Abstract
Organizations are looking for ways to harness the power of big data and to incorporate the shift that big data brings into their competitive strategies in order to seek competitive advantage and to improve their decision making by becoming data-driven organizations. Despite the potential benefits to be gained from becoming data-driven, the number of organizations that efficiently use it and successfully transform into data-driven organizations stays low. The emphasis in the literature has mostly been technology oriented with limited attention paid to the organizational challenges it entails. This paper presents an empirical study that investigates the challenges and benefits faced by organizations when moving toward becoming a data-driven organization. Data were collected through semi-structured interviews with 15 practitioners from nine software developing companies. The study identifies 49 challenges an organization may face when implementing a data-driven organization in practice, and it identifies 23 potential benefits of a data-driven organization compared to a non-data-driven organization.
M. Taghavianfar—Independent Researcher.
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References
Anderson, C.: Creating a Data-Driven Organization. O’Reilly Media, Newton (2015)
Baskerville, R., Lee, A.S.: Distinctions among different types of generalizing in information systems research. In: Ngwenyama, O., Introna, L.D., Myers, M.D., DeGross, J.I. (eds.) New Information Technologies in Organizational Processes. ITIFIP, vol. 20, pp. 49–65. Springer, Boston, MA (1999). https://doi.org/10.1007/978-0-387-35566-5_5
Bean, R., Davenport, T.: Companies are failing in their efforts to become data-driven. Harvard Bus. Rev. (2019)
Berndtsson, M., Forsberg, D., Stein, D., Svahn, T.: Becoming a data-driven organisation. In: Proceedings of the 26th European Conference on Information Systems (2018)
Berndtsson, M., Lennerholt, C., Svahn, T., Larsson, P.: 13 organizations’ attempts to become data-driven. Int. J. Bus. Intell. Res. 11(1), 1–21 (2020)
Svensson, R.B., Feldt, R., Torkar, R.: The unfulfilled potential of data-driven decision making in agile software development. In: Kruchten, P., Fraser, S., Coallier, F. (eds.) XP 2019. LNBIP, vol. 355, pp. 69–85. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-19034-7_5
Boyd, D., Crawford, K.: Critical questions for big data: provocations for a cultural, technological, and scholarly phenomenon. Inf. Commun. Soc. 15, 662–679 (2012)
Braun, V., Clarke, V.: Using thematic analysis in psychology. Qual. Res. Psychol. 3(2), 77–101 (2006)
Bremser, C.: Starting points for big data adoption. In: Proceedings of the 26th European Conference on Information Systems (2018)
Constantiou, I., Kallinikos, J.: New games, new rules: big data and the changing context of strategy. J. Inf. Technol. 30(1), 44–57 (2015)
Davenport, T., Bean, R.: Big companies are embracing analytics, but most still don’t have a data-driven culture. Harvard Bus. Rev. (2018)
Halaweh, M., Massry, A.: Conceptual model for successful implementation of big data in organizations. J. Int. Technol. Inf. Manag. 24(2), 34 (2015)
Halper, F., Stodder, D.: What it takes to be data-driven. TDWI, vol. Q4 (2017)
Hannila, H., Silvola, R., Harkonen, J., Haapasalo, H.: Data-driven begins with data; potential of data assets. J. Comput. Inf. Syst. 1–10 (2019)
Jensen, M., Nielsen, P., Persson, J.: Managing big data analytics projects: the challenges of realizing value. In: Proceedings of the 27th European Conference on Information Systems (2019)
Kahneman, D.: Maps of bounded rationality: psychology for behavioral economics. Am. Econ. Rev. 93, 1449–1475 (2003)
Kart, L.: Big data industry insights. Technical report, Gartner (2015). http://public.brighttalk.com/resource/core/80421/september_29_industry_insights_lkart_118453.pdf
LaValle, S., Lesser, E., Shockley, R., Hopkins, M., Kruschwitz, N.: Big data, analytics, and the path from insights to value. MIT Sloan Manag. Rev. 52(2), 21–32 (2011)
McAfee, A., Brynjolfsson, E.: Big data: the management revolution. Harvard Bus. Rev. (2012)
Mikalef, P., Pappas, I.O., Krogstie, J., Giannakos, M.: Big data analytics capabilities: a systematic literature review and research agenda. Inf. Syst. e-Bus. Manag. 16(3), 547–578 (2017). https://doi.org/10.1007/s10257-017-0362-y
Partners, N.V.: Big data executive survey 2018 executive summary of findings. Technical report, NewVantage Partners (2018)
Patil, D.: Building Data Science Teams. O’Reilly Media, Newton (2011)
Patton, M.: Qualitative Research and Evaluation Methods. Sage Publications, New York (2002)
Robson, C.: Real World Research. Blackwell, Oxford (2002)
Sivarajah, U., Kamal, M., Irani, Z., Weerakkody, V.: Critical analysis of big data challenges and analytical methods. J. Bus. Res. 70(2), 263–286 (2017)
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Berntsson Svensson, R., Taghavianfar, M. (2020). Toward Becoming a Data-Driven Organization: Challenges and Benefits. In: Dalpiaz, F., Zdravkovic, J., Loucopoulos, P. (eds) Research Challenges in Information Science. RCIS 2020. Lecture Notes in Business Information Processing, vol 385. Springer, Cham. https://doi.org/10.1007/978-3-030-50316-1_1
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