Robotic Process Automation in Supply Chain

Abstract

This study investigates the transformative impact of Robotic Process Automation (RPA) on supply chain performance, analyzing its implications across diverse regions, including the USA, Canada, Europe, and African countries. The research explores key dimensions of supply chain performance, considering metrics such as order fulfillment cycle time, inventory turnover, on-time delivery, and sustainability initiatives. Drawing on examples from leading companies in North America and Europe, the study highlights the adoption of advanced technologies, such as RFID and automation, to optimize supply chain processes. In African countries, despite facing unique challenges, innovative approaches like leveraging mobile technology showcase adaptability and resilience. The study delves into the role of government policies, emphasizing how regulatory frameworks influence supply chain performance, with examples like the Food Safety Modernization Act (FSMA) in the USA. The second part of the study focuses on RPA, outlining its fundamental principles and applications within supply chain management. Case studies from companies like Walmart and Canadian Pacific Railway demonstrate RPA's impact on operational efficiency, data accuracy, demand forecasting, and supplier relationship management. The study emphasizes RPA's adaptability to diverse supply chain structures, addressing challenges in different contexts. While acknowledging the potential benefits, the study also highlights challenges associated with RPA adoption, including the need for skilled personnel and potential job displacement. The research concludes by underlining RPA as a continuous improvement tool, fostering a culture of innovation and adaptability within organizations. The study contributes to theory by extending Resource Dependence Theory (RDT), emphasizing RPA as a critical technological resource influencing organizational behavior and decision-making in supply chains. Practical implications include valuable insights for supply chain practitioners, offering a phased implementation strategy and aligning RPA with specific needs. From a policy perspective, the study advocates for supportive regulatory frameworks and policies facilitating RPA integration. Overall, the study positions itself as a comprehensive reference, addressing regional nuances, technological implications, and policy considerations, providing insights for academics, practitioners, and policymakers navigating the dynamic landscape of supply chain automation.