Transforming Medical Retail: Data-Driven Inventory Insights and Machine Learning-Powered Sales Forecasting

Success in the cutthroat medical retail sector depends on effective inventory control and precise sales forecasting. Due to their reliance on manual procedures and inadequate analytics, traditional methods frequently fail. In order to overcome these obstacles, the study “Transforming Medical Retail: Data-Driven Inventory Insights and Machine Learning-Powered Sales Forecasting,” creates a methodology that combines predictive modeling with historical data analysis utilizing ARIMA and Prophet. Through an integrated dashboard, the solution offers sales projections and actionable information, facilitating proactive inventory management and cutting down on inefficiencies like overstocking and stockouts. The model’s dependability is confirmed by performance measures like RMSE and MAE. This study demonstrates how data-driven tactics may be used to update inventory procedures and give medical retailers the tools they need to develop sustainably.