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Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing

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Business Process Management (BPM 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13420))

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Abstract

Existing process mining methods are primarily designed for processes that have reached a high degree of digitalization and standardization. In contrast, the literature has only begun to discuss how process mining can be applied to knowledge-intensive processes—such as product innovation processes—that involve creative activities, require organizational flexibility, depend on single actors’ decision autonomy, and target process-external goals such as customer satisfaction. Due to these differences, existing Process Mining methods cannot be applied out-of-the-box to analyze knowledge-intensive processes. In this paper, we employ Action Design Research (ADR) to design and evaluate a process mining approach for knowledge-intensive processes. More specifically, we draw on the two processes of product innovation and engineer-to-order in manufacturing contexts. We collected data from 27 interviews and conducted 49 workshops to evaluate our IT artifact at different stages in the ADR process. From a theoretical perspective, we contribute five design principles and a conceptual artifact that prescribe how process mining ought to be designed for knowledge-intensive processes in manufacturing. From a managerial perspective, we demonstrate how enacting these principles enables their application in practice.

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Acknowledgements

This research and development project is funded by the Ministry of Economic Affairs, Innovation, Digitalization, and Energy of the State of North Rhine-Westphalia (MWIDE) as part of the Leading-Edge Cluster, Intelligente Technische Systeme OstWestfalenLippe (it’s OWL) and supervised by the project administration in Jülich (PtJ). The responsibility for the content of this publication lies with the authors.

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Authors and Affiliations

  1. Faculty of Business Administration and Economics, Paderborn University, Warburger Street 100, 33098, Paderborn, Germany

    Bernd Löhr, Katharina Brennig, Christian Bartelheimer, Daniel Beverungen & Oliver Müller

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  1. Bernd Löhr
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  2. Katharina Brennig
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  3. Christian Bartelheimer
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  4. Daniel Beverungen
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  5. Oliver Müller
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Correspondence to Bernd Löhr .

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Editors and Affiliations

  1. Sapienza University of Rome, Rome, Italy

    Claudio Di Ciccio

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Remco Dijkman

  3. Universidad de Sevilla, Seville, Spain

    Adela del Río Ortega

  4. Technical University of Munich, Garching, Germany

    Stefanie Rinderle-Ma

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Löhr, B., Brennig, K., Bartelheimer, C., Beverungen, D., Müller, O. (2022). Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing. In: Di Ciccio, C., Dijkman, R., del Río Ortega, A., Rinderle-Ma, S. (eds) Business Process Management. BPM 2022. Lecture Notes in Computer Science, vol 13420. Springer, Cham. https://doi.org/10.1007/978-3-031-16103-2_18

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  • DOI: https://doi.org/10.1007/978-3-031-16103-2_18

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