Success Story #1
Commodity Price Forecasting for Strategic Procurement
FMCG / CPG
Marketing
Business Problem
A global FMCG organization relied on traditional forecasting methods for commodity futures, resulting in limited visibility beyond short-term horizons. Forecast inaccuracies across soft commodities, energy, and metals led to suboptimal purchasing timing, inefficient inventory positioning, and increased exposure to market volatility.
Actions Taken
- Developed and operationalized multivariate AI forecasting models, including LSTM neural networks.
- Incorporated demand: supply signals, macroeconomic indicators, financial market data, and commodity-specific drivers.
- Applied ensemble modeling and advanced feature engineering to capture non-linear interactions.
- Validated models through back-testing and continuous performance monitoring.
Outcomes Achieved
- Achieved best-in-class forecasting accuracy over a 4–6 month horizon.
- Enabled more disciplined and timely purchasing strategies.
- Optimized inventory levels and order frequency across commodities.
- Generated CHF 1M+ in monetized benefits through improved price visibility and decision-making.
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