Apply Little's Law to predict how long work will spend in your process — so you can manage queues, set realistic delivery promises and target WIP reductions.
Enter your current WIP and throughput on the left, then press Calculate.
85 open tickets, 25 closed per day. Enter the lab and use Little's Law to see exactly how long each customer is waiting.
Use the calculator above to apply Little’s Law and predict how long work will sit in your process. Lead time is the end-to-end time from when a unit enters a value stream to when it leaves — including every queue, wait and hand-off. It is the metric customers actually feel and the one most exposed to WIP.
Lead time is the total elapsed time for one unit of work to move through a process or value stream, from start to finish. Unlike cycle time, which measures one step, lead time includes all the queues and waits between steps — which is usually where most of the time hides.
Little’s Law: Lead Time = Work In Process ÷ Throughput. WIP is the number of units inside the process at any moment. Throughput is the rate at which finished units exit. The relationship is mathematical, not assumed, and holds for any stable process — manufacturing, software, services or healthcare.
A claims team has 100 cases in progress and closes 20 cases per day. Lead Time = 100 ÷ 20 = 5 days. Customers wait an average of 5 days for a decision — regardless of how fast any single case is actually worked.
If the team caps WIP at 40 cases (same throughput), lead time drops to 2 days. The work isn’t done faster — the queue is simply shorter. That is why WIP limits are the single most powerful Lean lever for lead-time reduction.
Lead time is what customers experience. Reducing it improves cash flow, lowers inventory, reduces obsolescence risk, and frees capacity that was previously locked up in WIP.
Use Little’s Law any time you need to predict delivery promises, set WIP limits, justify a kanban system, or estimate the impact of a queue-reduction initiative.
Lead time is the headline metric of flow. Throughput sets the rate; WIP sets the queue; lead time is the consequence. Cut WIP without changing throughput and lead time falls proportionally.
Measure WIP and throughput, then set a clear WIP limit. Re-measure lead time after each round of WIP reduction so the cause-and-effect is visible. Pair the change with explicit kanban signals so the WIP limit holds under pressure.
Combine Little’s Law with value stream mapping and visual WIP control. The resources below help convert the calculation into a working pull system.
Lead time is the total elapsed time from when a unit enters a process to when it exits, including all queues, hand-offs and waits. It is what customers experience as delivery time.
Little’s Law states that average lead time equals average work-in-process divided by average throughput. It holds mathematically for any stable system — manufacturing, software, services or healthcare.
Cycle time measures one unit through one process step. Lead time measures one unit through the whole value stream including all queues. Lead time is usually many times longer than total cycle time.
The most powerful lever is reducing WIP — fewer items in the queue means a shorter wait. Other levers include smaller batch sizes, reducing setup times, and removing bottlenecks. Speeding up individual tasks rarely moves lead time much.
Yes. WIP becomes the number of open tickets; throughput becomes the average number of tickets completed per week or sprint. Reducing WIP through kanban limits is the most reliable way to shorten delivery lead time.
Want to understand how lead time analysis drives value stream improvement? The Lean Associate course covers this in full.
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