Data-Driven Organizations: Review, Conceptual Framework, and Empirical Illustration

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Abstract

With companies and other organizations increasingly striving to become (more) data-driven, there has been growing research interest in the notion of a data-driven organization (DDO). In existing literature, however, different understandings of such an organization emerged. The study at hand sets forth to synthesize the fragmented body of research through a review of existing DDO definitions and implicit understandings of this concept in the information systems and related literatures. Based on the review results and drawing on the established concept of the “knowing organization,” our study identifies five core dimensions of a DDO—namely, data sourcing & sensemaking, data capabilities, data-driven culture, data-driven decision-making, and data-driven value creation—which we integrate into a conceptual DDO framework. Most notably, the proposed framework suggests that—like its predecessor, the knowing organization—a DDO may draw on an outside-in view; however, it may also draw on an inside-out view, or even combine the two views, thereby setting itself apart from the knowing organization. To illustrate our conceptual DDO framework and demonstrate its usefulness, we apply this framework to three empirical examples. Theoretical and practical contributions as well as directions for future research are discussed.

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APA

Fischer, H., Wiener, M., Strahringer, S., Kotlarsky, J., & Bley, K. (2023). Data-Driven Organizations: Review, Conceptual Framework, and Empirical Illustration. Australasian Journal of Information Systems, 27, 1–26. https://doi.org/10.3127/AJIS.V27I0.4425

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