Data science and business value: Insight into the alignment process

Abstract

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 in the capacities of C-level executives, semi-structured interviews were conducted to unfold their data science journey. The study extends the understanding from the business - IT/IS alignment literature 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 learnings from the literature and practitioners. With the proposed data science alignment framework, our study offers to craft data science projects by guiding business executives in achieving business value.