DATA-DRIVEN DECISION-MAKING IN HIGHER EDUCATION GOVERNANCE

Abstract

This study investigated the role of Data-Driven Decision-Making (DDDM) in enhancing governance outcomes in public and private universities in South Eastern Nigeria. The focus was on institutional policy development, student success initiatives, and financial sustainability, while addressing privacy and implementation challenges. Guided by three research questions and three hypotheses, the study adopted a mixed-methods design involving 300 participants—comprising administrators, faculty, and IT staff—from 10 universities (5 public and 5 private) selected via stratified random sampling. A 30-item structured questionnaire and an interview guide with open-ended questions were used for data collection. Quantitative data were analyzed using descriptive statistics and independent samples t-tests, while qualitative data were analyzed thematically. Findings revealed that DDDM significantly improves institutional policy formulation by promoting transparency, responsiveness, and data-aligned strategies. It enhances student success through predictive analytics, curriculum adaptations, and intervention programs. Financial sustainability is also strengthened through data-informed budgeting, monitoring, and grant strategies. All three null hypotheses were rejected, showing statistically significant relationships between data analytics and each governance domain. Thematic analysis of interview data further validated these results and revealed implementation barriers such as infrastructure gaps, resistance to change, and data privacy concerns. The study concluded that effective DDDM integration can transform governance systems across Nigerian universities. It recommends investment in analytics infrastructure, training for stakeholders, and the establishment of data governance units. The study contributes to the theoretical understanding of DDDM by validating the Data-Driven Leadership Theory and the Technology Acceptance Model (TAM) within the Nigerian higher education context. These findings provide actionable insights for policy makers, administrators, and educators seeking to improve educational governance through data