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The bulk of products is produced in South East Asia, and hence the lead time to Western retailers is long. The typical lead time from fabric manufacturers is 3 months (Gutgeld and Beyer, 1995). The speci?c mail order company that we study faces lead times of 6-14 weeks. Long lead times dictated by powerful suppliers and strong competition fromother retailers trying to secure enough production capacity force retailers to commit to initial order quantities long, usually several months, before the start of the selling season. We remark that there are a few well-known apparel/fashion retailers like Zara and Hennes & Mauritz that have deviating strategies based on local manufacturing. However, for the large majority of apparel retailers, who have a low-cost focus and often sell private label products, the situation is as we described.
So, formost products that an apparel retailer sells in any season, a demand forecast is needed well before the start of the season, when no historic demand data is available. An apparel retailer's success hinges to a large extent on the accuracy of those preseason forecasts on which the initial orders are based. These initial orders comprise the bulk of the total volume ordered (Fisher and Raman, 1999).
Additional in-season replenishment opportunities, if available, are essentially emergency replenishment opportunities and only serve to prevent shortages resulting frompossible initial underestimation of demand. We refer interested readers to Mostard and Teunter (2006) for a further discussion and analysis of inventory control issues. In this paper, the focus is on forecasting.
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This method simply calculates the average of a number of expert estimates. Let E denote the number of experts, and mn,e denote the forecast of expert e, e =1, ... ,E, for SKU n 2N.
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