Although developed as a tool in the social sciences, R-mode factor analysis, a multivariate statistical tool, has proven highly effective in studies of groundwater quality. The technique examines the relationships between variables (such as chemical parameters in groundwater), which are shown by a number of cases (such as sampling points). In this study, two examples are presented. The first is of groundwater around a southern African iron ore mine and the second is of groundwater in the vicinity of a southern African municipal sewage disposal works. Groundwater samples were collected, their chemistry analysed and factor analysis was performed on each of the chemical datasets. In the first case study, factor analysis successfully separated signatures due to uncontaminated groundwater (calcium, magnesium and bicarbonate), agricultural activities (potassium and ammonium) and mining activities (sodium, chloride and sulphate). In the second case study, factor analysis did identify a chemical signature (nitrate and phosphate; minor iron) related to the sewage works-but since this signature involved parameters that were within regulated limits, the finding was of limited value for management purposes. Thus although R-mode factor analysis can be a valuable tool studies of groundwater quality, this is not always the case. Multivariate statistical techniques like factor analysis should thus be used as supplementary to, but not in replacement of, conventional groundwater quality data treatment methods.