Equipment Logistics Performance Measurement Using Data-Driven Social Network Analysis

Abstract

The construction industry relies heavily on the use of equipment. Equipment management for a single project is, in itself, challenging, and large contractors who want to achieve long-term success must also manage equipment at an intraorganizational level. While vast amounts of data are collected and updated dynamically to track equipment status within an organization, current practices do not consider these data during the decision-making process. Rather, companies often rely on a single metric, equipment utilization, for evaluating management performance. Inspired by the ability of social network analysis (SNA) to examine the interactions and relationships between objects, a SNA-based method for investigating equipment movement between project sites and equipment shops is proposed. This study proposes a novel performance metric, the direct dispatch index (DDI), which adds a distance weight to the clustering coefficient of SNA, to measure equipment dispatching performance from equipment logistics data. Historical equipment logistics data from the equipment and project management systems of a company in Alberta, Canada, were used to demonstrate the functionality and feasibility of the proposed approach. The methodology was found capable of evaluating the logistical effort associated with equipment dispatch and planning, thereby enhancing equipment management through improved decision-making.