Enhancing manufacturing supply chain resilience using data-centric ERP system design

Manufacturing supply chains have entered a stage in which resilience depends not only on redundancy, but also on the speed, quality, and governability of enterprise data. This review examines how data-centric ERP architecture can strengthen manufacturing supply chain resilience by repositioning ERP from a transactional repository to an operationally supported decision-making system. The article reviews recent peer-reviewed literature on resilience, digital supply chain twins, Industry 4.0 integration, analytics, blockchain-based traceability, and manufacturing recovery planning, especially with regard  to architectural implications in the context of ERP-driven environments. Across the reviewed studies, common themes include the strategic importance of real-time visibility, semantic consistency across plants and partners, scenario-based replanning, and closed-loop execution control. At the same time, the literature remains divided: most resilience studies emphasize digital tools without addressing ERP data structures, whereas most enterprise-systems studies discuss integration without directly quantifying resilience. Important gaps remain in causal explanation, interoperability management, latency-sensitive master data design, and treatment of multi-tier manufacturing networks. A data-centric ERP design is therefore presented as one promising path for integrating sensing, planning, execution, and learning within a unified and robust information architecture.