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International Conference on Business Process Management

BPM 2017: Business Process Management pp 3–21Cite as

Temporal Network Representation of Event Logs for Improved Performance Modelling in Business Processes

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10445))

Abstract

Analysing performance of business processes is an important vehicle to improve their operation. Specifically, an accurate assessment of sojourn times and remaining times enables bottleneck analysis and resource planning. Recently, methods to create respective performance models from event logs have been proposed. These works are severely limited, though: They either consider control-flow and performance information separately, or rely on an ad-hoc selection of temporal relations between events. In this paper, we introduce the Temporal Network Representation (TNR) of a log, based on Allen’s interval algebra, as a complete temporal representation of a log, which enables simultaneous discovery of control-flow and performance information. We demonstrate the usefulness of the TNR for detecting (unrecorded) delays and for probabilistic mining of variants when modelling the performance of a process. In order to compare different models from the performance perspective, we develop a framework for measuring performance fitness. Under this framework, we provide guarantees that TNR-based process discovery dominates existing techniques in measuring performance characteristics of a process. To illustrate the practical value of the TNR, we evaluate the approach against three real-life datasets. Our experiments show that the TNR yields an improvement in performance fitness over state-of-the-art algorithms.

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Notes

  1. 1.

    https://hu.berlin/TNR-extended.

  2. 2.

    Data is available at http://seeserver.iem.technion.ac.il/databases/HomeHospital/.

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Authors and Affiliations

  1. Technion – Israel Institute of Technology, Haifa, Israel

    Arik Senderovich & Avigdor Gal

  2. Humboldt-Universität zu Berlin, Berlin, Germany

    Matthias Weidlich

Authors
  1. Arik Senderovich
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  2. Matthias Weidlich
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  3. Avigdor Gal
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Corresponding author

Correspondence to Arik Senderovich .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Universitat Politècnica de Catalunya, Barcelona, Spain

    Josep Carmona

  2. Department of Computer Science, University of Paderborn, Paderborn, Germany

    Gregor Engels

  3. Department of Supply Chain and Information Systems, Pennsylvania State University, University Park, Pennsylvania, USA

    Akhil Kumar

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Senderovich, A., Weidlich, M., Gal, A. (2017). Temporal Network Representation of Event Logs for Improved Performance Modelling in Business Processes. In: Carmona, J., Engels, G., Kumar, A. (eds) Business Process Management. BPM 2017. Lecture Notes in Computer Science(), vol 10445. Springer, Cham. https://doi.org/10.1007/978-3-319-65000-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-65000-5_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64999-3

  • Online ISBN: 978-3-319-65000-5

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