This study applies Cooper, Fusarelli & Randall’s (2004) multidimensional policy analysis model to the 2025 National Action Plan for Industrial Education and University–Industry–Research Collaboration, diagnosing policy coherence and limitations across the normative, structural, constitutive, and technical dimensions. Using the joint central–local plan and related reports, we combine text mining with a codebook-guided qualitative content analysis to extract salient keywords (e.g., “commercialization,” “RISE,” “talent development,” “settlement pipeline”) and interpret their contexts. Findings show that, while the normative vision—region- and field-based advanced talent development with entrepreneurship, commercialization, and innovation ecosystems—is clearly articulated, translation into indicators, budgeting, and implementation rules is insufficient. Structurally, misaligned authority and accountability among ministries, local governments, and universities weaken the plan–implementation–evaluation–feedback cycle; constitutively, SME demand reflection and incentive alignment for firm-led tracks remain limited. Technically, instruments such as BRIDGE 3.0, TCC, and technology-transfer platforms operate, yet KPI schemes skew toward short-term quantitative outputs, undercapturing qualitative outcomes (startup survival, scale-up, regional retention). We propose standardizing a vision–strategy–indicator logic model, establishing a cross-ministerial Common Data Model (CDM) and integrated performance/budget dashboard, institutionalizing firm-led tracks, and shifting to a BSC-based, multi-layer KPI system. We further specify expected effects of CDM and multi-layer KPIs (continuous detection of task/indicator/budget overlaps and gaps, reporting automation with reduced field burden, longitudinal tracking of the education →employment/entrepreneurship → regional settlement pathway) alongside implementation constraints (privacy and legal alignment, standardization/interoperability costs, institutional capacity gaps, and KPI gaming risks). We also discuss cross-dimensional interactions, showing that normative–technical misalignment can attenuate feedback efficacy, and argue that data governance (structural) and incentive design (constitutive) are required to restore effective feedback loops. Limitations include single-year scope and document dependence; future work should employ longitudinal trend analysis and comparative studies across ministries and local governments to test the persistence and heterogeneity of policy effects.