Abstract
Becoming a data-driven organization is a vision for several organizations. It has been frequently mentioned in the literature that data-driven organizations are likely to be more successful than organizations that mostly make decisions on gut feeling. However, few organizations make a successful shift to become data-driven, due to a number of different types of barriers. This article investigates, the initial journey to become a data-driven organization for 13 organizations. Data has been collected via documents and interviews, and then analyzed with respect to: i) how they scaled up the usage of analytics to become data-driven; ii) strategies developed; iii) barriers encountered; and iv) usage of an overall change process. The findings are that most organizations start their journey via a pilot project, take shortcuts when developing strategies, encounter previously reported top barriers, and do not use an overall change management process.
Highlights
Managers have taken several steps to initiate transformations to a data-driven organization, by introducing mantras such as - business insights are based on data and not opinions - into strategy documents, held large kick-off events, educated employees in Self-Service Business Intelligence (SSBI) tools, and hired data scientists and AI-programmers
We interviewed in total of 15 respondents who have participated in the project of implementing and using SSBI in the organizations J and K
We investigated the initial journey that 13 organizations took, to scale up their usage of analytics to become a data-driven organization
Summary
Several organizations have a vision to become data-driven (Davenport & Bean, 2018; Halper & Stodder, 2017; Watson, 2016), since those type of organizations are likely to capitalize on business insights more frequently than organizations that are not data-driven (LaValle, Lesser, Shockley, Hopkins, & Kruschwitz, 2011). Halper and Stodder (2017) classify an organization as data-driven “when it uses data and analysis to help drive action—even if that action is a deliberate inaction.” In theory, datadriven organizations can apply data-driven decisions for all types of analytics (descriptive, predictive, prescriptive), and all types of decisions (operational, tactical, strategical). Managers have taken several steps to initiate transformations to a data-driven organization, by introducing mantras such as - business insights are based on data and not opinions - into strategy documents, held large kick-off events, educated employees in Self-Service Business Intelligence (SSBI) tools, and hired data scientists and AI-programmers. Despite these good intentions, most of the organizations still struggle and few of them seem to reach their vision. As decisions in data-driven organizations can span all types of analytics (descriptive, predictive, prescriptive), data-driven organizations have a DSS that overlaps both knowledge management-based DSS, and business analytics
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