Predictive analytics and machine learning for reducing waste in the Pharmaceutical and Retail sectors: A comprehensive model integration approach

This paper introduces a predictive framework using advanced machine learning models to improve demand forecasting and inventory management in the pharmaceutical and retail sectors. By integrating real-time data, the approach dynamically aligns production with market conditions, reducing waste and enhancing operational efficiency. Pilot implementations showed significant gains in profitability and sustainability, demonstrating the framework's potential for data-driven, adaptive solutions in a volatile market.