DIRECT ANSWER
Use current issued POs to identify order requirements and treat forecast volume as a separate planning scenario. Compare item scope, units, locations, dates and snapshot times before explaining a gap. Review inventory, inbound supply and unresolved assumptions with the replenishment owner.
The forecast suggests a large week, but the POs are much smaller. Production wants a number. Start by naming which number answers which question, then document the planning decision your company is making.
This guide covers Walmart U.S. first-party store-supplier planning. DSV customer orders, Marketplace inventory recommendations and Sam’s Club forecasts need their own sources. It is a comparison method, not a reconstruction of Walmart’s replenishment algorithm.
Separate three records before choosing a production quantity
Demand forecast: expected customer demand for a defined item, location population and selling period. Order forecast or supply plan: projected ordering activity. Issued POs: the specific orders already recorded, subject to their current terms and subsequent changes. Neither forecast becomes an issued order because it appears in a Walmart report.
Walmart’s Supplier One overview describes Store Demand Forecast for Owned suppliers. Its public BI Link documentation separately identifies an Order Forecast table and its date, location, item and sequence dimensions. Walmart’s public glossary distinguishes an adjusted sales forecast quantity from order-forecast quantities and dates.
Those BI Link definitions apply to that product. They do not establish your Report Builder access, a common refresh clock or identical field names in every screen. Read the definition beside the actual report you use. Record which date means expected sales, order placement or arrival.
Build a comparison you can explain
Preserve the forecast as it looked when the plan was made. A later export can contain a revised forecast; overwriting the earlier file loses the evidence behind the original decision.
For each number, record:
- Identity and scope: Walmart item configuration, supplier agreement, store/DC population and channel. A national item forecast cannot be compared with one DC’s orders as though both covered the whole business. Confirm which party supplies each destination: a forecast of Walmart DC-to-store movement is not an order to your company. Keep that movement separate from projected supplier-to-Walmart orders.
- Quantity and unit: eaches, cases or another documented unit. Retain the pack conversion and its source. Use the PO quantity and case-pack guide if that is the immediate mismatch.
- Time: the measurement dates, the meaning of the date field, forecast snapshot time and PO extraction cutoff, including timezone where relevant.
- Counting rule: the row grain and treatment of versions or repeated exports. Define whether PO quantities are original or revised as of a stated cutoff. Repeated copies are not additional orders; distinct forecast rows are not necessarily duplicates merely because the item and date match.
Do not infer a location’s role from its column label alone. The BI Link Order Forecast documentation uses store_nbr for the destination even when that destination is a DC. Confirm the location type and ordering flow in your actual source; this is not a universal Report Builder field or filter recipe.
Use the Walmart week guide to map week labels to dates. Matching the week label does not make sales dates and order-placement dates the same business event.
A fictional same-week comparison
This example uses one invented item and a defined U.S. store population with its supplying DCs. For this example, those stores represent the full modeled store population for the selected DCs. The order forecast and issued POs both describe orders to this supplier for those DCs; neither includes DC-to-store transfers. All quantities have been expressed in eaches using the example’s documented pack basis. Both forecasts were saved on September 4, 2026. Issued POs were extracted on September 12, after the comparison week ended. No PO revisions or cancellations occur in this example.
| Record | What falls in September 5 through 11, 2026 | Quantity |
|---|---|---|
| Saved customer-demand forecast | Expected customer sales during those dates | 10,000 eaches |
| Saved order forecast | Projected orders with order-placement dates in that interval | 6,000 eaches |
| Issued PO records | Orders with confirmed placement dates to the supplier in that interval, counted once per relevant line | 5,400 eaches |
The issued quantity is 600 eaches below the saved order projection, or 10% of that 6,000-each projection. This measures a gap between that saved order estimate and the selected issued-order records. It is not a customer-demand forecast accuracy score.
The 4,600-each difference between demand forecast and issued POs has no automatic “missing order” interpretation. The dates cover the same calendar interval but different events. Existing inventory, earlier inbound orders and later replenishment can cross that interval. None of those possibilities is established as the cause merely by listing them.
The next request is specific: “For this item and mapped locations, what explains the 600-each difference from the saved order projection? Here are the snapshot, PO lines and date definitions.” Do not manufacture a formula that subtracts inventory from demand and labels the remainder Walmart’s required order.
What should change in the plan?
First resolve missing evidence. If a known PO cannot be found, use the PO visibility investigation. If two reports claim to measure the same sales quantity, use the Scintilla reconciliation guide.
Then check dated inventory and inbound evidence, item/order settings, distribution changes, events and other documented operating changes with the replenishment owner. Ask which explanation is supported and which remains a hypothesis. A forecast increase alone does not authorize a production commitment or establish that more POs will arrive.
Use a short internal decision record: issued-order requirement; additional forecast exposure; available stock/capacity; unresolved assumptions; chosen production quantity; decision owner; next review time. Your team can decide to prepare for forecast demand while keeping that inventory risk separate from issued-order work. This article does not prescribe a buffer percentage.
Startup Success Lab’s guide to turning a retail investigation into a merchant decision helps turn the comparison into a clear request and follow-through. Its cost-model guide helps keep volume assumptions visible in the economics.
Source scope
Source review: September 13, 2026. Supplier One and the BI Link glossary were reviewed through indexed official text; direct requests required sign-in or timed out. The public Order Forecast table documentation was read directly. Current account access, live forecast records and Walmart’s internal calculation were not verified. The comparison, arithmetic and decision record are original instructional material.