Pharmacy Supply Chain Optimization and Stock-Out Prediction System for Indian Retail

Objective: To develop a predictive system that minimizes stock-outs and optimizes inventory in Indian pharmacy supply chains.

Indian pharmacies often face frequent stock-outs due to fragmented supply chains, unpredictable demand patterns, and limited visibility across inventory and supplier networks. This impacts patient care and business profitability, especially in Tier 2 and Tier 3 cities.

The project will involve collecting real-world data from local pharmacy chains, analyzing historical sales and replenishment patterns, and applying statistical and machine learning models to predict stock-outs. The team will also map supply chain bottlenecks and identify improvement opportunities.

Deliverables include a working predictive dashboard (prototype), detailed supply chain analysis, actionable recommendations, and a business case for implementation. Analysis will be supported by visualizations and scenario simulations for pharmacy managers.

The solution aims to improve inventory management, reduce lost sales, and enable data-driven procurement decisions, contributing to better healthcare delivery and operational efficiency in the Indian context.