Organizations frequently face challenges in balancing financial planning, operational resource utilization, and performance monitoring under changing market conditions. This study proposes an integrated analytical framework that combines time-series forecasting techniques with optimization-based resource allocation models to support organizational decision-making. The framework incorporates historical operational and financial data to estimate future demand patterns, revenue fluctuations, and resource requirements. Forecasting models are developed using statistical methods to identify trends and seasonal variations, while optimization procedures are applied to allocate resources under budgetary and operational constraints. Enterprise information systems are utilized to structure and process organizational data for analysis and reporting. The proposed approach is evaluated through simulation-based scenarios and comparative performance analysis using forecasting accuracy and resource utilization indicators. Results demonstrate improvements in planning accuracy, operational efficiency, and decision consistency. The framework provides a practical methodology for organizations seeking to improve financial and operational performance through data-driven planning and structured decision-support mechanisms.