Abstract

The increasing globalization of business operations has intensified the demand for Enterprise Resource Planning (ERP) systems capable of integrating diverse functions across geographies, business units, and regulatory environments. However, managing large-scale ERP implementations in global organizations remains a complex challenge involving technological, organizational, and cultural dimensions. This study proposes a Conceptual Framework for Managing Large-Scale ERP Implementations in Global Organizations, designed to address the multifaceted nature of ERP projects and ensure alignment with strategic objectives, operational efficiency, and financial control. The framework integrates principles from project management, change management, and systems theory to establish a holistic model for planning, execution, and post-implementation optimization. The proposed framework emphasizes five core dimensions: strategic alignment, ensuring that ERP initiatives support global business goals; governance and stakeholder engagement, fostering coordination among cross-functional and cross-cultural teams; process standardization and localization balance, managing the tension between global uniformity and regional flexibility; technological integration and data governance, ensuring system interoperability and data accuracy; and change management and capacity building, cultivating organizational readiness and digital competence. The framework further highlights the importance of performance measurement through key indicators such as implementation cost, system adoption rate, data accuracy, and return on investment (ROI). By providing a structured approach to ERP management, this study contributes to the body of knowledge on digital transformation and enterprise systems governance. It offers practical insights for global organizations seeking to mitigate implementation risks, enhance system adoption, and achieve sustainable value creation. Future research should empirically test the framework’s applicability across industries and explore its extension to cloud-based ERP and AI-driven decision-support systems.