Lean Six Sigma - Green Belt

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Lean Six Sigma Green Belt

Course eBook This eBook is for personal use only. Please DO NOT use this eBook for presentations and training facilitation purposes.

2Copyright © 2016 Acuity Institute LLC. All rights reserved.

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For information contact: Acuity Institute LLC 4610 South Ulster Street, Suite 150 Denver, CO 80237 Printed in the United States of America Visit: www.acuityinstitute.com

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eBook Overview Welcome to the eBook for the Acuity Institute Lean Six Sigma Green Belt Certification Program.  You will need the most recent version of Adobe Reader to view the eBook. We do not recommend viewing

the eBook with Adobe Acrobat.  We recommend becoming familiar with the eBook and its features. A few features include printing, viewing

notes, and capturing your comments.  For ease of use, we have included numerous bookmarks in the eBook so you can quickly access common

course concepts.  The eBook is for personal use only. Please do not use the eBook for presentations and training facilitation.  The eBook is for the intended parties only.  This eBook contains various exercises that are represented by the following icons:

General ExercisesEXERCISE

1

Simco International Products Simulated Project. When you see this icon you will be completing an exercise within the simulation. We call these exercises “deliverables”. When you are done with the Deliverable you can return to the course material by selecting the “Go Back To Lesson” link.

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Course Objectives

2

Upon completion of this course, students will be able to:  Apply Lean Six Sigma and the DMAIC methodology  Apply skills in project management, process management, lean, change

management, and statistical analysis  Define their role in a successful Lean Six Sigma deployment  Recognize how to scope, define and lead Lean Six Sigma projects  Recognize how to transition projects from phase to phase  Complete projects  Present projects to peers, managers and senior leadership  Apply methods learned in the DMAIC process to business issues  Apply statistical analysis to determine the relationship between key inputs and

process outputs  Characterize the equation y = f(x)  Implement controls to sustain gains  Effectively manage team dynamics  Navigate statistical analysis software (SigmaXL or Minitab)

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Course Lessons

Define Measure Analyze Improve Control

1. Lean Six Sigma Introduction

2. Define Overview 3. Project Charter 4. Project

Management 5. Process

Definition 6. Stakeholder

Management 7. Voice of

Customer

8. Measure Overview

9. Identify Measures

10. Data Collection 11. Describe &

Display Data 12. Baseline

Performance

13. Analyze Overview

14. Root Cause Analysis

15. Lean Process Analysis

16. Graphical Data Analysis

17. Statistical Data Analysis

18. Identify Root Causes

19. Improve Overview

20. Identify & Select Solutions

21. Financial Impact of Solutions

22. Risk Planning & Testing

23. Implement Solution

24. Control Overview

25. Process Control

26. Response Planning

27. Project Documentation

The Lean Six Sigma Green Belt course contains 27 lessons, and 5 Simulated Project sections (32 Project Deliverables)

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Lean Six Sigma Toolkit

The Lean Six Sigma Toolkit icon is periodically introduced in this eBook The toolkit icon informs you that a Lean Six Sigma template is available for your use. The templates are located in the “Lean Six Sigma Toolkit Templates” folder. To access the templates you will need to download this folder onto your computer.

The Lean Six Sigma Toolkit assists practitioners in keeping focused on their project work and not creating “templates”. The toolkit includes common templates used throughout the Lean Six Sigma DMAIC phases. The templates are developed in common formats (MS Word, MS Excel or MS PowerPoint).

Included Templates  Solutions Benefits and Implications  Solutions Prioritization Matrix  Solutions Selection Matrix  Stakeholder Identification  Stakeholder Management Plan  Stakeholder Map  Standardized Procedures  Team Meeting Agenda  Team Profile  VOC Research Plan  XY Matrix

 Pilot Plan  Process Monitoring Plan  Process Value Analysis  Project Charter  Project Storyboard  Quick Win Identification  Response Plan  Sigma Calculator  SIPOC

 5 Whys  Communication Plan  CTQ Chart  Dashboard Measurement Plan  Data Collection Plan  DMAIC Project Plan  DMAIC Tollgate Presentation  FMEA  Force Field Diagram  Implementation Plan – Detailed  Implementation Plan – High Level

Template Name

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Acuity Institute Support

For product support questions please contact Acuity Institute at [email protected]

Please visit www.acuityinstitute.com for additional product and course offerings

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Lean Six Sigma Introduction

Lean Six Sigma Training

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By the end of this lesson, you will be able to:

 Learn what Lean Six Sigma is

 Learn about various Lean Six Sigma Improvement Methodologies

 Learn what the Lean Six Sigma Roles and Responsibilities are

Overview – Objectives – Key Topics

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Experience with Other Quality InitiativesEXERCISE

Objective  Identify past experiences with other Quality or Process Improvement

initiatives.

Instructions  Answer the following questions:

 What has been your experience with other Quality or Process Improvement initiatives?

 What was good about the other Quality or Process Improvement initiatives you were involved in?

 What struggles or challenges have you had with other Quality or Process Improvement initiatives?

 What could have made them better?

 Prepare your findings.

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Please Do Not Proceed Forward

Experience with Other Quality InitiativesEXERCISE

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When you see this symbol, please do not continue forward in the materials until you have completed the exercise.

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Experience with Other Quality Initiatives

Discussion

EXERCISE

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Lean Six Sigma Training

Lean Six Sigma Overview

Lean Six Sigma Roles

Lean Six Sigma Improvement Methodologies

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Does your current performance meet customer expectations? Is there a gap between what your company’s leaders want to achieve and the

organization’s ability to deliver it?

“Leaders who execute look for deviation from desired managerial tolerances – the gap between the desired and actual outcome in everything

from profit margins to the selection of people for promotion… Like Six Sigma, the discipline of execution doesn’t work unless people are

schooled in it and practice it constantly… Execution has to be part of an organization’s culture…”

-- Larry Bossidy, Former CEO of Allied Signal -- -- Execution: The Discipline of Getting Things Done --

Vital Questions in an Increasingly Competitive World

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Lean Six Sigma was developed out of necessity as a very rigorous and disciplined approach for companies to improve products and services based on their customers’ expectations and requirements…an “outside looking in” approach. Lean Six Sigma has many facets.

Lean Six Sigma Definition

Lean Six Sigma can improve profits and cut costs, but more importantly, it can keep customers loyal as well as improve a company’s competitive advantage.

Goal Vision

Philosophy Benchmark

Methodology Symbol Metric Tool

Process Focused

Business FocusedCustomer Focused

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Lean Six Sigma Definition

Lean Six Sigma uses a variety of tools and techniques to achieve superior process performance, such as:

 Customer Surveying (Voice of Customer)

 Metric Identification and Collection

 Baselining / Measuring Process Performance

 Data Based Decision Making (Analysis and Statistics)

 Lean Process Flow / Value Analysis

 Benchmarking “Best In Class” Companies

 Risk Analysis / Assessment

 Implementation Planning / Management

 Change Management

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A process is defined as a repetitive and systematic series of actions or operations whereby one or more inputs from suppliers is used to

achieve an output of value to the customer (internal/external)

Input Output Process

Actions

Process Model

What is a Process?

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I P O

The Work Process

I P O

The Improvement Process

Relationship of Work Process and Improvement Process

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For every process there is a dependent variable called Y that we are attempting to influence. The independent variables which determine what happens to our Y are called the process X’s. Thus, we can boil down every process into a simple formula:

Y = f(x1,x2,x3…xn) The goal of Lean Six Sigma is to understand the relationship between our various Xs and our Y, so we can manipulate the Xs to modify Y as desired, then lock down the process so that Y remains within the proper range and is meeting customer requirements.

The Focus of Lean Six Sigma

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Lean Six Sigma Focuses on Reducing Variation

Variation Happens  All repetitive activities of a process have a certain amount of

fluctuation or variation  Variation is the “Voice of the Process”  When plotted, process variation becomes visible over time  Input, process, and output measures will have variation  Failure to understand variation could be costly

Time Frequency

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Why it’s Important to Understand Variation

PROCESS VARIATION INHIBITS OUR ABILITY TO MEET CUSTOMER REQUIREMENTS

Product or Service Output

Critical to Quality (CTQ)

Defects: Service unacceptable to

customer

A

Product or Service Output

Critical to Quality (CTQ)

Defects: Service unacceptable to

customer

A

Variation 14

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Sigma is a Greek letter that is a statistical unit of measurement used to define the standard deviation of a population. It measures the variability or spread of the data.

Sigma is a name given to indicate how much of the data falls within the customers’ requirements. The higher the process sigma, the more the process outputs, products and services, meet customers’ requirements – or, the fewer the defects.

“Sigma” Defined

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Notes: Defects are defined as not meeting customer requirements. Put simply, sigma is the measure of how far a process is away from achieving near perfect customer satisfaction. “6” Sigma is measured at near perfect… meeting customer expectations 99.99966% of the time.

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In this diagram, the Sigma is calculated by the number of occurrences (defects) that fall outside of the customer requirement (for Process A). Process B represents the optimal performance with no occurrences outside of the requirement.

Optimal Performance

Product or Service Output

Critical to Quality (CTQ)

Defects: Service unacceptable to

customer

B A

Customer Requirement

“Sigma” Defined

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Notes: Process (A) has considerable variability or spread and is not meeting the critical customer requirement (identified by the defects). By reducing the variation of the Process (B), the process is more capable of meeting customer requirements and will lead to higher sigma performance and greater customer satisfaction.

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With performance at 2 Sigma: ONLY 69.146% of products and/or services meet customer requirements with 308,538 defects per million opportunities.

With performance at 4 Sigma: 99.379% of products and/or services meet customer requirements…with 6,210 defects per million opportunities.

With performance at 6 Sigma: 99.99966% – As close to flaw-free as a business can get, with just 3.4 defects per million opportunities.

Superior business performance target

(common goal in manufacturing environments)

Realistic business performance target for transaction / service

industry

Most companies processes perform at this

level or below prior to improvement

Sigma Scale

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Notes: Most companies measured, prior to business performance improvement, perform around a 1 to 2 sigma, which equates to meeting customer expectations only 30.9% to 69.1% of the time. These numbers are staggering and can be extremely detrimental to customer satisfaction with products and services. Although 6 Sigma is difficult to achieve in some industries, a 3.5 Sigma (meeting customer expectations 97.7% of the time) is realistic for most service related companies.

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Why “6” Sigma?

When Processes Operate at less than 6 Sigma:

 Two unsafe plane landings per day at most major airports

 500 incorrect surgical operations per week

 One hour unsafe drinking water per month

 16,000 pieces of mail lost every day

 No electricity for 7 hours per month

Even if your goal is 99.0% quality… Your results would be:

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 Lean Six Sigma is a framework to improve performance

 Lean Six Sigma is not the solution for everything

 Lean Six Sigma does apply to every function and business

 Lean Six Sigma is not just about statistics

 Lean Six Sigma is about Business Performance

 Lean Six Sigma is not new work

 Lean Six Sigma is a better way to work

Lean Six Sigma – What it is and What it is not

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Applying Lean Six Sigma

Lean Six Sigma can be applied to any process problem to achieve significant improvement results. The following are a few examples…..

Results After Applying Lean Six

Sigma

Application of Lean Six Sigma

Core Process Area

Operations - Claims Payment

(Insurance Provider)

 Reduced claims eligibility determination errors to 5%

 Saved over $1 MM per year in cost avoidance dollars

 Inaccurate determination of claims eligibility occurred 26% of the time resulting in a loss of $1.1 MM per year.

 Applied Lean Six Sigma to identify root causes of claims eligibility determination errors.

HR - Staffing (Employee Benefits

Provider)

 Increased employee retention by 20% utilizing exit interview data

 Applied Lean Six Sigma to identify root causes of high employee turnover and loss of high potential employees.

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Applying Lean Six Sigma

Results After Applying Lean Six

Sigma

Core Process Area

Application of Lean Six Sigma

Sales (Vehicle Service Contract

Provider)

 Increased sales volume by 40%

 Increased revenue by 35%

 Sales run rate data indicated by year end there would be a 110,000 shortfall between actual contract sales volume and the sales volume goal.

 Applied Lean Six Sigma to identify root causes of reduced sales volume.

IT - QA/Testing (Software

Development Company)

 Extended cycle time of the software bug fixing process drove increased costs of releasing a new software product.

 Utilized Lean Six Sigma to identify drivers of extended cycle time.

 Reduced average bug fixing process time from 16 to 5 business days

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Companies Deploying Lean Six Sigma (a sample)

Motorola

Allied Signal

General Electric

Sony

Honda

Maytag

Raytheon

Bombardier

Canon

Polaroid

IBM

American Express

Dow

Lockheed Martin

Texas Instruments

DuPont

Toshiba Fidelity Investments

Johnson & Johnson

Bank of America

Nokia

Digital Electronics

Kodak

Jaguar

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Lean Six Sigma Training

Lean Six Sigma Overview

Lean Six Sigma Roles

Lean Six Sigma Improvement Methodologies

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Process Management Kaizen DMAIC DFSS

Just Do It

• Problem identified and solution is known

• Implement a fix and establish a dashboard to continuously monitor process

• Process performance is unknown or not understood

• Implement a process monitoring dashboard to decide what to do next

• Problem identified and solution is unknown.

• Small in scale or urgency needed for process improvement

• Initiate 2-5 day Kaizen Event to analyze the process and implement improvements

• Existing process is not meeting customer requirements or business objectives

• Initiate a DMAIC project to identify root causes of the problem and initiate breakthrough improvements

• New product or process needs to be designed or significant problems to current process exist

• Initiate DFSS project to design processes to meet customer requirements

Types of Improvement Methodologies

Lean

• Process is inefficient and contains wasteful activities

• Initiate a Lean project to identify non value-add activities and remove waste from the process

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“Process Management” and “Just Do It”

Process Management

 Manage processes more effectively by the collection, display, and evaluation of process data.

 Data is important in that it fuels the various problem solving approaches, specifically the ability to execute Lean Six Sigma projects.

Just Do It

 Pinpoint process problem

 Solution(s) already known

 Implement solution(s)

 Measure performance (ongoing Process Management)

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A Kaizen Event is a very concentrated team- oriented effort to rapidly improve the performance of a process.

Kaizen Event

 Team effort is coordinated over a brief period of time – typically no more than 5 days.

 A Kaizen Event can be very chaotic for a short period until solutions can be implemented as numerous and major improvements will be implemented at the same time.

 Kaizen involves deliverables and activities prior to and right after the Kaizen Event that must be completed to ensure successful execution.

“Kaizen” Events

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“Lean”

Lean is utilized for the following purposes:

 To reduce or eliminate capacity constraints of the process

 To reduce the lead time of the process

Step 1 Step 2 Step 3 Step 4

Bottleneck

Inputs Outputs

2 Days 10 Days 4 Days 6 DaysInputs Outputs

=22 Days

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“DMAIC” and “DFSS”

 Define  Measure  Analyze  Improve  Control

 Define  Measure  Analyze  Design  Verify

Continuous Process

Improvement (DMAIC)

CTQ Tree

ID Root Causes that drive process performance

Design for Six Sigma (DFSS)

QFD

Optimized Design across processes

Methodology and Primary Focus of Each Discipline

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Process Management Kaizen

DMAIC

DFSS

Just Do It

Selecting the Lean Six Sigma Methodology

Lean

Process performance understood?

Can the problem be

solved in less than 5 days? Is it a

process flow / cycle time problem?

Is it a variation /

defect driven problem?

Is a new process or redesign

required?

Is the solution to

the problem simple & known?

Start

Yes

No

Explore Other Methodologies

No

No

No

No

No

Yes

Yes

Yes

Yes

Yes

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Improvement Techniques – Lean and Six Sigma

Combining Lean and Six Sigma is Best in Class

Six SigmaLean

Effect

Cause A

Cause D

Cause C

Cause B

Quality and Efficiency Improvement

Efficiency Improvement

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Lean Six Sigma DMAIC Methodology Defined

DMAIC is a Common Lean Six

Sigma Problem Solving

Methodology

ANALYZE “Identify root cause for performance shortfalls”

CONTROL “Monitor new

processes or products”

IMPROVE “Identify and implement

solutions”

MEASURE “Measure current

performance”

DEFINE “Identify customer

requirements”

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Notes: The focus of this course is the Lean Six Sigma DMAIC Methodology.

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Define Measure Analyze Improve Control

Project Charter Project Management

Project Plan Process Definition

SIPOC As-Is Process

Map Quick Win

Identification Stakeholder

Management Stakeholder Map Stakeholder

Management Plan Communication

Plan Voice of Customer

Customer Identification

VOC Research Plan

Kano Analysis CTQ Identification

 Root Cause Analysis Affinity Diagram Fishbone Diagram

and/or 5 Why’s Lean Process

Analysis Lean Tools and

Measures Graphical Data

Analysis Histogram Pareto Chart Box Plots Correlation

Analysis Statistical Data

Analysis Linear Regression Multiple

Regression Root Causes

Identified Quick Win

Identification

Identify Measures X/Y Matrix

Data Collection Operational

Definitions Measurement

Systems Analysis (MSA)

Data Collection Plan

Describe and Display Data Histogram Pareto Chart Pie Chart Run Chart Control Charts

Baseline Performance Sigma

Performance Yield Process

Capability Quick Win

Identification

Identify and Select Solutions Generate Solutions Benchmarking Solutions

Prioritization Matrix Solution Selection

Matrix To-Be Process Map

Financial Impact of Solutions Cost/Benefit Analysis

Risk Planning and Testing Failure Modes and

Effects Analysis (FMEA)

Pilot Plan Implement Solutions

Multi-Generational Product Plan (MGPP)

Implementation Plan Stakeholder

Management Project Storyboard

Process Control Control Charts Process

Monitoring Plan Dashboard

Response Plan Project

Documentation Process

Procedures Replication

Opportunities Solution Transfer

Plan

Key DMAIC Project Deliverables

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Lean Six Sigma Training

Lean Six Sigma Overview

Lean Six Sigma Roles

Lean Six Sigma Improvement Methodologies

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Champions

Black Belts and Green

Belts

Master Black Belts

Process Owners & Project Sponsors Projects

Project Team Members and

SMEs

Collaborative Effort is the Key

Lean Six Sigma Roles

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Notes: Roles are structured to support project success and drive business performance results. It is critical to gain agreement of roles and time commitment early so teams can establish chemistry and focus on project deliverables.

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Champions / Executive Leadership

 Monitors the external and internal factors affecting the business

 Defines business strategy

 Communicates the plan for business success

 Champions Lean Six Sigma vision

 Establishes improvement priorities and targets

 Provides and aligns resources (Sponsors, Black Belts / Green Belts), ensures cross-functional collaboration

 Establishes accountability for results

 Role modeling appropriate behaviors, change leader

 Integrates Lean Six Sigma into business direction & plan

 Markets Lean Six Sigma program and results

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Process Owners

 Assists in identifying potential Lean Six Sigma projects

 Approves and supports projects

 Provides resources to serve as team members and subject mater experts (SMEs) on projects

 Approves changes in project scope and removes barriers

 Owns the solution delivered by the project team

 Responsible for supporting implementation of improvement actions

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Notes: In many cases the Process Owner and Project Sponsor are the same person supporting the project.

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Project Sponsors

 Provides and aligns resources (Black Belts / Green Belts, Team Members), ensures cross-functional collaboration

 Establishes improvement priorities, targets and accountability for results

 Role modeling appropriate behaviors, change leader

 Ensures project is aligned with department and strategic objectives

 Approves all phases of Lean Six Sigma projects

 Ensures project deliverables are being maintained and project is on time and on budget

 Approves changes in scope of the project, removes barriers

 Markets Lean Six Sigma program and results

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Notes: In many cases the Process Owner and Project Sponsor are the same person supporting the project.

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Master Black Belt

 Part-time or full-time position

 Provides expertise on Lean Six Sigma tools and techniques, including project management and change management

 Provides strategic direction to leadership and project team

 Identifies projects critical to achieving business goals

 Is ultimately accountable for project success

 Serves as main champion during change implementation

 Identifies, trains, coaches and evaluates Black Belts / Green Belts and Team Members

 Ensures cross-functional & cross-team collaboration

 Acts as Lean Six Sigma advisor to Champions, Sponsors and Process Owners

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Black Belt

 Full-time position

 Provides direction and leadership for project team, manages inter-project communications

 Delivers results through application of Lean Six Sigma methodologies

 Provides skills training when needed

 Accountable for reporting project progress and coordinating communication to project stakeholders

 Maintains all documentation from project, prepares and submits deliverables

 Manages implementation of solutions, ensures transition of improved process to the business

 Acts as a change catalyst 39

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Green Belt

 Part-time position

 Provides direction and leadership for project team, manages inter-project communications

 Delivers results through application of Lean Six Sigma methodologies

 Provides skills training when needed

 Accountable for reporting project progress and coordinating communication to project stakeholders

 Maintains all documentation from project, prepares and submits deliverables

 Manages implementation of solutions, ensures transition of improved process to the business

 Acts as a change catalyst 40

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Project Team Members

 Part-time position

 Team player in application of Lean Six Sigma methodologies

 Provides expertise and feedback to the project team

 Is responsible for tasks within the team action plan

 Delivers regular updates to team on status of action steps

 Acts as a change catalyst

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Notes: In many organizations Project Team Members are referred to as “Yellow Belts”.

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Subject Matter Experts (SME)

 As-needed position

 Provides subject matter expertise and feedback to the project team

 Acts as a change catalyst

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Finance Analysts (also a SME)

 Part-time role

 Responsible for providing financial support to Lean Six Sigma deployment

 Provides standard, consistent guidelines for project valuation

 Provides financial savings forecast for potential projects

 Estimate project savings during the project execution

 Track / validate actual project savings after project closure

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Project Status Phase

Potential Defined

Define

Active

Measure Improve / Implement

Control

Realization

Ty pi

ca l L

ev el

o f E

ffo rt Champion/Sponsor

Black Belt / Green Belt

Define Project

& Scope

Select Black Belt/Green

Belt

Project Team

Kickoff

Develop, Sell, Pilot, and Implement Solutions

Standardize and Replicate Solutions

Master Black Belt

Analyze

Fi na

l P ro

je ct

V al

id at

io n

Process Owner

Project Team In

iti al

P ro

je ct

V al

id at

io n

(B y

B B

o r G

B )

Pr oj

ec t A

ut ho

riz at

io n

(A ss

ig ne

d to

B B

o r G

B )

DMAIC Project Deployment Effort Required

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What you learned during this lesson:

Summary of Lesson

 Understanding what Lean Six Sigma is

 Introduction to the various Lean Six Sigma Improvement Methodologies

 Understanding of what the Lean Six Sigma Roles and Responsibilities are

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End of Lesson: Lean Six Sigma Introduction

Lean Six Sigma Training

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Define Phase

Lean Six Sigma Training

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Define Phase Overview

Lean Six Sigma Training

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Define establishes the project scope and boundaries, the problem the team is improving and the goals that will be achieved once improvements have been implemented, the process that the team is improving, and the customer requirements of the process.

Define Phase Introduction

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 Develop Project Charter for Business Problem/Case, Roles and Project Plan

 Key Characteristics of Effective Teams

 Document and Understand the Current Process

 Identify Quick Win Opportunities

 Understand How to Manage Stakeholders

 Identify Customer Requirements (CTQ’s) through Voice of Customer (VOC)

Voice of Customer Voice of

Customer

ANALYZE

CONTROL

IMPROVE

MEASURE

DEFINE

Define Phase Overview

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Define Phase Deliverables

Define Measure Analyze Improve Control

Project Charter Project Management

Project Plan Process Definition

SIPOC As-Is Process

Map Quick Win

Identification Stakeholder

Management Stakeholder Map Stakeholder

Management Plan Communication

Plan Voice of Customer

Customer Identification

VOC Research Plan

Kano Analysis CTQ Identification

 Root Cause Analysis Affinity Diagram Fishbone Diagram

and/or 5 Why’s Lean Process

Analysis Lean Tools and

Measures Graphical Data

Analysis Histogram Pareto Chart Box Plots Correlation

Analysis Statistical Data

Analysis Linear Regression Multiple

Regression Root Causes

Identified Quick Win

Identification

Identify Measures X/Y Matrix

Data Collection Operational

Definitions Measurement

Systems Analysis (MSA)

Data Collection Plan

Describe and Display Data Histogram Pareto Chart Pie Chart Run Chart Control Charts

Baseline Performance Sigma

Performance Yield Process

Capability Quick Win

Identification

Identify and Select Solutions Generate Solutions Benchmarking Solutions

Prioritization Matrix Solution Selection

Matrix To-Be Process Map

Financial Impact of Solutions Cost/Benefit Analysis

Risk Planning and Testing Failure Modes and

Effects Analysis (FMEA)

Pilot Plan Implement Solutions

Multi-Generational Product Plan (MGPP)

Implementation Plan Stakeholder

Management Project Storyboard

Process Control Control Charts Process

Monitoring Plan Dashboard

Response Plan Project

Documentation Process

Procedures Replication

Opportunities Solution Transfer

Plan

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End of Lesson: Define Phase Overview

Lean Six Sigma Training

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

Project Charter Development

Project Selection

Define – Project Charter

Lean Six Sigma Training

Effective Teams

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By the end of this section, you will be able to:

 Learn why developing a Lean Six Sigma project selection criteria is important

 Learn how to select Lean Six Sigma projects

Overview – Objectives – Key Topics

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Why Establish a Lean Six Sigma Project Selection Process?

 Ensure all business process issues from all possible sources have been incorporated

 Ensure alignment of potential improvement ideas with business and customer satisfaction goals

 Resource and time constraints require the business to work on the most important issues first

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Select key improvement areas that

will drive key performance indicators

(KPIs), strategy, and improve customer

satisfaction

Brainstorm potential projects

Prioritize potential projects

Select projects by consensus of business

leaders

Active Projects Initiatives

Key Improvement Areas

A B EC D

Potential Projects ________ ________

Prioritize Prioritize Prioritize Prioritize Prioritize

Potential Projects ________ ________

Potential Projects ________ ________

Potential Projects ________ ________

Strategy

Customer Requirements

Core Processes

KPIs

Key Performance Indicators

KPIs

Potential Projects ________ ________

Project Identification

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L M H

Understanding of How to Solve the Problem

B us

in es

s or

C us

to m

er Im

pa ct

“Boiling the Ocean”

“Just Do It”

“Looking Good”

“Why Bother?”

H

M

L

Quick Wins

Lean Six Sigma

Projects

What Makes a Good Lean Six Sigma Project

Step 2: Project Identification

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High potential Lean Six Sigma opportunity, develop Project Charter

Potential Lean Six Sigma opportunity

Low potential Lean Six Sigma opportunity

Prioritized list of Potential Projects

1

4

5

2

6

3

9

10

12

147

11

13

21

17

18

15

16

20

19

Low Medium High

Impact on Key Business Drivers

Lo w

M ed

iu m

H ig

h

Fi na

nc ia

l I m

pa ct

Step 3: Prioritize Potential Projects

8

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Lean Six Sigma Projects Selected

Low Medium High

Impact on Key Drivers

Lo w

M ed

iu m

H ig

h

Fi na

nc ia

l I m

pa ct

Step 4: Select Projects

21

17

18

15

16

20

19

Next Step: Assign Black Belts / Green

Belts to the Projects and Complete the Individual Project

Charters

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What you learned during this section:

Summary of Section

 Understand why developing a Lean Six Sigma project selection criteria is important

 Understand how to select Lean Six Sigma projects

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

Project Charter Development

Project Selection

Define – Project Charter

Lean Six Sigma Training

Effective Teams

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By the end of this section, you will be able to:

 Understand what a project charter is and why it’s important

 Learn the steps and components for drafting a project charter

 Learn the tips and traps for drafting each component of a charter

 Learn how to calculate estimated project benefit

 Gain experience applying effective criteria to developing the charter

 Learn how to identify when you need to change your project scope

Overview – Objectives – Key Topics

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A project charter is a document that defines the project initiative. It provides purpose, focus and goals for an improvement project team.

 Defines what is expected of the team  Clarifies the desired outcomes of the project  Keeps the team focused  Aligns the team with organizational objectives  Transfers the project from the Sponsor to the

improvement team

Definition:

Purpose:

Definition and Purpose of a Project Charter Project Charter

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Notes: The project charter is the first deliverable a project team will undertake. The first draft of the project charter is completed by the Sponsor, Master Black Belt, and Black Belt / Green Belt. Once the project is initiated, the project charter is owned by the project team. The Sponsor will continually provide input and approve elements of the project charter throughout the project. A project charter is often referred to as a “living document”, since it is continuously updated throughout the engagement of the project.

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 Name the project  What is the business unit being impacted?  Identify the project primary resources  What is the timeline for the project?  When was the charter revised?

 How will this project drive strategic initiatives and goals?  Why is it important to do now? Why is it a priority?  What customer (s) will benefit from this project (may also

include internal customers) and how?

Business Case

General Information1. Project Overview

2. Project Description

 What problem is the project addressing?  Where and when does the problem occur?  What are the defects? (not meeting customer expectations)

Problem Statement

Elements of a Project Charter

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2. Project Description (continued)

 What are the high level goals?  What are the goals for the project? Starts with a verb (i.e.,

reduce time; eliminate defects; control costs; increase revenue).  Include measurable targets  How will we know if this project is successful?

Project Goals

 What is the primary area or process that the project will be focused on?

 What process(s) / department(s) are included in the project?  What process(s) / department(s) are excluded in the project?  What are the boundaries of the process we are improving?

Process start point? Process stop point?

Project Scope

 What are the potential dollar benefits from the project?  Separate hard savings (cost reduction, increase in profits) from

soft savings (cost avoidance, customer retention)

Estimated Benefit ($$)

Elements of a Project Charter

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 Determine people who will be involved in the project  Their function in the business (i.e. VP of Sales, Risk

Manager, Customer Service Representative)  Their role on the project (Champion/Sponsor, Master Black

Belt, Black Belt / Green Belt, Team Member, Subject Matter Expert/SME, Financial Analyst)

 List the anticipated amount of time the resource will spend on the project (hours per week)

 Identify other resources that may be required; such as contract IM/IT help, outside consultants, market research, etc.

 Includes ad hoc members such as HR, IM/IT, Finance

Project Resources

 Complete a preliminary, high-level project plan with start & completion dates for each phase

Project Milestones

3. Project Resources

4. Project Milestones

Elements of a Project Charter

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Notes: Resources should be approved by the Champion (and/or Sponsor) and direct managers of the employees that will participate on the team prior to project kick-off. Guidelines for Milestones: Dates should be tied directly to the DMAIC phases. Project plan and timeline should be aggressive but realistic. Should be approved by all team members and Champion (and/or Sponsor) and updated regularly.

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 Defines the project name  Clearly distinguishes the project from other projects  Uses a name that is easy to remember

 Documents the project primary area of focus and resources assigned

 Identifies the timeline of the overall project

 Documents each time the charter is revised

Project Overview

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 Explains/validates the project

 Defines the “value-add” of the project  Explains the rationale for doing the project  Describes why it is important to the organization to do this

project now?  Indicates how internal/external customers will benefit

 Describes potential consequences of not doing the project

 Indicates the link between the project and current business goals

Project Description – Business Case

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Notes: The business case describes the project and communicates the rationale for doing the project. Typically, the business case is one area of the project charter that usually does not get revised or modified throughout the life of the project.

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Pharmaceutical Provider

Pharmaceutical publications generate extensive publicity and marketing opportunities for our most important drugs. These publications need to be released to the market place within crucial timelines from when the drugs are to be sold. Currently, these publication releases are very time consuming and are not being released until long after the new drugs have been distributed. This leads to loss of revenue due to the initial and crucial advertising opportunities when the drugs are initially distributed.

Claims Processing Center

The Customer Inquiry process is an important touch point with our customers. Therefore, one of our strategic objectives is to ensure the customer inquiry process is consistent in meeting our customer’s needs. Customers have indicated that our customer inquiry process needs improvement. Currently, there is no consistent approach or standard to handling customer inquiries. The handling and response to customer inquiries varies a great deal from one customer service representative to another. This lack of consistency leads to inaccurate handling of customer inquiries, rework, increased customer complaints, and ultimately lost customers.

Telecommunications Provider

Customer survey results indicate that the timeliness of installing additional phone lines is critical to satisfaction for our large business customers. Our large business customers are our most profitable customer segment, therefore, meeting their requirements for the installation process is critical to our ability to meet our annual profitability goals. Currently our installation process is meeting customer requirements only 50% of the time. If we do not improve the timeliness of the installation process, we will continue to receive customer complaints, lose customers, and lose revenue.

Business Case Examples

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Notes: The business case should describe the broad areas of the project and answer the question of why the project should be conducted. The business case should be written in such a way that it creates a compelling case for why the organization needs to do this project now.

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 Identifies what problem the improvement project is addressing  Usually describes the “pain”, issue or problem  Can also describe an opportunity  Should be measurable

 Identifies where and when problems occur

 Defines what is not meeting customer expectations

 Describes the magnitude and impact of the problem  Quantifies how large the problem is  Describes the impact presented by the problem

Project Description – Problem Statement

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Notes: We recommend including the baseline performance and capability (entitlement) of your current process in the problem statement.

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Tips:  Validate problem is based on data vs. perception or “gut feel”

 Ensure the customers of the process and the organization think working on this process is valuable and necessary

Traps:  Prejudging a root cause within the problem statement

 Including a solution in the statement

 Writing a statement that is too narrowly defined or too broadly defined

Problem Statement Tips and Traps

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Pharmaceutical Publications

During the past year, publications have increased by a rate of 20% per month. The time it takes to get a publication released is approximately 4 months. In addition, there are on average 4 drafts of each publication that are created before it is approved for release. These problems lead to slow market distribution and could lead to lost revenue if the publication is released too late to have a positive impact on the new drug sales.

Claims Processing Center

Customer inquiries account for 65% of incoming claims calls. Currently, our response time to these inquiries varies from 2 hours to 5 days. In addition, approximately 10% of inquiry calls are call backs from customers who have not received follow-up from their initial call. These problems are leading to customer dissatisfaction with our services and ultimately loss of business.

Problem Statement Example

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 Defines and clarifies the goals the project team is focused on accomplishing

 Includes measurable targets and completion date

 Starts with a verb  Eliminate defects  Reduce time  Increase revenue  Decrease costs

 If these goals are met the project is considered successful

Project Description – Project Goals

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Goal Statements Should be SMART !!

S - specific M - measurable

A - attainable R - relevant

T - time bound

Criteria for Developing Goal Statements

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Measurable Assigns a quantifiable metric

for the goal

Attainable While the goal should be a stretch goal, it should also have a high probability of

success given an assessment of the potential resources, timelines and challenges

Specific A SMART goal identifies a

specific action driving a specific outcome

Time Bound The goal has an aggressive but reasonable timeline for

meeting desired results

Relevant The project goal should be

relevant to the organizational strategy

Criteria for Developing Goal Statements

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Tips:  Should focus on the results that will drive and define project

success

Traps:  Including a solution as part of the project goals

 Assigning blame in the statement

Goal Statement Tips and Traps

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Pharmaceutical Publications  Problem Statement - During the past year, publications have increased by a rate of 20% per

month. The time it takes to get a publication released is approximately 4 months. In addition, there are on average 4 drafts of each publication that are created before it is approved for release. This problems leads to slow market distribution and could lead to lost revenue if the publication is released too late to have a positive impact on the new drug sales.

 Goal Statement - Reduce publications release time by 50% and drafts to 1 for each publication by August 30th.

Claims Processing Center  Problem Statement - Customer inquiries account for 65% of incoming claims calls.

Currently, our response time to these inquiries varies from 2 hours to 5 days. In addition, approximately 10% of inquiry calls are call backs from customers who have not received follow-up from their initial call. These problems are leading to customer dissatisfaction with our services and ultimately loss of business.

 Goal Statement - Reduce the response time <1 day and eliminate call backs from customers by January 15th.

Problem and Goal Statement Examples

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 Indicates the financial benefit of doing the project  What are the potential costs of not doing this project?  Quantify the potential financial impact and link to

business pain

 Separate hard benefits (cost reduction, profit increase) from soft benefits (cost avoidance, customer retention)

 During the front-end of a project, detailed data and information may not be available, so estimates may be required at the beginning of a project

 Updated and refined as the project proceeds and more data becomes available

Project Description – Estimated Benefit

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 One of the main goals of Lean Six Sigma is to improve the company’s bottom line financial results over the long term

 Capturing and reporting the financial benefits of the project are important to determine:  Are we getting a return for our investment of valuable resources?  Are we having an impact on our key financial performance

measures?  How process improvements affect our organization’s financial

health and overall performance

 Project benefits will be reported to the Leadership Team  The results must be verifiable and supported

Why the Estimated Project Benefit is Important

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Notes: To fully commit to and support a project, your Champion (and/or Sponsor) and other key stakeholders need to have at least a rough estimate of the projects impact. They then have an opportunity to buy into the project, or suggest revisions in scope or direction that will improve the business impact and estimated benefit.

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 Hard Benefits - Improvements that result in real and measurable cost or asset reductions.  Examples of Hard Benefits:

– Incremental revenues – Cost reductions such as fewer headcount

 Soft Benefits - Improvements that do not immediately reduce cost or assets but provide benefits through improved process efficiency, employee productivity, improved customer satisfaction, improved competitiveness, etc.  Examples of Soft Benefits:

– Avoidance of lost sales – Cost avoidance such as the need to hire 5 instead of 10

The Two Categories of Project Benefits ($$)

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Gross Hard Project Benefits

+

Gross Soft Project Benefits

Less: Project Implementation Costs

= Net Project Benefits

Net Project Benefits

Method to Calculate Estimated Project Benefits ($$)

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Hard benefits…such as:  Incremental Revenues…less Cost of

Goods Sold (COGS)  Cost Reductions

Soft benefits…such as:  Avoidance of lost sales…less COGS  Cost avoidance

Gross Hard Project Benefits

+ Gross Soft Project Benefits

Less: Project Implementation Costs

Implementation costs include...  Full-time resources assigned to the project  Consultants, contractors and temps  Other considerations for running the project Implementation costs exclude…  Direct costs of Quality resources assigned

to the project prior to implementation

Gross Project Benefits

Net Project Benefits

Project Implementation Costs

Method to Calculate Estimated Project Benefits ($$)

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Reduce costs by 30% ($50,000 annually)

Reduce rework, increase productivity per person

Reduce task time by 3 hours per week

10% increase in monthly revenues ($725,000 annually)

Reduce re-work, speeds up workflow cycle time

Reduce processing accuracy defects

Reduce costs of potential legal fees by 40% ($1.5 million annual impact)

Avoid legal costsEliminate compliance risk

20% increase in repeat business ($2 million annual impact)

Increase customer satisfaction; increase customer retention

Increase in on time delivery and installation of phone line from 80%-90%

Estimated dollar impact of improvement

($$)

Benefit of ImprovementType of Improvement

Examples of Estimated Project Benefits ($$)

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 Identifies the process the team will be focusing on improving

 Establishes project boundaries  Clarifies the process start and stop points

 Clarifies which process(s) / department(s) are included in the project

 Identifies which process(s) / department(s) are excluded from the project

Project Description – Project Scope

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Properly scoped projects are critical for success and optimal benefit so pay attention to the following tips and traps:

Tips:  Avoid scopes that are too small to justify the manpower

commitment of a Lean Six Sigma project  Avoid too large of scopes which can take the team’s focus off the

key project objective and put the success of the project at risk

Traps:  Tendency in the beginning of the project to try to do too much  Overestimating the level of resource commitment  Overestimating the willingness of our stakeholders to embrace

radical change  Assigning blame in the statement

Project Scope Tips and Traps

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Be wary of scope creep!

Allowing the scope of your project to balloon can cause a team to lose sight of the project objective and lead to project failure.

As a project’s scope increases linearly, its complexity tends to increase geometrically. It is therefore in our best interest to keep our projects as narrowly-focused as will yield significant benefits.

Scope Creep

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There is a marked tendency at the outset of a Lean Six Sigma project to attempt to do too much, to solve a problem so large and so profound that the effort involved will be enormous. We call these types of initiatives “boiling the ocean” projects, as they are likely to fail no matter how many resources are employed to work on them.

IF YOUR PROJECT...  Requires a project team of 6 or more  Requires either several pages of detailed

process mapping or process blocks which are broad and cross-functional

 Contains a problem statement which is not specific to one issue

 Has multiple Ys or customer requirements  Does not have a clear start and end point  Involves multiple Champions (and/or

Sponsors) from the highest levels of the business

 Requires more than a year of time to complete start to finish

 Encompasses multiple Lean Six Sigma projects

REDUCE THE

PROJECT SCOPE!

Guidelines to Project Scope

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A problem which occurs far less frequently in Lean Six Sigma projects than “boiling the ocean” projects, is the project that is so small in scope that it doesn’t yield significant benefits or organizational impacts. If your project is too small in scope, it may not be worth the investment of resources necessary to achieve its potential benefits.

IF YOUR PROJECT...  Is not related to a strategic business

imperative  Has little or no impact on your customers  Project savings < cost to implement  Drives improvements which could be

implemented instantly without issue  Serves only to justify “common sense”

approach to problem

INCREASE THE

PROJECT SCOPE!

Guidelines to Project Scope

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To properly re-scope your project:

 If the scope needs to be decreased: reexamine your process map, business case, and problem statement and consider breaking the project into manageable pieces

 If the scope needs to be increased: reexamine your process map, business case, and problem statement and cast your net wider for potential improvements

Changing the Scope of Your Project

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Claims Processing Center Area of Focus: New Claims Processing Process

Includes:  Claims Queue  Initial Claims  Reimbursement

Start: New claim is received from customer Stop: Claim is approved and reimbursed or claim is denied

Excludes:  Denied Claims  Customer Complaints

Pharmaceutical Publications Area of Focus: Publication Creation and Distribution Process

Includes:  Articles, Flyers, Marketing Materials  Review  Distribution

Start: Publication order is received Stop: Publication is distributed

Excludes:  Publication Planning

Project Scope Examples

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 Identifies all of the people that need to be involved on the project team  Includes both formal members and satellite team members

(members involved in critical decisions, may help on key team deliverables but not serve as a formal team member)

 Identifies the resource’s functional role (VP Sales) in the organization and their role on the project team (Champion)

 Lists the anticipated amount of time the resource will spend on the project (hours per week)

 Should be approved by the Champion and direct managers of employees that will participate on the project prior to kick-off

Project Resources

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 A high level project plan with start and completion dates for each phase

 Critical points in the DMAIC process where progress is reviewed

 Are reviewed at tollgate reviews

 Negotiated with Champion/Process Owner based on  Scope of project  Complexity of project  Existence of relevant data  Amount of resource allocation

Project Milestones

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Notes: Guidelines for Milestones: Dates should be tied directly to the DMAIC phases. Project plan and timeline should be aggressive but realistic. Should be approved by all team members and Champion and updated regularly.

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 Most projects evolve, few are cast in stone from the beginning so the charter is a living document

 In each phase of DMAIC as you gather more data, the information in the project charter can be further refined and updated

 Be open to revising the scope, problem statement, and goal statement as the team makes progress and learns more about the process they are improving

 Check with your Champion before making substantial changes to the charter

Things to Keep in Mind when Developing a Project Charter

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PROJECT DESCRIPTION

Business Case The Customer Inquiry process is an important touch point with our customers. Therefore, one of our strategic objectives is to ensure the customer inquiry process is consistent in meeting our customer’s needs. Customers have indicated that our customer inquiry process needs improvement. Currently, there is no consistent approach or standard to handling customer inquiries. The handling and response to customer inquiries varies a great deal from one customer service representative to another. This lack of consistency leads to inaccurate handling of customer inquiries, rework, increased customer complaints, and ultimately lost customers

Problem Statement Customer inquiries account for 65% of incoming claims calls. Currently, our response time to these inquiries varies from 2 hours to 5 days. In addition, approximately 10% of inquiry calls are call backs from customers who have not received follow-up from their initial call. These problems are leading to customer dissatisfaction with our services and ultimately loss of business

Project Goals Reduce the response time <1 day and eliminate call backs from customers by January 15th

Estimated Benefits ($$)

Approximately $500K in hard savings (line charges, vendor charges) and $1.2MM in soft savings (people time)

Project Scope Area of Focus: New Claims Processing Process

Includes: Claims Queue, Initial Claims, Reimbursement

Excludes: Denied Claims, Customer Complaints

Start Point: New claim is received from customer

Stop Point: Send notification to customer

Project Charter Example – Processing Center

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Notes: Pay particular attention to the measurable elements of the example above. The problems and benefits are concise and easily understood by the organization.

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Project Resources

Team Members Function in the Business Project Role Time Dedicated to Project (Hrs/Week)

Chris Matthews Claims Service Rep Black Belt / Green Belt 20

Donna Hillary Accounts Reimbursement Team Member 5

Jason Whitley Customer Service Rep Team Member 5

Clyde Mahoney Risk Assessment SME 2

Kristine Swanson Quality MBB 2

Suzy Maculvey VP, Claims Champion 1

Additional Support Finance, IT (resources to be named later)

Project Milestones

Milestone Phase Start Date Completion Date

Define January 1st February 14th

Measure February 11th In Progress

Analyze March 23rd April 9th - To Be Completed

Improve April 10th May 29th - To Be Completed

Control May 30th June 30th - To Be Completed

Closure July 1st August 1st - To Be Completed

Project Charter Example – Processing Center

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Notes: Pay particular attention to the measurable elements of the example above. The problems and benefits are concise and easily understood by the organization.

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Objective  Practice applying SMART criteria to various goal statements from project

charters.

Instructions  Utilize the SMART criteria to identify which of the following goal statements

on the following page are:  Specific  Measurable  Attainable  Relevant  Time Bound

 Identify which element(s) of the SMART criteria is missing, if any.  Prepare your findings.

SMART Project Charter EXERCISE

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1. Reduce credit card resolution time by 75% in 2 weeks. In addition maintain credit card resolution accuracy.

2. Improve the meeting room scheduling process.

3. Reduce failed installs by 30%

4. Achieve an 80% or greater small business customer retention rate by year end.

5. Improve profitability.

6. Reduce late and early appliance deliveries in 6 months from the project kick off date.

7. Reduce contract processing cycle time by 40% and reduce required resources by 10% by July 06.

8. Decrease costs by end of year.

SMART Project Charter EXERCISE

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Please Do Not Proceed Forward

SMART Project Charter EXERCISE

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When you see this symbol, please do not continue forward in the materials.

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1. Reduce credit card resolution time by 75% in 2 weeks. In addition maintain credit card resolution accuracy. (not attainable)

2. Improve the meeting room scheduling process. (not relevant)

3. Reduce failed installs by 30%. (not time bound)

4. Achieve an 80% or greater small business customer retention rate by year end. (no change)

5. Improve profitability. (not specific, not time bound, don’t know if it’s attainable because we don’t have enough info)

6. Reduce late and early appliance deliveries in 6 months from the project kick off date. (no quantifiable goal, by what percent?)

7. Reduce contract processing cycle time by 40% and reduce required resources by 10% by July 06. (no change)

8. Decrease costs by end of year. (not specific)

SMART Project Charter – Answers EXERCISE

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What you learned during this section:

 Understanding of what a project charter is and why it’s important

 Steps and components for drafting a project charter

 Tips and traps for drafting each component of a charter

 How to calculate estimated project benefit

 Gained experience applying effective criteria to developing the charter

 How to identify when you need to change your project scope

Summary of Section

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

Project Charter Development

Project Selection

Define – Project Charter

Lean Six Sigma Training

Effective Teams

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By the end of this section, you will be able to:

 Know the keys to successfully operating as a team

 Identify critical team roles and responsibilities

 Identify team member profiles and interpersonal styles

 Understand guidelines to communicate effectively within the team

 Understand the importance of utilizing a conflict-resolution process

 Understand team decision making methods

Overview – Objectives – Key Topics

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“SMART” Charter Project Goals and

Objectives

Clearly Identified Roles & Responsibilities Who does What

Team Procedures How does the Team Complete Deliverables

Effective Teams

Key Characteristics of Effective Teams

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 Roles and responsibilities are clear

 Members agree on how to work together and make decisions

 Members leverage differences in team member profiles and interpersonal styles

 Communication is clear and honest among the team

 Members use a conflict-resolution process

Keys to Operating as a Successful Project Team

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 Formalized team roles enables the team to effectively avoid the “too many chiefs” syndrome (too many leaders).

 Team members work more effectively when they know what is expected of them

 Having clear roles and responsibilities creates an environment of accountability

 Lack of clear roles can cause expectations to not be met which increases team conflict

 Roles that are not clearly defined lead to work overlap or significant gaps, resulting in rework or catch-up effort

Importance of Team Roles and Responsibilities

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 Black Belt / Green Belt

 Provide mentoring and Lean Six Sigma tool expertise support to team

 Validate that the team is following DMAIC process

 Facilitate team communication internally and with other teams and stakeholders

 Work with team to overcome roadblocks and sources of resistance

 Keeps project team on track, coordinates team activities

 Process Owner

 Provide input and encourage the team

 Attend critical team meetings when input on critical decisions is required

 Takes ownership for the implementation of the process improvement and is accountable for process results after implementation

Team Meeting Roles and Responsibilities

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 Team Members

 Come prepared to meetings

 Complete tasks assigned and report back to the team

 Support team and any consensus decisions by the team

 Master Black Belt

 Attend critical team meetings

 Provides guidance and coaching to the Black Belt / Green Belt

Team Meeting Roles and Responsibilities

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 Facilitator (Usually Black Belt / Green Belt, but role can be rotated)

 Creates team meeting agenda

 Guides team through agenda, tests for consensus, and clarifies discussion points

 Gather all team member’s input, ensures all are engaged and given the opportunity to participate

 Schedules, arranges and conducts meetings

 Timekeeper

 Keeps meetings focused and on track

 Helps maintain time limits on the agenda

 Scribe/Recorder

 Maintains shared files (electronic and paper)

 Records meeting minutes and action items

Team Meeting Roles and Responsibilities

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What is a team member profile?

 How individuals translate information

 How individuals accomplish key tasks

 How individuals interact with others

 How individuals influence others

 How individuals react to change

Understanding Team Member Profiles

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 Stays clear of confrontation

 Avoids difficult or challenging discussions

 Risk adverse  Calls for caution and

is often critical  Tentative or

restrained

 Often waits until the last minute to complete deliverables/tasks

 Hesitates in diving in due to fear of failure

 Works well under pressure

 Seeks alternative ideas

 Does not pay much attention to detail

 Characterized by originality and expressiveness

AvoiderCautiousProcrastinatorCreative

 Often positive about things

 One who usually expects a favorable outcome

 Requires information and data to make decisions

 Focuses on details  Often over analyzing

things

 Skilled at planning  Linear in thought

process  Enjoys the role of

“Gatekeeper”  Often completes

deliverables ahead of schedule

 Often takes control of situations

 Constantly pushing for results

 Sometimes individual goals dominate situations

OptimistAnalyzerTacticianDriver

Common Individual Behaviors

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Review the Individual Profiles among your team:

 Do individuals share common behaviors?

 If yes, should this be a concern?

 If no, should this be a concern?

 What behaviors may have a tendency to contradict each other?

 What should the team do about this?

 How can the team work effectively together given the various Individual Profiles?

Developing a Team Profile Team Profile

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 Good communication practices for all team members:

 Honest, candid team feedback

 Balance positive and negative feedback

 Support ideas with examples, information, data or pictures

 Listening actively

 Common communication mistakes to avoid:

 Inadequate time for discussion

 Faking understanding

 Not paying attention to body language

Poor or ineffective communication can hinder team effectiveness

Team Communication Considerations

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Conflict is a normal part of team development, but here are some guidelines…..

Tolerate conflict when it:  Enables ideas to be tested and built upon and is proving to be

constructive  Allows team members to gain a deeper understanding of one another  Increases creative thought  Increases involvement

Intervene to resolve conflict when it:  Team members become more concerned about “winning” the conflict

than communicating their point of view  Polarizes the team  Involves personal insult or attack  Disrespects the values of the organization

Team Conflict

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 Talk through issues until a higher-level solution is found and is supported by all team members

 Openly discuss personal differences of opinion, dealing with them directly but tactfully

 Listen carefully to each person/group’s point of view

 Clarify the core issue by separating areas of agreement from areas of disagreement, then try to build small agreements to reach a compromise

 To calm the agitation, have disagreeing team members write down their issues and ideas before discussing with the group

 Consider taking members who conflict outside of the meeting to mediate the disagreement and come to a compromise

Team Conflict Management and Resolution Techniques

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Method Description Effect Non-intervention Avoids/Withdraws from addressing

situation Does not solve problem

Smoothing De-emphasizes conflict, attempts to smooth over

Short-term solution, can resurface later

Compromising Giving up some things in exchange for getting other things

Can provide resolution, but can cause resentment

Forcing Forcing only one viewpoint High probability of conflict re- emerging, increased resentment

Collaborating Incorporates multiple viewpoints to gain commitment from all

Long-term resolution

Confronting/ Problem Solving

Examine alternatives to find resolution that meets everyone’s goals

Provides ultimate resolution

Methods to Deal with Conflict within the Team

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Decision making often requires time and effort to reach agreement within the team. There are many internal and external influences that can delay the decision making process. To assist you, the following are 5 potential options that a team can utilize in making a decision.

 Decide and Announce

 Delegate with Constraints  Consensus  Gather Input from the Team and Decide  Gather Input from Others (influencers) and Decide

Decision Making

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What you learned during this section:

 Know the keys to successfully operating as a team

 Identify critical team roles and responsibilities

 Identify team member profiles and interpersonal styles

 Understand guidelines to communicate effectively within the team

 Understand the importance of utilizing a conflict-resolution process

 Understand team decision making methods

Summary of Section

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

End of Lesson: Define – Project Charter

Lean Six Sigma Training

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

Tollgate Reviews

Meeting Planning

Project Planning

Define – Project Management

Lean Six Sigma Training

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 Understand the importance of effective project planning

 Learn tools for effective project planning

 Understand how to develop a DMAIC Milestone plan for your project

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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1. When is the project going to end?

2. What deliverables and tasks do I have to complete before the project is completed?

3. Who is going to own completion of the project deliverables?

4. How are the Lean Six Sigma deliverables and tasks linked to one another?

5. How will the team members and other project resources allocate their time to the project?

6. When are critical milestones supposed to be met?

Effective planning early in the project will help answer the following questions:

Why Invest Time Planning?

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Start Date Stop Date

Milestone A

Milestone B

Milestone C

Task B

Task A

Task C

Task D

Task E

Task F

Resources Aligned

Typical Project Planning Process

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Project planning is a set of milestones and activities that ends in specific accomplishments.

 Clear milestones and tasks

 Start and end dates for each milestone, task, and sub-task

 Resources aligned to tasks

Milestones of Lean Six Sigma

Project Planning Basics

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Milestones of Lean Six Sigma

Milestones – are key phases of the project where major deliverables are completed and key decisions are made and approved by project stakeholders and management. Each phase of Lean Six Sigma is considered a milestone.

Tasks – are the activities that are completed to reach the milestone. Tasks include Charter, SIPOC, VOC. Every project plan should also have sub-tasks. Sub-tasks are the detailed activities that the team will complete in order to finish the tasks. All sub-tasks should use a verb-noun format, e.g., complete, deliver, check, collect, etc.

Note: Both milestones and tasks/sub-tasks have start and end points to keep the team aligned to the overall project timeline.

Project Planning Basics

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Milestone

Task

Sub-Tasks

Resources Completion Dates

Predecessor

% Complete

Duration

Project Planning Elements DMAIC Project

Plan

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Project Planning Element

Definition

Resources The team members or other organizational resources who will be responsible for completing the tasks.

Duration The time in days that the milestone, task, and sub- task is planned to take. This is based on the calculation of the start date and end date.

% Complete The % complete of each milestone, task, and sub- task. (Completion % should be updated regularly as activities are completed on the project).

Predecessor The task or sub-task that proceeds the noted task (A task marked with predecessors can not be completed until the other tasks are completed).

Project Planning Elements Defined

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What you learned during this section:

 The importance of effective project planning

 Tools for effective project planning

 How to develop a DMAIC Milestone plan for your project

Summary of Section

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

Tollgate Reviews

Meeting Planning

Project Planning

Define – Project Management

Lean Six Sigma Training

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 Understand the importance of effective meeting planning

 Learn tools for effective meeting planning

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Objective  Identify effective meeting challenges and barriers in your organization.

Instructions  Identify current challenges and barriers to effective meetings in your

organization.  Prepare your findings.

Effective MeetingsEXERCISE

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Please Do Not Proceed Forward

Effective MeetingsEXERCISE

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When you see this symbol, please do not continue forward in the materials.

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Discussion

Effective MeetingsEXERCISE

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Effective meetings have the following characteristics:

 The right people participating

 Clear objectives

 Understanding of objectives before meeting begins

 Good facilitation of discussion, time, note taking

 Good amount of breaks

 Action items from meeting

 Continuation from previous meeting(s) – if needed

Meeting Planning Basics

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Agenda Template:

Task Method Owner Time Agenda Review Review Desired Outcomes & Tasks <Owner> <Time> Minutes Review minutes from previous meeting <Owner> <Time> <Task> Presentation <Owner> <Time> <Task> Review

Agreement <Owner> <Time>

Break (if needed) <Time> <Task> Discussion

Brainstorm Ideas <Owner> <Time>

Wrap/Up and Next Steps 1.Review Action Items 2.Review Next Steps

Present Agreement

<Owner> <Time>

<Project Name> Team Meeting Agenda <Date> <Time>

<Room # and/or Teleconference Information> Desired Outcomes:  <Desired Outcome>  <Desired Outcome>  <Desired Outcome>

Good Planning Starts with an Agenda Team Meeting

Agenda

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Notes: Key Agenda Elements: - Meeting location, date, time - Participants attending - Desired outcomes of the meeting - Tasks to be completed - Method to complete each task (discussion, presentation, brainstorming, review, etc) - Time and owner for each task - Action items and minutes from previous meeting

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 Meeting date, location, time, agenda with desired outcomes, and materials that will be reviewed during the meeting should be sent to participants at least 24 hours in advance of meeting

 Allow ample time for agenda planning (a solid, organized agenda is key to having a successful, productive meeting)

 If difficult or challenging topics are to be discussed, meet with participants ahead of time to get input and support for meeting objectives

 Have participants confirm participation by accepting meeting request or obtain verbal during one-on-one meeting

 Follow-up with completed tasks, next steps, and meeting minutes should be sent out to participants no later than 24 hours after meeting completion

Meeting Planning Tips

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The minutes should contain the following elements:

 Outcomes of the meeting

 Developed or updated materials

 Action items and owners

 Next steps

 Next meeting schedule – location, date, time if planned

Each meeting should be followed up with minutes which document what was discussed during the meeting and captures key action items.

Meeting Minutes

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What you learned during this section:

 The importance of effective meeting planning

 Tools for effective meeting planning

Summary of Section

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

Tollgate Reviews

Meeting Planning

Project Planning

Define – Project Management

Lean Six Sigma Training

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By the end of this section, you will be able to:

 Understand the purpose and importance of project tollgates

 Know the process and guidelines for project tollgate reviews

 Identify key deliverables required for each project tollgate review

 Understand important considerations for tollgate review planning

Overview – Objectives – Key Topics

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DEFINE

MEASURE

ANALYZE

CONTROL

IMPROVE

A tollgate review is a checkpoint that ensures completion of each phase of a DMAIC project.

Tollgate Purpose DMAIC Tollgate

Presentation

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 Sponsor (mandatory) – actively engaged in representing, supporting and questioning the data and team members.

 MBB (mandatory) – Sets expectation of tollgate process and objectives to leadership. Engaged in supporting the team as needed.

 Black Belt / Green Belt (mandatory) – leads presentation to leadership and is overall accountable for presentation development and desired outcomes of tollgate review.

 Select Team Members (optional) – selected members actively participate during review.

 Champion (optional) – actively engaged in questioning the team for completion of required tasks/objectives for each phase. Projects with cross- team dependencies would have other teams’ champions participate.

 Process Owner(s) (optional) – may attend all phases, but required for Improve and Control phases.

Who Attends the Tollgate?

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DMAIC Deliverables for Tollgates

Define Measure Analyze Improve Control

Project Charter Project Management Project Plan

Process Definition SIPOC As-Is Process

Map Quick Win

Identification Stakeholder

Management Stakeholder Map Stakeholder

Management Plan Communication

Plan Voice of Customer Customer

Identification VOC Research

Plan Kano Analysis CTQ Identification

 Root Cause Analysis Affinity Diagram Fishbone Diagram

and/or 5 Why’s Lean Process

Analysis Lean Tools and

Measures Graphical Data

Analysis Histogram Pareto Chart Box Plots Multi-vari Correlation

Analysis Statistical Data

Analysis Linear Regression Multiple

Regression Root Causes

Identified Quick Win

Identification

Identify Measures X/Y Matrix

Data Collection Operational

Definitions Measurement

Systems Analysis (MSA) Data Collection

Plan Describe and Display

Data Histogram Pareto Chart Pie Chart Run Chart Control Charts

Baseline Performance Sigma

Performance Yield Process

Capability Quick Win

Identification

Identify and Select Solutions Generate Solutions Benchmarking Solutions

Prioritization Matrix Solution Selection

Matrix To-Be Process Map

Financial Impact of Solutions Cost/Benefit Analysis

Risk Planning and Testing Failure Modes and

Effects Analysis (FMEA) Pilot Plan

Implement Solutions Multi-Generational

Product Plan (MGPP) Implementation Plan Stakeholder

Management Project Storyboard

Process Control Control Charts Process

Monitoring Plan Dashboard

Response Plan Project

Documentation Process

Procedures Replication

Opportunities Solution Transfer

Plan

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In addition to the DMAIC deliverables, teams should be prepared to review the following throughout the tollgate process:

 Open issues/barriers for project  Action items from previous tollgate  Decisions from previous tollgate  Next steps for project

Define Measure Analyze Improve Control

DMAIC Deliverables for Tollgates

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 Business Case is aligned with strategic objectives  Problem Statement and Goal Statement are clearly

defined and measurable (SMART)  Resources are identified and have been approved  DMAIC timeline is realistic

 All segments have been completed  Relationships of S-I-P-O-C are clearly defined  Process start and end points are scoped properly for

project  Segments contain enough granularity for proper scoping

and identification of relationships.

Project Charter

SIPOC

As-Is Process Map

 Process map reflects the true “as is” process Was developed and validated with subject matter experts  Is at the appropriate level of detail to highlight quick win

opportunities

Define Tollgate Planning

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 VOC research plan is documented and contains necessary detail (customers, method, information to be gathered, resources)

 Customers have been selected that can provide feedback to problem being fixed

 Clear link between customer issues to needs to CTQ’s  CTQ’s are measurable and related to problem statement

in charter

 Project plan contains all necessary milestones, tasks, and sub-tasks to complete project

 Timeline is realistic for project  Resources are aligned to tasks

VOC/CTQ’s

Project Plan

 All customer/project/individual groups have been identified  Stakeholder Map, Stakeholder Management Plan  Communication methods and timings are relevant for each

customer/project/individual group

Stakeholder Management Plan

Define Tollgate Planning

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 Ensure coordination of dependencies among all transition projects

 Share best practices/lessons learned

 Remove organizational barriers to team success

 Request funding to move forward where applicable

 Reward and recognize the team efforts

 Check for consistent understanding of the project and its objectives

 Monitor team progress for cost and schedule compliance

 Alignment to company strategy  Ensure data quality/integrity  Identify additional resource needs  Assist team with escalation of

issues and risks

Sponsor’s Guide for Tollgate Reviews

Be Prepared – Sponsor’s Tollgate Guidelines

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 Challenge the purpose and objectives of the project  Determine if project goals are achievable and realistic  Ensure alignment between business case, objectives and problem

statement  Assess the impact on stakeholders  Determine if right customers have been included in VOC  Remove barriers to success

Champions Guide for Define Tollgate Review

Be Prepared – Champions Tollgate Guidelines

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 The purpose and importance of project tollgates

 The process and guidelines for project tollgate reviews

 Key deliverables required for each project tollgate review

 Key considerations for tollgate review planning

What you learned during this section:

Summary of Section

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Notes:

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

End of Lesson: Define – Project Management

Lean Six Sigma Training

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

Process Mapping

Quick Wins

SIPOC

Process Overview

Define – Process Definition

Lean Six Sigma Training

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 Understand the levels of processes in an organization

 Learn the difference between core and enabling processes

 Understand what an organizational process model is

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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A process is defined as a repetitive and systematic series of actions or operations whereby one or more inputs from suppliers is used to

achieve an output of value to the customer (internal/external)

Input Output Process

Actions

Process Model

What is a Process?

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There are various levels to all organizational processes.

LEVEL 1 High-Level Organizational Process

LEVEL 2 Sub-Processes

LEVEL 3 Activities

LEVEL 4, 5 Procedures and Tasks

Process Levels

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Notes: There are multiple levels of process – from the highest level organizational process (30,000 foot view) to the task steps (“worm’s eye” view). Organizational Process An organizational process is a macro-process, or a bundle of several processes which result in providing the customer with a product or service. An organizational process is all the functions and sequence of activities (regardless of where they reside in the organization), policies and procedures, and supporting systems required to meet a marketplace need through a specific strategy. It includes all functions involved in the development, production, and provision of specific products or services to particular customers.

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Core Process A core process is one of the major processes required in managing the operation and providing day to day services to the customer.

These are processes that are seen as having greater value by external customers Examples: Service Claims, Develop Product

Key enabling Processes that support one or more other processes, typically by supplying indirect inputs; do not usually have direct impact on the external customer  Support the core processes and

enable a company to manage the operation and provide day to day services to the customer

 Enabling processes often direct or tune other processes

Examples: Finance, Info Technology

Types of Processes

Core Process

Sub-Process Sub-Process

E N A B L I N G

E N A B L I N G

E N A B L I N G

E N A B L I N G

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A core business process is one which is:

 Closely linked to external customers at both the beginning of the process and the end of the process

 Closely tied to the organization’s core competencies

 An integral part of the organization’s “identity” with customers/markets

 Key to achieving strategic objectives

4.0 Authorize Claim

3.0 Process Contract

5.0 Pay Claim

1.0 Develop Product

6.0 Service

Customers

2.0 Distribute Product

Criteria For Identifying Core Processes

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A key enabling process is one which:

 Typically supplies indirect inputs to the core process

 The impact, positive or negative on the core process(es) is potentially significant

 Governs or “fine tunes” the core process

9.0 Legal

8.0 Human Resources

10.0 Information Technology

7.0 Finance

11.0 Risk

Management

Identifying Key Enabling Processes

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Notes: In an organization there are many enabling processes that exist in an organization. It is important to identify the “key” enabling processes or those that are most critical or impactful to the core processes for two reasons: 1) An enabling process can have an impact on the process the improvement team is focused on improving. 2) A DMAIC project can also be conducted on an enabling process as well as a core process.

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 An organization is a chain of interwoven core and enabling processes, each of which contributes to the product or service provided to the external customer.

The Process Chain is only as strong as its weakest link

Process Chain

Your Organization

CoreCoreCore enabling enabling enabling

Internal Suppliers / Customers

Product/Process Requirements

Product/Process Outputs

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Notes: Each link represents a process, or work group within the organization. It may often be only the last link (process) that directly serves the external customer. Yet the product or service you provide to the next internal process customer has an effect on the external customer. �

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CORE PROCESSES

KEY ENABLING PROCESSES

2.1 Qualify

Customer

2.3 Complete

Census

2.2 Sell Product

1.3 Price

Product

1.2 Design Product

3.1 Review Packet

3.3 Audit

Contract

3.2 Enter

Contract

4.1 Evaluate Eligibility

4.3 Authorize

Claim

4.2 Adjudicate

Claim

5.1 Review Claim

5.3 Distribute Payment

5.2 Settle Claim

6.1 Route Inquiry

6.3 Address Inquiry

6.2 Gather

Information

7.1 Cash

Management

8.1 Manage

Employees

8.2 Recruit

Employees

9.1 Product Filing/

Approval

10.1 Manage Network

11.1 Monitor

Risk

10.2 Deliver Tech.

Solutions

4.0 Authorize Claim

3.0 Process Contract

5.0 Pay Claim

1.0 Develop Product

6.0 Service

Customers

2.0 Distribute Product

1.1 Collect Market

Data

9.0 Legal

8.0 Human Resources

10.0 Information Technology

7.0 Finance

11.0 Risk

Management

Example of Core & Enabling Process Model

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Notes:

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What you learned during this section:

 Understand the levels of processes in an organization

 Learn the difference between core and enabling processes

 Understand what an organizational process model is

Summary of Section

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Notes:

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

Process Mapping

Quick Wins

SIPOC

Process Overview

Define – Process Definition

Lean Six Sigma Training

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 Understand the relationships of a process

 Define the suppliers, inputs, process, outputs, and customers of a process

 Identify the boundaries of a process

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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 To develop a high-level view of the process

 Developing an accurate “picture” of the process is made easier by first understanding its elements

 To avoid scope creep

Purpose of Developing a SIPOC

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Effective improvement requires information from the entire Supplier-Customer Relationship

Elements Common to All Processes

Suppliers Inputs Process Outputs Customers

S I P O C

Process Map

SIPOC

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Notes: All company activities constitute a process. A process is defined as taking one or more inputs from suppliers and creating outputs, whether these are a service or product. The graphical display of these activities is known as process mapping. Understanding business processes is made easier by first identifying the key components of a SIPOC: Suppliers, Inputs, Process, Outputs, and Customers.

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The products or services resulting from a process, which address a customer’s need

Output

A process is a collection of activities that takes one or more kinds of input and creates output that is of value to the customer

Process

Materials, resources, data, information, guidelines required to execute your process

Input

The limits of a particular process, usually identified by the inputs and outputs, identifies where the process starts and stops

Boundary

Whoever receives the output(s) of your process – may be internal or external

Customer

Whoever provides the inputs to your processSupplier

SIPOC Elements

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1. Work backwards when completing the SIPOC 2. Start by identifying the customers first, then the process outputs 3. Identify the process start and stop points, then complete the remaining steps 4. Identify process steps - rapid brainstorming

 Use your sticky notes  One step per note Write big  Don’t worry about order  Don’t discuss in detail  Begin all steps with a verb

5. Finally, define the inputs and suppliers 6. The suppliers may be the customers as well

Steps to Complete a SIPOC

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Suppliers Inputs Process Outputs Customers

Customer

Collection Agency

Customer Complaint

Billing Question

Statement Question

Renewal or New Account Set-up

Credit Card Resolution

Accurate Statement

Credit / Debit to Account

Credit Card Customer

Collection Agency

Accounts Payables

Accounts ReceivableUpdate Customer Data

Start Boundary

Stop Boundary

Receive Customer Call Gather Data

Review History Identify Problem

Resolve Problem

Call Center SIPOC Example SIPOC

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Notes: In this call center example, all components of the SIPOC chain are identified and lead into the next segment, creating a visual depiction of the process stream. Only the high-level process steps are identified in the SIPOC.

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What you learned during this section:

 The relationships of a process

 The use of SIPOC to define suppliers, inputs, process, outputs, and customers of a process

 The identification of boundaries of a process

Summary of Section

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Notes:

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

Process Mapping

Quick Wins

SIPOC

Process Overview

Define – Process Definition

Lean Six Sigma Training

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 Understand the basic process mapping shapes

 Document the detailed steps and activities of a process

 Understand the concept of deployment flow charts

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Definition: A process map is the graphical representation of the steps, actions, and operations that constitute a process

Purpose: In order to control or evaluate a process the team needs to have a clear picture of the current process

Who develops it: The team works with those who perform the process itself to map out the process

Basic Process Mapping Shapes Start / Stop Point Task / Activity Decision Point Direction of Flow

What is a Process Map?

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Notes: Once the primary segments of the process are identified through the SIPOC, the team can further drill down into the detailed process steps. Detailed process mapping is necessary to fully understand the flow and tasks that occur to produce the outputs to the customer. The process mapping shapes identified above are standard for most processes, however additional shapes are available for different processes. Tips in sub-process mapping: Involve the people who work directly in the process when completing the map. Clarify the boundaries of the process first by identifying the start and stop points. Brainstorm the steps that occur between the start and stop points using verbs (Review, Determine, Contact). Combine and eliminate duplicate steps. Organize steps into logical order using the direction of flow arrows.

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 Describe how activities are being done

 Identify where a team should measure in a process to evaluate performance

 Investigate where problems might occur

 Aid in the re-design or improvement of a process

 Help all stakeholders understand their part of the process and how it fits into the process as a whole

 To perform gap analysis against regional processes or potential duplicate processes

 Aid in training new people

Process Mapping Uses

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Example of “As-Is” Process

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Basic flowchart

Deployment flowchart (“swim lanes”) Processing Administration Adjusters Payables

Start

Activity

Activi ty

End30 5

70

20

Alternate Path flowchart

Activity

Activity

Types of Process Maps

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 Indicates specific steps that occur in a process

 Indicates decision points

 Illustrates rework loops, bottlenecks, etc.

Clear start point

Clear stop point

Number each step

Represents Decision Point

1. Activity

Yes

No

Yes

No

2. Activity

3. Activity

Basic Flowchart

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Key:

Percentage of time task is done via phone or e-mail

Task

Phone

70

30 E-mail

 Indicates percentage of Time one path of a process is taken over another path

Start Activity

Activity

End30

70

Alternate Path Process Map

Activity

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Notes: In this technique, alternative “paths” are noted by split arrows. Teams can then note the relative percentages of time/incidents the process follows each path. This approach helps in the study of workload issues.

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Ordering Dept.

Processing Dept.

Delivery Dept.

Customer

Start

Activity Activity

End

Decision Activity Activity Activity

Activity Activity Activity

Decision Activity

Horizontal Deployment Flowchart

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Notes: Deployment Process Maps are useful for defining large or complex processes. The number of functions (or “bands”) are easily defined and can be layered vertically or horizontally. Initial horizontal maps are often done on walls so that time can stretch off to the right as far as necessary. Horizontal maps have the advantage that they can show the entire process in a continuous flow. There are many software solutions that can assist you in creating process maps (example: Microsoft Visio). PowerPoint can also be used to create process maps.

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What you learned during this section:

 The basic process mapping shapes

 How to document the detailed steps and activities of a process

 The concept of deployment flow charts

Summary of Section

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

Process Mapping

Quick Wins

SIPOC

Process Overview

Define – Process Definition

Lean Six Sigma Training

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 Learn how to identify quick win opportunities

 Practice applying quick win criteria

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Utilizing Lean Six Sigma techniques (i.e. process mapping) often uncovers many easy and obvious improvement opportunities. These are referred to as “Quick Wins”. Teams should be prepared to react to these opportunities and implement changes to the process.

The criteria for defining an improvement opportunity as a “Quick Win” are:

 Easy to Implement – the improvement does not require significant planning and coordination

 Reversible – the improvement is reversible (i.e. it is easy to go back to the original process)

 Fast to Implement – the improvement does not require a significant amount of time to implement

 Within the Team’s Control – the scope of the improvement is within the control of the Team or Sponsor (i.e. the improvement does not cross multiple departments/areas within the business)

 Cheap to Implement – the improvement does not require a significant amount of capital and/or resources to implement

Quick Win Opportunities Quick Win

Identification

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Notes: We also recommend using “Lean” tools to identify Quick Win Opportunities. Lean tools will be introduced later in this course.

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What you learned during this section:

 Understanding how to identify quick win opportunities

 Understanding of how to apply the quick win criteria

Summary of Section

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

End of Lesson: Define – Process Definition

Lean Six Sigma Training

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Communication Planning

Stakeholder Analysis

Define – Stakeholder Management

Lean Six Sigma Training

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 Identify the Stakeholders for the projects

 Understand how to overcome resistance to change

 Develop a Stakeholder Management Plan

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Stakeholder Management should be done early and throughout the initiative to continually influence key individuals. The process for

managing stakeholders is the following:

Identify Stakeholders

Develop Stakeholder Map

Develop Stakeholder

Management Plan

Step 1 Step 2 Step 3

The Process for Managing Stakeholders

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Anyone who is affected by the

process or product the project team is working

on.

Who is a Stakeholder?

4

Internal Customers

External Customers

Suppliers Customers

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Identify Stakeholders

Step 1

External Internal Suppliers 1. 10. 19.

2. 11. 20.

3. 12. 21.

4. 13. 22.

5. 14. 23.

6. 15. 24.

7. 16. 25.

8 16. 26.

9. 18. 27.

Identify All Stakeholders

The Process for Identifying Stakeholders Stakeholder Identification

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Lean Six Sigma will be driven by the support from key individuals throughout the organization. The project team’s communication and influence strategy needs to focus not only on the individuals engaged directly in the initiative, but those individuals who can have an impact on the success of implementation. These individuals are often referred to as stakeholders. Stakeholders include executive leadership, managers, process owners, or any individuals who have a “stake” in the outcome of the teams efforts.

Team Members

Project Sponsor Process Owner

Middle Management Executive Leadership

Front Line Employees

Enabling Functions Supplier

Stakeholder Influence

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Step 2 Develop

Stakeholder Map

Impact of Change (from the Project)

In flu

en ce

o n

Pr oj

ec t

Lo w

M ed

iu m

H ig

h

1. Place Stakeholder #s on the Stakeholder Map 2. Add Stakeholder Position

Stakeholder Position

Enthusiast

Neutral

Opponent

Low Medium High

9

4

5

6 8

3

7 6

1

2

The Process for Managing Stakeholders Stakeholder

Map

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Give those most affected by change the responsibility for implementing the change

Overcoming Resistance

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Notes: Planning to Deal with Resistance Being aware of potential areas of resistance is a critical issue for the Lean Six Sigma project team. As a team progresses through its implementation, it should continuously identify ways in which resistance could occur. One of the best ways to overcome resistance is if those impacted by the change take ownership for implementing the change. Not only does the project team have to deal with issues and consensus within the team, but it also has to seek a teamwork relationship with stakeholders, frontline employees, and managers. Ownership forces the resistance to be dealt with and resolved.

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Common Sources of Resistance

Determine Sources Of Resistance

Technical Example: Lack of skills to complete

required tasks

Cultural Example: Locked into the way it has always

been done

Political Example: Difficulty

managing power and authority

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Step 3 Develop

Stakeholder Management Plan

Great action plans identify what, why, who, when and how. Preparing your team’s stakeholder management plan will enable proactive change management. The key elements of a stakeholder management plan are:

Stakeholder Who does the team need to focus on?

Objective What is the purpose/desired outcome of the action?

Action How will the purpose/desired outcome be achieved (i.e. meeting)?

Completion Date When will the action be completed?

Owner Who is responsible for following through with the action?

The Process for Managing Stakeholders Stakeholder Management

Plan

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What you learned during this section:

 How to identify the Stakeholders for your project

 Understand methods to overcome resistance to change

 How to develop a Stakeholder Management Plan

Summary of Section

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

Communication Planning

Stakeholder Analysis

Define – Stakeholder Management

Lean Six Sigma Training

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 Understand key considerations to making communication effective

 Understand the key elements of a Communication Plan

 Develop a communication plan

 Understand how to create an effective Elevator Speech

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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The #1 Reason communication efforts fail to achieve the level of understanding and influence intended is due to:

Emails, large meetings, print announcements, and even videos alone tend to:  Be ignored  Fail to engage recipients in active thinking  Focus on “What’s in it for the company” rather

than credibly persuade “What’s in it for the individual”

Method of Communication

Effective Communication

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 Have a clear message  Involve and engage your audience  Be candid  Demonstrate, don’t lecture  Follow up

Communication of the improvement project message should be 80% Face to Face meetings

80%

20%

Face to Face Company Wide

80%

20%

Face to Face Company Wide

Project Communication

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 Organizational communication is a change agent The purpose of communication is not just to convey information, but to change behavior. Project communication should change behavior by building support of and buy-in toward the project's objectives.

 Communication is a two way process 

Listening and encouragement of feedback is critical to understanding whether project communication has been effective.

 Craft communication in the interests and language of the target audience 

To be effective, the message should be focused on the receiver of the communication’s interests in both content and context.

 Communication must be compelling and continuous 

To be compelling consider creative ways to deliver your message. To be remembered and internalized, communication needs to be continuous and consistent.

Communication Considerations

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A Communication Plan should be developed early in the project. The basic steps and components are as follows:

Target Audience:  Identify the project audience(s) - include internal and external stakeholder groups

The “What” (message):  Assess information needs - determine what groups need to know, want to know, and

expect. NOTE: Utilize project resources only on communicating information that contributes to success or where a lack of communication can lead to failure

 Identify key project messages, announcements, that need to be delivered on a recurring basis

When:  Define when communications will be provided

The Method:  Identify the best media and methods available to communicate, e.g. face to face

meetings, presentations, email - remember people absorb information in different ways

Developing a Plan – What to Include Communication

Plan

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Owner:

 Assign responsibilities for creating and delivering the various types of communications

Approval Process:

 Document the approval process needed for any of the communications

Feedback Loop:

 Create internal and external feedback loops to help evaluate the effectiveness of communications

Schedule tasks:

 Schedule the work of communications and related dependencies into the project schedule to ensure they are part of the overall plan

Update Process:

 Define a process for updating/changing the Communications Plan

Developing a Plan – What to Include

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Audience What When Method Owner Required Approval

Feedback Loop

• Team • Process owner

Project Kickoff

Project start date (June 5th)

Meeting Black Belt / Green Belt

Sponsor Plus/delta

All employees

Major Milestone Announce- ments

As completed

Email Black Belt /Green Belt

Sponsor Survey Questions

Communication Plan Example

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 Make the Communication Plan readily accessible to the project team members.

 Make sure project stakeholders buy into the Communication Plan.

 Scale the Communication Plan to fit the complexity, duration, and size of the project.

 Update the Communication Plan when significant changes occur.

 Periodically ask team members if they are getting the right information at the right time.

 Enter communication tasks in the project plan.

 Be specific when assigning communication tasks - list responsible person(s).

 Get proper approval before disseminating communication, when applicable.

Developing a Plan – For Best Results

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What is an elevator speech?

 A tool used for helping team members practice articulating the project vision, purpose and objectives in a clear, concise and meaningful way.

 It’s a simple but effective communication method to help build project support and buy-in from all members of the organization.

Elevator Speech

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Steps to develop an elevator speech for your project:

 Imagine a chance meeting of a project team member with a key project stakeholder on the elevator. The project team member has five floors (90 seconds) to articulate to the stakeholder the project vision and objectives.

 Identify the key 4-7 bullet points that should be communicated to the stakeholder while on the elevator ride. Some possible themes:

 Problem statement/opportunity

 Benefit to the organization

 Current project status

 What action others can take (show support, help communicate)

 Team members practice reciting the elevator speech so the message is delivered consistently among all members.

Elevator Speech

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What you learned during this section:

 Key considerations to making communication effective

 The key elements of a Communication Plan

 How to develop a communication plan

 How to create an effective Elevator Speech

Summary of Section

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

End of Lesson: Define – Stakeholder Management

Lean Six Sigma Training

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

How to Translate VOC into CTQ’s

What is Voice of Customer (VOC)

Who is the Customer

Define – Voice of Customer

Lean Six Sigma Training

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 Understand the definition and types of customers

 Identify and apply methods to segment customers

 Understand methods to prioritize customers

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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It is our customers who determine whether or not our products and services and our work output are considered quality or not. Therefore being focused on the customer’s wants, needs and expectations is a central focus of Lean Six Sigma.

Customer

Business/Shareholder

The Customer’s Role

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Identify Customers

 Review Charter and SIPOC

 Define customers

 Segment customers

Develop VOC

Research Plan

 Identify research methods

 Develop research plan

 Develop VOC questions

Gather Customer Issues / Needs

 Collect VOC  Organize

customer issues into needs

Translate Issues /

Needs to CTQ’s

 Translate needs into requirements (CTQ’s)

 Set specification limits

Voice of Customer (VOC) Process

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The Recipient of a Product or Service

External Product/Service

Internal Product/Service

Customer

Downstream in Process Leadership/Management Associates

Clients End-Use Consumers Regulators Brokers Shareholders

What is a Customer?

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Notes: While not every process will touch external customers directly, the more we can do �to make each process better, the more likely we’ll be able to exhibit “quality” to our customers in all we do. Remember, too, that “internal customer” partnerships are essential to smoothly-run processes.

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External Customers are groups or individuals external to the organization who receive or are affected by our products and services.

Internal Customers are groups or individuals whose ability to perform a job is impacted by the quality of products and services we provide to them, e.g., other processing departments, enabling departments (Finance), etc.

External Customers

Direct Customers

Indirect Customers

Those who receive and use our products and services.

Those who are affected by our work, or who have authority over us, but who may not actually use our products or services themselves, e.g., government agencies, stakeholders, etc.

Definitions of the Types of Customers

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A process is a chain of internal suppliers and customers, each of whom contributes to the product or service provided to the external customer.

The Process Chain is only as strong as its Weakest Link

Customer Process Chain

Your Organization

CoreCoreCore enabling enabling enabling

Internal Suppliers / Customers

Product/Process Requirements

Product/Process Outputs

Customers

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Notes: Each link represents a process, or work group within the organization. It may often be only the last link (process) that directly serves the external customer. Yet the product or service you provide to the next internal process customer has an effect on the external customer.

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 It may be necessary to segment customers so customer research is focused on the most important customers.

 Customers can be segmented by region, size, revenue, etc.

Region

Large Medium

Small

Size of Deal

Customer Segmentation

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Notes: If you have many different customers, segmenting them will help the team focus on the vital few and prioritize issues and needs (covered later in this section). Examples include: - Channel – direct vs. distribution - Regional – North vs. South - Price – high-end vs. low-end

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 A process may have many customers

 It is difficult to address all the needs of all the customers

 There is a need to focus on the vital-few key customers

 Customers who purchase the majority of products/services (external)

 Customers who provide the most revenue (external)

 Customers who use your output at a critical juncture in their process (internal)

 Once needs are addressed for the vital few, the project team can then focus on the needs of the next layer of customers

Why is it necessary to prioritize customers?

Prioritizing Customers

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Prioritization Matrix – Credit Union Example

5 = Major Impact of Customer on Criterion. 3= Moderate Impact. 1= Small Impact. 0= No Impact

Customer Criteria Total Large Dollar Transactions

Large Volume Transactions

Loans Certificates of Deposit

Money Market Funds

Large Commercial Customers

5 5 5 5 3 23

Small Businesses

1 1 3 0 1 6

Retail Customers

3 5 5 1 1 15

Elderly / Disabled

0 0 1 5 5 11

Tellers 0 3 1 1 1 6 Federal Examiners

1 0 0 1 1 3

Prioritizing Customers

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What you learned during this section:

 The definition and types of customers

 Methods to segment customers

 Methods to prioritize customers

Summary of Section

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

How to Translate VOC into CTQ’s

What is Voice of Customer (VOC)

Who is the Customer

Define – Voice of Customer

Lean Six Sigma Training

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 Understand how to develop a VOC research plan

 Understand methods to collect data around customer requirements

 Develop effective VOC questions

 Learn how to organize customer feedback into customer needs

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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 A philosophy and approach of understanding the “voice” of customers through continuous research

 The term used to describe stated or unstated requirements that customers have of products or services

Voice of Customer (VOC) is:

Product/Process Outputs

What do customers want? How do customers communicate with us? Why should we listen to our customers?

What is most important? How are we doing?

Where can we improve?

Voice of Customer Defined

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Notes: Understanding customers requirements is critical if real achievement of project success is to be validated. Voice of Customer is a useful method for identifying the customers of the process (either internal or external) and their requirements.

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Identify Customers

 Review Charter and SIPOC

 Define customers

 Segment customers

Develop VOC

Research Plan

 Identify research methods

 Develop research plan

 Develop VOC questions

Gather Customer Issues / Needs

 Collect VOC  Organize

customer issues into needs

Translate Issues /

Needs to CTQ’s

 Translate needs into requirements (CTQ’s)

 Set specification limits

Voice of Customer (VOC) Process

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Focus Groups

Used to pull together a group of similar customers with a broad range of opinions.

Surveys

Used as a comprehensive data gathering technique. Very valuable in gathering and prioritizing requirements.

Interviews

Used to ask probing questions from one-on-one sessions with customers. Can be structured or informal.

Market Research

Used to gather competitive comparison data. This is particularly useful if you want to compare strengths/weaknesses to competitors.

Be a Customer

Used to gain first hand experience from your products and services as your customers experience them.

Customer Complaints

Used to gather initial issues with products/services. Usually come from a small percentage of customers so do not necessarily represent majority of customers.

Research Methods to Collect VOC

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Complaints from Customers Feedback from Internal Associate

Qualitative InformationFrom

To QuantitativeInformation

Written Surveys Telephone Interviews

VOC Progression

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Notes: The VOC process is the progression of taking qualitative feedback from customers and translating those into quantitative requirements. This process will lead the team through the necessary steps to ensure the requirements of the organization’s products and services are documented.

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1. Start Broad - What is important?

2. Get Specific – What does that mean?

3. Prioritize – How important is this?

Complaints Requests Observations

Focus Groups  Interviews

Surveys Requirements

Needs

Issues

The “Funnel” Effect for VOC Research

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Elements of a Customer Research Plan

Customer Segments to be Contacted

Identifies the groups (internal and external) that VOC data will be collected from

Information to be Gathered

Identifies the specific VOC questions to be used for each group

Data Collection Method

Identifies the medium for collecting the VOC (face to face interview, focus group, survey)

Customers to Contact

Identifies the # from each group (external) or specific individuals (internal) that data will be collected from

Project Team Owner

Assigns who on the project team is responsible for collecting the VOC

VOC Completed

Tracks when the VOC is complete

Develop Customer Research Plan VOC Research

Plan

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Notes: Conducting customer research can be very time consuming for a project team. The time to complete the research and gather all of the input depends on: The number of customers being researched The availability of the customers The number of team members who will conduct the research The time available of the team members Each element of the Customer Research Plan must be documented and agreed to by the team and Sponsor/Champion.

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 Clearly define the objectives of the survey (use qualitative information for developing objectives)

 Draft questions that will meet objectives

 Order questions appropriately (funnel from broad to specific)

1. Start Broad - What is important? 2. Get Specific – What does that mean? 3. Prioritize – How important is this?

 Use a mix of open and close ended questions

 Test the questions with a small sample of customers, then review to ensure objectives are being met

Developing VOC Questions

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Notes: Pitfalls with developing questions: Being too broad with questions can lead to non-measurable responses. However, being too specific can bias or lead customer responses or lead to narrow issue identification.

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Sample Open Ended Questions:

 What are the product/service features that are most important to you? (primary and secondary)

 What are your expectations relative to delivery dates?

 How do we compare to our competitors?

 What are some additional features that would enhance the product or service?

Examples of Effective Questions to Gather VOC

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Notes: Open-Ended Questions: Initial questioning to ensure interviewee isn’t being led to specific responses. Allows the interviewer to probe for more specific answers. Good for gathering exact responses to be used for presentations

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Sample Close Ended Questions:

 Would you continue to buy other products/services from us?

 Did we meet all of your service expectations?

 How important are the product/service features you mentioned: 1. Not important at all 2. Below average importance 3. Average importance 4. Above average importance 5. Extremely important 6. Not Applicable

Yes No

1 2 3 4 5 6 Not Satisfied Moderately

Satisfied Very Satisfied Not Applicable

Examples of Effective Questions to Gather VOC

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Notes: Close-Ended Questions: Allows the interviewer to rank specific responses to questions. Good for gathering rankings to be used for presentations.

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Objective  Practice identifying bias in questions.

Instructions  Review the questions below and determine how each one is biased.  Prepare your findings.

1. What service qualities, such as quick loan approval or excellent customer service, are most important to you (external)?

2. When did you mail in your application (external)?

3. What department caused the most problems in your ability to process the application (internal)?

4. What % of the time do you normally see the following types of errors (internal)?

Determining Question BiasEXERCISE

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Please Do Not Proceed Forward

Determining Question BiasEXERCISE

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When you see this symbol, please do not continue forward in the materials.

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1. What service qualities, such as quick loan approval or excellent customer service, are most important to you (external)?

Question contains a narrow list of qualities. Neither may be the most important to the customer.

2. When did you mail in your application (external)?

Too much subjectivity. Difficult to remember actual time for customer.

3. What department caused the most problems in your ability to process the application (internal)?

Leading. There may have not been any problems. Also, focusing blame on a particular group.

4. What % of the time do you normally see the following types of errors (internal)?

Over-generalization. Doesn’t get to the requirement or expectation. Not based on actual data – assumptions.

Determining Question Bias – AnswersEXERCISE

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Identify Customers

Develop VOC

Research Plan

Gather Customer Issues / Needs

Translate Issues /

Needs to CTQ’s

 Review Charter and SIPOC

 Define customers

 Segment customers

 Identify research methods

 Develop research plan

 Develop VOC questions

 Collect VOC  Organize

customer issues into needs

 Translate needs into requirements (CTQ’s)

 Set specification limits

Voice of Customer (VOC) Process

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 Qualitative data is different, it requires translation

 Customer data can be overwhelming

 Different voices heard at the same time

 Customers often have difficulty in expressing requirements

 Different “voices” from the same customer

 Bias by the collector

Challenges and Key Issues with Gathering VOC

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Key Steps in Translating Qualitative Customer Feedback into Needs

1. Collect VOC

2. Probe for clear understanding

3. Identify key issue

4. Organize issues into central categories/themes

5. Translate into customer need in terms that make sense to the organization

Organize Customer Feedback

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Organization Tool: Affinity Diagram

Customer ResponseCustomer ResponseCustomer Response

Customer Response

Customer ResponseCustomer Response

Customer Response

Customer Response

Customer ResponseCustomer ResponseCustomer ResponseCustomer ResponseCustomer Response

Customer ResponseCustomer ResponseCustomer Response

Customer Response

Customer Response

Customer Response

Customer ResponseCustomer Response

Customer Response

Customer Response

Issues -

Hold Time Inaccurate Statement Phone

Transfers Process DifficultIssue Category -

Organizing Customer Feedback

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Notes: Once VOC has been gathered, it is necessary to organize the feedback from the customers. Categorizing the issues will help bring out central themes for the team to focus on. Instructions for Affinity Matrix: Using raw VOC issues/feedback, write down the feedback on sticky notes. Post the stick notes to a white board or flip chart paper. Once completed, sort issues into 4-8 related groups. Create a summary issue category for each issue group. Make sure everyone agrees to headings.

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Examples of Translating Qualitative Information into Needs

Customer Issue Customer Need

“On hold too long”

“My statement is inaccurate”

“I keep getting transferred”

Reduce Hold Time

Statement Accuracy

Resolve Problem 1st Time

Organize Customer Feedback

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Notes: Guidelines for translating customer needs: Combine feedback into central themes Write the corresponding need, not the solution Use terms that are measurable Avoid words like “should” or “must”

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What you learned during this section:

 How to develop a VOC research plan

 Methods to collect data around customer requirements

 How to develop effective VOC questions

 How to organize and analyze customer feedback

Summary of Section

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

How to Translate VOC into CTQ’s

What is Voice of Customer (VOC)

Who is the Customer

Define – Voice of Customer

Lean Six Sigma Training

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 Know how to translate customer needs into a measurable, actionable customer requirement

 Learn tools for analyzing and prioritizing customer requirements

 Understand how to identify customer specification limits

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Identify Customers

 Review Charter and SIPOC

 Define customers

 Segment customers

Develop VOC

Research Plan

 Identify research methods

 Develop research plan

 Develop VOC questions

Gather Customer Issues / Needs

 Collect VOC  Organize

customer issues into needs

Translate Issues /

Needs to CTQ’s

 Translate needs into requirements (CTQ’s)

 Set specification limits

Voice of Customer (VOC) Process

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Common Customer Requirements Reliability Durability Features

Prestige Usability Failure Recovery

Product Quality

Convenience Accuracy Speed/Timeliness

Treatment/Interaction Tangibles Failure Recovery

Service Quality

Low Original Price Value Ratio Discounts/Sales

Total Costs Frequent Buyer Plans Terms, Tax

Price/ Value

What Matters to Customers?

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Notes: During the VOC process, customers may express their issues in the form of solutions or complaints, or the issue may be too general or abstract to glean any meaningful information from. By conducting translation of VOC feedback, the “real” or hidden requirements being vocalized by the customers will be identified.

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 Understanding customer requirements is essential to assure the outputs of your processes meet the customer’s needs

 To identify whether your organization’s processes are meeting customer needs and expectations, these customer needs must be translated into customer requirements that are measurable and quantifiable

 The term for a measurable and quantifiable customer requirement is CTQ (Critical to Quality), because these are the characteristics of a product or service that are “Critical to Quality” for the customer

What is a CTQ?

Defining Critical to Quality (CTQ’s)

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– Dissatisfaction

Primary SatisfierDelighters

Must Be

Satisfaction +

Service Dysfunctional

Service Fully

Functional

Prioritizing Customer Needs – Kano Analysis

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Notes: Kano Model developed by Professor Noriaki Kano. Identified needs are not of equal importance to customers. The Kano analysis frames needs into must be’s, primary satisfiers, and delighters. Kano’s theory is that for some customer needs, customer satisfaction is directly proportional to the extent to which the product or service is fully functional. The horizontal axis represents how fully functional a product or service is, whereas the vertical axis represents how satisfied a customer is. Think about the following travel needs. Where would they fit on the Kano Analysis? - In flight movie - Hot meal - On time flight arrival - Safe landing

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Requirements Type Definition Must Be – Priority #1 Requirement that can dissatisfy, but

cannot increase satisfaction

Primary Satisfiers – Priority #2 The more of these requirements that are met, the more the customer is satisfied

Delighters If the requirement is absent it does not cause dissatisfaction, but it will delight customers if present

Indifferent Customer is indifferent to whether the feature is present or not

Reverse Feature actually causes dissatisfaction

Kano Analysis Definitions

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Requirement Type Ease/Expense to Capture Approach to Use

Must Be  Difficult, more expensive  Information is known but difficult

to access and organize

 Customer complaints  One-on-One interviews  Focus groups

Delighters  Very difficult and expensive  Information is unknown and

must be created or combined from many unrelated sources

 Carefully orchestrated focus groups

 Customer observation

Primary Satisfiers  Easy and inexpensive information

 Information is known and can be easily captured

Mail and phone surveys Market research  Be a customer

Level of Effort to Capture Each Requirement Type

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Need Rating ~~~~~~~~ 4.2 ~~~ 3.6 ~~~~~ 1.2 ~~~~~~~~~~ 2.4 ~~~~~ 2.8

Q. How important are the product/service features:

1. Not important at all 2. Below average importance 3. Average importance 4. Above average importance 5. Extremely important

Survey/Interview Feedback

 Complaints from Customers

 Feedback from Internal Associate

Qualitative Feedback

Determine priority needs through analysis of all VOC methods

Must-Be Requirements

Determining Priority Needs

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Notes: Prioritizing needs is based on combining qualitative feedback methods that are used to collect complaints and issues and the quantitative methods used by the team to drill down and understand the specific needs of the customers. In this example the team used two different criteria to evaluate each need . #1: The total number of customer responses per need. #2: The overall importance of the need to the customer. Each of the criteria had a maximum value of 2.5. When combined the highest rating is 5 for each need. Prioritization Process: Combine the importance rating responses for each need and calculate the average. You can also add the satisfaction rating averages to the subsequent importance rating. Avoid having the team prioritize the needs. Use your qualitative and quantitative analysis.

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CTQ’s are the translated customer needs into quantifiable and measurable requirements of our products and services

Reduce Hold Time

Process Output

Characteristic

Measure

Target

Answer Call <15 Seconds

Prioritized Need

= Speed of Answer

= Customer call to answer time

= <15 seconds

CTQ

Translating Must-Be Needs into CTQ’s

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Notes: Once CTQ’s have been identified, review and update the charter to align with your new findings. Once updated, remember to review with your project Sponsor/Champion. Questions to consider are: Is your problem and goal statements aligned with your CTQ’s? Have you scoped your project to focus on the critical requirements of the customer?

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 Once CTQ’s have been identified and documented, it may be necessary to develop specification limits.

 Specification limits (specs) are specific tolerances that the CTQ must fall within for the customer to be satisfied with performance.

Example of CTQ’s and specification limits:

Pay Federal filing fee by

12th of month

CTQ

6th of each month

Lower Spec Limit

12th of each month

Upper Spec Limit

Developing Specification Limits for CTQ’s CTQ Chart

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Notes: Spec limits are separated into the lower spec limit and the upper spec limit. The upper spec limit is usually the CTQ defined in the VOC (i.e. 100% Accuracy, Answer Phone <15 seconds). However, sometimes a lower spec limit is also defined. This is particularly common in CTQ’s around delivery. (Example would be that the CTQ for delivery of a product is between 8AM-12PM. Anything below the lower spec limit or above the upper spec limit could lead to customer dissatisfaction) Specification limits are also necessary in the Control Phase so tolerances to track process performance are documented and proactive action can be taken if process performance begins to near either the upper spec limit or the lower spec limit.

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What you learned during this section:

 How to translate customer needs into a measurable, actionable customer requirement

 Tools for analyzing and prioritizing customer requirements

 How to identify customer specification limits

Summary of Section

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Define Measure Analyze ControlImproveDefine MeasureMeasure AnalyzeAnalyze ControlControlImproveImprove

End of Lesson: Define – Voice of Customer

Lean Six Sigma Training

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Measure Phase

Lean Six Sigma Training

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Measure Phase Overview

Lean Six Sigma Training

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Measure identifies the measures that will be used to baseline process performance and determine how well processes are meeting customer requirements, describes and displays variation in the process, and calculates process performance through statistical measures of sigma and yield.

Measure Phase Introduction

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 Identify and Define Key Indicators of Process Performance

 Develop Data Collection Plan

 Calculate Baseline Performance (Sigma)

 Display Performance Data

 Promote Productive Team and Change Management Atmosphere

Population of Calls

Population of Calls

Sample

Pareto Diagram

The types of complaints received from customers (January 1 – December 31)

DiscreteOutputTypes of Complaints

Run ChartThe number of inbound calls to the call resolution group (January 1 – December 31)

ContinuousInputNumber of Customer Calls

Measure

DisplayOperational Definition

Type of Data

Type of Measure

Population of Calls

Population of Calls

Sample

Pareto Diagram

The types of complaints received from customers (January 1 – December 31)

DiscreteOutputTypes of Complaints

Run ChartThe number of inbound calls to the call resolution group (January 1 – December 31)

ContinuousInputNumber of Customer Calls

Measure

DisplayOperational Definition

Type of Data

Type of Measure

Defects: 102 Opportunities: 4 Units: 221 DPMO: 115,385

Sigma: 2.7

Defects: 102 Opportunities: 4 Units: 221 DPMO: 115,385

Sigma: 2.7

0 10 20 30 40 50

0

100

200

300

400

Days

Fr eq

ue nc

y

CTQ = 15 Days

N = 4267 Average = 22.18 Days

Measure Phase Overview

4

ANALYZE

CONTROL

IMPROVE

MEASURE

DEFINE

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Measure Phase Deliverables

Define Measure Analyze Improve Control

Project Charter Project Management

Project Plan Process Definition

SIPOC As-Is Process

Map Quick Win

Identification Stakeholder

Management Stakeholder Map Stakeholder

Management Plan Communication

Plan Voice of Customer

Customer Identification

VOC Research Plan

Kano Analysis CTQ Identification

 Root Cause Analysis Affinity Diagram Fishbone Diagram

and/or 5 Why’s Lean Process

Analysis Lean Tools and

Measures Graphical Data

Analysis Histogram Pareto Chart Box Plots Correlation

Analysis Statistical Data

Analysis Linear Regression Multiple

Regression Root Causes

Identified Quick Win

Identification

Identify Measures X/Y Matrix

Data Collection Operational

Definitions Measurement

Systems Analysis (MSA)

Data Collection Plan

Describe and Display Data Histogram Pareto Chart Pie Chart Run Chart Control Charts

Baseline Performance Sigma

Performance Yield Process

Capability Quick Win

Identification

Identify and Select Solutions Generate Solutions Benchmarking Solutions

Prioritization Matrix Solution Selection

Matrix To-Be Process Map

Financial Impact of Solutions Cost/Benefit Analysis

Risk Planning and Testing Failure Modes and

Effects Analysis (FMEA)

Pilot Plan Implement Solutions

Multi-Generational Product Plan (MGPP)

Implementation Plan Stakeholder

Management Project Storyboard

Process Control Control Charts Process

Monitoring Plan Dashboard

Response Plan Project

Documentation Process

Procedures Replication

Opportunities Solution Transfer

Plan

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End of Lesson: Measure Phase Overview

Lean Six Sigma Training

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

Measure Relationships (X/Y)

Types of Measures

Measure – Identify Measures

Lean Six Sigma Training

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 Understand and identify measures of the process

 Identify the types of process indicators

 Identify relationships between measures and CTQ’s

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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 Selecting key output measures (Ys)

 Collecting baseline data for key output (Ys), input and process measures (Xs)

 Studying the variation in the output measures (Ys)

 Calculating the capability of the process

 Preparing for the Analyze Phase

Focus of the Measure Phase

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I P O

I P O

The Work Process

The Improvement Process

Relationship of Work Process and Improvement Process

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Dictionary says - “the dimensions, capacity, or amount of something ascertained by measuring”

A measure takes a concept such as time, error rate, length, width, height, amount, percent, or duration, and describes it in terms of a number (data)  Overall  At a specific point in the process  At a specific point in time  Over a period of time

What is a Measure?

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Process Effectiveness The extent to which customer

requirements are met

 Defect Rate  Accuracy  Actual/Plan

 Cost per transaction  Time per activity

(Cycle Time)

 Set up time for new customer needs  Cycle Time for special customer requests  Percentage of special requests not met

Process Efficiency The internal allocation of

resources

Adaptability The ability to quickly adapt to

changing requirements

 Service Level(s)  Timeliness  Response Time

 Output per unit (Space, FTE, Time)

 Process Yield

3 Process Measurement Categories

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Notes: There are two primary categories of measurements to determine process performance. They are Process Effectiveness and Process Efficiency. Adaptability is a process objective involving effectiveness and efficiency over time. Process adaptability is an objective that a project team should aim for after effectiveness and efficiency goals have been achieved. A process that is adaptable to changing customer needs, and the ability to remain capable in spite of variation that may exist within ones customer group’s needs is said to be “robust”.

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Data

Continuous Discrete

 Countable

 Indivisible

No values possible between

whole units

Never fewer than 1

 Counts in categories

 Measurable

 Divisible

Unit on scale is endlessly sub-divisible

Precision is limited only by the accuracy

of the measuring instrument

 Measures variation of a characteristic

Examples

 True/False Yes/No Satisfaction

(poor, good, excellent)

Examples

Dimensions  Time Currency

Two Types of Data

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Notes: A simple method to determine if your data is continuous is to ask the following question: Is the unit of data divisible? If yes, does the unit still retain a meaningful value. If yes, your data is continuous. Example, if you have 50 hours, the unit is hours, if you divide an hour in half you have 30 minutes, hence the unit is continuous because 30 minutes is of value. For discrete data, if you divide it in half it does not retain a meaningful value. Example, if you have 10 false answers on a survey, the unit is answers, if you divide an answer in half you have a half of an answer, which is not a meaningful value. Individuals often misunderstand their data when they focus on the quantity of units in determining if they have continuous or discrete data. In the previous example the quantity is “10” false answers. In determining if the data is continuous or discrete you need to focus on the unit, which is answers, and not the quantity of answers “10”.

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Data type is often determined at the outset of identifying your process CTQ (Y). If your Y is discrete, you will severely limit the tools available to you to Analyze and dissect your process. Generally speaking, continuous Ys and Xs are preferred, as the information provided by a given sample is typically greater with continuous data than with discrete data. However, as long as your Y is continuous, statistical analysis tools will largely remain available, even though your Xs might be discrete.

CONTINUOUS DATA ALLOWS

PROCESSES TO BE BROUGHT

INTO SHARP FOCUS

DISCRETE

Implications Based on the Type of Data

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Objective  Practice identifying discrete and continuous data types.

Instructions  Identify if the following data descriptions are discrete or continuous.

1. The time it takes to schedule a meeting. 2. The difference between when a meeting is supposed to start and when it

actually starts. 3. The numbers on a telephone. 4. The questions on a survey. 5. The assortment of candy delivered during afternoon snack time of a

meeting. 6. The price of a ticket.

 Prepare your findings.

Types of DataEXERCISE

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Please Do Not Proceed Forward

Types of DataEXERCISE

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1. The time it takes to schedule a meeting. (Continuous)

2. The difference between when a meeting is supposed to start and when it actually starts. (Continuous)

3. The numbers on a telephone. (Discrete)

4. The questions on a survey. (Discrete)

5. The assortment of candy delivered during afternoon snack time of a meeting. (Discrete)

6. The price of a ticket. (Continuous)

Types of Data – AnswersEXERCISE

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To understand how your processes are performing and to determine whether they are meeting internal or external customer requirements requires measuring the process.

In developing measures for your process, you must identify your indicators…

What is an Indicator?

 A measure

 A measurement that indicates how well the process is performing

 Should describe both the condition of a part of a process and the quality of the output or result of the entire process.

Identify Process Indicators

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Elements Common to All Processes

S I P O C Suppliers Inputs Process Outputs Customers

Process Map

Process Indicators

Quality Indicators

Process and Measures

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Quality Indicators

 Used to determine the quality of the output provided to customers  Assess the degree of conformance or non-conformance to CTQ (customer

requirement)  Are a lagging indicator, therefore, are not very useful in identifying reasons for

non-conformance

Process Indicators

 Measures taken at critical points in the process to describe what the process is doing

 Can serve as early warning signs (leading indicator) that something is wrong before the defect in the output occurs

 Monitored to evaluate process stability  Monitored and taken corrective action on to avoid adverse impact on customers

Types of Indicators

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Output Measures Measures that are placed on your internal processes. These are the measures for internal customers (i.e. departments) or those that influence output measures.

Measures used to determine how well customer needs and requirements are met.

Measures that are placed on your suppliers to ensure quality inputs are received.

Input Measures Process Measures

Process Indicators Quality Indicators

Linking Indicators to the Three Types of Measures

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Measures used to determine how well customer needs and requirements are met.

Measures that are placed on your internal processes. These are the measures for internal customers (i.e. departments) or those that influence output measures.

Measures that are placed on your suppliers to ensure quality inputs are received.

Examples:  # of calls/hour taken by each

service rep  2nd year customer retention

figures  Total # of meals delivered  % customer complaints

Examples:  Availability of service personnel  Time required to perform credit

review  % of non-standard approvals

required  # of qualified applicants  Total cost of service delivery  Total overtime hours

Examples:  # of customer inquiries  Type of customer inquiries  # of orders  # of positions open  Type of position open  Accuracy of the credit

analysis  Timeliness of the contract

submitted for review

Output MeasuresProcess MeasuresInput Measures

Linking Indicators to the Three Types of Measures

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The Improvement Process

I P O C

1.

Measures

Output Measures to CTQ’s

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 An output measure expresses the “voice of the process” because changes in input or process conditions drive changes in the output measure

 A good output measure serves as the translation of the voice of the customer

 Changes in the values of a good output measure should predict changes in the degree to which the process meets the customer need

 As changes are made upstream (to the process or to the inputs to the process), the output measure is a good indication of the success of changes being made upstream in the process

Why Start Measurement with Output Measures?

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1. Make the output measure and the requirement as closely related as possible

 For each customer requirement there should be a corresponding output measure

Example:

Customer Requirement Customer Specification Output Measure

Timely delivery of merchandise

0 late deliveries of merchandise

# or % of late deliveries

Accurate statements 0 statements with errors # or % of inaccurate statements

Guidelines for Developing Output Measures

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2. Measure at intervals that allow you to make useful judgments

 Measure often enough to catch problems before too much damage has been done, but balance this with time and cost to collect data.

3. Avoid using averages as quality output measures

 Averages can be misleading.

Example:

When a vendor who is supposed to be paid 30 days after invoice date receives a late payment (after 30 days), the contractor does not care about the company’s claim that they pay all invoices on an average of 25 days after the invoice date.

Guidelines for Developing Output Measures

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The Improvement Process

I P O C

2.

Measures

Process Measures to Output Measures

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1. Review the Process Map and Identify “Points of Pain”  Measure steps that experience has shown are problem area or “points of pain”.

Example: Areas of rework, long delay, or errors

 Measure steps that have long cycle times

 Measure where there is logical change or a decision point when the process moves from one process customer to the next

P1 Inputs to the process

P2 “Rework loops – rework points

P3 At the end of major process steps

P4 Hand-offs between departments

5 m

in 10

m in

Customer Payment

Processor AP

Processor

Y N

P1

P2

P4

P5

P3

P1

?

Guidelines for Developing Process Measures (Critical X’s)

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2. Measure critical “Moments of Truth” (customer touch point)

 Evaluate situations where a customer can leave a point of contact with the company and can have either a positive or negative experience.

3. Ensure process measures are linked/correlated to output measures

 These are the steps in the process that are leading indicators of downstream performance of the final process output. These are the most important!

4. Include measuring critical inputs as part of your process measures

 The timing and accuracy of inputs can have a great effect on the process, including these measurements can be telling about the process.

Guidelines for Developing Process Measures

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The Improvement Process

I P O C

3.

Measures

Input Measures to Process Measures

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1. Review the process map and identify incoming “Points of Pain”

 Measure inputs that experience has shown are problem area or “points of pain”.

Example: # of documents, types of documents, or location of supplier

 Measure where the inputs enter for the first time or throughout the process 2. Ensure input measures are linked/correlated to process measures  These are the inputs to the process that are leading indicators of

downstream performance of the final process output.

Guidelines for Developing Input Measures (Critical X’s)

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Key: Little Relationship Moderate Relationship Strong Relationship

X/Y Matrix - Input/Process/Output Measures Process: Bills Sent To Customer’s Home

Output Measures

On Time Bill Delivery

# of Errors Per Bill

% Received Response Time

# Of Processing

# per Bill %

Statements Accurate

Input and Process Variables

Input/Process Measures

Linking Output Measures to Process and Input Measures

H

M

L

H

M:

M L L

L: H:

X/Y Matrix

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Notes: Selecting Input and Process Measures 1. List output measures. 2. List potential process and input measures. 3. Assess relationship between output measures and potential process and input � measures. 4. Select set measures for process monitoring.

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Process Check: Measures and DMAIC

 Understand Core and Sub Processes

 SIPOC

 Develop Measures Around SIPOC  Effectiveness  Efficiency  Customer Satisfaction

 Measurement Criteria  Importance  Understandability  Sensitivity  Actionable  Accessibility

 Customer Requirements  Cost Benefit of

Data Collection

 Collect Data  Establish Relationships to Key Measures  Scatter Plots  Regression  Process/Output

Measures Matrix  Tree Diagram

Finalize Process Measures

Dashboard

Determine Process Measures with Best

Relationships

Narrow List of Measures

Data Collection to Select Measures

 Judgment And Linkage

Measure ControlAnalyze

Identify and Define Universe of Potential

Measures

Narrow the Measures Down to the Critical Few

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Principles of Good Measures

 The measure must be important

 The measure must be easy to understand

 The measure is sensitive to the right things and insensitive to other things

 The measure promotes appropriate analysis and action

 The measure should be easy to get

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What you learned during this section:

 What measures are

 The types of process indicators

 Method to document the relationships between measures and CTQ’s

Summary of Section

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

Measure Relationships (X/Y)

Types of Measures

Measure – Identify Measures

Lean Six Sigma Training

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By the end of this section, you will be able to:

 Understand the statistical relationship of process and input measures to outputs

 Understand the focus of monitoring measures

Overview – Objectives – Key Topics

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 Y relates to the outputs

 X relates to the process and inputs

 Identifying Xs that might explain variation in the output measure

 Collecting data efficiently: both the Ys and the suspected Xs

Now we are talking!!!!

Prepare for the Analyze Phase

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Process Variables (Xs)

Input Variables

(Xs)

Outputs (Ys)

Process X

X

X

X X X X

Y

Y

Y

Process Flow

Predictor and Response Variables

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Notes: Outputs (Ys) Product or service produced or delivered by the process. Key measures include cycle time, CTQs and defects, customer satisfaction, cost, etc. Process Variables (Xs) Those variables that influence the output and are generally controllable by those who operate the process. Key measure might include timeliness of step-by-step processing of the unit, accuracy/reliability, availability of products and staff, service provider behaviors, etc. Input Variables (Xs) Materials and information used by the process to create the outputs. Inputs are often outside the control of the process operator.

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Input Measures

Process Measures

Output Performance

Measures

Efficiency Measures Cost per transaction  Time per activity Amount of rework  Turnaround time Variability of an activity  # of inbound items

Effectiveness Measures Percent defective Number of errors  Total response time  Invoice/billing accuracy Revenue

X’s X’s Y’s

Monitoring and Controlling the Critical X’s

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To get results, should we focus our behavior on the Y or the X?

 X1...Xn

 Independent

 Input or Process

 Cause

 Problem

 Control

Response Predictor

x

x

x

xx x

x x

 Y

 Dependent

 Output

 Effect

 Symptom

 Monitor

Focus on the Process

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Notes: Understanding variation requires understanding the relationship between the process response (Y) and the process predictors (Xs).�� Y = f (X1, X2 , . . . , Xn )� The process predictors (Xs) affect (drive) the process outputs (Y).

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For every process there is a dependent variable called Y that we are attempting to influence. The independent variables which determine what happens to our Y are called the process X’s. Thus, we can boil down every process into a simple formula:

Y = f(X1,X2,X3…Xn) Once we understand the relationship between our various Xs and our Y, we can monitor and manipulate the Xs if necessary to modify Y as desired, then lock down the process so that Y remains within the proper range and is meeting customer requirements.

Monitoring and Controlling the Critical X’s

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What you learned during this section:

 The statistical relationship of process and input measures to outputs

 The focus of monitoring measures

Summary of Section

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

End of Lesson: Measure – Identify Measures

Lean Six Sigma Training

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

Data Consistency and Stability

Collecting Data

Data Sampling

Operational Definitions

Measure – Data Collection

Lean Six Sigma Training

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 Understand the importance of operational definitions

 Understand the criteria for documenting operational definitions

 Develop sound definitions for measures

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Data will help the team to:  Shift from “gut feel” understanding to

“Measurable” and “Quantifiable” understanding

 Support or disprove preconceived ideas and theories

 Determine a baseline of current process performance

 Document the history of the problem over time

 Develop metrics to measure the impact of changes on a process

 Identify and understand relationships that might help explain process variation

Data Collection

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Data and measurement play vital roles in every business improvement initiative. The right metrics give the organization a fact based view of current process performance. Think for a moment. 1. How well does your organization make decisions based on data? 2. How effective is your organization at meeting or exceeding customers expectations? Data will help answer these questions.

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In developing your data collection plan you will need to define:

 What you are trying to evaluate and measure

 Whether you need to collect new data or if existing data can be used

 How you will attach a value to what you are measuring

 How will you collect the data

 How frequently you will collect data

 The appropriate sample size (if needed)

 What data will the team collect

Guidelines for Developing Data Collection Plan

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Step 1 Develop

Operational Definitions,

Procedures, & Sample Size

Step 2 Plan for Data

Consistency and Stability

Step 3 Collect Data

Step 4 Continue Improving

Measurement Consistency

The Data Collection Process

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Purpose:

 To remove ambiguity

 Everyone who is collecting the data has the same understanding

 Identifies what to measure

 Identifies how to measure

 Reduces collector to collector variation to ensure that no matter who does the measuring, the results are the same

Definition:

An operational definition is a precise description that tells how to get a value for the characteristic you are trying to measure. It includes what it is and how to measure it.

Operational Definitions and Procedures

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 Definitions Must Have Specific Criteria

Everyone understands the definition and can use the definition to collect data in the same way. Example: If a team were measuring the time it takes to drive to work, the team would need to agree on “what” to measure (how long the drive is, how much time it takes) and agree on the method that will be used to measure it.

 Definitions Must Have a Method for Measuring the Criteria

The definition describes how to get the value (either variable or continuous). Example: The team would need to know how to calculate the length of the drive – is it in miles or kilometers?

 Definitions Must be Useful to the Customer and Team

The definition relates directly to the issue the customer is having with the process. Example: Are customers really interested in the distance of the drive or how long the drive is?

Operational Definitions Guidelines

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How would you define these?

 Office meeting “first thing in the morning”

 On time flight departures

 Computer downtime

 Accurate bill

Measure Type of Measure

Type of Data

Operational Definition What

Operational Definition

How

Billing Accuracy

Output Discrete Inaccurate = Bill with any of the 5 fields not matching customer order form

Reconcile invoice with customer order for 5 fields

Example:

Examples of Why Operational Definitions are Necessary

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What you learned during this section:

 The importance of operational definitions

 The criteria for documenting operational definitions

 How to develop sound definitions for measures

Summary of Section

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

Data Consistency and Stability

Collecting Data

Data Sampling

Operational Definitions

Measure – Data Collection

Lean Six Sigma Training

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By the end of this section, you will be able to:

 Understand the importance of data sampling

 Understand the uses of sampling in process and population types

Overview – Objectives – Key Topics

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Statistical Inference is the process of drawing conclusions about a population based on analysis of a portion of that population. Sampling is the process of selecting the portion of the population to study.

SAMPLEPOPULATION

As it is the population we wish to study, not merely a subset of it, there is an inherent danger in sampling. If we are to have confidence in our results, the sample must be representative of the overall population. The illustration above shows a population (area under the black line or top line) and a representative sample (area under the red line).

Fr eq

ue nc

y Pop. Sample

m

(N = 5,000 People) (n = 100 People)

What is Sampling?

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Why Sampling is Necessary

Why Sample?

 Data collection can be costly and timely

 Sometimes data collection is a destructive process (ex. taste testing)

 Sound conclusions can often be drawn from a relatively small amount of data

Sample Frequency

 Collect often enough to catch fluctuation

 Better to collect several small samples over different times than one large sample at a single point in time

 Greater the instability (variability), greater the sampling frequency

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 Process Sampling: predicting WHY a measure takes on certain values We have a process that we want to measure, analyze or control  Establishing baseline performance of the process  Conducting a special study to improve the process  Ongoing monitoring to control the process

 Population Sampling: estimating or characterizing the WHAT or HOW MANY of a measure We have a large population that we want to describe  Income level of a certain customer segment  % of customers who would purchase a new service  Reasons for being behind in credit card payments

2 Important Uses of Sampling

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25-30Control Chart

25Scatter Diagram

50Pareto Chart

50Histogram

100 and nP≥5Proportion Defective (P)

25-30Standard Deviation

5-10Average

Minimum Sample SizeTool or Statistic

Simple Sample Size Guidelines for Process Sampling

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 Monitor process frequency enough to catch it going from good to bad

 Better to collect several small samples over different times than one large sample at a single point in time

 Unstable process – more frequently

 Stable process – less frequently

Covered in the “Describe and Display Data”

lesson

Simple Frequency Guidelines for Process Sampling

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Where to Sample

Locating your “Sampling Sweet Spot”

 Location in the process where the process variable affects the output variable

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What you learned during this section:

 The importance of data sampling

 The uses of sampling in process and population types

Summary of Section

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

Data Consistency and Stability

Collecting Data

Data Sampling

Operational Definitions

Measure – Data Collection

Lean Six Sigma Training

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By the end of this section, you will be able to:

 Understand the importance of measurement system analysis

 Understand the different measurement system analysis techniques (accuracy, repeatability, reproducibility, stability)

 Take the actions necessary to ensure the measurement system functions properly

Overview – Objectives – Key Topics

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Plan for Data Consistency and Stability

Measurement systems must be validated to ensure that data is consistently free from errors

 Data is only as good as the process that measures it

 Methodology must be developed to teach the measurement system to ensure consistency and stability, also known as Gage R&R (Gage R&R analysis quantifies the precision of a measurement system to determine its acceptability)

 Determine factors that could cause the measurement of an item to vary

 Find ways to reduce the effects of those factors

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Key Questions for Measurement System Analysis

 How much variation is caused by the measurement system vs. actual process variation?

 How much error is considered allowable for this data?

 What are the sources of the measurement error?

 How can the error sources be eliminated or minimized?

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Guidelines for Measurement System Analysis

A Measurement System must be:

 Accurate

 Repeatable

 Reproducible

 Stable

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Issues when Validating a Measurement System

Why do a Gage R&R?

 To determine if different workers across a given process use the same criteria to determine “good” from “bad”

 To assess work standards against customer requirements

 To identify how well people are conforming to themselves

 To identify how well people are conforming to a “known master”

 To identify training, procedural, or standards gaps

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The difference between observed average measurement and a master/standard.

Accuracy

Standard Value

Observed Average

Accuracy in Measurement Systems

Measurement System Accuracy

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Notes: This is the most common approach for correcting inaccuracy (or bias) in a measurement process. This is driven by the people or equipment “drifting” over time.

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Variation experienced when one person repeatedly measures the same unit with the same measuring equipment.

(Minimum Variation)

Repeatability

Repeatability in Measurement Systems

Measurement System Repeatability

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Variation when two or more people measure the same unit with the same measuring equipment.

Reproducibility

Data Collector 2

Data Collector 1

Reproducibility in Measurement Systems

Measurement System Reproducibility

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Variation obtained when the same person measures the same unit with the same equipment over an extended

period of time.

Stability

Time 1

Time 2

Stability in Measurement Systems

Measurement System Stability

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 Develop a master standard for everyone to utilize

 Train data collectors together

 Define each measure (operational definitions)

 Test for accuracy, repeatability, reproducibility early and make changes to system accordingly

 Audit the process frequently (stability)

Improving the Measurement System

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What you learned during this section:

 The importance of measurement system analysis

 The different measurement system analysis techniques (accuracy, repeatability, reproducibility, stability)

 How to take the actions necessary to ensure the measurement system functions properly

Summary of Section

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

Data Consistency and Stability

Collecting Data

Data Sampling

Operational Definitions

Measure – Data Collection

Lean Six Sigma Training

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By the end of this section, you will be able to:

 Understand the elements of a data collection plan

 Understand the purpose of data collection forms

 Determine the benefits of using existing data collection methods or developing new methods

 Develop elements of a data collection plan for your project

Overview – Objectives – Key Topics

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 Communicate the purpose (what and why) to the data collectors and process participants

 Train everyone who will be collecting data

 Make data collection procedures error proofed (consistency and stability)

 Oversee data collection and perform a pilot test (check in frequently with collectors)

Begin Data Collection

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Measure

Specify the name of what you are measuring (billing accuracy, billing cycle time).

Type of Data

Discrete or Continuous.

Type of Measure

Specify whether it is an output, input or process measure.

Operational Definition

Define what is being measured, how it will be measured, and how it will be recorded

Sample

- Number to be sampled - Where in the process to sample

- Frequency

Display

- What tool or tools will you use to display the data

Data Collection Plan Elements Data Collection

Plan

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Sample 100 Calls

Sample 225 Statements

Population of Calls

Population of Calls

Population of Calls

Sample

HistogramThe average hold time per hour / day / week / month (January 1 – December 31)

ContinuousProcessHold Time Average

Pareto Diagram

The types of complaints received from customers (January 1 – December 31)

DiscreteOutputTypes of Complaints

Run ChartThe number of inbound calls to the call resolution group (January 1 – December 31)

DiscreteInputNumber of Customer Calls

Call Resolution

Statement Accuracy

Measure

Pie ChartThe % of calls resolved without transfer to another department (March 1 – June 31)

DiscreteProcess

Pareto Diagram

The inaccurate fields for each statement (March 1 – June 31)

DiscreteOutput

DisplayOperational DefinitionType of Data

Type of Measure

Data Collection Plan Example

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Data Collection Forms

A Data Collection Form:

 Defines exactly what is to be measured  Standardizes data collection between different people  Makes it easier to keep track of data

Data Collection Form Considerations:

 Descriptions of data that is being collected  Space to record the data  Space for comments  Space to keep track of stratification factors

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Loan # Location

Inaccurate Fields

Notes Incomplete Application

Wrong Amount

Address Incorrect

No Signature

A1234 Chicago X Missing address

A2234 Chicago X

B3432 London X

A3487 Chicago X X

B9872 London X

B2903 London X

Totals 1 3 2 1

Check Sheets  A type of data collection form that helps collect the data

 Standardizes the data collection to ensure consistency if more than one person will be collecting

Data Collection Form Example – Check Sheet

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Guidelines for determining the cost/benefit trade off for data collection

 Can the new data be generated through systems modifications?

 Can data collection efforts be easily integrated into existing work processes?

 Is all the data being collected necessary to calculate key process measures?

 Can some existing data collection efforts be curtailed because they do not add value?

Cost/Benefits of Data Collection

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 Check to make sure measurements are stable

 Review the measurement procedures periodically to ensure consistency

 Check to see if the data looks reasonable

Continue Improving Measurement Consistency

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 Keep in mind that data collection costs time and money. Ask yourself:

 Is it worth it?

 Know how you will use the data before launching a large collection. Ask yourself:

 Can we test it through a quick pilot?

 How we will gather and use the data?

 Data is the output of a measurement process. Ask yourself:

 How can I apply my process perspective to the issue of measurement quality?

Data Collection Summary Points

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What you learned during this section:

 The elements of a data collection plan

 The purpose of data collection forms

 The benefits of using existing data collection methods or developing new methods

 How to develop elements of a data collection plan for your project

Summary of Section

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

End of Lesson: Measure – Data Collection

Lean Six Sigma Training

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

Types of Variation

Understanding Variation

Measure – Describe and Display Data

Lean Six Sigma Training

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By the end of this section, you will be able to:

 Understand what variation is and how to display and describe it

 Develop a Histogram and use it to interpret variation

 Understand normal and non-normal data

 Utilize additional tools for categorical data

Overview – Objectives – Key Topics

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Reducing the process variability to meet customer requirements (CTQ’s) is a central theme for Lean Six Sigma improvement. We must first document this variability before we can understand the problems that drive it (Analyze Phase) and how to improve it (Improve Phase).

 The goal of Lean Six Sigma improvement is to center a process well within customer requirements by reducing variation.

 To determine whether this goal is achieved, Sigma requires that two elements are measured:  Customer requirements (CTQ’s) – Define Phase  Process baseline performance (mean & standard deviation) –

Measure Phase

Variation and Sigma

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Variation Happens  All repetitive activities of a process have a certain amount of fluctuation

or variation  Variation is the “Voice of the Process”  When plotted, process variation becomes visible over time  Input, process, and output measures will have variation  Failure to understand variation could be costly

Time Frequency

What is Variation?

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PROCESS VARIATION INHIBITS OUR ABILITY TO MEET CUSTOMER REQUIREMENTS

Variation

Product or Service Output

Critical to Quality (CTQ)

Defects: Service unacceptable to

customer

A

Product or Service Output

Critical to Quality (CTQ)

Defects: Service unacceptable to

customer

A

Why it’s Important to Understand Variation

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Histograms – a histogram is a bar graph that displays data in picture form. Often times called a frequency distribution because it shows clearly how frequently each separate value appears in the data.

 A histogram reveals several factors about the data. Such as:  The central position of the data. For example, the mode or most

frequently appearing value shows one measure of central position. (Another measure of central tendency is the average.)

 The dispersion (spread or variation) of the data.  The shape (pattern) of the data.

Charting Variation – Histograms

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The first question to be answered in describing variation is “What is the central tendency of the data?”

Central Tendency:  Refers to the “center” of the

frequency distribution  Represents where most of the

values (in this example cycle time) tend to occur

Histograms – Central Tendency

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Descriptive Statistics:

 Mean: 30.60 Days  Often referred to as the average, it is the

most likely or expected value. The formula for mean is:

 Median: 31 Days  The middle of the data set, where 50%

of the data is greater than the median, and 50% of the data set is less than the median

 Mode: 31 Days  The most frequently occurring value.

Central Tendency can be estimated using the graphical display of the histogram, but is more precisely measured by statistical measures of central tendency.

_

n ΣxiX =

_ X is the value we are trying to solve (mean) Σ is a mathematical notation for adding values (summation)

Xi is the I’th (where I runs from 1-n) data value of all the data

n is the number of data points

Statistics Overview:

Histograms – Central Tendency

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Notes: Example: Calculate Mean, Median and Mode from the following data set: 1, 2, 6, 6, 10, 11, 12, 13, 14, 28 Mean = 10.3; Median = 10.5; Mode = 6

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Many companies often use mean or average to describe their process variation and performance. Example: A call center answers the phone on average within 30 seconds of the customer call. The customer’s requirement of the speed of answer is <1 minute.  How well is this process performing at meeting the customer’s

requirement? What additional information is missing to draw sound conclusions?

Mean = 30 Seconds CTQ = 1 Minute

time

Histograms – Central Tendency

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The second question to be answered in describing variation is “What is the dispersion of the data?” Or, how much variation exists in the data?

Dispersion:  Often referred to as the spread or

variation in the measurements

Histograms – Dispersion

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Descriptive Statistics:

 Range: 23 Days  The maximum value in the data set minus the

minimum value in the data set. The formula for range is: R = MAX - MIN

 Standard Deviation: 4.67 Days  The most common measure of dispersion, the

standard deviation is the average distance, or deviation, that a given point is away from the mean. The formula is:

Dispersion can be estimated using the graphical display of the histogram, but is more precisely measured by statistical measures of dispersion

S = n - 1

Σ (xi – x)2 _

_ X is the average of all of the data

Σ is a mathematical notation for adding values (summation)

n is the number of data points

s is the value we are trying to solve (standard deviation)

Xi is the I’th (where I runs from 1-n) data value of all the data

Statistics Overview:

Histograms – Dispersion

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While the central tendency and dispersion of data provide valuable information, they still are not sufficient in describing variation. Example: 2 call centers have almost identical average and standard deviations.  Is one center performing better than the other? What additional information is missing to draw sound conclusions?

Histograms – Central Tendency and Dispersion

N = 100, Mean = 30.42, StDev = 4.452 12

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The final question to be answered in describing variation is “What is the shape of the data?”

Histograms – Shape

13

Shape:  Refers to the pattern of the data

when plotted on a histogram

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Notes: These histogram examples above represent the 3 commonly encountered shapes. They are the normal distribution, bimodal distribution, and exponential distribution (which can be skewed either to the right-positive or left-negative). Many processes do not follow a “normal” distribution and non-normal data should not be considered bad data. Some examples of non-normal processes would include: Cycle time Calls per hour Customer waiting time And many others

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The Normal Curve – a probability distribution where the most frequently occurring values are centered around the middle (or center point) and the other values tail off symmetrically in both directions.

 In theory, the curve or distribution never ends  Equal proportions fall on either side of the most frequently occurring value  The center of the data is at the peak of the distribution  Almost 100% of the results are contained within 3 standard deviations on either side

of the average

Normal Curve

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Notes: The normal distribution is of special interest because it naturally arises from measurement data. In addition, many statistical tools assume a normal distribution: Continuous Data Control Charts Continuous Data Hypothesis Tests Process Capability Design of Experiments We can use a “Normal Probability Plot” to test whether the data is normally distributed.

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The Normal Curve – can be divided into segments, mathematically called standard deviations. Roughly 100% of the data falls within 3 standard deviations on either side of the average .

Normal Curve and Standard Deviation

15

Number of Standard Deviations from the Mean

x

-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6

Standard Deviations (Sigma’s)

1 2 3 4 5 6

% of Data Between Limits

68.26 95.46 99.73

99.9937 99.999943

99.9999998

68.26%

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Normal Probability Plot – Roughly Normal

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Normal Probability Plot – Bimodal Distribution

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Normal Probability Plot – Exponential Distribution

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After you have plotted data using the Normal Probability Plot, check the P-value.

Normality Test: P-value

Normal data will fall on a straight line within the probability confidence intervals (95% CI) and have a P-value of >0.05. Normal: P-value >= 0.05, Not Normal: P-value < 0.05

 Example: In the normal distribution probability plot (see previous pages):  Almost all of the data points fall within the limits  The P Value is 0.229

We would conclude that there is no serious departure from normality in this data.

 Example: In the bimodal and exponential probability plots (see previous pages):  Many of the data points fall outside of the limits  The P Value is <0.05

We would conclude therefore that these data sets depart significantly from normal distribution.

You can also perform the Anderson-Darling Normality Test to calculate the P-value (this test is found in many statistical software applications).

There are several methods for handling non-normal data. These include stratifying differently, sub-group averaging, using different distributions, and transforming data. Transforming data is an advanced statistical technique that will not be covered in this course.

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As we have covered in displaying variation, histograms allow us to answer the following questions:  What is the central position of the distribution?  What is the dispersion or spread of the distribution – is it wide or

narrow?  What is the shape of the distribution – symmetrical, twin peaked,

skewed to one side or the other, flat, etc?  Are there outliers or extreme data points?

Interpreting Histograms

20

After describing the data, we can use the histogram to determine the appropriate strategy for improvement: 1. Reduce the process variation 2. Reduce the process mean 3. Reduce both the process variation and mean

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1. Reduce the process variation

 Process A (dashed line)  Excessive variation  Defects are created when

process variation exceeds CTQ (also known as USL – upper spec limit)

 Process B (solid line)  Reduced variation  Defects are eliminated or

reduced when process variation stays within CTQ Product or Service Output

Critical to Quality (CTQ)

Defects: Service unacceptable to

customer

A

B

Product or Service Output

Critical to Quality (CTQ)

Defects: Service unacceptable to

customer

A

B

Interpreting Histograms

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2. Reduce the process mean

 Process A  Mean > CTQ creates defects  Virtually all of the process

distribution is causing defects or is “out-of-spec” for USL

 Process B  Mean reduction* < CTQ

eliminates defects  Defects are eliminated or reduced

when process mean is shifted within CTQ requirements Product or Service Output

Critical to Quality (CTQ)

Defects: Service unacceptable to

customer

AB

*Remember that just measuring the mean alone will not be sufficient to determine if process is meeting CTQ’s

Interpreting Histograms

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3. Reduce the process variation then reduce the mean

 Process A  Variation and mean exceed CTQ

requirements  Only shifting mean, the variation

would still cause defects  Reducing variation first will make

the process more stable  Process B  Mean > CTQ creates defects  Reduce process mean

 Process C  Defects are eliminated or reduced

when process variation is reduced and mean is shifted within CTQ requirements

Product or Service Output

Critical to Quality (CTQ)

A

C B

Interpreting Histograms

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Reduce the Process Variation

Process may be stable with no outliers

present

Symmetric, bell shaped

Revise measurement process

Measurement may not be sensitive

enough

No distinctive values

Investigate reason for asymmetric

Process data may not be normally distributed

Asymmetric, long tail (either positive or

negative)

Investigate reason for bi-modal, try segmentation

There may be 2 or more processes or

segments

Bi-modal, two humps

Standardize measurement

process

Inconsistent roundingMultiple dominant observations

Investigate cause of bias

Measurement may be biased

One value dominant

ActionConcludeObservationShape

Common Histogram Shapes

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Objective  Practice interpreting histogram shapes.

Instructions  Interpret the shapes on the following page.

 What can you gather from the shape?  What actions might you take on it?

 Prepare your findings.

Histogram InterpretationEXERCISE

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Histogram InterpretationEXERCISE

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Please Do Not Proceed Forward

Histogram InterpretationEXERCISE

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When you see this symbol, please do not continue forward in the materials.

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Histogram Interpretation – ResultsEXERCISE

Symmetric 28

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Pie Chart – the pie chart is a tool that displays discrete variation by breaking down the frequency of the data distribution into categories.

Pie Charts and Variation

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What you learned during this section:

 What variation is and how to display and describe it

 How to develop a Histogram and use it to interpret variation

 What normal and non-normal data is and how to differentiate between the two

 Other variation tools that can be used for displaying categorical data

Summary of Section

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

Types of Variation

Understanding Variation

Measure – Describe and Display Data

Lean Six Sigma Training

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By the end of this section, you will be able to:

 Understand what common cause and special cause variation are

 Develop a Run Chart and Control Chart and use them to distinguish common and special cause

 Select the appropriate control chart based on the type of data

Overview – Objectives – Key Topics

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V A R I A T I O N

Machines

Materials

Methods

Measurement

Mother Nature

People

Describing and understanding the sources of variation is a first step in reducing it.

Sources of Variation

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Notes: Potential sources of variation: Machines – The equipment used to transform inputs into outputs. Materials – The outputs of the process. These may be tangible (i.e. documents) or not. Methods – The procedures used to transform inputs into outputs. These may be as formal as standard operating procedures or not documented at all. Measurement – Any tools that are used to monitor or track the performance of the process. Mother Nature – Environmental elements within the process that have an impact on its performance. People – The workers who perform the process.

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Variation

Common Cause (natural/inherent)

Special Cause (assignable/imposed)

 Common Cause – natural inherent causes from the interaction of all of the sources of variation.  Can only be reduced by changing the process

 Special Cause - assignable cause from especially large influence by one of the sources of variation.  Must be removed or reduced for a process to be considered stable or in control

Approximately 85 to 95 percent of variation within a process can be attributed to the overall system in which the work is done rather than to the individuals

involved in the process

Two Types of Variation Defined

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Where does process variation come from in the first place? Given the same input, shouldn’t the process produce the same output every time? Dr. Walter Shewhart wrestled with this dilemma in the 1920s. He discovered that process variation has two components: a stable, omnipresent variation inherent in the process; and an unstable, intermittent variation attributable to assignable causes.

Total Process Variation = VARSPECIAL + VARCOMMON SPECIAL CAUSE COMMON CAUSE

Special Cause vs. Common Cause Variation

35

 New procedure implemented

 Machinery failure  Power outage  Untrained operator  Employee strike  Improper setup

 Different levels of training

 Inadequate inspection/test

 Lack of machinery capability

 Failure to understand customer requirements

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Common Cause

Special Cause

Not significantly influenced by one of the sources

Significantly influenced by one of the sources

 Expected  Predictable  Normal  Random  Chance

 Unexpected  Unpredictable  Not Normal  Not Random  Chance

It is important to understand this distinction so the strategy for process improvement and control can be determined.

Characteristics of the Two Types of Variation

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Common Cause

Investigate to determine the “vital few” causes (X’s)

Develop solutions for “vital few” causes

The actions that will be taken are driven by the type of variation.

Analyze and Improve Phases

Special Cause

Investigate the specific causes from the problem source

Develop solutions and implement as needed

Measure Phase

Improvement Strategies for Common and Special Causes

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The first question most teams will ask is “How do we know whether we have common cause or special cause variation?”

Distinguishing Common Cause vs. Special Cause Variation

2 tools that distinguish

Common and Special Cause

Run Chart

Control Chart

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Run Charts – time ordered plots of data that can be used to search for special cause variation.

Run Charts and Variation

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Advantages

 Most data collected over time can be used

 Provides baseline of current process performance

 Easy to create

 No calculations needed

 Easy to interpret

Disadvantages

 Detecting special causes takes time

 Won’t detect:

 Short duration shifts

 Variation increases

 Hard to assess process capability

Run Chart Advantages and Disadvantages

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Notes: Run Charts should be used in conjunction with the Histogram to develop a full picture of process performance. A process may not have detectable patterns of special cause variation, but have considerable variation that can only be determined when using the Histogram.

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Control Charts – similar to the run chart, control charts are time-ordered plots of data that can be used to search for special cause variation. The additional

benefit of control charts is that they also have “control limits”.

Upper Control Limit

Lower Control Limit

Control Charts and Variation

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Notes: Control limits are calculated at 3 standard deviations on either side of the mean (or center line).

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Control Limits – are a statistical calculation from the process data and define the boundaries of common cause variation. Remember that a process is

considered out of control if it contains special cause variation.

Upper Control Limit

Lower Control Limit

 Defined based on the performance of the process

 Help to determine if your process in “in control” (only common cause variation is present)

 Plotted on control charts by statistical calculation

 Can change based on changes to the process

“Control Limits”

Control Limits Defined

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Control limits (UCL and LCL) may be recalculated when the following guidelines have been met.

 No special cause variation exists in the process

 Either the methods of collecting or operational definitions of the data have changed in the process

 When a change in the process has occurred that has fundamentally changed the performance in the process

Recalculating Control Limits

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 Defined by the customer

 Help determine if the process is producing defects

 Not plotted on control charts

 Change when customers requirements change

 Defined by the process performance

 Help determine if the process is in control

 Plotted on control charts

 Change when the process changes

Upper Control Limit

Lower Control Limit

“Control Limits” Voice of Process

Upper Spec Limit

Lower Spec Limit

“Spec Limits” Voice of Customer

Control Limits vs. Specification Limits

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 Only common cause variation is present in the process

 The process is predictable

 The process is stable

A process that is “in control” may not be meeting customer requirements

Definition of Control

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Look for patterns in the graph that indicate special cause. Patterns to look for are:

Shift – 8 or more consecutive points on the same side of the center line

Outlier – 1 or more points that fall outside of the control limits

Trend – 6 or more consecutive points increasing or decreasing

Cycle – Data points that cycle up and down

Interpreting Control Charts

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Notes: We can conclude that special cause variation is present if one of these patterns is present in the data. Next steps would include: Investigate the specific data points where the pattern occurs Determine the source of the variation Develop solutions and implement as needed

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In addition to the previous patterns, when the Control Chart is divided into zones, as shown below, a process is out of control when any of the following is true:  2 points out of 3 consecutive points are on the same side of the average in Zone A or

beyond  4 points out of 5 consecutive points are on the same side of the average in Zone B or

beyond  There are 15 consecutive points within Zone C (above and below the average)

UCL

CL

LCL

Zone A

Zone B

Zone C Zone B

Zone C

Zone A

Interpreting Control Charts

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Notes: By dividing the control chart into zones, we can better detect special cause variation. Each zone represents standard deviations from the mean: Zone C represents +/- 1 standard deviations from the average (center line) Zone B represents +/- 2 standard deviations from the average (center line) Zone A represents +/- 3 standard deviations from the average (center line)

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2 points out of 3 consecutive points are on the same side of the average in Zone A or beyond

UCL

CL

LCL

A B C C B A

UCL

CL

LCL

A B C C B A

4 points out of 5 consecutive points are on the same side of the average in Zone B or beyond

There are 15 consecutive points within Zone C (above and below the average)

UCL

CL

LCL

A B C C B A

Examples of Zone Variation Detection

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Use this chart to select the type of control chart to use.

Discrete

ImR Chart

Continuous

Type of Data

Subgroup Size of 1

Rational Small Subgroups (<8-

10)

Rational Large Subgroups (>8-

10)

X and S Chart

_

np Chart

Classification (binomial data)

Sample Size is Constant

Sample Size Varies p chart

u Chart

Count

Opportunity Varies

Opportunity is Constant c chart

OR

OR

OR

OR

OR

X and R Chart

_

Selecting a Control Chart

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Notes: For X-bar and R and X-bar and S you will need to collect data in sets of points called subgroups, or logical groupings of data.

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Overview of the different types of control charts Discrete data control charts: np Chart – used with classification data (i.e. pass/fail, good/bad) and charts the number of defectives in each subgroup (sample size is constant).

p Chart – used with classification data (i.e. pass/fail, good/bad) and charts the proportion of defectives in each subgroup (sample size varies).

u Chart – used with count data (e.g. number of defects) and charts the number of defects per unit sampled in each subgroup (opportunity for defects varies).

c Chart – used with count data (e.g. number of defects) and charts the defect count per sample (opportunity for defects is constant).

Continuous data control charts: ImR Chart (Individuals) – for analyzing individual data points and rational subgroups can not be formed from the data (data is assumed to be normally distributed).

X and R Chart – for analyzing the averages of small subgroups (<8-10) can be formed from the data.

X and S Chart – for analyzing the averages of large subgroups (>8-10) can be formed from the data.

Selecting a Control Chart

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What you learned during this section:

 What common cause and special cause variation are

 How to develop a Run Chart and Control Chart and use them to distinguish common and special cause

 How to select the appropriate control chart based on the type of data

Summary of Section

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

End of Lesson: Measure – Describe and Display Data

Lean Six Sigma Training

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

Yield

Sigma

Measure – Baseline Performance

Lean Six Sigma Training

Process Capability

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 Understand the concept and benefits of sigma

 Understand how sigma relates to process capability

 Utilize the formula to calculate baseline performance

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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By now, you have gathered your data from Outputs (Y’s) and Process and Inputs (X’s). You have displayed and described your data. The next question to solve is:

How well is my process performing against my customer’s requirements?

Voice of Process (variation)

Voice of Customer (CTQ’s)

I P O C

?

Measure Phase Review

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Sigma is a name given to indicate how much of the data falls within the customers’ requirements. The higher the process sigma, the more the process outputs, products and services, meet customers’ requirements – or, the fewer the defects.

Sigma is a Measurement scale which compares the output (variation) of a process to the customer’s requirements (CTQ’s). Sigma shows how capable a process is of meeting CTQ’s.

What is Sigma?

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Notes: Defects are defined as not meeting customer requirements. Put simply, sigma is the measure of how far a process is away from achieving near perfect customer satisfaction. Six, or 6 Sigma is measured at near perfect… meeting customer expectations 99.99966% of the time.

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If you were the VP of a company and these were current process performance figures, how would you know which process is performing better?

Process Performance

Customer Service Speed of answer is 20 seconds

Systems

Loan Processing

Systems up time is 95%

Loans processed on average 15 days

Why Having a Common Metric for Comparison is Critical

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Notes: It’s difficult to compare processes with very different kinds of measures. There is no common metric between these processes.

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In this diagram, the number of occurrences that fall outside of the customer requirement for Process A are considered defects. Process B represents the optimal performance (most capable) with no occurrences (defects) outside of the requirement.

B

Product or Service Output

Critical to Quality (CTQ)

Defects: Service unacceptable to

customer

A

Optimal Performance

Process Variation and CTQ’s

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Notes: Process A has considerable variability or spread and is not meeting the critical customer requirement (identified by the defects). By reducing the variation and mean of the process (B), the process is more capable of meeting customer requirements and will lead to higher sigma performance and greater customer satisfaction.

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The most capable process has variation and mean that are well within customer requirements.

Product or Service Output

Critical to Quality (CTQ)

Sigma is calculated by the variation against the CTQ’s, so the smaller the variation the higher the Sigma.

Capable Process

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There are 2 ways a process can be non-capable.

Product or Service Output

Critical to Quality (CTQ)

Defects: Service

unacceptable to customer

High Process Variation – the process variation exceeds the customer requirement (specification limits which could have a lower or LSL and upper or USL)

Process Mean Not Aligned – the process mean exceeds the customer requirement (specification limits which could have a lower or LSL and upper or USL)

Product or Service Output

Critical to Quality (CTQ)

Defects: Service

unacceptable to customer

Product or Service Output

Critical to Quality (CTQ)

Defects: Service

unacceptable to customer

Non-Capable Process

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The term “Six Sigma” refers to process capability equivalent to produce 3.4 defects per million opportunities (DPMO). A defect is considered any event which fails to meet customer critical-to-quality (CTQ) requirements, while an opportunity is any event where failure to meet CTQs is possible.

99% performance is generally considered quite good. Yet if many of the processes we encounter in our daily lives functioned only at 99% effectiveness, we would reconsider our definition of “good” performance:

 20,000 lost articles of mail per hour  15 minutes worth of unsafe drinking

water each day  5000 incorrect surgical operations a

week  2 short or long landings at most major

airports every day  No electricity for 7 hours per month

99% Defect-Free 6σ (99.99966% Defect-Free)  7 lost articles of mail per hour  9 seconds worth of unsafe drinking

water each month  2 incorrect surgical operations a

week  1 short or long landing at most major

airports every 4 years  No electricity for 1 second per year

(Adapted from Mikel J. Harry, The Nature of Six Sigma Quality, 1987)

Which world would you rather live in?

Sigma Defined

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With performance at 2 Sigma: 69.146% of products and/or services meet customer requirements with 308,538 defects per million opportunities.

With performance at 4 Sigma: 99.379% of products and/or services meet customer requirements… but there are still 6,210 defects per million opportunities.

With performance at 6 Sigma: 99.99966% – As close to flaw-free as a business can get, with just 3.4 defects per million opportunities (e.g., products, services or transactions).

Sigma Performance

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Notes: Most companies measured, prior to business performance improvement, perform around a 1 to 2 sigma, which equates to meeting customer expectations only 30.9% to 69.1% of the time. These numbers are staggering and can be extremely detrimental to customer satisfaction with products and services. Although 6 Sigma is difficult to achieve in some industries, a 3.5 Sigma (meeting customer expectations 97.7% of the time) is realistic for most service related companies.

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A capable process is statistically defined as a process that has all of its variation within 6 standard deviations (sigma’s) of the customer requirements.

Number of Standard Deviations from the Mean

x

-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6

Standard Deviations (Sigma’s)

1 2 3 4 5 6

% of Data Between Limits

68.26 95.46 99.73

99.9937 99.999943

99.9999998

CTQ (Upper Spec)

CTQ (Lower Spec)

Capable Process and Sigma

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 A measurement scale focused on improvement

 Focuses on defects

 Common metric for comparison

Why Sigma Measures?

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Yield exclusive of rework at a process stepFirst time yield

A unit with one or more defectsDefective

Any event which can be measured that provides a chance of not meeting a customer requirement

Defect Opportunity

Any event that does not meet the specification of a CTQ. For DPMO method, defects or non-defects must be at least 5*.

Defect:

The item produced or processed – either a product or service transaction

Unit:

How these are operationally defined is critical to your data collection effort

*Additional methods for calculating Six Sigma are utilized when defects and non- defects are <5. These methods are an advanced statistical technique that will not be covered in this course.

Six Sigma Calculation Definitions – DPMO Method

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 There may be more than one defect opportunity per unit.  Ex. Fields on an invoice

 The opportunity for the defect must be important to the customer (relate directly to a CTQ).  Ex. Only count fields on an invoice that are requirements of

the customer  Don’t count every field, doing this can inflate the opportunities

and the sigma  Some defects may cause others. Only count the original defect

as the opportunity.

Guidelines for Determining Opportunity

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Unit Defect Opportunity

Invoice Incorrect fields identified by customer

The fields on the invoice

Employee Check

Customer Phone Call

Check not received on date specified

Call not answered within 30 seconds

Each check processed

Each customer call

Six Sigma Calculation Definition Examples

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General Worksheet for Calculating Process Sigma (DPMO)

1. Number of Units Processed (N) N = __________ 2. Total Number of Defects Made (D)

(Include Defects Made and Later Fixed) D = __________ 3. Number of Defect Opportunities

Per Unit (O) O = __________

4. Solve for Defects Per Million DPMO = 1,000,000 X Opportunities

=1,000,000 X

= __________ 5. Look up Process Sigma in an Abridged

Sigma Conversion Table = __________ Sigma

D N•O

( ) ( ) ( )

Sigma Calculator

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Unit Defect Opportunity

Employee Check

Check not received on date specified

Each check processed

Unit = Employee Processed Checks

Critical to Quality (CTQ) = 5th of each month

Defects: Checks received after 5th

Total Opportunities

Calculating Process Sigma (DPMO) Example

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Calculating Process Sigma (DPMO) Example

1. Number of Units Processed (employee checks) N = __________ 2. Total Number of Defects Made

(checks received after the 5th) D = __________ 3. Number of Defect Opportunities

Per Unit (each check) O = __________

4. Solve for Defects Per Million DPMO = 1,000,000 X Opportunities

=1,000,000 X = 356,000

1,000

356

1

D N•O

( ) ( ) ( )

356 1,000 1

A company that pays its employees on the 5th of the month, has collected data on the number of checks that are received by the employee after the required date.

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Yield Sigma DPMO Yield Sigma DPMO 99.99966% 6.00 3.4 98.60966% 3.70 13,903 99.99946% 5.90 5.4 98.21356% 3.60 17,864 99.99915% 5.80 8.5 97.72499% 3.50 22,750 99.99867% 5.70 13 97.12834% 3.40 28,717 99.99793% 5.60 21 96.40697% 3.30 35,930 99.99683% 5.50 32 95.54345% 3.20 44,565 99.99519% 5.40 48 94.52007% 3.10 54,799 99.99277% 5.30 72 93.31928% 3.00 66,807 99.98922% 5.20 108 91.92433% 2.90 80,757 99.98409% 5.10 159 90.31995% 2.80 96,800 99.97674% 5.00 233 88.49303% 2.70 115,070 99.96631% 4.90 337 86.43339% 2.60 135,666 99.95166% 4.80 483 84.13447% 2.50 158,655 99.93129% 4.70 687 81.99519% 2.40 184,060 99.90323% 4.60 968 78.81446% 2.30 211,855 99.86501% 4.50 1,350 75.80363% 2.20 241,964 99.81342% 4.40 1,866 72.57469% 2.10 274,253 99.74449% 4.30 2,555 69.14625% 2.00 308,538 99.65330% 4.20 3,467 65.54217% 1.90 344,578 99.53388% 4.10 4,661 61.79114% 1.80 382,089 99.37903% 4.00 6,210 57.92597% 1.70 420,740 99.18025% 3.90 8,198 53.98278% 1.60 460,172 98.92759% 3.80 10,724 50.00000% 1.50 500,000

Abridged Sigma Table (For calculation of long-term sigma, subtract 1.5 sigma)

4. Solve for Defects Per Million Opportunities = 5. Look up Process Sigma in an Abridged

Sigma Conversion Table = __________ Sigma 1.90

356,000

Calculating Process Sigma (DPMO) Example

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Time

Co nt

in uo

us D

at a

Long-Term Data

Short-Term Data

The amount of variation in the process is influenced by whether the data is long-term or short-term.

 Long-Term Data – Data that is collected over a long enough

period of time that it contains the diversity of conditions within the process to contain large process shifts and special causes.

 Short-Term Data – Data that is collected over a short enough

period of time that large shifts and special causes are not likely to occur.

For the purposes of this training, all data (continuous and discrete) will be treated as long-term data and contain short-term process sigma's that are automatically built into the Abridged Sigma Table.

Long-Term vs. Short-Term Data

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What you learned during this section:

 The concept and benefits of utilizing sigma

 How sigma relates to process capability

 How to calculate baseline performance with sigma

Summary of Section

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

Yield

Sigma

Measure – Baseline Performance

Lean Six Sigma Training

Process Capability

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 Understand the concept of process yield

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Buy Seed

Sell Corn

Plant Seed

Gather Corn

45,000 PPM Wasted

95.5% Yield Following Excess Disposed and Lost Seed…

21,965 PPM Wasted

97.7% Yield Following Damaged and Underdeveloped Corn…

46,652 PPM Wasted

95.0% Yield Available to Sell After Packaging

113,617 Parts Per Million Wasted Opportunities

Concept of Yield

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Yield and Defect Counts are related measures

Ex. 356,000Ex. 0.356Ex. 64%

= 1,000,000 ●== 1 -

The count of defects per opportunity times 1 million

in products or services

The count of defects per opportunity in

products or services

The % of good products or

services

Defects per Million Opportunity (DPMO)

Defects per Opportunity

(DPO)

Yield

D N•O

D N•O

D N•O

Yield and Defect Count

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If you were the VP of a company and these were current process performance figures, how would you know which process is performing better?

Customer Service Speed of answer is 20 seconds

Process Performance Sigma

Systems

Loan Processing

Systems up time is 95%

Loans processed on average 15 days

4.8 Sigma

3.2 Sigma

2.1 Sigma

Why Having a Common Metric for Comparison is Critical

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Notes: With sigma included, we have a common metric in order to gauge process performance. Loan Processing is not meeting customer requirements based on the low sigma.

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What you learned during this section:

 The concept of process yield

Summary of Section

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

Yield

Sigma

Measure – Baseline Performance

Lean Six Sigma Training

Process Capability

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Overview – Objectives – Key Topics

 Understand the concept of Process Capability

 Understand the necessary data and calculations to determine Process Capability

 Calculate Process Capability

By the end of this section, you will be able to:

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What is Process Capability

Process Capability measures the Voice of Process against its ability to meet Customer Requirements (Voice of the Customer).

Voice of the Customer

Voice of Process

U pp

er S

pe ci

fic at

io n

Li m

it

Lo w

er S

pe ci

fic at

io n

Li m

it

Is this process capable of meeting customer requirements?

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Why Process Capability

 Provides a single value to assess the capability of a process in meeting customer expectations.

 Evaluates the baseline of a process against customer expectations.

 Validates the capability of a process over time.

 Validates the capability of a pilot against expected results.

 Capability indices are without a unit (i.e. does not have a value like minutes, dollars, etc,) therefore you can compare one process to another.

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Process Capability Assumptions

 Data is normally* distributed

 Data is continuous*

 Process is in statistical control

 Data is time ordered

*Process Capability can be calculated for non-normal data and discrete data. This course will only cover calculating Process Capability for normal continuous data.

1019181716151413121111

30

15

0

In di

vi du

al V

al ue

_ X=15.42

UCL=29.74

LCL=1.10

1019181716151413121111

20

10

0

M ov

in g

R an

ge

__ MR=5.38

UCL=17.59

LCL=0

I Chart

Moving Range Chart

Control Chart for Cycle Time

3020100

Normal Prob Plot A D: 0.580, P: 0.128

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Capability Roadmap for Normal Continuous Data

Start

YES NO

LSL USL

Is Short Term Data

Available ?

Conduct Capability Analysis & Specify Subgroup Size for Short Term “Subgroup

Data Set”

Conduct Capability Analysis in Long Term with

Subgroup Size of “1”

Note: Look at Both Short Term

& Long Term Data

Note: Only Look at Long Term

Results

Conduct Analysis

Calculate Sigma Levels To Further

Understand Results (not covered in this

course)

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Process Capability Definitions – Capability Indices

 Cp (short term data) or Pp (long term data) = Potential capability of the process or the ratio of the Specification Range (Voice of the Customer) to the natural range of the process, it does not look at how well the process average is centered to the target value. This value gives you an idea of whether the process could meet customer requirements.

Example: Let’s say you are driving your car into your garage, Cp tells you if you are capable in the short term of fitting into the garage or not. It does not tell you if the driver has driven in straight or centered the car properly. Pp tells you if you are capable of fitting into the garage over the long term.

 Cpk (short term data) or Ppk (long term data) = Actual capability of the process and takes into account the location of the process average.

Example: Let’s say you are driving your car into your garage, Cpk tells you if you are capable in the short term of fitting into the garage or not, and if the driver has driven in straight or centered the car properly. Ppk tells you if you are capable of fitting into the garage in the long term and if the driver has driven in straight or centered the car properly.

Note: The problem with Cp or Pp is that it is a theoretical capability (entitlement) and you cannot compare two processes that have the same Cp or Pp when one is off center (obviously creating defects).

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Calculating Process Capability

 Step 1: Identify/Calculate the following from your data:

a. Identify Specification Range

 Upper Specification Limit: USL

and/or

 Lower Specification Limit: LSL

b. Calculate the Process Range

 Standard Deviation: “s”

c. Calculate the Location of the Process

 Process Average: “X”

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Calculating Process Capability

 Step 2: Determine if your data is Short Term or Long Term. Data tends to vary over time due to many internal and external factors. It is important to separate short term from long term data in order to determine current process capability.  Short Term data generally does not include special cause

variation.

Example: data collected only for: 1 day, 1 operator, or 1 call center rep.

 Long Term data includes the effects of special cause variation. This means that you have collected enough data over a long enough period of time to be confident that you have seen 80% of the process variation. This is the variation that the customer actually experiences over the long term. Example: data collected for multiple: days, operators, or call center reps.

Time

A

B

D

C

A + B + C + D

The truth about process capability is Long Term. So you have to determine what type of data you have and convert it from Short Term

to Long Term.

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Notes: Sigma values for Long Term data are generally lower than Sigma values for Short Term data. The difference between the two is called Sigma Shift. The Sigma Shift from Long Term to Short Term is 1.5 Sigma. Example, to convert Short Term Sigma into Long Term Sigma you will need to subtract 1.5 Sigma from the Short Term Sigma value.

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Calculating Process Capability

 Interpreting Cp and Pp Values:

 Above 1.33 is acceptable and capable of meeting customer expectations

In general, the higher the Cp or Pp value, the more capable your process is.

 Cp or Pp Interpretation Example: A value of 1 would mean the Specification range and the Process range are the same and that any variation would mean the process could easily not meet the customer requirements therefore 1.3 and greater is acceptable.

 Step 3: Calculate and Interpret Process Capability

 Cp (short term data) or Pp (long term data) =

Voice of Customer

Voice of the Process

USL - LSL

6 * s =

Requires both USL and LSL

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Calculating Process Capability

 Step 3: Calculate and Interpret Process Capability

 Cpk (short term data) or Ppk (long term data)=

 Interpreting Cpk and Ppk Values:

 Below 1.0 is generally not acceptable for meeting customer expectations

 Above 1.33 is acceptable and capable of meeting customer expectations

Min*: In the case that you have both USL and LSL, calculate both values and report the lower value.

Note: Cpk or Ppk divides the formula of Cp or Pp into 2 and takes into account where the process is situated.

38

Cpk or Ppk = Min* USL - X

3 * s

X - LSL

3 * s or

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Notes: Cpk or Ppk & Z score (Z score = the number of standard deviations that can fit between the mean and the nearest customer specification limit). Something interesting that explains what range is acceptable and how short term, long term and Z score tie together. Cpk = Z(short term) / 3 & Ppk = Z(long term) / 3 or 3 * Cpk = Z(short term) So Z(short term) = 6 sigma then Cpk = 6/3 = Cpk of 2 Z (long term) = 6-1.5(shift for conversion to long term from short term) = Ppk 4.5/3 = 1.5 So a capability of 1 means the process is just capable and 2 is Six Sigma so the range has to depend on the requirements of the process. Some processes need to be closer to 2 and for others it is okay to be at 1.

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Summary of Section

What you learned during this section:

 The concept of Process Capability

 The necessary data and calculations to determine Process Capability

 How to calculate Process Capability

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Define Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine Measure ControlAnalyze ImproveDefine MeasureMeasure ControlControlAnalyzeAnalyze ImproveImprove

End of Lesson: Measure – Baseline Performance

Lean Six Sigma Training

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Analyze Phase

Lean Six Sigma Training

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Analyze Phase Overview

Lean Six Sigma Training

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In Analyze, the questions of why the organization is unable to meet customer requirements is understood. Analyze utilizes both process and data analysis techniques to drill down to the root cause problems that will ultimately lead to solutions.

Analyze also keeps the team from jumping to premature solutions from Measure.

Analyze Phase Introduction

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 Identify Potential Root Causes

 Identify Value Added and Non- Value Added Processes

 Identify Cause and Effect Relationships

 Analyze the Data and Process to Determine Root Causes

ANALYZE

CONTROL

IMPROVE

MEASURE

DEFINE

Why are customer hold times so long?

Machinery

Methods

People Inconsistent processes

Too much rework

Systems do not interact

Too much review

Use different technology platforms

Customer information is not easy to access

Reps are not well trained

International Products “As-Is” Process Map (Page 1)

R ea

l Es

ta te

Ag en

t (R

A)

IP M

or tg

ag e

Sa le

s As

so ci

at e

(M SA

)

IP L

oa n

Pr oc

es so

r (L

P)

IP L

oa n

O ffi

ce r

(L O

)

H om

e Lo

an C

us to

m er

Contact RA to request loan

Mail loan application to

customer

Complete loan application

Mail loan application to

RA

Forward application to

MSA

Forward application to

LP

Review application

Request additional info from customer

Gather additional

information

Mail additional information to

LP

Go to Step 12 (Next Page)

Review application

and additional information

1

2

3 4

5

6

7 8

9 10

11

X = Non-Value Added Step

X

X

X X X

X

X

X

X

y = 15.213x + 0.7012 R2 = 0.5149

0

1

2

3

4

5

0.00 0.05 0.10 0.15 0.20 0.25

% of Defective Incoming Applications

# o f F

in al

De te

rm in

at io

n Pa

ck ag

es w

ith E

rro rs

Analyze Phase Overview

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 Necessary to identify the “real” root causes of a problem

 Ensures accurate focus on the real culprit so we avoid jumping to the wrong conclusions and solutions

 Enables understanding of the magnitude of the problem

 Provides understanding of what is causing variation

Why Analyze is So Important

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Process Variables (Xs)

Process

Input Variables

(Xs)

Outputs (Ys)

Analyze the Process to Identify the Critical X’s

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Notes: Definitions Outputs Product or service produced or delivered �by the process. Process Variables (Xs) Those variables that influence the output and are generally controllable by those who operate the process. Input Variables (Xs) Materials and information used by the process to create the outputs. Inputs are often outside the control of the internal operations group.

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For every process there is a dependent variable called Y that we are attempting to influence. The independent variables which determine what happens to our Y are called the process X’s. Thus, we can boil down every process into a simple formula:

The goal of analyze is to understand the relationship between our various Xs and our Y, so we can manipulate the Xs to modify Y as desired, then lock down the process so that Y remains within the proper range and is meeting customer requirements.

The Focus of Process Analysis

Y = f(x1,x2,x3…xn)

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Process Variables (Xs)

Process

Input Variables

(Xs)

Outputs (Ys)

Narrow down to the vital few process X’s that will be useful in indicating the final process output (measures conformance

to CTQ)

Identify which of these has the greatest impact or affect on the

output and its performance against the customer

requirements

The performance of the Y indicates whether

customer requirements have been met or not

Analyze Which are the Most Critical Process Variables

Y = f(x1,x2,x3…xn)

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Process Door Data Door

0

2

4

6

8

10

12

In the analyze phase, improvement teams will go through both the process “door” and the data “door” using both process tools and data tools to identify and validate root causes.

Analyze Phase Overview

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Notes: It is recommended to go through both “doors” to make sure that potential causes and opportunities are not overlooked and true root causes are validated by statistical analysis.

Chart1

2 5 6 7 10 8 6 3 2

Sheet1

2 5 6 7 10 8 6 3 2

Sheet1

Sheet2

Sheet3

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Analyze the Process

Develop Theories

and Formulate Potential Causes

Analyze the Data

Understand Cause and Effect and Verify Root

Causes

• Process Value Analysis

• Lean Measures

• Value Stream Mapping

• Error Proofing

• 5s and Waste

• Fishbone Diagram

• 5 Whys

• Histogram

• Pareto

• Box Plot

• Scatter Diagram

• Regression

Analyze Tools

Analyze Approach

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Analyze Phase Deliverables

Define Measure Analyze Improve Control

Project Charter Project Management

Project Plan Process Definition

SIPOC As-Is Process

Map Quick Win

Identification Stakeholder

Management Stakeholder Map Stakeholder

Management Plan Communication

Plan Voice of Customer

Customer Identification

VOC Research Plan

Kano Analysis CTQ Identification

 Root Cause Analysis Affinity Diagram Fishbone Diagram

and/or 5 Why’s Lean Process

Analysis Lean Tools and

Measures Graphical Data

Analysis Histogram Pareto Chart Box Plots Correlation

Analysis Statistical Data

Analysis Linear Regression Multiple

Regression Root Causes

Identified Quick Win

Identification

Identify Measures X/Y Matrix

Data Collection Operational

Definitions Measurement

Systems Analysis (MSA)

Data Collection Plan

Describe and Display Data Histogram Pareto Chart Pie Chart Run Chart Control Charts

Baseline Performance Sigma

Performance Yield Process

Capability Quick Win

Identification

Identify and Select Solutions Generate Solutions Benchmarking Solutions

Prioritization Matrix Solution Selection

Matrix To-Be Process Map

Financial Impact of Solutions Cost/Benefit Analysis

Risk Planning and Testing Failure Modes and

Effects Analysis (FMEA)

Pilot Plan Implement Solutions

Multi-Generational Product Plan (MGPP)

Implementation Plan Stakeholder

Management Project Storyboard

Process Control Control Charts Process

Monitoring Plan Dashboard

Response Plan Project

Documentation Process

Procedures Replication

Opportunities Solution Transfer

Plan

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End of Lesson: Analyze Phase Overview

Lean Six Sigma Training

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

Analyze – Root Cause Analysis

Lean Six Sigma Training

Root Cause Analysis

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 Understand how to use an affinity diagram to identify and organize potential root causes

 Learn how to develop and analyze a cause and effect diagram

 Understand how the “five why’s” technique can guide a team to identify deeper root causes

By the end of this lesson, you will be able to:

Overview – Objectives – Key Topics

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Identifying Potential Causes – Where to Begin?

Add res

s

Inac cur

ate

Line Item T

ota l

Am oun

t Ove rch

arg e

Oth ers

42 32 14 9 3 42.0 32.0 14.0 9.0 3.0

42.0 74.0 88.0 97.0 100.0

0

50

100

0

20

40

60

80

100

Defect

Count Percent Cum %

Pe rc

en t

C ou

nt

Pareto Chart for Statement Accuracy

9080706050403020100

60

50

40

30

20

10

0

Average Hold Time

# of

C al

ls

January Avg. Hold Time Distribution Plot

 A good starting point for analysis is to go back to the data that was collected and graphed during the Measure phase to begin to formulate possible causes

 The data display tools that were conducted in Measure that described the process and indicated information on variation, distribution, and defects can be helpful in developing theories on potential causes

I-MR or Individuals Control Chart

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Identifying Potential Causes – Where to Begin?

Add res

s

Inac cur

ate

Line Item T

ota l

Am oun

t Ove rch

arg e

Oth ers

42 32 14 9 3 42.0 32.0 14.0 9.0 3.0

42.0 74.0 88.0 97.0 100.0

0

50

100

0

20

40

60

80

100

Defect

Count Percent Cum %

Pe rc

en t

C ou

nt

Pareto Chart for Statement Accuracy Pareto Chart

 The largest defect/problem area(s) indicated on the Pareto point to the section(s) of the process the team should focus on to formulate potential causes

 A Pareto can help prioritize analysis efforts

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 Brainstorming  Affinity diagram (previously seen

in define)  Cause and Effect Diagram

(Fishbone)  The “Five Why’s”

There are several tools that a team can employ to identify potential root causes. Some of these tools include:

These tools can be used as stand alone tools or in some cases in conjunction with one another to drill deeper into potential causes.

Lack of staffing

Poor Training

Missing info

Cause Cause

Cause

Cause

Cause

Cause

Cause

Cause

Cause

Cause

Cause

Cause

Identifying Potential Causes

EFFECT

Cause A

Cause D

Cause C

Cause B

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 Purpose  Brainstorming is a method of generating lots of ideas

quickly  Encourage creativity  Involve everyone  Generate excitement and energy  Separate people from ideas they suggest

 Uses in Analyze  Use brainstorming to generate a lot of potential causes

of the problem you defined in Measure  Key question is “why does that happen?”

Identifying Potential Causes – Brainstorming

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Brainstorming

1. Generation 2. Clarification 3. Evaluation

Brainstorming

 The Generation phase is a free open forum for all participants to generate ideas.

 During the Clarification phase of brainstorming, the team reviews the list to make sure everyone understands all the items.

 During the Evaluation phase of brainstorming, the team reviews the list to eliminate duplicates or combine like items.

Stages of Brainstorming

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Rules for Brainstorming:

 Clearly state purpose of what you are brainstorming

 Each person takes a turn, in sequence, around the group

 Present one thought at a time

 Do not criticize or discuss any idea

 Build on ideas of others

 Record ideas and make visible to the whole group (flipchart)

Brainstorming

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Problem: Why do 85% of claims take 37 days or longer to pay?

Lack of staffing

Poor Training Missing info

Process Difficult

Cause CauseCause

Cause A

Cause B

Cause C

Cause D

Cause E

Cause F

Cause ResponseCause ResponseCause ResponseCause ResponseCause G

Cause ResponseCause ResponseCause H

Cause I

Cause J

Cause K

Cause ResponseCause L

Cause M

Cause N

Like or similar causes

Cause Category

An affinity diagram can help a team organize brainstormed potential root causes

Good tool to use as pre-cursor to a fishbone diagram or 5 Why’s

Identify and Organize Potential Causes – Affinity Diagram

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Instructions for Affinity Diagram:

 Brainstorm potential causes of problem, write down the feedback on sticky notes.

 Post the stick notes to a white board or flip chart paper.

 Once completed, sort issues into 4 – 8 related groups.

 Create a summary issue category for each issue group. Make sure everyone agrees to headings.

Identify and Organize Potential Causes – Affinity Diagram

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 Finds major themes out of large number of ideas

 Groups items that are naturally related

 Identifies one concept that ties each grouping together

 Creative, rather than logical

 Good tool to facilitate consensus on major cause categories

Affinity Diagram Summary

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Fishbone diagrams, also known as “cause-and-effect” diagrams, are employed to help teams brainstorm possible causes of a problem (or effect) and rationally group potential causes together. This diagram is called a fishbone as it resembles the skeletal structure of a fish once completed.

Fishbone Diagram

Problem Statement

Main Category A

Main Category C

Main Category B

Potential Root Cause

Cause

Cause

Cause

Potential Root Cause

Potential Root Cause

Primary Effect

Potential Causes

Identify Potential Causes – Fishbone Diagram

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Notes: A Fishbone Diagram (also known as a Cause and Effect diagram is the starting point for analysis. Based on the organizations experience, a problem is drilled down to potential causes by asking the question “Why”, thus showing the cause of each effect until the team is satisfied that they have reached the low-level cause (potential root cause). These low-level causes are then validated through data analysis.

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Fishbone diagrams link potential causes to effects

 To brainstorm potential root causes to a problem (effect)

 To identify reoccurring causes across multiple fishbone categories

 To create a visual picture that identifies the link between cause and effect

 To provide areas (potential causes) where data can be collected for root cause validation

Fishbone…

...Get it?

Fishbone Diagram Uses

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STEP 1: Draw a box on the far right-hand side of the paper with a horizontal arrow to the box and write the description of the problem in the box.

It is critical for the team to agree upon the problem under study. In most cases, the problem will be identical to the definition of Y.

STEP 2: As a team, come to consensus on the 4-5 major cause categories to use on the fishbone diagram. Write the names of the major cause categories above and below the horizontal line. Connect them to the “back bone” of the fish.

EFFECT

Cause C Cause A

Cause BCause D

How to Construct a Fishbone Diagram

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STEP 3: Brainstorm a list of possible causes that could be driving the problem.

Brainstorming can be done by category or can be done prior to placing the potential causes on the major bones. It is recommended that the entire list of possible causes be generated first before attempting to place them on the major category bones. This keeps the creative flow of ideas.

STEP 4: Place the brainstormed data causes in the appropriate category.

STEP 5: For each cause, drill down into “causes of the causes” by asking repeatedly, “why does this happen?” Arrange contributing causes on the smaller bones.

STEP 6: Select 2-3 potential root causes from the fishbone diagram to verify with data.

Look for causes that appear repeatedly within or across major bones. Use multi-voting to narrow down the list of potential causes and come to consensus on 2-3 potential root causes from the fishbone diagram to drill down on further with additional analysis tools.

STEP 7: Select possible causes to verify with data.

How to Construct a Fishbone Diagram

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 Machines (equipment)  Methods/procedures (how work is done/tasks and steps)  Materials (components or raw materials)  People (the human element)  Mother Nature (Environment)  Measurement (data collection)  Policies (higher level decision rules)

Typical categories utilized for the major bones of the fishbone are the following:

Other possible categories are:

 Utilize the major steps of the process in place of the major cause categories listed above.

Note: The key is to select categories that are relevant to the problem that the team is improving.

Fishbone Diagram Categories

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Why are customer hold times so long?

Machinery

Methods

People Inconsistent processes

Too much rework

Systems do not interact

Too much review

Use different technology platforms

Customer information is not easy to access

Reps are not well trained

Potential Causes

Call Center Fishbone Diagram Example

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Notes: The call center team completed their cause and effect analysis utilizing a fishbone diagram and determined 3 potential root causes.

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The Five Why’s technique is a classic approach to root cause analysis of a problem situation by asking the question “Why?” a number of times. While the name of the approach contemplates 5 iterations, this is a recommendation only.

True root causes generally are deep, not as simple as first suspected. In order to get long lasting and far reaching corrective actions in place, the true root cause must be found. If problems are identified before enough questions are addressed, then the problems will diminish at first, but will often resurface.

The “5 Why’s” technique digs deep into the root of the problem

The Five Why’s technique can be used in conjunction with a fishbone diagram to identify potential root causes or can be used as a stand alone tool to formulate potential root causes.

Identify Potential Causes – The Five Why’s 5 Whys

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WHY? Why do we have an increase in customer complaints?

Because of late orders.

Why don’t the orders leave the store in time? Because the cooks receive the order 10 minutes after the call was

received, not instantly as they should.

Why do the cooks receive the orders 10 minutes after the calls were received?

Because the new order entry method takes longer.

Why do we have late orders? Because the orders don’t leave the restaurant in time.

Why does the new order-entry method take longer? Because the employees were not properly trained.

WHY?

WHY?

WHY?

WHY?

The Potential Root Cause - Employee Order Entry Training Deficiency

The Five Why’s Example

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 Helps assign a cause to the correct sub-category

 Guides team to deeper root causes

 Provides link from effect to cause

Purpose of the Five Why’s

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What you learned during this lesson:

 How to use an affinity diagram to identify and organize potential root causes

 How to develop and analyze a cause and effect diagram

 How to use the “five why’s” technique to guide a team to identify deeper root causes

Summary of Lesson

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

End of Lesson: Analyze – Root Cause Analysis

Lean Six Sigma Training

Root Cause Analysis

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

Lean Techniques

Lean Process Analysis and Measures

Analyze – Lean Process Analysis

Lean Six Sigma Training

Lean Process Analysis

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 Understand the purpose of process analysis

 Understand how to calculate Lean measures of time

 Understand how to analyze a process to identify potential causes and effects

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Process Door

 To analyze and understand current process flow

 To identify process efficiency problems and bottlenecks

 To establish cause and effect relationships

Detailed Process Maps

Value Added Analysis

Cycle Time Analysis

Process Door

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To get results, we need to focus in on the X’s

Focus on the Process

 Y  Dependent  Output  Effect  Symptom  Monitor

 X1...XN

 Independent

 Input or Process

 Cause

 Problem

 Control

Response Predictor

x

x

x

xx x

x x

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Notes: Understanding variation requires understanding the relationship between the process response (Y) and the process predictors (Xs).�� Y = f (X1, X2 , . . . , XN )� The process predictors (Xs) affect (drive) the process outputs (Y).

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Process - Level 1

Step #1

Process - Level 2

Step #1 Step #2

Process - Level 3

Step #3

Step #1 Step #2 Step #3

Step #3

Step #2

Process analysis is typically focused on a level 3 process or

below

To highlight process problems, break out process

steps in detail

Selecting the Right Level for Process Analysis

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 Drilling down into a detailed process map can provide clues for what is causing our process to not meet CTQ’s

 It can help a team begin to identify and formulate what the potential critical X’s are which might be driving the problem and process variation.

 Enables a team to identify process streamlining opportunities

1. Activity

Yes

No

Yes

No

2. Activity

3. Activity

Process Analysis

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Review the Detailed Process Map and Identify “Points of Pain”  Examine steps that experience has shown are problem area or “points of pain”.

Example: Areas of rework, long delay, or errors

 Examine steps that have long cycle times

 Examine decision points and handoffs where the process moves from one process customer to the next

X1 Inputs to the process

X2 “Rework” loops – rework points

X3 At the end of major process steps

X4 Hand-offs between departments

5 m

in 10

m in

Customer Claims

Reviewer Claims

Adjuster

Y N

X1

X2

X4

X5

X3

X1

Y

?

Y Output (Measure of conformance to CTQ)

Drilling Down in the Process to Identify Potential X’s

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Analysis Techniques – Lean and Six Sigma

Six SigmaLean

Effect

Cause A

Cause D

Cause C

Cause B

Quality and Efficiency Improvement

Efficiency Improvement

Combining Lean and Six Sigma is Best in Class

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What is Lean?

Lean is utilized for the following purposes:

 To reduce or eliminate capacity constraints of the process

 To reduce the lead time of the process

Inputs Step 1 Step 2 Step 3 Step 4

Bottleneck

Outputs

2 Days 10 Days 4 Days 6 DaysInputs Outputs

=22 Days

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Lean Definition

The AIM of Lean is to eliminate waste in every area including:

 Customer relations  Product design  Supplier networks  And office management

Its GOAL is to incorporate:

 Less human effort  Less inventory  Less time to develop products  And less space to become highly responsive to customer demand

while producing top quality services in the most efficient and economical manner possible

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Lean Concepts – Measures of Time

Lead Time: Amount of Time a unit spends in the process  Lead Time (T) = Cycle time (Value Add) and Inactive Time (Non Value Add)  Advantages of Short Lead Times  Customer satisfaction through increased responsiveness  Reduced inventory at constant throughput  Reduced working capital  Increased throughput at constant inventory levels  Increases accuracy

Lead Time

Non Value Add

Value Add

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Lean Concepts – Measures of Time

Cycle Time: Total time that elapses from the beginning of a process step until its completion. It is the time a unit is being worked on.

12 min

1 min

15 min

Cycle Time

Start Finish

Cycle Time

Cycle Time

Reference: Value Stream Management for the Lean Office: Don Tapping and Tom Shuker

Total Process Cycle Time = 28 minutes

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Elements of Cycle Time

Cycle Time

Value Added

Value Activities Decisions

Non Value Added

Transport Inspection Over Processing Defects / Rework

Over Processing

Lead Time can be reduced by

eliminating Non- Value Added

Activities

Lead Time can be reduced by

reducing the cycle time of value

added activities

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Lean Efficiency Metrics:  Measure need to reflect how efficiently you

are utilizing time and resources  Look at what happens to time and how

efficiently we use it.  Here we will learn the Lean Efficiency

Metrics of:

Applying Lean Can Improve Efficiency

Lean Efficiency Metrics

14

- Utilization - Efficiency - Quality - Overall Resource Effectiveness

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What Happens to Time

*Service Time = Standard Service Time multiplied by the Quantity Serviced

15

Total Time = Total time in the shift

Target Time = Total Time less planned breaks & shutdowns

Available Time = Target Time less lost time

Effective Time Serviced**

Service Time*

450 min.

210 min.

120 min.

1

2

3

4

5

480 min.

540 min.

Example:

**Effective Time Serviced = Standard Service Time multiplied by the number of good units produced.

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Lean Efficiency Metrics

 Utilization, the % of time made available for service

 Efficiency, how well did we work while we were working

 Quality, the % Good units we serviced out of the total units serviced

 ORE (Overall Resource Effectiveness), the % of time that we spent and got back in good units

16

Utilization = Available Time/Target Time

Efficiency = Service Time/Available Time

Quality = Effective Time Serviced/Service Time

ORE = Effective Time Serviced/Target Time

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Lean Process Analysis Tool – Process Value Analysis

Non Value-Added Work • Customer does not recognize value in the step • Step is not done right the first time • Step does not change the process

Value-Added Work • Customer recognizes the value in the step • Step is done right the first time • Step changes the process

Examples of Non Value-Added Work

Delay Steps “Re” Steps (ex. Re-Work)

“Checker Checking the Checker”

Approvals

Back Office

Internal Failure

External Failures

Hand-offs

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Notes: Any steps in the process not meeting value-added criteria is considered non value-added work.

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Lean Analysis – Process Value Analysis Process Value

Analysis

Process Step 1 2 3 4 5 6 7 8 9 Total % Total

Time (Hours) 100%

Value-Added

Non Value-Added

Delay

Set-up

Inspection

Transporting

Rework

Total

To better understand the process  Review detailed process map (deployment flow chart)

 Identify which of the process steps are value-added and which are non value-added

 Determine cycle time and identify bottlenecks

 Look for errors or inefficiencies that contribute to defects

Value-Added Questions: 1.Change the process? 2.Customer recognizes the value? 3.Done right the first time? 4.Required by law or regulation?

Non Value-Added Examples: - Waiting - Storing - Counting - Inspecting - Recording - Obtaining - Approvals - Reviewing - Copying - Reworking - Filing - Tracking

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Lean Analysis – Process Value Analysis

 To easily identify non value-add steps in the process, the following symbols can be used to label non value-added activity on the process map:

 D = Delay

 S = Set-up

 I = Inspection

 T = Transporting

 R = Rework

 Lean Six Sigma teams can develop and customize symbols as necessary

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Lean Process Analysis

Analyzing a process is a valuable tool for identifying process disconnects such as:

By linking the cycle time (hours/minutes) with the process analysis, we can begin to develop a complete picture of the need for change and where this change should occur.

 Process gaps

 Redundant work

 Implicit or unclear requirements

 Tricky hand-offs

 Conflicting objectives

 Common problem areas

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What you learned during this section:

Summary of Section

 The purpose of process analysis

 How to calculate Lean measures of time

 How to analyze a process to identify potential causes and effects

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

Lean Techniques

Lean Process Analysis and Measures

Analyze – Lean Process Analysis

Lean Six Sigma Training

Lean Process Analysis

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 Understand how to identify the process value stream

 Understand how to indentify opportunities to implement error proofing techniques

 Determine how to identify waste in your process

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Lean Analysis Techniques

5s & WasteError ProofingValue Stream

Identify the Process Value Stream

Implement Process Checks to Identify and Fix Incoming / Outgoing Errors

Clean Up the Work Environment and

Standardize Processes

I P O Inputs Process Outputs

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Lean Analysis Techniques – Value Stream

 Successful companies are sustainable in the long term because they define value from the Customer’s perspective

The Flow of Units through a process that produce value to the customer is a Value Stream

 Identifying the Value Streams and what value the Customer is prepared to pay for in the Value Stream is the first step in creating a better flow.

For each Value Stream, identify the customer’s needs and their demand

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What is Value?

 Value is defined in terms of specific products and services having specific capabilities, offered at specific prices to specific customers, to be delivered defect- free at specific times

 Value must be viewed in terms of the entire Customer Experience

 Any action or resource expenditure that does not contribute directly to the goal of creating value is Waste (Muda) and should be eliminated to the greatest extent possible

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Difference Between Waste and Value

In assessing a process, it is important to understand what activities in the process actually add value to the end result, all other activities are wasteful

 CVA (Customer Value-Added - or just VA for Value-Added): an activity that the customer would be willing to pay for in isolation if they knew it was being done – e.g. Implementing functionality to a product/process

 BVA (Business Value-Added - non-negotiable waste): an activity that is required to operate the business but the customer is unwilling to pay for – e.g. Budget tracking, code documentation

 NVA (Non Value-Added): an activity that is not required by the business nor is the customer willing to pay for – e.g. Waiting for resource allocation, requirements documents

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The Value Stream

Suppliers Your Company Customer

TOTAL VALUE STREAM

The flow of activity required to turn raw materials into

finished products Fit for purpose, for use by

the end customer

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Implement Flow in the Value Stream

 Standardize work Mistake proof processes  Achieve process control  Implement self inspection Cross train workforce Reduce set up times  Implement visual controls

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Value Stream Mapping

 Value Stream Mapping is a pencil and paper tool that helps you to see and understand the flow of material and information as an order makes its way through your transactional process.

 Value stream mapping is a way to evaluate the current transactional process, identify the value-added steps, and envision the improved (future) transactional process.

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General Icons used in Value Stream Mapping

Dedicated Process Box

Customer or Supplier

Mail Delivery Database (Excel, Access, etc)

Queue Time

Schedule Box

Schedule

Worker

Shared Process Box

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General Icons used in Value Stream Mapping

Push Arrow

Manual Information Flow

Exceptions or Disruptions

Electronic Information Flow

F I F O Max. 5 pieces

First In First Out Sequence Flow

Kaizen Focus

Physical Material

Pull

Non Value-Added Time

Value-Added Time

hrs/min hrs/min

hrs/min

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Value Stream Mapping Example

Customers

Orders processed within 1 day

Central Mail Sort

Joe

Sort orders To depts/5s

Place in out Box/5s

Sales Mail Sort

Debbie

Sort orders By customer

Date stamp/ 2s

Place for CSR/10s

Initiate Order

CSR 1 - Susan/Cathy

Initiate Order /45s Per line

Check Parts Numbers

CSR 2 - John/Jane

Check part# 10s per line

Attach Revisions/ 10s

Assign part# 15s per line

Assign Delivery Date

CSR 1 - Susan/Cathy

Assign Delivery date/30s line

File hard copy /90s

Verify Order

CSR 2 - John/Jane

Review/15s per line

Sales Mail Sort

Debbie

Sort/30s

Central Mail Sort

Joe

Post order/30s

8 Hrs 4 Hrs 4 Hrs 2 Hrs 1 Hr 4 Hrs 4 Hrs 8 Hrs

Schedule

8:00, 2:00 & 3:00

3 x Daily

Mail Orders

Order Acknowledgements

1 x Daily

Phone Orders (Expedited)

Faxed Orders

.16

480

.28

240

11.25

240 120 60 240 240 480

23.75 9 3.75 5 5

NVA / VA Minutes

Lead Time 33

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Notes: Background to this VSM example: A Lean Six Sigma team chose to focus on the Value Stream Map for orders for its customers. The main processes were determined and are as follows: Central mail sort – Joe; Sales mail sort – Debbie; Initiate Order – Customer sales rep 1 – Susan/Cathy; Check parts numbers – Customer sales rep 2 – Jane/John; Assign delivery date - Customer sales rep 1 – Susan/Cathy; Verify order - Customer sales rep 2 – Jane/John; Sales mail sort – Debbie; Central mail sort – Joe

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Tips for Value Stream Mapping

DO’s DON’T

• Do begin at the end and work your way upstream

• Don’t sit at the computer (Get up, walk around, and collect the required information)

• Do map things as they are, and not the way they are supposed to be

• Don’t try to map all of your process flows in one map (Its too confusing)

• Do map the value stream yourself and refrain from using the committee approach

• Don’t rely on standard times/information that you did not collect (Get a stopwatch and collect the data yourself)

• Do use a customer focus approach • Don’t try to map all the parts (Just flow a few of the main raw materials)

• Do walk the process, documenting as you go, and gathering information

• Don’t‘ be hasty, take your time as this is a very important exercise

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Lean Analysis Techniques – Error Proofing

Implementing process checks may be necessary to ensure quality and timely input and outputs. Examples include:  Inspecting inputs from suppliers and not accepting defective inputs

 Introducing required information on inputs

 Implementing auto correcting techniques

 Training employees on the process

 Inspecting outputs to ensure quality and timeliness before the customer is affected

I P O Inputs Process Outputs

Error Proofing Checks

*Additional information on Error Proofing will be covered in the Improve Phase

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Lean Analysis Techniques – 5s

Cleaning up the work environment will make it easier for employees to get to needed information.  Sort – Sort through the contents of a work area and

remove unnecessary items.

 Set – Set necessary items for easy and efficient access in demarcated areas.

 Shine – Clean everything to ensure that your workplace and equipment are properly maintained.

 Standardize – Create guidelines to keep the area organized, orderly and clean. You may also standardize the way you work by determining that work will flow using the FIFO principle (First-In, First- Out) – This means that first work in, is the first work to be processed (first out).

 Sustain – Educate and communicate to ensure that 5S standards are followed.

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Lean Analysis Techniques – Waste

WASTE IS...

 Any human activity which absorbs resource but creates NO VALUE – This is the direct translation of “Muda” the Japanese term for waste

 Use of resources over and above what is actually required to produce the product/service as defined by the customer

 If the customer does not need it or will not pay for it then it is waste

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Two Major Categories of Waste

1. Obvious Waste

2. Hidden Waste

Obvious waste is easily recognizable

 Examples: Undisciplined meetings, excessive paperwork systems, working ahead of schedule, and doing more than is actually required

Hidden waste refers to work which is necessary under current methods of operation, but could be eliminated if improved methods were adopted

 Examples: Poor office layout, excess overtime, excess labor

We must always strive to minimize the amount of resources utilized to create products and services. Identification and Elimination of all types of waste is imperative to succeed.

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8 Types Of Waste

There are 8 basic categories of waste:

MotionTransportation

Over-Processing

Waiting

Over-ProductionDefects / Rework

Inventory

SkillsHey Tim Woods!!

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Notes: “WHEN LOOKING FOR WASTE, BE LOOKING FOR “TIMWOODS”

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8 Types of Waste – Definitions TYPES OF WASTE DEFINITION

TRANSPORTATION Back and forth work - handling documents more than once, unnecessary moving or handling of work between departments

INVENTORY Any amount of work greater than single-piece flow. Excessive work in process (WIP), calls on hold, people waiting in line.

MOTION Movement of people that adds no value (searching for paperwork, quotes, supplies etc)

WAITING When work is sent from one department to another then waits for the next processing to occur (queues, time when no value is added to the product/service)

OVER-PRODUCTION Producing more than the next operation can handle.

OVER-PROCESSING Over-processing, unnecessary processing, or procedures (work carried out on the product/service which adds no value) often caused by bureaucracy

DEFECTS / REWORK Ineffective work practices that result in poor data collection and poor data entry – result in data integrity issues; wrong customer details

SKILLS Not listening to employees ideas or not asking them to use their brain and help solve problems

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Notes: The idea of 8 wastes is useful because it allows a company to categorize problems and then focus attention in the appropriate areas once they have been identified. There are many tools and techniques in the Lean tool box which can be applied to many areas of service in order to tackle any one of these wastes. Reference: http://www.swmas.co.uk/Lean_Tools/The_7_Wastes.php

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What you learned during this section:

Summary of Section

 How to identify the process value stream

 How to indentify opportunities to implement error proofing techniques

 How to identify waste in your process

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

End of Lesson: Analyze – Lean Process Analysis

Lean Six Sigma Training

Lean Process Analysis

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

Analyzing Data Graphically

Stratification

Data Analysis Overview

Analyze – Graphical Data Analysis

Lean Six Sigma Training

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 To understand the drivers of variation in the process

 To validate cause and effect relationships

 To understand the root cause of differences between inputs, process, and outputs

Stratification

Graphical Analysis

Hypothesis Testing

Regression

Experimentation

Data Door

0

2

4

6

8

10

12

Data Door

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Chart1

2 5 6 7 10 8 6 3 2

Sheet1

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0

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12

 The data door for Analyze functions more as a toolbox of tools and techniques than a step by step linear process. Depending on the problem that is being addressed and what the suspected causes are, the set of tools and the order of tools will vary according to the specific needs of each individual project.

 Depending on the problem being addressed, some teams will pass through all doors and some teams may only go through 1 door to identify root causes.

Graphical Data Analysis

Statistical Data Analysis

 Within the data door there are many different “doors” a team can pass through to analyze for root causes.

Data Door

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Chart1

2 5 6 7 10 8 6 3 2

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

Analyzing Data Graphically

Stratification

Data Analysis Overview

Analyze – Graphical Data Analysis

Lean Six Sigma Training

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 Know what stratification is and how it’s used in analysis

 Understand the importance of stratification

 Know common stratification factors

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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DATA

Process

Subset 1

Subset 2

Subset 3

 A data analysis technique by which data is sorted into various categories by specific factors

 Divides data into several subgroups with common themes that may be the cause of observed variation

 Enables suspicious patterns to surface

 Unveils differences in processes

 Allows for more accurate focus and prioritization of analysis efforts

Stratification – What it is and What it’s Used for

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-Region -City -Office site

Where

-Business Unit -Department -Individual

Who

-Year -Month -Week -Day

When

-Defect type -Problem type -Complaint type

Type of Category

ExampleFactor

Common Stratification Factors

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Notes: Stratification is critical to getting down to the deeper root cause level. However stratification should be balanced with the time it takes to analyze each factor. It is recommended that a team narrows their list of stratification factors down to 3-4 key categories of possible causes of variation. The most efficient way to stratify data is to identify what stratification factors you want to analyze prior to collecting data in the measure phase. Otherwise it may be necessary to collect more data.

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Example of “delivery time” data stratified by “day of week”

Monday Tuesday Wednesday Thursday Friday

D el

iv er

y Ti

m e

Since Tuesdays are consistently later than other days - the next step would be to look into Tuesday and analyze why

Examples of Stratification

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Example of trend data on complaints broken out by product type

Total Complaints

Month

Pr ob

le m

s

2000

2200

2400

2600

2800

3000

3200

1 2 113 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 21 22 23 24

Month

Product B Complaints

Pr ob

le m

s

300

500

700

900

1100

1300

1 2 113 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 21 22 23

Product A Complaints

Pr ob

le m

s

300

500

700

900

1100

1300

1 2 113 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 21 22 23

Month

Product C Complaints

Month

Pr ob

le m

s

300

500

700

900

1100

1300

1 2 113 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 21 22 23 24

Examples of Stratification

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What you learned during this section:

 What stratification is and how it’s used in analysis

 The importance of stratification

 Common stratification factors

Summary of Section

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

Analyzing Data Graphically

Stratification

Data Analysis Overview

Analyze – Graphical Data Analysis

Lean Six Sigma Training

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 Know how, why and when to use pareto charts, stratified histograms, box plots, and scatter diagrams (correlation analysis).

 Understand what type of data is required to use various analysis tools.

 Learn how to interpret pareto charts, histograms, box plots, and scatter diagrams.

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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 You most likely identified many potential causes through your fishbone diagram and process value analysis

 The potential cause is really a theory that two factors—a cause and an effect—are related

 You need data to verify whether the cause-and-effect relationship truly exists

 You can analyze historical data to test that theory, or collect new data  It’s possible the data you collected in the Measure phase can be

analyzed in new ways to answer your questions about cause-effect relationships

 Use other existing data only if you have confidence in its reliability and accuracy (presuming it is appropriate for your needs)

 If historical or existing data will not answer the questions you are now trying to answer or if the existing data is unreliable, then you must collect new data

Analyzing Data

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 Remember we are trying to identify which X’s (input/process variables) have the greatest impact on the process Y (output).

 There are a variety of graphical tools that can be used to examine the relationship between X’s and Y’s, the key is selecting the right tool.

 Selecting the right tool depends on the type of data for both X and Y.

 Some of the analysis tools have already been presented in the Measure phase, in this section we will summarize new tools that have not yet been fully presented.

9080706050403020100

60

50

40

30

20

10

0

Average Hold Time

# of

C al

ls

January Avg. Hold Time Distribution Plot

Potential Root Potential Root CausesCauses

Potential Root Potential Root CausesCauses

Tools for Analyzing Data Graphically

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 A Pareto chart is a graphical tool that assists in segmenting a large problem into multiple components and identifying which components are the most important

 Pareto charts rely on the Pareto Principle, postulated in the 19th century by Vilfredo Pareto, who found that 80 percent of Italy’s wealth was held by 20 percent of the Italian population.

 This 80/20 Rule applied to Lean Six Sigma says that 80% of the process defects are caused by 20% of the problems.

Pareto Chart

A B C D

50 10 6 5 70.4 14.1 8.5 7.0

70.4 84.5 93.0 100.0

0

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80

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Defect Count

Percent Cum %

Pe rc

en t

C ou

nt

Defects  Pareto charts are one of the

most widely used Lean Six Sigma tools

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 To analyze categorical or discrete data

 Aids in understanding the pattern of occurrence for a problem

 To identify the relative impact of various parts of a problem (quantifying the problem)

 To identify the biggest contributors to a problem

 Prioritizes where to focus analysis and improvement efforts

 Helps prevent “shifting the problem” where the solution removes some causes, but worsens others

Why Use a Pareto Chart

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You can use a Pareto Chart when:

 The problem under study can be broken down into categories

 You want to identify the “vital few” categories—focus your improvement effort

When to Use a Pareto Chart

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Understanding How to Read a Pareto

Add res

s

Inac cura

te

Line I te

m Tota l

Am oun

t Ove rcha

rge

Oth ers

0

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100

0

20

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100

Defect

Pe rc

en t

Co un

t Pareto Chart for Statement Accuracy

Height of vertical axis represents all occurrences

Bar height arranged in descending order with tallest bar on left, shows relative importance

“Other” category is always last

Cumulative count line

Potential X’s

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Notes: Pareto Charts are used to graphically summarize and display the relative importance of the differences between groups of data. Further, it is used to identify and prioritize problems or causes of problems. What Questions Does The Pareto Chart Answer: - What are the largest issues facing our team or business? - What 20% of sources are causing 80% of the problems (80/20 Rule)? - Where should we focus our efforts to achieve the greatest improvements?

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1. Decide which problem you want to know more about 2. Choose the causes or problems that will be monitored, compared, and rank ordered 3. Choose the time period for study (pareto charts show variation for a period of time)

Tip: Select a time period that is long enough to represent the situation, consider volume and variety within the data.

4. Gather the appropriate data (either historical or new) 5. Compare the relative frequency of each problem category (see example below)

6. List the problem categories (sorted by frequency, in descending order) on the horizontal line and frequencies on the vertical line

7. Draw the cumulative percentage line showing the portion of the total that each problem category represents Tip: Always include the source of data and time period covered on the chart.

8. Interpret the results (This tool can and should be done using statistical software)

Problem Category Frequency

Printing problems 15

Erroneous configuration 30

Filing problems 10

Network problems 6

How to Construct a Pareto Chart

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Indicates Pareto Principle holds true: one or a few categories account for the majority of the problem

Focus analysis/improvement efforts on top one or two bars

If the Pareto looks like this…

Indicates Pareto Principle does not hold (bars are all close to equal in height)

Look for other ways to categorize data or stratify data

Interpretation:

Response:

Interpretation:

Response:

How to Interpret and Respond to a Pareto Chart

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Notes: Check the Pareto chart to evaluate whether the Pareto principle holds true. A few of the categories should account for the majority of the problem.

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Data has been correctly distributed among categories, with the “other” category consisting only of issues that have a relatively low frequency of occurrence

Continue with analysis efforts on top one or two bars

If the Pareto looks like this…

“Other” category has categories included in it that should be broken out into other separate categories

Evaluate whether “other” items should be redistributed to existing categories or to newly created categories

Interpretation:

“Other” bar is relatively small

“Other” bar is relatively tall

Response:

Interpretation:

Response:

How to Interpret and Respond to a Pareto Chart

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If Pareto principle holds true, the largest bar on the pareto should be further broken into sub-causes to identify potential X’s.

Defects

A

0

5000

10000

15000

20000

25000

D ef

ec ts

Defect Type

B C D E

0

2500

5000

7500

10000

12500

Am ou

nt

M on

Day of Week

For Defect A

Tu es

W ed

Th ur

s Fr iTeam focus for further analysis: defects on Monday

Pareto Chart Drill Down

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3020100

150

100

50

0

Location 1

Fr eq

ue nc

y

Days

CTQ = 15 Days Av erage = 12.29 Day s

5040302010

100

50

0

Location 3

Fr eq

ue nc

y CTQ = 15 Days

Days

Av erage = 30.02 Day s

3020100

100

50

0

Days

Fr eq

ue nc

y

Location 2

CTQ = 15 Days Av erage = 15.88 Day s

Remember this? Going back to the histograms we learned in previous lessons….. In Analyze a Stratified Histogram enables you to compare distributions by providing one graph for each group, which aids in formulating potential causes.

0 10 20 30 40 50

0

100

200

Days

Fr eq

ue nc

y

15 Days CTQ =

Average = 19.39 Days N = 4266

Example of Stratified Histogram

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0 10 20 30 40 50

0

100

200

Days

Fr eq

ue nc

y

15 Days CTQ =

Average = 19.39 Days N = 4266

3020100

150

100

50

0

Location 1

Fr eq

ue nc

y

Days

CTQ = 15 Days Av erage = 12.29 Day s

5040302010

100

50

0

Location 3

Fr eq

ue nc

y CTQ = 15 Days

Days

Av erage = 30.02 Day s

3020100

100

50

0

Days

Fr eq

ue nc

y

Location 2

CTQ = 15 Days Av erage = 15.88 Day s

Sample Size

Guideline: n > 50 for

each group

Team’s Theory: The total variation in how long it takes to pay claims at all locations combined is caused by variation in training and procedures at different locations. What conclusions would the team have drawn from the results of the stratified histograms below?

Example of Stratified Histogram

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When to Use:

 To analyze results when one variable has continuous data and another has attribute or discrete data

Why use it:

 To compare distributions and measures of central tendency

 To look for patterns

How to create:

 Gather appropriate continuous data for each of the attribute types or categories you want to investigate

 Create a histogram for each category (use the same numeric scale and plot size for each individual histogram so you can easily compare distributions)

 Sample size for each group should be greater than 50 data points

Stratified Histograms

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 A box plot is a tool used to draw comparisons between different distributions based on quartiles

 Box plots take key statistics from the data and summarize them in a box format

Box plots of shift A and shift B

BA

1020

1010

1000

990

(means are indicated by solid circles)

*

Box Plots

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Why Use it:

 To compare several distributions against each other

 To identify variability and centering of two or more distributions

When To Use It:

 When you want to identify differences in distributions between groups

 When you want to identify variability and centering in a variable output (y) vs. an attribute input (x)

 An excellent tool to provide visibility to outliers

Box Plots – Why and When to use them

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 Box Plots measure variation (spread) by dividing data into four equal groups to see how far apart the extreme groups are. It is based off of the Inter-quartile range (IQR).

 The IQR is the distance between the first quartile (Q1) and the third quartile (Q3). The IQR = Q3 – Q1.

 A box plot indicates:  Where the median of the dataset lies (represented by the middle line)  A view of the size of each quartile of the data set  Easy identification of data points that might be deemed extreme values or outliers (here an outlier is

defined as a point that is more than 1.5 IQR from an end of the box.)  The dispersion or spread of the data (the whiskers)

Fourth Quartile First Quartile

Second Quartile Third Quartile

Median

Outlier

Whisker

Mean

Understanding How to Read a Box Plot

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1. Gather appropriate continuous data for each of the attribute types you want to investigate.

2. Draw a box between the first and third quartiles of data, this represents 50% of the data values.

3. Draw horizontal lines from the middle of the sides of the box to the minimum and maximum values. (These represent the whiskers).

4. Draw a vertical line inside the box to represent the median value.

5. Indicate any outliers with a dot or an asterisk.

6. Sample size for each subgroup should not have less than 25 data points.

7. Box plots can be constructed vertically or horizontally.

(Of course this can and should be done using statistical software)

How to Construct a Box Plot

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* 80 70

60

50

40

30

20 10 0

Phone Queue A Phone Queue B

Box Plot of Hold Time of Queue A and Queue B

H ol

d Ti

m e

Stratified Box Plot Example

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Symmetrical (based off of median)

If the median is close to the center of the box, the distribution of the data will be symmetrical.

Negatively Skewed (based off of median)

If the median is in the upper half of the box, the distribution of the data values will be negatively skewed.

Positively Skewed (based off of median)

If the median is in the lower half of the box, the distribution of the data values will be positively skewed.

Symmetrical (based off of whisker)

If the whiskers are approximately the same length, the distribution of the data values will be symmetrical.

Positively Skewed (based off of whisker)

If the upper whisker is longer than the lower whisker then the distribution of the data values will be positively skewed.

Negatively Skewed (based off of whisker)

If the lower whisker is longer than the upper whisker then the distribution of the data values will be negatively skewed.

How to Interpret a Box Plot

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 A Scatter Diagram assists in studying the relationship between 2 variables

Output Variable

(Y)

Process Variable (X)

 A Scatter Diagram is a graph that helps you visualize the relationship between two variables. It can be used to check whether one variable is related to another

Scatter Diagram or Correlation Analysis

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Notes: One tool that can be used for identifying the relationship between input and process variables (X’s) and the process output (Y) is a scatter diagram.

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 Tests and verifies cause and effect relationship between input/process variable (X’s) and output variable (Ys)

 Analyzes the strength of relationship or correlation between potential cause and effect

 Provides indication of a root cause

Scatter Diagram – Why Use it?

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 To discover whether two variables are related

 To find out if changes in one variable are associated with changes in the other

 To test for a cause and effect relationship (but finding a relationship does not always imply causation)

Scatter Diagram – When to Use it

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Each data point represents a pair of measurements (ex. 10 defects for 5 min process time)

Cause on the X axis

High

# Defects (Y)

Low Low

Speed (X) High

The pattern

Effect on the Y axis

Both axis need to be roughly equal in length, so the plot is square

The pattern indicates how the variables are related

Understanding How to Read a Scatter Diagram

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Notes: Both axes need to be about the same length so the plot is square. If you make one axis is longer or shorter than the other, the pattern formed by the scatter can be distorted.

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1. Gather appropriate data

2. Determine which variable will be on the horizontal axis (X) and which will be on the vertical axis (Y)

3. Find the minimum and maximum value of X and Y

4. Set up the axes (ensure they are the same length)

5. Plot all the X & Y pairs on the graph (need 30 -100 pairs of data)

(This can and should be done using statistical software)

How to Construct a Scatter Diagram

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High

# Defects (Y)

Low Low

Speed (X) High

Scatter Diagram Example

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Notes: In this scatter diagram, there appears to be a positive relationship between speed of the process and the number of process defects.

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Scatter Diagram Example: Printers Installed – Printer Calls

Printer Calls

Pr in

te rs

In st

al le

d

420400380360340320

475

450

425

400

375

350

Scatterplot of Printers Installed vs Printer Calls

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Notes: This scatter diagram indicates that there appears to be a positive correlation between increased printer installation and printer calls to the Helpdesk.

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Common Mistakes Constructing Scatter Diagrams

 Mixing up the “X” and the “Y” variables

 Data is not paired correctly

 Improper scaling – scatter diagram not square

 Incorrect increment spacing between tick marks

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Notes: Mixing Up The “X” And The “Y” Variables In analyzing variables for potential cause and effect, the process variable as the predictor is on the “X” axis and the output or process performance variable as the response is on the “Y” axis. Data Is Not Paired Correctly Scatter Diagrams require that the “X” and “Y” variables be paired. It means that there has to be a logical correspondence between the data to appropriately study the correlation. For example, if one examines the relationship between length of time to approve loans and number of telephone calls to the applicant, the paired data would be based on a specific loan application. Taking a sample of loan applications, it will be necessary to know the length of the time to approve and the number of telephone calls for each loan. Improper Scaling – Scatter Diagram Not Square To ensure proper interpretation, it is necessary to use the fullest possible extent of both the “X” and “Y” axis to cover the range of the data collected. Improper scaling can result in the pattern being obscured. Incorrect Increment Spacing Between Tick Marks The increment, or the space width between tick marks on the Scatter Diagram, should be a value that makes it easy to plot the data and easy to read. A general guideline is to have between 5 to 15 increments of equal width along the full length of each axis.

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No Correlation

Possible Positive Correlation

Strong Positive Correlation

Other PatternPossible Negative Correlation

Strong Negative Correlation

Look For Patterns

Interpreting a Scatter Diagram

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Notes: In examining Scatter Diagrams, it is helpful to look for patterns. First, is there a pattern or correlation between the X and Y variables? Second, the direction of the pattern, either positive or negative. For example, a strong positive correlation indicates an increase in the process variable (X) and increases the process performance (Y).� Examples of positive correlation include:�- Hours worked and amount of production - Age and height of school children - Advertising costs and sales receipts If a relationship is such that as one quantity increases the other quantity decreases, we call the relationship a negative correlation. ��Examples of negative correlation include:�- Time spent designing a piece of equipment and the time spent maintaining it - Hours spent on training new employees and hours spent correcting errors - Speed of a vehicle and time required to complete a trip

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 Common patterns in the data

 Range of the predictor variable (X’s)

 Irregularities in the data pattern (investigate outliers)

Look for:

Interpretation of a Scatter Diagram

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Correlation Between Butterflies and Hurricanes It is important to understand that correlation, no matter how strong, does not imply causation. As tempting as it may be for us to leap to causation, we must understand that two variables may be strongly correlated with no causal link whatsoever.

Just because the correlation between number of butterflies and number of hurricanes in a given year is very strong does not mean that hurricanes are caused by butterflies flapping their wings.

50

80

70

60

50

80

70

60

100 200 300 H

ur ric

an es

Butterflies (Billions)

Be Careful – Correlation Does Not Imply Causation

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Summary of Data Tools

Tool Purpose Box Plot Used to identify variability and centering of two or more groups

of data Control Chart (Measure Phase)

Used to help understand variation and to control and improve a process

Histogram (Measure Phase)

Used to determine shape, center and range of numeric data, also used to prepare Pareto charts

Pareto Chart Used to identify and prioritize problems or causes of problems Pie Chart Used to depict percentages of total in a circular diagram Run Chart (Measure Phase)

Type of chart used to display data related to a process variable in sequence over time to identify changes

Scatter Diagram Used to confirm relationship between two variables

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What you learned during this section:

 How, why and when to use Pareto charts, stratified histograms, box plots, and scatter diagrams (correlation analysis).

 What type of data is required to use various analysis tools.

 How to Interpret pareto charts, histograms, box plots, and scatter diagrams.

Summary of Section

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

End of Lesson: Analyze – Graphical Data Analysis

Lean Six Sigma Training

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

Hypothesis Testing Tools

Hypothesis Testing Overview

Statistical Data Analysis Overview

Analyze – Statistical Data Analysis

Lean Six Sigma Training

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 At this point, the vital few potential root causes have been identified. Now we need to validate the root causes with 95% confidence in the results. Statistical data enables us to do this.

 Allows us to draw meaningful conclusions from data samples

 So we can have a greater level of certainty in our identified vital few X’s

 Enables us to pinpoint the root cause so we can select the best fit solutions to improve our process problems

 Helps to make the case for change with solid data to back up our plan for change

Why do we Need to Use Statistical Data?

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Statistical Problem

Understand the process

• Only two issues can exist:

• Is the mean not centered properly

• Is the variability (spread) to large?

2

Practical Solution

• Once root causes are validated, implement focused solutions

43 Statistical Solution • Understand what drives the process

output

• Measure the influence of the vital few X’s on the mean and the variability

1 Practical Problem Problem Statement

• Magnitude

• Impact to business

Translate the Practical Problem into a Statistical Problem. Solve the Statistical Problem and translate into practical terms and implement a

solution.

Statistical Thought Process

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 Just like graphical analysis tools, there are several statistical tools to help you identify which X’s (input/process variables) affect the process output (Y).

 Again, in order to select the right tool to examine the relationship between X’s and Y’s it depends on the type of data you are testing for both X and Y.

 The tools this course will cover are:

 Simple Linear & Multiple Regression

5040302010 0

65

55

45

35

25

15

5

Cycle Time Sending Information

To ta

l C yc

le T

im e

Correlation Plot of Cycle Time

Statistical Analysis Tools

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

Hypothesis Testing Tools

Hypothesis Testing Overview

Statistical Data Analysis Overview

Analyze – Statistical Data Analysis

Lean Six Sigma Training

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 Understand what a hypothesis test is

 Know how to properly state a null and alternative hypothesis

 Understand the significance of a p-value

 Know when to reject the null hypothesis

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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 A hypothesis test is used to detect differences between two or more groups that may be important to the business

 Because of variation, no two things will be exactly alike

The question is whether differences you see between samples, groups, processes, etc., are due to random, common cause variation, or if there is a real difference.

Hypothesis testing answers this question for us.

Are A and B really different?

Statistically speaking?

10

20

30

40

A B

What is a Hypothesis Test?

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 To determine whether making a change to an input or process (X) significantly changes the output (Y) of the overall process.

 Statistically determine if there are differences between two or more process outputs.

 Bottom Line: To determine which process factors are the cause of the variation in our output that is causing defects.

Y = f(X1, X2, X3…, Xn) mmm….is it X1 or X2 that’s causing the problem?

Why Use a Hypothesis Test?

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 Hypothesis testing consists of a set of tools that can tell us how certain we can be in the observations and formulated causes we made from our process analysis and graphical analysis.

 There are different hypothesis testing methods to use for each situation

Type of Data What You

Can Compare Example

Continuous

Proportions Is the % of on-time application completions the same for group 1 as for group 2

Discrete

Averages

Variation

Shapes or Distributions

Is the average productivity the same for multiple regions? Do results from the department using the improved process have less variation than the results from the department using the old process? How does the cycle time distribution compare for various processes?

Hypothesis Testing

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The goal of a Hypothesis test is to either reject or not reject the Null Hypothesis.

The way it works:

 Test the null hypothesis  H0: no difference between groups

 Against the alternative hypothesis (represents the theory you are trying test or prove)  Ha: groups are different

…to determine if we can reject the null hypothesis or not

Overview of Hypothesis

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There is a difference in the waiting time across the different regions

There is no difference in the waiting time across the different regions

Process waiting times across different regions

There is a difference in the variation of the dimension from the different machines

There is no difference in the variation of the dimension from the different machines

The variation in a product dimension from different machines

There is a difference in customer satisfaction levels between product A and Product B

There is no difference in customer satisfaction levels between product A and Product B

Customer satisfaction levels for different products

There is a difference in average wait times between call centers

There is no difference in average wait times between call centers

Average call answer times between call centers

The Alternative Hypothesis

The Null HypothesisWhat you are looking at

Your aim is to disprove or reject the null hypothesis

Examples of Determining the Correct Null Hypothesis

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Example: What is the p-value?  The p-value is the probability that the observed difference between the

means is caused by sampling variation, OR  The p-value is the probability that these two samples came from the

same population.  P-values range from 0.0 to 1.0 (0% chance to 100% chance)  By convention, usually treat P < 0.05 as indicative that the difference is

significant.

How do I Interpret the p-value? If p < 0.05, we declare a significant difference exists and therefore we should reject the null hypothesis. (In other terms, if P < 0.05, reject the H0 and conclude the Ha)

When performing a Hypothesis test, an output of the test will be a calculated p- value. Identifying the p-value will tell us whether a significant difference exists.

How do we Know When to Reject the Null Hypothesis?

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P-values are probabilities for values of interest

P-value =  Tail area  Area beyond value-of-interest Probability of being at the value-of-interest or beyond

A small P-value (0 to 0.05) means:  The probability is small that the value-of-interest did, indeed,

come from that distribution. . . . It is likely to have come from some other distribution

A practical definition of the p-value is: The p-value is your confidence in the null hypothesis, so when it’s low you reject the null.

Value of interest

0 0.05 p 1.0

Understanding P-values

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“If p falls below, H0 must go.”

Simple Method to Remember How to Interpret the Hypothesis

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Hypothesis Terminology:

 So…..If the “null hypothesis” (H0) is that there is no difference between the two groups.

 Then…..If we are able to reject the “null hypothesis” then we will be able to say that the two groups are statistically different with 95% confidence.

 If p < 0.05, we declare a significant difference exists.

 The p-value is the probability that the observed difference between the means is caused by sampling variation, OR

 The p-value is the probability that these two samples came from the same population.

Hypothesis Overview Summary

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What you learned during this section:

 What a hypothesis test is

 How to properly state a null and alternative hypothesis

 The significance of a p-value

 When it is appropriate to reject the null hypothesis

Summary of Section

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

Hypothesis Testing Tools

Hypothesis Testing Overview

Statistical Data Analysis Overview

Analyze – Statistical Data Analysis

Lean Six Sigma Training

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 Know how to perform linear regression analysis

 Understand how to perform multiple regression

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Note: This is not an exhaustive list and in this course we will only introduce Regression Analysis

 Hypothesis testing consists of a set of tools that can tell us how certain we can be in the observations and formulated causes we made from our process analysis and graphical analysis.

 There are different hypothesis testing methods to use for each situation

Overview of Hypothesis Testing Tools

Hypothesis Test Purpose Regression Identify if two variables are correlated t-test Compare two group averages ANOVA (Analysis Of Variance) Compare two or more group

averages Chi-Square Compare two or more group

proportions Design of Experiments (DOE) Identify the cause and effect

relationships between Xs and a Y

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Hypothesis tests rely on the following assumptions:

 Data is normally distributed (If continuous data).

 When comparing groups from different populations, we assume samples are independent samples, were randomly selected, and representative of the population.

 When comparing groups from different populations, we assume variances are not dramatically different.

 When comparing groups from different processes, each process is stable (no special cause variation exists in the process.)

CAUTION: Bear in mind that many processes are not stable, hypothesis testing should not be applied until the process is in control.

For the purposes of learning and discussing hypothesis testing in this course, we will assume the above conditions have been met.

Hypothesis Testing Assumptions

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Regression

Takes correlation one step further by developing a mathematical model that represents the relationship between the X (input) and Y (output).

Y

X

Correlation

is used to determine the strength of a linear relationship between two continuous process variables. If two variables have a strong relationship, they are said to be correlated.

R= +0.82

Y

X

Correlation and Regression Analysis – What is it?

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Correlation

 To validate root causes by quantifying the magnitude of the relationship between variables.

 This relationship of variables may be between:

• A potential root cause (X) and the problem or output (Y).

• Two potential causes, inputs, or factors (X1 and X2 ).

Regression

 To define the mathematical relationship between 2 or more variables so we can:

• Make predictions of process performance, Y, based on a given value of the process variable, X.

• Improve process performance (Y) based on controlling or manipulating process conditions (X) to generate desired results.

Y

X

R= +0.82

Y

X

Correlation and Regression Analysis – Why use it?

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 Correlation and regression are intended to be used in conjunction with one another.

 Conducting regression analysis involves several steps and uses multiple tools.

We can break down regression analysis into a 3 step process:

Step 1: Graph the data

Step 2: Measure strength of correlation

Step 3: Run regression

Y

X

Using a scatter diagram

Y

X

By developing fitted line plot

R= +0.82 By obtaining correlation coefficient

The Process of Regression Analysis Overview

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X Variable Is an input or process variable (sometimes called a predictor) which we are hoping to be able to manipulate to influence our project Y. If not, it can be used to predict Y

Y Variable Is an output variable or a measure of process performance which we are hoping to positively affect by managing or manipulating X. If not, at least it can be predicted from X

The scatter diagram indicates how a change in an input or process (X) can affect a change in output (Y) based on the strength of the relationship.

Scatter Diagram – Identifying Possible Correlations

Speed (X)

# Defects (Y)

Scatter Diagram

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 A correlation coefficient is used to measure the degree of linear association (correlation) between continuous sets of data.

 The correlation coefficient is referred to as “r.”

 The possible range of “r” is: +1 to -1  r = +1 Perfect positive relationship  r = 0 No linear relationship  r = -1 Perfect negative relationship

(the higher the absolute value of r, the stronger the correlation)

 The correlation coefficient (r):  Reflects the degree to which the data points are tightly clustered  Is sometimes referred to as the Pearson Coefficient

Once scatter diagrams have been used to look for correlations, a correlation coefficient can be used to measure the strength of any correlations found.

Correlation analysis places a quantifiable magnitude on the graphical scatter diagram relationship.

Correlation Coefficient

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Examples of scatter diagrams and their associated correlation coefficients:

Indicates a strong negative correlation, so the r value is very high. The r is a negative number to represent the downhill slope.

Interpretation: the more call center reps available, the faster the speed of answer.

Indicates a strong positive correlation, so the r value is very high. The r is a positive number to represent the upward slope.

Interpretation: the more call center reps, the longer the talk time.

No. of call center reps

Sp ee

d of

a ns

w er

r = - 0.98

100 110

10

120

30

50

Indicates no correlation exists, so the r value is very low.

Interpretation: there is no relationship between the number of call center reps, and the claims payment cycle time.

No. of call center reps

r = +0.06

Pa ym

en t c

yc le

ti m

e

120110100

30 Ta

lk T

im e

No. of call center reps

r = +0.96

120110100

10

50

Interpreting Correlation Coefficient

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 Before you can use the correlation coefficient the statistical significance of the correlation coefficient should be assessed.

 Because of the random nature of data, it is possible for a scatter diagram to suggest a correlation between variables when in reality, none exists.

 There is a greater risk of this occurring if a scatter diagram is based on a small sample size

 To solve for this issue, look at the correlation coefficient’s corresponding p-value

 Just like hypothesis testing, a p-value is generated for a correlation coefficient using statistical software.

 If the p-value < 0.05, you can be 95% confident that a correlation exists. r = - 0.98

p-value 0.000 y-

ef fe

ct

r = - 0.98

Interpreting Correlation Coefficient

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 Linear regression develops a mathematical model to represent the data in a scatter diagram

 It defines the mathematical relationship between two variables

 It generates a fitted line that quantifies the relationship between X and Y

 Enables us to predict the value of Y given a certain value of X

 The line or regression equation is represented as:

y = b0 + b1 “multiplied by” x1, where

y = output

x1 = an input

b1 = the slope of the line (rise over run, or change in Y per unit increase in X)

b0 = the predicted value of y when x1 = 0

Linear Regression Analysis

X1

Y

Residuals

Fitted Line

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Notes: Residuals are the difference between the fitted line (in the model) and the actual data point. Residuals can be analyzed to validate if the fitted line models the shape of the relationship intended.

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 Regression analysis has its own measure for the strength of the relationship. This measure is the square of the correlation coefficient, and is simply referred to as “r-squared” (R-sq).

 r-squared is the measure of how much variation in the process output is accounted for by the model. Another way to look at it is, it’s the measure of how well the regression line describes the data. (Therefore, the closer to 100% the better).

 Since it is a squared value, it can range from 0 to positive 1.  It is defined as the proportion of the variability in

Y (the output) that is explained by X (the input and/or process).

 The regression process creates a line that best resembles the relationship between the process or input (X) and output (Y).

Y

X

Linear Regression – How it Works

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There are two values that are generated from regression analysis that serve as indicators for how to interpret regression results:

P-value

R-sq value

Interpreting P-value:

Null Hypothesis

H0: slope = 0 (or no difference in Y when X changes)

Alternative Hypothesis

Ha: slope = 0 (or Y changes as X changes)

Interpreting R-sq value:

Represents how much of the variation in the process output is accounted for by the model so the closer to 100% the more confident we can be in our results.

Linear Regression Interpretation

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Theory:

 A Lean Six Sigma team wanted to see if the number of call center representatives had an affect on the speed of answer.

Steps Used:

 They took their data and first developed a scatter diagram and obtained their r- value.

 Next, they ran regression analysis in a statistical software program to create the fitted line.

 Finally they obtained, the R-sq value and the P value

The results:

 R-sq = 95.4%

 P-value = 0.0

# of Call Center Representatives

Sp ee

d of

A ns

w er

X1

Y

Interpretation: The number of call center reps has a large affect on the speed of answer (95.4% of the variation in speed of answer is explained by the number of call center reps.)

This is a critical X (since p < 0.05, we rejected H0, and determined Y changes as X changes)

Linear Regression Interpretation Example

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0.055

0.045

0.035

0.025

0.015

0.005

Speed of Answer

Ab an

do n

R at

e

10 20 30

The range of data ends here

Do not attempt to make predictions beyond the range of your data!

Regression Tips and Traps

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Notes: As tempting as it might be to extrapolate beyond the range of data, don’t attempt to do this because it’s risky. Predictions using regression equations are more reliable for X’s that are within the range of the data set collected.

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Y= f (X1, X2, X3, etc.)  Multiple regression is the same concept as linear regression, but it is an equation to

show the mathematical relationship between several X’s and one Y.

 Multiple regression is used to sift through many X’s (input and process variables) at the same time to find the most critical variables that affect the Y (the output variable). This enables us to select the best improvement solution.

Multiple Regression equation:

Y= b0 + b1 X1 + b2 X2 + b3 X3 + …etc. Where…

Y = output variable XS = predictor variables (input or process variables) b0 = intercept (predicted value of Y when each X = 0) b1 = slope of the linear relationship between Y and X1,

or the change in Y per unit increase in X1 holding all other XS constant

b2 = slope for X2 b3 = slope for X3 etc….

Multiple Regression

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Scenario: A Lean Six Sigma team working in a call center focused on improving speed of answer wanted to see if the number of customer service calls and the number of inquiries on active accounts were correlated to the speed of answer.

For this scenario predictor and response variables were: Y = Speed of Answer

X1 = number of calls

X2 = number of inquiries

Speed of Answer (seconds)

Number of Calls (per hour)

Number of Inquiries (per hour)

21 503 45

24 654 52

30 709 22

16 598 16

Data Sheet:

Multiple Regression Example

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Results: R-Sq = 94.3%

P-value for number of calls = 0.0 P-value for number of inquiries = 0.785

Interpretation:  The R-sq value indicates that the input variables in the regression account for

94.3% of the variation in speed of answer, however…

 Since the p-value of number of inquiries is greater than 0.05 it does not influence the speed of answer

 Since the p-value for number of calls is less than 0.05, it does influence the speed of answer and therefore is a critical X.

Conclusion: It must be the number of calls that is creating all the variation in speed of answer.

The number of calls is causing the variation in the speed of answer

Multiple Regression Example Continued

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 Determine the type of test suited to your data and question

 Arrange the data appropriately in the statistical software program of your choice.

 Perform the statistical test

 Obtain the p-value from statistical software output; declare a statistically significant difference if the p < 0.05

How to Perform a Hypothesis Test Summary

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What you learned during this section:

 How to perform linear regression analysis

 How to perform multiple regression

Summary of Section

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

End of Lesson: Analyze – Statistical Data Analysis

Lean Six Sigma Training

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

Analyze – Identify Root Causes

Lean Six Sigma Training

Identify Root Causes

Validated Root Causes

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Validated Root Causes

The Process of Identifying Root Causes

Pareto

Regression

Stratification Process Value Analysis

Fishbone 5 Whys

Potential Root Causes

Value Stream Map

Root Cause Analysis Lean Process Analysis Graphical Data Analysis Statistical Data Analysis

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Notes: The process of identifying root causes is similar to a funnel. It begins at a macro level with a multitude of possible root causes. Through root cause analysis, lean process analysis, graphical data analysis and statistical data analysis, the list of potential root causes gets narrowed down to the vital few process and input variables that affect CTQ process output performance.

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Root Cause Analysis

Graphical Data Analysis

Statistical Data Analysis

Potential causes identified (fishbone, 5 whys)

Statistical tests conducted to validate differences in data groups Testing method utilized is appropriate for the data P-value determined Root causes identified to target for improvement

Data graphically analyzed to identify the Xs that account for variation in the process Data sample is random and independent Data stratifications conducted to identify variation

Analyze Completion Checklist

Lean Process Analysis Process value analysis and Lean measures Value Stream Waste identification

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Identify potential root causes

Statistical Data Analysis

X1

Y

Validate root causes through statistical

tools

Investigate potential root causes through

graphical tools

Graphical Data Analysis

10

20

30

40

A B

Next Steps…… Move to Improve Phase

to Identify Solutions

Identify Root Cause Summary

Root Cause Analysis & Lean Process Analysis

Cause A

Cause D

Cause C

Cause B

Effect

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Notes: Once the Lean Six Sigma improvement team has analyzed which of the process variables (X’s) have the have the strongest relationship to the output measures (Y), they can confidently select the best solution.

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Define Measure ControlImproveDefine Analyze ControlMeasure ImproveDefine Measure ControlImproveDefine Analyze ControlMeasure Improve

End of Lesson: Analyze – Identify Root Causes

Lean Six Sigma Training

Identify Root Causes

Validated Root Causes

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Improve Phase

Lean Six Sigma Training

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Improve Phase Overview

Lean Six Sigma Training

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Once root causes are understood, the team can begin to develop solutions for the process. Generating both obvious and creative solutions requires innovation, technology, and discipline.

Improve Phase Introduction

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ANALYZE

CONTROL

IMPROVE

MEASURE

DEFINE

 Generate Solutions

 Prioritize and Document Improved Process

 Document Solution Impacts and Cost/Benefits

 Pilot Solutions and Identify Potential Problem Analysis

 Develop Implementation Plan

Best Practices

Root Causes

Project Goals

“Discoveries” During Analysis

Benchmark Ideas

Ideas from Other Projects

Brainstorming

Performance Targets

Generate Solution

Ideas

Generate Solution

Ideas

Implement Solution ID

1

2

3

4

5

6

7

8

9

Install new hardware

Revalidate System

Install new software

Train Processing Staff

Update documentation

Develop Training Plan

Train Staff

Test

Task Name 5/31 6/7 6/14 6/21 MAY JUNE

6/28

Jen, Kris, Sue

Conroy

Conroy

Gwen

Team, TBD Team, TBD

Improve Phase Overview

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Identify and Select

Solutions

Financial Impact of Solutions

Risk Planning

and Testing

Implement Solution

 Benchmarking

 Brainstorming

 Solution Selection Matrix

 Deployment Flowchart

 Quantify Benefits

 Quantify Costs

 CBA

Improve Tools

 FMEA

 Error Proofing

 Pilot Planning

MGPP

 Change Management Strategy

 Implementation Plan

Improve Approach

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Improve Phase Deliverables

Define Measure Analyze Improve Control

Project Charter Project Management

Project Plan Process Definition

SIPOC As-Is Process

Map Quick Win

Identification Stakeholder

Management Stakeholder Map Stakeholder

Management Plan Communication

Plan Voice of Customer

Customer Identification

VOC Research Plan

Kano Analysis CTQ Identification

 Root Cause Analysis Affinity Diagram Fishbone Diagram

and/or 5 Why’s Lean Process

Analysis Lean Tools and

Measures Graphical Data

Analysis Histogram Pareto Chart Box Plots Correlation

Analysis Statistical Data

Analysis Linear Regression Multiple

Regression Root Causes

Identified Quick Win

Identification

Identify Measures X/Y Matrix

Data Collection Operational

Definitions Measurement

Systems Analysis (MSA)

Data Collection Plan

Describe and Display Data Histogram Pareto Chart Pie Chart Run Chart Control Charts

Baseline Performance Sigma

Performance Yield Process

Capability Quick Win

Identification

Identify and Select Solutions Generate Solutions Benchmarking Solutions

Prioritization Matrix Solution Selection

Matrix To-Be Process Map

Financial Impact of Solutions Cost/Benefit Analysis

Risk Planning and Testing Failure Modes and

Effects Analysis (FMEA)

Pilot Plan Implement Solutions

Multi-Generational Product Plan (MGPP)

Implementation Plan Stakeholder

Management Project Storyboard

Process Control Control Charts Process

Monitoring Plan Dashboard

Response Plan Project

Documentation Process

Procedures Replication

Opportunities Solution Transfer

Plan

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End of Lesson: Improve Phase Overview

Lean Six Sigma Training

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

Document/Design Solution

Select Solutions

Identify Potential Solutions

Improve – Identify and Select Solutions

Lean Sigma Training

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 Understand how to conduct a gap analysis

 Understand the difference between an incremental improvement strategy vs. an exponential improvement strategy

 Understand various methods and techniques to generate solution ideas

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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ANALYZE→ Identify the vital few root causes IMPROVE→ Generate solution ideas using both logical and creative thinking

Look outside of the box for innovative solution ideas

Obvious remedies to root causes of problem

Project goals and targets

Benchmarking +

Review process and data analysis results

Select “best fit” solution

Filter ideas against criteria

Process to Identify and Select Improvement Solutions

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Things to consider before generating solution ideas:

 Assess gap between current performance and required performance

 Determine if incremental or exponential process improvement is required to meet project goals

Key Considerations to Generating & Developing Solutions

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To comprehend the gap between current and desired performance, a Gap Analysis can be utilized to provide a structured approach to understanding this difference.

After the root causes (critical Xs) have been identified, the project team can evaluate each root cause and assess what level of improvement the team needs for each critical X. The larger the gap, the more effort and risk associated with crossing it.

An example of a gap analysis is below (some teams may only have one root cause):

Gap Analysis Defines Delta Between Current & Desired Performance

Root Cause Current Performance Desired Performance Gap

Key Considerations to Generating & Developing Solutions

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Incremental Improvement

Is the gap large?

Customer Requirements

Process Capability

YesNo

Design for Six Sigma (DFSS or DMADV)

DMAIC

Example: Modify the existing process

Exponential Improvement

Example: Completely re-design the existing process and/or build a new process

Define Measure Analyze Improve Control

Define Measure Analyze Design Verify

Improvement Strategies

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 Process entirely broken: the existing process is unable to meet many CTQs, too many successive DMAIC projects required

 Technology development: new technology solution enables all customer requirements to be met at lower cost or gain a competitive advantage

 Process has reached entitlement

When to Utilize Design for Six Sigma Methodology

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Best Practices

Root Causes

Project Goals

“Discoveries” During Analysis

Benchmark Ideas

Ideas from Other Projects

Brainstorming

Performance Targets

Generate Solution

Ideas

Improve: Sources of Solution Ideas

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Notes: Generating solution ideas should be based on all of the analysis and conclusions the team has developed through the project.

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These techniques allow a team to think outside of the box which can lead a team to build upon or discover a new idea which can lead to a better, more improved solution than the obvious or conventional solution.

 Brainstorming

 Benchmarking

The following techniques enable creative thinking beyond the obvious solutions.

Creative Solution Generation Techniques

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Traditional Brainstorming Review

1. Generation 2. Clarification 3. Evaluation

Brainstorming

 The Generation phase is a free open forum for all participants to generate solution ideas.

 During the Clarification phase of brainstorming, the team reviews the list to make sure everyone understands all the items.

 During the Evaluation phase of brainstorming, the team reviews the list to eliminate duplicates or combine like items.

Stages of Brainstorming

In preparation for brainstorming, the team should begin by reviewing the “as is” process, the gap analysis and the verified root causes.

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Rules for Brainstorming:

 Clearly state the purpose of what you are brainstorming

 Each person takes a turn, in sequence, around the group

 Present one thought at a time

 Do not criticize or discuss any idea

 Build on ideas of others

 Record ideas and make visible to the whole group (flipchart)

Traditional Brainstorming Review

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dopt- Other Companies’ Best Practices

A

dapt- Best Practices to our Business Processes

A

dvance- Our Business Performance

A So We Can . . .

What is Benchmarking?

Benchmarking

A Continuous, systematic approach to improving processes by identifying, evaluating and implementing World-Class processes, practices, products and services of highly successful organizations.

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Notes: Benchmarking is an improvement methodology that an organization can use to assist in identifying solutions. By identifying best practices in other organizations and companies and determining the reasons for success, an organization can integrate valuable knowledge into its processes, practices, products and services.

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…And not reinvent the wheel?

 Benchmarking

 Benchmarking promotes the discovery of best practices and processes of successful external organizations or internal teams, units or segments.

 The Benchmarking methodology focuses on adapting and building on these innovations to improve them even further.

 Benchmarking is an excellent tool for identifying potential solutions during the improve phase.

How do you Develop Innovative Solution Ideas for Breakthrough Change?

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 A continuous process

 A process of investigation that provides valuable information

 A process of learning from others; a pragmatic search for ideas

 A time consuming, labor-intensive process requiring discipline

 A viable tool that provides useful information for improving virtually any business process

Benchmarking Is . . .

 A one-time event

 A process of investigation that provides simple answers

 Copying; imitating

 Quick and easy

 A buzzword, a fad

Benchmarking Isn’t . . .

Benchmarking Defined

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 Internal Benchmarking  Work processes are compared between departments, divisions or

internal company segments

 Competitive Benchmarking  Measuring process performance against peers or competitors

 Functional/Industry Benchmarking  Comparing similar process performance of the same function at

companies outside your industry

 Generic Process/Best In Class Benchmarking  Internal processes are compared against truly innovative practices

and world class performance levels, regardless of industry

Types of Benchmarking

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Notes: Determining who to benchmark is a critical step. Research and analysis to decide which organizations have best in class processes have to be carefully conducted. This is particularly important when benchmarking a competitor. Collection of data is best performed by site visits to benchmarking partners. Telephone and written surveys are often satisfactory for preliminary screening or supplemental data. Site visits and surveys should be carefully planned to ensure good data is obtained.

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Benchmarking Evaluation Example

XXFunctional leaders XXGeneric processes

XDirect competitors XXInternal operations

Innovative PracticesData Collection EaseRelevanceBenchmarking Operation

To determine which type of Benchmarking might be the best approach for your team to generate solution ideas, consider the relevance to your process, the level of effort required to collect the benchmarking information, and the level of creativity.

Evaluation by Type of Benchmarking

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Notes: To help determine who are the best benchmarking partners to focus efforts on, above is an example of a matrix of criteria used to flush out which type of benchmarking might provide the most best practice information with the least effort and time.

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Thinking “out-of-the-box” produces the best results when selecting benchmark partners and analyzing their processes

Company: Remington Rifle Co.

Issue: Surveys revealed Remington’s customers’ prefer shiny rifle shells

Benchmark Maybelline Cosmetics Partner:

Results: Remington adopted Maybelline’s practice of making shiny tubes of lipstick to improve the shininess of their rifle shells

Company: Southwest Airlines

Issue: Southwest was interested in reducing aircraft maintenance and turnaround time

Benchmark Indy 500 Pit Crews Partner:

Results: Southwest adopted some of the crews’ ideas to develop an action plan and incorporate these Best Practices into it’s own organization

Southwest Airlines Indy 500

Maybelline CosmeticsRemington Rifle Company

Innovative Benchmarking Examples (Different Process and Industry)

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To contribute to efficient, effective and ethical benchmarking, individuals agree for themselves and their organization to abide by the following principles:

 Keep it legal  Be willing to give what you get  Respect confidentiality  Keep information internal  Use benchmarking contacts  Don’t refer without permission  Be prepared at initial contact

Benchmarking Code of Conduct

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What you learned during this section:

 How to conduct a gap analysis

 The difference between an incremental improvement strategy vs. an exponential improvement strategy

 Various methods and techniques to generate solution ideas

Summary of Section

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

Document/Design Solution

Select Solutions

Identify Potential Solutions

Improve – Identify and Select Solutions

Lean Six Sigma Training

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 Understand how to organize solutions

 Know how to use various methods and tools to prioritize solutions

 Know how to use various methods and tools to select solutions

 Understand how to select solutions in the event that no clear solution option emerges

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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After solution ideas have been generated, duplicates need to be removed and they need to be organized into like categories.

One of the best tools for categorizing the solutions is a familiar tool - the Affinity Diagram.

Solution 1

Solution 2

Solution 3

Affinity Diagram

Organize Solutions

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 Develop the Evaluation Criteria  Remove Show Stoppers  Consider Organization Fit  Determine Sigma Impact

 Evaluate Time Impact  Evaluate Cost Benefit Impact  Evaluate Other Impacts  Narrow the List

Narrowing List Select Solutions

Solution Evaluation and Selection Process Po

te nt

ia l S

ol ut

io ns

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Notes: Once solution ideas have been generated, the next step is to select the best solutions. Developing evaluation criteria helps identify those solutions that meet specific requirements. These requirements should be based on the needs of the customers and the organization. Eliminating ideas that do not meet certain criteria will save time and energy discussing unacceptable solutions. Criteria examples: - Show Stoppers contain minimum requirements that must be met for a solution to be considered. - Solutions may not fit into the current organization structure and should be eliminated or considered for later implementation. - Any solution selected should have a favorable impact to the process Sigma.

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Payoff Matrix

In this example, solution C and solution D would be eliminated from the list because of the relatively high level of effort and low benefit.

Estimated Financial Benefit

Implementation Level of Effort

Solution A

Solution B

Solution C L

H

L

Solution D

H

Narrow the List By Removing the Low Payoff Solutions

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Notes: The Payoff Matrix is an effective tool used to narrow down the list of solutions by eliminating those solutions that are low “pay-offs” for the organization in terms of estimated cost benefit. Although we have not yet completed a detailed cost benefit analysis, at this stage of the project, the team should have enough information from quantifying the cost associated with the problem during the Define phase and a sense of the level of effort to be able to estimate the Level of Effort and Financial Benefit to use this tool.

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A tool used to narrow and prioritize those solutions that have the greatest impact to key criteria. Example of criteria include:

Root cause identified in the Analyze Phase that will be impacted by the solution

The description of the solution that was generated from the brainstorming session

Customer / CTQ Impact (H, M, L) The impact the solution will have on the CTQ, measured by High Impact, Medium Impact, or Low Impact

The costs required to implement the solution suggested, measured by High, Medium, or Low

The solution represents a quick win and can be implemented immediately

Technology is required to implement the solution

Root Cause Addressed

Solution Description

Implementation Cost (H,M,L)

Quick Win (Yes, No)

Technology Required (Yes, No)

Solution Prioritization Matrix Solution

Prioritization Matrix

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Notes: Choosing the right solutions can be challenging. The Solution Prioritization Matrix is another tool that will help drill down to a list of the best potential solutions. By comparing each idea against the criteria listed above, the project team can narrow down the list of solutions based on key requirements and not on gut feeling or popularity.

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Criteria

Develop 1 platform for systems to interact

Increase approval levels of reps

4 2 1

Imp costs Quick-Win Tech. Rqd.CTQ Impact SUM

3Weight

Standardize training materials/program

Standardize & document resolution process

9

3

9

3

36

12

36

12

1

9

3

9

3

27

9

27

1

9

3

3

2

18

6

6

1

9

9

9

1

9

9

9

42

66

60

54

Weight (based on

rank ordering

Score against criteria 1(L), 3(M), 9(H)

Score multiplied against weight

To quantitatively select the final “best fit” solutions for your organization based on criteria, a Solution Selection Matrix can be used. See example and explanation below:

Note: the implementation costs for this solution are high, but we give it a 1 instead of a 9 because increased cost is a negative.

The sum of the multiplied

scores

Selected Solution

Selected Solution

Highest score solutions are

selected

Solution Selection Matrix Solution

Selection Matrix

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Steps to Developing Solution Selection Matrix: 1. Record a list of final solutions

2. Create a list of criteria

 This criteria should include the common criteria (root cause addressed, customer impact, implementation effort, etc. as seen on the previous page) as well as criteria that is specific and most important to the organization.

3. Weight the criteria

 To identify the appropriate weighting of each criterion the individual criterion should be either rank ordered or weighted on a scale of 1-10. Criterion that are the most important are weighted a 10; lower weighted criterion are weighted a 2 or 1.

 One method of determining the weight of each criterion is to have the team multi-vote .

4. Evaluate the list of solutions against the weighted criteria using a 1 for low, 3 for medium and 9 for high.

5. Tally the scores for each solution, discuss, and select those solutions that had the highest score.

Developing a Solution Selection Matrix

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 On rare occasions, the choice may be obvious given your knowledge of the process and problem

 More often, you need to carefully weigh pros and cons utilizing tools such as, the pay-off matrix, solution prioritization matrix, and solution selection matrix

 If the solution selection matrix does not result in a clear choice—and perhaps even if it does—you can get more information about a solution by…

 Modeling or simulating the solutions  Doing trial implementations (small scale tests)  Observation (find a person or organization who is doing

something similar and observe)

Selecting Solutions

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Since a solution selection decision is typically high impact, emotionally charged, and sometimes offers a wide diversity of opinion, consensus is generally the best decision making method to use when using a fall back solution selection method like decision making is required.

Gathers upon every team members

opinion

Increased participation and

buy-in

Provides a structured process to arrive at

decision

Ensure you have allocated enough time

Take thorough notes

The Benefits of Using Consensus

Tips to Using Consensus Decision Making

Balance Power

Listen carefully and check for understanding

Decision Making Method – Consensus

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To aid in the selection of solutions and aid in evaluating solutions against criteria, often more information must be gathered on each solution idea. Below are some effective and recommended methods:

 Visit an organization that uses the particular solution option you are evaluating to see how effective it is.  Hopefully, you have already done this through benchmarking during the solution

generation phase. If not, make a site visit to benchmark the solution at this stage.  Making a site visit to an organization who has a particular solution option can also

provide valuable information about lessons learned through implementation and estimated costs to implement.

 If evaluating potential solutions that involve a level of automation or technology:  Ask for a demonstration.  Compare different vendors (if applicable).  Visit an organization that uses this particular solution.  Prepare a list of questions.

Obtaining More Information to Aid in Selecting Solutions

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 Consensus  Delegate with Constraints

 Gather Input from Others (influencers) and Decide

 Gather Input from the Team and Decide

 Decide and Announce

High Level of Involvement/Time

Required to Make a Decision

Medium Level of Involvement/Time

Required to Make a Decision

Low Level of Involvement/Time

Required to Make a Decision

What to Do if No Clear Solution Option Emerges

31

If the criteria-based comparison tools, and methods to gather additional information on solutions as discussed on previous pages still does not result in a clear solution choice or if many solutions are equally scored, a fallback method is using decision making methods. See below….

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What you learned during this section:

 How to organize solutions

 How to use various methods and tools to prioritize solutions

 How to use various methods and tools to select solutions

 How to select solutions in the event that no clear solution option emerges

Summary of Section

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

Document/Design Solution

Select Solutions

Identify Potential Solutions

Improve – Identify and Select Solutions

Lean Six Sigma Training

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 Understand the importance of documenting the new process

 Understand tools to document the new solution

 Understand how to document the new process solution by creating a “to-be” process map

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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 Documenting the newly selected solution is critical to understanding costs and risks, training associates, and achieving desired improvement results.

 The tools for documenting the improved process solution design can include the following:

 Process maps/flowcharts  Functional requirements document (for solutions that involve

technology)  Drawings

Documenting the New “To-Be” Process Solution

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 Once the solution has been selected we need to go back to the baseline “as-is” process and identify and document how the process will change as a result of implementing the new solution.

 The new “to-be” process map will also be a valuable tool for training the organization before implementation.

S I P O C Suppliers Inputs Process Outputs Customers

Process Map

Documenting the New “To-Be” Process

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Notes: It is helpful in documenting the new “to-be” process, to go back to the SIPOC first and identify what will change. In addition to the process steps, often suppliers and inputs will change as a result of the selected solution.

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Deployment flowchart (“swim lanes”) Processing Administration Adjusters Payables

Since both “who” conducts each process step and “how” work gets accomplished in a process changes after the improvement solution is applied, the best process mapping tool to document these changes is a Deployment flowchart.

Deployment flowcharts clearly indicate both who handles each process step and how it gets done.

Documenting the New “To-Be” Process

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Requirement documents for IT solutions can include items such as:

 Business requirements

 Data requirements

 Functional requirements of product or service

 Historic data specs

 Production data specs

 Functionality of product or service

 User access/security

If the solutions selected involves technology or automation, a detailed requirements and design document would also need to be developed with the support of an IT SME (information technology subject matter expert) that is assigned by the organization to be on the implementation team.

Documenting Solution which Involves Technology

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What you learned during this section:

 Understand the importance of documenting the new process solution

 Understand tools to document the new solution

 Understand how to document the new process solution by creating a “to-be” process map

Summary of Section

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

End of Lesson: Improve – Identify and Select Solutions

Lean Six Sigma Training

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

Cost/Benefit Analysis

Costs of the “As-Is” Process

Improve – Financial Impact of Solutions

Lean Six Sigma Training

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 Understand the costs of poor quality and defects

 Understand how to quantify the costs and inefficiencies of the “As-Is” process

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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 For many companies, performance depends on meeting shareholder expectations. Given limited resources, an executive is unlikely to support quality for quality’s sake--- the business environment requires getting the most “bang for the buck” by increasing revenue and reducing cost.

 The focus of Lean Six Sigma projects is to reduce defects and inefficiency to increase earnings and value for the shareholder.

Overview of the Financial Side of Poor Quality and Defects

generating gross revenue

which minus costs

results in profits

some of which is reinvested

the remainder reported as

earnings

thus meeting financial

expectations

Organizations produce products/services to the marketplace, thereby (which gets reduced by poor quality)

(increased by inefficiency)

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To identify the costs of the “As-Is” process, we need to identify the labor, material, and equipment costs to operate the process, plus the cost effect of the non value- added activities in the process.

To do this assessment, go back to the process map analysis conducted earlier in the project where the percentage of value-added activity vs. non value-added activity was identified and calculate the cost of the non value-added activities.

Method to Quantify the Cost of the “As-Is” Process

Examples of Cost Categories

Material Costs:

 Postage

 Paper

 Ink

 Forms

Equipment Costs:

 Computers

 Phones

 Office Furniture

 Office Space

Labor Costs:

 Salary

 Benefits

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 Collect data on how many times the problem/defect occurs per unit of time (example: 12 occurrences/week)

 Work with process owners and finance to collect data on the cost per occurrence in terms of labor, materials and equipment costs. (example, $200 per occurrence)

 Identify time involved (example: 52 weeks)

 Calculate total annual cost by multiplying the above three factors (example: 12 X $200 X52 = $124,800)

Quantifying the Cost of the “As-Is” Process

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The Cost of Conformance

The money and time spent to ensure valid customer requirements are being met.

 Includes money and time spent on both prevention (finding mistakes before they happen) and inspection (finding defects after they happen but before they touch the customer).

The Cost of Lost Opportunity

The profit impact of lost revenues that result from failure to meet customer requirements . If a company loses business because it has a reputation for poor quality, it loses revenue. The profit the company could have made on that revenue is the cost of lost opportunity.

The Cost of Non-conformance

The money spent to fix products and services that do not meet valid customer requirements.

This cost includes money spent on warranties, credits, and other customer concessions paid as a result of poor product and service performance.

These are considered external failures and are the worst type of cost because they touch the customer.

Remember non-value added activities, such as, rework and defects cost money, this is considered the cost of poor quality. The cost of poor quality generally breaks down into three major categories:

Considerations for Capturing the Costs of Non- Value Added Activities

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Once the team has collected data around the costs associated with the inefficiencies of the “As-Is” process, and has selected the solution to target these inefficiencies, the team now has enough information to perform a Cost/Benefit Analysis.

Selected Solution“As Is” Costs

Cost/Benefit Analysis

Inputs to the Cost/Benefit Analysis

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What you learned during this section:

 The costs of poor quality and defects (poor effectiveness)

 How to quantify the costs and inefficiencies of the “As-Is” process (poor efficiency)

Summary of Section

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

Cost/Benefit Analysis

Costs of the “As-Is” Process

Improve – Financial Impact of Solutions

Lean Six Sigma Training

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 Understand the elements of capturing the financial impact of the selected solutions

 Understand why performing a cost/benefit analysis on selected solutions is necessary

 Know how to develop a cost/benefit analysis

 Understand examples of various cost/benefit analysis formats

 Understand key considerations and lessons learned around capturing financial benefits of improvement projects

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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 An analysis which quantifies the benefits of your project and compares them to the cost of pursuing the project.

 A document which communicates in financial terms why the organization should implement your selected improvement solution(s).

 A cost/benefit analysis includes calculations and financial measurements that fit your particular project and are important to the organization. These vary from project to project and might include measurements such as:

 Return on investment  Return on equity  Return on capital  Cash flow  Net present value  Pay back period

What is a Cost/Benefit Analysis?

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 It identifies the criteria against which we can measure the project success. Remember the key reason for conducting Lean Six Sigma improvement projects is to have a positive financial impact and increase value to the shareholder.

 Before implementing the solution that has been selected we need to ensure that it meets the financial requirements of the business.

 Allows us to determine if implementing improvement solutions will have clear financial payback.

 The business case for implementing the selected solution might not be apparent to those stakeholders outside of the project team.

 Data that indicates implementing the selected solution will result in a positive impact to the bottom line by creating buy-in and mobilize the organization’s commitment and support for the project.

Why Perform a Cost/Benefit Analysis?

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 Ties process defects to dollar impact

 Translates “Quality Lingo” into common financial terms

 Eliminates perception of Quality improvements as being “pie in the sky”

 Enables Lean Six Sigma projects to compete effectively with other business initiatives for human and financial resources

 Makes Lean Six Sigma project savings auditable

 Increases credibility and support of Lean Six Sigma philosophy with business and finance leaders

 Greatly enhances project success

The Benefits of Quantifying Project Costs and Benefits

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Benefits generally fall into 2 categories:

 Hard Benefits  Soft Benefits

Cost categories:

 Direct Project Costs  Indirect Project/Process Costs

Benefits Costs

When performing a cost/benefit analysis we are evaluating whether the benefits to be gained with the new improved process outweigh the costs of implementing the improvement solution, and to what degree.

It is important to understand that every organization has its own guidelines and methodology to justify cost/benefit analysis. It is critical to work with the organization’s Quality/Financial Analyst to gain agreement and approval on the Cost/Benefit methodology used.

Developing a Cost/Benefit Analysis Solutions

Benefits and Implications

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 Hard Benefits - Improvements that result in real and measurable cost or asset reductions.  Examples of Hard Benefits:

– Incremental revenues – Cost reductions such as fewer headcount

 Soft Benefits - Improvements that do not immediately reduce cost or assets but provide benefits through improved process efficiency, employee productivity, improved customer satisfaction, improved competitiveness, etc.  Examples of Soft Benefits:

– Avoidance of lost sales – Cost avoidance such as the need to hire 5 instead of 10*

*Note: in some organizations cost avoidance is considered a hard dollar benefit

The Two Categories of Project Benefits ($$)

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Additional Examples of Hard Benefits (typically tracked by the company accounting system).  Reduction in unit cost of operations  Reduction in unit cost of production  Reduction in transaction cost  Reduction in overhead cost  Reduction in transportation cost  Reduction in manpower  Increased throughput, resulting in increased sales or revenue

Additional Examples of Soft Benefits (less tangible, typically not tracked by accounting system).  Reduced cycle time  Improved on-time delivery  Increased flexibility  Faster response  Reduced effort  Increased availability  Fewer defects  Higher scores on customer satisfaction scores

Additional Examples of Project Benefits ($$)

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 Direct Project Costs – Costs that can be tied directly to a particular process or project. These include incremental costs (costs which are only being incurred as a result of deciding to implement the selected Improvement solution). Incremental costs are the costs above the current cost to operate the process.  Example of Incremental Costs:

̶ If recommended improvement solution was to implement a new computer system to improve the processing of loans, the purchase cost of the computer would be an incremental cost of the project.

 Indirect Project/Process Costs – Costs associated with running the enterprise or organization (often called facilities and administrative costs.)  Examples of Indirect Costs:

̶ Utilities and rent ̶ Cost of Quality resources working on the project prior to

implementation of solution.

Note: in most organizations only incremental costs should be considered in the cost/benefit analysis.

Implementation Costs ($$)

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Gross Hard Project Benefits

+

Gross Soft Project Benefits

Less: Project Implementation Costs

= Net Project Benefits

Net Project Benefits

Method to Calculate Estimated Project Benefits ($$)

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Hard benefits…such as:  Incremental Revenues…less Cost of

Goods Sold (COGS)  Cost Reductions

Soft benefits…such as:  Avoidance of lost sales…less COGS  Cost avoidance

Implementation costs include...  Full-time resources assigned to the

implementation  Consultants, contractors and temps  Other considerations for running the project

Implementation costs exclude…  Costs of Quality resources assigned to the

project prior to implementation

Gross Project Benefits

Gross Hard Project Benefits

+ Gross Soft Project Benefits

Less: Project Implementation Costs

Net Project Benefits

Project Implementation Costs

Method to Calculate Estimated Project Benefits ($$)

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Time

Fi na

nc ia

l & p

ro ce

ss p

er fo

rm an

ce

Before improvement

Minimize this effect

After improvement

In the initial stages of the solution being implemented, there is often a period of time when process participants are adjusting to the new process which causes a degradation to both the process and financial performance. After the adjustment period, performance will gradually improve to the new desired level.

Implementing the solution quickly and minimizing this adjustment period will result in realizing improved process performance and therefore improved financial benefits faster.

Key Considerations

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 Start with the “As-Is” process analyzed earlier in the life of the project

 Use the data generated in the previous project phases to illustrate the difference between the “as-is” state and your solution.

 Cost out the various “Should-Be” alternatives

 Use the process map and personnel in associated departments to identify cost and benefit information.

 “As-Is” minus “Should-Be” represents the cost savings associated with the proposed solution

 Determine cost of implementing the proposed solution

 Concentrate on direct costs and direct benefits. Use indirect costs that are generally acceptable to all stakeholders

 Use standard methods and rates in your calculations

 Document your assumptions

How to Perform a Cost/Benefit Analysis

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Project Name: Improve credit card billing process Problem Statement: The credit card billing process is inaccurate resulting in incorrect bills being sent to card holders. Proposed Solution: Improve credit card billing process by implementing new software.

Implementation Costs: Measurement Variable Cost Estimate Total Notes

Software 1 site license $50,000 $50,000

Training 2 contractors @ 40hrs each/week for 1 week

$50/hr/each $4,000

Implementation team personnel time 4 people @10 hrs./wk. for 5 weeks $50/hr. $10,000

Hard Benefits: Measurement Variable Cost Estimate Total Notes

Reduce billing inquiries 1 staff eliminated @ $9.50/hr. $20,000/yr. $20,000

Hard Benefits:

Cardholder receives more accurate and understandable statement

5 day reduction in receivables days outstanding per quarter

Avg. receivables balance = $1.5M @15% cost of capital

$123,000 Time value of money indicates because of interest costs, a dollar received today is worth more than a dollar in the future so collecting receivables sooner is a benefit

Net Benefit (equals total benefits, less costs): $79,000

Example of Cost/Benefit Analysis

*A cost/benefit analysis can be done in many different formats. If a standardized cost/benefit analysis template does not exist within your organization, then propose one to the organization.

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Company: Auto Insurance provider Problem: Extended claims payment cycle time due to manual claims payment process with multiple handoffs. Process Solution: Implement an automated workflow system with built in automated payment system to reduce process cycle time to pay auto claims.

Cost/Benefit Summary:

Implementation Costs: $58,000

Hard Benefits: Head Count Reductions $398,261

Overtime Elimination $56,799

Reduction in check writing costs $69,176

Soft Benefits: Productivity Increases $121,750

Total Project Benefit: $645,986

Net Benefit: (Benefits less costs) $587,986 See back up data on following pages

Example of Cost/Benefit Analysis with Back Up Data Detail

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Notes: In this example, an auto insurance provider’s auto repair claims payment process was incapable of meeting its cycle time CTQ of paying claims within 7 days. The “as-is” process was completely manual and they paid the majority of their claims via checks. Due to the manual nature of the process, it required a lot of labor to complete the process effectively. To improve the process, the improvement team recommended implementing an automated workflow system with a built in automated payment process. This solution enabled the auto insurance provider to reduce the staff required to process claims manually, expand their payment capabilities, reduce check writing costs, and improve cycle time.

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Automated Workflow System with Build in the payment system:

$58,000Total Costs:

$3,000 User Training on new system (10 @ $300 each)

Training:

$50,000Software program (1 site license @ $50,000)

$5,000Hardware (10 computers @ $500 each)

Implementation Costs:

Example of Cost/Benefit Analysis with Back Up Data Detail

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The back up data to the CBA shows the comparison of the “As-Is” process to the new “To-Be” process Old Process Department Makeup:

Count Job Title Gross Annual Pay* (avg. annual pay for 1 x total count)

1 Supervisor $33,141 (1 @ $33,141)

3 Fax People $55,029 (3 @ $18,343)

3 Filers $63,426 (3 @ $21,142)

5 Mail Openers $91,615 (5 @ $18,323)

3 Researchers $67,476 (3 @ $22,492)

Total= $310,687

New Process Department Makeup: Clerical: Clerical:

Count Job Title Gross Annual Pay*

1 Manager $37,343 (1 @ $37,343)

9 Payment Reps $225,000 (9 @ $25,000)

3 Exceptions $66,669 (3 @ $22,223)

Total= $329,012

Count Job Title Gross Annual Pay*

1 Manager $37,343 (1 @ $37,343)

4 Payment Reps $100,000 (4 @ $25,000)

0 Exceptions $0

2 Master Card Reps $49,066 (2 @ $24,533)

Total= $186,409

Accounts Payable: Accounts Payable:

Expected Annual Savings from headcount reduction: Old process $639,699 New Process $241,438 Total head count savings = $398,261

Count Job Title Gross Annual Pay* (avg. annual pay for 1 x total count)

0 Supervisor $0

3 Fax People $55,029 (3 @ $18,343)

0 Filers $0

0 Mail Openers $0

0 Researchers $0

Total= $55,029

*Reflects salary with benefits, exclusive of overtime

Example of Cost/Benefit Analysis with Back Up Data Detail

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Savings From Elimination of Overtime: Overtime paid from week 9-43 4,863 Avg. hourly pay, non exempt employees* $ 11.68 Total Over time elimination savings $ 56,799 *fully loaded labor rate based on average of the time periods studied

FINANCIAL WEEK HEAD

COUNT TOTAL HOURS TOTAL OT

HOURS Loaded Labor Rate 9 62 5,336.00 721.28 11.25

PRIOR TO 11 68 6,904.57 796.28 11.31 IMPROVE- 13 67 5,990.67 667.80 11.45

MENT 15 67 5,956.65 641.63 11.19 17 62 5,169.00 114.02 11.42 19 63 5,074.25 2.25 11.24 21 61 4,768.00 - 12.01

I 23 60 4,879.27 115.95 11.23 M 25 59 4,688.00 - 11.42 P 27 58 4,625.25 17.25 12.26 R 29 57 4,541.70 16.50 12.24 O 31 58 4,705.87 97.88 11.34 V 33 56 4,487.75 39.75 12.26 E 35 56 4,403.45 54.75 12.11 M 37 56 4,652.43 369.38 12.61 E 39 55 4,918.54 631.95 11.44 N 41 55 4,918.02 563.33 12.23 T 43 55 4,381.12 13.13 11.23

90, 400.54 4,863.13

Example of Cost/Benefit Analysis with Back Up Data Detail

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Elimination of Check Writing Costs: Old Process: New Process:

Check printing and postage costs $120,000 $50,824

Check processing volume (percent of total volume) 85% 36%

Check Printing and Postage Cost Check printing and postage after improvement

$120,000 $ 50,824

Total Cost Savings from reduction in check writing as a result of automation: $69,176

Productivity Increases: Old Process: New process:

Avg. number of transactions per payment rep./day (based on time studies) 31.8 49.0

Expected annual savings from productivity increases:

Productivity Improvement as a result of new process = (49.0 -31.8)/31.8 54%

Required additional payment reps, old process, to achieve new process productivity level (% change * 9 people) = 4.87 additional people Avg. annual salary, net of overtime

4.87

$25,000

Productivity Increase Savings: $121,750

Example of Cost/Benefit Analysis with Back Up Data Detail

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When analyzing the costs it is important to distinguish between the design/implementation and the operational impacts

 Cost associated with design and implementation  Training Cost  System Cost  Design and Development Cost  Cost of Change

 Costs associated with operational impacts  Resource Consumption  Rework Cost  Cost of Capital  Maintenance Cost

Considerations for Analyzing Costs

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Lean Six Sigma focuses on tying process improvement to the company bottom line. The Finance function is responsible for reporting this bottom line---the effectiveness of any Lean Six Sigma implementation is therefore dependent on building credibility with Finance. This can be accomplished through either a separate Finance tollgate or a Finance representative being present at the regularly scheduled tollgates at the end of each phase.

AnalyzeDefine Measure Improve Control

PHASE TOLLGATE

PHASE TOLLGATE

PHASE TOLLGATE

PHASE TOLLGATE

PHASE TOLLGATE

FINANCE TOLLGATE

FINANCE TOLLGATE

Phase Tollgates are reviews with Lean Six Sigma Mentors and Sponsors after every phase to ensure that all phase deliverables have been met and sufficient rigor maintained to move on to the next phase. Finance Tollgates occur during or after Improve (when one knows enough about the process to develop a cost/benefit analysis) and Control phases (when project savings are to be booked).

The Importance of Finance Review at Tollgates

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A lot can change during the course of a Lean Six Sigma project: key business assumptions, strategy, execution, processes, etc. This change can have dramatic impact upon a project’s cost/benefit analysis model. As a result, most companies set up periodic audits of Lean Six Sigma projects after implementation to review and update cost models and savings.

Auditing and Updating Cost/Benefit Analysis

PROJECT COMPLETE

SAVINGS START

PROJECT AUDIT

COST MODEL

OK?

UPDATE MODEL

UPDATE SAVINGS

END

START

Y

N

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When presenting CBA, consider focusing on the following:

 Keep it simple

 Focus on the summary benefits and costs; have back up data and be prepared to go into detail if necessary, but be careful not to go “into the weeds” in terms of detail

 Discuss benefits, be clear on what are soft vs. hard benefits

 Speak frankly about the costs

 Speak the language of the business: use standard methods and techniques

 Ask for input

 Confirm go/no go decision

Gaining Approval on Cost/Benefit Analysis

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What you learned during this section:

 The elements of capturing the financial impact of selected solutions

 Why performing a cost/benefit analysis on selected solutions is necessary

 How to develop a cost/benefit analysis

 Examples of various cost/benefit analysis formats

 Key considerations and lessons learned around capturing financial benefits of improvement projects

Summary of Section

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

End of Lesson: Improve – Financial Impact of Solutions

Lean Six Sigma Training

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

Test Solution

Plan for Risks

Improve – Risk Planning and Testing

Lean Six Sigma Training

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 Understand the importance of assessing and managing risks

 Learn how to conduct a Failure Mode and Effects Analysis (FMEA)

 Understand the concept of Errorproofing

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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 Every process change carries risk. Unintended consequences can strike even the best-planned implementation. While we cannot eliminate risk, we can certainly mitigate it.

 In the following pages, we will examine some tools that allow us to anticipate potential problems with the new “to-be” process and therefore reduce the risks.

RED

YELLOW

GREEN Minimal risk to implementation

Moderate risk to implementation

Severe risk to implementation

Risk Assessment and Mitigation

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Common tools for risk assessment and mitigation:

 Failure Mode and Effects Analysis (FMEA)

 Errorproofing

Risk Assessment and Management Tools

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 Is a structured approach to evaluating and prioritizing risks in a process and/or product

 Can be used to identify and mitigate risks prior to making changes to a process and/or product

 Can be used to prevent failures in a process and/or product

Failure Mode and Effects Analysis (FMEA)

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 To identify specific parts of the product or process that need improvement

 To improve the quality, reliability, and safety of products and services

 To increase customer satisfaction

 To document and track actions taken to reduce risk

Why Use an FMEA

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1. Review the product, service or process (use process map) 2. Brainstorm to identify potential failure modes. These are ways

in which the product, service, or process might fail (ask the question, if the failure occurs, what are the consequences?)

3. Identify 1 or more potential effects of each failure (consequences of that failure) and rate its severity

4. Identify causes of the potential failures and rate their likelihood of occurrence (frequency)

5. Rate your ability to detect each failure mode 6. Multiply the three numbers (severity, occurrence, detection)

together to determine the risk of each failure mode (RPN = Risk Priority Number)

7. Identify ways to reduce or eliminate risk associated with high RPNs

How to Conduct an FMEA

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FMEA Worksheet FMEA

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Severity = likely impact of the failure

Rating Criteria: A failure could…

10 Customer leaves you because of poor customer service

5 Poor customer service likely to result in a complaint from the customer

1 Be unnoticed and not affect customer service

Bad

Good

Sample Severity Rating Scale

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Notes: This scale is just one example; you can develop your own scale customized to your specific product, service, or process. For example, you can have more rating levels, and use other criteria.

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Occurrence = frequency of occurrence

Rating Time Period

Sample Occurrence Rating Scale

10 Once an hour

5 Once a week

1 Once a quarter

Bad

Good

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Notes: This scale is just one example; you can develop your own scale customized to your specific product, service, or process. For example, you can have more rating levels, and use other criteria.

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Detection = how easily the failure can be detected

Rating Definition

Defect caused by failure is not detectable

Process is monitored and manually inspected

Defect is obvious and can be kept from affecting customer

Sample Detection Rating Scale

10

5

1

Bad

Good

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RPN = (severity) x (frequency of occurrence) x (likelihood of detection)

 The idea is to focus action/improvement efforts on the failures that have the biggest impact on customers. The highest scoring failure modes are those that happen a lot, that are bad when they happen, and/or that are unlikely to be detected. Difficult-to-detect errors obviously are more likely to get through to customers.

 The RPN number identifies those items or process steps in the new “to-be” process that pose the greatest risk. Anticipating these risks ahead of time will allow the team to put countermeasures in place to mitigate the risks associated with the new process, thereby increasing the chances of success.

Calculating the Risk Priority Number (RPN)

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Item or Process Step

Potential Failure Mode

Potential Effect(s) of

Failure

S E V E R I T Y

Potential Cause(s)

O C C U R R E N C E

Current Controls

D E T E C T I O N

R P N

Recommended Action Responsible

Computers Viruses Loss of data, corrupted files, network invasion

4 Virus software isn’t up to date or gets disabled

8 Virus protection software

2 64 Ensure that virus protection software is up to date

Susan K.

Files not backed up

Data loss, rework

4 Staff forgets, low priority

6 None 9 216 Keep files on LAN, notify IT of remote files for automatic backup

Sam T.

Stolen Lost data, rework

8 Not locked up at night

7 None 10 560 IT Security awareness training and communication

Bob J.

Example of FMEA – IT Security

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Notes: Focus taking action on those process steps which have the highest RPN.

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 Before you use the standard scales, make sure they are in line with your process or product

 Make the tool work for you and your particular process

 The scales for severity, occurrence, and detection can be adjusted if necessary

 If standard scales don’t apply, brainstorm the appropriate FMEA scales that best fit your particular process

Adjusting FMEA Scales

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No matter how good people’s intentions are, if a process allows for the generation of defects, the process will generate defects.

A common tendency to eliminate errors is to add inspection steps. Inspection does not prevent errors, it just detects them. Inspection requires time and resources and is not an efficient method to reduce errors.

Another technique to combat this propensity toward defect generation is Errorproofing. Errorproofing is an alternative to inspection.

Error-proofing a process is a technique to help prevent errors and increase the chances of detection so that failure mode occurrences are eliminated.

Similar to FMEA, teams can use this tool to identify many possible actions to prevent errors or mitigate their effects.

Errorproofing

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What is considered an error?

 Errors are inadvertent, unintentional, accidental mistakes made by people because of the human sensitivity designed into processes.

 Errors result in those once in a while defects that we always find difficult to control.

Errorproofing

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It’s Origins:

Errorproofing (also known as Poka-Yoke technique) was developed to mistake-proof processes.

Poka-Yoke translates into English as to avoid (yokeru) inadvertent errors (poka). The result is a business that wastes less energy, time and resources doing things wrong in the future.

How it works:

Errorproofing involves physical process modifications to eliminate the opportunity for defects. Errorproofing measures or techniques should be an integral part of the process. The technique or device to eliminate or reduce the error is placed sufficiently close to where mistakes occur, providing fast feedback to the process operator of mistakes occurring.

The selected errorproofing technique should qualify the following criteria:

 Inexpensive.

 Based upon common sense, preferably of the operator or the 1st line employee.

 It MUST eliminate or reduce occurrence and/or provide detection of the problem at the source itself.

Errorproofing

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Eliminates errors in counting out change owed back to the customer

Cash register is programmed to calculate correct change

Eliminates safety hazardChild locks on car doors

Error reduced or prevented as a result of errorproofing

Errorproofing Technique

Examples of Errorproofing

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This prevents the processing department from reviewing an incomplete document, sending it back to the loan department, delaying the processing of paperwork

The online banking form requires all fields to be filled in for a loan (including the loaner signature) before allowing the form to be sent to processing

Reduces spelling errorsSpell check function and auto correct function in a word processor

Error reduced or prevented as a result of errorproofing

Errorproofing Technique

Examples of Errorproofing

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Prevents surgery from being conducted on the wrong limb or side of the body

Before surgery patient’s incision site is marked with a marker

Reduces plane collisionsCollision avoidance radar in planes

Error reduced or prevented as a result of errorproofing

Errorproofing Technique

Examples of Errorproofing

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What you learned during this section:

 Understand the importance of assessing and managing risks

 Learn how to conduct a Failure Mode and Effects Analysis (FMEA)

 Understand the concept of errorproofing

Summary of Section

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

Test Solution

Plan for Risks

Improve – Risk Planning and Testing

Lean Six Sigma Training

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 Understand the importance of testing the new solution

 Learn what a pilot is and the benefits of conducting one

 Learn the elements of an effective pilot plan and the key considerations for making the pilot successful

 Learn how to evaluate and confirm pilot results

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Before we can implement our solution, we need to test our solution to confirm the expected impact on our process performance. The Shewhart Cycle of Plan- Do-Check-Act (PDCA) applies to this effort:

PLAN DO

CHECKACT

Develop a plan of how we will test the solution

Conduct a pilot test

Check the plan and the results

Compare estimated improved process performance (Y) to goals for project

Revise action plan if improved process performance (Y) would not be sufficient

 Implement action plan if improved Y is sufficient

Testing Our Solution

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Definition of a Pilot: A test of all or part of a proposed solution on a small scale in order to better understand its effects and to learn about how to make the

full scale implementation more effective and successful.

It is important to test your solution to identify any problems and manage risks prior to implementing the solution across the organization.

One method we use to test our solution is a Pilot.

Testing Your Solution

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 Make further improvements to the solution

 Gain additional understanding of the risks

 Identify opportunities to reduce risks

 Validate assumptions

 Validate solution cost/benefit

 Practice run prior to full implementation

 Facilitate stakeholder buy-in

Reasons to Pilot

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 The scope of the implementation is large

 The scope of the implementation is complex

 Confirmation of the desired results is required

 Validation of the selected solutions is required

 Additional stakeholder commitment is needed

When to Pilot

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Test product/process:

 With a specific market or customer segment

 Within a particular business unit or location

 With a single row of employees or shift (morning shift employees, afternoon shift employees, etc.)

 With a focus group

 When processing a subset of items

Pilot Strategy

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Defined Roles/Responsibilities Pilot steering

committee/team (select those who will be supportive) Pilot participants Liaison between pilot area

and core pilot team

Workplan

Have a detailed project plan Identify tasks and owners Identify dates of

completion Pilot plan outline

Communication Plan

Inform and motivate steering committee and pilot participants Inform and motivate all

associates Conduct daily briefings

with steering committee

Training Plan

Train all employees which are affected by the pilot Review pilot plan with

trainees

Goals/Targets

Identify success measure Make continuous, small

improvements towards the CTQ and specifications

Evaluation Process

Record observations Set up a feedback loop Compare actuals to goal

Elements of an Effective Pilot Plan Pilot Plan

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Step 1. Select pilot oversight committee

Step 2. Identify pilot participants

Step 3. Develop pilot plan

Step 4. Communicate to the organization about the pilot

Step 5. Train pilot participants

Step 6. Execute pilot

Step 7. Evaluate pilot results

Step 8. Debrief on lessons learned from the pilot

Step 9. Adjust process where necessary based on pilot results

Step 10. Prepare for full scale implementation or increase scope of pilot to a second area prior to implementation if necessary

Steps to Piloting

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Product/Service: Insurance Services

Function/Process Tested: Claims Payment process

Pilot Plan Objectives: 1. Test new “to-be” process 2. Validate expected results 3. Identify risks

Pilot Strategy: Pilot within claims department in location A Pilot Duration: 30 days

Plan Pilot Actuals Measure Target Tolerance Average Sigma CTQ 5 day cycle time + 1 day

Measurement Plan:

Pilot Observations:

Gaps:

Follow-up Actions:

Pilot Plan Outline Example

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 Where to pilot? What location, department or segment of the organizational process?

 How do we ensure that the full range of process conditions are tested during the pilot (i.e. cyclical business cycles)?

 How long do we need to pilot or how many samples do we need to statistically be sure that the process is capable to produce the desired outcome?

 What needs to be measured? How? When? Where?

 How do we ensure that pilot process is contained (i.e. not influenced by other processes or departments)?

 How to minimize service or production disruptions that the pilot may cause to the business?

Key Considerations when Planning the Pilot

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PLAN DO

CHECKACT

Check the Plan

Check the Results

Date Completed

 Develop Form 4/28  Test Form 5/03  Revise Form 5/10  Roll-Out 5/12

Check Results:

Compare graphs such as paretos, histograms, etc. before pilot to the same graphs post pilot

Confirm the results via hypothesis testing tools

Check Plan and Results

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Add more data to an existing run chart or control chart

Prepare new Pareto charts for those you created in Measure/Analyze. Make the scale and dimensions the same so you can more accurately judge degree of improvement

Draw new histograms on the same scale as the original graphs

Before After

}Improvement

Target }Remaining Gap

Good

Step 4 changes implemented

} Improvement Before After

A1 A2 A3 A4 A2 A1 A3 A4

151050

8

7

6

5

4

3

2

1

0

Fr eq

ue nc

y

654321

8

7

6

5

4

3

2

1

0

Fr eq

ue nc

y

Before After

Evaluating Before and After Data

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Total Opportunities Total Defects Before Pilot Total Defects After Pilot

960 846 86

Sigma = 0.3

Yield = 1 –

= 1 – .88

= 12%

960 846

BEFORE

Sigma = 2.8

Yield = 1 –

= 1 – .09

= 91%

960 86

AFTER

Assessing Pilot Results – Recalculate Process Sigma

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Results  How much was the gap between desired and actual reduced?  What targets were missed and why?  Were the plans effective in addressing the root causes you targeted?  What do customers tell you now that the changes are in place?  Has enough progress been made or do you need to go back and try other solutions?  Were there unintended benefits or negative side effects?

Methods  Did you follow your plan? Did the pilot represent the conditions of what the actual

implementation will be like?  Do you need to modify the plan/solution prior to implementation?  In what ways do you need to modify the process/solution before implementation?

When evaluating pilot results, both the results and the methods need to be considered

What to Consider when Evaluating Pilot Results

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 Confirm that you followed the plan and didn’t deviate from it, causing poor results

 Retrace your steps and look for flaws or gaps in your analysis

 Pick up with that step and start again if necessary

 Go back and select another solution if necessary

What to do if Desired Results aren’t Achieved After Pilot

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What you learned during this section:

 The importance of testing the new solution

 What a pilot is and the benefits of conducting one

 The elements of an effective pilot plan and the key considerations for making the pilot successful

 How to evaluate and confirm pilot results

Summary of Section

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

End of Lesson: Improve – Risk Planning and Testing

Lean Six Sigma Training

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

Implementation of Solutions

Implementation Planning - Cultural

Implementation Planning - Technical

Improve – Implement Solution

Lean Six Sigma Training

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 Understand the two sides to implementation planning

 Learn the elements of the technical implementation plan

 Understand how to use an MGPP

 Learn various work planning tools

 Know what a Gantt Chart is and how to use it

 Gain experience developing an implementation plan

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Planning for Implementation

The project team has selected the solution, analyzed the potential risks and conducted a pilot test of the solution and is now ready to implement it. You must now translate the drawing board solution design into a working, breathing implementation plan.

Implementation Planning Implementation

Plan – High Level or

Implementation Plan - Detailed

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There are two sides to Implementation:

The technical side The people/cultural side

To successfully implement the solution we must plan for both! We will begin by learning about the technical plan….

And

The Two Sides to Implementation Planning

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Elements of the technical plan include:

 Project definition and objective  A plan for the work involved to

implement the solution  Tasks and subtasks to complete

the work  Time and schedule to complete

the tasks  People and resources (money,

equipment, etc.) needed to fulfill the plan

The Technical Plan

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 The source of this information should come from your project charter.

 Just like the purpose of the charter, the purpose of the project definition is to keep the implementation team on track.

 It also serves as the foundation of the implementation plan.

 Project Definition should include:  Purpose/goal  Objectives  Specifications  Constraints  Scope

The project definition is a statement of the project objective, purpose, goal and scope.

Develop Project Definition and Goals of the Implementation

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Purpose/Goal: Why are we doing this project? (Ex. To improve productivity? Increase Sales? Reduce lost customers?)

Objectives: What specific outcomes are desired? What is the definition of success? (Ex. To implement the new MasterCard payment process with as little impact on the business as possible.)

Specifications: What are the targets and specifications for the improved process? (Ex. 5 day cycle time)

Constraints: What parameters must the implementation be completed under? (Ex. Time to implement solution must not exceed 3 weeks)

Scope: Are there any processes or locations that the solution will not be implemented in? (Ex. Excluded: Tokyo office)

Develop Project Definition

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When implementing solutions that are very large in scope or large in the magnitude of change from the “as-is” process, a Multi-Generational Product Plan (MGPP) can be a useful tool to scope the implementation effort into three separate phases.

 The Multi-Generational Product Plan (MGPP) is a tool used to define the scope of a new product or new service process as well as to plan the long-term direction of future product/service generations.

 It is built around core technologies, competencies or platforms (this can be an excellent tool for solutions that involve technology)

Definition of MGPP:

Project Definition – Scoping Large Implementation Efforts

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Notes: Not all teams will use this tool. Many DMAIC solutions are scoped to only require 1 generation. However even for those teams with a small to medium scope, it can still be an effective tool for long term planning and future enhancements to the product/process.

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Product/ Process

Generations

Platforms and

Technology

Vision Long Term direction for each key product/service process based on anticipated evolution of the market and competitor products/services beyond current applications

Series of releases; each release characterized by distinct combinations of features or technology

Product/service/process competencies which can be leveraged to introduce a number of product generations quickly and to reduce the cost of new product/process development

Elements of an MGPP

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Generation 1

Generation II

Generation III

Stop the Bleeding

Fill selected product/process voids

Take the offensive

Fill new target markets

Attain technical leadership

Deliver productivity breakthroughs

Step

Stretch

Leap

Generations of an MGPP

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Notes: Most DMAIC project are focused on achieving generation 1.

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MGPP’s uses in the Improve phase:

 To break large scoped improvement solutions into manageable phases

 To help the organization focus on long term planning around the solution

 To plan future releases or enhancements to improvement solution

 If some part of the solution is going to have a very unfavorable impact, you can look to the MGPP to see whether it might make sense to move that capability to a later generation

 MGPP can control scope additions/changes to current improvement solution design

 MGPP can prevent products/services/processes from stagnating while the market changes around them

MGPP

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Create Work Plan

The work plan will be the specific set of tasks and objectives, aligned with identified resources and a defined schedule. It will define the integrated activities and their sequence that the team will use to implement the improvement solution.

Tasks & Timeline

Aug. Sept. Oct. Nov. Dec. Jan. Feb.Step

Budget & Resources

Expenses

Staff time

xxxxx 00.00 xxxxx 00.00 xxxxx 00.00

Bob 5 hrs

Develop the Work Plan for Implementing the Solution

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When listing the tasks and activities that must be completed for the solution to be implemented successfully, consider these major activities/elements the plan should include:

Tasks & Timeline

Aug. Sept. Oct. Nov. Dec. Jan. Feb.Step

 Training Plan

 Communication Plan

 Rollout Schedule

 Implementation of Equipment, and Materials (if applicable)

 Evaluation Process

 Change Management Plan

Develop the Work Plan for Implementing the Solution

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Project Plans April. May. June July Aug. Sept OctStep

Gantt Charts

Flowcharts Processing Administration Adjusters Payables

Work Planning Tools

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Notes: Now we want to put all of the tasks associated with the elements of the Implementation plan into a work plan which indicates the dates and owners of each of the tasks and activities. Project plans, Gantt charts and flowcharts are all excellent work planning tools.

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 A Gantt chart is a project management tool that shows the timing, duration, and interrelationship of steps in a process.

Implement New Claim’s Processing System

Implement Solution ID

1

2

3

4

5

6

7

8

9

Install new hardware

Revalidate System

Install new software

Train Processing Staff

Update documentation

Develop Training Plan

Train Staff

Test

Task Name 5/31 6/7 6/14 6/21 MAY JUNE

6/28

Jen, Kris, Sue

Conroy

Conroy

Gwen

Team, TBD Team, TBD

Gantt Chart

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Tasks (level of detail

will vary)

Tasks ID # Length of bar indicates duration

of task. Also indicates start and end point in relationship to other

tasks

Implement New Claim’s Processing System

Implement Solution ID

1

2

3

4

5

6

7

8

9

Install new hardware

Revalidate System

Install new software

Train Processing Staff

Update documentation

Develop Training Plan

Train Staff

Test

Task Name 5/31 6/7 6/14 6/21 MAY JUNE

6/28

Jen, Kris, Sue

Conroy

Conroy

Gwen

Team, TBD Team, TBD

Indicates owner of

task

Illustrates duration of main task

Gantt Chart Elements

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Notes: There are generally five kinds of relationships between steps in a Gantt chart: 1. No relationship (the tasks are independent) 2. Start-to-end (one task can’t start until another ends) 3. End-to-start (one task can’t end until another starts) 4. Parallel start (both tasks need to start at the same time) 5. Parallel stop (both tasks need to end at the same time)

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What you learned during this section:

 The two sides to implementation planning

 The elements of the implementation plan

 How to use an MGPP

 Various work planning tools

 What a Gantt Chart is and how to use it

 How to develop an implementation plan

Summary of Section

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

Implementation of Solutions

Implementation Planning - Cultural

Implementation Planning - Technical

Improve – Implement Solution

Lean Six Sigma Training

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 Understand the importance of developing a plan to prepare the organization to successfully accept and transition through to using the new improvement process

 Learn the key elements of a change management plan

 Learn tools and techniques to effectively manage stakeholder support for your selected solution

 Understand the critical role communication planning plays in a successful implementation

 Learn how to develop a project storyboard

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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 To enable a smooth implementation of the improvement solution

 To identify sources of resistance, uncover the reasons, and convert resistors

 To build commitment and support for the improvement solution across the organization

 For the critical stakeholders to fully support or even embrace the change

To help the team develop a comprehensive change management plan and keep the efforts focused, you should clearly define the goals and objectives of the change management effort.

Change Management Goals

Change Management Plan – Objectives and Goals

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Early on in the project we identified the importance of stakeholder influence on the projects success. The implementation of the solution is one of the most critical junctures in the life of the project where stakeholder influence can either make or break the project’s success.

Because positive stakeholder influence is so essential to a smooth and successful implementation, it is important to review and re-evaluate our stakeholder analysis specifically for the implementation effort.

Project Sponsor Process Owner

Middle Management Executive Leadership

Front Line Employees

Enabling Functions Supplier

Team Members

Stakeholder Influence During the Implementation Phase

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Once the actual solution has been selected to address the process problem, often times stakeholder support can shift either positively or negatively.

Therefore it is important to revisit the process for managing stakeholders.

In flu

en ce

o n

Pr oj

ec t

Impact of Change (from the Solution)

After Solution Selected

Low Medium High

Lo w

M ed

iu m

H ig

h

9

4

5

6 8

3

9 6

1

2

In flu

en ce

o n

Pr oj

ec t

Before Solution Selected

Impact of Change (from the Solution) Low Medium High

Lo w

M ed

iu m

H ig

h

9

4

5

6 8

3

9 6

1

2

Stakeholder Shift

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Notes: Often times a stakeholder who is supportive of the project during the earlier phases of the DMAIC project lifecycle can shift once the solution is selected for the following reasons: - The selected solution is perceived as a threat to the stakeholder’s position of power - The stakeholder wanted a different solution to be selected - The selected solution is perceived by the stakeholder as being too risky or not likely to succeed The selected solution is perceived by the stakeholder as adding too much to daily workload. Stakeholder Map Legend: Triangle = Enthusiast, Square/Rectangle = Neutral, Circle/Oval = Opponent

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Identify Stakeholders

Develop Stakeholder Map

Develop Stakeholder

Management Plan

Step 1 Step 2 Step 3

 Re-examine the list of stakeholders

 Are there any new stakeholders that should be added when considering the newly selected solution and implementation effort?

 Re-evaluate the stakeholder map and identify positive and negative stakeholder shifts in support, based on the selected solution

 Identify where key stakeholders need to be for successful implementation

To meet the objective of a successful implementation and effectively manage stakeholder shift, we must re-tool the process for managing stakeholders with a focus on the newly selected solution.

 Identify source of concern and develop action plan to convert resistors who are critical stakeholders to the successful implementation of the solution.

Readdress the Process for Managing Stakeholders

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Benefits and Barriers:

Assume that it is now two years in the future and we have been successful in implementing the process. What benefits do you see for yourself as an individual, for your dept., and for the company as a whole?

Benefits

What are the barriers that we as an organization are going to have to overcome in order to make the implemented change a success and thereby achieve the benefits?

Barriers

Brainstorm the benefits and barriers to implementation with stakeholders, identify top three, and develop action plans

Force Field Analysis:

Additional Tools to Manage Stakeholders Forcefield Diagram

24

Driving Forces Restraining Forces

Goal

Brainstorm the driving forces and restraining forces with stakeholders, identify top three, and develop action plans

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Teams can impede their own success when they don’t consider the following when managing stakeholder support:

 The importance of political sensitivity  Failing to recognize the need to “share the glory”  Assume technical solution is sufficient  Don’t involve others due to time constraints  Use only one or two conflict resolution styles  Fail to appreciate the human side of implementing

solutions

Tips and Traps for Managing Stakeholders

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Another component to building and maintaining support for the implementation of the improvement solution is aligning systems and structures with the new process solution.

When we are expecting stakeholders to be supportive and enthusiastic about the new solution, it is important to make sure the way we organize, train, reward, compensate, and promote aligns with the behavior we are expecting.

If organizational measures and rewards don’t link to the desired behavior and the new process solution, we run the risk of the change not being effective or not lasting long term.

Aligning Systems and Structures

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 Do any measurements exist around achieving sigma goals and service quality?

 Do any rewards exist around rewarding sigma goals and service quality?

 What type of behavior do we want to reward?

 What types of behaviors do we want to eliminate?

 Are there measurements in place today that actually promote the wrong behavior or are in conflict with what we are trying to achieve with the new “to-be” process?

Aligning Systems and Structures

Key considerations for aligning systems and structures with the new process goals:

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One of the most important elements to facilitate change is communication to those affected by the change.

Consistent and effective communication also fosters cooperation and collaboration which are key elements to an efficient transition to the “to-be” process.

Communication

Collaboration Change

Communication Planning

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Below is a review of some key considerations when developing your communication plan for the implementation of the solution.

 Organizational communication is a change agent The purpose of communication is not just to convey information, but to change behavior. Project communication should change behavior by building support of and buy-in toward the project's objectives.

 Communication is a two way process Listening and encouragement of feedback is critical to understanding whether project communication has been effective and to evaluate whether the project is being supported or not; and if not why.

 Craft communication in the interests and language of the target audience To be effective, the message should be focused on the receiver of the communication’s interests in both content and context.

 Communication must be compelling and continuous To be compelling consider creative ways to deliver your message. To be remembered and internalized, communication needs to be continuous and consistent.

Communication Planning Considerations

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A communication plan for the project was developed back in the Define phase. That plan should be revisited at this stage in the project to identify specific messages that need to be delivered regarding the implementation of the solution.

 Communication regarding the solution and why that particular solution was selected

 Communication to key stakeholders to prevent resistance and gain support for the solution

 Communication around the implementation schedule and timeline

 Selling the project story and its benefits to the organization

The key communication messages that should be disseminated regarding the implementation fall into the following major categories:

Communication Plan for Implementation of the Solution

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All employees

All employees

Audience

SurveySponsorDMAIC Team

Gallery Walk to present project story board

August 30Selling the project story and benefits

Check in with key stakeholders for feedback

SponsorBlack Belt / Green Belt

Mass e-mail campaign to the organization

August 5Selling the project story and benefits

Feedback Loop

Required Approval

OwnerMethodWhenWhat

Implementation Communication Plan Example Communication

Plan

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When looking at the core categories of communication that should be considered for the implementation plan, we have looked at all the categories but the last.

Communicating the “project story” and its benefits to the organization is an important part of facilitating change and building support for the project across the organization.

Communication regarding the solution and why that particular solution was selected

Communication to key stakeholders to prevent resistance and gain support for the solution

Communication around the implementation schedule and timeline

Selling the project story and its benefits to the organization as a whole

Communication Planning

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What is a Project Story?  A presentation and visual depiction of the steps the team took during each phase of the

DMAIC process.

 It communicates key deliverables and accomplishments that were completed by the team during each phase of the improvement process.

 A project story brings all the work and effort the team put into their DMAIC project to life through a storyboard presentation.

Why Communicate your Project Story?

 Provides the organization with a full understanding and appreciation of the rigor that went into selecting the solution.

 It provides a standard way to communicate the team’s progress.

 Builds enthusiasm and support for the project.

 Educates the organization on the Lean Six Sigma DMAIC process and the DMAIC project lifecycle.

 “Selling the project story” and its benefits to the organization is crucial in developing a critical mass of support for the Quality initiative.

The Project Story

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The most effective way to tell and “sell” the project story is by developing and presenting a storyboard.

What’s a Storyboard?

 A visual illustration of the project story (steps, tasks, key deliverables, and results from each phase of the project) typically displayed on a large board so it can be easily read and viewed.

How to Communicate the Project Story

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Team Information DEFINE MEASURE

Project Overview

ANALYZE IMPROVE CONTROL

9080706050403020100

60

50

40

30

20

10

0

Average Hold Time

# of

C al

ls

January Avg. Hold Time Distribution Plot

Add res

s

Inac cur

ate

Line Item T

ota l

Am oun

t Ove rch

arg e

Oth ers

42 32 14 9 3 42.0 32.0 14.0 9.0 3.0

42.0 74.0 88.0 97.0 100.0

0

50

100

0

20

40

60

80

100

Defect

Count Percent Cum %

Pe rc

en t

C ou

nt

Pareto Chart for Statement Accuracy

0Subgroup 5 10 0.000 0.001 0.002 0.003 0.004 0.005 0.006 0.007

Pr op

or tio

n

IncreasedOpportunities per Unit

Charter

CTQ’s

Process Map

Data Coll.

Sigma

Capability

Root Causes Solution Selected

FMEA

Pilot

Monitoring

Response plan

A 12 22 145

B 52 43 130

C 48 43 180

“1 Page” Project Storyboard Example Project Storyboard

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The Gallery walk also provides an opportunity for the members of the organization to ask questions of the project team about the project.

Gallery walks are a very effective communication method to use before the solution is implemented, as well as, throughout the life of the project to communicate project progress and generate enthusiasm for the project.

Project Storyboards are typically presented at a Gallery Walk.

What’s a Gallery Walk? Gallery walks are scheduled coordinated meetings where members of the organization are invited to attend the meeting to hear about each of the Lean Six Sigma projects that are being worked on by DMAIC teams throughout the organization.

How to Communicate the Project Story at a Gallery Walk

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1. Communicate the focus of your project and the phase of DMAIC the team is currently in

2. When presenting the storyboard, consider your audience

3. Identify the story you want to tell them. What do you really want the organization to know and understand about your project?

4. Emphasize the benefits of your project

5. Use strong visual aids to tell your story (graphs and charts)

6. Communicate the key deliverable, lessons learned and output of each DMAIC phase of the project

7. Have the entire team participate in the gallery walk presentation, this is a great team builder

Storyboard and Gallery Walk Tips and Traps

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8. Keep your storyboard to no more than 10 slides (for a gallery walk)

9. Slides can have a lot packed in, but be careful not to make too busy

10. When developing the gallery walk presentation for the storyboard, draw it out on paper first before you create your final presentation

11. Developing a presentation script makes the presentation more effective and can be a good exercise for the team, particularly if the team has inexperienced presenters

12. Be creative!

13. Be sure to conduct a survey after the gallery walk to determine if your communication was effective

14. Allow sufficient time to develop your project storyboard and practice the gallery walk presentation

Storyboard and Gallery Walk Tips and Traps

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What you learned during this section:

 The importance of developing a plan to prepare the organization to successfully accept and transition through to using the new improvement process

 The key elements of a change management plan

 Tools and techniques to effectively manage stakeholder support for your selected solution

 The critical role communication planning plays in a successful implementation

 How to develop a project storyboard

Summary of Section

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Notes:

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

Implementation of Solutions

Implementation Planning - Cultural

Implementation Planning - Technical

Improve – Implement Solution

Lean Six Sigma Training

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 Know the steps to implementing the solution

 Understand the key questions that need to be answered to complete the Improve phase

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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 Now that the planning process is complete it is time to execute the plans

 If the appropriate amount of time and attention to detail was put into the planning of the implementation, the rollout of the solution should be successful

Implementing the Plans

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1. Update “to-be” process maps to reflect any changes that came out of the pilot

2. Prepare data collection forms

3. Conduct training

4. Rollout process on a small scale first if possible, then move to full scale rollout

5. Monitor implementation and evaluate results

Steps to Implementing the Solution

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 Use the same methods and procedures used during the pilot to monitor and evaluate results

PLAN ACTUALS

 Conduct daily “book end” meetings with the implementation team

 Meet at the beginning of each morning to discuss any key information points or plans

 Meet at the end of each day to debrief on the outcome and results of process performance for that day

Before implementation

151050

8

7

6

5

4

3

2

1

0

Fr eq

ue nc

y

654321

8

7

6

5

4

3

2

1

0

Fr eq

ue nc

y

After Implementation

Monitoring the Implementation and Establishing Check Points

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Solution Selection:

What other potential solutions did the team consider? What were the primary criteria for selecting the solution(s)?

Cost/Benefit:

What is the net project benefit? What are the assumptions of the cost/benefit analysis?

Risk Assessment:

 How did the team analyze process risks? What risks were identified? What was done to mitigate the risks?  In what ways has the solution been modified based on pilot results?

Yes No

Yes No

Yes No

Tollgate Questions and Check list Items:

Improvement Completion Checklist

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Tollgate Questions and Check list Items:

Solutions Pilot:

Was the solution tested? Did the pilot represent the conditions of the actual implementation?

What measures were established for pilot results? What target performance levels were set for those measures? What targets were missed, and why?

 In what ways has the solution been modified based on pilot results?

Implementation Planning:

What is the implementation schedule and timeline? What new stakeholders were added as a result of the selected solution? Did any of the

stakeholders negatively shift their position after solution selection? What were the survey results from the gallery walk?

Yes No

Yes No

Improvement Completion Checklist

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What you learned during this section:

 Know the steps to implementing the solution

 Understand the key questions that need to be answered to complete the Improve phase.

Summary of Section

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Define Measure Analyze Improve ControlDefine Measure Analyze Improve ControlDefineDefine MeasureMeasure AnalyzeAnalyze ImproveImprove ControlControlDefine Measure Analyze Improve Control

End of Lesson: Improve – Implement Solution

Lean Six Sigma Training

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Control Phase

Lean Six Sigma Training

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Control Phase Overview

Lean Six Sigma Training

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Control develops the monitoring plan that will be used to ensure the process gains are maintained, develops the response plans should a problem with the process develop, documents all processes and procedures for the organization, reviews any replication opportunities from the project, and celebrates the projects success.

Control Phase Introduction

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ANALYZE

CONTROL

IMPROVE

MEASURE

DEFINE

 Develop Process Control Monitoring Plan

 Standardize Processes and Develop Change Implementation Plans

 Create Storyboards of Improvement

 Identify Replication Opportunities

 Complete Project Closure and Celebrate Success

Processing Administration Adjusters PayablesProcessing Administration Adjusters Payables

Control Phase Overview

4

Loan Processing Cycle Time Sigma = >6

Mean CL: 8.86

1.91

15.81

1.31

3.31

5.31

7.31

9.31

11.31

13.31

15.31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

In di

vi du

al s

- C hi

ca go

L oa

n P

ro ce

ss in

g C

yc le

T im

e

Mean CL: 1.52

-0.11

3.15

-0.11

0.39

0.89

1.39

1.89

2.39

2.89

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

In di

vi du

al s

- C hi

ca go

L P

L oa

n R

ev ie

w in

g Ti

m e

Chicago Loan Processing Cycle Time

Chicago LP Reviewing Time Chicago Package Accuracy – Error Type

Final Package Accuracy Sigma = 3.5 LP Reviewing Time Sigma = 3.1

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Develop Process

Control Plan

Develop Response

Plan

Document Solutions

 Control Chart

 Dashboard Measurement Plan Matrix

 Dashboard

 Benefits Realization

 Response Plan

 Process Management Chart

 Process Reviews

 Process and Procedures

 Communication Plan

Control Tools

Control Approach

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Control Phase Deliverables

Define Measure Analyze Improve Control

Project Charter Project Management

Project Plan Process Definition

SIPOC As-Is Process

Map Quick Win

Identification Stakeholder

Management Stakeholder Map Stakeholder

Management Plan Communication

Plan Voice of Customer

Customer Identification

VOC Research Plan

Kano Analysis CTQ Identification

 Root Cause Analysis Affinity Diagram Fishbone Diagram

and/or 5 Why’s Lean Process

Analysis Lean Tools and

Measures Graphical Data

Analysis Histogram Pareto Chart Box Plots Correlation

Analysis Statistical Data

Analysis Linear Regression Multiple

Regression Root Causes

Identified Quick Win

Identification

Identify Measures X/Y Matrix

Data Collection Operational

Definitions Measurement

Systems Analysis (MSA)

Data Collection Plan

Describe and Display Data Histogram Pareto Chart Pie Chart Run Chart Control Charts

Baseline Performance Sigma

Performance Yield Process

Capability Quick Win

Identification

Identify and Select Solutions Generate Solutions Benchmarking Solutions

Prioritization Matrix Solution Selection

Matrix To-Be Process Map

Financial Impact of Solutions Cost/Benefit Analysis

Risk Planning and Testing Failure Modes and

Effects Analysis (FMEA)

Pilot Plan Implement Solutions

Multi-Generational Product Plan (MGPP)

Implementation Plan Stakeholder

Management Project Storyboard

Process Control Control Charts Process

Monitoring Plan Dashboard

Response Plan Project

Documentation Process

Procedures Replication

Opportunities Solution Transfer

Plan

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End of Lesson: Control Phase Overview

Lean Six Sigma Training

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Control – Process Control

Dashboards

Process Monitoring

Introduction to Process Management

Lean Six Sigma Training

Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl

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 Define Process Management

 Understand the benefits of an organization using Process Management vs. Functional Management

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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A Process Management System is a measurement system used to ensure the outputs

of processes are predictable (stable) and meet customer requirements (capable).

Definition of Process Management System

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Why Process Management?

Provides a framework that will facilitate process improvement and process design activity that ultimately drives the fulfillment of important organizational goals.

Process Management enables an organization to:

 Understand operations – process metrics  Select the right processes for improvements  Enable clear links between customer requirements and

internal operational activities  Drive process ownership and accountability

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What are the functional objectives of these departments?

What are their real priorities?

Functional Management

FUNCTIONAL OBJECTIVES

Sales Under- writing Processing Claims

Info. Technology

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Many organizations have been based on functional differentiation or specialization. This has resulted in the traditional vertical/hierarchical organizations. Management direction, goals, and measurements have been deployed or cascaded down the existing organizational structure. In a traditional functional organization, the dominant focus of people is:

 Please the boss…

 The department’s specialized knowledge or skill.

 The functional goals which may not have been stated in terms that the external customer would recognize.

 The people in your silo.

Successful performance is defined as winning for the function. Things often fall through the cracks in this model causing fragmented efforts at satisfying external customers’ needs.

Functional Management System

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What are employees’

REAL priorities?

Process G oals

Sales Under- writing Processing Claims

Info. Technology

Sell Products

& Services

Process Contracts

FUNCTIONAL OBJECTIVES

Process Claims

Process Performance What We Sell...

Process Performance How We Sell...

Process Performance The Service We Provide...

Process Performance The Service We Provide...

Process Management

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The need to manage process quality with a link to strategic objectives

What are employees’

REAL priorities?

Functional Management vs. Process Management

8

What are employees’

REAL priorities?

CustomerDevelop Products &

Services

Sales Process Claims Info. Tech

Process Contracts

FUNCTIONAL OBJECTIVES

Process G oalsProcess

Claims

Process Performance

Process Performance

Process Performance

Process Performance

Under- writing

Customer

Customer

Customer

STRATEGIC OBJECTIVES

What are employees’

REAL priorities?

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Notes: Functional And Process Management Systems From the figure above, we see the connection of core processes with Strategic Objectives, the linkage of process deliverables with customers, and the ongoing interest that Shareholders and Upper Management will have in functional contributions to traditional business indicators such as revenue, market share, profit, ROI, etc. To meet customer needs, Functional and Process Management systems must be integrated and harmonized so that both support Strategic Objectives.

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 Provides a system of processes and indicators to help manage objectively

 Focuses on the customer

 Provides a common language within or across departments

 Internally you know how well you are doing in the eyes of the customer

 Provides accurate focus for improvement teams

 Provides learnings supported by data that can be applied to other processes

Benefits to Process Management

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From To

Function-Oriented

Somewhat Flexible, Efficient, Effective Processes

High Walls between Functions

Uneven Cycle Time

Focus on the Function/Project

Value Stream is in the middle

Quality is added on

Cross-Functional Process Focus

Increased Flexibility, Better Efficiency, Greater Effectiveness

Walls between Functions broken down

Improved Cycle Time

Focus on the Customer

Value Stream is end-to-end

Quality is built in

Sub-Optimization Integrated System

What will Change as a Result of Process Management?

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Notes: Eliminating departmental barriers and becoming process focused takes time. As the shift occurs from well-defended functional-silos to cross-functional processes, the process becomes more flexible, efficient and effective at delivering quality to its customers. Department walls become less visible as the process and its outputs become more visible and dominant. Process improvement results in processes that take less time, have steps that only add value to the customer, have fewer hand-offs, and fewer defects and errors.

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What does a Process Management System Look Like?

 There will be as much focus to processes as to individual functions

 Everyone will be able to more efficiently utilize resources

 Employees will know all of the process steps and how they add value

 Employees will understand how the process is performing

 Customers’ requirements will become known and everyone in the organization will strive to meet or exceed them

 Employees will help manage each other instead of escalating conflicts

 Hand-offs between employees are smooth and boundaryless

 Processes will be objectively and frequently measured and reviewed

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Notes: 1. How are these different from traditional management approaches? 2. When your Process Management System is in place, what will be different for your organization compared to the past?

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What you learned during this section:

 The definition of Process Management

 The benefits of an organization using Process Management vs. Functional Management

Summary of Section

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Control – Process Control

Dashboards

Process Monitoring

Introduction to Process Management

Lean Six Sigma Training

Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl

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 Understand what is meant by process control

 Understand the types of control charts

 Determine how to develop a monitoring plan

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Document and Standardize (covered later in Project Documentation

section)

4. How can I assure that things will continue?

Response Planning3. What do I do if I detect a change in the process?

Process Monitoring2. How can I detect changes in my process?  Earliest possible detection  Acceptable false alarm

Process Monitoring1. What should I monitor? TopicQuestion

Four Key Questions for Managing and Controlling Processes

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Process Control is:

The activities necessary to help to maintain the gains the project team has accomplished through

their improvements.

What is Process Control?

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Using Control Charts to Monitor for Process Control

The more we know about our process, the more likely we will be able to predict process performance

Using Control Charts to track and monitor our process indicators is critical to being able to Control and manipulate the process outcome (output)

17

therefore……

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Monitoring a Process for Control

Ongoing monitoring of the process is important for two reasons:

 Ensure that the process is in control

 Maintain process in its stable state  Compare with standards or control limits  If not within standard or out of control,

seek to identify special cause, eliminate it and prevent recurrence

 Identify opportunities for future improvements

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Monitoring a process helps us answer 5 key questions:  What is the current performance level?  Has the performance changed?  Do we need to adjust the process?  Do we need to improve the process?  How will the process perform in the future?

Adjust & Improve

Compare

Current Status

Predict

Future Performance

Past Performance

Present Performance

For comparison with baseline performance in Measure

Monitoring a Process

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X

X

X

X X X X

Y

Y

Y

Process Flow

 Key input and process measures (X) that track variables identified in your project as Key drivers of Project Y variables

 Key output measures (Y) from the customers’ perspective

Process Variables (Xs)

Input Variables

(Xs)

Outputs (Ys)

NOTE: Whether or not improvements were made to inputs, process, or outputs –

Monitoring should still be developed for all critical measures

What Should We Monitor

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Notes: The measures that you choose to monitor in the control plan are the critical measures for your process. These are the process management measures that the Process Owner will rely on to track process performance over time.

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Special Cause Variation Sporadic, isolated events that affect a Process Management Role: Eliminate

Common Cause Variation Expected, normal, random

fluctuations in Process Management role: Reduce

Categorizing Variation on a Control Chart

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By observing how variation in the process causes results to fluctuate, we can make some objective decisions about when to take action.

We do not always Want to take action.

When a process has special or assignable causes (i.e. out of control points) the action necessary to improve the process is investigation and removal of those special causes.

Processes that vary only from common causes will perform within the upper and lower control limits. If a process has only normal or common causes of variation, the focus should be on improving the process itself.

If process variation is not understood, time and money may be wasted reacting to a variation that is normal. Fixing something that does not need to be fixed can introduce more variation to the process and reduce the ability to meet customer’s needs.

Key Point:

Using Control Charts to Make Decisions

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Out of Control

Upper Control Limit

Lower Control Limit

#1

fre qu

en cy

LSL USL

Not Capable of Meeting Specification

fre qu

en cy

LSL USL

Not Capable of Meeting Specification

In Control Upper Control Limit

Lower Control Limit

#2

Four Possible States of the Process

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Notes: - Out of control and out of specification This situation is the least optimal because you have two types of variation problems to consider and the process clearly isn’t meeting customer expectations. - In control and not meeting customer specifications Getting the process in control/stable is the first step in improving the process, however it is still not meeting customer expectations. Note: It’s possible to be inside the control limits, yet still out of control as a result of shifts, patterns or trends in the data.

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Capable of Meeting Specification

fre qu

en cy

LSL USL

Out of Control

Upper Control Limit

Lower Control Limit

#3

In Control Upper Control Limit

Lower Control Limit

#4

Capable of Meeting Specification

fre qu

en cy

LSL USL

Four Possible States of the Process – Continued

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Notes: - Not in control but meeting customer specifications In this scenario, the customer specifications are broad enough to accommodate the instability in the process but the customer is being satisfied purely by chance. Because the process is not predictable, we cannot guarantee the customers specifications will continue to be met. - In control and meeting customer specifications This is the most optimal state of the process. The process is both stable and capable. The goal is to have all processes in this state. Note: It’s possible to be inside the control limits, yet still out of control as a result of shifts, patterns or trends in the data.

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It is inaccurate to put specification limits on a Control Chart.

Upper Control Limit

Lower Control Limit

“Control Limits”

Upper Spec Limit

Lower Spec Limit

“Spec Limits”

 Defined by the customer

 Help determine if the process is producing defects

 Not plotted on control charts

 Change when customer requirements change

 Defined by the process performance

 Help determine if the process is in control

 Plotted on control charts

 Change when the process changes

Voice of Process

Voice of Customer

Key Concept – Control Limits vs. Specification Limits

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Common Errors in Using Control Charts

 Management/Process Owners do not buy into the concept

 Special cause variation goes unnoticed

 Non-random patterns are not studied for special causes

 Poor or erroneous measurements are used

 Data on charts is not current

 Specifications are plotted on charts

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Use this chart to select the type of control chart to use.

Discrete

ImR Chart

Continuous

Type of Data

Subgroup Size of 1

Rational Small Subgroups (<8-

10)

Rational Large Subgroups (>8-

10)

X and S Chart

_

np Chart

Classification (binomial data)

Sample Size is Constant

Sample Size Varies p chart

u Chart

Count

Opportunity Varies

Opportunity is Constant c chart

OR

OR

OR

OR

OR

X and R Chart

_

Control Chart Types

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Notes: For X-bar and R and X-bar and S you will need to collect data in sets of points called subgroups, or logical groupings of data.

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Overview of the different types of control charts Discrete data control charts: np Chart – used with classification data (i.e. pass/fail, good/bad) and charts the number of defectives in each subgroup (sample size is constant).

p Chart – used with classification data (i.e. pass/fail, good/bad) and charts the proportion of defectives in each subgroup (sample size varies).

u Chart – used with count data (e.g. number of defects) and charts the number of defects per unit sampled in each subgroup (opportunity for defects varies).

c Chart – used with count data (e.g. number of defects) and charts the defect count per sample (opportunity for defects is constant).

Continuous data control charts: ImR Chart (Individuals) – for analyzing individual data points and rational subgroups can not be formed from the data (data is assumed to be normally distributed).

X and R Chart – for analyzing the averages of small subgroups (<8-10) can be formed from the data.

X and S Chart – for analyzing the averages of large subgroups (>8-10) can be formed from the data.

Selecting a Control Chart

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Number of defects, accidents or flaws

# of accidents/month

# of times the phone is not answered within three ring

# of breakdowns/week

# of flaws on an automobile

Fraction of “defectives”

fraction of requests not processed within 15 minutes; fraction of orders not processed perfectly the first time through (first-pass quality)

Situation Chart Used

c Chart

u Chart

p Chart

np Chart

Variables data, one figure at a time

sales, cost variances, customer satisfaction score, total cycle time per order, average cycle time per month

Variables data, sets of measurements

Situation Chart Used

ImR Chart

(Individuals)

X and R Chart

X and S Chart

_

_

Examples of which Control Chart to Use

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X Chart

0 5

10 15 20 25 30 35 40 45 50

1/1 /20

04

1/8 /20

04

1/1 5/2

004

1/2 2/2

004

1/2 9/2

004

2/5 /20

04

2/1 2/2

004

2/1 9/2

004

2/2 6/2

004

3/4 /20

04

3/1 1/2

004

3/1 8/2

004

3/2 5/2

004

Date

Ch ica

go Lo

an P

ro ce

ss ing

Cy

cle Ti

me

Range Chart

0

5

10

15

20

25

1/1 /20

04

1/8 /20

04

1/1 5/2

004

1/2 2/2

004

1/2 9/2

004

2/5 /20

04

2/1 2/2

004

2/1 9/2

004

2/2 6/2

004

3/4 /20

04

3/1 1/2

004

3/1 8/2

004

3/2 5/2

004

Date

Ra ng

e

 The first control chart (X Chart) is designed to monitor the variation from data point to data point or subgroup to subgroup (depending on the control chart used).

 The second control chart (Range Chart) is designed to monitor variation within a sample of data points. The range of a process is a reflection of the amount of variation in the process and can be useful to detect changes in variation.

 It is possible that the averages could remain fairly consistent, but the spread within the samples could fluctuate wildly. By monitoring both the variation between data points and variation within data points, we can detect special cause variation more effectively.

Why Two Charts with Continuous Data?

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Chart3

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37 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
23 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
38 29.5384615385 45.2634615385 13.8134615385
22 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
35 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
19 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
23 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
19 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
15 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
Data1
Average
UCL
LCL
Date
Chicago Loan Processing Cycle Time
X Chart

Case Study Histogram

Chicago Loan Processing Cycle Time
45
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41
31
31
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34
20
24
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32
30
29
27
36
25
33
23
34
33
28
17
27
29
29
32
43
30
25
29
27
28
31
31
40
28
26
33
33
33
22
40
36
27
30
40
22
26
26
29
36
22
38
24
36
29
29
35
33
31
26
27
25
26
30
32
34
32
29
42
33
25
27
26
26
15
46
20
40
26
33
22
28
25
34
34
31
25
37
23
38
23
31
32
38
28
35
24
25
29
34
33
33
38
23
30
28
33
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31
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30
26
30
30
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31
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22
30
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32
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34
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23
The data set is the Loan Processing Cycle Time for Chicago. We want to display and describe the variation in the process. Follow these instructions to create the Histogram: 1. Click "Engine Room" from the toolbar above. 2. Select Measure from the menu. 3. Select Histogram from the menu. 4. Select Case Study Histogram from the menu in "Select Worksheet". 5. Click "OK" 6. Select Chicago Loan Processing Cycle Time from the menu in "First Variable". 7. Click "OK" 8. Engine Room will generate a new worksheet entitled "Histogram". When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Histogram and descriptive statisics?

Case Study Run Chart

Date Chicago Loan Processing Cycle Time
1-Jan 39
2-Jan 25
3-Jan 26
4-Jan 45
5-Jan 30
6-Jan 27
7-Jan 22
8-Jan 25
9-Jan 32
10-Jan 32
11-Jan 30
12-Jan 33
13-Jan 26
14-Jan 21
15-Jan 34
16-Jan 34
17-Jan 32
18-Jan 33
19-Jan 27
20-Jan 21
21-Jan 35
22-Jan 37
23-Jan 24
24-Jan 27
25-Jan 27
26-Jan 29
27-Jan 20
28-Jan 32
29-Jan 14
30-Jan 37
31-Jan 32
1-Feb 39
2-Feb 34
3-Feb 36
4-Feb 25
5-Feb 31
6-Feb 31
7-Feb 24
8-Feb 28
9-Feb 41
10-Feb 24
11-Feb 33
12-Feb 34
13-Feb 30
14-Feb 30
15-Feb 21
16-Feb 37
17-Feb 32
18-Feb 27
19-Feb 34
20-Feb 36
21-Feb 23
22-Feb 25
23-Feb 29
24-Feb 32
25-Feb 26
26-Feb 31
27-Feb 38
28-Feb 22
29-Feb 29
1-Mar 37
2-Mar 35
3-Mar 30
4-Mar 34
5-Mar 30
6-Mar 21
7-Mar 37
8-Mar 24
9-Mar 32
10-Mar 19
11-Mar 24
12-Mar 23
13-Mar 27
14-Mar 19
15-Mar 30
16-Mar 27
17-Mar 32
18-Mar 31
19-Mar 29
20-Mar 28
21-Mar 31
22-Mar 36
23-Mar 15
24-Mar 30
25-Mar 33
26-Mar 31
27-Mar 30
28-Mar 34
29-Mar 28
30-Mar 32
31-Mar 29
The sample data set is the Loan Processing Cycle Time for Chicago with dates. We want to display and describe the variation in the process. Follow these instructions to create the Run Chart (Trend Chart in Engine Room): 1. Click "Engine Room" from the toolbar above. 2. Select Measure from the menu. 3. Select Trend Chart from the menu. 4. Select Chicago Loan Processing Cycle Time from the menu in "Data". 5. Select Date from the menu in "Time Period". 6. Click "OK" 7. Engine Room will generate a new worksheet entitled "Trend". When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Run Chart?

Case Study Control Chart

Date Chicago Loan Processing Cycle Time
1-Jan 39
2-Jan 25
3-Jan 26
4-Jan 45
5-Jan 30
6-Jan 27
7-Jan 22
8-Jan 25
9-Jan 32
10-Jan 32
11-Jan 30
12-Jan 33
13-Jan 26
14-Jan 21
15-Jan 34
16-Jan 34
17-Jan 32
18-Jan 33
19-Jan 27
20-Jan 21
21-Jan 35
22-Jan 37
23-Jan 24
24-Jan 27
25-Jan 27
26-Jan 29
27-Jan 20
28-Jan 32
29-Jan 14
30-Jan 37
31-Jan 32
1-Feb 39
2-Feb 34
3-Feb 36
4-Feb 25
5-Feb 31
6-Feb 31
7-Feb 24
8-Feb 28
9-Feb 41
10-Feb 24
11-Feb 33
12-Feb 34
13-Feb 30
14-Feb 30
15-Feb 21
16-Feb 37
17-Feb 32
18-Feb 27
19-Feb 34
20-Feb 36
21-Feb 23
22-Feb 25
23-Feb 29
24-Feb 32
25-Feb 26
26-Feb 31
27-Feb 38
28-Feb 22
29-Feb 29
1-Mar 37
2-Mar 35
3-Mar 30
4-Mar 34
5-Mar 30
6-Mar 21
7-Mar 37
8-Mar 24
9-Mar 32
10-Mar 19
11-Mar 24
12-Mar 23
13-Mar 27
14-Mar 19
15-Mar 30
16-Mar 27
17-Mar 32
18-Mar 31
19-Mar 29
20-Mar 28
21-Mar 31
22-Mar 36
23-Mar 15
24-Mar 30
25-Mar 33
26-Mar 31
27-Mar 30
28-Mar 34
29-Mar 28
30-Mar 32
31-Mar 29
The sample data set is the Loan Processing Cycle Time for Chicago with dates. We want to display and describe the variation in the process. Follow these instructions to create the Individuals Chart (XmR in Engine Room): 1. Click "Engine Room" from the toolbar above. 2. Select Measure from the menu. 3. Select XmR Chart from the menu. 4. Select Chicago Loan Processing Cycle Time from the menu in "Data". 5. Select Date from the menu in "Time Period". 6. Click "OK" 7. Engine Room will generate a new worksheet entitled "X and Moving Range". When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Individuals Charts and descriptive statistics?

Case Study Pareto

Application Fields Number of Errors
Name 12
Address 3
Loan # 0
Loan Amount 26
Loan Duration 2
City 1
State 0
The data set is from a checksheet. We want to display and describe the variation in the process. Follow these instructions to create the Pareto: 1. Click "Engine Room" from the toolbar above. 2. Select Define from the menu. 3. Select Pareto Analysis from the menu. 4. Select Case Study Pareto from the menu in "Select Worksheet". 5. Click "OK" 6. Select Number of Errors from the menu in "Data". 7. Select Application Fields from the menu in "Category". 8. Click "OK" 9. Engine Room will generate a new worksheet entitled "Pareto". When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Pareto and descriptive statistics?

Case Study Correlation

Number of Personnel Loans Processed
26 111
24 114
27 111
16 118
21 115
22 112
15 117
21 116
38 103
48 102
39 107
50 101
18 116
20 114
28 110
31 109
50 100
41 103
42 103
40 105
21 115
18 116
42 104
15 119
42 106
9 119
52 101
36 107
46 102
21 113
41 104
22 115
30 110
25 112
31 108
19 115
17 118
47 102
17 118
21 114
15 118
31 108
21 114
22 115
43 104
28 111
22 110
17 115
48 101
25 111
18 117
33 108
13 118
17 118
42 106
27 112
41 105
40 106
28 109
50 101
21 114
28 111
50 101
48 101
35 108
34 111
41 104
29 110
22 115
26 111
12 119
16 115
35 108
24 113
23 116
21 113
28 110
46 103
20 116
46 101
The data set is the number of loans processed per day. We want to see if there is a strong relationship (correlation) between the loans processed per day and the number of personnel. Follow these instructions to perform correlation: 1. Click "Engine Room" from the toolbar above. 2. Select Measure from the menu. 3. Select scatter plot from the menu. 4. Select Case Study Correlation from the menu in "Select Worksheet". 5. Click "OK" 6. Select Loans Processed from the menu in "Data". 7.Select number of personnel from the menu in 'Data-2 ". 8. Click "OK" 9. Engine Room will generate a new worksheet entitled "Scatter". When completed, answer the following questions: 1. How would you interpret the graph 2. What conclusions can you draw from p-value and the R-squared value?

Obtaining R Value

Number of Personnel Loans Processed
26 111
24 114
27 111
16 118
21 115
22 112
15 117
21 116
38 103
48 102
39 107
50 101
18 116
20 114
28 110
31 109
50 100
41 103
42 103
40 105
21 115
18 116
42 104
15 119
42 106
9 119
52 101
36 107
46 102
21 113
41 104
22 115
30 110
25 112
31 108
19 115
17 118
47 102
17 118
21 114
15 118
31 108
21 114
22 115
43 104
28 111
22 110
17 115
48 101
25 111
18 117
33 108
13 118
17 118
42 106
27 112
41 105
40 106
28 109
50 101
21 114
28 111
50 101
48 101
35 108
34 111
41 104
29 110
22 115
26 111
12 119
16 115
35 108
24 113
23 116
21 113
28 110
46 103
20 116
46 101
This is the same data set we used for the scatter plot. Now we want to obtain the "r" value (correlation coefficient) to help us detrmine the strength of the correlation. Follow these instructions to identify the correlation coefficient (a.k.a pearson coefficient): 1. Click "Insert" from the Excel toolbar above. 2. Select function from the menu. 3. Select statistical from the "Select a Category" menu 4. In the "Select a Function" menu, scroll down to PEARSON and select. 5. Click "OK" 6. To populate the field "Array 1", in the excel worksheet select and highlight fields A1-A81. 7.To populate the field "Array 2", in the excel worksheet select and highlight fields B1-B81 8. Click "OK" 9. Excel will generate an "r" value in the worksheet itself. When completed, answer the following questions: 1. How would you interpret the "r" value (correlation coefficient)?

Case Study Regression

Loans Processed Loans per hour (average) (mins)
111 6.1
114 6.2
111 5.9
118 6.7
115 6.4
112 5.7
117 6.9
116 7
103 5.8
102 5.8
107 5.2
101 5.7
116 6.6
114 6.4
110 6
109 6
100 5.1
103 5.2
103 4.9
105 5.8
115 6.5
116 6.8
104 5.7
119 6.9
106 5.4
119 7
101 5.3
107 5.8
102 5.1
113 6.1
104 5.4
115 6.5
110 6
112 6
108 5.9
115 6.1
118 6.5
102 5.2
118 6.7
114 6.6
118 6.7
108 5.9
114 6.5
115 6.3
104 5.7
111 6.9
110 5.7
115 6.8
101 5.2
111 5.9
117 6.6
108 5.6
118 6.4
118 6.6
106 5.3
112 6
105 5.5
106 5.6
109 5.6
101 5.4
114 6.4
111 6.1
101 6.5
101 5.9
108 5.5
111 6.3
104 6
110 6.5
115 6.8
111 6.2
119 7
115 6.9
108 5.9
113 6.1
116 6.9
113 5.9
110 5.4
103 4.8
116 6.4
101 5.8
The data set is the Loans Processed. We want to see if there is a correlation between the loans processed per hour and the total loans processed per day. Follow these instructions to perform regression: 1. Click "Engine Room" from the toolbar above. 2. Select Analyze from the menu. 3. Select Simple Regression from the menu. 4. Select Case Study Regression from the menu in "Select Worksheet". 5. Click "OK" 6. Select Loans Processed from the menu in the "Dependent Variable". 7.Select Loans per hour from the menu in 'Independent Variable". 8. Click "OK" 9. Engine Room will generate a new worksheet entitled "Regression". When completed, answer the following questions: 1. How would you interpret the graph 2. What conclusions can you draw from p-value and the R-squared value?

Case Study Regression Results

SUMMARY OUTPUT 8.27 60.09
100 5.1
Regression Statistics 101 5.7
Multiple R 0.8193026767 101 5.3
R Square 0.671256876 101 5.2
Adjusted R Square 0.6670422206 101 5.4
Standard Error 3.2887153692 101 6.5
Observations 80 101 5.9
101 5.8
ANOVA 102 5.8
df SS MS F Significance F 102 5.1
Regression 1 1722.5793951901 1722.5793951901 159.26732 1.56980839556793E-20 102 5.2
Residual 78 843.6206048099 10.8156487796 103 5.8
Total 79 2566.2 103 5.2
103 4.9
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% 103 4.8
Intercept 60.0865544884 3.983959925 15.0821181987 7.84476407641124E-25 52.1550977424 68.0180112345 104 5.7
X Variable 1 8.2681165172 0.6551537816 12.6201156889 1.56980839556406E-20 6.9638052344 9.5724278 104 5.4
104 5.7
104 6
Formula: y = 8.27x + 60.09 105 5.8
RESIDUAL OUTPUT 105 5.5
106 5.4
Observation Predicted Y Residuals 106 5.3
1 102.2539487261 -2.2539487261 106 5.6
2 107.2148186364 -6.2148186364 107 5.2
3 103.9075720295 -2.9075720295 107 5.8
4 103.0807603778 -2.0807603778 108 5.9
5 104.7343836812 -3.7343836812 108 5.9
6 113.8293118501 -12.8293118501 108 5.6
7 108.8684419398 -7.8684419398 108 5.5
8 108.0416302881 -7.0416302881 108 5.9
9 108.0416302881 -6.0416302881 109 6
10 102.2539487261 -0.2539487261 109 5.6
11 103.0807603778 -1.0807603778 110 6
12 108.0416302881 -5.0416302881 110 6
13 103.0807603778 -0.0807603778 110 5.7
14 100.6003254227 2.3996745773 110 6.5
15 99.7735137709 3.2264862291 110 5.4
16 107.2148186364 -3.2148186364 111 6.1
17 104.7343836812 -0.7343836812 111 5.9
18 107.2148186364 -3.2148186364 111 6.9
19 109.6952535916 -5.6952535916 111 5.9
20 108.0416302881 -3.0416302881 111 6.1
21 105.561195333 -0.561195333 111 6.3
22 104.7343836812 1.2656163188 111 6.2
23 103.9075720295 2.0924279705 112 5.7
24 106.3880069847 -0.3880069847 112 6
25 103.0807603778 3.9192396222 112 6
26 108.0416302881 -1.0416302881 113 6.1
27 108.8684419398 -0.8684419398 113 6.1
28 108.8684419398 -0.8684419398 113 5.9
29 106.3880069847 1.6119930153 114 6.2
30 105.561195333 2.438804667 114 6.4
31 108.8684419398 -0.8684419398 114 6.6
32 109.6952535916 -0.6952535916 114 6.5
33 106.3880069847 2.6119930153 114 6.4
34 109.6952535916 0.3047464084 115 6.4
35 109.6952535916 0.3047464084 115 6.5
36 107.2148186364 2.7851813636 115 6.5
37 113.8293118501 -3.8293118501 115 6.1
38 104.7343836812 5.2656163188 115 6.3
39 110.5220652433 0.4779347567 115 6.8
40 108.8684419398 2.1315580602 115 6.8
41 117.136558457 -6.136558457 115 6.9
42 108.8684419398 2.1315580602 116 7
43 110.5220652433 0.4779347567 116 6.6
44 112.1756885467 -1.1756885467 116 6.8
45 111.348876895 -0.348876895 116 6.9
46 107.2148186364 4.7851813636 116 6.4
47 109.6952535916 2.3047464084 117 6.9
48 109.6952535916 2.3047464084 117 6.6
49 110.5220652433 2.4779347567 118 6.7
50 110.5220652433 2.4779347567 118 6.5
51 108.8684419398 4.1315580602 118 6.7
52 111.348876895 2.651123105 118 6.7
53 113.0025001984 0.9974998016 118 6.4
54 114.6561235019 -0.6561235019 118 6.6
55 113.8293118501 0.1706881499 119 6.9
56 113.0025001984 0.9974998016 119 7
57 113.0025001984 1.9974998016 119 7
58 113.8293118501 1.1706881499
59 113.8293118501 1.1706881499
60 110.5220652433 4.4779347567
61 112.1756885467 2.8243114533
62 116.3097468053 -1.3097468053
63 116.3097468053 -1.3097468053
64 117.136558457 -2.136558457
65 117.9633701087 -1.9633701087
66 114.6561235019 1.3438764981
67 116.3097468053 -0.3097468053
68 117.136558457 -1.136558457
69 113.0025001984 2.9974998016
70 117.136558457 -0.136558457
71 114.6561235019 2.3438764981
72 115.4829351536 2.5170648464
73 113.8293118501 4.1706881499
74 115.4829351536 2.5170648464
75 115.4829351536 2.5170648464
76 113.0025001984 4.9974998016
77 114.6561235019 3.3438764981
78 117.136558457 1.863441543
79 117.9633701087 1.0366298913
80 117.9633701087 1.0366298913

Case Study Regression Results

Y
Predicted Y
Loans per hour (average) (mins)
Loans Processed
Loans per hour (average) (mins) Line Fit Plot

X and Moving Range

Date Chicago Loan Processing Cycle Time Average - X 30
1-Jan 39 Median - Range 5
2-Jan 25 LCL - X 14
3-Jan 26 UCL - X 45
4-Jan 45 UCL - Range 19
5-Jan 30
6-Jan 27
7-Jan 22
8-Jan 25
9-Jan 32
10-Jan 32
11-Jan 30
12-Jan 33
13-Jan 26
14-Jan 21
15-Jan 34
16-Jan 34
17-Jan 32
18-Jan 33
19-Jan 27
20-Jan 21
21-Jan 35
22-Jan 37
23-Jan 24
24-Jan 27
25-Jan 27
26-Jan 29
27-Jan 20
28-Jan 32
29-Jan 14
30-Jan 37
31-Jan 32
1-Feb 39
2-Feb 34
3-Feb 36
4-Feb 25
5-Feb 31
6-Feb 31
7-Feb 24
8-Feb 28
9-Feb 41
10-Feb 24
11-Feb 33
12-Feb 34
13-Feb 30
14-Feb 30
15-Feb 21
16-Feb 37
17-Feb 32
18-Feb 27
19-Feb 34
20-Feb 36
21-Feb 23
22-Feb 25
23-Feb 29
24-Feb 32
25-Feb 26
26-Feb 31
27-Feb 38
28-Feb 22
29-Feb 29
1-Mar 37
2-Mar 35
3-Mar 30
4-Mar 34
5-Mar 30
6-Mar 21
7-Mar 37
8-Mar 24
9-Mar 32
10-Mar 19
11-Mar 24
12-Mar 23
13-Mar 27
14-Mar 19
15-Mar 30
16-Mar 27
17-Mar 32
18-Mar 31
19-Mar 29
20-Mar 28
21-Mar 31
22-Mar 36
23-Mar 15
24-Mar 30
25-Mar 33
26-Mar 31
27-Mar 30
28-Mar 34
29-Mar 28
30-Mar 32
31-Mar 29
67% of the variation in total loans processed is explained by loans processed per hour. ** Since this is transactional data, this is considered a high r-squared value.
High R-Square value
The E-20 means there are 20 zeros before the 1.56981…so this number is effectively zero. Since this is less than 0.05 we reject the null hypothesis that m= 0. In practical terms, this indicates a strong correlation between loans per hour and total loans processed per day.
Low P-value so Strong Correlation indicated.

X and Moving Range

39 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
45 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
22 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
35 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
20 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
14 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
39 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
41 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
23 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
38 29.5384615385 45.2634615385 13.8134615385
22 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
35 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
19 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
23 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
19 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
15 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
Data1
Average
UCL
LCL
Date
Chicago Loan Processing Cycle Time
X Chart

XMRData-4

37987 5 19.325
14 5 19.325
1 5 19.325
19 5 19.325
15 5 19.325
3 5 19.325
5 5 19.325
3 5 19.325
7 5 19.325
0 5 19.325
2 5 19.325
3 5 19.325
7 5 19.325
5 5 19.325
13 5 19.325
0 5 19.325
2 5 19.325
1 5 19.325
6 5 19.325
6 5 19.325
14 5 19.325
2 5 19.325
13 5 19.325
3 5 19.325
0 5 19.325
2 5 19.325
9 5 19.325
12 5 19.325
18 5 19.325
23 5 19.325
5 5 19.325
7 5 19.325
5 5 19.325
2 5 19.325
11 5 19.325
6 5 19.325
0 5 19.325
7 5 19.325
4 5 19.325
13 5 19.325
17 5 19.325
9 5 19.325
1 5 19.325
4 5 19.325
0 5 19.325
9 5 19.325
16 5 19.325
5 5 19.325
5 5 19.325
7 5 19.325
2 5 19.325
13 5 19.325
2 5 19.325
4 5 19.325
3 5 19.325
6 5 19.325
5 5 19.325
7 5 19.325
16 5 19.325
7 5 19.325
8 5 19.325
2 5 19.325
5 5 19.325
4 5 19.325
4 5 19.325
9 5 19.325
16 5 19.325
13 5 19.325
8 5 19.325
13 5 19.325
5 5 19.325
1 5 19.325
4 5 19.325
8 5 19.325
11 5 19.325
3 5 19.325
5 5 19.325
1 5 19.325
2 5 19.325
1 5 19.325
3 5 19.325
5 5 19.325
21 5 19.325
15 5 19.325
3 5 19.325
2 5 19.325
1 5 19.325
4 5 19.325
6 5 19.325
4 5 19.325
3 5 19.325
Range
Average
UCL(R)
Date
Range
Range Chart

XMRData-3

Date Chicago Loan Processing Cycle Time Average Range R-Median UCL - Range LCL - X UCL - X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385

XMRData-2

Date Chicago Loan Processing Cycle Time Average Range R-Median UCL - Range LCL - X UCL - X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385

XMRData-1

Date Chicago Loan Processing Cycle Time Average Range R-Mean UCL - Range LCL - X UCL - X
1-Jan 39 29.5384615385 6.6222222222 21.6414222222 11.9233504274 47.1535726496
2-Jan 25 29.5384615385 14 6.6222222222 21.6414222222 11.9233504274 47.1535726496
3-Jan 26 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
4-Jan 45 29.5384615385 19 6.6222222222 21.6414222222 11.9233504274 47.1535726496
5-Jan 30 29.5384615385 15 6.6222222222 21.6414222222 11.9233504274 47.1535726496
6-Jan 27 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
7-Jan 22 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
8-Jan 25 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
9-Jan 32 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
10-Jan 32 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
11-Jan 30 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
12-Jan 33 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
13-Jan 26 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
14-Jan 21 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
15-Jan 34 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
16-Jan 34 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
17-Jan 32 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
18-Jan 33 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
19-Jan 27 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
20-Jan 21 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
21-Jan 35 29.5384615385 14 6.6222222222 21.6414222222 11.9233504274 47.1535726496
22-Jan 37 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
23-Jan 24 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
24-Jan 27 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
25-Jan 27 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
26-Jan 29 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
27-Jan 20 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
28-Jan 32 29.5384615385 12 6.6222222222 21.6414222222 11.9233504274 47.1535726496
29-Jan 14 29.5384615385 18 6.6222222222 21.6414222222 11.9233504274 47.1535726496
30-Jan 37 29.5384615385 23 6.6222222222 21.6414222222 11.9233504274 47.1535726496
31-Jan 32 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
1-Feb 39 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
2-Feb 34 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
3-Feb 36 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
4-Feb 25 29.5384615385 11 6.6222222222 21.6414222222 11.9233504274 47.1535726496
5-Feb 31 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
6-Feb 31 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
7-Feb 24 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
8-Feb 28 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
9-Feb 41 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
10-Feb 24 29.5384615385 17 6.6222222222 21.6414222222 11.9233504274 47.1535726496
11-Feb 33 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
12-Feb 34 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
13-Feb 30 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
14-Feb 30 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
15-Feb 21 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
16-Feb 37 29.5384615385 16 6.6222222222 21.6414222222 11.9233504274 47.1535726496
17-Feb 32 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
18-Feb 27 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
19-Feb 34 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
20-Feb 36 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
21-Feb 23 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
22-Feb 25 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
23-Feb 29 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
24-Feb 32 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
25-Feb 26 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
26-Feb 31 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
27-Feb 38 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
28-Feb 22 29.5384615385 16 6.6222222222 21.6414222222 11.9233504274 47.1535726496
29-Feb 29 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
1-Mar 37 29.5384615385 8 6.6222222222 21.6414222222 11.9233504274 47.1535726496
2-Mar 35 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
3-Mar 30 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
4-Mar 34 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
5-Mar 30 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
6-Mar 21 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
7-Mar 37 29.5384615385 16 6.6222222222 21.6414222222 11.9233504274 47.1535726496
8-Mar 24 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
9-Mar 32 29.5384615385 8 6.6222222222 21.6414222222 11.9233504274 47.1535726496
10-Mar 19 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
11-Mar 24 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
12-Mar 23 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
13-Mar 27 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
14-Mar 19 29.5384615385 8 6.6222222222 21.6414222222 11.9233504274 47.1535726496
15-Mar 30 29.5384615385 11 6.6222222222 21.6414222222 11.9233504274 47.1535726496
16-Mar 27 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
17-Mar 32 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
18-Mar 31 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
19-Mar 29 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
20-Mar 28 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
21-Mar 31 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
22-Mar 36 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
23-Mar 15 29.5384615385 21 6.6222222222 21.6414222222 11.9233504274 47.1535726496
24-Mar 30 29.5384615385 15 6.6222222222 21.6414222222 11.9233504274 47.1535726496
25-Mar 33 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
26-Mar 31 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
27-Mar 30 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
28-Mar 34 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
29-Mar 28 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
30-Mar 32 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
31-Mar 29 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496

XMRData

Date Chicago Loan Processing Cycle Time Average Range R-Median UCL - Range LCL - X UCL - X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385

XBSData

Date Chicago Loan Processing Cycle Time Average Range R-Median UCL - Range LCL - X UCL - X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385

HistData

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 Average StdDev X Bar Bar S Bar LCL - S UCL - S LCL - X UCL - X
1 37987 37988 37989 37990 37991 37992 37993 37994 37995 37996 37997 37998 37999 38000 38001 38002 38003 38004 38005 38006 38007 38008 38009 38010 38011 38012 38013 38014 38015 38016 38017 38018 38019 38020 38021 38022 38023 38024 38025 38026 38027 38028 38029 38030 38031 38032 38033 38034 38035 38036 38037 38038 38039 38040 38041 38042 38043 38044 38045 38046 38047 38048 38049 38050 38051 38052 38053 38054 38055 38056 38057 38058 38059 38060 38061 38062 38063 38064 38065 38066 38067 38068 38069 38070 38071 38072 38073 38074 38075 38076 38077 38032 26.4133804475 19030.7692307692 16.0598635958 -127.8720872474 159.9918144389 19014.8581890309 19046.6802725076
2 39 25 26 45 30 27 22 25 32 32 30 33 26 21 34 34 32 33 27 21 35 37 24 27 27 29 20 32 14 37 32 39 34 36 25 31 31 24 28 41 24 33 34 30 30 21 37 32 27 34 36 23 25 29 32 26 31 38 22 29 37 35 30 34 30 21 37 24 32 19 24 23 27 19 30 27 32 31 29 28 31 36 15 30 33 31 30 34 28 32 29 29.5384615385 5.706346744 19030.7692307692 16.0598635958 -127.8720872474 159.9918144389 19014.8581890309 19046.6802725076

HistData-1

Observation Max 46 Bin Frequency Cum Count Bins
1 45 Min 12 12 1 0.1% 1423 10
2 20 Interval 3.7777777778 15.7777777778 4 0.0035137034
3 24 19.5555555556 28 0.0231904427
4 31 23.3333333333 124 0.1103302881
5 24 27.1111111111 303 0.3232607168
6 29 30.8888888889 283 0.5221363317
7 28 34.6666666667 392 0.7976106817
8 34 38.4444444444 213 0.9472944483
9 33 42.2222222222 57 0.9873506676
10 25 46 18 1
11 25 0 0 0
12 25 0 0 0
13 24 0 0 0
14 30 0 0 0
15 30 0 0 0
16 32 0 0 0
17 31 0 0 0
18 27 0 0 0
19 21 0 0 0
20 36 0 0 0
21 28 0 0 0
22 35 0 0 0
23 35 0 0 0
24 26 0 0 0
25 42 0 0 0
26 35 0 0 0
27 29 0 0 0
28 22 0 0 0
29 29 0 0 0
30 26 0 0 0
31 32
32 27
33 28
34 28
35 26
36 30
37 32
38 36
39 28
40 39
41 22
42 30
43 32
44 24
45 31
46 31
47 45
48 36
49 25
50 37
51 21
52 31
53 28
54 22
55 43
56 33
57 32
58 38
59 26
60 28
61 26
62 26
63 27
64 40
65 24
66 29
67 27
68 37
69 20
70 37
71 31
72 30
73 39
74 34
75 33
76 43
77 31
78 36
79 29
80 30
81 37
82 31
83 25
84 33
85 33
86 25
87 25
88 29
89 37
90 28
91 38
92 39
93 21
94 28
95 36
96 30
97 32
98 35
99 21
100 18
101 29
102 26
103 27
104 30
105 32
106 35
107 25
108 25
109 28
110 24
111 33
112 28
113 30
114 26
115 36
116 33
117 27
118 28
119 24
120 27
121 40
122 25
123 29
124 33
125 32
126 24
127 22
128 26
129 37
130 28
131 29
132 35
133 26
134 33
135 23
136 27
137 34
138 29
139 25
140 36
141 35
142 31
143 32
144 36
145 32
146 29
147 39
148 32
149 33
150 30
151 20
152 36
153 31
154 34
155 33
156 32
157 24
158 24
159 26
160 37
161 33
162 27
163 22
164 30
165 27
166 37
167 26
168 34
169 30
170 32
171 36
172 30
173 33
174 35
175 24
176 31
177 27
178 27
179 26
180 32
181 35
182 25
183 30
184 14
185 36
186 34
187 30
188 28
189 35
190 31
191 32
192 28
193 24
194 40
195 31
196 24
197 30
198 33
199 28
200 21
201 31
202 38
203 34
204 26
205 27
206 34
207 28
208 18
209 26
210 28
211 34
212 28
213 34
214 24
215 32
216 34
217 30
218 33
219 37
220 36
221 30
222 33
223 32
224 35
225 33
226 30
227 31
228 22
229 29
230 33
231 26
232 23
233 32
234 28
235 29
236 28
237 32
238 41
239 35
240 29
241 34
242 26
243 28
244 35
245 32
246 17
247 33
248 35
249 37
250 25
251 33
252 33
253 26
254 36
255 35
256 27
257 26
258 30
259 25
260 28
261 32
262 36
263 33
264 31
265 34
266 24
267 28
268 29
269 38
270 32
271 29
272 31
273 25
274 30
275 37
276 34
277 25
278 19
279 29
280 32
281 22
282 36
283 31
284 24
285 37
286 36
287 31
288 27
289 26
290 21
291 41
292 31
293 24
294 30
295 24
296 19
297 37
298 41
299 21
300 21
301 32
302 19
303 20
304 27
305 34
306 37
307 36
308 45
309 31
310 33
311 30
312 29
313 36
314 18
315 23
316 37
317 36
318 36
319 30
320 29
321 33
322 39
323 27
324 27
325 28
326 29
327 35
328 24
329 26
330 32
331 31
332 31
333 26
334 18
335 29
336 37
337 28
338 22
339 38
340 26
341 31
342 31
343 41
344 27
345 35
346 27
347 38
348 32
349 33
350 30
351 34
352 32
353 38
354 27
355 29
356 31
357 14
358 33
359 30
360 31
361 35
362 27
363 31
364 34
365 33
366 27
367 37
368 37
369 21
370 22
371 32
372 20
373 38
374 28
375 31
376 22
377 29
378 33
379 36
380 26
381 17
382 25
383 29
384 41
385 39
386 38
387 36
388 33
389 22
390 32
391 34
392 25
393 29
394 23
395 30
396 26
397 30
398 29
399 32
400 27
401 26
402 35
403 34
404 30
405 29
406 41
407 26
408 37
409 25
410 33
411 43
412 29
413 37
414 42
415 29
416 28
417 30
418 39
419 34
420 28
421 24
422 34
423 29
424 35
425 27
426 42
427 37
428 42
429 31
430 29
431 37
432 30
433 30
434 18
435 22
436 24
437 40
438 35
439 32
440 38
441 32
442 36
443 34
444 19
445 32
446 31
447 30
448 29
449 36
450 33
451 36
452 36
453 25
454 33
455 24
456 32
457 27
458 34
459 27
460 28
461 27
462 40
463 26
464 30
465 26
466 31
467 28
468 24
469 35
470 31
471 25
472 29
473 38
474 31
475 23
476 30
477 40
478 33
479 30
480 27
481 30
482 31
483 30
484 30
485 30
486 25
487 36
488 32
489 32
490 26
491 34
492 31
493 28
494 31
495 26
496 33
497 37
498 35
499 28
500 16
501 31
502 32
503 26
504 28
505 25
506 34
507 30
508 32
509 35
510 31
511 33
512 22
513 31
514 38
515 29
516 33
517 26
518 43
519 36
520 29
521 33
522 27
523 31
524 16
525 38
526 36
527 27
528 25
529 34
530 31
531 28
532 31
533 21
534 27
535 35
536 33
537 21
538 36
539 37
540 37
541 43
542 29
543 36
544 34
545 33
546 26
547 26
548 29
549 31
550 32
551 24
552 33
553 24
554 36
555 31
556 38
557 30
558 19
559 34
560 38
561 38
562 24
563 39
564 27
565 30
566 35
567 30
568 31
569 32
570 23
571 27
572 32
573 30
574 34
575 27
576 20
577 37
578 31
579 35
580 35
581 32
582 29
583 34
584 36
585 23
586 26
587 33
588 31
589 20
590 22
591 37
592 25
593 25
594 26
595 38
596 37
597 24
598 26
599 32
600 25
601 25
602 30
603 28
604 32
605 29
606 18
607 30
608 21
609 32
610 32
611 32
612 37
613 37
614 32
615 23
616 26
617 41
618 33
619 26
620 29
621 30
622 24
623 22
624 30
625 40
626 24
627 35
628 23
629 28
630 34
631 29
632 27
633 27
634 30
635 23
636 29
637 33
638 26
639 37
640 30
641 34
642 29
643 31
644 25
645 24
646 28
647 36
648 29
649 28
650 31
651 20
652 31
653 32
654 32
655 25
656 30
657 34
658 30
659 34
660 21
661 27
662 32
663 30
664 26
665 29
666 32
667 24
668 27
669 25
670 32
671 30
672 35
673 27
674 41
675 22
676 35
677 26
678 27
679 21
680 33
681 33
682 20
683 29
684 28
685 31
686 32
687 24
688 21
689 37
690 36
691 30
692 30
693 35
694 38
695 33
696 40
697 30
698 35
699 20
700 29
701 35
702 35
703 35
704 26
705 32
706 29
707 28
708 18
709 26
710 21
711 30
712 33
713 32
714 29
715 31
716 26
717 36
718 37
719 40
720 35
721 28
722 29
723 32
724 30
725 27
726 27
727 29
728 24
729 34
730 32
731 24
732 22
733 32
734 30
735 25
736 31
737 33
738 39
739 30
740 44
741 23
742 31
743 23
744 32
745 28
746 40
747 12
748 30
749 25
750 27
751 28
752 29
753 27
754 25
755 30
756 37
757 23
758 29
759 30
760 30
761 37
762 30
763 28
764 32
765 25
766 35
767 33
768 31
769 34
770 31
771 23
772 32
773 29
774 31
775 28
776 23
777 25
778 31
779 28
780 27
781 24
782 38
783 38
784 29
785 41
786 37
787 38
788 20
789 33
790 24
791 27
792 29
793 25
794 31
795 23
796 27
797 30
798 34
799 30
800 44
801 24
802 35
803 33
804 29
805 32
806 29
807 35
808 33
809 34
810 29
811 40
812 24
813 40
814 30
815 25
816 29
817 27
818 24
819 33
820 27
821 24
822 31
823 29
824 31
825 34
826 35
827 24
828 30
829 26
830 33
831 36
832 28
833 27
834 30
835 36
836 25
837 37
838 39
839 39
840 32
841 40
842 21
843 24
844 24
845 30
846 36
847 29
848 36
849 29
850 26
851 32
852 34
853 37
854 30
855 27
856 31
857 26
858 31
859 28
860 31
861 40
862 32
863 26
864 31
865 29
866 33
867 31
868 33
869 25
870 28
871 28
872 29
873 30
874 31
875 25
876 26
877 36
878 22
879 29
880 39
881 45
882 29
883 38
884 26
885 27
886 33
887 30
888 29
889 23
890 31
891 37
892 27
893 26
894 40
895 28
896 40
897 24
898 34
899 31
900 29
901 21
902 21
903 29
904 29
905 33
906 34
907 35
908 20
909 34
910 27
911 25
912 27
913 32
914 26
915 19
916 15
917 32
918 26
919 25
920 25
921 26
922 30
923 31
924 32
925 23
926 27
927 23
928 23
929 33
930 33
931 33
932 32
933 28
934 19
935 40
936 30
937 31
938 25
939 31
940 33
941 43
942 36
943 34
944 29
945 34
946 27
947 30
948 29
949 31
950 31
951 16
952 26
953 27
954 31
955 18
956 23
957 27
958 35
959 27
960 33
961 32
962 36
963 29
964 32
965 31
966 27
967 44
968 27
969 31
970 37
971 35
972 25
973 33
974 29
975 34
976 32
977 32
978 27
979 29
980 23
981 30
982 20
983 28
984 34
985 31
986 33
987 28
988 35
989 31
990 36
991 24
992 35
993 24
994 34
995 33
996 34
997 25
998 32
999 27
1000 21
1001 34
1002 32
1003 35
1004 21
1005 23
1006 32
1007 30
1008 35
1009 24
1010 21
1011 32
1012 38
1013 32
1014 32
1015 36
1016 39
1017 25
1018 29
1019 28
1020 23
1021 35
1022 32
1023 21
1024 27
1025 28
1026 23
1027 37
1028 30
1029 29
1030 24
1031 32
1032 24
1033 28
1034 34
1035 23
1036 35
1037 22
1038 24
1039 33
1040 28
1041 17
1042 36
1043 26
1044 38
1045 26
1046 33
1047 29
1048 25
1049 33
1050 34
1051 28
1052 29
1053 33
1054 23
1055 32
1056 35
1057 25
1058 29
1059 25
1060 31
1061 26
1062 35
1063 35
1064 27
1065 34
1066 29
1067 31
1068 36
1069 34
1070 37
1071 37
1072 25
1073 32
1074 24
1075 35
1076 32
1077 25
1078 33
1079 34
1080 32
1081 28
1082 37
1083 24
1084 36
1085 31
1086 30
1087 37
1088 22
1089 20
1090 19
1091 29
1092 32
1093 22
1094 32
1095 41
1096 35
1097 37
1098 31
1099 32
1100 36
1101 36
1102 23
1103 37
1104 34
1105 31
1106 44
1107 30
1108 30
1109 32
1110 28
1111 20
1112 35
1113 24
1114 28
1115 33
1116 27
1117 26
1118 36
1119 32
1120 35
1121 28
1122 36
1123 31
1124 26
1125 27
1126 32
1127 31
1128 29
1129 34
1130 37
1131 24
1132 29
1133 37
1134 20
1135 33
1136 33
1137 22
1138 24
1139 22
1140 31
1141 25
1142 30
1143 22
1144 34
1145 37
1146 20
1147 23
1148 39
1149 19
1150 20
1151 25
1152 21
1153 27
1154 33
1155 31
1156 21
1157 34
1158 25
1159 35
1160 24
1161 23
1162 28
1163 31
1164 27
1165 29
1166 29
1167 25
1168 28
1169 29
1170 24
1171 19
1172 29
1173 42
1174 32
1175 35
1176 33
1177 32
1178 30
1179 18
1180 31
1181 20
1182 36
1183 21
1184 25
1185 39
1186 25
1187 30
1188 27
1189 29
1190 35
1191 34
1192 29
1193 32
1194 32
1195 43
1196 29
1197 40
1198 32
1199 25
1200 27
1201 33
1202 26
1203 27
1204 26
1205 24
1206 31
1207 27
1208 20
1209 27
1210 33
1211 25
1212 31
1213 30
1214 32
1215 36
1216 27
1217 32
1218 32
1219 32
1220 36
1221 39
1222 34
1223 24
1224 33
1225 30
1226 35
1227 34
1228 30
1229 32
1230 42
1231 24
1232 34
1233 34
1234 26
1235 28
1236 35
1237 30
1238 31
1239 38
1240 22
1241 32
1242 32
1243 22
1244 23
1245 35
1246 35
1247 31
1248 33
1249 36
1250 37
1251 24
1252 23
1253 33
1254 21
1255 34
1256 32
1257 28
1258 31
1259 29
1260 34
1261 17
1262 34
1263 22
1264 21
1265 34
1266 23
1267 41
1268 31
1269 31
1270 28
1271 26
1272 34
1273 20
1274 24
1275 21
1276 32
1277 30
1278 29
1279 27
1280 36
1281 25
1282 33
1283 23
1284 34
1285 33
1286 28
1287 17
1288 27
1289 29
1290 29
1291 32
1292 43
1293 30
1294 25
1295 29
1296 27
1297 28
1298 31
1299 31
1300 40
1301 28
1302 26
1303 33
1304 33
1305 33
1306 22
1307 40
1308 36
1309 27
1310 30
1311 40
1312 22
1313 26
1314 26
1315 29
1316 36
1317 22
1318 38
1319 24
1320 36
1321 29
1322 29
1323 35
1324 33
1325 31
1326 26
1327 27
1328 25
1329 26
1330 30
1331 32
1332 34
1333 32
1334 29
1335 42
1336 33
1337 25
1338 27
1339 26
1340 26
1341 15
1342 46
1343 20
1344 40
1345 26
1346 33
1347 22
1348 28
1349 25
1350 34
1351 34
1352 31
1353 25
1354 37
1355 23
1356 38
1357 23
1358 31
1359 32
1360 38
1361 28
1362 35
1363 24
1364 25
1365 29
1366 34
1367 33
1368 33
1369 38
1370 23
1371 30
1372 28
1373 33
1374 21
1375 35
1376 33
1377 35
1378 25
1379 31
1380 28
1381 24
1382 35
1383 30
1384 26
1385 30
1386 30
1387 30
1388 33
1389 24
1390 39
1391 31
1392 27
1393 22
1394 30
1395 23
1396 25
1397 28
1398 32
1399 25
1400 31
1401 34
1402 37
1403 21
1404 31
1405 36
1406 34
1407 25
1408 33
1409 34
1410 26
1411 35
1412 27
1413 24
1414 25
1415 26
1416 28
1417 31
1418 29
1419 33
1420 43
1421 18
1422 27
1423 23
Observation Max 46 Bin Frequency Cum Count Bins
1 45 Min 12 12 1 0.1% 1423 10
2 20 Interval 3.7777777778 15.7777777778 4 0.0035137034
3 24 19.5555555556 28 0.0231904427
4 31 23.3333333333 124 0.1103302881
5 24 27.1111111111 303 0.3232607168
6 29 30.8888888889 283 0.5221363317
7 28 34.6666666667 392 0.7976106817
8 34 38.4444444444 213 0.9472944483
9 33 42.2222222222 57 0.9873506676
10 25 46 18 1
11 25 0 0 0
12 25 0 0 0
13 24 0 0 0
14 30 0 0 0
15 30 0 0 0
16 32 0 0 0
17 31 0 0 0
18 27 0 0 0
19 21 0 0 0
20 36 0 0 0
21 28 0 0 0
22 35 0 0 0
23 35 0 0 0
24 26 0 0 0
25 42 0 0 0
26 35 0 0 0
27 29 0 0 0
28 22 0 0 0
29 29 0 0 0
30 26 0 0 0
31 32
32 27
33 28
34 28
35 26
36 30
37 32
38 36
39 28
40 39
41 22
42 30
43 32
44 24
45 31
46 31
47 45
48 36
49 25
50 37
51 21
52 31
53 28
54 22
55 43
56 33
57 32
58 38
59 26
60 28
61 26
62 26
63 27
64 40
65 24
66 29
67 27
68 37
69 20
70 37
71 31
72 30
73 39
74 34
75 33
76 43
77 31
78 36
79 29
80 30
81 37
82 31
83 25
84 33
85 33
86 25
87 25
88 29
89 37
90 28
91 38
92 39
93 21
94 28
95 36
96 30
97 32
98 35
99 21
100 18
101 29
102 26
103 27
104 30
105 32
106 35
107 25
108 25
109 28
110 24
111 33
112 28
113 30
114 26
115 36
116 33
117 27
118 28
119 24
120 27
121 40
122 25
123 29
124 33
125 32
126 24
127 22
128 26
129 37
130 28
131 29
132 35
133 26
134 33
135 23
136 27
137 34
138 29
139 25
140 36
141 35
142 31
143 32
144 36
145 32
146 29
147 39
148 32
149 33
150 30
151 20
152 36
153 31
154 34
155 33
156 32
157 24
158 24
159 26
160 37
161 33
162 27
163 22
164 30
165 27
166 37
167 26
168 34
169 30
170 32
171 36
172 30
173 33
174 35
175 24
176 31
177 27
178 27
179 26
180 32
181 35
182 25
183 30
184 14
185 36
186 34
187 30
188 28
189 35
190 31
191 32
192 28
193 24
194 40
195 31
196 24
197 30
198 33
199 28
200 21
201 31
202 38
203 34
204 26
205 27
206 34
207 28
208 18
209 26
210 28
211 34
212 28
213 34
214 24
215 32
216 34
217 30
218 33
219 37
220 36
221 30
222 33
223 32
224 35
225 33
226 30
227 31
228 22
229 29
230 33
231 26
232 23
233 32
234 28
235 29
236 28
237 32
238 41
239 35
240 29
241 34
242 26
243 28
244 35
245 32
246 17
247 33
248 35
249 37
250 25
251 33
252 33
253 26
254 36
255 35
256 27
257 26
258 30
259 25
260 28
261 32
262 36
263 33
264 31
265 34
266 24
267 28
268 29
269 38
270 32
271 29
272 31
273 25
274 30
275 37
276 34
277 25
278 19
279 29
280 32
281 22
282 36
283 31
284 24
285 37
286 36
287 31
288 27
289 26
290 21
291 41
292 31
293 24
294 30
295 24
296 19
297 37
298 41
299 21
300 21
301 32
302 19
303 20
304 27
305 34
306 37
307 36
308 45
309 31
310 33
311 30
312 29
313 36
314 18
315 23
316 37
317 36
318 36
319 30
320 29
321 33
322 39
323 27
324 27
325 28
326 29
327 35
328 24
329 26
330 32
331 31
332 31
333 26
334 18
335 29
336 37
337 28
338 22
339 38
340 26
341 31
342 31
343 41
344 27
345 35
346 27
347 38
348 32
349 33
350 30
351 34
352 32
353 38
354 27
355 29
356 31
357 14
358 33
359 30
360 31
361 35
362 27
363 31
364 34
365 33
366 27
367 37
368 37
369 21
370 22
371 32
372 20
373 38
374 28
375 31
376 22
377 29
378 33
379 36
380 26
381 17
382 25
383 29
384 41
385 39
386 38
387 36
388 33
389 22
390 32
391 34
392 25
393 29
394 23
395 30
396 26
397 30
398 29
399 32
400 27
401 26
402 35
403 34
404 30
405 29
406 41
407 26
408 37
409 25
410 33
411 43
412 29
413 37
414 42
415 29
416 28
417 30
418 39
419 34
420 28
421 24
422 34
423 29
424 35
425 27
426 42
427 37
428 42
429 31
430 29
431 37
432 30
433 30
434 18
435 22
436 24
437 40
438 35
439 32
440 38
441 32
442 36
443 34
444 19
445 32
446 31
447 30
448 29
449 36
450 33
451 36
452 36
453 25
454 33
455 24
456 32
457 27
458 34
459 27
460 28
461 27
462 40
463 26
464 30
465 26
466 31
467 28
468 24
469 35
470 31
471 25
472 29
473 38
474 31
475 23
476 30
477 40
478 33
479 30
480 27
481 30
482 31
483 30
484 30
485 30
486 25
487 36
488 32
489 32
490 26
491 34
492 31
493 28
494 31
495 26
496 33
497 37
498 35
499 28
500 16
501 31
502 32
503 26
504 28
505 25
506 34
507 30
508 32
509 35
510 31
511 33
512 22
513 31
514 38
515 29
516 33
517 26
518 43
519 36
520 29
521 33
522 27
523 31
524 16
525 38
526 36
527 27
528 25
529 34
530 31
531 28
532 31
533 21
534 27
535 35
536 33
537 21
538 36
539 37
540 37
541 43
542 29
543 36
544 34
545 33
546 26
547 26
548 29
549 31
550 32
551 24
552 33
553 24
554 36
555 31
556 38
557 30
558 19
559 34
560 38
561 38
562 24
563 39
564 27
565 30
566 35
567 30
568 31
569 32
570 23
571 27
572 32
573 30
574 34
575 27
576 20
577 37
578 31
579 35
580 35
581 32
582 29
583 34
584 36
585 23
586 26
587 33
588 31
589 20
590 22
591 37
592 25
593 25
594 26
595 38
596 37
597 24
598 26
599 32
600 25
601 25
602 30
603 28
604 32
605 29
606 18
607 30
608 21
609 32
610 32
611 32
612 37
613 37
614 32
615 23
616 26
617 41
618 33
619 26
620 29
621 30
622 24
623 22
624 30
625 40
626 24
627 35
628 23
629 28
630 34
631 29
632 27
633 27
634 30
635 23
636 29
637 33
638 26
639 37
640 30
641 34
642 29
643 31
644 25
645 24
646 28
647 36
648 29
649 28
650 31
651 20
652 31
653 32
654 32
655 25
656 30
657 34
658 30
659 34
660 21
661 27
662 32
663 30
664 26
665 29
666 32
667 24
668 27
669 25
670 32
671 30
672 35
673 27
674 41
675 22
676 35
677 26
678 27
679 21
680 33
681 33
682 20
683 29
684 28
685 31
686 32
687 24
688 21
689 37
690 36
691 30
692 30
693 35
694 38
695 33
696 40
697 30
698 35
699 20
700 29
701 35
702 35
703 35
704 26
705 32
706 29
707 28
708 18
709 26
710 21
711 30
712 33
713 32
714 29
715 31
716 26
717 36
718 37
719 40
720 35
721 28
722 29
723 32
724 30
725 27
726 27
727 29
728 24
729 34
730 32
731 24
732 22
733 32
734 30
735 25
736 31
737 33
738 39
739 30
740 44
741 23
742 31
743 23
744 32
745 28
746 40
747 12
748 30
749 25
750 27
751 28
752 29
753 27
754 25
755 30
756 37
757 23
758 29
759 30
760 30
761 37
762 30
763 28
764 32
765 25
766 35
767 33
768 31
769 34
770 31
771 23
772 32
773 29
774 31
775 28
776 23
777 25
778 31
779 28
780 27
781 24
782 38
783 38
784 29
785 41
786 37
787 38
788 20
789 33
790 24
791 27
792 29
793 25
794 31
795 23
796 27
797 30
798 34
799 30
800 44
801 24
802 35
803 33
804 29
805 32
806 29
807 35
808 33
809 34
810 29
811 40
812 24
813 40
814 30
815 25
816 29
817 27
818 24
819 33
820 27
821 24
822 31
823 29
824 31
825 34
826 35
827 24
828 30
829 26
830 33
831 36
832 28
833 27
834 30
835 36
836 25
837 37
838 39
839 39
840 32
841 40
842 21
843 24
844 24
845 30
846 36
847 29
848 36
849 29
850 26
851 32
852 34
853 37
854 30
855 27
856 31
857 26
858 31
859 28
860 31
861 40
862 32
863 26
864 31
865 29
866 33
867 31
868 33
869 25
870 28
871 28
872 29
873 30
874 31
875 25
876 26
877 36
878 22
879 29
880 39
881 45
882 29
883 38
884 26
885 27
886 33
887 30
888 29
889 23
890 31
891 37
892 27
893 26
894 40
895 28
896 40
897 24
898 34
899 31
900 29
901 21
902 21
903 29
904 29
905 33
906 34
907 35
908 20
909 34
910 27
911 25
912 27
913 32
914 26
915 19
916 15
917 32
918 26
919 25
920 25
921 26
922 30
923 31
924 32
925 23
926 27
927 23
928 23
929 33
930 33
931 33
932 32
933 28
934 19
935 40
936 30
937 31
938 25
939 31
940 33
941 43
942 36
943 34
944 29
945 34
946 27
947 30
948 29
949 31
950 31
951 16
952 26
953 27
954 31
955 18
956 23
957 27
958 35
959 27
960 33
961 32
962 36
963 29
964 32
965 31
966 27
967 44
968 27
969 31
970 37
971 35
972 25
973 33
974 29
975 34
976 32
977 32
978 27
979 29
980 23
981 30
982 20
983 28
984 34
985 31
986 33
987 28
988 35
989 31
990 36
991 24
992 35
993 24
994 34
995 33
996 34
997 25
998 32
999 27
1000 21
1001 34
1002 32
1003 35
1004 21
1005 23
1006 32
1007 30
1008 35
1009 24
1010 21
1011 32
1012 38
1013 32
1014 32
1015 36
1016 39
1017 25
1018 29
1019 28
1020 23
1021 35
1022 32
1023 21
1024 27
1025 28
1026 23
1027 37
1028 30
1029 29
1030 24
1031 32
1032 24
1033 28
1034 34
1035 23
1036 35
1037 22
1038 24
1039 33
1040 28
1041 17
1042 36
1043 26
1044 38
1045 26
1046 33
1047 29
1048 25
1049 33
1050 34
1051 28
1052 29
1053 33
1054 23
1055 32
1056 35
1057 25
1058 29
1059 25
1060 31
1061 26
1062 35
1063 35
1064 27
1065 34
1066 29
1067 31
1068 36
1069 34
1070 37
1071 37
1072 25
1073 32
1074 24
1075 35
1076 32
1077 25
1078 33
1079 34
1080 32
1081 28
1082 37
1083 24
1084 36
1085 31
1086 30
1087 37
1088 22
1089 20
1090 19
1091 29
1092 32
1093 22
1094 32
1095 41
1096 35
1097 37
1098 31
1099 32
1100 36
1101 36
1102 23
1103 37
1104 34
1105 31
1106 44
1107 30
1108 30
1109 32
1110 28
1111 20
1112 35
1113 24
1114 28
1115 33
1116 27
1117 26
1118 36
1119 32
1120 35
1121 28
1122 36
1123 31
1124 26
1125 27
1126 32
1127 31
1128 29
1129 34
1130 37
1131 24
1132 29
1133 37
1134 20
1135 33
1136 33
1137 22
1138 24
1139 22
1140 31
1141 25
1142 30
1143 22
1144 34
1145 37
1146 20
1147 23
1148 39
1149 19
1150 20
1151 25
1152 21
1153 27
1154 33
1155 31
1156 21
1157 34
1158 25
1159 35
1160 24
1161 23
1162 28
1163 31
1164 27
1165 29
1166 29
1167 25
1168 28
1169 29
1170 24
1171 19
1172 29
1173 42
1174 32
1175 35
1176 33
1177 32
1178 30
1179 18
1180 31
1181 20
1182 36
1183 21
1184 25
1185 39
1186 25
1187 30
1188 27
1189 29
1190 35
1191 34
1192 29
1193 32
1194 32
1195 43
1196 29
1197 40
1198 32
1199 25
1200 27
1201 33
1202 26
1203 27
1204 26
1205 24
1206 31
1207 27
1208 20
1209 27
1210 33
1211 25
1212 31
1213 30
1214 32
1215 36
1216 27
1217 32
1218 32
1219 32
1220 36
1221 39
1222 34
1223 24
1224 33
1225 30
1226 35
1227 34
1228 30
1229 32
1230 42
1231 24
1232 34
1233 34
1234 26
1235 28
1236 35
1237 30
1238 31
1239 38
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Chart4

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Range
Average
UCL(R)
Date
Range
Range Chart

Case Study Histogram

Chicago Loan Processing Cycle Time
45
20
24
31
24
29
28
34
33
25
25
25
24
30
30
32
31
27
21
36
28
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42
35
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32
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32
36
28
39
22
30
32
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31
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45
36
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37
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31
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43
33
32
38
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28
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40
24
29
27
37
20
37
31
30
39
34
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43
31
36
29
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37
31
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33
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39
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36
30
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35
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18
29
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30
32
35
25
25
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24
33
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30
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36
33
27
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40
25
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32
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22
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33
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32
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36
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34
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41
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24
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32
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45
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39
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45
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32
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40
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31
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39
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32
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28
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29
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28
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36
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38
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41
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39
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36
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39
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34
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43
29
40
32
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39
34
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34
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42
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34
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28
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30
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38
22
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32
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35
31
33
36
37
24
23
33
21
34
32
28
31
29
34
17
34
22
21
34
23
41
31
31
28
26
34
20
24
21
32
30
29
27
36
25
33
23
34
33
28
17
27
29
29
32
43
30
25
29
27
28
31
31
40
28
26
33
33
33
22
40
36
27
30
40
22
26
26
29
36
22
38
24
36
29
29
35
33
31
26
27
25
26
30
32
34
32
29
42
33
25
27
26
26
15
46
20
40
26
33
22
28
25
34
34
31
25
37
23
38
23
31
32
38
28
35
24
25
29
34
33
33
38
23
30
28
33
21
35
33
35
25
31
28
24
35
30
26
30
30
30
33
24
39
31
27
22
30
23
25
28
32
25
31
34
37
21
31
36
34
25
33
34
26
35
27
24
25
26
28
31
29
33
43
18
27
23
The data set is the Loan Processing Cycle Time for Chicago. We want to display and describe the variation in the process. Follow these instructions to create the Histogram: 1. Click "Engine Room" from the toolbar above. 2. Select Measure from the menu. 3. Select Histogram from the menu. 4. Select Case Study Histogram from the menu in "Select Worksheet". 5. Click "OK" 6. Select Chicago Loan Processing Cycle Time from the menu in "First Variable". 7. Click "OK" 8. Engine Room will generate a new worksheet entitled "Histogram". When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Histogram and descriptive statisics?

Case Study Run Chart

Date Chicago Loan Processing Cycle Time
1-Jan 39
2-Jan 25
3-Jan 26
4-Jan 45
5-Jan 30
6-Jan 27
7-Jan 22
8-Jan 25
9-Jan 32
10-Jan 32
11-Jan 30
12-Jan 33
13-Jan 26
14-Jan 21
15-Jan 34
16-Jan 34
17-Jan 32
18-Jan 33
19-Jan 27
20-Jan 21
21-Jan 35
22-Jan 37
23-Jan 24
24-Jan 27
25-Jan 27
26-Jan 29
27-Jan 20
28-Jan 32
29-Jan 14
30-Jan 37
31-Jan 32
1-Feb 39
2-Feb 34
3-Feb 36
4-Feb 25
5-Feb 31
6-Feb 31
7-Feb 24
8-Feb 28
9-Feb 41
10-Feb 24
11-Feb 33
12-Feb 34
13-Feb 30
14-Feb 30
15-Feb 21
16-Feb 37
17-Feb 32
18-Feb 27
19-Feb 34
20-Feb 36
21-Feb 23
22-Feb 25
23-Feb 29
24-Feb 32
25-Feb 26
26-Feb 31
27-Feb 38
28-Feb 22
29-Feb 29
1-Mar 37
2-Mar 35
3-Mar 30
4-Mar 34
5-Mar 30
6-Mar 21
7-Mar 37
8-Mar 24
9-Mar 32
10-Mar 19
11-Mar 24
12-Mar 23
13-Mar 27
14-Mar 19
15-Mar 30
16-Mar 27
17-Mar 32
18-Mar 31
19-Mar 29
20-Mar 28
21-Mar 31
22-Mar 36
23-Mar 15
24-Mar 30
25-Mar 33
26-Mar 31
27-Mar 30
28-Mar 34
29-Mar 28
30-Mar 32
31-Mar 29
The sample data set is the Loan Processing Cycle Time for Chicago with dates. We want to display and describe the variation in the process. Follow these instructions to create the Run Chart (Trend Chart in Engine Room): 1. Click "Engine Room" from the toolbar above. 2. Select Measure from the menu. 3. Select Trend Chart from the menu. 4. Select Chicago Loan Processing Cycle Time from the menu in "Data". 5. Select Date from the menu in "Time Period". 6. Click "OK" 7. Engine Room will generate a new worksheet entitled "Trend". When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Run Chart?

Case Study Control Chart

Date Chicago Loan Processing Cycle Time
1-Jan 39
2-Jan 25
3-Jan 26
4-Jan 45
5-Jan 30
6-Jan 27
7-Jan 22
8-Jan 25
9-Jan 32
10-Jan 32
11-Jan 30
12-Jan 33
13-Jan 26
14-Jan 21
15-Jan 34
16-Jan 34
17-Jan 32
18-Jan 33
19-Jan 27
20-Jan 21
21-Jan 35
22-Jan 37
23-Jan 24
24-Jan 27
25-Jan 27
26-Jan 29
27-Jan 20
28-Jan 32
29-Jan 14
30-Jan 37
31-Jan 32
1-Feb 39
2-Feb 34
3-Feb 36
4-Feb 25
5-Feb 31
6-Feb 31
7-Feb 24
8-Feb 28
9-Feb 41
10-Feb 24
11-Feb 33
12-Feb 34
13-Feb 30
14-Feb 30
15-Feb 21
16-Feb 37
17-Feb 32
18-Feb 27
19-Feb 34
20-Feb 36
21-Feb 23
22-Feb 25
23-Feb 29
24-Feb 32
25-Feb 26
26-Feb 31
27-Feb 38
28-Feb 22
29-Feb 29
1-Mar 37
2-Mar 35
3-Mar 30
4-Mar 34
5-Mar 30
6-Mar 21
7-Mar 37
8-Mar 24
9-Mar 32
10-Mar 19
11-Mar 24
12-Mar 23
13-Mar 27
14-Mar 19
15-Mar 30
16-Mar 27
17-Mar 32
18-Mar 31
19-Mar 29
20-Mar 28
21-Mar 31
22-Mar 36
23-Mar 15
24-Mar 30
25-Mar 33
26-Mar 31
27-Mar 30
28-Mar 34
29-Mar 28
30-Mar 32
31-Mar 29
The sample data set is the Loan Processing Cycle Time for Chicago with dates. We want to display and describe the variation in the process. Follow these instructions to create the Individuals Chart (XmR in Engine Room): 1. Click "Engine Room" from the toolbar above. 2. Select Measure from the menu. 3. Select XmR Chart from the menu. 4. Select Chicago Loan Processing Cycle Time from the menu in "Data". 5. Select Date from the menu in "Time Period". 6. Click "OK" 7. Engine Room will generate a new worksheet entitled "X and Moving Range". When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Individuals Charts and descriptive statistics?

Case Study Pareto

Application Fields Number of Errors
Name 12
Address 3
Loan # 0
Loan Amount 26
Loan Duration 2
City 1
State 0
The data set is from a checksheet. We want to display and describe the variation in the process. Follow these instructions to create the Pareto: 1. Click "Engine Room" from the toolbar above. 2. Select Define from the menu. 3. Select Pareto Analysis from the menu. 4. Select Case Study Pareto from the menu in "Select Worksheet". 5. Click "OK" 6. Select Number of Errors from the menu in "Data". 7. Select Application Fields from the menu in "Category". 8. Click "OK" 9. Engine Room will generate a new worksheet entitled "Pareto". When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Pareto and descriptive statistics?

Case Study Correlation

Number of Personnel Loans Processed
26 111
24 114
27 111
16 118
21 115
22 112
15 117
21 116
38 103
48 102
39 107
50 101
18 116
20 114
28 110
31 109
50 100
41 103
42 103
40 105
21 115
18 116
42 104
15 119
42 106
9 119
52 101
36 107
46 102
21 113
41 104
22 115
30 110
25 112
31 108
19 115
17 118
47 102
17 118
21 114
15 118
31 108
21 114
22 115
43 104
28 111
22 110
17 115
48 101
25 111
18 117
33 108
13 118
17 118
42 106
27 112
41 105
40 106
28 109
50 101
21 114
28 111
50 101
48 101
35 108
34 111
41 104
29 110
22 115
26 111
12 119
16 115
35 108
24 113
23 116
21 113
28 110
46 103
20 116
46 101
The data set is the number of loans processed per day. We want to see if there is a strong relationship (correlation) between the loans processed per day and the number of personnel. Follow these instructions to perform correlation: 1. Click "Engine Room" from the toolbar above. 2. Select Measure from the menu. 3. Select scatter plot from the menu. 4. Select Case Study Correlation from the menu in "Select Worksheet". 5. Click "OK" 6. Select Loans Processed from the menu in "Data". 7.Select number of personnel from the menu in 'Data-2 ". 8. Click "OK" 9. Engine Room will generate a new worksheet entitled "Scatter". When completed, answer the following questions: 1. How would you interpret the graph 2. What conclusions can you draw from p-value and the R-squared value?

Obtaining R Value

Number of Personnel Loans Processed
26 111
24 114
27 111
16 118
21 115
22 112
15 117
21 116
38 103
48 102
39 107
50 101
18 116
20 114
28 110
31 109
50 100
41 103
42 103
40 105
21 115
18 116
42 104
15 119
42 106
9 119
52 101
36 107
46 102
21 113
41 104
22 115
30 110
25 112
31 108
19 115
17 118
47 102
17 118
21 114
15 118
31 108
21 114
22 115
43 104
28 111
22 110
17 115
48 101
25 111
18 117
33 108
13 118
17 118
42 106
27 112
41 105
40 106
28 109
50 101
21 114
28 111
50 101
48 101
35 108
34 111
41 104
29 110
22 115
26 111
12 119
16 115
35 108
24 113
23 116
21 113
28 110
46 103
20 116
46 101
This is the same data set we used for the scatter plot. Now we want to obtain the "r" value (correlation coefficient) to help us detrmine the strength of the correlation. Follow these instructions to identify the correlation coefficient (a.k.a pearson coefficient): 1. Click "Insert" from the Excel toolbar above. 2. Select function from the menu. 3. Select statistical from the "Select a Category" menu 4. In the "Select a Function" menu, scroll down to PEARSON and select. 5. Click "OK" 6. To populate the field "Array 1", in the excel worksheet select and highlight fields A1-A81. 7.To populate the field "Array 2", in the excel worksheet select and highlight fields B1-B81 8. Click "OK" 9. Excel will generate an "r" value in the worksheet itself. When completed, answer the following questions: 1. How would you interpret the "r" value (correlation coefficient)?

Case Study Regression

Loans Processed Loans per hour (average) (mins)
111 6.1
114 6.2
111 5.9
118 6.7
115 6.4
112 5.7
117 6.9
116 7
103 5.8
102 5.8
107 5.2
101 5.7
116 6.6
114 6.4
110 6
109 6
100 5.1
103 5.2
103 4.9
105 5.8
115 6.5
116 6.8
104 5.7
119 6.9
106 5.4
119 7
101 5.3
107 5.8
102 5.1
113 6.1
104 5.4
115 6.5
110 6
112 6
108 5.9
115 6.1
118 6.5
102 5.2
118 6.7
114 6.6
118 6.7
108 5.9
114 6.5
115 6.3
104 5.7
111 6.9
110 5.7
115 6.8
101 5.2
111 5.9
117 6.6
108 5.6
118 6.4
118 6.6
106 5.3
112 6
105 5.5
106 5.6
109 5.6
101 5.4
114 6.4
111 6.1
101 6.5
101 5.9
108 5.5
111 6.3
104 6
110 6.5
115 6.8
111 6.2
119 7
115 6.9
108 5.9
113 6.1
116 6.9
113 5.9
110 5.4
103 4.8
116 6.4
101 5.8
The data set is the Loans Processed. We want to see if there is a correlation between the loans processed per hour and the total loans processed per day. Follow these instructions to perform regression: 1. Click "Engine Room" from the toolbar above. 2. Select Analyze from the menu. 3. Select Simple Regression from the menu. 4. Select Case Study Regression from the menu in "Select Worksheet". 5. Click "OK" 6. Select Loans Processed from the menu in the "Dependent Variable". 7.Select Loans per hour from the menu in 'Independent Variable". 8. Click "OK" 9. Engine Room will generate a new worksheet entitled "Regression". When completed, answer the following questions: 1. How would you interpret the graph 2. What conclusions can you draw from p-value and the R-squared value?

Case Study Regression Results

SUMMARY OUTPUT 8.27 60.09
100 5.1
Regression Statistics 101 5.7
Multiple R 0.8193026767 101 5.3
R Square 0.671256876 101 5.2
Adjusted R Square 0.6670422206 101 5.4
Standard Error 3.2887153692 101 6.5
Observations 80 101 5.9
101 5.8
ANOVA 102 5.8
df SS MS F Significance F 102 5.1
Regression 1 1722.5793951901 1722.5793951901 159.26732 1.56980839556793E-20 102 5.2
Residual 78 843.6206048099 10.8156487796 103 5.8
Total 79 2566.2 103 5.2
103 4.9
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% 103 4.8
Intercept 60.0865544884 3.983959925 15.0821181987 7.84476407641124E-25 52.1550977424 68.0180112345 104 5.7
X Variable 1 8.2681165172 0.6551537816 12.6201156889 1.56980839556406E-20 6.9638052344 9.5724278 104 5.4
104 5.7
104 6
Formula: y = 8.27x + 60.09 105 5.8
RESIDUAL OUTPUT 105 5.5
106 5.4
Observation Predicted Y Residuals 106 5.3
1 102.2539487261 -2.2539487261 106 5.6
2 107.2148186364 -6.2148186364 107 5.2
3 103.9075720295 -2.9075720295 107 5.8
4 103.0807603778 -2.0807603778 108 5.9
5 104.7343836812 -3.7343836812 108 5.9
6 113.8293118501 -12.8293118501 108 5.6
7 108.8684419398 -7.8684419398 108 5.5
8 108.0416302881 -7.0416302881 108 5.9
9 108.0416302881 -6.0416302881 109 6
10 102.2539487261 -0.2539487261 109 5.6
11 103.0807603778 -1.0807603778 110 6
12 108.0416302881 -5.0416302881 110 6
13 103.0807603778 -0.0807603778 110 5.7
14 100.6003254227 2.3996745773 110 6.5
15 99.7735137709 3.2264862291 110 5.4
16 107.2148186364 -3.2148186364 111 6.1
17 104.7343836812 -0.7343836812 111 5.9
18 107.2148186364 -3.2148186364 111 6.9
19 109.6952535916 -5.6952535916 111 5.9
20 108.0416302881 -3.0416302881 111 6.1
21 105.561195333 -0.561195333 111 6.3
22 104.7343836812 1.2656163188 111 6.2
23 103.9075720295 2.0924279705 112 5.7
24 106.3880069847 -0.3880069847 112 6
25 103.0807603778 3.9192396222 112 6
26 108.0416302881 -1.0416302881 113 6.1
27 108.8684419398 -0.8684419398 113 6.1
28 108.8684419398 -0.8684419398 113 5.9
29 106.3880069847 1.6119930153 114 6.2
30 105.561195333 2.438804667 114 6.4
31 108.8684419398 -0.8684419398 114 6.6
32 109.6952535916 -0.6952535916 114 6.5
33 106.3880069847 2.6119930153 114 6.4
34 109.6952535916 0.3047464084 115 6.4
35 109.6952535916 0.3047464084 115 6.5
36 107.2148186364 2.7851813636 115 6.5
37 113.8293118501 -3.8293118501 115 6.1
38 104.7343836812 5.2656163188 115 6.3
39 110.5220652433 0.4779347567 115 6.8
40 108.8684419398 2.1315580602 115 6.8
41 117.136558457 -6.136558457 115 6.9
42 108.8684419398 2.1315580602 116 7
43 110.5220652433 0.4779347567 116 6.6
44 112.1756885467 -1.1756885467 116 6.8
45 111.348876895 -0.348876895 116 6.9
46 107.2148186364 4.7851813636 116 6.4
47 109.6952535916 2.3047464084 117 6.9
48 109.6952535916 2.3047464084 117 6.6
49 110.5220652433 2.4779347567 118 6.7
50 110.5220652433 2.4779347567 118 6.5
51 108.8684419398 4.1315580602 118 6.7
52 111.348876895 2.651123105 118 6.7
53 113.0025001984 0.9974998016 118 6.4
54 114.6561235019 -0.6561235019 118 6.6
55 113.8293118501 0.1706881499 119 6.9
56 113.0025001984 0.9974998016 119 7
57 113.0025001984 1.9974998016 119 7
58 113.8293118501 1.1706881499
59 113.8293118501 1.1706881499
60 110.5220652433 4.4779347567
61 112.1756885467 2.8243114533
62 116.3097468053 -1.3097468053
63 116.3097468053 -1.3097468053
64 117.136558457 -2.136558457
65 117.9633701087 -1.9633701087
66 114.6561235019 1.3438764981
67 116.3097468053 -0.3097468053
68 117.136558457 -1.136558457
69 113.0025001984 2.9974998016
70 117.136558457 -0.136558457
71 114.6561235019 2.3438764981
72 115.4829351536 2.5170648464
73 113.8293118501 4.1706881499
74 115.4829351536 2.5170648464
75 115.4829351536 2.5170648464
76 113.0025001984 4.9974998016
77 114.6561235019 3.3438764981
78 117.136558457 1.863441543
79 117.9633701087 1.0366298913
80 117.9633701087 1.0366298913

Case Study Regression Results

Y
Predicted Y
Loans per hour (average) (mins)
Loans Processed
Loans per hour (average) (mins) Line Fit Plot

X and Moving Range

Date Chicago Loan Processing Cycle Time Average - X 30
1-Jan 39 Median - Range 5
2-Jan 25 LCL - X 14
3-Jan 26 UCL - X 45
4-Jan 45 UCL - Range 19
5-Jan 30
6-Jan 27
7-Jan 22
8-Jan 25
9-Jan 32
10-Jan 32
11-Jan 30
12-Jan 33
13-Jan 26
14-Jan 21
15-Jan 34
16-Jan 34
17-Jan 32
18-Jan 33
19-Jan 27
20-Jan 21
21-Jan 35
22-Jan 37
23-Jan 24
24-Jan 27
25-Jan 27
26-Jan 29
27-Jan 20
28-Jan 32
29-Jan 14
30-Jan 37
31-Jan 32
1-Feb 39
2-Feb 34
3-Feb 36
4-Feb 25
5-Feb 31
6-Feb 31
7-Feb 24
8-Feb 28
9-Feb 41
10-Feb 24
11-Feb 33
12-Feb 34
13-Feb 30
14-Feb 30
15-Feb 21
16-Feb 37
17-Feb 32
18-Feb 27
19-Feb 34
20-Feb 36
21-Feb 23
22-Feb 25
23-Feb 29
24-Feb 32
25-Feb 26
26-Feb 31
27-Feb 38
28-Feb 22
29-Feb 29
1-Mar 37
2-Mar 35
3-Mar 30
4-Mar 34
5-Mar 30
6-Mar 21
7-Mar 37
8-Mar 24
9-Mar 32
10-Mar 19
11-Mar 24
12-Mar 23
13-Mar 27
14-Mar 19
15-Mar 30
16-Mar 27
17-Mar 32
18-Mar 31
19-Mar 29
20-Mar 28
21-Mar 31
22-Mar 36
23-Mar 15
24-Mar 30
25-Mar 33
26-Mar 31
27-Mar 30
28-Mar 34
29-Mar 28
30-Mar 32
31-Mar 29
67% of the variation in total loans processed is explained by loans processed per hour. ** Since this is transactional data, this is considered a high r-squared value.
High R-Square value
The E-20 means there are 20 zeros before the 1.56981…so this number is effectively zero. Since this is less than 0.05 we reject the null hypothesis that m= 0. In practical terms, this indicates a strong correlation between loans per hour and total loans processed per day.
Low P-value so Strong Correlation indicated.

X and Moving Range

39 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
45 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
22 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
35 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
20 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
14 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
39 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
41 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
23 29.5384615385 45.2634615385 13.8134615385
25 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
26 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
38 29.5384615385 45.2634615385 13.8134615385
22 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
35 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
21 29.5384615385 45.2634615385 13.8134615385
37 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
19 29.5384615385 45.2634615385 13.8134615385
24 29.5384615385 45.2634615385 13.8134615385
23 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
19 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
27 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
36 29.5384615385 45.2634615385 13.8134615385
15 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
33 29.5384615385 45.2634615385 13.8134615385
31 29.5384615385 45.2634615385 13.8134615385
30 29.5384615385 45.2634615385 13.8134615385
34 29.5384615385 45.2634615385 13.8134615385
28 29.5384615385 45.2634615385 13.8134615385
32 29.5384615385 45.2634615385 13.8134615385
29 29.5384615385 45.2634615385 13.8134615385
Data1
Average
UCL
LCL
Date
Chicago Loan Processing Cycle Time
X Chart

XMRData-4

37987 5 19.325
14 5 19.325
1 5 19.325
19 5 19.325
15 5 19.325
3 5 19.325
5 5 19.325
3 5 19.325
7 5 19.325
0 5 19.325
2 5 19.325
3 5 19.325
7 5 19.325
5 5 19.325
13 5 19.325
0 5 19.325
2 5 19.325
1 5 19.325
6 5 19.325
6 5 19.325
14 5 19.325
2 5 19.325
13 5 19.325
3 5 19.325
0 5 19.325
2 5 19.325
9 5 19.325
12 5 19.325
18 5 19.325
23 5 19.325
5 5 19.325
7 5 19.325
5 5 19.325
2 5 19.325
11 5 19.325
6 5 19.325
0 5 19.325
7 5 19.325
4 5 19.325
13 5 19.325
17 5 19.325
9 5 19.325
1 5 19.325
4 5 19.325
0 5 19.325
9 5 19.325
16 5 19.325
5 5 19.325
5 5 19.325
7 5 19.325
2 5 19.325
13 5 19.325
2 5 19.325
4 5 19.325
3 5 19.325
6 5 19.325
5 5 19.325
7 5 19.325
16 5 19.325
7 5 19.325
8 5 19.325
2 5 19.325
5 5 19.325
4 5 19.325
4 5 19.325
9 5 19.325
16 5 19.325
13 5 19.325
8 5 19.325
13 5 19.325
5 5 19.325
1 5 19.325
4 5 19.325
8 5 19.325
11 5 19.325
3 5 19.325
5 5 19.325
1 5 19.325
2 5 19.325
1 5 19.325
3 5 19.325
5 5 19.325
21 5 19.325
15 5 19.325
3 5 19.325
2 5 19.325
1 5 19.325
4 5 19.325
6 5 19.325
4 5 19.325
3 5 19.325
Range
Average
UCL(R)
Date
Range
Range Chart

XMRData-3

Date Chicago Loan Processing Cycle Time Average Range R-Median UCL - Range LCL - X UCL - X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385

XMRData-2

Date Chicago Loan Processing Cycle Time Average Range R-Median UCL - Range LCL - X UCL - X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385

XMRData-1

Date Chicago Loan Processing Cycle Time Average Range R-Mean UCL - Range LCL - X UCL - X
1-Jan 39 29.5384615385 6.6222222222 21.6414222222 11.9233504274 47.1535726496
2-Jan 25 29.5384615385 14 6.6222222222 21.6414222222 11.9233504274 47.1535726496
3-Jan 26 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
4-Jan 45 29.5384615385 19 6.6222222222 21.6414222222 11.9233504274 47.1535726496
5-Jan 30 29.5384615385 15 6.6222222222 21.6414222222 11.9233504274 47.1535726496
6-Jan 27 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
7-Jan 22 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
8-Jan 25 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
9-Jan 32 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
10-Jan 32 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
11-Jan 30 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
12-Jan 33 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
13-Jan 26 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
14-Jan 21 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
15-Jan 34 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
16-Jan 34 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
17-Jan 32 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
18-Jan 33 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
19-Jan 27 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
20-Jan 21 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
21-Jan 35 29.5384615385 14 6.6222222222 21.6414222222 11.9233504274 47.1535726496
22-Jan 37 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
23-Jan 24 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
24-Jan 27 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
25-Jan 27 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
26-Jan 29 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
27-Jan 20 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
28-Jan 32 29.5384615385 12 6.6222222222 21.6414222222 11.9233504274 47.1535726496
29-Jan 14 29.5384615385 18 6.6222222222 21.6414222222 11.9233504274 47.1535726496
30-Jan 37 29.5384615385 23 6.6222222222 21.6414222222 11.9233504274 47.1535726496
31-Jan 32 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
1-Feb 39 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
2-Feb 34 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
3-Feb 36 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
4-Feb 25 29.5384615385 11 6.6222222222 21.6414222222 11.9233504274 47.1535726496
5-Feb 31 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
6-Feb 31 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
7-Feb 24 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
8-Feb 28 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
9-Feb 41 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
10-Feb 24 29.5384615385 17 6.6222222222 21.6414222222 11.9233504274 47.1535726496
11-Feb 33 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
12-Feb 34 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
13-Feb 30 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
14-Feb 30 29.5384615385 0 6.6222222222 21.6414222222 11.9233504274 47.1535726496
15-Feb 21 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
16-Feb 37 29.5384615385 16 6.6222222222 21.6414222222 11.9233504274 47.1535726496
17-Feb 32 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
18-Feb 27 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
19-Feb 34 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
20-Feb 36 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
21-Feb 23 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
22-Feb 25 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
23-Feb 29 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
24-Feb 32 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
25-Feb 26 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
26-Feb 31 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
27-Feb 38 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
28-Feb 22 29.5384615385 16 6.6222222222 21.6414222222 11.9233504274 47.1535726496
29-Feb 29 29.5384615385 7 6.6222222222 21.6414222222 11.9233504274 47.1535726496
1-Mar 37 29.5384615385 8 6.6222222222 21.6414222222 11.9233504274 47.1535726496
2-Mar 35 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
3-Mar 30 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
4-Mar 34 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
5-Mar 30 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
6-Mar 21 29.5384615385 9 6.6222222222 21.6414222222 11.9233504274 47.1535726496
7-Mar 37 29.5384615385 16 6.6222222222 21.6414222222 11.9233504274 47.1535726496
8-Mar 24 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
9-Mar 32 29.5384615385 8 6.6222222222 21.6414222222 11.9233504274 47.1535726496
10-Mar 19 29.5384615385 13 6.6222222222 21.6414222222 11.9233504274 47.1535726496
11-Mar 24 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
12-Mar 23 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
13-Mar 27 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
14-Mar 19 29.5384615385 8 6.6222222222 21.6414222222 11.9233504274 47.1535726496
15-Mar 30 29.5384615385 11 6.6222222222 21.6414222222 11.9233504274 47.1535726496
16-Mar 27 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
17-Mar 32 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
18-Mar 31 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
19-Mar 29 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
20-Mar 28 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
21-Mar 31 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
22-Mar 36 29.5384615385 5 6.6222222222 21.6414222222 11.9233504274 47.1535726496
23-Mar 15 29.5384615385 21 6.6222222222 21.6414222222 11.9233504274 47.1535726496
24-Mar 30 29.5384615385 15 6.6222222222 21.6414222222 11.9233504274 47.1535726496
25-Mar 33 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496
26-Mar 31 29.5384615385 2 6.6222222222 21.6414222222 11.9233504274 47.1535726496
27-Mar 30 29.5384615385 1 6.6222222222 21.6414222222 11.9233504274 47.1535726496
28-Mar 34 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
29-Mar 28 29.5384615385 6 6.6222222222 21.6414222222 11.9233504274 47.1535726496
30-Mar 32 29.5384615385 4 6.6222222222 21.6414222222 11.9233504274 47.1535726496
31-Mar 29 29.5384615385 3 6.6222222222 21.6414222222 11.9233504274 47.1535726496

XMRData

Date Chicago Loan Processing Cycle Time Average Range R-Median UCL - Range LCL - X UCL - X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385

XBSData

Date Chicago Loan Processing Cycle Time Average Range R-Median UCL - Range LCL - X UCL - X
1-Jan 39 29.5384615385 5 19.325 13.8134615385 45.2634615385
2-Jan 25 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
3-Jan 26 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
4-Jan 45 29.5384615385 19 5 19.325 13.8134615385 45.2634615385
5-Jan 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
6-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
7-Jan 22 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
8-Jan 25 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
9-Jan 32 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
10-Jan 32 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
11-Jan 30 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
12-Jan 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
13-Jan 26 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
14-Jan 21 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
15-Jan 34 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
16-Jan 34 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
17-Jan 32 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
18-Jan 33 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Jan 27 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
20-Jan 21 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
21-Jan 35 29.5384615385 14 5 19.325 13.8134615385 45.2634615385
22-Jan 37 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Jan 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
24-Jan 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Jan 27 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
26-Jan 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Jan 20 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
28-Jan 32 29.5384615385 12 5 19.325 13.8134615385 45.2634615385
29-Jan 14 29.5384615385 18 5 19.325 13.8134615385 45.2634615385
30-Jan 37 29.5384615385 23 5 19.325 13.8134615385 45.2634615385
31-Jan 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
1-Feb 39 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
2-Feb 34 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
3-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
4-Feb 25 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
5-Feb 31 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
6-Feb 31 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
7-Feb 24 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
8-Feb 28 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
9-Feb 41 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
10-Feb 24 29.5384615385 17 5 19.325 13.8134615385 45.2634615385
11-Feb 33 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
12-Feb 34 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Feb 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Feb 30 29.5384615385 0 5 19.325 13.8134615385 45.2634615385
15-Feb 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
16-Feb 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
17-Feb 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Feb 27 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
19-Feb 34 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
20-Feb 36 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
21-Feb 23 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
22-Feb 25 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
23-Feb 29 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
24-Feb 32 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
25-Feb 26 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
26-Feb 31 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
27-Feb 38 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
28-Feb 22 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
29-Feb 29 29.5384615385 7 5 19.325 13.8134615385 45.2634615385
1-Mar 37 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
2-Mar 35 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
3-Mar 30 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
4-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
5-Mar 30 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
6-Mar 21 29.5384615385 9 5 19.325 13.8134615385 45.2634615385
7-Mar 37 29.5384615385 16 5 19.325 13.8134615385 45.2634615385
8-Mar 24 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
9-Mar 32 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
10-Mar 19 29.5384615385 13 5 19.325 13.8134615385 45.2634615385
11-Mar 24 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
12-Mar 23 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
13-Mar 27 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
14-Mar 19 29.5384615385 8 5 19.325 13.8134615385 45.2634615385
15-Mar 30 29.5384615385 11 5 19.325 13.8134615385 45.2634615385
16-Mar 27 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
17-Mar 32 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
18-Mar 31 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
19-Mar 29 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
20-Mar 28 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
21-Mar 31 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
22-Mar 36 29.5384615385 5 5 19.325 13.8134615385 45.2634615385
23-Mar 15 29.5384615385 21 5 19.325 13.8134615385 45.2634615385
24-Mar 30 29.5384615385 15 5 19.325 13.8134615385 45.2634615385
25-Mar 33 29.5384615385 3 5 19.325 13.8134615385 45.2634615385
26-Mar 31 29.5384615385 2 5 19.325 13.8134615385 45.2634615385
27-Mar 30 29.5384615385 1 5 19.325 13.8134615385 45.2634615385
28-Mar 34 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
29-Mar 28 29.5384615385 6 5 19.325 13.8134615385 45.2634615385
30-Mar 32 29.5384615385 4 5 19.325 13.8134615385 45.2634615385
31-Mar 29 29.5384615385 3 5 19.325 13.8134615385 45.2634615385

HistData

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 Average StdDev X Bar Bar S Bar LCL - S UCL - S LCL - X UCL - X
1 37987 37988 37989 37990 37991 37992 37993 37994 37995 37996 37997 37998 37999 38000 38001 38002 38003 38004 38005 38006 38007 38008 38009 38010 38011 38012 38013 38014 38015 38016 38017 38018 38019 38020 38021 38022 38023 38024 38025 38026 38027 38028 38029 38030 38031 38032 38033 38034 38035 38036 38037 38038 38039 38040 38041 38042 38043 38044 38045 38046 38047 38048 38049 38050 38051 38052 38053 38054 38055 38056 38057 38058 38059 38060 38061 38062 38063 38064 38065 38066 38067 38068 38069 38070 38071 38072 38073 38074 38075 38076 38077 38032 26.4133804475 19030.7692307692 16.0598635958 -127.8720872474 159.9918144389 19014.8581890309 19046.6802725076
2 39 25 26 45 30 27 22 25 32 32 30 33 26 21 34 34 32 33 27 21 35 37 24 27 27 29 20 32 14 37 32 39 34 36 25 31 31 24 28 41 24 33 34 30 30 21 37 32 27 34 36 23 25 29 32 26 31 38 22 29 37 35 30 34 30 21 37 24 32 19 24 23 27 19 30 27 32 31 29 28 31 36 15 30 33 31 30 34 28 32 29 29.5384615385 5.706346744 19030.7692307692 16.0598635958 -127.8720872474 159.9918144389 19014.8581890309 19046.6802725076

HistData-1

Observation Max 46 Bin Frequency Cum Count Bins
1 45 Min 12 12 1 0.1% 1423 10
2 20 Interval 3.7777777778 15.7777777778 4 0.0035137034
3 24 19.5555555556 28 0.0231904427
4 31 23.3333333333 124 0.1103302881
5 24 27.1111111111 303 0.3232607168
6 29 30.8888888889 283 0.5221363317
7 28 34.6666666667 392 0.7976106817
8 34 38.4444444444 213 0.9472944483
9 33 42.2222222222 57 0.9873506676
10 25 46 18 1
11 25 0 0 0
12 25 0 0 0
13 24 0 0 0
14 30 0 0 0
15 30 0 0 0
16 32 0 0 0
17 31 0 0 0
18 27 0 0 0
19 21 0 0 0
20 36 0 0 0
21 28 0 0 0
22 35 0 0 0
23 35 0 0 0
24 26 0 0 0
25 42 0 0 0
26 35 0 0 0
27 29 0 0 0
28 22 0 0 0
29 29 0 0 0
30 26 0 0 0
31 32
32 27
33 28
34 28
35 26
36 30
37 32
38 36
39 28
40 39
41 22
42 30
43 32
44 24
45 31
46 31
47 45
48 36
49 25
50 37
51 21
52 31
53 28
54 22
55 43
56 33
57 32
58 38
59 26
60 28
61 26
62 26
63 27
64 40
65 24
66 29
67 27
68 37
69 20
70 37
71 31
72 30
73 39
74 34
75 33
76 43
77 31
78 36
79 29
80 30
81 37
82 31
83 25
84 33
85 33
86 25
87 25
88 29
89 37
90 28
91 38
92 39
93 21
94 28
95 36
96 30
97 32
98 35
99 21
100 18
101 29
102 26
103 27
104 30
105 32
106 35
107 25
108 25
109 28
110 24
111 33
112 28
113 30
114 26
115 36
116 33
117 27
118 28
119 24
120 27
121 40
122 25
123 29
124 33
125 32
126 24
127 22
128 26
129 37
130 28
131 29
132 35
133 26
134 33
135 23
136 27
137 34
138 29
139 25
140 36
141 35
142 31
143 32
144 36
145 32
146 29
147 39
148 32
149 33
150 30
151 20
152 36
153 31
154 34
155 33
156 32
157 24
158 24
159 26
160 37
161 33
162 27
163 22
164 30
165 27
166 37
167 26
168 34
169 30
170 32
171 36
172 30
173 33
174 35
175 24
176 31
177 27
178 27
179 26
180 32
181 35
182 25
183 30
184 14
185 36
186 34
187 30
188 28
189 35
190 31
191 32
192 28
193 24
194 40
195 31
196 24
197 30
198 33
199 28
200 21
201 31
202 38
203 34
204 26
205 27
206 34
207 28
208 18
209 26
210 28
211 34
212 28
213 34
214 24
215 32
216 34
217 30
218 33
219 37
220 36
221 30
222 33
223 32
224 35
225 33
226 30
227 31
228 22
229 29
230 33
231 26
232 23
233 32
234 28
235 29
236 28
237 32
238 41
239 35
240 29
241 34
242 26
243 28
244 35
245 32
246 17
247 33
248 35
249 37
250 25
251 33
252 33
253 26
254 36
255 35
256 27
257 26
258 30
259 25
260 28
261 32
262 36
263 33
264 31
265 34
266 24
267 28
268 29
269 38
270 32
271 29
272 31
273 25
274 30
275 37
276 34
277 25
278 19
279 29
280 32
281 22
282 36
283 31
284 24
285 37
286 36
287 31
288 27
289 26
290 21
291 41
292 31
293 24
294 30
295 24
296 19
297 37
298 41
299 21
300 21
301 32
302 19
303 20
304 27
305 34
306 37
307 36
308 45
309 31
310 33
311 30
312 29
313 36
314 18
315 23
316 37
317 36
318 36
319 30
320 29
321 33
322 39
323 27
324 27
325 28
326 29
327 35
328 24
329 26
330 32
331 31
332 31
333 26
334 18
335 29
336 37
337 28
338 22
339 38
340 26
341 31
342 31
343 41
344 27
345 35
346 27
347 38
348 32
349 33
350 30
351 34
352 32
353 38
354 27
355 29
356 31
357 14
358 33
359 30
360 31
361 35
362 27
363 31
364 34
365 33
366 27
367 37
368 37
369 21
370 22
371 32
372 20
373 38
374 28
375 31
376 22
377 29
378 33
379 36
380 26
381 17
382 25
383 29
384 41
385 39
386 38
387 36
388 33
389 22
390 32
391 34
392 25
393 29
394 23
395 30
396 26
397 30
398 29
399 32
400 27
401 26
402 35
403 34
404 30
405 29
406 41
407 26
408 37
409 25
410 33
411 43
412 29
413 37
414 42
415 29
416 28
417 30
418 39
419 34
420 28
421 24
422 34
423 29
424 35
425 27
426 42
427 37
428 42
429 31
430 29
431 37
432 30
433 30
434 18
435 22
436 24
437 40
438 35
439 32
440 38
441 32
442 36
443 34
444 19
445 32
446 31
447 30
448 29
449 36
450 33
451 36
452 36
453 25
454 33
455 24
456 32
457 27
458 34
459 27
460 28
461 27
462 40
463 26
464 30
465 26
466 31
467 28
468 24
469 35
470 31
471 25
472 29
473 38
474 31
475 23
476 30
477 40
478 33
479 30
480 27
481 30
482 31
483 30
484 30
485 30
486 25
487 36
488 32
489 32
490 26
491 34
492 31
493 28
494 31
495 26
496 33
497 37
498 35
499 28
500 16
501 31
502 32
503 26
504 28
505 25
506 34
507 30
508 32
509 35
510 31
511 33
512 22
513 31
514 38
515 29
516 33
517 26
518 43
519 36
520 29
521 33
522 27
523 31
524 16
525 38
526 36
527 27
528 25
529 34
530 31
531 28
532 31
533 21
534 27
535 35
536 33
537 21
538 36
539 37
540 37
541 43
542 29
543 36
544 34
545 33
546 26
547 26
548 29
549 31
550 32
551 24
552 33
553 24
554 36
555 31
556 38
557 30
558 19
559 34
560 38
561 38
562 24
563 39
564 27
565 30
566 35
567 30
568 31
569 32
570 23
571 27
572 32
573 30
574 34
575 27
576 20
577 37
578 31
579 35
580 35
581 32
582 29
583 34
584 36
585 23
586 26
587 33
588 31
589 20
590 22
591 37
592 25
593 25
594 26
595 38
596 37
597 24
598 26
599 32
600 25
601 25
602 30
603 28
604 32
605 29
606 18
607 30
608 21
609 32
610 32
611 32
612 37
613 37
614 32
615 23
616 26
617 41
618 33
619 26
620 29
621 30
622 24
623 22
624 30
625 40
626 24
627 35
628 23
629 28
630 34
631 29
632 27
633 27
634 30
635 23
636 29
637 33
638 26
639 37
640 30
641 34
642 29
643 31
644 25
645 24
646 28
647 36
648 29
649 28
650 31
651 20
652 31
653 32
654 32
655 25
656 30
657 34
658 30
659 34
660 21
661 27
662 32
663 30
664 26
665 29
666 32
667 24
668 27
669 25
670 32
671 30
672 35
673 27
674 41
675 22
676 35
677 26
678 27
679 21
680 33
681 33
682 20
683 29
684 28
685 31
686 32
687 24
688 21
689 37
690 36
691 30
692 30
693 35
694 38
695 33
696 40
697 30
698 35
699 20
700 29
701 35
702 35
703 35
704 26
705 32
706 29
707 28
708 18
709 26
710 21
711 30
712 33
713 32
714 29
715 31
716 26
717 36
718 37
719 40
720 35
721 28
722 29
723 32
724 30
725 27
726 27
727 29
728 24
729 34
730 32
731 24
732 22
733 32
734 30
735 25
736 31
737 33
738 39
739 30
740 44
741 23
742 31
743 23
744 32
745 28
746 40
747 12
748 30
749 25
750 27
751 28
752 29
753 27
754 25
755 30
756 37
757 23
758 29
759 30
760 30
761 37
762 30
763 28
764 32
765 25
766 35
767 33
768 31
769 34
770 31
771 23
772 32
773 29
774 31
775 28
776 23
777 25
778 31
779 28
780 27
781 24
782 38
783 38
784 29
785 41
786 37
787 38
788 20
789 33
790 24
791 27
792 29
793 25
794 31
795 23
796 27
797 30
798 34
799 30
800 44
801 24
802 35
803 33
804 29
805 32
806 29
807 35
808 33
809 34
810 29
811 40
812 24
813 40
814 30
815 25
816 29
817 27
818 24
819 33
820 27
821 24
822 31
823 29
824 31
825 34
826 35
827 24
828 30
829 26
830 33
831 36
832 28
833 27
834 30
835 36
836 25
837 37
838 39
839 39
840 32
841 40
842 21
843 24
844 24
845 30
846 36
847 29
848 36
849 29
850 26
851 32
852 34
853 37
854 30
855 27
856 31
857 26
858 31
859 28
860 31
861 40
862 32
863 26
864 31
865 29
866 33
867 31
868 33
869 25
870 28
871 28
872 29
873 30
874 31
875 25
876 26
877 36
878 22
879 29
880 39
881 45
882 29
883 38
884 26
885 27
886 33
887 30
888 29
889 23
890 31
891 37
892 27
893 26
894 40
895 28
896 40
897 24
898 34
899 31
900 29
901 21
902 21
903 29
904 29
905 33
906 34
907 35
908 20
909 34
910 27
911 25
912 27
913 32
914 26
915 19
916 15
917 32
918 26
919 25
920 25
921 26
922 30
923 31
924 32
925 23
926 27
927 23
928 23
929 33
930 33
931 33
932 32
933 28
934 19
935 40
936 30
937 31
938 25
939 31
940 33
941 43
942 36
943 34
944 29
945 34
946 27
947 30
948 29
949 31
950 31
951 16
952 26
953 27
954 31
955 18
956 23
957 27
958 35
959 27
960 33
961 32
962 36
963 29
964 32
965 31
966 27
967 44
968 27
969 31
970 37
971 35
972 25
973 33
974 29
975 34
976 32
977 32
978 27
979 29
980 23
981 30
982 20
983 28
984 34
985 31
986 33
987 28
988 35
989 31
990 36
991 24
992 35
993 24
994 34
995 33
996 34
997 25
998 32
999 27
1000 21
1001 34
1002 32
1003 35
1004 21
1005 23
1006 32
1007 30
1008 35
1009 24
1010 21
1011 32
1012 38
1013 32
1014 32
1015 36
1016 39
1017 25
1018 29
1019 28
1020 23
1021 35
1022 32
1023 21
1024 27
1025 28
1026 23
1027 37
1028 30
1029 29
1030 24
1031 32
1032 24
1033 28
1034 34
1035 23
1036 35
1037 22
1038 24
1039 33
1040 28
1041 17
1042 36
1043 26
1044 38
1045 26
1046 33
1047 29
1048 25
1049 33
1050 34
1051 28
1052 29
1053 33
1054 23
1055 32
1056 35
1057 25
1058 29
1059 25
1060 31
1061 26
1062 35
1063 35
1064 27
1065 34
1066 29
1067 31
1068 36
1069 34
1070 37
1071 37
1072 25
1073 32
1074 24
1075 35
1076 32
1077 25
1078 33
1079 34
1080 32
1081 28
1082 37
1083 24
1084 36
1085 31
1086 30
1087 37
1088 22
1089 20
1090 19
1091 29
1092 32
1093 22
1094 32
1095 41
1096 35
1097 37
1098 31
1099 32
1100 36
1101 36
1102 23
1103 37
1104 34
1105 31
1106 44
1107 30
1108 30
1109 32
1110 28
1111 20
1112 35
1113 24
1114 28
1115 33
1116 27
1117 26
1118 36
1119 32
1120 35
1121 28
1122 36
1123 31
1124 26
1125 27
1126 32
1127 31
1128 29
1129 34
1130 37
1131 24
1132 29
1133 37
1134 20
1135 33
1136 33
1137 22
1138 24
1139 22
1140 31
1141 25
1142 30
1143 22
1144 34
1145 37
1146 20
1147 23
1148 39
1149 19
1150 20
1151 25
1152 21
1153 27
1154 33
1155 31
1156 21
1157 34
1158 25
1159 35
1160 24
1161 23
1162 28
1163 31
1164 27
1165 29
1166 29
1167 25
1168 28
1169 29
1170 24
1171 19
1172 29
1173 42
1174 32
1175 35
1176 33
1177 32
1178 30
1179 18
1180 31
1181 20
1182 36
1183 21
1184 25
1185 39
1186 25
1187 30
1188 27
1189 29
1190 35
1191 34
1192 29
1193 32
1194 32
1195 43
1196 29
1197 40
1198 32
1199 25
1200 27
1201 33
1202 26
1203 27
1204 26
1205 24
1206 31
1207 27
1208 20
1209 27
1210 33
1211 25
1212 31
1213 30
1214 32
1215 36
1216 27
1217 32
1218 32
1219 32
1220 36
1221 39
1222 34
1223 24
1224 33
1225 30
1226 35
1227 34
1228 30
1229 32
1230 42
1231 24
1232 34
1233 34
1234 26
1235 28
1236 35
1237 30
1238 31
1239 38
1240 22
1241 32
1242 32
1243 22
1244 23
1245 35
1246 35
1247 31
1248 33
1249 36
1250 37
1251 24
1252 23
1253 33
1254 21
1255 34
1256 32
1257 28
1258 31
1259 29
1260 34
1261 17
1262 34
1263 22
1264 21
1265 34
1266 23
1267 41
1268 31
1269 31
1270 28
1271 26
1272 34
1273 20
1274 24
1275 21
1276 32
1277 30
1278 29
1279 27
1280 36
1281 25
1282 33
1283 23
1284 34
1285 33
1286 28
1287 17
1288 27
1289 29
1290 29
1291 32
1292 43
1293 30
1294 25
1295 29
1296 27
1297 28
1298 31
1299 31
1300 40
1301 28
1302 26
1303 33
1304 33
1305 33
1306 22
1307 40
1308 36
1309 27
1310 30
1311 40
1312 22
1313 26
1314 26
1315 29
1316 36
1317 22
1318 38
1319 24
1320 36
1321 29
1322 29
1323 35
1324 33
1325 31
1326 26
1327 27
1328 25
1329 26
1330 30
1331 32
1332 34
1333 32
1334 29
1335 42
1336 33
1337 25
1338 27
1339 26
1340 26
1341 15
1342 46
1343 20
1344 40
1345 26
1346 33
1347 22
1348 28
1349 25
1350 34
1351 34
1352 31
1353 25
1354 37
1355 23
1356 38
1357 23
1358 31
1359 32
1360 38
1361 28
1362 35
1363 24
1364 25
1365 29
1366 34
1367 33
1368 33
1369 38
1370 23
1371 30
1372 28
1373 33
1374 21
1375 35
1376 33
1377 35
1378 25
1379 31
1380 28
1381 24
1382 35
1383 30
1384 26
1385 30
1386 30
1387 30
1388 33
1389 24
1390 39
1391 31
1392 27
1393 22
1394 30
1395 23
1396 25
1397 28
1398 32
1399 25
1400 31
1401 34
1402 37
1403 21
1404 31
1405 36
1406 34
1407 25
1408 33
1409 34
1410 26
1411 35
1412 27
1413 24
1414 25
1415 26
1416 28
1417 31
1418 29
1419 33
1420 43
1421 18
1422 27
1423 23
Observation Max 46 Bin Frequency Cum Count Bins
1 45 Min 12 12 1 0.1% 1423 10
2 20 Interval 3.7777777778 15.7777777778 4 0.0035137034
3 24 19.5555555556 28 0.0231904427
4 31 23.3333333333 124 0.1103302881
5 24 27.1111111111 303 0.3232607168
6 29 30.8888888889 283 0.5221363317
7 28 34.6666666667 392 0.7976106817
8 34 38.4444444444 213 0.9472944483
9 33 42.2222222222 57 0.9873506676
10 25 46 18 1
11 25 0 0 0
12 25 0 0 0
13 24 0 0 0
14 30 0 0 0
15 30 0 0 0
16 32 0 0 0
17 31 0 0 0
18 27 0 0 0
19 21 0 0 0
20 36 0 0 0
21 28 0 0 0
22 35 0 0 0
23 35 0 0 0
24 26 0 0 0
25 42 0 0 0
26 35 0 0 0
27 29 0 0 0
28 22 0 0 0
29 29 0 0 0
30 26 0 0 0
31 32
32 27
33 28
34 28
35 26
36 30
37 32
38 36
39 28
40 39
41 22
42 30
43 32
44 24
45 31
46 31
47 45
48 36
49 25
50 37
51 21
52 31
53 28
54 22
55 43
56 33
57 32
58 38
59 26
60 28
61 26
62 26
63 27
64 40
65 24
66 29
67 27
68 37
69 20
70 37
71 31
72 30
73 39
74 34
75 33
76 43
77 31
78 36
79 29
80 30
81 37
82 31
83 25
84 33
85 33
86 25
87 25
88 29
89 37
90 28
91 38
92 39
93 21
94 28
95 36
96 30
97 32
98 35
99 21
100 18
101 29
102 26
103 27
104 30
105 32
106 35
107 25
108 25
109 28
110 24
111 33
112 28
113 30
114 26
115 36
116 33
117 27
118 28
119 24
120 27
121 40
122 25
123 29
124 33
125 32
126 24
127 22
128 26
129 37
130 28
131 29
132 35
133 26
134 33
135 23
136 27
137 34
138 29
139 25
140 36
141 35
142 31
143 32
144 36
145 32
146 29
147 39
148 32
149 33
150 30
151 20
152 36
153 31
154 34
155 33
156 32
157 24
158 24
159 26
160 37
161 33
162 27
163 22
164 30
165 27
166 37
167 26
168 34
169 30
170 32
171 36
172 30
173 33
174 35
175 24
176 31
177 27
178 27
179 26
180 32
181 35
182 25
183 30
184 14
185 36
186 34
187 30
188 28
189 35
190 31
191 32
192 28
193 24
194 40
195 31
196 24
197 30
198 33
199 28
200 21
201 31
202 38
203 34
204 26
205 27
206 34
207 28
208 18
209 26
210 28
211 34
212 28
213 34
214 24
215 32
216 34
217 30
218 33
219 37
220 36
221 30
222 33
223 32
224 35
225 33
226 30
227 31
228 22
229 29
230 33
231 26
232 23
233 32
234 28
235 29
236 28
237 32
238 41
239 35
240 29
241 34
242 26
243 28
244 35
245 32
246 17
247 33
248 35
249 37
250 25
251 33
252 33
253 26
254 36
255 35
256 27
257 26
258 30
259 25
260 28
261 32
262 36
263 33
264 31
265 34
266 24
267 28
268 29
269 38
270 32
271 29
272 31
273 25
274 30
275 37
276 34
277 25
278 19
279 29
280 32
281 22
282 36
283 31
284 24
285 37
286 36
287 31
288 27
289 26
290 21
291 41
292 31
293 24
294 30
295 24
296 19
297 37
298 41
299 21
300 21
301 32
302 19
303 20
304 27
305 34
306 37
307 36
308 45
309 31
310 33
311 30
312 29
313 36
314 18
315 23
316 37
317 36
318 36
319 30
320 29
321 33
322 39
323 27
324 27
325 28
326 29
327 35
328 24
329 26
330 32
331 31
332 31
333 26
334 18
335 29
336 37
337 28
338 22
339 38
340 26
341 31
342 31
343 41
344 27
345 35
346 27
347 38
348 32
349 33
350 30
351 34
352 32
353 38
354 27
355 29
356 31
357 14
358 33
359 30
360 31
361 35
362 27
363 31
364 34
365 33
366 27
367 37
368 37
369 21
370 22
371 32
372 20
373 38
374 28
375 31
376 22
377 29
378 33
379 36
380 26
381 17
382 25
383 29
384 41
385 39
386 38
387 36
388 33
389 22
390 32
391 34
392 25
393 29
394 23
395 30
396 26
397 30
398 29
399 32
400 27
401 26
402 35
403 34
404 30
405 29
406 41
407 26
408 37
409 25
410 33
411 43
412 29
413 37
414 42
415 29
416 28
417 30
418 39
419 34
420 28
421 24
422 34
423 29
424 35
425 27
426 42
427 37
428 42
429 31
430 29
431 37
432 30
433 30
434 18
435 22
436 24
437 40
438 35
439 32
440 38
441 32
442 36
443 34
444 19
445 32
446 31
447 30
448 29
449 36
450 33
451 36
452 36
453 25
454 33
455 24
456 32
457 27
458 34
459 27
460 28
461 27
462 40
463 26
464 30
465 26
466 31
467 28
468 24
469 35
470 31
471 25
472 29
473 38
474 31
475 23
476 30
477 40
478 33
479 30
480 27
481 30
482 31
483 30
484 30
485 30
486 25
487 36
488 32
489 32
490 26
491 34
492 31
493 28
494 31
495 26
496 33
497 37
498 35
499 28
500 16
501 31
502 32
503 26
504 28
505 25
506 34
507 30
508 32
509 35
510 31
511 33
512 22
513 31
514 38
515 29
516 33
517 26
518 43
519 36
520 29
521 33
522 27
523 31
524 16
525 38
526 36
527 27
528 25
529 34
530 31
531 28
532 31
533 21
534 27
535 35
536 33
537 21
538 36
539 37
540 37
541 43
542 29
543 36
544 34
545 33
546 26
547 26
548 29
549 31
550 32
551 24
552 33
553 24
554 36
555 31
556 38
557 30
558 19
559 34
560 38
561 38
562 24
563 39
564 27
565 30
566 35
567 30
568 31
569 32
570 23
571 27
572 32
573 30
574 34
575 27
576 20
577 37
578 31
579 35
580 35
581 32
582 29
583 34
584 36
585 23
586 26
587 33
588 31
589 20
590 22
591 37
592 25
593 25
594 26
595 38
596 37
597 24
598 26
599 32
600 25
601 25
602 30
603 28
604 32
605 29
606 18
607 30
608 21
609 32
610 32
611 32
612 37
613 37
614 32
615 23
616 26
617 41
618 33
619 26
620 29
621 30
622 24
623 22
624 30
625 40
626 24
627 35
628 23
629 28
630 34
631 29
632 27
633 27
634 30
635 23
636 29
637 33
638 26
639 37
640 30
641 34
642 29
643 31
644 25
645 24
646 28
647 36
648 29
649 28
650 31
651 20
652 31
653 32
654 32
655 25
656 30
657 34
658 30
659 34
660 21
661 27
662 32
663 30
664 26
665 29
666 32
667 24
668 27
669 25
670 32
671 30
672 35
673 27
674 41
675 22
676 35
677 26
678 27
679 21
680 33
681 33
682 20
683 29
684 28
685 31
686 32
687 24
688 21
689 37
690 36
691 30
692 30
693 35
694 38
695 33
696 40
697 30
698 35
699 20
700 29
701 35
702 35
703 35
704 26
705 32
706 29
707 28
708 18
709 26
710 21
711 30
712 33
713 32
714 29
715 31
716 26
717 36
718 37
719 40
720 35
721 28
722 29
723 32
724 30
725 27
726 27
727 29
728 24
729 34
730 32
731 24
732 22
733 32
734 30
735 25
736 31
737 33
738 39
739 30
740 44
741 23
742 31
743 23
744 32
745 28
746 40
747 12
748 30
749 25
750 27
751 28
752 29
753 27
754 25
755 30
756 37
757 23
758 29
759 30
760 30
761 37
762 30
763 28
764 32
765 25
766 35
767 33
768 31
769 34
770 31
771 23
772 32
773 29
774 31
775 28
776 23
777 25
778 31
779 28
780 27
781 24
782 38
783 38
784 29
785 41
786 37
787 38
788 20
789 33
790 24
791 27
792 29
793 25
794 31
795 23
796 27
797 30
798 34
799 30
800 44
801 24
802 35
803 33
804 29
805 32
806 29
807 35
808 33
809 34
810 29
811 40
812 24
813 40
814 30
815 25
816 29
817 27
818 24
819 33
820 27
821 24
822 31
823 29
824 31
825 34
826 35
827 24
828 30
829 26
830 33
831 36
832 28
833 27
834 30
835 36
836 25
837 37
838 39
839 39
840 32
841 40
842 21
843 24
844 24
845 30
846 36
847 29
848 36
849 29
850 26
851 32
852 34
853 37
854 30
855 27
856 31
857 26
858 31
859 28
860 31
861 40
862 32
863 26
864 31
865 29
866 33
867 31
868 33
869 25
870 28
871 28
872 29
873 30
874 31
875 25
876 26
877 36
878 22
879 29
880 39
881 45
882 29
883 38
884 26
885 27
886 33
887 30
888 29
889 23
890 31
891 37
892 27
893 26
894 40
895 28
896 40
897 24
898 34
899 31
900 29
901 21
902 21
903 29
904 29
905 33
906 34
907 35
908 20
909 34
910 27
911 25
912 27
913 32
914 26
915 19
916 15
917 32
918 26
919 25
920 25
921 26
922 30
923 31
924 32
925 23
926 27
927 23
928 23
929 33
930 33
931 33
932 32
933 28
934 19
935 40
936 30
937 31
938 25
939 31
940 33
941 43
942 36
943 34
944 29
945 34
946 27
947 30
948 29
949 31
950 31
951 16
952 26
953 27
954 31
955 18
956 23
957 27
958 35
959 27
960 33
961 32
962 36
963 29
964 32
965 31
966 27
967 44
968 27
969 31
970 37
971 35
972 25
973 33
974 29
975 34
976 32
977 32
978 27
979 29
980 23
981 30
982 20
983 28
984 34
985 31
986 33
987 28
988 35
989 31
990 36
991 24
992 35
993 24
994 34
995 33
996 34
997 25
998 32
999 27
1000 21
1001 34
1002 32
1003 35
1004 21
1005 23
1006 32
1007 30
1008 35
1009 24
1010 21
1011 32
1012 38
1013 32
1014 32
1015 36
1016 39
1017 25
1018 29
1019 28
1020 23
1021 35
1022 32
1023 21
1024 27
1025 28
1026 23
1027 37
1028 30
1029 29
1030 24
1031 32
1032 24
1033 28
1034 34
1035 23
1036 35
1037 22
1038 24
1039 33
1040 28
1041 17
1042 36
1043 26
1044 38
1045 26
1046 33
1047 29
1048 25
1049 33
1050 34
1051 28
1052 29
1053 33
1054 23
1055 32
1056 35
1057 25
1058 29
1059 25
1060 31
1061 26
1062 35
1063 35
1064 27
1065 34
1066 29
1067 31
1068 36
1069 34
1070 37
1071 37
1072 25
1073 32
1074 24
1075 35
1076 32
1077 25
1078 33
1079 34
1080 32
1081 28
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1100 36
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1120 35
1121 28
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1123 31
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1125 27
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1128 29
1129 34
1130 37
1131 24
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1199 25
1200 27
1201 33
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1210 33
1211 25
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1216 27
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1219 32
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1234 26
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Important Distinctions

Defective

Defect

Discrete Data: Defect vs. Defective

Any nonconformance; may have multiple “defects” per unit

Use: “c” or “u” charts

A unit or product that contains one or more defects (i.e. it does not matter the amount of defects it is either right or wrong)

Use: “p” or “np” charts

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Summary of Variation and Control Charts

 Control limits are calculated from the process data; specification limits come from the customer: they are both important

 Process variation can be stable and still be unacceptable; to reduce common cause variation, make fundamental improvements to the vital few root causes

 Variation is the “voice of the process” – learn to listen and respond appropriately

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Interpret Control Chart or Run Chart

Develop solutions for special causes and

implement as appropriate

Investigate the specific data points related to

the special causes

Special Causes

Develop solutions for the “vital few” process

and input Xs

Common Causes

Investigate all of the variation by identifying the “vital few” process

Xs and input Xs

Response Strategy Summary

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Notes: Understanding the source of variation is important to devising a sound strategy for process control and improvement. The source of variation has important consequences for the type of actions required. If a process exhibits common cause variation the appropriate action is to investigate all of the data points. Finding the “vital few” causal factors (Xs) that explain common cause variation is more difficult than finding causal factors for special causes because they are not as obvious. If a process exhibits special cause variation the appropriate action is to investigate those specific data points related to the special cause signals. In most cases the investigation will reveal important causal factors (Xs) related to the special cause (s). The results of the investigation should be integrated into an action plan for immediately addressing the special causes.

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What is a Process Monitoring Plan?

The Process Monitoring Plan Includes:

 CTQ – The measurable requirement (Critical to Quality aspect) the customer has of the process.

 Process Steps Where the CTQ is Measured – The step in the process where the CTQ will be measured and data collected.

 Data Collection Method – A description of the method that will be followed to collect the data.

 Data Collection Frequency – The frequency that the data will be collected (hourly, daily, twice a week, monthly, etc.).

 Owner – The person responsible for collecting the data.

Process Monitoring Plan

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What you learned during this section:

 What is meant by process control

 The types of control charts

 How to develop a monitoring plan

Summary of Section

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Control – Process Control

Dashboards

Process Monitoring

Introduction to Process Management

Lean Six Sigma Training

Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl

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 Understand what a dashboard is

 Understand the questions to consider when developing a dashboard

 Utilize a dashboard example to begin development of your project dashboard

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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A process dashboard provides a visual picture of the process through data diagrams and charts. Visualizing your process allows you to fully comprehend process performance and communicate it to your champions and stakeholders.

Preliminary Process Dashboard

Customer: Applicant CTQ Spec: 100% Process: New Business Department: Customer Engagement Owner: M. Gunner Projects: 0 88 Defects/28908 Opps Weighted average: 5-7 opportunities/unit 4.4 Sigma without India. India Sigma is 3.6 on 100% QA. Improving steadily.

Some Customer Satisfaction COPQ

Defects

0

2

4

6

8

10

12

14

16

18

20

Unplanned Emp. AbsenceCustomer Not Available for Call Back

Rejected System Downtime Hold for Sup Approval

Category

# O

bs er

va tio

ns

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

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In planning for the design of a process dashboard you must select which chart/tool is the best to use to display process performance and results. To do this, you must first decide what you want the process dashboard to tell or describe about the process it is monitoring.

Some key questions your process dashboard should answer:

1. Is my process capable? Is it meeting customer requirements?

2. If it isn’t meeting customer requirements, what might be driving the lack of capability? What is the biggest defect contributing to the overall defect rate?

3. How much variation is in my process?

Preliminary Process Dashboard

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Used to confirm relationship between two variablesAnalysisScatter Plot

Type of chart used to display data related to a process variable in sequence over time to identify changes

MonitoringRun Charts

Used to track the relationship between two sets of data over time

AnalysisRegression (Advanced tool)

Used to depict percentages of total in a circular diagramDisplayPie Chart

Used to identify and prioritize problems or causes of problems

Monitoring/AnalysisPareto Analysis

Used to display frequency of data in column form. Also used to prepare Pareto charts

MonitoringHistogram

Used to help understand variation and to control and improve a process

MonitoringControl Charts

Used to brainstorm and logically organize possible causes for a particular effect

AnalysisCause and Effect Diagrams

Used to display simple comparisons between series of data

DisplayBar Chart

PurposeTypeChart/Tool

It is not necessary to use all of the charts, just choose the ones that best suit the type of data and purpose of display for your process.

Overview of Data Tools

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√Run ChartPercent of Invoices that are received via electronic data interchange EDI InvoicingInvoice

OutputProcessInputDisplayMeasurementCustomer Requirement or

Process Indicator

Unit Being Processed

√Histogram and/or Run Chart

Customer Set-Up: Time form CMM launch to input completed

Credit Approval: Time from credit application hand-off to credit application approved/rejected.

Lease/Sale Contract: Time from lease created to lease activated

Case Creation: Time from lease created to delivery case created

Order Fulfillment Sub- process Cycle times

Order

√Run ChartPercent of Invoices that are adjustedAdjustments

A method for organizing and identifying your preliminary dashboard

Preliminary Dashboard Measurement Plan Matrix – Example

Dashboard Measurement

Plan

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In addition to tracking and monitoring process results during the Control phase, it also important to track and monitor financial results.

Teams should include financial metrics in the dashboard design to continuously track the financial impact of the improved process and to ensure that the organization has realized the benefits that the project projected.

Additional Dashboard Metrics

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Financial Metrics Commonly Tracked:

 Project Benefits Projected vs. Actual

 Cost of Poor Quality (COPQ)  Often tracked for individual projects

and also as a rollup metric for all projects

Guidelines:

 Most financial benefits from projects are tracked over a 12 month period of time after implementation

 Remember to involve Finance representatives in dashboard design to agree on what financial metrics will be tracked and how they will be measured.

Financial Dashboard Metrics Considerations

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Cycle Time

Sales Sigma

Accuracy

Accuracy Defects

What Should Your Gauges/Dials Be?

Process Dashboard

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Notes: The dashboard is the key communication tool to the organization that indicates process performance and the health of the process. The dashboard, provides the means for assuring continuing effective and efficient process performance; or detecting defects requiring removal; or, special cause variation requiring troubleshooting; or, triggering the need for new process design or reengineering to restore performance at a level that meets our customer’s needs. The dashboard indicators should tie to process goals and strategic objectives.

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The dashboard is:

 A business management tool

 Set of critical indicators

 It serves as a control infrastructure for existing improvement projects once they go into the control phase

 It can also serve as the platform for identifying new improvement projects

 An indicator system that must be developed, tested, and recalibrated as requirements and measurement systems change

Dashboard Attributes

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 How do you want the information displayed for your indicators/measures?

 To what level do you want to “drill down” in the information?

 How might you want to segment the information for making critical decisions?

 Who should have access to the information?

Key Questions for Developing Your Dashboard

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What you learned during this section:

 Understand what a dashboard is

 Understand the questions to consider when developing a dashboard

 Utilize a dashboard example to practice developing a dashboard for your project

Summary of Section

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End of Lesson: Control – Process Control

Lean Six Sigma Training

Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl

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Control – Response Planning

Action Planning

Process Reviews

Lean Six Sigma Training

Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl

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 Understand the purpose and benefits of regular process reviews

 Understand the role of the process owner in monitoring and responding to process issues

By the end of this section, you will be able to:

Overview – Purpose – Objectives – Key Topics

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Process Reviews

External Environmental

Information

Internal Environmental

Information

Satisfied With Indicators?

– Yes – Continue Control

Actions

Satisfied With Indicators?

– No – Plan & Implement

Improvement Actions

Dashboard Indicators

Process Reviews

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The Dashboard is the mechanism used to monitor and assess process performance and determine what actions to take. During process review meetings the process owner and team will review dashboard results and determine what remedial actions need to be taken.

Process Reviews

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When to review?

Process Owners hold regular (monthly, weekly) updates with their Process Teams

 Receive updates on process performance

 Conduct question and answer session

 Perform joint problem solving

 Reinforcing success

Conducting Process Review Meetings

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How often should Process Owners review processes?

Formal audits/reviews conducted under the auspices of an outside authority.

Formal meeting of Process Owner and Sub-Process Owners. Used primarily when processes and sub processes are performing within expected parameters and are meeting or exceeding goals. Can occur within regular operations reviews.

Less formal meeting of Process Owner and Sub-Process Owners. Detailed review of sub-process dashboards and performance.

Informal meeting with Sub-Process Owners. Detailed review similar to the bi-weekly to monthly review. Used primarily when sub-processes are critical to overall process cycle times or sub-processes are performing poorly.

Quarterly to Annually

Monthly to Quarterly

Bi-weekly to Monthly

As Needed

Process Reviews by Process Owner

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Notes: The timing of the review meetings is typically set at the discretion of the Process Owner and sometimes at the request of the team. Some factors that affect the frequency of reviews are: - Poorly performing processes/sub-processes (more frequent reviews) - Processes/sub-processes cycle times (completion of a cycle provides better information mid-cycle) - Availability of data (updated date is needed since last review meeting)

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Process review meetings should be structured to address these types of questions and trigger the appropriate response to address gaps.

1. How is the process performing compared to the goals we set for it? Are there gaps? Why or why not?

2. How are the sub-processes performing against the goals? Are they stable? Are they capable? How should we respond?

3. How does our process compare to our competitors, or those “best in class”?

4. Are we maintaining gains made by our changes – e.g. Quick Wins, DMAIC or DFSS projects?

5. Are we making changes in one part of our process that could impact another part of our process or impact another process? Will it help or hurt? Are other project teams making changes that impact our process?

Process Review Questions

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6. Are we measuring the right process indicators? Do they predict how well our process outputs will satisfy customers? Are there better indicators we should be measuring?

7. Do we need to make changes to: Measures? Training? Staffing? Rewards? Communications and feedback? Goals? Resource allocation? Action plans?

8. Are our work procedures being used? Why or why not?

9. What do we need to communicate to Leadership and to our process teams?

10. How can we recognize process contributions and successes?

Process Review Questions (Continued)

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Review Dashboards  Sigmas  Trends  Specific Transactions

Perform Analysis  Special/Common Causes (Stability)  Root Causes  Assess Capability

 Identify Next Steps  Stabilization  Management Emphasis & Inspection  Project Scoping  Training  Advanced Statistical Tools  QRB Report-Out

 Monthly (3rd week of each month)  2 hours or as needed

Standardized Meeting Agendas with Action Items

Process Owner Report-Outs

Champion Process Owner(s) MBB or Quality Analyst Quality Leader, if appropriate Customers, when appropriate

WHAT WHEN

HOW WHO

Example Guidelines for Process Review Meetings

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Consequences of not having an accountable process owner:  Defects start to occur and remain unchecked

 Internal complaints go unaddressed

 Changing customer needs are not identified, let alone planned for

 Improvement projects aren’t identified or implemented on a timely basis

 Teamwork and morale deteriorate

Creating an environment of process accountability is important:  Establishing what results and processes the Process Team will be accountable for (set goals)

 Explaining those expectations to the Process Team Leader and assuring understanding

 Giving the Process Team and Process Owner the tools, resources and information to succeed

 Measuring and giving performance feedback (timely, specific, accurate to all levels of the team)

 Applying judgment in evaluation of performance

Process Accountability

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What you learned during this section:

 The purpose and benefits of regular process reviews  The role of the process owner in monitoring and

responding to process issues

Summary of Section

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Control – Response Planning

Action Planning

Process Reviews

Lean Six Sigma Training

Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl

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 Understand what response planning is  Understand the course of action to take if out of control

issues should occur  Troubleshoot to fix common and special cause

problems

By the end of this section, you will be able to:

Overview – Purpose – Objectives – Key Topics

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What is a Response Plan?

 A response plan is a documented method for how a process owner/team should respond to any out-of-control conditions that may occur in a process

 A good response plan will help ensure a timely and appropriate response to processing problems as they occur, thereby decreasing the risk of defects getting to the customer

Response Plan

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Provides a response if the process should fail to meet customer requirements for each variable (both the X and Y)

OwnerTimingActionMeasure

Specific Action to be

Taken

Responsibility to Take Action

Timing of Action

What is a Response Plan?

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Notes: All Xs and Ys that are being monitored must be included in the response plan. For each measurement tracked, document the specific action to be taken when an out-of-control event occurs. The action that is taken will depend on the severity of the situation. If the situation is minor, specific corrective actions can be executed as planned. In the event of a serious problem, the process owner may need to become more involved. The timing of the response should also be included in the response plan. The plan should specify a time frame in which the team needs to respond for each out-of-control situation. Finally, the person responsible for each X and Y must be named in the response plan. Be specific about action to be taken. Remember to operationally define any terms that may be ambiguous so that little confusion exists about the specific response needed.

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Looks Like

Type

Common Cause Variation

Special Cause Variation

Action To Be Taken

Study individual points or specific cluster of points to determine what was reason for difference

Make changes to sustain or prevent special causes in the future

Study all data points collectively to better understand sources of variation

Make basic process change to reduce common cause variation, shift the average, or both

What should you do when you are not Satisfied with Current Performance?

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Yes No Are there differences in the methods used by different employees?

Yes No Has there been a significant change in the internal/external environment?

Yes No Is the process affected by predictable conditions?

Yes No Were any untrained employees involved in the process at any time?

Yes No Has there been a change in the supplier of inputs to the process?

Yes No Has there been a change in policies or procedures?

Yes No Could the employees be afraid to report “bad news?”

Common Questions for Investigating an Out-Of- Control Process

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Strategy for Eliminating Special Causes of Variation

 Work to get special causes signaled quickly. Use early warning indicators throughout your operation.

 Immediately search for cause when a control chart gives a signal that a special cause has occurred.

 Find out what was different on that occasion.

 Keep asking - “Why”

 Do not make fundamental changes in the process.

 Immediate remedy to contain any damage.  Remove assignable cause and seek ways

to prevent that special cause from recurring, or if results are good, retain that lesson.

Timely Data

Search for Cause

No Changes

Prevent and Retain

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 Quick hit tools the team can use to analyze, troubleshoot, and diagnose why a process is not performing up to requirements:  Cause and Effect Diagram  Value-Add/Non Value-Add Process Analysis

Process Step

Time (Minutes)

Value-Added

Nonvalue-added

Transferring

Retrieving Information

Reviewing

Prep/Set-up

Waiting for Help

Total

1 2 3 4 5 6 7 8 9 10 Total %Total

1 5 3 2 4 2 8 2 5 8 40 100%

4

5

16

8

40

4

10%

12.5%

40%

20%

10%

100%

3 7.5%

Problem Statement

Main Category A

Main Category C

Main Category B

Potential Root Cause

Cause

Cause

Cause

Potential Root Cause

Potential Root Cause

Tools for Quick Process Analysis, Diagnosis, and Remedy

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What you learned during this section:

 What response planning is  The course of action to take if out of control issues should

occur  How to troubleshoot to fix common and special cause

problems

Summary of Section

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End of Lesson: Control – Response Planning

Lean Six Sigma Training

Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl

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Control – Project Documentation

Solution Replication and Closure

Communicate Project Outcomes

Document and Standardize

Lean Six Sigma Training

Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl

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 Understand the purpose and importance of standards to effective Control

 Understand the use and importance of documenting procedures

 Understand some of the keys to success and pitfalls with writing procedures

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Definition

A documented method which identifies in detail all the steps necessary to produce a product or meet a desired service outcome.

They are a written agreement between the associate and the company regarding how the job will be done.

Questions to ask when there is trouble with a Standard Practice:

 Do we have a standard practice?

 Does the employee know the standard practice?

 Does the employee use the standard practice?

 Do we enforce the standard practice?

What are Standard Practices?

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 Everyone does things in a different way

 Some individual learning and improvement

 No group learning

 No accepted methods

Right Amount

 Best available methods are used

 Less wasted effort

 Group and individual learning

 Methods are improved

 People are frustrated

 Creativity is stifled

 No learning and improvement

 People fight the system, cut corners

Too Little

Too Much

Degrees of Standardization

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 Greater process variation

 Unhappy customers

 Lack of organizational learning

 Inability to hold the gains of improvement efforts

 Lack of agreement among employees on how to do the job

 Increased supervisory time and training required

Costs of Not Standardizing

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Documentation is Critical to:

 Describe the flow of the process and standardize procedures for operating the process

 Provide approved information for all current and future employees who will need it

 Increase organizational learning and provide training materials

 Use results in consistent operating procedures and reduced process variation

 A necessary step to ensure that the learning gained via Process Management is shared and institutionalized

Why Document?

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A procedure is the documented sequence of steps and other instructions necessary to carry

out an activity.

Documentation – Procedures

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What is a Procedure Procedures are the details behind the activities documented on the business process map. They serve as a method for every employee to gain an understanding in their context of the process.

Purpose

To gather process skill in written form and to make it easier for everyone to do his/her work.

Questions To Ask When There Is Trouble with Procedures:  Do we have a standard procedure?  Does the employee know the standard procedure?  Does the employee use the standard procedure? (Do we enforce the standard

procedure?)

In Summary…  A procedure is a written agreement between an associate and the company regarding

how the job will be done.

Documentation – Procedures

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Pitfalls in Writing Procedures

 Not involving the affected persons in the creation of the procedures

 Not testing the procedures

 Omitting information

 Results to be obtained

 How to do a step

 Lowering the importance of procedures

 Not readily available

 Ignored by management

 No method to update procedures

 Obsolete procedures not destroyed

 Procedure documentation is not readily available

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Procedures Example Standardized Procedures

10

1.0 Activity: Conduct Market Analysis including Market Segmentation

 Description: Marketing group will gather market research information and conduct analysis including identification of competitor intelligence and market segmentation.

 Tools:  Various Market Research Reports  Buying Process and Market Map Tools

 Timing:  Within 3 weeks of market data availability

 Deliverable:  Buying process to uncover key customer behavioral objectives that we want to

change and one which will give the maximum leverage in driving business

 Responsibility:  Marketing Group taking the lead, but involving Sales

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Direct Ways  Observation

 Ask associates directly, “What difficulties do you have following the procedures? Are there any ways to make the work easier and get the results we need?”

Indirect Ways  Observe the last time the instruction was revised. If the instructions

have stayed the same for six months, do associates really use them?

Checking Procedures

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What you learned during this section:

 The purpose and importance of standards to effective Control

 The use and importance of documenting procedures

 Some of the keys to success and pitfalls with writing procedures

Summary of Section

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Control – Project Documentation

Solution Replication and Closure

Communicate Project Outcomes

Document and Standardize

Lean Six Sigma Training

Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl

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 Understand key considerations to making communication effective

 Understand the key elements of a Communication Plan

 Develop a Communication Plan

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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The #1 Reason communications efforts fail to achieve the level of understanding and influence intended is due to:

E-mails, large meetings, print announcements, and even videos alone tend to:  Be ignored  Fail to engage recipients in active thinking  Focus on “What’s in it for the company” rather

than credibly persuade “What’s in it for the individual”

Method of Communication

Effective Communication Reviewed

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 Have a clear message  Involve and engage your audience  Be candid  Demonstrate, don’t lecture  Follow up

Communication of the improvement project message should be 80% Face to Face meetings

80%

20%

Face to Face Company Wide

Project Communication Reviewed

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The Final Communication Plan should be developed once the documentation has been completed. The basic components of the Communication Plan include:

Target Audience:  Identify the project audience(s) - include internal and external stakeholder

groups.

The “What” (message):  Assess information needs - determine what groups need to know, want to know,

and expect. NOTE: Utilize project resources only on communicating information that contributes to success or where a lack of communication can lead to failure.

 Identify key project messages, announcements, that need to be delivered on the project outcomes.

When:

 Define when communications will be provided to the different stakeholder groups.

Developing a Communication Plan – What to Include

Communication Plan

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The Method:

 Identify the best media and methods available to communicate, e.g. face to face meetings, presentations, e-mail - remember people absorb information in different ways.

Owner:

 Assign responsibilities for creating and delivering the various types of communications. At this point, the process owner should be utilized to aid in communicating the project results.

Required Approval:

 Document the approval process needed for any of the communications.

Feedback Loop:

 Create internal and external feedback loops to help evaluate the effectiveness of communications.

Developing a Communication Plan – What to Include

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Audience What When Method Owner Required Approval

Feedback Loop

Leadership  Overview of Solutions

 Financial Benefits

Project End Date (October 1st)

Leadership Team Meeting

Black Belt / Green Belt and Process Owner

Sponsor Discussion

All employees Overview of Solutions

October 15th

Gallery Walk in Lunch Room

Black Belt / Green Belt and Team

Sponsor Feedback Cards

Operations Detailed Solutions

October 6th

Meeting Black Belt / Green Belt and Team

Sponsor Discussion

Communication Plan Example

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What you learned during this section:

 The key considerations to making communication effective

 The key elements of a Communication Plan

 How to develop a Communication Plan

Summary of Section

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Control – Project Documentation

Solution Replication and Closure

Communicate Project Outcomes

Document and Standardize

Lean Six Sigma Training

Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl

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 Understand the process of replicating opportunities from project solutions to other parts of the organization

 Understand the roles of the team and the process to transition the project outcomes to the process owner

By the end of this section, you will be able to:

Overview – Objectives – Key Topics

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Replication opportunities are key learnings and documented solutions that may be applicable to other processes or projects.

Looking for these opportunities can:

 Increase process improvement in other areas

 Reduce resource time solving similar problems

 Increase customer satisfaction in other areas of the business

Solution Replication Opportunities

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Look for replication opportunities across the organization that have similar processes

Solution Replication Opportunities – Organization

24

Level 1 Processing Processing Processing

Chicago London Singapore

Process Improvement Accomplished

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Look for replication opportunities across the “end to end” process either upstream or downstream

Level 3

Accounts Payable Process

Re plic

ate

Process Improvement Accomplished

Re pli

ca te

Solution Replication Opportunities – Process

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1. Identify existing improvement efforts or problems within the organization that relate to the process improvement outcomes of your project.

2. Develop a project charter summarizing problems and goals of the replication opportunity.

3. Develop a summary of the “just completed” project outcomes that include the following deliverables:  Lessons learned from project

 Project Charter

 Key metrics and how they link to potential replication opportunity

 All final project documentation (including control plan and dashboards for use as best practice sharing)

 Action plan with owners to transition project outcomes to new process

Solution Replication Opportunities – Process

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Once the process is in control, the final step of the project team is to transition the new process to the process owner.

The materials include:

All project outcomes

Project binders

Process monitoring plans

Training materials

Transition to Process Owner

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What Does Successful Transition Mean?

1. The process is completely integrated into the organization and under control.

2. The process owner has approved all deliverables and has agreed to take ownership of the project outcomes.

3. The process will be managed by the outcomes of the project, including all monitoring techniques defined in the Control Phase.

4. The project team is no longer needed to monitor and make adjustments to the process.

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Black Belt / Green Belt

 Ensure that an actionable, measurable and comprehensive Monitoring Plan is defined, communicated and implemented

 Jointly ensure that the handoff to the Process Owner is successful

Process Owner

Sponsor

Project Team

 Commit to own the project outcomes and Monitoring Plan  Designate the appropriate resources to manage the plan

 Ensure the project outcomes meet strategic objectives  Jointly ensure that the handoff to the Process Owner is

successful  Monitor the ongoing compliance to the Monitoring Plan

 Assist in designing and implementing the Monitoring Plan  If applicable, members of the team should assist the

Process Owner in managing the ongoing Monitoring Plan

Roles of a Successful Transition

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Once Transition is Complete, the Project Team Should Celebrate

Their Success

Celebrate Success

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What you learned during this section:

 The process of replicating opportunities from project solutions to other parts of the organization

 The roles of the team and the process to transition the project outcomes to the process owner

Summary of Section

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End of Lesson: Control – Project Documentation

Lean Six Sigma Training

Measure ControlAnalyze ImproveDefine ControlControlImproveMeasure ControlControlAnalyze ImproveImproveDefine ControlControl

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Lean Six Sigma Green Belt

Simulated Project Workbook This eBook is for personal use only. Please DO NOT use this eBook for presentations and training facilitation purposes.

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Simulated Project Overview

Welcome to the Lean Six Sigma Green Belt Simulated Project.

At Acuity Institute we recognize that not every individual has the opportunity to complete an actual Lean Six Sigma project while completing training, therefore we have created a real world simulated project that takes students from the beginning to the end of a problem and solution. The simulated project helps to build the students understanding of the concepts taught in training and provides practical application of the tools. Students complete the course better prepared to apply what they have learned in the real world.

The simulation is based on a hypothetical company (Simco International or “SI”) that faces many of the same problems companies are dealing with today. The simulation is designed to illustrate the entire business improvement effort through every phase of the Lean Six Sigma DMAIC methodology. Students complete challenging exercises (project deliverables) which build on previously learned tools and concepts taught in training. When complete, students have a significant perspective on what true business improvement means and a tangible “project story” that they can utilize throughout their process improvement journey.

There is no comparison to Acuity Institute’s Simulated Project in the marketplace.

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Simulated Project Deliverables Acuity Institute’s Lean Six Sigma Green Belt Simulated Project includes 32 project deliverables which are introduced throughout the DMAIC Methodology.

Define Measure Analyze Improve Control

1. Project Charter Development

2. SIPOC 3. As-Is Process

Mapping 4. Quick Win

Opportunities 5. Identify

Stakeholders 6. Develop

Stakeholder Map 7. Stakeholder

Management Plan 8. Communication

Plan 9. VOC Questions 10.CTQ Determination

11. Operational Definitions

12. Data Collection Planning

13. Histogram 14. Run Chart 15. Control Chart 16. Sigma

Performance (DPMO)

17. Cause and Effect Analysis

18. Lean Process Analysis

19. Pareto 20. Box Plots 21. Correlation

Analysis 22. Regression

Analysis

23. Solution Selection Matrix

24. Cost/Benefit Analysis

25. Mitigating Risks (FMEA)

26. Pilot Plan 27. Implementation

Planning 28. Storyboarding

29. Process Monitoring Plan

30. Dashboard Development

31. Response Planning

32. Final Project Storyboard

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Simulated Project Templates

There are “blank” templates for you to complete for all 32 Simulated Project deliverables. The templates are located in the “LSS GB_SI Project Templates” file folder. The templates are developed in common formats (MS Word, MS Excel, or MS PowerPoint). To access the templates you will need to download this file folder onto your computer.

For your reference, the name of the specific template that you are to complete is included in the instructions of the project deliverable you are working on (example: “SI Project Template: Project Charter Development_SI”). Please note, answers are provided as a reference point for many of the project deliverables. In most cases we do not recommend updating your answers to match the answers provided. It is important for your answers to be authentic to your experience as you complete the Simulated Project.

In addition to the project templates, the “LSS GB_SI Project Templates” file folder also contains the MS Excel file “LSS SI Data File”. This file includes data to be used for various Simulated Project deliverables. This course includes step by step instructions on how to complete these deliverables using both SigmaXL and Minitab statistical analysis software.

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Lean Six Sigma – Simco International

Define Phase 1

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Simco International – Define Phase Deliverables

Deliverable Page Lesson (Deliverable Originated From)

Project Charter Development 3 Project Charter SIPOC 10 Process Definition As-Is Process Mapping 15 Process Definition Quick Win Opportunities 21 Process Definition Identify Stakeholders 26 Stakeholder Management Develop Stakeholder Map 31 Stakeholder Management Stakeholder Management Plan 36 Stakeholder Management Communication Plan 41 Stakeholder Management VOC Questions 46 Voice of Customer CTQ Determination 51 Voice of Customer

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Lean Six Sigma – Project Simulation

Project Charter Development

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Objective  Develop key sections of a Project Charter for the Simco International (SI) Consumer Home

Loan project.

Instructions  Utilize the information from the Simco International Overview information on the following

pages to draft the following Project Charter elements in the worksheet below:  Problem Statement  Project Goals

 Prepare your findings.

PROJECT DESCRIPTION

Problem Statement

Project Goals

Project Charter Development

SI Project Template: Project Charter Development_SI

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Simco International “SI” is a global financial services company that conducts business in 84 different countries. During the past 2 years SI has fallen from the 3rd largest financial services provider to 6th in the world. The primary reason for this decline is poor customer service which is driving customers to SI’s competition.

SI recently formed multiple Lean Six Sigma teams to address their customer service issues. In selecting the Lean Six Sigma projects, SI studied their organization to learn where customer expectations were being least met. Through this process they learned that their Global Consumer Home Loan division was performing well below customer expectations, therefore the “Home Loan” Lean Six Sigma project was initiated.

Simco International Overview

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During the pre-project research, SI learned that it required an average of 22 days to process home loans. Their competition was completing the same process in 15 days. The process time of 15 days was what home loan customers consider to be Critical to Quality (CTQ). By not meeting the CTQ of 15 days, SI estimated that it was losing $26.2 million in lost revenues and $2.4 million in process inefficiencies per year.

The primary goal of the “Home Loan” Lean Six Sigma team is to meet customer expectations for consumer home loans throughout the world. If the team achieves this goal, they believe that they will be well positioned to re-capture market share, increase revenues, and improve customer satisfaction.

Simco International Overview

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Please Do Not Proceed Forward

Project Charter Development

7

For additional information about this concept, see

Lesson 3 Project Charter, in the Project Charter section.

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When you see this symbol, please do not continue forward in the materials.

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PROJECT DESCRIPTION Business Case Increasing customer satisfaction will assist SI to re-capture market

share and ultimately increase revenues while improving process efficiencies.

Problem Statement The Global Consumer Home Loan process cycle time currently averages 22 days to complete, which exceeds customer expectation by 7 days.

Project Goals Reduce the Consumer Home Loan process cycle time by 32% by September 1st. Improve process accuracy by 50%.

Estimated Benefits ($$) Increased revenues by $20 million and reduced process costs by $650,000.

Project Scope Area of Focus:

Consumer Home Loan processes in Singapore, Chicago, and London.

Includes: Home Loan Customer, Real Estate Agent, Underwriting, Credit Agency, processing of application, and approval/denial of home loan

Excludes: Accounts Payables and Receivables, re-finance processes

Start Point: When a customer requests a loan

Stop Point: Home loan acceptance or rejection package is received by the customer

SI Project Charter

* Additional Project Charter information has been provided for your reference. 8

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PROJECT RESOURCES

Team Members Function in the Business Project Role Time Dedicated to Project (Hrs/Week)

John Davis VP of Operations Sponsor 1-2

Susan Terrell Performance Improvement Expert Master Black Belt 2

Steve McCaffrey Project Manager Black Belt / Green Belt 25

Ellen Mobley Finance Team Member 8-16

Rod Elway Operations SME Team Member 8-16

Erin Anderson Processing SME Team Member 8-16

Owen Atwater Sales SME Team Member 8-16

Additional Support Legal, Compliance, Information Technology, External Business Partners

PROJECT MILESTONES

Milestone Phase Start Date Completion Date

Define January 1st In Progress

Measure April 1st June 15th

Analyze June 1st June 30th

Improve July 1st July 31st

Control August 1st August 30th

Closure August 30th September 30th

SI Project Charter

* Additional Project Charter information has been provided for your reference.

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SIPOC

Lean Six Sigma – Project Simulation

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Objective  Develop a SIPOC for the SI Consumer Home Loan process.

Instructions  Complete the worksheet on the following page by utilizing the SI Overview

and Project Charter to develop the SIPOC.  Prepare your findings.

SIPOC

SI Project Template: SIPOC_SI

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Utilize the SI Overview and Project Charter to complete each element of the SIPOC diagram.

Suppliers Inputs Process Outputs Customers

• • 1. • •

• • 2. • •

• • 3. • •

• • 4. • •

SIPOC

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Notes: Tips in SIPOC completion: - Brainstorm information that is common to all home loan processes. - Work backwards when completing the SIPOC. - Start by identifying the customers first, then the process outputs. - Identify the process start and stop points, then complete the remaining steps (you can identify more than the 4 high-level steps provided if needed). - Finally, define the inputs and suppliers. - The suppliers may be the customers as well.

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Please Do Not Proceed Forward

SIPOC

13

For additional information about this concept, see

Lesson 5 Process Definition, in the SIPOC

section.

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Suppliers Inputs Process Outputs Customers

• Home Loan Customer

• Application 1.Receive Application

• Home Loan Acceptance Package

• Home Loan Customer

• Real Estate Agents (Partners)

• Customer Information (Bank, Employment, etc.)

2.Complete Application Process

• Home Loan Rejection Package

• Real Estate Agents (Partners)

• Credit Agency

• Credit Score 3.Complete Underwriting Process

• Loan Products

4.Send Notification

SI SIPOC

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As-Is Process Mapping

Lean Six Sigma – Project Simulation

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Objective  Develop the as-is process map for the SI Consumer Home Loan process.

Instructions  Using the description of the SI Consumer Home Loan process on the

following page, develop a deployment flow chart process map.  Document each step in the process  Align the steps with the personnel (deployment flow chart)

 Prepare your findings.

As-Is Process Mapping

SI Project Template: As Is Process Mapping_SI

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Primary People and Departments Involved in the SI Home Loan Process  Home Loan Customer  Real Estate Agent (RA)

Home Loan Process Flow The SI Consumer Home Loan process starts when a customer contacts a Real Estate Agent (RA) to request a loan. The RA’s are located across the country. The RA mails the customer a home loan application which is to be completed and mailed back to the RA. The RA forwards the application to their local SI Mortgage Sales Associate (MSA). The MSA’s are organized by region. The MSA forwards the application to an SI Loan Processor (LP). There are LP’s in every local SI office. The LP reviews the application. The LP contacts the customer to request additional information (bank info, employment info, etc.). The customer gathers the additional information and mails it to the LP. With the additional information, the LP reviews the application and additional information to ensure that it is complete. If there is missing or incorrect information, the LP contacts the customer to make the necessary corrections. If the information is correct, the LP forwards the information to an SI Loan Officer (LO). There are LO’s in every local SI office. Certain LO’s are responsible for managing each of the Local SI offices. The LO reviews the customer information to determine the loan qualifications for final determination (acceptance or rejection). When this is complete, the LO forwards the final determination to the LP. If the loan is accepted, the LP creates an SI “Home Loan Acceptance Package”. If the loan is rejected, the LP creates an SI “Home Loan Rejection Package”. When this is complete, the LP forwards the final determination package to the MSA. When the MSA receives the package they schedule a meeting with the RA to review the final determination package. The RA reviews the final determination package. The RA sends the final determination package to the customer. When the customer receives the final determination package the SI Consumer Home Loan process is complete.

 SI Mortgage Sales Associate (MSA)  SI Loan Processor (LP)

 SI Loan Officer (LO)

As-Is Process Mapping

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Notes: Tips in sub-process mapping: - Clarify the boundaries of the process first by identifying the start and stop points. - Document (brainstorm) the steps/activities that occur during the process. - Combine and eliminate any duplicate process steps that team members repeated. - Organize steps into logical order using the direction of flow arrows.

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As-Is Process Mapping

18

For additional information about this concept, see

Lesson 5 Process Definition, in the Process

Mapping section.

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Simco International “As-Is” Process Map (Page 1)

Re al

Es

ta te

Ag

en t

(R A)

SI M

or tg

ag e

Sa le

s As

so cia

te

( M SA

)

SI L

oa n

Pr oc

es so

r (L

P)

SI L

oa n

O ffi

ce r

(L O

)

Ho m

e Lo

an

Cu st

om er

Contact RA to request loan

Mail loan application to

customer

Complete loan application

Mail loan application to

RA

Forward application to

MSA

Forward application to

LP

Review application

Request additional info from customer

Gather additional

information

Mail additional information to

LP

Go to Step 12 (Next Page)

Review application

and additional information

1

2

3 4

5

6

7 8

9 10

11

SI As-Is Process Map

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Notes: The above process map is known as a Deployment Flow Chart (DFC). A DFC is a type of process map. It is a graphical display of the actions and activities of a business process and their alignment with resources. DFC’s are particularly helpful when multiple and diverse groups have accountability in the process being managed.

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Simco International “As-Is” Process Map (Page 2)

SI L

oa n

O ffi

ce r

(L O

)

SI L

oa n

Pr oc

es so

r (L

P)

SI M

or tg

ag e

Sa le

s As

so cia

te

(M SA

)

Re al

Es

ta te

Ag

en t

(R A)

Ho m

e Lo

an

Cu st

om er

Go to Step 8 (Previous Page)

Is info complete?

Forward customer info

to LO

Determine loan

qualification

Send final determination

to LP

Is loan accepted?

Create SI Home Loan acceptance

package

Create SI Home Loan

rejection package

Forward final determination

package to MSA

Schedule meeting with RA to review final package

Review final package

Send final package to customer

Receive final determination

package

Yes

No No

Yes 12

13

14 15

16 17

18 19

20

21 22

23

SI As-Is Process Map

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Quick Win Opportunities

Lean Six Sigma – Project Simulation

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Objective  Identify Quick Wins for the SI Consumer Home Loan process.

Instructions  Using the worksheet on the following page, utilize the outcomes of your

charter, SIPOC, and process mapping to identify quick wins.  Brainstorm a few opportunities for quick improvements to the process  Complete the remaining sections by answering “Yes” or “No” to each

category  Decide on the Quick Wins based on your analysis

 Prepare your findings.

Quick Win Opportunities

SI Project Template: Quick Win Opportunities_SI

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Quick Win Opportunity

Easy to Implement

Reversible Fast to Implement

Within Team’s Control

Cheap to Implement

Quick Win Opportunities

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Quick Win Opportunities

24

For additional information about this concept, see

Lesson 5 Process Definition, in the Quick Wins

section.

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Quick Win Opportunity

Easy to Implement

Reversible Fast to Implement

Within Team’s Control

Cheap to Implement

Have application mailed directly to LP from Customer

Yes Yes Yes Yes Yes

Have application completed with LP via phone, remove paper application

Yes Yes No Yes No

Gather additional information from customer via phone

Yes Yes Yes Yes Yes

Remove MSA Position from process

Yes No No No Yes

Have LP determine loan qualification

No Yes No No Yes

SI Quick Win Opportunities

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Identify Stakeholders

Lean Six Sigma – Project Simulation

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Objective  Develop a list of Stakeholders for the SI Consumer Home Loan project.

Instructions  Using the list of potential stakeholders below, complete the worksheet on the following page

to identify the actual stakeholders of the SI process  Identify stakeholders by name  Determine the stakeholder type: external, internal, or supplier

 Prepare your findings.

Name Function / Organization Name Function / Organization

John Davis VP, Operations/Sponsor Susan Terrell MBB

Jason Cody IT Systems Analyst Sean White Compliance Officer

Vince Joseph VP, Accounts Payable Lori Emtman Equifax Credit Agency

Home Loan Customers NA Chris Simms VP, Sales

Barbara Kissinger VP, Processing Steven O’Malley Loan Officer

Sandra Williams Real Estate Agent, Chicago Lynn Washington Real Estate Agent, Los Angeles

Xiu Len Real Estate Agent, Singapore Mark Clayton Real Estate Agent, London

Petra Lubiwitz VP, Underwriting Davin Carter Accounts Payable Rep

Identify Stakeholders

SI Project Template: Identify Stakeholders_SI 27

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Identify Stakeholders

Stakeholder Name Type

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Identify Stakeholders

29

For additional information about this concept, see Lesson 6 Stakeholder Management, in the Stakeholder Analysis

section.

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Stakeholder Name Type Lori Emtman (Equifax Credit Agency) Supplier Sandra Williams (Real Estate Agent, Chicago) Supplier/External Xiu Len (Real Estate Agent, Singapore) Supplier/External Mark Clayton (Real Estate Agent, London) Supplier/External Lynn Washington (Real Estate Agent, Los Angeles) Supplier/External John Davis (VP, Operations/Sponsor) Internal Chris Simms (VP, Sales) Internal Barbara Kissinger (VP, Processing) Internal Steven O’Malley (Loan Officer) Internal Petra Lubiwitz (VP, Underwriting) Internal Jason Cody (IT Systems Analyst) Internal Vince Joseph (VP, Accounts Payable) Internal Susan Terrell (MBB) Internal Sean White (Compliance Officer) Internal Davin Carter (Accounts Payable Rep) Internal Home Loan Customers External

SI Stakeholders

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Develop Stakeholder Map

Lean Six Sigma – Project Simulation

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Objective  Develop a Stakeholder Map for the SI Consumer Home Loan project.

Instructions  Using the summary developed by the team on their current perceptions of the stakeholders

on the project, complete the stakeholder map on the following page.  Prepare your findings.

Name Influence Impact of Change Perception on Project 1. Lori Emtman Low Low Has heard about it and wants problem solved

2. Sandra Williams Medium High Has been calling team members about project status

3. Xiu Len Low High Not aware of project or Lean Six Sigma

4. Mark Clayton Medium High Has resisted change in the past

5. John Davis High High Very supportive and engaged in project

6. Chris Simms High Medium Understands need, wants to know more

7. Barbara Kissinger High High Has expressed dissatisfaction with scope

8. Steven O’Malley Medium Medium Wanted to participate on team

9. Petra Lubiwitz Low Medium Was involved in drafting original charter

10.Home Loan Customers Low High Not aware of project

Develop Stakeholder Map

SI Project Template: Develop Stakeholder Map_SI

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In flu

en ce

Impact of change

H

M L

L M H

Enthusiast

Neutral

Opponent

Develop Stakeholder Map

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Develop Stakeholder Map

34

For additional information about this concept, see Lesson 6 Stakeholder Management, in the Stakeholder Analysis

section.

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In flu

en ce

Impact of change

H

M L

L M H

1

2

3

4

56 7

8

9 10

Enthusiast

Neutral

Opponent

SI Stakeholder Map

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Stakeholder Management Plan

Lean Six Sigma – Project Simulation

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Objective  Develop a Stakeholder Management Plan for the SI Consumer Home Loan

project.

Instructions  Using the Stakeholder Map from the previous deliverable, use the worksheet

on the following page to develop a management plan for the stakeholders you select.  Which stakeholders need to be influenced?  How will this occur?

 Prepare your findings.

Stakeholder Management Plan

SI Project Template: Stakeholder Management Plan_SI

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Stakeholder Objective Actions

Stakeholder Management Plan

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Stakeholder Management Plan

39

For additional information about this concept, see Lesson 6 Stakeholder Management, in the Stakeholder Analysis

section.

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Stakeholder Objective Actions Completion Date

Owner

#5 Utilize influence with #7 to help gain support

Review charter Discuss help needed in working

with #7

March 2nd Steve M.

#7 Gain support in processing department Help sell project

to associates

Schedule one-on-one meeting to review project charter and scope Discuss communication support

needed in Processing Gain commitment for support

March 3rd Erin A.

#4 Overcome resistance to project initiative

Schedule one-on-one meeting to review project charter  Take feedback and initiate follow-

up meeting Escalate if necessary

March 15th Rod E.

#3, #6. #10 Gain understanding of project

Schedule one-on-one meeting to review project charter  Take feedback and initiate follow-

up meeting Gain commitment for support

March 15th Steve M.

SI Stakeholder Management Plan

* Additional Stakeholder Management Plan information has been provided for your reference. 40

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Communication Plan

Lean Six Sigma – Project Simulation

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Objective  Develop a Communication Plan for the SI Consumer Home Loan project.

Instructions  Use the worksheet on the following page to develop a communication plan for

the target audience(s) for the project.  Who needs to receive communication about the project?  What kind of information will be communicated?  When/how often will communication take place?  What will be the method of delivery?

 Prepare your findings.

Communication Plan

SI Project Template: Communication Plan_SI

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Audience What When Method

Communication Plan

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Communication Plan

44

For additional information about this concept, see Lesson 6 Stakeholder Management, in the

Communication Planning section.

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Audience What When Method Owner Required Approval

Feedback Loop

Champion / Sponsor

 Status Reports  Milestones  Obstacles /

Resources  Scope Reviews

Bi-Monthly / As Needed

 Face to Face Project Lead MBB Minutes from Meeting

Stakeholders  Status Reports  Milestones

Completion of Phases / As Needed

 Face to Face  Memo’s/Email

Owners on Stakeholder Management Plan

Champion / Sponsor / MBB

Minutes from Meeting

MBB  Status Reports  Milestones  Obstacles /

Resources  Scope Reviews

Bi-Monthly / As Needed

 Face to Face Project Lead None Minutes from Team Meeting

Legal / Compliance / Finance / IT

 Status Reports As Needed  Face to Face  Department

Meeting

Project Lead MBB Minutes from Meeting

Organization (Sales, Processing, Underwriting)

 Project Results End of Project  Email  Town Hall

Project Team Champion / Sponsor / MBB

Surveys

Customers / Credit Agencies

 Update New Process

End of Project  Update Materials Real Estate Agents

Champion / Sponsor /MBB

Surveys

SI Communication Plan

* Additional Communication Plan information has been provided for your reference.

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VOC Questions

Lean Six Sigma – Project Simulation

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Objective  Develop a list of VOC questions for the SI Consumer Home Loan process.

Instructions  Using the worksheet on the following page, develop a list of VOC questions

you feel will gather information on SI’s customer requirements.  Prepare your findings.

VOC Questions

SI Project Template: VOC Questions_SI

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Brainstorm 5-7 SI VOC Questions (Be as detailed as possible)

VOC Questions

VOC Questions

1.

2.

3.

4.

5.

6.

7.

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Notes: Defining the right questions to ask customers can be difficult. Being too broad with questions can lead to non-measurable responses. However, being too specific can direct customer responses and lead to narrow issue identification. Make sure your questions have a good mix of open-ended (i.e. summary or free form) and close-ended (i.e. rating 1 through 4) criteria. Another pit fall in collecting VOC is to utilize the questions to collect data on the existing process. Try and avoid questions that will identify the current performance or roles within the process. This information will be determined in the Measure Phase.

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VOC Questions

49

For additional information about this concept, see

Lesson 7 Voice of Customer, in the What is

Voice of Customer section.

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Example SI VOC Questions

1. How long did it take for you to receive your Home Loan?

2. On a scale of 1-4, with 1 being completely dissatisfied and 4 being completely satisfied, how satisfied were you with this time?

3. What would have been an acceptable timeframe to receive your Home Loan?

4. On a scale of 1-4, with 1 being completely dissatisfied and 4 being completely satisfied, how satisfied were you with your overall Home Loan experience?

5. Why did you rate your experience this way?

6. Did SI fail to meet your service expectations in any way?

SI VOC Questions

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CTQ Determination

Lean Six Sigma – Project Simulation

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Objective  Identify “Customer Needs” and “CTQ’s” for the SI Consumer Home Loan

process.

Instructions  Using the worksheet on the following page, identify the remaining “Customer

Needs” from the “Customer Issues” listed. Once complete, translate the “Customer Needs” into “CTQs”.

 Prepare your findings.

CTQ Determination

SI Project Template: CTQ Determination_SI

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Translate the following VOC into CTQ’s

Segment Customer Issue Customer Need CTQ

External It takes too long to process loans Reduce loan processing cycle time

15 day loan processing cycle time

External There are too many errors on the final determination packages

Reduce errors on final determination package

100% accuracy on final determination package

External It is very difficult to reach anyone at SI

Internal No clear roles and responsibilities to who owns the loan process

Internal Too much time is spent reviewing the application

CTQ Determination

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Notes: Tips in CTQ determination: - Document the need, not the solution (this is done in the Improve Phase). - Use measurable terms. - Avoid words like “should” or “must”. Utilize the previous pages as a guide for CTQ determination.

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CTQ Determination

54

For additional information about this concept, see

Lesson 7 Voice of Customer, in the How to

Translate VOC into CTQs section.

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Segment Customer Issue Customer Need CTQ

External It takes too long to process loans Reduce loan processing cycle time

15 day loan processing cycle time

External There are too many errors on the final determination packages

Reduce errors on final determination package

100% accuracy on final determination package

External It is very difficult to reach anyone at SI

First call contact with SI personnel

100% first call contact

Internal No clear roles and responsibilities to who owns the loan process

Clearly defined and documented roles and responsibilities

100% documentation of roles and responsibilities

Internal Too much time is spent reviewing the application

Reduce loan reviewing time

2 day loan reviewing time

SI CTQ Determination

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Lean Six Sigma – Simco International

Measure Phase 1

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Simco International – Measure Phase Deliverables

Deliverable Page Lesson (Deliverable Originated From)

Operational Definitions 3 Data Collection Data Collection Planning 8 Data Collection Histogram 13 Describe & Display Data Run Chart 20 Describe & Display Data Control Chart 27 Describe & Display Data Sigma Performance (DPMO) 34 Baseline Performance

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Operational Definitions

Lean Six Sigma – Project Simulation

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Objective  Develop operational definitions for some of the measures identified in the X/Y

Matrix for the Consumer Home Loan process.

Instructions  Using the worksheet on the following page, develop specific operational

definitions for each measure identified.  Prepare your findings.

Operational Definitions

SI Project Template: Operational Definitions_SI

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% of Defective Incoming Applications

Application Cycle Time per Department Segment

# of Final Determination Packages with Errors

Total Loan Processing Cycle Time

Operational DefinitionPerformance Measure

Operational Definitions

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Operational Definitions

6

For additional information about this concept, see

Lesson 10 Data Collection, in the Operational Definitions section.

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Performance Measure Operational Definition

Total Loan Processing Cycle Time

The total time in business days from when a customer submits the application to when the loan is mailed by location

# of Final Determination Packages with Errors

The total # of final determination packages that have an inaccurate field by defect type (name, address, loan #, loan amount, loan duration, city, state) from total packages processed

% of Defective Incoming Applications

The total # of applications that are inaccurate (by type) or incomplete when received from the customer divided by the total # of applications received

Application Cycle Time Per Department Segment

The total time in business days to complete the application processing per department (RA, MSA, LP, LO)

SI Operational Definitions

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Data Collection Planning

Lean Six Sigma – Project Simulation

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Objective  Develop a data collection plan for the SI Consumer Home Loan process.

Instructions  Using the worksheet on the following page, develop a data collection plan for

the performance measures previously identified.  Prepare your findings.

Data Collection Planning

SI Project Template: Data Collection Planning_SI

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Measure Type of Measure

Type of Data

Operational Definitions Sampling Display

Total Loan Processing Cycle Time

The total time in days from when a customer submits the application to when the loan is mailed by location; Time stamp calculation in SI database

SI Database: Sample of 105 Loans (1/1- 3/31) from Chicago, London, Singapore

Histogram, Run Chart, Control Chart

# of Final Determination Packages with Errors

The total # of final determination packages that have an inaccurate field by defect type (name, address, loan #, loan amount, loan duration, city, state) from total packages processed; Check Sheet completed by associates

Real Time: Sample of 240 Determination Packages (April) from Chicago, London, Singapore

Pareto

% of Defective Incoming Applications

The total # of applications that have an inaccurate field (by type) or incomplete when received from the customer divided by the total # of applications received; Check Sheet completed by associates

Real Time: Sample of 240 Applications (April) from Chicago, London, Singapore

Pareto

Application Cycle Time Per Department Segment

The total time in days to complete the application processing per department (RA, MSA, LP, LO); Time stamp calculation in SI database

SI Database: Sample of 105 Applications (1/1-3/31) from Chicago, London, Singapore

Histogram, Run Chart, Control Chart; Pareto by department

Data Collection Planning

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Data Collection Planning

11

For additional information about this concept, see

Lesson 10 Data Collection, in the Collecting Data

section.

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Measure Type of Measure

Type of Data

Operational Definitions Sampling Display

Total Loan Processing Cycle Time

Output Continuous The total time in days from when a customer submits the application to when the loan is mailed by location; Time stamp calculation in SI database

SI Database: Sample of 105 Loans (1/1- 3/31) from Chicago, London, Singapore

Histogram, Run Chart, Control Chart

# of Final Determination Packages with Errors

Output Discrete The total # of final determination packages that have an inaccurate field by defect type (name, address, loan #, loan amount, loan duration, city, state) from total packages processed; Check Sheet completed by associates

Real Time: Sample of 240 Determination Packages (April) from Chicago, London, Singapore

Pareto

% of Defective Incoming Applications

Input Discrete The total # of applications that have an inaccurate field (by type) or incomplete when received from the customer divided by the total # of applications received; Check Sheet completed by associates

Real Time: Sample of 240 Applications (April) from Chicago, London, Singapore

Pareto

Application Cycle Time Per Department Segment

Process Continuous The total time in days to complete the application processing per department (RA, MSA, LP, LO); Time stamp calculation in SI database

SI Database: Sample of 105 Applications (1/1-3/31) from Chicago, London, Singapore

Histogram, Run Chart, Control Chart; Pareto by department

SI Data Collection Plan

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Histogram

Lean Six Sigma – Project Simulation

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Objective  Create a Histogram from the Chicago Total Loan Processing Cycle

Time data and conduct initial analysis.

Instructions  Open up the Excel file “LSS SI Data File”.

The data set is in the worksheet “Chicago Cycle Time”. Utilize your statistical software to display and describe the variation in the process using a “Histogram.”

 When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Histogram and

descriptive statistics?

Histogram

SI Project Template: Histogram_SI

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Histogram

15

For additional information about this concept, see Lesson 11 Describe and

Display Data, in the Understanding Variation

section.

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Histogram SigmaXL Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is in the worksheet “Chicago Cycle Time”.  We want to display and describe the variation in the process. Follow these instructions to create the Histogram: 1. Select “SigmaXL" from the toolbar in Excel 2. Select “Graphical Tools” from the menu 3. Select “Histograms & Descriptive Statistics” from the menu 4. Select “Use entire data table” from the data window 5. Select “Next" 6. Select “Numeric Data Variables (Y)” to move the Chicago Loan Processing Cycle

Time data set into the function window 7. Select "OK" 8. SigmaXL will generate a new worksheet "Hist Descript"

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SI Histogram SigmaXL Results

* Additional information is provided (which we do not always use) when you perform this analysis.

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Notes: SI Team Analysis - Large variation and spread in cycle time - No data points are below the CTQ of 15 days - 2 loans took considerably more time to complete than the rest of the data set - Data is non-normal as identified by the p-value less than 0.05 from the Anderson-Darling Normality Test

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SI Histogram Minitab Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is in the worksheet “Chicago Cycle Time”.  We want to display and describe the variation in the process. Follow these instructions to create the Histogram: 1. Copy the entire data set including the header 2. Open the Minitab software 3. Paste the data set into Column 1 (C1) of Minitab 4. Select “Paste as a single column” 5. Select “OK” 6. Select “Stat” from the toolbar 7. Select “Basic Statistics” from the menu 8. Select “Graphical Summary” from the menu 9. Highlight “C1 Chicago Loan” from the menu 10. Click on "Select” 11. Select "OK" 12. Minitab will generate a summary with the Histogram and descriptive statistics for

Chicago Cycle Time

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SI Histogram Minitab Results

* Additional information is provided (which we do not always use) when you perform this analysis. 19

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Notes: SI Team Analysis - Large variation and spread in cycle time - No data points are below the CTQ of 15 days - 2 loans took considerably more time to complete than the rest of the data set - Data is non-normal as identified by the p-value less than 0.05 from the Anderson-Darling Normality Test

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Run Chart

Lean Six Sigma – Project Simulation

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Objective  Create a Run Chart from the Chicago Total Loan Processing Cycle Time

data and conduct initial analysis.

Instructions  Open up the Excel file “LSS SI Data File”.

The data set is in the worksheet “Chicago Cycle Time”. Utilize your statistical software to display and describe the variation in the process using a “Run” chart.

 When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Run Chart?

Run Chart

SI Project Template: Run Chart_SI

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Run Chart

22

For additional information about this concept, see Lesson 11 Describe and

Display Data, in the Types of Variation section.

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Run Chart SigmaXL Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is in the worksheet “Chicago Cycle Time”.  We want to display and describe the variation in the process. Follow these instructions to create the Run Chart: 1. Select “SigmaXL" from the toolbar in Excel 2. Select “Graphical Tools” from the menu 3. Select “Run Chart” from the menu 4. Select “Use entire data table” from the data window 5. Select “Next" 6. Select “Numeric Data Variables (Y)” to move the Chicago Loan Processing Cycle

Time data set into the function window 7. Select “Show Mean” 8. Select “OK” 9. SigmaXL will generate a new worksheet “Run Chart"

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SI Run Chart SigmaXL Results

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Notes: SI Team Analysis - Large variation and spread in cycle time - 2 loans took considerably more time to complete than the rest of the data set - Cycle time is not trending upwards or downwards

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Run Chart Minitab Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is in the worksheet “Chicago Cycle Time”.  We want to display and describe the variation in the process. Follow these instructions to create the Run Chart: 1. Copy the entire data set including the header 2. Open the Minitab software 3. Paste the data set into Column 1 (C1) of Minitab 4. Select “Paste as a single column” 5. Select “OK” 6. Select “Stat” from the toolbar 7. Select “Quality Tools” from the menu 8. Select “Run Chart” from the menu 9. Select “Subgroups across rows of” from the menu 10. Click inside the data box 11. Highlight “C1 Chicago Loan” from the menu 12. Click on "Select” 13. Select "OK" 14. Minitab will generate a summary with the Run Chart and descriptive statistics for Chicago Cycle

Time

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SI Run Chart Minitab Results

* Additional information is provided (which we do not always use) when you perform this analysis.

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Notes: SI Team Analysis - Large variation and spread in cycle time - 2 loans took considerably more time to complete than the rest of the data set - Cycle time is not trending upwards or downwards

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Control Chart

Lean Six Sigma – Project Simulation

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Objective  Create a Control Chart from the Singapore Total Loan Processing

Cycle Time data and conduct initial analysis.

Instructions  Open up the Excel file “LSS SI Data File”.

The data set is in the worksheet “Singapore Cycle Time”. Utilize your statistical software to display and describe the variation in the process using an “Individuals & Moving Range” control chart.

 When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Individuals & Moving

Range control chart and special cause tests?

Control Chart

SI Project Template: Control Chart_SI

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Control Chart

29

For additional information about this concept, see Lesson 11 Describe and

Display Data, in the Types of Variation section.

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When you see this symbol, please do not continue forward in the materials.

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Control Chart SigmaXL Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is in the worksheet “Singapore Cycle Time”.  We want to display and describe the variation in the process. Follow these instructions to create the Control Chart: 1. Select “SigmaXL" from the toolbar in Excel 2. Select “Control Charts” from the menu 3. Select “Individuals & Moving Range” from the menu 4. Select “Use entire data table” from the data window 5. Select “Next" 6. Select “Numeric Data Variables (Y)” to move Singapore Cycle Time data set into the

function window 7. Select “Tests for Special Causes” 8. Select “OK” 9. SigmaXL will generate a new worksheet “Indiv & MR Charts“

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SI Control Chart SigmaXL Results

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Notes: SI Team Analysis - Process is not in statistical control due to failing one of the tests for special cause variation (4 out of 5 points more than 1 standard deviation from center line, on one side of center line)

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Control Chart Minitab Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is in the worksheet “Singapore Cycle Time”.  We want to display and describe the variation in the process. Follow these instructions to create the Control Chart: 1. Copy the entire data set including the header 2. Open the Minitab software 3. Paste the data set into Column 1 (C1) of Minitab 4. Select “Paste as a single column” 5. Select “OK” 6. Select “Stat” from the toolbar 7. Select “Control Charts” from the menu 8. Select “Variables Charts for Individuals” from the menu 9. Select “I-MR” menu 10. Highlight “C1 Singapore Cycle Time” from the menu 11. Click on "Select” 12. Select “I-MR Options…” 13. Select “Tests” 14. Select “Perform all tests for special causes” from the drop down menu 15. Select “OK” 16. Select "OK" 17. Minitab will generate the I-MR Charts for Singapore Cycle Time

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SI Control Chart Minitab Results

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Notes: SI Team Analysis - Process is not in statistical control due to failing one of the tests for special cause variation (4 out of 5 points more than 1 standard deviation from center line, on one side of center line)

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Sigma Performance (DPMO)

Lean Six Sigma – Project Simulation

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Objective  Calculate Sigma Performance for Chicago Final Determination Package accuracy.

Instructions  Utilize the information below and complete the fields for Units, Defects, and Opportunities.

 Total number of loans = 240  Total number defects = 72  Total number of critical fields to customer = 7

 Calculate the DPMO and Sigma for accuracy. Sigma can be found on the abridged sigma table on the following page.

 Prepare your findings.

DPMO = 1M Units x Opportunities

Defects

_______ Units

_______ Defects

_______ Opportunities

_____________ DPMO

_____________ Sigma

( ) ( ) ( )=

Sigma Performance (DPMO)

SI Project Template: Sigma Performance_SI

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Yield Sigma DPMO Yield Sigma DPMO 99.99966% 6.00 3.4 98.60966% 3.70 13,903 99.99946% 5.90 5.4 98.21356% 3.60 17,864 99.99915% 5.80 8.5 97.72499% 3.50 22,750 99.99867% 5.70 13 97.12834% 3.40 28,717 99.99793% 5.60 21 96.40697% 3.30 35,930 99.99683% 5.50 32 95.54345% 3.20 44,565 99.99519% 5.40 48 94.52007% 3.10 54,799 99.99277% 5.30 72 93.31928% 3.00 66,807 99.98922% 5.20 108 91.92433% 2.90 80,757 99.98409% 5.10 159 90.31995% 2.80 96,800 99.97674% 5.00 233 88.49303% 2.70 115,070 99.96631% 4.90 337 86.43339% 2.60 135,666 99.95166% 4.80 483 84.13447% 2.50 158,655 99.93129% 4.70 687 81.99519% 2.40 184,060 99.90323% 4.60 968 78.81446% 2.30 211,855 99.86501% 4.50 1,350 75.80363% 2.20 241,964 99.81342% 4.40 1,866 72.57469% 2.10 274,253 99.74449% 4.30 2,555 69.14625% 2.00 308,538 99.65330% 4.20 3,467 65.54217% 1.90 344,578 99.53388% 4.10 4,661 61.79114% 1.80 382,089 99.37903% 4.00 6,210 57.92597% 1.70 420,740 99.18025% 3.90 8,198 53.98278% 1.60 460,172 98.92759% 3.80 10,724 50.00000% 1.50 500,000

Abridged Sigma Table

Abridged Process Sigma Conversion Table

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Sheet1

Yield Sigma DPMO Yield Sigma DPMO
99.99966% 6.00 3.4 98.60966% 3.70 13,903
99.99946% 5.90 5.4 98.21356% 3.60 17,864
99.99915% 5.80 8.5 97.72499% 3.50 22,750
99.99867% 5.70 13 97.12834% 3.40 28,717
99.99793% 5.60 21 96.40697% 3.30 35,930
99.99683% 5.50 32 95.54345% 3.20 44,565
99.99519% 5.40 48 94.52007% 3.10 54,799
99.99277% 5.30 72 93.31928% 3.00 66,807
99.98922% 5.20 108 91.92433% 2.90 80,757
99.98409% 5.10 159 90.31995% 2.80 96,800
99.97674% 5.00 233 88.49303% 2.70 115,070
99.96631% 4.90 337 86.43339% 2.60 135,666
99.95166% 4.80 483 84.13447% 2.50 158,655
99.93129% 4.70 687 81.99519% 2.40 184,060
99.90323% 4.60 968 78.81446% 2.30 211,855
99.86501% 4.50 1,350 75.80363% 2.20 241,964
99.81342% 4.40 1,866 72.57469% 2.10 274,253
99.74449% 4.30 2,555 69.14625% 2.00 308,538
99.65330% 4.20 3,467 65.54217% 1.90 344,578
99.53388% 4.10 4,661 61.79114% 1.80 382,089
99.37903% 4.00 6,210 57.92597% 1.70 420,740
99.18025% 3.90 8,198 53.98278% 1.60 460,172
98.92759% 3.80 10,724 50.00000% 1.50 500,000

Sheet2

Sheet3

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Sigma Performance (DPMO)

37

For additional information about this concept, see

Lesson 12 Baseline Performance, in the

Sigma section.

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Baseline Performance

240 Units 72 Defects 7 Opportunities

42,857 DPMO

3.2 Sigma

DPMO = 1M Units x Opportunities Defects

( 240 ) =

( 72 ) ( 7 )

SI Sigma Performance

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Lean Six Sigma – Simco International

Analyze Phase 1

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Simco International – Analyze Phase Deliverables

Deliverable Page Lesson (Deliverable Originated From)

Cause and Effect Analysis 3 Root Cause Analysis Lean Process Analysis 8 Lean Process Analysis Pareto 18 Graphical Data Analysis Box Plots 25 Graphical Data Analysis Correlation Analysis 32 Graphical Data Analysis Regression Analysis 39 Statistical Data Analysis

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Cause and Effect Analysis

Lean Six Sigma – Project Simulation

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Objective  Develop cause and effect relationships for the SI Consumer Home Loan

process problem statement.

Instructions  Complete the “Process” component of the Fishbone diagram on the following

page.  Then, circle all significant Potential Root Causes in the entire Fishbone.  Prepare your findings.

Cause and Effect Analysis

SI Project Template: Cause and Effect Analysis_SI

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Loan Processing Cycle Time in Chicago Takes an Average of

31 Days to Complete

People

Process

Staffing not aligned with peak volume

It is difficult to handle the volume at different times throughout the year

The LP does not know which forms to use for different loan types

The Loan Processor often does the job of the Loan Officer

Waiting for information from another department

Unclear number of loans required to complete per day

Internal mail department only picks up and delivers once a day

Work load for Loan Processors and Loan Officers is inconsistent

It is difficult for the LP to understand the

LO final determination

Waiting for applications and information in the mail

The LP was not trained on different loan types

Work load for Loan Processors and Loan Officers is inconsistent

Cause and Effect Analysis

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Notes: The above cause-and-effect diagram was generated by the project team for the Chicago loan processing cycle time. Note the problem statement (primary effect) that is being analyzed at the head of the diagram and the corresponding major categories (or “bones”) of Process and People. Take a moment to review the causes and effects for each category and their relationships to the overall problem. Utilize your understanding of the process to create potential root causes. Remember to ask the question “Why?”.

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Cause and Effect Analysis

6

For additional information about this concept, see Lesson 14 Root Cause Analysis, in the Root Cause Analysis section.

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Loan Processing Cycle Time in

31 Days to Complete

People

Chicago Takes an Average of

Process

Staffing not aligned with peak volume

It is difficult to handle the volume at different times throughout the year

The LP does not know which forms to use for different loan types

The Loan Processor often does the job of the Loan Officer

Requirement to send everything by regular mail

No Process Controls

Waiting for information from another department

Unclear how long it should take to perform individual tasks

Unclear number of loans required to complete per day

Internal mail department only picks up and delivers once a day

One mail person on staff

Work load for Loan Processors and Loan Officers is inconsistent

It is difficult for the LP to understand the

LO final determination

Budget only allows for one

mail person

Waiting for applications and information in the mail

The LP was not trained on different loan types

Work load for Loan Processors and Loan Officers is inconsistent

SI Cause and Effect Analysis

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Lean Process Analysis

Lean Six Sigma – Project Simulation

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Lean Process Analysis

Objective  Complete a Lean Analysis for the SI Consumer Home Loan process.

Instructions  Using the descriptions below and the “SI Deployment Flowchart with Time” (on the following

pages), complete the Lean Analysis worksheet (value-add/non value-add) on the following page.

 Calculate the total value-add and non value-add steps, total time, and % of total time.  Prepare your findings.

Value-Added Questions: 1.Change the process? 2.Customer recognizes the value? 3.Done right the first time? 4.Required by law or regulation?

Non Value-Added Examples: - Waiting - Storing - Counting - Inspecting - Recording - Obtaining - Approvals - Reviewing - Copying - Reworking - Filing - Tracking

SI Project Template: Lean Process Analysis_SI

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Lean Process Analysis

Process Step 1 2 3 4 5 6 7 8 9 1 0

1 1

1 2

1 3

1 4

1 5

1 6

1 7

1 8

1 9

2 0

2 1

2 2

2 3

Total Steps

Total Time

% of Total Time

Time (Hours)

Value-Added

Non Value- Added

Delay

Set-up

Inspection

Transporting

Rework

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SI Cycle Time Per Process Step

Process Step

Cycle Time (Hours)

1 1/2

2 32

3 2

4 32

5 8

6 8

7 1

8 1/2

Process Step

Cycle Time (Hours)

9 2

10 32

11 1

12 1/2

13 1/2

14 1

15 1/2

16 1/2

Process Step

Cycle Time (Hours)

17 1

18 1

19 8

20 1/2

21 1

22 32

23 1/2

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Lean Process Analysis – SI As-Is Process Map

SIMCO International “As-Is” Process Map (Page 1)

R ea

l Es

ta te

Ag en

t (R

A)

SI M

or tg

ag e

Sa le

s As

so ci

at e

(M SA

)

SI L

oa n

Pr oc

es so

r (L

P)

SI L

oa n

O ffi

ce r

(L O

)

H om

e Lo

an C

us to

m er

Contact RA to request loan

Mail loan application to

customer

Complete loan application

Mail loan application to

RA

Forward application to

MSA

Forward application to

LP

Review application

Request additional info from customer

Gather additional

information

Mail additional information to

LP

Go to Step 12 (Next Page)

Review application

and additional information

1

2

3 4

5

6

7 8

9 10

11

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Lean Process Analysis – SI As-Is Process Map

SIMCO International “As-Is” Process Map (Page 2)

SI L

oa n

O ffi

ce r

(L O

)

SI L

oa n

Pr oc

es so

r (L

P)

SI M

or tg

ag e

Sa le

s As

so ci

at e

(M SA

)

R ea

l Es

ta te

Ag en

t (R

A)

H om

e Lo

an C

us to

m er

Go to Step 8 (Previous Page)

Is info complete?

Forward customer info

to LO

Determine loan

qualification

Send final determination

to LP

Is loan accepted?

Create SI Home Loan acceptance

package

Create SI Home Loan

rejection package

Forward final determination

package to MSA

Schedule meeting with RA to review final package

Review final package

Send final package to customer

Receive final determination

package

Yes

No No

Yes 12

13

14 15

16 17

18 19

20

21 22

23

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Lean Process Analysis

14

For additional information about this concept, see Lesson 15 Lean Process Analysis, in the Lean Process Analysis and Measures section.

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SI Lean Process Analysis

Process Step 1 2 3 4 5 6 7 8 9 1 0

1 1

1 2

1 3

1 4

1 5

1 6

1 7

1 8

1 9

2 0

2 1

2 2

2 3

Total Steps

Total Time

% of Total Time

Time (Hours) 23 166 Hrs 100%

Value-Added x x x x x x 6 6 Hrs 4%

Non Value-Added x x x x x x x x x x x x x x x x x 17 160 Hrs 96%

Delay x 1 .5 Hrs .5%

Set-up x x 2 2 Hrs 1%

Inspection x x 2 1 Hour .5%

Transporting x x x x x x x 7 144.5 Hrs 87%

Rework x x x x x 5 12 Hrs 7%

15

See SI Cycle Time Per Process Step

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SI Lean Process Analysis

Simco International “As-Is” Process Map (Page 1)

Re al

Es ta

te

Ag en

t (R

A)

SI M

or tg

ag e

Sa les

As

so cia

te

(M SA

)

SI L

oa n

Pr oc

es so

r (L

P)

SI L

oa n

Of fic

er (L

O)

Ho m

e Lo

an

Cu sto

m er

Contact RA to request loan

Mail loan application to

customer

Complete loan application

Mail loan application to

RA

Forward application to

MSA

Forward application to

LP

Review application

Request additional info from customer

Gather additional

information

Mail additional information to

LP

Go to Step 12 (Next Page)

Review application

and additional information

1

2

3 4

5

6

7 8

9 10

11

X = Non Value-Added Step

X

X

X

X

X X

X

X

X

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SI Lean Process Analysis

Simco International “As-Is” Process Map (Page 2)

SI L

oa n

O ffi

ce r

(L O

)

SI L

oa n

Pr oc

es so

r (L

P)

SI M

or tg

ag e

Sa le

s As

so cia

te

(M SA

)

Re al

Es

ta te

Ag

en t

(R A)

Ho m

e Lo

an

Cu st

om er

Go to Step 8 (Previous Page)

Is info complete?

Forward customer info

to LO

Determine loan

qualification

Send final determination

to LP

Is loan accepted?

Create SI Home Loan acceptance

package

Create SI Home Loan

rejection package

Forward final determination

package to MSA

Schedule meeting with RA to review final package

Review final package

Send final package to customer

Receive final determination

package

Yes

No No

Yes 12

13

14 15

16 17

18 19

20

21 22

23

X

X

X X

X

XXX

X = Non Value-Added Step

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Process Stratification and Analysis – Pareto

Lean Six Sigma – Project Simulation

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Objective  Create a Pareto Chart from the # of Final Determination Packages with Errors for

London and conduct initial analysis.

Instructions  Open up the Excel file “LSS SI Data File”.

The data set is from a check sheet and is located in the worksheet “# of Package Errors”. Utilize your statistical software to display and describe the variation in the process using a Pareto Chart.

 When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Pareto?

 Prepare your findings.

Pareto

SI Project Template: Pareto_SI

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Pareto

20

For additional information about this concept, see Lesson 16 Graphical Data Analysis, in the Analyzing Data Graphically section.

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Pareto SigmaXL Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is from a check sheet and is located in the worksheet “# of Package

Errors”.  We want to display and describe the variation in the process. Follow these instructions to create the Pareto: 1. Click “SigmaXL" from the toolbar in Excel 2. Select “Graphical Tools” from the menu 3. Select “Basic Pareto Chart” from the menu 4. Select “Use entire data table” from the data window 5. Click “Next" 6. Select “Pareto Category (X)” to move Application Fields data set into the function

window 7. Select “Optional Numeric Count (Y)” to move Number of Errors data set into the

function window 8. Select “Finish” 9. SigmaXL will generate a new worksheet "Pareto"

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SI Pareto SigmaXL Results

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Notes: SI Team Analysis - Loan Amount and Name account for 86% of the total final determination package errors.

Copyright © 2016 Acuity Institute LLC. All rights reserved.

Pareto Minitab Instructions

The following are the instructions to complete this deliverable using Minitab.  Open up the Excel file “LSS SI Date file”  The data set is from a check sheet and is located in the worksheet “# of Package Errors”

 We want to display and describe the variation in the process

Follow these instructions to create the Pareto:

1. Copy the entire data set including the headers 2. Open the Minitab software 3. Paste the data set into Minitab 4. Select “Stat” from the toolbar 5. Select “Quality Tools” from the menu 6. Select “Pareto Chart” from the menu 7. Click inside the data box for "Defects or attribute data in:" 8. Highlight “C1 Application Fields” from the menu 9. Click on “Select” 10. Highlight “C2 Numbers of Errors” from the menu 11. Click on “Select” to add to “Frequencies in” 12. Select “OK” 13. Minitab will generate a Pareto Chart for # of Package Errors

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SI Pareto Minitab Results

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Notes: SI Team Analysis - Loan Amount and Name account for 86% of the total final determination package errors.

Copyright © 2016 Acuity Institute LLC. All rights reserved.

Process Stratification and Analysis – Box Plots

Lean Six Sigma – Project Simulation

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Objective  Create a Box Plot from the SI Loan Processing Cycle Time from all 3 locations and

conduct initial analysis.

Instructions  Open up the Excel file “LSS SI Data File”.

The data set is located in the worksheet “Cycle Time for 3 Locations”. We want to display and describe the variation in the process. Utilize your statistical software to display and describe the variation in the process using a Box Plot.

 When completed, answer the following questions: 1. How would you describe the variation in the data? 2. What conclusions can you draw from the Box Plot?

 Prepare your findings.

Box Plots

SI Project Template: Box Plots_SI

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Box Plots

27

For additional information about this concept, see Lesson 16 Graphical Data Analysis, in the Analyzing Data Graphically section.

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Box Plots SigmaXL Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is located in the worksheet “Cycle Time for 3 Locations”.  We want to display and describe the variation in the process. Follow these instructions to create the Pareto: 1. Click “SigmaXL" from the toolbar in Excel 2. Select “Graphical Tools” from the menu 3. Select “Boxplots” from the menu 4. Select “Use entire data table” from the data window 5. Click “Next" 6. Select “Numeric Data Variables (Y)” 3 times to move cycle time data sets into the

function window 7. Select “Show Legend” 8. Select “OK” 9. SigmaXL will generate a new worksheet “Boxplot".

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SI Box Plots SigmaXL Results

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Notes: SI Team Analysis Chicago has the highest average between the 3 sites Chicago has 2 significant outliers - Both Chicago and Singapore have significant variation - London variation is less than the other sites and the average cycle time is below the CTQ of 15 days

Copyright © 2016 Acuity Institute LLC. All rights reserved.

Box Plots Minitab Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is located in the worksheet “Cycle Time for 3 Locations”.  We want to display and describe the variation in the process. Follow these instructions to create the Box Plot: 1. Copy the entire data set including the headers 2. Open the Minitab software 3. Paste the data set into Minitab 4. Select “Graph” from the toolbar 5. Select “Boxplot” from the menu 6. Select “Simple” from the menu under “Multiple Y’s” 7. Select “OK” 8. Click inside the data box for “Graph variables” 9. Highlight “C1 Chicago Cycle Time” from the menu 10. Click on "Select” (repeat for C2 and C3) 11. Select "OK" 12. Minitab will generate a Boxplot for Cycle Time for 3 Locations

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SI Box Plots Minitab Results

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Notes: SI Team Analysis Chicago has the highest average between the 3 sites Chicago has 2 significant outliers - Both Chicago and Singapore have significant variation - London variation is less than the other sites and the average cycle time is below the CTQ of 15 days

Copyright © 2016 Acuity Institute LLC. All rights reserved.

Correlation Analysis

Lean Six Sigma – Project Simulation

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Objective  Create a Scatter Diagram from data to determine correlation and conduct initial

analysis.

Instructions  Open up the Excel file “LSS SI Data File”.

The data set is in the worksheet “Singapore LP Cycle Time”. We want to determine if there is a strong relationship (correlation) between the Singapore LP Cycle Time (X) and the Singapore Total Cycle Time (Y). Utilize your statistical software to perform correlation.

 When completed, answer the following question: 1. How would you interpret the graph?

 Prepare your findings.

Correlation Analysis

SI Project Template: Correlation Analysis_SI

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Correlation Analysis

34

For additional information about this concept, see Lesson 16 Graphical Data Analysis, in the Analyzing Data Graphically section.

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Correlation Analysis SigmaXL Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is in the worksheet “Singapore LP Cycle Time”.  We want to determine if there is a strong relationship (correlation) between the

Singapore LP Cycle time (X) and the Singapore Total Cycle Time (Y). Follow these instructions to perform correlation: 1. Click “SigmaXL" from the toolbar in Excel 2. Select “Graphical Tools” from the menu 3. Select “Scatter Plots” from the menu 4. Select “Use entire data table” from the data window 5. Click “Next“ 6. Select the first measure “Singapore Total Cycle Time” 7. Select “Singapore Total Cycle Time” for your Numeric Response (Y) 8. Select “Singapore LP Cycle Time” for your Numeric Predictor (X1) 9. Click "OK" 10. SigmaXL will generate a new worksheet "Scatterplot".

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SI Correlation Analysis SigmaXL Results

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Notes: SI Team Analysis - A possible positive correlation exists between the Singapore LP Cycle Time and the Singapore Total Cycle Time

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Correlation Analysis Minitab Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is in the worksheet “Singapore LP Cycle Time”.  We want to determine if there is a strong relationship (correlation) between the Singapore LP

Cycle time (X) and the Singapore Total Cycle Time (Y). Follow these instructions to perform correlation: 1. Copy the entire data set including the headers 2. Open the Minitab software 3. Paste the data set into Minitab 4. Select “Graph” from the toolbar 5. Select “Scatterplot” from the menu 6. Select “With Regression” from the menu 7. Select “OK” 8. Click inside the data box for “Y variables” 9. Highlight “C2 Singapore Total Cycle Time” from the menu 10. Click on "Select” to move under “Y variables” 11. Highlight “C3 Singapore LP Cycle Time” from the menu 12. Click on "Select” to move under “X variables” 13. Select "OK" 14. Minitab will generate a Scatterplot for Singapore LP Cycle Time

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SI Correlation Analysis Minitab Results

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Notes: SI Team Analysis - A possible positive correlation exists between the Singapore LP Cycle Time and the Singapore Total Cycle Time

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Regression Analysis

Lean Six Sigma – Project Simulation

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Objective  Conduct Regression Analysis from data and conduct root cause analysis.

Instructions  Open up the Excel file “LSS SI Data File”.

The data set is in the worksheet “Singapore LP Cycle Time”. We want to determine if there is a statistical correlation between the Singapore LP Cycle Time (X) and the Singapore Total Cycle Time (Y). Utilize your statistical software to perform Regression Analysis.

 When completed, answer the following questions: 1. How would you interpret the output of the analysis? 2. What conclusions can you draw from the p-value and the R2 value?

 Prepare your findings.

Regression Analysis

SI Project Template: Regression Analysis_SI

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Regression Analysis

41

For additional information about this concept, see Lesson 17 Statistical Data Analysis, in the Hypothesis Testing Tools section.

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Regression Analysis SigmaXL Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is in the worksheet “Singapore LP Cycle Time”.  We want to see if there is a statistical correlation between the Singapore LP Cycle time (X) and

the Singapore Total Cycle Time (Y). Follow these instructions to perform Regression: 1. Select “SigmaXL" from the toolbar in Excel 2. Select “Statistical Tools” from the menu 3. Select “Regression” from the menu 4. Select “Multiple Regression” from the menu 5. Select “Use entire data table” from the data window 6. Select “Next” 7. Select the first measure “Singapore Total Cycle Time” 8. Select “Numeric Response (Y)” to move Singapore Total Cycle Time data set into the function

window 9. Select “Continuous Predictors (X)” 1 time to move the cycle time data set for Singapore LP Cycle

Time into the function window 10. Select “OK” 11. SigmaXL will generate a new worksheet “Multiple Regression“ and a second worksheet “Mult

Reg Residuals”

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SI Regression Analysis SigmaXL Results

* Additional information is provided (which we do not always use) when you perform this analysis.

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Notes: SI Team Analysis - R-Sq = 47.1% of the variation in the process output is accounted for by the model - P-Value < 0.05, the Singapore LP Cycle Time does influence the Singapore Total Cycle Time

Copyright © 2016 Acuity Institute LLC. All rights reserved.

Regression Analysis Minitab Instructions

 Open up the Excel file “LSS SI Data File”.  The data set is in the worksheet “Singapore LP Cycle Time”.  We want to see if there is a statistical correlation between the Singapore LP Cycle time (X) and the

Singapore Total Cycle Time (Y). Follow these instructions to perform Regression: 1. Copy the entire data set including the headers 2. Open the Minitab software 3. Paste the data set into Minitab 4. Select “Stat” from the toolbar 5. Select “Regression” from the menu 6. Select “Fitted Line Plot…” from the menu 7. Click inside the data box for “Response “(Y)” 8. Highlight “C2 Singapore Total Cycle Time” from the menu 9. Click on "Select” 10. Click inside the data box for “Predictor “(X)” 11. Highlight “C3 Singapore LP Cycle Time” from the menu 12. Click on "Select” 13. Select “OK” 14. Minitab will generate a Fitted Line Plot and summary for Singapore Cycle Time

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SI Regression Analysis Minitab Results

* Additional information is provided (which we do not always use) when you perform this analysis. 45

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Notes: SI Team Analysis - R-Sq = 47.1% of the variation in the process output is accounted for by the model - P-Value < 0.05, the Singapore LP Cycle Time does influence the Singapore Total Cycle Time

Copyright © 2016 Acuity Institute LLC. All rights reserved.

Lean Six Sigma – Simco International

Improve Phase 1

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Simco International – Improve Phase Deliverables

Deliverable Page Lesson (Deliverable Originated From)

Solution Selection Matrix 3 Identify & Select Solutions Cost/Benefit Analysis 8 Financial Impact of Solutions Mitigating Risks (FMEA) 13 Risk Planning and Testing Pilot Plan 18 Risk Planning and Testing Implementation Planning 23 Implement Solution Storyboarding 28 Implement Solution

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Solution Selection Matrix

Lean Six Sigma – Project Simulation

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Objective  Complete a Solution Selection Matrix for the SI Consumer Home Loan process.

Instructions  Utilize the worksheet on the following page to complete the Solution Selection Matrix.  Rate each solutions impact on the criteria using the following scale (1=low impact,

3=medium impact, 9=high impact). Impact for each criteria should be calculated as follows:  Sigma Impact = rate the solutions impact on improving sigma  Time Impact = rate the solutions impact on time investment needed to implement  Cost / Benefit Impact = rate the solutions impact of financial benefits over costs  Other Impacts = rate the solutions impact to other criteria (organization, morale, etc)

 Multiply each rating by the weighting for the criteria and document the totals for each solution.

 Rank the solutions from highest to lowest and select the solutions for the SI process.  Prepare your findings.

Solution Selection Matrix

SI Project Template: Solution Selection Matrix_SI

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Criteria Total Rank

Weight Solutions Rating Score Rating Score Rating Score Rating Score

Have LP determine loan qualification

Develop email/internet based system to exchange information and remove paperwork Combine LP and MSA processes to eliminate MSA from loan processing Develop online application submission with mandatory fields and accuracy checks Identify and track process segment requirements on processing time and accuracy

3 2 3 1

Sigma Impact Time Impact Cost/ Benefit Impact

Other Impacts

Solution Selection Matrix Worksheet

Develop training program on different types of loans for LP

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Solution Selection Matrix

6

For additional information about this concept, see Lesson 20 Identify and Select Solutions, in the Select Solutions section.

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Criteria Total Rank

Weight Solutions Rating Score Rating Score Rating Score Rating Score

Develop training program on different types of loans for LP

3 9 9 18 1 3 3 3 33 5

Have LP determine loan qualification

9 27 3 6 3 9 1 1 43 3

Develop email/internet based system to exchange information and remove paperwork

9 27 1 2 9 27 9 9 65 1

Combine LP and MSA processes to eliminate MSA from loan processing

3 9 9 18 3 9 3 3 39 4

Develop online application submission with mandatory fields and accuracy checks

3 9 1 2 9 27 9 9 47 2

Identify and track process segment requirements on processing time and accuracy

1 3 3 6 1 3 3 3 15 6

Sigma Impact Time Impact Cost/ Benefit Impact

Other Impacts

3 2 3 1

SI Solution Selection Matrix

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Cost/Benefit Analysis

Lean Six Sigma – Project Simulation

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Objective  Complete a Cost/Benefit Analysis for the SI Consumer Home Loan process.

Instructions  Using the costs and benefits below, utilize the worksheet on the following page to complete

the Cost/Benefit Analysis.  Total all costs and benefits and calculate net benefits  Would you recommend implementing the solutions based on the results?

 Prepare your findings.

Implementation Costs Project Benefits Hardware – SI Loan System development = $300,000 Temporary Headcount Eliminated – 15 people @ all 3 sites =

$10,000/year Hardware – 50 PC’s with Processing Software = $1,200/each MSA/LO Processing Time Eliminated – 5 FTE’s @ all 3 sites

= $35,000/year Consultant Training – 2 IT Consultants @ 24hrs/week for 3 weeks (includes all 3 sites) = $100/hr.

Improved cycle time – interest accrued earlier by 80% of total loan volume = $125,000

Training Site – Training facility @ 3 days/week for 3 weeks = $200/day

Reduction in Mail Cost – elimination of application and loan mail costs by 80% of loan volume ($10 per approved loan @ ~ 3,152 loans) = $31,520 Increased customer retention revenue ~ 300 customers annually @ 10% interest on $200,000 home loan = $6MM

Cost/Benefit Analysis

SI Project Template: Cost Benefit Analysis_SI

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Implementation Costs: Measurement Variable Cost Estimate Total Hardware

Hardware

Consultant Training

Training Site

Total Costs

Benefits: Measurement Variable Benefit Estimate Total Temporary Headcount Eliminated MSA/LO Processing Time Eliminated Improved Cycle Time Mail Cost Reduction Increased Customer Retention

Total Benefits

Net Benefit (equals total benefits, less costs)

Cost/Benefit Analysis

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Cost/Benefit Analysis

11

For additional information about this concept, see Lesson 21 Financial Impact of Solutions, in the Cost/Benefit section.

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Implementation Costs: Measurement Variable Cost Estimate Total

Hardware SI Loan System Development $300,000 $300,000

Hardware 50 PC’s with Processing Software $1,200/each $60,000

Consultant Training 2 IT Consultants @ 24hrs./week for 3 weeks (includes all 3 sites)

$100/hr. $14,400

Training Site Training facility @ 3 days/week for 3 weeks $200/day $1,800

Total Costs $376,200

Benefits: Measurement Variable Benefit Estimate Total

Temporary Headcount Eliminated 15 people @ all 3 sites $10,000/year $150,000

MSA/LO Processing Time Eliminated 5 FTE’s @ all 3 sites $35,000/year $175,000

Improved Cycle Time Interest accrued earlier by 80% of total loan volume

$125,000/year $125,000

Mail Cost Reduction Elimination of application and loan mail costs by 80% of loan volume ($10 per approved loan @ ~ 3,152 loans)

$31,520/year $31,520

Increased Customer Retention 300 customers annually @ 10% interest on $200K home loan

$6MM $6MM

Total Benefits ~$6.5MM

Net Benefit (equals total benefits, less costs) ~$6.1MM

SI Cost/Benefit Analysis

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Mitigating Risks (FMEA)

Lean Six Sigma – Project Simulation

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Objective  Complete a Failure Modes and Effects Analysis for the SI Consumer Home Loan

process.

Instructions  Utilize the worksheet on the following page to complete an FMEA.  Complete the possible Effect, Cause and Current Controls for each Error listed.  Rate each error for the listed criteria using the following scale (1=low, 3=medium,

9=high). Each criteria should be calculated as follows:  Frequency = a value reflecting the likelihood that the error will occur  Severity = a value reflecting the degree of adversity the errors effect  Detection = a value reflecting the ease or likelihood that the error will be visible or

noticed (a score of 9 is not good in this case)  Multiply all of the values and document the totals for each error (Risk Priority Number

or RPN).  Document any countermeasures to eliminate and/or monitor (recommended actions).  Prepare your findings.

Mitigating Risks (FMEA)

SI Project Template: Mitigating Risks_SI

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LP sends final package to customer

LP determines loan qualification

LP reviews paper application

Customer completes online application

Item or Process Step

Final package is not sent

Loan is incorrectly denied

Application is missing information

System does not accept application

Recommended Action

R P N

D E T E C T I O N

Current Controls

O C C U R R E N C E

Potential Cause(s)

S E V E R I T Y

Potential Effect(s) of

Failure

Potential Failure Mode

Mitigating Risks (FMEA) Worksheet

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Mitigating Risks (FMEA)

16

For additional information about this concept, see Lesson 22 Risk Planning and Testing, in the Plan for Risks section.

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LP sends final package to customer

LP determines loan qualification

LP reviews paper application

Customer submits application online

Item or Process Step

 Add procedure for mailing, internal audit

273Manual Check3Loan package is sitting in outgoing mail

3Customer does not receive loan package

Final package is not sent

 Internal audit, document procedures

819Minimal1Inaccurate qualification was completed

9Customer is denied loan

Loan is incorrectly denied

 None (low RPN)91Manual Check1Customer failed to provide all information

9Application is sent back to customer, delay in processing

Application is missing information

 Auto notification of system down  Manual submission

of application

2439Minimal3System is down9Customer unable to submit online application

System does not accept application

Recommended Action

R P N

D E T E C T I O N

Current ControlsO C C U R R E N C E

Potential Cause(s)

S E V E R I T Y

Potential Effect(s) of Failure

Potential Failure Mode

SI Mitigating Risks (FMEA)

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Pilot Plan

Lean Six Sigma – Project Simulation

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Objective  Complete a Pilot Plan for the SI Consumer Home Loan process.

Instructions  Utilize the worksheet on the following page to complete the Pilot Plan.  The following parameters have been determined by the team:

 Both the new SI Home Loan Process and SI Loan System will be piloted  The pilot will be conducted in the Chicago site  The pilot will take place in the first 2 weeks of July  5 LP’s will be trained on the new process and system  Northwest Regional customers will have their loans processed with the

new process and system  Prepare your findings.

Pilot Plan

SI Project Template: Pilot Plan_SI

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4. What materials are required to conduct the training?

3. Who will deliver the training?

2. Who will be trained?

1. When and where will the training take place?

Training Plan 4. How is Pilot failure defined?

3. How is Pilot success defined?

2. Who and how will the data be collected?

1. What will be measured (CTQs)?

Data Collection Plan 4. Who will be involved in the pilot?

3. Where will the pilot take place (business, location)?

2. When will the pilot occur (dates from start to stop)?

1. What processes will be piloted?

Scope of Pilot

Description (be as detailed as possible)

Task/Deliverable

Pilot Plan

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Pilot Plan

21

For additional information about this concept, see Lesson 22 Risk Planning and Testing, in the Test Solutions section.

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Task/Deliverable Description (be as detailed as possible)

Scope of Pilot

1. What processes will be piloted? The new SI Consumer Home Loan process and Loan System

2. When will the pilot occur (dates from start to stop)? July 1 – July 15

3. Where will the pilot take place (business, location)? Chicago site

4. Who will be involved in the pilot? Northwest Regional customers, 5 LP’s, LP Manager, Northwest Regional RA

Data Collection Plan

1. What will be measured (CTQs)?  15 day loan processing cycle time  100% accuracy on final determination packages  2 day loan reviewing time

2. Who and how will the data be collected? Project team will collect data using SI Loan System for cycle time CTQ’s and tick sheets for accuracy CTQ

3. How is Pilot success defined? Meet or exceed CTQ’s

4. How is Pilot failure defined? Do not meet 2 or more CTQ’s

Training Plan

1. When and where will the training take place? June 21 – 23 in the Chicago Training Room

2. Who will be trained? 5 LP’s, LP Manager, Northwest Regional RA

3. Who will deliver the training? Project Team on SI Consumer Home Loan process, IT Consultants on Loan System

4. What materials are required to conduct the training? To-Be Process Map, Standard Operating Procedures, Roles and Responsibilities, PC’s installed with Loan System, LCD projector

SI Pilot Plan

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Implementation Planning

Lean Six Sigma – Project Simulation

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Objective  Develop an Implementation Plan for the SI Consumer Home Loan process.

Instructions  Using the worksheet on the following page, develop an implementation plan

for the new process.  Who will be responsible for leadership of the implementation?  Document any barriers you feel the team will have to overcome in order

for implementation to be successful and actions required to mitigate them.

 Develop the training plan: – Who will need to be trained in the new process? – What will they be trained on? – What materials will be required to conduct the training? (perhaps

the same materials in the pilot) – How long will the training occur and who will conduct it?

 Prepare your findings.

Implementation Planning

SI Project Template: Implementation Planning_SI

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Leadership

Implementation Owner(s) Training Owner(s) Process Owner(s)

Barriers to Success

Barriers Actions Necessary to Overcome Barriers Owner

Training Plan

Group To Be Trained

Description of Training Materials Required Length of Training

Trainer(s)

Implementation Planning

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Implementation Planning

26

For additional information about this concept, see Lesson 23 Implement Solution, in the Implementation Planning - Technical section.

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Barbara KissingerProcess Owner(s)

Steve McCaffrey, Erin AndersonTraining Owner(s)

Steve McCaffrey, Erin AndersonImplementation Owner(s)

Leadership

SI Implementation Plan

Erin A.Approval from Processing VP, begin scheduling earlyPulling associates from floor for training

Steve M.Approval from IT VP and assignment of resourcesIT resources needed to build new system

Erin A.Gain leadership support, Process Owners to work with associates

Resistance to combining LO and LP roles and eliminating MSA responsibility from process

OwnerActions Necessary to Overcome BarriersBarriers

Barriers to Success

Erin A.½ DayBinderProcess review, roles and responsibilitiesAgents

Erin A.½ DayBinderProcess review, roles and responsibilitiesSales

Steve M., Erin A.

3 DaysBinder (new process, SOP’s, R&R’s), PC’s

Process review, Internet System review, roles and responsibilities

Processing

Trainer(s)Length of Training

Materials RequiredDescription of TrainingGroup To Be Trained

Training Plan

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Storyboarding

Lean Six Sigma – Project Simulation

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Objective  Develop a “1 page” Storyboard for the SI Consumer Home Loan project.

Instructions  Using the worksheet on the following page, develop a “1 page” storyboard for

communication to the organization through the Improve phase.  Document key deliverables from each phase of the project under the

designated sections  Be creative…think about the story you are trying to tell and the key

deliverables you want the organization to see that will help sell the project outcomes

 Use graphs, statements and visual aides  Prepare your findings.

Storyboarding

SI Project Template: Storyboarding_SI

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Background DEFINE

MEASURE ANALYZE IMPROVE

Storyboarding

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Storyboarding

31

For additional information about this concept, see Lesson 23 Implement Solution, in the Implementation Planning - Cultural section.

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Background DEFINE

MEASURE ANALYZE IMPROVE

During the past 2 years SI has fallen from the 3rd largest financial services provider to 6th in the world. The primary reason for this decline is poor customer service which is driving customers to our competition.

Through analyzing our processes we learned that our Global Consumer Home Loan division was performing well below customer expectations, therefore the “Home Loan” Lean Six Sigma project was initiated.

Team Members Project Role

John Davis Sponsor

Susan Terrell Master Black Belt

Steve McCaffrey Black / Green Belt

Ellen Mobley Team Member

Rod Elway Team Member

Erin Anderson Team Member

Owen Atwater Team Member

Project Goals (by September 1st):

1.Reduce the Consumer Home Loan process cycle time by 45%

2.Improve process accuracy by 50%

CTQ’s: 15 day loan processing cycle time 100% final determination accuracy 100% documented roles and responsibilities 2 day loan reviewing time

0 5

10 15

20 25 30

35 40 45

20 .0

24 .3

28 .7

33 .0

37 .3

41 .7

46 .0

50 .3

54 .7

59 .0

63 .3

67 .7

72 .0

Chicago Loan Processing Cycle Time

Accuracy Baseline Sigma for Chicago = 3.2

Root Causes: 1.Too Much Inter-

Department Processing Time

2.Staffing Model Not Aligned with Peak Volume

3. Incoming Applications are Inaccurate

4.No Process Controls

5.Non Value-Added Process Steps

Median: 30.00

0.90

5.90

10.90

15.90

20.90

25.90

30.90

35.90

40.90

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 9910 1 10

3 10

5 10

7 10

9 11

1 11

3 11

5 11

7 11

9 12

1 12

3 12

5

Ru n

Ch ar

t - C

hi ca

go L

oa n

Pr oc

es si

ng C

yc le

T im

e Project Benefits = ~$6.1MM

Pilot Results

Baseline Performance

SI Storyboard

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Chart4

6.5140688934 12
7.4594354069 19
8.48613712 41
9.5910158579 28
10.7688579977 3
12.012272298 0
13.3116277219 0
14.6550611711 0
16.0285628548 1
17.4161441501 0
18.800089363 0
20.1612889329 0
21.4796475287 1
22.7345563899
23.9054154296
24.9721872717
25.9159628042
26.7195161675
27.3678265349
27.8485446582
28.1523839526
28.2734188254
28.2092768612
27.9612161566
27.5340842817
26.9361607397
26.1788900765
25.2765176574
24.2456443015
23.1047192105
21.8734927916
20.5724519549
19.2222602603
17.8432239533
16.4548026025
15.0751799165
13.7209066056
12.4066231116
11.1448659099
9.9459571253
8.8179736125
7.7667885908
6.7961765134
5.9079701595
5.1022579739
4.3776094181
3.7313164606
3.1596402307
2.6580531625
2.2214685423
1.8444511161
1.5214041911
1.2467303849
1.0149647441
0.820880325
0.6595674476
0.526488703
0.4175123991
0.3289274931
0.2574432146
0.2001765506
0.154630596
0.1186665005
0.0904714014
0.0685243583
0.0515619239
0.0385446163
0.0286252189
0.0211195366
0.0154799812
0.0112721549
0.0081544364
0.0058604562
0.0041842669
0.0029679584
0.0020914463
0.0014641518
0.0010183005
0.0007035845
0.0004829555
0.000329343
0.0002231209
0.0001501697
0.0001004096
0.0000666988
0.0000440161
0.0000288573
0.0000187954
0.0000121617
0.0000078179
0.0000049927
0.0000031676
0.0000019966
0.0000012502
0.0000007777
0.0000004806
0.0000002951
0.00000018
0.0000001091
0.0000000657
0.0000000393
Chicago Loan Processing Cycle Time

Sheet134

Sheet133

Sheet132

Sheet131

Sheet130

Sheet129

Sheet128

Sheet127

1 2

Sheet126

Sheet125

Sheet124

Chicago Loan Processing Cycle Time

Chicago Cycle Time

Chicago Loan Processing Cycle Time
30
30
27
31
31
21
32
28
31
30
28
35
26
55
32
24
34
28
40
31
32
36
31
34
29
34
28
30
30
35
22
23
32
33
32
28
41
32
34
20
31
31
29
30
35
30
28
31
29
31
37
36
21
27
28
33
32
32
24
29
72
35
28
21
32
32
29
37
32
29
33
20
31
34
23
33
36
31
30
26
25
37
35
30
33
23
30
27
35
35
36
29
25
35
38
26
24
25
36
31
33
28
34
25
32

Sheet2

Sheet3

Hist Descript

SigmaXLChartSheet Chicago Loan Processing Cycle Time Count = 105 Mean = 31 Stdev = 6.4196 Range = 52.0 Minimum = 20 25th Percentile (Q1) = 28 50th Percentile (Median) = 31 75th Percentile (Q3) = 34.00 Maximum = 72 95% CI Mean = 29.76 to 32.2 95% CI Sigma = 5.65 to 7.43
1
6.5140688934
7.4594354069
8.48613712
9.5910158579
10.7688579977
12.012272298
13.3116277219
14.6550611711
16.0285628548
17.4161441501
18.800089363
20.1612889329
21.4796475287
22.7345563899
23.9054154296
24.9721872717
25.9159628042
26.7195161675
27.3678265349
27.8485446582
28.1523839526
28.2734188254
28.2092768612
27.9612161566
27.5340842817
26.9361607397
26.1788900765
25.2765176574
24.2456443015
23.1047192105
21.8734927916
20.5724519549
19.2222602603
17.8432239533
16.4548026025
15.0751799165
13.7209066056
12.4066231116
11.1448659099
9.9459571253
8.8179736125
7.7667885908
6.7961765134
5.9079701595
5.1022579739
4.3776094181
3.7313164606
3.1596402307
2.6580531625
2.2214685423
1.8444511161
1.5214041911
1.2467303849
1.0149647441
0.820880325
0.6595674476
0.526488703
0.4175123991
0.3289274931
0.2574432146
0.2001765506
0.154630596
0.1186665005
0.0904714014
0.0685243583
0.0515619239
0.0385446163
0.0286252189
0.0211195366
0.0154799812
0.0112721549
0.0081544364
0.0058604562
0.0041842669
0.0029679584
0.0020914463
0.0014641518
0.0010183005
0.0007035845
0.0004829555
0.000329343
0.0002231209
0.0001501697
0.0001004096
0.0000666988
0.0000440161
0.0000288573
0.0000187954
0.0000121617
0.0000078179
0.0000049927
0.0000031676
0.0000019966
0.0000012502
0.0000007777
0.0000004806
0.0000002951
0.00000018
0.0000001091
0.0000000657
0.0000000393
20.0
24.3
28.7
33.0
37.3
41.7
46.0
50.3
54.7
59.0
63.3
67.7
72.0
12
19
41
28
3
0
0
0
1
0
0
0
1

Hist Descript

Chicago Loan Processing Cycle Time

Run Chart

SigmaXLChartSheet $A$1 1 Chicago Loan Processing Cycle Time RunChart 30.44 Chicago Loan Processing Cycle Time
Chicago Cycle Time 1 30 30.0 105 30
2 30 30.0 30
106 3 27 27.0 30
4 31 31.0 0 30
5 31 31.0 105 30
6 21 21.0 -105 30
Mean 7 32 32.0 30
8 28 28.0 30
9 31 31.0 30
10 30 30.0 30
11 28 28.0 30
12 35 35.0 30
13 26 26.0 30
14 34 34.0 30
15 32 32.0 30
16 24 24.0 30
17 34 34.0 30
18 28 28.0 30
19 40 40.0 30
20 31 31.0 30
21 32 32.0 30
22 36 36.0 30
23 31 31.0 30
24 34 34.0 30
25 29 29.0 30
26 34 34.0 30
27 28 28.0 30
28 30 30.0 30
29 30 30.0 30
30 35 35.0 30
31 22 22.0 30
32 23 23.0 30
33 32 32.0 30
34 33 33.0 30
35 32 32.0 30
36 28 28.0 30
37 41 41.0 30
38 32 32.0 30
39 34 34.0 30
40 20 20.0 30
41 31 31.0 30
42 31 31.0 30
43 29 29.0 30
44 30 30.0 30
45 35 35.0 30
46 30 30.0 30
47 28 28.0 30
48 31 31.0 30
49 29 29.0 30
50 31 31.0 30
51 37 37.0 30
52 36 36.0 30
53 21 21.0 30
54 27 27.0 30
55 28 28.0 30
56 33 33.0 30
57 32 32.0 30
58 32 32.0 30
59 24 24.0 30
60 29 29.0 30
61 34 34.0 30
62 35 35.0 30
63 28 28.0 30
64 21 21.0 30
65 32 32.0 30
66 32 32.0 30
67 29 29.0 30
68 37 37.0 30
69 32 32.0 30
70 29 29.0 30
71 33 33.0 30
72 20 20.0 30
73 31 31.0 30
74 34 34.0 30
75 23 23.0 30
76 33 33.0 30
77 36 36.0 30
78 31 31.0 30
79 30 30.0 30
80 26 26.0 30
81 25 25.0 30
82 37 37.0 30
83 35 35.0 30
84 30 30.0 30
85 33 33.0 30
86 23 23.0 30
87 30 30.0 30
88 27 27.0 30
89 35 35.0 30
90 35 35.0 30
91 36 36.0 30
92 29 29.0 30
93 25 25.0 30
94 35 35.0 30
95 38 38.0 30
96 26 26.0 30
97 24 24.0 30
98 25 25.0 30
99 36 36.0 30
100 31 31.0 30
101 33 33.0 30
102 28 28.0 30
103 34 34.0 30
104 25 25.0 30
105 32 32.0 30

Run Chart

Run Chart - Chicago Loan Processing Cycle Time
Mean: 30.44

Indiv & MR Charts

SigmaXL Control Charts tests $A$1 IMR 6.3461538462 31 imean Chicago Loan Processing Cycle Time
Chicago Cycle Time 1 30 30 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154 indvmean
105 2 30 0 30 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
106 3 27 3 27 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
4 31 4 31 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154
5 31 0 31 14.1219312602 31 47.8780687398 10 0 6.3461538462 20.7328846154
6 21 10 21 14.1219312602 31 47.8780687398 11 0 6.3461538462 20.7328846154
7 32 11 32 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
8 28 4 28 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
9 31 3 31 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
10 30 1 30 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
11 28 2 28 14.1219312602 31 47.8780687398 7 0 6.3461538462 20.7328846154
12 35 7 35 14.1219312602 31 47.8780687398 9 0 6.3461538462 20.7328846154
13 26 9 26 14.1219312602 31 47.8780687398 29 0 6.3461538462 20.7328846154
14 55 29 55 14.1219312602 31 47.8780687398 23 0 6.3461538462 20.7328846154
15 32 23 32 14.1219312602 31 47.8780687398 8 0 6.3461538462 20.7328846154
16 24 8 24 14.1219312602 31 47.8780687398 10 0 6.3461538462 20.7328846154
17 34 10 34 14.1219312602 31 47.8780687398 6 0 6.3461538462 20.7328846154
18 28 6 28 14.1219312602 31 47.8780687398 12 0 6.3461538462 20.7328846154
19 40 12 40 14.1219312602 31 47.8780687398 9 0 6.3461538462 20.7328846154
20 31 9 31 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
21 32 1 32 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
22 36 4 36 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
23 31 5 31 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
24 34 3 34 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
25 29 5 29 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
26 34 5 34 14.1219312602 31 47.8780687398 6 0 6.3461538462 20.7328846154
27 28 6 28 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
28 30 2 30 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154
29 30 0 30 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
30 35 5 35 14.1219312602 31 47.8780687398 13 0 6.3461538462 20.7328846154
31 22 13 22 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
32 23 1 23 14.1219312602 31 47.8780687398 9 0 6.3461538462 20.7328846154
33 32 9 32 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
34 33 1 33 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
35 32 1 32 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
36 28 4 28 14.1219312602 31 47.8780687398 13 0 6.3461538462 20.7328846154
37 41 13 41 14.1219312602 31 47.8780687398 9 0 6.3461538462 20.7328846154
38 32 9 32 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
39 34 2 34 14.1219312602 31 47.8780687398 14 0 6.3461538462 20.7328846154
40 20 14 20 14.1219312602 31 47.8780687398 11 0 6.3461538462 20.7328846154
41 31 11 31 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154
42 31 0 31 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
43 29 2 29 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
44 30 1 30 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
45 35 5 35 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
46 30 5 30 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
47 28 2 28 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
48 31 3 31 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
49 29 2 29 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
50 31 2 31 14.1219312602 31 47.8780687398 6 0 6.3461538462 20.7328846154
51 37 6 37 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
52 36 1 36 14.1219312602 31 47.8780687398 15 0 6.3461538462 20.7328846154
53 21 15 21 14.1219312602 31 47.8780687398 6 0 6.3461538462 20.7328846154
54 27 6 27 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
55 28 1 28 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
56 33 5 33 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
57 32 1 32 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154
58 32 0 32 14.1219312602 31 47.8780687398 8 0 6.3461538462 20.7328846154
59 24 8 24 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
60 29 5 29 14.1219312602 31 47.8780687398 43 0 6.3461538462 20.7328846154
61 72 43 72 14.1219312602 31 47.8780687398 37 0 6.3461538462 20.7328846154
62 35 37 35 14.1219312602 31 47.8780687398 7 0 6.3461538462 20.7328846154
63 28 7 28 14.1219312602 31 47.8780687398 7 0 6.3461538462 20.7328846154
64 21 7 21 14.1219312602 31 47.8780687398 11 0 6.3461538462 20.7328846154
65 32 11 32 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154
66 32 0 32 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
67 29 3 29 14.1219312602 31 47.8780687398 8 0 6.3461538462 20.7328846154
68 37 8 37 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
69 32 5 32 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
70 29 3 29 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
71 33 4 33 14.1219312602 31 47.8780687398 13 0 6.3461538462 20.7328846154
72 20 13 20 14.1219312602 31 47.8780687398 11 0 6.3461538462 20.7328846154
73 31 11 31 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
74 34 3 34 14.1219312602 31 47.8780687398 11 0 6.3461538462 20.7328846154
75 23 11 23 14.1219312602 31 47.8780687398 10 0 6.3461538462 20.7328846154
76 33 10 33 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
77 36 3 36 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
78 31 5 31 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
79 30 1 30 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
80 26 4 26 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
81 25 1 25 14.1219312602 31 47.8780687398 12 0 6.3461538462 20.7328846154
82 37 12 37 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
83 35 2 35 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
84 30 5 30 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
85 33 3 33 14.1219312602 31 47.8780687398 10 0 6.3461538462 20.7328846154
86 23 10 23 14.1219312602 31 47.8780687398 7 0 6.3461538462 20.7328846154
87 30 7 30 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
88 27 3 27 14.1219312602 31 47.8780687398 8 0 6.3461538462 20.7328846154
89 35 8 35 14.1219312602 31 47.8780687398 0 0 6.3461538462 20.7328846154
90 35 0 35 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
91 36 1 36 14.1219312602 31 47.8780687398 7 0 6.3461538462 20.7328846154
92 29 7 29 14.1219312602 31 47.8780687398 4 0 6.3461538462 20.7328846154
93 25 4 25 14.1219312602 31 47.8780687398 10 0 6.3461538462 20.7328846154
94 35 10 35 14.1219312602 31 47.8780687398 3 0 6.3461538462 20.7328846154
95 38 3 38 14.1219312602 31 47.8780687398 12 0 6.3461538462 20.7328846154
96 26 12 26 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
97 24 2 24 14.1219312602 31 47.8780687398 1 0 6.3461538462 20.7328846154
98 25 1 25 14.1219312602 31 47.8780687398 11 0 6.3461538462 20.7328846154
99 36 11 36 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
100 31 5 31 14.1219312602 31 47.8780687398 2 0 6.3461538462 20.7328846154
101 33 2 33 14.1219312602 31 47.8780687398 5 0 6.3461538462 20.7328846154
102 28 5 28 14.1219312602 31 47.8780687398 6 0 6.3461538462 20.7328846154
103 34 6 34 14.1219312602 31 47.8780687398 9 0 6.3461538462 20.7328846154
104 25 9 25 14.1219312602 31 47.8780687398 7 0 6.3461538462 20.7328846154
105 32 7 32 14.1219312602 31.00 47.8780687398

Indiv & MR Charts

Individuals - Chicago Loan Processing Cycle Time
1
1
Mean CL: 31.00

Indiv - Tests

MR - Chicago Loan Processing Cycle Time
Tests for Special Causes - Indiv - Chicago Loan Processing Cycle Time
Number of Data Points Failing Tests = 2
Observation No. Test 1: 1 point more than 3 sigma from CL Test 2: 9 points in a row on same side of CL Test 3: 6 points in a row all increasing or all decreasing Test 4: 14 points in a row alternating up and down Test 5: 2 out of 3 points more than 2 sigma from CL (same side) Test 6: 4 out of 5 points more than 1 sigma from CL (same side) Test 7: 15 points in a row within 1 sigma from CL (either side) Test 8: 8 points in a row more than 1 sigma from CL (either side)
14 x
61 x

Chart5

30 30
30 30
27 30
31 30
31 30
28 30
32 30
28 30
31 30
30 30
28 30
35 30
26 30
34 30
32 30
24 30
34 30
28 30
31 30
31 30
32 30
36 30
31 30
34 30
29 30
34 30
28 30
30 30
30 30
35 30
25 30
27 30
32 30
33 30
32 30
28 30
32 30
32 30
34 30
37 30
31 30
31 30
29 30
30 30
35 30
30 30
28 30
31 30
29 30
31 30
37 30
36 30
31 30
27 30
28 30
33 30
32 30
32 30
24 30
29 30
34 30
35 30
28 30
32 30
32 30
32 30
29 30
37 30
32 30
29 30
33 30
20 30
31 30
34 30
28 30
33 30
36 30
31 30
30 30
26 30
25 30
37 30
35 30
30 30
33 30
29 30
30 30
27 30
35 30
35 30
36 30
29 30
25 30
35 30
38 30
26 30
24 30
25 30
36 30
31 30
33 30
28 30
34 30
25 30
32 30
3 30
6 30
5 30
7 30
7 30
6 30
6 30
4 30
4 30
7 30
1 30
12 30
7 30
4 30
5 30
6 30
9 30
8 30
6 30
7 30
Run Chart - Chicago Loan Processing Cycle Time
Median: 30.00

Sheet134

Sheet133

Sheet132

Sheet131

Sheet130

Sheet129

Sheet128

Sheet127

1 2

Sheet126

Sheet125

Sheet124

Chicago Loan Processing Cycle Time

Dataxl1

Sum of Number of Errors 44 Application Fields
0 Total
Loan Amount 26 0.5909090909 26
Name 12 0.8636363636 38
Address 3 0.9318181818 41
Loan Duration 2 0.9772727273 43
City 1 1 44
Loan # 0 1 44
State 0 1 44
1

Sheet24

Sheet23

Sheet22

Sheet21

Sheet20

Sheet19

Sheet18

Sheet17

1 2

Sheet16

Application Fields Number of Errors
Name 12
Address 3
Loan # 0
Loan Amount 26
Loan Duration 2
City 1
State 0

Dataxl1 (2)

Sum of Number of Errors 44 82 7 Loan Amount 26 0.5909090909
Application Fields Total 0 Name 12 0.8636363636
Loan Amount 26 59% 26 Address 3 0.9318181818
Name 12 86% 38 100 Loan Duration 2 0.9772727273
Address 3 93% 41 City 1 1
Loan Duration 2 98% 43 Loan # 0 1
City 1 100% 44 State 0 1
Loan # 0 100% 44
State 0 100% 44

Dataxl1 (3)

Sum of Number of Errors 44 Application Fields
0 Total
Loan Amount 26 0.5909090909 26
Name 12 0.8636363636 38
Address 3 0.9318181818 41
Loan Duration 2 0.9772727273 43
City 1 1 44
Loan # 0 1 44
State 0 1 44
1

# of Package Errors

Application Fields Number of Errors
Name 12
Address 3
Loan # 0
Loan Amount 26
Loan Duration 2
City 1
State 0
44

Sheet13

Sheet12

Sheet11

Sheet10

Sheet8

Sheet7

4286
0
4286
0
2

Sheet5

Chicago Loan Processing Cycle Time RA Cycle Time MSA Cycle Time LP Cycle Time LO Cycle Time
30 1 15 11 3
30 2 15 9 4
27 3 14 7 3
31 4 16 8 3
31 3 16 10 4
21 4 11 3 3
32 5 16 8 3
28 6 14 5 3
31 3 16 8 4
30 4 15 8 3
28 2 14 9 3
35 3 18 13 2
26 4 13 6 3
55 5 28 15 7
32 3 16 11 2
24 2 12 6 4
34 3 17 11 3
28 4 14 7 3
40 2 20 16 2
31 3 16 9 3
32 4 16 9 3
36 2 18 11 2
31 3 16 9 3
34 3 17 10 4
29 2 15 9 5
34 2 17 10 4
28 1 14 8 3
30 1 15 9 3
30 2 15 9 2
35 3 18 11 3
22 2 11 7 1
23 3 12 7 3
32 4 16 10 2
33 5 17 10 3
32 4 16 10 3
28 3 14 8 3
41 4 21 12 4
32 3 16 10 3
34 2 17 10 3
20 3 10 6 2
31 4 16 9 3
31 3 16 9 3
29 2 15 9 3
30 2 15 9 3
35 2 18 11 4
30 3 15 9 3
28 3 14 8 3
31 2 16 9 3
29 1 15 9 3
31 2 16 9 3
37 3 19 11 4
36 4 18 11 4
21 3 11 6 2
27 2 14 8 3
28 1 14 8 3
33 2 17 10 3
32 3 16 10 3
32 4 16 10 3
24 4 12 7 3
29 4 15 9 4
72 3 36 22 6
35 4 18 11 5
28 4 14 8 3
21 5 11 6 4
32 3 16 10 3
32 3 16 10 4
29 2 15 9 2
37 1 19 11 4
32 2 16 10 3
29 3 15 9 3
33 2 17 10 3
20 3 10 6 2
31 3 16 9 3
34 4 17 10 3
23 3 12 7 2
33 2 17 10 2
36 3 18 11 3
31 4 16 9 1
30 3 15 9 3
26 2 13 8 4
25 2 13 8 3
37 2 19 11 4
35 2 18 11 4
30 3 15 9 4
33 3 17 10 3
23 4 12 7 2
30 3 15 9 3
27 4 14 8 3
35 5 18 11 4
35 4 18 11 4
36 3 18 11 5
29 2 15 9 3
25 1 13 8 2
35 2 18 11 4
38 3 19 11 4
26 4 13 8 3
24 5 12 7 3
25 4 13 8 4
36 3 18 11 4
31 4 16 9 3
33 5 17 10 3
28 4 14 8 3
34 3 17 10 3
25 4 13 8 3
32 5 16 10 4

Sheet4

Sheet3

Chicago Loan Processing Cycle Time Chicago Loan Processing Cycle Time
RA Cycle Time RA Cycle Time
MSA Cycle Time MSA Cycle Time
LP Cycle Time LP Cycle Time
LO Cycle Time LO Cycle Time

Sheet45

Sheet44

Sheet43

Sheet42

Sheet40

Sheet39

4286
0
4286
0
2

Sheet37

Chicago Loan Processing Cycle Time RA Cycle Time MSA Cycle Time LP Cycle Time LO Cycle Time
30 1 15 11 3
30 2 15 9 4
27 3 14 7 3
31 4 16 8 3
31 3 16 8 4
21 4 11 3 3
32 5 16 8 3
28 6 14 5 3
31 3 16 8 4
30 4 15 8 3
28 2 14 9 3
35 3 18 12 2
26 4 13 6 3
55 5 28 15 7
32 3 16 11 2
24 2 12 6 4
34 3 17 11 3
28 4 14 7 3
40 2 20 16 2
31 3 16 9 3
32 4 16 9 3
36 2 18 14 2
31 3 16 9 3
34 3 17 10 4
29 2 15 7 5
34 2 17 11 4
28 1 14 10 3
30 1 15 11 3
30 2 15 11 2
35 3 18 11 3
22 2 11 8 1
23 3 12 5 3
32 4 16 10 2
33 5 17 8 3
32 4 16 9 3
28 3 14 8 3
41 4 21 12 4
32 3 16 10 3
34 2 17 12 3
20 3 10 5 2
31 4 16 8 3
31 3 16 9 3
29 2 15 10 3
30 2 15 10 3
35 2 18 12 4
30 3 15 9 3
28 3 14 8 3
31 2 16 10 3
29 1 15 11 3
31 2 16 10 3
37 3 19 12 4
36 4 18 11 4
21 3 11 5 2
27 2 14 9 3
28 1 14 10 3
33 2 17 11 3
32 3 16 10 3
32 4 16 9 3
24 4 12 5 3
29 4 15 6 4
72 3 36 27 6
35 4 18 8 5
28 4 14 7 3
21 5 11 1 4
32 3 16 10 3
32 3 16 9 4
29 2 15 10 2
37 1 19 13 4
32 2 16 11 3
29 3 15 9 3
33 2 17 11 3
20 3 10 5 2
31 3 16 9 3
34 4 17 10 3
23 3 12 7 2
33 2 17 12 2
36 3 18 12 3
31 4 16 10 1
30 3 15 9 3
26 2 13 7 4
25 2 13 8 3
37 2 19 12 4
35 2 18 11 4
30 3 15 8 4
33 3 17 10 3
23 4 12 5 2
30 3 15 9 3
27 4 14 6 3
35 5 18 8 4
35 4 18 9 4
36 3 18 10 5
29 2 15 9 3
25 1 13 9 2
35 2 18 11 4
38 3 19 12 4
26 4 13 6 3
24 5 12 4 3
25 4 13 4 4
36 3 18 11 4
31 4 16 8 3
33 5 17 8 3
28 4 14 7 3
34 3 17 11 3
25 4 13 5 3
32 5 16 7 4

Sheet36

Sheet35

Chicago Loan Processing Cycle Time Chicago Loan Processing Cycle Time
RA Cycle Time RA Cycle Time
MSA Cycle Time MSA Cycle Time
LP Cycle Time LP Cycle Time
LO Cycle Time LO Cycle Time

Sheet56

Sheet55

Sheet54

Sheet53

Sheet51

Sheet50

4286
0
4286
0
2

Sheet48

Chicago Loan Processing Cycle Time RA Cycle Time MSA Cycle Time LP Cycle Time LO Cycle Time
30 1 15 11 3
30 2 15 9 4
27 3 14 7 3
31 4 16 8 3
31 3 16 8 4
21 4 11 3 3
32 5 16 8 3
28 6 14 5 3
31 3 16 8 4
30 4 15 8 3
28 2 14 9 3
35 3 18 12 2
26 4 13 6 3
55 5 28 15 7
32 3 16 11 2
24 2 12 6 4
34 3 17 11 3
28 4 14 7 3
40 2 20 16 2
31 3 16 9 3
32 4 16 9 3
36 2 18 14 2
31 3 16 9 3
34 3 17 10 4
29 2 15 7 5
34 2 17 11 4
28 1 14 10 3
30 1 15 11 3
30 2 15 11 2
35 3 18 11 3
22 2 11 8 1
23 3 12 5 3
32 4 16 10 2
33 5 17 8 3
32 4 16 9 3
28 3 14 8 3
41 4 21 12 4
32 3 16 10 3
34 2 17 12 3
20 3 10 5 2
31 4 16 8 3
31 3 16 9 3
29 2 15 10 3
30 2 15 10 3
35 2 18 12 4
30 3 15 9 3
28 3 14 8 3
31 2 16 10 3
29 1 15 11 3
31 2 16 10 3
37 3 19 12 4
36 4 18 11 4
21 3 11 5 2
27 2 14 9 3
28 1 14 10 3
33 2 17 11 3
32 3 16 10 3
32 4 16 9 3
24 4 12 5 3
29 4 15 6 4
72 3 36 27 6
35 4 18 8 5
28 4 14 7 3
21 5 11 1 4
32 3 16 10 3
32 3 16 9 4
29 2 15 10 2
37 1 19 13 4
32 2 16 11 3
29 3 15 9 3
33 2 17 11 3
20 3 10 5 2
31 3 16 9 3
34 4 17 10 3
23 3 12 7 2
33 2 17 12 2
36 3 18 12 3
31 4 16 10 1
30 3 15 9 3
26 2 13 7 4
25 2 13 8 3
37 2 19 12 4
35 2 18 11 4
30 3 15 8 4
33 3 17 10 3
23 4 12 5 2
30 3 15 9 3
27 4 14 6 3
35 5 18 8 4
35 4 18 9 4
36 3 18 10 5
29 2 15 9 3
25 1 13 9 2
35 2 18 11 4
38 3 19 12 4
26 4 13 6 3
24 5 12 4 3
25 4 13 4 4
36 3 18 11 4
31 4 16 8 3
33 5 17 8 3
28 4 14 7 3
34 3 17 11 3
25 4 13 5 3
32 5 16 7 4

Sheet47

Sheet46

Chicago Loan Processing Cycle Time Chicago Loan Processing Cycle Time
RA Cycle Time RA Cycle Time
MSA Cycle Time MSA Cycle Time
LP Cycle Time LP Cycle Time
LO Cycle Time LO Cycle Time

Chicago Cycle Time with Pilot

Loan # Chicago Loan Processing Cycle Time
1 30
2 30
3 27
4 31
5 31
6 28
7 32
8 28
9 31
10 30
11 28
12 35
13 26
14 34
15 32
16 24
17 34
18 28
19 31
20 31
21 32
22 36
23 31
24 34
25 29
26 34
27 28
28 30
29 30
30 35
31 25
32 27
33 32
34 33
35 32
36 28
37 32
38 32
39 34
40 37
41 31
42 31
43 29
44 30
45 35
46 30
47 28
48 31
49 29
50 31
51 37
52 36
53 31
54 27
55 28
56 33
57 32
58 32
59 24
60 29
61 34
62 35
63 28
64 32
65 32
66 32
67 29
68 37
69 32
70 29
71 33
72 20
73 31
74 34
75 28
76 33
77 36
78 31
79 30
80 26
81 25
82 37
83 35
84 30
85 33
86 29
87 30
88 27
89 35
90 35
91 36
92 29
93 25
94 35
95 38
96 26
97 24
98 25
99 36
100 31
101 33
102 28
103 34
104 25
105 32
1 3
2 6
3 5
4 7
5 7
6 6
7 6
8 4
9 4
10 7
11 1
12 12
13 7
14 4
15 5
16 6
17 9
18 8
19 6
20 7

Sheet61

Normal Random Data (1)

Chicago Pilot Loan Processing Time
3
6
5
7
7
6
6
4
4
7
1
12
7
4
5
6
9
8
6
7

Run Chart (2)

SigmaXLChartSheet $B$1 1 Chicago Loan Processing Cycle Time RunChart 30.00 Chicago Loan Processing Cycle Time
Chicago Cycle Time Per Dept 1 30 30.00 125 30
Nonparametric Runs Test: Chicago Loan Processing Cycle Time 2 30 30.00 30
126 3 27 27.00 30
Number of Runs about Median: 57 4 31 31.00 0 30
Expected Number of Runs about Median: 63 5 31 31.00 125 30
Number of Points above Median: 60 6 28 28.00 -125 30
Number of Points equal to or below Median: 65 Median 7 32 32.00 30
P-Value for Clustering: 0.1248 8 28 28.00 30
P-Value for Mixtures: 0.8752 9 31 31.00 30
P-Value for Lack of Randomness (2-Sided): 0.2496 10 30 30.00 30
11 28 28.00 30
Number of Runs Up or Down: 82 12 35 35.00 30
Expected Number of Runs Up or Down: 83 13 26 26.00 30
P-Value for Trends: 0.4154 14 34 34.00 30
P-Value for Oscillation: 0.5846 15 32 32.00 30
16 24 24.00 30
17 34 34.00 30
18 28 28.00 30
19 31 31.00 30
20 31 31.00 30
21 32 32.00 30
22 36 36.00 30
23 31 31.00 30
24 34 34.00 30
25 29 29.00 30
26 34 34.00 30
27 28 28.00 30
28 30 30.00 30
29 30 30.00 30
30 35 35.00 30
31 25 25.00 30
32 27 27.00 30
33 32 32.00 30
34 33 33.00 30
35 32 32.00 30
36 28 28.00 30
37 32 32.00 30
38 32 32.00 30
39 34 34.00 30
40 37 37.00 30
41 31 31.00 30
42 31 31.00 30
43 29 29.00 30
44 30 30.00 30
45 35 35.00 30
46 30 30.00 30
47 28 28.00 30
48 31 31.00 30
49 29 29.00 30
50 31 31.00 30
51 37 37.00 30
52 36 36.00 30
53 31 31.00 30
54 27 27.00 30
55 28 28.00 30
56 33 33.00 30
57 32 32.00 30
58 32 32.00 30
59 24 24.00 30
60 29 29.00 30
61 34 34.00 30
62 35 35.00 30
63 28 28.00 30
64 32 32.00 30
65 32 32.00 30
66 32 32.00 30
67 29 29.00 30
68 37 37.00 30
69 32 32.00 30
70 29 29.00 30
71 33 33.00 30
72 20 20.00 30
73 31 31.00 30
74 34 34.00 30
75 28 28.00 30
76 33 33.00 30
77 36 36.00 30
78 31 31.00 30
79 30 30.00 30
80 26 26.00 30
81 25 25.00 30
82 37 37.00 30
83 35 35.00 30
84 30 30.00 30
85 33 33.00 30
86 29 29.00 30
87 30 30.00 30
88 27 27.00 30
89 35 35.00 30
90 35 35.00 30
91 36 36.00 30
92 29 29.00 30
93 25 25.00 30
94 35 35.00 30
95 38 38.00 30
96 26 26.00 30
97 24 24.00 30
98 25 25.00 30
99 36 36.00 30
100 31 31.00 30
101 33 33.00 30
102 28 28.00 30
103 34 34.00 30
104 25 25.00 30
105 32 32.00 30
106 3 3.00 30
107 6 6.00 30
108 5 5.00 30
109 7 7.00 30
110 7 7.00 30
111 6 6.00 30
112 6 6.00 30
113 4 4.00 30
114 4 4.00 30
115 7 7.00 30
116 1 1.00 30
117 12 12.00 30
118 7 7.00 30
119 4 4.00 30
120 5 5.00 30
121 6 6.00 30
122 9 9.00 30
123 8 8.00 30
124 6 6.00 30
125 7 7.00 30

Run Chart (2)

Run Chart - Chicago Loan Processing Cycle Time
Median: 30.00

Hist Descript

SigmaXLChartSheet Chicago Pilot Loan Processing Time Count = 20 Mean = 6 Stdev = 2.3170 Range = 11.0 Minimum = 1 25th Percentile (Q1) = 4.2500 50th Percentile (Median) = 6 75th Percentile (Q3) = 7.00 Maximum = 12 95% CI Mean = 4.92 to 7.1 95% CI Sigma = 1.76 to 3.38 An
1
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
11.0
12.0
13.0
1
0
1
3
2
5
5
1
1
0
0
1
0

Hist Descript

Chicago Pilot Loan Processing Time

Step 3 Corr

LO Cycle Time MSA Cycle Time LP Cycle Time SUMMARY OUTPUT MSA Cycle Time
5 15 9
2 15 9 Regression Statistics
3 14 8 Multiple R 1
1 16 9 R Square 1
5 16 9 Adjusted R Square 1
2 14 8 Standard Error 1
1 16 10 Observations 105
3 14 8
3 16 9 ANOVA
5 15 9 df SS MS F Significance F
4 14 8 Regression 2 307 154 606 0
3 18 11 Residual 102 26 0
3 13 8 Total 104 333
1 17 10
4 16 10 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
3 12 7 Intercept 2 0 4 0 1 2 1 2
4 17 10 LP Cycle Time 1 0 32 0 1 2 1 2
4 14 8 LO Cycle Time 0 0 2 0 0 0 0 0
4 16 9
3 16 9 SUMMARY OUTPUT LP Cycle Time
2 16 10
5 18 11 Regression Statistics
3 16 9 Multiple R 1
4 17 10 R Square 1
3 15 9 Adjusted R Square 1
5 17 10 Standard Error 0
3 14 8 Observations 105
5 15 9
4 15 9 ANOVA
3 18 11 df SS MS F Significance F
2 13 8 Regression 2 123 62 582 0
1 14 8 Residual 102 11 0
5 16 10 Total 104 134
1 17 10
2 16 10 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
3 14 8 Intercept -0 0 -1 0 -1 0 -1 0
2 16 10 MSA Cycle Time 1 0 32 0 1 1 1 1
4 16 10 LO Cycle Time -0 0 -1 0 -0 0 -0 0
5 17 10
4 19 11 SUMMARY OUTPUT LO Cycle Time
2 16 9
5 16 9 Regression Statistics
1 15 9 Multiple R 0
4 15 9 R Square 0
4 18 11 Adjusted R Square 0
3 15 9 Standard Error 1
5 14 8 Observations 105
4 16 9
4 15 9 ANOVA
1 16 9 df SS MS F Significance F
4 19 11 Regression 2 25 13 9 0
3 18 11 Residual 102 149 1
5 16 9 Total 104 175
4 14 8
5 14 8 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
5 17 10 Intercept -1 1 -1 0 -3 1 -3 1
3 16 10 MSA Cycle Time 1 0 2 0 0 1 0 1
2 16 10 LP Cycle Time -1 0 -1 0 -1 0 -1 0
1 12 7
4 15 9
5 17 10
2 18 11
2 14 8
3 16 10
3 16 10
3 16 10
4 15 9
6 19 11
4 16 10
2 15 9
4 17 10
1 10 6
3 16 9
5 17 10
3 14 8
4 17 10
6 18 11
2 16 9
3 15 9
2 13 8
2 13 8
5 19 11
3 18 11
3 15 9
3 17 10
3 15 9
3 15 9
1 14 8
3 18 11
2 18 11
4 18 11
3 15 9
3 13 8
4 18 11
5 19 11
1 13 8
3 12 7
2 13 8
4 18 11
2 16 9
1 17 10
5 14 8
4 17 10
2 13 8
3 16 10

Step 3 Data

MSA Cycle Time LP Cycle Time LO Cycle Time
15 9 5
15 9 2
14 8 3
16 9 1
16 9 5
14 8 2
16 10 1
14 8 3
16 9 3
15 9 5
14 8 4
18 11 3
13 8 3
17 10 1
16 10 4
12 7 3
17 10 4
14 8 4
16 9 4
16 9 3
16 10 2
18 11 5
16 9 3
17 10 4
15 9 3
17 10 5
14 8 3
15 9 5
15 9 4
18 11 3
13 8 2
14 8 1
16 10 5
17 10 1
16 10 2
14 8 3
16 10 2
16 10 4
17 10 5
19 11 4
16 9 2
16 9 5
15 9 1
15 9 4
18 11 4
15 9 3
14 8 5
16 9 4
15 9 4
16 9 1
19 11 4
18 11 3
16 9 5
14 8 4
14 8 5
17 10 5
16 10 3
16 10 2
12 7 1
15 9 4
17 10 5
18 11 2
14 8 2
16 10 3
16 10 3
16 10 3
15 9 4
19 11 6
16 10 4
15 9 2
17 10 4
10 6 1
16 9 3
17 10 5
14 8 3
17 10 4
18 11 6
16 9 2
15 9 3
13 8 2
13 8 2
19 11 5
18 11 3
15 9 3
17 10 3
15 9 3
15 9 3
14 8 1
18 11 3
18 11 2
18 11 4
15 9 3
13 8 3
18 11 4
19 11 5
13 8 1
12 7 3
13 8 2
18 11 4
16 9 2
17 10 1
14 8 5
17 10 4
13 8 2
16 10 3

Step 2 Corr

Step 2 Data

LO Cycle Time LP Cycle Time
5 9
2 9
3 8
1 9
5 9
2 8
1 10
3 8
3 9
5 9
4 8
3 11
3 8
1 10
4 10
3 7
4 10
4 8
4 9
3 9
2 10
5 11
3 9
4 10
3 9
5 10
3 8
5 9
4 9
3 11
2 8
1 8
5 10
1 10
2 10
3 8
2 10
4 10
5 10
4 11
2 9
5 9
1 9
4 9
4 11
3 9
5 8
4 9
4 9
1 9
4 11
3 11
5 9
4 8
5 8
5 10
3 10
2 10
1 7
4 9
5 10
2 11
2 8
3 10
3 10
3 10
4 9
6 11
4 10
2 9
4 10
1 6
3 9
5 10
3 8
4 10
6 11
2 9
3 9
2 8
2 8
5 11
3 11
3 9
3 10
3 9
3 9
1 8
3 11
2 11
4 11
3 9
3 8
4 11
5 11
1 8
3 7
2 8
4 11
2 9
1 10
5 8
4 10
2 8
3 10

UserInfo

Number of Variables 3 Variable 1 MSA Cycle Time 1 3 4 0 90 95 A 0 0 Keep in ©
Variable 2 LP Cycle Time 2 95 B 0 Keep in
Variable 3 LO Cycle Time 3 C 0 Keep in
Variable 4 0 0 D
Variable 5 0 0 E
Variable 6 0 0 F
Variable 7 0 0 G
DO NOT MAKE ANY CHANGES TO THIS SHEET!!

MRData

RA Cycle Time MSA Cycle Time LP Cycle Time LO Cycle Time
1 15 9 5
4 15 9
2 14 8
5 16 9
1 16 9
4 14 8 2
5 16 10 1
3 14 8 3
3 16 9 3
1 15 9 5
2 14 8 4
3 18 11 3
2 13 8 3
6 17 10 1
2 16 10 4
2 12 7 3
3 17 10 4
2 14 8 4
2 16 9 4
3 16 9 3
4 16 10 2
2 18 11 5
3 16 9 3
3 17 10 4
2 15 9 3
2 17 10 5
3 14 8 3
1 15 9 5
2 15 9 4
3 18 11 3
2 13 8 2
4 14 8 1
1 16 10 5
5 17 10 1
4 16 10 2
3 14 8 3
4 16 10 2
2 16 10 4
2 17 10 5
3 19 11 4
4 16 9 2
1 16 9 5
4 15 9 1
2 15 9 4
2 18 11 4
3 15 9 3
1 14 8 5
2 16 9 4
1 15 9 4
5 16 9 1
3 19 11 4
4 18 11 3
1 16 9 5
1 14 8 4
1 14 8 5
1 17 10 5
3 16 10 3
4 16 10 2
4 12 7 1
1 15 9 4
2 17 10 5
4 18 11 2
4 14 8 2
3 16 10 3
3 16 10 3
3 16 10 3
1 15 9 4
1 19 11 6
2 16 10 4
3 15 9 2
2 17 10 4
3 10 6 1
3 16 9 3
2 17 10 5
3 14 8 3
2 17 10 4
1 18 11 6
4 16 9 2
3 15 9 3
3 13 8 2
2 13 8 2
2 19 11 5
3 18 11 3
3 15 9 3
3 17 10 3
2 15 9 3
3 15 9 3
4 14 8 1
3 18 11 3
4 18 11 2
3 18 11 4
2 15 9 3
1 13 8 3
2 18 11 4
3 19 11 5
4 13 8 1
2 12 7 3
2 13 8 2
3 18 11 4
4 16 9 2
5 17 10 1
1 14 8 5
3 17 10 4
2 13 8 2
3 16 10 3

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Lean Six Sigma – Simco International

Control Phase 1

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Simco International – Control Phase Deliverables

Deliverable Page Lesson (Deliverable Originated From)

Process Monitoring Plan 3 Process Control Dashboard Development 10 Process Control Response Planning 15 Response Planning Final Project Storyboard 20 Project Documentation

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Process Monitoring Plan

Lean Six Sigma – Project Simulation

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Objective  Create a Process Monitoring Plan for the SI Consumer Home Loan process.

Instructions  Using the worksheet on the following page, develop a process monitoring

plan for the ongoing monitoring of the new process.  Identify the process step(s) where the CTQs will be measured  Document the data collection process  Finally, document the frequency you feel the data will need to be

collected and who will have ownership of the collection  Prepare your findings.

Process Monitoring Plan

SI Project Template: Process Monitoring Plan_SI

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CTQ #1: 15 Day Loan Processing Cycle Time Owner Responsible

for Collection Data

Collection Frequency

Data Collection MethodProcess Steps Where the CTQ is Measured

CTQ #2: 2 Day Loan Reviewing Time Process Steps Where the CTQ is Measured

Data Collection Method Data Collection Frequency

Owner Responsible for Collection

CTQ #3: 100% Final Determination Package Accuracy Process Steps Where the CTQ is Measured

Data Collection Method Data Collection Frequency

Owner Responsible for Collection

Process Monitoring Plan

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Please Do Not Proceed Forward

Process Monitoring Plan

6

For additional information about this concept, see

Lesson 25 Process Control, in the Process Monitoring

section.

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CTQ #1: 15 Day Loan Processing Cycle Time Process Steps Where the CTQ

is Measured

Data Collection Method Data Collection Frequency

Owner Responsible for

Collection Customer receives final determination package (either internet or mail)

1. Loan cycle time for Internet will be collected through the SI Loan System; Mail will be collected from the date the customer submits the application to the date of the outgoing final package (+5 days for shipping)

2. Query will be run each week to pull loan data

3. All loans processed will be entered into the SI Quality Assurance spreadsheet and Control Charts and Sigma’s will be created

Weekly Processing Manager

SI Process Monitoring Plan

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CTQ #2: 2 Day Loan Reviewing Time Process

Steps Where the CTQ is Measured

Data Collection Method Data Collection Frequency

Owner Responsible for

Collection

LP determines loan qualification

1. Loan cycle time for Internet will be collected through the SI Loan System; Mail will be collected from the date of the incoming application to the date the final determination package letter is generated

2. Query will be run each week to pull loan data

3. All loans processed will be entered into the SI Quality Assurance spreadsheet and Control Charts and Sigma’s will be created

Weekly Processing Manager

SI Process Monitoring Plan

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CTQ #3: 100% Final Determination Package Accuracy Process Steps Where the CTQ

is Measured

Data Collection Method Data Collection Frequency

Owner Responsible for Collection

Generate (Internet) or create final determination package

1. A sample of 50 loans per week will be pulled for inspection using an accuracy tick sheet

2. Accuracy data will be entered into the SI Quality Assurance spreadsheet and Pareto Charts and Sigma’s will be created

Weekly Processing Manager

SI Process Monitoring Plan

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Dashboard Development

Lean Six Sigma – Project Simulation

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Objective  Create a Dashboard for the SI Consumer Home Loan process.

Instructions  Open up the Excel file “LSS SI Data File”.  The data set is in the worksheet “SI Quality Assurance”.  Develop a dashboard from the data that has been collected so far in the

Control Phase.  Utilize whatever graphical display tools and calculations you feel would

summarize the current process performance of the new SI loan process.  Utilize the following page to arrange these tools and calculations in the format

of a dashboard.  Prepare your findings.

Dashboard Development

SI Project Template: Dashboard Development_SI

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Dashboard Development

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Dashboard Development

13

For additional information about this concept, see

Lesson 25 Process Control, in the Dashboards section.

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Chicago Loan Processing Cycle Time (Sigma = 3.6)

Chicago LP Reviewing Time (Sigma = 3.0) Chicago Package Accuracy (Sigma = 3.5)

Count 3 1 1 0 Percent 60.0 20.0 20.0 0.0 Cum % 60.0 80.0 100.0 100.0

Co un

t

Pe rc

en t

Loan Fields OtherNameAddressLoan Amount

5

4

3

2

1

0

100

80

60

40

20

0

Pareto Chart

SI Dashboard

16141210864

12

10

8

6

4

2

0

Fr eq

ue nc

y

Mean 8.98 StDev 2.290 N 50

Normal Histogram of Chicago Loan Processing Cycle Time

50454035302520151051

3.0

2.5

2.0

1.5

1.0

Observation

Ch ica

go LP

Lo an

R ev

iew ing

Ti me

Run Chart (Mean 1.52)

14

8

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Notes: - The SI Team used statistical analysis software to create the graphs for the new process dashboard.

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Response Planning

Lean Six Sigma – Project Simulation

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Objective  Develop a Response Plan for the SI Consumer Home Loan process.

Instructions  Using the worksheet on the following page, develop a response plan for the

ongoing monitoring of the new process.  What actions should be taken if the process goes out of control?  How frequently should action be taken?  Who will own taking the action?

 Prepare your findings.

Response Planning

SI Project Template: Response Planning_SI

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LP Reviewing Time

Loan Accuracy

Loan Processing Cycle Time

OwnerTimingActionMeasure

Response Planning

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Please Do Not Proceed Forward

Response Planning

18

For additional information about this concept, see Lesson 26 Response Planning, in the Action

Planning section.

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Processing Manager

 Analysis should take place when process has been out of control for 2 weeks or more.  Quick Win improvements should

be continuous  New DMAIC project should be

implemented if process is out of control >2 months

1. Review qualification procedures with LP’s 2. Look for causal relationships (special or common) 3. Continue to monitor and initiate Quick Win

improvement for special cause and initiate a new DMAIC project for common cause

LP Reviewing

Time

Processing Manager

 Analysis should take place when process has been out of control for 2 weeks or more.  Quick Win improvements should

be continuous  New DMAIC project should be

implemented if process is out of control >2 months

1. Review incoming application accuracy from customers

2. Review qualification procedures with LP’s 3. Identify and stratify accuracy defects by type 4. Look for causal relationships (special or common) 5. Continue to monitor and initiate Quick Win

improvement for special cause and initiate a new DMAIC project for common cause

Loan Accuracy

Processing Manager

 Analysis should take place when process has been out of control for 2 weeks or more.  Quick Win improvements should

be continuous  New DMAIC project should be

implemented if process is out of control >2 months

1. Identify and stratify overall cycle time defects by location, day of week, and process segment

2. Look for causal relationships (special or common) 3. Check that SI Loan System has been functioning

properly 4. Continue to monitor and initiate Quick Win

improvements for special cause and initiate a new DMAIC project for common cause

Loan Processing Cycle Time

OwnerTimingActionMeasure

SI Response Plan

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Final Project Storyboard

Lean Six Sigma – Project Simulation

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Final Project Storyboard

SI Project Template: Final Project Storyboard_SI

Objective  Develop a Final Project Storyboard for the SI Consumer Home Loan project.

Instructions  Using the “Final Project Storyboard” template, develop the Final Project Storyboard for

communication to the organization about the entire SI Consumer Home Loan project.  The Final Project Storyboard is a presentation and visual depiction of the steps you took during

each phase of the DMAIC process. It communicates key deliverables and accomplishments that were completed during the project (i.e. steps, tasks, key deliverables, and results). The project story brings all the work and effort you put into your project to life through a storyboard presentation.

 Document key deliverables from each phase of the project under the designated sections of the “Final Project Storyboard” template

 For each phase where applicable, use a combination of graphs, pictures, statements and annotations

 Be creative…think about the story you are trying to tell and the key deliverables you want the organization to see that will help sell the overall project story

 Prepare your findings.

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Notes: The Final Project Storyboard is different from the “1 Page” storyboard you completed in the Improve Phase. The Final Project Storyboard consists of 7 slides (we highly recommend keeping it to 7 slides total). Slide 1: Cover Slide 2: Define Phase Outcomes Slide 3: Measure Phase Outcomes Slide 4: Analyze Phase Outcomes Slide 5: Improve Phase Outcomes Slide 6: Control Phase Outcomes Slide 7: Project Takeaways/Lessons Learned

Copyright © 2016 Acuity Institute LLC. All rights reserved.

SI Final Project Storyboard – Example #1 This is an example of a poor SI Final Project Storyboard slide (from the Improve Phase)

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Notes: - This is an example of one slide from a poor SI Final Project Storyboard. This example has a simple screen shot of one deliverable from the Improve Phase. A screen shot without any annotations does not mean much (what does the tool tell you?). Also, what about the other deliverables from the Improve Phase.

Copyright © 2016 Acuity Institute LLC. All rights reserved.

SI Final Project Storyboard – Example #2 This is an example of a good SI Final Project Storyboard slide (from the Analyze Phase)

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Notes: This is an example of one slide from a good SI Final Project Storyboard. This example includes graphs, charts and annotations from the entire Analyze Phase. Please do not copy this slide for your SI Final Project Storyboard.

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Final Project Storyboard

24

For additional information about this concept, see

Lesson 27 Project Documentation, in the

Solution Replication and Closure section.

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Acuity Institute Support

For product support questions please contact Acuity Institute at [email protected]

Please visit www.acuityinstitute.com for additional product and course offerings

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  • Lean Six Sigma Green Belt eBook
  • eBook Overview
  • LSS Introduction
    • Lean Six Sigma Overview
    • Lean Six Sigma Improvement Methodologies
    • Lean Six Sigma Roles
  • Define Phase
    • Define Overview
    • Project Charter
    • Project Management
    • Process Definition
    • Stakeholder Management
    • Voice of Customer
  • Measure Phase
    • Measure Overview
    • Identify Measures
    • Data Collection
    • Describe and Display Data
    • Baseline Performance
  • Analyze Phase
    • Analyze Overview
    • Root Cause Analysis
    • Lean Process Analysis
    • Graphical Data Analysis
    • Statistical Data Analysis
    • Identify Root Causes
  • Improve Phase
    • Improve Overview
    • Identify and Select Solutions
    • Financial Impact of Solutions
    • Risk Planning and Testing
    • Implement Solution
  • Control Phase
    • Control Overview
    • Process Control
    • Response Planning
    • Project Documentation
  • Lean Six Sigma Green Belt Simulated Project Workbook
    • Simulated Project Overview
    • Define Phase Deliverables
      • Project Charter Development
      • SIPOC
      • As-Is Process Mapping
      • Quick Win Opportunities
      • Identify Stakeholders
      • Develop Stakeholder Map
      • Stakeholder Management Plan
      • Communication Plan
      • VOC Questions
      • CTQ Determination
    • Measure Phase Deliverables
      • Operational Definitions
      • Data Collection Planning
      • Histogram
      • Run Chart
      • Control Chart
      • Sigma Performance (DPMO)
    • Analyze Phase Deliverables
      • Cause and Effect Analysis
      • Lean Process Analysis
      • Process Stratification and Analysis – Pareto
      • Process Stratification and Analysis – Box Plots
      • Correlation Analysis
      • Regression Analysis
    • Improve Phase Deliverables
      • Solution Selection Matrix
      • Cost/Benefit Analysis
      • Mitigating Risks (FMEA)
      • Pilot Plan
      • Implementation Planning
      • Storyboarding
    • Control Phase Deliverables
      • Process Monitoring Plan
      • Dashboard Development
      • Response Planning
      • Final Project Storyboard
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