In November, Jeff Hastings of the fashion skiwear manufacturer Hastings Sportswear, Inc., faces the task of...

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In November, Jeff Hastings of the fashion skiwear manufacturer Hastings Sportswear, Inc., faces the task of committing to specific production quantities for each skiwear item the company will offer in the coming year's line. Commitments are needed immediately, in order to reserve space in production facilities located throughout Asia. Actual demand for these products will not become known for at least six months. In fact, demand for the current year's line is only beginning to become available. In an initial experiment, Jeff has asked six of his most knowledgeable people to make forecasts of demand for the various models of parkas. Forecasts for one product are given in the table below, along with the average and standard deviation of the forecasts. Experience suggests that the actual standard deviation in demand is roughly twice that of the standard deviation in the forecasts. Forecaster 1 Forecaster 2 Forecaster 3 Forecaster 4 Forecaster 5 Forecaster 6 Average Standard deviation 900 units 1,000 900 1,300 800 1,200 1,017 194 Production costs for a typical parka run about 75 percent of the wholesale price, which in this case is $110. Unsold parkas can be sold at salvage for around 8 percent of the wholesale price. What quantity should Jeff order for this model of parka? This assignment is based on the Hastings Sportswear case. Jeff Hastings would like to construct a spreadsheet that will calculate the company's pre-tax profit for any combination of order quantity and actual demand at the end of the selling season. For now, just ignore the forecasts and the demand uncertainty. The spreadsheet should use the demand as an input parameter, but it should correctly calculate the profit for every possible pair of order quantity and demand values. 1. Draw an influence chart that shows all of the relationships that must be modeled in this spreadsheet. 2. Now, develop a spreadsheet model to compute the pre-tax profit for any specific values of order quantity and demand. Again, don't try to account for the demand uncertainty in this problem. We'll do that later in the course. 3. Use your spreadsheet to answer the following questions. a. What is the outcome for this problem if Jeff orders 1,000 parkas and the demand turns out to be 1,200? b. What is the outcome for this problem if Jeff orders 1,000 parkas and the demand turns out to be 800? In November, Jeff Hastings of the fashion skiwear manufacturer Hastings Sportswear, Inc., faces the task of committing to specific production quantities for each skiwear item the company will offer in the coming year's line. Commitments are needed immediately, in order to reserve space in production facilities located throughout Asia. Actual demand for these products will not become known for at least six months. In fact, demand for the current year's line is only beginning to become available. In an initial experiment, Jeff has asked six of his most knowledgeable people to make forecasts of demand for the various models of parkas. Forecasts for one product are given in the table below, along with the average and standard deviation of the forecasts. Experience suggests that the actual standard deviation in demand is roughly twice that of the standard deviation in the forecasts. Forecaster 1 Forecaster 2 Forecaster 3 Forecaster 4 Forecaster 5 Forecaster 6 Average Standard deviation 900 units 1,000 900 1,300 800 1,200 1,017 194 Production costs for a typical parka run about 75 percent of the wholesale price, which in this case is $110. Unsold parkas can be sold at salvage for around 8 percent of the wholesale price. What quantity should Jeff order for this model of parka? This assignment is based on the Hastings Sportswear case. Jeff Hastings would like to construct a spreadsheet that will calculate the company's pre-tax profit for any combination of order quantity and actual demand at the end of the selling season. For now, just ignore the forecasts and the demand uncertainty. The spreadsheet should use the demand as an input parameter, but it should correctly calculate the profit for every possible pair of order quantity and demand values. 1. Draw an influence chart that shows all of the relationships that must be modeled in this spreadsheet. 2. Now, develop a spreadsheet model to compute the pre-tax profit for any specific values of order quantity and demand. Again, don't try to account for the demand uncertainty in this problem. We'll do that later in the course. 3. Use your spreadsheet to answer the following questions. a. What is the outcome for this problem if Jeff orders 1,000 parkas and the demand turns out to be 1,200? b. What is the outcome for this problem if Jeff orders 1,000 parkas and the demand turns out to be 800?

Answer rating: 100% (QA)

To determine the optimal quantity of parkas to order Jeff can use the newsvendor model The goal is to minimize the expected cost which includes the co... View the full answer