Six Sigma Overview

1. Six Sigma Overview Simply Left Mouse Click to advance through animations & slides.

2. Define Measure Improve Analyze Control Verify Define Measure Design Analyze Optimize What is Six Sigma? A Methodology … For Continuous Improvement Six Sigma is a highly disciplined data - based methodology of problem solving leveraging tools & techniques where appropriate. • Six Sigma follows two rigorous approaches: • DMAIC Methodology …for improving EXISTING processes • DMADOV Methodology …for CREATING a new product or process Let’s Look At Each Method

4. 1s defects Variation & Defects are the Enemy Every Human Activity Has Variability... Customer Specification X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X Target

5. A 3s process because 3 standard deviations fit between target and spec 1s 2s 3s “No Defects” 6s 1s 2s 3s 4s 5s 6s Reliability thru Variance Reduction Target CustomerSpecification CustomerSpecification Target

6. And … What About Discrete Data? We have an Invoice Payment Process of 45 Days or less and recent data for last month shows that of 100 invoices, 92 were paid in 45 days or less. 92% “On Time” Question…How many were paid in 30 days? Between 40-45 Days? What was my shortest payment cycles? With Discrete Data you’d have to go back and re-measure! And you can’t model new performance limits. And…

7. What is Six Sigma Quality? CustomerSpecification Average Considerations 3s 67,000 Defects per Million Opportunities • Customer Specification • Average • Variation 3s CustomerSpecification Average Six Sigma - A Stretch Goal For many processes BUT Not Good Enough for Some! 3.4 Defects per Million Opportunities 6s 6s _________________________________________________________________________

8. DPMO  % 6 3.4 99.9997% 5 233 99.98% 4 6,210 99% 3 66,807 93% 2 308,537 69% ProcessCapability Defects Per MillionOpportunities Percentage Good What is Six Sigma Quality? • Sigma is a statistical unit of measure that reflects process capability s Increase Requires Exponential DPMO Reduction

9. Sigma Quality Level - Examples IRS Tax Advice (phone in) 1,000,000 Order Write-up Doctor Prescription Writing Restaurant Bills 10,000 Airline Baggage Handling Defects per Million 1,000 “Average” Industrial Company 100 10 Best-in-Class Industrial Company Domestic Airline Fatality Rate (0.43 PPM) 1 6 2 4 5 7 3 Sigma Scale of Measure “Typical” Service Industry Processes are 1.5s to 3s

10. Six Sigma DMAIC Process Define Define Measure Measure Characterization Characterization Characterization Analyze Analyze s s s s 6 6 6 6 Improve Improve Optimization Optimization Optimization Control Control

11. Six Sigma DMAIC Overview Define Define What’s The Problem? Practical Problem Problem Solving Practical Problem Need Practical Problem Measure Measure Flow Do Statistical Problem Analyze Analyze Statistical Problem Need Do Improve Improve Statistical Solution Statistical Solution Need Do Practical Solution Control Control Practical Solution Need Practical Problem: Low Yield Statistical Problem: Mean Off Target Statistical Solution: Isolate Key Variables Practical Solution: Install Automatic Controller

12. DMAIC Step 0: Build the House of Quality A. Identify Needs B. Team Charter C. Process/SIPOC Step 1: Select the CTQ Characteristic Step 2: Define Performance Standards Step 3: Validate MSA and Data Collection DMAIC DMAIC DMAIC DMAIC Step 4: Establish Process Capability Step 5: Define Performance Objectives Step 6: Identify Variation Sources DMAIC DMAIC DMAIC Step 7: Screen Potential Causes Step 8: Discover Variable Relationships Step 9: Establish Operating Tolerances DMAIC DMAIC DMAIC Step 10: Validate MSA on the Xs Step 11: Determine Process Capability Step 12: Implement Process Controls DMAIC DMAIC DMAIC – The 12 + 3 Steps Six Sigma DMAIC The 12+3 Step DMAIC Strategy Formulating the Practical Problem How do my customers look at me? What do I want to improve? What’s the best way to measure? Can I trust the output data? How good am I today? How good do I need to be? What factors make a difference? Changing to a Statistical Problem What’s at the root of the problem? How can I predict the output? How tight does the control have to be? Developing a Statistical Solution Can I trust the in-process data? Have I reached my goal? How can I sustain the improvement? Implementing the Practical Solution

14. When To Use DMADOV DMAIC/DMADOV Transition Points: Define Measure Analyze Improve Control Yes Yes No Is the Improvement a New or Redesigned Product/Service? IsIncremental Improvement Enough? Does a Process Exist? No No Yes Verify Define Measure Analyze Design Optimize

15. DMADOV – The 5 Phases and 14 Steps

16. The DMADOV Methodology – 14 Steps 1. Identify customer needs (CTQ’s) and set performance goals. 2. Perform QFD/CTQ flowdown…Needs to Design Requirements 3. Establish measurement system capability. • DMADOV • Fundamentals • (Key Concepts) • QFD-CTQ • Flow-Down • FMEA • Business Model • (Transfer Function) • Scorecards 4. Develop conceptual designs 5. Reliability Analysis of Designs 6. Build Scorecard of Customer Needs (CTQ’s) 7. Perform risk assessment • 8. Generate and validate models - Identify transfer functions. • 9. Capability flow-up utilizing scorecards…watch for: • Low Zst on scorecard. • Lack of transfer function. • Unknown process capability. • 10. Optimize design • Statistical analysis of variance drivers • Robustness • Error proofing • 11. Generate process specs and verify measurement system X’s 12. Statistically confirm predictions. 13. Develop control plan for CTQ’s (mean and variance). 14. Document the effort and results. QUALITY BY DESIGN!

18. DMADOV Project Progress Overview Web IT Design Example Define Measure Analyze Design Optimize Verify • Project Charter • Problem Statement & Goal • Project Scope • Project Milestones (with firm dates for DMA, targets for DOV) • High-Level CTQ’s • Project Team (Leader, Champion, Sponsor, Black Belt, Master Black Belt, Team Members, Other Resources) • Internal Communication Plan • Business Case • Project Risk Assessment (FMEA or written assessment) • Multi-Generational Plan • Cost-Benefit Analysis • Identify, segment & prioritize customer • User Profiling (how many, how often, from where) • Identify & prioritize CTQ’s • Interviews, surveys, or focus groups • Measurement Plan • Acceptance Criteria • As-Is Process Documentation • QFD to determine how to satisfy CTQ’s • Benchmarking (within your team, within company, external) • To-Be Process Map/High-Level Solution • Make vs. Buy Analysis • Vendor/Technology Selection • Detailed Functional Specification • Prototype (use to iteratively refine functional specification) • Define Test Cases • Final Project Schedule and Project Plan • Phased Rollout Schedule • End-User Communication and Marketing Plan • Technical Specification • Interface Design • Application Architecture • Information Architecture (DB) • Server Architecture • Code Reuse Strategy • System FMEA • Security Plan (engage SSO team) • Backup & DR Plan • Monitoring Solution • Peer Technical Reviews • Packaged Software Customization Review • Help Desk Strategy • Purchase Hardware and Software • Schedule Stress Test and Security Review • Code Application • Develop User & Training Documentation • System Documentation • Application Kit (for Production Support) • Help Desk Documentation • Unit Test • Integration Test • Browser Lab Test • Peer Code Review • Freeze Code • Performance & Load Test • Security Code Review • Data Migration • Production Deployment • Preliminary Acceptance Testing • Launch Monitoring Tools • User Training • Production Pilot • Update System FMEA • Transition to Production Support • Transition to Help Desk • GO LIVE • Performance and Usage Monitoring • Issues Log • Feedback Management • Bug Fixes and Further Optimization • Final Acceptance Testing and CTQ Measurement • Document & Share Best Practices