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A Generic Framework for Context-Aware Process Performance Analysis

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On the Move to Meaningful Internet Systems: OTM 2016 Conferences (OTM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10033))

Abstract

Process mining combines model-based process analysis with data-driven analysis techniques. The role of process mining is to extract knowledge and gain insights from event logs. Most existing techniques focus on process discovery (the automated extraction of process models) and conformance checking (aligning observed and modeled behavior). Relatively little research has been performed on the analysis of business process performance. Cooperative business processes often exhibit a high degree of variability and depend on many factors. Finding root causes for inefficiencies such as delays and long waiting times in such flexible processes remains an interesting challenge. This paper introduces a novel approach to analyze key process performance indicators by considering the process context. A generic context-aware analysis framework is presented that analyzes performance characteristics from multiple perspectives. A statistical approach is then utilized to evaluate and find significant differences in the results. Insights obtained can be used for finding high-impact points for optimization, prediction, and monitoring. The practical relevance of the approach is shown in a case study using real-life data.

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Notes

  1. 1.

    \(\mathcal {P}(\mathcal {E})\) denotes the powerset over \(\mathcal {E}\), i.e. all possible subsets of \(\mathcal {E}\).

  2. 2.

    See http://promtools.org.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands

    Bart F. A. Hompes, Joos C. A. M. Buijs & Wil M. P. van der Aalst

  2. Philips Research, Eindhoven, The Netherlands

    Bart F. A. Hompes

Authors
  1. Bart F. A. Hompes
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  2. Joos C. A. M. Buijs
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  3. Wil M. P. van der Aalst
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Corresponding author

Correspondence to Bart F. A. Hompes .

Editor information

Editors and Affiliations

  1. ADAPT Centre, Trinity College Dublin, Dublin 2, Ireland

    Christophe Debruyne

  2. University of Lorraine, Vandoeuvre-les-Nancy, France

    Hervé Panetto

  3. TU Graz, Graz, Austria

    Robert Meersman

  4. La Trobe University, Melbourne, Australia

    Tharam Dillon

  5. Institute of Computer Languages, TU Wien, Vienna, Austria

    eva Kühn

  6. ADAPT Centre, Trinity College Dublin, Dublin 2, Ireland

    Declan O'Sullivan

  7. Università degli Studi di Milano Crema, Crema, Italy

    Claudio Agostino Ardagna

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Hompes, B.F.A., Buijs, J.C.A.M., van der Aalst, W.M.P. (2016). A Generic Framework for Context-Aware Process Performance Analysis. In: Debruyne, C., et al. On the Move to Meaningful Internet Systems: OTM 2016 Conferences. OTM 2016. Lecture Notes in Computer Science(), vol 10033. Springer, Cham. https://doi.org/10.1007/978-3-319-48472-3_17

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  • DOI: https://doi.org/10.1007/978-3-319-48472-3_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48471-6

  • Online ISBN: 978-3-319-48472-3

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