Service performance

OTIF & Dock-to-Stock

A single OTIF percentage tells you that something is wrong but not what. Split into its two halves it becomes actionable — because late-but-complete and on-time-but-short have completely different causes and completely different fixes.

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Example inputs and performance bands are illustrative, not industry benchmarks. Confirm assumptions for your site. Method and limitations.

Your numbers
Outbound performance
Enter a positive number

Measured OTIF. If you don't track it directly, leave it and the calculator will estimate the range it must fall within.

Dock-to-stock (optional)
Result
OTIF
 
0%50%100%
On time
In full
Failing orders
Dock-to-stock
Longest stage
vs target
Where the inbound hours go

Why the two halves must stay separate

Separate the measures to guide investigation. Causes and ownership may overlap; verify them from order-level evidence.

FailureUsual causesWho fixes it
Late but completeDispatch scheduling, transport capacity, cut-off discipline, dock congestion, documentation delaysWarehouse operations and transport
On time but shortStock availability, inaccurate inventory, allocation rules, supplier shortagesPlanning and procurement

Reporting only the combined number guarantees that the monthly review produces a general exhortation to do better rather than a specific action. Split it, and each half lands on a desk that can actually do something.

OTIF is not on-time × in-full

The two failures are usually correlated — an order short on stock often waits for the shortage and then ships late as well. Multiplying the two percentages assumes they are independent and can misstate your true OTIF. The honest approach is to measure it directly, order by order. Where you cannot, this calculator shows the mathematical range your OTIF must fall inside, which is more useful than a false point estimate.

Dock-to-stock

Dock-to-stock is the time from a vehicle arriving to the goods being available to pick. It matters more than most warehouses treat it, because stock sitting in the receiving bay is invisible to the order system — you own it, you paid for it, and you still cannot sell it. A 48-hour dock-to-stock on a 21-day lead time is effectively a 10% extension of that lead time, and it feeds straight back into your safety stock requirement.

Most operations find the bottleneck is not unloading but the waiting between stages: goods sit after unloading waiting for QC, then after QC waiting for a put-away resource. The stage bars above show the split; the honest version includes the waiting, not just the touch time.

Common mistakes

  • Measuring on-time against your own revised date. If a promised date slips and the new date is met, that is not on time. Measure against the date first confirmed to the customer.
  • Counting the shipment date instead of the delivery date. Customers experience delivery. Dispatching on time and delivering late is a transport problem, not a success.
  • Averaging dock-to-stock across all receipts. One import container with a long QC hold distorts the mean badly. Track the median and the 90th percentile — the tail is what hurts.
  • Excluding waiting time. Adding up touch times gives a flattering number that nobody on the floor recognises. Measure arrival timestamp to stock-available timestamp.
  • Treating OTIF as a warehouse KPI. Agree shared responsibility based on the failure evidence; warehouse, planning and transport can all contribute.

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Turn this result into an action

Check the assumptions with your team, compare a second scenario, and keep the result in your monthly review.

Explore the matching workbooks · Methods and limitations