Abstract ABSTRACT: This study provides real-world evidence about the validity of the results of an experimental lens model study evaluating the prediction accuracy of corporate executives versus that of regression models. The decision task involves predictions of annual advertising page sales used in current operating budgets at Time magazine. Actual quarterly predictions by Time executives for the years 1977-1981 are compared with predictions made by regression models that were based on data available to the executives when they made their predictions. Comparisons of executives and models are based on an accuracy criterion of actual absolute error. The present results agree with prior experimental results, which show that models predict more accurately than people. Therefore, one of the principal conclusions from lens model research--that simple models might successfully replace people in certain time-consuming, repetitive decision tasks--is supported. However, consistent underprediction by executives is observed. A crude correction for mean error is applied to predictions made by executives and by regression models, with the result that the executives' corrected predictions are more accurate than the models' corrected predictions.
Alison Hubbard Ashton (Sun,) studied this question.