Sometimes companies implement a forecasting system but do not realize the anticipated gains in the forecast accuracy. Very often, it is not the actual software but the setup that is to be blamed. And I do not mean the setup at the technical (parameter level) but more the process level. Read this blog post on how to get the setup right.

Supply Chain Planning deals with the future and therefore uncertainty with economy. As a result, the planners sometimes have to question other people’s assumptions. Whether for this or some other reason, they do not get credit that is due to them for the great job they do. Eric Wilson from Tempur Sealy gives them the due credit and then some and calls them the super heroes of business. We agree!

Are the researchers in the academic world aligned with the expectations and needs of the business world when it comes to the world of forecasting? Or are the two very different? What can the academe do that will be of value to the business folks? Read on to see some of my thoughts on this topic.

Have you ever wondered whether you should forecast: Bottom-up? Top-down? Middle-Out? It turns many in the demand planning profession do. Read along to see why you can do all of that and more with attribute based demand planning.

Should one forecast at the SKU-Customer-Location level and aggregate the results up? Or should one forecast at the product-family-region level and dis-aggregate the results down? Or should one do both and try to triangulate the results? Which method gives the best results to the business? Let us look at this together.

In one of my previous posts, I wrote about using coefficient of variation (CV) as a predictor of forecastability. In...

Key Point: Coefficient of Variation is not a perfect measure of forecastability. However, if used properly, it can add value...

You have a favorite forecast accuracy metric(s) you’ve been practicing within the organization for a while, and now you think...

I saw this news article on CNN (here) about our planet's earth bigger, older cousin. Quite an interesting discovery if...

I spent some time discussing MAPE and WMAPE in prior posts. In this post, I will discuss Forecast BIAS. Forecast BIAS can...

In our line of work at Arkieva, when we ask this question of business folks: What is your forecast accuracy?...

Key Points on MAPE: Mean Absolute Percent Error (MAPE) is a useful measure of forecast accuracy and should be used...