The achievement of a high level of logistical performance is a primary goal of manufacturing companies. In order to remain competitive, companies must constantly improve order processing to ensure short delivery times and high delivery reliability. Production planning and control is a core function of manufacturing companies and is responsible for routing production orders through the stations involved in order processing such as procurement, production and dispatch. Yet managing production efficiently and achieving a high logistical performance remains a genuine issue, even with increasingly digitalized and automated processes. The concept of the digital twin promises an improved database to enable companies to reach more informed decisions. As yet, the potential for utilizing this database has not been thoroughly explored in the context of a constant measurement of the backlog and output. In addition, there are various divergent definitions and approaches to the application of digital twins. This paper discusses the potentials of the different tasks of production control and monitoring in relation to the acquisition of dynamic data in real-time. A method is provided that continuously calculates the backlog and output. Furthermore, an example of application is presented that shows how this information can be used for production control. Our results indicate that by exploiting this information, logistic performance can be improved.