Executive Summary MAD is a universally accepted forecast error measurement. MAD is generally low in effectiveness in providing feedback to improve the forecast. Introduction MAD, or Mean Absolute Deviation, is one of the most common forecast error measurements in use. MAD is moderately easy to understand and relatively easy to calculate. However, when MAD is…
Executive Summary MAPE is a universally accepted forecast error measurement. MAPE is generally low in effectiveness in providing feedback to improve the forecast. Introduction (Skip if You Watched the Video) MAPE, or Mean Absolute Percentage Error, is a forecast error calculation method that removes negatives from the equation. It is easy to understand and easy…
Executive Summary The standard forecast error measurements are universally accepted, but they are not comparative. Comparative forecast error is rarely discussed. Introduction Forecast error is nearly universally reported without comparison. The forecast error is reported as a single number, which is the forecast using whatever is the current forecasting approach. In companies, people will often…
Executive Summary The standard forecast error measurements are universally accepted. What is rare is to ask the question of whether they direct companies to improve forecast accuracy. Video Introduction: Forecast Error Myth #4: Most Forecast Error Measurement Supports Identifying How to Improve Forecast Accuracy Text Introduction (Skip if You Watched the Video) Forecast error calculation…
Executive Summary Companies typically have Sales and Marketing departments that never have to worry about their forecast error is measured. We cover the problems that arise when Sales and Marketing have no forecast accountability. Video Introduction on Forecast Error Myth #3: Sales And Marketing Have their Forecast Error Measured Text Introduction (Skip if You Watched the…
Executive Summary Companies tend to think that weighing a forecast error and forecasting accuracy is unnecessary, and grouping is just fine. We cover the issues with relying on unweighted forecast error. Video Introduction: Forecast Error Myth #2: An Unweighted Forecast Error Measurement Makes Sense Text Introduction (Skip if You Watched the Video) Unweighted forecast errors…
Executive Summary Surveilling users is the business model for many SaaS and AI companies. We cover what is little discussed, which is how much it is worth to them. Introduction AI proponents and stock followers of FAANG or Facebook Apple Amazon and Google continually promote how AI will leverage Big Data for insights and allow…
Executive Summary Forecast error is often presented as a cut and dried affair. Our research shows that forecast error is measured much differently than generally known. Video Introduction: How is Forecast Error Measured in All Dimensions in Reality? Text Introduction (Skip if You Watched the Video) A brief synopsis of how forecasting error measurement goes…
Executive Summary This page is designed to walk potential customers through the second process after Brightwork Explorer’s demo has been viewed. This article covers the sequence of things to do to get a sample data set to us. Introduction This page is for potential customers who want to go to the next step after receiving…
Executive Summary This is a reference page for articles Brightwork Research & Analysis has used in our research. Introduction This is a page of references on interesting AI articles, videos etc.. References Having a quotation listed here should not be viewed as an endorsement of the source. Some sources are listed because they contain false…