Decision making for initial shipment ratio on fashion products

Abstract

Supply chain management (SCM) of fashion industry have started to receive attention, after big fashion companies used their own database servers to improve their distribution processes of vendor managed inventory (VMI) systems. Our research started from “KAIST and Kolon Sport (K/S) Big Data & Business Analytics Project”, whose objective is to improve the real distribution process of the K/S. We focused on decision supporting by setting new initial shipment ratio and adjusting base stock levels of a product for stores during sales period in initial shipment and replenishment process. We firstly represented the sales process of the K/S by a mathematical model, and used a grid search method to get approximately optimal initial shipment ratios and proper base stock levels of products during the season with real sales data of the K/S. This paper shows that our proposal has positive effect to increase the sales quantity of past products of the K/S. Additionally, we mathematically analyze the initial shipment ratio problem for the reliability of our approach in a macroscopic viewpoint. To apply our research result in the real K/S distribution system, we are in the progress of pilot experiment during the K/S 2016 F/W season.