1. Discovering Coordination Patterns using Process Mining Prof.dr.ir. Wil van der Aalst Eindhoven University of Technology Department of Information and Technology P.O. Box 513, 5600 MB Eindhoven The Netherlands w.m.p.v.d.aalst@tm.tue.nl Joint work with Ana Karla Alves de Medeiros, Boudewijn van Dongen, Ton Weijters, et al.

2. Outline Motivation Process mining –An overview –The alpha algorithm –Challenges Applications Conclusion

3. Motivation Coordination occurs at many levels. In this talk we focus on techniques for monitoring coordination mechanisms present in enterprise information systems. Most enterprise information systems store relevant events in some structured form (cf. WFM, CRM, ERP, B2B, etc.). Process mining allows for new ways of analysing event logs (beyond basic KPIs).

4. Process mining Process mining can be used for: –Process discovery (What is the process?) –Delta analysis (Are we doing what was specified?) –Performance analysis (How can we improve?) process mining www.processmining.org

5. Process mining: Overview 1) basic performance metrics 2) process model3) organizational model4) social network 5) performance characteristics If …then … 6) auditing/security

6. Process Mining: The alpha algorithm alpha algorithm

7. Process log Minimal information in log: case id’s and task id’s. Additional information: event type, time, resources, and data. In this log there are three possible sequences: –ABCD –ACBD –EF case 1 : task A case 2 : task A case 3 : task A case 3 : task B case 1 : task B case 1 : task C case 2 : task C case 4 : task A case 2 : task B case 2 : task D case 5 : task E case 4 : task C case 1 : task D case 3 : task C case 3 : task D case 4 : task B case 5 : task F case 4 : task D

8. >, ,||,# relations Direct succession: x>y iff for some case x is directly followed by y. Causality: x  y iff x>y and not y>x. Parallel: x||y iff x>y and y>x Choice: x#y iff not x>y and not y>x. case 1 : task A case 2 : task A case 3 : task A case 3 : task B case 1 : task B case 1 : task C case 2 : task C case 4 : task A case 2 : task B case 2 : task D case 5 : task E case 4 : task C case 1 : task D case 3 : task C case 3 : task D case 4 : task B case 5 : task F case 4 : task D A>B A>C B>C B>D C>B C>D E>F ABACBDCDEFABACBDCDEF B||C C||B

9. Basic idea (1) xyxy

10. Basic idea (2) x  y, x  z, and y||z

11. Basic idea (3) x  y, x  z, and y#z

12. Basic idea (4) x  z, y  z, and x||y

13. Basic idea (5) x  z, y  z, and x#y

14. It is not that simple: Basic alpha algorithm Let W be a workflow log over T.  (W) is defined as follows. 1.T W = { t  T     W t   }, 2.T I = { t  T     W t = first(  ) }, 3.T O = { t  T     W t = last(  ) }, 4.X W = { (A,B)  A  T W  B  T W   a  A  b  B a  W b   a1,a2  A a 1 # W a 2   b1,b2  B b 1 # W b 2 }, 5.Y W = { (A,B)  X   (A,B)  X A  A  B  B  (A,B) = (A,B) }, 6.P W = { p (A,B)  (A,B)  Y W }  {i W,o W }, 7.F W = { (a,p (A,B) )  (A,B)  Y W  a  A }  { (p (A,B),b)  (A,B)  Y W  b  B }  { (i W,t)  t  T I }  { (t,o W )  t  T O }, and  (W) = (P W,T W,F W ).

15. Example case 1 : task A case 2 : task A case 3 : task A case 3 : task B case 1 : task B case 1 : task C case 2 : task C case 4 : task A case 2 : task B case 2 : task D case 5 : task E case 4 : task C case 1 : task D case 3 : task C case 3 : task D case 4 : task B case 5 : task F case 4 : task D  (W) W

16. Challenges Mining other perspectives (data, resources, roles, …) Refining existing algorithm for (control-flow/process perspective) –Hidden tasks –Duplicate tasks –Non-free-choice constructs –Loops –Mining and exploiting time –Dealing with noise –Dealing with incompleteness Gathering data from heterogeneous sources Visualization of results Delta analysis

17. Hidden tasks

18. Duplicate tasks

19. Non-free-choice constructs

20. Loops

21. Incompleteness

22. Process Mining: Tooling

23. Applications We have applied/are applying our process mining techniques within several organizations (CJIB, RWS, UWV, …). Let us consider coordination in the context of cross-organizational processes.

24. Application scenario: Web services Are organizations working the way they should? See BPEL4WS: “ Business processes can be described in two ways. Executable business processes model actual behavior of a participant in a business interaction. Business protocols, in contrast, use process descriptions that specify the mutually visible message exchange behavior of each of the parties involved in the protocol, without revealing their internal behavior. The process descriptions for business protocols are called abstract processes. BPEL4WS is meant to be used to model the behavior of both executable and abstract processes.” http://www.ibm.com/developerworks/library/ws-bpel/ http://xml.ahg.com/

25. Example “single non-binding offer” negotiation pattern taken from Andries van Dijk About 10 negotiations are needed to discover the Petri net. Can be used for: –Process discovery (What is the process?) –Delta analysis (Are we doing what was specified?) –Performance analysis (How can we improve?)

26. Conclusion Process mining seems to be interesting in the context of coordination. There are many challenges: –Improving the algorithms (hidden/duplicate tasks, …) –Gathering the data –Visualizing the results –Etc. Join us at www.processmining.org