In their comprehensive apologetic treatment of synthetic validity, Johnson et al. (2010) echo Hough (2001), advocating development of a central synthetic validation database, which would serve as a repository of validity information to support future synthetic validation efforts. They offer two potential approaches for developing such a database. The first entails the conduct of “a large-scale study in which tests are administered to and performance ratings gathered on incumbents in a large number of jobs in a variety of organizations.” The authors consider this approach to be “ideal but impractical,” largely because of the scope and cost of the data collection required and the resulting investment required by any sponsoring organization. The second entails the conduct of multiple local studies to generate empirical estimates of relationships between measures of various predictor constructs and a standardized set of job components. Johnson et al. consider this approach more practical, citing Meyer, Dalal, and Bonaccio (2009) as a benchmark example.