CheckRPA: Checklist-based support of knowledge-workers in RPA projects

Project Description

In our continuously changing world, it is crucial for business processes to be highly adaptive and become more efficient and cost-effective. As a consequence, companies require an increasing degree of process automation to stay competitive in their markets. A promising approach is provided by Robotic Process Automation (RPA), which aims to automate business processes or parts of them using software robots mimicking human interactions. Thus, an increasing number of companies run RPA initiatives. In practice, it is common that RPA projects are implemented by knowledge workers without an IT background. However, there exists little research on applying RPA to knowledge-intensive domains, which are dependent on the employees who perform decision-making tasks. In general, RPA projects often fail, therefore, we aim to sustainably support the project implementation.
In this project, a checklist-based framework for RPA in a knowledge-intensive domain, i.e., automotive, is developed. The research is based on design science methodology. In particular, we  conduct interviews and distribute questionnaires to understand the effects that are achieved with RPA projects in engineering. Further, through an exploratory case study, we identify  challenges in current RPA projects that lead to undesired effects. The current state-of-the-art is analyzed by a systematic mapping study (SMS). Using the framework resulting from the SMS, we determine challenges that have not been addressed in the literature so far. To overcome challenges, we develop and empirically validate an RPA user acceptance model as well as investigating desired human robot interactions empirically. For both research projects, we include 50 RPA users in the automotive industry as participants in the study. The findings are used to derive the checklist-based framework. The latter is evaluated along the framework for evaluation in design science, within four evaluation steps taking into account users from different industries and with different backgrounds.
To conclude, the artifact developed and evaluated in the CheckRPA project, improves the implementation of RPA projects in knowledge-intensive domains while satisfying the special requirements of knowledge workers and, therefore, represents a valuable contribution to practice and scientific literature.

Project Team

Judith Wewerka
Ulm University, Institute of Databases and Information Systems
BMW Group, Agile und Digitale Transformation, Data Analytics
Prof. Dr. Manfred Reichert
Ulm University, Institute of Databases and Information Systems

Project Partners

Ulm University, Institute of Databases and Information Systems

BMW Group, Agile und Digitale Transformation, Data Analytics

Duration

2019 - 2021

Publications

| 2021 | 2020 |

2021

Wewerka, Judith and Reichert, Manfred (2021) Robotic Process Automation in the Automotive Industry - Lessons Learned from an Exploratory Case Study. In: 15th International Conference on Research Challenges in Information Science (RCIS 2021), Limassol, Cyprus, 11 - 14 May 2021, Lecture Notes in Business Information Processing 415(415): 3-19, Springer. file
Wewerka, Judith and Micus, Christian and Reichert, Manfred (2021) Seven Guidelines for Designing the User Interface in Robotic Process Automation. In: IEEE Int'l Workshop on Intelligent Digital Architecture, Methods, and Services for Industry 4.0 and Society 5.0 (IDAMS 2021), Workshop at the EDOC 2021 Conference, Gold Coast, Australia, 25 - 26 October 2021, IEEE Computer Society Press. (Accepted for Publication) file
Wewerka, Judith and Reichert, Manfred (2021) Checklist-based Support of Knowledge Workers in Robotic Process Automation Projects. In: IEEE 23rd Conference on Business Informatics (CBI 2021), Bozen-Bolzano, Italy, 1 - 3 September 2021, IEEE Digital Library. (Accepted for Publication) file

2020

Wewerka, Judith and Dax, Sebastian and Reichert, Manfred (2020) A User Acceptance Model for Robotic Process Automation. In: 24th IEEE Int'l Enterprise Distributed Object Computing Conference (EDOC 2020), Eindhoven, The Netherlands, 5 - 8 October 2020, IEEE Computer Society Press, pp. 97-106. file
Wewerka, Judith and Reichert, Manfred (2020) Towards Quantifying the Effects of Robotic Process Automation. In: Int'l Workshop on Frontiers of Process Aware Systems (FoPAS 2020), in conjunction with EDOC 2020 Workshops, Eindhoven, The Netherlands, 5 October 2020, IEEE Computer Society Press, pp. 11-19. file
Wewerka, Judith and Reichert, Manfred (2020) Robotic Process Automation - A Systematic Literature Review and Assessment Framework. Technical Report arXiv:2012.11951v1, arXiv. file