Agri-Input Demand Forecasting and Supply Chain Optimisation for Rural India

Objective: To develop a data-driven solution for accurately forecasting agri-input demand and optimising supply chain operations for agri-input distributors in rural India.

Rural agri-input distributors in India often face challenges in predicting demand for seeds, fertilizers, and pesticides, leading to frequent stockouts or overstocking, increased costs, and farmer dissatisfaction. The fragmented nature of agricultural supply chains and fluctuating demand based on seasonality, weather, and crop cycles further complicates efficient inventory management.

The project will use historical sales data, weather patterns, and crop calendars from government and public sources. The team will apply time series forecasting models and supply chain optimisation techniques to build dashboards and actionable tools for demand prediction and inventory planning.

Deliverables include a predictive model for agri-input demand at the village/block level, a supply chain optimisation framework, a Power BI dashboard for visualising demand forecasts and inventory recommendations, and a report analysing accuracy and business implications.

The project will help agri-input distributors minimise losses from unsold inventory, improve service levels to farmers, and inform critical procurement and logistics decisions, ultimately supporting sustainable agricultural productivity in India.