Embedding data science innovations in organizations: a new workflow approach

This study could contribute to the community of data science in the following aspects: (a) introducing a new data workflow method (DWM) to address the limitations of current process workflows, enhancing both social and individual capital that is necessary for successful embedding; (b) more practically, with the support of interview findings, this study points to a whole-of-organization pathway to foster data science capability for the digital future in industrial operations; and (c) presenting an in-depth analysis to enhance the understanding of the DWM and its application in operational contexts. This insight showcases how data science could be adopted not only as technical solutions for a single project, but also to improve organization data strategy, and in turn overall business operations.