A Stage Model for Uncovering Inertia in Big Data Analytics Adoption

Abstract

Big data and analytics have been credited with being a revolution that will radically transform the way firms do business. Nevertheless, the process of adopting and diffusing big data analytics, as well as actions taken in response to generated insight, require organizational transformation. Yet, as with any form of organizational transformation, there are multiple inhibiting factors that threaten successful change. The purpose of this study is to examine the inertial forces that can hamper the value of big data analytics throughout this process. We draw on a multiple case study approach of 27 firms to examine this question. Building on a stage model of adoption, our findings suggest that inertia is present in different forms, including economic, political, socio-cognitive, negative psychology, and socio- technical. The ways in which firms attempt to mitigate these forces of inertia is elaborated on, and best practices are presented. We conclude the paper by discussing the implications that these findings have for both research and practice.