Rethinking Demand Planning [Episode 04] Data Models and Engines

In Episode 4 of our demand planning series, we dive into the world of data models and engines—the critical components that power accurate forecasting and planning.

Now that you've learned how to segment demand flows using volume and Coefficient of Variation (CoV), it’s time to test and measure the right models and engines for each flow.

What you’ll learn in this episode:
What a data model is and how it connects demand data through nodes, edges, and hierarchies using the o9 Graph Cube
The role of demand history, drivers, granularity, and horizon in modeling
How engines use data models to generate forecasts—via machine learning, best-fit, and ensemble methods
Why tuning and frequency matter for engine performance
This episode sets the stage for evaluating whether your planning outputs are actually working—which we’ll explore next.

Watch now and learn how to power your demand flows with the right data models and engines.

Learn more about the o9 Demand Planning software

Building a superior forecasting model with AI/ML. Download the guide