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Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
Colloquium@TUe
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Colloquium@TUe

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Slides of my presentation at Eindhoven University of Technology, 3 October 2013, Eindhoven, the Netherlands

Slides of my presentation at Eindhoven University of Technology, 3 October 2013, Eindhoven, the Netherlands

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  • Start point(s)End point(s)ActivitiesOrderDecision pointsThroughput timesetc
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    • 1. Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info TU/e Colloquium 2013 2 October, 2013 FACULTY OF ECONOMICS AND BUSINESS ADMINISTRATION The process of process modeling and process model quality Jan Claes Teaching assistant : PhD 2009 – 2015 : Joint PhD Supervisors : Geert Poels (UGent) and Paul Grefen (TU/e) Co-supervisors : Frederik Gailly (UGent) and Irene Vanderfeesten (TU/e)
    • 2. TU/e Colloquium 2013 2/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Outline Process of process modeling (PPM)  PPMChart visualization  Structured process modeling (SPM) Future work: preliminary ideas  Process model quality  Experiments to link SPM with quality
    • 3. TU/e Colloquium 2013 3/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) Properties of textual description Properties of modeler Properties of modeling process Properties of resulting model PRIMARY RESEARCH FOCUS Properties of real process Properties of observation process Properties of software and modeling language Properties of model reader Properties of reading process Properties of process engine
    • 4. TU/e Colloquium 2013 4/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) Observational modeling sessions  People construct models  Every action on modeling canvas is logged  Different datasets • 120 students in Eindhoven 2010 • 14 experts in Berlin 2010 • 14 experts in Eindhoven 2011 • 118 students in Eindhoven 2012 • 146 students in Gent 2013
    • 5. TU/e Colloquium 2013 5/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) Properties of the modeling process Activity Timestamp Attributes Create start event 10:00 Id = 1; x = 10; y = 10 Create activity 10:04 Id = 2; x = 40; y = 10; name = “Receive order” Create edge 10:05 Id = 3; from = 1, to = 2 Move activity 10:07 Id = 2; x = 15; y = 10 Create gateway 10:08 Id = 4; x = 65; y = 10; type = “XOR” Create edge 10:09 Id = 5; from = 2, to = 4 Create activity 10:24 Id = 6; x = 80; y = 0; name = “Reject order” Create activity 10:25 Id = 7; x = 80; y = 20; name = “Prepare order” Create gateway 10:27 Id = 8; x = 105; y = 10; type = “XOR”
    • 6. TU/e Colloquium 2013 6/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info  CREATE_ACTIVITY  CREATE_START_EVENT  CREATE_END_EVENT  CREATE_AND  CREATE_XOR  CREATE_EDGE  MOVE_ACTIVITY  MOVE_START_EVENT  MOVE_END_EVENT  MOVE_AND  MOVE_XOR  DELETE_ACTIVITY  DELETE_START_EVENT  DELETE-END_EVENT  DELETE_AND  DELETE_XOR  DELETE_EDGE  NAME_ACTIVITY  RENAME_ACTIVITY  NAME_EDGE  RENAME_EDGE Process of Process Modeling (PPM) Visualization in PPMChart time modelelements
    • 7. TU/e Colloquium 2013 7/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) 9 design principles of visual notations(Moody 2009)  Visual expressiveness  Perceptual discriminability  Graphic economy  Semantic transparency  Semiotic clarity  Dual coding  Cognitive fit  Complexity management  Cognitive integration
    • 8. TU/e Colloquium 2013 8/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) Visual expressiveness  Optimal use of graphical variables  8 graphical variables: shape, size, color, brightness, orientation, texture, horizontal position and vertical position(Bertin, 2010)  Color is most effective(Lohse, 1993; Treisman, 1982; Winn, 1993)  But can also cause problems (e.g., color blindness, black-and-white printers)
    • 9. TU/e Colloquium 2013 9/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) 8 graphical variables  Shape: model element type (   )  Size: not used  Color: operation type (   )  Brightness: model element type (   )  Orientation: not used  Texture: not used  Horizontal position: time  Vertical position: model element
    • 10. TU/e Colloquium 2013 10/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) Perceptual discriminability  Symbols are clearly distinguishable  The more two concepts differ, the more the corresponding symbols should differ(Winn, 1990)  Visual distance is determined by • Number of different values for the graphical variables • Size of these differences  CREATE_ACTIVITY  CREATE_START_EVENT  CREATE_END_EVENT  CREATE_AND  CREATE_XOR  CREATE_EDGE  MOVE_ACTIVITY  MOVE_START_EVENT  MOVE_END_EVENT  MOVE_AND  MOVE_XOR  DELETE_ACTIVITY  DELETE_START_EVENT  DELETE-END_EVENT  DELETE_AND  DELETE_XOR  DELETE_EDGE  NAME_ACTIVITY  RENAME_ACTIVITY  NAME_EDGE  RENAME_EDGE
    • 11. TU/e Colloquium 2013 11/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) Graphic economy  Limited amount of values for each variable  Assures cognitive effectiveness(Nordbotten & Crosby, 1999)  Span of absolute judgment • Is the amount of distinct observable perceptual values • Estimated at seven (Miller, 1956)  Span of attention • Is the amount of different objects that can be distinguished at a glance • Estimated at six objects(Miller, 1956)
    • 12. TU/e Colloquium 2013 12/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) Semantic transparency  If a novice would be able to guess the meaning of each symbol  Achieved through natural mappings (Norman, 2002)  Shapes similar to bpmn (   )  Logical colors (creation, deletion, movement)  Horizontal timing
    • 13. TU/e Colloquium 2013 13/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) Semiotic clarity  Every concept is represented by exactly one symbol and every symbol represents exactly one concept (Goodman, 1968)  Same default symbol for XOR and AND gateway ()  Same default symbol for start and end event ()
    • 14. TU/e Colloquium 2013 14/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) Dual coding  For information processing  Graphical representation is better than textual  Combination has highest cognitive effectiveness (Paivio, 1990)  Textual line identifiers and time intervals  No textual code on the dots  Textual information in pop-up on selected items
    • 15. TU/e Colloquium 2013 15/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) Cognitive fit  Optimal representation depends on the task  Cognitive load is lower for experts(Vessey & Galletta, 1991) (Optimal representation depends on the modeler)  View is customizable through various options  View can be filtered (e.g. hide deleted elements)
    • 16. TU/e Colloquium 2013 16/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) Complexity management  Reduce complexity(R. Weber, 1997) • by modularization (divide the diagram in smaller subsystems) • hierarchical structuring (make separate diagrams of the same information at different levels of abstraction)  Only one PPM instance at a time
    • 17. TU/e Colloquium 2013 17/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process of Process Modeling (PPM) Cognitive integration  Mechanisms to integrate different diagrams (Hahn & Kim, 1999; Kim, Hahn, & Hahn, 2000)  Fixed default values for easy comparison  Line identifiers correspond to model element id’s  Lines are sorted according to model (start to end)
    • 18. TU/e Colloquium 2013 18/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info  CREATE_ACTIVITY  CREATE_START_EVENT  CREATE_END_EVENT  CREATE_AND  CREATE_XOR  CREATE_EDGE  MOVE_ACTIVITY  MOVE_START_EVENT  MOVE_END_EVENT  MOVE_AND  MOVE_XOR  DELETE_ACTIVITY  DELETE_START_EVENT  DELETE-END_EVENT  DELETE_AND  DELETE_XOR  DELETE_EDGE  NAME_ACTIVITY  RENAME_ACTIVITY  NAME_EDGE  RENAME_EDGE Process of Process Modeling (PPM) Visualization in PPMChart  Start event  Edge  Activity  Gateway  Edge  Activity  Edge  Edge  Activity  Edge  Gateway  Edge 7 29 8 9 32 14 30 31 10 33 56 34 time modelelements
    • 19. TU/e Colloquium 2013 19/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Structured Process Modeling (SPM) UNSTRUCTURED (rather) chaotic process
    • 20. TU/e Colloquium 2013 20/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Structured Process Modeling (SPM) FLOW-ORIENTED From start event to end event
    • 21. TU/e Colloquium 2013 21/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info ASPECT-ORIENTED Content – structure – lay-out Structured Process Modeling (SPM)
    • 22. TU/e Colloquium 2013 22/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info CHUNKING Work on model part by part Structured Process Modeling (SPM)
    • 23. TU/e Colloquium 2013 23/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Structured Process Modeling (SPM) Structured process modeling  Applying a modeling strategy consistently  Flow-oriented modeling versus aspect-oriented  First content, then structure, then lay-out  Finish aspect before continuing  Separate vertical zones  From start to end (according to the process flow)  Finish part before continuing  Diagonal zone in charts With or within chunks
    • 24. TU/e Colloquium 2013 24/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Structured Process Modeling (SPM) Cognitive aspects  Cognitive Load Theory (CLT) limited capacity of working memory  Cognitive Fit Theory (CFT) effect increase if task representation fits
    • 25. TU/e Colloquium 2013 25/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Structured Process Modeling (SPM) Conclusion 1 How to construct models? Apply a modeling style consistently! Properties of modeling process Properties of resulting model PRIMARY RESEARCH FOCUS Structured process modeling Aspect-oriented modeling Flow-oriented modeling Chunked modeling
    • 26. TU/e Colloquium 2013 26/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Different studies  Apply process mining techniques on historical data (Eo-BS)  Develop PPM visualization (Co-DS)  Different structuring styles (Ea-BS)  Link modeling strategy with model quality (Co-BS)  Develop method/tool to increase model quality (Co-DS) Different research methods  Behavioral science (BS) vs. Design science (DS)  Explorative (Eo) vs. Explanatory (Ea) vs. Confirmative (Co) Different studies  Apply process mining techniques on historical data  Develop PPM visualization  Different structuring styles  Link modeling strategy with model quality  Develop method/tool to increase model quality Methodology
    • 27. TU/e Colloquium 2013 27/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Business Process Modeling (BPM) Business process model  Graphical, abstract representation of a process  Important tool for analysis and improvement Business process model in BPMN notation
    • 28. TU/e Colloquium 2013 28/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Process model quality  Less nodes  Less crossing arcs  Less nested gateways  …  More realistic  More precise  More complete  … Which model is better?
    • 29. TU/e Colloquium 2013 29/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Which model is better? Process model quality  Less nodes  Less crossing arcs  Less nested gateways  …  More realistic  More precise  More complete  … InspectionExecution
    • 30. TU/e Colloquium 2013 30/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Execution Inspection Process model quality Conclusion 2 Process model quality? Depends on the goal of the model!
    • 31. TU/e Colloquium 2013 31/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Structured Process Modeling (SPM) How does SPM influence model quality? Structured process modeling lowers cognitive efforts and cognitive overload Less unintentional quality issues in model  Focus on correctness and completeness  Focus on understandability and maintainability But no effect on  Missing knowledge of domain or model language  Wrong quality focus
    • 32. TU/e Colloquium 2013 32/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Structured Process Modeling (SPM) Structured process modeling causes model quality improvement!  Explanation 1: • Apply structured modeling style • Lowers cognitive load • Results in improved process model quality  Explanation 2: • Have a lot of modeling experience • Results in a consistent modeling style • And in improved process model quality Or not?
    • 33. TU/e Colloquium 2013 33/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Experiments How to prove causality?  Take two identical groups of people  Give only one group a treatment  Let both groups make the same exercise  Check for significant difference of the results  Difference can only be caused by treatment
    • 34. TU/e Colloquium 2013 34/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Experiments Two identical groups  Randomized: assign participants randomly to group  Block randomized: control for secondary variables • E.g. equal amount of (fe)male participants in each group  Check with pre-test: check primary variables • E.g. check difference in experience of both groups
    • 35. TU/e Colloquium 2013 35/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Experiments Give only one group a treatment  Traditionally pharmaceutical  In our case learning a technique  Placebo effect  Treatment effect (TE) should be verified and separated from learning effect (LE)  Treatment group: TE + LE  Control group: LE
    • 36. TU/e Colloquium 2013 36/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Experiments Triple blinded  Blind experiment: participants do not know if they are in the treatment group or the control group  Double blind: participants and administrators do not know to which group participants belong  Triple blind: participants, administrators and data analysts do not know the group assignment
    • 37. TU/e Colloquium 2013 37/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Experiments Make the same exercise under the same conditions  Keep as much variables constant as possible  Try to control for the others  Literally the only difference between the two groups should be the treatment
    • 38. TU/e Colloquium 2013 38/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Participants for comparative experiment  High school students? OK!  Undergraduates? OK!  Experienced modelers? OK!  Non human movie characters? Not OK!  Cognitive processes in the human mind Experiments Participants for comparative experiment  High school students?  Undergraduates?  Experienced modelers?  Non human movie characters?
    • 39. TU/e Colloquium 2013 39/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Experiments with undergraduates When use students?  For confirmative, comparative experiments  No reason to believe that effect is different (general human cognitive processes)  Very homogeneous group, large groups When not to use students?  For explanatory, observational experiments  Use real modelers with varying levels of experience  Representative sample
    • 40. TU/e Colloquium 2013 40/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Experiments Conclusion 3 Use undergraduate students in experiments? Sometimes no, sometimes yes! ComparativeExplanatory
    • 41. TU/e Colloquium 2013 41/41 Ghent University & Eindhoven University of Technology jan.claes@ugent.be - www.janclaes.info Contact information Jan Claes jan.claes@ugent.be http://www.janclaes.info Twitter: @janclaesbelgium Thanks for your attention! Do you have feedback on my research plans? > explanatory theories < > behavioral science < > methodology < > evaluation <

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