Data science and business value: Insight into the alignment process

We develop a comprehensive business–data-science alignment model for deriving business value from data-science initiatives, thus assisting business organizations in transforming digitally. With a purposive sample of 13 data science leaders employed as C-level executives, we conducted semistructured interviews to unfold their data-science journeys. Our study extends the findings from recent literature on the alignment between business and information technology to data-science initiatives. The alignment dimensions and their components are extracted through the interview transcripts using a general inductive approach. We propose a business–data-science alignment model as a dynamic and iterative process in which the data-science initiatives are shaped while aligning with intellectual, operational, social, cultural, and societal dimensions to derive business value. The five most relevant components represent each of these alignment dimensions. The study emphasizes the groundwork to be done before investing in data-science endeavors by capturing the findings from the literature and the wisdom of practitioners. With the proposed data-science alignment framework, our study offers ways to shape data-science projects by guiding business executives in achieving business value.