Session 1: Managing & Defining Black Belt Projects

• DMAIC versus DMADV projects
• Scoping complex cross-functional projects
• Value stream mapping as a scoping tool
• Aligning the project to business strategy
• Managing project reviews (tollgates)
• Considering project risks

Session 2: Value Stream Mapping

• Introduction to Value Stream Mapping
• Creating a Current State Map
• Using VSM as a Scoping Tool
• Identifying the Opportunities

Session 3: Data Collection

• The role of data collection planning throughout a DMAIC project
• Use of Is/Is Not to find gaps in knowledge
• Understanding variation
• Selecting what to measure
• Calculating sample size
• Sampling considerations
• Developing a robust data collection plan
• Guidelines for survey sampling

Session 4: MSA for Business Projects

• MSA fundamentals
• Alternative approaches to checking measurement error in a business process project context
• Practical validation of the measurement system
• Attribute agreement analysis
• Type II studies (overview)

Session 5: Process Capability & Process Control

• Assessing process control
• Anatomy & use of control charts
• Applications of SPC charts for variable and attribute data
• Understanding process capability
• Calculating process capability for continuous and attribute data
• Selecting appropriate capability metrics & indices

Session 6: Advanced Statistical Approaches

• Understanding probability distributions for variable and attribute data
• Dealing with non- normal data
• Capability analysis for non-normal data
• Statistical process control charts for non-normal data
• The central limit theorem
• Understanding and using data transformations

Session 7: Analyse Phase

• Verifying the root cause
• Taking a structured approach to data analysis
• Links to the cause and effect diagram
• 5 Why approach to problem solving
• Box plots & scatter diagrams
• Significance testing approach
• Tips for summarising and presenting the analysis

Session 8: Hypothesis Testing

• Use of inferential statistics
• Writing a hypothesis statement
• Setting a confidence level
• Understanding the P-Value
• Tests for variable and attribute data
• Power & sample size
• Non-parametric techniques

Session 9: Intro to DOE

• Overview of DOE techniques
• Optimisation challenge
• Applications of DOE techniques

Session 10: Optimising the Process

• Regression analysis
• Understanding correlation
• Introduction to simple linear regression
• Introduction to multiple regression

Session 11: Situational Leadership

• Transformational leadership
• Influencing change
• Concepts and models for change
• Persuasion campaigning

Session 12: Coaching Improvement Teams

• The key skills of coaching
• The coaching continuum expert to discovery
• Using the GROW model

Session 13: Implementing Control

• Key steps of the Control phase
• Confirming the improvement
• Developing a control plan
• Different types of process control
• The principle of mistake proofing
• Monitoring effectiveness
• Closing the improvement project