Case Study: a global retailer achieves more accurate lead time predictions with C3 AI

Global Retailer improves lead time predictions by 55% with C3.ai

The customer, a global retailer of home improvement products, faced significant challenges in predicting inbound order lead times due to an unreliable rolling-average approach and recent supply chain variability. This led to manual updates, inventory backlogs, and increased costs. C3.ai implemented its Supply Network Risk application to address these issues by providing AI-driven predictions for estimated delivery dates.

The solution from C3.ai involved configuring two machine learning models for static and daily updated lead time predictions, integrating extensive historical and external data. This resulted in a potential annual economic benefit of $30 million for imports, a 55% improvement in lead time predictions, and a foundational data model for future AI applications. The global retailer achieved reduced inventory, transportation, and labor costs.