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Correcting analytics maturity myopia

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  • Ali, Abdul
  • Mancha, Ruben
  • Pachamanova, Dessislava

Abstract

Companies face increasing pressure to compete in the practice of analytics and strive for analytics maturity to sustain their competitive advantage. A single-minded, narrow focus on gaining analytics maturity, however, leads to analytics maturity myopia. Based on our studies of analytical capabilities and numerous conversations with executives and managers, we offer a scorecard for organizations to identify the presence of analytics maturity myopia and propose a framework for organizations to correct this issue. The proposed framework partially explains the mixed and conflicting results regarding the relationship between analytics maturity and business value found in the literature. Specifically, we recommend that companies focus on three factors that are critical to realizing value from analytics initiatives: (1) a balanced view of value to different stakeholders, (2) a continuous expansion of the business ecosystem beyond current stakeholders to identify and pursue new opportunities, and (3) use of an emergent strategy to take advantage of unexpected opportunities and develop organizational agility.

Suggested Citation

  • Ali, Abdul & Mancha, Ruben & Pachamanova, Dessislava, 2018. "Correcting analytics maturity myopia," Business Horizons, Elsevier, vol. 61(2), pages 211-219.
    • Handle: RePEc:eee:bushor:v:61:y:2018:i:2:p:211-219
    DOI: 10.1016/j.bushor.2017.11.003
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    References listed on IDEAS

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    Cited by:

    1. Dessislava Pachamanova & Vera Tilson & Keely Dwyer-Matzky, 2022. "Case Article—Machine Learning, Ethics, and Change Management: A Data-Driven Approach to Improving Hospital Observation Unit Operations," INFORMS Transactions on Education, INFORMS, vol. 22(3), pages 178-187, May.
    2. Matthew D. Vollrath & Salvador G. Villegas, 2022. "Avoiding digital marketing analytics myopia: revisiting the customer decision journey as a strategic marketing framework," Journal of Marketing Analytics, Palgrave Macmillan, vol. 10(2), pages 106-113, June.
    3. David Kopcso & Dessislava Pachamanova, 2018. "Case Article—Business Value in Integrating Predictive and Prescriptive Analytics Models," INFORMS Transactions on Education, INFORMS, vol. 19(1), pages 36-42, September.
    4. David Kopcso & Dessislava Pachamanova, 2018. "Case Article—Managing Staffing Inefficiencies Using Analytics (B): Business Value in Predictive and Prescriptive Analytics Models," INFORMS Transactions on Education, INFORMS, vol. 19(1), pages 43-47, September.

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