A hybrid sales forecasting system based on clustering and decision trees

This work proposes a forecasting system, based on clustering and classification tools, which performs mid-term forecasting of the textile sales, and evaluates the models using real data from an important French textile distributor.

Abstract

Competition and globalization imply a very accurate production and sourcing management of the Textile–Apparel–Distribution network actors. A sales forecasting system is required to respond to the versatile textile market and the needs of the distributors. Nowadays, due to the specific constraints of the textile sales (numerous and new items, short life time), existing forecasting models are generally unsuitable or unusable. We propose a forecasting system, based on clustering and classification tools, which performs mid-term forecasting. Performances of our models are evaluated using real data from an important French textile distributor.