How to Forecast High-Profit Intermittent Products?

How should you deal with low-volume intermittent products? We’ll discuss forecasting, inventory and supply chain optimization

📊 Should You Optimize Your Forecasting Process?

Forecasting low-volume products have always been a challenge. Historically, Croston models have been used to forecast intermittent demand (see my article Forecasting Intermittent Demand with the Croston Model). More recently, Nikolaos Kourentzes proposed a temporal aggregation method (see it here). It is usually good with intermittent demand, but not perfect.

To improve low-volume products further, you can also work with judgmental forecasts (for more info, see the second upcoming edition of my book Data Science for Supply Chain Forecasting or the book The business forecasting deal by Michael Gilliland). Using shared information by your customers or looking at the sales pipeline with your sales team might help.

In the end, an optimized, accurate forecast model will only marginally improve the forecast accuracy of low-volume items — their demand will still be inherently highly variable. What is the added value of knowing that next week’s forecast is 0.12 units and not 0.11?