Does updating judgmental forecasts improve forecast accuracy?

This study investigates whether updating judgmental forecasts of time series leads to more accurate forecasts by examining the impact of temporal information on forecast accuracy and found improved forecast accuracy from updating time series forecasts when new temporal information arrived if the time series was trended.

Abstract

This study investigates whether updating judgmental forecasts of time series leads to more accurate forecasts. The literature is clear that accurate contextual information will improve forecast accuracy. However, forecasts are sometimes updated when pure temporal information like the most recent time series value becomes available. The key assumption in the latter case is that forecast accuracy improves as one gets closer in time to the event to be forecasted; that is, accuracy improves as new times series values become available. There is evidence both to support and to question this assumption. To examine the impact of temporal information on forecast accuracy, an experiment was conducted. The experiment found improved forecast accuracy from updating time series forecasts when new temporal information arrived if the time series was trended. However, there appeared to be no value in updating time series forecasts when the time series were relatively stable.