Case Study: UPL improves demand forecasting and optimizes supply chain operations with Databricks

Improving supply chain operations to feed the world

UPL, a global leader in sustainable agriculture, needed a better way to manage and analyze large volumes of internal and third-party data across its fast-growing global operations. Its fragmented data environment made it difficult to produce accurate demand forecasts, increasing the risk of product spoilage and inefficiencies in supply chain planning. Databricks Data Intelligence Platform was used to help address these challenges.

Databricks implemented a real-time data and AI foundation for UPL, using advanced machine learning and Unity Catalog to unify data access, improve governance, and support better forecasting. As a result, UPL improved demand forecast accuracy, optimized supply chain operations, reduced product spoilage, and deployed AI solutions across 20 countries, with plans to expand to 50.

UPL

Mohan Rao

Global Head of Digital and Analytics