@techreport{ImgrundJanieschFischeretal.2019, author = {Imgrund, Florian and Janiesch, Christian and Fischer, Marcus and Winkelmann, Axel}, title = {Success Factors for Process Modeling Projects: An Empirical Analysis}, doi = {10.25972/OPUS-17924}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-179246}, pages = {68}, year = {2019}, abstract = {Business process modeling is one of the most crucial activities of BPM and enables companies to realize various benefits in terms of communication, coordination, and distribution of organizational knowledge. While numerous techniques support process modeling, companies frequently face challenges when adopting BPM to their organization. Existing techniques are often modified or replaced by self-developed approaches so that companies cannot fully exploit the benefits of standardization. To explore the current state of the art in process modeling as well as emerging challenges and potential success factors, we conducted a large-scale quantitative study. We received feedback from 314 respondents who completed the survey between July 2 and September 6, 2017. Thus, our study provides in-depth insights into the status quo of process modeling and allows us to provide three major contributions. Our study suggests that the success of process modeling projects depends on four major factors, which we extracted using exploratory factor analysis. We found employee education, management involvement, usability of project results, and the companies' degree of process orientation to be decisive for the success of a process modeling project. We conclude this report with a summary of results and present potential avenues for future research. We thereby emphasize the need of quantitative and qualitative insights to process modeling in practice is needed to strengthen the quality of process modeling in practice and to be able to react quickly to changing conditions, attitudes, and possible constraints that practitioners face.}, language = {en} } @article{HermJanieschHelmetal.2023, author = {Herm, Lukas-Valentin and Janiesch, Christian and Helm, Alexander and Imgrund, Florian and Hofmann, Adrian and Winkelmann, Axel}, title = {A framework for implementing robotic process automation projects}, series = {Information Systems and e-Business Management}, volume = {21}, journal = {Information Systems and e-Business Management}, number = {1}, issn = {1617-9846}, doi = {10.1007/s10257-022-00553-8}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-323798}, pages = {1-35}, year = {2023}, abstract = {Robotic process automation is a disruptive technology to automate already digital yet manual tasks and subprocesses as well as whole business processes rapidly. In contrast to other process automation technologies, robotic process automation is lightweight and only accesses the presentation layer of IT systems to mimic human behavior. Due to the novelty of robotic process automation and the varying approaches when implementing the technology, there are reports that up to 50\% of robotic process automation projects fail. To tackle this issue, we use a design science research approach to develop a framework for the implementation of robotic process automation projects. We analyzed 35 reports on real-life projects to derive a preliminary sequential model. Then, we performed multiple expert interviews and workshops to validate and refine our model. The result is a framework with variable stages that offers guidelines with enough flexibility to be applicable in complex and heterogeneous corporate environments as well as for small and medium-sized companies. It is structured by the three phases of initialization, implementation, and scaling. They comprise eleven stages relevant during a project and as a continuous cycle spanning individual projects. Together they structure how to manage knowledge and support processes for the execution of robotic process automation implementation projects.}, language = {en} }