Executive Summary Calculating a statistical forecast is far more straightforward to create than is often thought in practice. We cover the calculation of the forecast and what it means. Introduction How do you calculate a forecast is a common question that we receive. Because statistical forecasts, in developed countries at least, are generated by systems,…
Executive Summary Being able to explain forecast accuracy is essential to getting people to consider forecast accuracy important. We cover the most basic way to explain forecast accuracy. Video Introduction: How Do You Explain Forecast Accuracy? Text Introduction (Skip if You Watched the Video) The question of how do you explain forecast accuracy is a…
Executive Summary MAE is a universally accepted forecast error measurement. MAE is generally low in effectiveness in providing feedback to improve the forecast. Introduction MAE, or Mean Absolute Error, is easy to understand and calculate. It is also proportional. MAE is a universally accepted forecast error measurement; even still, MAE is generally moderate ineffectiveness in…
Executive Summary MASE is one of the alternatives presented for limitations with MASE forecast error measurement. MASE is an interesting entry into forecast accuracy. Video Introduction: How MASE is Calculated for Forecast Error Measurement Text Introduction (Skip if You Watched the Video) How MASE for Mean Absolute Scaled Error is a forecast error measurement calculation…
Executive Summary Most companies are dissatisfied with their forecast error but are not aware of how to forecast error can be reduced. We cover some of the significant shortcomings and, therefore, areas of opportunity for forecast improvement. Video Introduction: How Can Forecast Error Be Reduced? Text Introduction (Skip if You Watched the Video) There is…
Executive Summary A frequently asked question is what is a good or an acceptable forecast accuracy. Is there a real answer to this question? Introduction What is good forecast accuracy is a common question. Companies typically want to know if their forecast accuracy is where it should be. However, this question opens up another question…
Executive Summary sMAPE is one of the alternatives presented for limitations with MAPE forecast error measurement. sMAPE is generally low in effectiveness in providing feedback to improve the forecast. Introduction sMAPE, or Symmetrical Mean Absolute Percentage Error, is a significant but uncommon forecast error measurement. However, its complexity in calculation and difficulty in explanation make…
Executive Summary Companies often have statistical forecast models assigned to product locations, but without knowing if the model assignment is up to date. Model assignment also allows for the overall product database to be profiled. Introduction The statistical forecast model assignment is which statistical forecasting models apply to which product locations combinations. This does not…
Executive Summary Coronavirus is having an enormous impact on purchasing. Companies need to perform adjustments on their demand history to account for Coronavirus. Introduction Coronavirus is an international pandemic that so far has had the following effects on demand. See our references for this article and related articles at this link. A dramatic spike in…
Executive Summary RMSE is a universally accepted forecast error measurement. RMSE is generally low in effectiveness in providing feedback to improve the forecast. Introduction RMSE, or Root Mean Square Error, is listed as one of the significant forecast error measurements. However, its complexity in calculation and difficulty in explanation make it a distant third to…