Application of operational data analysis in the optimization and enhancement of logistics process safety

Abstract

PURPOSE: The purpose of this article is to evaluate the efficiency of transport processes and operational safety levels based on a set of logistics and operational indicators obtained from the Logistics Information System (LIS) and telematics systems for a selected fleet of 10 vehicles. The analysis demonstrates how combining technical and economic indicators allows for the diagnosis of logistics processes and the formulation of recommendations in the context of variability and risk.

DESIGN/METHODOLOGY/APPROACH: The study was conducted in a logistics and transport company implementing LIS and vehicle telematics. Quantitative analysis was used to evaluate operational indicators such as the number of deliveries, vehicle load utilization, waiting time, number and causes of delays, the OTIF index, and 𝑇𝐴𝑈 representing the unit value of the utilized vehicle load capacity. Data were collected from telematics and CRM systems and aggregated into the central LIS database. Non-parametric DEA (Data Envelopment Analysis) and indicator analysis methods were applied.

FINDINGS: The conducted analysis demonstrated that the highest efficiency and safety of the logistics process were achieved by vehicles exhibiting low delay rates and high values of the unit indicator for utilized vehicle load capacity. The lowest OTIF (On-Time In-Full) values characterized vehicles with the highest share of logistics delays. The findings also indicated that the number of completed deliveries alone does not guarantee high process efficiency or operational safety.

PRACTICAL IMPLICATIONS: The results draw fleet managers’ attention to the need for continuous data analytics to quickly identify weak points and implement corrective measures. It emphasizes the importance of conducting regular statistical analyses of delay causes and managing operational risk within a dynamically changing transport environment. Raising the level of safety requires not only responding to threats but also prediction and prevention based on LIS and telematics data.

ORIGINALITY/VALUE: This article presents a practical application of advanced LIS and telematics tools in a comprehensive assessment of transport fleet efficiency and safety. The findings provide actionable recommendations for managers on how data analysis can directly enhance competitiveness, operational performance, and resilience to disruptions.