  Complexity is an important characteristic of any business process. The key
assumption of much research in Business Process Management is that process
complexity has a negative impact on process performance. So far, behavioral
studies have measured complexity based on the perception of process
stakeholders. The aim of this study is to investigate if such a connection can
be supported based on the analysis of event log data. To do so, we employ a set
of 38 metrics that capture different dimensions of process complexity. We use
these metrics to build various regression models that explain process
performance in terms of throughput time. We find that process complexity as
captured in event logs explains the throughput time of process executions to a
considerable extent, with the respective R-squared reaching up to 0.96. Our
study offers implications for empirical research on process performance and can
serve as a toolbox for practitioners.
