ABSTRACT: This extensive research relies on Bayesian Dynamic Time Warping (BDTW) for deep insight into the time series dynamics of the performance of business administration programs in the subjects of Business Economics, Financial Management, HR Management, and Marketing Management. The complexity of interdisciplinary relationships, unique program-specific performance profiles, and robust diagnostics for model fit were evident from the analysis. Such recommendations include the implementation of focused curricular adjustment, the development of cross-disciplinary alignment, investment in continuous assessment and improvement, and using data-driven insights for strategic planning. These findings equip educational institutions with the power to optimize learning outcomes for their students, encourage cross-programming, and ensure that business administration curricula remain responsive to industry change. The study’s approach to the holistic evaluation of performance makes it an excellent tool for sustaining the success of future business leaders.

 KEYWORDS – Bayesian Dynamic Time Warping, Business Administration, Cross-Disciplinary Alignment, Curriculum Design, Performance Assessment, Temporal Dynamics