The critical success factor of the supply chain management process in a modern manufacturing company consists in the company’s capability to exploit the data produced by a growing number of different sources. The latter include a network of collaborative sensors, digital tools, and services, made available to suppliers and other involved supply chain actors by the recent advancements in digitalization. The collected data can be processed and analyzed in near real time to extract significant information useful for the company to take some relevant decisions. However, these data are typically produced under the form of heterogeneous formats, as they arrive from different types of sources. This is the reason why the real challenge is finding valid solutions that support the data integration. In this regard, this paper investigates the potential of a solution for data integration that allows supporting a set of interacting decision-support tools within the inbound logistics of the automotive manufacturing. This solution is based on a message-oriented middleware which enables a collaborative approach where suppliers, trucks, dock managers and production plants can share information about their own status for the optimization of the overall system.