Role-Based Programme
RB1609

AI-Powered Continuous Improvement & Lean Six Sigma

Smarter Process Analysis, Root Cause & Performance Improvement

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Continuous Improvement and Lean Six Sigma across process analysis, waste identification, root-cause investigation, and performance improvement.
  • Apply AI-assisted techniques to analyse process data, identify variation, recurring defects, delays, bottlenecks, and improvement opportunities.
  • Use structured prompting for process mapping, DMAIC support, root-cause questioning, solution generation, and management reporting.
  • Explore AI-supported approaches for prioritising improvement initiatives, tracking actions, and measuring process performance.
  • Build responsible AI-assisted improvement workflows while maintaining data accuracy, evidence-based analysis, professional judgement, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisProcess Mapping AIRoot Cause Analysis AILean Six Sigma AnalysisWorkflow Automation

Who should attend

  • Continuous Improvement Professionals
  • Lean Six Sigma Practitioners
  • Process Excellence Professionals
  • Quality Managers
  • Quality Executives
  • Operational Excellence Professionals
  • Process Improvement Analysts
  • Business Process Professionals
  • Lean Practitioners
  • Six Sigma Yellow Belt Professionals
  • Six Sigma Green Belt Professionals
  • Quality Assurance Professionals
  • Process Owners
  • Continuous Improvement Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of process improvement, Quality Management, Lean, or Six Sigma concepts
  • Familiarity with process maps, performance data, defects, delays, or improvement projects is helpful
  • Basic computer, spreadsheet, and document-handling skills
  • No AI or programming knowledge required
  • No previous AI training required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to process improvement
  • Identifying AI applications across Lean, Six Sigma, DMAIC, process analysis, and reporting
  • Understanding AI assistance versus process-owner and improvement-professional judgement
  • Recognising limitations such as incomplete data, hallucinations, weak assumptions, and unsupported causes
Practical activities
  • Mapping a typical Continuous Improvement lifecycle
  • Identifying repetitive and information-intensive improvement activities suitable for AI assistance
  • Comparing a traditional process-improvement task with an AI-assisted approach

Scenarios

Process Problem to DMAIC Improvement Plan

Business Problem → Define → Baseline Data → Process Map → Root Cause → Improvement Options → Control Plan

Participants use AI to structure a sample process-improvement problem, analyse the workflow, identify evidence-based root causes, and prepare a practical DMAIC improvement plan.

Operational Data to Lean Improvement Opportunity

Process Data → AI Analysis → Delays / Defects / Waste → Pareto Priorities → Improvement Ideas → Impact / Effort Review → Management Summary

Participants use AI to analyse sample operational data, identify high-impact improvement opportunities, and prepare a management-ready Lean improvement recommendation.

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