<![CDATA[The development of sectoral statistics is a strategic function designed to ensure that statistics produced by government agencies meet established standards, maintain high quality, and support the National Statistical System. This study aims to examine the current state of governance in the development of sectoral statistics, identify existing governance gaps, and translate these findings into a framework for sustainable improvement. Employing a descriptive qualitative approach, the study conducted an in-depth analysis of sectoral statistical development in 2025, involving 18 development teams comprising 5 provincial-level teams and 13 regency/city-level teams. The primary data consist of qualitative accounts regarding respondents' experiences, challenges, practices, and recommendations, while closed-ended responses serve as contextual information to strengthen interpretation rather than as a basis for statistical generalization. The findings indicate that while an operational foundation for governance exists covering preparation, execution, reporting, and monitoring and evaluation the current framework remains overly dependent on specific individuals, lacks uniformity, and is not yet fully documented. The study identifies six key gaps: clarity of roles and accountability, process standardization, capacity, coordination, digital support, and monitoring and feedback. Based on these findings, the study proposes a "closed-loop governance" model that integrates network governance, quality assurance, public-sector data governance, and continuous improvement through a cycle of: plan → execute → document → verify → evaluate → correct → re-assess. This model emphasizes minimum standardization, needs-based flexibility, quality gates, capacity building, the use of a digital platform as a central control hub, and traceable follow-up actions. Ultimately, the study suggests that the effectiveness of statistical development should be evaluated based on improvements in process quality and an institution's capacity to sustainably reduce identified issues, rather than merely by the number of activities conducted or the completeness of administrative documentation.]]>
