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Process Mining - Chapter 14 - Epilogue

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Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.

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Process Mining - Chapter 14 - Epilogue

  1. 1. Chapter 14Epilogueprof.dr.ir. Wil van der Aalstwww.processmining.org
  2. 2. OverviewChapter 1IntroductionPart I: PreliminariesChapter 2 Chapter 3Process Modeling and Data MiningAnalysisPart II: From Event Logs to Process ModelsChapter 4 Chapter 5 Chapter 6Getting the Data Process Discovery: An Advanced Process Introduction Discovery TechniquesPart III: Beyond Process DiscoveryChapter 7 Chapter 8 Chapter 9Conformance Mining Additional Operational SupportChecking PerspectivesPart IV: Putting Process Mining to WorkChapter 10 Chapter 11 Chapter 12Tool Support Analyzing “Lasagna Analyzing “Spaghetti Processes” Processes”Part V: ReflectionChapter 13 Chapter 14Cartography and EpilogueNavigation PAGE 1
  3. 3. Process Mining: A bridge between datamining and business process management PAGE 2
  4. 4. Challenge: process discovery Fitness: Is the event log possible according to the model?Precision: Is the model Generalization: Is the modelnot underfitting (allow for not overfitting (only allow fortoo much)? the “accidental” examples)? Structure: Is this the simplest model (Occams Razor)? PAGE 3
  5. 5. Challenge: supporting the wholeprocess mining spectrum people organizations machines business “world” processes documents information system(s) provenance event logs “pre “post mortem” current historic mortem” data datanavigation auditing cartography recommend diagnose compare enhance discover promote explore predict detect check models de jure models de facto models control-flow control-flow data/rules data/rules resources/ resources/ organization organization PAGE 4
  6. 6. Start Today!• The threshold to start an (off-line) process mining project is really low.• Most organizations have event data hidden in their systems.• Once the data is located, conversion is typically easy. For instance, software tools such as ProMimport, Nitro, XESame, and OpenXES support the conversion of different sources to MXML or XES.• The freely available open-source process mining tool ProM can be downloaded from www.processmining.org. ProM can be applied to any MXML or XES file and supports all of the process mining techniques mentioned. PAGE 5
  7. 7. Experience the “magic” of process mining, i.e.,discovering and improvingprocesses based on facts rather than fiction! PAGE 6
  8. 8. PAGE 7

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