Digitalisation and automation of existing processes are key competitive factors for industry. Still, logistic operations often comprise manual effort, because the movement of goods and material places stringent requirements on the interactions between different systems, human-computer/robot-interaction as well as on changes in the operative processes. In general, the introduction and up-take of new enabling technologies, like the IoT, in complex systems evolved over decades, are challenging. The experience has shown that it is hard to assess all restrictions and interactions between new and old components before any new equipment or infrastructure is implemented and put in operation. This paper presents and discusses the usage of digital twins for supporting the decision-making processes in two different areas: Workstation design and logistics operation analysis. The results are based on tests and experiments carried out in a production logistics test-bed that includes physical devices, an IoT-infrastructure and simulation software. The digital twin is realised in a combination of using Unity and the simulation software IPS. The primary results show that there is no one-size fit all in terms of granularity of the underlying simulation model as well as for the reduction of reality in the digital twin, but the results also indicate that a context-aware digital twin supports the decision-making within a given scope.