For the coming season , SuperFun plans to introduce a new product called Weather Teddy . This variation of a talking teddy bear is made by a company in Taiwan . When a child presses Teddy ’ s hand , the bear begins to talk . A built-in barometer selects one of five responses predicting the weather conditions . The responses range from “ It looks to be a very nice day ! Have fun ” to “ I think it may rain today . Don ’ t forget your umbrella .” Tests with the product show even though it is not a perfect weather predictor , its predictions are surprisingly good . Several of SuperFun ’ s managers claimed Teddy gave predictions of the weather that were as good as many local television weather forecasters .
As with other products , SuperFun faces the decision of how many Weather Teddy units to order for the coming holiday season . Members of the management team suggested order quantities of 15,000 , 18,000 , 24,000 , or 28,000 units . The wide range of order quantities suggested indicates considerable disagreement concerning the market potential .
Having a sound background in statistics and business , you are required to perform statistical analysis and the profit projections which is typically done by the product management group . You want to provide management with an analysis of the stock-out probabilities for various order quantities , an estimate of the profit potential , and to help make an order quantity recommendation .
SuperFun expects to sell Weather Teddy for $ 24 based on a cost of $ 16 per unit . If inventory remains after the holiday season , SuperFun will sell all surplus inventories for $ 5 per unit . After reviewing the sales history of similar products , SuperFun ’ s senior sales forecaster predicted an expected demand of 20,000 units with a 95 % probability that demand would be between 10,000 units and 30,000 units .