Software process improvement is a very important topic. Almost all companies and organizations face the necessity for improvement sooner or later. Sometimes, there is obvious potential for improvement (e.g., if the number of developers does not fit the project size). Nonetheless, fixing all obvious issues does not necessarily lead to a “perfect” project. There are a lot of interdependencies between project parameters that are difficult to detect – sometimes due to the influences of social aspects which can be hardly grasped.We want to support the process of improving daily work by simulating and visualizing how project parameters evolve over time. Our approach is based on building a System Dynamics model that takes into account key performance indicators as well as assumptions about social aspects. In the present case, we chose parameters of capacity, customer satisfaction, and mood. The model uncovers interdependencies between the available parameters. Furthermore, it is able to simulate consequences of different preconditions and incidents during a sprint such as change requests.In this contribution, we present our approach and apply it in a case study with three agile teams in industry. We build a System Dynamics model and use it for sprint simulations. Our analysis determined, e.g., the teams’ productivity during the sprint and their workload each day. The simulation increased the teams’ awareness of the negative influences due to interventions during the sprint.