Evaluating and Developing Methods to Assess Business Process Suitability for Robotic Process Automation - A Design Research Approach
Examensarbete för masterexamen
Software engineering and technology (MPSOF), MSc
Robotic Process Automation (RPA) is an emerging approach to automation within or across information systems. While it has grown immensely during recent years, academic studies on the topic have been quite scarce. This study focuses on one aspect of this automation, namely how to select which processes to automate. The purpose of this study is to review existing methods for selecting processes to automate and if possible, suggest improvements to these. In addition, this study also aims to investigate if BPMN (Business Process Model and Notation) can be used to assist in the process selection. In order to fulfill this purpose, the study began by reviewing existing methods and gathered a total of 23 methods or recommendations for how to select processes. These methods were then applied at a partner company for four specific processes. The processes were selected during a set of interviews after which the processes were modelled using BPMN and assessed using the criteria from the existing methods. This revealed a number of issues with existing methods and the use of BPMN for this purpose. A new methodology was designed, the RPA Suitability Framework, which tried to address these issues, both with the existing selection methods as well as BPMN. The RPA Suitability Framework was then applied to five new processes from the partner company to see how it fared compared to previous methods. This evaluation was done by comparing the outcome of the methods, the content of the methods as well as during an evaluation workshop with the partner company. Many improvements could be seen, but further testing of the new framework would be needed before a general recommendation to use it could be given.
Informations- och kommunikationsteknik , Data- och informationsvetenskap , Information & Communication Technology , Computer and Information Science