Case Study: a global Food and Beverage conglomerate reduces inventory waste with C5i and Databricks on Azure

Enabling Pre-emptive Recommendations for Inventory Waste Reduction using Databricks and Azure Data Factory

The global Food and Beverage (F&B) company faced a significant challenge with finished goods inventory waste, an issue costing approximately $100 million annually. Their existing systems only provided backward-looking data, which was insufficient for preventing waste caused by products expiring or being damaged. To address this, they partnered with vendor C5i to develop a proactive solution.

C5i implemented an AI-powered analytics platform, C5i Discovery, on the client's Azure stack, utilizing Databricks and Azure Data Factory. The solution aggregated data from multiple sources to identify inventory at high risk of waste and provide prescriptive recommendations to site managers. This resulted in 100% adoption by users and led to a roughly 30% reduction in waste from stales and damages, while also cutting query processing time in half.