How many customers are in the shop, on average? You don’t need to count heads — just multiply how fast they arrive by how long each one stays. That’s Little’s Law, and it holds for any stable queue whatsoever, no matter how chaotic the arrivals. Slide the arrival rate and watch the crowd track the product.
Little’s Law: L = λ·W — the long-run average number of items in a system equals the average arrival rate times the average time each spends there. It needs no assumption about the arrival pattern or service order; it is a conservation law of flow. The instrument runs a real discrete-event queue and measures L, λ, and W independently. A fail-loud self-check throws unless the measured L matches λ·W within a few percent — the identity that lets you infer any one of the three from the other two.
Measured over a finite run, so L and W carry sampling noise (they converge as the run lengthens); the LAW itself is exact for any stable system. A single-server queue here; it holds for whole networks too.