Perfect order rate
The share of orders that went through without a single failure — right items, right time, undamaged, invoiced correctly.
01 What it is
Why anyone looks at this number
The share of orders that went through without a single failure — right items, right time, undamaged, invoiced correctly.
Customers do not experience four separate metrics. This is the only measure that matches how they actually judge you, and it is always lower than any of its parts.
02 The formula
How it is worked out
Perfect order rate = orders with no error at any step ÷ total_orders grain : month × channel × customer unit : percentage source : Order management, transport, quality and billing
This one metric spans four systems, which is exactly why it is rarely reported. It is the clearest case for a governed layer over the sources rather than a spreadsheet each month.
03 Worked example
The same number, with real inputs
| On time | 94% |
| In full | 96% |
| Undamaged | 99% |
| Invoiced correctly | 97% |
| Calculation | 0.94 × 0.96 × 0.99 × 0.97 |
| Result | 86.7% |
Four respectable numbers produce one poor one. Roughly one order in seven goes wrong somewhere, and each of those costs service time on top of the failure itself.
04 What moves it
Four things that actually change this number
Each component
The rate is the product of them, so small failures compound quickly.
Master data quality
Wrong addresses, wrong prices, wrong units of measure.
Handover points
Most failures happen where one system or team passes to another.
Documentation
An accurate delivery invoiced wrongly is still a failed order.
05 Where the number lives
The system, the record and the fields
| System of record | Key record | Fields you need |
|---|---|---|
| Order management, transport, quality and billing | Order joined to Delivery, Return, Claim and Invoice | on_time_flag, in_full_flag, damage_flag, invoice_error_flag |
This one metric spans four systems, which is exactly why it is rarely reported. It is the clearest case for a governed layer over the sources rather than a spreadsheet each month.
06 How it goes wrong
Three ways this metric misleads people
Reporting the components only
Every function shows a good number and the customer still complains.
Fix: Report the product of them, and let the components explain it.Leaving out invoice accuracy
A billing error is the failure most likely to delay payment.
Fix: Include it — it links service directly to DSO.Sampling instead of measuring
A monthly sample of 50 orders cannot find a 2% failure mode.
Fix: Measure every order; the data already exists in the four systems.08 Questions
Frequently asked
Why is the perfect order rate always lower than expected?
Because the components multiply. Four steps at 95% each give 81%, not 95%.
Which component should we fix first?
The one with the most orders failing, not the lowest percentage. A 2% failure on a high-volume step affects more customers than a 10% failure on a rare one.
One definition, everywhere it is used
SCIKIQ stores this metric once and serves it to every dashboard, board pack and agent that asks.