–D is normally distributed, what is the probability that this path will be finished in 22 weeks or less?

f) Explain why the probability that the critical path will be finished in 22 weeks or less is not necessarily the probability that the project will be finished in 22 weeks or less.

• • • 3.22 Jack Kanet Manufacturing produces custom-built pol- lution control devices for medium-size steel mills. The most recent project undertaken by Jack requires 14 different activities. a) Jack’s managers would like to determine the total project com-

pletion time (in days) and those activities that lie along the critical path. The appropriate data are shown in the following table.

b) What is the probability of being done in 53 days? c) What date results in a 99% probability of completion?

Activity Immediate

Predecessor(s) Optimistic

Time

Most Likely Time

Pessimistic Time

A — 4 6 7

B — 1 2 3

C A 6 6 6

D A 5 8 11

E B, C 1 9 18

F D 2 3 6

G D 1 7 8

H E, F 4 4 6

I G, H 1 6 8

J I 2 5 7

K I 8 9 11

L J 2 4 6

M K 1 2 3

N L, M 6 8 10

• • • 3.23 A firm hired to coordinate the release of the movie Goon (starring Jay Baruchel) identified 16 activities to be com- pleted before the release of the film.

a) How many weeks in advance of the film release should the pro- moter have started its marketing campaign? What is the critical path? The tasks (in time units of weeks) are as follows:

Activity Immediate

Predecessors Optimist

Time

Most Likely Time

Pessimistic Time

A — 1 2 4

B — 3 3.5 4

C — 10 12 13

D — 4 5 7

E — 2 4 5

F A 6 7 8

G B 2 4 5.5

H C 5 7.7 9

I C 9.9 10 12

J C 2 4 5

K D 2 4 6

L E 2 4 6

M F, G, H 5 6 6.5

N J, K, L 1 1.1 2

O I, M 5 7 8

P N 5 7 9

b) If activities I and J were not necessary, what impact would this have on the critical path and the number of weeks needed to complete the marketing campaign?

• • 3.24 Using PERT, Jennifer Benson was able to determine that the expected project completion time for the construction of a pleasure yacht is 21 months, and the project variance is 4. a) What is the probability that the project will be completed in

17 months? b) What is the probability that the project will be completed in

20 months? c) What is the probability that the project will be completed in

23 months? d) What is the probability that the project will be completed in

25 months? e) What is the due date that yields a 95% chance of completion?

• • • 3.25 Bolling Electronics manufactures DVD players for commercial use. W. Blaker Bolling, president of Bolling Electronics, is contemplating producing DVD players for home use. The activities necessary to build an experimental model and related data are given in the following table:

Activity

Normal Time

(weeks)

Crash Time

(weeks) Normal Cost ($)

Crash Cost ($)

Immediate Predecessor(s)

A 3 2 1000 1600 —

B 2 1 2000 2700 —

C 1 1 300 300 —

D 7 3 1300 1600 A

E 6 3 850 1000 B

F 2 1 4000 5000 C

G 4 2 1500 2000 D, E

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96 PART 1 Introduction to Operations Management

a) What is the project completion date? b) Crash this project to 10 weeks at the least cost. c) Crash this project to seven weeks (which is the maximum it can

be crashed) at the least cost.

• • • 3.26 The Maser is a new custom-designed sports car. An analysis of the task of building the Maser reveals the following list of relevant activities, their immediate predecessors, and their duration:5

5 Source: STONER, MANAGEMENT 3RD EDTN., 3rd Ed., ©1986. Reprinted and Electronically reproduced by permission of Pearson Education, Inc., New York, NY..

a) Draw a network diagram for the project. b) Mark the critical path and state its length.

c) If the Maser had to be completed two days earlier, would it help to:

i) Buy preassembled transmissions and drivetrains? ii) Install robots to halve engine-building time? iii) Speed delivery of special accessories by three days? d) How might resources be borrowed from activities on the noncrit-

ical path to speed activities on the critical path?

Fast Creek Lightning: (A)*

Fast Creek is a city in south central Saskatchewan located along the Trans-Canada Highway. Fast Creek has a population of just over 27 000 residents and is a regional hub for the many smaller towns and hundreds of farms in the surrounding area. Fast Creek is a trans- portation and industrial centre, and has several federal and provin- cial government offices.

Fast Creek is also a sports centre, and its junior hockey team, the Fast Creek Lightning, have a long history of success in the Central Hockey League but have not won a major trophy in close

to 10 years. To reach their long-desired goal of winning the league championship and reaching the Memorial Cup final, the Lightning have hired the legendary Scotty Beauchamp as head coach.

One of Beauchamp’s demands on joining the Lightning had been a new arena. With attendance increasing, Lightning executives and city officials began to face the issue head-on. After six months of study, much political arm wrestling, and some serious financial analysis, Keith MacLennan, owner of the Lightning, had reached a decision to expand the capacity at the current arena.

CASE STUDIES

* This integrated study runs throughout the text. Other issues facing Fast Creek’s hockey expansion include (B) forecasting game attendance (Chapter 4); (C) quality of facilities (Chapter 6); (D) break-even analysis for food services (Supplement 7 MyLab Operations Management); (E) location of the new arena (Chapter 8 MyLab Operations Management); (F) inventory planning of hockey programs (Chapter 12 MyLab Operations Management); and (G) scheduling of site security officers/staff for game days (Chapter 13). Recurring cases are also available in a separate file for instructors using the PCL.

Job Letter Description Immediate Predecessor(s) Normal Time (days)

A Start — 0 B Design A 8 C Order special accessories B 0.1 D Build frame B 1 E Build doors B 1 F Attach axles, wheels, gas tank D 1 G Build body shell B 2 H Build transmission and drivetrain B 3 I Fit doors to body shell G, E 1 J Build engine B 4 K Bench-test engine J 2 L Assemble chassis F, H, K 1 M Road test chassis L 0.5 N Paint body I 2 O Install wiring N 1 P Install interior N 1.5 Q Accept delivery of special accessories C 5 R Mount body and accessories on chassis M, O, P, Q 1 S Road test car R 0.5 T Attach exterior trim S 1 U Finish T 0

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Chapter 3 Project Management 97

Adding over a thousand seats, including many luxury boxes, would not please everyone. The influential Beauchamp had argued the need for a first-class arena, with state-of-the-art training facili- ties and a palatial office appropriate for a future hall of fame coach. But the decision was made, and everyone, including the coach, would learn to live with it.

The job now was to get construction going immediately after the 2016 season ended. This would allow exactly 270 days until the 2017 season opening game. The contractor, Hill Construction, signed his contract. Bob Hill looked at the tasks his engineers had outlined and looked MacLennan in the eye. “I guarantee the team will be able to take to the ice on schedule next season,” he said with a sense of confidence. “I sure hope so,” replied MacLennan. “The contract penalty of $10 000 per day for running late is nothing compared to what Coach Beauchamp will do to you if our opening game with Saskatoon is delayed or cancelled.” Hill, sweating slightly, did not

Table 3.6 Fast Creek Lightning Project

      Time Estimates (days)  

Activity Description Predecessor(s) Optimistic Most Likely Pessimistic Crash Cost/Day

A Bonding, insurance, tax structuring — 20 30 40 $1500

B Foundation, concrete footings for boxes A 20 65 80 3500

C Upgrading box seating A 50 60 100 4000

D Upgrading walkways, stairwells, elevators

C 30 50 100 1900

E Interior wiring, lathes B 25 30 35 9500

F Inspection approvals E 0.1 0.1 0.1 0

G Plumbing D, F 25 30 35 2500

H Painting G 10 20 30 2000

I Hardware/AC/metal workings H 20 25 60 2000

J Tile/carpet/windows H 8 10 12 6000

K Inspection J 0.1 0.1 0.1 0

L Final detail work/cleanup I, K 20 25 60 4500

need to respond. In hockey-crazy Saskatchewan, Hill Construction would be in trouble if the 270-day target was missed.

Back in his office, Hill again reviewed the data (see Table 3.6) and noted that optimistic time estimates could be used as crash times. He then gathered his foremen. “Folks, if we’re not 75% sure we’ll finish this stadium in less than 270 days, I want this project crashed! Give me the cost figures for a target date of 250 days—also for 240 days. I want to be early, not just on time!”

Discussion Questions 1. Develop a network drawing for Hill Construction, and determine

the critical path. How long is the project expected to take? 2. What is the probability of finishing in 270 days? 3. If it is necessary to crash to 250 or 240 days, how would Hill do

so, and at what costs? As noted in the case, assume that optimis- tic time estimates can be used as crash times.

The equivalent of a new kindergarten class is born every day at Orlando’s Arnold Palmer Hospital. With more than 12 300 births in 2005 in a hospital that was designed in 1989 for a capacity of 6500 births a year, the newborn intensive care unit was stretched to the limit. Moreover, with continuing strong population growth in central Florida, the hospital was often full. It was clear that new facilities were needed. After much analysis, forecasting, and discus- sion, the management team decided to build a new 273-bed build- ing across the street from the existing hospital. But the facility had to be built in accordance with the hospital’s “Guiding Principles” and its uniqueness as a health centre dedicated to the specialized needs of women and infants. Those Guiding Principles are: Family- centred focus, a healing environment where privacy and dignity are respected, sanctuary of caring that includes warm, serene sur- roundings with natural lighting, sincere and dedicated staff provid- ing the highest quality care, and patient-centred flow and function.

The vice-president of business development, Karl Hodges, wanted a hospital that was designed from the inside out by the

people who understood the Guiding Principles, who knew most about the current system, and who were going to use the new sys- tem, namely, the doctors and nurses. Hodges and his staff spent 13 months discussing expansion needs with this group, as well as with patients and the community, before developing a proposal for the new facility on December 17, 2001. An administrative team cre- ated 35 user groups, which held over 1000 planning meetings (last- ing from 45 minutes to a whole day). They even created a “Supreme Court” to deal with conflicting views on the multifaceted issues facing the new hospital.

Funding and regulatory issues added substantial complexity to this major expansion, and Hodges was very concerned that the project stays on time and within budget. Tom Hyatt, director of facility development, was given the task of onsite manager of the U.S. $100 million project, in addition to overseeing ongoing reno- vations, expansions, and other projects. The activities in the mul- tiyear project for the new building at Arnold Palmer are shown in Table 3.7.

Project Management at Arnold Palmer HospitalVideo Case

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98 PART 1 Introduction to Operations Management

Table 3.7 Expansion Planning and Arnold Palmer Hospital Construction Activities and Timesa

Activity Scheduled Time Precedence Activity(ies)

1. Proposal and review 1 month —

2. Establish master schedule 2 weeks 1

3. Architect selection process 5 weeks 1

4. Survey whole campus and its needs 1 month 1

5. Conceptual architect’s plans 6 weeks 3

6. Cost estimating 2 months 2, 4, 5

7. Deliver plans to board for consideration/decision 1 month 6

8. Surveys/regulatory review 6 weeks 6

9. Construction manager selection 9 weeks 6

10. State review of need for more hospital beds (“Certificate of Need”) 3.5 months 7, 8

11. Design drawings 4 months 10

12. Construction documents 5 months 9, 11

13. Site preparation/demolish existing building 9 weeks 11

14. Construction start/building pad 2 months 12, 13

15. Relocate utilities 6 weeks 12

16. Deep foundations 2 months 14

17. Building structure in place 9 months 16

18. Exterior skin/roofing 4 months 17

19. Interior buildout 12 months 17

20. Building inspections 5 weeks 15, 19

21. Occupancy 1 month 20 a This list of activities is abbreviated for the purposes of this case study. For simplification, assume each week 5 0.25 months (i.e., 2 weeks 5 0.5 month, 6 weeks 5 1.5 months, etc.).

Discussion Questions* 1. Develop the network for planning and construction of the new

hospital at Arnold Palmer. 2. What is the critical path, and how long is the project expected to

take? 3. Why is the construction of this 11-storey building any more

complex than construction of an equivalent office building?

4. What percent of the whole project duration was spent in plan- ning that occurred prior to the proposal and reviews? Prior to the actual building construction? Why?

* You may wish to view the video accompanying this case before address- ing these questions.

At the Hard Rock Cafe, like many organizations, project manage- ment is a key planning tool. With Hard Rock’s constant growth in hotels and cafes, remodelling of existing cafes, scheduling for Hard Rock Live concert and event venues, and planning the annual Rockfest, managers rely on project management techniques and software to maintain schedule and budget performance.

“Without Microsoft Project,” says Hard Rock vice-president Chris Tomasso, “there is no way to keep so many people on the same page.” Tomasso is in charge of the Rockfest event, which is attended by well over 100 000 enthusiastic fans. The challenge is pulling it off within a tight nine-month planning horizon. As the event approaches, Tomasso devotes greater energy to its activities. For the first three months, Tomasso updates his Microsoft Project charts monthly. Then at the six-month mark, he updates his pro- gress weekly. At the nine-month mark, he checks and corrects his schedule twice a week.

Early in the project management process, Tomasso identi- fies 10 major tasks (called level 2 activities in a work breakdown structure, or WBS)†: talent booking, ticketing, marketing/PR, online promotion, television, show production, travel, sponsorships, oper- ations, and merchandising. Using a WBS, each of these is further divided into a series of subtasks. Table 3.8 identifies 26 of the major activities and subactivities, their immediate predecessors, and time estimates. Tomasso enters all these into the Microsoft Project soft- ware.‡ Tomasso alters the Microsoft Project document and the time- line as the project progresses. “It’s okay to change it as long as you keep on track,” he states.

Managing Hard Rock’s RockfestVideo Case

† The level 1 activity is the Rockfest concert itself. ‡ There are actually 127 activities used by Tomasso; the list is abbreviated for this case study.

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Chapter 3 Project Management 99

The day of the rock concert itself is not the end of the project planning. “It’s nothing but surprises. A band not being able to get to the venue because of traffic jams is a surprise, but an ‘anticipated’ surprise. We had a helicopter on stand-by ready to fly the band in,” says Tomasso.

On completion of Rockfest in July, Tomasso and his team have a three-month reprieve before starting the project planning process again.

Discussion Questions* 1. Identify the critical path and its activities for Rockfest. How long

does the project take?

Table 3.8 Some of the Major Activities and Subactivities in the Rockfest Plan

Activity Description Predecessor(s) Time (weeks)

A Finalize site and building contracts — 7

B Select local promoter A 3

C Hire production manager A 3

D Design promotional website B 5

E Set TV deal D 6

F Hire director E 4

G Plan for TV camera placement F 2

H Target headline entertainers B 4

I Target support entertainers H 4

J Travel accommodations for talent I 10

K Set venue capacity C 2

L Ticketmaster contract D, K 3

M Onsite ticketing L 8

N Sound and staging C 6

O Passes and stage credentials G, R 7

P Travel accommodations for staff B 20

Q Hire sponsor coordinator B 4

R Finalize sponsors Q 4

S Define/place signage for sponsors R, X 3

T Hire operations manager A 4

U Develop site plan T 6

V Hire security director T 7

W Set police/fire security plan V 4

X Power, plumbing, AC, toilet services U 8

Y Secure merchandise deals B 6

Z Online merchandise sales Y 6

2. Which activities have a slack time of eight weeks or more? 3. Identify five major challenges a project manager faces in events

such as this one. 4. Why is a work breakdown structure useful in a project such as

this? Take the 26 activities and break them into what you think should be level 2, level 3, and level 4 tasks.

* You may wish to view the video accompanying this case before address- ing these questions.

cAdditional Case Study: Visit MyLab Operations Management for this case study: Shale Oil Company: This oil refinery must shutdown for maintenance of a major piece of equipment.

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100 PART 1 Introduction to Operations Management

Main Heading Review Material

MyLab Operations Management

THE IMPORTANCE OF PROJECT MANAGEMENT (pp. 59–60)

The management of projects involves three phases:

1. Planning—This phase includes goal setting, defining the project, and team organization.

2. Scheduling—This phase relates people, money, and supplies to specific activities and relates activities to each other.

3. Controlling—Here, the firm monitors resources, costs, quality, and budgets. It also revises or changes plans and shifts resources to meet time and cost demands.

VIDEO 3.1 Project Management at Hard Rock’s Rockfest

PROJECT PLANNING (pp. 60–62)

Projects can be defined as a series of related tasks directed towards a major output.

• Project organization—An organization formed to ensure that programs (projects) receive the proper management and attention.

• Work breakdown structure (WBS)—A hierarchical description of a project into more and more detailed components.

Problem 3.1

PROJECT SCHEDULING (pp. 62–63)

• Gantt charts—Planning charts used to schedule resources and allocate time.

Project scheduling serves several purposes:

1. It shows the relationship of each activity to others and to the whole project.

2. It identifies the precedence relationships among activities.

3. It encourages the setting of realistic time and cost estimates for each activity.

4. It helps make better use of people, money, and material resources by identifying critical bottlenecks in the project.

Problem 3.8

PROJECT CONTROLLING (pp. 64–65)

Computerized programs produce a broad variety of PERT/CPM reports, including

(1) detailed cost breakdowns for each task, (2) total program labour curves, (3) cost distribution tables, (4) functional cost and hour summaries, (5) raw material and expenditure forecasts, (6) variance reports, (7) time analysis reports, and (8) work status reports.

VIDEO 3.2 Project Management at Arnold Palmer Hospital

PROJECT MANAGEMENT TECHNIQUES: PERT AND CPM (pp. 65–69)

• Program evaluation and review technique (PERT)—A project man- agement technique that employs three time estimates for each activity.

• Critical path method (CPM)—A project management technique that uses only one time factor per activity.

• Critical path—The computed longest time path(s) through a network.

PERT and CPM both follow six basic steps.

The activities on the critical path will delay the entire project if they are not completed on time.

• Activity-on-node (AON)—A network diagram in which nodes designate activities.

• Activity-on-arrow (AOA)—A network diagram in which arrows desig- nate activities.

In an AOA network, the nodes represent the starting and finishing times of an activity and are also called events.

• Dummy activity—An activity having no time that is inserted into a network to maintain the logic of the network.

A dummy ending activity can be added to the end of an AON diagram for a project that has multiple ending activities.

Problems: 3.3–3.7, 3.9, 3.10, 3.12, 3.15

Virtual Office Hours for Solved Prob- lems: 3.1, 3.2

CHAPTER 3 RAPID REVIEW

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Chapter 3 Project Management 101

Main Heading Review Material

MyLab Operations Management

DETERMINING THE PROJECT SCHEDULE (pp. 70–75)

• Critical path analysis— A process to find the most effective sequence of activities that helps determine a project schedule.

To find the critical path, we calculate two distinct starting and ending times for each activity:

• Earliest start (ES) 5 Earliest time at which an activity can start, assuming that all predecessors have been completed.

• Earliest finish (EF) 5 Earliest time at which an activity can be finished.

• Latest start (LS) 5 Latest time at which an activity can start, without delaying the completion time of the entire project.

• Latest finish (LF) 5 Latest time by which an activity has to finish so as not to delay the completion time of the entire project.

Problems: 3.11, 3.14, 3.15, 3.17, 3.20, 3.22, 3.23, 3.26

• Forward pass—A process that identifies all the early start and early finish times.

ES 5 Maximum EF of all immediate predecessor (3-1) EF 5 ES 1 Activity time (3-2)

• Backward pass—A process that identifies all the late start and late finish times.

LF 5 Minimum LS of all immediate following activities (3-3) LS 5 LF 2 Activity time (3-4)

• Slack time—Free time for an activity.

Slack 5 LS 2 ES or Slack 5 LF 2 EF (3-5)

The activities with zero slack are called critical activities and are said to be on the critical path.

The critical path is a continuous path through the project network that starts at the first activity in the project, terminates at the last activity in the project, and includes only critical activities.

Virtual Office Hours for Solved Problem: 3.3

ACTIVE MODEL 3.1

VARIABILITY IN ACTIVITY TIMES (pp. 75–81)

• Total slack—Time shared among more than one activity.

• Optimistic time (a)—The “best” activity completion time that could be obtained in a PERT network.

• Pessimistic time (b)—The “worst” activity time that could be expected in a PERT network.

• Most likely time (m)—The most probable time to complete an activity in a PERT network.

When using PERT, we often assume that activity time estimates follow the beta distribution.

Expected activity time t = (a + 4m + b) > 6 (3-6) Variance of Activity Completion Time = (b - a) >62 (3-7) s2p = project variance = a (variances of activities on critical path) (3-8) Z = (Due date - expected data of completion) >sp (3-9) Due date = Expected completion time + (Z * sp ) (3-10)

Problems: 3.13, 3.14. 3.21, 3.24

Virtual Office Hours for Solved Problems: 3.4, 3.5, 3.6

COST–TIME TRADE- OFFS AND PROJECT CRASHING (pp. 81–83)

• Crashing—Shortening activity time in a network to reduce time on the critical path so total completion time is reduced.

Crash cost per period = (Crash cost - Normal cost ) (Normal time - Crash time)

(3-11)

Problems: 3.16, 3.18, 3.19, 3.25

Virtual Office Hours for Solved Problem: 3.7

A CRITIQUE OF PERT AND CPM (pp. 83–84)

As with every technique for problem solving, PERT and CPM have a num- ber of advantages as well as several limitations.

USING MICROSOFT PROJECT TO MANAGE PROJECTS (pp. 84–87)

Microsoft Project, the most popular example of specialized project manage- ment software, is extremely useful in drawing project networks, identifying the project schedule, and managing project costs and other resources.

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102 PART 1 Introduction to Operations Management

Answers: LO1. c; LO2. e; LO3. b; LO4. d; LO5. b; LO6. d.

LO1 Which of the following statements regarding Gantt charts is true? a) Gantt charts give a timeline and precedence relationships for each

activity of a project. b) Gantt charts use the four standard spines: Methods, Materials,

Manpower, and Machinery. c) Gantt charts are visual devices that show the duration of activities

in a project. d) Gantt charts are expensive. e) All of the above are true.

LO2 Which of the following is true about AOA and AON networks? a) In AOA, arrows represent activities. b) In AON, nodes represent activities. c) Activities consume time and resources. d) Nodes are also called events in AOA. e) All of the above.

LO3 Slack time equals: a) ES 1 t. b) LS 2 ES. c) zero. d) EF 2 ES.

LO4 The critical path of a network is the: a) shortest time path through the network. b) path with the fewest activities. c) path with the most activities. d) longest time path through the network.

LO5 PERT analysis computes the variance of the total project completion time as:

a) the sum of the variances of all activities in the project. b) the sum of the variances of all activities on the critical path. c) the sum of the variances of all activities not on the critical path. d) the variance of the final activity of the project.

LO6 The crash cost per period: a) is the difference in costs divided by the difference in times (crash

and normal). b) is considered to be linear in the range between normal and crash. c) needs to be determined so that the smallest cost values on the

critical path can be considered for time reduction first. d) all of the above.

Self-Test  Before taking the self-test, refer to the learning objectives listed at the beginning of the chapter and the key terms listed at the end of the chapter.

Most of these questions can be found in MyLab Operations Management. Visit MyLab Operations Management to access cases, videos, downloadable software, and much more. MyLab Operations Management Management also features a personalized Study Plan that helps you identify which chapter concepts you’ve mastered and guides you towards study tools for additional practice.

MyLab Operations Management

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Forecasting

Learning Objectives LO1 Understand the three time

horizons and which models apply for each 105

LO2 Explain when to use each of the four qualitative models 107

LO3 Apply the naive, moving-average, exponential smoothing, and trend methods 110

LO4 Compute three measures of forecast accuracy 113

LO5 Develop seasonal indices 122

LO6 Conduct a regression and correlation analysis 126

LO7 Use a tracking signal 132

Forecasting Provides a Competitive Advantage for Disney When it comes to the world’s most respected brands, Walt Disney Parks &

Resorts is a visible leader. Although the monarch of this magic kingdom is no

man but a mouse—Mickey Mouse—it is CEO, Robert Iger, who daily man-

ages the entertainment giant.

Disney’s global portfolio includes Shanghai Disney (2016), Hong Kong

Disneyland (2005), Disneyland Paris (1992), and Tokyo Disneyland (1983).

But it is the Walt Disney World Resort (in Florida) and Disneyland Resort (in

California) that drive profits in this U.S. $50 billion corporation, which is ranked

in the top 100 in both the Fortune 500 and the Financial Times Global 500.

Revenues at Disney are all about people—how many visit the parks and

how they spend money while there. When Iger receives a daily report from

his six theme parks near Orlando, the report contains only two numbers:

the forecast of yesterday’s attendance at the parks (Magic Kingdom, Epcot,

Disney’s Animal Kingdom, Disney’s Hollywood Studios, Typhoon Lagoon,

and Blizzard Beach) and the actual attendance. An error close to zero is

expected. Iger takes his forecasts very seriously.

103

Global Company Profile Walt Disney Parks & Resorts

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104 PART 1 Introduction to Operations Management

The forecasting team at Walt Disney World Resort

doesn’t just do a daily prediction, however, and Iger

is not its only customer. The team also provides daily,

weekly, monthly, annual, and five-year forecasts to

the labour management, maintenance, operations,

finance, and park scheduling departments. Forecast-

ers use judgmental models, econometric models,

moving-average models, and regression analysis.

With 20% of Walt Disney World Resort’s customers

coming from outside the United States, its economic

model includes variables such as gross domestic

product (GDP), cross-exchange rates, and arrivals into

the United States. Disney also uses 35 analysts and

70 field people to survey 1 million people each year.

The surveys—administered to guests at the parks

and its 20 hotels, to employees, and to travel industry

professionals—examine future travel plans and expe-

riences at the parks. This helps forecast not only the

attendance but behaviour at each ride (e.g., how long

people will wait, how many times they will ride). Inputs

to the monthly forecasting model include airline spe-

cials, speeches by the chair of the Federal Reserve, and

Wall Street trends. Disney even monitors 3000 school

districts inside and outside the United States for holi-

day/vacation schedules. With this approach, Disney’s

five-year attendance forecast yields just a 5% error on

average. Its annual forecasts have a 0% to 3% error.

Attendance forecasts for the parks drive a whole

slew of management decisions. For example, capacity

on any day can be increased by opening at 8:00 a.m.

instead of the usual 9:00 a.m., by opening more

shows or rides, by adding more food/beverage carts

(9 million hamburgers and 50 million Cokes are sold

per year!), and by bringing in more employees (called

“cast members”). Cast members are scheduled in

15-minute intervals throughout the parks for flexibility.

Demand can be managed by limiting the number of

guests admitted to the parks, with the “FAST PASS”

reservation system, and by shifting crowds from rides

to more street parades.

At Disney, forecasting is a key driver in the com-

pany’s success and competitive advantage.

What Is Forecasting? Every day, managers like those at Disney make decisions without knowing what will happen in the future. They order inventory without knowing what sales will be, purchase new equipment despite uncertainty about demand for products, and make investments without knowing what profits will be. Managers are always trying to make better estimates of what will happen in the future in the face of uncertainty. Making good estimates is the main purpose of forecasting.

In this chapter, we examine different types of forecasts and present a variety of forecasting models. Our purpose is to show that there are many ways for managers to forecast. We also provide an overview of business sales forecasting and describe how to prepare, monitor, and

An increasingly complex world economy makes forecasting challenging.

Mickey and Minnie Mouse, and other Disney characters, with Cinderella’s Castle in the background, provide the public image of Disney to the world. Forecasts drive the work schedules of 58 000 cast members working at Walt Disney World Resort near Orlando.

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Chapter 4 Forecasting 105

judge the accuracy of a forecast. Good forecasts are an essential part of efficient service and manufacturing operations.

Forecasting is the art and science of predicting future events. Forecasting may involve taking historical data and projecting them into the future with some sort of mathematical model. It may be a subjective or intuitive prediction. Or it may involve a combination of these—that is, a math- ematical model adjusted by a manager’s good judgment.

As we introduce different forecasting techniques in this chapter, you will see that there is seldom one superior method. What works best in one firm under one set of conditions may be a complete disaster in another organization, or even in a different department of the same firm. In addition, you will see that there are limits as to what can be expected from forecasts. They are seldom, if ever, perfect. They are also costly and time-consuming to prepare and monitor.

Few businesses, however, can afford to avoid the process of forecasting by just waiting to see what happens and then taking their chances. Effective planning in both the short run and long run depends on a forecast of demand for the company’s products.

FORECASTING TIME HORIZONS A forecast is usually classified by the future time horizon that it covers. Time horizons fall into three categories:

1. Short-range forecast: This forecast has a time span of up to one year but is generally less than three months. It is used for planning purchasing, job scheduling, workforce levels, job assignments, and production levels.

2. Medium-range forecast: A medium-range, or intermediate, forecast generally spans from three months to three years. It is useful in sales planning, production planning and budget- ing, cash budgeting, and analysis of various operating plans.

3. Long-range forecast: Generally three years or more in time span, long-range forecasts are used in planning for new products, capital expenditures, facility location or expansion, and research and development.

Medium- and long-range forecasts are distinguished from short-range forecasts by three features:

1. First, intermediate and long-run forecasts deal with more comprehensive issues and sup- port management decisions regarding planning and products, plants, and processes. Implementing some facility decisions, such as GM’s decision to open a new Brazilian man- ufacturing plant, can take five to eight years from inception to completion.

2. Second, short-term forecasting usually employs different methodologies than longer-term forecasting. Mathematical techniques, such as moving averages, exponential smoothing, and trend extrapolation (all of which we shall examine shortly), are common to short- run projections. Broader, less quantitative methods are useful in predicting such issues as whether a new product, like the optical disk recorder, should be introduced into a company’s product line.

3. Finally, as you would expect, short-range forecasts tend to be more accurate than longer- range forecasts. Factors that influence demand change every day. Thus, as the time horizon lengthens, it is likely that forecast accuracy will diminish. It almost goes without saying, then, that sales forecasts must be updated regularly to maintain their value and integrity. After each sales period, forecasts should be reviewed and revised.

THE INFLUENCE OF PRODUCT LIFE CYCLE Another factor to consider when developing sales forecasts, especially longer ones, is product life cycle. Products, and even services, do not sell at a constant level throughout their lives. Most successful products pass through four stages: (1) introduction, (2) growth, (3) maturity, and (4) decline.

Products in the first two stages of the life cycle (such as virtual reality and the Boeing 787 Dreamliner) need longer forecasts than those in the maturity and decline stages (such as large SUVs and skateboards). Forecasts that reflect life cycle are useful in projecting different staff- ing levels, inventory levels, and factory capacity as the product passes from the first to the last stage. The challenge of introducing new products is treated in more detail in Chapter 5.

Forecasting The art and science of predicting future events.

LO1 Understand the three time horizons and which models apply for each

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106 PART 1 Introduction to Operations Management

TYPES OF FORECASTS Organizations use three major types of forecasts in planning future operations:

1. Economic forecasts address the business cycle by predicting inflation rates, money sup- plies, housing starts, and other planning indicators.

2. Technological forecasts are concerned with rates of technological progress, which can result in the birth of exciting new products, requiring new plants and equipment.

3. Demand forecasts are projections of demand for a company’s products or services. These forecasts, also called sales forecasts, drive a company’s production, capacity, and schedul- ing systems and serve as inputs to financial, marketing, and personnel planning.

Economic and technological forecasting are specialized techniques that may fall outside the role of the operations manager. The emphasis in this book will therefore be on demand forecasting.

The Strategic Importance of Forecasting Good forecasts are of critical importance in all aspects of a business: The forecast is the only estimate of demand until actual demand becomes known. Forecasts of demand therefore drive decisions in many areas. Let’s look at the impact of product demand forecast on three activities:

1. Supply chain management. 2. Human resources. 3. Capacity.

SUPPLY CHAIN MANAGEMENT Good supplier relations and the ensuing advantages in product innovation, cost, and speed to market depend on accurate forecasts. Here are just three examples:

• Apple has built an effective global system where it controls nearly every piece of the supply chain, from product design to retail store. With rapid communication and accurate data shared up and down the supply chain, innovation is enhanced, inventory costs are reduced, and speed to market is improved. Once a product goes on sale, Apple tracks demand by the hour for each store and adjusts production forecasts daily. At Apple, forecasts for its supply chain are a strategic weapon.

• Toyota develops sophisticated car forecasts with input from a variety of sources, includ- ing dealers. But forecasting the demand for accessories such as navigation systems, custom wheels, spoilers, and so on is particularly difficult. And there are over 1000 items that vary by model and colour. As a result, Toyota not only reviews reams of data with regard to vehi- cles that have been built and wholesaled but also looks in detail at vehicle forecasts before it makes judgments about the future accessory demand. When this is done correctly, the result is an efficient supply chain and satisfied customers.

• Walmart collaborates with suppliers such as Sara Lee and Procter & Gamble to make sure the right item is available at the right time in the right place and at the right price. For instance, in hurricane season, Walmart’s ability to analyze 700 million store–item combinations means it can forecast that not only flashlights but also Pop-Tarts and beer sell at seven times the normal demand rate. These forecasting systems are known as collaborative planning, forecasting, and replenishment (CPFR). They combine the intelligence of multiple supply chain partners. The goal of CPFR is to create significantly more accurate information that can power the supply chain to greater sales and profits.

HUMAN RESOURCES Hiring, training, and laying off workers all depend on anticipated demand. If the human resources department must hire additional workers without warning, the amount of training declines and the quality of the workforce suffers. A large chemical firm almost lost its biggest customer when a quick expansion to around-the-clock shifts led to a total breakdown in quality control on the second and third shifts.

CAPACITY When capacity is inadequate, the resulting shortages can lead to loss of customers and market share. This is exactly what happened to Nabisco when it underestimated the huge demand for its new low-fat Snackwell's Devil’s Food Cookies. Even with production lines working overtime, Nabisco could not keep up with demand, and it lost customers. Amazon

Economic forecasts Planning indicators that are valuable in helping organizations prepare medium- to long-range forecasts.

Technological forecasts Long-term forecasts concerned with the rates of technological progress.

Demand forecasts Projections of a company’s sales for each time period in the plan- ning horizon.

VIDEO 4.1 Forecasting at Hard Rock Cafe

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Chapter 4 Forecasting 107

made the same error with its Kindle. On the other hand, when excess capacity exists, costs can skyrocket.

Seven Steps in the Forecasting System Forecasting follows seven basic steps. We use Disney World, the focus of this chapter’s Global Company Profile, as an example of each step:

1. Determine the use of the forecast: Disney uses park attendance forecasts to drive decisions about staffing, opening times, ride availability, and food supplies.

2. Select the items to be forecasted: For Disney World, there are six main parks. A forecast of daily attendance at each is the main number that determines labour, maintenance, and scheduling.

3. Determine the time horizon of the forecast: Is it for the short, medium, or long term? Disney develops daily, weekly, monthly, annual, and five-year forecasts.

4. Select the forecasting model(s): Disney uses a variety of statistical models that we shall discuss, including moving averages, econometrics, and regression analysis. It also employs judgmental, or nonquantitative, models.

5. Gather the data needed to make the forecast: Disney’s forecasting team employs 35 analysts and 70 field personnel to survey 1 million people/businesses every year. Disney also uses a firm called Global Insights for travel industry forecasts and gathers data on exchange rates, arrivals into the United States, airline specials, Wall Street trends, and school vacation schedules.

6. Make the forecast. 7. Validate and implement the results: At Disney, forecasts are reviewed daily at the highest

levels to make sure that the model, assumptions, and data are valid. Error measures are applied; then the forecasts are used to schedule personnel down to 15-minute intervals.

These seven steps present a systematic way of initiating, designing, and implementing a fore- casting system. When the system is to be used to generate forecasts regularly over time, data must be routinely collected. Then actual computations are usually made by computer.

Regardless of the system that firms like Disney use, each company faces several realities:

• Forecasts are seldom perfect. This means that outside factors that we cannot predict or control often impact the forecast. Companies need to allow for this reality.

• Most forecasting techniques assume that there is some underlying stability in the system. Consequently, some firms automate their predictions using computerized forecasting soft- ware, and then closely monitor only the product items whose demand is erratic.

• Both product family and aggregated forecasts are more accurate than individual product forecasts. Disney, for example, aggregates daily attendance forecasts by park. This approach helps balance the over- and underpredictions of each of the six attractions.

Forecasting Approaches There are two general approaches to forecasting, just as there are two ways to tackle all deci- sion modelling. One is a quantitative analysis; the other is a qualitative approach. Quantitative forecasts use a variety of mathematical models that rely on historical data and/or associative variables to forecast demand. Subjective or qualitative forecasts incorporate such factors as the decision maker’s intuition, emotions, personal experiences, and value system in reaching a forecast. Some firms use one approach and some use the other. In practice, a combination of the two is usually most effective.

OVERVIEW OF QUALITATIVE METHODS In this section, we consider four different qualitative forecasting techniques:

1. Jury of executive opinion: Under this method, the opinions of a group of high-level experts or managers, often in combination with statistical models, are pooled to arrive at a group estimate of demand. Bristol-Myers Squibb Company, for example, uses 220 well-known research scientists as its jury of executive opinion to get a grasp on future trends in the world of medical research.

2. Delphi method: There are three different types of participants in the Delphi method: deci- sion makers, staff personnel, and respondents. Decision makers usually consist of a group

Quantitative forecasts Forecasts that employ mathemat- ical modelling to forecast demand.

Qualitative forecasts Forecasts that incorporate such factors as the decision maker’s intuition, emotions, personal experiences, and value system.

LO2 Explain when to use each of the four qualitative models

Jury of executive opinion A forecasting technique that uses the opinion of a small group of high-level managers to form a group estimate of demand.

Forecasting is part science and part art.

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108 PART 1 Introduction to Operations Management

of five to 10 experts who will be making the actual forecast. Staff personnel assist decision makers by preparing, distributing, collecting, and summarizing a series of questionnaires and survey results. The respondents are a group of people, often located in different places, whose judgments are valued. This group provides inputs to the decision makers before the forecast is made.

3. Sales force composite: In this approach, each salesperson estimates what sales will be in his or her region. These forecasts are then reviewed to ensure that they are realistic. Then they are combined at the district and national levels to reach an overall forecast. A variation of this approach occurs at Lexus, where every quarter Lexus dealers have a “make meeting”. At this meeting, they talk about what is selling, in what colours, and with what options, so the factory knows what to build.

4. Consumer market survey: This method solicits input from customers or potential custom- ers regarding future purchasing plans. It can help not only in preparing a forecast but also in improving product design and planning for new products. The consumer market survey and sales force composite methods can, however, suffer from overly optimistic forecasts that arise from customer input. The 2001 crash of the telecommunication industry was the result of overexpansion to meet “explosive customer demand”. Where did these data come from? Oplink Communications, a Nortel Networks supplier, says its “company forecasts over the last few years were based mainly on informal conversations with customers.”1

OVERVIEW OF QUANTITATIVE METHODS Five quantitative forecasting methods, all of which use historical data, are described in this chapter. They fall into two categories:

Delphi method A forecasting technique using a group process that allows experts to make forecasts.

Sales force composite A forecasting technique based on salespersons’ estimates of expected sales.

1 “Lousy Sales Forecasts Helped Fuel the Telecom Mess,” The Wall Street Journal (July 9, 2001): B1–B4.

Consumer market survey A forecasting method that solicits input from customers or potential customers regarding future purchasing plans.

1. Naive approach 2. Moving averages 3. Exponential smoothing 4. Trend projection 5. Linear regression

Time-series models

Associative model

TIME-SERIES MODELS Time-series models predict on the assumption that the future is a func- tion of the past. In other words, they look at what has happened over a period of time and use a series of past data to make a forecast. If we are predicting sales of lawn mowers, we use the past sales for lawn mowers to make the forecasts.

ASSOCIATIVE MODELS Associative models, such as linear regression, incorporate the variables or factors that might influence the quantity being forecast. For example, an associative model for lawn mower sales might use factors such as new housing starts, advertising budget, and compet- itors’ prices.

Time-Series Forecasting A time series is based on a sequence of evenly spaced (weekly, monthly, quarterly, and so on) data points. Examples include weekly sales of Sher-Wood hockey sticks, quarterly earnings reports of Bell Canada stock, daily shipments of Labatt’s beer, and annual consumer price indi- ces. Forecasting time-series data implies that future values are predicted only from past values and that other variables, no matter how potentially valuable, may be ignored.

DECOMPOSITION OF A TIME SERIES Analyzing time series means breaking down past data into components and then projecting them forward. A time series has four components:

1. Trend is the gradual upward or downward movement of the data over time. Changes in income, population, age distribution, or cultural views may account for movement in trend.

Time series A forecasting technique that uses a series of past data points to make a forecast.

Here is the meat of this chapter. We now show you a wide variety of models that use time-series data.

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Chapter 4 Forecasting 109

2. Seasonality is a data pattern that repeats itself after a period of days, weeks, months, or quar- ters. There are six common seasonality patterns:

Period of Pattern “Season” Length Number of

“Seasons” in Pattern

Week Day 7

Month Week 4 - 412 Month Day 28–31

Year Quarter 4

Year Month 12

Year Week 52

Restaurants and barber shops, for example, experience weekly seasons, with Saturday being the peak of business. Beer distributors forecast yearly patterns, with monthly seasons. Three “seasons”—May, July, and September—each contain a big beer-drinking holiday.

3. Cycles are patterns in the data that occur every several years. They are usually tied into the business cycle and are of major importance in short-term business analysis and planning. Predicting business cycles is difficult because they may be affected by political events or by international turmoil.

4. Random variations are “blips” in the data caused by chance and unusual situations. They follow no discernible pattern, so they cannot be predicted.

Figure 4.1 illustrates a demand over a four-year period. It shows the average, trend, seasonal components, and random variations around the demand curve. The average demand is the sum of the demand for each period divided by the number of data periods.

NAIVE APPROACH The simplest way to forecast is to assume that demand in the next period will be equal to demand in the most recent period. In other words, if sales of a product—say, Nokia cell phones—were 68 units in January, we can forecast that February’s sales will also be 68 phones. Does this make any sense? It turns out that for some product lines, this naive approach is the most cost-effective and efficient objective forecasting model. At least it provides a starting point against which more sophisticated models that follow can be compared.

MOVING AVERAGES Moving-averages forecasts use a number of historical actual data values to generate a forecast. Moving averages are useful if we can assume that market demands will stay fairly steady over time. A four-month moving average is found by simply summing the demand during the past four months and dividing by four. With each passing month, the most recent month’s data are added to the sum of the previous three months’ data, and the earliest month is dropped. This practice tends to smooth out short-term irregularities in the data series.

Naive approach A forecasting technique that assumes that demand in the next period is equal to demand in the most recent period.

Moving averages A forecasting method that uses an average of the n most recent periods of data to forecast the next period.

Seasonal peaks

Random variation

Actual demand line

Average demand over four years

Trend component

1

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Time (years) 2 3 4

FIGURE 4.1

Demand Charted Over Four Years with the Growth Trend and Seasonality Indicated

The peak “seasons” for sales of potato chips are the Super Bowl, Canada Day, Labour Day, and during the Stanley Cup final.

STUDENT TIP

Forecasting is easy when demand is stable. But with trend, seasonality, and cycles considered, the job is a lot more interesting.

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110 PART 1 Introduction to Operations Management

Mathematically, the simple moving average (which serves as an estimate of the next period’s demand) is expressed as

Moving average = Σ demand in previous n periods

n (4-1)

where n is the number of periods in the moving average—for example, four, five, or six months, respectively, for a four-, five-, or six-period moving average.

Example 1 shows how moving averages are calculated.

When a detectable trend or pattern is present, weights can be used to place more emphasis on recent values. This practice makes forecasting techniques more responsive to changes because more recent periods may be more heavily weighted. Choice of weights is somewhat arbitrary because there is no set formula to determine them. Therefore, deciding which weights to use requires some experience. For example, if the latest month or period is weighted too heavily, the forecast may reflect a large unusual change in the demand or sales pattern too quickly.

A weighted moving average may be expressed mathematically as:

Weighted moving average = Σ (Weight for period n) (Demand in period n)

ΣWeights (4-2)

LO3 Apply the naive, moving-average, exponential smoothing, and trend methods

Donna’s Garden Supply wants a three-month moving-average forecast, including a forecast for next January, for shed sales.

APPROACH c Storage shed sales are shown in the middle column of the table. A three-month moving average appears on the right.

Month Actual Shed Sales Three-Month Moving Average

January 10

February 12

March 13

April 16 (10 1 12 1 13) / 3 5 1123 May 19 (12 1 13 1 16) / 3 5 1323 June 23 (13 1 16 1 19) / 3 5 16

July 26 (16 1 19 1 23) / 3 5 19 13 August 30 (19 1 23 1 26) / 3 5 22 23 September 28 (23 1 26 1 30) / 3 5 26 13 October 18 (26 1 30 1 28) / 3 5 28

November 16 (30 1 28 1 18) / 3 5 2513 December 14 (28 1 18 1 16) / 3 5 20 23

SOLUTION c The forecast for December is 2023. To project the demand for sheds in the coming January, we sum the October, November, and December sales and divide by three: January forecast 5 (18 1 16 1 14)/3 5 16.

INSIGHT c Management now has a forecast that averages sales for the last three months. It is easy to use and understand.

LEARNING EXERCISE c If actual sales in December were 18 (rather than 14), what is the new January forecast? [Answer: 17 13]

RELATED PROBLEMS c 4.1a, 4.2b, 4.5a, 4.6, 4.8ab, 4.10a, 4.13b, 4.15, 4.47

EXCEL OM Data File Ch04Ex1.xlsx can be found at MyLab Operations Management.

ACTIVE MODEL 4.1 This example is further illustrated in Active Model 4.1 at MyLab Operations Management.

EXAMPLE 1

Determining the Moving Average

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Chapter 4 Forecasting 111

Example 2 shows how to calculate a weighted moving average.

Both simple and weighted moving averages are effective in smoothing out sudden fluctua- tions in the demand pattern to provide stable estimates. Moving averages do, however, present three problems:

1. Increasing the size of n (the number of periods averaged) does smooth out fluctuations bet- ter, but it makes the method less sensitive to real changes in the data.

2. Moving averages cannot pick up trends very well. Because they are averages, they will always stay within past levels and will not predict changes to either higher or lower levels. That is, they lag the actual values.

3. Moving averages require extensive records of past data.

2Donna’s Garden Supply (see Example 1) wants to forecast storage shed sales by weighting the past three months, with more weight given to recent data to make them more significant.

APPROACH c Assign more weight to recent data, as follows:

EXAMPLE

Determining the Weighted Moving Average

SOLUTION c The results of this weighted average forecast are as follows:

Month Actual Shed Sales Three-Month Weighted Moving Average

January 10

February 12

March 13

April 16 [(3 3 13) 1 (2 3 12) 1 (10)] / 6 5 12 16 May 19 [(3 3 16) 1 (2 3 13) 1 (12)] / 6 5 14 13 June 23 [(3 3 19) 1 (2 3 16) 1 (13)] / 6 5 17

July 26 [(3 3 23) 1 (2 3 19) 1 (16)] / 6 5 20 12 August 30 [(3 3 26) 1 (2 3 23) 1 (19)] / 6 5 23 56 September 28 [(3 3 30) 1 (2 3 26) 1 (23)] / 6 5 27 12 October 18 [(3 3 28) 1 (2 3 30) 1 (26)] / 6 5 28 13 November 16 [(3 3 18) 1 (2 3 28) 1 (30)] / 6 5 23 13 December 14 [(3 3 16) 1 (2 3 18) 1 (28)] / 6 5 18 23

INSIGHT c In this particular forecasting situation, you can see that more heavily weighting the latest month provides a much more accurate projection.

LEARNING EXERCISE c If the assigned weights were 0.50, 0.33, and 0.17 (instead of 3, 2, and 1), what is the forecast for January’s weighted moving average? Why? [Answer: There is no change.] These are the same relative weights. Note that the sum of the weights is 1 now, so there is no need for a denominator. When the weights sum to 1, calculations tend to be simpler.

RELATED PROBLEMS c 4.1b, 4.2c, 4.5c, 4.6, 4.7, 4.10b

EXCEL OM Data file Ch04Ex2.xlsx can be found at MyLab Operations Management.

Weights Applied Period

3 Last month 2 2 months ago 1 3 months ago 6 Sum of weights

Forecast for this month 5

3 * Sales last mo. + 2 * Sales 2 mos. ago + 1 * Sales 3 mos. ago Sum of the weights

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112 PART 1 Introduction to Operations Management

Figure 4.2, a plot of the data in Examples 1 and 2, illustrates the lag effect of the moving- average models. Note that both the moving-average and weighted moving average lines lag the actual demand. The weighted moving average, however, usually reacts more quickly to demand changes. Even in periods of downturn (see November and December), it more closely tracks the demand.

EXPONENTIAL SMOOTHING Exponential smoothing is a sophisticated weighted moving average forecasting method that is still fairly easy to use. It involves very little recordkeeping of past data. The basic exponential smoothing formula can be shown as follows:

New forecast = Last period’s forecast + α (Last period’s actual demand - Last period’s forecast) (4-3)

where a is a weight, or smoothing constant, chosen by the forecaster, that has a value between 0 and 1. Equation (4-3) can also be written mathematically as:

Ft = Ft - 1 + α (At-1 - Ft-1) (4-4)

where Ft 5 new forecast Ft−1 5 previous period’s forecast

a 5 smoothing (or weighting) constant (0 ≤ a ≤ 1) At−1 5 previous period’s actual demand

The concept is not complex. The latest estimate of demand is equal to the old estimate adjusted by a fraction of the difference between the last period’s actual demand and the old esti- mate. Example 3 shows how to use exponential smoothing to derive a forecast.

Weighted moving average

Actual sales

Moving average

Jan. Feb. Mar. Apr. May June

Month

July Aug. Sept. Oct. Nov. Dec.

20

S a le

s d

e m

a n

d

15

10

5

25

30

FIGURE 4.2

Actual Demand vs. Moving- Average and Weighted – Moving- Average Methods for Donna’s Garden Supply

Exponential smoothing A weighted moving average forecasting technique in which data points are weighted by an exponential function.

Smoothing constant The weighting factor, α, used in an exponential smoothing fore- cast, a number between 0 and 1.

In January, a car dealer predicted February demand for 142 Ford Mustangs. Actual February demand was 153 autos. Using a smoothing constant chosen by management of a 5 0.20, the dealer wants to forecast March demand using the exponential smoothing model.

APPROACH c The exponential smoothing model in Equations (4-3) and (4-4) can be applied.

SOLUTION c Substituting the sample data into the formula, we obtain:

New forecast (for March demand) = 142 + 0.2(153 - 142) = 142 + 2.2 = 144.2

Thus, the March demand forecast for Ford Mustangs is rounded to 144.

EXAMPLE 3

Determining a Forecast Via Exponential Smoothing

Moving-average methods always lag behind when there is a trend present, as shown by the blue line (actual sales) for January through August.

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The smoothing constant, a, is generally in the range from 0.05 to 0.50 for business appli- cations. It can be changed to give more weight to recent data (when a is high) or more weight to past data (when a is low). When a reaches the extreme of 1.0, then in Equation (4-4), Ft 5 1.0At−1. All the older values drop out, and the forecast becomes identical to the naive model mentioned earlier in this chapter. That is, the forecast for the next period is just the same as this period’s demand.

The following table helps illustrate this concept. For example, when a 5 0.5, we can see that the new forecast is based almost entirely on demand in the last three or four periods. When a 5 0.1, the forecast places little weight on recent demand and takes many periods (about 19) of historical values into account.

Weight Assigned to

Smoothing Constant

Most Recent Period (A)

2nd Most Recent Period

A(1 – A)

3rd Most Recent Period

A(1 − A)2

4th Most Recent Period

A(1 − A)3 5th Most Recent Period A(1 − A)4

a 5 0.1 0.1 0.09 0.081 0.073 0.066

a 5 0.5 0.5 0.25 0.125 0.063 0.031

SELECTING THE SMOOTHING CONSTANT The exponential smoothing approach is easy to use, and it has been successfully applied in virtually every type of business. However, the appropriate value of the smoothing constant, a, can make the difference between an accurate forecast and an inaccurate forecast. High values of a are chosen when the underlying average is likely to change. Low values of a are used when the underlying average is fairly stable. In picking a value for the smoothing constant, the objective is to obtain the most accurate forecast.

MEASURING FORECAST ERROR The overall accuracy of any forecasting model—moving average, exponential smoothing, or other—can be determined by comparing the forecasted values with the actual or observed val- ues. If Ft denotes the forecast in period t, and At denotes the actual demand in period t, the fore- cast error (or deviation) is defined as:

Forecast error = Actual demand - Forecast value = At - Ft Several measures are used in practice to calculate the overall forecast error. These measures

can be used to compare different forecasting models, as well as to monitor forecasts to ensure they are performing well. Three of the most popular measures are mean absolute deviation (MAD), mean squared error (MSE), and mean absolute percent error (MAPE). We now describe and give an example of each.

MEAN ABSOLUTE DEVIATION The first measure of the overall forecast error for a model is the mean absolute deviation (MAD). This value is computed by taking the sum of the absolute values of the individual forecast errors (deviations) and dividing by the number of periods of data (n):

MAD = Σ ∙ Actual - Forecast ∙

n (4-5)

INSIGHT c    Using just two pieces of data, the forecast and the actual demand, plus a smoothing constant, we developed a forecast of 144 Ford Mustangs for March.

LEARNING EXERCISE c   If the smoothing constant is changed to 0.30, what is the new forecast? [Answer: 145.3]

RELATED PROBLEMS c   4.1c, 4.3, 4.4, 4.5d, 4.6, 4.9d 4.11, 4.12, 4.13a, 4.17, 4.18, 4.37, 4.43, 4.47, 4.49

Mean absolute deviation (MAD) A measure of the overall forecast error for a model.

LO4 Compute three measures of forecast accuracy

The forecast error tells us how well the model performed against itself using past data.

STUDENT TIP

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114 PART 1 Introduction to Operations Management

During the past eight quarters, the Port of Halifax has unloaded large quantities of grain from ships. The port’s operations manager wants to test the use of exponential smoothing to see how well the tech- nique works in predicting tonnage unloaded. He guesses that the forecast of grain unloaded in the first quarter was 175 tonnes. Two values of a are to be examined: a 5 0.10 and a 5 0.50.

APPROACH c   Compare the actual data with the data we forecast (using each of the two a-values) and then find the absolute deviation and MADs.

SOLUTION c   The following table shows the detailed calculations for a 5 0.10 only:

Quarter

Actual Tonnage Unloaded Forecast with A 5 0.10

Forecast with A 5 0.50

1 180 175 175

2 168 175.50 5 175.00 1 0.10(180 − 175) 177.50

3 159 174.75 5 175.50 1 0.10(168 − 175.50) 172.75

4 175 173.18 5 174.75 1 0.10(159 − 174.75) 165.88

5 190 173.36 5 173.18 1 0.10(175 − 173.18) 170.44

6 205 175.02 5 173.36 1 0.10(190 − 173.36) 180.22

7 180 178.02 5 175.02 1 0.10(205 − 175.02) 192.61

8 182 178.22 5 178.02 1 0.10(180 − 178.02) 186.30

9 ? 178.59 5 178.22 1 0.10(182 − 178.22) 184.15

To evaluate the accuracy of each smoothing constant, we can compute forecast errors in terms of abso- lute deviations and MADs:

Quarter

Actual Tonnage Unloaded

Forecast with

A 5 0.10

Absolute Deviation for A 5 0.10

Forecast with A 5 0.50

Absolute Deviation for A 5 0.50

1 180 175 5.00 175 5.00

2 168 175.50 7.50 177.50 9.50

3 159 174.75 15.75 172.75 13.75

4 175 173.18 1.82 165.88 9.12

5 190 173.36 16.64 170.44 19.56

6 205 175.02 29.98 180.22 24.78

7 180 178.02 1.98 192.61 12.61

8 182 178.22 3.78 186.30 4.30 Sum of absolute deviations:

MAD = Σ ∙ Deviations ∙

n

82.45

10.31

98.62

12.33

INSIGHT c On the basis of this comparison of the two MADs, a smoothing constant of a 5 0.10 is preferred to a 5 0.50 because its MAD is smaller.

LEARNING EXERCISE c If the smoothing constant is changed from a 5 0.10 to a 5 0.20, what is the new MAD? [Answer: 10.21.]

RELATED PROBLEMS c 4.5b, 4.8c, 4.9c, 4.14, 4.23, 4.37a

EXCEL OM Data File Ch04Ex4a.xlsx and Ch04Ex4b.xlsx can be found at MyLab Operations Management.

ACTIVE MODEL 4.2 This example is further illustrated in Active Model 4.2 at MyLab Operations Management.

EXAMPLE 4

Determining the Mean Absolute Deviation (MAD)

Most computerized forecasting software includes a feature that automatically finds the smoothing constant with the lowest forecast error. Some software modifies the a-value if errors become larger than acceptable.

Example 4 applies MAD, as a measure of overall forecast error, by testing two values of a.

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Chapter 4 Forecasting 115

MEAN SQUARED ERROR The mean squared error (MSE) is a second way of measuring over- all forecast error. MSE is the average of the squared differences between the forecasted and observed values. Its formula is:

MSE = Σ(Forecast errors)2

n (4-6)

Example 5 finds the MSE for the Port of Halifax introduced in Example 4.

Mean squared error (MSE) The average of the squared differ- ences between the forecasted and observed values.

5The operations manager for the Port of Halifax now wants to compute MSE for a 5 0.10.

APPROACH c Use the same forecast data for a 5 0.10 from Example 4, then compute the MSE using Equation (4-6).

SOLUTION c

EXAMPLE

Determining the Mean Squared Error (MSE)

Quarter Actual Tonnage Unloaded Forecast for A 5 0.10 (Error)2

1 180 175 52 5 25

2 168 175.50 (−7.5)2 5 56.25

3 159 174.75 (−15.75)2 5 248.06

4 175 173.18 (1.82)2 5 3.33

5 190 173.36 (16.64)2 5 276.89

6 205 175.02 (29.98)2 5 898.70

7 180 178.02 (1.98)2 5 3.92

8 182 178.22 (3.78)2 5 14.31

Sum of errors squared 5 1526.46

MSE = Σ(Forecast errors)2

n = 1526.46>8 = 190.8

INSIGHT c Is this MSE 5 190.8 good or bad? It all depends on the MSEs for other forecasting approaches. A low MSE is better because we want to minimize MSE. MSE exaggerates errors because it squares them.

LEARNING EXERCISE c Find the MSE for a 5 0.50. [Answer: MSE 5 195.24. The result indi- cates that a 5 0.10 is a better choice because we seek a lower MSE. Coincidentally, this is the same conclusion we reached using MAD in Example 4.]

RELATED PROBLEMS c 4.8d, 4.14, 4.20

A drawback of using the MSE is that it tends to accentuate large deviations due to the squared term. For example, if the forecast error for period 1 is twice as large as the error for period 2, the squared error in period 1 is four times as large as that for period 2. Hence, using MSE as the measure of forecast error typically indicates that we prefer to have several smaller deviations rather than even one large deviation.

MEAN ABSOLUTE PERCENT ERROR A problem with both the MAD and MSE is that their values depend on the magnitude of the item being forecast. If the forecast item is measured in thou- sands, the MAD and MSE values can be very large. To avoid this problem, we can use the mean absolute percent error (MAPE). This is computed as the average of the absolute difference between the forecasted and actual values, expressed as a percentage of the actual values. That is, if we have forecasted and actual values for n periods, the MAPE is calculated as:

MAPE = a

n

i = 1 100 ∙ Actuali - Forecasti ∙>Actua li

n (4-7)

Example 6 illustrates the calculations using the data from Examples 4 and 5.

Mean absolute percent error (MAPE) The average of the absolute differences between the forecast and actual values, expressed as a percentage of actual values.

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116 PART 1 Introduction to Operations Management

The MAPE is perhaps the easiest measure to interpret. For example, a result that the MAPE is 6% is a clear statement that is not dependent on issues such as the magnitude of the input data. Table 4.1 summarizes how MAD, MSE, and MAPE differ.

EXPONENTIAL SMOOTHING WITH TREND ADJUSTMENT Simple exponential smoothing, the technique we just illustrated in Examples 3 to 6, is like any other moving-average technique: It fails to respond to trends. Other forecasting techniques that can deal with trends are certainly available. However, because exponential smoothing is such a popular modelling approach in business, let us look at it in more detail.

Here is why exponential smoothing must be modified when a trend is present. Assume that demand for our product or service has been increasing by 100 units per month and that we have

The Port of Halifax wants to now calculate the MAPE when a 5 0.10.

APPROACH c Equation (4-7) is applied to the forecast data computed in Example 4.

SOLUTION c

Quarter Actual Tonnage

Unloaded Forecast for A 5 0.10

Absolute Percent Error 100(|error|/actual)

1 180 175.00 100(5/180) 5 2.78%

2 168 175.50 100(7.5/168) 5 4.46%

3 159 174.75 100(15.75/159) 5 9.90%

4 175 173.18 100(1.82/175) 5 1.05%

5 190 173.36 100(16.64/190) 5 8.76%

6 205 175.02 100(29.98/205) 5 14.62%

7 180 178.02 100(1.98/180) 5 1.10%

8 182 178.22 100(3.78/182) 5 2.08%

Sum of % errors 5 44.75%

MAPE = Σ absolute percent errors

n =

44.75% 8

= 5.59%

INSIGHT c MAPE expresses the error as a percentage of the actual values, undistorted by a single large value.

LEARNING EXERCISE c What is MAPE when a is 0.50? [Answer: MAPE 5 6.75%. As was the case with MAD and MSE, the a 5 0.1 was preferable for this series of data.]

RELATED PROBLEMS c 4.8e, 4.33c

EXAMPLE 6

Determining the Mean Absolute Percent Error (MAPE)

Table 4.1 Comparison of Measures of Forecast Error

Measure Meaning Equation Application to chapter example

Mean absolute deviation (MAD)

How much the forecast missed the target

MAD = g 0 Actual - Forecast 0

n (4-5)

For α = 0.10 in Example 4, the forecast for grain unloaded was off by an average of 10.31 tonnes.

Mean squared error (MSE)

The square of how much the forecast missed the target

MSE = g(Forecast errors)2

n (4-6)

For α = .10 in Example 5, the square of the forecast error was 190.8. This number does not have a physical meaning but is useful when compared to the MSE of another forecast.

Mean absolute percent error (MAPE)

The average percent error

MAPE = a

n

i = 1 100 ∙ Actuali - Forecasti ∙ >Actuali

n (4-7)

For α = .10 in Example 6, the forecast is off by 5.59% on average. As in Examples 4 and 5, some forecasts were too high, and some were low.

M04_HEIZ8076_03_SE_C04.indd 116 27/11/18 8:50 PM

Chapter 4 Forecasting 117

been forecasting with a 5 0.4 in our exponential smoothing model. The following table shows a severe lag in the second, third, fourth, and fifth months, even when our initial estimate for the first month is perfect:

Month Actual Demand Forecast for Month T(FT)

1 100 F 1 5 100 (given)

2 200 F 2 5 F 1 1 a (A 1 − F 1 ) 5 100 1 0.4(100 − 100) 5 100

3 300 F 3 5 F 2 1 a (A 2 − F 2 ) 5 100 1 0.4(200 − 100) 5 140

4 400 F 4 5 F 3 1 a (A 3 − F 3 ) 5 140 1 0.4(300 − 140) 5 204

5 500 F 5 5 F 4 1 a (A 4 − F 4 ) 5 204 1 0.4(400 − 204) 5 282

To improve our forecast, let us illustrate a more complex exponential smoothing model, one that adjusts for trend. The idea is to compute an exponentially smoothed average of the data and then adjust for positive or negative lag in trend. The new formula is:

Forecast including trend(FITt) = Exponentially smoothed forecast(Ft) + Exponentially smoothed trend(Tt) (4-8)

With trend-adjusted exponential smoothing, estimates for both the average and the trend are smoothed. This procedure requires two smoothing constants: a for the average and b for the trend. We then compute the average and trend each period:

Ft 5 a(Actual demand last period) 1 (1 − a)(Forecast last period 1 Trend estimate last period)

or:

Ft = α(At - 1) + (1 - α)(Ft - 1 + Tt - 1) (4-9)

Tt = b(Forecast this period - Forecast last period) + (1 - b)(Trend estimate last period)

or:

Tt = b(Ft - Ft - 1) + (1 - b)Tt - 1 (4-10) where Ft 5 exponentially smoothed forecast of the data series in period t

Tt 5 exponentially smoothed trend in period t At 5 actual demand in period t a 5 smoothing constant for the average (0 ≤ a ≤ 1) b 5 smoothing constant for the trend (0 ≤ b ≤ 1)

So the three steps to compute a trend-adjusted forecast are:

Step 1: Compute Ft, the exponentially smoothed forecast for period t, using Equation (4-9). Step 2: Compute the smoothed trend, Tt, using Equation (4-10). Step 3: Calculate the forecast including trend, FITt, by the formula FITt 5 Ft 1 Tt (from

Equation (4-8)).

Example 7 shows how to use trend-adjusted exponential smoothing.

7A large Quebec manufacturer wants to forecast demand for a piece of pollution control equipment. A review of past sales, as shown below, indicates that an increasing trend is present:

EXAMPLE

Computing a Trend- Adjusted Exponential Smoothing Forecast

Month (t) Actual Demand (At) Month (t) Actual Demand (At)

1 12 6 21

2 17 7 31

3 20 8 28

4 19 9 36

5 24 10 ?

Smoothing constants are assigned the values of a 5 0.2 and b 5 0.4. The firm assumes the initial fore- cast for month 1 (F1) was 11 units and the trend over that period (T1) was 2 units.

M04_HEIZ8076_03_SE_C04.indd 117 27/11/18 8:50 PM

118 PART 1 Introduction to Operations Management

APPROACH c A trend-adjusted exponential smoothing model, using Equations (4-9), (4-10), and (4-8) and the three steps above, is employed.

SOLUTION c Step 1: Forecast for month 2:

F2 = α A1 + (1 - α)(F1 + T1) F2 = (0.2)(12) + (1 - 0.2)(11 + 2)

= 2.4 + (0.8)(13) = 2.4 + 10.4 = 12.8 units

Step 2: Compute the trend in period 2:

T2 = b(F2 - F1) + (1 - b)T1 = 0.4(12.8 - 11) + (1 - 0.4)(2) = (0.4)(1.8) + (0.6)(2) = 0.72 + 1.2 = 1.92

Step 3: Compute the forecast including trend (FITt):

FIT2 = F2 + T2 = 12.8 + 1.92 = 14.72 units

We will also do the same calculations for the third month:

Step 1: F3 = α A2 + (1 - α)(F2 + T2) = (0.2)(17) + (1 - 0.2)(12.8 + 1.92) = 3.4 + (0.8)(14.72) = 3.4 + 11.78 = 15.18 Step 2: T3 = b (F3 - F2) + (1 - b)T2 = (0.4)(15.18 - 12.8) + (1 - 0.4)(1.92) = (0.4)(2.38) + (0.6)(1.92) = 0.952 + 1.152 = 2.10 Step 3: FIT3 = F3 + T3 = 15.18 + 2.10 = 17.28 Table 4.2 completes the forecasts for the 10-month period.

Month Actual Demand Smoothed

Forecast, Ft

Smoothed Trend, Tt

Forecast Including Trend, FITt

1 12 11.00 2.00 13.00

2 17 12.80 1.92 14.72

3 20 15.18 2.10 17.28

4 19 17.82 2.32 20.14

5 24 19.91 2.23 22.14

6 21 22.51 2.38 24.89

7 31 24.11 2.07 26.18

8 28 27.14 2.45 29.59

9 36 29.28 2.32 31.60

10 — 32.48 2.68 35.16

Table 4.2 Forecast With α 5 0.2 and β 5 0.4

INSIGHT c Figure 4.3 compares actual demand (At) to an exponential smoothing forecast that includes trend (FITt). FIT picks up the trend in actual demand. A simple exponential smoothing model (as we saw in Examples 3 and 4) trails far behind.

M04_HEIZ8076_03_SE_C04.indd 118 27/11/18 8:50 PM

Chapter 4 Forecasting 119

The value of the trend-smoothing constant, b, resembles the a constant because a high b is more responsive to recent changes in trend. A low b gives less weight to the most recent trends and tends to smooth out the present trend. Values of b can be found by the trial-and-error approach or by using sophisticated commercial forecasting software, with the MAD used as a measure of comparison.

Simple exponential smoothing is often referred to as first-order smoothing, and trend-adjusted smoothing is called second-order, or double, smoothing. Other advanced exponential smoothing models are also used, including seasonal-adjusted and triple smoothing, but these are beyond the scope of this book.2

TREND PROJECTIONS The last time-series forecasting method we will discuss is trend projection. This technique fits a trend line to a series of historical data points and then projects the line into the future for medium- to long-range forecasts. Several mathematical trend equations can be developed (e.g., exponential and quadratic), but in this section we will look at linear (straight-line) trends only.

If we decide to develop a linear trend line by a precise statistical method, we can apply the least squares method. This approach results in a straight line that minimizes the sum of the squares of the vertical differences or deviations from the line to each of the actual observations. Figure 4.4 illustrates the least squares approach.

A least squares line is described in terms of its y-intercept (the height at which it intercepts the y-axis) and its expected change (slope). If we can compute the y-intercept and slope, we can express the line with the following equation:

yn = a + bx (4-11)

Trend projection A time-series forecasting method that fits a trend line to a series of historical data points and then projects the line into the future for forecasts.

Actual demand (At )

40

35

30

25

20

15

10

5

0

1 2 3 4 5 Time (months)

Forecast including trend (FITt ) with a = 0.2 and b = 0.4

P ro

d u

c t

d e m

a n

d

6 7 8 9

FIGURE 4.3

Exponential Smoothing With Trend-Adjustment Forecasts Compared to Actual Demand Data

LEARNING EXERCISE c Using the data for actual demand for the nine months, compute the exponentially smoothed forecast without trend (using Equation (4-4), as we did earlier in Examples 3 and 4). Apply a 5 0.2 and assume an initial forecast for month 1 of 11 units. Then plot the months 2–10 forecast values on Figure 4.3. What do you notice? [Answer: Month 10 forecast 5 24.65. All the points are below and lag the trend-adjusted forecast.]

RELATED PROBLEMS c 4.19, 4.20, 4.21, 4.22, 4.44

EXCEL OM Data File Ch04Ex7.xlsx can be found at MyLab Operations Management.

ACTIVE MODEL 4.3 This example is further illustrated in Active Model 4.3 at MyLab Operations Management.

2 For more details, see D. Groebner, P. Shannon, P. Fry, and K. Smith, Business Statistics, 8th ed. (Upper Saddle River, NJ: Prentice Hall, 2011).

M04_HEIZ8076_03_SE_C04.indd 119 27/11/18 8:50 PM

120 PART 1 Introduction to Operations Management

where yn (called “y hat”) 5 computed value of the variable to be predicted (called the depend- ent variable)

a 5 y-axis intercept b 5 slope of the regression line (or the rate of change in y for given

changes in x) x 5 the independent variable (which in this case is time)

Statisticians have developed equations that we can use to find the values of a and b for any regression line. The slope b is found by:

b = Σxy - nxy Σx2 - nx2

(4-12)

where b 5 slope of the regression line Σ 5 summation sign x 5 known values of the independent variable y 5 known values of the dependent variable x 5 average of the x-values y 5 average of the y-values n 5 number of data points or observations

We can compute the y-intercept a as follows:

a = y - bx (4-13) Example 8 shows how to apply these concepts.

The demand for electric power at Niagara Power Generation over the period 2010 to 2016 is shown in the following table, in megawatts. The firm wants to forecast 2017 demand by fitting a straight-line trend to these data.

Year Electrical Power

Demand Year Electrical Power

Demand

2010 74 2014 105

2011 79 2015 142

2012 80 2016 122

2013 90

APPROACH c With a series of data over time, we can minimize the computations by transforming the values of x (time) to simpler numbers. Thus, in this case, we can designate 2010 as year 1, 2011 as year 2, and so on. Then Equations (4-12) and (4-13) can be used to create the trend projection model.

EXAMPLE 8

Forecasting With Least Squares

Time period

Trend line, y = a + bx V

a lu

e s o

f d

e p

e n

d e n

t v a ri

a b

le (

y -v

a lu

e s )

Deviation3

Deviation1 (error)

Deviation4

Deviation5 Deviation6

Deviation7

Deviation2

Actual observation (y-value)

1 2 3 4 5 6 7

ˆ

FIGURE 4.4

The Least Squares Method for Finding the Best-Fitting Straight Line, Where the Asterisks Are the Locations of the Seven Actual Observa- tions or Data Points

M04_HEIZ8076_03_SE_C04.indd 120 27/11/18 8:50 PM

Chapter 4 Forecasting 121

LEARNING EXERCISE c Estimate demand for 2018. [Answer: 151.56 or 152 megawatts.]

RELATED PROBLEMS c 4.6, 4.13c, 4.16, 4.25, 4.39, 4.49

EXCEL OM Data file Ch4Ex8.xlsx can be found at MyLab Operations Management.

ACTIVE MODEL 4.4 This example is further illustrated in Active Model 4.4 at MyLab Operations Management.

2010 2011 2012 2013 2014 2015 2016 2017 2018

160

150

140

130

120

110

100

90

80

70

60

50

Year

P o

w e r

d e m

a n

d (

m e g

a w

a tt

s )

Trend line, y = 56.70 + 10.54xˆ

FIGURE 4.5

Electrical Power and the Computed Trend Line

SOLUTION c

Year Time

Period (x) Electric Power

Demand (y) x2 xy

2010 1 74 1 74

2011 2 79 4 158

2012 3 80 9 240

2013 4 90 16 360

2014 5 105 25 525

2015 6 142 36 852

2016 7 122 49 854 Σx = 28 Σy = 692 Σx2 = 140 Σxy = 3063

x = Σx n

= 28 7

= 4 y = Σy n

= 692 7

= 98.86

b = Σxy - nx y Σx2 - nx2

= 3063 - (7)(4)(98.86)

140 - (7)(42) =

295 28

= 10.54

a = y - bx = 98.86 - 10.54(4) = 56.70

Thus, the least squares trend equation is yn5 56.70 1 10.54x. To project demand in 2017, we first denote the year 2017 in our new coding system as x 5 8:

Demand in 2017 = 56.70 + 10.54(8) = 141.02, or 141 megawatts

INSIGHT c To evaluate the model, we plot both the historical demand and the trend line in Figure 4.5. In this case, we may wish to be cautious and try to understand the 2015 to 2016 swing in demand.

M04_HEIZ8076_03_SE_C04.indd 121 27/11/18 8:51 PM

122 PART 1 Introduction to Operations Management

Here are the steps we will follow for a company that has “seasons” of one month:

1. Find the average historical demand each season (or month in this case) by summing the demand for that month in each year and dividing by the number of years of data available. For example, if, in January, we have seen sales of 8, 6, and 10 over the past three years, average January demand equals (8 1 6 1 10)/3 5 8 units.

2. Compute the average demand over all months by dividing the total average annual demand by the number of seasons. For example, if the total average demand for a year is 120 units and there are 12 seasons (each month), the average monthly demand is 120/12 5 10 units.

3. Compute a seasonal index for each season by dividing that month’s actual historical demand (from step 1) by the average demand over all months (from step 2). For example, if the aver- age historical January demand over the past three years is 8 units and the average demand over all months is 10 units, the seasonal index for January is 8/10 5 0.80. Likewise, a sea- sonal index of 1.20 for February would mean that February’s demand is 20% larger than the average demand over all months.

LO5 Develop seasonal indices

Demand for many products is seasonal. Yamaha, the manufacturer of these jet skis and snowmobiles, produces products with complemen- tary demands to address seasonal fluctuations.

Ci ty

Fi le

s/ W

ire Im

ag e/

G et

ty Im

ag es

D ic

k Lo

ek /T

or on

to S

ta r/

G et

ty Im

ag es

NOTES ON THE USE OF THE LEAST SQUARES METHOD Using the least squares method implies that we have met three requirements:

1. We always plot the data because least squares data assume a linear relationship. If a curve appears to be present, curvilinear analysis is probably needed.

2. We do not predict time periods far beyond our given database. For example, if we have 20 months’ worth of average prices of Microsoft stock, we can forecast only three or four months into the future. Forecasts beyond that have little statistical validity. Thus, you cannot take five years’ worth of sales data and project 10 years into the future. The world is too uncertain.

3. Deviations around the least squares line (see Figure 4.4) are assumed to be random. They are nor- mally distributed, with most observations close to the line and only a smaller number farther out.

SEASONAL VARIATIONS IN DATA Seasonal variations in data are regular up-and-down movements in a time series that relate to recurring events such as weather or holidays. Demand for coal and fuel oil, for example, peaks during cold winter months. Demand for golf clubs or sunscreen may be highest in summer.

Seasonality may be applied to hourly, daily, weekly, monthly, or other recurring patterns. Fast-food restaurants experience daily surges at noon and again at 5:00 p.m. Movie theatres see higher demand on Friday and Saturday evenings. Canada Post, Toys “R” Us, and Hallmark card shops also exhibit seasonal variation in customer traffic and sales.

Similarly, understanding seasonal variations is important for capacity planning in organizations that handle peak loads. These include electric power companies during extreme cold and warm peri- ods, banks on Friday afternoons, and buses and subways during the morning and evening rush hours.

Time-series forecasts like those in Example 8 involve reviewing the trend of data over a series of time periods. The presence of seasonality makes adjustments in trend-line forecasts necessary. Seasonality is expressed in terms of the amount that actual values differ from average values in the time series. Analyzing data in monthly or quarterly terms usually makes it easy for a statistician to spot seasonal patterns. Seasonal indices can then be developed by several common methods.

In what is called a multiplicative seasonal model, seasonal factors are multiplied by an esti- mate of average demand to produce a seasonal forecast. Our assumption in this section is that trend has been removed from the data. Otherwise, the magnitude of the seasonal data will be distorted by the trend.

Seasonal variations Regular upward or downward movements in a time series that tie to recurring events.

John Deere understands seasonal variations: It has been able to obtain 70% of its orders in advance of seasonal use so it can smooth production.

STUDENT TIP

M04_HEIZ8076_03_SE_C04.indd 122 27/11/18 8:51 PM

Chapter 4 Forecasting 123

A Winnipeg distributor of Sony laptop computers wants to develop monthly indices for sales. Data from 2016–2018, by month, are available.

APPROACH c Follow the five steps listed above.

SOLUTION c

Demand Average 2016–2018 Demand

Average Monthly Demanda

Seasonal IndexbMonth 2016 2017 2018

Jan. 80 85 105 90 94 0.957 (5 90/94)

Feb. 70 85 85 80 94 0.851 (5 80/94)

Mar. 80 93 82 85 94 0.904 (5 85/94)

Apr. 90 95 115 100 94 1.064 (5 100/94)

May 113 125 131 123 94 1.309 (5 123/4)

June 110 115 120 115 94 1.223 (5 115/94)

July 100 102 113 105 94 1.117 (5 105/94)

Aug. 88 102 110 100 94 1.064 (5 100/94)

Sept. 85 90 95 90 94 0.957 (5 90/94)

Oct. 77 78 85 80 94 0.851 (5 80/94)

Nov. 75 82 83 80 94 0.851 (5 80/94)

Dec. 82 78 80 80 94 0.851 (5 80/94)

Total average annual demand 5 1128

aAverage monthly demand = 1128

12 months = 94 bSeasonal index =

Average 201692018 monthly demand

Average monthly demand

EXAMPLE 9

Determining Seasonal Indices

If we expected the 2019 annual demand for computers to be 1200 units, we would use these seasonal indices to forecast the monthly demand as follows:

Month Demand Month Demand

Jan. 1200 12

* 0.957 = 96 July 1200

12 * 1.117 = 112

Feb. 1200 12

* 0.851 = 85 Aug. 1200

12 * 1.064 = 106

Mar 1200 12

* 0.904 = 90 Sept. 1200

12 * 0.957 = 96

Apr. 1200 12

* 1.064 = 106 Oct. 1200

12 * 0.851 = 85

May 1200 12

* 1.309 = 131 Nov. 1200

12 * 0.851 = 85

June 1200 12

* 1.223 = 122 Dec. 1200

12 * 0.851 = 85

INSIGHT c  Think of these indices as percentages of average sales. The average sales (without sea- sonality) would be 94, but with seasonality, sales fluctuate from 85% to 131% of average.

LEARNING EXERCISE c   If 2019 annual demand is 1150 laptops (instead of 1200), what will the January, February, and March forecasts be? [Answer: 91.7, 81.5, and 86.6, which can be rounded to 92, 82, and 87.]

RELATED PROBLEMS c  4.27, 4.28

EXCEL OM Data File Ch04Ex9.xlsx can be found at MyLab Operations Management.

4. Estimate next year’s total annual demand. 5. Divide this estimate of total annual demand by the number of seasons, and then multiply it

by the seasonal index for that month. This provides the seasonal forecast.

Example 9 illustrates this procedure as it computes seasonal indices from historical data.

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124 PART 1 Introduction to Operations Management

10 San Diego Hospital wants to improve its forecasting by applying both trend and seasonal indices to 66 months of data it has collected. It will then forecast “patient-days” over the coming year.

APPROACH c  A trend line is created; then monthly seasonal indices are computed. Finally, a mul- tiplicative seasonal model is used to forecast months 67 to 78.

SOLUTION c    Using 66 months of adult inpatient hospital days, the following equation was computed:

yn = 8090 + 21.5x where yn = patient-days

x 5 time, in months

Based on this model, which reflects only trend data, the hospital forecasts patient-days for the next month (period 67) to be:

Patient@days = 8090 + (21.5)(67) = 9530(trend only)

While this model, as plotted in Figure 4.6, recognized the upward trend line in the demand for inpatient services, it ignored the seasonality that the administration knew to be present.

EXAMPLE

Applying Both Trend and Seasonal Indices

Jan. 67

Feb. 68

9 000

9 600

9 800

10 000

10 200

9 400

9 200I n

p a

ti e

n t-

d ay

s

Mar. 69

Apr. 70

9594 9530

9551

9573

May 71

9616

June 72

9637

July 73

9659

Aug. 74

Sept. 75

9680

9702

Oct. 76

9724

Dec. 78

9766

Nov. 77

9745

Month (period = 67 for Jan. through 78 for Dec.)

FIGURE 4.6

Trend Data for San Diego Hospital

Source: From “Modern Methods Improve Hospital Forecasting” by W. E. Sterk and E. G. Shryock from Healthcare Financial Man- agement, Vol. 41, no. 3, p. 97. Reprinted by permission of Healthcare Financial Manage- ment Association.

The following table provides seasonal indices based on the same 66 months. Such seasonal data, by the way, were found to be typical of hospitals nationwide.

Seasonality Indices for Adult Inpatient-Days at San Diego Hospital

Month Seasonality Index Month Seasonality Index

January 1.04 July 1.03

February 0.97 August 1.04

March 1.02 September 0.97

April 1.01 October 1.00

May 0.99 November 0.96

June 0.99 December 0.98

These seasonal indices are graphed in Figure 4.7. Note that January, March, July, and August seem to exhibit significantly higher patient-days on average, while February, September, November, and December experience lower patient-days.

For simplicity, only three periods are used for each monthly index in the preceding example. Example 10 illustrates how indices that have already been prepared can be applied to adjust trend-line forecasts for seasonality.

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Chapter 4 Forecasting 125

Jan. 67

Feb. 68

0.94

0.96

0.92

0.98

1.00

1.02

1.04

1.06

Month (period = 67 for Jan. through 78 for Dec.)

In d

e x f

o r

in p

a ti

e n

t- d

a y s

Mar. 69

Apr. 70

1.01

1.04

0.97

1.02

May 71

0.99

June 72

0.99

July 73

1.03

Aug. 74

Sept. 75

1.04

0.97

Oct. 76

1.00

Dec. 78

0.98

Nov. 77

0.96

FIGURE 4.7

Seasonal Index for San Diego Hospital

A graph showing the forecast that combines both trend and seasonality appears in Figure 4.8.

Jan. 67

Feb. 68

9400

9200

9800

9000

10 200

10 000

9600

Month (period = 67 for Jan. through 78 for Dec.)

In p

a ti

e n

t- d

a y s

Mar. 69

Apr. 70

May 71

June 72

July 73

Aug. 74

Sept. 75

Oct. 76

Dec. 78

Nov. 77

9691

9911

9265

9764

9520 9542

9949

10 068

9411

9724

9572

9355

FIGURE 4.8

Combined Trend and Seasonal Forecast

INSIGHT c    Notice that with trend only, the September forecast is 9702, but with both trend and seasonal adjustments, the forecast is 9411. By combining trend and seasonal data, the hospital was better able to forecast patient-days and the related staffing and budgeting vital to effective operations.

LEARNING EXERCISE c  If the slope of the trend line for patient-days is 22.0 (rather than 21.5) and the index for December is 0.99 (instead of 0.98), what is the new forecast for December patient- days? [Answer: 9708.]

RELATED PROBLEMS c  4.26, 4.29

However, neither the trend data nor the seasonal data alone provide a reasonable forecast for the hospital. Only when the hospital multiplied the trend-adjusted data times the appropriate seasonal index did it obtain good forecasts. Thus, for period 67 (January):

Patient@days = (Trend@adjusted forecast) (Monthly seasonal index) = (9530)(1.04) = 9911

The patient-days for each month are:

Period 67 68 69 70 71 72 73 74 75 76 77 78

Month Jan. Feb. March April May June July Aug. Sept. Oct. Nov. Dec.

Forecast 9911 9265 9764 9691 9520 9542 9949 10 068 9411 9724 9355 9572 with Trend and Seasonality

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126 PART 1 Introduction to Operations Management

Example 11 further illustrates seasonality for quarterly data at a department store.

11 Management at Davis’s Department Store has used time-series regression to forecast retail sales for the next four quarters. Sales estimates are $100 000, $120 000, $140 000, and $160 000 for the respective quar- ters. Seasonal indices for the four quarters have been found to be 1.30, 0.90, 0.70, and 1.10, respectively.

APPROACH c  To compute a seasonalized or adjusted sales forecast, we just multiply each seasonal index by the appropriate trend forecast:

ynseasonal = Index * yntrend forecast SOLUTION c   Quarter I: ynI 5 (1.30)($100 000) 5 $130 000

Quarter II: ynII 5 (0.90)($120 000) 5 $108 000

Quarter III: ynIII 5 (0.70)($140 000) 5 $98 000

Quarter IV: ynIV 5 (1.10)($160 000) 5 $176 000

INSIGHT c  The straight-line trend forecast is now adjusted to reflect the seasonal changes.

LEARNING EXERCISE c  If the sales forecast for Quarter IV was 180 000 (rather than 160 000), what would be the seasonally adjusted forecast? [Answer: $198 000.]

RELATED PROBLEMS c  4.26, 4.29

EXAMPLE

Adjusting Trend Data With Seasonal Indices

CYCLICAL VARIATIONS IN DATA Cycles are like seasonal variations in data but occur every several years, not weeks, months, or quarters. Forecasting cyclical variations in a time series is difficult. This is because cycles include a wide variety of factors that cause the economy to go from recession to expansion to recession over a period of years. These factors include national or industry-wide overexpansion in times of euphoria and contraction in times of concern. Forecasting demand for individual products can also be driven by product life cycles—the stages products go through from introduction through decline. Life cycles exist for virtually all products; striking examples include floppy disks, video recorders, and the original Game Boy. We leave cyclical analysis to forecasting texts.

Developing associative techniques of variables that affect one another is our next topic.

Associative Forecasting Methods: Regression and Correlation Analysis Unlike time-series forecasting, associative forecasting models usually consider several variables that are related to the quantity being predicted. Once these related variables have been found, a statistical model is built and used to forecast the item of interest. This approach is more powerful than the time-series methods that use only the historical values for the forecasted variable.

Many factors can be considered in an associative analysis. For example, the sales of Dell PCs may be related to Dell’s advertising budget, the company’s prices, competitors’ prices and promotional strategies, and even the nation’s economy and unemployment rates. In this case, PC sales would be called the dependent variable, and the other variables would be called independ- ent variables. The manager’s job is to develop the best statistical relationship between PC sales and the independent variables. The most common quantitative associative forecasting model is linear-regression analysis.

USING REGRESSION ANALYSIS FOR FORECASTING We can use the same mathematical model that we employed in the least squares method of trend projection to perform a linear-regression analysis. The dependent variables that we want to forecast will still be yn. But now the independent variable, x, need no longer be time. We use the equation:

yn = a + bx

where yn 5 value of the dependent variable (in our example, sales) a 5 y-axis intercept b 5 slope of the regression line x 5 independent variable

Cycles Patterns in the data that occur every several years.

LO6 Conduct a regression and correlation analysis

Linear-regression analysis A straight-line mathematical model to describe the functional relationships between independ- ent and dependent variables.

We now deal with the same mathematical model that we saw earlier, the least squares method. But we use any potential “cause- and-effect” variable as x.

STUDENT TIP

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Chapter 4 Forecasting 127

12EXAMPLE

Computing a Linear Regression Equation

Nodel Construction Company renovates old homes in North Bay, Ontario. Over time, the company has found that its dollar volume of renovation work is dependent on the North Bay area payroll. Management wants to establish a mathematical relationship to help predict sales.

APPROACH c    Nodel’s VP of operations has prepared the following table, which lists company revenues and the amount of money earned by wage earners in North Bay during the past six years:

Nodel’s Sales (in $ millions), y

Area Payroll (in $ billions), x

Nodel’s Sales (in $ millions), y

Area Payroll (in $ billions), x

2.0 1 2.0 2

3.0 3 2.0 1

2.5 4 3.5 7

The VP needs to determine whether there is a straight-line (linear) relationship between area payroll and sales. He plots the known data on a scatter diagram:

From the six data points, there appears to be a slight positive relationship between the independent var- iable (payroll) and the dependent variable (sales): As payroll increases, Nodel’s sales tend to be higher.

SOLUTION c  We can find a mathematical equation by using the least squares regression approach:

Area payroll (in $ billions) 0

1.0

2.0

3.0

4.0

1 2 3 54 6 7

N o

d e l’ s s

a le

s (i

n $

m il li o

n s )

Sales, y Payroll, x x2 xy

2.0 1 1 2.0

3.0 3 9 9.0

2.5 4 16 10.0

2.0 2 4 4.0

2.0 1 1 2.0

3.5 7 49 24.5

Σy 5 15.0 Σx 5 18 Σx2 5 80 Σxy 5 51.5

x = Σx 6

= 18 6

= 3

y = Σy 6

= 15 6

= 2.5

b = Σxy - nx y

Σx2nx2 =

51.5 - (6)(3)(2.5) 80 - (6)(3)2

= 0.25

a = y - bx = 2.5 - (2.5)(3) = 1.75

The estimated regression equation, therefore, is:

yn = 1.75 + 0.25x

or:

Sales = 1.75 + 0.25(payroll)

Example 12 shows how to use linear regression.

A scatter diagram is a powerful data analysis tool. It helps quickly size up the relationship between two variables.

STUDENT TIP

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128 PART 1 Introduction to Operations Management

The final part of Example 12 shows a central weakness of associative forecasting methods like regression. Even when we have computed a regression equation, we must provide a forecast of the independent variable x—in this case, payroll—before estimating the dependent variable y for the next time period. Although this is not a problem for all forecasts, you can imagine the difficulty of determining future values of some common independent variables (such as unem- ployment rates, gross national product, price indices, and so on).

STANDARD ERROR OF THE ESTIMATE The forecast of $3 250 000 for Nodel’s sales in Example 12 is called a point estimate of y. The point estimate is really the mean, or expected value, of a distribution of possible values of sales. Figure 4.9 illustrates this concept.

If the local chamber of commerce predicts that the North Bay area payroll will be $6 billion next year, we can estimate sales for Nodel with the regression equation:

Sales(in $ millions) = 1.75 + 0.25(6) = 1.75 + 1.50 = 3.25

or:

Sales = $3 250 000

INSIGHT c  Given our assumptions of a straight-line relationship between payroll and sales, we now have an indication of the slope of that relationship: on average, sales increase at the rate of a million dollars for every quarter billion dollars in the local area payroll. This is because b 5 0.25.

LEARNING EXERCISE c  What are Nodel’s sales when the local payroll is $8 billion? [Answer: $3.75 million.]

RELATED PROBLEMS c  4.24, 4.30, 4.31, 4.32, 4.33, 4.35, 4.38, 4.40, 4.41, 4.46, 4.48, 4.49

EXCEL OM Data file Ch4Ex12.xlsx can be found at MyLab Operations Management.

1 2 3 4 5 6 7

3.25

4.0

3.0

2.0

1.0

Area payroll (in $ billions)

N o

d e l’ s s

a le

s (

in $

m il li o

n s )

Regression line, y = 1.75 + 0.25xˆ

x

yFIGURE 4.9

Distribution About the Point Estimate of $3.25 Million Sales

Standard error of the estimate A measure of variability around the regression line—its standard deviation.

To measure the accuracy of the regression estimates, we must compute the standard error of the estimate, Sy,x. This computation is called the standard deviation of the regression. It measures the error from the dependent variable, y, to the regression line, rather than to the mean. Equation (4-14) is a similar expression to that found in most statistics books for computing the standard deviation of an arithmetic mean:

Sy,x = B Σ(y - yc)2n - 2 (4-14) where y 5 y-value of each data point

yc 5 computed value of the dependent variable, from the regression equation n 5 number of data points

Equation (4-15) below may look more complex, but it is actually an easier-to-use version of Equation (4-14). Both formulas provide the same answer and can be used in setting up prediction intervals around the point estimate:3

3 When the sample size is large (n > 30), the prediction interval value of y can be computed using normal tables. When the number of observations is small, the t-distribution is appropriate. See D. Groebner et al., Business Statistics, 8th ed. (Upper Saddle River, NJ: Prentice Hall, 2011).

M04_HEIZ8076_03_SE_C04.indd 128 27/11/18 8:51 PM

Chapter 4 Forecasting 129

Sy, x = B Σy2 - aΣy - bΣxyn - 2 (4-15) Example 13 shows how we would calculate the standard error of the estimate in Example 12.

Glidden Paints’ assembly lines fill thousands of cans per hour. To predict demand, the firm uses associative forecasting methods such as linear regression, with independent variables such as disposable personal income and GNP. Although housing starts would be a natural variable, Glidden found that it correlated poorly with past sales. It turns out that most Glidden paint is sold through retailers to customers who already own homes or businesses.

13Nodel’s VP of operations now wants to know the error associated with the regression line computed in Example 12.

APPROACH c  Compute the standard error of the estimate, Sy, x, using Equation (4-15).

SOLUTION c  The only number we need that is not available to solve for Sy, x is Σy 2. Some quick

addition reveals Σy2 = 39.5. Therefore:

Sy, x = B Σy2 - aΣy - bΣxyn - 2 = B 39.5 - 1.75(15) - 0.25(51.5)6 - 2 = 30.09375 = 0.306 (in $ millions)

The standard error of the estimate is then $306 000 in sales.

INSIGHT c  The interpretation of the standard error of the estimate is similar to the standard devia- tion; namely, ±1 standard deviation 5 0.6827. So there is a 68.27% chance of sales being ±$306 000 from the point estimate of $3 250 000.

LEARNING EXERCISE c  What is the probability sales will exceed $3 556 000? [Answer: About 16%.]

RELATED PROBLEMS c  4.41e, 4.48b

EXAMPLE

Computing the Standard Error of the Estimate

CORRELATION COEFFICIENTS FOR REGRESSION LINES The regression equation is one way of expressing the nature of the relationship between two variables. Regression lines are not cause-and-effect relationships. They merely describe the rela- tionships among variables. The regression equation shows how one variable relates to the value and changes in another variable.

Another way to evaluate the relationship between two variables is to compute the coefficient of correlation. This measure expresses the degree or strength of the linear relationship. Usually identified as r, the coefficient of correlation can be any number between 11 and −1. Figure 4.10 illustrates what different values of r might look like.

M ic

ha el

R os

en fe

ld /M

ax im

ili an

S /R

G B

Ve nt

ur es

/S up

er St

oc k/

Al am

y St

oc k

Ph ot

o

Coefficient of correlation A measure of the strength of the relationship between two variables.

M04_HEIZ8076_03_SE_C04.indd 129 28/11/18 2:42 PM

130 PART 1 Introduction to Operations Management

To compute r, we use much of the same data needed earlier to calculate a and b for the regres- sion line. The rather lengthy equation for r is:

r = nΣxy - ΣxΣy2[nΣx2 - (Σx)2][nΣy2 - (Σy)2] (4-16)

Example 14 shows how to calculate the coefficient of correlation for the data given in Examples 12 and 13.

(e) Perfect positive correlation: r = 1

x

y

(a) Perfect negative correlation: r = –1

x

y

(b) Negative correlation

High

–1.0 –0.8 –0.6 –0.4 –0.2 0 Correlation coefficient values

0.2 0.4 0.6 0.8 1.0

HighModerate ModerateLow Low

x

y

(c) No correlation: r = 0

x

y

(d) Positive correlation x

y

FIGURE 4.10

Four Values of the Correlation Coefficient

In Example 12, we looked at the relationship between Nodel Construction Company’s renovation sales and payroll in its hometown of North Bay. The VP now wants to know the strength of the association between area payroll and sales.

APPROACH c  We compute the r value using Equation (4-16). We need first to add one more col- umn of calculations—for y2.

SOLUTION c  The data, including the column for y2 and the calculations, are shown here:

y x x2 xy y2

2.0 1 1 2.0 4.0

3.0 3 9 9.0 9.0

2.5 4 16 10.0 6.25

2.0 2 4 4.0 4.0

2.0 1 1 2.0 4.0

3.5 7 49 24.5 12.25

Σy 5 15.0 Σx 5 18 Σx2 5 80 Σxy 5 51.5 Σy2 5 39.5

r =

(6)(51.5) - (18)(15.0)2[(6)(80) - (18)2][(6)(39.5) - (15.0)2] =

309 - 2702(156)(12) = 3921872 =

39

43.3 = 0.901

EXAMPLE 14

Determining the Coefficient of Correlation

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Chapter 4 Forecasting 131

Although the coefficient of correlation is the measure most commonly used to describe the relationship between two variables, another measure does exist. It is called the coefficient of determination and is simply the square of the coefficient of correlation—namely, r2. The value of r2 will always be a positive number in the range 0 … r2 … 1. The coefficient of determination is the percentage of variation in the dependent variable (y) that is explained by the regression equation. In Nodel’s case, the value of r2 is 0.81, indicating that 81% of the total variation is explained by the regression equation.

MULTIPLE-REGRESSION ANALYSIS Multiple regression is a practical extension of the simple regression model we just explored. It allows us to build a model with several independent variables instead of just one variable. For example, if Nodel Construction wanted to include average annual interest rates in its model for forecasting renovation sales, the proper equation would be:

yn = a + b1x1 + b2x2 (4-17)

where yn 5 dependent variable, sales a 5 a constant, the y intercept

x1 and x2 5 values of the two independent variables, area payroll and interest rates, respectively

b1 and b2 5 coefficients for the two independent variables

The mathematics of multiple regression becomes quite complex (and is usually tackled by computer), so we leave the formulas for a, b1, and b2 to statistics textbooks. However, Example 15 shows how to interpret Equation (4-17) in forecasting Nodel’s sales.

Coefficient of determination A measure of the amount of var- iation in the dependent variable about its mean that is explained by the regression equation.

Multiple regression An associative forecasting method with more than one independent variable.

15Nodel Construction wants to see the impact of a second independent variable, interest rates, on its sales.

APPROACH c  The new multiple-regression line for Nodel Construction, calculated by computer software, is:

yn = 1.80 + 0.30x1 - 5.0x2

We also find that the new coefficient of correlation is 0.96, implying that the inclusion of the varia- ble x2, interest rates, adds even more strength to the linear relationship.

SOLUTION c  We can now estimate Nodel’s sales if we substitute values for next year’s payroll and interest rate. If North Bay’s payroll will be $6 billion and the interest rate will be 0.12 (5 12%), sales will be forecast as:

Sales($ millions) = 1.80 + 0.30(6) - 5.0(0.12) = 1.8 + 1.8 - 0.6 = 3.0

or:

Sales = $ 3 000 000

INSIGHT c  By using both variables—payroll and interest rates—Nodel now has a sales forecast of $3 million and a higher coefficient of correlation. This suggests a stronger relationship between the two variables and a more accurate estimate of sales.

LEARNING EXERCISE c    If interest rates were only 6%, what would be the sales forecast? [Answer: 1.8 1 1.8 – 5.0(0.06) 5 3.3, or $3 300 000.]

RELATED PROBLEMS c  4.34, 4.36

EXAMPLE

Using a Multiple- Regression Equation

INSIGHT c  This r of 0.901 appears to be a significant correlation and helps confirm the closeness of the relationship between the two variables.

LEARNING EXERCISE c  If the coefficient of correlation was −0.901 rather than 10.901, what would this tell you? [Answer: The negative correlation would tell you that as payroll went up, Nodel’s sales went down—a rather unlikely occurrence that would suggest you recheck your math.]

RELATED PROBLEMS c  4.24d, 4.35d, 4.38c, 4.41f, 4.48b

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132 PART 1 Introduction to Operations Management

Monitoring and Controlling Forecasts Once a forecast has been completed, it should not be forgotten. No manager wants to be reminded that his or her forecast is horribly inaccurate, but a firm needs to determine why actual demand (or whatever variable is being examined) differed significantly from that projected. If the forecaster is accurate, that individual usually makes sure that everyone is aware of his or her talents. Very seldom does one read articles in Report on Business, Financial Times, or The Wall Street Journal, however, about money managers who are consistently off by 25% in their stock market forecasts.

One way to monitor forecasts to ensure that they are performing well is to use a tracking signal. A tracking signal is a measurement of how well a forecast is predicting actual values. As forecasts are updated every week, month, or quarter, the newly available demand data are compared to the forecast values.

The tracking signal is computed as the cumulative error divided by the mean absolute devia- tion (MAD):

(Tracking signal) =

Cumulative error MAD

= Σ(Actual demand in period i - Forecast demand in period i)

MAD

(4-18)

Where (MAD) = Σ ∙ Actual - Forecast ∙

n

as seen earlier, in Equation (4-5). Positive tracking signals indicate that demand is greater than forecast. Negative signals mean

that demand is less than forecast. A good tracking signal—that is, one with a low cumulative error—has about as much positive error as it has negative error. In other words, small deviations are okay, but positive and negative errors should balance one another so that the tracking signal centres closely around zero. A consistent tendency for forecasts to be greater or less than the actual values (i.e., for a high absolute cumulative error) is called a bias error. Bias can occur if, for example, the wrong variables or trend line are used or if a seasonal index is misapplied.

Once tracking signals are calculated, they are compared with predetermined control limits. When a tracking signal exceeds an upper or lower limit, there is a problem with the forecasting method, and management may want to re-evaluate the way it forecasts demand. Figure 4.11 shows the graph of a tracking signal that is exceeding the range of acceptable variation. If the model being used is exponential smoothing, perhaps the smoothing constant needs to be readjusted.

How do firms decide what the upper and lower tracking limits should be? There is no single answer, but they try to find reasonable values—in other words, limits not so low as to be trig- gered with every small forecast error and not so high as to allow bad forecasts to be regularly overlooked. One MAD is equivalent to approximately 0.8 standard deviation, ±2 MADs 5 ±1.6 standard deviations, ±3 MADs 5 ±2.4 standard deviations, and ±4 MADs 5 ±3.2 standard devi- ations. This fact suggests that for a forecast to be “in control,” 89% of the errors are expected to fall within ±2 MADs, 98% within ±3 MADs, or 99.9% within ±4 MADs.4

Tracking signal A measurement of how well a forecast is predicting actual values.

Bias A forecast that is consistently higher or consistently lower than actual values of a time series.

+

–

0 MADs

Upper control limit

Lower control limit

Time

Signal exceeded limit

Tracking signal

Acceptable range

*

FIGURE 4.11

A Plot of Tracking Signals

4 To prove these three percentages to yourself, just set up a normal curve for ±1.6 standard deviations (z-values). Using the normal table in Appendix I, you find that the area under the curve is 0.89. This represents ±2 MADs. Likewise, ±3 MADs 5 ±2.4 standard deviations encompass 98% of the area, and so on for ±4 MADs.

LO7 Use a tracking signal

Using a tracking signal is a good way to make sure the forecasting system is continuing to do a good job.

STUDENT TIP

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Chapter 4 Forecasting 133

ADAPTIVE SMOOTHING Adaptive forecasting refers to computer monitoring of tracking signals and self-adjustment if a signal passes a preset limit. For example, when applied to exponential smoothing, the a and b coefficients are first selected on the basis of values that minimize error forecasts and then adjusted accordingly whenever the computer notes an errant tracking signal. This process is called adaptive smoothing.

FOCUS FORECASTING Rather than adapt by choosing a smoothing constant, computers allow us to try a variety of fore- casting models. Such an approach is called focus forecasting. Focus forecasting is based on two principles:

1. Sophisticated forecasting models are not always better than simple ones. 2. There is no single technique that should be used for all products or services.

Bernard Smith, inventory manager for American Hardware Supply, coined the term focus forecasting. Smith’s job was to forecast quantities for 100 000 hardware products purchased by American’s 21 buyers.5 He found that buyers neither trusted nor understood the exponential smoothing model then in use. Instead, they used very simple approaches of their own. So Smith developed his new computerized system for selecting forecasting methods.

Smith chose to test seven forecasting methods. They ranged from the simple ones that buyers used (such as the naive approach) to statistical models. Every month, Smith applied the forecasts of all seven models to each item in stock. In these simulated trials, the forecast values were subtracted from the most recent actual demands, giving a simulated forecast error. The forecast

16Carlson’s Bakery wants to evaluate performance of its croissant forecast.

APPROACH c  Develop a tracking signal for the forecast and see if it stays within acceptable limits, which we define as ±4 MADs.

SOLUTION c  Using the forecast and demand data for the past six quarters for croissant sales, we develop a tracking signal in the table below:

Quarter Actual

Demand Forecast Demand Error

Cumulative Error

Absolute Forecast

Error

Cumulative Absolute Forecast

Error MAD

Tracking Signal (Cumulative Error/MAD)

1 90 100 −10 −10 10 10 10.0 −10/10 5 −1

2 95 100 −5 −15 5 15 7.5 −15/7.5 5 −2

3 115 100 115 0 15 30 10.0 0/10 5 0

4 100 110 −10 −10 10 40 10.0 −10/10 5 −1

5 125 110 115 15 15 55 11.0 15/11 5 10.5

6 140 110 130 135 30 85 14.2 135/14.2 5 12.5

At the end of quarter 6, MAD = Σ ∙ Forecast errors ∙

n =

85 6

= 14.2

and Tracking signal = Cumulative error

MAD =

35 14.2

= 2.5 MADs

INSIGHT c  Because the tracking signal drifted from −2 MAD to 12.5 MAD (between 1.6 and 2.0 standard deviations), we can conclude that it is within acceptable limits.

LEARNING EXERCISE c  If actual demand in quarter 6 was 130 (rather than 140), what would be the MAD and resulting tracking signal? [Answer: MAD for quarter 6 would be 12.5, and the tracking signal for period 6 would be 2 MADs.]

RELATED PROBLEMS c  4.37, 4.45

EXAMPLE

Computing the Tracking Signal at Carlson’s Bakery

Adaptive smoothing An approach to exponential smoothing forecasting in which the smoothing constant is auto- matically changed to keep errors to a minimum.

Focus forecasting Forecasting that tries a variety of computer models and selects the best one for a particular application.

5 Bernard T. Smith, Focus Forecasting: Computer Techniques for Inventory Control (Boston, MA: CBI Publishing, 1978).

Example 16 shows how the tracking signal and cumulative error can be computed.

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134 PART 1 Introduction to Operations Management

method yielding the least error is selected by the computer, which then uses it to make next month’s forecast. Although buyers still have an override capability, American Hardware finds that focus forecasting provides excellent results.

Forecasting in the Service Sector Forecasting in the service sector presents some unusual challenges. A major technique in the retail sector is tracking demand by maintaining good short-term records. For instance, a barber- shop catering to men expects peak flows on Fridays and Saturdays. Indeed, most barbershops are closed on Sunday and Monday, and many call in extra help on Friday and Saturday. A downtown restaurant, on the other hand, may need to track conventions and holidays for effective short- term forecasting. The OM in Action box “Forecasting at FedEx’s Customer Service Centres” provides an example of a major service sector industry, the call centre.

SPECIALTY RETAIL SHOPS Specialty retail facilities, such as flower shops, may have other unusual demand patterns, and those patterns will differ depending on the holiday. When Valentine’s Day falls on a weekend, for example, flowers can’t be delivered to offices, and those romantically inclined are likely to celebrate with outings rather than flowers. If a holiday falls on a Monday, some of the celebra- tion may also take place on the weekend, reducing flower sales. However, when Valentine’s Day falls midweek, busy midweek schedules often make flowers the optimal way to celebrate. Because flowers for Mother’s Day are to be delivered on Saturday or Sunday, this holiday fore- cast varies less. Due to special demand patterns, many service firms maintain records of sales, noting not only the day of the week but also unusual events, including the weather, so that pat- terns and correlations that influence demand can be developed.

FAST-FOOD RESTAURANTS Fast-food restaurants are well aware not only of weekly, daily, and hourly but even quarter-hourly (15-minute) variations in demands that influence sales. Therefore, detailed forecasts of demand are needed. Figure 4.12(a) shows the hourly forecast for a typical fast-food restaurant. Note the lunchtime and dinnertime peaks. This contrasts to the mid-morning and mid-afternoon peaks at FedEx’s call centre in Figure 4.12(b).

Firms such as Taco Bell now use point-of-sale computers that track sales every quarter-hour. Taco Bell found that a six-week moving average was the forecasting technique that mini- mized its mean squared error (MSE) of these quarter-hour forecasts. Building this forecasting

11–12

5%

Hour of day

P e rc

e n

t o

f s a le

s b

y h

o u

r o

f d

ay

12–1 (Lunch time)

1–2 2–3

3–4 4–5

5–6 6–7

7–8 8–9

9–10

10%

15%

20%

10–11 (Dinner time)

Hourly sales at a fast-food restaurant

(a)

1 0%

Hour of day

2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 1210 11

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

11%

12% Monday calls at a FedEx call centre

(b)

A.M. P.M.

FIGURE 4.12 Forecasts Are Unique: Note the Variations between (a) Hourly Sales at a Fast-Food Restaurant and (b) Hourly Call Volume at FedEx

Source: Based on historical data: see Journal of Business Forecasting (Winter 1999–2000): 6–11.

Forecasting at McDonald’s, FedEx, and Walmart is as important and complex as it is for manufacturers such as Toyota and Dell.

STUDENT TIP

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Chapter 4 Forecasting 135

methodology into each of Taco Bell’s 6500 stores’ computers, the model makes weekly projec- tions of customer transactions. These in turn are used by store managers to schedule staff, who begin in 15-minute increments, not one-hour blocks as in other industries. The forecasting model has been so successful that Taco Bell has increased customer service while documenting more than U.S. $50 million in labour cost savings in four years of use.6

6 J. Hueter and W. Swart, “An Integrated Labor Management System for Taco Bell,” Interfaces 28, no. 1 (January–February 1998): 75–91.

The world’s largest express shipping company, FedEx, generates US $38 billion in revenues, using 675 planes, 44 000 trucks, and a workforce of 145 000 in 220 coun- tries. To support this global network, the company has 51 customer service call centres, whose service goal is to answer 90% of all calls within 20 seconds. With a half-million daily calls just in the United States, FedEx makes extensive use of forecasting models for staffing decisions and to ensure that customer satisfaction lev- els stay the highest in the industry.

FedEx’s forecasting and modelling department makes several different forecasts. One-year and five-year models predict number of calls, average handle time, and staffing needs. They break forecasts into weekday, Saturday, and Sunday and then use the Delphi method and time-series analysis.

FedEx’s tactical forecasts are monthly and use eight years of historical daily data. This time-series model

addresses month, day of week, and day of month to predict caller volume. Finally, the operational forecast uses a weighted moving average and six weeks of data to project the number of calls on a half-hourly basis.

FedEx’s forecasts are consistently accurate to within 1% to 2% of

actual call volumes. This means coverage needs are met, service levels are maintained, and costs are controlled.

Sources: Hoover’s Company Records (July 1, 2009): 10552; Baseline (January 2005): 54; and Journal of Business Forecasting (Winter 1999– 2000): 7–11.

Forecasting at FedEx’s Customer Service CentresOM in Action

Forecasts are a critical part of the operations manager’s func- tion. Demand forecasts drive a firm’s production, capacity, and scheduling systems and affect the financial, marketing, and personnel planning functions.

There are a variety of qualitative and quantitative forecasting techniques. Qualitative approaches employ judgment, experience, intuition, and a host of other fac- tors that are difficult to quantify. Quantitative forecasting uses historical data and causal, or associative, relations to project future demands. The Rapid Review for this chap-

ter summarizes the formulas we introduced in quantitative forecasting. Forecast calculations are seldom performed by hand. Most operations managers turn to software packages such as Forecast PRO, NCSS, Minitab, Systat, Statgraphics, SAS, SPSS, or Excel.

No forecasting method is perfect under all conditions. And even once management has found a satisfactory approach, it must still monitor and control forecasts to make sure errors do not get out of hand. Forecasting can often be a very challeng- ing, but rewarding, part of managing.

CHAPTER SUMMARY

In 2017, the board of regents responsible for all public higher-educa- tion funding in a major Canadian city hired a consultant to develop a series of enrolment forecasting models, one for each college. These models used historical data and exponential smoothing to forecast the following year’s enrolments. Based on the model, which included a smoothing constant (a) for each school, each institution’s budget was set by the board. The head of the board personally selected each

smoothing constant based on what she called her “gut reactions and political acumen”.

What do you think the advantages and disadvantages of this sys- tem are? Answer from the perspective of (a) the board of regents and (b) the president of each school. How can this model be abused, and what can be done to remove any biases? How can a regression model be used to produce results that favour one forecast over another?

ETHICAL DILEMMA

4X 5

Co lle

ct io

n/ Su

pe rs

to ck

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136 PART 1 Introduction to Operations Management

Discussion Questions

1. What is a qualitative forecasting model, and when is its use appropriate?

2. Identify and briefly describe the two general forecasting approaches.

3. Identify the three forecasting time horizons. State an approxi- mate duration for each.

4. Briefly describe the steps that are used to develop a forecasting system.

5. A sceptical manager asks what medium-range forecasts can be used for. Give the manager three possible uses/purposes.

6. Explain why such forecasting devices as moving averages, weighted moving averages, and exponential smoothing are not well suited for data series that have trends.

7. What is the basic difference between a weighted moving aver- age and exponential smoothing?

8. What three methods are used to determine the accuracy of any given forecasting method? How would you determine whether time-series regression or exponential smoothing is better in a specific application?

9. Research and briefly describe the Delphi technique. How would it be used by an employer you have worked for?

10. What is the primary difference between a time-series model and an associative model?

11. Define time series. 12. What effect does the value of the smoothing constant have on

the weight given to the recent values? 13. Explain the value of seasonal indices in forecasting. How are

seasonal patterns different from cyclical patterns? 14. Which forecasting technique can place the most emphasis on

recent values? How does it do this? 15. In your own words, explain adaptive forecasting. 16. What is the purpose of a tracking signal? 17. Explain, in your own words, the meaning of the correlation

coefficient. Discuss the meaning of a negative value of the cor- relation coefficient.

18. What is the difference between a dependent and an independent variable?

19. Give examples of industries that are affected by seasonality. Why would these businesses want to filter out seasonality?

20. Give examples of industries in which demand forecasting is dependent on the demand for other products.

21. What happens to the ability to forecast for periods further into the future?

Using Software in Forecasting

This section presents three ways to solve forecasting problems with computer software. First, you can create your own Excel spreadsheets to develop forecasts. Second, you can use the Excel OM software that comes with the text and is found on our text website. Third, POM for Windows is another program that is located on our website at MyLab Operations Management.

CREATING YOUR OWN EXCEL SPREADSHEETS Excel spreadsheets (and spreadsheets in general) are frequently used in forecasting. Exponential smooth- ing, trend analysis, and regression analysis (simple and multiple) are supported by built-in Excel functions.

Program 4.1 illustrates how to build an Excel forecast for the data in Example 8. The goal for N.Y. Edison is to create a trend analysis of the year 1 to year 7 data. As an alternative, you may want to exper- iment with Excel’s built-in regression analysis. To do so, under the Data menu bar selection choose

=B$16+A5*B$17

=INTERCEPT(B5:B11,A5:A11)

=SLOPE(B5:B11,A5:A11)

=STEYX(B5:B11,A5:A11)

=CORREL(B5:B11,A5:A11)

Actions Copy C5 to C6:C13

To create the graph, select A5:C13 and choose Insert Line Chart

PROGRAM 4.1

Using Excel to Develop Your Own Forecast, With Data From Example 8

Source: Courtesy of Microsoft Corporation.

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Chapter 4 Forecasting 137

Data Analysis, then Regression. Enter your Y and X data into two columns (say A and B). When the regression window appears, enter the Y and X ranges, then select OK. Excel offers several plots and tables to those interested in more rigorous analysis of regression problems.

Computations

Value Cell Excel Formula Action

Trend line column D4 5$B$161$B$17*C4 Copy to D5:D14

(or 5TREND($B$4:$B$10,$C$4:$C$10,C4))

Intercept B16 5INTERCEPT(B4:B10, C4:C10)

Slope (trend) B17 5SLOPE(B4:B10, C4:C10)

Standard error B19 5STEYX(B4:B10, C4:C10)

Correlation B20 5CORREL(B4:B10, C4:C10)

As an alternative, you may want to experiment with Excel’s built-in regression analysis. To do so, under the Data menu bar selection choose Data Analysis, then Regression. Enter your Y and X data into two columns (say, B and C). When the regression window appears, enter the Y and X ranges, then select OK. Excel offers several plots and tables to those interested in more rigorous analysis of regression problems.

X USING EXCEL OM Excel OM’s forecasting module has five components: (1) moving averages, (2) weighted moving aver- ages, (3) exponential smoothing, (4) regression (with one variable only), and (5) decomposition. Excel OM’s error analysis is much more complete than that available with the Excel add-in.

Program 4.2 illustrates Excel OM’s input and output, using Example 2’s weighted moving average data.

P USING POM FOR WINDOWS POM for Windows can project moving averages (both simple and weighted), handle exponential smoothing (both simple and trend adjusted), forecast with least squares trend projection, and solve line- ar-regression (associative) models. A summary screen of error analysis and a graph of the data can also be generated. As a special example of exponential smoothing adaptive forecasting, when using an a of 0, POM for Windows will find the a value that yields the minimum MAD.

Appendix IV provides further details.

Enter the weights to be placed on each of the last three periods at the top of column C. Weights must be entered from oldest to most recent.

Forecast is the weighted sum of past sales (SUMPRODUCT) divided by the sum of the weights (SUM) because weights do not sum to 1.

Error (B11 – E11) is the difference between the demand and the forecast.

= AVERAGE(H11: H19)

The standard error is given by the square root of the total error divided by n – 2 , where n is the number of periods for which forecasts exist, i.e., 9.

= SUMPRODUCT(B17:B19, $C$8:$C$10)/SUM($C$8:$C$10)

PROGRAM 4.2 Analysis of Excel OM’s Weighted Moving Average Program, Using Data From Example 2 as Input

Source: Courtesy of Microsoft Corporation.

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138 PART 1 Introduction to Operations Management

Solved Problems Virtual Office Hours help is available at MyLab Operations Management.

. SOLVED PROBLEM 4.1 Sales of Chevrolet’s popular Camaro grew steadily at auto dealer- ships in Alberta during five years (see table below). The sales man- ager had predicted in 2013 that 2014 sales would be 410 Camaros. Using exponential smoothing with a weight of a 5 0.30, develop forecasts for 2015 through 2019.

Year Sales Forecast

2014 450 410

2015 495

2016 518

2017 563

2018 584

2019 ?

. SOLUTION

Year Forecast

2014 410.0

2015 422.0 5 410 1 0.3(450 − 410)

2016 443.9 5 422 1 0.3(495 − 422)

2017 466.1 5 443.9 1 0.3(518 − 443.9)

2018 495.2 5 466.1 1 0.3(563 − 466.1)

2019 521.8 5 495.2 1 0.3(584 − 495.2)

. SOLVED PROBLEM 4.2 In Example 7, we applied trend-adjusted exponential smoothing to forecast demand for a piece of pollution control equipment for months 2 and 3 (out of nine months of data provided). Let us now continue this process for month 4. We want to confirm the forecast for month 4 shown in Table 4.2 and Figure 4.3.

For month 4, A4 5 19, with a 5 0.2, and b 5 0.4.

. SOLUTION

F4 = αA3 + (1 - α)(F3 + T3) = (0.2)(20) + (1 - 0.2)(15.18 + 2.10) = 4.0 + (0.8)(17.28) = 4.0 + 13.82 = 17.82

T4 = b(F4 - F3) + (1 - b)T3 = (0.4)(17.82 - 15.18) + (1 - 0.4)(2.10) = (0.4)(2.64) + (0.6)(2.10) = 1.056 + 1.26 = 2.32

FIT4 = 17.82 + 2.32

= 20.14

. SOLVED PROBLEM 4.3 Room registrations in the Toronto Towers Plaza Hotel have been recorded for nine years. To project future occupancy, management would like to determine the mathematical trend of guest registra- tion. This estimate will help the hotel determine whether future expansion will be needed. Given the following time-series data,

develop a regression equation relating registrations to time (e.g., a trend equation). Then forecast year 11 registrations. Room regis- trations are in the thousands:

Year 1: 17 Year 2: 16 Year 3: 16 Year 4: 21 Year 5: 20

Year 6: 20 Year 7: 23 Year 8: 25 Year 9: 24

. SOLUTION

Year, x Registrants, y (in thousands) x2 xy

1 17 1 17 2 16 4 32 3 16 9 48 4 21 16 84 5 20 25 100 6 20 36 120 7 23 49 161 8 25 64 200 9 24 81 216

Σx 5 45 Σy 5 182 Σx2 5 285 Σxy 5 978

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Chapter 4 Forecasting 139

b = Σxy - nx y Σx2 - nx2

= 978 - (9)(5)(20.22)

285 - (9)(25) =

978 - 909.9 285 - 225

= 68.1 60

= 1.135

a = y - bx = 20.22 - (1.135)(5) = 20.22 - 5.675 = 14.545

yn(registrations) = 14.545 + 1.135x

The projection of registrations in the year 11 is:

yn = 14.545 + (1.135)(11) = 27.03 or 27 030 guests in year 11

. SOLVED PROBLEM 4.4 Quarterly demand for Ford F150 pickups at a St. John’s auto dealer is forecast with the equation:

yn = 10 + 3x

where x 5 quarters, and:

Quarter I of 2014 5 0

Quarter II of 2014 5 1

Quarter III of 2014 5 2

Quarter IV of 2014 5 3

Quarter I of 2015 5 4

and so on

and:

yn = quarterly demand

The demand for trucks is seasonal, and the indices for Quarters I, II, III, and IV are 0.80, 1.00, 1.30, and 0.90, respectively. Forecast

demand for each quarter of 2016. Then, seasonalize each forecast to adjust for quarterly variations.

. SOLUTION Quarter II of 2015 is coded x 5 5; Quarter III of 2015, x 5 6; and Quarter IV of 2015, x 5 7. Hence, Quarter I of 2016 is coded x 5 8; Quarter II, x 5 9; and so on.

yn(2016 Quarter I) = 10 + 3(8) = 34 yn(2016 Quarter II) = 10 + 3(9) = 37 yn(2016 Quarter III) = 10 + 3(10) = 40 yn(2016 Quarter IV) = 10 + 3(11) = 43

Adjusted forecast = (0.80)(34) = 27.2 Adjusted forecast = (1.00)(37) = 37 Adjusted forecast = (1.30)(40) = 52 Adjusted forecast = (0.90)(43) = 38.7

Problems* • 4.1 The following gives the number of units of type A blood used at Woodlawn Hospital in the past six weeks:

Week Of Pints Used

August 31 360

September 7 389

September 14 410

September 21 381

September 28 368

October 5 374

a) Forecast the demand for the week of October 12 using a three- week moving average.

b) Use a three-week weighted moving average, with weights of 0.1, 0.3, and 0.6, using 0.6 for the most recent week. Forecast demand for the week of October 12.

c) Compute the forecast for the week of October 12 using exponential smoothing with a forecast for August 31 of 360 and a 5 0.2. PX

• • 4.2

Year 1 2 3 4 5 6 7 8 9 10 11

Demand 7 9 5 9 13 8 12 13 9 11 7

a) Plot the above data on a graph. Do you observe any trend, cycles, or random variations?

b) Starting in year 4 and going to year 12, forecast demand using a three-year moving average. Plot your forecast on the same graph as the original data.

c) Starting in year 4 and going to year 12, forecast demand using a three-year moving average with weights of 0.1, 0.3, and 0.6, using 0.6 for the most recent year. Plot this forecast on the same graph.

d) As you compare forecasts with the original data, which seems to give the better results? PX

• 4.3 Refer to Problem 4.2. Develop a forecast for years 2 through 12 using exponential smoothing with a 5 0.4 and a fore- cast for year 1 of 6. Plot your new forecast on a graph with the actual data and the naive forecast. Based on a visual inspection, which forecast is better? PX

• 4.4 A cheque-processing centre uses exponential smooth- ing to forecast the number of incoming cheques each month. The number of cheques received in June was 40 million, while the fore- cast was 42 million. A smoothing constant of 0.2 is used. a) What is the forecast for July? b) If the centre received 45 million cheques in July, what would be

the forecast for August? c) Why might this be an inappropriate forecasting method for this

situation? PX * Note: PX means the problem may be solved with POM for windows and/or Excel OM.

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140 PART 1 Introduction to Operations Management

• • 4.5 The Bonavista Patient Transfer Company is consider- ing the purchase of a new ambulance. The decision will rest partly on the anticipated distance to be driven next year. The kilometres driven during the past five years are as follows:

Year Distance (km)

1 3000

2 4000

3 3400

4 3800

5 3700

a) Forecast the number of kilometres for next year using a two-year moving average.

b) Find the MAD based on the two-year moving-average forecast in part (a). (Hint: You will have only three years of matched data.)

c) Use a weighted two-year moving average with weights of 0.4 and 0.6 to forecast next year’s mileage. (The weight of 0.6 is for the most recent year.) What MAD results from using this approach to forecasting? (Hint: You will have only three years of matched data.)

d) Compute the forecast for year 6 using exponential smoothing, an initial forecast for year 1 of 3000 kilometres and a 5 0.5. PX

• • 4.6 The monthly sales for Telco Batteries, Inc., were as follows:

Month Sales

January 20

February 21

March 15

April 14

May 13

June 16

July 17

August 18

September 20

October 20

November 21

December 23

a) Plot the monthly sales data. b) Forecast January sales using each of the following: i) Naive method. ii) A three-month moving average. iii) A six-month weighted average using 0.1, 0.1, 0.1, 0.2, 0.2, and

0.3, with the heaviest weights applied to the most recent months. iv) Exponential smoothing using an a 5 0.3 and a September

forecast of 18. v) A trend projection. c) With the data given, which method would allow you to forecast

next March’s sales? PX

• • 4.7 The actual demand for the patients at Moncton Medical Clinic for the first six weeks of this year follows:

Week Actual No. of Patients

1 65

2 62

3 70

4 48

5 63

6 52

Clinic administrator Marc Schniederjans wants you to forecast patient demand at the clinic for week 7 by using this data. You decide to use a weighted moving average method to find this fore- cast. Your method uses four actual demand levels, with weights of 0.333 on the present period, 0.25 one period ago, 0.25 two periods ago, and 0.167 three periods ago. a) What is the value of your forecast? PX b) If instead the weights were 20, 15, 15, and 10, respectively, how

would the forecast change? Explain why. c) What if the weights were 0.40, 0.30, 0.20, and 0.10, respec-

tively? Now what is the forecast for week 7?

• 4.8 A Canadian tourist travelling to Miami learned that the local temperatures in Fahrenheit for the last week were as follows: 93, 94, 93, 95, 96, 88, 90 (yesterday). a) Forecast the high temperature today, using a three-day moving

average. b) Forecast the high temperature today, using a two-day moving

average. c) Calculate the mean absolute deviation based on a two-day mov-

ing average. d) Compute the mean squared error for the two-day moving aver-

age. e) Calculate the mean absolute percent error for the two-day mov-

ing average. PX

• • • 4.9 Dell uses the CR5 chip in some of its laptop computers. The prices for the chip during the past 12 months were as follows:

Month Price per Chip Month Price per Chip

January $1.80 July $1.80

February 1.67 August 1.83

March 1.70 September 1.70

April 1.85 October 1.65

May 1.90 November 1.70

June 1.87 December 1.75

a) Use a two-month moving average on all the data and plot the averages and the prices.

b) Use a three-month moving average and add the three-month plot to the graph created in part (a).

c) Which is better (using the mean absolute deviation): the two- month average or the three-month average?

d) Compute the forecasts for each month using exponential smooth- ing, with an initial forecast for January of $1.80. Use a 5 0.1, then a 5 0.3, and finally a 5 0.5. Using MAD, which a is the best? PX

• • 4.10 Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table:

Year 1 2 3 4 5 6 7 8 9 10 11

Registrations (000)

4 6 4 5 10 8 7 9 12 14 15

a) Develop a three-year moving average to forecast registrations from year 4 to year 12.

b) Estimate demand again for years 4 to 12 with a three-year weighted moving average in which registrations in the most recent year are given a weight of 2, and registrations in the other two years are each given a weight of 1.

c) Graph the original data and the two forecasts. Which of the two forecasting methods seems better? PX

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Chapter 4 Forecasting 141

• 4.11 Use exponential smoothing with a smoothing constant of 0.3 to forecast the registrations at the seminar given in Problem 4.10. To begin the procedure, assume that the forecast for year 1 was 5000 people signing up. a) What is the MAD? PX b) What is the MSE?

• • 4.12 Consider the following actual and forecast demand levels for Big Mac hamburgers at a local McDonald’s restaurant:

Day Actual Demand Forecast Demand

Monday 88 88

Tuesday 72 88

Wednesday 68 84

Thursday 48 80

Friday

The forecast for Monday was derived by observing Monday’s demand level and setting Monday’s forecast level equal to this demand level. Subsequent forecasts were derived by using exponential smoothing with a smoothing constant of 0.25. Using this exponential smoothing method, what is the forecast for Big Mac demand for Friday? PX

• • • 4.13 As you can see in the following table, demand for heart transplant surgery at Vancouver General Hospital has increased steadily in the past few years:

Year 1 2 3 4 5 6

Heart Transplants 45 50 52 56 58 ?

The director of medical services predicted six years ago that demand in year 1 would be 41 surgeries. a) Use exponential smoothing, first with a smoothing constant of 0.6

and then with one of 0.9, to develop forecasts for years 2 through 6. b) Use a three-year moving average to forecast demand in years 4,

5, and 6. c) Use the trend projection method to forecast demand in years 1

through 6. d) With MAD as the criterion, which of the four forecasting meth-

ods is best? PX

• • 4.14 Following are two weekly forecasts made by two dif- ferent methods for the number of litres of gasoline, in thousands, demanded at a local gasoline station. Also shown are actual demand levels, in thousands of litres:

Forecasts

Week Method 1 Method 2 Actual Demand

1 0.90 0.80 0.70

2 1.05 1.20 1.00

3 0.95 0.90 1.00

4 1.20 1.11 1.00

What are the MAD and MSE for each method?

• 4.15 Refer to Solved Problem 4.1. Use a three-year mov- ing average to forecast the sales of Chevrolet Camaros in Alberta through 2016. What is the MAD? PX

• 4.16 Refer to Solved Problem 4.1. Using the trend projec- tion method, develop a forecast for the sales of Chevrolet Camaros in Alberta through 2016. What is the MAD? PX

• 4.17 Refer to Solved Problem 4.1. Using smoothing con- stants of 0.6 and 0.9, develop forecasts for the sales of Chevrolet Camaros. What effect did the smoothing constant have on the

forecast? Use MAD to determine which of the three smoothing con- stants (0.3, 0.6, or 0.9) gives the most accurate forecast. PX

• • • • 4.18 Consider the following actual (At) and forecast (Ft) demand levels for a product:

Time Period, Actual Demand, Forecast Demand,

T At Ft 1 50 50

2 42 50

3 56 48

4 46 50

5

The first forecast, F1, was derived by observing A1 and setting F1 equal to A1. Subsequent forecasts were derived by exponential smoothing. Using the exponential smoothing method, find the forecast for time period 5. (Hint: You need first to find the smoothing constant, a.)

• • • 4.19 Income at the law firm Smith and Jones for the period February to July was as follows:

Month February March April May June July

Income (in $000s)

70.0 68.5 64.8 71.7 71.3 72.8

Use trend-adjusted exponential smoothing to forecast the law firm’s August income. Assume that the initial forecast for February is $65  000 and the initial trend adjustment is 0. The smoothing con- stants selected are a 5 0.1 and b 5 0.2. PX

• • • 4.20 Resolve Problem 4.19 with a 5 0.1 and b 5 0.8. Using MSE, determine which smoothing constants provide a better forecast. PX

• 4.21 Refer to the trend-adjusted exponential smoothing illustra- tion in Example 7. Using a 5 0.2 and b 5 0.4, we forecast sales for nine months, showing the detailed calculations for months 2 and 3. In Solved Problem 4.2, we continued the process for month 4. In this problem, show your calculations for months 5 and 6 for Ft, Tt, and FITt.

PX

• 4.22 Refer to Problem 4.21. Complete the trend-adjusted exponential smoothing forecast computations for periods 7, 8, and 9. Confirm that your numbers for Ft, Tt, and FITt match those in Table 4.2. PX

• • 4.23 Sales of vegetable dehydrators at Bud Banis’s discount department store in Gander over the past year are shown below. Management prepared a forecast using a combination of exponential smoothing and its collective judgment for the four months March, April, May, and June:

Month Unit Sales Management’s

Forecast

July 100 August 93 September 96 October 110 November 124 December 119 January 92 February 83 March 101 120 April 96 114 May 89 110 June 108 108

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142 PART 1 Introduction to Operations Management

a) Compute MAD and MAPE for management’s technique. b) Do management’s results outperform (i.e., have smaller MAD

and MAPE than) a naive forecast? c) Which forecast do you recommend, based on lower forecast

error?

• • 4.24 Howard Weiss, owner of a musical instrument dis- tributorship, thinks that demand for bass drums may be related to the number of television appearances by the popular group Stone Temple Pilots during the previous month. Weiss has collected the data shown in the following table:

Demand for Bass Drums 3 6 7 5 10 7

Stone Temple Pilots’ TV Appearances

3 4 7 6 8 5

a) Graph these data to see whether a linear equation might describe the relationship between the group’s television shows and bass drum sales.

b) Use the least squares regression method to derive a forecasting equation.

c) What is your estimate for bass drum sales if the Stone Temple Pilots performed on TV nine times last month?

d) What are the correlation coefficient (r) and the coefficient of determination (r2) for this model, and what do they mean? PX

• 4.25 The following gives the number of accidents that occurred on a section of the Trans-Canada Highway during the past four months:

Month Number of Accidents

January 30

February 40

March 60

April 90

Forecast the number of accidents that will occur in May, using least squares regression to derive a trend equation. PX

• 4.26 In the past, Arup Mukherjee’s tire dealership in Sudbury sold an average of 1000 radials each year. In the past two years, 200 and 250, respectively, were sold in fall, 350 and 300 in winter, 150 and 165 in spring, and 300 and 285 in summer. With a major expan- sion planned, Mukherjee projects sales next year to increase to 1200 radials. What will be the demand during each season?

• • 4.27 Mark Cotteleer owns a company that manufactures canoes. Actual demand for Mark’s canoes during each season in 2015 through 2018 was as follows:

Year

Season 2015 2016 2017 2018

Winter 1400 1200 1000 900

Spring 1500 1400 1600 1500

Summer 1000 2100 2000 1900

Fall 600 750 650 500

Mark has forecasted that annual demand for his canoes in 2019 will equal 5600 canoes. Based on this data and the multiplicative sea- sonal model, what will the demand level be for Mark’s canoes in the spring of 2019?

• • 4.28 Attendance at Victoria’s newest theme park has been as follows:

Quarter Guests

(in thousands) Quarter Guests

(in thousands)

Winter 2015 73 Summer 2016 124

Spring 2015 104 Fall 2016 52

Summer 2015 168 Winter 2017 89

Fall 2015 74 Spring 2017 146

Winter 2016 65 Summer 2017 205

Spring 2016 82 Fall 2017 98

Compute seasonal indices using all of the data. PX

• 4.29 Central Electric Company estimates its demand trend line (in millions of kilowatt hours) to be:

D = 77 + 0.43Q

where Q refers to the sequential quarter number and Q 5 1 for winter of year 1. In addition, the multiplicative seasonal factors are as follows:

Quarter Factor (Index)

Winter 0.8

Spring 1.1

Summer 1.4

Fall 0.7

Forecast energy use for the four quarters of year 26, beginning with winter.

• 4.30 Brian Buckley has developed the following forecasting model:

yn = 36 + 4.3x

where yn 5 demand for Aztec air conditioners and

x 5 the outside temperature (°F)

a) Forecast demand for the Aztec when the temperature is 70°F. b) What is demand when the temperature is 80°F? c) What is demand when the temperature is 90°F? PX

• • 4.31 Coffee Palace’s manager, Joe Felan, suspects that demand for mocha latte coffees depends on the price being charged. Based on historical observations, Joe has gathered the following data, which show the numbers of these coffees sold over six differ- ent price values:

Price Number Sold

$2.70 760

$3.50 510

$2.00 980

$4.20 250

$3.10 320

$4.05 480

Using these data, how many mocha latte coffees would be forecast to be sold according to simple linear regression if the price per cup were $2.80? PX

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Chapter 4 Forecasting 143

• 4.32 The following data relate the sales figures of the bar in Marty and Polly Starr’s small bed-and-breakfast inn in Summerside, Prince Edward Island, to the number of guests registered that week:

Week Guests Bar Sales

1 16 $330

2 12 270

3 18 380

4 14 300

a) Perform a linear regression that relates bar sales to guests (not to time). b) If the forecast is for 20 guests next week, what are the sales

expected to be? PX

• 4.33 The number of transistors (in millions) made at a plant in Japan during the past five years follows:

Year Transistors

1 140

2 160

3 190

4 200

5 210

a) Forecast the number of transistors to be made next year, using linear regression.

b) Compute the mean squared error (MSE) when using linear regression.

c) Compute the mean absolute percent error (MAPE). PX

• 4.34 The number of auto accidents in a certain region is related to the regional number of registered automobiles in thousands (X1), alcoholic beverage sales in $10 000s (X2), and rainfall in inches (X3). Furthermore, the regression formula has been calculated as:

Y = a + b1X1 + b2X2 + b3X3 where Y 5 number of automobile accidents

a 5 7.5 b1 5 3.5 b2 5 4.5 b3 5 2.5

Calculate the expected number of automobile accidents under con- ditions (a), (b), and (c):

X1 X2 X3 (a) 2 3 0

(b) 3 5 1

(c) 4 7 2

• • 4.35 John Howard, a Toronto real estate developer, has devised a regression model to help determine residential housing prices in southern Ontario. The model was developed using recent sales in a particular neighbourhood. The price (Y) of the house is based on the size (square footage 5 X) of the house. The model is:

Y = 13 473 + 37.65X

The coefficient of correlation for the model is 0.63. a) Use the model to predict the selling price of a house that is 1860

square feet. b) An 1860-square-feet house recently sold for $95 000. Explain

why this is not what the model predicted.

c) If you were going to use multiple regression to develop such a model, what other quantitative variables might you include?

d) What is the value of the coefficient of determination in this problem? PX

• 4.36 Accountants at the firm Michael Vest, Chartered Accountants, believed that several travelling executives were sub- mitting unusually high travel vouchers when they returned from business trips. First, they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple- regression equation relating expected travel cost to number of days on the road (x1) and distance travelled (x2) in kilometres:

yn = $90.00 + $48.50x1 + $0.40x2 The coefficient of correlation computed was 0.68. a) If Wanda Fennell returns from a 300-kilometre trip that took

her out of town for five days, what is the expected amount she should claim as expenses?

b) Fennell submitted a reimbursement request for $685. What should the accountant do?

c) Should any other variables be included? Which ones? Why? PX

• • 4.37 Sales of music stands at Johnny Ho’s music store in Burnaby over the past 10 weeks are shown in the table.

Week Demand Week Demand

1 20 6 29

2 21 7 36

3 28 8 22

4 37 9 25

5 25 10 28

a) Forecast demand for each week, including week 10, using expo- nential smoothing with a 5 0.5 (initial forecast 5 20).

b) Compute the MAD. c) Compute the tracking signal. PX

• • 4.38 City government has collected the following data on annual sales tax collections and new car registrations:

Annual Sales Tax Collections (in millions)

1.0 1.4 1.9 2.0 1.8 2.1 2.3

New Car Registrations (in thousands)

10 12 15 16 14 17 20

Determine the following: a) The least squares regression equation. b) Using the results of part (a), find the estimated sales tax collec-

tions if new car registrations total 22 000. c) The coefficients of correlation and determination. PX

• • 4.39 Dr. Susan Sweeney, an Edmonton psychologist, spe- cializes in treating patients who are agoraphobic (i.e., afraid to leave their homes). The following table indicates how many patients Dr. Sweeney has seen each year for the past 10 years. It also indi- cates what the robbery rate was in Edmonton during the same year:

Year 1 2 3 4 5 6 7 8 9 10

Number of Patients

36 33 40 41 40 55 60 54 58 61

Robbery Rate per 1000 Population

58.3 61.1 73.4 75.7 81.1 89.0 101.1 94.8 103.3 116.2

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144 PART 1 Introduction to Operations Management

Using trend analysis, predict the number of patients Dr. Sweeney will see in years 11 and 12 as a function of time. How well does the model fit the data? PX

• • 4.40 Using the data in Problem 4.39, apply linear regression to study the relationship between the robbery rate and Dr. Sweeney’s patient load. If the robbery rate increases to 131.2 in year 11, how many phobic patients will Dr. Sweeney treat? If the robbery rate drops to 90.6, what is the patient projection? PX

• • • 4.41 Bus and subway ridership for the summer months in London, England, is believed to be tied heavily to the number of tourists visiting the city. During the past 12 years, the following data have been obtained:

Year (summer months)

Number of Tourists (in millions)

Ridership (in millions)

1 7 1.5

2 2 1.0

3 6 1.3

4 4 1.5

5 14 2.5

6 15 2.7

7 16 2.4

8 12 2.0

9 14 2.7

10 20 4.4

11 15 3.4

12 7 1.7

a) Plot these data and decide if a linear model is reasonable. b) Develop a regression relationship. c) What is expected ridership if 10 million tourists visit London in

a year? d) Explain the predicted ridership if there are no tourists at all. e) What is the standard error of the estimate? f) What is the model’s correlation coefficient and coefficient of

determination? PX

• • • 4.42 Ontario Power Generation has been collecting data on demand for electric power in its western subregion for only the past two years. Those data are shown in the table below.

Demand in Megawatts

Month Last Year This Year

January 5 17

February 6 14

March 10 20

April 13 23

May 18 30

June 15 38

July 23 44

August 26 41

September 21 33

October 15 23

November 12 26

December 14 17

To plan for expansion and to arrange to borrow power from neigh- bouring utilities during peak periods, the utility needs to be able to forecast demand for each month next year. However, the stand- ard forecasting models discussed in this chapter will not fit the data observed for the two years. a) What are the weaknesses of standard forecasting techniques as

applied to this set of data? b) Because known models are not appropriate here, propose your

own approach to forecasting. Although there is no perfect solu- tion to tackling data such as these (in other words, there are no 100% right or wrong answers), justify your model.

c) Forecast demand for each month next year using the model you propose.

• • • 4.43 Emergency calls to the 911 system of Winnipeg for the past 24 weeks are shown in the following table:

Week 1 2 3 4 5 6 7 8 9 10 11 12

Calls 50 35 25 40 45 35 20 30 35 20 15 40

Week 13 14 15 16 17 18 19 20 21 22 23 24

Calls 55 35 25 55 55 40 35 60 75 50 40 65

a) Compute the exponentially smoothed forecast of calls for each week. Assume an initial forecast of 50 calls in the first week, and use a 5 0.2. What is the forecast for week 25?

b) Reforecast each period using a 5 0.6. c) Actual calls during week 25 were 85. Which smoothing constant

provides a superior forecast? Explain and justify the measure of error you used. PX

• • • 4.44 Using the 911 call data in Problem 4.43, forecast calls for weeks 2 through 25 with a trend-adjusted exponential smooth- ing model. Assume an initial forecast for 50 calls for week 1 and an initial trend of zero. Use smoothing constants of a 5 0.3 and b 5 0.2. Is this model better than that of Problem 4.43? What adjust- ment might be useful for further improvement? (Again, assume that actual calls in week 25 were 85.) PX

• • • 4.45 The following are monthly actual and forecast demand levels for May through December for units of a product manufac- tured by the N. Tamimi Pharmaceutical Company:

Month Actual Demand Forecast Demand

May 100 100

June 80 104

July 110 99

August 115 101

September 105 104

October 110 104

November 125 105

December 120 109

What is the value of the tracking signal as of the end of December?

• • 4.46 Thirteen students entered the business program at Hillcrest College two years ago. The following table indicates what students scored on their initial placement math exams and their grade point averages (GPAs) after students were in the Hillcrest program for two years.

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Chapter 4 Forecasting 145

Student A B C D E F G Exam Score 421 377 585 690 608 390 415 GPA 2.90 2.93 3.00 3.45 3.66 2.88 2.15

Student H I J K L M Exam Score 481 729 501 613 709 366 GPA 2.53 3.22 1.99 2.75 3.90 1.60

a) Is there a meaningful relationship between their initial place- ment math scores and grades?

b) If a student scores a 350, what do you think his or her GPA will be? c) What about a student who scores 800?

• • • 4.47 City Cycles has just started selling the new Z-10 moun- tain bike, with monthly sales as shown in the table. First, co-owner Amit wants to forecast by exponential smoothing by initially setting February’s forecast equal to January’s sales with a 5 0.1. Co-owner Barbara wants to use a three-period moving average.

Sales Amit Barbara Amit’s Error

Barbara’s Error

January 400 —

February 380 400

March 410

April 375

May

a) Is there a strong linear trend in sales over time? b) Fill in the table with what Amit and Barbara each forecast for

May and the earlier months, as relevant. c) Assume that May’s actual sales figure turns out to be 405.

Complete the table’s columns and then calculate the mean abso- lute deviation for both Amit’s and Barbara’s methods.

d) Based on these calculations, which method seems more accu- rate? PX

• • 4.48 Sundar Balakrishnan, the general manager of Precision Engineering Corporation (PEC), thinks that his firm’s engineer- ing services contracted to highway construction firms are directly related to the volume of highway construction business contracted with companies in his geographic area. He wonders if this is really so and, if it is, can this information help him plan his operations better by forecasting the quantity of his engineering services required by construction firms in each quarter of the year? The fol- lowing table presents the sales of his services and total amounts of contracts for highway construction over the past eight quarters:

Quarter 1 2 3 4 5 6 7 8

Sales of PEC Services (in $ thousands)

8 10 15 9 12 13 12 16

Contracts Released (in $ thousands)

153 172 197 178 185 199 205 226

a) Using this data, develop a regression equation for predicting the level of demand of Precision’s services.

b) Determine the coefficient of correlation and the standard error of the estimate. PX

• • • • 4.49 Western Provincial Trust Company is proud of its long tradition in Canada. It has bucked the trend of financial and liquid- ity problems that has repeatedly plagued the industry. Deposits have increased slowly but surely over the years, despite recessions in 1983, 1988, 1991, 2001, and 2008. Management believes it is necessary to have a long-range strategic plan including a one-year forecast and preferably even a give-year forecast of deposits. They examine the past deposit data and also contrast it against the pro- vincial gross domestic product (GDP) over the same 44 years. The resulting data are in the following table:

Year Depositsa GDPb Year Depositsa GDPb

1966 0.25 0.4 1988 6.2 2.5

1967 0.24 0.4 1989 4.1 2.8

1968 0.24 0.5 1990 4.5 2.9

1969 0.26 0.7 1991 6.1 3.4

1970 0.25 0.9 1992 7.7 3.8

1971 0.30 1.0 1993 10.1 4.1

1972 0.31 1.4 1994 15.2 4.0

1973 0.32 1.7 1995 18.1 4.0

1974 0.24 1.3 1996 24.1 3.9

1975 0.26 1.2 1997 25.6 3.8

1976 0.25 1.1 1998 30.3 3.8

1977 0.33 0.9 1999 36.0 3.7

1978 0.50 1.2 2000 31.1 4.1

1979 0.95 1.2 2001 31.7 4.1

1980 1.70 1.2 2002 38.5 4.0

1981 2.3 1.6 2003 47.9 4.5

1982 2.8 1.5 2004 49.1 4.6

1983 2.8 1.6 2005 55.8 4.5

1984 2.7 1.7 2006 70.1 4.6

1985 3.9 1.9 2007 70.9 4.6

1986 4.9 1.9 2008 79.1 4.7

1987 5.3 2.3 2009 94.0 5.0

aIn $ millions. bIn $ billions.

a) Using exponential smoothing, with a 5 0.6, then trend analysis, and finally linear regression, discuss which forecasting model fits best for Western Provincial’s strategic plan. Justify the selec- tion of one model over another.

b) Carefully examine the data. Can you make a case for exclud- ing a portion of the information? Why? Would that change your choice of model? PX

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146 PART 1 Introduction to Operations Management

Fast Creek Lightning: (B)*

Fast Creek is a city in south central Saskatchewan located along the Trans-Canada Highway. Fast Creek has a population of just over 27 000 residents and is a regional hub for the many smaller towns and hundreds of farms in the surrounding area. Fast Creek is a trans- portation and industrial centre, and has several federal and provin- cial government offices.

Fast Creek is also a sports centre, and its junior hockey team, the Fast Creek Lightning, has a long history of success in the Central Hockey League but has not won a major trophy in close to 10 years. Since the legendary Scotty Beauchamp was hired as head coach in 2011 (in the hopes of winning the elusive league and national championship), total attendance at home games for each month has increased. Prior to Beauchamp’s arrival, attendance averaged 25 000 to 29 000 per month (or between 5000 and 5800 tickets for each of the five home games per month). Season ticket sales bumped up by almost 2000 just with the announcement of the new coach’s arrival. The Fast Creek Lightning are ready to move to the big time!

The immediate issue facing the Lightning, however, is not the championship. It is capacity. The existing Fast Creek arena, built in 1953, has seating for 10 800 fans. The following table indicates total home game attendance each month of the season for the past six years.

One of Beauchamp’s demands on joining the Lightning had been a new arena. With attendance increasing, Lightning executives and city officials have begun to face the issue head-on. Beauchamp would like a state-of-the-art training facility solely for his players as an additional feature of any expansion.

The Lightning’s owner, Keith MacLennan, has decided it is time for his vice-president of development to forecast when the existing arena will “max out”. The expansion is, in his mind, a given. But MacLennan needs to know how long he could wait. He also seeks a revenue projection, assuming an average ticket price of $50 in 2017–2018 and a 5% increase each season in future prices.

Discussion Questions 1. Develop a forecasting model, justifying its selection over other

forecasting techniques, and project attendance through the 2018–2019 season.

2. What revenues are to be expected in the 2017–2018 and 2018–2019 seasons?

3. Discuss the team’s options.

CASE STUDIES

With the growth of Hard Rock Cafe—from one pub in London in 1971 to more than 145 restaurants in 60 countries today—came a corporate-wide demand for better forecasting. Hard Rock uses long- range forecasting in setting a capacity plan and intermediate-term forecasting for locking in contracts for leather goods (used in jack- ets) and for such food items as beef, chicken, and pork. Its short- term sales forecasts are conducted each month, by cafe, and then aggregated for a headquarters view.

The heart of the sales forecasting system is the point-of-sale system (POS), which, in effect, captures transaction data on nearly every person who walks through a cafe’s door. The sale of each entrée represents one customer; the entrée sales data are transmit- ted daily to the Orlando corporate headquarters’ database. There, the financial team, headed by Todd Lindsey, begins the forecast

process. Lindsey forecasts monthly guest counts, retail sales, ban- quet sales, and concert sales (if applicable) at each cafe. The general managers of individual cafes tap into the same database to prepare a daily forecast for their sites. A cafe manager pulls up prior years’ sales for that day, adding information from the local chamber of commerce or tourist board on upcoming events such as a major convention, sporting event, or concert in the city where the cafe is located. The daily forecast is further broken into hourly sales, which drives employee scheduling. An hourly forecast of $5500 in sales translates into 19 workstations, which are further broken down into a specific number of wait staff, hosts, bartenders, and kitchen staff. Computerized scheduling software plugs people in based on their availability. Variances between forecast and actual sales are then examined to see why errors occurred.

Forecasting at Hard Rock CafeVideo Case

*This integrated study runs throughout the text. Issues facing Fast Creek’s hockey expansion include (A) managing the arena project (Chapter 3); (C) quality of facilities (Chapter 6); (D) break-even analysis for food services (Supplement 7 MyLab Operations Management); (E) location of the new arena (Chapter 8 MyLab Operations Management); (F) inventory planning of hockey programs (Chapter 12 MyLab Operations Management); and (G) scheduling of campus security officers/staff for game days (Chapter 13). Recurring cases are also available in a separate file for instructors using the PCL.

Month 2011–2012 2012–2013 2013–2014

November 34 200 36 100 35 900

Decembera 39 800 40 200 46 500

January 38 200 39 100 43 100

Februaryb 26 900 25 300 27 900

March 35 100 36 200 39 200

Month 2014–2015 2015–2016 2016–2017

November 41 900 42 500 46 900

Decembera 46 100 48 200 50 100

January 43 900 44 200 45 900

Februaryb 30 100 33 900 36 300

March 40 500 47 800 49 900 aEvery December, Fast Creek hosts a Holiday Classic weekend with special promo- tions and an old-timers’ game that draws large crowds

bA popular week-long winter carnival in nearby Helmsville every February has a negative impact on attendance.

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Chapter 4 Forecasting 147

Hard Rock doesn’t limit its use of forecasting tools to sales. To evaluate managers and set bonuses, a three-year weighted moving average is applied to cafe sales. If cafe general managers exceed their targets, a bonus is computed. Todd Lindsey, at corporate head- quarters, applies weights of 40% to the most recent year’s sales, 40% to the year before, and 20% to sales two years ago in reaching his moving average.

An even more sophisticated application of statistics is found in Hard Rock’s menu planning. Using multiple regression, man- agers can compute the impact on demand of other menu items if the price of one item is changed. For example, if the price of a cheeseburger increases from $7.99 to $8.99, Hard Rock can predict the effect this will have on sales of chicken sandwiches, pork sand- wiches, and salads. Managers do the same analysis on menu place- ment, with the centre section driving higher sales volumes. When an item such as a hamburger is moved off the centre to one of the side flaps, the corresponding effect on related items, say French fries, is determined.

Discussion Questions* 1. Describe three different forecasting applications at Hard Rock.

Name three other areas in which you think Hard Rock could use forecasting models.

2. What is the role of the POS system in forecasting at Hard Rock? 3. Justify the use of the weighting system used for evaluating man-

agers for annual bonuses. 4. Name several variables besides those mentioned in the case that

could be used as good predictors of daily sales in each cafe. 5. At Hard Rock’s Moscow restaurant, the manager is trying to

evaluate how a new advertising campaign affects guest counts. Using data for the past 10 months (see the table), develop a least- squares regression relationship and then forecast the expected guest count when advertising is $65 000.

Hard Rock’s Moscow Cafea

Month 1 2 3 4 5 6 7 8 9 10

Guest count (in thousands)

21 24 27 32 29 37 43 43 54 66

Advertising (in $ thousands)

14 17 25 25 35 35 45 50 60 60

aThese figures are used for purposes of this case study.

cAdditional Case Study: Visit MyLab Operations Management for this case study: North-South Airlines: Reflects the merger of two airlines and addresses their maintenance costs.

Main Heading Review Material

MyLab Operations Management

WHAT IS FORECASTING? (pp. 104–106)

• Forecasting—The art and science of predicting future events. • Economic forecasts—Planning indicators that are valuable in helping organi-

zations prepare medium- to long-range forecasts. • Technological forecasts—Long-term forecasts concerned with the rates of

technological progress. • Demand forecasts—Projections of a company’s sales for each time period in

the planning horizon.

THE STRATEGIC IMPORTANCE OF FORECASTING (pp. 106–107)

The forecast is the only estimate of demand until actual demand becomes known. Forecasts of demand drive decisions in many areas, including Human resources, Capacity, Supply chain management.

VIDEO 4.1

Forecasting at Hard Rock Cafe

SEVEN STEPS IN THE FORECASTING SYSTEM (p. 107)

Forecasting follows seven basic steps: (1) Determine the use of the forecast; (2) Select the items to be forecasted; (3) Determine the time horizon of the forecast; (4) Select the forecasting model(s); (5) Gather the data needed to make the forecast; (6) Make the forecast; (7) Validate and implement the results.

FORECASTING APPROACHES (pp. 107–108)

• Quantitative forecasts—Forecasts that employ mathematical modelling to forecast demand.

• Qualitative forecasts—Forecasts that incorporate factors such as the decision maker’s intuition, emotions, personal experiences, and value system.

• Jury of executive opinion—A forecasting technique that uses the opinion of a small group of high-level managers to form a group estimate of demand.

CHAPTER 4 RAPID REVIEW

*You may wish to view the video that accompanies this case before addressing these questions.

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148 PART 1 Introduction to Operations Management

Main Heading Review Material

MyLab Operations Management

• Delphi method—A forecasting technique using a group process that allows experts to make forecasts.

• Sales force composite—A forecasting technique based on salespersons’ estimates of expected sales.

• Consumer market survey—A forecasting method that solicits input from customers or potential customers regarding future purchasing plans.

• Time series—A forecasting technique that uses a series of past data points to make a forecast.

TIME-SERIES FORECASTING (pp. 108–126)

• Naive approach—A forecasting technique that assumes that demand in the next period is equal to demand in the most recent period.

• Moving averages—A forecasting method that uses an average of the n most recent periods of data to forecast the next period.

Moving average = ΣDemand in previous n periods

n (4-1)

Weighted moving average = Σ(Weight for period n) (Demand in period n)

ΣWeights (4-2)

• Exponential smoothing—A weighted moving average forecasting technique in which data points are weighted by an exponential function.

• Smoothing constant—The weighting factor, a, used in an exponential smoothing forecast, a number between 0 and 1.

New forecast 5 Last period’s forecast 1 a (Last period’s actual demand − Last period’s forecast) (4-3)

Exponential smoothing formula: Ft 5 Ft−1 1 a(At−1 – Ft−1) (4-4) where Ft 5 new forecast

Ft−1 5 previous period’s forecast

a 5 smoothing (or weighting) constant (0 ≤ a ≤ 1) At−1 5 previous period’s actual demand

• Mean absolute deviation (MAD)—A measure of the overall forecast error for a model.

MAD = Σ ∙ Actual - Forecast ∙

n (4-5)

• Mean squared error (MSE)—The average of the squared differences between the forecasted and observed values.

MSE = Σ(Forecast errors)2

n (4-6)

• Mean absolute percent error (MAPE)—The average of the absolute dif- ferences between the forecast and actual values, expressed as a percentage of actual values.

MAPE = a

n

i = 1 100 ∙ Actualt - Forecastt ∙>Actualt

n (4-7)

Exponential Smoothing With Trend Adjustment

Forecast including trend (FITt) 5 Exponentially smoothed forecast (Ft)

1 Exponentially smoothed trend (Tt) (4-8)

• Trend projection—A time-series forecasting method that fits a trend line to a series of historical data points and then projects the line into the future for forecasts.

Forecast including trend (FITt) 5 Exponentially smoothed forecast (Ft)

1 Exponentially smoothed trend (Tt) (4-8)

Ft = α(At-1) + (1 - α)(Ft-1 + Tt-1) (4-9)

Problems: 4.1–4.23, 4.25–4.29, 4.33, 4.37, 4.39, 4.43, 4.44, 4.47, 4.49 Virtual Office Hours for Solved Problems: 4.2–4.4

ACTIVE MODELS 4.1–4.4

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Chapter 4 Forecasting 149

Main Heading Review Material

MyLab Operations Management

Tt = b(Ft - Ft-1) + (1 - b)Tt - 1 (4-10)

where Ft 5 exponentially smoothed forecast of the data series in period t Tt 5 exponentially smoothed trend in period t At 5 actual demand in period t a 5 smoothing constant for the average (0 ≤ a ≤ 1) b 5 smoothing constant for the trend (0 ≤ b ≤ 1)

Trend Projection and Regression Analysis

yn = a + bx, where b = Σxy - nx y Σx2 - nx2

, and a = y - bx (4-11),(4-12),(4-13)

• Seasonal variations—Regular upward or downward movements in a time series that tie to recurring events.

• Cycles—Patterns in the data that occur every several years.

ASSOCIATIVE FORECASTING METHODS: REGRESSION AND CORRELATION ANALYSIS (pp. 126–131)

• Linear-regression analysis—A straight-line mathematical model to describe the functional relationships between independent and dependent variables.

• Standard error of the estimate—A measure of variability around the regres- sion line—its standard deviation.

Sy, x = B Σ(y - yc)2n - 2 (4-14) Sy, x = B Σy2 - aΣy - bΣxyn - 2 (4-15) • Coefficient of correlation—A measure of the strength of the relationship

between two variables.

r = nΣxy - ΣxΣy2[nΣx2 - (Σx)2][nΣy2 - (Σy)2] (4-16)

• Coefficient of determination—A measure of the amount of variation in the dependent variable about its mean that is explained by the regression equation.

• Multiple regression—An associative forecasting method with more than one independent variable.

Multiple@regression forecast: yn = a + b1x1 + b2x2 (4-17)

Problems: 4.24, 4.30–4.32, 4.34– 4.36, 4.38, 4.40, 4.41, 4.46, 4.48

MONITORING AND CONTROLLING FORECASTS (pp. 132–134)

• Tracking signal—A measurement of how well the forecast is predicting actual values.

(Tracking signal) = Cumulative error

MAD

= Σ(Actual demand in period i - Forecast demand in period i)

MAD

Where (MAD) = Σ ∙ Actual - Forecast ∙

n (4-18)

• Bias—A forecast that is consistently higher or consistently lower than actual values of a time series.

• Adaptive smoothing—An approach to exponential smoothing forecasting in which the smoothing constant is automatically changed to keep errors to a minimum.

• Focus forecasting—Forecasting that tries a variety of computer models and selects the best one for a particular application.

Problems: 4.37, 4.45

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150 PART 1 Introduction to Operations Management

LO1 Forecasting time horizons include: a) long range. b) medium range. c) short range. d) all of the above.

LO2 Qualitative methods of forecasting include: a) sales force composite. b) jury of executive opinion. c) consumer market survey. d) exponential smoothing. e) all except (d).

LO3 The difference between a moving-average model and an exponential smoothing model is that ____________.

LO4 Three popular measures of forecast accuracy are: a) total error, average error, and mean error. b) average error, median error, and maximum error. c) median error, minimum error, and maximum absolute error. d) mean absolute deviation, mean squared error, and mean absolute

percent error.

LO5 Average demand for iPods in Apple store in Rome, Italy, is 800 units per month. The May monthly index is 1.25. What is the seasonally adjusted sales forecast for May?

a) 640 units b) 798.75 units c) 800 units d) 1000 units e) cannot be calculated with the information given

LO6 The main difference between simple and multiple regression is ____________.

LO7 The tracking signal is the: a) standard error of the estimate. b) cumulative error. c) mean absolute deviation (MAD). d) ratio of the cumulative error to MAD. e) mean absolute percent error (MAPE).

Self-Test  Before taking the self-test, refer to the learning objectives listed at the beginning of the chapter and the key terms listed at the end of the chapter.

Answers: LO1. d; LO2. e; LO3. exponential smoothing is a weighted moving average model in which all prior values are weighted with a set of exponen- tially declining weights; LO4. d; LO5. d; LO6. simple regression has only one independent variable; LO7. d.

Main Heading Review Material

MyLab Operations Management

FORECASTING IN THE SERVICE SECTOR (pp. 134–135)

Service sector forecasting may require good short-term demand records, even per 15-minute intervals. Demand during holidays or specific weather events may also need to be tracked.

Most of these questions can be found in MyLab Operations Management. Visit MyLab Operations Management to access cases, videos, downloadable software, and much more. MyLab Operations Management Management also features a personalized Study Plan that helps you identify which chapter concepts you’ve mastered and guides you towards study tools for additional practice.

MyLab Operations Management

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Design of Goods and Services

PART TWO Designing Operations (Chapters 5–10)

Learning Objectives LO1 Define product life cycle 154

LO2 Describe a product development system 157

LO3 Build a house of quality 157

LO4 Describe how time-based competition is implemented by OM 164

LO5 Describe how products and services are defined by OM 166

LO6 Describe the documents needed for production 169

LO7 Explain how the customer participates in the design and delivery of services 170

LO8 Apply decision trees to product issues 173

Product Strategy Provides Competitive Advantage at Regal Marine Thirty years after its founding by potato farmer Paul Kuck, Regal Marine

has become a powerful force on the waters of the world. The world’s

third-largest boat manufacturer (by global sales), Regal exports to

30 countries, including Russia and China. Almost one-third of its sales

are overseas.

Product design is critical in the highly competitive pleasure boat busi-

ness: “We keep in touch with our customers and we respond to the market-

place,” says Kuck. “We’re introducing six new models this year alone. I’d say

we’re definitely on the aggressive end of the spectrum.”

With changing consumer tastes, compounded by material changes and

ever-improving marine engineering, the design function is under constant

pressure. Added to these pressures is the constant issue of cost competi-

tiveness combined with the need to provide good value for customers.

Consequently, Regal Marine is a frequent user of computer-aided design

(CAD). New designs come to life via Regal’s three-dimensional CAD system

borrowed from automotive technology. Regal’s naval architects’ goal is to

5

151

Global Company Profile Regal Marine

Jochen Tack/Alamy Stock Photo

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152 PART 2 Designing Operations

continue to reduce the time from concept to proto-

type to production. The sophisticated CAD system not

only has reduced product development time but also

has reduced problems with tooling and production,

resulting in a superior product.

All of Regal’s products, from its $14 000 5.7-metre

boat to the $500 000 13-metre Commodore yacht,

follow a similar production process. Hulls and decks

are separately hand-produced by spraying pre-formed

moulds with three to five layers of a fibreglass lami-

nate. The hulls and decks harden and are removed to

become the lower and upper structure of the boat. As

they move to the assembly line, they are joined and

components are added at each workstation.

Wooden components, precut in-house by computer-

driven routers, are delivered on a just-in-time basis for

installation at one station. Engines—one of the few

purchased components—are installed at another

station. Racks of electrical wiring harnesses, engi-

neered and rigged in-house, are then installed. An

in-house upholstery department delivers customized

seats, beds, dashboards, or other cushioned compo-

nents. Finally, chrome fixtures are put in place, and

the boat is sent to Regal’s test tank for watertight,

gauge, and system inspection.

Goods and Services Selection Global firms like Regal Marine know that the basis for an organization’s existence is the good or service it provides society. Great products are the keys to success. Anything less than an excellent product strategy can be devastating to a firm. To maximize the potential for success, top companies focus on only a few products and then concentrate on those products. For instance, Honda’s focus is engines. Virtually all of Honda’s sales (autos, motorcycles, generators, lawn mowers) are based on its outstanding engine technology. Likewise, Intel’s focus is on microprocessors, and Michelin’s is on tires. However, because most products have a limited and even predictable life cycle, companies must constantly be looking for new products to design, develop, and take to market. Good opera- tions managers insist on strong communication among customer, product, processes, and suppliers, which results in a high success rate for their new products. 3M’s goal is to produce 30% of its profit from products introduced in the last four years. Benchmarks vary by industry, of course; Regal introduces six new boats a year, and Rubbermaid introduces a new product each day!

One product strategy is to build particular competence in customizing an established family of goods or services. This approach allows the customer to choose product variations while reinforcing the organization’s strength. Dell Computer, for example, has built a huge market by delivering computers with the exact hardware and software desired by end users. And Dell does it fast—it understands that speed to market is imperative to gain a competitive edge.

Note that many service firms also refer to their offerings as products. For instance, when Allstate Insurance offers a new homeowner’s policy, it is referred to as a new “product”. Similarly, when CIBC opens a mortgage department, it offers a number of new mortgage “products”. Although the term product may often refer to tangible goods, it also refers to offer- ings by service organizations.

An effective product strategy links product decisions with investment, market share, and prod- uct life cycle, and defines the breadth of the product line. The objective of the product decision is to develop and implement a product strategy that meets the demands of the marketplace with a competitive advantage. As one of the 10 decisions of OM, product strategy may focus on develop- ing a competitive advantage via differentiation, low cost, rapid response, or a combination of these.

VIDEO 5.1 Product Strategy at Regal Marine

Product decision The selection, definition, and design of products.

Once a hull has been pulled from the mould, it travels down a monorail assembly path. JIT inventory delivers engines, wiring, seats, flooring, and interiors when needed.

Ba rr

y Re

nd er

Product strategy is critical to achieving competitive advantage.

STUDENT TIP

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Chapter 5 Design of Goods and Services 153

PRODUCT STRATEGY OPTIONS SUPPORT COMPETITIVE ADVANTAGE A world of options exists in the selection, definition, and design of products. Product selection is choosing the good or service to provide to customers or clients. For instance, hospitals specialize in various types of patients and medical procedures. In consultation with a province’s Ministry of Health, it could be determined that the public is best served if a particular hospital will operate as a general-purpose hospital, a maternity hospital, or, as in the case of the Canadian hospital Shouldice, will specialize in hernias. Hospitals select their products when they decide what kind of hospital to be. Numerous other options exist for hospitals, just as they exist for Taco Bell and Toyota.

Service organizations like Shouldice Hospital differentiate themselves through their prod- uct. Shouldice differentiates itself by offering a distinctly unique and high-quality product. Its world-renowned specialization in hernia repair service is so effective it allows patients to return to normal living in eight days as opposed to the average two weeks—and with very few com- plications. The entire production system is designed for this one product. Local anaesthetics are used, patients enter and leave the operating room on their own, rooms are spartan, and meals are served in a common dining room, encouraging patients to get out of bed for meals and join their fellows in the lounge. As Shouldice has demonstrated, product selection affects the entire production system.

Taco Bell has developed and executed a low-cost strategy through product design. By designing a product (its menu) that can be produced with a minimum of labour in small kitchens, Taco Bell has developed a product line that is both low cost and high value. Successful product design has allowed Taco Bell to increase the food content of its products from 27¢ to 45¢ of each sales dollar.

Toyota’s strategy is rapid response to changing consumer demand. By executing the fastest automobile design in the industry, Toyota has driven the speed of product development down to well under two years in an industry whose standard is still over two years. The shorter design time allows Toyota to get a car to market before consumer tastes change and to do so with the latest technology and innovations.

Product decisions are fundamental to an organization’s strategy and have major implications throughout the operations function. For instance, GM’s steering columns are a good example of the strong role product design plays in both quality and efficiency. The redesigned steering col- umn has a simpler design, with about 30% fewer parts than its predecessor. The result: Assembly

Product Design Can Manifest Itself in Concepts, Technology, and Packaging. Whether it is a design focused on style at Nike (a), the application of technology at Samsung (b), or a new container at Sherwin Williams (c), operations managers need to remind themselves that the creative process is ongoing with major implications for production.

(a) Concepts: Nike, in its creative way, has moved athletic shoes from utilitarian necessities into glam- orous accessories and in the process is constantly reinventing all parts of the shoe, including the heel.

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M05A_HEIZ8076_03_SE_C05A.indd 153 27/11/18 9:03 PM

154 PART 2 Designing Operations

time is one-third that of the older column, and the new column’s quality is about seven times higher. As an added bonus, machinery on the new line costs a third less than that on the old line.

PRODUCT LIFE CYCLES Products are born. They live and they die. They are cast aside by a changing society. It may be helpful to think of a product’s life as divided into four phases. Those phases are introduction, growth, maturity, and decline.

Product life cycles may be a matter of a few hours (a newspaper), months (seasonal fashions and personal computers), years (video cassette tapes), or decades (cars). Regardless of the length of the cycle, the task for the operations manager is the same: to design a system that helps introduce new products successfully. If the operations function cannot perform effectively at this stage, the firm may be saddled with losers—products that cannot be produced efficiently or perhaps at all.

Figure 5.1 shows the four life cycle stages and the relationship of product sales, cash flow, and profit over the life cycle of a product. Note that typically a firm has a negative cash flow while it develops a product. When the product is successful, those losses may be recovered. Eventually, the successful product may yield a profit prior to its decline. However, the profit is fleeting—hence, the constant demand for new products.

LIFE CYCLE AND STRATEGY Just as operations managers must be prepared to develop new products, they must also be pre- pared to develop strategies for new and existing products. Periodic examination of products is appropriate because strategies change as products move through their life cycle. Successful product strategies require determining the best strategy for each product based on its position in its life cycle. A firm, therefore, identifies products or families of products and their position in the life cycle. Let us review some strategy options as products move through their life cycles.

INTRODUCTORY PHASE Because products in the introductory phase are still being “fine-tuned” for the market, as are their production techniques, they may warrant unusual expenditures for (1) research, (2) product development, (3) process modification and enhancement, and (4) supplier development. For example, when cellular phones were first introduced, the features desired by the public were still being determined. At the same time, operations managers were still groping for the best manufacturing techniques.

GROWTH PHASE In the growth phase, product design has begun to stabilize, and effective fore- casting of capacity requirements is necessary. Adding capacity or enhancing existing capacity to accommodate the increase in product demand may be necessary.

MATURITY PHASE By the time a product is mature, competitors are established. So high-volume, innovative production may be appropriate. Improved cost control, reduction in options, and a paring down of the product line may be effective or necessary for profitability and market share.

DECLINE PHASE Management may need to be ruthless with those products whose life cycle is at an end. Dying products are typically poor products in which to invest resources and managerial talent. Unless dying products make some unique contribution to the firm’s reputation or its prod- uct line or can be sold with an unusually high contribution, their production should be terminated.1

LO1 Define product life cycle

Introduction Growth Maturity Decline

Cost of development and production

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s, c

o st

, a n d c

a sh

fl o w Sales revenue

Loss

Net revenue (profit)

Cash flow

Negative cash flow

FIGURE 5.1

Product Life Cycle, Sales, Cost, and Profit

1 Contribution is defined as the difference between direct cost and selling price. Direct costs are labour and material that go into the product.

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Chapter 5 Design of Goods and Services 155

PRODUCT-BY-VALUE ANALYSIS The effective operations manager selects items that show the greatest promise. This is the Pareto principle (i.e., focus on the critical few, not the trivial many) applied to product mix: Resources are to be invested in the critical few and not the trivial many. Product-by-value analysis lists products in descending order of their individual dollar contribution to the firm. It also lists the total annual dollar contribution of the product. Low contribution on a per-unit basis by a particular product may look substantially different if it represents a large portion of the company’s sales.

A product-by-value report allows management to evaluate possible strategies for each prod- uct. These may include increasing cash flow (e.g., increasing contribution by raising selling price or lowering cost), increasing market penetration (improving quality and/or reducing cost or price), or reducing costs (improving the production process). The report may also tell manage- ment which product offerings should be eliminated and which fail to justify further investment in research and development or capital equipment. Product-by-value analysis focuses manage- ment’s attention on the strategic direction for each product.

Generating New Products Because products die; because products must be weeded out and replaced; because firms generate most of their revenue and profit from new products—product selection, definition, and design take place on a continuing basis. Consider recent product changes: TV to HDTV, radio to satellite radio, coffee shop to Starbucks lifestyle coffee, travelling circus to Cirque du Soleil, land line to cell phone, cell phone to smartphone, Walkman to iPod, an Internet of digital information to an Internet of “things”—and the list goes on. Knowing how to find and develop new products suc- cessfully is a requirement.

NEW PRODUCT OPPORTUNITIES Aggressive new product development requires that organizations build structures internally that have open communication with customers, innovative organizational cultures, aggressive R&D, strong leadership, formal incentives, and training. Only then can a firm profitably and energeti- cally focus on specific opportunities such as the following:

1. Understanding the customer is the premier issue in new product development. Many com- mercially important products are initially thought of and even prototyped by users rather than producers. Such products tend to be developed by “lead users”—companies, organizations, or individuals that are well ahead of market trends and have needs that go far beyond those of average users. The operations manager must be “tuned in” to the market and particularly to these innovative lead users.

2. Economic change brings increasing levels of affluence in the long run but economic cycles and price changes in the short run. In the long run, for instance, more and more people can afford automobiles, but in the short run, a recession may weaken the demand for automobiles.

3. Sociological and demographic change may appear in such factors as decreasing family size. This trend alters the size preference for homes, apartments, and automobiles.

4. Technological change makes possible everything from cell phones to iPads to artificial hearts.

5. Political/legal change brings about new trade agreements, tariffs, and government requirements. 6. Other changes may be brought about through market practice, professional standards, sup-

pliers, and distributors.

Operations managers must be aware of these dynamics and be able to anticipate changes in product opportunities, the products themselves, product volume, and product mix.

IMPORTANCE OF NEW PRODUCTS The importance of new products cannot be overestimated. As Figure 5.2(a) shows, leading com- panies generate a substantial portion of their sales from products less than five years old. Even Disney (Figure 5.2(b)) needs new theme parks to boost attendance. And giant Cisco Systems is expanding from its core business of making routers and switches into building its own computer servers (Figure 5.2(c)). The need for new products is why Gillette developed its multi blade

Product-by-value analysis A list of products, in descending order of their individual dollar contribution to the firm, as well as the total annual dollar contribution of the product.

Societies reward those who supply new products that reflect their needs.

STUDENT TIP

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156 PART 2 Designing Operations

razors, in spite of continuing high sales of its phenomenally successful Sensor razor, and why Disney innovates in spite of being the leading family entertainment company in the world.

Despite constant efforts to introduce viable new products, many new products do not succeed. Indeed, for General Mills to come up with a winner in the breakfast cereal market—defined as a cereal that gets a scant half of 1% of the market—isn’t easy. Among the top 10 brands of cereal, the youngest, Honey Nut Cheerios, was created in 1979. DuPont estimates that it takes 250 ideas to yield one marketable product.2

As one can see, product selection, definition, and design occur frequently—perhaps hundreds of times for each financially successful product. Operations managers and their organizations must be able to accept risk and tolerate failure. They must accommodate a high volume of new product ideas while maintaining the activities to which they are already committed.

Product Development PRODUCT DEVELOPMENT SYSTEM An effective product strategy links product decisions with cash flow, market dynamics, product life cycle, and the organization’s capabilities. A firm must have the cash for product develop- ment, understand the changes constantly taking place in the marketplace, and have the necessary

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FIGURE 5.2 Innovation and New Products Yield Results for Both Manufacturing and Services

2 Rosabeth Kanter, John Kao, and Fred Wiersema, Innovation Breakthrough Thinking at 3M, DuPont, GE, Pfizer, and Rubbermaid (New York, NY: HarperBusiness, 1997).

Motorola went through 3000 working models before it developed its first pocket cell phone.

STUDENT TIP

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Chapter 5 Design of Goods and Services 157

talents and resources available. The product development system may well determine not only product success but also the firm’s future. Figure 5.3 shows the stages of product development. In this system, product options go through a series of steps, each having its own screening and evaluation criteria but providing a continuing flow of information to prior steps.

The screening process extends to the operations function. Optimum product development depends not only on support from other parts of the firm but also on the successful integration of all 10 of the OM decisions, from product design to maintenance. Identifying products that appear likely to capture market share, be cost effective, and be profitable, but are in fact very difficult to produce, may lead to failure rather than success.

QUALITY FUNCTION DEPLOYMENT (QFD) Quality function deployment (QFD) refers to both (1) determining what will satisfy the cus- tomer and (2) translating those customer desires into the target design. The idea is to capture a rich understanding of customer wants and to identify alternative process solutions. This informa- tion is then integrated into the evolving product design. QFD is used early in the design process to help determine what will satisfy the customer and where to deploy quality efforts.

One of the tools of QFD is the house of quality. The house of quality is a graphic technique for defining the relationship between customer desires and product (or service). Only by defining this relationship in a rigorous way can operations managers design products and processes with features desired by customers. Defining this relationship is the first step in building a world-class production system. To build the house of quality, we perform seven basic steps:

1. Identify customer wants. (What do prospective customers want in this product?) 2. Identify how the good/service will satisfy customer wants. (Identify specific product charac-

teristics, features, or attributes and show how they will satisfy customer wants.)

LO2 Describe a product development system

Quality function deployment (QFD) A process for determining customer requirements (customer “wants”) and translating them into the attributes (the “hows”) that each functional area can understand and act on.

LO3 Build a house of quality

House of quality A part of the QFD process that utilizes a planning matrix to relate customer “wants” to “how” the firm is going to meet those “wants”.

Scope for

design and

engineering teams

Scope of

product development

team

Design review: Are these product specifications the best way to meet

customer requirements?

Functional specifications: How the product will work

Customer requirements to win orders

Does firm have ability to carry out idea?

Ideas from many sources

Product specifications: How the product will be made

Test market: Does product meet customer expectations?

Introduction to market

Evaluation (success?)

FIGURE 5.3

Product Development Stages Product concepts are developed from a variety of sources, both external and internal to the firm. Concepts that survive the product idea stage progress through various stages, with nearly constant review, feed- back, and evaluation in a highly participative environment to minimize failure.

M05A_HEIZ8076_03_SE_C05A.indd 157 27/11/18 9:03 PM

158 PART 2 Designing Operations

3. Relate customer wants to product hows. (Build a matrix, as in Example 1, that shows this relationship.)

4. Identify relationships between the firm’s hows. (How do our hows tie together? For instance, in the following example, there is a high relationship between low electricity requirements and auto focus, auto exposure, and a paint pallet because they all require electricity. This relationship is shown in the “roof” of the house in Example 1.)

5. Develop importance ratings. (Using the customer’s importance ratings and weights for the relationships shown in the matrix, compute our importance ratings, as in Example 1.)

6. Evaluate competing products. (How well do competing products meet customer wants? Such an evaluation, as shown in the two columns on the right of the figure in Example 1, would be based on market research.)

7. Determine the desirable technical attributes, your performance, and the competitors’ perfor- mance against these attributes. (This is done at the bottom of the figure in Example 1.)

The following step-by-step illustration for Example 1 shows how to construct a house of quality.

Great Cameras, Inc., wants a methodology that strengthens its ability to meet customer desires with its new digital camera.

APPROACH c Use QFD’s house of quality.

SOLUTION c Build the house of quality for Great Cameras, Inc. We do so here going step by step.

EXAMPLE 1

Constructing a House of Quality

Quality Function Deployment’s (QFD's) House of Quality

Relationship between the things we can do

What we can do (how the organization is going to translate customer wants into product and process attributes and design targets)

G = good F = fair P = poor

How well what we do meets the customer’s wants (relationship matrix)

Customer importance

ratings (5 = highest)

What the customer wants

Weighted rating

Competitive assessment

Target values (technical attributes)

Technical evaluation

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Chapter 5 Design of Goods and Services 159

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Third, the team evaluated each of the customer wants against the hows. In the relationship matrix of the house, the team evaluated how well its design meets customer needs. Fourth, the “roof” of the house indicates the relationship between the attributes. Fifth, the team developed importance ratings for its design attributes on the bot- tom row of the table. This was done by assigning values (5 for high, 3 for medium, and 1 for low) to each entry in the relationship matrix, and then multiplying each of these values by the customer’s impor- tance rating. The values in the “Our importance ratings” row provide a ranking of how to proceed with product and process design, with the highest values being the most critical to a successful product.

Sixth, the house of quality is also used for the evaluation of com- petitors. The two columns on the right indicate how market research thinks competitors A and B satisfy customer wants (Good, Fair, or Poor). Products from other firms and even the proposed product can be added next to company B.G

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Seventh, the team identifies the technical attributes and evaluates how well Great Cameras, Inc., and its competitors address these attrib- utes. Here, the team decided on the noted technical attributes.

First, through market research, Great Cameras, Inc., determined what the customer wants. Those wants are shown on the left of the house of quality. Second, the prod- uct development team determined how the organization is going to translate those customer wants into product design and process attribute targets. These hows are entered across the top portion of the house of quality.

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160 PART 2 Designing Operations

Another use of QFD is to show how the quality effort will be deployed. As Figure 5.4 shows, design characteristics of House 1 become the inputs to House 2, which are satisfied by specific components of the product. Similarly, the concept is carried to House 3, where the specific components are to be satisfied through particular production processes. Once those production processes are defined, they become requirements of House 4 to be satisfied by a quality plan that will ensure conformance of those processes. The quality plan is a set of specific tolerances, procedures, methods, and sampling techniques that will ensure that the production process meets the customer requirements.

Much of the QFD effort is devoted to meeting customer requirements with design char- acteristics (House 1 in Figure 5.4), and its importance is not to be underestimated. However, the sequence of houses is a very effective way of identifying, communicating, and allocating resources throughout the system. The series of houses helps operations managers determine where to deploy quality resources. In this way we meet customer requirements, produce quality products, and win orders.

ORGANIZING FOR PRODUCT DEVELOPMENT Let’s look at four approaches to organizing for product development. First, the traditional North American approach to product development is an organization with distinct departments: a research and development department to do the necessary research; an engineering department to design the product; a manufacturing engineering department to design a product that can be produced; and a production department that produces the product. The distinct advantage of this approach is that fixed duties and responsibilities exist. The distinct disadvantage is lack of for- ward thinking: How will downstream departments in the process deal with the concepts, ideas, and designs presented to them, and ultimately what will the customer think of the product?

A second and popular approach is to assign a product manager to “champion” the product through the product development system and related organizations.

However, a third, and perhaps the best, product development approach used in North America seems to be the use of teams. Such teams are known variously as product development teams, design for manufacturability teams, and value engineering teams.

The Japanese use a fourth approach. They bypass the team issue by not subdividing organ- izations into research and development, engineering, production, and so forth. Consistent with

INSIGHT c   QFD provides an analytical tool that structures design features and technical issues, as well as providing importance rankings and competitor comparison.

LEARNING EXERCISE c  If the market research for another country indicates that “lightweight” has the most important customer ranking (5), and reliability is 3, what is the new total importance ranking for low electricity requirements, aluminum components, and ergonomic design? [Answer: 18, 15, 27, respectively.]

RELATED PROBLEMS c  5.1, 5.2, 5.3, 5.4

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FIGURE 5.4 House of Quality Sequence Indicates How to Deploy Resources to Achieve Customer Requirements

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Chapter 5 Design of Goods and Services 161

the Japanese style of group effort and teamwork, these activities are all in one organization. Japanese culture and management style are more collegial and the organization less structured than in most Western countries. Therefore, the Japanese find it unnecessary to have “teams” provide the necessary communication and coordination. However, the typical Western style, and the conventional wisdom, is to use teams.

Product development teams are charged with the responsibility of moving from market requirements for a product to achieving a product success (refer to Figure 5.3). Such teams often include representatives from marketing, manufacturing, purchasing, quality assurance, and field service personnel. Many teams also include representatives from vendors. Regardless of the formal nature of the product development effort, research suggests that success is more likely in an open, highly participative environment where those with potential contributions are allowed to make them. The objective of a product development team is to make the good or service a success. This includes marketability, manufacturability, and serviceability.

Use of such teams is also called concurrent engineering and implies a team representing all affected areas (known as a cross-functional team). Concurrent engineering also implies speedier product development through simultaneous performance of various aspects of product develop- ment.3 The team approach is the dominant structure for product development by leading organi- zations in North America.

MANUFACTURABILITY AND VALUE ENGINEERING Manufacturability and value engineering activities are concerned with improvement of design and specifications at the research, development, design, and production stages of product devel- opment. In addition to immediate, obvious cost reduction, design for manufacturability and value engineering may produce other benefits. These include:

1. Reduced complexity of the product. 2. Reduction of environmental impact. 3. Additional standardization of components. 4. Improvement of functional aspects of the product. 5. Improved job design and job safety. 6. Improved maintainability (serviceability) of the product. 7. Robust design.

Manufacturability and value engineering activities may be the best cost-avoidance technique available to operations management. They yield value improvement by focusing on achieving the functional specifications necessary to meet customer requirements in an optimal way. Value engineering programs, when effectively managed, typically reduce costs between 15% and 70% without reducing quality. Some studies have indicated that for every dollar spent on value engi- neering, $10 to $25 in savings can be realized.

Product design affects virtually all aspects of operating expense and sustainability. Consequently, the development process needs to ensure a thorough evaluation of design prior to a commitment to produce. The cost reduction achieved for a specific bracket via value engineer- ing is shown in Figure 5.5.

Product development teams Teams charged with moving from market requirements for a product to achieving product success.

Concurrent engineering Use of participating teams in design and engineering activities.

Manufacturability and value engineering Activities that help improve a product’s design, production, maintainability, and use.

3 Firms that have high technological or product change in their competitive environment tend to use more con- current engineering practices. See X. Koufteros, M. Vonderembse, and W. Doll, “Concurrent Engineering and Its Consequences,” Journal of Operations Management 19, no. 1 (January 2001): 97–115.

1 3

$3.50 $2.00

2

$0.80

FIGURE 5.5

Cost Reduction of a Bracket via Value Engineering

Each time the bracket is redesigned and simplified, we are able to produce it for less.

STUDENT TIP

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162 PART 2 Designing Operations

Issues for Product Design In addition to developing an effective system and organization structure for product development, several techniques are important to the design of a product. We will now review six of these: (1) robust design, (2) modular design, (3) computer-aided design (CAD) and computer-aided manufacturing (CAM), (4) virtual reality technology, (5) value analysis, and (6) sustainability/ life cycle assessment (LCA).

ROBUST DESIGN Robust design means that the product is designed so that small variations in production or assembly do not adversely affect the product. For instance, Lucent developed an integrated cir- cuit that could be used in many products to amplify voice signals. As originally designed, the circuit had to be manufactured very expensively to avoid variations in the strength of the signal. But after testing and analyzing the design, Lucent engineers realized that if the resistance of the circuit was reduced—a minor change with no associated costs—the circuit would be far less sensitive to manufacturing variations. The result was a 40% improvement in quality.

MODULAR DESIGN Products designed in easily segmented components are known as modular designs. Modular designs offer flexibility to both production and marketing. Operations managers find modular- ity helpful because it makes product development, production, and subsequent changes easier. Moreover, marketing may like modularity because it adds flexibility to the ways customers can be satisfied. For instance, virtually all premium high-fidelity sound systems are produced and sold this way. The customization provided by modularity allows customers to mix and match to their own taste. This is also the approach taken by Harley-Davidson, where relatively few different engines, chassis, gas tanks, and suspension systems are mixed to produce a huge variety of motorcycles. It has been estimated that many automobile manufacturers can, by mixing the available modules, never make two cars alike. This same concept of modularity is carried over to many industries, from airframe manufacturers to fast-food restaurants. Airbus uses the same wing modules on several planes, just as McDonald’s and Harvey’s use relatively few modules (cheese, lettuce, buns, sauces, pickles, meat patties, French fries, etc.) to make a variety of meals.

COMPUTER-AIDED DESIGN (CAD) Computer-aided design (CAD) is the use of computers to interactively design products and prepare engineering documentation. The use and variety of CAD software is extensive and is rapidly expanding. CAD software allows designers to use three-dimensional drawings to save time and money by shortening development cycles for virtually all products. The speed and ease with which sophisticated designs can be manipulated, analyzed, and modified with CAD makes the review of numerous options possible before final commitments are made. Faster develop- ment, better products, accurate flow of information to other departments—all contribute to a tremendous payoff for CAD. The payoff is particularly significant because most product costs are determined at the design stage.

One extension of CAD is design for manufacture and assembly (DFMA) software, which focuses on the effect of design on assembly. It allows designers to examine the integration of product designs before the product is manufactured. For instance, DFMA allows automobile designers to examine how a transmission will be placed in a car on the production line, even while both the transmission and the car are still in the design stage.

A second CAD extension is 3-D object modelling. The technology is particularly useful for small prototype development. 3-D object modelling rapidly builds up a model in very thin layers of synthetic materials for evaluation. This technology speeds development by avoid- ing a more lengthy and formal manufacturing process. 3-D printers, costing as little as $5000, are also now available. Shoemaker Timberland, Inc., uses this technology to allow footwear designers to see their constructions overnight rather than waiting a week for model-makers to carve them.

Robust design A design that can be produced to requirements even with unfavour- able conditions in the production process.

Modular designs Designs in which parts or compo- nents of a product are subdivided into modules that are easily interchanged or replaced.

Computer-aided design (CAD) Interactive use of a computer to develop and document a product.

Design for manufacture and assembly (DFMA) Software that allows designers to look at the effect of design on manufacturing of the product.

3-D object modelling An extension of CAD that builds small prototypes.

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Chapter 5 Design of Goods and Services 163

Some CAD systems have moved to the internet through ecommerce, where they link com- puterized design with purchasing, outsourcing, manufacturing, and long-term maintenance. This move supports rapid product change and the growing trend towards “mass customization”. With CAD on the internet, customers can enter a supplier’s design libraries and make design changes. The supplier’s software can then automatically generate the drawings, update the bill of material, and prepare instructions for the supplier’s production process. The result is customized products produced faster and at less expense.

As product life cycles shorten and design becomes more complex, collaboration among departments, facilities, and suppliers throughout the world becomes critical. The potential of such collaboration has proven so important that a standard for its exchange has been developed, known as the standard for the exchange of product data (STEP). STEP permits manufactur- ers to express 3-D product information in a standard format so it can be exchanged internation- ally, allowing geographically dispersed manufacturers to integrate design, manufacture, and support processes.4

COMPUTER-AIDED MANUFACTURING (CAM) Computer-aided manufacturing (CAM) refers to the use of specialized computer programs to direct and control manufacturing equipment. When computer-aided design (CAD) information is translated into instructions for computer-aided manufacturing (CAM), the result of these two technologies is CAD/CAM.

The benefits of CAD and CAM include:

1. Product quality: CAD permits the designer to investigate more alternatives, potential prob- lems, and dangers.

2. Shorter design time: A shorter design phase lowers cost and allows a more rapid response to the market.

3. Production cost reductions: Reduced inventory, more efficient use of personnel through improved scheduling, and faster implementation of design changes lower costs.

4. Database availability: Provides information for other manufacturing software and accurate product data so everyone is operating from the same information, resulting in dramatic cost reductions.

Standard for the exchange of product data (STEP) A standard that provides a format allowing the electronic transmittal of three-dimensional data.

Computer-aided manufacturing (CAM) The use of information technology to control machinery.

At the Next GEN Science Fair in 2011, visitors are intrigued by advances in 3-D printers and the ability to capture intricate details of objects onto paper.

4 The STEP format is documented in the European Community’s standard ISO 10303.

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164 PART 2 Designing Operations

5. New range of capabilities: For instance, the abilities to rotate and depict objects in three- dimensional form, to check clearances, to relate parts and attachments, and to improve the use of numerically controlled machine tools all provide new capability for manufacturing. CAD/CAM removes substantial detail work, allowing designers to concentrate on the con- ceptual and imaginative aspects of their task.

VIRTUAL REALITY TECHNOLOGY Virtual reality is a visual form of communication in which images substitute for the real thing but still allow the user to respond interactively. The roots of virtual reality technology in oper- ations are in computer-aided design. Once design information is in a CAD system, it is also in electronic digital form for other uses, such as developing 3-D layouts of everything from restau- rants to amusement parks. Changes to mechanical design, restaurant layouts, or amusement park rides are much less expensive at the design stage than later.

VALUE ANALYSIS Although value engineering focuses on preproduction design improvement, value analysis, a related technique, takes place during the production process, when it is clear that a new product is a success. Value analysis seeks improvements that lead to either a better product, or a prod- uct made more economically, or a product with less environmental impact. The techniques and advantages for value analysis are the same as for value engineering, although minor changes in implementation may be necessary because value analysis is taking place while the product is being produced.

SUSTAINABILITY AND LIFE CYCLE ASSESSMENT (LCA) Product design requires that managers evaluate product options. Addressing sustainability and life cycle assessment (LCA) are two ways of doing this. Sustainability means meeting the needs of the present without compromising the ability of future generations to meet their needs. An LCA is a formal evaluation of the environmental impact of a product. Both sustainability and LCA are discussed in depth in the supplement to this chapter.

Time-Based Competition As product life cycles shorten, the need for faster product development increases. Additionally, as technological sophistication of new products increases, so do the expense and risk. For instance, drug firms invest an average of 12 to 15 years and $1 billion before receiving regu- latory approval of each new drug. And even then, only one of five will actually be a success. Those operations managers who master this art of product development continually gain on slower product developers. To the swift goes the competitive advantage. This concept is called time-based competition.

Often, the first company into production may have its product adopted for use in a variety of applications that will generate sales for years. It may become the “standard”. Consequently, there is often more concern with getting the product to market than with optimum product design or process efficiency. Even so, rapid introduction to the market may be good manage- ment because, until competition begins to introduce copies or improved versions, the product can sometimes be priced high enough to justify somewhat inefficient production design and methods.

Because time-based competition is so important, instead of developing new products from scratch (which has been the focus thus far in this chapter) a number of other strategies can be used. Figure 5.6 shows a continuum that goes from new, internally developed products (on the lower left) to “alliances”. Enhancements and migrations use the organization’s existing product strengths for innovation and therefore are typically faster while at the same time being less risky than developing entirely new products. Enhancements may be changes in colour, size, weight, or features, such as are taking place with cell phones (see OM in Action box “Chasing Fads in the Cell Phone Industry”), or even changes in commercial aircraft. Boeing’s enhancements of the 737 since its introduction in 1967 have made the 737 the largest- selling commercial aircraft in history. Boeing also uses its engineering prowess in air frames

Virtual reality A visual form of communication in which images substitute for reality and typically allow the user to respond interactively.

Value analysis A review of successful products that takes place during the production process.

Time-based competition Competition based on time, rapidly developing products and moving them to market.

LO4 Describe how time-based competition is

implemented by OM

Fast communication, rapid technological change, and short product life cycles push product development.

STUDENT TIP

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Chapter 5 Design of Goods and Services 165

Internal Lengthy High

Shared Rapid and/or Existing

Shared

External development strategies

Product Development Continuum

Internal development strategies Migrations of existing products

Enhancements to existing products New internally developed products

Alliances Joint ventures

Purchase technology or expertise by acquiring the developer

Cost of product development Speed of product development Risk of product development

FIGURE 5.6

Product Development Continuum

Managers seek a variety of approaches to obtain speed to market. The president of one U.S. firm says: “If I miss one product cycle, I’m dead.”

STUDENT TIP

to migrate from one model to the next. This allows Boeing to speed development while reduc- ing both cost and risk for new designs. This approach is also referred to as building on prod- uct platforms. Black & Decker has used its “platform” expertise in hand-powered tools to build a leading position in that market. Similarly, Hewlett-Packard has done the same in the printer business. Enhancements and migrations are a way of building on existing expertise and extending a product’s life cycle.

The product development strategies on the lower left of Figure 5.6 are internal development strategies, while the three approaches we now introduce can be thought of as external devel- opment strategies. Firms use both. The external strategies are (1) purchase the technology, (2) establish joint ventures, and (3) develop alliances.

In the shrinking world marketplace, innovations that appeal to customers in one region rapidly become glob- al trends. The process shakes up the structure of one industry after another, from computers to automobiles to consumer electronics.

Nowhere has this impact been greater in recent years than in the cell phone industry. The industry sells about 1.3 billion phones each year, but product life cycle is short. Competition is intense. Higher margins go to the innova- tor—and manufacturers that jump on an emerging trend early can reap substantial rewards. The swiftest Chinese manufacturers, such as Ningbo Bird and TCL, now replace some phone models after just six months. In the past, Motorola, Nokia, and other industry veterans enjoyed what are now considered long life cycles—two years. New styles and technological advances in cell phones constantly appear somewhere in the world. Wired, well-travelled consumers seek the latest innovation; local retailers rush to offer it; and telecommunication providers order it.

Contemporary cell phones may be a curvy, boxy, or clamshell fashion item; have a tiny keyboard for quick and

easy typing or a more limited number pad for a phone; have a built-in radio or a digital music player; have a camera, internet access, or TV clips; function on cellular or wireless (Wi-Fi) networks; or have games or personal organizers. Mattel and Nokia even have Barbie phones for preteen girls, complete with prepaid minutes, customized ringtones, and faceplates. The rapid changes in features and demand are forcing manufacturers into a frenzied race to keep up or simply to pull out.

“We got out of the handset business because we couldn’t keep up with the cycle times,” says Jeffrey Belk, Marketing VP for Qualcomm Inc., the San Diego company that now focuses on making handset chips.

Developing new products is always a challenge, but in the dynamic global marketplace of cell phones, product development takes on new technology and new markets at breakneck speed.

Sources: Supply Chain Management Review (October 2007): 28; The Wall Street Journal (October 30, 2003): A1 and (September 8, 2004): D5; and International Business Times (March 3, 2009).

Chasing Fads in the Cell Phone IndustryOM in Action

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166 PART 2 Designing Operations

PURCHASING TECHNOLOGY BY ACQUIRING A FIRM Microsoft and Cisco Systems are examples of companies on the cutting edge of technology that often speed development by acquiring entrepreneurial firms that have already developed the technology that fits their mission. The issue then becomes fitting the purchased organization, its technology, its product lines, and its culture into the buying firm, rather than an issue of product development.

JOINT VENTURES Joint ventures are combined ownership, usually between just two firms, to form a new entity. Ownership can be 50–50, or one owner can assume a larger portion to ensure tighter control. Joint ventures are often appropriate for exploiting specific product opportunities that may not be central to the firm’s mission. Such ventures are more likely to work when the risks are known and can be equitably shared.

ALLIANCES Alliances are cooperative agreements that allow firms to remain independent but use comple- menting strengths to pursue strategies consistent with their individual missions. When new products are central to the mission, but substantial resources are required and sizable risk is pres- ent, then alliances may be a good strategy for product development. Alliances are particularly beneficial when the products to be developed also have technologies that are in ferment. For example, Microsoft is pursuing a number of alliances with a variety of companies to deal with the convergence of computing, the internet, and television broadcasting. Alliances in this case are appropriate because the technological unknowns, capital demands, and risks are significant. Similarly, three firms—Mercedes Benz, Ford Motor, and Ballard Power Systems—have formed an alliance to develop “green” cars powered by fuel cells. However, alliances are much more difficult to achieve and maintain than are joint ventures because of the ambiguities associated with them. It may be helpful to think of an alliance as an incomplete contract between the firms. The firms remain separate.

Enhancements, migration, acquisitions, joint ventures, and alliances are all strategies for speeding product development. Moreover, they typically reduce the risk associated with product development while enhancing the human and capital resources available.

Defining a Product Once new goods or services are selected for introduction, they must be defined. First, a good or service is defined in terms of its functions—that is, what the product is to do. The product is then designed, and the firm determines how the functions are to be achieved. Management typically has a variety of options as to how a product should achieve its functional purpose. For instance, when an alarm clock is produced, aspects of design such as the colour, size, or loca- tion of buttons may make substantial differences in ease of manufacture, quality, and market acceptance.

Rigorous specifications of a product are necessary to assure efficient production. Equipment, layout, and human resources cannot be determined until the product is defined, designed, and documented. Therefore, every organization needs documents to define its products. This is true of everything from meat patties, to cheese, to computers, to medical procedures. In the case of cheese, a written specification is typical. Indeed, written specifications or standard grades exist and provide the definition for many products. For instance, Cheddar cheese has a written description that specifies the characteristics necessary for each Department of Justice grade. A portion of the Department of Justice grade requirements for Cheddar cheese is shown in Figure 5.7. Similarly, McDonald’s has 60 specifications for potatoes that are to be made into French fries.

Most manufactured items as well as their components are defined by a drawing, usually referred to as an engineering drawing. An engineering drawing shows the dimensions, toler- ances, materials, and finishes of a component. The engineering drawing will be an item on a

Joint ventures Firms establishing joint ownership to pursue new products or markets.

Alliances Cooperative agreements that allow firms to remain independ- ent, but cooperatively pursue strategies consistent with their individual missions.

Engineering drawing A drawing that shows the dimen- sions, tolerances, materials, and finishes of a component.

LO5 Describe how products and services are defined by

OM

Before anything can be produced, a product’s functions and attributes must be defined.

STUDENT TIP

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Chapter 5 Design of Goods and Services 167

bill of material. An engineering drawing is shown in Figure 5.8. The bill of material (BOM) lists the components, their description, and the quantity of each required to make one  unit of a product. A bill of material for a manufactured item is shown in Figure 5.9(a). Note that subassemblies and components (lower-level items) are indented at each level to indicate their subordinate position. An engineering drawing shows how to make one item on the bill of material.

In the food-service industry, bills of material manifest themselves in portion-control stand- ards. The portion-control standard for Hard Rock Cafe’s hickory BBQ bacon cheeseburger is shown in Figure 5.9(b). In a more complex product, a bill of material is referenced on other bills of material of which they are a part. In this manner, subunits (subassemblies) are part of the next higher unit (their parent bill of material) that ultimately makes a final product. In addition to being defined by written specifications, portion-control documents, or bills of material, products can be defined in other ways. For example, products such as chemicals, paints, and petroleum may be defined by formulas or proportions that describe how they are to be made. Movies are defined by scripts, and insurance coverage by legal documents known as policies.

MAKE-OR-BUY DECISIONS For many components of products, firms have the option of producing the components them- selves or purchasing them from outside sources. Choosing between these options is known as the make-or-buy decision. The make-or-buy decision distinguishes between what the firm wants to produce and what it wants to purchase. Because of variations in quality, cost, and delivery schedules, the make-or-buy decision is critical to product definition. Many items can be pur- chased as a “standard item” produced by someone else. Examples are the standard bolts listed on the bill of material shown in Figure 5.9(a), for which there will be SAE (Society of Automotive Engineers) specifications. Therefore, there typically is no need for the firm to duplicate this specification in another document.

Bill of material (BOM) A list of the components, their description, and the quantity of each required to make one unit of a product.

Make-or-buy decision The choice between producing a component or a service and purchasing it from an outside source.

Grade Requirements for Cheddar Cheese

13. (1) Cheddar cheese may be graded Canada 1 if the cheese meets the requirements of section 4 and subsection 6(3), and (a) its flavour and aroma are typical and desirable; (b) its body is reasonably compact and firm; (c) its texture is smooth; (d) its surface is clean, smooth and unbroken; (e) except in the case of marbled cheddar cheese, its colour is uniform and characteristic

of cheddar cheese; and (f) the cheese is uniform in size and regular in shape.

FIGURE 5.7

Grade Requirements for Cheddar Cheese

Source: www.justice.gc.ca (2) and (3) [Repealed, SOR/98-216, s. 7] SOR/88- 195, s. 1; SOR/98-216, s. 7.

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Engineering Drawings Such as This One Show Dimensions, Tolerances, Materials, and Finishes

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168 PART 2 Designing Operations

GROUP TECHNOLOGY Engineering drawings may also include codes to facilitate group technology. Group technology requires that components be identified by a coding scheme that specifies the type of processing (such as drilling) and the parameters of the processing (such as size). This facilitates standardi- zation of materials, components, and processes as well as the identification of families of parts. As families of parts are identified, activities and machines can be grouped to minimize setups, routings, and material handling. An example of how families of parts may be grouped is shown in Figure 5.10. Group technology provides a systematic way to review a family of components to see if an existing component might suffice on a new project. Using existing or standard compo- nents eliminates all the costs connected with the design and development of the new part, which is a major cost reduction. For these reasons, successful implementation of group technology leads to the following advantages:

1. Improved design (because more design time can be devoted to fewer components). 2. Reduced raw material and purchases. 3. Simplified production planning and control. 4. Improved layout, routing, and machine loading. 5. Reduced tooling setup time, and work-in-process and production time.

The application of group technology helps the entire organization, as many costs are reduced.

Group technology A product and component coding system that specifies the type of processing and the parameters of the processing; it allows similar products to be grouped.

(a) Ungrouped Parts (b) Grouped Cylindrical Parts (families of parts)

Grooved Slotted Threaded Drilled Machined

FIGURE 5.10

A Variety of Group Technology Coding Schemes Move Man- ufactured Components from (a) Ungrouped to (b) Grouped (families of parts)

Bill of Material for a Panel Weldment

A 60–7 R 60–17 R 60–428 P 60–2

A 60–72 R 60–57–1 A 60–4 02–50–1150

A 60–73 A 60–74 R 60–99 02–50–1150

LOWER ROLLER ASSM. ROLLER PIN LOCKNUT

GUIDE ASSM. REAR SUPPORT ANGLE ROLLER ASSEM. BOLT

GUIDE ASSM. FRONT SUPPORT WELDM’T WEAR PLATE BOLT

1 1 1 1

1 1 1 1

1 1 1 1

(a) Hard Rock Cafe’s Hickory BBQ Bacon Cheeseburger

Bun Hamburger patty Cheddar cheese Bacon BBQ onions Hickory BBQ sauce Burger set Lettuce Tomato Red onion Pickle French fries Seasoned salt 11-inch plate HRC flag

1 8 oz. 2 slices 2 strips 1/2 cup 1 oz.

1 leaf 1 slice 4 rings 1 slice 5 oz. 1 tsp. 1 1

(b)

PANEL WELDM’T 1A 60–71

NUMBER DESCRIPTION QTY DESCRIPTION QTY

FIGURE 5.9

Bills of Material Take Differ- ent Forms in (a) Manufactur- ing Plant and (b) Restaurant, but in Both Cases, the Product Must Be Defined

Hard Rock’s recipe here serves the same purpose as a bill of material in a factory: It defines the product for production.

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Chapter 5 Design of Goods and Services 169

Documents for Production Once a product is selected, designed, and ready for production, production is assisted by a vari- ety of documents. We will briefly review some of these.

An assembly drawing simply shows an exploded view of the product. An assembly drawing is usually a three-dimensional drawing, known as an isometric drawing; the relative locations of components are drawn in relation to each other to show how to assemble the unit (see Figure 5.11(a)).

The assembly chart shows in schematic form how a product is assembled. Manufactured components, purchased components, or a combination of both may be shown on an assembly chart. The assembly chart identifies the point of production at which components flow into sub- assemblies and ultimately into a final product. An example of an assembly chart is shown in Figure 5.11(b).

The route sheet lists the operations necessary to produce the component with the material specified in the bill of material. The route sheet for an item will have one entry for each operation to be performed on the item. When route sheets include specific methods of operation and labour standards, they are often known as process sheets.

The work order is an instruction to make a given quantity of a particular item, usually to a given schedule. The order ticket that a waiter in your favourite restaurant writes down is a work order. In a hospital or factory, the work order is a more formal document that provides authoriza- tion to draw various pharmaceuticals or items from inventory, to perform various functions, and to assign personnel to perform those functions.

An engineering change notice (ECN) changes some aspect of the product’s definition or documentation, such as an engineering drawing or a bill of material. For a complex product that has a long manufacturing cycle, such as a Boeing 777, the changes may be so numerous that no two 777s are built exactly alike—which is indeed the case. Such dynamic design change has fos- tered the development of a discipline known as configuration management, which is concerned with product identification, control, and documentation. Configuration management is the sys- tem by which a product’s planned and changing configurations are accurately identified and for which control and accountability of change are maintained.

PRODUCT LIFE CYCLE MANAGEMENT (PLM) Product life cycle management (PLM) is an umbrella of software programs that attempts to bring together phases of product design and manufacture—including tying together many of the techniques discussed in the prior two sections, Defining a Product and Documents for Production. The idea behind PLM software is that product design and manufacture decisions can be performed more creatively, faster, and more economically when the data are integrated and consistent.

LO6 Describe the documents needed for production

Assembly drawing An exploded view of the product.

Assembly chart A graphic means of identifying how components flow into subas- semblies and final products.

Route sheet A listing of the operations neces- sary to produce a component with the material specified in the bill of material.

Work order An instruction to make a given quantity of a particular item.

Configuration management A system by which a product’s planned and changing compo- nents are accurately identified.

Engineering change notice (ECN) A correction or modification of an engineering drawing or bill of material.

Product life cycle management (PLM) Software programs that tie together many phases of product design and manufacture.

R 209 Angle

R 207 Angle

Bolts w/nuts (2)

Left bracket

assembly

R 209 Angle

R 207 Angle

Bolts w/nuts (2)

Right bracket

assembly

Bolt w/nut

Part number tag

R 404 Roller

Lock washer

Box w/packing material

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A1

A2

A3

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R 207

31/2"* 3/8" Hex head bolt

3/8" Hex nut

R 404

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R 207

3/8" Lock washer

3/8" Hex nut

(a) Assembly Drawing

1

2

3

4

5

6

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8

9

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SA 2

SA 1

FIGURE 5.11

Assembly Drawing and Assembly Chart

Production personnel need clear, specific documents to help them make the product.

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170 PART 2 Designing Operations

Although there is not one standard, PLM products often start with product design (CAD/ CAM); move on to design for manufacture and assembly (DFMA); and then into product rout- ing, materials, layout, assembly, maintenance, and even environmental issues.5 Integration of these tasks makes sense because many of these decisions areas require overlapping pieces of data. PLM software is now a tool of many large organizations, including Bombardier, Lockheed Martin, GE, Procter & Gamble, Toyota, and Boeing. Boeing estimates that PLM will cut final assembly of its 787 jet from two weeks to three days. PLM is now finding its way into medium and small manufacture as well.

Shorter life cycles, more technologically challenging products, more regulations about materials and manufacturing processes, and more environmental issues all make PLM an appealing tool for operations managers.

Service Design Much of our discussion so far has focused on what we can call tangible products—that is, goods. On the other side of the product coin are, of course, services. Service industries include banking, finance, insurance, transportation, and communications. The products offered by service firms range from a medical procedure that leaves only the tiniest scar after an appendectomy, to a shampoo and cut at a hair salon, to a great sandwich. Designing services is challenging because they have a unique characteristic—customer interaction.

PROCESS–CHAIN–NETWORK (PCN) ANALYSIS Process–chain–network (PCN) analysis, developed by Professor Scott Sampson, focuses on the ways in which processes can be designed to optimize interaction between firms and their cus- tomers.6 A process chain is a sequence of steps that accomplishes an activity, such as building a home, completing a tax return, or preparing a sandwich. A process participant can be a manufac- turer, a service provider, or a customer. A network is a set of participants.

5 Some PLM vendors include supply chain elements such as sourcing, material management, and vendor evaluation in their packages, but in most instances, these are considered part of the ERP systems discussed along with MRP in Chapter 14. See, for instance, SAP PLM (www.mySAP.com), Parametric Technology Corp. (www.ptc.com), UGS Corp. (www.ugs.com), and Proplanner (www.proplanner.com).

LO7 Explain how the customer participates in the design and delivery of

services

Process–chain–network (PCN) analysis Analysis that focuses on the ways in which processes can be designed to optimize interac- tion between firms and their customers.

Process chain A sequence of steps that accom- plishes an identifiable purpose (of providing value to process participants).

6 See Scott Sampson, “Visualizing Service Operations,” Journal of Service Research (May 2012). More details about PCN analysis are available at services.byu.edu.

Each year, the J.R. Simplot Company potato processing facilities in North America, Australia, China, and New Zealand produce billions of pounds of French fries and formed potato products for quick-service restaurants and other foodservice customers around the world (left photo). Sixty specifications (including a special blend of frying oil, a unique steaming process, and exact time and temperature for prefrying and drying) define how these potatoes become French fries. Further, 40% of all French fries must be 2 to 3 inches long, 40% must be over 3 inches long, and a few shorter ones constitute the final 20%. Quality control personnel use a micrometer to measure the fries (right photo).

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Chapter 5 Design of Goods and Services 171

Each participant has a process domain that includes the set of activities over which it has con- trol. The domain and interactions between two participants for sandwich preparation are shown in the PCN diagram (Figure 5.12). The activities are organized into three process regions for each participant:

1. The direct interaction region includes process steps that involve interaction between partici- pants. For example, a sandwich buyer directly interacts with employees of a sandwich store (e.g., Subway, in the middle of Figure 5.12).

2. The surrogate (substitute) interaction region includes process steps in which one participant is acting on another participant’s resources, such as their information, materials, or technologies. This occurs when the sandwich supplier is making sandwiches in the restaurant kitchen (left side of Figure 5.12) or, alternatively, when the customer has access to buffet ingredients and assembles the sandwich himself (right side of the figure). Under surrogate interaction, direct interaction is limited.

3. The independent processing region includes steps in which the sandwich supplier and/or the sandwich customer is acting on resources where each has maximum control. Most make-to- stock production fits in this region (left side of Figure 5.12; think of the firm that assembles all those prepackaged sandwiches available in vending machines and convenience stores). Similarly, those sandwiches built at home occur to the right, in the customer’s independent processing domain.

All three process regions have similar operating issues—quality control, facility location and layout, job design, inventory, and so on—but the appropriate way of handling the issues differs across regions. Service operations exist only within the area of direct and surrogate interaction.

From the operations manager’s perspective, the valuable aspect of PCN analysis is insight to aid in positioning and designing processes that can achieve strategic objectives. A firm’s operations are strategic in that they can define what type of business the firm is in and what value proposition it desires to provide to customers. For example, a firm may assume a low-cost strategy, operating on the left of Figure 5.12 as a manufacturer of premade sandwiches. Other firms (e.g., Subway) adopt a differentiation strategy with high customer interaction. Each of the process regions depicts a unique operational strategy.

Firms wanting to achieve high economies of scale or more control in their operations should probably position towards the independent processing region of their process domain. Firms intending to provide a value offering that focuses on customization should be positioned more

Sandwich supplier Assemble sandwich

Supplier’s process domain

Prepare sandwiches at factory for resale at convenience stores

Make sandwich in restau- rant kitchen from menu offerings with modest modifications

Assemble custom sandwich at Subway as customer orders

Customer assembles sandwich from buffet offerings

Assemble sandwich at home using ingredients from refrigerator

Independent processing

Independent processing

Surrogate interaction

Surrogate interaction

Direct interaction

Direct interaction

Sandwich consumer

Consumer’s process domain

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172 PART 2 Designing Operations

towards the consumer’s process domain. PCN analysis can be applied in a wide variety of busi- ness settings.

ADDING SERVICE EFFICIENCY Service productivity is notoriously low, in part because of customer involvement in the design or delivery of the service, or both. This complicates the product design challenge. We will now discuss a number of ways to increase service efficiency and, among these, several ways to limit this interaction.

LIMIT THE OPTIONS Because customers may participate in the design of the service (e.g., for a funeral or a hairstyle), design specifications may take the form of everything from a menu (in a restaurant), to a list of options (for a funeral), to a verbal description (a hairstyle). However, by providing a list of options (in the case of the funeral) or a series of photographs (in the case of the hairstyle), ambiguity may be reduced. An early resolution of the product’s definition can aid efficiency as well as aid in meeting customer expectations.

DELAY CUSTOMIZATION Design the product so that customization is delayed as late in the pro- cess as possible. This is the way a hair salon operates. Although shampoo and condition are done in a standard way with lower-cost labour, the colour and styling (customizing) are done last. It is also the way most restaurants operate: How would you like your meal cooked? Which dressing would you prefer with your salad?

MODULARIZATION Modularize the service so that customization takes the form of changing modules. This strategy allows for “custom” services to be designed as standard modular entities. Just as modular design allows you to buy a high-fidelity sound system with just the features you want, modular flexibility also lets you buy meals, clothes, and insurance on a mix-and-match (modular) basis. Investments (portfolios of stocks and bonds) and education (university and college curricula) are examples of how the modular approach can be used to customize a service.

AUTOMATION Divide the service into small parts and identify those parts that lend themselves to automation. For instance, by isolating cheque-cashing activity via ATM, banks have been very effective at designing a product that both increases customer service and reduces costs. Similarly, airlines have moved to ticketless service via kiosks. A technique such as kiosks reduces both costs and lines at airports—thereby increasing customer satisfaction—and providing a win–win “product” design.

MOMENT OF TRUTH High customer interaction means that in the service industry there is a moment of truth when the relationship between the provider and the customer is crucial. At that moment, the customer’s satisfaction with the service is defined. The moment of truth is the moment that exemplifies, enhances, or detracts from the customer’s expectations. That moment may be as simple as a smile from a Starbucks barista or having the checkout clerk focus on you rather than talking over his shoulder to the clerk at the next counter. Moments of truth can occur when you order at McDonald’s, get a haircut, or register for college courses. The operations manager’s task is to identify moments of truth and design operations that meet or exceed the customer’s expectations.

DOCUMENTS FOR SERVICES Because of the high customer interaction of most services, the documents for moving the product to production are different from those used in goods-producing operations. The documentation for a service will often take the form of explicit job instructions that specify what is to happen at the moment of truth. For instance, regardless of how good a pharmacy’s products may be in terms of variety, access to brand names and generic equivalents, and so forth, if the moment of truth is not done well, the product may be poorly received. Example 2 shows the kind of documentation a pharmacy may use to move a product (drive-up pharmacy)

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Chapter 5 Design of Goods and Services 173

to “production”. In a telemarketing service, the product design is communicated to produc- tion personnel in the form of a telephone script, while a storyboard is used for movie and TV production.

2 Nova Scotia Pharmaceuticals wants to ensure effective delivery of service to its drive-up customers.

APPROACH c  Develop a “production” document for the pharmacists at the drive-up window that provides the information necessary to do an effective job.

SOLUTION c  

EXAMPLE

Service Documentation for Production

Documentation for Pharmacists at Drive-Up Windows

Customers who use the drive-up windows rather than walk up to the counter require a different customer relations technique. The distance and machinery between the pharmacist and the customer raises communication barriers. Guidelines to ensure good customer relations at the drive-up win- dow are:

• Be especially discreet when talking to the customer through the microphone. • Provide written instructions for customers who must fill out forms you provide. • Mark lines to be completed or attach a note with instructions. • Always say “please” and “thank you” when speaking through the microphone. • Establish eye contact with the customer if the distance allows it. • If a transaction requires that the customer park the car and walk up to the counter, apologize

for the inconvenience.

INSIGHT c  By providing documentation in the form of a script/guideline for pharmacists, the likeli- hood of effective communication and a good product/service is improved.

LEARNING EXERCISE: c  Modify the guidelines above to show how they would be different for a drive-through restaurant. [Answer: Written instructions, marking lines to be completed, or coming into the store are seldom necessary, but techniques for making change and proper transfer of the order should be included.]

RELATED PROBLEM: c  5.7

Application of Decision Trees to Product Design Decision trees can be used for new product decisions as well as for a wide variety of other man- agement problems. They are particularly helpful when there are a series of decisions and various outcomes that lead to subsequent decisions followed by other outcomes. To form a decision tree, we use the following procedure:

1. Be sure that all possible alternatives and states of nature are included in the tree. This includes an alternative of “doing nothing”.

2. Payoffs are entered at the end of the appropriate branch. This is the place to develop the payoff of achieving this branch.

3. The objective is to determine the expected value of each course of action. We accomplish this by starting at the end of the tree (the right-hand side) and working towards the begin- ning of the tree (the left), calculating values at each step and “pruning” alternatives that are not as good as others from the same node.

Example 3 shows the use of a decision tree applied to product design.

LO8 Apply decision trees to product issues

A decision tree is a great tool for thinking through a problem.

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174 PART 2 Designing Operations

Silicon, Inc., a semiconductor manufacturer, is investigating the possibility of producing and mar- keting a microprocessor. Undertaking this project will require either purchasing a sophisticated CAD system or hiring and training several additional engineers. The market for the product could be either favourable or unfavourable. Silicon, Inc., of course, has the option of not developing the new product at all.

With favourable acceptance by the market, sales would be 25 000 processors selling for $100 each. With unfavourable acceptance, sales would be only 8000 processors selling for $100 each. The cost of CAD equipment is $500 000, but that of hiring and training three new engineers is only $375 000. However, manufacturing costs should drop from $50 each when manufacturing without CAD, to $40 each when manufacturing with CAD.

The probability of favourable acceptance of the new microprocessor is 0.40; the probability of unfa- vourable acceptance is 0.60.

APPROACH c Use of a decision tree seems appropriate as Silicon, Inc., has the basic ingredients: a choice of decisions, probabilities, and payoffs.

SOLUTION c In Figure 5.13, we draw a decision tree with a branch for each of the three decisions, assign the respective probabilities payoff for each branch, and then compute the respective expected monetary values (EMVs). The EMVs have been circled at each step of the decision tree. For the top branch:

EMV (purchase CAD system) 5 (0.4)($1 000 000) 1 (0.6)(2$20 000)

5 $388 000

This figure represents the results that will occur if Silicon, Inc., purchases CAD. The expected value of hiring and training engineers is the second series of branches:

EXAMPLE 3

Decision Tree Applied to Product Design

$2 500 000 –1 000 000 – 500 000 ––––––––– $1 000 000

Revenue Mfg. cost ($40 * 25 000) CAD cost Net

(0.4)

High sales

$800 000 –320 000 –500 000 ––––––– –$20 000

Revenue Mfg. cost ($40 * 8 000) CAD cost Net loss

(0.6)

Low sales

$2 500 000 –1 250 000 – 375 000 –––––––––

$875 000

Revenue Mfg. cost ($50 * 25 000) Hire and train cost Net

(0.4)

High sales

$800 000 –400 000 –375 000 ––––––– $25 000

Revenue Mfg. cost ($50 * 8 000) Hire and train cost Net

(0.6)

Low sales

$0 Net

Do nothing $0

Hire and train engineers $365 000

Purchase CAD $388 000

FIGURE 5.13

Decision Tree for Develop- ment of a New Product

The manager’s options are to purchase CAD, hire/train engineers, or do nothing. Purchasing CAD has the highest expected monetary value (EMV).

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Chapter 5 Design of Goods and Services 175

Transition to Production Eventually, a product, whether a good or service, has been selected, designed, and defined. It has progressed from an idea to a functional definition, and then perhaps to a design. Now, management must make a decision as to further development and production or termi- nation of the product idea. One of the arts of modern management is knowing when to move a product from development to production; this move is known as transition to production. The product development staff is always interested in making improvements in a product. Because this staff tends to see product development as evolutionary, they may never have a completed product, but as we noted earlier, the cost of late product introduction is high. Although these conflicting pressures exist, management must make a decision—more devel- opment or production.

Once this decision is made, there is usually a period of trial production to ensure that the design is indeed producible. This is the manufacturability test. This trial also gives the opera- tions staff the opportunity to develop proper tooling, quality control procedures, and training of personnel to ensure that production can be initiated successfully. Finally, when the product is deemed both marketable and producible, line management will assume responsibility.

Some companies appoint a project manager; others use product development teams to ensure that the transition from development to production is successful. Both approaches allow a wide range of resources and talents to be brought to bear to ensure satisfactory production of a product that is still in flux. A third approach is integration of the product development and manufactur- ing organizations. This approach allows for easy shifting of resources between the two organ- izations as needs change. The operations manager’s job is to make the transition from R&D to production seamless.

EMV(Hire/train engineers) 5 (0.4)($875 000) 1 (0.6)($25 000)

5 $365 000

The EMV of doing nothing is $0. Because the top branch has the highest expected monetary value (an EMV of $388 000 versus

$365 000 versus $0), it represents the best decision. Management should purchase the CAD system.

INSIGHT c Use of the decision tree provides both objectivity and structure to our analysis of the Silicon, Inc., decision.

LEARNING EXERCISE c If Silicon, Inc., thinks the probabilities of high sales and low sales may be equal, at 0.5 each, what is the best decision? [Answer: Purchase CAD remains the best decision, but with an EMV of $490 000.]

RELATED PROBLEMS c 5.10, 5.11, 5.12, 5.13, 5.14, 5.15, 5.16, 5.18

ACTIVE MODEL 5.1 This example is further illustrated in Active Model 5.1 at MyLab Operations Management.

One of the arts of management is knowing when a product should move from development to production.

STUDENT TIP

Effective product strategy requires selecting, designing, and defining a product and then transitioning that product to pro- duction. Only when this strategy is carried out effectively can the production function contribute its maximum to the organ- ization. The operations manager must build a product devel- opment system that has the ability to conceive, design, and produce products that will yield a competitive advantage for the firm. As products move through their life cycle (introduc- tion, growth, maturity, and decline), the options that the oper- ations manager should pursue change. Both manufactured

and service products have a variety of techniques available to aid in performing this activity efficiently.

Written specifications, bills of material, and engineer- ing drawings aid in defining products. Similarly, assembly drawings, assembly charts, route sheets, and work orders are often used to assist in the actual production of the product. Once a product is in production, value analysis is appropri- ate to ensure maximum product value. Engineering change notices and configuration management provide product documentation.

CHAPTER SUMMARY

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176 PART 2 Designing Operations

Madhu Ranadive, president of Davisville Toy Company, Inc., in Stratford, Ontario, has just reviewed the design of a new pull-toy locomotive for one- to three-year-olds. Madhu’s design and mar- keting staff are very enthusiastic about the market for the product and the potential of follow-on circus train cars. The sales manager is looking forward to a very good reception at the annual toy show in Toronto next month. Madhu is delighted as well, since she is faced with a layoff if orders do not improve.

Madhu’s production people have worked out the manufacturing issues and produced a successful pilot run. However, the quality testing staff suggests that under certain conditions, a hook to attach cars to the locomotive and the crank for the bell can be broken off. This is an issue because children can choke on small parts such as these. In the quality test, one- to three-year-olds were unable to break off these parts; there were no failures. But when the test sim- ulated the force of an adult tossing the locomotive into a toy box or a five-year-old throwing it on the floor, there were failures. The estimate is that one of the two parts can be broken off four times out of 100 000 throws. Neither the design nor the material people

knows how to make the toy safer and still perform as designed. The failure rate is low and certainly normal for this type of toy, but not at the Six Sigma level that Madhu’s firm strives for. And, of course, someone, someday may sue. A child choking on the broken part is a serious matter.

The design of successful, ethically produced, new products, as suggested in this chapter, is a complex task. What should Madhu do?

ETHICAL DILEMMA

Discussion Questions

1. Why is it necessary to document a product explicitly? 2. What techniques do we use to define a product? 3. In what ways are product strategies linked to product decisions? 4. Once a product is defined, what documents are used to assist

production personnel in its manufacture? 5. What is time-based competition? 6. Describe the differences between joint ventures and alliances. 7. Describe four organizational approaches to product develop-

ment. Which of these is generally thought to be best? 8. Explain what is meant by robust design. 9. What are three specific ways in which computer-aided design

(CAD) benefits the design engineer? 10. What information is contained in a bill of material? 11. What information is contained in an engineering drawing?

12. What information is contained in an assembly chart? In a pro- cess sheet?

13. Explain what is meant in service design by the “moment of truth”.

14. Explain how the house of quality translates customer desires into product/service attributes.

15. What is meant by sustainability in the context of operations management?

16. What strategic advantages does computer-aided design provide?

17. What is a process chain? 18. Why are the direct interaction and surrogate interaction regions

in a PCN diagram important in service design? 19. Why are documents for service useful? Provide examples of

four types.

Solved Problem Virtual Office Hours help is available at MyLab Operations Management.

. SOLVED PROBLEM 5.1 Sarah King, president of King Electronics, Inc., has two design options for her new line of high-resolution cathode-ray tubes (CRTs) for CAD workstations. The life cycle sales forecast for the CRT is 100 000 units.

Design option A has a 0.90 probability of yielding 59 good CRTs per 100 and a 0.10 probability of yielding 64 good CRTs per 100. This design will cost $1 000 000.

Design option B has a 0.80 probability of yielding 64 good units per 100 and a 0.20 probability of yielding 59 good units per 100. This design will cost $1 350 000.

Good or bad, each CRT will cost $75. Each good CRT will sell for $150. Bad CRTs are destroyed and have no salvage value. We ignore any disposal costs in this problem.

. SOLUTION We draw the decision tree to reflect the two decisions and the probabilities associated with each decision. We then determine the payoff associated with each branch. The resulting tree is shown in Figure 5.14.

For design A:

EMV(design A) 5 (0.9)($350 000) 1 (0.1)($1 100 000) 5 $425 000

For design B:

EMV(design B) 5 (0.8)($750 000) 1 (0.2)($0)

5 $600 000 The highest payoff is design option B, at $600 000.

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Chapter 5 Design of Goods and Services 177

Problems* • • 5.1 Construct a house of quality matrix for a wristwatch. Be sure to indicate specific customer wants that you think the general public desires. Then complete the matrix to show how an operations manager might identify specific attributes that can be measured and controlled to meet those customer desires.

• • 5.2 Using the house of quality, pick a real product (a good or service) and analyze how an existing organization satisfies cus- tomer requirements.

• • 5.3 Prepare a house of quality for a mousetrap.

• • 5.4 Conduct an interview with a prospective purchaser of a new bicycle and translate the customer’s wants into the specific hows of the firm.

• • 5.5 Prepare a bill of material for (a) a pair of eyeglasses and its case or (b) a fast-food sandwich (visit a local sandwich shop like Subway, McDonald’s, Mr. Submarine, Quiznos; perhaps a clerk or the manager will provide you with details on the quantity or weight of various ingredients—otherwise, estimate the quantities).

• • 5.6 Draw an assembly chart for a pair of eyeglasses and its case.

• • 5.7 Prepare a script for telephone callers at the university’s annual “phone-a-thon” fund-raiser.

• • 5.8 Prepare an assembly chart for a table lamp.

• • 5.9 Prepare a product-by-value analysis for the following products, and given the position in its life cycle, identify the issues likely to confront the operations manager, and his or her possible actions. Product Alpha has annual sales of 1000 units and a contri- bution of $2500; it is in the introductory stage. Product Bravo has annual sales of 1500 units and a contribution of $3000; it is in the growth stage. Product Charlie has annual sales of 3500 units and a contribution of $1750; it is in the decline stage.

• • 5.10 Given the contribution made on each of the three prod- ucts in the following table and their position in the life cycle, iden- tify a reasonable operations strategy for each:

Product

Product Contribution

(% of selling price)

Company Contribution

(%: total annual contribution

divided by total annual sales)

Position in Life Cycle

Kindle 2 30 40 Growth

Netbook computer

30 50 Introduction

Hand calculator

50 10 Decline *Note: PX means the problem may be solved with POM for windows and/or Excel OM.

EMV = $425 000 (0.9)

(0.1)

$8 850 000 –7 500 000 –1 000 000 –––––––––

Sales 59 000 at $150 Mfg. cost 100 000 at $75 Design cost

$350 000

Yield 59

Yield 64

EMV = $600 000

(0.8)

(0.2)

Yield 64

Yield 59

$9 600 000 –7 500 000 –1 000 000 –––––––––

Sales 64 000 at $150 Mfg. cost 100 000 at $75 Design cost

$1 100 000

$9 600 000 –7 500 000 –1 350 000 –––––––––

Sales 64 000 at $150 Mfg. cost 100 000 at $75 Design cost

$750 000

$8 850 000 –7 500 000 –1 350 000 –––––––––

Sales 59 000 at $150 Mfg. cost 100 000 at $75 Design cost

0

Design A

Design B

FIGURE 5.14

Decision Tree for Solved Problem 5.1

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178 PART 2 Designing Operations

• • 5.11 The product design group of Flores Electric Supplies, Inc., has determined that it needs to design a new series of switches. It must decide on one of three design strategies. The market forecast is for 200 000 units. The better and more sophisticated the design strategy and the more time spent on value engineering, the less will be the variable cost. The chief of engineering design, Dr. W. L. Berry, has decided that the following costs are a good estimate of the initial and variable costs connected with each of the three strategies: a) Low-tech: A low-technology, low-cost process consisting of hir-

ing several new junior engineers. This option has a fixed cost of $45 000 and variable cost probabilities of 0.3 for $0.55 each, 0.4 for $0.50, and 0.3 for $0.45.

b) Subcontract: A medium-cost approach using a good outside design staff. This approach would have a fixed cost of $65 000 and variable cost probabilities of 0.7 of $0.45, 0.2 of $0.40, and 0.1 of $0.35.

c) High-tech: A high-technology approach using the very best of the inside staff and the latest computer-aided design technol- ogy. This approach has a fixed cost of $75 000 and variable cost probabilities of 0.9 of $0.40 and 0.1 of $0.35.

What is the best decision based on an expected monetary value (EMV) criterion? (Note: We want the lowest EMV, as we are deal- ing with costs in this problem.)

• • 5.12 Tremblay Products, Inc., of Quebec City, has the option of (a) proceeding immediately with production of a new top- of-the-line stereo TV that has just completed prototype testing or (b) having the value analysis team complete a study. If Ed Lusk, VP for operations, proceeds with the existing prototype (option (a)), the firm can expect sales to be 100 000 units at $550 each, with a prob- ability of 0.6 and a 0.4 probability of 75 000 at $550. If, however, he uses the value analysis team (option (b)), the firm expects sales of 75 000 units at $750, with a probability of 0.7 and a 0.3 proba- bility of 70 000 units at $750. Value analysis, at a cost of $100 000, is used only in option (b). Which option has the highest expected monetary value (EMV)? PX

• • 5.13 Residents of Mill River have fond memories of ice skating at a local park. An artist has captured the experience in a drawing and is hoping to reproduce it and sell framed copies to cur- rent and former residents. He thinks that if the market is good, he can sell 400 copies of the elegant version at $125 each. If the market is not good, he will sell only 300 at $90 each. He can make a deluxe version of the same drawing instead. He feels that if the market is good, he can sell 500 copies of the deluxe version at $100 each. If the market is not good, he will sell only 400 copies at $70 each. In either case, production costs will be approximately $35 000. He can also choose to do nothing. If he believes there is a 50% probability of a good market, what should he do? Why? PX

• • 5.14 Ritz Products’s materials manager, Bruce Elwell, must determine whether to make or buy a new semiconductor for the wrist TV that the firm is about to produce. One million units are expected to be produced over the life cycle. If the product is made, start-up and production costs of the make decision total $1 million, with a probability of 0.4 that the product will be satisfactory and a 0.6 prob- ability that it will not. If the product is not satisfactory, the firm will have to re-evaluate the decision. If the decision is re-evaluated, the choice will be whether to spend another $1 million to redesign the semiconductor or to purchase. Likelihood of success the second time that the make decision is made is 0.9. If the second make decision also fails, the firm must purchase. Regardless of when the purchase takes place, Elwell’s best judgment of cost is that Ritz will pay $0.50

for each purchased semiconductor plus $1 million in vendor devel- opment cost. a) Assuming that Ritz must have the semiconductor (stopping or

doing without is not a viable option), what is the best decision? b) What criteria did you use to make this decision? c) What is the worst that can happen to Ritz as a result of this

particular decision? What is the best that can happen? PX

• • 5.15 Page Engineering designs and constructs air condi- tioning and heating systems for hospitals and clinics. Currently, the company’s staff is overloaded with design work. There is a major design project due in eight weeks. The penalty for completing the design late is $14 000 per week, since any delay will cause the facil- ity to open later than anticipated, and cost the client significant reve- nue. If the company uses its inside engineers to complete the design, it will have to pay them overtime for all work. Page has estimated that it will cost $12 000 per week (wages and overhead), including late weeks, to have company engineers complete the design. Page is also considering having an outside engineering firm do the design. A bid of $92 000 has been received for the completed design. Yet another option for completing the design is to conduct a joint design by having a third engineering company complete all electromechan- ical components of the design at a cost of $56 000. Page would then complete the rest of the design and control systems at an estimated cost of $30 000.

Page has estimated the following probabilities of completing the project within various time frames when using each of the three options. Those estimates are shown in the following table:

Probability of Completing the Design

Option On

Time

1 Week Late

2 Weeks Late

3 Weeks Late

Internal engineers 0.4 0.5 0.1 —

External engineers 0.2 0.4 0.3 0.1

Joint design 0.1 0.3 0.4 0.2

What is the best decision based on an expected monetary value cri- terion? (Note: You want the lowest EMV because we are dealing with costs in this problem.) PX

• • • 5.16 Use the data in Solved Problem 5.1 to examine what happens to the decision if Sarah King can increase yields from 59 000 to 64 000 by applying an expensive phosphorus to the screen at an added cost of $250 000. Prepare the modified decision tree. What are the payoffs, and which branch has the greatest EMV?

• • • • 5.17 Using the house of quality sequence, as described in Figure 5.4, determine how you might deploy resources to achieve the desired quality for a product or service whose production pro- cess you understand. • • • • 5.18 McBurger, Inc., wants to redesign its kitchens to improve productivity and quality. Three designs, called designs K1, K2, and K3, are under consideration. No matter which design is used, daily demand for sandwiches at a typical McBurger restaurant is for 500 sandwiches. A sandwich costs $1.30 to produce. Non- defective sandwiches sell, on the average, for $2.50 per sandwich. Defective sandwiches cannot be sold and are scrapped. The goal is to choose a design that maximizes the expected profit at a typ- ical restaurant over a 300-day period. Designs K1, K2, and K3 cost $100 000, $130 000, and $180 000 respectively. Under design K1, there is a 0.80 chance that 90 out of each 100 sandwiches are nondefective and a 0.20 chance that 70 out of each 100 sandwiches

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are nondefective. Under design K2, there is a 0.85 chance that 90 out of each 100 sandwiches are non defective and a 0.15 chance that 75 out of each 100 sandwiches are nondefective. Under design K3, there is a 0.90 chance that 95 out of each 100 sandwiches are nondefective and a 0.10 chance that 80 out of each 100 sandwiches are nondefective. What is the expected profit level of the design that achieves the maximum expected 300-day profit level?

•• 5.19 Draw a two-participant PCN diagram (similar to Figure 5.12) for one of the following processes: a) The process of having your computer repaired. b) The process of pizza preparation. c) The process of procuring tickets for a concert.

• • 5.20 Review strategic process positioning options for the regions in Figure 5.12, discussing the operational impact (in terms of the 10 strategic OM decisions) for: a) Manufacturing the sandwiches. b) Direct interaction. c) Establishing a sandwich buffet.

• • • 5.21 Select a service business that involves interaction between customers and service providers, and create a PCN diagram similar to Figure 5.12. Pick a key step that could be performed either by the service provider or by the customers. Show process position- ing options for the step. Describe how the options compare in terms of efficiency, economies of scale, and opportunity for customization.

Source: Based on www.stackteck.com.

StackTeck

With its headquarters and its largest manufacturing site based in Brampton, Ontario, StackTeck has become the largest plastics mould-maker in the world. In order to capitalize on global opportu- nities, the company has expanded its operations to include facilities in Hong Kong and Mexico.

To remain on the cutting edge, StackTeck is always seeking to challenge itself and its 250 employees with a process of constant improvement. Achieving both Six Sigma and ISO certification is testament to this fact.

Lou Dimaulo, VP of operations, suggests that one of their key strengths is in product development, design, and execution. Through extensive collaboration with internal and external stake- holders (including customers), solutions to complex product needs are created. This approach has garnered StackTeck a reputation for innovation, quality, and creativity.

In 1991, StackTeck pioneered the first four-level stack mould, a patented technology that has been proven in numerous applications. Stack moulds are opening new opportunities in flex- ible manufacturing as moulders turn to larger tonnage machines, more multi-material applications, and faster system automation. StackTeck has developed 70% of the four-level moulds that are in production today.

By virtually doubling, tripling, or quadrupling the output of a conventional single face moulding system, stack mould technology increases plant productivity while reducing manufacturing and cap- ital investment costs.

Flexible manufacturing using larger tonnage injection machines has spurred development of four-level stack mould appli- cations beyond traditional packaging. Delivering four times the output from a single machine has a tremendous impact on part pro- duction costs, machine productivity, and factory planning. High- volume moulders are developing new stack mould systems for multi-material applications and running multiple tools in the same stack mould to minimize inventories and product handling costs.

Stack moulds are only one area where StackTeck excels and has distinguished itself as a world leader. It is also a leader in flexible manufacturing, in-mould labelling (IML), quick product change (QPC) moulds, and alternative mould cooling technology. In each case, the product design was developed in consultation with customers and end users. StackTeck ensures that everyone wins when it ensures its customers’ needs are met, such as improv- ing productivity, better product design, reduced cycle time, etc. But the company won’t stop here as the improvement process is never ending.

Discussion Questions 1. Name three Canadian companies in different industries that mir-

ror StackTeck’s approach to continuous improvement and inno- vation in product design.

2. Discuss why it is important for StackTeck never to stop design- ing and developing new products.

CASE STUDIES

With hundreds of competitors in the boat business, Regal Marine must work to differentiate itself. As we saw in the Global Company Profile that opened this chapter, Regal continuously introduces innovative, high-quality new boats. Its differentiation strategy is reflected in a product line consisting of 22 models.

To maintain this stream of innovation, and with so many boats at varying stages of their life cycles, Regal constantly seeks design

input from customers, dealers, and consultants. Design ideas rapidly find themselves in the styling studio, where they are placed onto CAD machines in order to speed the development process. Existing boat designs are always evolving as the company tries to stay stylish and competitive. Moreover, with life cycles as short as three years, a steady stream of new products is required. A few years ago, the new product was the three-passenger $11 000 Rush, a small but

Product Strategy at Regal MarineVideo Case

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GOODS AND SERVICES SELECTION (pp. 152–155)

Although the term products may often refer to tangible goods, it also refers to offerings by service organizations.

The objective of the product decision is to develop and implement a product strategy that meets the demands of the marketplace with a competitive advantage.

• Product decision—The selection, definition, and design of products.

The four phases of the product life cycle are introduction, growth, maturity, and decline.

• Product-by-value analysis—A list of products, in descending order of their individual dollar contribution to the firm, as well as the total annual dollar contribution of the product.

Problem: 5.9

VIDEO 5.1 Product Strategy at Regal Marine

GENERATING NEW PRODUCTS (pp. 155–156)

Product selection, definition, and design take place on a continuing basis.

Changes in product opportunities, the products themselves, product volume, and product mix may arise due to understanding the customer, econom- ic change, sociological and demographic change, technological change, political/legal change, market practice, professional standards, suppliers, or distributors.

PRODUCT DEVELOPMENT (pp. 156–161)

• Quality function deployment (QFD)—A process for determining cus- tomer requirements (customer “wants”) and translating them into attrib- utes (the “hows”) that each functional area can understand and act on.

• House of quality—A part of the QFD process that utilizes a planning ma- trix to relate customer wants to how the firm is going to meet those wants.

• Product development teams—Teams charged with moving from market requirements for a product to achieving product success.

• Concurrent engineering—Use of participating teams in design and engineering activities.

• Manufacturability and value engineering—Activities that help improve a product’s design, production, maintainability, and use.

CHAPTER 5 RAPID REVIEW

powerful boat capable of pulling a water-skier. This was followed with a 6-metre inboard–outboard performance boat with so many innovations that it won prize after prize in the industry. Another new boat is a redesigned 13-metre Commodore that sleeps six in luxury staterooms. With all these models and innovations, Regal designers and production personnel are under pressure to respond quickly.

By getting key suppliers on board early and urging them to participate at the design stage, Regal improves both innovations and quality while speeding product development. Regal finds that the sooner it brings suppliers on board, the faster it can bring new boats to the market. After a development stage that constitutes concept and styling, CAD designs yield product specifications. The first stage in actual production is the creation of the “plug,” a foam-based carving used to make the moulds for fibreglass hulls and decks. Specifications from the CAD system drive the carving process. Once the plug is carved, the permanent moulds for each new hull and deck design are formed. Moulds take about four to

eight weeks to produce and are all handmade. Similar moulds are made for many of the other features in Regal boats—from galley and stateroom components to lavatories and steps. Finished moulds can be joined and used to make thousands of boats.

Discussion Questions* 1. How does the concept of product life cycle apply to Regal

Marine products? 2. What strategy does Regal use to stay competitive? 3. What kind of engineering savings is Regal achieving by using

CAD technology rather than traditional drafting techniques? 4. What are the likely benefits of the CAD design technology?

* You may wish to view the video that accompanies this case before addressing these questions.

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ISSUES FOR PRODUCT DESIGN (pp. 162–164)

• Robust design—A design that can be produced to requirements even with unfavourable conditions in the production process.

• Modular designs—Designs in which parts or components of a product are subdivided into modules that are easily interchanged or replaced.

• Computer-aided design (CAD)—Interactive use of a computer to develop and document a product.

• Design for manufacture and assembly (DFMA)—Software that allows designers to look at the effect of design on manufacturing of a product.

• 3-D object modelling—An extension of CAD that builds small prototypes.

• Standard for the exchange of product data (STEP)—A standard that provides a format allowing the electronic transmission of three-dimensional data.

• Computer-aided manufacturing (CAM)—The use of information tech- nology to control machinery.

• Virtual reality—A visual form of communication in which images substi- tute for reality and typically allow the user to respond interactively.

• Value analysis—A review of successful products that takes place during the production process.

TIME-BASED COMPETITION (pp. 164–166)

• Time-based competition—Competition based on time; rapidly develop- ing products and moving them to market.

Internal development strategies include (1) new internally developed prod- ucts, (2) enhancements to existing products, and (3) migrations of existing products.

External development strategies include (1) purchase of the technology or expertise by acquiring the developer, (2) establishment of joint ventures, and (3) development of alliances.

• Joint ventures—Firms establishing joint ownership to pursue new prod- ucts or markets.

• Alliances—Cooperative agreements that allow firms to remain independ- ent but pursue strategies consistent with their individual missions.

DEFINING A PRODUCT (pp. 166–168)

• Engineering drawing—A drawing that shows the dimensions, tolerances, materials, and finishes of a component.

• Bill of material (BOM)—A list of the components, their description, and the quantity of each required to make one unit of a product.

• Make-or-buy decision—The choice between producing a component or a service and purchasing it from an outside source.

• Group technology—A product and component coding system that speci- fies the type of processing and the parameters of the processing; it allows similar products to be grouped.

DOCUMENTS FOR PRODUCTION (pp. 169–170)

• Assembly drawing—An exploded view of a product.

• Assembly chart—A graphic means of identifying how components flow into subassemblies and final products

• Route sheet—A listing of the operations necessary to produce a compo- nent with the material specified in the bill of material.

• Work order—An instruction to make a given quantity of a particular item.

• Engineering change notice (ECN)—A correction or modification of an engineering drawing or bill of material.

• Configuration management—A system by which a product’s planned and changing components are accurately identified.

• Product life cycle management (PLM)—Software programs that tie together many phases of product design and manufacture.

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SERVICE DESIGN (pp. 170–173)

• Process–chain–network (PCN) analysis—Analysis that focuses on the ways in which processes can be designed to optimize interaction between firms and their customers.

• Process chain—A sequence of steps that accomplishes an identifiable purpose (of providing value to process participants).

Techniques to reduce costs and enhance the service offering include (1) lim- iting options, (2) delaying customization, (3) modularizing, (4) automating, and (5) designing for the “moment of truth”.

APPLICATION OF DECISION TREES TO PRODUCT DESIGN (pp. 173–175)

To form a decision tree, (1) include all possible alternatives (including “do nothing”) and states of nature; (2) enter payoffs at the end of the appropriate branch; and (3) determine the expected value of each course of action by starting at the end of the tree and working towards the beginning, calculating values at each step and “pruning” inferior alternatives.

Problems: 5.10–5.15, 5.18

ACTIVE MODEL 5.1 Virtual Office Hours for Solved Problem: 5.1

TRANSITION TO PRODUCTION (p. 175)

One of the arts of modern management is knowing when to move a product from development to production; this move is known as transition to production.

LO1 A product’s life cycle is divided into four stages, including: a) introduction. b) growth. c) maturity. d) all of the above.

LO2 Product development systems include: a) bills of material. b) routing charts. c) functional specifications. d) product-by-value analysis. e) configuration management.

LO3 A house of quality is: a) a matrix relating customer “wants” to the firm’s “hows”. b) a schematic showing how a product is put together. c) list of the operations necessary to produce a component. d) an instruction to make a given quantity of a particular item. e) a set of detailed instructions about how to perform a task.

LO4 Time-based competition focuses on: a) moving new products to market more quickly. b) reducing the life cycle of a product. c) linking QFD to PLM. d) design database availability. e) value engineering.

LO5 Products are defined by: a) value analysis. b) value engineering.

c) routing sheets. d) assembly charts. e) engineering drawings.

LO6 A route sheet: a) lists the operations necessary to produce a component. b) is an instruction to make a given quantity of a particular item. c) is a schematic showing how a product is assembled. d) is a document showing the flow of product components. e) all of the above.

LO7 Decision trees use: a) probabilities. b) payoffs. c) logic. d) options. e) all of the above.

LO8 The three process regions in a process–chain–network diagram are: a) manufacture, supplier, customer. b) direct and surrogate, customer, provider. c) independent, dependent, customer interaction. d) direct interaction, surrogate interaction, independent processing.

Self-Test  Before taking the self-test, refer to the learning objectives listed at the beginning of the chapter and the key terms listed at the end of the chapter.

Answers: LO1. d; LO2. c; LO3. a; LO4. a; LO5. e; LO6. a; LO7. e; LO8. d.

Most of these questions can be found in MyLab Operations Management. Visit MyLab Operations Management to access cases, videos, downloadable software, and much more. MyLab Operations Management Management also features a personalized Study Plan that helps you identify which chapter concepts you’ve mastered and guides you towards study tools for additional practice.

MyLab Operations Management

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183

Supplement Outline • Corporate Social Responsibility 184

• Sustainability 185

Sustainability in the Supply Chain

Supplement

5• Design and Production for Sustainability 188

• Regulations and Industry Standards 193

Learning Objectives LO1 Describe corporate social

responsibility 184

LO2 Describe sustainability 185

LO3 Explain the 3R s for sustainability 188

LO4 Calculate Design for Disassembly 189

LO5 Explain the Impact of Sustainable Regulations on Operations 193

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184 PART 2 Designing Operations

Corporate Social Responsibility1

Managers must consider how the products and services they provide affect both people and the environment. Certainly, firms must provide products and services that are innovative and attrac- tive to buyers. But today’s technologies allow consumers, communities, public interest groups, and regulators to be well informed about all aspects of an organization’s performance. As a result, stakeholders can have strong views about firms that fail to respect the environment or that engage in unethical conduct. Firms need to consider all the implications of a product—from design to disposal.

Many companies now realize that “doing what’s right” and doing it properly can be beneficial to all stakeholders. Companies that practice corporate social responsibility (CSR) introduce policies that consider environmental, societal, and financial impacts in their decision making. As managers consider approaches to CSR, they find it helpful to consider the concept of creating shared value. Shared value suggests finding policies and practices that enhance the organiza- tion’s competitiveness while simultaneously advancing the economic and social conditions in the communities in which it operates. For instance, note how automakers Tesla, Toyota, and Nissan find shared value in low-emission vehicles—vehicles that enhance their competiveness in a global market while meeting society’s interest in low-emission vehicles. Similarly, Dow Chemical finds social benefits and profit in Nexera canola and sunflower seeds. These seeds yield twice as much cooking oil as soybeans, enhancing profitability to the grower. They also have a longer shelf life, which reduces operating costs throughout the supply chain. As an added bonus, the oils have lower levels of saturated fat than traditional products and contain no trans fats. A win–win for Dow and society.

Operations functions—from supply chain management to product design to production to packaging and logistics—provide an opportunity for finding shared value and meeting CSR goals.2

LO1 Describe corporate social responsibility

Corporate social responsibility (CSR) Managerial decision making that considers environmental, societal, and financial impacts.

Airlines from around the world, including Air Canada, Air China, Virgin Atlantic Airways, KLM, Alaska, Air New Zealand, and Japan Airlines, are experimenting with alternative fuels to power their jets in an effort to reduce greenhouse gas emissions and to reduce their dependence on traditional petro- leum-based jet fuel. Alternative biofuels are being developed from recycled cooking oil, sewage sludge, municipal waste, coconuts, sugar cane, and genetically modi- fied algae that feed on plant waste.

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Shared value Developing policies and practices that enhance the competitiveness of an organization while advanc- ing the economic and social conditions in the communities in which it operates.

1 The authors wish to thank Dr. Steve Leon, University of Central Florida, for his contributions to this supplement. 2 See related discussions in M. E. Porter and M. R. Kramer, “Creating Shared Value,” Harvard Business Review (Jan.–Feb. 2011) and M. Pfitzer, V. Bockstette, and M. Stamp, “Innovating for Shared Values,” Harvard Business Review (Sept. 2013).

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Supplement 5 Sustainability in the Supply Chain 185

Sustainability Sustainability is often associated with corporate social responsibility. The term sustainability refers to meeting the needs of the present without compromising the ability of future generations to meet their needs. Many people who hear of sustainability for the first time think of green products or “going green”—recycling, global warming, and saving rainforests. This is certainly part of it. However, it is more than this. True sustainability involves thinking not only about environmental resources but also about employees, customers, community, and the company’s reputation. Three concepts may be helpful as managers consider sustainability decisions: a sys- tems view, the commons, and the triple bottom line.

SYSTEMS VIEW Managers may find that their decisions regarding sustainability improve when they take a sys- tems view. This means looking at a product’s life from design to disposal, including all the resources required. Recognizing that both raw materials and human resources are subsystems of any production process may provide a helpful perspective. Similarly, the product or service itself is a small part of much larger social, economic, and environmental systems. Indeed, man- agers need to understand the inputs and interfaces between the interacting systems and identify how changes in one system affect others. For example, hiring or laying off employees can be expected to have morale implications for internal systems (within an organization), as well as socioeconomic implications for external systems. Similarly, dumping chemicals down the drain has implications on systems beyond the firm. Once managers understand that the systems imme- diately under their control have interactions with systems below them and above them, more informed judgments regarding sustainability can be made.

COMMONS Many inputs to a production system have market prices, but others do not. Those that do not are those held by the public, or in the common. Resources held in the common are often misallocated. Examples include depletion of fish in international waters and polluted air and waterways. The attitude seems to be that just a little more fishing or a little more pollution will not matter, or the adverse results may be perceived as someone else’s problem. Society is still groping for solutions for use of those resources in the common. The answer is slowly being found in a number of ways: (1) moving some of the common to private property (e.g., selling radio frequency spectrum), (2) allocation of rights (e.g., establishing fishing boundaries), and (3) allocation of yield (e.g., only a given quantity of fish can be harvested). As managers understand the issues of the com- mons, they have further insight about sustainability and the obligation of caring for the commons.

TRIPLE BOTTOM LINE Firms that do not consider the impact of their decisions on all their stakeholders see reduced sales and profits. Profit maximization is not the only measure of success. A one-dimensional bottom line, profit, will not suffice; the larger socioeconomic systems beyond the firm demand more. One way to think of sustainability is to consider the systems necessary to support the tri- ple bottom line of the three Ps: people, planet, and profit (see Figure S5.1), which we will now discuss.

PEOPLE Companies are becoming more aware of how their decisions affect people—not only their employees and customers but also those who live in the communities in which they operate. Most employers want to pay fair wages, offer educational opportunities, and pro- vide a safe and healthy workplace. So do their suppliers. But globalization and the reliance on outsourcing to suppliers around the world complicate the task. This means companies must create policies that guide supplier selection and performance. Sustainability suggests that supplier selection and performance criteria evaluate safety in the work environment, whether living wages are paid, if child labour is used, and whether work hours are excessive. Apple, GE, Procter & Gamble, and Walmart are examples of companies that conduct supplier audits to uncover any harmful or exploitative business practices that are counter to their sustainability goals and objectives.

Sustainability Meeting the needs of the present without compromising the ability of future generations to meet their needs.

LO2 Describe sustainability

VIDEO S5.1 Building Sustainability at the Orlando Magic’s Amway Center

Profit is now just one of the three P s: people, planet, and profit.

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Recognizing that customers increasingly want to know that the materials in the products they buy are safe and produced in a responsible way, Walmart initiated the development of the world- wide sustainable product index for evaluating the sustainability of products. The goals of that initiative are to create a more transparent supply chain, accelerate the adoption of best practices, and drive product innovation.

Walmart found a correlation between supply chain transparency, positive labour practices, community involvement, and quality, efficiency, and cost. Walmart is committed to working with its suppliers to sell quality products that are safe, that create value for customers, and that are produced in a sustainable way. The firm is accomplishing this in four ways:

1. Improving livelihoods through the creation of productive, healthy, and safe workplaces and promoting quality of life

2. Building strong communities through access to affordable, high-quality services such as education and job training that support workers and their families

3. Preventing exposure to substances that are considered harmful or toxic to human health 4. Promoting health and wellness by increasing access to nutritious products, encouraging

healthy lifestyles, and promoting access to healthcare

Walmart’s CEO has said that companies that are unfair to their people are also likely to skimp on quality and that he will not continue to do business with those suppliers. Accordingly, operations managers must consider the working conditions in which they place their employees. This includes training and safety orientations, before-shift exercises, earplugs, safety goggles, and rest breaks to reduce the possibility of worker fatigue and injury. Operations managers must also make decisions regarding the disposal of material and chemical waste, including hazardous materials, so they don’t harm employees or the community.

PLANET When discussing the subject of sustainability, our planet’s environment is the first thing that comes to mind, so it understandably gets the most attention from managers. Operations managers look for ways to reduce the environmental impact of their operations, whether from raw material selection, process innovation, alternative product delivery methods, or disposal of products at their end-of-life. The overarching objective for operations managers is to conserve scarce resources, thereby reducing the negative impact on the environment. Here are a few exam- ples of how organizations creatively make their operations more environmentally friendly:

• S.C. Johnson, the company that makes Windex, Saran Wrap, Pledge, Ziploc bags, and Raid, developed Greenlist, a classification system that evaluates the impact of raw materials on human and environmental health. By using Greenlist, S.C. Johnson has eliminated millions of kilograms of pollutants from its products.

FIGURE S5.1

Improving the Triple Bottom Line with Sustainability

Raw material

Concept Design Raw material

Transport Transport TransportConsume DisposalManufacture

Energy Water

Minimize

Planet People Profit

Waste

Maximize the triple bottom line

Walmart has become a global leader in sustainability. Read Force of Nature: The Unlikely Story of Walmart’s Green Revolution.

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Supplement 5 Sustainability in the Supply Chain 187

• Thirty-one public school districts across the state of Kentucky operate hybrid electric school buses. They estimate fuel savings as high as 40%, relative to standard diesel buses.

• Levi’s has started a campaign to save water in the creation of jeans, as seen in the OM in Action box “Blue Jeans and Sustainability.”

To gauge their environmental impact on the planet, many companies are measuring their carbon footprint. Carbon footprint is a measure of the total greenhouse gas (GHG) emissions caused directly and indirectly by an organization, a product, an event, or a person. A substantial portion of greenhouse gases are released naturally by farming, cattle, and decaying forests and, to a lesser degree, by manufacturing and services. The most common greenhouse gas produced by human activities is carbon dioxide, primarily from burning fossil fuels for electricity genera- tion, heating, and transport. Operations managers are being asked to do their part to reduce GHG emissions.

Industry leaders such as Frito-Lay have been able to break down the carbon emissions from various stages in the production process. For instance, in potato chip production, a 34.5-gram (1.2-ounce) bag of chips is responsible for about twice its weight in emissions—75 grams per bag (see Figure S5.2).

PROFIT Social and environmental sustainability do not exist without economic sustainability. Economic sustainability refers to how companies remain in business. Staying in business requires making investments, and investments require making profits. Though profits may be relatively easy to determine, other measures can also be used to gauge economic sustainability. The alternative measures that point to a successful business include risk profile, intellectual prop- erty, employee morale, and company valuation. To support economic sustainability, firms may supplement standard financial accounting and reporting with some version of social accounting. Social accounting can include brand equity, management talent, human capital development and benefits, research and development, productivity, philanthropy, and taxes paid.

Carbon footprint A measure of total greenhouse gas emissions caused directly or indirectly by an organization, a product, an event, or a person.

VIDEO S5.2 Green Manufacturing and Sustaina- bility at Frito-Lay

Economic sustainability Appropriately allocating scarce resources to make a profit.

The recent drought in California is hurting more than just farmers. It is also having a significant impact on the fashion industry and spurring changes in how jeans are made and how they should be laundered. Southern California is estimated to be the world’s largest supplier of so-called premium denim, the $100- to $200-plus-a- pair of designer jeans. Water is a key component in the various steps of the processing and repeated washing with stones, or bleaching and dyeing that create that “distressed” vintage look. Southern California produces 75% of the high-end denim in the United States that is sold worldwide. The area employs about 200 000 people, making it the largest U.S. fashion manufacturing hub.

Now that water conservation is a global priority, major denim brands are working to cut water use. Levi’s, with sales of $5 billion, is using ozone machines to replace the bleach traditionally used to lighten denim. It is also reduc- ing the number of times it washes jeans. The company has saved more than a billion litres of water since 2011 with its Levi’s Water Less campaign. By 2020, the company plans to have 80% of Levi’s brand products made using the Water Less process, up from about 25% currently.

Traditionally, about 34 litres of water are used in the cutting, sewing, and finishing process to make a pair of Levi’s signature 501 jeans. Nearly 3800 litres of water are used throughout the lifetime of a pair of Levi’s 501. A study found cotton cultivation represents 68% of that and consumer washing another 23%. So Levi’s is promoting

the idea that jeans only need washing after 10 wears. (The average North American consumer washes after two wears.) Levi’s CEO recently urged people to stop washing their jeans, saying he hadn’t washed his one-year-old jeans at the time. “You can air dry and spot clean instead,” he said.

Sources: The Wall Street Journal (April 10, 2015) and New York Times (March 31, 2015).

Blue Jeans and SustainabilityOM in Action

Fibre 68%

Consumer care 23%

Cradle to grave water consumption percentage

Sundries & Packaging 2%

Cut, Sew, Finish 1%

Fabric production 6%

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188 PART 2 Designing Operations

Design and Production for Sustainability The operations manager’s greatest opportunity to make substantial contributions to the com- pany’s environmental objectives occurs during product life cycle assessment. Life cycle assessment evaluates the environmental impact of a product, from raw material and energy inputs all the way to the disposal of the product at its end-of-life. The goal is to make decisions that help reduce the environmental impact of a product throughout its entire life. Focusing on the 3Rs—reduce, reuse, and recycle— can help accomplish this goal. By incorporating the 3Rs, product design teams, process managers, and supply chain personnel can make great strides towards reducing the environmental impact of products—to the benefit of all stakeholders.

PRODUCT DESIGN Product design is the most critical phase in product life cycle assessment. The decisions that are made during this phase greatly affect materials, quality, cost, processes, related packaging and logistics, and ultimately how the product will be processed when discarded. During design, one of the goals is to incorporate a systems view in the product or service design that lowers the environmental impact. This is the first R. Such an approach reduces waste and energy costs at the supplier, in the logistics system, and for the end user. For instance, by taking a systems view, Procter & Gamble developed Tide Coldwater, a detergent that gets clothes clean with cold water, saving the consumer about three-fourths of the energy used in a typical wash. Other successful design efforts include:

• Boston’s Park Plaza Hotel eliminated bars of soap and bottles of shampoo by installing pump dispensers in its bathrooms, saving the need for 1 million plastic containers a year.

• UPS reduced the amount of materials it needs for its envelopes by developing its reusable express envelopes, which are made from 100% recycled fibre. These envelopes are designed to be used twice, and after the second use, the envelope can be recycled.

• Coca-Cola’s redesigned Dasani bottle reduced the amount of plastic needed and is now 30% lighter than when it was introduced.

Product design teams also look for alternative materials from which to make their products. Innovating with alternative materials can be expensive, but it may make autos, trucks, and air- craft more environmentally friendly while improving payload and fuel efficiency. Aircraft and auto makers, for example, constantly seek lighter materials to use in their products. Lighter materials translate into better fuel economy, fewer carbon emissions, and reduced operating cost. For instance:

• Mercedes is building some car exteriors from a banana fibre that is both biodegradable and lightweight.

• Some Fords have seat upholstery made from recycled plastic soda bottles and old clothing. • Boeing is using carbon fibre, epoxy composites, and titanium graphite laminate to reduce

weight in its new 787 Dreamliner.

Life cycle assessment Analysis of environmental impacts of products from the design stage through end-of-life.

LO3 Explain the 3Rs for sustainability

FIGURE S5.2

Carbon Footprint of a 34.5- gram Bag of Frito-Lay Chips

Shipping 9%

Packaging 15%

Manufacture 30%

Farming 44%

Total carbon footprint

Disposal 2%

75 g

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Supplement 5 Sustainability in the Supply Chain 189

Product designers often must decide between two or more environmentally friendly design alternatives. Example S1 deals with a design for disassembly cost–benefit analysis. This process focuses on the second and third Rs: reuse and recycle. The design team analyzes the amount of revenue that might be reclaimed against the cost of disposing of the product at its end-of-life.

An excellent place for operations managers to begin the sustainability challenge is with good product design. Here Tom Malone, CEO of MicroGreen Polymers, discusses the company’s new ultra-light cup with production personnel (left). The cup can be recycled over and over and never go to a landfill. Another new design is the “winglet” (right). These wing tip extensions increase climb speed, reduce noise by 6.5%, cut CO2 emissions by 5%, and save 6% in fuel costs. Alaska Air has retrofitted its entire 737 fleet with winglets, saving $20 million annually.

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Sound Barrier, Inc., needs to decide which of two speaker designs is better environmentally.

APPROACH c  The design team collected the following information for two audio speaker designs, the Harmonizer and the Rocker:

1. Resale value of the components minus the cost of transportation to the disassembly facility 2. Revenue collected from recycling 3. Processing costs, which include disassembly, sorting, cleaning, and packaging 4. Disposal costs, including transportation, fees, taxes, and processing time

SOLUTION c  The design team developed the following revenue and cost information for the two speaker design alternatives: Harmonizer

Part Resale Revenue

Per Unit Recycling Reve-

nue Per Unit Processing Cost

Per Unit Disposal Cost

Per Unit

Printed circuit board $5.93 $1.54 $3.46 $0.00

Laminate back 0.00 0.00 4.53 1.74

Coil 8.56 5.65 6.22 0.00

Processor 9.17 2.65 3.12 0.00

Frame 0.00 0.00 2.02 1.23

Aluminum case 11.83 2.10 2.98 0.00

Total $35.49 $11.94 $22.33 $2.97

EXAMPLE S1

Design for Disassembly

LO4 Calculate design for disassembly

A fourth R, improved reputation, follows the success of reduce, reuse, and recycle.

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190 PART 2 Designing Operations

Rocker

Part Resale Revenue

Per Unit Recycling Revenue

Per Unit Processing

Cost Per Unit Disposal Cost

Per Unit

Printed circuit board $7.88 $3.54 $2.12 $0.00

Coil 6.67 4.56 3.32 0.00

Frame 0.00 0.00 4.87 1.97

Processor 8.45 4.65 3.43 0.00

Plastic case 0.00 0.00 4.65 3.98

Total $23.00 $12.75 $18.39 $5.95

Using the Equation (S5-1), the design team can compare the two design alternatives:

Revenue retrieval = Total resale revenue + Total recycling revenue - Total processing cost - Total disposal cost (S5-1) Revenue retrieval for Harmonizer 5 $35.49  $11.94 2 $22.33 2 $2.97 5 $22.13

Revenue retrieval for Rocker 5 $23.00  $12.75 2 $18.39 − $5.95 5 $11.41

INSIGHT c    After analyzing both environmental revenue and cost components of each speaker design, the design team finds that the Harmonizer is the better environmental design alternative as it achieves a higher revenue retrieval opportunity. Note that the team is assuming that both products have the same market acceptance, profitability, and environmental impact.

LEARNING EXERCISE c    What would happen if there was a change in the supply chain that caused the processing and disposal costs to triple for the laminate back part of the Harmonizer? [Answer: The revenue retrieval from the Harmonizer is $35.49 + $11.94 − $31.39 − $6.45 = $9.59. This is less than the Rocker’s revenue retrieval of $11.41, so the Rocker becomes the better environ- mental design alternative, as it achieves a higher revenue retrieval opportunity.]

RELATED PROBLEMS c  S5.1, S5.2, S5.3, S5.9, S5.12, S5.13, S5.14

PRODUCTION PROCESS Manufacturers look for ways to reduce the amount of resources in the production process. Opportunities to reduce environmental impact during production typically revolve around the themes of energy, water, and environmental contamination. Conservation of energy and improving energy efficiency come from the use of alternative energy and more energy-efficient machinery. For example:

• S.C. Johnson built its own power plant that runs on natural gas and methane piped in from a nearby landfill, cutting back its reliance on coal-fired power.

• PepsiCo developed Resource Conservation (ReCon), a diagnostic tool for understanding and reducing in-plant water and energy usage. In its first two years, ReCon helped sites across the world identify 2.2 billion litres of water savings, with a corresponding cost savings of nearly $2.7 million.

• Frito-Lay decided to extract water from potatoes, which are 80% water. Each year, a single factory processes 350 000 tonnes of potatoes, and as those potatoes are processed, the com- pany reuses the extracted water for that factory’s daily production.

These and similar successes in the production process reduce both costs and environmental concerns. Less energy is consumed, and less material is going to landfills.

LOGISTICS As products move along in the supply chain, managers strive to achieve efficient route and delivery networks, just as they seek to drive down operating cost. Doing so reduces environ- mental impact. Management analytics (such as linear programming, queuing, and vehicle rout- ing software) help firms worldwide optimize elaborate supply chain and distribution networks. Networks of container ships, airplanes, trains, and trucks are being analyzed to reduce the num- ber of kilometres traveled or the number of hours required to make deliveries. For example:

• UPS has found that making left turns increases the time it takes to make deliveries. This in turn increases fuel usage and carbon emissions. So UPS plans its delivery truck routes with

Las Vegas, always facing a water shortage, pays residents $40 000 an acre to take out lawns and replace them with rocks and native plants.

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Supplement 5 Sustainability in the Supply Chain 191

Three key success factors in the trucking industry are (1) getting shipments to customers promptly (rapid response), (2) keeping trucks busy (capacity utilization), and (3) buying inexpensive fuel (driving down costs). Many firms have now developed devices like the one shown on the right to track location of trucks and facilitate communication between drivers and dispatchers. Some systems use global positioning satellites (shown on the left), to speed shipment response, maximize utilization of the truck, and ensure purchase of fuel at the most economical location. Sensors are also being added inside trailers. These sensors communicate whether the trailer is empty or full and detect if the trailer is connected to a truck or riding on a railroad car.

the fewest possible left turns. Likewise, airplanes fly at different altitudes and routes to take advantage of favourable wind conditions in an effort to reduce fuel use and carbon emissions.

• Food distribution companies now have trucks with three temperature zones (frozen, cool, and nonrefrigerated) instead of using three different types of trucks.

• Whirlpool radically revised its packaging to reduce “dings and dents” of appliances during delivery, generating huge savings in transportation and warranty costs.

To further enhance logistic efficiency, operations managers also evaluate equipment alterna- tives, taking into account cost, payback period, and the firm’s stated environmental objectives. Example S2 deals with decision making that takes into account life cycle ownership costs. A firm must decide whether to pay more up front for vehicles to further its sustainability goals or to pay less up front for vehicles that do not.

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Blue Star is starting a new distribution service that delivers auto parts to the service departments of auto dealerships in the local area. Blue Star has found two light-duty trucks that would do the job well, so now it needs to pick one to perform this new service. The Ford TriVan costs $28 000 to buy and uses regular unleaded gasoline, with an average fuel efficiency of 24 kilometres per litre. The TriVan has an operating cost of $0.20 per kilometre. The Honda CityVan, a hybrid truck, costs $32 000 to buy and uses regular unleaded gasoline and battery power; it gets an average of 37 kilometres per litre. The CityVan has an operating cost of $0.22 per kilometre. The distance traveled annually is estimated to be 22 000 kilometres, with the life of either truck expected to be eight years. The average gas price is $4.25 per litre.

APPROACH c  Blue Star applies Equation (S5-2) to evaluate total life cycle cost for each vehicle:

Total life cycle cost 5 Cost of vehicle  Life cycle cost of fuel  Life cycle operating cost (S5-2)

a) Based on life cycle cost, which model truck is the best choice? b) How many kilometres does Blue Star need to put on a truck for the costs to be equal? c) What is the crossover point in years?

SOLUTION c  

a) Ford TriVan:

Total life@ cycle cost

= $28 000 + ≥ 22 000

kilometres year

24 kilometres

litre

¥ ($4.25>litre) (8 years)

+ a22 000kilometres year

b($0.20>kilometre)(8 years) = $28 000 + $31 167 + $35 200 = $94 367

EXAMPLE S2

Life Cycle Ownership and Crossover Analysis

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192 PART 2 Designing Operations

Honda CityVan:

Total life@ cycle cost

= $32 000 + ≥ 22 000

kilometres year

37 kilometres

litre

¥ ($4.25>litre)(8 years)

+ a22 000 kilometres year

b($0.22>kilometre)(8 years) = $32 000 + $20 216 + $38 720 = $90 936 b) Blue Star lets M be the crossover (break-even) point in kilometres, sets the two life cycle cost equations equal to each other, and solves for M:

Total cost for Ford TriVan = Total cost for Honda CityVan

$28 000 + ≥ 4.25

$ litre

24 kilometres

litre

+ .20 $

kilometre ¥ (M kilometres) = $32 000

+ ≥ 4.25

$ litre

37 kilometres

litre

+ .22 $

kilometre ¥ (M kilometres)

or,

$28 000 + a.3770 $ kilometre

b(M) = $32 000 + a.3349 $ kilometre

b (M)

or,

a.0421 $ kilometre

b(M ) = $4 000

M = $4 000

.0421 $

kilometre

= 95 012 kilometres

(Rounding to four decimal places was used in these calculations.)

c) The crossover point in years is:

Crossover point = 95 012 kilometres

22 000 kilometres

year

= 4.32 years

INSIGHT c  

a) Honda CityVan is the best choice, even though the initial fixed cost and variable operating cost per kilometre are higher. The savings comes from the better fuel mileage (more kilometres per litre) for the Honda CityVan. b) The crossover (break-even) point is at 95 012 kilometres, which indicates that at this mileage point, the cost for either truck is the same. c) It will take 4.32 years to recoup the cost of purchasing and operating either vehicle. It will cost Blue Star approximately $0.03 per kilometre less to operate the Honda CityVan than the Ford TriVan over the eight-year expected life.

LEARNING EXERCISE c  If the cost of gasoline drops to $3.25, what will be the total life cycle cost of each van, the break-even point in kilometres, and the crossover point in years? [Answer: The cost of the Ford TriVan is $87 033; the Honda CityVan costs $86 179; the break-even is 144 927 kilo- metres; and the crossover point is 6.59 years.]

RELATED PROBLEMS c  S5.4, S5.5, S5.6, S5.10, S5.11, S5.15, S5.16, S5.17, S5.18, S5.19

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Supplement 5 Sustainability in the Supply Chain 193

END-OF-LIFE PHASE We noted earlier that during product design, managers need to consider what happens to a prod- uct or its materials after the product reaches its end-of-life stage. Products with less material, with recycled material, or with recyclable materials all contribute to sustainability efforts, reduc- ing the need for the “burn or bury” decision and conserving scarce natural resources.

Innovative and sustainability-conscious companies are now designing closed-loop supply chains, also called reverse logistics. Firms can no longer sell a product and then forget about it. They need to design and implement end-of-life systems for the physical return of products that facilitate recycling or reuse.

Caterpillar, through its expertise in remanufacturing technology and processes, has devised Cat Reman, a remanufacturing initiative, in an effort to show its commitment to sustainabil- ity. Caterpillar remanufactures parts and components that provide same-as-new performance and reliability at a fraction of new cost, while reducing the impact on the environment. The remanufacturing program is based on an exchange system where customers return a used com- ponent in exchange for a remanufactured product. The result is lower operating costs for the customer, reduced material waste, and less need for raw material to make new products. In a one-year period, Caterpillar took back 2.1 million end-of-life units and remanufactured over 130 million pounds of material from recycled iron.

The OM in Action box “From Assembly Lines to Green Disassembly Lines” describes one automaker’s car design philosophy to facilitate the disassembly, recycling, and reuse of its autos that have reached their end-of-life.

Regulations and Industry Standards Government, industry standards, and company policies are all important factors in operational decisions. Failure to recognize these constraints can be costly. Over the last 100 years, we have seen development of regulations, standards, and policies to guide managers in product design, manufacturing/assembly, and disassembly/disposal.

To guide decisions in product design laws and regulations provide guidance and often explicit regulations.

Closed-loop supply chains Supply chains that consider forward and reverse product flows over the entire life cycle.

LO5 Explain the impact of sustainable regulations on operations

A century has passed since assembly lines were devel- oped to make automobiles—and now we’re developing disassembly lines to take them apart. So many automo- biles are disassembled that recycling is the 16th-largest industry in the United States The motivation for this comes from many sources, including mandated industry recycling standards and a growing consumer interest in purchasing cars based on how “green” they are.

New car designs have traditionally been unfriendly to recyclers, with little thought given to disassembly. Some components, such as air bags, are hard to handle and dangerous, and they take time to disassemble. However, manufacturers now design in such a way that materials can be easily reused in the next generation of cars. The 2015 Mercedes S-class is 95% recyclable. BMW has dis- assembly plants in Europe, Japan, New York, Los Angeles, and Orlando.

A giant 200 000-square-foot facility in Baltimore (called CARS) can disassemble up to 30 000 vehicles per year. At CARS’s initial “greening station,” special tools puncture tanks and drain fluids and remove the battery and gas tank. Then wheels, doors, hood, and trunk are removed;

next come the interior items; plastic parts are removed and sorted for recycling; then glass and interior and trunk mate- rials. Eventually the chassis is a bale and sold as a com- modity to minimills that use scrap steel. Reusable parts are bar-coded and entered into a database. The photo shows an operator controlling the car recycling plant.

Sources: Wall Street Journal (April 29, 2008) and Time (February 4, 2010).

From Assembly Lines to Green Disassembly LinesOM in Action

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194 PART 2 Designing Operations

Manufacturing and assembly activities have their own set of regulatory agencies providing guidance and standards of operations. These include many federal, provincial, and local agencies that regulate workers’ rights and employment standards.

As product life spans shorten due to ever-changing trends and innovation, product designers are under added pressure to design for disassembly. This encourages designers to create products that can be disassembled and whose components can be recovered, minimizing impact on the environment.

Organizations are obliged by society and regulators to reduce harm to consumers, employees, and the environment. The result is a proliferation of community, provincial, federal, and even international laws that often complicate compliance. The lack of coordination of regulations and reporting requirements between jurisdictions adds not just complexity but cost.

From the following examples it is apparent that nearly all industries must abide by regulations in some form or another:

• Commercial homebuilders are required not just to manage water runoff but to have a pollu- tion prevention plan for each site.

• Hospitals are required to meet the terms of regulations that govern the storage and handling of hazardous material.

The consequences of ignoring regulations can be disastrous and even criminal. The govern- ment investigates environmental crimes in which companies and individuals are held account- able. Prison time and expensive fines can be handed down. (British Petroleum paid billions of dollars in fines in the past few years for breaking environmental and safety laws.) Even if a crime has not been committed, the financial impacts and customer upheaval can be disastrous to companies that do not comply with regulations. Due to lack of supplier oversight, Mattel, Inc., one of the world’s largest toymakers, has recalled over 10 million toys in recent years because of consumer health hazards such as lead paint.

INTERNATIONAL ENVIRONMENTAL POLICIES AND STANDARDS Organizations such as the U.N. Framework Convention on Climate Change (UNFCCC), International Organization for Standardization (ISO), and governments around the globe are guiding businesses to reduce environmental impacts from disposal of materials to reductions in greenhouse gas (GHG) emissions. Some governments are implementing laws that mandate the outright reduction of GHG emissions by forcing companies to pay taxes based on the amount of GHG emissions that are emitted. We now provide an overview of some of the international standards that apply to how businesses operate, manufacture, and distribute goods and services.

European Union Emissions Trading System The European Union has developed and imple- mented the EU Emissions Trading System (EUETS) to combat climate change. This is the key tool for reducing industrial greenhouse gas emissions in the EU. The EUETS works on the “cap- and-trade” principle. This means there is a cap, or limit, on the total amount of certain greenhouse gases that can be emitted by factories, power plants, and airlines in EU airspace. Within this cap, companies receive emission allowances, which they can sell to, or buy from, one another as needed.

ISO 14000 The International Organization for Standardization (ISO) is widely known for its contributions in ISO 9000 quality assurance standards (discussed in Chapter 6). The ISO 14000 family grew out of the ISO’s commitment to support the 1992 U.N. objective of sustaina- ble development. ISO 14000 is a series of environmental management standards that contain five core elements: (1) environmental management, (2) auditing, (3) performance evaluation, (4)  labelling, and (5) life cycle assessment. Companies that demonstrate these elements may apply for certification. ISO 14000 has several advantages:

• Positive public image and reduced exposure to liability • Good systematic approach to pollution prevention through minimization of ecological impact

of products and activities • Compliance with regulatory requirements and opportunities for competitive advantage • Reduction in the need for multiple audits

ISO 14000 A series of environmental man- agement standards established by the International Organization for Standardization (ISO).

A group of 100 apparel brands and retailers have created the Eco Index to display an eco-value on a tag, like the Energy Star rating does for appliances.

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Supplement 5 Sustainability in the Supply Chain 195

ISO 14000 standards have been implemented by more than 200 000 organizations in 155  countries. Companies that have implemented ISO 14000 standards report environmental and economic benefits such as reduced raw material/resource use, reduced energy consumption, lower distribution costs, improved corporate image, improved process efficiency, reduced waste generation and disposal costs, and better utilization of recoverable resources.