Standard procedures for processing and interpreting data in personality assessment run the risk of losing their audience. Most notably, relative scaling of data, whether through interindividual or intra-individual comparison, leads to losing either the persons or the variables from view. I set out an alternative, more congenial procedure for handling personality data, consisting of (i) translating assessments to a bipolar bounded scale running from − 1 to + 1, (ii) adopting the uncorrected average cross-product (ACP) as the index of association or correspondence between variables and between individuals, and (iii) applying raw-scores principal component analysis to find factors and types. The ACP index appears eminently fit for handling individual (N = 1) cases. Adoption of the congenial procedure would imply a substantive correction of one's views of individual differences in personality and their structure. Copyright © 2002 John Wiley & Sons, Ltd.