Summary Stepped wedge and other multiple-period cluster randomized trials, which collect data from multiple clusters across multiple time periods, are being conducted with increasing frequency; statistical research into these designs has not kept apace. In particular, some stepped wedge designs with missing cluster–period “cells” have been proposed without any formal justification. Indeed there are no general guidelines regarding which cells of a stepped wedge design contribute the least information toward estimation of the treatment effect, and correspondingly which may be preferentially omitted. In this article, we define a metric of the information content of cluster–period cells, entire treatment sequences, and entire periods of the standard stepped wedge design as the increase in variance of the estimator of the treatment effect when that cell, sequence, or period is omitted. We show that the most information-rich cells are those that occur immediately before or after treatment switches, but also that there are additional cells that contribute almost as much to the estimation of the treatment effect. However, the information content patterns depend on the assumed correlation structure for the repeated measurements within a cluster.