A comparative analysis of predictive analytics tools with integrated What-if modules for transport industry

Abstract

The freight transport sector is facing more than ever major innovations and challenges. Digital transformation and analytics tend to optimize traditional work methods and accelerate workflows. This paper focuses on the problem of choosing an analytics solution that allows the prediction of future cases based on historical data and integrates packages that permit to run what-if simulations. Faced with a multitude of criteria required by freight transport professionals, we propose to solve it by implementing the Analytical Hierarchy Process-AHP method. The use of a collaborative approach during the AHP process allowed us to obtain relevant and accurate results.