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Supply chain management depends on a complex, interconnected network of suppliers, manufacturers and distributors with the goal of predicting, monitoring and controlling operations and processes. Globalization has introduced relentless competition, forcing supply chains to innovate and enhance their performance and capabilities. To compete, companies must adopt emergent technologies to enhance their SC operations. Modern SCs utilize enterprise resource planning (ERP) systems for inventory management, supply chain management, accounting, customer relations management and supplier coordination. These systems store & retrieve information using databases that employ centralized storage architectures. However, centralized infrastructures have known limitations including using single point data storage, are prone to hacking and lack decentralized solutions for global networks. This study investigates decentralized database ERP implementations using blockchain technology (BCT) frameworks within centralized global supply chain (SC) network. A novel framework was created to introduce a new methodology for a decentralized data storage architectures and to lay the foundation for ERP simulation modeling. Using statistics and probability values, based on degrees of freedom and t-statistics, the mean of the data is considered significant or not significant. A comparative study will be conducted to see when it is suitable to implement each architecture, and which system had the better results in terms of flexibility, monetary, program efficiency and system efficiency.