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On the Discovery of Preferred Work Practice Through Business Process Variants

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4801))

Abstract

Variance in business process execution can be the result of several situations, such as disconnection between documented models and business operations, workarounds in spite of process execution engines, dynamic change and exception handling, flexible and ad-hoc approaches, and collaborative and/or knowledge intensive work. It is imperative that effective support for managing process variance be extended to organizations mature in their BPM (Business Process Management) uptake so that they can ensure organization wide consistency, promote reuse and capitalize on their BPM investments. Process variants are complex objects that contain features of different dimensions, such as variant design or variant execution data. This paper provides a technique for effective utilization of the adaptations manifested in process variants. In particular, we will present a facility for discovery of preferred variants through effective search and retrieval based on the notion of process similarity, where multiple aspects of the process variants are compared according to specific query requirements. The major advantage of this approach is the ability to provide a quantitative measure for the similarity between process variants, which further facilitates various BPM activities such as process reuse, analysis and discovery.

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Christine Parent Klaus-Dieter Schewe Veda C. Storey Bernhard Thalheim

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© 2007 Springer-Verlag Berlin Heidelberg

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Lu, R., Sadiq, S. (2007). On the Discovery of Preferred Work Practice Through Business Process Variants. In: Parent, C., Schewe, KD., Storey, V.C., Thalheim, B. (eds) Conceptual Modeling - ER 2007. ER 2007. Lecture Notes in Computer Science, vol 4801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75563-0_13

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  • DOI: https://doi.org/10.1007/978-3-540-75563-0_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75562-3

  • Online ISBN: 978-3-540-75563-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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