The Smart Forecaster
Pursuing best practices in demand planning,
forecasting and inventory optimization
Improve Forecast Accuracy, Eliminate Excess Inventory, & Maximize Service Levels
In this video tutorial Dr. Thomas Willemain, co–Founder and SVP Research at Smart Software, presents Regression Analysis, a specialized statistical modeling technique to identify and harness leading indicators to achieve more accurate forecasts. Regression analysis is a statistical procedure to estimate the relationship between a response variable and one or more predictor variables. Housing starts, for example, might be a good leading indicator of vinyl siding demand. Tom explains how and when to use regression analysis and works through a practical example.
Do your statistical forecasts suffer from the wiggle effect?
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:
How to Handle Statistical Forecasts of Zero
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?
Smart Software’s article has won 1st place in the 2022 Supply Chain Brief MVP Awards Forecasting category!
Smart Software is pleased to announce that our article “Managing Inventory amid Regime Change” has won 1st place in the Forecasting category of the 2022 Supply Chain Brief MVP Awards.