Queueing theory: The science of waiting in line

The simplest models in queueing theory have nice closed-form solutions. One of the insights from basic queueing theory is that variability in arrival and service times matters a great deal. This is unlike revenue, for example, where you can estimate total revenue simply by multiplying the estimated number of customers by the estimated average revenue per customer. But if there’s not much slack, and there’s the slightest bit of variability in arrival or service times, long lines will form. In that example, going from one server to two doesn’t just cut the waiting time in half, but reduces it by a couple orders of magnitude.

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