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A Model-Driven Engineering Approach to Complex Performance Indicators: Towards Self-Service Performance Management (SS-PM)

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Research Challenges in Information Science (RCIS 2021)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 415))

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Abstract

Every modern organization nowadays produces data and consumes information through Decision-Support Systems (DSS) which produce more and more Complex Performance Indicators (CPI). This allows business monitoring, decision-making support and tracking of decisions effects. With the increasing complexity, DSS suffer from two main limitations that inhibit their use. First, DSS tend to be opaque to Business Managers who cannot observe how the data is treated to produce indicators. Second, DSS are owned by the technicians, resulting in an IT-bottleneck and a business-exclusion. From a Business Management perspective, the consequences are damaging. DSS result in sunk costs of development, fail to receive full confidence from Business Managers and to fit dynamic business environments. In this research, preliminary insights are proposed to build a solution that tackles the previous limitations. The literature review, the research contributions and methodology are presented to conclude with the work plan of the PhD.

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Authors and Affiliations

  1. NaDI, Namur Digital Institute, PReCISE Research Center, Université de Namur, Namur, Belgium

    Benito Giunta

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  1. Benito Giunta
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Correspondence to Benito Giunta .

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Editors and Affiliations

  1. Conservatoire National des Arts et Métiers, Paris, France

    Samira Cherfi

  2. Fondazione Bruno Kessler, Trento, Italy

    Anna Perini

  3. University Paris 1 Panthéon-Sorbonne, Paris, France

    Selmin Nurcan

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Giunta, B. (2021). A Model-Driven Engineering Approach to Complex Performance Indicators: Towards Self-Service Performance Management (SS-PM). In: Cherfi, S., Perini, A., Nurcan, S. (eds) Research Challenges in Information Science. RCIS 2021. Lecture Notes in Business Information Processing, vol 415. Springer, Cham. https://doi.org/10.1007/978-3-030-75018-3_50

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  • DOI: https://doi.org/10.1007/978-3-030-75018-3_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-75017-6

  • Online ISBN: 978-3-030-75018-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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