Reducing the Cost of Demand Uncertainty Through Accurate Response to Early Sales

TLDR

Fashion products suffer high losses from stockouts and obsolescence because long lead times and concentrated selling seasons force early production commitments before demand is known, but Quick Response shortens lead times to allow more production to be scheduled after initial demand. The study models and analyzes Quick Response decisions and proposes a method for estimating demand probability distributions. The authors develop a model and estimation method for demand probability distributions used in Quick Response decision analysis. In a major fashion skiwear firm, the procedures reduced costs relative to the informal system, boosting profits by 60%, and, compared to no response, cut costs enough to roughly quadruple profits.

Abstract

Traditionally, fashion products have incurred high losses due to stockouts and inventory obsolence because long lead times coupled with a concentrated selling season force all or at least most production to be committed before demand information is available. Under a Quick Response system, lead times are shortened sufficiently to allow a greater portion of production to be scheduled in response to initial demand. We model and analyze the decisions required under Quick Response and give a method for estimating the demand probability distributions needed in our model. We applied these procedures with a major fashion skiwear firm and found that cost relative to the current informal response system was reduced by enough to increase profits by 60%. Relative to the cost that would have been incurred if no response were used, optimized response reduces cost by enough to roughly quadruple profits.