Different individuals will take different approaches to the analysis and interpretation of data. The study attempted to quantify the effect of such individual differences on the quality of geostatistical spatial estimates. Identical spatial data sets were sent to 12 investigators, who independently analyzed the data and produced spatial interpolations. The results varied considerably. Differences in the interpolations could be attributed to differences in choice of methodology, differences in data interpretation, and, in a few cases, errors in procedure. The potential differences in economic and societal costs between decisions based on 'good' vs. 'bad' interpolations warrant a systematic approach to the identification and testing of interpolation methods.