National Steel Manufacturer (anonymous)

The raw materials unit struggled with short forecasting horizons, price volatility, and manual data consolidation across 15 disparate data sources. These limitations led to increased inventory costs and supply chain risks, constraining the company's ability to plan raw material purchasing effectively.

C3 AI Demand Planning unified 15 disparate data sources and configured 23 machine learning models to generate 20-week order forecasting horizons. C3 Generative AI was integrated to accelerate data analysis and support raw material and inventory managers.

Demand forecast accuracy improved to 92%+, representing a 13% improvement over baseline. The solution streamlined raw material inventory management across a $200 million inventory pool, improving procurement planning and reducing supply chain risk.

• Unifying disparate data sources into a single ML platform is a prerequisite for reliable forecasting at enterprise scale
• A 20-week forecasting horizon provides meaningful lead time for raw material procurement decisions
• Integrating generative AI for analyst-facing workflows accelerates adoption and insight generation