
This large agricultural distributor with 350 branches experienced inventory issues due to inaccurate forecasting, which resulted in high costs and an aging inventory.
challenges
Complexity to Clarity
Challenge
For each season, the company needed to place a product order (eg, seeds for crops) one year in advance, which was forecast poorly due to reliance on lagging indicators to predict demand. This resulted in a large write-off of seasonal inventory.
Solution
With o9, the company was able to implement automated forecasting on products with high and low variability using ML and statistical modeling. The forecast for high variability products used active forecasting to ensure quicker responses to market changes.
Value Delivery
Customer Benefits
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