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Actualizing business analytics for organizational transformation: A case study of Rovio Entertainment

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  • Tim, Yenni
  • Hallikainen, Petri
  • Pan, Shan L
  • Tamm, Toomas

Abstract

Increased access to data and affordable technologies today has made business analytics within the reach of most organizations. However, many organizations are unsure of how to translate their analytics use into organizational value. While the area of business analytics value creation has become a popular point of discussion amongst practitioners, much research is needed to provide insights into the effective use of business analytics. The objective of this paper is to deepen understanding in the effective implementation of analytics within organizations. Specifically, we performed an in-depth case study at Rovio Entertainment to investigate how a pioneer in mobile games initiated an analytics-driven transformation. This study contributes to the theory and practice of business analytics in two ways. First, drawing on the perspective of technology affordances, this study sheds light on the varying affordances of business analytics. Second, this study presents empirically-informed insights on how these affordances could be effectively actualized for an analytics-driven transformation in an organization. Collectively, this study opens up the black-box of effective implementation of business analytics for organizational value creation.

Suggested Citation

  • Tim, Yenni & Hallikainen, Petri & Pan, Shan L & Tamm, Toomas, 2020. "Actualizing business analytics for organizational transformation: A case study of Rovio Entertainment," European Journal of Operational Research, Elsevier, vol. 281(3), pages 642-655.
    • Handle: RePEc:eee:ejores:v:281:y:2020:i:3:p:642-655
    DOI: 10.1016/j.ejor.2018.11.074
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    References listed on IDEAS

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    Cited by:

    1. Steffen Kurpiela & Frank Teuteberg, 2024. "Linking business analytics affordances to corporate strategic planning and decision making outcomes," Information Systems and e-Business Management, Springer, vol. 22(1), pages 33-60, March.
    2. Kusi-Sarpong, Simonov & Orji, Ifeyinwa Juliet & Gupta, Himanshu & Kunc, Martin, 2021. "Risks associated with the implementation of big data analytics in sustainable supply chains," Omega, Elsevier, vol. 105(C).

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