It is fairly common, following a principal component analysis, to rotate components in order to simplify their structure. Here, we propose an alternative to this two-stage procedure which involves only one stage and combines the objectives of variance maximization and simplification. It is shown, using examples, that the new technique can provide alternative ways of interpreting a dataset. Some properties of the technique are investigated using a simulation study.