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Process Mining: Extension Mining Algorithms

Process Mining: Extension Mining Algorithms. Ana Karla Alves de Medeiros Eindhoven University of Technology Department of Information Systems a.k.medeiros@tue.nl. Process Mining. Short Recap Extension Techniques Decision Miner Performance Analysis with Petri Nets Summary

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Process Mining: Extension Mining Algorithms

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  1. Process Mining: Extension Mining Algorithms Ana Karla Alves de Medeiros Eindhoven University of Technology Department of Information Systems a.k.medeiros@tue.nl

  2. Process Mining • Short Recap • Extension Techniques • Decision Miner • Performance Analysis with Petri Nets • Summary • Announcements • Presentation Futura Technology

  3. Process Mining • Short Recap • Extension Techniques • Decision Miner • Performance Analysis with Petri Nets • Summary • Announcements • Presentation Futura Technology

  4. Types of Algorithms

  5. Types of Algorithms Process Model Organizational Model Organizational Miner Social Network Miner Analyze Social Network Social Network

  6. Types of Algorithms Compliance Process Model Auditing/Security Conformance Checker LTL Checker

  7. Main Points Lecture 4 • Organizational mining plug-ins can discover • Roles/Teams in organizations • Social networks for originators • Some metrics of social networks are based on ordering relations (e.g., the ordering relations used by the Alpha algorithm) • Conformance Checker assesses how much a process model matches process instances • LTL Checker uses logics to verify properties in event logs

  8. Process Mining • Short Recap • Extension Techniques • Decision Miner • Performance Analysis with Petri Nets • Summary • Announcements • Presentation Futura Technology

  9. Process Mining • Short Recap • Extension Techniques • Decision Miner • Performance Analysis with Petri Nets • Summary • Announcements • Presentation Futura Technology

  10. Types of Algorithms Bottlenecks/ Business Rules Process Model Performance Analysis

  11. Process Mining • Short Recap • Extension Techniques • Decision Miner • Performance Analysis with Petri Nets • Summary • Announcements • Presentation Futura Technology

  12. Process Mining • Short Recap • Extension Techniques • Decision Miner • Performance Analysis with Petri Nets • Summary • Announcements • Presentation Futura Technology

  13. Decision Point Analysis: Main Idea • Detection of data dependencies that affect the rounting the routing of process instances Which conditions influence the choice between a full check and a policy only one?

  14. Decision Point Analysis: Motivation • Make tacit knowledge explicit • Better understand the process model

  15. Decision Point Analysis: Motivation

  16. Decision Point Analysis: Algorithm's Main Steps • Read a log + model • Identify the decision points in a model • Find out which alternative branch has been taken for a given process instance and decision point • Discover the rules for each decision point • Return the enhanced model with the discovered rules

  17. Decision Point Analysis: Algorithm's Main Steps • Read a log + model • Identify the decision points in a model • Find out which alternative branch has been taken for a given process instance and decision point • Discover the rules for each decision point • Return the enhanced model with the discovered rules How can we spot the decision points in a Petri net?

  18. Decision Point Analysis: Algorithm's Main Steps • Read a log + model • Identify the decision points in a model • Find out which alternative branch has been taken for a given process instance and decision point • Discover the rules for each decision point • Return the enhanced model with the discovered rules

  19. Quick Recap Lecture 1: Decision Trees Attributes Classes: Yes/No

  20. Decision Point Analysis: Algorithm's Main Steps • Read a log + model • Identify the decision points in a model • Find out which alternative branch has been taken for a given process instance and decision point • Discover the rules for each decision point • Return the enhanced model with the discovered rules Which elements are the classes and which are the attributes?

  21. Step 4 Training examples for decision point "p0" Discovered decision tree for point "p0"

  22. Decision Point Analysis: Example in ProM

  23. Decision Point Analysis: Example in ProM

  24. Decision Point Analysis

  25. Process Mining • Short Recap • Extension Techniques • Decision Miner • Performance Analysis with Petri Nets • Summary • Announcements • Presentation Futura Technology

  26. Process Mining • Short Recap • Extension Techniques • Decision Miner • Performance Analysis with Petri Nets • Summary • Announcements • Presentation Futura Technology

  27. Performance Analysis with Petri Nets • Motivation • Provide different Key Performance Indicators (KPIs) relating to the execution of processes • Main idea • Replay the log in a model and detect • Bottlenecks • Throughput times • Execution times • Waiting times • Synchronization times • Path probabilities etc

  28. Bottlenecks – Waiting Times and Execution Times How can we spot the difference between waiting and execution times?

  29. Bottlenecks – Throughput Times

  30. Bottlenecks – Synchronization Times

  31. What are these average synchronization times telling us? Bottlenecks – Synchronization Times 1.3 minutes 20.8 minutes

  32. Bottlenecks – Path Probabilities What are these path probabilities telling us?

  33. Performance Analysiswith Petri Nets

  34. Process Mining • Short Recap • Extension Techniques • Decision Miner • Performance Analysis with Petri Nets • Summary • Announcements • Presentation Futura Technology

  35. Process Mining • Short Recap • Extension Techniques • Decision Miner • Performance Analysis with Petri Nets • Summary • Announcements • Presentation Futura Technology

  36. Summary • Extension techniques enhance existing models with information discovered from event logs • The Decision Point Analysis plug-in can discover the “business rules” for the moments of choice in a process model • The Performance Analysis with Petri Nets plug-in provides various KPIs w.r.t. the execution of processes • The results of both techniques can be used to create simulation models for CPN Tools

  37. Process Mining • Short Recap • Extension Techniques • Decision Miner • Performance Analysis with Petri Nets • Summary • Announcements • Presentation Futura Technology

  38. Process Mining • Short Recap • Extension Techniques • Decision Miner • Performance Analysis with Petri Nets • Summary • Announcements • Presentation Futura Technology

  39. Announcements • Assignment 5 • Individual assignment • Q&A session during Instruction 5 • Posting of Report with Answers • Digital version at StudyWeb (folder Assignment 5) • Printed version to be delivered at secretary’s office of IS group (room Pav D3) • There will be a box on the desk • Deadline: March 14th, 2008 at 6pm • Invited talk after the break!

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