Cycle time—the minimum amount of time necessary for a task or series of tasks to be completed—is usually associated with manufacturing systems and depends on whether tasks are accomplished in a series or as parallel units. For example, in a textile factory production of a shirt requires cutting, sewing, and packaging. Assuming cutting requires 3 minutes per shirt, sewing 12 minutes per shirt and packaging 5 minutes per shirt, if the work is being done by one person (in a series of steps) then the minimum cycle time is 20 minutes. If three people are working in parallel, each performing one task, the minimum cycle time is 12 minutes, the time it takes to do the longest task. PRODUCTION managers use the concept of cycle time to estimate the minimum amount of time needed to produce PRODUCTs, the maximum output in a fixed time period, and the coordination and allocation of resources to maximize efficiency. In the example above, the minimum time depends on whether the operations are conducted simultaneously or not. If it takes 12 minutes for a team of workers to make a shirt working in parallel, then in 8 hours the maximum number of shirts that could be produced is 8 hours ÷ 12 minutes = 480 minutes ÷ 12 = 40 shirts. But to maximize output, a manager would have to shift workers from one task to another. At 3 minutes per shirt, it will take only 120 minutes to cut the material for 40 shirts and only 200 minutes to package the 40 shirts. In order to maximize output with a given level of workers and machines, production managers allocate machines and workers to fully utilize resources in production. In materials management, cycle time is defined as the time it takes from when materials enter the production process to when they leave the system. Similarly, one retail company sets as its goal to never have products in their distribution center for more than 24 hours. Recognizing that customers do not buy products from distribution centers, minimizing the time products are in storage increases the availability of products on the company’s retail shelves. Reducing cycle time increases productivity. In complex production systems, statistical models are used to minimize variation in production and reduce cycle times.