Strong validation evidence starts with strong criterion measures—but outcome data are often overlooked, leading practitioners to rely on familiar measures despite known limitations. This panel explores how assessment professionals can strengthen validation by selecting better outcome criteria, improving data quality, and using innovative alternatives when traditional measures fall short. Drawing on examples from education, employment, and licensure/certification, panelists will discuss objective indicators, proxy measures, and emerging approaches that better reflect success in today's evolving assessment landscape. Through a moderated discussion and audience Q&A, attendees will gain practical strategies for evaluating criterion quality, addressing common data challenges, balancing scientific rigor with real-world constraints, and rethinking validation as AI and changing workforce demands reshape what assessments are expected to predict.