Effects of personality on the efficacy of judgmental adjustments of statistical forecasts

Abstract

PurposeThe purpose of this paper is to investigate the effects of personality dimensions (conscientiousness, neuroticism, extraversion, agreeableness, openness to experience, locus of control) on the efficacy of judgmental adjustments of statistical forecasts.Design/methodology/approachThis paper uses a two-level hierarchical linear model to analyze a large data set obtained from an organizational setting (a quick service restaurant chain) that includes 3,812 judgmental adjustments of sales forecasts made by 112 store managers.FindingsThe results indicate that the average forecast accuracy improves as a result of judgmental adjustments, but performance of individual forecasters varies considerably based on their personality. Specifically, the trait of openness to experience tends to improve forecast accuracy while extraversion and external locus of control have negative effects.Originality/valueIntegration of human judgment with analytics algorithms is a major challenge for organizations. Documenting the impact of these traits on forecast accuracy opens the door for forecasting support system design, training, personnel selection and correction strategies that can be applied to judgmental adjustments.