An obvious answer is to allow an organisation to decide how many people they should employ for serving customers. That may be tellers in a bank or post office, or telephone operators at a call centre.
Obviously, employing too many is a waste of the organisations resource. Unfortunately, most organisations do not realise that not employing enough, so that the customers are left waiting (or left on hold and forced to listen to some revolting "music") does not do much for their image. But hey, they saved some money, so they're good!
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All the time. Statistic is based on the application of probability theory!
Probability theory and distributive theory.
Traffic intensity describes the mean number of simultaneous call in progress. A.K. Erlang (1878-1929) was the pioneer of traffic theory, which he applied to studytelephone systems.
It is a study of queues. A typical example is one that may be found in banks. Customers arrive at intervals that are determined by some probability distribution function. There are then two possible queueing scenarios: one in which there is a single queue which feeds into several cashiers or a system where there are multiple queues: one for each cashier. When a customer reaches a cashier, it takes the cashier an amount of time to serve him or her. This time also has a probability distribution function - different from the one governing arrival times. The theory studies the optimum queueing scenario, time spent by customers in queues rather than being served, the optimum number of cashiers. The bank must find the best trade-off between the cost of employing more cashiers and the irritation of their customers.
u mean formula?