UPL optimizes supply chain operations with demand forecasting on Databricks
UPLDatabricks SQL · Delta Lake · Delta Sharing +2
Global agriculture company UPL unified internal and third-party data sources (SAP, Salesforce, IoT, weather) on the Databricks Data + AI Platform with Unity Catalog to build a demand forecasting model that reduces product spoilage and supports AI-driven crop management and pest control across 20 countries.
Overview
Global agriculture company UPL unified internal and third-party data sources (SAP, Salesforce, IoT, weather) on the Databricks Data + AI Platform with Unity Catalog to build a demand forecasting model that reduces product spoilage and supports AI-driven crop management and pest control across 20 countries.
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Inspect the highlighted sourceThe challenge
UPL's rapid growth left it managing vast, fragmented data from sources like SAP, Salesforce, plant IoT sensors and external weather, regulatory and microeconomic data, which hindered its ability to generate accurate demand forecasts and risked product spoilage given the narrow multi-day windows in which agricultural products must be applied.
The solution
UPL implemented the Databricks Data + AI Platform to unify internal and external data sources into a centralized data lake, using Unity Catalog to democratize and govern data access across the organization and Databricks SQL's serverless engine to process and analyze data quickly, enabling a more accurate demand forecasting model.
Reported business value
UPL has deployed AI solutions across 20 countries, driving significant improvements in demand forecasting accuracy, crop management and pest control, minimizing product spoilage and ensuring agricultural inputs are delivered precisely when needed, and plans to expand deployment from 20 to 50 countries.
Sources
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This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)
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