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Modularity in Process Models: Review and Effects

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Business Process Management (BPM 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5240))

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Abstract

The use of subprocesses in large process models is an important step in modeling practice to handle complexity. While there are several advantages attributed to such a modular design, including ease of reuse, scalability, and enhanced understanding, the lack of precise guidelines turns out to be a major impediment for applying modularity in a systematic way. In this paper we approach this area of research from a critical perspective. Our first contribution is a review of existing approaches to process model modularity. This review shows that aside from some limited insights, a systematic and grounded approach to finding the optimal modularization of a process model is missing. Therefore, we turned to modular process models from practice to study their merits. In particular, we set up an experiment involving professional process modelers and tested the effect of modularization on understanding. Our second contribution, stemming from this experiment, is that modularity appears to pay off. We discuss some of the limitations of our research and implications for future design-oriented approaches.

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Author information

Authors and Affiliations

  1. Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven, The Netherlands

    Hajo Reijers

  2. Queensland University of Technology, Level 5, 126 Margaret Street, Brisbane, QLD 4000, Australia

    Jan Mendling

Authors
  1. Hajo Reijers
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  2. Jan Mendling
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Editor information

Editors and Affiliations

  1. University of Tartu, J Liivi 2, 50409, Tartu, Estonia

    Marlon Dumas

  2. Department of Computer Science, Information Systems Group, University of Twente, P.O. Box 217, 7500 AE, Enschede, The Netherlands

    Manfred Reichert

  3. SAP Labs, LLC 3475 Deer Creek Road, CA 94304, Palo Alto, USA

    Ming-Chien Shan

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Reijers, H., Mendling, J. (2008). Modularity in Process Models: Review and Effects. In: Dumas, M., Reichert, M., Shan, MC. (eds) Business Process Management. BPM 2008. Lecture Notes in Computer Science, vol 5240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85758-7_5

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  • DOI: https://doi.org/10.1007/978-3-540-85758-7_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85757-0

  • Online ISBN: 978-3-540-85758-7

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