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Supporting Variability While Enabling Cross-Organizational Process Mining

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Supporting Variability While Enabling Cross-Organizational Process Mining Configurable Services in the Cloud Supporting variability while enabling cross-organizational process mining Wil van der Aalst Acknowledgements • Marcello La Rosa • Florian Gottschalk • CoSeLoG: Joos Buijs, Jan Vogelaar, Boudewijn van Dongen, Eric Verbeek, Hajo Reijers. • Marlon Dumas, Arthur ter Hofstede, Niels Lohmann, Michael Rosemann, Jan Mendling, … • ProM team (www.processmining.org) • YAWL team (www.yawlfoundation.org) PAGE 1 The need for configurable process models: CoSeLoG project +/- 430 Dutch municipalities PAGE 2 The need for configurable process models: Suncorp case End to end process has between 250-1000 process steps Product Sales Service Claims 500 Dev steps • 25+ steps • 50+ steps • 75+ steps • 100+ steps Sources: Guidewire reference models, GIO CISSS Project, CI US&S P4PI Project Home Motor 30 Commercial variations Liability CTP / WC PAGE 3 Two variants of the same process … PAGE 4 Variation points … in the cloud PAGE 5 Cloud computing PAGE 6 Traditional Situation IS1 IS2 ISn E1 M1 E2 M2 ... En Mn Processes Processes Processes Organization 1 Organization 2 Organization n IS = Information System E = Event log M = Models PAGE 7 Example Acknowledgement of an Unborn Child • Same but different … • “Couleur Locale” • Different from NVVB models. • Configurable process models! PAGE 8 Using SaaS Technology IS-SaaS E CM C1 C2 Cn Processes Processes Processes Municipality 1 Municipality 2 ... Municipality n IS-SaaS = Information System (using a SaaS-based BPMS) E = Event log CM = Configurable Models C = Configuration PAGE 9 Process Mining: Before IS1 IS2 ISn E1 M1 E2 M2 ... En Mn Processes Processes Processes Municipality 1 Municipality 2 Municipality n PAGE 10 Process Mining: After cross-organizational process mining PAGE 11 Configuration Positioning of Configuration Some quotes from Michelangelo • “Every block of stone has a statue inside it and it is the task of the sculptor to discover it.” • “I saw the angel in the marble and carved until I set him free.” • “Carving is easy, you just go down to the skin and stop.” Michelangelo's David Life is about making choices … PAGE 14 Time and artifacts • Design time (generic model, i.e., is not released for instantiation) • Configuration time (specific model, i.e., can be instantiated) • Instantiation time (specific model + instance) • Run time (specific model + instance + state/partial trace) • Auditing time (specific model + instance + full trace) PAGE 15 Continuum • In The Netherlands, … • In Brisbane, … • When the sun shines, … • On Sunday, … • When very busy, … • For these customers, … Branching structure • … PAGE 16 Hiding and blocking Configuration = limiting behavior ! Activate Hide/skip Block Blocking Hiding Blocking Action Activating PAGE 17 Configurable Process Models Purchase Service is Goods receipt Invoice order created accepted posted received V C-EPC V Consignment/ Consignment/ a b pipeline pipeline Goods Invoicing liability is liabilities are receipts plans require created to be settled to be settled settlement V automatically GUIDELINE ERS = ON, if Evaluated - long term Receipt REQUIRED: Consignment/ contract Process Invoicing Plan c Settlement IPS = ON Pipeline - goods and Invoice Settlement ⇒ (ERS) ERS = ON Settlement conditions are specified V C-Petri Net V XOR d e j l Consignment/ pipeline Invoice XOR settlement transmitted document for vendor’s transmitted records XOR Invoice posted Invoice posted Material is and not and blocked f g released blocked for k m for release release C-YAWL V Release Release Invoice Invoice n manually automatically h i XOR C-LTS Payment must C-BPEL be effectes o p Configuration Blocking Hiding Purchase Service is Goods receipt Invoice order created accepted posted received EPC V a b V Process c Petri Net Invoice XOR e l Invoice posted Invoice posted Material is and not and blocked released blocked for for release release YAWL V g m Release Release Invoice Invoice manually automatically n XOR i LTS Payment must BPEL be effectes o p PAGE 18 Inheritance of dynamic behavior Inheritance Inheritance a a b a b c c c d e d e j l e j l f g f g k m g k m n h i h i i n o Configuration o p Configuration o p SuperclassVariant A ReferenceSubclass Model VariantSuperclass B PAGE 19 Configuration Techniques • Blocking a b a b (removing an option) c c • Hiding (skipping activities)d e j l d e j l l τ f g k mf g k τm i τ Blocking and hidingh are ithe n h i n essential concepts of configuration. o p o p “Every block of stone has a statue inside it and it is the task of the sculptor to discover it.” PAGE 20 Cross-organizational mining PAGE 21 Process Mining = (RM,RD) c11 modify conditions (YE,RD) c5 (RM,RD) c2 check_A check_A c8 (E,SD) needed? (RM,RD) (E,RD) Smoker c6(YE,RD) No start register c1 initial c3 check_B check_B c9 asses c12 decline Yes conditions needed? risk c7(FE,FD) Drinker c4 check_C check_C c10 needed? Short Yes No (91/10) (SM,SD) (E,SD) c13 (E,SD) Weight (E,FD) Long + <81.5 ≥81.5 (30/1) make c14 handle c15 handle c16 send offer response payment insurance documents (E,SD) Long Short (150/20) (321/25) c17 timeout1 timeout2 withdraw offer Data Mining Process AnalysisPAGE 22 Process mining: Linking events to models supports/ “world” controls business software processes people machines system components organizations records events, e.g., messages, specifies models transactions, configures analyzes etc. implements analyzes discovery (process) event model conformance logs extension PAGE 23 Example: WMO Harderwijk • Process related to the execution of “Wet Maatschappelijke Ondersteuning” (WMO) Harderwijk • Handling WMO applications • WMO: supporting citizens of municipalities (illness, handicaps, elderly, etc.). • Examples: • wheelchair, scootmobiel, ... • adaptation of house (elevator), ... • household help, ... PAGE 24 Event log (796 applications, 5187 events) PAGE 25 Helicopter view of 1.5 years PAGE 26 Process discovered using Genetic Miner PAGE 27 Various representations PAGE 28 Seamless abstraction more detailed more abstract PAGE 29 Fuzzy Replay PAGE 30 Conformance checking using Replay = should not have happened but did = should have happened but did not PAGE 31 Performance analysis using Replay PAGE 32 Prediction based on Replay “Your application is expected to be finalized in 65 days” PAGE 33 From one to many organizations • More than 80,000 organizations are using Salesforce • More than 1 million organizations are using Google Apps • All 430 Dutch municipalities are implementing the same set of processes • All 94 U.S. District Courts in the United States share the same set of workflows • All car-rental offices of Hertz, Avis, … • … PAGE 34 Consider n organizations event process process 1 log 1 model 1 event process process 2 log 2 model 2 ... ... ... event process process n log n model n PAGE 35 Cross-organizational process mining event process process 1 log 1 model 1 C event process (configurable) process 2 log 2 model 2 process model C ... ... ... event process process n log n model n C event log PAGE 36 Pure model-based event process process 1 log 1 model 1 C event process (configurable) process 2 log 2 model 2 process model C ... ... ... event process process n log n model n C PM1 + PM2 + … + PMn = CM PAGE 37 Pure log-based α(EL1 + EL2 + … + ELn) = CM event process process 1 log 1 model 1 C event process (configurable) process 2 log 2 model 2 process model C ... ... ... event process process n log n model n C event log PAGE 38 How to find and How to merge characterize Questions process models into a differences among single configurable processes using What are the effectsmodel? of event logs? these differences on the event performanceprocess of a process 1 log 1 process?model 1 C How to find and event process (configurable) process 2 characterize differenceslog 2 model 2 process model C using models / How to derive the configurations? ... ...configuration... for a process given a eventconfigurableprocess model? process n log n model n C How to discover a configurable model from a collection of event log event logs? PAGE 39 Evidence-based “best practices” • Organizations can learn from each other. • Configuration support and diagnostics. • Software vendors/service providers can improve their products/services. PAGE 40 Correctness PAGE 41 Remember … Configuration = limiting behavior ! Activate Hide/skip Block Blocking Hiding Blocking Action Activating PAGE 42 Correctness of configurations + = Configurable Model + Configuration = Configured model • Question 1: Is a particular configuration correct? • Question 2: Is there a correct configuration? • Question 3: How to characterize the set of all correct configurations? • Question 4: How to auto-complete a configuration? PAGE 43 Transition Flow Place XOR-split AND-split XOR-join Can t3 be blocked? AND-join Token pI pI t1 t2 t1 t2 p2 p3 p4 p2 p3 p4 t5 t6 t5 t6 t3 t4 t4 p 6 p6 t8 p5 p5 t8 p7 p7 t7 t7 pO pO PAGE 44 Transition Flow Place XOR-split Block t and hide t ? AND-split XOR-join 1 3 AND-join Token p 1 p1 Prepare Prepare Prepare Travel Form t1 t2 Travel Form t Travel Form (Secretary) (Employee) 2 (Employee p2 p2 Arrange travel p3 t3 p4 insurance p3 t3 τ p4 (Employee) p5 p5 Request for Check & Update Request for Check & Update change t7 t4 Travel Form t5 τ Travel Form τ (Admin) (Employee) change t7 t4 t5 (Admin) (Employee) p6 p6 Submit Travel Form Submit t6 Travel Form for Approval t6 (Employee) for Approval (Employee) p7 p7 Approve Reject Travel Form t8 Travel Form t9 Approve Reject (Admin) (Admin) Travel Form t8 Travel Form t9 (Admin)
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