Streamlining enterprise resource planning through digital technologies
Hariprasad Mandava
Abstract
This study explores dynamic adaptation and evolutionary frameworks within Enterprise Resource Planning (ERP) systems, presenting an advanced strategy to enhance system agility and responsiveness. It investigates how these frameworks empower ERP systems to adjust to evolving business requirements, technological advancements, and market dynamics. The discussion covers key elements such as adaptive algorithms, evolutionary architectures, and real-time integration. Case studies illustrate how dynamic adaptation improves ERP system scalability, performance, and user satisfaction. The study also addresses challenges including integration complexity, data interoperability, and organizational change management, offering strategies to mitigate these issues. Future research recommendations emphasize the advancement of dynamic ERP frameworks, the integration of AI and machine learning, and the enhancement of agility in enterprise software systems. This research underscores the potential of dynamic adaptation and evolutionary approaches to future-proof ERP systems and promote sustainable business growth in dynamic environments.