Sport Obermeyer currently has a problem with matching supply with demand. Right as you begin to read the case-study, you notice how far in advance they must predict what styles are going to be popular and how much to produce. The difficult part is, they must do this almost two years in advance and hope their forecasting is close enough to what the actual demand ends up being. To make matters even more complicated, as Sport Obermeyer is forecasting for the next season, little data is available about how the current season's clothing line is doing. So the possibility exists that an incorrect forecast could be costly in both the current season sales and the future season projected sales.
Wally has two options available: having one production run for all the styles, or having two productions runs split between the styles (known as "Quick Response with Reactive Capacity." By using the Buying Committee's forecast for the sample of 10 women's parkas, we can come up with an optimal quantity to produce of each style. We can further take the data and find out what the mismatch costs are for each style. To clarify, mismatch costs are the sum of the lost profits due to lost sales and total losses due to leftover inventory.
Looking at the first option, Sport Obermeyer must figure out what styles will be popular two years later and how much of each style to produce. After they submit off their desired production runs, they attend the Las Vegas trade show to receive feedback on those styles just submitted. This is a large cause for leftover inventory and lost sales. One way to look at this is as if Sport Obermeyer submitting a heavily-graded homework assignment, then after the submission, seeking professional feedback. But even with that feedback, they can do little to change ...