<![CDATA[Digital transformation in education requires supervision systems capable of generating strategic information to support evidence-based decision-making. However, supervisory practices in many schools remain predominantly administrative, limiting the effective utilisation of supervisory data for continuous school quality improvement. This study aimed to develop the Data-Driven Supervision Dashboard Framework (DDSDF) as a conceptual data-based decision support system for enhancing school quality. The study employed a Research and Development (R&D) approach integrated with Design Science Research (DSR). The research stages consisted of problem identification, needs analysis, conceptual model development, expert-based conceptual validation, and theoretical evaluation. The findings indicate that the proposed DDSDF integrates academic supervision data, managerial supervision data, teacher performance, student learning outcomes, and school quality indicators into an interactive dashboard equipped with data analytics, information visualisation, improvement priority recommendations, and the Plan–Do–Check–Act (PDCA) cycle. The framework has the potential to improve decision-making effectiveness by providing objective, adaptive, transparent, and sustainable information for school management. This study contributes a novel conceptual framework that extends the function of supervision from an administrative activity to an organisational intelligence system supporting evidence-based and continuous school quality improvement.]]>
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