Bot Log Mining: Using Logs from Robotic Process Automation for Process Mining

Abstract

Robotic Process Automation (RPA) is an emerging technology for automating tasks using bots that can mimic human actions on computer systems. Most existing research focuses on the earlier phases of RPA implementations, e.g. the discovery of tasks that are suitable for automation. To detect exceptions and explore opportunities for bot and process redesign, historical data from RPA-enabled processes in the form of bot logs or process logs can be utilized. However, the isolated use of bot logs or process logs provides only limited insights and not a good understanding of an overall process. Therefore, we develop an approach that merges bot logs with process logs for process mining. A merged log enables an integrated view on the role and effects of bots in an RPAenabled process. We first develop an integrated data model describing the structure and relation of bots and business processes. We then specify and instantiate a 'bot log parser' translating bot logs of three leading RPA vendors into the XES format. Further, we develop the 'log merger' functionality that merges bot logs with logs of the underlying business processes. We further introduce process mining measures allowing the analysis of a merged log.

An Overview on Robot Process Automation: Advancements, Design Standards, its Application, and Limitations

“…In order to see and evaluate the process flow, data must first be extracted from multiple sources, including databases, transaction logs, and other systems, using data mining algorithms. Robotic process automation, or RPA, automates routine, rule-based processes using software robots [22]. RPA may assist firms in locating opportunities for automation and putting automated solutions into place fast and effectively when used in conjunction with process mining.…”

Towards Discovering Erratic Behavior in Robotic Process Automation with Statistical Process Control

“…The quality and preparation of data for process mining is very time-consuming and, therefore, process mining should provide significant added value and companies should use the insights to take action (De Weerdt and Wynn, 2022;van der Aalst, 2016). Process mining in RPA processes is not very typical at the moment, however, it can be applied to automated processes for RPA (Egger et al, 2020;Průcha, 2021), where duration rates, bottlenecks and deviations can be identified. With advanced methods of process mining such as predictive process monitoring, enhancing the process data with data from other systems, root-cause analysis and online monitoring, it is possible to gain more valuable insights about the behavior of RPA processes including information why an RPA bot fails, whether the bot fails when executing a particular variant and whether RPA bots can keep up with the queue of cases (Burattin, 2022;Di Francescomarino and Ghidini, 2022;Fahland, 2022;Van Houdt and Martin, 2021).…”

Enhancing Robotic Process Automation Task Selection: An Integrated Approach Leveraging Process Mining and Feature Extraction

“…The combined deployment of RPA and process mining could unearth valuable insights into an organization's business processes. On one hand, the data and insights garnered from process mining can be applied across various stages of RPA [22]; on the other, the logs generated can be analyzed using process mining techniques to enhance the understanding of the business processes executed by the RPA bot [23].…”