Manfred Reichert, Barbara Weber
Enabling Flexibility in
Process-Aware Information
Systems
Challenges, Methods, Technologies
March 29, 2012
Springer
(c) Springer-Verlag, Berlin Heidelberg, 2012
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Contents
Part I Basic Concepts and Flexibility Issues
1 Introduction ................................................... 3
1.1 Motivation ................................................ 3
1.2 Goal and Intended Audience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3 Learning Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.4 Outline and Organization of the Chapters. . . . . . . . . . . . . . . . . . . . . . . 6
2 Process-Aware Information Systems .............................. 9
2.1 Introduction............................................... 9
2.2 Pre-specified and Repetitive Processes . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2.1 Motivation.......................................... 11
2.2.2 Examples of Pre-specified Processes . . . . . . . . . . . . . . . . . . . . 11
2.2.3 Discussion.......................................... 14
2.3 Knowledge-Intensive Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.3.1 Motivation.......................................... 15
2.3.2 Examples of Knowledge-Intensive Processes . . . . . . . . . . . . . 16
2.3.3 Discussion.......................................... 19
2.4 Perspectives on a Process-Aware Information System . . . . . . . . . . . . 20
2.4.1 Function Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.4.2 Behavior Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.4.3 Information Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.4.4 Organization Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.4.5 Operation Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.4.6 Time Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.5 Components of a Process-Aware Information System . . . . . . . . . . . . 29
2.5.1 Overview........................................... 29
2.5.2 Build-time Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.5.3 Run-time Environment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.6 Summary ................................................. 39
Exercises ...................................................... 41
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3 Flexibility Issues in Process-Aware Information Systems ............ 43
3.1 Motivation ................................................ 43
3.2 A Taxonomy of Flexibility Needs in Process-aware Information
Systems .................................................. 44
3.2.1 Variability .......................................... 45
3.2.2 Looseness .......................................... 46
3.2.3 Adaptation.......................................... 46
3.2.4 Evolution........................................... 48
3.3 Requirements for a Flexible PAIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.4 Summary ................................................. 52
3.5 BookStructure............................................. 53
Exercises ...................................................... 54
Part II Flexibility Support for Pre-Specified Processes
4 Process Modeling & Flexibility-by-Design ......................... 59
4.1 Motivation ................................................ 59
4.2 Modeling Pre-specified Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.2.1 Basic Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.2.2 Control Flow Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4.2.3 Flexibility-by-Design through Control Flow Patterns . . . . . . 69
4.2.4 Granularity of Process Models and its Relation to Flexibility 71
4.3 Executing Pre-specified Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.3.1 Process Instance and Execution Trace . . . . . . . . . . . . . . . . . . . 73
4.3.2 Enabled Activities and Instance Completion . . . . . . . . . . . . . . 75
4.4 Verifying Pre-specified Process Models . . . . . . . . . . . . . . . . . . . . . . . . 76
4.4.1 Process Model Soundness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
4.4.2 Correctness of Data Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
4.4.3 Well-structured versus Unstructured Process Models . . . . . . . 83
4.5 Summary ................................................. 85
Exercises ...................................................... 85
5 Process Configuration Support .................................. 89
5.1 Motivation ................................................ 89
5.2 Behavior-based Configuration Approaches . . . . . . . . . . . . . . . . . . . . . 92
5.2.1 Hiding and Blocking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
5.2.2 Configurable Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.3 Structural Configuration Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . 103
5.3.1 Representing a Process Family through a Base Process
and Pre-specified Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
5.3.2 Configuring a Process Variant through Structural Changes . . 110
5.4 End-User Support in Configuring Process Variants . . . . . . . . . . . . . . . 112
5.4.1 Questionnaire-driven Process Configuration . . . . . . . . . . . . . . 112
5.4.2 Feature-driven Process Configuration . . . . . . . . . . . . . . . . . . . 118
5.4.3 Context-driven Process Configuration . . . . . . . . . . . . . . . . . . . 120
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5.5 FurtherAspects............................................120
5.5.1 Capturing Variability of Multiple Process Perspectives . . . . . 120
5.5.2 Ensuring Correctness of Configured Process Variants . . . . . . 121
5.5.3 Merging Process Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
5.5.4 Adaptive Reference Process Modeling . . . . . . . . . . . . . . . . . . 123
5.6 Summary .................................................123
Exercises ......................................................123
6 Exception Handling ............................................127
6.1 Motivation ................................................127
6.2 Exception Sources and Their Detection . . . . . . . . . . . . . . . . . . . . . . . . 129
6.2.1 Sources of Exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
6.2.2 Detecting Exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
6.3 Handling Exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
6.3.1 Exception Handling Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
6.4 Compensation Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
6.4.1 Semantic Rollback through Compensation . . . . . . . . . . . . . . . 143
6.4.2 Compensation Spheres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
6.5 Exception Handling in Selected Approaches . . . . . . . . . . . . . . . . . . . . 147
6.5.1 Compensation and Exception Handling in WS-BPEL . . . . . . 147
6.5.2 Exception Handling in the Exlet Approach . . . . . . . . . . . . . . . 148
6.6 Summary .................................................149
Exercises ......................................................150
7 Ad-hoc Changes of Process Instances .............................153
7.1 Motivation ................................................153
7.2 Changing the Behavior of a Running Process Instance . . . . . . . . . . . . 156
7.2.1 Core Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
7.2.2 A Basic Taxonomy for Ad-hoc Changes . . . . . . . . . . . . . . . . . 160
7.3 Structurally Adapting Pre-specified Process Models . . . . . . . . . . . . . . 162
7.3.1 Basics..............................................162
7.3.2 Adaptation Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
7.3.3 Defining Structural Changes with Adaptation Patterns . . . . . 168
7.3.4 Ensuring Correctness of Structural Changes . . . . . . . . . . . . . . 173
7.4 Ensuring State Compliance with a Changed Process Model . . . . . . . 175
7.4.1 Ad-hoc Changes and Process Instance States . . . . . . . . . . . . . 176
7.4.2 A Correctness Notion for Dynamic Instance Changes . . . . . . 178
7.4.3 A Relaxed Correctness Notion for Coping with Loop
Changes............................................180
7.4.4 Efficient Realization of Ad-hoc Changes . . . . . . . . . . . . . . . . . 184
7.5 Manual Definition of Ad-hoc Changes . . . . . . . . . . . . . . . . . . . . . . . . . 187
7.6 Assisting End-users through the Reuse of Ad-hoc Changes . . . . . . . . 189
7.6.1 Reusing Knowledge about Similar Ad-hoc Changes . . . . . . . 189
7.6.2 Memorizing Ad-hoc Changes . . . . . . . . . . . . . . . . . . . . . . . . . . 191
7.6.3 Retrieving and Adapting Similar Ad-hoc Changes . . . . . . . . . 197
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7.6.4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
7.7 Automated Adaptation and Evolution of Process Instances . . . . . . . . 204
7.8 Duration of Ad-hoc Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
7.9 ChangeScope .............................................206
7.10 FurtherIssues..............................................207
7.10.1 Controlling Access to Process Change Functions . . . . . . . . . . 207
7.10.2 Controlling Concurrent Ad-hoc Changes. . . . . . . . . . . . . . . . . 208
7.10.3 Ensuring Traceability of Ad-hoc Changes . . . . . . . . . . . . . . . . 209
7.10.4 Ensuring Business Process Compliance . . . . . . . . . . . . . . . . . 210
7.11 Discussion ................................................210
7.12 Summary .................................................211
Exercises ......................................................212
8 Monitoring and Mining Flexible Processes ........................217
8.1 Introduction...............................................217
8.2 Execution and Change Logs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
8.3 Mining Execution Logs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222
8.3.1 Process Discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
8.3.2 Conformance Checking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225
8.4 Mining Change Logs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
8.4.1 Anatomy of Process Changes . . . . . . . . . . . . . . . . . . . . . . . . . . 227
8.4.2 Directly Applying Process Mining to Change Logs . . . . . . . . 230
8.4.3 Understanding Change Dependencies . . . . . . . . . . . . . . . . . . . 231
8.4.4 Enhancing Multi-Phase Mining with Commutativity . . . . . . . 233
8.4.5 Mining Change Processes with Regions . . . . . . . . . . . . . . . . . 237
8.5 Mining Process Variants in the Absence of a Change Log . . . . . . . . . 238
8.5.1 Closeness of a Reference Process Model and a Collection
of Process Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
8.5.2 Scenarios for Mining Process Variants. . . . . . . . . . . . . . . . . . . 241
8.5.3 A Heuristic Approach for Process Variant Mining . . . . . . . . . 242
8.5.4 Other Approaches for Process Variant Mining . . . . . . . . . . . . 245
8.6 Summary .................................................246
Exercises ......................................................247
9 Process Evolution and Instance Migration ........................249
9.1 Motivation ................................................249
9.2 Fundamentals of Process Model Evolution . . . . . . . . . . . . . . . . . . . . . 250
9.2.1 Evolving a Process Model at the Process Type Level . . . . . . . 250
9.2.2 Deferred Process Model Evolution . . . . . . . . . . . . . . . . . . . . . . 252
9.2.3 Immediate Process Model Evolution and Instance Migration 253
9.2.4 User Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258
9.2.5 Existing Approaches for Migrating Process Instances . . . . . . 260
9.3 Common Support of Type and Instance Changes . . . . . . . . . . . . . . . . 262
9.3.1 Migrating Biased Process Instances . . . . . . . . . . . . . . . . . . . . . 263
9.3.2 Overlapping Changes at the Type and Instance Level . . . . . . 266
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9.3.3 Integrated Change Support in Existing Approaches . . . . . . . . 270
9.4 Coping with Non-compliant Process Instances . . . . . . . . . . . . . . . . . . 271
9.4.1 Example Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272
9.4.2 Bringing Non-compliant Instances into a Compliant State . . 273
9.4.3 Advanced Strategies for Treating Non-compliant Instances . 274
9.5 Evolving other PAIS Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277
9.5.1 Changes of the Organization Perspective . . . . . . . . . . . . . . . . . 277
9.5.2 Changes of the Information Perspective . . . . . . . . . . . . . . . . . 278
9.5.3 Changes of other Perspectives. . . . . . . . . . . . . . . . . . . . . . . . . . 278
9.6 Process Model Refactoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279
9.6.1 Identifying Refactoring Opportunities . . . . . . . . . . . . . . . . . . . 279
9.6.2 Refactoring Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282
9.7 Summary .................................................287
Exercises ......................................................287
10 Business Process Compliance ....................................293
10.1 Motivation ................................................293
10.2 Modeling Compliance Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 296
10.3 A-priori Compliance Checking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302
10.4 Compliance Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304
10.5 A-posteriori Compliance Checking . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306
10.6 Effects of Process Changes on Compliance . . . . . . . . . . . . . . . . . . . . . 308
10.7 UserPerspective ...........................................310
10.8 Existing Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312
10.9 Summary .................................................312
Exercises ......................................................313
Part III Flexibility Support for Loosely-Specified Processes
11 Concretizing Loosely-Specified Processes .........................319
11.1 Motivation ................................................319
11.2 Taxonomy of Decision Deferral . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 320
11.2.1 Degree of Freedom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 320
11.2.2 Planning Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322
11.2.3 Scope of Decision Deferral . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322
11.2.4 Process Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323
11.2.5 Degree of Automation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323
11.2.6 Decision Making and Decision Support. . . . . . . . . . . . . . . . . . 324
11.3 Decision Deferral Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324
11.4 LateSelection .............................................326
11.5 Late Modeling & Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330
11.6 Ad-hoc Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332
11.7 Iterative Refinement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333
11.8 Summary .................................................335
Exercises ......................................................336
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12 Constraint-based Process Models ................................337
12.1 Motivation ................................................337
12.2 Modeling Constraint-based Processes . . . . . . . . . . . . . . . . . . . . . . . . . . 338
12.2.1 Constraint-based Process Models . . . . . . . . . . . . . . . . . . . . . . . 339
12.2.2 Overview of Control Flow Constraints . . . . . . . . . . . . . . . . . . 341
12.3 Executing Constraint-based Processes . . . . . . . . . . . . . . . . . . . . . . . . . 347
12.3.1 Executing Constraint-based Models without Overlapping
Activities...........................................349
12.3.2 Executing Constraint-based Models with Overlapping
Activities...........................................351
12.4 Verifying Constraint-based Process Models . . . . . . . . . . . . . . . . . . . . . 353
12.5 Adapting and Evolving Constraint-based Process Models . . . . . . . . . 356
12.6 Assistance for Modeling and Evolving Constraint-based Processes . 359
12.6.1 Understandability and Maintainability Issues of
Constraint-based Process Models . . . . . . . . . . . . . . . . . . . . . . . 359
12.6.2 Test-driven Modeling of Constraint-based Process Models . . 361
12.7 Assistance for Executing Constraint-based Process Models . . . . . . . . 363
12.8 Combining Constraint-based and Pre-specified Models . . . . . . . . . . . 364
12.9 Summary and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366
Exercises ......................................................367
Part IV User- and Data-driven Processes
13 User- and Data-driven Processes .................................373
13.1 Introduction ...............................................373
13.2 The Case Handling Paradigm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375
13.2.1 Basic Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375
13.2.2 Strengths and Weaknesses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377
13.2.3 Discussion..........................................379
13.3 Object-aware Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380
13.3.1 Object Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 382
13.3.2 Object Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 382
13.3.3 Data-driven Execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384
13.3.4 Variable Activity Granularity . . . . . . . . . . . . . . . . . . . . . . . . . . 385
13.3.5 Integrated Access to Business Processes and Objects . . . . . . 386
13.4 Existing Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387
13.4.1 Case Handling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387
13.4.2 Proclets ............................................389
13.4.3 Business Artifacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 390
13.4.4 Data-driven Process Coordination . . . . . . . . . . . . . . . . . . . . . . 392
13.4.5 Product-based Workflow Support . . . . . . . . . . . . . . . . . . . . . . . 393
13.4.6 Other Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395
13.4.7 Discussion..........................................395
13.5 Summary .................................................395
Exercises ......................................................397
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14 A Framework for Object-Aware Processes ........................401
14.1 Introduction ...............................................401
14.2 Overview of the Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403
14.3 DataModel ...............................................405
14.3.1 Object Relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 406
14.3.2 Integrating Users . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 408
14.4 MicroProcesses............................................410
14.4.1 MicroSteps.........................................411
14.4.2 Process States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412
14.4.3 Internal Micro Transitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 414
14.4.4 External Micro Transitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415
14.4.5 Further Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417
14.5 Process and Data Authorization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 418
14.5.1 Authorization Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 418
14.5.2 Automatic Generation of Form-based Activities. . . . . . . . . . . 421
14.6 MacroProcesses ...........................................422
14.6.1 Basic Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 423
14.6.2 Process Context Coordination Component . . . . . . . . . . . . . . . 424
14.6.3 Aggregation Coordination Component . . . . . . . . . . . . . . . . . . 425
14.6.4 Transverse Coordination Component . . . . . . . . . . . . . . . . . . . . 428
14.6.5 Integrating Black-box Activities . . . . . . . . . . . . . . . . . . . . . . . . 428
14.6.6 Further Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429
14.7 Discussion ................................................430
14.8 Summary .................................................433
Exercises ......................................................433
Part V Technologies Enabling Flexibility Support in Process-Aware
Information Systems
15 AristaFlow BPM Suite ..........................................437
15.1 Introduction ...............................................437
15.2 Handling Errors and Exceptions in AristaFlow . . . . . . . . . . . . . . . . . . 439
15.2.1 Illustrating Application Scenario . . . . . . . . . . . . . . . . . . . . . . . 439
15.2.2 Perspectives on the Handling of Exceptions and Errors . . . . . 440
15.3 System Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451
15.4 Using the AristaFlow BPM Suite in Actual Practice . . . . . . . . . . . . . . 454
15.4.1 Case Study 1: Disaster Management . . . . . . . . . . . . . . . . . . . . 454
15.4.2 Case Study 2: Healthcare Process Management . . . . . . . . . . . 455
15.4.3 Case Study 3: Software Engineering Processes . . . . . . . . . . . 456
15.4.4 Other Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457
15.5 Summary .................................................457
Exercises ......................................................458
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xiv Contents
16 Alaska Simulator Toolset........................................461
16.1 Motivation ................................................461
16.2 Alaska Simulator Toolset: Meta-Model . . . . . . . . . . . . . . . . . . . . . . . . 462
16.3 Deciding at the Last Responsible Moment . . . . . . . . . . . . . . . . . . . . . . 466
16.4 Architecture of Alaska Simulator Toolset . . . . . . . . . . . . . . . . . . . . . . . 467
16.5 Case Studies: Using Alaska Simulator Toolset in Practice . . . . . . . . . 469
16.6 Summary .................................................469
Exercises ......................................................472
17 Existing Tool Support for Flexible Processes ......................475
17.1 SelectedTools .............................................475
17.2 FurtherTools ..............................................476
Part VI Summary, References, Appendices
18 Epilogue ......................................................479
18.1 Enabling Flexibility in Process-Aware Information Systems . . . . . . . 480
18.2 OpenChallenges...........................................481
A Overview of BPMN Elements ....................................485
References.....................................................487
Index .............................................................505
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Chapter 3
Flexibility Issues in Process-Aware Information
Systems
Abstract Traditionally, process-ware information systems (PAISs) have focused on
the support of predictable and repetitive business processes. Even though respec-
tive processes are suited to be fully pre-specified in a process model, flexibility is
required to support dynamic process adaptations in case of exceptions. Flexibility
is also needed to accommodate the need for evolving business processes and to
cope with business process variability. Furthermore, PAISs are increasingly used to
support less structured processes which can often be characterized as knowledge-
intensive. Processes of this category are neither fully predictable nor repetitive, and
therefore cannot be fully pre-specified at build-time. The (partial) unpredictability
of these processes also demands a certain amount of looseness. This chapter deals
with the flexibility needs of both pre-specified and loosely-specified processes and
elicitates requirements for flexible process support in a PAIS. In addition, the chap-
ter discusses PAIS features needed to accommodate flexibility needs in practice like,
for example, traceability, business compliance and user support.
3.1 Motivation
Traditionally, PAISs have focused on the support of predictable and repetitive busi-
ness processes, which can be fully described prior to their execution in terms of for-
mal process models [179]. Typical examples falling in this category include business
processes in banking and insurance companies; e.g., opening a new bank account or
granting a loan. Even though repetitive business processes are usually predictable,
a certain degree of flexibility is needed to support dynamic process adaptations in
case of exceptions; e.g., death of a policyholder or a marital divorce requiring a
change of insurance and/or beneficiaries [337]. Moreover, flexibility is required to
accommodate the need for evolving business processes. As example consider pro-
cess changes due to altered legal requirements. Finally, support for business process
variability is needed. For example, different process variants may exist depending
on the type of insurances.
43
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44 3 Flexibility Issues in Process-Aware Information Systems
PAISs are increasingly used to support less structured business processes as well.
The latter are often characterized as knowledge-intensive. Processes of this cat-
egory feature non-repeatability, i.e., the models of two process instances do not
fully resemble one another. Generally, knowledge-intensive processes tend to be
unpredictable since the exact course of action depends on situation-specific param-
eters [337]. The values of these parameters are usually not known a priori and may
change during process execution. Moreover, knowledge-intensive processes can be
characterized as emergent, i.e., knowledge gathered during the execution of the pro-
cess determines its future course of action [141]. Consequently, respective processes
cannot be prescribed at a fine-grained level at build-time. In addition to variabil-
ity, adaptation and evolution that is required for predictable processes, they require
looseness. Typical examples of the latter process category include innovation pro-
cesses (e.g., introducing a new product or service) and call center processes (e.g.,
handling of a computer problem by the helpdesk).
The vast majority of business processes, however, can be characterized by a com-
bination of predictable and unpredictable elements falling in between these two ex-
tremes. Healthcare processes, for example, reflect the combination of predictable
and unpredictable elements quite well. While procedures for handling single medi-
cal orders or examinations are relatively predictable, complex patient treatment pro-
cesses are rather unpredictable and unfold during process execution [173]. Similar
considerations hold for law enforcement processes (i.e., investigation of a crime)
[337]. A criminal investigation constitutes an example of a knowledge-intensive
process that can be characterized by non-repeatability, unpredictability, and emer-
gence. However, this process has predictable elements as well; e.g., lab analysis or
witness deposition.
Providing appropriate support for this wide range of business processes poses
several challenges, which will be detailed in this chapter. In Section 3.2 we elaborate
in detail on the different flexibility needs. Once these are identified, Section 3.3
elicitates fundamental requirements for flexible business process support by a PAIS.
Finally, Section 3.4 discusses the organization of the remaining book chapters along
the identified flexibility needs.
3.2 A Taxonomy of Flexibility Needs in Process-aware
Information Systems
Flexible process support by a PAIS can be characterized by four major flexibility
needs, namely support for variability, looseness, adaptation, and evolution (cf. Fig.
3.1). Each of these flexibility needs may affect each of the process perspectives
(i.e., behavior, organization, information, operation, function, and time) introduced
in Chapter 2. In the subsequent sections of this chapter we present a brief summary
of each flexibility need and present real-world processes to illustrate it. A detailed
discussion of concepts and methods satisfying these needs follows in the remaining
book chapters.
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3.2 A Taxonomy of Flexibility Needs in Process-aware Information Systems 45
Fig. 3.1 A Taxonomy of Process Flexibility Needs
3.2.1 Variability
Process variability can be found in many domains and requires processes to be han-
dled differently—resulting in different process variants—depending on the given
context [107, 125, 130]. Process variants typically share the same core process
whereas the concrete course of action fluctuates from variant to variant. Product and
service variability, for example, often require support for different process variants
depending on the concrete product variant [227]. Moreover, process variants might
exist due to differences in regulations found in different countries and regions [129].
Variability might be also introduced due to different groups of customers (e.g., pri-
ority care for premium customers) or due to temporal differences (e.g., seasonal
changes). The parameters causing process variability are mostly known a priori
(e.g., country-specific regulations). Even though the concrete variant can often only
be determined during process execution, the course of action for a particular context
is well understood.
Example 3.1 (Vehicle Repair). The process for handling vehicle repair in a
garage constitutes a good example of a process showing high variability. De-
pending on the process context, different variants of this process are required.
While some parts of the process are shared by all variants, variability is in-
troduced due to country-specific, garage-specific, and vehicle-specific differ-
ences. Overall, hundreds of variants may exist in such a context [129].
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46 3 Flexibility Issues in Process-Aware Information Systems
3.2.2 Looseness
As discussed, knowledge-intensive processes can be characterized as non-repeatable
(i.e., every process instance looks slightly different), unpredictable (i.e., the exact
course of action is unknown and is highly situation-specific), and emergent (i.e., the
exact course of action only emerges during process execution when more informa-
tion becomes available). For processes of this category only their goal is known a
priori (e.g., treating the rupture of a patient’s cruciate ligament or the judical pro-
cess in seeking a criminal conviction). In turn, the parameters determining the exact
course of action are typically not known a priori and might change during process
execution. As a consequence, these processes cannot be fully pre-specified. In ad-
dition, it is not possible to establish a set of process variants for these processes,
since the parameters causing differences between process instances are not known
a priori (unlike with variability). Instead, processes of this category require a loose
specification.
Example 3.2 (Patient Treatment Processes). Patient treatment processes in a
hospital typically comprise activities related to patient intake, admission, di-
agnosis, treatment, and discharge [173]. Typically, such processes comprise
dozens up to hundreds of activities and are long-running (i.e., from a few days
to several months). Furthermore, the treatments of two different patients are
rarely identical; instead the course of action greatly depends on the specific
situation; e.g., health status of the patient, allergies and chemical intolerances,
decisions made by the physician, examination results, and clinical indications.
This situation can change during the treatment process, i.e., the course of ac-
tion is unpredictable. Moreover, treatment processes typically unfold during
their execution, i.e., examination results yield information determining how
to continue with the treatment. The overall treatment process thereby emerges
through the arrangement of simple, well structured processes (e.g., handling
medical orders) often resulting in complex process structures.
3.2.3 Adaptation
Adaptation represents the ability of a PAIS to adapt the process and its structure (i.e.,
pre-specified model) to emerging events. Respective events often lead to situations
in which the PAIS does not adequately reflect the real-world process anymore. As a
consequence, one or several process instances have to be adapted in order to realign
the computerized processes with the real-world ones.
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3.2 A Taxonomy of Flexibility Needs in Process-aware Information Systems 47
Drivers for Adaptation. Process adaptations are triggered by different drivers. Re-
spective adaptations might be required to cope with special situations during process
execution, which have not been foreseen in the process model [335], e.g., because
they only occur very rarely. Moreover, exceptions occurring in the real-world (e.g.,
an allergic reaction of a patient) or processing errors (e.g., a failed activity) often
require deviations from the standard process. A detailed discussion of sources for
exceptions will follow in Chapter 6.
Anticipation of Adaptation. Usually, many exceptions can be anticipated and
therefore be planned upfront by capturing them in the process model. Generally,
a deviation can only be planned if both the context of its occurrence and measures
to handle it are known. However, it is hardly possible to foresee all exceptions that
may occur in the context of a particular process. Therefore, support for dealing with
unplanned exceptions is additionally needed.
Example 3.3 (Examination Procedures in a Hospital). A simple examination
procedure in a hospital comprises activities like Enter Order,Schedule
Examination,Inform Patient,Transfer Patient,Perform Medical Examina-
tion,Medical Report, and Validate Report (cf. Example 2.2 in Chapter 2).
Even for such a simple process, exceptional situations might occur, that
require deviations from the pre-specified process. For example, in case of an
emergency there is no time to follow the usual procedure. Instead the patient
is immediately examined without making any appointment or preparing the
examination facility. To cope with such situation, it should be possible to skip
one or more activities. In exceptional situations it can further be required to
perform additional (i.e., unplanned) activities for a particular patient (e.g., to
carry out an additional preparation step for the examination). Besides changes
in appointments, cancellations, failures in the execution of activities (e.g.,
omitted preparations, loss of a sample, or incorrect collection of diagnostic
material) might also lead to deviations from the standard procedure (e.g., by
redoing activities). If an appointment is cancelled, for example, the patient
treatment process (including the previously made appointment) will have to
be aborted.
In the medical domain such deviations from the standard procedure are the
norm and have to be flexibly addressed by physicians and nursing staff.
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48 3 Flexibility Issues in Process-Aware Information Systems
3.2.4 Evolution
Evolution represents the ability of the process implemented in a PAIS to change
when the corresponding business process evolves [62, 291]. Since business pro-
cesses can evolve over time, it is not sufficient to implement them once and then
to never touch the PAIS again. In order to ensure that real-world processes and the
PAIS remain aligned, these changes have to be propagated to the PAIS as well.
Typically, such evolutionary changes are planned changes at the process type level,
which are conducted to accommodate evolving needs.
Drivers for Business Process Evolution. Process evolution is often driven by
changes in the business, the technological environment, and the legal context [14].
Another driver is organizational learning. All these drivers are external to the PAIS
(cf. Fig. 3.2). Evolution of real-world processes can be triggered by a changing
business context like an evolving market (e.g., emergence of new competitors) or
changing customer behavior. Changes in the technological context might have far
reaching effects on the business processes of an organization. For example, the in-
creasing popularity of mobile devices is revolutionizing the way how people are
interacting with each other. Changes might further be triggered by regulatory adap-
tations like, for example, the introduction of Sarbanes-Oxley [339] or Basel II [43].
Finally, changes of business processes might be a result of organizational learning
and be triggered by emerging optimization opportunities or misalignments between
real-world processes and the ones supported by PAISs.
In addition to external triggers, changes of processes implemented in a PAIS
might also become necessary due to developments inside the PAIS, i.e., there exist
internal drivers for changes as well [14]. For example, design errors might cause
problems during the execution of process instances in the PAIS (e.g., deadlocks
or missing data). Moreover, technical problems like performance degradation (e.g.,
due to an increasing amount of data) may require changes in the PAIS. Finally, poor
internal quality of process models (e.g., non intention revealing naming of activities
or redundant process model fragments) may require changes [352].
Extent of Evolution. Process evolution may be incremental (i.e., only requiring
small changes of the implemented process) as for continuous process improvements
[138, 239, 242], or be revolutionary (i.e., requiring radical changes) as in the context
of process innovation or process re-engineering [131].
Swiftness of Evolution. Depending on the kind of evolutionary change, different
requirements regarding the treatment of ongoing process instances exist [255]. In
some scenarios, it is sufficient to apply the changes only to those process instances
which will be newly created and to complete the ongoing ones according to the
old version of the business process. This, in turn, would require deferred evolu-
tion and co-existence of different versions of a process model within the PAIS. In
many practical scenarios, however, evolutionary changes have an effect on ongoing
process instances as well. For example, regulatory changes often have a retroactive
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3.2 A Taxonomy of Flexibility Needs in Process-aware Information Systems 49
PAIS
Real-world
Process
Design Errors
Technical Problems
Changing Technological Context
Changing Legal Context
Organizational Learning
Changing Business Context
represented in
provide feedback to
Poor Model Quality
External Drivers Internal Drivers
Fig. 3.2 Real-world Versus Computerized Processes
impact and require ongoing process instances (if they have not progressed too far) to
be adapted. Such immediate evolution is mostly relevant for long-running processes
instances, i.e., process instances with a duration up to several weeks or months.
Duration of Evolution. Evolutionary changes can be permanent or temporary.
While permanent changes are valid from the time they are introduced (unless they
are compensated by later permanent changes), temporary changes are only valid for
a certain period of time, e.g., during a special promotion period.
Visibility of Evolution. Evolutionary changes may either be changes of the ob-
servable process behavior or the internal structure of the PAIS. While changes of
the observable behavior are always reflected by the PAIS support of the real-world
processes, changes of the internal structure are kept inside the PAIS (e.g., to ad-
dress poor internal model quality) [352]. Adding or deleting activities from a pro-
cess model are examples of changes concerning the observable behavior. A typical
change only affecting the internal structure of the PAIS includes the removal of
process model redundancies by extracting common parts to sub-process models.
Example 3.4 (Tender Preparation). A typical process for tender preparation
comprises activities like Enter Customer Request,Check Feasibility,Create
Offer, and Submit Tender. For standard customers the offer is usually created
based on the latest price list, while for gold customers a special offer is pre-
pared which has to be authorized by the department head. Since the creation of
special offers (including checks of the special terms of the offer) turned out to
be more expensive than estimated benefits (e.g., through increased customer
loyalty), the management decided to evolve the process such that no special
offers would be made in future.
In this example the evolution is triggered through organizational learning
and economic concerns. The change is incremental and affects the external
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50 3 Flexibility Issues in Process-Aware Information Systems
behavior of the process in a permanent manner. Moreover, the change is de-
ferred; i.e., it only affects newly created offers (i.e., future process instances).
Example 3.5 (Introduction of New Medical Devices). The introduction of new
medical imaging devices in a hospital sometimes has implications on the cor-
responding examination process. Assume that due to the high acquisition cost
for the new device the hospital decides to use it for examining outpatients as
well (in addition to inpatient examinations). This, in turn, implies changes in
the registration procedure. These changes not only affect new patients, but
also ongoing examination processes.
In this example the evolution is triggered through economic concerns. As
in Example 3.4 the change is incremental and affects the external behavior of
the process in a permanent manner. Moreover, the change is immediate; i.e.,
it also affects ongoing examination processes.
Example 3.6 (Inconsistent Naming of Process Models). Large process model
repositories that have evolved over many years often have significant inconsis-
tencies regarding activity labels and labeling styles. For example, the reposi-
tory described in [324] contained 16 process models all having activities deal-
ing with the scheduling of medical procedures (e.g., surgeries, medical ex-
aminations and drug administrations). Though all these activities had similar
intentions, different labels and labeling styles were used (e.g., “Make Ap-
pointment”, “Appointment”, “Schedule Examination”, “Fix Day”, “Agree on
Surgery Date”, and “Plan”). This, in turn, required a huge effort when reusing
the models later in the context of a large process model harmonization. In par-
ticular, activity labels had to be consolidated by refactoring respective process
models [352].
3.3 Requirements for a Flexible PAIS
From the previously described flexibility needs (i.e., variability, looseness, adapta-
tion, and evolution), technical requirements can be derived which have to be met by
any PAIS supporting flexible processes (cf. Table 3.1). To enable process variability
at a technical level, PAISs need to provide support for configurable process models
and for the context-specific configuration of particular process variants. To accom-
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3.3 Requirements for a Flexible PAIS 51
modate the need for looseness, in turn, PAISs must provide support for loosely-
specified process models, which do not require a completely pre-specified process
model, but allow deferring modeling decisions to the run-time. Moreover, support
for planned exceptions in terms of exception handling support as well as unplanned
or unanticipated exceptions through the support of ad-hoc changes allowing for de-
viations from a pre-specified process model is needed. To adequately cope with
business process evolution, PAISs require versioning support for process models
(i.e., for deferred evolution) enabling the co-existence of different process model
versions at the same time. Additionally, immediate evolution requires the migration
of ongoing process instances to the new process model version. The problem of poor
process model quality, in turn, requires adequate support for process model refactor-
ing which improves the quality of a process model without altering the observable
behavior. Finally, to provide feedback regarding the execution of real-world pro-
cesses and to foster organizational learning, IT-support for monitoring, analyzing
and mining flexible processes becomes crucial.
Table 3.1 Mapping Flexibility Needs to Technical Requirements
Flexibility Need Dimension Technical Requirement
Variability Configuration
Looseness Loosely-specified Processes
Adaptation Planned Exception Handling
Unplanned Ad-hoc Changes
Evolution Deferred Evolution, Versioning
Immediate Evolution, Process Instance Migration
Poor Model Quality, Refactoring
Organizational Learning Monitoring, Analysis and Mining
In addition to the support for variability, looseness, adaptation and evolution,
flexible PAISs have to provide several other features to enable process flexibility in
practice.
Accountability and traceability. Even though PAISs become less prescriptive
with increasing flexibility, both traceability and accountability still need to be guar-
anteed. Organizations are required to comply with a wide range of regulations like
Sarbanes Oxley (SOX) [339] or Basel II [43]. In the context of SOX, for exam-
ple, it is important to be able to trace back who made which changes when and
why. For this, executed activities as well as applied process changes have to be
logged. If users need to bypass the PAIS, because a change requirement cannot be
implemented quickly enough in the PAIS, traceability is no longer guaranteed and a
mismatch between the PAIS and the real-world processes it supports exists.
Business compliance. In addition to accountability and traceability, compliance
with existing rules and regulations is another fundamental issue. Despite the pro-
vided flexibility, it has to be ensured that (dynamic) process changes in PAIS do not
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52 3 Flexibility Issues in Process-Aware Information Systems
lead to such violations or that the reasons of such compliance violations are at least
documented to ensure traceability as described above.
Access control. With increasing flexibility, PAISs become more vulnerable to
misuse [355, 78]. Therefore, the application of changes at the process type as well
as the process instance level must be restricted to authorized users.
Correctness of changes. When adapting or evolving business processes—potentially
in the midst of their execution—it has to be ensured that changes are performed in a
controlled manner and do not lead to run-time errors; e.g., crashed activity programs
due to missing input data, deadlocks due to blocking activities, or data inconsisten-
cies due to lost updates.
User support. With increasing PAIS flexibility the need for user support be-
comes more and more important [323]. While traditional PAISs provide little ma-
neuvering room for their users, loosely-specified processes require many decisions
to be made along the way and therefore require significantly more user experience.
Need for learning from process instance changes. Regarding instance-specific
process adaptations, same or similar exceptions might occur more than once, mak-
ing the reuse of existing exception handling procedures desirable [218, 360]. For
example, the knowledge that a magnetic resonance tomography (MRT) could not
be performed for a patient with cardiac pacemaker is highly relevant when treating
other patients with the same or similar problems. Generally, when similar exceptions
occur frequently, this often indicates a gap between the modeled processes and the
corresponding real-world ones. This misalignment often stems from errors in the
design of a process model or is the result of changing requirements. Therefore, flex-
ible PAISs should continuously monitor deviations between a pre-defined process
model and the actual process enactment in order to detect discrepancies between
modeled and observed process behavior.
In the context of loosely-specified processes two process instances are rarely
identical. However, similarities between process instances often exist. As a con-
sequence, reuse of previously conducted process instances or the discovery of fre-
quently occurring similar process fragments should be supported.
Concurrency of changes. Any PAIS supporting instance-specific adaptations
should be able to cope with concurrent changes. In particular, PAISs need to han-
dle situations in which instance-specific adaptations (i.e., ad hoc changes) and evo-
lutionary changes overlap. This is especially important when evolution has to be
immediate and not deferred.
3.4 Summary
This chapter discussed the flexibility needs of both pre-specified and loosely-
specified processes in detail; i.e., adaptation, evolution, looseness, and variability.
Based on these flexibility needs characteristic requirements were derived that any
PAIS enabling flexible business process support has to fulfill. PAISs and their pro-
cess models do not only need to be configurable, be able to deal with exceptions, and
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3.5 Book Structure 53
allow for changing the execution of single business cases (i.e., process instances)
on-the-fly, but must also support the evolution of business processes over time. Re-
sponsiveness to change is fundamental for any PAIS and thus continuous process
model refactorings are needed to ensure maintainability, especially when process
model repositories become increasingly large. Moreover, the monitoring, analysis
and mining of processes is fundamental. In addition, this chapter discussed funda-
mental PAIS features that are also needed to accommodate the described flexibility
needs in practice. In particular, traceability and accountability must be ensured at
all times and changes need to be performed in a controlled manner to guarantee
correctness. Furthermore, security constraints as well as compliance with existing
policies and regulations need to be ensured. Flexible PAISs should also assist their
users through recommendations and learning from instance deviations.
3.5 Book Structure
Fig. 3.3 depicts the overall organization of the remaining chapters of this book deal-
ing with the four major needs for variability, looseness, adaptation and evolution.
Part II of this book deals with flexibility support for pre-specified processes.
This part primarily considers predictable and repetitive processes. Chapter 5 ad-
dresses the need for variability in business processes and discusses techniques en-
abling process configuration support. Chapter 6 explores on the handling of planned
adaptations through exception handling techniques, while Chapter 7 deals with un-
planned exceptions and their support through ad-hoc changes of individual process
instances. Chapter 8 discusses monitoring, analysis and mining support for flexible
processes fostering the incremental evolution of business processes. Chapter 9 ad-
dresses the requirement for evolution and elaborates on versioning, instance migra-
tion and refactoring support. Part II ends with Chapter 10, which discusses business
compliance issues in the context of process changes.
Part III of this book focuses on less predictable processes with a comparably low
degree of repetition and deals with the need for looseness. Chapter 11 first provides
an overview of different approaches and techniques realizing loosely-specified pro-
cess models. With constraint-based processes, Chapter 12 then introduces one spe-
cific approach for realizing loosely-specified processes in more detail.
Part IV deals with the integration of data and processes and discusses the po-
tential for increasing flexibility through such an integrated approach. Chapter 13
introduces object-centric, artifact-based, and data-driven approaches, while Chapter
14 deals with a specific framework enabling flexible object-aware and data-driven
processes.
Finally, Part V focuses on tool support. Chapter 15 introduces the Aristaflow
BPM Suite process management technology as a representative for a system sup-
porting pre-specified processes including advanced support for adaptation and evo-
lution. Chapter 16 describes Alaska, which provides support for different ap-
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54 3 Flexibility Issues in Process-Aware Information Systems
proaches enabling loosely-specified processes. Additional tools are discussed in
Chapter 17.
Configurable Process Models (Chapter 5)
Loosely-specified Models (Chapter 11 + 12)
Planned Adaptations – Exception Handling (Chapter 6)
Unplanned Adaptations – Ad-hoc Changes (Chapter 7)
Deferred Evolution – Versioning (Chapter 9)
Immediate Evolution – Instance Migration (Chapter 9)
Dealing with Poor Internal Quality – Refactoring (Chapter 9)
Supporting Organizational Learning – Monitoring, Analysis
and Mining (Chapter 8)
Semantic Correctness and Compliance of Changes (Chapter 10)
Integrating Data and Processes (Chapter 13 + 14)
Tool Support and Technology Comparison (Chapter 15 - 17)
Fig. 3.3 Organization of the Remaining Chapters
Exercises
3.1. Flexibility Needs
In the following the check-in and boarding procedures from the perspective of two
hypothetical travelers we will call Tom and Tina Traveler are depicted.
Tom Traveler wants to spend the weekend in Barcelona to explore the city his
friends are so enthusiastic about. Since the flight is departing in 90 minutes from the
nearby airport in Innsbruck, Tom calls a taxi, which arrives a few minutes later and
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3.5 Book Structure 55
takes him to the airport which is just a few kilometers from his home. Tom arrives at
the airport about an hour before departure. He then immediately goes to the check-
in counter where he drops off his bag and gets the boarding pass. Since there is
still enough time before boarding Tom decides to drink a quick coffee. Afterwards
he gets through security, which is usually quite fast in Innsbruck and only requires a
few minutes to complete. For this, Tom has to get his laptop out of his carry-on bag
and puts it in the provided bin. He then places his bag as well as his jacket on the
conveyor belt to be X-rayed. Having placed the laptop, his bag and the jacket on the
conveyor belt, he waits for the signal to proceed through the metal detector. Once he
has passed the metal detector, Tom is asked by the screener to take out his camera
from the carry-on bag so that she can look through the lens. After this check he is
allowed to repack. Tom then buys a newspaper and walks to the gate to wait for the
boarding call. Five minutes later boarding starts and Tom enters the airplane.
Like Tom Traveler, Tina Traveler wants to spend the weekend in Barcelona. Tina
takes the bus to get to the airport in Innsbruck and arrives about 20 minutes later
at the airport. Having arrived at the airport she immediately goes to the check-
in counter where she drops off her bag. Unlike Tom, Tina has already printed out
her boarding pass at home. After baggage drop-off Tina immediately wants to get
through security. Tina places her jacket as well as her carry-on-bag in the provided
bin provided on the conveyor belt to be X-rayed. She then waits for the signal to
proceed through the metal detector. After the check she gets her carry-on bag as
well as her jacket. Tina then buys a newspaper and walks to the gate to wait for the
boarding call. A few minutes later boarding starts and Tina enters the airplane.
(a) How would you classify this process in terms of predictability and repeatability?
(b) What kind of flexibility needs can you identify in this context?
3.2. Flexibility Needs
Give examples (others than the ones described in this book) for business processes
requiring variability, looseness, adaptation, and evolution.
(a) Give examples where process variability is required. What are the driving forces
behind variability in these examples?
(b) Think about processes that are characterized by non-repeatability, unpredictabil-
ity and emergence and therefore require looseness.
(c) Give examples for both planned and unforeseen process adaptations.
(d) Think about situations where deferred evolution is sufficient. Give examples
where immediate evolution is required. Use the taxonomy depicted in Fig. 3.1
to characterize the scenarios.
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