
Introduction to the AI-Powered Lean Six Sigma & DMAIC
Develop a clear project charter that outlines the problem, business case, and scope.
Translate customer complaints (VOC) into measurable project objectives.
Collect and validate baseline loan approval process data (e.g., cycle time, SLA compliance).
Define key process metrics and establish a measurement system that ensures data accuracy.
Calculate baseline performance, including averages, variation, and Sigma level.
Identify patterns and bottlenecks in the loan approval process using VOC themes and data analysis.
Develop and prioritize hypotheses about root causes of loan approval delays.
Apply structured problem-solving tools (e.g., fishbone, 5 Whys) to validate root causes with evidence.
Generate, assess, and prioritize improvement ideas that directly address root causes.
Select solutions based on feasibility and impact to reduce cycle time.
Design small-scale pilots to test improvements and forecast benefits.
Develop a control plan with clear metrics, monitoring frequency, and ownership assignments.
Establish escalation rules and communication practices to sustain improvements.
Standardize best practices (SOPs, dashboards, checklists) to prevent regression and ensure cycle time stays at or below target levels.
AI case studies from multiple industries.
Real world AI case study from Penske Trucking translated into DMAIC terms.
Lean Six Sigma + AI: A Practical Walkthrough of DMAIC with ChatGPT
Learn how AI can support Lean Six Sigma projects — one phase at a time.
This course provides a straightforward, hands-on walkthrough of the DMAIC methodology using a hypothetical business scenario. In each phase of DMAIC, you’ll see exactly how ChatGPT can be used as a support tool to speed up thinking, generate ideas, organize information, and help you execute Lean Six Sigma problem-solving more effectively.
This is not a course about advanced automation or enterprise AI systems.
It is a practical demonstration of how everyday professionals can use ChatGPT inside the Lean Six Sigma framework to enhance clarity, structure, and execution during a project.
What You’ll Learn
• How the DMAIC framework works in a real project scenario
• How to use ChatGPT as a thinking partner in each DMAIC phase
• How AI can help you organize definitions, problem statements, measures, analysis ideas, and improvement options
• How to structure a Lean Six Sigma project using a simple case study
• How AI can assist with documentation, brainstorming, and insight-generation
What This Course Does Not Cover
(included to prevent inaccurate-expectation reviews)
• It does not teach automation tools or coding
• It does not cover advanced statistics or statistical software
• It does not replace formal Green Belt or Black Belt training
• It does not demonstrate every Lean Six Sigma tool — only those used in the example
This course is focused on one clear goal:
Showing how ChatGPT can support the execution of a Lean Six Sigma DMAIC project.
Who This Course Is For
• Green Belts, Black Belts, and Lean Six Sigma students
• Professionals who want a practical example of DMAIC with AI support
• Anyone curious about how AI can fit naturally into day-to-day problem solving
• Business professionals seeking a simple, real-world demonstration — not theory
Course Outcome
By the end of this course, you’ll understand how ChatGPT can be used as a practical enabler of Lean Six Sigma execution.
You’ll walk away with a clear, realistic picture of what AI can (and cannot) do to support DMAIC in real projects.