L.L. Bean Case

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Supply Chain Management L. L. Bean Case Questions 1. How does L.L. Bean use past demand data and a specific item forecast to decide how many units of that item to stock? L.L. Bean uses historical forecast errors to decide how many units of an item to stock. These are expressed as “A/F’ ratios, which is the ratio of actual demand to forecast demand, and they are computed for each item. If we get a ratio of 0.9, it means that L.L. Bean only sold 90% of the amount it had forecasted it would sell. Further, L.L. Bean computes the frequency distribution of these errors across items. Therefore, the use of past data allows L.L. Bean to obtain a probability distribution for the future unrealized forecast errors. For example, if 50% of the errors for a specific item category, i.e. the A/F ratios, fell between 0.8 and 1.2 in the past years, then the company assumes that with a probability of 0.5, the error for an item belonging to this specific category will fall between 0.8 and 1.2 this coming year. For a new item that has not any past data, there is a part of judgement from the people in charge of forecast. They will look at the demand generated by this new item: if the demand is incremental then they have to approximate new figures, but if it is not then they have to take in account of much demand it will steal from other items. 2. What item costs and revenues are relevant to the decision of how many units of that item to stock? The item costs relevant to the decision of how many units of that item to stock are the liquidation costs if the item has not been demanded. The revenues related to this same decision are the contribution margins of that item if it has been demanded. The two are used in a way that balances these costs and revenues. To obtain the contribution margin, L.L. Bean computes: item retail price if demanded – item cost To obtain the

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