Little's Law Calculator
Halve the work in progress and the lead time halves with it.
Work out Little's Law. Halve the work in progress and the lead time halves with it. Puts the estimate in your hands, not in a constant.
Hands-on time, excluding any waiting
Average lead time
28 days
14.3% flow efficiency — 86% of the time is queueing
Little's Law is an identity rather than a theory — work in progress equals throughput times lead time, and it holds for any stable system regardless of what the work is. That is what makes it useful: lead time cannot be reduced without either raising throughput or lowering work in progress, and only one of those is free. Halving the number of things in progress halves the lead time immediately, with no change to how fast anyone works. Flow efficiency is the uncomfortable companion figure. Most knowledge work sits between 5% and 25%, meaning the overwhelming majority of an item's lead time is spent waiting rather than being worked on — which is why doing fewer things at once outperforms working faster.
How the Little's Law Calculator works
Work in progress, throughput and lead time — enter any two and the third follows, with flow efficiency alongside. Little's Law is an identity rather than a theory, which is what makes it useful: lead time cannot fall unless throughput rises or work in progress drops.
Also known as: littles law · little's law · lead time · cycle time · wip · work in progress · wip limit · flow efficiency · throughput · kanban · queue time · takt time
An identity, not a theory
Work in progress equals throughput times lead time. It is not a model of how work behaves — it is arithmetic that holds for any stable queueing system regardless of what the work is, how it is prioritised, or who does it.
That is precisely what makes it useful. Lead time cannot be reduced without either raising throughput or lowering work in progress, and there is no third option however the process is rearranged.
Raising throughput means hiring, automating or removing work. Lowering work in progress means starting fewer things. Only one of those is free, and it takes effect immediately: halve the number of items in progress and the average lead time halves with it.
Flow efficiency, and the uncomfortable number
Flow efficiency is the share of an item's lead time actually spent being worked on. Most knowledge work measures somewhere between 5% and 25%.
Which means the overwhelming majority of the time between request and delivery is queueing — waiting for review, for a dependency, for someone to be free. Working faster attacks the small share; reducing queues attacks the large one.
It also explains why teams feel busy and slow simultaneously. Everyone having something to work on is what creates the queues, because it means nothing is ever waiting for a person and everything is waiting for a handoff.
Why WIP limits work, and why they feel wrong
A work-in-progress limit caps lead time directly, because the law guarantees the relationship. It is one of the few process interventions with a mathematical justification rather than an anecdotal one.
It also surfaces blockages that were previously invisible. When someone cannot start something new, the thing blocking them becomes everybody's problem instead of being routed around.
The objection is that people will sit idle, and sometimes they will. Idle time is visible and cheap; work sitting in a queue is invisible and expensive. Optimising for everyone being busy is what produced the queue in the first place.
Where to go next
The Little's Law question rarely arrives on its own. These are the ones that usually come with it:
- Sprint Velocity Calculator — A range is the honest form of a software estimate.
- Team Capacity Calculator — Contracted hours are not available hours.
- Deployment Frequency Calculator — The four metrics do not trade off — batch size explains them.
- Ring Size Calculator — Finger measurement to US, UK, EU and Japanese sizes.
Frequently asked questions
What is Little's Law?
Work in progress equals throughput times lead time. It holds for any stable queueing system regardless of what the work is, which is why it applies equally to a factory, a support queue and a software backlog.
How do I reduce lead time?
Raise throughput or lower work in progress, and only one of those is free. Halving the number of items in progress halves the average lead time immediately, with no change to how fast anyone works.
What is flow efficiency?
The share of an item's lead time actually spent being worked on. Most knowledge work sits between 5% and 25%, meaning the overwhelming majority of the elapsed time is queueing rather than working.
Why do WIP limits work?
Because Little's Law guarantees it. Capping work in progress caps lead time directly, and it also surfaces the blockages that were previously hidden behind everyone having something else to switch to.
Does the law require anything to be true?
Stability over the observation period — arrivals roughly matching departures. It does not assume anything about the distribution of work or the order it is done in, which is why it survives contact with reality so well.
What is the difference between lead time and cycle time?
Lead time usually runs from request to delivery; cycle time from when work started. The gap between them is queueing before work began, and it is often the larger of the two.
Does Little's Law apply to software teams?
It applies to any stable queueing system, and a team with a backlog is one. It is why work-in-progress limits reduce lead time reliably rather than occasionally.
Why is flow efficiency so low in knowledge work?
Because items spend most of their life waiting — for review, for a dependency, for someone to be free. Typical figures of 5% to 25% mean the vast majority of elapsed time is queueing, not working.
How do I set a WIP limit?
Start near the number of people who can work independently and lower it until blockages surface. A limit that never binds is not doing anything; one that binds constantly is too tight.
Does reducing WIP mean people sit idle?
Sometimes, briefly, and that is the point. Idle time is visible and cheap; work sitting in a queue is invisible and expensive. Optimising for everyone being busy is what created the queue.
What breaks the law's assumptions?
Sustained instability — arrivals persistently exceeding departures. During a build-up the observed averages lag reality, which is why it should be applied over a period long enough to be stable.
Can I use it to promise a delivery date?
For an item entering a stable system, the average lead time is a reasonable expectation and the distribution matters more. Quoting the 85th percentile of observed lead times is a far safer promise than the mean.
Put this calculator on your own site
Free to use, on any site, commercial or not. Paste this where you want it to appear. It is a plain iframe, so it works in WordPress, Squarespace, Wix, Webflow, Ghost and anything else that accepts HTML.
<iframe src="https://www.thecalclibrary.com/embed/littles-law-calculator" width="100%" height="640" style="border:1px solid #e2e8f0;border-radius:12px" loading="lazy" title="Little's Law Calculator"></iframe>
<p style="font:13px/1.5 system-ui,sans-serif;margin:6px 0 0;color:#64748b">Powered by <a href="https://www.thecalclibrary.com/littles-law-calculator" style="color:#64748b">Little's Law Calculator</a> from The Calc Library</p>The only condition is that the credit line below the frame stays in place. That one line is what pays for the tool being free — it is how anyone else finds it.
Related calculators
Sprint Velocity Calculator
A range is the honest form of a software estimate.
OpenTeam Capacity Calculator
Contracted hours are not available hours.
OpenDeployment Frequency Calculator
The four metrics do not trade off — batch size explains them.
OpenRing Size Calculator
Finger measurement to US, UK, EU and Japanese sizes.
Open