Dynamic Monitoring Method for Public Policy Implementation Efficiency in Digital Governance

This study proposes a dynamic monitoring method for evaluating public policy implementation efficiency in the context of digital governance. Existing approaches to policy evaluation are mostly retrospective and static, which limits their ability to provide timely insights and adaptive support. To address this gap, the proposed framework introduces a multi-dimensional indicator system that integrates policy execution progress, resource allocation efficiency, and social feedback. By leveraging big data sources and employing time series analysis techniques, the system enables real-time tracking, anomaly detection, and early warning of policy delays. A case study demonstrates that the method achieves higher prediction accuracy, reduced monitoring errors, and earlier detection of execution bottlenecks compared with traditional static approaches. The findings highlight the potential of combining digital technologies with governance research to enhance transparency, accountability, and adaptive management in public administration.