Data-Driven Decision-Making (DDDM) Systems Practices in Private Higher Education Institutions: A Systematic Literature Review - Bentayao, Gwen Jelly (International Journal of Research in Interdisciplinary Studies, 2025)
Data-driven decision-making (DDDM) systems are important in strategic planning and resource allocation in private higher education institutions (HEIs). Nonetheless, using data to improve education has challenges in finding the correct data and knowing how to use that data. The objectives of the systematic review were to explore (1) types of data-driven decision-making (DDDM) systems adopted by school administrators in strategic planning and resource allocation, (2) key elements of DDDM systems' successful implementation in the context of private higher education institutions (HEIs), and (3) whether DDDM systems improve quality and productivity in administrative decision-making. A systematic search for peer-reviewed articles on the topic published in 2019–2024 was made using Google Scholar, ERIC, and ScienceDirect databases. These include, but are not limited to, “data-driven decision-making tools,” “the impact of higher education data analytics,” “factors influencing assessment practices in private higher institutions,” “the impact of data mining in education,” and “quality and productivity in school management.” Of the 48 articles identified, 23 met inclusion criteria focused on DDDM in private HEIs. Data were extracted and thematically analyzed. The review revealed two main uses of DDDM tools: data-driven classroom instruction improvement tools to foster better student outcomes and data analytics to boost operational quality. Institutional culture, collaboration, resource access, and technological infrastructure were key success factors. Hence, the DDDM system seems a laudable tool for improving private HEI operations and student performance outcomes. However, successful implementation needs extensive institutional preparation, robust data governance frameworks, and multiple integrated DDDM tools. Future work should emphasize long-term impacts over time, comparative consideration of diverse contexts, and involvement of various stakeholders.