Data science to measure the last mile processes in the logistics

Abstract

One of the most critical parameters of logistics processes is to measure the efficiency of delivery of the final product to the customer, or last mile processes. Historically, the customer does not care about the processes that are carried out before delivering the product, the end customer is interested in the product reaching their hands on the promised date. The measurement of the efficiency of the logistics processes transit time is necessary to analyse it partially by the different processes and the entities that intervene, from suppliers, manufacturing centres, distribution centres, and carriers. The design of the layout to collect the information allows statistical analysis to evaluate the performance in each part of the process and the generation of algorithms to predict different compartments that can be potentially negative for the fulfilment of the product delivery promise times. The current investigation shows the application of statistical models for predicting delivery errors and delays in delivery in the last mile process in logistics.