For Walmart suppliers
You already have more Walmart data than anyone on your team can read. TenX Analytics reads it every morning and hands you a short list: what broke, what it is costing, and what to do about it. Then it tracks what came back.
Ask for a walkthroughThirty minutes, your data on the screen.
Walmart granted 765 new stores. Roughly 750 have nothing flowing.
Velocity-weighted DC push now, capped at order-up-to. Replenishment activation as the durable fix.
Real alert from a live client cockpit. Client and item withheld. Source: WSI, fiscal weeks 202601 to 202626, read 2026-08-05.
Proof, not promises
Anyone can point at a chart and call it savings. Our attribution is gated, and it argues against itself. A comeback that predates tracking is excluded. A comeback Walmart drove on its own is credited to Walmart. If the ask was flagged but never sent, no credit. What survives all three gates is the only number we put our name on.
Comebacks watched
$196K 314 store-item reactivationsCredited to Walmart
$62K 187 combos. Their move, their credit.Excluded, pre-tracking
$111K History is never claimed.Banked, and claimed
$13K 204 store-items across 187 stores, in a 30-day window. Every dollar postdates its ask.One live client tenant. Captured tracker, 30-day window, plus reactivation watch attribution, read 2026-08-05. Client identity withheld, metrics shared with permission. The other $183K stays on the board as watched, not claimed, which is the whole point.
The daily cycle
No dashboard to remember to open, no report to build. The work happens overnight and the answer is waiting for you.
OVERNIGHT
Scintilla files pull in and rebuild across every grain we track, down to item and store.
BEFORE 7AM
Each one looks for a specific failure worth money: phantom inventory, stranded distribution, a DC that quit shipping.
YOUR MORNING
Ranked by dollars at stake, naming the owner and the one Walmart setting to change, with the evidence attached so you can forward it without rebuilding the case.
AFTER
A comeback watcher checks whether the store actually started selling again, and banks only the dollars that followed an ask.
Alerts in action
Every alert names the failure, the dollars at stake, the owner, and the one Walmart setting that fixes it. It is written to be forwarded, and the evidence rides along.
Not flowing to store · a new-store grant sitting idle
765 new stores granted on one item; roughly 750 with nothing flowing. DC stock is in place. Store replenishment never activated, so every quiet week reads as a $0 on the item's scorecard.
The ask: velocity-weighted DC push now, capped at order-up-to. Durable fix: activate replenishment so GRS orders on its own.
Conversion forecast gap · the successor keyed low
A pack change issued a new item number and the demand history did not follow: proven 27 units per store-week, keyed at 12, selling 10. The low sales will confirm the low forecast at the next review.
The ask: raise the GRS store forecast to the predecessor's demonstrated rate before the review locks it in.
DC drain · a de-traited pack still holding the warehouse
The old pack is off the stores but 580 cases still sit across six DCs, with open POs still feeding two of them. Shelf-life and chargeback risk, and nothing on the store side will pull it down.
The ask: cancel the open POs on the dead item number and push the remainder while it can still sell through.
The push on the first alert landed. 835 stores selling by the July 4th week, weekly POS $57K to a $114K peak, and the tracker banked only the dollars that followed the ask. The rest stayed watched, not claimed.
Measured reads from live client cockpits, 2026. Client and item identities withheld, metrics shared with permission. The morning list ranks by dollars at stake.
What it finds
Every one of these came out of a live client cockpit. None of them looked broken on a scorecard.
Pack conversion
Walmart issues new item numbers on a size change, and the old item's demand history does not follow. The successor was keyed at less than half its predecessor's proven rate, so stores were stocked for less than half, and the low sales then confirm the low forecast at the next review.
Price
Units responded to the rollback, so the review page called it a win. Margin dollars per store fell by a third. Six weeks earlier the same brand raised a price on another size and units held while margin rose. Same shelf, both directions, measured the same way.
Replenishment
A de-trait, a reset, a forgotten rollback. Nobody calls. The item's sales go to zero in that store and stay there, and the loss hides inside a healthy-looking total until someone counts the stores that used to buy it.
Live cockpit reads, 2026-08-05 and 2026-08-06, across two client tenants. Identities withheld, metrics shared with permission. Units are per selling store per week. Margin is net IMU dollars per selling store per week, the retailer's own economics on the item.
Built on Scintilla
We ingest the daily and weekly feeds directly, keep the history, and reconcile across them so store movement and warehouse position line up in one place.
DSIDaily store inventory and movementWSIWeekly store inventoryWDCIWeekly distribution center inventoryDDCIDaily distribution center inventoryWho this fits
Start here
Thirty minutes on a call, your data on the screen. If there is nothing there worth fixing, I will tell you that.
ericfritts@tenxanalytics.comEric Fritts · Founder · 479-713-0714 · Rogers, Arkansas