Author(s)

Jie Wen

Corresponding Author

Jie Wen

Abstract

This research explores the restructuring and dynamic optimization of enterprise performance management systems driven by digital twin technology. As businesses face rapidly changing market environments and intense competitive pressures, traditional management models are becoming inadequate. Digital twins enable real-time interaction between physical entities and virtual models, enhancing operational efficiency and decision-making. This study analyzes the basic principles of digital twin technology, its application in performance management, and proposes a framework for restructuring performance management systems. It also presents dynamic optimization strategies, emphasizing data-driven decision-making, continuous feedback mechanisms, and cross-departmental collaboration. The findings highlight the significant potential of digital twins in improving enterprise performance and competitiveness.

Keywords

Digital Twin, Performance Management, Dynamic Optimization, Real-Time Data, Cross-Departmental Collaboration, Data-Driven Decision-Making