A Review of Data-driven Robotic Process Automation Exploiting Process Mining
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Purpose: Process mining aims to construct, from event logs, process maps that can help discover, automate, improve, and monitor organizational processes. Robotic process automation (RPA) uses software robots to perform some tasks usually executed by humans. It is usually difficult to determine what processes and steps to automate, especially with RPA. Process mining is seen as one way to address such difficulty. This paper aims to assess the applicability of process mining algorithms in accelerating and improving the implementation of RPA, along with the challenges encountered throughout project lifecycles. Methodology: A systematic literature review was conducted to examine the approaches where process mining techniques were used to understand the as-is processes that can be automated with software robots. Eight databases were used to identify papers on this topic. Findings: A total of 19 papers, all published since 2018, were selected from 158 unique candidate papers and then analyzed. There is an increase in the number of publications in this domain. Originality: The literature currently lacks a systematic review that covers the intersection of process mining and robotic process automation. The literature mainly focuses on the methods to record the events that occur at the level of user interactions with the application, and on the preprocessing methods that are needed to discover routines with the steps that can be automated. Several challenges are faced with preprocessing such event logs, and many lifecycle steps of automation project are weakly supported by existing approaches.
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