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Automating the Discovery of AS-IS Business Process Models: Probabilistic and Algorithmic Approaches

Author

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  • Anindya Datta

    (DuPree College of Management, Georgia Institute of Technology, 755 Ferst Drive, Atlanta, Georgia 30332-0520)

Abstract

In the current corporate environment, business organizations have to reengineer their processes to ensure that process performance efficiencies are increased. This goal has lead to a recent surge of work on Business Process Reengineering (BPR) and Workflow Management . While a number of excellent papers have appeared on these topics, all of this work assumes that existing (AS-IS) processes are known. However, as is also widely acknowledged, coming up with AS-IS process models is a nontrivial task, that is currently practiced in a very ad-hoc fashion. With this motivation, in this paper, we postulate a number of algorithms to discover, i.e., come up with models of, AS-IS business processes. Such methods have been implemented as tools which can automatically extract AS-IS process models. To the best of our knowledge, no such work exists in the BPR and workflow domain. We back up our theoretical work with a case study that illustrates the applicability of these methods to large real-world problems. We draw on previous work on process modeling and grammar discovery. This work is a requisite first step in any reengineering endeavor. Our methods, if adopted, have the potential to severely reduce organizational costs of process redesign.

Suggested Citation

  • Anindya Datta, 1998. "Automating the Discovery of AS-IS Business Process Models: Probabilistic and Algorithmic Approaches," Information Systems Research, INFORMS, vol. 9(3), pages 275-301, September.
    • Handle: RePEc:inm:orisre:v:9:y:1998:i:3:p:275-301
    DOI: 10.1287/isre.9.3.275
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    Cited by:

    1. Jans, Mieke & Hosseinpour, Marzie, 2019. "How active learning and process mining can act as Continuous Auditing catalyst," International Journal of Accounting Information Systems, Elsevier, vol. 32(C), pages 44-58.
    2. Gert Janssenswillen & Benoît Depaire, 2019. "Towards Confirmatory Process Discovery: Making Assertions About the Underlying System," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(6), pages 713-728, December.

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