The integration of Enterprise Resource Planning (ERP) systems with Manufacturing Information Scanning Systems is essential for establishing a robust infrastructure capable of supporting high-quality big data flows. This foundational integration enables more sophisticated analytical modeling, leading to enhanced decision-making capabilities and effective incorporation of Artificial Intelligence supply chain operations, ultimately driving cost optimization.

Key findings of this research highlight that successful implementation of integrated ERP solutions extends beyond technical complexities; it critically depends on management's strategic decision-making at each implementation stage. Effective integration contributes significantly to improved operational efficiency, stronger customer relationship management, and more accurate accounting processes. However, substantial challenges persist, particularly related to the complexities of migrating historical data from legacy systems such as MS Access to modern ERP systems Additionally, organizations face ongoing data management issues and significant organizational resistance toward developing and sustaining a data-driven culture

This paper explores these challenges in-depth, presenting strategic insights and practical methodologies for organizations to successfully integrate ERP and Manufacturing Information Systems. By overcoming the highlighted barriers, organizations can fully leverage their integrated ERP systems, unlock comprehensive analytical capabilities, and achieve substantial cost optimization within supply chain management.

Enterprise Resource Planning (ERP), ERP Integration, Manufacturing Information Systems, Big Data analytics, Artificial Intelligence, Digital Transformation, Supply Chain Management

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