Pairing mean scores with consensus metrics: Extending managers' toolkit for decision-making

Managers often rely on survey or assessment data, using mean scores to guide decision-making. However, mean scores alone do not reflect the underlying level of agreement among people whose scores were used to calculate that mean. Specifically, groups may have heterogeneous attitudes and beliefs, forming sub-group orientations that differ quantitatively and may even conflict. Since mean scores do not capture this variability, relying solely on mean scores can result in poor choices. We therefore propose an extension to the existing approach: pairing mean scores with within-group consensus information to gain a more nuanced understanding of group attitudes and beliefs. In this Perspective Article, we discuss the improvement of coupling means scores with within-group consensus information, demonstrate the need for it to make better management decisions, and elaborate on the advantages and limitations. We believe our extension enables managers (and scholars) to answer new questions and revisit existing ones.