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A Process Deviation Analysis – A Case Study

  • Conference paper
Business Process Management Workshops (BPM 2011)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 99))

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Abstract

Processes are not always executed as expected. Deviations assure the necessary flexibility within a company, but also increase possible internal control weaknesses. Since the number of cases following such a deviation can grow very large, it becomes difficult to analyze them case-by-case. This paper proposes a semi-automatic process deviation analysis method which combines process mining with association rule mining to simplify the analysis of deviating cases. Association rule mining is used to group deviating cases into business rules according to similar attribute values. Consequently, only the resulting business rules need to be examined on their acceptability which makes the analysis less complicated. Therefore, this method can be used to support the search for internal control weaknesses.

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Author information

Authors and Affiliations

  1. Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium

    Jo Swinnen, Benoît Depaire, Mieke J. Jans & Koen Vanhoof

Authors
  1. Jo Swinnen
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  2. Benoît Depaire
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  3. Mieke J. Jans
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  4. Koen Vanhoof
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Editor information

Editors and Affiliations

  1. University of Trento, Povo, Italy

    Florian Daniel

  2. CNAM-CEDRIC, Paris, France

    Kamel Barkaoui

  3. Vienna University of Technology, Vienna, Austria

    Schahram Dustdar

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© 2012 Springer-Verlag Berlin Heidelberg

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Swinnen, J., Depaire, B., Jans, M.J., Vanhoof, K. (2012). A Process Deviation Analysis – A Case Study. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds) Business Process Management Workshops. BPM 2011. Lecture Notes in Business Information Processing, vol 99. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28108-2_8

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  • DOI: https://doi.org/10.1007/978-3-642-28108-2_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28107-5

  • Online ISBN: 978-3-642-28108-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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