This chapter aims to extend analysis of factors that affect the scaling up of effective practices by presenting an approach to measurement that more deliberately selects, analyzes, and deploys measures that matter to a broad array of stakeholders. Our argument is that attention to measurement early in the research and development of interventions intended for broad dissemination will assist program leaders and policy makers in drawing valid inferences about the fit of an intervention to their context, needs, and intended outcomes and, as a result, will facilitate more rapid and successful scaling of effective interventions. To do this, we argue that reverse-engineering is needed to ensure that programs of research address the concerns and preferences of intended future constituents or consumers of emerging interventions. Further, we argue that this alignment will more likely occur when the social validity of outcomes and interventions is considered across all phases of research and development. Following examples of this approach to measurement in early childhood development and education, we offer design principles to consider when selecting or constructing measures built for scale.