Understanding business process models: the costs and benefits of structuredness

Marlon Dumas, Marcello La Rosa, Jan Mendling, Raul Mäesalu, Hajo A. Reijers, Nataliia Semenenko

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    41 Citations (Scopus)


    Previous research has put forward various metrics of business process models that are correlated with understandability. Two such metrics are size and degree of (block-)structuredness. What has not been sufficiently appreciated at this point is that these desirable properties may be at odds with one another. This paper presents the results of a two-pronged study aimed at exploring the trade-off between size and structuredness of process models. The first prong of the study is a comparative analysis of the complexity of a set of unstructured process models from industrial practice and of their corresponding structured versions. The second prong is an experiment wherein a cohort of students was exposed to semantically equivalent unstructured and structured process models. The key finding is that structuredness is not an absolute desideratum vis-a-vis for process model understandability. Instead, subtle trade-offs between structuredness and other model properties are at play.

    Original languageEnglish
    Title of host publicationAdvanced Information Systems Engineering - 24th International Conference, CAiSE 2012, Proceedings
    EditorsJ. Ralyté , X. Franch, S. Brinkkemper, S. Wrycza
    Place of PublicationHeidelberg
    Number of pages16
    ISBN (Electronic)978-3-642-31095-9
    ISBN (Print)978-3-642-31094-2
    Publication statusPublished - 29 Oct 2012
    Event24th International Conference on Advanced Information Systems Engineering, CAiSE 2012 - Gdansk, Poland
    Duration: 25 Jun 201229 Jun 2012

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume7328 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference24th International Conference on Advanced Information Systems Engineering, CAiSE 2012


    • process model complexity
    • process model understandability
    • structured process model


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