People, data and decisions: Overcoming individual barriers to data-driven practice in South African universities

Abstract

Background: Data-driven decision-making (D3M) has become essential for enhancing efficiency, accountability and student success in higher education institutions (HEIs). Yet, South African universities continue to face challenges in adopting D3M, particularly because of individual-level barriers among staff who engage with data systems.
Objectives: This study investigates individual barriers to D3M adoption among decision-makers in South African HEIs and proposes strategies to build capacity for effective and sustainable implementation.
Method: A qualitative case study approach was employed, involving 24 semi-structured interviews conducted with senior managers, data specialists and academic staff at the University of the Western Cape. Thematic analysis was utilised to identify personal and contextual factors shaping D3M engagement.
Results: The study recommends targeted capacity-building interventions, including awareness campaigns, diagnostic skills assessments and multi-tiered training programmes that integrate confidence-building and peer mentoring. Institutions should implement gradual, age-sensitive rollouts and appoint D3M champions to promote adoption by demonstrating success.
Conclusion: By foregrounding individual-level dynamics, the study extends the unified theory of acceptance and use of technology 2 (UTAUT2) and self-efficacy theory to the South African higher education context. It contributes actionable strategies for cultivating data-literate, confident and digitally empowered academic communities that support institutional transformation.
Contribution: This research fills a gap in understanding personal-level barriers to D3M adoption in the under-researched South African higher education context. It contributes actionable insights for higher education leaders and policymakers.