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Enterprise Resource Planning (ERP) systems have become foundational tools for business integration, operational efficiency, and strategic agility. However, their effectiveness relies heavily on the extent and quality of customization and post-implementation support provided throughout the ERP lifecycle. This paper proposes the Adaptive Customization and Support Framework (ACSF)—a layered model designed to address persistent challenges in ERP evolution, including upgrade rigidity, maintenance costs, and lack of business-IT alignment. Drawing from multidisciplinary literature and supported by empirical case studies, ACSF integrates real-time data analytics, predictive support mechanisms, modular design principles, and IT governance layers to enhance ERP adaptability and performance. The study offers a comprehensive comparative analysis of ACSF against existing frameworks such as Static Configuration Models, Critical Success Factor (CSF) Models, and Post-Implementation Lifecycle (PILC) Models. The results demonstrate ACSF’s superior predictive performance across key operational metrics such as downtime reduction, customization turnaround, system upgrade readiness, and support resolution rates. The paper concludes with implications for practitioners, policymakers, and researchers, and outlines directions for future studies aimed at refining ERP customization strategies and developing agile, intelligent, and sustainable ERP ecosystems.
Keywords:
ERP customization, Post-implementation support, Business process optimization, Adaptive ERP frameworks, IT governance, Predictive analytics, Agile ERP systems, ERP lifecycle management, Digital transformation, Enterprise system innovation.
Cite Article:
"Adaptive ERP System Customization and Support: A Strategic Framework for Business Process Optimization and Growth", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 7, page no.b497-b505, July-2025, Available :http://www.ijrti.org/papers/IJRTI2507172.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator