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Use case · Distributors & manufacturers
Buy what's about to sell.
Stockouts lose customers. Overstock eats margin. Both come from the same loose end: forecasts built on gut feel and last year's spreadsheet. A forecasting agent watches the signals continuously and tells purchasing what's coming.
In short
AI demand forecasting uses an agent to predict SKU-level demand from order history, seasonality, lead times, and live signals. It produces purchasing recommendations that update continuously, and flags unusual patterns, like a key account quietly doubling its order cadence, while there's still time to act.
The loose end
Written for the purchasing manager who got burned by a stockout and an overbuy in the same quarter. Industry benchmarking (APQC) associates advanced demand forecasting with 15–30% reductions in inventory. Capital that mid-sized distributors typically have sitting on shelves in the wrong SKUs while the right ones stock out. The gap isn't effort; purchasing teams work hard. It's that no human can continuously re-forecast thousands of SKUs against live signals.
What the agent does
- Forecasts at SKU level, updated continuously rather than quarterly.
- Recommends purchase quantities that respect lead times, minimums, and cash priorities.
- Alerts on anomalies: demand spikes, dying SKUs, a big account quietly changing its ordering pattern.
- Every forecast gets scored against what actually sold, and the agent adjusts. It learns from outcomes instead of repeating them.
The math that matters
Inventory carrying cost runs roughly 20–30% of inventory value per year. If better forecasting trims even 10% of stock while cutting stockouts, the pilot pays for itself on the balance sheet alone. The Opportunity Audit sizes your specific opportunity from your data.
We already forecast in our ERP. What's different?
ERP forecasts are static averages refreshed when someone remembers. The agent refreshes continuously, works at SKU level, and explains its alerts ("these 14 SKUs will stock out in 9 days at current velocity") in time to act.