A conceptual framework for integrating Robotic Process Automation in logistics audits and supply chain management

Résumé

Digital transformation has become a central theme in logistics auditing, especially with the increasing importance of digital technology in the organizational and societal environments. This study is based on an integrative literature review to propose a conceptual framework for integrating Robotic Process Automation (RPA) into logistics audits, aiming to enhance operational efficiency, accuracy, and strategic decision-making. The framework is structured around five stages: Requirements Analysis, Performance Analysis, Process Analysis, Structural Analysis, and Comparative Analysis. Each step of the conceptual framework is inspired by traditional audit methodologies, such as needs analysis, performance analysis, process analysis, structural analysis, and benchmarking. It leverages the capabilities of RPA to automate repetitive tasks, enhance data integrity, and instantly provide real-time process analyses on an annual basis. The findings highlight that RPA significantly enhances resilience and transparency in the supply chain by automating tasks related to invoice verification, shipment tracking, and compliance monitoring. However, organizational readiness and technological infrastructure could affect the applicability of the framework. The degree of difficulty in RPA amplitude integration with existing systems also contributes to the limitations placed on the framework's adoption. All of these reservations indicate the continued need for empirical studies to put the framework through its paces in various organizational contexts. From the viewpoint of practical contributions, the study provides actionable guidelines for organizations to implement RPA in logistics audits, emphasizing the importance of stakeholder alignment, continuous monitoring, and benchmarking against industry standards. The theoretical contribution lies in bridging the gap between RPA and auditing practices, offering a structured approach that combines traditional auditing methods with cutting-edge automation technologies.

Classification JEL: M15, L23, O33

Paper type: Theoretical Research