Software metrics are measurements of development processes, products, and resources. Once these measurements have been specified and collected they can be used as variables in empirically calibrated models for a wide range of project management purposes; including the task of predicting development effort based on some combination of size, complexity, and developer experience metrics. One difficulty encountered when using traditional algorithmic approaches to estimation has been the collection of the appropriate metrics required to use the model in its predictive capacity. Project managers are generally unable to make precise quantitative estimates for the independent variables, especially early in system development when these models are at their most valuable. The alternative of using qualitative values for the inputs, as in fuzzy logic, has been suggested but the stability and consistency of such labels has yet to be established, as well as considering the elicitation techniques available for deriving the membership functions. In this paper we examine the perceptions of data model size, functionality size, developer experience, and project effort in terms of three fuzzy membership functions from two separate surveys of project managers, each with a very different approach. The consistency of results across the two surveys is examined, and some discussion about the strengths and weaknesses of the two approaches is provided.