Technological innovations are constantly changing the IT landscape. One of these innovations is Robotic Process Automation (RPA). RPA is an emerging technology for the automation of business processes. It uses software robots (so called bots) to execute tasks in business processes in the same way a human actor would do via the graphical user interfaces (GUIs). This technology promises many advantages, such as efficiency gains, increased productivity, improved service quality, reduction of human errors, and shortened delivery time while automating business processes. Not every business process or business process activity is suitable for automation. Therefore, the selection of the right business process or business process activity is essential for the success of RPA projects. This takes place in the analysis phase of the RPA business process life cycle before the RPA implementation starts. There are certain business process or process activity characteristics and criteria, which can serve as indicators for the viability for RPA. These process characteristics form the basis for methods, frameworks, and guided approaches to find the right business processes. Furthermore, process mining and/or activity mining can support the detection of business processes suitable for automation. Therefore, this thesis evaluates and assesses different methods and approaches for the identification of business processes viable for RPA. To achieve this, we conduct a systematic literature review and use a real life running example to prove the applicability in practice of the methods and approaches presented in selected scientific publications. The result is twofold and not surprising: On the one hand, there are methods mostly based on process characteristics, which can be easily applied to real life business processes or business process activities to assess their usability. On the other hand, most of the methods proposing the usage of process and/or task mining, are still on an early stage of applicability in practice and require in my view additional research.
MA Abschlussvortrag, Helmut Kraft, Ort: Online, Datum: 28.09.2021, Zeit: 15:45 Uhr