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.

Self-Service Business Intelligence success factors that create value for business

“…One important factor which affects the SSBI environment is the staff training. Weiler et al (2019) argue that there are no standardized training programs for SSBI. This is also supported by the experts, which is presented in the empirical findings.…”

“…Flexibility Difficult to scale Software architecture Data governance and integration. (Imhoff & White, 2011) Saves resources (Lennerholt , et al, 2018) User uncertainty (Weiler , et al, 2019) Facilitates the access data Access of source data to business users (Alpar & Schulz, 2016) Improves decision making, agility and Business users lack the needed skills when efficiency (Schlesinger & Rahman, 2015; using SSBI tools. (Johannessen & Fuglseth, Lizotte-Latendresse & Beauregard, 2018;) Alpar & Schulz, 2016 Less dependency on the IT department Implementation challenges (Lennerholt , et al, (Alpar & Schulz, 2016) 2018)…”

“…Supports BI/big data analytics (Passlick, et Lack in training (Weiler , et al, 2019(Weiler , et al, ) al., 2017…”

The Triadic Relationship of Sense-Making, Analytics, and Institutional Influences

“…Eckerson [17] argues that implementing SSBA is more complex than it looks. Research by Weiler et al [21] has shown that user uncertainty also has a negative impact on the introduction of SSBA. The reasons for uncertainty can be due to 'hard factors' (e.g., a lack of technical skills and capabilities) and by 'soft factors' (social dynamics, fear of AI and non-transparency).…”

Patterns of Resource Integration in the Self-service Approach to Business Analytics

“…For example, authors have attempted to describe SSBA architecture to promote more understanding of what SSBA is from a technical perspective [6]. Others have explored the factors influencing SSBA acceptance [7], user uncertainty during engagement [8] and the gap it creates between a user and an IT department [9]. When it comes to the benefit of SSBA, empirical evidence suggests that SSBA enables organizational agility [5] and employees communication and collaboration [10].…”