Capturing value through data-driven internal logistics: case studies on enhancing managerial capacity

Abstract

A key motivation to adopt data-driven solutions in facility-internal logistic systems is to create more responsive, efficient, and sustainable systems through a seamless data flow. There is thus a need to analyse the logistics system’s requirements from a data efficiency perspective. This paper presents and demonstrates a novel method, based on established literature, to assure that a transition to data-driven internal logistics leads to improvements in operational performance objectives. First, we identify wastes on the shopfloor caused by inefficient data flows. Second, we portray the trajectories of managerial capacities enhancements, supporting decision makers toward a to-be scenario. Two case studies are presented where the method has been implemented and used for demonstration and validation purposes. The results show that the method is beneficial in a waste-elimination and continuous improvement setting, linking improvements, detected wastes, enabling technologies, and managerial capacities in terms of monitoring, control, optimization, and autonomy.