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abstract

Forecasting one’s own performance on tasks is important in a wide range of contexts. Over-forecasting can lead to an unresponsiveness to advice and feedback. In group forecasting, under-forecasting may lead individuals to discount valuable inputs that they could contribute. Research shows that those who perform relatively poorly in tasks tend to make predictions that are too high, while high performers tend to under-forecast their performances. Several explanations have been put forward for this ‘regressive forecasting’, such as a lack of metacognitive skills in poor performers and a false-consensus bias in high performers. Others claim that the bias is simply an artefact of regression. In this study, people were asked to forecast their performances on six multiple-choice tests. The results suggest that a simple explanation based on the anchoring and adjustment heuristic would account for the phenomenon, at least in part. © 2015 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

6. Discussion

The analysis above raises three questions: 1. Is it possible that other anchors were being used, rather than the prediction of a ‘norm’ mark, which appears to be represented by the expected cohort mean? 2. Is it possible that the prediction of the cohort mean anchored on the individual’s forecast of their marks, rather than the other way round? 3. Why would values distributed around 72% act as anchors? In this section we will begin by addressing these issues, before discussing various design issues associated with this study, such as why some tools and methods, such as verbal protocol analysis, were not used; why we used a task structure based on forecasting marks on multiple-choice tests; whether the framing of the questions would have had an impact on the quality of the data collected; and whether this task structure is suitable for drawing inferences in a teamwork setting.