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Chapter 11
Analyzing “Lasagna Processes”

 prof.dr.ir. Wil van der Aalst
 www.processmining.org
Overview
Chapter 1
Introduction



Part I: Preliminaries

Chapter 2                   Chapter 3
Process Modeling and        Data Mining
Analysis


Part II: From Event Logs to Process Models

Chapter 4                  Chapter 5               Chapter 6
Getting the Data           Process Discovery: An   Advanced Process
                           Introduction            Discovery Techniques


Part III: Beyond Process Discovery

Chapter 7                   Chapter 8              Chapter 9
Conformance                 Mining Additional      Operational Support
Checking                    Perspectives


Part IV: Putting Process Mining to Work

Chapter 10                  Chapter 11             Chapter 12
Tool Support                Analyzing “Lasagna     Analyzing “Spaghetti
                            Processes”             Processes”


Part V: Reflection

Chapter 13                  Chapter 14
Cartography and             Epilogue
Navigation
                                                                          PAGE 1
How can process mining help?

• Detect bottlenecks        • Provide mirror
• Detect deviations         • Highlight important
• Performance                 problems
  measurement               • Avoid ICT failures
• Suggest improvements      • Avoid management by
• Decision support (e.g.,     PowerPoint
  recommendation and        • From “politics” to
  prediction)                 “analytics”




                                                PAGE 2
Example of a Lasagna process: WMO
    process of a Dutch municipality




Each line corresponds to one of the 528 requests that were
handled in the period from 4-1-2009 until 28-2-2010. In total
there are 5498 events represented as dots. The mean time
needed to handled a case is approximately 25 days.              PAGE 3
WMO process
  (Wet Maatschappelijke Ondersteuning)

• WMO refers to the social support act that came into
  force in The Netherlands on January 1st, 2007.
• The aim of this act is to assist people with disabilities
  and impairments. Under the act, local authorities are
  required to give support to those who need it, e.g.,
  household help, providing wheelchairs and
  scootmobiles, and adaptations to homes.
• There are different processes for the different kinds of
  help. We focus on the process for handling requests
  for household help.
• In a period of about one year, 528 requests for
  household WMO support were received.
• These 528 requests generated 5498 events.
                                                         PAGE 4
C-net discovered using
heuristic miner (1/3)




                         PAGE 5
C-net discovered using
heuristic miner (2/3)




                         PAGE 6
C-net discovered using
heuristic miner (3/3)




                         PAGE 7
Conformance check WMO process (1/3)




                                  PAGE 8
Conformance check WMO process (2/3)




                                  PAGE 9
Conformance check WMO process (3/3)




            The fitness of the discovered
            process is 0.99521667. Of the 528
            cases, 496 cases fit perfectly
            whereas for 32 cases there are
            missing or remaining tokens.



                                                PAGE 10
Bottleneck analysis WMO process (1/3)




                                        PAGE 11
Bottleneck analysis WMO process (2/3)




                                        PAGE 12
Bottleneck analysis WMO process (3/3)




flow time of
approx. 25 days
with a standard
deviation of
approx. 28




                                        PAGE 13
Use cases for process mining



  improve KPIs related to time    goal              action   redesign (improve process)

                                                             adjust (improve control)
 improve KPIs related to costs           use case
                                                             intervene (handle problem in ad-hoc manner)

improve KPIs related to quality                              support (detect, predict, recommend)




                                                                                                    PAGE 14
L* life-cycle model

                              Stage 0: plan and justify


                 data understanding            business understanding
                                                                                                  For a Lasagna process all
                                    Stage 1: extract                                              stages are applicable (in
                                                                                                  principle).

                   historic     handmade     objectives   questions
                    data         models        (KPIs)

   explore
  discover
     check
  compare            Stage 2: create control-flow model
  promote                 and connect event log

                                                               diagnose


                        event log               control-flow model                    redesign
                                                                          interpret




   enhance
                     Stage 3: create integrated process
                                   model                                               adjust




  current data          event log                 process model                       intervene




     detect              Stage 4: operational support                                 support
    predict
recommend                                                                                                                PAGE 15
Functional areas

                                                   service

                   procurement
                                 product development




                                                        sales/CRM




                                                                       customers
 suppliers




                                  finance/accounting
                                 resource management
                                      production
                                       logistics



Lasagna processes are typically encountered in production,
finance/accounting, procurement, logistics, resource management, and
sales/CRM. Spaghetti processes are typically encountered in product
development, service, resource management, and sales/CRM.
                                                                       PAGE 16
We applied ProM in >100 organizations

• 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, Ricoh, Thales)
• Media companies (e.g. Winkwaves)
• ...
                                                        PAGE 17
Two Lasagna processes

                               RWS
                        (“Rijkswaterstaat”)
                              process




                        WOZ (“Waardering
                        Onroerende Zaken”)
                             process

                                       PAGE 18
RWS Process

• The Dutch national public works department, called
  “Rijkswaterstaat” (RWS), has twelve provincial offices.
  We analyzed the handling of invoices in one of these
  offices.
• The office employs about 1,000 civil servants and is
  primarily responsible for the construction and
  maintenance of the road and water infrastructure in its
  province.
• To perform its functions, the RWS office subcontracts
  various parties such as road construction companies,
  cleaning companies, and environmental bureaus. Also,
  it purchases services and products to support its
  construction, maintenance, and administrative
  activities.                                        PAGE 19
C-net discovered using heuristic miner




                                         PAGE 20
Social network constructed based on
handovers of work



                          Each of the 271 nodes
                          corresponds to a civil
                          servant. Two civil
                          servants are
                          connected if one
                          executed an activity
                          causally following an
                          activity executed by the
                          other civil servant




                                              PAGE 21
Social network consisting of civil servants that
executed more than 2000 activities in a 9 month period.




                                         The darker arcs
                                         indicate the strongest
                                         relationships in the
                                         social network.
                                         Nodes having the
                                         same color belong to
                                         the same clique.




                                                          PAGE 22
WOZ process

• Event log containing information about 745 objections
  against the so-called WOZ (“Waardering Onroerende
  Zaken”) valuation.
• Dutch municipalities need to estimate the value of
  houses and apartments. The WOZ value is used as a
  basis for determining the real-estate property tax.
• The higher the WOZ value, the more tax the owner needs
  to pay. Therefore, there are many objections (i.e.,
  appeals) of citizens that assert that the WOZ value is too
  high.
• “WOZ process” discovered for another municipality (i.e.,
  different from the one for which we analyzed the WMO
  process).
                                                        PAGE 23
Discovered process model




The log contains events related to 745 objections against the
so-called WOZ valuation. These 745 objections generated 9583
events. There are 13 activities. For 12 of these activities both
start and complete events are recorded. Hence, the WF-net has
                                                                   PAGE 24
25 transitions.
Conformance checker:
(fitness is 0.98876214)




                          PAGE 25
Performance analysis
                                               bottleneck detection: places are
                                               colored based on average durations




                  time required to
                  move from one
                  activity to another



                            information on
                             total flow time




                                                                          PAGE 26
Resource-activity matrix
(four groups discovered)



                                      clique 1



                           clique 2




                                                              clique 3


                                                 clique 4




                                                            PAGE 27

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Process Mining - Chapter 11 - Analyzing Lasagna Processes

  • 1. Chapter 11 Analyzing “Lasagna Processes” prof.dr.ir. Wil van der Aalst www.processmining.org
  • 2. Overview Chapter 1 Introduction Part I: Preliminaries Chapter 2 Chapter 3 Process Modeling and Data Mining Analysis Part II: From Event Logs to Process Models Chapter 4 Chapter 5 Chapter 6 Getting the Data Process Discovery: An Advanced Process Introduction Discovery Techniques Part III: Beyond Process Discovery Chapter 7 Chapter 8 Chapter 9 Conformance Mining Additional Operational Support Checking Perspectives Part IV: Putting Process Mining to Work Chapter 10 Chapter 11 Chapter 12 Tool Support Analyzing “Lasagna Analyzing “Spaghetti Processes” Processes” Part V: Reflection Chapter 13 Chapter 14 Cartography and Epilogue Navigation PAGE 1
  • 3. How can process mining help? • Detect bottlenecks • Provide mirror • Detect deviations • Highlight important • Performance problems measurement • Avoid ICT failures • Suggest improvements • Avoid management by • Decision support (e.g., PowerPoint recommendation and • From “politics” to prediction) “analytics” PAGE 2
  • 4. Example of a Lasagna process: WMO process of a Dutch municipality Each line corresponds to one of the 528 requests that were handled in the period from 4-1-2009 until 28-2-2010. In total there are 5498 events represented as dots. The mean time needed to handled a case is approximately 25 days. PAGE 3
  • 5. WMO process (Wet Maatschappelijke Ondersteuning) • WMO refers to the social support act that came into force in The Netherlands on January 1st, 2007. • The aim of this act is to assist people with disabilities and impairments. Under the act, local authorities are required to give support to those who need it, e.g., household help, providing wheelchairs and scootmobiles, and adaptations to homes. • There are different processes for the different kinds of help. We focus on the process for handling requests for household help. • In a period of about one year, 528 requests for household WMO support were received. • These 528 requests generated 5498 events. PAGE 4
  • 6. C-net discovered using heuristic miner (1/3) PAGE 5
  • 7. C-net discovered using heuristic miner (2/3) PAGE 6
  • 8. C-net discovered using heuristic miner (3/3) PAGE 7
  • 9. Conformance check WMO process (1/3) PAGE 8
  • 10. Conformance check WMO process (2/3) PAGE 9
  • 11. Conformance check WMO process (3/3) The fitness of the discovered process is 0.99521667. Of the 528 cases, 496 cases fit perfectly whereas for 32 cases there are missing or remaining tokens. PAGE 10
  • 12. Bottleneck analysis WMO process (1/3) PAGE 11
  • 13. Bottleneck analysis WMO process (2/3) PAGE 12
  • 14. Bottleneck analysis WMO process (3/3) flow time of approx. 25 days with a standard deviation of approx. 28 PAGE 13
  • 15. Use cases for process mining improve KPIs related to time goal action redesign (improve process) adjust (improve control) improve KPIs related to costs use case intervene (handle problem in ad-hoc manner) improve KPIs related to quality support (detect, predict, recommend) PAGE 14
  • 16. L* life-cycle model Stage 0: plan and justify data understanding business understanding For a Lasagna process all Stage 1: extract stages are applicable (in principle). historic handmade objectives questions data models (KPIs) explore discover check compare Stage 2: create control-flow model promote and connect event log diagnose event log control-flow model redesign interpret enhance Stage 3: create integrated process model adjust current data event log process model intervene detect Stage 4: operational support support predict recommend PAGE 15
  • 17. Functional areas service procurement product development sales/CRM customers suppliers finance/accounting resource management production logistics Lasagna processes are typically encountered in production, finance/accounting, procurement, logistics, resource management, and sales/CRM. Spaghetti processes are typically encountered in product development, service, resource management, and sales/CRM. PAGE 16
  • 18. We applied ProM in >100 organizations • 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, Ricoh, Thales) • Media companies (e.g. Winkwaves) • ... PAGE 17
  • 19. Two Lasagna processes RWS (“Rijkswaterstaat”) process WOZ (“Waardering Onroerende Zaken”) process PAGE 18
  • 20. RWS Process • The Dutch national public works department, called “Rijkswaterstaat” (RWS), has twelve provincial offices. We analyzed the handling of invoices in one of these offices. • The office employs about 1,000 civil servants and is primarily responsible for the construction and maintenance of the road and water infrastructure in its province. • To perform its functions, the RWS office subcontracts various parties such as road construction companies, cleaning companies, and environmental bureaus. Also, it purchases services and products to support its construction, maintenance, and administrative activities. PAGE 19
  • 21. C-net discovered using heuristic miner PAGE 20
  • 22. Social network constructed based on handovers of work Each of the 271 nodes corresponds to a civil servant. Two civil servants are connected if one executed an activity causally following an activity executed by the other civil servant PAGE 21
  • 23. Social network consisting of civil servants that executed more than 2000 activities in a 9 month period. The darker arcs indicate the strongest relationships in the social network. Nodes having the same color belong to the same clique. PAGE 22
  • 24. WOZ process • Event log containing information about 745 objections against the so-called WOZ (“Waardering Onroerende Zaken”) valuation. • Dutch municipalities need to estimate the value of houses and apartments. The WOZ value is used as a basis for determining the real-estate property tax. • The higher the WOZ value, the more tax the owner needs to pay. Therefore, there are many objections (i.e., appeals) of citizens that assert that the WOZ value is too high. • “WOZ process” discovered for another municipality (i.e., different from the one for which we analyzed the WMO process). PAGE 23
  • 25. Discovered process model The log contains events related to 745 objections against the so-called WOZ valuation. These 745 objections generated 9583 events. There are 13 activities. For 12 of these activities both start and complete events are recorded. Hence, the WF-net has PAGE 24 25 transitions.
  • 26. Conformance checker: (fitness is 0.98876214) PAGE 25
  • 27. Performance analysis bottleneck detection: places are colored based on average durations time required to move from one activity to another information on total flow time PAGE 26
  • 28. Resource-activity matrix (four groups discovered) clique 1 clique 2 clique 3 clique 4 PAGE 27