Process Simulation & Analysis
Concept & Motivation
A process model tells you how work should flow. Process mining tells you how it actually flows. Simulation tells you what would happen if you changed it.
Most organizations stop at the first step: they draw process models, perhaps in a workshop, and file them. The models become documentation — static, rarely updated, disconnected from decisions. The real power of process management begins when models become analytical tools.
This course takes you from static diagrams to dynamic analysis. You learn to simulate processes, mine reality from system logs, and build digital twins of your operations.
What You’ll Learn
- From models to simulation — discrete-event simulation of BPMN processes. How to assign timing, resources, and probabilities to your models and observe system behavior
- Petri nets and Coloured Petri nets — the formal mathematical foundation of process simulation. Taught as a practical tool: states, transitions, tokens, firing rules. Why understanding the formalism makes you better at interpreting simulation results
- Process mining — extracting real process flows from event logs (ERP, CRM, workflow systems). Discovery, conformance checking, and enhancement. Seeing what actually happens vs. what you modeled
- Scenario analysis — what-if simulations for capacity changes, timing variations, cost structures, and demand fluctuations. Testing process changes before you implement them
- Digital twins for processes — building a living model that stays synchronized with operational data. The bridge from periodic analysis to continuous monitoring
- Integration with decision support — feeding simulation results into decision frameworks. When to automate, when to alert, when to escalate
- Tool landscape — Celonis, ProM, Signavio, and self-hosted alternatives. What each does well and where they overlap
Who This Is For
- Process managers and analysts who have models and want to make them predictive
- Operations excellence teams seeking data-driven process improvement beyond Lean/Six Sigma checklists
- IT and data teams connecting process management with analytics and business intelligence
- Quality and compliance professionals in regulated industries who need to verify process conformance systematically
Prerequisite: BPMN modeling skills (from c-bpm-1 or equivalent professional experience).
Format & Duration
2-day seminar (on-site). Day 1: simulation fundamentals, Petri nets, and process mining with hands-on exercises using sample data. Day 2: participants simulate and mine their own processes (bring models from c-bpm-1 or your organization), build scenarios, and present findings.
What Makes This Course Different
Simulation and process mining are usually taught in separate courses, by separate communities, using separate tools. This course integrates them — because in practice, you need both. Mining tells you where you are. Simulation tells you where you could be. Together, they close the loop.
The academic rigor (Petri net theory, conformance metrics, statistical analysis of simulation output) is real — because sloppy simulation gives confidently wrong answers. But every formal concept is immediately applied to operational processes, not toy examples.
Participants use our Aipokit platform to build process digital twins — seeing how simulation, mining, and real-time monitoring come together in a single environment.
Next Steps
Graduates are well-prepared for Digital Twins for Operations (c-dtwin-1), which extends process twins to full operational twins covering production, maintenance, and asset management.