Knowra Little's law Little's law Little's law states that the long-run average number of items in a stable system equals their average arrival rate multiplied by their average time in the system.
Queueing theory : The mathematical study of waiting lines and systems where items compete for service. Little's law is a general result within queueing theory, independent of specific service-time distributions.
Work in process : Items that have entered production but have not yet become finished goods. In manufacturing, Little's law connects work in process, throughput, and production lead time.
John Little : An American operations researcher who proved the queueing result now known as Little's law. His 1961 paper established the result in its familiar general form.
M/M/1 queue : A single-server queue with Poisson arrivals, exponential service times, and unlimited waiting capacity. This specific model yields detailed formulas beyond the general relationship Little's law supplies.
Arrival rate : The average number of items entering a system per unit of time. This rate is one factor in the law's product for average system population.
Throughput : The rate at which a system completes or processes items. In a stable process, throughput serves as the arrival-rate factor in the law.
Operations research : The discipline of using mathematical methods to support decisions and improve complex systems. Little's law emerged from analysis of operational systems such as queues and production lines.
Erlang C formula : A formula for the probability that an arriving customer must wait in a multi-server queue. Unlike Little's law, Erlang C depends on a specific queueing model and its assumptions.
Sojourn time : The elapsed time an item spends in a system, from entry to exit. The law uses mean time in the system, including both waiting and service.
Cycle time : The elapsed time required for an item to pass through a process or production stage. Production managers use it as the time-in-system measure paired with work in process.
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