1. Beyond Tasks and Gateways: Discovering BPMN Models with subprocesses, boundary events and activity markers Raffaele Conforti, Marcello La Rosa Queensland University of Technology Marlon Dumas, Luciano García-Bañuelos University of Tartu 1 BPM’2014 Conference, Eindhoven 11 September 2014

2. 2 CIDTaskTime Stamp… 13219Enter Loan Application2007-11-09 T 11:20:10- 13219Retrieve Applicant Data2007-11-09 T 11:22:15- 13220Enter Loan Application2007-11-09 T 11:22:40- 13219Compute Installments2007-11-09 T 11:22:45- 13219Notify Eligibility2007-11-09 T 11:23:00- 13219Approve Simple Application2007-11-09 T 11:24:30- 13220Compute Installements2007-11-09 T 11:24:35- ………… Automated Process Discovery

3. What’s the catch?

4. There you are!

5. Automated Process Discovery: Handling Complexity Filter Filter out “irrelevant” events (tasks) Filter out “irrelevant” traces Abstract Zoom into most frequent tasks or paths Extract subprocesses Divide Divide log by variants based on similarity (trace clustering) Discover multiple process models rather than one 5

6. Bose, Veerbeck & van det Aalst: Discovering Hierarchical Process Models using ProM Related Work: ProM two-phase miner

7. ProM Two-Phase Miner 7 Instead of… Produces this…

8. Before 8

9. After 9

10. What’s the catch?

11. Data! 11

12. Extracting the Process Hierarchy Extract event tables Find primary keys Find foreign keys Cluster event types Split log per cluster 12 flat log log hierarchy TimePOIDAtt2Att3 11-24 17:121…… 11-25 08:532…… ………… ReceivePO TimeMOIDPOIDAtt3 11-24 17:1311… 11-26 09:3122… …2…… CreateMO ShipPO TimePOIDAtt2 11-25 12:11 1… …2… ………

13. … the rest Discover one model per (sub- )process Identify interrupting boundary events Identify interrupting timer events Identify event subprocesses Identify loop/multi- instance markers 13 -Heuristics miner -ILP -Inductive Miner -Fodina Heuristics

14. Evaluation Setup Four flat process discovery algos Heuristics, ILP, Inductive (H), Fodina Each algo with and without BPMN-Miner Quality measures Accuracy: Fitness, precision, F-score Understandability: Size, Control-Flow Complexity, … LogsTracesEventsEvent typesEvents/type IWT (FRIS)121147213113 Insurance8961243791382 Order-to-cash300032896132530 14

15. Evaluation - Results 15

16. Side-Effect: Correct Models 16

17. What’s Next Standalone tool implementation Currently in ProM nightly build Further evaluation Logs with larger number of event types Noise resilience Missing events can trick foreign key discovery Further enrichment Event-based gateways, more BPMN events… Adding data conditions, completion conditions, … 17