Model Online / On-Site
Duration
Modules 5 modules

Course Objective & Scope

AI value rarely appears across an entire process; it shows up in specific tasks within it. This course teaches how to make existing workflows visible with SIPOC, swimlane diagrams and value stream mapping, and analyse each step for volume, duration, error rate and knowledge intensity.

Participants practise choosing the right solution type for each task (rules, RPA, machine learning, generative AI, agents) and sizing the opportunity using process data or process mining outputs. In the workshops one of the organisation's real processes is mapped, producing an opportunity map backed by hypothesis cards.

Who Should Attend?

  • Process owners and process improvement (Lean, Six Sigma) specialists
  • Operations, finance, HR and customer service managers
  • Business analysts and enterprise architecture teams
  • RPA and automation Centre of Excellence staff
  • Basic process mapping knowledge helps; no technical background required

Key Takeaways

  • Map a process down to task level using SIPOC and swimlanes
  • Score tasks for AI suitability
  • Justify the choice of rules, RPA, machine learning, generative AI or agents per task
  • Estimate time and cost impact using process data
  • Produce a process opportunity map supported by hypothesis cards

Curriculum

Process Mapping: SIPOC, Swimlane and Value Stream
  • Defining process boundaries and stakeholders
  • Seeing roles and hand-offs with swimlanes
  • Spotting waiting time, rework and bottlenecks
Task-Level Decomposition and Suitability Scoring
  • Breaking tasks into input, decision and output
  • Criteria: repetition, knowledge intensity, unstructured data and cost of error
Rules, RPA, Machine Learning, GenAI or Agents?
  • Decision tree for solution types
  • Hybrid scenarios combining RPA with generative AI
  • Multi-step tasks suited to agents and their limits
Sizing Opportunities with Process Data
  • Calculating volume, cycle time and FTE load
  • Reading opportunities from process mining outputs
  • Rough benefit estimates and documenting assumptions
Opportunity Map and Hypothesis Cards
  • Visualising opportunities on the process
  • Hypothesis, metric and validation method per opportunity
  • Handing over to prioritisation

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