Your Fill Rate Says 99%. One in Six Walmart Shipments Still Misses.

A specialty food brand pulls its internal fill rate and reads 99.2%. Its receiving data shows only 84.5% of its Walmart shipments arrived on time and complete. Neither number is wrong. The 14.8-point gap between them (computed on unrounded rates: 99.24 vs. 84.46) is not a measurement error, and it is not free: on a $25M brand's Walmart volume it runs about $57,000 a year. The problem is that the brand watches the 99 and pays for the other 15.

These figures come from Cinderhaven Provisions, a fictional $25M specialty food brand whose shipment data is synthetic. The chargebacks they produce are computed from shipment and receiving events, not reverse-engineered to a target, and the gap they expose is the one almost every brand this size is carrying without seeing it.

Two honest numbers, measuring different things

Fill rate and OTIF sound like the same idea and are not. Internal fill rate is unit-weighted and forgiving: ship 99 of 100 units across the portfolio and it reads 99%. Fill rate is unit-weighted: a shipment missing one case in a hundred still reads 99%. Walmart's On-Time In-Full program scores by case too, so its scorecard can pass while shipments keep arriving short. But a short shipment is still short. The missing cases come back as chargebacks and receiving discrepancies, and the empty shelf slot costs sales until the next order lands. Both dashboards are doing exactly what they were designed to do; neither one shows the brand how many shipments arrive incomplete.

That is why the brand can believe it is a 99% performer, and even pass its OTIF scorecard, while its largest customer deducts for the cases that never arrived. The dashboard is not lying. It is answering a different question than the one the retailer's receiving dock is answering.

The gap is almost all in-full, and the brand is watching on-time

Decompose Cinderhaven's 14.8-point gap and it separates cleanly. On-time is fine: the trucks arrive in their windows, and timing accounts for barely two points of the shortfall. Nearly 13 of the 14.8 points are in-full failures, which means the brand's operational attention, appointment scheduling, carrier selection, routing compliance, is aimed at the part that is already working: on-time delivery.

Short-shipping drives 72% of the cost. A receiving discrepancy, where the retailer's dock scan disagrees with what the brand's records say shipped, adds another 14%, and it is pure data: the units may have arrived, but the numbers describing them did not agree, so the line scores short. Internal fill rate never sees either failure, because a line missing one case in a hundred is a rounding success by its math, but the missing case still arrives as a deduction.

What the short shipments cost

The exposure has two parts, and only one of them is a hard number. The measured cost is $23,697 a year: actual compliance fines deducted from remittances for short shipments, late deliveries, and receiving discrepancies. Those are real dollars, already gone.

The second part is modeled, and labeled as such. Short shipments do not only come back as chargebacks; an empty shelf slot costs sales while the next order is in transit, which costs velocity. Estimated at $3.50 per unit of retailer shortfall, that damage runs about $33,500 a year. It is an assumption, not a platform-derived figure, and it should be read as a modeled estimate rather than a deduction on a statement. Together the two come to roughly $57,197 in annual exposure, of which $23,697 is invoiced and the rest is the shelf paying for cases that never arrived.

The measured fines are the visible cost. The velocity and delisting pressure that follow a bad scorecard are the larger one, and they never appear on a remittance, which is exactly why they get ignored until the buyer raises them at the line review.

OTIF penalties are a measurement problem before they are an operations problem

The instinct after a bad OTIF score is to fix logistics. Better carriers, tighter appointments, a routing-guide audit. For most brands at this scale, that spends effort on the two points that are already fine. The 14.8-point gap is a short-ship and data problem, and it starts by reconciling the fill rate the brand watches against what the retailer's dock actually received, line by line, so the failures the internal dashboard rounds away become visible before the chargebacks post. This is the same pattern underneath most OTIF fines at brands this size, which trace to data rather than trucks. The gap calculator is here, and it turns "Walmart says we're failing" into a ranked list of what actually failed.

Made a monthly habit, that reconciliation is process hygiene, pointed at the thirteen points the dashboard cannot see.

Send me your fill-rate report and one OTIF scorecard

Send me your internal fill-rate report and one retailer OTIF scorecard for the same period. I will show you the gap between them, split it into short-ship, timing, and receiving-discrepancy points, and put a dollar figure on each, so you know which failures are costing you the fines and which are costing you the shelf. You'll get it back in writing.