Video from CamundaCon 2020.2

Speeding Up Robotic Process Automation through Behavioral Observation

Speeding Up Robotic Process Automation through Behavioral Observation

#RPA, #Architecture, #Automation Platform

In the last decade, a large number of Robotic Process Automation (RPA) projects have been conducted. In essense, these involve the use of software to mimic the behaviour of human employees. Typically, most commercial RPA platforms (e.g., BluePrism or UiPatch) rely on a manual analysis of the project context to identify the candidate processes that are suitable for automation. This is a time-consuming task. It does not only involve the analysis of much documentation, it is also necessary to determine the expected frequency of cases, the exceptions that can take place, and various other attributes that are complex to estimate.In this talk, we will explore the benefits of an alternative approach, which is completely agnostic with respect to the specific technology that is being used. Our starting point is to use log information, which captures various attributes of how humans behave. Specifically, we start out by monitoring the interactions between the employees and the information systems within the project context. We will first address how to transform that observed behaviour (i.e., in the form of screen captures, clicks and keystrokes) into a meaningful user interface event log (UI log) by using image-similarity techniques. We will proceed to show how this UI log can be leveraged to automate the process analysis and design phases in an RPA project. Beyond this explanation, we will elaborate on the open challenges as well as the opportunities that the UI log provides for further stages of an RPA project, i.e., development, testing, and maintenance.





Andres Jimenez Ramirez, Universidad de Sevilla
Andrés Jiménez Ramírez is a lecturer and researcher at the University of Seville. He started his career as a software engineer in the R&D department of a Spanish consultancy firm. Soon he moved to the University where is a member of the Web Engineering and Early Testing (IWT2) group. His main research interests are constraint programming, flexible process modelling, and process automation.


Hajo A. Reijers, Utrecht University
Hajo Reijers is a full professor at Utrecht University, where he leads the Business Process (BPM) Management & Analytics group. Previously, he worked for consultancy firms, including Accenture and Deloitte, and led a research group at Lexmark. Hajo’s research and teaching focus on BPM, process automation, and data science.