In this paper, we present a tool to help reduce the uncertainty presented in the resource selection problem when information is subjective in nature. The candidates and the "ideal" resource required by evaluators are modeled by fuzzy subsets whose elements are trapezoidal fuzzy numbers (TrFN). By modeling with TrFN the subjective variables used to determine the best among a set of resources, one should take into account in the decision-making process, not only their expected value, but also the uncertainty that they reflect. Respecting this condition, for each candidate an asymmetric index evaluates the distance between the TrFNs for each of the variables and the corresponding TrFNs of the "ideal" candidate, consolidating them through a weighted average that lets the decision-maker make the final comparison between the candidates, and the selection of the one best suited. We apply this contribution to the case of the selection of the product that is best suited for a "pilot test" to be carried out in some market segment.