A robotic process automation model for order-handling optimization in supply chain management

Abstract

This study proposes a robotic process automation (RPA) model to streamline and optimize order-handling procedures in supply chain management. The current manual approach to order handling poses challenges, including limited accessibility and significant cognitive demands on employees. An information systems design methodology is applied to analyze and improve the process, with data gathered through semi-structured interviews to address these issues. The findings highlight that reducing manual labor alleviates workload imbalances and saves time in supply chain automation. Moreover, automating repetitive tasks through well-designed software bots minimizes the risk of human error. While this research focuses on applying RPA in order handling, future studies should explore the potential of artificial intelligence-driven RPA to enhance process automation further.