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Visual ppinot: A Graphical Notation for Process Performance Indicators

Author

Listed:
  • Adela del-Río-Ortega

    (Universidad de Sevilla)

  • Manuel Resinas

    (Universidad de Sevilla)

  • Amador Durán

    (Universidad de Sevilla)

  • Beatriz Bernárdez

    (Universidad de Sevilla)

  • Antonio Ruiz-Cortés

    (Universidad de Sevilla)

  • Miguel Toro

    (Universidad de Sevilla)

Abstract

Process performance indicators (PPIs) allow the quantitative evaluation of business processes, providing essential information for decision making. It is common practice today that business processes and PPIs are usually modelled separately using graphical notations for the former and natural language for the latter. This approach makes PPI definitions simple to read and write, but it hinders maintenance consistency between business processes and PPIs. It also requires their manual translation into lower-level implementation languages for their operationalisation, which is a time-consuming, error-prone task because of the ambiguities inherent to natural language definitions. In this article, Visual ppinot, a graphical notation for defining PPIs together with business process models, is presented. Its underlying formal metamodel allows the automated processing of PPIs. Furthermore, it improves current state-of-the-art proposals in terms of expressiveness and in terms of providing an explicit visualisation of the link between PPIs and business processes, which avoids inconsistencies and promotes their co-evolution. The reference implementation, developed as a complete tool suite, has allowed its validation in a multiple-case study, in which five dimensions of Visual ppinot were studied: expressiveness, precision, automation, understandability, and traceability.

Suggested Citation

  • Adela del-Río-Ortega & Manuel Resinas & Amador Durán & Beatriz Bernárdez & Antonio Ruiz-Cortés & Miguel Toro, 2019. "Visual ppinot: A Graphical Notation for Process Performance Indicators," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(2), pages 137-161, April.
    • Handle: RePEc:spr:binfse:v:61:y:2019:i:2:d:10.1007_s12599-017-0483-3
    DOI: 10.1007/s12599-017-0483-3
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    References listed on IDEAS

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    1. August-Wilhelm Scheer & Wolfram Jost & Helge Heß & Andreas Kronz, 2006. "Corporate Performance Management," Springer Books, Springer, number 978-3-540-30787-7, December.
    2. Wil M. P. Aalst, 2015. "Extracting Event Data from Databases to Unleash Process Mining," Management for Professionals, in: Jan vom Brocke & Theresa Schmiedel (ed.), BPM - Driving Innovation in a Digital World, edition 127, pages 105-128, Springer.
    3. Andreas Kronz, 2006. "Managing of Process Key Performance Indicators as Part of the ARIS Methodology," Springer Books, in: Corporate Performance Management, pages 31-44, Springer.
    4. Stefan Jakoubi & Simon Tjoa & Sigrun Goluch & Gerhard Kitzler, 2010. "Risk-Aware Business Process Management—Establishing the Link Between Business and Security," Springer Optimization and Its Applications, in: Fatos Xhafa & Leonard Barolli & Petraq J. Papajorgji (ed.), Complex Intelligent Systems and Their Applications, chapter 0, pages 109-135, Springer.
    5. Arash Shahin & M. Ali Mahbod, 2007. "Prioritization of key performance indicators," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 56(3), pages 226-240, March.
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    Cited by:

    1. Amy Van Looy & Peter Trkman & Els Clarysse, 2022. "A Configuration Taxonomy of Business Process Orientation," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(2), pages 133-147, April.

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