Processes are complex phenomena that emerge from the interplay of human actors, materials, data, and machines. Process science is the discipline of studying and improving processes by developing effective methods and techniques to do so. The field has developed mature theories, models, and solutions for studying and improving process executions from the control-ow perspective. Also, the limitations of control-ow focused thinking are well-known in the field, leading to active involvement of various disciplines to study phenomena “beyond” control-ow. However, it remains challenging to relate models and techniques of various fields to the dominant control-ow oriented paradigm. This tutorial introduces several recently developed simple models that naturally describe phenomena beyond control-ow, but are inherently compatible with control-flow oriented thinking. We discuss the Performance Spectrum to study performance patterns and their propagation over time, Event Knowledge Graphs to study networks of behavior over data objects and actors, and Proclets as formal model that allows reasoning across control-ow, data object, queue and actor behavior. For each model, we discuss which phenomena can be studied, which insights can be gained, which tools are available, and to which other fields they relate.