OOS risk prioritized early
VOIDS helps e-commerce brands reduce stockouts: demand forecasting, inventory, open POs, and lead times become clear reorder priorities.
Over 250 e-commerce brands run forecasting, inventory, and purchasing with VOIDS.
Prioritize likely stockouts before they cost revenue
VOIDS combines forecast, current inventory, incoming deliveries, and lead time to calculate time until a critical stockout.
Learn from stockout data for the next purchasing decision
VOIDS connects to your existing commerce stack, maps the operating rules that shape purchasing, and supports the team through go-live.
How does VOIDS get from forecast to purchase decision?
How can e-commerce brands reduce stockouts?
Brands reduce stockouts when replenishment does not only react to past sales. Teams need a forecast per SKU that accounts for campaigns, seasonality, and demand hidden by unavailable inventory. Combined with stock, open POs, lead times, and minimum order quantities, that creates a prioritized reorder list that protects revenue first.
2,000 SKUs, 30+ markets. HYROX plans with VOIDS.
“VOIDS is our single source of truth for inventory. Without those dashboards, the operations simply wouldn't work.”
Jochen MollerCCO, HYROX
“Our problem was never demand, it was that our best-selling collars were always out of stock exactly when orders came in. Since VOIDS, we manage procurement down to the SKU. Warehouse costs dropped 35%, not a single stockout since.”
How VOIDS prevents stockouts
Surface risk per SKU
VOIDS combines forecast, current inventory, incoming deliveries, and lead time to calculate time until a critical stockout.
Account for hidden demand
Stockout periods are not read as real demand weakness, so the next purchase does not repeat the same planning error.
Direct reorders by revenue impact
The team sees the purchases that protect availability and revenue with the least necessary working capital first.
When stockout prevention matters
Bestsellers are regularly unavailable
When paid traffic or organic demand lands on sold-out variants, a retrospective inventory report is no longer enough.
Sales data underestimates demand
A sold-out product does not sell less because demand disappeared. It cannot be served. VOIDS corrects this bias in the forecast.
Purchasing decides too late or too broadly
With long lead times and MOQs, the team needs to know which decision protects revenue now and which order ties up cash without improving availability.
Prevent stockouts instead of only reporting them
A notification after a stockout is too late. VOIDS prioritizes the decisions before it and makes their commercial impact clear.
| Criterion | VOIDS | Typical alternative |
|---|---|---|
| Timing | Proactive risk detection using forecast, lead time, and open POs. | An alert only when inventory is low or already at zero. |
| Demand model | Corrects historical sales for stockout effects. | Treats sales as a complete picture of demand. |
| Prioritization | Ranks by revenue risk, lead time, and cash required. | Every low-stock product looks equally urgent. |
Live in days, not months. VOIDS connects to your existing commerce stack, maps the operating rules that shape purchasing, and supports the team through go-live.
Connect the tool stack
Bring together shop systems, marketplaces, marketing channels, and ERP data without a separate data-engineering project.
Configure operations
Model lead times, MOQs, purchase prices, bundle mappings, and supplier constraints in the planning workflow.
Go live with guidance
A dedicated go-live call and weekly check-ins help the team validate the setup and operationalize planning.