Correspondence analysis of a bivariate table has many different optimality properties. For instance, the scores computed by correspondence analysis linearize both regressions, and maximize the correlation coefficient. We try to generalize both properties to the multivariate situation, using the concept of maximizing any aspect of the correlation matrix, and the concept of simultaneously linearizing all bivariate regressions.