Policy Learning of One Data Indonesia for Supporting Data-Driven Policy

The One Data Indonesia policy, established through Presidential Regulation No. 39 of 2019, is a strategic initiative to support evidence-based decision-making through integrated and accessible data governance. This article explores policy learning in its implementation as a foundation for data-driven policymaking in Indonesia. This research uses a post-positivist paradigm where post-positivism uses theory as a guideline for research and acknowledges that values influence the interpretation of qualitative data. A descriptive qualitative method is used to explore the implementation dynamics of the policy in depth. An event or phenomenon of implementing the One Data Indonesia policy with policy learning theory as an analytical framework through semi-structured interviews and literature studies. The results show that the implementation of One Data Indonesia reflects three forms of policy learning (Howlett et al., 2017): cognitive-technical (improving data quality and interoperability), socio-political (cross-agency coordination), and institutional (strengthening regulations and data-based organisational culture). However, challenges such as sectoral ego, data fragmentation, and capacity constraints remain significant. In conclusion, strengthening the legal framework, data literacy, and interoperability is needed to optimise data-based policies in Indonesia. With an in-depth understanding of the policy learning process, this research provides strategic insights for policymakers in optimising the potential of data as a national strategic asset. Specifically, this study contributes by mapping concrete patterns of policy learning that can be replicated or adapted in future national data governance reforms. Effective implementation is expected to support more targeted and efficient development planning.