SAS remains widely used in regulated industries like clinical research, banking, and insurance due to its governance, auditability, and deep integration into established workflows. Organizations often keep SAS longer than necessary because of accumulated undocumented logic, system interdependencies, and shrinking specialist skills. Migrating to open source tools like R or Python is feasible but requires a phased, validated approach — running old and new systems in parallel, documenting differences, and rebuilding processes rather than just translating code. A hybrid approach using both SAS and R is often the safest path to modernization. The post concludes with a service pitch from Jumping Rivers, who offer SAS-to-R migration consulting and validation tooling.
