Looking for the Why in Event Logs for Robotic Process Automation

Abstract

The concept of Robotic Process Automation (RPA) has gained relevant attention in both industry and academia. RPA raises a way of automating mundane and repetitive human tasks requiring less intrusiveness with the IT infrastructure. Besides traditional user interviews and process document analysis, a common practice starts by observing the behavior of humans with the information systems while they perform the process to be automated. This sequence of human interactions with the user interface (i.e., mouse clicks and keystrokes) is stored in logs for later analysis. Analyzing these interactions brings significant benefits when conducting RPA projects. Nonetheless, some decision-based behaviors of humans require additional information to be explained. For example, a human may reject an invoice because some field is missing on a form. However, there is no interaction with that field since such information is not stored in the log. Therefore, this Ph.D. elaborates on a method to obtain additional information based on screenshots collected during the process execution. Some features are extracted from the screenshots to enrich the log, which is later used for classifying human decisions in a machine-and-human-readable form. The proposed method can be applied to generate advanced support in the RPA projects, e.g., producing an enhanced process analysis, supporting the robot development, or generating predictions and simulations. The approach has been validated using synthetic data where promising results were obtained.