The role of robotic process automation in Process Mining for digital projects

Abstract

A number of organisations have been struggling with process optimisation for a while. However, with the emergence of RPA and Process Mining, organisations may now enhance their process optimisation initiatives. RPA and Process Mining make use of technology to optimise business processes, reduce manual tasks, and improve operational efficiency. The approach allows organisations to achieve cost and time saving, improve accuracy and quality, improve employee productivity, ensure process compliance and standardisation, and, ultimately, improve customer experience and revenue. The research seeks to examine how the RPA and Process Mining may be used to accelerate digital transformation as well as improve processes within organizations while accelerating system implementation. The research will provide evidence on how combined implementation of RPA and Process Mining may be conducted as well as opportunities for improvement when it comes to implementing process optimization using RPA and Process Mining. The research expands on Siderska (2020) previous research on the implementation of process automation technologies. The aim of this research is to examine the benefits, challenges, and critical success factors associated with implementing RPA and Process Mining. To assess the research findings of the research on implementing RPA and Process successfully, the following research questions were used: • What are the benefits, potential challenges, and motivations for implementing RPA with Process Mining in digital projects compared to individual implementations? • What are the critical success factors for implementation of RPA with Process Mining in digital projects? The qualitative approach was used to collect information from 15 participants using semi-structured interviews. These participants were either current or past members of the Centre of Excellence teams, and they were involved on RPA and Process Mining projects both individually and in collaboration. The information iii that was gathered during these interviews has contributed to a more in-depth understanding of the issue in question. RPA and Process Mining adoption requires proper case selection, defined business goals, change management methods, clear business drivers, and measurable outcomes. Cost and time savings, employee time optimisation, human task replacement, process standardisation, holistic process improvement, process compliance, and simplicity of implementation are all benefits that can be measured. According to the research, process selection, system interface, business requirements, and organisational culture may all have a positive or negative impact on the outcome of the implementation. To ensure effective adoption, organisations have to carefully consider these challenges before implementing RPA and Process Mining. The executive's active backing and advocacy of the implementation can help connect the use case with the organization's strategic goals and ensuring that important business drivers are considered into the implementation strategy