Enterprise digital twin as an analytical tool for managerial decision support: a comparative analysis of practices and the concept of an integrated platform

This article examines the practical aspects of applying digital twin technology to address management challenges in modern industrial enterprises. The relevance of the topic is driven by the increasing complexity of industrial ecosystems and the insufficient effectiveness of traditional decision-support tools under conditions of high uncertainty and cognitive overload among managers. The aim of this work is to systematize practical experience in implementing digital twins across various industries and to identify their impact on the quality of managerial decision-making. The methodological framework is based on a comparative analysis of implemented projects at the Tugnuisky open-pit coal mine, MMK (Magnitogorsk Iron and Steel Works), the headquarters of Schneider Electric, the Siemens Mobility test center, and solutions developed by Tiqum. As a result of this study, three analytical tables were developed, enabling a comparison of the examined solutions in terms of technical characteristics, achieved managerial effects, implementation constraints, and risks. It is demonstrated that digital twins ensure end-to-end process transparency and forecasting capabilities; however, existing implementations are characterized by fragmentation and a weak focus on strategic planning. Based on the identified limitations, the study proposes a concept for an integrated platform that unifies operational, tactical, and strategic management loops. The conclusions drawn can be utilized by enterprise leaders when justifying investments in digital transformation, as well as by researchers studying the application of artificial intelligence technologies in management.