OTIF (On-Time In-Full) in 2026: Formula, Calculation and Why a Good Score Can Hide Empty Shelves

TL;DR

OTIF, short for on-time in-full, is the share of deliveries that arrive inside the agreed window with the full ordered quantity. A delivery fails if it misses either condition. You calculate it by dividing on-time, in-full deliveries by eligible deliveries and multiplying by 100, and the result changes depending on whether you count whole orders or order lines. An OTIF report can look healthy while shelves sit empty, because shipment records do not show a replenishment order that nobody placed. This guide is published by Sentra, which understands how a company really runs, and acts on it before anyone asks. Sentra connects operational records with the decisions captured in email, chat and meetings, which is where the reason replenishment stopped usually sits.

What OTIF means and why it fails on either half

OTIF measures whether an order arrives within the agreed delivery window with the complete ordered quantity. Both conditions must hold. If you order 100 units and receive 90 on time, the order fails. It also fails if all 100 units arrive after the window.

Define the delivery window before you calculate anything. Retailers and distributors set their own timing rules, including how many days early or late still count, and whether the clock runs to dispatch, carrier pickup or receipt at the dock. The same arrival can pass a supplier's timing test and fail a customer's.

The OTIF formula and how to calculate it

OTIF (%) = (deliveries on time AND in full / eligible deliveries in the period) x 100

Example: 432 qualifying deliveries out of 500 eligible = 86.4% -> 86%

Decide whether canceled orders, open orders, partial shipments and approved date changes belong in the denominator before you calculate the rate, and keep the rule the same every period.

A spreadsheet you can copy

Put one eligible delivery in each row. Enter the earliest and latest acceptable receipt dates in columns B and C, the actual receipt date in D, the delivered quantity in E and the ordered quantity in F. Then fill the pass flag down column G and divide the sum by the row count.

G2:  =IF(AND(ISNUMBER(D2),D2>=B2,D2<=C2,E2>=F2),1,0)
OTIF for 500 deliveries in rows 2 to 501:  =SUM(G2:G501)/COUNT(F2:F501)

Use timestamps instead of dates if the window ends at a set time, and use confirmed receipts instead of shipment dates if the customer measures arrival.

Order level vs line level

The unit you count changes the result. Order-level OTIF passes an order only when every line passes. Line-level OTIF scores each product line separately, which shows which products missed. Suppose each of 500 orders has two lines and 68 orders have exactly one failed line. Order-level OTIF is 432 of 500, or 86.4%. Line-level OTIF is 932 of 1,000, or 93.2%. Neither is wrong, but they answer different questions, so label which one a report uses.

Targets and retailer penalty programs

There is no independent industry standard for a good OTIF score. The target that matters is the one in your customer's supplier agreement or scorecard, including its window, its quantity rule and whether it measures on-time and in-full as separate percentages. Large retailers run OTIF compliance programs with their own thresholds and can fine suppliers on noncompliant orders, as Retail Dive has reported for Walmart. The thresholds change over time, so take them from the current scorecard rather than from a blog post.

Check which goal applies before you compare your OTIF report with a customer's. A supplier may measure arrival against its promised date while the retailer applies its own window and program thresholds. Both reports can use the same shipments and still return different results.

Why supplier and retailer OTIF numbers disagree

A supplier and a retailer can score the same shipment differently because they record different events. A dispatch-based report may mark an order on time when it leaves the warehouse, while the retailer measures arrival at its distribution center. Dispatch is not delivery, so confirm which event the agreement specifies.

Quantity rules differ too. One side may count a substituted item as in full while the other does not. Revised dates are a third source of disagreement: if someone replaces a missed date with a later promise and the report measures against the revision, a late delivery can count as on time. Keep the original date alongside any approved change.

Why a strong OTIF score can coexist with an empty shelf

A 95% OTIF score can accurately describe completed deliveries while a product is missing from the shelf. The score counts orders in a reporting period. It does not count a replenishment order that nobody placed.

Suppose a supplier asks by email to change a quantity, and a planner pauses replenishment while revising the forecast. If nobody updates the expected receipt in the inventory system, the dashboard keeps projecting stock that will never arrive, and the OTIF calculation still reflects earlier deliveries that passed both tests. The same failure shows up as phantom inventory when the record says units are on hand that a count cannot find.

How to find and fix the real cause

• Segment the score. Break OTIF down by product, customer and lane, then inspect the orders behind the weakest segments. A high overall score can hide repeated shortages on one product.
• Compare failures with live records. Check each failed order against ERP inventory, warehouse picks, carrier events and confirmed receipts. If ERP shows stock but the warehouse cannot fill the order, check when inventory last changed and whether replenishment was released.
• Check the measurement rules. Document the agreed window, the receipt event that counts as arrival and the original promise date before you assign a cause.
• Trace the decision behind each recurring miss. An ERP record may show that replenishment stopped without showing the email or planning discussion that explains why. Work the chain of causes with a root cause analysis template.
• Assign and verify the fix. Give the finding to the person who can change the next order, pick or carrier booking. Record the fix and its owner, then check whether the next delivery passes under the same rules.

Lenskart: reported stock versus shelf availability

At Lenskart, reports showed a top product line about 95% stocked, while Sentra measured 12.8% availability on the shelves after replenishment had stopped. In Sentra's own measurements as of October 2026, about $860K of sales were lost in the two weeks before the fix. Neither figure is an OTIF score. The case shows why a delivery metric cannot, by itself, explain an empty shelf.

Where Sentra fits

Sentra understands how a company really runs, and acts on it before anyone asks. It reads email, chat, meetings and documents alongside ERP, CRM, HRIS and BI data, works out what is true now and why, and raises what is going wrong to the person who can act. For OTIF, that means connecting a stalled replenishment decision in a planning thread to the inventory record it affected and naming the planner who can restart it.

A named person approves each finding before it reaches anyone else. Every claim cites its source, and permissions follow the source, so nobody sees a message they could not already open. Sentra replaces none of the company's systems. The ERP, the warehouse system and the scorecard keep doing their jobs.

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