Abstract
This study explores the development of decision-making methods for indicative planning within higher education institutions (HEIs). In the context of globalization and digital transformation, the ability to make informed management decisions is crucial for the success of HEIs. The research focuses on creating a system that improves decision quality by employing indicative planning and systemic-cognitive analysis. Indicative planning allows for the systematic organization of decisions by forecasting outcomes and optimizing strategies. Systemiccognitive analysis provides a comprehensive tool for modeling complex decision-making processes, enhancing the transparency and effectiveness of management. The study identifies both strengths and limitations of these methods, suggesting improvements such as the integration of machine learning to enhance adaptability. The proposed approach aims to create a flexible, adaptive decision support system that can rapidly respond to changes in the educational environment, ultimately contributing to more efficient and effective management in HEIs.