I'll be delivering a short introduction, covering the disappointing state of real life business forecasting in contrast to the potential shown in forecasting research and the M competitions. And then George Habek of CT Global Solutions will illustrate the use machine learning and traditional time series forecasting methods in SAS.
The live event is Tuesday, December 15 at 2:00pm EST (19:00 GMT). Registration is free.
About the webinar:
It has long been recognized that the real-life practice of forecasting falls well short of the potential exhibited in academic research and forecasting competitions. In 2018’s M4 competition, a simple benchmark combination method reduced error by 17.9% compared to a naïve (“no change”) forecast. The top six performing methods in M4 further reduced error by over 5% compared to the benchmark. But in forecasting practice, just bettering the accuracy of a naïve forecast has proven to be a surprising challenge.
Join SAS and CT Global Solutions, in association with Foresight: The International Journal of Applied Forecasting, as they discuss reasons why forecasting practice falls short of theory, and ways to bridge the gap