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Delivery Pipeline Flow Calculator

How long work takes to get through a delivery pipeline from how much is in progress and how fast it finishes — Little's law — and how much work in progress a target cycle time allows.

Little's law is three numbers and a division: items in progress equals throughput times cycle time.

Results update as you type
Results
Average cycle time (days)
21
In weeks
Items in progress per person
Maximum WIP for the target cycle time
Or throughput needed at the current WIP (per week)
Cycle time if WIP were halved (days)
Completed per person per week
Reading
Reviewed September 2026. Computing arithmetic: bytes, bits, seconds and probabilities do not change by country. Ofcom requires UK providers to quote a minimum guaranteed download speed.
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About delivery pipeline flow

How the delivery pipeline flow calculator works

Little's law is three numbers and a division: items in progress equals throughput times cycle time. Twenty-four open pull requests finishing at eight a week means each one takes three weeks, whatever anyone intended. The only ways to cut cycle time are to finish more or start less, and starting less is the one that is free.

It holds for any stable queue — tickets, deploys, code review — which is why it is the first thing to compute when a pipeline feels slow.

Formula: WIP = throughput × cycle time ⇒ cycle time = WIP / throughput

Worked examples

InputsAverage cycle time (days)Note
24 in progress, 8 a week21three weeks each
WIP capped7one week
A faster team7also one week

Frequently asked questions

What is Little's law?

For any stable system, the average number of items inside equals the arrival rate times the average time each spends. It needs no assumptions about the distribution — it is arithmetic, not statistics.

Why does limiting WIP speed things up?

Because cycle time is WIP over throughput. With throughput fixed by the team, the only lever that moves cycle time is how much is in flight.

Does it apply to software?

To any queue: pull requests awaiting review, tickets in progress, deploys waiting for a window. Kanban WIP limits are Little's law applied.

What if throughput is not stable?

Use averages over a period long enough to smooth it — a month or a quarter. The law holds on average even when individual weeks vary.

How many items per person is reasonable?

One or two. Beyond three, context-switching cuts throughput as well as stretching cycle time, and the law says both get worse together.

Where these figures come from

Last checked: September 2026. Units follow the SI decimal convention (IEC 80000-13 defines the binary alternatives); network and security figures cite the defining standard.