The University of Bayreuth, the Vienna University of Economics and Business, and the University of Liechtenstein are collaborating on the Erasmus+ funded project "Developing Process Mining Capabilities at the Enterprise Level." Process mining is a rapidly growing technology that deals with managing and enhancing business processes. The potentials of process mining are vast and the market is anticipated to grow tenfold within the next ten years. However, there is a lack of knowledge regarding how to implement, utilize, and manage this digital technology.

Our work intends to support practitioners, and future students, in understanding, estimating, and managing the implications of process mining. We are among the first to point out the importance of developing process mining capabilities, and we contribute to the field by providing a conceptualization of such process mining capabilities. Given the importance attached to process mining in organizations, and the important question of how organizations can benefit from process mining, we also expect our findings to be widely adopted in practice. To this end, we join recent calls for a better understanding of the managerial and organizational aspects of process mining and contribute to the discourse on the adoption and use of process mining in organizations.

 

Kipping, G., Djurica D., Franzoi, S., Grisold, T., Marcus, L., Schmid, S., vom Brocke, J., Mendling, J., & Röglinger, M. (2022). How to Leverage Process Mining in Organizations - Towards Process Mining Capabilities. Proceedings of the 20th International Conference on Business Process Management, Münster, Germany. Springer, Cham. (VHB_3: C; CORE: A)

https://doi.org/10.1007/978-3-031-16103-2_5

https://www.researchgate.net/publication/363343978_How_to_Leverage_Process_Mining_in_Organizations_-_Towards_Process_Mining_Capabilities

 

Badakhshan, P., Wurm, B., Grisold, T., Geyer-Klingeberg, J., Mendling, J., vom Brocke, J. (2023), Creating Business Value with Process Mining. Journal of Strategic Information Systems. (IF: 14.682; ABS_2021: 4; VHB_3: A; ABDC_2022: A*)

https://doi.org/10.1016/j.jsis.2022.101745

https://www.researchgate.net/publication/364314897_Creating_Business_Value_with_Process_Mining

 

Hartl, S., Franzoi, S., Grisold, T., & vom Brocke, J. (2023). Explaining Change with Digital Trace Data: A Framework for Temporal Bracketing. In Bui, T. X. (Ed.), Proceedings of the 56th Hawaii International Conference on System Sciences, Maui, Hawaii. ScholarSpace. (VHB_3: C)

https://doi.org/10.24251/HICSS.2023.689

https://www.researchgate.net/publication/363891697_Explaining_Change_with_Digital_Trace_Data_A_Framework_for_Temporal_Bracketing

 

Drechsler, K., Grisold, T., Gau, M., & Seidel, S. (2022). Digital Infrastructure Evolution: A Digital Trace Data Study. Proceedings of the 43rd International Conference on Information Systems, Copenhagen, Denmark. AIS eLibrary. (VHB_3: A)

https://aisel.aisnet.org/icis2022/is_design/is_design/4

https://www.researchgate.net/publication/364199024_Digital_Infrastructure_Evolution_A_Digital_Trace_Data_Study

 

Grisold, T., Gau, M., & Yoo, Y. (2022). Studying the Co-evolution of Individual Actions and Emergent Social Structures using Digital Trace Data. Proceedings of the 43rd International Conference on Information Systems, Copenhagen, Denmark. AIS eLibrary. (VHB_3: A)

https://aisel.aisnet.org/icis2022/adv_methods/adv_methods/11

https://www.researchgate.net/publication/364197231_Studying_the_Co-evolution_of_Individual_Actions_and_Emergent_Social_Structuring_Using_Digital_Trace_Data

 

Franzoi, S., Grisold, T., & vom Brocke, J. (2023). Studying Dynamics and Change with Digital Trace Data: A Systematic Literature Review. Proceedings of the 31st European Conference on Information Systems, Kristiansand, Norway. AIS eLibrary. (VHB_3: B)

https://aisel.aisnet.org/ecis2023_rp/212

https://www.researchgate.net/publication/370050675_Studying_Dynamics_and_Change_with_Digital_Trace_Data_A_Systematic_Literature_Review

This work has been funded by the ERASMUS+ program of the European Union (EU Funding 2021-1-LI01-KA220-HED-000027575 “Developing Process Mining Capabilities at the Enterprise Level”). We would like to express our gratitude to the European Union and AIBA Liechtenstein for their support.