Barriers to Service Innovation Using Data Science

Abstract

The benefits of adopting data science are increasingly clear in a variety of industries, yet adoption rates remain low. In this paper we examine the barriers faced by organizations in adopting data science approaches in the context of service innovation. We first characterize three types of barriers: legal framework, organizational challenges, and risks. The legal framework around data science is in a state of change, and certain aspects are outdated and fragmented. Organizational issues include recruitment and a lack of diversity. Finally, risk is inherent in any business, but data science investments may be especially uncertain due to the fundamental role that datasets play and the lack of familiarity that those making decisions may have with data science. We present results in which we identify and expand on the links between these barriers and service innovation using data science.