Process Mining Data Science in Action
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1 Process Mining Data Science in Action Wil van der Aalst Scientific director of the DSC/e Dutch Data Science Summit, Eindhoven,
2 Process Mining Data Science in Action
3 statistics data mining machine learning stochastics process mining databases algorithms data science large scale distributed computing industrial engineering visualization visual analytics behavioral/ social sciences privacy domain knowledge
4 statistics data mining machine learning stochastics process mining databases algorithms data science large scale distributed computing industrial engineering visualization visual analytics behavioral/ social sciences privacy domain knowledge
5 business process management business process reengineering process science statistics stochastics data mining machine learning process mining databases algorithms data science large scale distributed computing industrial engineering visualization visual analytics behavioral/ social sciences privacy domain knowledge model checking formal methods concurrency Petri nets BPMN
6 Internet of Events
7 Internet of Events: 4 sources of event data Internet of Events
8 Internet of Events: 4 sources of event data Internet of Content Big Data Internet of Events
9 Internet of Events: 4 sources of event data Internet of Content Internet of People Big Data social Internet of Events
10 Internet of Events: 4 sources of event data Internet of Content Internet of People Internet of Things Big Data social cloud Internet of Events
11 Internet of Events: 4 sources of event data Internet of Content Internet of People Internet of Things Internet of Places Big Data social cloud mobility Internet of Events
12 Starting point for process mining: Event data student name course name exam date mark Peter Jones Business Information systems Sandy Scott Business Information systems Bridget White Business Information systems John Anderson Business Information systems Sandy Scott BPM Systems Bridget White BPM Systems Sandy Scott Process Mining Bridget White Process Mining John Anderson Process Mining case id activity name timestamp other data every row is an event (here: an exam attempt)
13 Another event log: order handling order number activity timestamp user product quantity 9901 register order Sara Jones iphone5s register order @09.18 Sara Jones iphone5s register order @09.27 Sara Jones iphone4s check stock @09.49 Pete Scott iphone5s ship order @10.11 Sue Fox iphone5s check stock @10.34 Pete Scott iphone4s handle payment @10.41 Carol Hope iphone5s check stock @10.57 Pete Scott iphone5s cancel order @11.08 Carol Hope iphone5s 2 case id activity name timestamp resource other data
14 Another event log: patient treatment patient activity timestamp doctor age cost 5781 make X-ray Dr. Jones blood test Dr. Scott blood test Dr. Scott blood test Dr. Scott CT scan Dr. Fox surgery Dr. Scott handle payment Carol Hope radiation therapy Dr. Jones radiation therapy Dr. Jones case id activity name timestamp resource other data
15 Let's play Case Activity Timestamp Resource 432 register travel request (a) :9.15 John 432 get support from local manager (b) :9.25 Mary 432 check budget by finance (d) :8.55 John 432 decide (e) :9.36 Sue 432 accept request (g) :9.48 Mary Play-In Play-Out Replay start register travel request (a) get support from local manager (b) get detailed motivation letter (c) check budget by finance (d) reinitiate request (f) decide (e) accept request (g) reject request (h) end
16 Play-Out Case Activity Timestamp Resource 432 register travel request (a) :9.15 John 432 get support from local manager (b) :9.25 Mary 432 check budget by finance (d) :8.55 John 432 decide (e) :9.36 Sue 432 accept request (g) :9.48 Mary get support from local manager (b) register travel request (a) get detailed motivation letter (c) decide (e) accept request (g) start check budget by finance (d) reject request (h) end reinitiate request (f)
17 Play Out: A possible scenario a b d e g XORsplit get support from local manager (b) XORjoin start register travel request (a) XORjoin ANDsplit get detailed motivation letter (c) check budget by finance (d) reinitiate request (f) decide (e) accept request (g) reject request (h) ANDjoin XORsplit XORjoin end Case Activity Timestamp Resource 432 register travel request (a) :9.15 John 432 get support from local manager (b) :9.25 Mary 432 check budget by finance (d) :8.55 John 432 decide (e) :9.36 Sue 432 accept request (g) :9.48 Mary
18 Play Out: Another scenario get support from local manager (b) start register travel request (a) get detailed motivation letter (c) check budget by finance (d) reinitiate request (f) decide (e) accept request (g) reject request (h) end a d c e f b d e h
19 Play Out: Process model allows for many more scenarios get support from local manager (b) adcefcdefbdefbdeg adceg adbeh adbeh abdeg acdefcdefbdeh abcefbdeh acdefcdefbdeh acbefbdeg abdeg abdeg acbefbdeh acdefcdefbdeh adbeh adceh acbefbdeg adcefcdefbdefbdeg adceh adcefcdefbdefbdeg abdeg start register travel request (a) get detailed motivation letter (c) check budget by finance (d) reinitiate request (f) decide (e) accept request (g) reject request (h) end
20 Case Activity Timestamp Resource 432 register travel request (a) :9.15 John 432 get support from local manager (b) :9.25 Mary 432 check budget by finance (d) :8.55 John 432 decide (e) :9.36 Sue 432 accept request (g) :9.48 Mary Play-In get support from local manager (b) register travel request (a) get detailed motivation letter (c) decide (e) accept request (g) start check budget by finance (d) reject request (h) end reinitiate request (f)
21 Loesje van der Aalst desire line
22 Play In: Simple process allowing for 4 traces abdeg adbeg adbeg adbeh abdeh abdeg abdeh abdeh abdeh abdeh adbeh adbeh adbeh get support from local manager (b) accept request (g) register travel request (a) decide (e) start check budget by finance (d) reject request (h) end
23 Play In: Process allowing for more traces adcefcdefbdefbdeg abdeg adcefcdefbdefbdeg abcefbdeh acbefbdeg acdefcdefbdeh adceg adbeh adbeh adcefcdefbdefbdeg abdeg abdeg abdeg acbefbdeh acdefcdefbdeh acbefbdeg adceh adbeh adceh acdefcdefbdeh get support from local manager (b) register travel request (a) get detailed motivation letter (c) decide (e) accept request (g) start check budget by finance (d) reject request (h) end reinitiate request (f)
24 No modeling needed!
25 Example Process Discovery (Dutch housing agency, 208 cases, 5987 events)
26 Example process discovery for hospital (627 gynecological oncology patients, events)
27 Replay Case Activity Timestamp Resource 432 register travel request (a) :9.15 John 432 get support from local manager (b) :9.25 Mary 432 check budget by finance (d) :8.55 John 432 decide (e) :9.36 Sue 432 accept request (g) :9.48 Mary get support from local manager (b) start register travel request (a) get detailed motivation letter (c) check budget by finance (d) reinitiate request (f) decide (e) accept request (g) reject request (h) end
28 process model event data
29 desire line very safe system
30 Replay a c d e g get support from local manager (b) register travel request (a) get detailed motivation letter (c) decide (e) accept request (g) start check budget by finance (d) reject request (h) end reinitiate request (f)
31 Replay a c get support from local manager (b) e g? check budget (d) is missing! register travel request (a) get detailed motivation letter (c) decide (e) accept request (g) start check budget by finance (d) reject request (h) end reinitiate request (f)
32 Replay a c h d e g get support from local manager (b)? reject request (h) is impossible register travel request (a) get detailed motivation letter (c) decide (e) accept request (g) start check budget by finance (d) reject request (h) end reinitiate request (f)
33 Conformance Checking (WOZ objections Dutch municipality, 745 objections, 9583 event, f= 0.988)
34 Replay with timestamps a 9.15 c 9.20 d 9.35 e g start 9.15 register travel request (a) get support from local manager (b) get detailed motivation letter (c) check budget by finance (d) reinitiate request (f) decide (e) accept request (g) reject request (h) end
35 Replay with timestamps for many traces frequencies of paths frequencies of activities get support from local manager (b) waiting times and other delays between activities register travel request (a) get detailed motivation letter (c) decide (e) accept request (g) start check budget by finance (d) reinitiate request (f) durations of activities reject request (h) end
36 Performance Analysis Using Replay (WOZ objections Dutch municipality, 745 objections, 9583 event, f= 0.988)
37 Overview world business processes people machines components organizations models analyzes Play-Out supports/ controls specifies configures implements analyzes software system records events, e.g., messages, transactions, etc. (process) model discovery conformance Play-In event logs enhancement Replay
38 Process mining toolbox
39
40
41
42
43
44 examine thoroughly register request examine casually decide pay compensation start check ticket reject request end reinitiate request Process models can be seen as "process maps"
45 What we can learn from maps abstraction: leaving out insignificant roads and towns aggregation: smaller entities are amalgamated into larger ones (suburbs and cities) layout: positioning of elements has a clear meaning size and color: highlight more important entities (e.g. highways have a different color)
46 Compare process models to maps get support from local manager (b) start register travel request (a) abstraction? get detailed motivation letter (c) check budget by finance (d) reinitiate request (f) decide (e) accept request (g) reject request (h) size and color? end b aggregation? start A a register request c1 c2 examine thoroughly A c examine casually d check ticket c3 c4 e decide f M c5 reinitiate request g pay compensation h reject request end layout?
47 Can we see what matters most? get support from local manager (b) metropolis or village? register travel request (a) get detailed motivation letter (c) decide (e) accept request (g) start check budget by finance (d) reject request (h) end reinitiate request (f) highway or dirt road?
48 "the map" does not exist
49 Zoom
50
51
52 Subway map
53 Bicycle map
54 a map is a view on reality map reality same for process models
55 Model provides a view on reality (event data), just like a map!
56 Multiple views depending on purpose (performance, compliance, training, etc.).
57 breathing life into process models otherwise they end up in some drawer
58 Project on maps: traffic jams real estate for sale location of trucks/trains crime rates Project on process models: bottlenecks deviations costs
59 Examples
60 Not that new Charles Minard's 1869 chart showing the number of men in Napoleon s 1812 Russian campaign army, their movements, as well as the temperature they encountered on the return path
61 Actively using process models
62 What can we lean from navigation devices? detect prediction recommendation
63 Driven by maps, historic information, and current information. Flexible: Adapts to circumstances and does not force the driver to take a particular route. Can your information system do this?
64 Conclusion Process models are like maps! Connecting event data and process models! better models live models
65 Positioning process mining process model analysis (simulation, verification, optimization, gaming, etc.) performanceoriented questions, problems and solutions process mining complianceoriented questions, problems and solutions data-oriented analysis (data mining, machine learning, business intelligence)
66 data science process science
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