  This paper uses Bayesian tree models for statistical benchmarking in data
sets with awkward marginals and complicated dependence structures. The method
is applied to a very large database on corporate performance over the last four
decades. The results of this study provide a formal basis for making
cross-peer-group comparisons among companies in very different industries and
operating environments. This is done by using models for Bayesian multiple
hypothesis testing to determine which firms, if any, have systematically
outperformed their peer groups over time. We conclude that systematic
outperformance, while it seems to exist, is quite rare worldwide.
