Tips For Cleaning Your Dirty Data
We all work with data but we're not all data people. We must recognize that everybody who interacts with data plays an important part in cleaning and maint... Read More...
Analytics
Transitioning From Times Series To Predictive Analytics
I recently had a fascinating and enlightening conversation with one of the leading figures in predictive analytics and business forecasting, Dr. Barry Keati... Read More...
My Favorite Forecasting Model
One of the questions I get asked most frequently is “What is your favorite forecasting model?” My answer is “it depends” because not all problems need a ham... Read More...
How I React When Forecasted Demand Deviates from Actual Demand
As I have written about before in a previous article, Forecasting Materials Usage At An Electric Utilities Company, forecasting efforts for an electric util... Read More...
Tracking Forecasting Error With An Excel Model (With Free Download)
Peter Drucker’s famous axiom “You can't improve what you don't measure” is particularly relevant to business forecasting. As Demand Planners, we want to mea... Read More...
The 4 Cornerstones Of An Effective Demand Review
S&OP processes always include a demand review step. There are plenty of articles, webinars, and blogs about how to set up and optimize a Deman... Read More...
Simplifying Python For Business Forecasting With Mariya Sha
I recently spoke to Mariya Sha, Python guru and star of the Python Simplified YouTube channel. I asked her how forecasters and Demand Planners can get start... Read More...
Will AI Revolutionize Demand Planning? Maybe…
Have you ever heard the Chinese proverb about the farmer? I originally heard it on a podcast featuring Dan Bilzerian. The story goes: A farmer and his... Read More...
3 Sources Of Forecast Error To Avoid
Those seeking to reduce error can look in three places to find trouble: The data that go into a forecasting model, the choice of a forecasting method, and t... Read More...
How Forecastable Are Your Items?
Not all items are created equal. Not all customers are not created equal. We know this to be self-evident. If this is true, why do we assume our accuracy sh... Read More...