Nagham Elbreshy

Demand forecasting of fashion apparel products has to cope with seri-ous difficulties in order to get more accurate forecasts early enough to influence production decisions. Demand has to be anticipated at an early date due to long production lead times. Due to the absence of historical sales data for new prod-ucts, standard statistical forecasting methods, like e.g. regression, cannot easily be applied. This contribution applies selected methods in to improve forecasting cus-tomer demand of fashion or seasonal apparel products. We propose a model which uses retailer pre-orders of seasonal apparel articles before the start of their produc-tion to estimate later, additional post-orders of the same articles during the actual sales periods. This allows forecasting of total customer demand based on the pre-orders. The results show that under certain circumstances it is possible to find cor-relations between the pre-orders and post-orders of those articles, and thus better estimate total...