In a previous experiment, we have shown that risk assessments of purchasing experts are certainly not better than that of subjects untrained in purchasing, and worse than the decisions made by formal models (J. Purchas. Supply Manage. 9 (2003) 191-198). Since both these results are rather counterintuitive, we conducted a series of experiments geared at replication and extension of these findings. These new experiments show that our previous results are robust, and reveal an additional finding that is both worrying and puzzling. It actually seems to be the case that for the purchasing decision tasks in our experiments, experts perform worse with growing experience. It therefore seems that, at least for the kinds of purchasing decisions under study, it does not make much sense to use expert judgments at all. However, we show that there is a way in which expert judgments can be used in combination with formal models to improve the predictive accuracy of purchasing predictions. In our case, superior predictions are made when we combine the prediction of a formal model with the prediction of the 'average expert', thereby combining the robust linear trends as encapsulated in the formal model with the more intuitive configural rules used by experts. We provide several explanations for this phenomenon.