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Process Performance Measurement

In: Handbook on Business Process Management 2

Author

Listed:
  • Michael Leyer

    (Frankfurt School of Finance & Management)

  • Diana Heckl

    (McKinsey & Company, Inc.)

  • Jürgen Moormann

    (Frankfurt School of Finance & Management)

Abstract

Measuring performance is a precondition for analyzing and subsequently improving business processes. However, selecting the “right” criteria for measurements remains a difficult and highly debated topic, both in theory and practice. The objective of this chapter is to provide an overview how adequate measures can be identified and implemented. For this purpose, the main terms will be defined and the procedure of process measurement will be presented. This includes a number of approaches for measuring process performance. In more detail, two methodologies, Data Envelopment Analysis and Process Mining, to measure and calculate indicators for process performance are discussed. As an example, Process Mining is applied to real case data to demonstrate its possibilities.

Suggested Citation

  • Michael Leyer & Diana Heckl & Jürgen Moormann, 2015. "Process Performance Measurement," International Handbooks on Information Systems, in: Jan vom Brocke & Michael Rosemann (ed.), Handbook on Business Process Management 2, edition 2, pages 227-241, Springer.
    • Handle: RePEc:spr:ihichp:978-3-642-45103-4_9
    DOI: 10.1007/978-3-642-45103-4_9
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    Citations

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    Cited by:

    1. Patrick Afflerbach & Martin Hohendorf & Jonas Manderscheid, 2017. "Design it like Darwin - A value-based application of evolutionary algorithms for proper and unambiguous business process redesign," Information Systems Frontiers, Springer, vol. 19(5), pages 1101-1121, October.
    2. Martin Lehnert & Maximilian Röglinger & Johannes Seyfried, 2018. "Prioritization of Interconnected Processes," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 60(2), pages 95-114, April.
    3. Ismail Mohamed Ali & Yusmadi Yah Jusoh & Rusli Abdullah & Rozi Nor Haizan Nor, 2017. "A Conceptual Framework For Measuring The Performance of Big Data Analytics Process," Acta Informatica Malaysia (AIM), Zibeline International Publishing, vol. 1(2), pages 13-14, November.
    4. Patrick Afflerbach & Martin Hohendorf & Jonas Manderscheid, 0. "Design it like Darwin - A value-based application of evolutionary algorithms for proper and unambiguous business process redesign," Information Systems Frontiers, Springer, vol. 0, pages 1-21.

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