Medicinal chemists rely on their intuition to make decisions regarding the course of a medicinal chemistry program. Our ability to accurately and efficiently process large data sets routinely requires that we reduce the volume of information to manageable proportions. This prioritization process, however, can be affected by intuitive biases. One such situation is structure-activity relationship (SAR) analysis in nonadditive data sets in which attempts to intuitively predict the activity of compounds based on preliminary data can lead to erroneous conclusions. Matrix analysis can be a useful tool to accurately determine the nature of the SAR and to improve our decision-making process during an analoging campaign.