International Conference on Business Process Management 2018 (BPM2018 Sydney). Performance is central to processes management and event data pro-vides the most objective source for analyzing and improving performance. Currentprocess mining techniques give only limited insights into performance by aggre-gating all event data for each process step. In this paper, we investigate processperformance of all process behaviors without prior aggregation. We propose theperformance spectrumas a simple model that maps all observed flows betweentwo process steps together regarding their performance over time. Visualizing theperformance spectrum of event logs reveals a large variety of very distinctpatternsof process performanceand performance variability that have not been describedbefore. We provide a taxonomy for these patterns and a comprehensive overviewof elementary and composite performance patterns observed on several real-lifeevent logs from business processes and logistics. We report on a case study whereperformance patterns were central to identify systemic, but not globally visibleprocess problems.