Logistics transformation from an operational function to an intelligent decision-making platform

Abstract

The transformation of logistics into an intelligent platform is a key factor in improving the efficiency of managerial decision-making in modern business conditions. The study examines the evolution of logistics from an operational function to an integrated system that supports decision-making processes. Particular attention is given to its role as a strategic component of enterprise management, ensuring flexibility, adaptability, and efficiency of business processes. The purpose of the study is to analyze theoretical and practical approaches to the transformation of logistics into an intelligent decision-making system and to identify effective tools for improving performance. Special attention is paid to the impact of digitalization and economic instability, including the consequences of military actions, on the development of supply chain systems and the need to adapt management approaches to modern conditions. Research methods. The study is based on a systematic approach, methods of comparative analysis, generalization, and modeling, as well as analytical methods for evaluating the effectiveness of decisions and risks in supply chains. Results. The key stages of transformation have been identified, and the main characteristics of modern logistics systems have been determined, including proactivity, integration, and data orientation. It has been established that the use of digital technologies, big data analytics, and predictive models improves the quality and timeliness of managerial decisions. An integrated decision-making model is proposed, combining analytical and risk-oriented components to enhance management efficiency. Scientific novelty. The study develops an integrated approach to logistics as a continuous analytical environment for decision-making. Conclusions. The findings confirm the need to transform logistics into an intelligent platform within enterprise management systems. The use of digital technologies, analytical tools, and risk-oriented approaches enhances resilience and adaptability. The implementation of forecasting tools, process optimization, digital monitoring, and integration of information systems is recommended to ensure effective decision-making in a dynamic environment.