Development of a Practical and Effective Forecasting Performance Measure

Forecasting is a vital part of the planning process of most private and public organizations. A number of extant measures: Mean Absolute Deviation (MAD), Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE), have been used to assist in judging the forecast accuracy, and concomitantly, the consequences of those forecasts. In this paper we introduce, evolve, and implement a practical and effective method for assessing the accuracy of forecasts, the Percent Forecast Error (PFE). We test and evaluate the PFE, and modified optimized PFE (MOPFE), against the MAD, MSE, and MAPE measures of forecast accuracy using three time series datasets.