Fixing Forecasting Bottlenecks in Automotive Electronics

A Tier-1 supplier to major global automakers was stuck in a frustrating loop of inconsistent demand forecasts, manual reconciliation, and fire-drill planning cycles. Their forecasting models were brittle, required constant human intervention, and couldn’t scale across programs or plants.

By implementing DataPeak’s agentic AI forecasting framework, the company gained accurate, rolling 12-week forecasts with zero manual adjustment. RMSE scores improved dramatically. Planning teams finally had a forecasting model they could trust, one that learns, adapts, and scales with new program launches.

The result? Fewer surprises, faster decisions, and a foundation for long-term supply chain agility.

Read the full story of how they did it and see what DataPeak could do for your team.

Disclaimer: Results described in this case study are specific to the featured client’s experience. Actual outcomes may vary based on your business context and implementation.