Why is it crucial to identify “outliers” in Process Mining?

Identifying outliers in Process Mining is crucial because these anomalies can signal inefficiencies within the process. Outliers represent instances that deviate significantly from the expected pattern or norm in process execution. By recognizing these deviations, organizations can investigate the underlying causes, which may reveal bottlenecks, redundancies, or other issues that hinder optimal performance. This insight allows for targeted improvements, enabling a more efficient and effective process management strategy.

In contrast, the other choices do not accurately reflect the role of outliers. For instance, outliers do not indicate compliance with established processes; instead, they may suggest non-compliance or deviations that require attention. Similarly, outliers do not highlight expected behaviors; rather, they represent unexpected behaviors that can disrupt process flow. Lastly, while maintaining process uniformity is important, outliers typically indicate areas where uniformity is lacking, rather than being beneficial to it. Therefore, acknowledging the presence of outliers and understanding their implications is essential for continuous improvement in process management.