On time in full
The share of orders that arrived when promised, with everything the customer asked for.
01 What it is
Why anyone looks at this number
The share of orders that arrived when promised, with everything the customer asked for.
It is the customer's view of your supply chain, not yours. It also predicts churn: service failures show up in retention long before they show up in a survey.
02 The formula
How it is worked out
On time in full = orders_delivered_on_time_and_complete ÷ total_orders grain : week × customer × site unit : percentage source : Order management and transport systems
Measure against the date the customer asked for, not the date you confirmed. Measuring against your own confirmation lets you hit 98% while the customer experiences 80%.
03 Worked example
The same number, with real inputs
| Orders delivered on time and complete | 2,190 |
| Total orders | 2,400 |
| Calculation | 2,190 ÷ 2,400 |
| Result | 91.3% |
One in eleven orders disappoints. Split it: if most failures are "in full" rather than "on time", the problem is stock, not transport.
04 What moves it
Four things that actually change this number
Stock availability
You cannot ship what is not there.
Production reliability
Breakdowns and changeovers push out promised dates.
Transport performance
Carrier reliability and the last mile.
Order entry accuracy
A wrong address or wrong item is a failure even if the stock existed.
05 Where the number lives
The system, the record and the fields
| System of record | Key record | Fields you need |
|---|---|---|
| Order management and transport systems | Order line joined to Delivery and Goods issue | requested_date, confirmed_date, actual_delivery_date, ordered_qty, delivered_qty |
Measure against the date the customer asked for, not the date you confirmed. Measuring against your own confirmation lets you hit 98% while the customer experiences 80%.
06 How it goes wrong
Three ways this metric misleads people
Measuring against confirmed date
It excuses every promise you already moved and flatters the number.
Fix: Report against the requested date, and confirmed date separately.Measuring by line, not by order
An order that is 95% complete is still an incomplete order to the person receiving it.
Fix: Report both, and lead with the order-level number.Excluding the awkward customers
Accounts with hard delivery windows get carved out and the average improves.
Fix: Keep everyone in, and segment rather than exclude.08 Questions
Frequently asked
What is a good OTIF?
Retail customers routinely demand 98% and fine below it. Industrial supply often runs in the low 90s. What matters is the trend and what your customers actually contract for.
Should OTIF be measured by order or by line?
By order for the customer view, by line for diagnosis. Leading with lines makes performance look better than the experience.
One definition, everywhere it is used
SCIKIQ stores this metric once and serves it to every dashboard, board pack and agent that asks.