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This research paper explores the risks associated with Robotic Process Automation (RPA) projects, with a focus on the impact of disregarding key factors that affect project success. While previous studies have identified challenges and success factors for RPA projects, there is a lack of research that systematically and quantitatively evaluates these factors. To address this gap, the study uses a two-dimensional matrix to rate the impact and controllability of such risks associated with key factors in RPA projects, with data collected from 20 subject matter experts. The findings suggest that project managers should pay close attention to RPA development and process management. The high controllability ratings imply that proper planning and execution can effectively manage the identified risks. The study offers valuable insights into risk assessment for RPA projects and can assist project managers in increasing project success rates.
In recent years, the robotic process automation (RPA) technology, a software-based method to automate routine tasks in business processes, has gained significant interest and adoption. However, many implementation projects fail and current literature lacks a synthesis and comprehensive overview of factors that challenge the implementation of RPA, have an impact on success or failure of projects, or, play an enabling role in an RPA project. Hence, the purpose of this research is to identify key factors that should be considered by organizations when conducting an RPA project.
The paper adopts a qualitative methodology based on data collected in a systematic literature review (SLR) and interviews with 10 RPA experts. Using inductive coding, an integrated framework of key factors is developed.FindingsThe results suggest that the key factors for a successful RPA introduction can be divided into human, organizational and technical factors. Important aspects include for example project management techniques, capabilities and skills of employees, as well as data security considerations.
The paper contributes to knowledge by synthesizing previously dispersed knowledge into an integrated framework, as well as by complementing previous results with new qualitative, empirical data. Additionally, the RPA-specific factors are put into the perspective of persistent problems in information systems development.
