In an increasingly dynamic world, business processes must be able to respond to frequently occurring and random changes during their execution. Consequently, this means that the process models must be able to handle this complexity and enable process analysts to derive the right conclusions quickly. However, current approaches in the field of process mining do not distinguish between process activities associated with change and those with routine. This condition leads to more complicated, overloaded, and sometimes misguided process visualizations that make it difficult for analysts to evaluate them. In this paper, we address the research problem by conceptualizing a new type of process activity that we call change activity which we base on causal knowledge. We thereby extend the causal process mining approach with another important aspect for handling random occurrences of events. We evaluated our findings through a survey of process mining experts from research and practice. Our results indicate that a dedicated visualization of change activities reduces the complexity of process visualizations. In addition, unimportant information is hidden and important information is highlighted so that analysts can make better assessments.