Formal methods have always been an integral part of the BPM lifecycle. They are mathematically grounded techniques used to specify and analyze complex systems with a high degree of precision. In BPM, they help ensure that processes are correctly specified and capable of achieving the intended outcomes, by detecting design flaws and verifying compliance with defined goals. Among these techniques, the Constraint Satisfaction Problem (CSP) stands out as a powerful approach to specifying and solving problems with clearly defined constraints. CSP techniques are known for their high performance, yet a major barrier to broader use lies in the difficulty of defining suitable encodings, which require expert knowledge. Nevertheless, modern tools have made substantial progress in improving CSP accessibility for non-experts. In this paper, we define CSP, motivate its use in BPM, and showcase how two CSP instances, one over Boolean and the other over structured domains, can be used to solve BPM analysis problems via suitable encodings, and then by exploiting state-of-the-art CSP tools. As the main outcome, we would like to motivate the use of CSP-based formal methods and their integration into process analysis.