<![CDATA[This study was conducted to explore how data-enhanced supervisory practices evaluated through the CIPP (Context, Input, Process, Product) model can strengthen decision-making and improve teacher professional competence. This research employed a qualitative approach using the CIPP evaluation model. Participants were selected through purposive sampling, involving the principal, vice principal for curriculum, and teachers who had directly experienced data-based academic supervision at Senior High School 1 Central Bengkulu. Data were obtained through interviews, observations, and document analysis. Triangulation ensured data validity, while thematic analysis examined supervisory practices, teacher responses, and teacher professional competence outcomes. Findings reveal that data-enhanced supervision enables more precise identification of teacher challenges and facilitates evidence-based feedback. The CIPP analysis showed that contextual readiness is strong; however, input components, particularly digital competence and technical support, require further strengthening. Process evaluation indicated consistent use of data during supervision, while product evaluation demonstrated improvements in instructional planning, classroom management, reflective practice, and accountability. Teachers showed increased motivation and awareness of professional competence, and schools benefited from systematic monitoring of instructional quality. The study concludes that integrating data into supervisory practices significantly enhances teacher professional competence. It is recommended that schools strengthen supervisors' data literacy, improve digital infrastructure, and institutionalize data-based supervision as a sustainable professional development strategy to support long-term educational improvement.]]>
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