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Dutch-Belgian Database Day 2007 The Challenges of Process Mining

Dutch-Belgian Database Day 2007 The Challenges of Process Mining. A.J.M.M. Weijters (and many others). Content. Process mining ProM Challenges. Process Mining: basic idea.

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Dutch-Belgian Database Day 2007 The Challenges of Process Mining

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  1. Dutch-Belgian Database Day 2007The Challenges of Process Mining A.J.M.M. Weijters (and many others)

  2. Content • Process mining • ProM • Challenges

  3. Process Mining: basic idea • The basic idea of process mining is to extract process knowledge from a registration what happens during the execution of a process (a so called event log). • Process mining provide techniques and tools for discovering process, control, data, organizational, and social information from event logs. • Information about the real behavior within a process, not the expected behavior.

  4. Process discovery: Reversing the process process discovery 1

  5. Conformance testing 2

  6. Log based verification formula four_eyes_principle (a1:activity,a2:activity) := forall[p:person | (!(execute(p,a1)) \/ !(execute(p,a2)))]; 3

  7. ProM framework • ProM is open source and uses a plug-able architecture, e.g. (www.processmining.org) • people can add new process mining techniques by adding plug-ins without spending any efforts on the loading and filtering of event logs and the visualization of the resulting models. • ProM 4.2 provides six different types of plug-ins, and in total more than 200 plug-ins. This makes ProM a practical and versatile tool for process analysis and discovering.

  8. Event log • Case identifier (Case 33) • Activity (Test if repair is OK) • Time information or ordering • Event type (start, complete, …) • Recourse (John) • Task data (repair = OK) • Case data (telephone type = T1, ...)

  9. Simple Example

  10. Problems: bad performance NL (overtime work/quality)

  11. Event logXML format -<ProcessInstance id="1" description=""> - <AuditTrailEntry> - <Data> <Attribute name="phoneT">T1</Attribute> <Attribute name="countryT">B</Attribute> </Data> <WorkflowModelElement>Bregistration</WorkflowModelElement> <EventType>complete</EventType> <Timestamp>2006-01-01T00:01:00.000+01:00</Timestamp> <Originator>Badmin</Originator> </AuditTrailEntry> - <AuditTrailEntry> <WorkflowModelElement>Banalyse</WorkflowModelElement> <EventType>complete</EventType> <Timestamp>2006-01-01T00:02:00.000+01:00</Timestamp> <Originator>BT2</Originator> </AuditTrailEntry> -

  12. Need for more details • Performance B seems better than performance NL, but • differences between the two sub-processes (B-NL) • what is/are the bottleneck(s) • number of cases NL en B • number of re-repairs • workload of resources • difference in performance of the human resources • ....

  13. Process Mining (PM) can be used to discover • general log information • a control-flow model • performance information • bottlenecks • social models • extensions like decision rules for an XOR split in the model • ...

  14. Result of one of the mining techniques (Heuristics Miner) • Many other control-flow mining techniques available in ProM: • α-miner • Genetic mining algorithm • Association rules miner • Region miner • Fuzzy miner • ...

  15. Organization miner But NL: 851/11=77.4 ph/w B: 549/7=78.4 ph/w

  16. Performance Analysis

  17. Performance Analysis B NL Explanation for the long waiting times: Cases arrives in batches

  18. Use LTL checker to select cases • eventually_activity_A=NLrestartRepair oreventually_activity_B=BrestartRepair • cases with a restart = 524 • cases without a restart 876 • eventually_person_P=Jan ... etc. • Jan / Piet / Renate / Els = 78 / 163 / 83 / 153  477/851 = 0.56 (851 is number of NL cases) • Ties Sjef Lieve = 74 / 131 /194 = 399/549 = 0.73 (549 is the number of B cases)

  19. It is always possible to perform mining/analysis on selected cases. Example: mining and performance analysis on the 194 directly correct repaired cases of Lieve!

  20. Many other performance indicators • Performance Sequence Diagrams • Doted Chart • ...

  21. Performance Sequence Diagrams

  22. Doted Chart

  23. Staffware FLOWer Websphere YAWL ADEPT ARIS PPM/SIM Outlook Caramba SAP PeopleSoft InConcert IBM MQSeries CPN Tools CVS Oracle BPEL UML SD company specific systems ... How to get an event log • Prom Import

  24. CJIB UWV Rijkswaterstaat ASML AMC hospital Catharina hospital Eindhoven Heusden ING Bank Philips medical systems ... Practical experiences Rijkswaterstaat:Loops to get pay permission Heusden city hall: errors in workflow implemantation

  25. Lessons learned • Business Intelligence (BI) tools are NOT very intelligent! • Logs are everywhere! • Process mining is possible and provides valuable insights. • Process mining triggers process improvement. • Most processes do not conform. • Reality is much more complicated than people like to believe!

  26. Challenges • Data in SAP ERP systems into XML event-log format • Mining less structured data with many different tasks and complex splits and joins and very large (hospitals) • Visualization of results (Process Oriented OLAP-tools) • On-line monitoring (process optimization, prediction)

  27. Challenges • Measuring the quality of mined process models • Development of Benchmark event-logs • ...

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