Efficient supply chain management relies on a data management framework that guarantees accuracy, visibility and actionable information across the whole value chain. Enterprise architecture models such as TOGAF (The Open Group Architecture Framework), RAMI 4.0 (Reference Architecture Model for Industry 4.0) and IBM 4.0 provide structured approaches to enterprise systems management, but are limited when it comes to integrating real-time data, maintaining interoperability with IoT networks and responding to the dynamic nature of modern supply chains. To address these shortcomings, this article proposes a customized framework that describes what a data management system should ideally comprise to integrate properly with supply chain management. Rather than combining existing models, this framework provides a systematic platform for effective data collection, processing and use. Advanced analytics, digital twins and Industry 4.0 technologies are used to improve decision-making, end-to-end visibility and operational performance throughout the supply chain.