Effective evaluation requires balancing efficiency with depth, focusing on the data that matter most for accurate identification and meaningful recommendations. This session explores a selective and systematic approach to evaluation—one that begins with a strong foundation of core data and strategically expands only as needed. Participants will examine how to align assessment decisions with referral concerns, use existing data to inform test selection, and synthesize findings through converging evidence. Through case studies and practical application, evaluators will learn how to design defensible evaluations that are both comprehensive and purposeful. This session is aligned with the evaluation reevaluation components of the TEA-required self-assessment.