Scott Armstrong will present findings on the accuracy of forecasts from novel but evidence-based methods for forecasting election results in a keynote speech at the International Symposium on Forecasting in Hong Kong in June. The research is part of the PollyVote Project with colleagues Alfred G. Cuzán, Andreas Graefe, and Randall Jones. We encourage you to tell us what your expectations are for the research, by filling in the questionnaire.

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Do judgmental adjustments of statistical forecasts of demand improve accuracy? Companies certainly believe adjustment helps: a survey by Fildes and Goodwin estimated that 34% of statistical forecasts were subsequently judgmentally adjusted. Now a large empirical study by Fildes, Goodwin, Lawrence, and Nikolopoulos (2009) has shown that on average adjustments do help, but only when something important has happened, is planned, or is expected that has not been included in the statistical model.

While management adjustments can incorporate useful information to improve forecast accuracy, they are expensive and they may introduce bias. Because the managers' adjustments in the study were made in an unstructured manner, it seems likely that further improvements in the use of managerial judgments are possible.