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A Multi Perspective Framework for Enhanced Supply Chain Analytics

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Business Process Management (BPM 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12168))

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Abstract

Supply chain analytics, especially in the field of food supply has become a strategic business function. Monthly executive sales and operation planning meetings utilize supply chain analytics to inform strategic business decisions. Having identified gaps in the strategic management of food supply chains, a multi perspective supply chain analytics framework is developed incorporating process and data attributes to support decision making. Using Design Science as the research methodology, a novel framework with a supporting IT artefact is built and presented with early evaluation results.

The resulting multi perspective supply chain analytics framework equips practitioners to identify strategic issues, providing important decision support information. The case study further illustrates the framework has applicability across all integrated food supply chains. This research has highlighted gaps in the application of process science to the supply chain management domain, particularly in the area of simultaneous assessment of process and data. The outcomes contribute to research in this domain providing a framework that will enhance the significant reference modelling and operational management work that has occurred in this field.

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Notes

  1. 1.

    https://www.apics.org/apics-for-business/frameworks/scor.

  2. 2.

    We use the pseudo-name ‘Case A’, in line with the anonymity and research ethics agreements.

  3. 3.

    See https://www.mla.com.au for further details.

  4. 4.

    http://www.processmining.org/tools.

  5. 5.

    https://powerbi.microsoft.com.

  6. 6.

    Interview note from C Suite Executive large cattle business.

  7. 7.

    Radio Frequency Identification.

  8. 8.

    Interview with Sander Leemans, developer of the IVM and DFVM algorithms.

  9. 9.

    http://www.bom.gov.au/qld.

  10. 10.

    https://camunda.com.

  11. 11.

    https://rapidminer.com.

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Authors and Affiliations

  1. School of Information Systems, Queensland University of Technology, Brisbane, Australia

    Owen Keates, Moe Thandar Wynn & Wasana Bandara

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  1. Owen Keates
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  2. Moe Thandar Wynn
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  3. Wasana Bandara
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Corresponding author

Correspondence to Owen Keates .

Editor information

Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Dirk Fahland

  2. FBK-irst, Trento, Italy

    Chiara Ghidini

  3. University of Münster, Münster, Germany

    Jörg Becker

  4. University of Tartu, Tartu, Estonia

    Marlon Dumas

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Keates, O., Wynn, M.T., Bandara, W. (2020). A Multi Perspective Framework for Enhanced Supply Chain Analytics. In: Fahland, D., Ghidini, C., Becker, J., Dumas, M. (eds) Business Process Management. BPM 2020. Lecture Notes in Computer Science(), vol 12168. Springer, Cham. https://doi.org/10.1007/978-3-030-58666-9_28

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  • DOI: https://doi.org/10.1007/978-3-030-58666-9_28

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