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Applying business analytics for performance measurement and management. The case study of a software company

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  • Franco Visani

Abstract

The concept of Business Performance Analytics (BPA) represents the adoption of analytical methods to support strategy control and (re)formulation. The purpose of the paper is to explore the potential support that BPA can provide for performance management systems. The study, through an interventionist approach, empirically tests a 5-step BPA framework (Raffoni et al. - forthcoming -) and provides insights for further developments. The longitudinal study, conducted at a company operating in the data-security industry, supported the analysis of BPA potential and offered a number of insights to refine the framework and shed light on critical organisational issues. This paper offers both theoretical and practical suggestions. It is one of the few attempts to investigate the potential of Business Analytics in enhancing strategic control. It provides insights in a practical framework that could be used to guide further research in the area and provides an account of potential challenges faced by businesses when trying to move to strategic control with a data-driven approach.

Suggested Citation

  • Franco Visani, 2017. "Applying business analytics for performance measurement and management. The case study of a software company," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2017(2), pages 89-123.
    • Handle: RePEc:fan:macoma:v:html10.3280/maco2017-002006
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    Cited by:

    1. Pier Luigi Marchini & Alice Medioli & Laura Belli & Luca Davoli, 2019. "Internet of Things e Industria 4.0. Un case study di successo di digital manufacturing," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2019(3), pages 11-34.
    2. Marco Montemari & Christian Nielsen, 2021. "Big data for business modeling: Towards the next generation of performance measurement systems?," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2021(suppl. 1), pages 5-10.
    3. Dmitry Danilov & Jan R. Magnus, 2007. "Some equivalences in linear estimation (in Russian)," Quantile, Quantile, issue 3, pages 83-90, September.
    4. Francesco Badia & Fabio Donato, 2022. "Opportunities and risks in using big data to support management control systems: A multiple case study," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(3), pages 39-63.

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