<![CDATA[The persistent misalignment between national higher education policy mandates and institutional governance practices in Indonesian vocational higher education institutions (VHEIs) continues to obstruct effective lecturer performance management. This study develops and validates the Data-Driven Policy–Governance Alignment Model (DPGAM), a theoretically integrated framework that synthesizes policy alignment theory, institutional analytics theory, and organizational learning theory to diagnose and bridge the policy–governance gap in VHEIs. Employing a sequential explanatory mixed-methods design with a comparison group longitudinal component, this study aimed to analyze data from 4,424 lecturers across 142 VHEIs between 2022 and 2024. A 48-item validated instrument, the Governance Alignment Assessment Tool (GAAT), measured six governance dimensions. Common method bias was assessed using Harman's single-factor test (variance explained = 22.7%, below the 50% threshold) and procedural remedies. Structural equation modeling (SEM) identified Policy Compliance Index (? = 0.421, p < .001), Governance Transparency Score (? = 0.318, p < .001), and Data Infrastructure Quality (? = 0.287, p = .003) as the strongest predictors of the Policy Alignment Score (PAS). Post-DPGAM implementation demonstrated a statistically significant improvement in the Composite Lecturer Performance Index (CLPI) from 63.5 to 76.8 (Cohen's d = 1.32, p < .001; difference-in-differences = 11.4 points). Unexpectedly, private polytechnics showed disproportionately lower transparency compliance than community colleges, challenging assumptions about institutional size and governance capacity. The model demonstrated strong construct validity (Cronbach's ? = 0.74–0.87) and acceptable model fit (CFI = .962, RMSEA = .048). These findings offer a theoretically grounded, empirically validated, and reproducible governance framework for policymakers and administrators in vocational higher education]]>
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