SlideShare a Scribd company logo
1 of 47
Download to read offline
TomTom for Business
Process Management
(TomTom4BPM)



prof.dr.ir. Wil van der Aalst
www.processmining.org
Today's information systems are really crappy
compared to a TomTom system!


                            • Good maps?
                            • Navigation by
                              PowerPoints?
                            • Traffic information?
                            • Where is the next fuel
                              station?
                            • Who is in charge?
                            • Seamless zoom?
                            • Customizable views?
                            • When will the
                              destination be reached?


                                                PAGE 1
PAGE 2
PAGE 3
Process Mining

                 • Process discovery: "What is
                   really happening?"
                 • Conformance checking: "Do
                   we do what was agreed
                   upon?"
                 • Performance analysis:
                   "Where are the bottlenecks?"
                 • Process prediction: "Will this
                   case be late?"
                 • Process improvement: "How
                   to redesign this process?"
                 • Etc.
                                            PAGE 4
• Process discovery: "What is the real curriculum?"
• Conformance checking: "Do students meet the prerequisites?"
• Performance analysis: "Where are the bottlenecks?"
• Process prediction: "Will a student complete his studies (in time)?"
• Process improvement: "How to redesign the curriculum?"
                                                                         PAGE 5
Process Mining
A step towards TomTom functionality
for business processes
Where to start?


     process
                    diagnosis
     control
                                process mining

     process                      process
    enactment                     design


                implementation/
                  configuration

                                             PAGE 7
Process mining: Linking events to models




                                       PAGE 8
Process mining as a mirror ...




                                 PAGE 9
Where did we apply process mining?

• Municipalities (e.g., Alkmaar, Heusden, Harderwijk, etc.)
• Government agencies (e.g., Rijkswaterstaat, Centraal
  Justitieel Incasso Bureau, Justice department)
• Insurance related agencies (e.g., UWV)
• Banks (e.g., ING Bank)
• Hospitals (e.g., AMC hospital, Catharina hospital)
• Multinationals (e.g., DSM, Deloitte)
• High-tech system manufacturers and their customers
  (e.g., Philips Healthcare, ASML, Thales)
• Media companies (e.g. Winkwaves)
• ...
                                                        PAGE 10
Example: WMO process of
   a Dutch Municipality




                                           144 cases (i.e., requests
                                           for adaptation of house)
WMO = Wet Maatschappelijke Ondersteuning
                                           1326 recorded events
                                                                PAGE 11
Conformance check of discovered model

                                 both




         performed
         while not
          allowed      activity is      good fit
                     sometimes not       97.9%
                       performed
     drill
    down


                                               PAGE 12
Performance analysis




      time    bottle
      from    neck
     A to B            flow
                       time




                              PAGE 13
Events sorted by duration




                            PAGE 14
"Real" animation




                   PAGE 15
And of course ...




                    PAGE 16
Reality ≠ PowerPoint (or Visio)




                            PAGE 17
Process spectrum




structured          unstructured
(Lasagna)           (Spaghetti)

                           PAGE 18
375 houses
   18640 events
82 different activities


                          PAGE 19
2712 patients
    29258 events
264 different activities


                           PAGE 20
874 patients
    10478 events
181 different activities


                           PAGE 21
24 machines
   154966 events
360 different activities


                           PAGE 22
37.5% OK
         62.5% NOK




design       reality
                 PAGE 23
PAGE 24
Process Mining: TomTom for
Business Processes
How can process mining help?
                    • Good maps?
                    • Navigation by
                      PowerPoints?
                    • Traffic information?
                    • Where is the next fuel
                      station?
                    • Who is in charge?
                    • Seamless zoom?
                    • Customizable views?
                    • When will the
                      destination be
                      reached?
                                      PAGE 26
city   highway




                 PAGE 27
ProM's "real animation"




                          PAGE 28
When will I be home?
PAGE 30
Approach




When?      12-6-2009!




                        PAGE 31
Input: partial trace and historic information

                   (A B C D C D C D E)? (14-6-2009)!




                        (12-6-2009)!




                                                       PAGE 32
Input




        PAGE 33
Building transition systems
                                      C                     D
                          {A,B}               {A,B,C}           {A,B,C,D}


                             B                    B
                 A                    C
            {}             {A}                 {A,C}
                                                                                    many
                             E                                                abstractions
ABCD                                  D                                       are possible
                          {A,E}               {A,D,E}
ACBD                                                                        and supported
AED
ABCD                  (a) transition system based on sets                       by ProM's
ABCD                                                                           FSM miner
AED
                                      C                     D
ACBD                     <A,B>               <A,B,C>            <A,B,C,D>
...

                             B
                 A                    E                     D
           <>             <A>                 <A,E>             <A,E,D>


                             C

                                      B                     D
                         <A,C>               <A,C,B>            <A,C,B,D>


                     (b) transition system based on sequences                     PAGE 34
Annotated transition system based on
remaining time




                                       PAGE 35
Predictive information
                         average: 7.2                   average: 0
    average: 10.33       st. dev.: 1.79                 st. dev.: 0
    st. dev.: 1.53       min: 6                         min: 0
    min: 9               max: 10                        max: 0
    max: 12

                                      predict: 10.33                       predict: 0
  average: 25.75                          [12,9,10]         [6,10,6,6,8]       [0,0,0,0,0]
  st. dev.: 12.25                                       C                  D
                                            {A,B}               {A,B,C}         {A,B,C,D}
  min: 13
  max: 44                       [18,26,44,13,
                                  14,40,24]       B     predict: 7.2
                                                              B
                                                        C
                           {}                   {A}              {A,C}
                                      A
average: 25.75
                                                                [22,19]
st. dev.: 12.25      [18,26,44,13,    predict: 25.75
                                             E

min: 13                14,40,24]
                                                        D
                                            {A,E}
max: 44                                                         {A,D,E}

                                           [34,31]               [0,0]

average: 32.5
st. dev.: 2.12                                                             A B C D
min: 31              average: 20.5                average: 0
max: 34              st. dev.: 2.12               st. dev.: 0
                     min: 19                      min: 0
                                                                                             PAGE 36
                     max: 22                      max: 0
Example: WOZ process in Dutch Municipality

                          1882 objections
                          triggering 11985
                              activities




                                             PAGE 37
All 11985 events at a glance




                         Average flow time is 107 days
                               (with a huge variation)




                                                   PAGE 38
For partial traces
corresponding to
  this state the
 estimated time
until completion
   is 8.5 days


                     PAGE 39
Cross validation:
 Mean     rooted
Average    MSE
                   MAPE
                          training set and test set
  Error
 (MAE)




                                              PAGE 40
Some results




               PAGE 41
PAGE 42
Conclusion
Conclusion
• The abundance of event data enables a wide
  variety of process mining techniques ranging
  from process discovery to conformance
  checking.
• A reality check for people that are involved in
  process modeling.
• TomTom functionality is already possible
  today!
• Check out ProM with its 250+ plug-ins.
• Contribute: case studies, plug-ins, etc.
                                                PAGE 44
Thanks!                       cf. www.processmining.org


•   Wil van der Aalst             •   Mercy Amiyo              •   Jan Martijn van der Werf
•   Peter van den Brand           •   Carmen Bratosin          •   Martin van Wingerden
•   Boudewijn van Dongen          •   Toon Calders             •   Jianhong Ye
•   Christian Günther             •   Jorge Cardoso            •   Huub de Beer
•   Eric Verbeek                  •   Ronald Crooy             •   Elena Casares
•   Ana Karla Alves de Medeiros   •   Florian Gottschalk       •   Alina Chipaila
•   Anne Rozinat                  •   Monique Jansen-Vullers   •   Walid Gaaloul
•   Minseok Song                  •   Peter Khisa Wakholi      •   Martijn van Giessel
•   Ton Weijters                  •   Nicolas Knaak            •   Shaifali Gupta
•   Remco Dijkman                 •   Sven Lambrechts          •   Thomas Hoffmann
•   Gianluigi Greco               •   Joyce Nakatumba          •   Peter Hornix
•   Antonella Guzzo               •   Mariska Netjes           •   René Kerstjens
•   Kristian Bisgaard Lassen      •   Mykola Pechenizkiy       •   Ralf Kramer
•   Ronny Mans                    •   Maja Pesic               •   Wouter Kunst
•   Jan Mendling                  •   Hajo Reijers             •   Laura Maruster
•   Vladimir Rubin                •   Stefanie Rinderle        •   Andriy Nikolov
•   Nikola Trcka                  •   Domenico Saccà           •   Adarsh Ramesh
•   Irene Vanderfeesten           •   Helen Schonenberg        •   Jo Theunissen
•   Barbara Weber                 •   Marc Voorhoeve           •   Kenny van Uden
•   Lijie Wen                     •   Jianmin Wang             •   ...              PAGE 45
Relevant WWW sites
                                       http://www.senternovem.nl/innovatievouchers
                                                 MKB 2.500 – 7.500 euro




• http://www.processmining.org
• http:// promimport.sourceforge.net
• http://prom.sourceforge.net
• http://www.workflowpatterns.com
• http://www.workflowcourse.com
• http://www.vdaalst.com


                                                                         PAGE 46

More Related Content

Viewers also liked

Business Process Managment
Business Process ManagmentBusiness Process Managment
Business Process ManagmentMark Carlson
 
Digital finance, crowdfunding and creative content business
Digital finance, crowdfunding and creative content businessDigital finance, crowdfunding and creative content business
Digital finance, crowdfunding and creative content businessGrow VC Group
 
Process of Strategic Managment
Process of Strategic ManagmentProcess of Strategic Managment
Process of Strategic Managmentegamor
 
Quality management systems
Quality management systemsQuality management systems
Quality management systemsQaisar Mehmud
 
Process management
Process managementProcess management
Process managementMohd Arif
 
Management process powerpoint
Management process powerpointManagement process powerpoint
Management process powerpointElizabethLampson2
 
The Project Management Process - Week 6 Leadership
The Project Management Process - Week 6   LeadershipThe Project Management Process - Week 6   Leadership
The Project Management Process - Week 6 LeadershipCraig Brown
 
The Project Management Process - Week 1
The Project Management Process -  Week 1The Project Management Process -  Week 1
The Project Management Process - Week 1Craig Brown
 
Introduction to Business Process Management
Introduction to Business Process ManagementIntroduction to Business Process Management
Introduction to Business Process ManagementAlan McSweeney
 
Human resource management process
Human resource management processHuman resource management process
Human resource management processZeeshan Sabir
 
State of the Word 2011
State of the Word 2011State of the Word 2011
State of the Word 2011photomatt
 

Viewers also liked (16)

BPM and BizFlow
BPM and BizFlowBPM and BizFlow
BPM and BizFlow
 
Business Process Managment
Business Process ManagmentBusiness Process Managment
Business Process Managment
 
Digital finance, crowdfunding and creative content business
Digital finance, crowdfunding and creative content businessDigital finance, crowdfunding and creative content business
Digital finance, crowdfunding and creative content business
 
Process of Strategic Managment
Process of Strategic ManagmentProcess of Strategic Managment
Process of Strategic Managment
 
Quality management systems
Quality management systemsQuality management systems
Quality management systems
 
Introduction to BPM
Introduction to BPMIntroduction to BPM
Introduction to BPM
 
Process management
Process managementProcess management
Process management
 
Management process powerpoint
Management process powerpointManagement process powerpoint
Management process powerpoint
 
The Project Management Process - Week 6 Leadership
The Project Management Process - Week 6   LeadershipThe Project Management Process - Week 6   Leadership
The Project Management Process - Week 6 Leadership
 
The Project Management Process - Week 1
The Project Management Process -  Week 1The Project Management Process -  Week 1
The Project Management Process - Week 1
 
What is BPM?
What is BPM?What is BPM?
What is BPM?
 
Processes of management
Processes of managementProcesses of management
Processes of management
 
Proposal Management Process
Proposal  Management  ProcessProposal  Management  Process
Proposal Management Process
 
Introduction to Business Process Management
Introduction to Business Process ManagementIntroduction to Business Process Management
Introduction to Business Process Management
 
Human resource management process
Human resource management processHuman resource management process
Human resource management process
 
State of the Word 2011
State of the Word 2011State of the Word 2011
State of the Word 2011
 

Similar to TomTom for Business Process Managment (TomTom4BPM)

Process Mining: Data Science in Action - Wil van der Aalst, TU/e, DSC/e, HSE
 Process Mining: Data Science in Action - Wil van der Aalst, TU/e, DSC/e, HSE Process Mining: Data Science in Action - Wil van der Aalst, TU/e, DSC/e, HSE
Process Mining: Data Science in Action - Wil van der Aalst, TU/e, DSC/e, HSEYandex
 
Orbitz World Wide An Architectures Response To Growth And Change
Orbitz World Wide An Architectures Response To Growth And ChangeOrbitz World Wide An Architectures Response To Growth And Change
Orbitz World Wide An Architectures Response To Growth And ChangeConSanFrancisco123
 
Keynote Gartner Business Process Management Summit, February 2009, London
Keynote Gartner Business Process Management Summit, February 2009, London Keynote Gartner Business Process Management Summit, February 2009, London
Keynote Gartner Business Process Management Summit, February 2009, London Wil van der Aalst
 
MAYA HTT NX ST CAD-CAE Workflows
MAYA HTT NX ST CAD-CAE WorkflowsMAYA HTT NX ST CAD-CAE Workflows
MAYA HTT NX ST CAD-CAE WorkflowsDora Smith
 
Maya HTT NX CAD Assoc Fluid Domains
Maya HTT NX CAD Assoc Fluid DomainsMaya HTT NX CAD Assoc Fluid Domains
Maya HTT NX CAD Assoc Fluid DomainsDora Smith
 
Easy Mobile - Making Your Application Easier To Use - Gravity Switch
Easy Mobile - Making Your Application Easier To Use - Gravity SwitchEasy Mobile - Making Your Application Easier To Use - Gravity Switch
Easy Mobile - Making Your Application Easier To Use - Gravity Switchgravityswitch
 
stackconf 2023 | Dynamic Image Optimization with imgproxy at Schwarz IT by An...
stackconf 2023 | Dynamic Image Optimization with imgproxy at Schwarz IT by An...stackconf 2023 | Dynamic Image Optimization with imgproxy at Schwarz IT by An...
stackconf 2023 | Dynamic Image Optimization with imgproxy at Schwarz IT by An...NETWAYS
 
Scorecard Integration v3 Manifold Certified
Scorecard Integration v3 Manifold CertifiedScorecard Integration v3 Manifold Certified
Scorecard Integration v3 Manifold CertifiedBrij Consulting, LLC
 
Scorecard Integration V2 Entry to Gate and Scale to Manifold
Scorecard Integration V2 Entry to Gate and Scale to ManifoldScorecard Integration V2 Entry to Gate and Scale to Manifold
Scorecard Integration V2 Entry to Gate and Scale to ManifoldBrij Consulting, LLC
 
Process mining chapter_06_advanced_process_discovery_techniques
Process mining chapter_06_advanced_process_discovery_techniquesProcess mining chapter_06_advanced_process_discovery_techniques
Process mining chapter_06_advanced_process_discovery_techniquesMuhammad Ajmal
 
Process Mining - Chapter 6 - Advanced Process Discovery_techniques
Process Mining - Chapter 6 - Advanced Process Discovery_techniquesProcess Mining - Chapter 6 - Advanced Process Discovery_techniques
Process Mining - Chapter 6 - Advanced Process Discovery_techniquesWil van der Aalst
 
digger 3_d
digger 3_ddigger 3_d
digger 3_dALI ISSA
 
Introduction of super map gis 10i(2020) (1)
Introduction of super map gis 10i(2020) (1)Introduction of super map gis 10i(2020) (1)
Introduction of super map gis 10i(2020) (1)GeoMedeelel
 
Applying Linear Optimization Using GLPK
Applying Linear Optimization Using GLPKApplying Linear Optimization Using GLPK
Applying Linear Optimization Using GLPKJeremy Chen
 
Process Mining: Past, Present, and Open Challenges (AIST 2017 Keynote)
Process Mining: Past, Present, and Open Challenges (AIST 2017 Keynote)Process Mining: Past, Present, and Open Challenges (AIST 2017 Keynote)
Process Mining: Past, Present, and Open Challenges (AIST 2017 Keynote)Dirk Fahland
 
Rob Bernard: IT Solutions For A Low Carbon Economy
Rob Bernard: IT Solutions For A Low Carbon EconomyRob Bernard: IT Solutions For A Low Carbon Economy
Rob Bernard: IT Solutions For A Low Carbon EconomyGigaom
 
Network Design in Gurobi - final.pptx
Network Design in Gurobi - final.pptxNetwork Design in Gurobi - final.pptx
Network Design in Gurobi - final.pptxDebarpanHaldar1
 
Optimisation of Industrial Processes SimQRi - A Query-oriented Tool for the E...
Optimisation of Industrial Processes SimQRi - A Query-oriented Tool for the E...Optimisation of Industrial Processes SimQRi - A Query-oriented Tool for the E...
Optimisation of Industrial Processes SimQRi - A Query-oriented Tool for the E...Agence du Numérique (AdN)
 

Similar to TomTom for Business Process Managment (TomTom4BPM) (20)

Process Mining: Data Science in Action - Wil van der Aalst, TU/e, DSC/e, HSE
 Process Mining: Data Science in Action - Wil van der Aalst, TU/e, DSC/e, HSE Process Mining: Data Science in Action - Wil van der Aalst, TU/e, DSC/e, HSE
Process Mining: Data Science in Action - Wil van der Aalst, TU/e, DSC/e, HSE
 
Orbitz World Wide An Architectures Response To Growth And Change
Orbitz World Wide An Architectures Response To Growth And ChangeOrbitz World Wide An Architectures Response To Growth And Change
Orbitz World Wide An Architectures Response To Growth And Change
 
Keynote Gartner Business Process Management Summit, February 2009, London
Keynote Gartner Business Process Management Summit, February 2009, London Keynote Gartner Business Process Management Summit, February 2009, London
Keynote Gartner Business Process Management Summit, February 2009, London
 
MAYA HTT NX ST CAD-CAE Workflows
MAYA HTT NX ST CAD-CAE WorkflowsMAYA HTT NX ST CAD-CAE Workflows
MAYA HTT NX ST CAD-CAE Workflows
 
Maya HTT NX CAD Assoc Fluid Domains
Maya HTT NX CAD Assoc Fluid DomainsMaya HTT NX CAD Assoc Fluid Domains
Maya HTT NX CAD Assoc Fluid Domains
 
Easy Mobile - Making Your Application Easier To Use - Gravity Switch
Easy Mobile - Making Your Application Easier To Use - Gravity SwitchEasy Mobile - Making Your Application Easier To Use - Gravity Switch
Easy Mobile - Making Your Application Easier To Use - Gravity Switch
 
stackconf 2023 | Dynamic Image Optimization with imgproxy at Schwarz IT by An...
stackconf 2023 | Dynamic Image Optimization with imgproxy at Schwarz IT by An...stackconf 2023 | Dynamic Image Optimization with imgproxy at Schwarz IT by An...
stackconf 2023 | Dynamic Image Optimization with imgproxy at Schwarz IT by An...
 
Scorecard Integration v3 Manifold Certified
Scorecard Integration v3 Manifold CertifiedScorecard Integration v3 Manifold Certified
Scorecard Integration v3 Manifold Certified
 
Scorecard Integration V2 Entry to Gate and Scale to Manifold
Scorecard Integration V2 Entry to Gate and Scale to ManifoldScorecard Integration V2 Entry to Gate and Scale to Manifold
Scorecard Integration V2 Entry to Gate and Scale to Manifold
 
Process mining chapter_06_advanced_process_discovery_techniques
Process mining chapter_06_advanced_process_discovery_techniquesProcess mining chapter_06_advanced_process_discovery_techniques
Process mining chapter_06_advanced_process_discovery_techniques
 
Process Mining - Chapter 6 - Advanced Process Discovery_techniques
Process Mining - Chapter 6 - Advanced Process Discovery_techniquesProcess Mining - Chapter 6 - Advanced Process Discovery_techniques
Process Mining - Chapter 6 - Advanced Process Discovery_techniques
 
digger 3_d
digger 3_ddigger 3_d
digger 3_d
 
Introduction of super map gis 10i(2020) (1)
Introduction of super map gis 10i(2020) (1)Introduction of super map gis 10i(2020) (1)
Introduction of super map gis 10i(2020) (1)
 
Applying Linear Optimization Using GLPK
Applying Linear Optimization Using GLPKApplying Linear Optimization Using GLPK
Applying Linear Optimization Using GLPK
 
Process Mining: Past, Present, and Open Challenges (AIST 2017 Keynote)
Process Mining: Past, Present, and Open Challenges (AIST 2017 Keynote)Process Mining: Past, Present, and Open Challenges (AIST 2017 Keynote)
Process Mining: Past, Present, and Open Challenges (AIST 2017 Keynote)
 
Previous work on Access Management Federations
Previous work on Access Management FederationsPrevious work on Access Management Federations
Previous work on Access Management Federations
 
Rob Bernard: IT Solutions For A Low Carbon Economy
Rob Bernard: IT Solutions For A Low Carbon EconomyRob Bernard: IT Solutions For A Low Carbon Economy
Rob Bernard: IT Solutions For A Low Carbon Economy
 
Network Design in Gurobi - final.pptx
Network Design in Gurobi - final.pptxNetwork Design in Gurobi - final.pptx
Network Design in Gurobi - final.pptx
 
Optimisation of Industrial Processes SimQRi - A Query-oriented Tool for the E...
Optimisation of Industrial Processes SimQRi - A Query-oriented Tool for the E...Optimisation of Industrial Processes SimQRi - A Query-oriented Tool for the E...
Optimisation of Industrial Processes SimQRi - A Query-oriented Tool for the E...
 
Grensesnitt i bevegelse
Grensesnitt i bevegelseGrensesnitt i bevegelse
Grensesnitt i bevegelse
 

More from Wil van der Aalst

Process Mining: BPM on Steroids (CPOs@BPM&O 2019 Keynote)
Process Mining: BPM on Steroids (CPOs@BPM&O 2019 Keynote)Process Mining: BPM on Steroids (CPOs@BPM&O 2019 Keynote)
Process Mining: BPM on Steroids (CPOs@BPM&O 2019 Keynote)Wil van der Aalst
 
Everything You Always Wanted To Know About Petri Nets, But Were Afraid To Ask
Everything You Always Wanted To Know About Petri Nets, But Were Afraid To AskEverything You Always Wanted To Know About Petri Nets, But Were Afraid To Ask
Everything You Always Wanted To Know About Petri Nets, But Were Afraid To AskWil van der Aalst
 
20 years of Process Mining Research (ICPM 2019 keynote)
20 years of Process Mining Research (ICPM 2019 keynote)20 years of Process Mining Research (ICPM 2019 keynote)
20 years of Process Mining Research (ICPM 2019 keynote)Wil van der Aalst
 
Earth Movers’ Stochastic Conformance Checking
Earth Movers’ Stochastic Conformance CheckingEarth Movers’ Stochastic Conformance Checking
Earth Movers’ Stochastic Conformance CheckingWil van der Aalst
 
Using Process Mining to Remove Operational Friction in Shared Services
Using Process Mining to Remove Operational Friction in Shared ServicesUsing Process Mining to Remove Operational Friction in Shared Services
Using Process Mining to Remove Operational Friction in Shared ServicesWil van der Aalst
 
Object-Centric Process Mining: Dealing With Divergence and Convergence in Eve...
Object-Centric Process Mining: Dealing With Divergence and Convergence in Eve...Object-Centric Process Mining: Dealing With Divergence and Convergence in Eve...
Object-Centric Process Mining: Dealing With Divergence and Convergence in Eve...Wil van der Aalst
 
Process Mining In Today’s Platforms Economy: Opportunities and Challenges (WI...
Process Mining In Today’s Platforms Economy: Opportunities and Challenges (WI...Process Mining In Today’s Platforms Economy: Opportunities and Challenges (WI...
Process Mining In Today’s Platforms Economy: Opportunities and Challenges (WI...Wil van der Aalst
 
Event Logs: What kind of data does process mining require?
Event Logs: What kind of data does process mining require?Event Logs: What kind of data does process mining require?
Event Logs: What kind of data does process mining require?Wil van der Aalst
 
Configurable Declare: Designing Customizable Flexible Models
Configurable Declare: Designing Customizable Flexible ModelsConfigurable Declare: Designing Customizable Flexible Models
Configurable Declare: Designing Customizable Flexible ModelsWil van der Aalst
 
On the Role of Fitness, Precision, Generalization and Simplicity in Process D...
On the Role of Fitness, Precision, Generalization and Simplicity in Process D...On the Role of Fitness, Precision, Generalization and Simplicity in Process D...
On the Role of Fitness, Precision, Generalization and Simplicity in Process D...Wil van der Aalst
 
A Decade of Business Process Management Conferences: Reflections on a Develop...
A Decade of Business Process Management Conferences: Reflections on a Develop...A Decade of Business Process Management Conferences: Reflections on a Develop...
A Decade of Business Process Management Conferences: Reflections on a Develop...Wil van der Aalst
 
Service Interaction: Patterns, Formalization, and Analysis
Service Interaction: Patterns, Formalization, and AnalysisService Interaction: Patterns, Formalization, and Analysis
Service Interaction: Patterns, Formalization, and AnalysisWil van der Aalst
 
Keynote on Process Mining at SSCI 2010 / CIDM 2011
Keynote on Process Mining at SSCI 2010 / CIDM 2011Keynote on Process Mining at SSCI 2010 / CIDM 2011
Keynote on Process Mining at SSCI 2010 / CIDM 2011Wil van der Aalst
 
Process Mining - Chapter 14 - Epilogue
Process Mining - Chapter 14 - EpilogueProcess Mining - Chapter 14 - Epilogue
Process Mining - Chapter 14 - EpilogueWil van der Aalst
 
Process Mining - Chapter 11 - Analyzing Lasagna Processes
Process Mining - Chapter 11 - Analyzing Lasagna ProcessesProcess Mining - Chapter 11 - Analyzing Lasagna Processes
Process Mining - Chapter 11 - Analyzing Lasagna ProcessesWil van der Aalst
 
Process Mining - Chapter 10 - Tool Support
Process Mining - Chapter 10 - Tool SupportProcess Mining - Chapter 10 - Tool Support
Process Mining - Chapter 10 - Tool SupportWil van der Aalst
 
Process Mining - Chapter 9 - Operational Support
Process Mining - Chapter 9 - Operational SupportProcess Mining - Chapter 9 - Operational Support
Process Mining - Chapter 9 - Operational SupportWil van der Aalst
 
Process Mining - Chapter 8 - Mining Additional Perspectives
Process Mining - Chapter 8 - Mining Additional PerspectivesProcess Mining - Chapter 8 - Mining Additional Perspectives
Process Mining - Chapter 8 - Mining Additional PerspectivesWil van der Aalst
 
Process Mining - Chapter 5 - Process Discovery
Process Mining - Chapter 5 - Process DiscoveryProcess Mining - Chapter 5 - Process Discovery
Process Mining - Chapter 5 - Process DiscoveryWil van der Aalst
 
Process Mining - Chapter 4 - Getting the Data
Process Mining - Chapter 4 - Getting the DataProcess Mining - Chapter 4 - Getting the Data
Process Mining - Chapter 4 - Getting the DataWil van der Aalst
 

More from Wil van der Aalst (20)

Process Mining: BPM on Steroids (CPOs@BPM&O 2019 Keynote)
Process Mining: BPM on Steroids (CPOs@BPM&O 2019 Keynote)Process Mining: BPM on Steroids (CPOs@BPM&O 2019 Keynote)
Process Mining: BPM on Steroids (CPOs@BPM&O 2019 Keynote)
 
Everything You Always Wanted To Know About Petri Nets, But Were Afraid To Ask
Everything You Always Wanted To Know About Petri Nets, But Were Afraid To AskEverything You Always Wanted To Know About Petri Nets, But Were Afraid To Ask
Everything You Always Wanted To Know About Petri Nets, But Were Afraid To Ask
 
20 years of Process Mining Research (ICPM 2019 keynote)
20 years of Process Mining Research (ICPM 2019 keynote)20 years of Process Mining Research (ICPM 2019 keynote)
20 years of Process Mining Research (ICPM 2019 keynote)
 
Earth Movers’ Stochastic Conformance Checking
Earth Movers’ Stochastic Conformance CheckingEarth Movers’ Stochastic Conformance Checking
Earth Movers’ Stochastic Conformance Checking
 
Using Process Mining to Remove Operational Friction in Shared Services
Using Process Mining to Remove Operational Friction in Shared ServicesUsing Process Mining to Remove Operational Friction in Shared Services
Using Process Mining to Remove Operational Friction in Shared Services
 
Object-Centric Process Mining: Dealing With Divergence and Convergence in Eve...
Object-Centric Process Mining: Dealing With Divergence and Convergence in Eve...Object-Centric Process Mining: Dealing With Divergence and Convergence in Eve...
Object-Centric Process Mining: Dealing With Divergence and Convergence in Eve...
 
Process Mining In Today’s Platforms Economy: Opportunities and Challenges (WI...
Process Mining In Today’s Platforms Economy: Opportunities and Challenges (WI...Process Mining In Today’s Platforms Economy: Opportunities and Challenges (WI...
Process Mining In Today’s Platforms Economy: Opportunities and Challenges (WI...
 
Event Logs: What kind of data does process mining require?
Event Logs: What kind of data does process mining require?Event Logs: What kind of data does process mining require?
Event Logs: What kind of data does process mining require?
 
Configurable Declare: Designing Customizable Flexible Models
Configurable Declare: Designing Customizable Flexible ModelsConfigurable Declare: Designing Customizable Flexible Models
Configurable Declare: Designing Customizable Flexible Models
 
On the Role of Fitness, Precision, Generalization and Simplicity in Process D...
On the Role of Fitness, Precision, Generalization and Simplicity in Process D...On the Role of Fitness, Precision, Generalization and Simplicity in Process D...
On the Role of Fitness, Precision, Generalization and Simplicity in Process D...
 
A Decade of Business Process Management Conferences: Reflections on a Develop...
A Decade of Business Process Management Conferences: Reflections on a Develop...A Decade of Business Process Management Conferences: Reflections on a Develop...
A Decade of Business Process Management Conferences: Reflections on a Develop...
 
Service Interaction: Patterns, Formalization, and Analysis
Service Interaction: Patterns, Formalization, and AnalysisService Interaction: Patterns, Formalization, and Analysis
Service Interaction: Patterns, Formalization, and Analysis
 
Keynote on Process Mining at SSCI 2010 / CIDM 2011
Keynote on Process Mining at SSCI 2010 / CIDM 2011Keynote on Process Mining at SSCI 2010 / CIDM 2011
Keynote on Process Mining at SSCI 2010 / CIDM 2011
 
Process Mining - Chapter 14 - Epilogue
Process Mining - Chapter 14 - EpilogueProcess Mining - Chapter 14 - Epilogue
Process Mining - Chapter 14 - Epilogue
 
Process Mining - Chapter 11 - Analyzing Lasagna Processes
Process Mining - Chapter 11 - Analyzing Lasagna ProcessesProcess Mining - Chapter 11 - Analyzing Lasagna Processes
Process Mining - Chapter 11 - Analyzing Lasagna Processes
 
Process Mining - Chapter 10 - Tool Support
Process Mining - Chapter 10 - Tool SupportProcess Mining - Chapter 10 - Tool Support
Process Mining - Chapter 10 - Tool Support
 
Process Mining - Chapter 9 - Operational Support
Process Mining - Chapter 9 - Operational SupportProcess Mining - Chapter 9 - Operational Support
Process Mining - Chapter 9 - Operational Support
 
Process Mining - Chapter 8 - Mining Additional Perspectives
Process Mining - Chapter 8 - Mining Additional PerspectivesProcess Mining - Chapter 8 - Mining Additional Perspectives
Process Mining - Chapter 8 - Mining Additional Perspectives
 
Process Mining - Chapter 5 - Process Discovery
Process Mining - Chapter 5 - Process DiscoveryProcess Mining - Chapter 5 - Process Discovery
Process Mining - Chapter 5 - Process Discovery
 
Process Mining - Chapter 4 - Getting the Data
Process Mining - Chapter 4 - Getting the DataProcess Mining - Chapter 4 - Getting the Data
Process Mining - Chapter 4 - Getting the Data
 

Recently uploaded

Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostLeverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostZilliz
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupFlorian Wilhelm
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubKalema Edgar
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):comworks
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningLars Bell
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Manik S Magar
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity PlanDatabarracks
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Scott Keck-Warren
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsSergiu Bodiu
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
Artificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxArtificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxhariprasad279825
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Commit University
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationSlibray Presentation
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .Alan Dix
 

Recently uploaded (20)

Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostLeverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project Setup
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding Club
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine Tuning
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity Plan
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
Artificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxArtificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptx
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck Presentation
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .
 

TomTom for Business Process Managment (TomTom4BPM)

  • 1. TomTom for Business Process Management (TomTom4BPM) prof.dr.ir. Wil van der Aalst www.processmining.org
  • 2. Today's information systems are really crappy compared to a TomTom system! • Good maps? • Navigation by PowerPoints? • Traffic information? • Where is the next fuel station? • Who is in charge? • Seamless zoom? • Customizable views? • When will the destination be reached? PAGE 1
  • 5. Process Mining • Process discovery: "What is really happening?" • Conformance checking: "Do we do what was agreed upon?" • Performance analysis: "Where are the bottlenecks?" • Process prediction: "Will this case be late?" • Process improvement: "How to redesign this process?" • Etc. PAGE 4
  • 6. • Process discovery: "What is the real curriculum?" • Conformance checking: "Do students meet the prerequisites?" • Performance analysis: "Where are the bottlenecks?" • Process prediction: "Will a student complete his studies (in time)?" • Process improvement: "How to redesign the curriculum?" PAGE 5
  • 7. Process Mining A step towards TomTom functionality for business processes
  • 8. Where to start? process diagnosis control process mining process process enactment design implementation/ configuration PAGE 7
  • 9. Process mining: Linking events to models PAGE 8
  • 10. Process mining as a mirror ... PAGE 9
  • 11. Where did we apply process mining? • Municipalities (e.g., Alkmaar, Heusden, Harderwijk, etc.) • Government agencies (e.g., Rijkswaterstaat, Centraal Justitieel Incasso Bureau, Justice department) • Insurance related agencies (e.g., UWV) • Banks (e.g., ING Bank) • Hospitals (e.g., AMC hospital, Catharina hospital) • Multinationals (e.g., DSM, Deloitte) • High-tech system manufacturers and their customers (e.g., Philips Healthcare, ASML, Thales) • Media companies (e.g. Winkwaves) • ... PAGE 10
  • 12. Example: WMO process of a Dutch Municipality 144 cases (i.e., requests for adaptation of house) WMO = Wet Maatschappelijke Ondersteuning 1326 recorded events PAGE 11
  • 13. Conformance check of discovered model both performed while not allowed activity is good fit sometimes not 97.9% performed drill down PAGE 12
  • 14. Performance analysis time bottle from neck A to B flow time PAGE 13
  • 15. Events sorted by duration PAGE 14
  • 16. "Real" animation PAGE 15
  • 17. And of course ... PAGE 16
  • 18. Reality ≠ PowerPoint (or Visio) PAGE 17
  • 19. Process spectrum structured unstructured (Lasagna) (Spaghetti) PAGE 18
  • 20. 375 houses 18640 events 82 different activities PAGE 19
  • 21. 2712 patients 29258 events 264 different activities PAGE 20
  • 22. 874 patients 10478 events 181 different activities PAGE 21
  • 23. 24 machines 154966 events 360 different activities PAGE 22
  • 24. 37.5% OK 62.5% NOK design reality PAGE 23
  • 26. Process Mining: TomTom for Business Processes
  • 27. How can process mining help? • Good maps? • Navigation by PowerPoints? • Traffic information? • Where is the next fuel station? • Who is in charge? • Seamless zoom? • Customizable views? • When will the destination be reached? PAGE 26
  • 28. city highway PAGE 27
  • 30. When will I be home?
  • 32. Approach When? 12-6-2009! PAGE 31
  • 33. Input: partial trace and historic information (A B C D C D C D E)? (14-6-2009)! (12-6-2009)! PAGE 32
  • 34. Input PAGE 33
  • 35. Building transition systems C D {A,B} {A,B,C} {A,B,C,D} B B A C {} {A} {A,C} many E abstractions ABCD D are possible {A,E} {A,D,E} ACBD and supported AED ABCD (a) transition system based on sets by ProM's ABCD FSM miner AED C D ACBD <A,B> <A,B,C> <A,B,C,D> ... B A E D <> <A> <A,E> <A,E,D> C B D <A,C> <A,C,B> <A,C,B,D> (b) transition system based on sequences PAGE 34
  • 36. Annotated transition system based on remaining time PAGE 35
  • 37. Predictive information average: 7.2 average: 0 average: 10.33 st. dev.: 1.79 st. dev.: 0 st. dev.: 1.53 min: 6 min: 0 min: 9 max: 10 max: 0 max: 12 predict: 10.33 predict: 0 average: 25.75 [12,9,10] [6,10,6,6,8] [0,0,0,0,0] st. dev.: 12.25 C D {A,B} {A,B,C} {A,B,C,D} min: 13 max: 44 [18,26,44,13, 14,40,24] B predict: 7.2 B C {} {A} {A,C} A average: 25.75 [22,19] st. dev.: 12.25 [18,26,44,13, predict: 25.75 E min: 13 14,40,24] D {A,E} max: 44 {A,D,E} [34,31] [0,0] average: 32.5 st. dev.: 2.12 A B C D min: 31 average: 20.5 average: 0 max: 34 st. dev.: 2.12 st. dev.: 0 min: 19 min: 0 PAGE 36 max: 22 max: 0
  • 38. Example: WOZ process in Dutch Municipality 1882 objections triggering 11985 activities PAGE 37
  • 39. All 11985 events at a glance Average flow time is 107 days (with a huge variation) PAGE 38
  • 40. For partial traces corresponding to this state the estimated time until completion is 8.5 days PAGE 39
  • 41. Cross validation: Mean rooted Average MSE MAPE training set and test set Error (MAE) PAGE 40
  • 42. Some results PAGE 41
  • 45. Conclusion • The abundance of event data enables a wide variety of process mining techniques ranging from process discovery to conformance checking. • A reality check for people that are involved in process modeling. • TomTom functionality is already possible today! • Check out ProM with its 250+ plug-ins. • Contribute: case studies, plug-ins, etc. PAGE 44
  • 46. Thanks! cf. www.processmining.org • Wil van der Aalst • Mercy Amiyo • Jan Martijn van der Werf • Peter van den Brand • Carmen Bratosin • Martin van Wingerden • Boudewijn van Dongen • Toon Calders • Jianhong Ye • Christian Günther • Jorge Cardoso • Huub de Beer • Eric Verbeek • Ronald Crooy • Elena Casares • Ana Karla Alves de Medeiros • Florian Gottschalk • Alina Chipaila • Anne Rozinat • Monique Jansen-Vullers • Walid Gaaloul • Minseok Song • Peter Khisa Wakholi • Martijn van Giessel • Ton Weijters • Nicolas Knaak • Shaifali Gupta • Remco Dijkman • Sven Lambrechts • Thomas Hoffmann • Gianluigi Greco • Joyce Nakatumba • Peter Hornix • Antonella Guzzo • Mariska Netjes • René Kerstjens • Kristian Bisgaard Lassen • Mykola Pechenizkiy • Ralf Kramer • Ronny Mans • Maja Pesic • Wouter Kunst • Jan Mendling • Hajo Reijers • Laura Maruster • Vladimir Rubin • Stefanie Rinderle • Andriy Nikolov • Nikola Trcka • Domenico Saccà • Adarsh Ramesh • Irene Vanderfeesten • Helen Schonenberg • Jo Theunissen • Barbara Weber • Marc Voorhoeve • Kenny van Uden • Lijie Wen • Jianmin Wang • ... PAGE 45
  • 47. Relevant WWW sites http://www.senternovem.nl/innovatievouchers MKB 2.500 – 7.500 euro • http://www.processmining.org • http:// promimport.sourceforge.net • http://prom.sourceforge.net • http://www.workflowpatterns.com • http://www.workflowcourse.com • http://www.vdaalst.com PAGE 46