Forecasting in the fashion industry: a model for minimising supply-chain costs

Abstract

Fashion is replaced every season and collections change rapidly, depending on certain events. There are only a few weeks between the fashion shows and the collections reaching their sale points. As the pattern of demand is seasonal, new items must be produced every season. Additionally, colours and patterns change rapidly, creating a need for producers and consumers to continually remain updated. This research study proposes a forecasting model that enhances the accuracy of fashion trend forecasting in the context of multiple variants of colour clothing. The model aims to maximise the firms’ profits, while minimising forecasting errors and reducing costs that result from excess production or, alternatively, from the loss of potential revenues due to low demand. In the proposed model, the expected profit was notably higher when the customers’ readiness to compromise was low or when only one type of product was in stock.

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