Little's Law explains the relationship between work-in-process, throughput, and lead time, giving teams a simple way to understand flow and queue behavior.
Definition
Little's Law states that average work-in-process equals average throughput rate multiplied by average lead time. It is often written as WIP = Throughput x Lead Time. Rearranged, Lead Time = WIP / Throughput.
For improvement teams, the message is direct: if throughput stays constant, more WIP creates longer lead time. Reducing WIP and improving flow often reduces waiting dramatically.
History
Little's Law is named for John Little, who proved the relationship in queueing theory. It became widely used in operations, Lean, supply chain, service systems, software flow, and factory physics.
When to Use
Use Little's Law when analyzing queues, lead time, WIP, cycle time, throughput, service backlogs, production flow, and knowledge work. It is useful for explaining why excess work in the system slows delivery.
The law assumes a stable system boundary and consistent averages. Be careful when demand, arrivals, or throughput are highly unstable.
Step-by-Step
- Define the system boundary.
- Measure average WIP inside the boundary.
- Measure average throughput over the same period.
- Calculate lead time or validate observed lead time.
- Identify where WIP accumulates.
- Reduce queue size, batch size, or blockers.
- Monitor whether lead time improves.
- Use visual controls to prevent WIP creep.
Examples
- Office queue: 100 cases in WIP and 20 cases completed per day imply about 5 days lead time.
- Production: Reducing WIP between operations lowers waiting time.
- Software: Limiting active work improves delivery predictability.
Common Pitfalls
- Mixing time periods for WIP and throughput.
- Using unstable system data without caution.
- Confusing cycle time and lead time.
- Ignoring blocked or rework items.
- Reducing WIP without protecting constraints.
- No visual management for WIP limits.