Abstract
This brief article is a direct and invited rejoinder to the comments by David Bartram on our original paper on the use of 360 degree feedback in coaching. Bartram raises important issues which are likely to be of concern and interest to coaches and other users of psychometric tools, even if they do not relate directly to the primary focus of our original paper. This rejoinder reiterates our original approach which was based on a practical workshop on coaching that included a case study reinforcing the benefits of good structural alignment and validity between psychometric trait measures and criterion measures of work effectiveness. This we consider a logical and practical extension of the criterion-centric perspective to measurement, which is a measurement perspective we share with Bartram. Next, our rejoinder addresses how the Great Eight model mapping was used in the analysis as a unit weighted aggregate to predict overall effectiveness at work rather than predict behavioural competencies. Overall effectiveness (and ability) is central to Saville Consulting Wave© Performance 360 criterion measure, and we put this in the context of a hypothetical gap analysis to make the link back to the application in coaching. High level models which lead to aggregation of both predictors and criterion variables are increasingly commonplace in the literature and include Bartram (2005). We further this work by defining a reliable overall (global) effectiveness scale and reporting validities against the total scale source as well as its deaggregated items each of which represents a distinct segment of overall performance. Rather than differentially weighting these predictors we used a priori unit weighting of the Great Eight predictors from Wave© Professional Styles and OPQ32i. We were primarily concerned with testing the hypothesis that the results were non-zero in predicting overall effectiveness in the original article. We confirm that Wave© Professional Styles trait measure of Competency Potential clearly improved on OPQ32i’s prediction of overall effectiveness (p<.05, two tailed, N=169) in this study. Finally, we emphasise the advantages of single co-validation studies in the comparison of the validity of different models and psychometric tools based on fully pre-hypothesised equations to aggregate predictor scales. This approach, paired with other methodologies, we argue will lead to the scientific advancement of the field.