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Ll Bean Inc Item Forcasting and Inventory Management

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Ll Bean Inc Item Forcasting and Inventory Management
Executive Summary
Organizational Profile L.L. Bean Inc. was established in 1912 by Leon Leonwood Bean. He obtained a list of nonresident hunters to establish his first client list for his mail order business. His golden rule for the company is “Sell good merchandise at a reasonable profit, treat your customers like humans beings, and they’ll always come back for more.” In 1967 when L.L Bean died, his mail order business had grown to $4.75 Million in annual sales, the catalog was distributed to 600,000 customers, and employed 200 people. Since his grandson has taken over the company as of 2010 annual catalog and retail store sales are $1.44 billion. The company just in one year had 11 million customer contacts received and regular, year-round employment was 4,600 with winter holiday employment over 9,000 employees. ("L.L. bean 2011," 2011)
Critical Issues1
LL bean send out 4 major catalogs each year Spring summer fall and Christmas with average of 6000 items appearing in one or another of the catalogs. They have each item broken down into two categories: “new” is a recent time added to the company, “never out” is a more permanent item to the company. The way they forecast items now could use some improvement for example their own employee Barbara Hamaluk said “We really ought to have an intermediate level of forecasts at the Demand Center level, reconcile item forecasts with Demand Center forecasts, and the latter with book forecast.” That statement right there shows that even the buyers in the company know there is some improvement to be made.
The way they currently forecast for “new” and “never out” items is, they take the historical data from the previous year and compute historical forecast errors. Then they compute their commitment quantity and make the purchase for the next season.
Alternative 1
One way to improve their forecasting methods would be to incorporate a quantitative forecasting model. A quantitative forecasting model utilizes

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