This workshop will introduce Coincidence Analysis (CNA), a relatively new member within the family of Configurational Comparative Methods.  CNA is specifically designed to analyze causal complexity, which is common in implementation research. Presenters will discuss the types of studies for which CNA is useful, provide worked examples of applying CNA to datasets, and share practical resources for using CNA.  Participants will learn how CNA works through hands-on exercises involving Boolean algebra, the bottom-up algorithm used by CNA and model performance measures like coverage.