Role-Based Programme
RB1326

AI for Process Excellence & Continuous Improvement

Process Intelligence, Root-Cause Analysis & Operational Transformation

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Develop practical AI capabilities for process analysis, operational excellence, root-cause investigation, and continuous improvement.
  • Apply AI to identify bottlenecks, waste, process variation, recurring failures, control gaps, and improvement opportunities.
  • Use AI to strengthen process mapping, problem-solving, SOP improvement, action planning, and performance reporting.
  • Improve continuous-improvement decisions through structured prioritisation, evidence-based analysis, impact assessment, and implementation planning.
  • Apply responsible AI practices related to operational data, process recommendations, accuracy, confidentiality, governance, and human validation.

Tools covered

Generative AI AssistantsAI Search & ResearchProcess MappingWorkflow AnalysisRoot-Cause AnalysisWaste & Bottleneck AnalysisKPI AnalysisProcess Mining ConceptsImprovement PrioritisationSOP OptimisationContinuous Improvement AnalyticsExecutive Summarisation

Who should attend

  • Process Excellence Managers
  • Continuous Improvement Managers
  • Operational Excellence Professionals
  • Process Improvement Specialists
  • Business Process Analysts
  • Process Managers
  • Lean Practitioners
  • Six Sigma Practitioners
  • Operations Managers
  • Quality Improvement Professionals
  • Transformation Professionals
  • Business Excellence Professionals
  • Operations Analysts
  • Process Owners
  • Operational Excellence Leaders

Prerequisites & Participant Readiness

  • Experience in process improvement, operational excellence, business operations, quality, transformation, or continuous improvement
  • Familiarity with process mapping, KPIs, root-cause analysis, SOPs, and improvement initiatives
  • Basic familiarity with Generative AI tools is recommended
  • Ability to interpret operational and process information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, and AI assistants
  • Exploring AI applications across process analysis, problem solving, documentation, and improvement
  • Understanding how AI complements Lean, Six Sigma, BPM, process mining, and operational excellence approaches
  • Recognising hallucinations, unsupported recommendations, and process-analysis limitations
Practical activities
  • Mapping the continuous-improvement lifecycle to practical AI applications
  • Identifying high-value versus high-risk process use cases
  • Comparing traditional and AI-assisted improvement workflows

Scenarios

High-Turnaround-Time Process to Future-State Redesign

Process Mapping → Performance Data → Bottleneck Analysis → Waste Identification → Root-Cause Analysis → Improvement Options → Future-State Design → Implementation Plan

Participants use AI to analyse a simulated process with excessive turnaround time, identify bottlenecks and non-value-added activities, and design a streamlined future-state workflow.

Recurring Operational Defects to Continuous Improvement Roadmap

Defect Data → Pareto Analysis → Root-Cause Hypotheses → Process Variation → Corrective Actions → Automation Opportunities → KPI Targets → Improvement Roadmap

Participants use AI to investigate recurring operational defects, prioritise the most significant causes, develop corrective and preventive actions, and create a structured continuous-improvement roadmap.

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