Increasingly governments and donors seek to invest in programs and policies that are cost-effective rather than those that just maximize impact. Cost-effectiveness analysis aims to estimate how much an intervention costs per outcome delivered and benchmark this against similar metrics estimated for alternative interventions targeting the same outcome. In this paper, the authors argue that this approach is problematic. This paper proposes an alternative way of presenting the main components of cost-effectiveness -- namely, unit costs and average treatment impacts -- that avoids out-of-sample estimates of either impact or cost, that preserves information about the distribution of impacts coming from experimental or quasi-experimental studies, and that presents a menu of options for different country contexts. In particular, the authors propose replacing league tables with charts like the following that display unit cost alongside estimated average treatment effects. [SREE documents are structured abstracts of SREE conference symposium, panel, and paper or poster submissions.]