One central challenge public organizations face is coping with uncertainty—something that arises from both internal processes and environmental changes. Despite calls for greater attention to topics of risk and uncertainty, the field has fairly limited theoretical or empirical tools for studying such issues. This study introduces a novel approach to studying uncertainty regarding performance. Drawing on prior studies of organizational change and executive turnover, we argue that replacing an executive is an example of an organizational intervention with the potential to alter not only the expected performance level but also the unpredictability of future performance. Using a panel dataset of approximately 4,000 U.S. hospitals over 10 years, we test how executive turnover is associated with stability versus unexplained variance in organizational performance. To estimate this relationship, we introduce heteroskedastic regression models to the literature, while also drawing on the familiar autoregressive function to explain performance. Our results indicate that executive turnover is associated with decreased stability (and increased unpredictability) in patient satisfaction. For clinical outcomes, the results are more mixed, but we find some indication that executive succession decreases stability while increasing predictability, with outlier performers tending to regress back toward the mean.