The present research explored the effects of various strategies of weighting criterion dimensions on adverse impact, minority hiring, and job performance. In particular, this research compared strategies that vary the weight of task and contextual performance dimensions in calculating a composite criterion measure, in terms of their effects on regression weights assigned to predictors and effects on adverse impact, percentage of minorities hired, and predicted performance. With a Monte Carlo simulation based on meta-analytic evidence of multiple predictor and criterion relationships, the authors illustrate how organizations might think through the consequences of varying conceptualizations of job performance in selection contexts. Approaches that simultaneously increase aggregate predicted job performance and reduce adverse impact are described and illustrated.A consistent body of research has offered support for conceptualizations of the job performance domain that emphasize the multidimensional nature of performance in organizations (e.g.,

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