Although missing data are often viewed as a challenge for applied researchers, in fact missing data can be highly beneficial. Specifically, when the amount of missing data on specific variables is carefully controlled, a balance can be struck between statistical power and research costs. This article presents the issue of planned missing data by discussing specific designs (i.e., multiform designs, longitudinal wave-missing designs, and 2-method measurement designs), introducing the power and cost benefits of such scenarios to applied education and educational psychology researchers.