We propose to summarize the variable’s distribution by specifying a grid of proportions that divide its mean into a sum of components. From these components, one can easily derive the variable’s expected value on different segments of its support. Our approach results in a set-valued summary measure, which we refer to as compound expectation, that describes the variable’s entire distribution in terms of expected values, and whose elements relate to specific fractions of the variable’s support.