SS-0702-CS-GB-01-OS : Six Sigma for Business Process Improvement [2 Days | 16 Hours of Study]



Course Description
In this 2-day course, you will the five phases of Six Sigma methodology, acronymed as DMAIC. You will gain insight into definition, measurement, analysis, improvement and control techniques to improve overall process capability for better results. This primer on Six Sigma serves as the foundation for Six Sigma Black Belt role that leads a Six Sigma project.


Course Objectives
As a Quality Professional on a business process improvement project, you should be able to : -
  • Define the scope of work through well documented Voice of the Customer
  • Collect data to measure the process variables
  • Analyze the measurements for improvement actions
  • Implement improvement steps to increase the capability of a business process
  • Control the process for sustenance of improved process capability


Who Should Attend

Anyone interested in assuming the role of leading a Lean Six Sigma project that is lauched with an aim to improve the affected business process(es).



Course Outline
    Session 1: Introduction
  • History of Quality
  • Evolution of Six Sigma
  • Overview of Six Sigma DMAIC Processes


  • Session 2: Stakeholders Customers and Financial Measures
  • Identifying stakeholders
  • Benefits of Balanced Scorecard
  • Determining critical Vital Xs
  • Voice of the Customer
  • Data collection and analysis
  • Data types
  • Conducting surveys
  • Quality Function Deployment (QFD)
  • Benchmarking
  • Financial measures


  • Session 3: Setting Up a Six Sigma Project
  • Charter negotiation
  • Initiating teams
  • Stages of team evolution
  • Handling conflicts
  • Management styles
  • Brainstorming
  • Nominal Group Technique
  • Field Force Analysis
  • Multivoting


  • Session 4: Define
  • Organizational Hierarchy
  • Process Maps
  • Pareto Chart
  • Problem statement
  • Established Metrics


  • Session 5: Measure
  • Conversion of Data Types
  • Collecting data using checksheet
  • Other data collection techniques
  • Validation techniques
  • Important characteristics of measurement systems
  • Gauge R&R Study
  • Probability distributions
  • Data mining
  • Run charts
  • Detailed process maps and Pareto charts
  • Process costs
  • Process capability
  • Cost of Poor Quality


  • Session 6: Analyze
  • Ishikawa diagrams
  • Failure Mode and Effects Analysis
  • Hypothesis testing
  • Process capability study
  • Special and common causes of variation
  • DPMO and Sigma level


  • Session 7: Improve
  • Return on Investment
  • Solution Design Matrix
  • Design of Experiments
  • Taguchi Robustness concepts
  • Response surface methodology
  • Selection of solutions for implementation
  • Implementation plan


  • Session 8: Control
  • Control plan
  • Statistical Process Control
  • Lean Enterprise
  • 5S
  • Kaizen
  • KanBan
  • Total Productive Maintenance
  • Measurement System Re-analysis
  • Control plan for sustaining benefits
  • Improved process capability
  • Lessons learned