This study aims to analyze concepts and implementation strategies for optimizing academic supervision through the use of a digital learning observation platform. The study employs a qualitative library research method by reviewing relevant scholarly sources, including journal articles, books, conference proceedings, and education policy documents. Data were analyzed using content analysis to identify major themes, recurring patterns, and to formulate an implementation framework for digital-based academic supervision. The findings indicate that digital platforms have the potential to improve the efficiency of supervision processes, strengthen the standardization of observation instruments, enhance the traceability of documentation, and support more evidence-based supervision practices. However, the literature also emphasizes that the effectiveness of digitalizing supervision is not determined solely by technology; it depends on the quality of feedback, consistency of follow-up actions, users’ digital literacy readiness, infrastructure support, a coaching-oriented organizational culture, and data governance. Based on the synthesis, this study proposes an implementation framework consisting of pre-implementation readiness, instrument design, observation execution, reflective feedback, and follow-up monitoring. The study recommends strengthening human resource capacity, simplifying procedures, ensuring technical support, and establishing clear data privacy SOPs so that digital platforms can genuinely optimize academic supervision and contribute to improving learning quality.