Information Sharing for Customized Dynamic Visual Analytics: A Framework

Abstract

Supply chain activities generate massive amount of data by several actors such as, suppliers, manufacturers, warehouses, distributers, and wholesalers. Visual analytics (VA) plays a key role in knowledge discovery and insight generation from this data and helps various players to enhance their operational and strategic decision making. This is more essential for Fast moving consumer goods (FMCG) industry, given the size of the industry and its sensitivity to the diverse market uncertainties. In this paper, we present a PhD research plan that responds to the requirements of a FMCG supply chain VA system by means of a comprehensive framework. In this regard, the information flow throughout the supply chain is a significant factor for developing a reliable and efficient VA solution and a proper information flow throughout the supply chain can be enhanced with the help of the framework consisting of modules including Data Generation, Data Integration and Management, Data Analytics, Data Visualization, and Data-driven decision making. The aim of the study is to explore the development of a VA framework that acts as a guideline for supply chain players to improve their analytical capabilities