Order Statistics Case Study
This assignment has two cases. The first case is on expansion strategy. Managers constantly have to make decisions under uncertainty. This assignment gives students an opportunity to use the mean and standard deviation of probability distributions to make a decision on expansion strategy. The second case is on determining at which point a manager should re-order a printer so he or she doesn’t run out-of-stock. The second case uses normal distribution. The first case demonstrates application of statistics in finance and the second case demonstrates application of statistics in operations management.
Case Study – Bell Computer Company
The Bell Computer Company is considering a plant expansion enabling the company to begin production of a new computer product. You have obtained your MBA from the University of Phoenix and, as a vice-president, you must determine whether to make the expansion a medium- or large- scale project. The demand for the new product involves an uncertainty, which for planning purposes may be low demand, medium demand, or high demand. The probability estimates for the demands are 0.20, 0.50, and 0.30, respectively.
Order Statistics Case Study
Case Study – Kyle Bits and Bytes
Kyle Bits and Bytes, a retailer of computing products sells a variety of computer-related products. One of Kyle’s most popular products is an HP laser printer. The average weekly demand is 200 units. Lead time (lead time is defined as the amount of time between when the order is placed and when it is delivered) for a new order from the manufacturer to arrive is one week.
If the demand for printers were constant, the retailer would re-order when there were exactly 200 printers in inventory. However, Kyle learned demand is a random variable in his Operations Management class. An analysis of previous weeks reveals the weekly demand standard deviation is 30. Kyle knows if a customer wants to buy an HP laser printer but he has none available, he will lose that sale, plus possibly additional sales. He wants the probability of running short (stock-out) in any week to be no more than 6%.
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