LL Bean Case Study
Case Report: L.L. Bean, Inc.
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 different type of calculation to determine the number of units of a particular item it should stock (new item or never out item). First we detect a frozen demand forecast for the item in the upcoming season. This figure is a result of an agreement between product people, merchandising, design and inventory specialists. Then, we analyze the historical forecast errors (named A/F ratios) and the frequency distribution of these errors for each individual item by using the historical demand and forecast data. Once the historical forecast errors is determined, we define future forecast errors by using frequency distribution of past forecast errors as probability distribution. Finally we find the service level based on a profit margin calculation: determine by balancing contribution margin if demanded against its liquidation cost if not demanded.
We can notice that for new items it is more complicated to have good prevision because we know very little about them.
2. What item costs and revenues are relevant to the decision of how many units of that item to stock?
Principally, L.L. Bean will need 3 types of data to decide how many units of an item to stock. First, they need to know the buying cost of the item. Then, they need the selling price of the item. With these 2 figures, they can calculate the profit margin and the costs of understocking. The 3rd figure they need is the liquidation cost of an item. With the liquidation cost, they can calculate the costs of overstocking.
With all these data, we can decide the final amount of items to stock by comparing the understocking costs and overstocking costs.
3. What information should Scott Sklar have available to help him arrive at a demand forecast for a particular style of men’s shirt that is a new catalog item?
Scott Sklar should have data about
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 different type of calculation to determine the number of units of a particular item it should stock (new item or never out item). First we detect a frozen demand forecast for the item in the upcoming season. This figure is a result of an agreement between product people, merchandising, design and inventory specialists. Then, we analyze the historical forecast errors (named A/F ratios) and the frequency distribution of these errors for each individual item by using the historical demand and forecast data. Once the historical forecast errors is determined, we define future forecast errors by using frequency distribution of past forecast errors as probability distribution. Finally we find the service level based on a profit margin calculation: determine by balancing contribution margin if demanded against its liquidation cost if not demanded.
We can notice that for new items it is more complicated to have good prevision because we know very little about them.
2. What item costs and revenues are relevant to the decision of how many units of that item to stock?
Principally, L.L. Bean will need 3 types of data to decide how many units of an item to stock. First, they need to know the buying cost of the item. Then, they need the selling price of the item. With these 2 figures, they can calculate the profit margin and the costs of understocking. The 3rd figure they need is the liquidation cost of an item. With the liquidation cost, they can calculate the costs of overstocking.
With all these data, we can decide the final amount of items to stock by comparing the understocking costs and overstocking costs.
3. What information should Scott Sklar have available to help him arrive at a demand forecast for a particular style of men’s shirt that is a new catalog item?
Scott Sklar should have data about