The role of policies in economic, cultural, and political development is undeniable; thus, organizational policymakers strive to formulate proactive and impactful policies. Therefore, the purpose of this study is to propose a data governance-based policymaking model to enhance organizational performance in commercial banks. This study was conducted using a qualitative approach and thematic analysis. The statistical population comprised managers and experts holding a master's degree or higher, with a minimum of 15 years of work experience at Bank. The experts were selected from this population via snowball sampling until theoretical saturation was reached, yielding a final sample of 13 participants. Data extracted from semi-structured interviews with experts were analyzed using MAXQDA software. Through the process of open, axial, and selective coding, basic themes, organizing themes (components), and global themes (dimensions) were identified, leading to the development of the final research model. The results indicate that the data governance-based policymaking model for enhancing organizational performance in banks comprises five dimensions and their respective components: (1) Strategic (strategic alignment, vision, and board support); (2) Data Technology (data architecture, data integration infrastructure and quality, data analytics tools and dashboards, and data security and control); (3) Process and Operational (data lifecycle, data change management process, data risk management process, and linking business processes with data); (4) Cultural and Human Competencies (data-driven organizational culture, training and empowerment, and motivational mechanisms); and (5) Performance Measurement and Value Creation (data governance performance indicators, data-driven business indicators, and data valuation framework). Accordingly, all research questions were addressed.