Understanding User Uncertainty during the Implementation of Self-Service Business Intelligence: A Thematic Analysis

Abstract

Owing to Self-Service Business Intelligence (SSBI) systems’ transformative power for organizations, substantial user uncertainties often blight their potential. Although these uncertainties pose a significant threat to effective SSBI implementation, their sources and determinants remain unclear. We conducted semi-structured interviews with 15 current users of a recently implemented SSBI system to empirically explore the relevant factors of user uncertainty. We undertook a rigorous thematic analysis of the collected data, thereafter developing a thematic map to visualize user uncertainties. This map uncovered three unexplored important factors (work routine change, social dynamics and fear of AI) for future research. Our findings show that users are not only perturbed by “hard” factors (e.g. a lack of technical understanding), but also by “soft” factors (social dynamics, fear of AI and nontransparency). Practitioners can use the thematic map to identify and observe potential uncertainties and to develop adequate procedures.