Use of real-time data to make strategic and operational decisions in the trucking industry

Abstract

Real-time data collection and analysis allows an organisation to obtain accurate insights on the efficiency of its operations as well as the utilisation of resources. It also helps to formalise strategies which can help in optimising the operations, making it more efficient in the process. For an organisation in the trucking industry, efficient use of its truck fleet is paramount. Hence, real-time data can aid a trucking organisation in its objective of efficient operations. The organisation, KM Trans Logistics, the subject of this study, has provided a year worth of trucking operations data which was analysed to extract relevant information for the organisation. Analysis of the data has led us to create a predictive regression model using a data mining open software, Rapidminer Studio, that could help the organisation to calculate or predict the trip time of a truck before it starts a trip. This predictive model can further allow the organisation to take further decisions on operations and scheduling to make efficient use of the fleet at their disposal.