Quick answer
To forecast demand through VIP, project both the distributor's replenishment draw and the sell-through at the retailers it serves, and plan production to protect fill rate. Connecting VIP data to a live model ties downstream demand to cash.
What VIP data brings to inventory forecasting
VIP is a distributor serving downstream retail and specialty channels from its distribution network.
Forecasting for VIP follows distributor economics: project the DC draw and downstream sell-through, and protect fill rate to avoid deductions.
| VIP data | What it drives in the forecast |
|---|---|
| Distributor draw / POs | DC replenishment demand |
| Downstream retail sell-through | True consumption |
| Fill-rate performance | Service level and deductions |
| DC inventory | Channel coverage |
Forecasting through a distributor
With a distributor, you ship into its DCs and it fills downstream retailers. The forecast has to project both the distributor's replenishment draw and the sell-through at the retailers it serves, and plan fill rate to avoid deductions.
Formula: Weeks of supply at retail = units on shelf and in the retailer's DCs / average weekly sell-through (units per store per week x active stores). Replenishment timing works back from the retailer's reorder cadence and your production lead time.
The trap is mistaking a distributor's one-time stocking order for real demand. Watch downstream retail sell-through so you produce to consumption, not to a warehouse fill that will not repeat.
From VIP data to a cash-aware forecast
Retail sell-through is only actionable when it connects to what you must produce and the cash it consumes. Drivepoint pulls VIP data through its VIP integration into a live, Excel-native model, turning store-level velocity into forward weeks of supply, replenishment timing, and the cash each production run requires.
For a wholesale brand, that connection answers the real question before you commit a purchase order: can we afford it? It is the same discipline that turned an Oats Overnight timing decision into a $4M EBITDA gain. For the underlying method, see our guide to purchase order forecasting.