Exploring the potential of retail customer demand analytics for supply decision support
Résumé
In this article, a demand analytics decision support system is presented, which is an integration, visualization, mapping and assessment system using direct-from-customer product trial demand data. It allows analysts and decision-makers to explore efficiently large quantities of data from different information systems about the products and their trial demand within a supply network based on forward relationships. The system allows a visual mining and representation of relations existing between multiple products (present and past) as well as forecasts according to a customizable time window. These representations are done through multi-dimensional summarizing diagrams. These diagrams take the form of relationships graphs, chronological graphs, dashboards, Pareto and forecasts interfaces. The data that feeds these diagrams come from product trial demand and sales recorded directly in the information systems of the various sales points. The article presents a prototype developed in our laboratories and tested on a large scale case in the retailing of fashion shoes and articles.