Understanding how Six Sigma can be applied to industry challenges will help you produce exemplary results for your organization.
Six Sigma Online Training
Our online training course lets you learn at your own pace and focuses on real world scenarios so you can get the most from your training time. To be effective, you need a solid foundation that will let you identify and reduce variation in any process.
Register Online
Price per student: 1,850.00
- Web-Based Training
- Focused on Applying Six Sigma
- Includes real world case studies
- Includes all necessary project tools
- Accredited by the Council for Six Sigma Certification
Here Is What You Will Learn
Look through our Table of Contents to see more information.
Six Sigma Overview
- What is Six Sigma?
- A Specific Statistical Definition
- A Problem-Solving Approach
- A Management Philosophy
- Ideal Six Sigma Implementation
- Why do we use Six Sigma?
- Isn’t 99% Good Enough?
- Where is Industry Today?
- Industry’s Challenge
- Must We Change?
- Six Sigma – Part of The Solution
- The Promise of Six Sigma
- Three Levels of Six Sigma Benefits
- How do we use Six Sigma?
- Six Sigma Problem Solving
- The Six Sigma DMAIC Process
- The Six Sigma Knowledge Funnel
- Six Sigma: Before and After
Common Cause and Special Cause Variation
- Understanding and Using Control Charts
- Process Variation Scenario
- Introducing the Control Chart
- Interpreting Control Charts
- Special Cause: Process Shift
- Special Cause: Process Trend
- Is Every Picture Worth The Same 1,000 Words?
- Process Stability
- Control Charts for Making Decisions
- Why Control Charts?
- Control Charts: Special Cause = Process Information
- Western Electric Rules
- Common Cause Also Provides Information
- Control Charts In Problem Solving
- Control Charts for Leaders
- Misinterpreting 3 Data Points
- Control Charts: Leadership Imperative
- Variation Management Paradox
- Selecting and Creating Control Charts
- Which Chart? Initial Answers
- Generating an “Individuals” Control Chart
- Generating “Individuals” Chart, Part 2
- How Many Observations Are Enough?
- How Many Observations Are Too Many?
- Usage Example (Case Study)
- Using a Control Chart
Project Selection, Scope and Kick-off
- The Project Charter
- Project Charter Template
- Problem Statement
- Project Scope
- Performance Goals
- Business Benefits
- Team Members
- Support Required
- Issues / Risks / Constraints
- Basic Meeting Management
- Managing Meetings
- Agendas and Minutes
- Purpose / Process / Payoff
- Team Roles
- Seeking Consensus
- The Parking Lot
- Meeting Management = Meeting Productivity
- Selecting Appropriate DMAIC Projects
- Ideal DMAIC Projects
- DMAIC Project Alarms
- Project Selection Guidelines
- DMAIC or DFSS
- Managing Project Scope
- A Word About First Projects
- Project Complexity
- DMAIC and Scope Reduction
- Successful Project Launches
- Project Launches
- Preliminary Meeting
- Team Kick-Off
- Finalize Project
- Adjust Team Roster
Customers and Metrics
- Customer Focus
- Priorities In Six Sigma
- Jack Welch Speaks
- Outcomes vs. Measures
- Why Use Data
- Customer Needs Are Obvious
- Who Says We Need Data?
- Data Throughout DMAIC
- Procedure: Developing Process Metrics
- Developing Effective Process Metrics
- A Word of Caution
- Identify Process Outputs: Service As A Product
- Introductory Concept: SIPOC
- SIPOC In Context
- Transactional Process Outputs
- Service Products
- Practice
- Establish Customer Types
- Describing Our Customers
- How About Internal and External Customers?
- Establish Customer Types Based On How They Use Service Products
- Broker Customers: Special Challenges
- Modifier Customers: Special Opportunities
- Customer Types and SIPOC
- Prioritize Requirements
- Multiple Customers Equal Multiple Priorities
- List Potential Requirements
- Organize The List
- Prioritize: Multi-Voting
- Other Prioritizing Options
- Process – Defined
- Process Role Definition
- Service-Profit Chain and Its Link to Customers
- Customers – Needs and Requirements
- Step #1 – Know What A Customer Is
- Step #2 – Segment Customers
- Step #3 – Determine Customer Needs and Requirements
- Voice of Customer (VOC)
- The (Noriaki) Kano VOC Model
- Using The Kano Model: Must-Be
- Using The Kano Model:1-Dimensional
- Using The Kano Model: Delighters
- Kano Model Migration
- Kano’s Model – Examples
- Kano’s Model – Example
- Bringing It Together – The SIPOC Tool
- Steps in Using the SIPOC
- Questions To Help With SIPOC
- Project Example
- Convert Requirements To Metrics (CT Tree)
- Critical To
- CT Tree: From Outcomes to Measures
- Benefits Of CT Trees
- Deploy Operational Definitions
- Examples of Operational Definitions
- Example: Operational Definition
- Never Assume that Everyone is Using the Same Definition
- Data Collection Plan
Basic Probability and Statistics
- Introduction
- Probability – Independent Outcomes
- The Basis of Probability Theory
- Rolling A Single Die
- Independent Events: Blackjack
- Independent Outcomes On The Job
- Probability – Dependent Outcomes
- What Happens When We Roll A Pair Of Dice
- Multiplying The Probabilities
- Blood Types
- Probability – Mixed Outcomes
- What If We Mix Independent and Dependent Events?
- Probability of Rolling A Seven?
- Blood Types and Mixed Outcomes
- Continuous vs. Attribute Data
- Continuous and Attribute Data
- How Many Samples?
- Dealing With Attribute Data
- np Chart (Simulated Data)
- Introducing The Normal Distribution
- The Normal Distribution
- Introducing Normal Probabilities
- Summarizing The Normal Distribution
- A “Six Sigma” Process
- Statistics – Descriptive vs. Inferential
- Descriptive vs. Inferential Statistics
- Statistics – Central Tendency (Mean and Median)
- Example Data Set
- Central Tendency
- Median vs. Mean
- When To Use the Median
- Statistics – Dispersion (Standard Deviation and Variance)
- Standard Deviation
- Computing “s”
- Variance and Standard Deviation
- Practice #1
- Statistics – Sampling Issues – Population vs. Sample
- Population vs. Sample
- Symbols: Population vs. Sample
Process Capability
- Review: Normal Distribution
- The Normal Distribution
- Six Sigma Process
- Process Capability Terminology
- Normal Probabilities
- Moving Forward
- Continuous Data
- Z Value Equations
- Example #1: Time from arrival in ED until Treatment (aka “Door to Doc”)
- Applying the Normal Distribution
- Example #1: Now We Use the Equations
- Example #1: Interpreting ZU=12
- Example #1: Z → Probability
- Example #1: Summary Results
- Practice
- Practice Demonstration: Scenario #1
- Terminology: Z and Cpk
- Easier Still: COMPASS®
- Attribute Data
- Units or Opportunities?
- Opportunity Counting: Beware!
- Example #2: Data and Equations
- Short-term vs. Long-term Variation (ZST vs. ZLT)
- Practice
- Converting Between Z and PPM
- Z ←→ PPM: 4 Options
- Rules of Thumb: Z ←→ PPM
- Z ←→ PPM Lookup Tables
- Z ←→ PPM Graph
- Z ←→ PPM Equations
Basic Measurement Systems
- Measurement: A Process With Variation
- Outcome of DMAIC Projects
- Measurement Is A Data-Producing Process
- Even “High-Tech” Systems Experience Significant Measurement Variation
- The Ideal Measurement System
- Components of S2 Measurement (“Measurement Variation”)
- It’s a Matter of Integrity
- Defining the perfect MandM®
- Start with Operational Definitions
- Next: Define the scope of your intended MSA
- Repeatability in a Gage R&R Study
- Reproducibility in a Gage R&R Study
- Basic Terminology, Concept and Requirements
- R&R Procedure
- Generating R&R Template in COMPASS®
- COMPASS® R&R Template
- Entering R&R Data
- Interpreting R&R Output
- How Good Is Good Enough?
- Dealing With Unacceptable R&R
- R&R After Improve Phase
- R&R’s Moving Target
- Data integrity has the final word
Cost of Poor Quality: COPQ
- More Traditional View Of COPQ
- “Traditional” COPQ Model
- Containment Is Costly
- Six Sigma View Towards COPQ
- Pitfalls of Doing Inspection in Quality
- American Society for Quality (ASQ) COPQ Categories
- ASQ COPQ Categories
- COPQ “Iceberg”
- Applying COPQ
- COPQ Worksheet
- Approaches to Consider
- Pitfalls to Avoid
Yield and the “Hidden Factory”
- By Way of Introduction
- Formal vs. Informal Inspection
- Formal Inspection
- Not All Errors Make It to Formal Inspection
- Informal Inspection and Hidden Rework
- Informal Find-and-Fix Works, Right?
- Quality And Rework
- Terminology
- Poisson Distribution and Throughput Yield
- Rolled Throughput Yield
- The YRT “Bucket Brigade” Concept
- Let Us Try an Example
- YRT Example: Step #1
- YRT Example: Step #2
- YRT Through the Entire Process
- YRT: Computation Shortcut
- Z-Values
- YTP and Process Capability
- Excel Formula: Using Yield to Estimate Z
- Yield and Z in Non-Repetitive Processes
- Hidden Factory
- Resources for Rework
- Rework and Resources
- Higher DPU Processes and Rework
- “Hidden Factory” For High DPU
Basic Process Analysis
- Getting Started: Analyze Strategies
- Flow Charts Overview
- Why Flow Charts?
- Benefiting From Flow Charts
- Flow Chart Case Study
- Review: Flow Chart Basics
- Getting More out of Flow Charts
- The Mapping Challenge: How Much Detail?
- Guidelines: Flow Chart Detail
- Value-Added Analysis
- Value / Non-Value Grid
- Value / Non-Value Analysis
- List Expansion
- List Expansion and Reduction Opportunities
- Expansion vs. Reduction
- List Expansion: Traditional Brainstorming
- List Expansion: Post-it Blitz
- List Reduction
- Right After List Expansion, Just Before List Reduction
- The Fish-Bone Diagram
- Fish-Bone Categories
- Affinity Diagrams
- Multi-Voting
- Multi-Voting Silly Example: Prioritizing Beer Characteristics
- Nominal Group Technique (NGT)
- IPO Diagram / CN(X)
- Input-Process-Output Terminology
- Many Inputs, Few Outputs
- The IPO Diagram
- Basic Data Display Techniques
- Benefits of Graphical Tools
- Pareto Charts and Pivot Charts
- Creating a Pareto Chart in COMPASS®
- Resulting Pareto Chart
- Histograms
- Histograms – Pros and Cons
- Creating Histograms in COMPASS®
- COMPASS® Histogram Output
- Grouping Histograms in COMPASS®
- After Eliminating Bimodality
- Box Plots
- Grouped Histogram or Box Plot?
- From Histogram to Box Plot
- Box Plot Using Histogram Data
- Box Plot Scenario
- Creating Box Plots in COMPASS®
- Box Plot Results
Basic Hypothesis Testing
- Standard Error of the Mean
- Repeated Samples from a Process
- Standard Error of the Mean and the Central Limit Theorem
- Example – Central Limit Theorem in Use
- Confidence Interval of the Mean
- Recall: Normal Distribution
- Normal Distribution Using the Standard Error of the Mean
- Example #1a: Confidence Interval of Person-Hours
- Example #1a: Using COMPASS®
- Standard Error of the Mean and Confidence Intervals with Hypothesis Testing
- The Process of Learning
- Design of Experiments
- Design of Experiments: How Do We Learn?
- Design of Experiments – Methods
- Trial and Error
- Trial and Error Experiments
- OFAT
- OFAT (One Factor at a Time) Experiments
- Full Factorial
- Full Factorial Experiments
- Fractional Factorial
- Fractional Factorial Experiments
- Basics of Hypothesis Tests COMPASS® P-Value
- 4 Ways X Impacts Y
- How Sure Are We?
- Process: The Hypothesis Test
- The P-Value
- Tests of Means: Single Data Set
- Example #1b: Scenario
- Example #1b: Hypothesis Test Process
- Example #1c: Another Approach to the Same Hypothesis Test
- Example #1c: Select t-Statistic and Compute t
- Example #1c
- How Many Tails on that Test?
- 1-Tail vs. 2-Tail Tests
- A Non-Statistical Issue
- 2 Data Sets
- Scenario: Comparing Two Data Sets
- Example #2: Start with Descriptive Statistics
- Example #2: Descriptive Stats Output
- Example #2: 2 Sample t-Test (Part 1)
- Example #2: 2 Sample t-Test (Part 2)
- Example #2: Output COMPASS® 2 Sample t-Test
- Test of Variances
- Why the F-Test?
- Example #3a: Manual F-Test Procedure
- Example #3a: Manual F-Test Computations
- Example #3b: COMPASS® F-Test and More (Part 1)
- Example #3b: COMPASS® F-Test and More (Part 2)
- Example #3b: COMPASS® “Comparison Tests” Output
- Sequencing Hypothesis Tests
Transactional Six Sigma
- Summary: Transactional Six Sigma
- Transactional Process Defined
- 10 Financial Six Sigma Projects
- Process Summary: Transactional Six Sigma
- Flow Chart Varieties
- Interrelationship Diagraph
- Relationship Maps
- Relationship Map (RM) Example: Lemonade Stand
- Developing the RM: The Relationship Table
- Problem Solving Using Relationship Maps
- RM Disconnects
- Swim Charts
- Swim Chart of a Sub-Process: Building the Lemonade Stand
- Swim Chart Considerations
- Why do Disconnects Exist?
- Work Flow Layouts
- Work Flow Layouts
- Identifying Improvement Opportunities
- Organizational Drivers
- Scientific Basis of Consequence Analysis
- Consequence Analysis Worksheet
- Process: Consequence Analysis Worksheet
- Consequence Analysis in the News: Accounting Scandals in Publicly Held
- Companies
- Process: Developing Should-Be
Data Analysis
- Selecting Hypothesis Tests
- Basis for Selecting Hypothesis Tests
- Selecting Hypothesis Tests
- Analysis of Variance (ANOVA)
- Overview of ANOVA
- ANOVA Scenario
- Example: ANOVA with COMPASS®
- Interpreting COMPASS® ANOVA Output
- Taking ANOVA Further
- Tests of 2 Proportions
- Overview: 2-Proportion Test
- Proportion Test Scenario
- Proportions Test Using COMPASS®
- Taking it Further
- Basic Linear Regression
- Linear Regression Overview
- Prediction Equation
- Concept of R2
- Example: Linear Regression
- Linear Regression using COMPASS®
- Linear Regression Output
- Correlation = Causation?
- Advanced Regression Topics
- Hypothesis Testing Tradeoffs
- Decision Errors
- Hypothesis Tests and Sample Sizes
- Determining Sample Sizes
- Granularity Guidelines: t-test
- When to Consider ( α = β) ≠ 0.05
- Pivot Tables
- More than One X
- 2 or More Factors: Excel Pivot Table and Pivot Chart
- Building the Pivot Table
- Pivot Table: Selecting the Fields
- Pivot Table Output
- Pivot Chart – After Editing
- Other Uses for Pivot Tables
- Multi-Vari Charts
- Multi-Vari: Sources of Variation
- Logging Multi-Vari Data
- Creating a Multi-Vari in COMPASS®
- Interpreting the Multi-Vari Chart
- Criteria for Using Multi-Vari
- Analyze This!
Generating Solutions
- Open-Narrow-Close
- Generating Solutions
- Brainstorming
- Modified Brainstorming
- Best Practices
- Organizing Solutions
- Selecting Solutions
- Multi-Voting (15 Items or Fewer)
- Selecting Solutions: Multi-Voting Example
- Selecting Solutions: Multi-Voting Example Results
- Pay-Off Matrix
- Selecting Solutions: Pay-Off Matrix Example
- Musts/Wants Criteria
- Selecting Solutions: Musts/Wants Example
- Project Selection Matrix
Failure Modes and Effects Analysis: FMEA
- Introduction to FMEA
- The Concept Of Risk
- Process and Product Risk
- Producer and Customer Risk
- FMEA: Dealing with Potential Failures
- The FMEA Process
- FMEA Template
- Invoking COMPASS® FMEA Template
- Overview: COMPASS® FMEA Template
- Failure Modes vs. Effects
- FMEA Terms
- More Terms
- Modes vs. Effects
- Risk Priority Number (RPN)
- RPN Elements
- Rating RPN Elements
- How to Use FMEA
- The FMEA Process
- Hints To Make FMEA Work
- More Hints
- Step 6: Develop Action Plans
- Step 7: Follow-Up
Change Management
- Why People Resist Change
- How Can We Help Reduce Uncertainty?
- Uncertainty and Perceived Threats
- Influencing Individuals’ Behavior
- Individuals We Want to Influence
- Communicate to Motivate
- Specifying the Desired Behaviors
- Handling Performance Gaps: A 3-Step Process
- Challenges of 3-Step Process
- Step #1: Describe Performance Gap
- Step #2: Explore How We Can Help
- Step #3: Explain Consequences
- Managing Organizational Change
- Non-Delegable Roles of Leadership
- 10 Questions Leaders Should Answer
- 10 Questions Leaders Should Ask
- Driving Cultural Change
- Aligning the Reward System
- Influencing Process Change
- 10 Ways To Sell Change
- Confirming Project Stakeholders
- Confirming Project Stakeholders: Example
- Creating the Need for Your Solutions
- Threat-Opportunity Matrix
- Force Field Analysis
- Restraining Force Strategy
- Resistance Strategies
- Questioning Systems and Structures
- Piloting
- When to Pilot
- Steps for Pilots
- Tips for Pilots
Design for Six Sigma and Lean
- Design for Six Sigma (DFSS)
- What is DFSS
- DMAIC and DFSS Differences
- DFSS = DMADV
- Map of DFSS and DMAIC
- Introduction to Lean Principals
- What is Lean
- Get Rid of the Waste
- Examples of Muda
- Five Principles of Lean Thinking
- Value
- Value Stream
- Value-Added / Non-Value-Added
- Rework
- Other Non-Value-Added Activities
- Flow
- What Affects Flow?
- Pull
- Perfection
- Linking Lean Thinking and Six Sigma
Statistical Process Control
- Process Improvement Monitoring
- Monitoring Strategies
- Example
- Patient Evaluation Audit Scores
- Run Chart
- Central Tendency
- Frequency Distribution
- Statistical Process Control Methods
- Statistical Process Control
- Control Chart Review
- Control Chart Selection
- Selecting a Control Chart
- Application for Control Phase in Six Sigma
- Process: Launching SPC
- SPC and Statistical Software
- Recall: CNX
- Revising Control Limits
- Can Processes Change After DMAIC?
- Criteria for Computing New Control Limits
Control Plans
- Introduction
- Why Control Plans
- What is a Control Plan?
- What to Include
- Process Improvement Hand-Off: The Response Plan
- Example – Completed Response Plan
- Backup Documentation and Data
- Backup Documentation Examples
- Implementation
- Selected Project Management Questions
- Stakeholders and Resources
- Milestone Examples
- Resources: Planning the Rollout
- Resources: Planning for Training
- Risk Management: Issues to Anticipate
- Sustaining Gains
- Compliance Audits
- Overview: Audit Process
- Auditor Responsibilities
- Corrective Action
- Final Comments
External Benchmarking and National Patient Safety Goals
- Sources for External Reporting and Benchmarking
- Joint Commission (JCAHO)
- JCAHO Reviewable Sentinel Events
- JCAHO National Sentinel Event Statistics
- JCAHO National Sentinel Event Statistics – Root Causes
- Research into Action – National Patient Safety Goals
- National Patient Safety Goals for 2005
- Center for Medicare and Medicaid Services (CMS)
- CMS Initiative
- Sample CMS Report
- UHC
- Solucient
- Patient Satisfaction
- Report Cards
- Issues with Report Cards
- Pay for Performance (P4P)
- Issues with Pay for Performance
Human Factors and Usability
- What Are Human Factors?
- Why Human Factors?
- Taking Human Factors Into Account
- Donald Norman’s Principles of Good Design
- Other Things To Consider
- Some Factors Affecting Performance
- What Can Go Wrong?
- Usability: ISO 9000 Standards
- Usability
- Usability: The 5 E’s
- Case Example: OR Suite Set-Up
Malcolm Baldrige National Quality Award
- The Baldrige Award
- Core Values
- Scoring
- Scoring Matrix: Categories 1-6
- Pursuing the Award
- Baldrige-Based Assessments
- Management and Resources
- Example: Assessment Outcome
- Example: Prioritizing the Opportunities
- Example: Clustering of Opportunities
- Example: Customized Six Sigma Rollout
- Conclusions
The Balanced Scorecard
- Balanced Scorecard’s Four Perspectives
- Learning and Growth Perspective
- Internal – Business Process Perspective
- Customer Perspective
- Financial Perspective
- Additional Perspectives
- Critical Requirements
- Applying the Balanced Scorecard
- Balanced Scorecard and Baldrige Criteria
- Balanced Scorecard and Six Sigma