Business Process Quality Management

Part of the International Handbooks on Information Systems book series (INFOSYS)


Process modeling is a central element in any approach to Business Process Management (BPM). However, what hinders both practitioners and academics is the lack of support for assessing the quality of process models – let alone realizing high quality process models. Existing frameworks are highly conceptual or too general. At the same time, various techniques, tools, and research results are available that cover fragments of the issue at hand. This chapter presents the SIQ framework that on the one hand integrates concepts and guidelines from existing ones and on the other links these concepts to current research in the BPM domain. Three different types of quality are distinguished and for each of these levels concrete metrics, available tools, and guidelines will be provided. While the basis of the SIQ framework is thought to be rather robust, its external pointers can be updated with newer insights as they emerge.


  1. Adrion WR, Branstad MA, Cherniavsky JC (1982) Validation, verification, and testing of computer software. ACM Comput Surv 14(2):159–192CrossRefGoogle Scholar
  2. Alves A, Arkin A, Askary S, Barreto C, Bloch B, Curbera F, Ford M, Goland Y, Guizar A, Kartha N, Liu CK, Khalaf R, Koenig D, Marin M, Mehta V, Thatte S, van der Rijn D, Yendluri P, Yiu A (2007) Web services business process execution language version 2.0. Committee specification, 31 January 2007Google Scholar
  3. Becker J, Rosemann M, von Uthmann C (2000) Guidelines of business process modeling. In: van der Aalst WMP, Desel J, Oberweis A (eds) Business process management Models, techniques, and empirical studies. Springer, Berlin, pp 30–49Google Scholar
  4. Becker J, Kugeler M, Rosemann M (eds) (2003) Process management, a guide for the design of business processes. Springer, Berlin, pp 41–78Google Scholar
  5. Bodart F, Patel A, Sim M, Weber R (2001) Should optional properties be used in conceptual modelling? A theory and three empirical tests. Inf Syst Res 12(4):384–405CrossRefGoogle Scholar
  6. Boehm BW, Brown JR, Kaspar JR et al (1978) Characteristics of software quality. TRW Series of Software Technology, AmsterdamGoogle Scholar
  7. Brooks LR (1967) The suppression of visualization by reading. Q J Exp Psychol 19(4):289–299CrossRefGoogle Scholar
  8. Curtis B, Kellner MI, Over J (1992) Process modeling. Commun ACM 35(9):75–90CrossRefGoogle Scholar
  9. D’Atri A, Solvberg A, Willcocks L (eds) (2001) Using prototyping in a product-driven design of business processes. In: Proceedings of the open enterprise solutions: systems, experiences, and organizations conference, Luiss EdizioniGoogle Scholar
  10. Davenport TH (1993) Process innovation: reengineering work through information technology. Harvard Business School Press, BostonGoogle Scholar
  11. Dehnert J, van der Aalst WMP (2004) Bridging the gap between business models and workflow specifications. Int J Cooper Inf Syst 13(3):289–332CrossRefGoogle Scholar
  12. Fliedl G, Kop C, Mayr HC (2005) From textual scenarios to a conceptual schema. Data Knowl Eng 55(1):20–37CrossRefGoogle Scholar
  13. Frederiks PJM, van der Weide TP (2006) Information modeling: the process and the required competencies of its participants. Data Knowl Eng 58(1):4–20CrossRefGoogle Scholar
  14. Gemino A (2004) Empirical comparisons of animation and narration in requirements validation. Requir Eng 9(3):153–168CrossRefGoogle Scholar
  15. Gemino A, Wand Y (2005) Complexity and clarity in conceptual modeling: comparison of mandatory and optional properties. Data Knowl Eng 55(3):301–326CrossRefGoogle Scholar
  16. Gruhn V, Laue R (2007) What business process modelers can learn from programmers. Sci Comput Program 65(1):4–13CrossRefGoogle Scholar
  17. Halpin TA, Curland M (2006) Automated verbalization for orm 2. In: Meersman R, Tari Z, Herrero P (eds) On the move to meaningful internet systems 2006. OTM 2006 workshops, Montpellier, October 29–November 3. Proceedings, Lecture notes in computer science, part II, vol 4278. Springer, Heidelberg, pp 1181–1190Google Scholar
  18. Hammer M, Champy J (1993) Reengineering the corporation: a manifesto for business revolution. Harpercollins, New YorkGoogle Scholar
  19. Keller G, Nüttgens M, Scheer AW (1992) Semantische Prozessmodellierung auf der Grundlage “Ereignisgesteuerter Prozessketten (EPK)”, Heft 89. Institut für Wirtschaftsinformatik, SaarbrückenGoogle Scholar
  20. Krogstie J, Sindre G, Jørgensen HD (2006) Process models representing knowledge for action: a revised quality framework. Eur J Inform Syst 15(1):91–102CrossRefGoogle Scholar
  21. Laue R, Mendling J (2008) The impact of structuredness on error probability of process models. In: Kaschek R, Kop C, Steinberger C, Fliedl G (eds) Information systems and e-business technologies. 2nd international united information systems conference. Lectures notes in business information processing, vol 5. Springer, HeidelbergGoogle Scholar
  22. Lindland OI, Sindre G, Sølvberg A (1994) Understanding quality in conceptual modeling. IEEE Software 11(2):42–49CrossRefGoogle Scholar
  23. Mayer RE (1989) Models for understanding. Rev Educ Res 59(1):43–64CrossRefGoogle Scholar
  24. Mayer RE (2001) Multimedia learning. Cambridge University Press, Cambridge, MACrossRefGoogle Scholar
  25. Mendling J (2008) Metrics for process models: empirical foundations of verification, error prediction, and guidelines for correctness, vol 6, Lecture notes in business information processing. Springer, BerlinGoogle Scholar
  26. Mendling J, Reijers HA (2008) How to define activity labels for business process models? In: Oberweis A, Hesse W (eds) Proceedings of the third AIS SIGSAND European symposium on analysis, design, use and societal impact of information systems (SIGSAND Europe 2008), Lecture notes in informatics, MarburgGoogle Scholar
  27. Mendling J, van der Aalst WMP (2007) Formalization and verification of EPCs with OR-joins based on state and context. In: Krogstie J, Opdahl AL, Sindre G (eds) Proceedings of the 19th conference on advanced information systems engineering (CAiSE 2007). Lecture notes in computer science, vol 4495. Springer, Trondheim, pp 439–453Google Scholar
  28. Mendling J, Neumann G, van der Aalst WMP (2007a) Understanding the occurrence of errors in process models based on metrics. In: Meersman R, Tari Z (eds) OTM conference 2007. Proceedings, Lecture notes in computer science, part I, vol 4803. Springer, Heidelberg, pp 113–130Google Scholar
  29. Mendling J, Reijers HA, Cardoso J (2007b) What makes process models understandable? In: Alonso G, Dadam P, Rosemann M (eds) Business process management. 5th international conference, BPM 2007, Brisbane, 24–28 September 2007. Proceedings, Lecture notes in computer science, vol 4714. Springer, Berlin, pp 48–63Google Scholar
  30. Mendling J, Lassen KB, Zdun U (2008a) Transformation strategies between block-oriented and graph-oriented process modelling languages. Int J Bus Process Integr Manag 3(2):297–312CrossRefGoogle Scholar
  31. Mendling J, Reijers HA, van der Aalst WMP (2008b) Seven process modeling guidelines (7PMG). Queensland University of Technology, Brisbane, Qut eprintGoogle Scholar
  32. Mendling J, Verbeek HMW, van Dongen BF, van der Aalst WMP, Neumann G (2008c) Detection and prediction of errors in EPCs of the SAP reference model. Data Knowl Eng 64(1):312–329CrossRefGoogle Scholar
  33. Moody DL (2003) Measuring the quality of data models: an empirical evaluation of the use of quality metrics in practice. In: Proceedings of the 11th European conference on information systems, ECIS 2003, Naples, 16–21 June 2003Google Scholar
  34. Moody DL (2005) Theoretical and practical issues in evaluating the quality of conceptual models: current state and future directions. Data Knowl Eng 55(3):243–276CrossRefGoogle Scholar
  35. Nuseibeh B, Easterbrook SM (2000) Requirements engineering: a roadmap. In: Proceedings of the conference on software engineering on the future of software engineering, ACM, New York, pp 35–46Google Scholar
  36. Ouyang C, Dumas M, Breutel S, ter Hofstede AHM (2006) Translating standard process models to bpel. In: Dubois E, Pohl K (eds) Advanced information systems engineering. 18th international conference, CAiSE 2006, Luxembourg, 5–9 June 2006. Proceedings, Lecture notes in computer science, vol 4001. Springer, Heidelberg, pp 417–432Google Scholar
  37. Paivio A (1991) Dual coding theory: retrospect and current status. Can J Psychol 45(3):255–287CrossRefGoogle Scholar
  38. Philippi S, Hill HJ (2007) Communication support for systems engineering – process modelling and animation with April. J Syst Softw 80(8):1305–1316CrossRefGoogle Scholar
  39. Puhlmann F, Weske M (2006) Investigations on soundness regarding lazy activities. In: Dustdar S, Fiadeiro JL, Sheth A (eds) Business process management, 4th international conference, BPM 2006, Lecture notes in computer science, vol 4102. Springer, Heidelberg, pp 145–160Google Scholar
  40. Recker J, Dreiling A (2007) Does it matter which process modelling language we teach or use? An experimental study on understanding process modelling languages without formal education. In: Toleman M, Cater-Steel A, Roberts D (eds) 18th Australasian conference on information systems. The University of Southern Queensland, Toowoomba, pp 356–366Google Scholar
  41. Reijers HA (2003) Design and control of workflow processes: business process management for the service industry. Springer, BerlinCrossRefGoogle Scholar
  42. Reijers HA, van der Aalst WMP (2005) The effectiveness of workflow management systems: predictions and lessons learned. Int J Inf Manag 25(5):458–472CrossRefGoogle Scholar
  43. Rosemann M (2006a) Potential pitfalls of process modeling: part A. Bus Process Manag J 12(2):249–254CrossRefGoogle Scholar
  44. Rosemann M (2006b) Potential pitfalls of process modeling: part B. Bus Process Manag J 12(3):377–384CrossRefGoogle Scholar
  45. Scheer A-W (2000) ARIS business process modelling. Springer, BerlinCrossRefGoogle Scholar
  46. Sharp A, McDermott P (2001) Workflow modeling: tools for process improvement and application development. Artech House Publishers, NorwoodGoogle Scholar
  47. ter Hofstede AHM, Benatallah B, Paik H-Y (eds) (2008) Trade-offs in the performance of workflows–quantifying the impact of best practices, vol 4928, Lecture notes in computer science. Springer, BerlinGoogle Scholar
  48. van der Aalst WMP (1997) Verification of workflow nets. In: Azéma P, Balbo G (eds) Application and theory of petri nets 1997, vol 1248, Lecture notes in computer science. Springer, Heidelberg, pp 407–426CrossRefGoogle Scholar
  49. van der Aalst WMP, Lassen KB (2008) Translating unstructured workflow processes to readable BPEL: theory and implementation. Inform Softw Tech 50(3):131–159CrossRefGoogle Scholar
  50. van der Aalst WMP, van Dongen BF, Herbst J, Maruster L, Schimm G, Weijters AJMM (2003) Workflow mining: a survey of issues and approaches. Data Knowl Eng 47(2):237–267CrossRefGoogle Scholar
  51. van der Aalst WMP, Reijers HA, Weijters AJMM, van Dongen BF, Alves de Medeiros AK, Song M, Verbeek HMW (2007) Business process mining: an industrial application. Inf Syst 32(5):713–732CrossRefGoogle Scholar
  52. van Dongen BF, Vullers-Jansen MH, Verbeek HMW, van der Aalst WMP (2007) Verification of the sap reference models using epc reduction, state-space analysis, and invariants. Comput Ind 58(6):578–601CrossRefGoogle Scholar
  53. van Hee K, Sidorova N, Somers L, Voorhoeve M (2006) Consistency in model integration. Data Knowl Eng 56:4–22CrossRefGoogle Scholar
  54. van der Aalst WMP (2014) Business process simulation survival guide. In: vom Brocke J, Rosemann M (eds) Handbook on business process management, vol 1, 2nd edn. Springer, Heidelberg, pp 337–370Google Scholar
  55. Vanhatalo J, Völzer H, Leymann F (2007) Faster and more focused control-flow analysis for business process models through SESE decomposition. In: Krämer BJ, Lin K-J, Narasimhan P (eds) Service-oriented computing – ICSOC 2007. Fifth international conference, Vienna, 17–20 September 2007. Proceedings, Lecture notes in computer science, vol 4749. Springer, Berlin, pp 43–55Google Scholar
  56. Verbeek HMW, Basten T, van der Aalst WMP (2001) Diagnosing workflow processes using Woflan. Comput J 44(4):246–279CrossRefGoogle Scholar
  57. Weber B, Rinderle S, Reichert M (2007) Change patterns and change support features in process- aware information systems. In: Krogstie J, Opdahl AL, Sindre G (eds) Advanced information systems engineering. 19th international conference, CAiSE 2007, Trondheim, 11–15 June 2007. Proceedings, Lecture notes in computer science, vol 4495. Springer, Heidelberg, pp 574–588Google Scholar
  58. Wynn MT, Verbeek HMW, van der Aalst WMP, ter Hofstede AHM, Edmond D (2006) Reduction rules for yawl workflow nets with cancellation regions and or-joins. BPMCenter Report BPM- 06-24, BPMcenter.orgGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Eindhoven University of TechnologyEindhovenThe Netherlands
  2. 2.Wirtschaftsuniversität Wien Institute for Information BusinessViennaAustria
  3. 3.Information Systems SchoolQueensland University of TechnologyBrisbaneAustralia

Personalised recommendations