Daniel Viner

Daniel Viner is an alumnus of Friedrich-Alexander University Erlangen-Nürnberg (FAU) in Germany. He concluded his Master's studies in Industrial Engineering and Management in 2021, specializing in process improvement with a focus on Lean Management and Process Mining.

As part of his Master thesis, Daniel conducted a Conjoint survey to analyze the preferences of executives and other stakeholders in the Process Mining software selection phase. Process Mining is a relatively young technology that helps companies reconstruct their real “as is” processes based on event data extracted from databases and IT systems (e.g. ERP). The achieved transparency serves as a basis to identify bottlenecks, discover coherence, and improve processes.

In his ACBC study, Daniel investigated which characteristics of Process Mining software influence the stakeholders’ purchasing behavior. Conformance Checking and Process Monitoring appeared as the main decisive features. Process Discovery, the fundamental Process Mining technique, played a subordinate role for practitioners in selecting suitable PM software. With his research, Daniel shed light on the practical relevance of recent developments in the research community. Process Mining researchers are encouraged to better accommodate the trade-off between practicability and correctness of process models (DFGs).