Managing Wireless networks, particularly in indus- trial and factory environments, to meet the escalating demands of time critical applications has become more complex and warrants proactive management strategies. This work introduces an innovative approach to wireless network management enabled by a Digital Twin (DT) designed and continuously enhanced by real-time device telemetry and user inputs through an Ex- tended Reality interface. By collecting real telemetry data from network devices, our methodology defines and calibrates a DT representation of the network, enabling accurate prediction of wireless signal properties and network performance based on simulation models. The DT serves as an automation tool to analyze various scenarios, allowing for informed adjustments to user applications, devices and network configurations. The paper describes a real-life DT implementation of a wireless system in a real enterprise network scenario. Experimental results are provided demonstrating improved performance and user experi- ence enabled by the proposed DT-based network management. The proposed methodology addresses the challenges of real- time network optimization and contributes to advance wireless network management based on device and network telemetry.