How to Take Your Demand Planning Skills to the Next Level
Data Science will allow demand planners to bring their forecast accuracy to unprecedented levels. Learning data science is possible for anyone — but will require time.
This article was initially published in Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning (Wiley and SAS Business Series)
Based on my experience as a consultant working with clients on forecasting models and teaching forecasting to master students, I see three main ideas that will take any demand planner to the next level. After discussing those ideas, I will show you how to get started using machine learning for demand forecasting.
Taking Demand Planning Skills to the Next Level
1. Machine Learning is easy to use. You can do it.
While the first machine learning models date back to the 1960s with the work of Morgan & Sonquist (1963) on decision trees, and Rosenblatt (1957) on perceptrons (the inner neurons of a neural network), the revolution of machine learning in forecasting started in the mid-2010s.
