Need and Value of Information in ITS : Supply Chain Performance Through Predictive Analytics

Abstract

In a context of globalization of supply chains, increasing demand and supply uncertainty, supply chain network complexity, changes in environmental rules and regulations, growing human and freight transportation, big risks and Big Data, supply chains dynamics have changed significantly. In the transportation industry, the data collected by the numerous technologies of ITS are complex and characterized by large quantity, volume and heterogeneity of data. In addition to the complexity of data structure, supply chin manager suffers from a lack of visibility. In this way, supply chain managers had to find new tools and methods to analyze the big quantity of data, improve their visibility and the performance of their supply chain. Hence, they agree in saying that Big Data and Predictive Analytics will be new levers for supply chain managers to identify, assess, mitigate and manage global risk and, logically global performance of the supply chain. The utilization of emerging data analytics software and technology, with efficient data collection process and accurate information communication systems, offer great opportunities to build ITS of tomorrow. After having defined the key components of Intelligent Transportation Systems and the technologies related to it, also as the nature and need for information in these systems. Different research questions and arguments related to visibility and Big Data will prove that Predictive Analytics is a vector of performance.