“L.L. Bean, Inc.” Case Study Report
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Case Assumptions & Observations:
In 1990, L.L. Bean received 87% of its revenue from customers who purchased merchandise through their mail order catalogs. The remaining 13% of revenue was realized through their single company store in Freeport, Maine.
They print twenty-two catalogs (or “books”) with four primary seasonal catalogs: spring, summer, fall, and Christmas. Additionally there are various specialty catalogs: Spring Weekend, Summer Camp, Fly Fishing, etc as well as a smaller “prospect” version. The catalogs have a “gestation period” of about nine months that involves creation, planning, and forecasting of each item for each catalog.
They shipped 114 million pieces that reached six million active customers with 80% of the customers ordering via the telephone.
L.L. Bean was rated number one in customer satisfaction of mail-order companies in 1991 by consumer reports.
The product line is divided in a hierarchical structure progressing from the highest level of aggregation with “Merchandise Groups”, then “Demand Centers”, to “Item Sequences”, and finally “Individual Items” distinguished by color and categorized by season. “About 6,000 items appeared in one or another of the catalogs in the course of a year.” Also items were characterized as either “new” which means they have never carried this item or “never out” which included more permanent items with established historical sales data.
At the item level, forecasts have to be issued and ultimately purchase commitments have to be made. Problem: the large number of errors (either over stock or under stock) at the item level is disturbing to top management. Estimated costs of lost sales and backorders is about $11 million dollars, and liquidation costs associated with having too much of the wrong inventory is an additional $10 million totaling $21 million or 4% of catalog sales.
The item forecast process involves a group of four to five individuals that include inventory buyers and product people and was typically accomplished by:
Rank various items in terms of expected dollar sales
Assign actual dollar values according to item ranking on excel spreadsheet
This could result in discussions, arguments, and complaints among the group members
Evaluate forecast for each book and make adjustments: “check it for reality, does it feel good, does it make sense”
This is done book-by-book, item-by-item resulting in the item level forecast of each item.
If a new item is added a judgment of what the incremental demand might or might not be and those items are adjusted accordingly.
The forecast is “frozen” and submitted to the inventory managers.
“The sum of the item forecasts for a catalog was often at variance with the dollar target for that book.” And this was usually on the high side and they would try to reduce forecasts on certain items. Or reduce the entire order by a percentage across the board.
Usually they only have a “one-shot” opportunity to place an order with their production vendors with a production lead time of eight to twelve weeks to receive the finished product ready for that selling season.
The production commitments were generally NOT equal in size to the forecast and were determined in two steps:
Historical forecast errors expressed in the ratio of (Actual Demand / Forecast Demand) are calculated for each item of the previous year. The frequency distribution of these errors was compiled across items and used as a probability distribution for future forecast errors.
Balanced each items contribution margin (profit) against its liquidation cost