The Smart Forecaster
Pursuing best practices in demand planning,
forecasting and inventory optimization
Most demand forecasts are partial or incomplete: They provide only one single number: the most likely value of future demand. This is called a point forecast. Usually, the point forecast estimates the average value of future demand. Interval forecasts provide an estimate of the possible future range of demand (i.e. demand has a 90% chance of being between 50 – 100 units). Probabilistic forecasts take it a step further and provide additional information. Knowing more is always better than knowing less and the probabilistic forecast provides that extra information so crucial for inventory management. This video blog by Dr. Thomas Willemain explains each type of forecast and the advantages of probabilistic forecasting.
[inbound_button font_size=”20″ color=”#00a429″ text_color=”#ffffff” icon=”” url=”http://www.screencast.com/t/Ut4I5dOY8″ width=”” target=”_blank”]Watch Now[/inbound_button]
Point forecast (green) shows what is most likely to happen. The Interval Forecast shows the range (blue) of possibilities.
Probability Forecast shows the probability of each value occurring
Smart Software is pleased to announce the award of US Patent 11,656,887. The patent directs “technical solutions for analyzing historical demand data of resources in a technology platform to facilitate management of an automated process in the platform.
What is the wiggle effect? It’s when your statistical forecast incorrectly predicts the ups and downs observed in your demand history when there really isn’t a pattern. It’s important to make sure your forecasts don’t wiggle unless there is a real pattern. Here is a transcript from a recent customer where this issue was discussed:
A statistical forecast of zero can cause lots of confusion for forecasters, especially when the historical demand is non-zero. Sure, it’s obvious that demand is trending downward, but should it trend to zero?