Draft reference — content review pending
Perfect Order Rate
The percentage of eligible completed orders meeting every defined completeness, accuracy, damage, documentation, and timeliness condition.
Business question
How often are eligible orders completed without any defined fulfillment failure?
Formula
Perfect order rate = eligible orders meeting every completeness, accuracy, damage, documentation, and timeliness condition ÷ eligible completed orders × 100.
Calculation notes
Define perfect-order conditions before measuring: complete quantities, correct items, no documented damage, required documents, and delivery within the committed window. Keep the order basis distinct from line and unit measures.
Edge-case guidance
Document partial shipments, approved substitutions, customer-caused changes, disputed damage, missing proof of delivery, and revised dates. Do not silently remove failures from the cohort.
Required data
| Input | Type | Status | Available source hints |
|---|---|---|---|
| Eligible perfect ordersCompleted eligible orders satisfying every documented perfect-order condition. | Number | Required | Excel · Google Sheets · Manual records |
| Eligible completed ordersCompleted orders included after applying the agreed cohort and completion rules. | Number | Required | Excel · Google Sheets · Manual records |
Interpretation
Use this composite service measure only after documenting each condition. One missed condition makes the order non-perfect, while component rates explain the reason.
Caution
A composite rate can hide which condition failed. Changing the definition of a perfect order breaks comparability, and excluding partial or disputed orders can overstate performance.
Implementation recommendation
Publish the condition checklist and reconcile it with warehouse, transport, documentation, and customer-service records before reporting.
Target guidance
Set the first target for perfect order rate from comparable internal history, then adjust it for assortment, service commitments, seasonality, capacity, and data quality. Review the direction with the accountable owner and consider this trade-off: improving the composite score by relaxing conditions damages its meaning and may conceal specific service failures.