IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v281y2020i3p642-655.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037722171831018X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2018.11.074?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    2. Andrew Burton-Jones & Olga Volkoff, 2017. "How Can We Develop Contextualized Theories of Effective Use? A Demonstration in the Context of Community-Care Electronic Health Records," Information Systems Research, INFORMS, vol. 28(3), pages 468-489, September.
    3. Pape, Tom, 2016. "Prioritising data items for business analytics: Framework and application to human resources," European Journal of Operational Research, Elsevier, vol. 252(2), pages 687-698.
    4. Voigt, Sebastian & Hinz, Oliver, 2016. "Making Digital Freemium Business Models a Success - Predicting Customers' Lifetime Value via Initial Purchase Information," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 84850, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Vidgen, Richard & Shaw, Sarah & Grant, David B., 2017. "Management challenges in creating value from business analytics," European Journal of Operational Research, Elsevier, vol. 261(2), pages 626-639.
    6. Raymond F. Zammuto & Terri L. Griffith & Ann Majchrzak & Deborah J. Dougherty & Samer Faraj, 2007. "Information Technology and the Changing Fabric of Organization," Organization Science, INFORMS, vol. 18(5), pages 749-762, October.
    7. Hindle, Giles A. & Vidgen, Richard, 2018. "Developing a business analytics methodology: A case study in the foodbank sector," European Journal of Operational Research, Elsevier, vol. 268(3), pages 836-851.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Burger, Katharina & White, Leroy & Yearworth, Mike, 2019. "Developing a smart operational research with hybrid practice theories," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1137-1150.
    2. Roman Lukyanenko & Andrea Wiggins & Holly K. Rosser, 0. "Citizen Science: An Information Quality Research Frontier," Information Systems Frontiers, Springer, vol. 0, pages 1-23.
    3. Zhan, Yuanzhu & Tan, Kim Hua, 2020. "An analytic infrastructure for harvesting big data to enhance supply chain performance," European Journal of Operational Research, Elsevier, vol. 281(3), pages 559-574.
    4. Kim, Jaemin & Dibrell, Clay & Kraft, Ellen & Marshall, David, 2021. "Data analytics and performance: The moderating role of intuition-based HR management in major league baseball," Journal of Business Research, Elsevier, vol. 122(C), pages 204-216.
    5. Conboy, Kieran & Mikalef, Patrick & Dennehy, Denis & Krogstie, John, 2020. "Using business analytics to enhance dynamic capabilities in operations research: A case analysis and research agenda," European Journal of Operational Research, Elsevier, vol. 281(3), pages 656-672.
    6. Jovana Karanović & Hans Berends & Yuval Engel, 2021. "Regulated Dependence: Platform Workers’ Responses to New Forms of Organizing," Journal of Management Studies, Wiley Blackwell, vol. 58(4), pages 1070-1106, June.
    7. Kayabay, Kerem & Gökalp, Mert Onuralp & Gökalp, Ebru & Erhan Eren, P. & Koçyiğit, Altan, 2022. "Data science roadmapping: An architectural framework for facilitating transformation towards a data-driven organization," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    8. Aydiner, Arafat Salih & Tatoglu, Ekrem & Bayraktar, Erkan & Zaim, Selim & Delen, Dursun, 2019. "Business analytics and firm performance: The mediating role of business process performance," Journal of Business Research, Elsevier, vol. 96(C), pages 228-237.
    9. Duan, Yanqing & Cao, Guangming & Edwards, John S., 2020. "Understanding the impact of business analytics on innovation," European Journal of Operational Research, Elsevier, vol. 281(3), pages 673-686.
    10. Osman, Ibrahim H. & Anouze, Abdel Latef & Irani, Zahir & Lee, Habin & Medeni, Tunç D. & Weerakkody, Vishanth, 2019. "A cognitive analytics management framework for the transformation of electronic government services from users’ perspective to create sustainable shared values," European Journal of Operational Research, Elsevier, vol. 278(2), pages 514-532.
    11. Balta, Maria & Valsecchi, Raffaella & Papadopoulos, Thanos & Bourne, Dorota Joanna, 2021. "Digitalization and co-creation of healthcare value: A case study in Occupational Health," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    12. Cécile Godé & Sébastien Brion & Amélie Bohas, 2020. "The Affordance-Actualization process in a Predictive Policing Context: insights from the French Military Police," Post-Print hal-02500125, HAL.
    13. Pace, Stefano & Buzzanca, Stefano & Fratocchi, Luciano, 2016. "The structure of conversations on social networks: Between dialogic and dialectic threads," International Journal of Information Management, Elsevier, vol. 36(6), pages 1144-1151.
    14. Mikalef, Patrick & Boura, Maria & Lekakos, George & Krogstie, John, 2019. "Big data analytics and firm performance: Findings from a mixed-method approach," Journal of Business Research, Elsevier, vol. 98(C), pages 261-276.
    15. Roman Lukyanenko & Andrea Wiggins & Holly K. Rosser, 2020. "Citizen Science: An Information Quality Research Frontier," Information Systems Frontiers, Springer, vol. 22(4), pages 961-983, August.
    16. Tabesh, Pooya & Mousavidin, Elham & Hasani, Sona, 2019. "Implementing big data strategies: A managerial perspective," Business Horizons, Elsevier, vol. 62(3), pages 347-358.
    17. Rahman, Shaikh Moksadur, 2020. "Relationship between Job Satisfaction and Turnover Intention: Evidence from Bangladesh," Asian Business Review, Asian Business Consortium, vol. 10(2), pages 99-108.
    18. Swen Nadkarni & Reinhard Prügl, 2021. "Digital transformation: a review, synthesis and opportunities for future research," Management Review Quarterly, Springer, vol. 71(2), pages 233-341, April.
    19. Naveena Prakasam & Louisa Huxtable-Thomas, 2021. "Reddit: Affordances as an Enabler for Shifting Loyalties," Information Systems Frontiers, Springer, vol. 23(3), pages 723-751, June.
    20. Valeriy Makarov & Albert Bakhtizin, 2014. "The Estimation Of The Regions’ Efficiency Of The Russian Federation Including The Intellectual Capital, The Characteristics Of Readiness For Innovation, Level Of Well-Being, And Quality Of Life," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 9-30.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:281:y:2020:i:3:p:642-655. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.