Automation and Digital Twins Framework Reducing Procurement Errors and Turnaround Time - Oluwagbemisola Faith Akinlade,; Opeyemi Morenike Filani,; Priscilla Samuel Nwachukwu, (International Journal of Scientific Research in Humanities and Social Sciences, 2024)
The evolving complexity of modern procurement processes demands innovative approaches to enhance accuracy, efficiency, and strategic alignment. Automation and digital twins frameworks have emerged as transformative tools in this context, enabling organizations to reduce procurement errors and accelerate turnaround time. Automation leverages technologies such as Robotic Process Automation (RPA), workflow orchestration, and rule-based decision systems to minimize manual intervention in repetitive tasks, including purchase order generation, invoice validation, and supplier communications. By reducing human error, automation enhances data accuracy, ensures compliance with procurement policies, and streamlines operational workflows, contributing to faster and more reliable procurement cycles. Digital twins extend these capabilities by creating virtual replicas of procurement operations, supply chain networks, and supplier interactions. These digital models simulate real-time processes, monitor procurement performance, and predict potential bottlenecks or disruptions before they affect operations. By integrating data from Enterprise Resource Planning (ERP) and Supplier Relationship Management (SRM) systems, digital twins provide actionable insights for decision-makers, enabling proactive interventions and continuous process optimization. The combination of automation and digital twins allows organizations to anticipate errors, optimize supplier selection, manage inventory levels, and reduce the turnaround time for requisitions and approvals. Empirical applications demonstrate significant operational benefits, including improved accuracy in order fulfillment, reduced cycle times, and enhanced transparency across procurement workflows. Additionally, these frameworks support strategic objectives by aligning procurement performance with organizational goals, enabling risk-aware sourcing, and facilitating evidence-based decision-making. Challenges, such as data integration, model calibration, and workforce adaptation, require careful management to maximize the framework’s potential. An integrated automation and digital twins framework provides a powerful approach to reducing procurement errors and accelerating turnaround times. By combining predictive simulations, real-time monitoring, and automated operational workflows, organizations can achieve higher efficiency, improved compliance, and strategic alignment, ultimately transforming procurement into a responsive and resilient function within modern supply chains.
Keywords: Automation; Digital Twins Framework; Procurement Errors; Turnaround Time Reduction; Process Optimization; Real-Time Monitoring; Predictive Simulation; Supply Chain Efficiency; Data-Driven Decision-Making; Procurement Accuracy; Operational Reliability