Rethinking Demand Planning [Episode 01] Introduction

Welcome to our series on rethinking demand planning in an era of increasing variability. Traditional methods rely on outdated forecasting models, treating demand as a single monolithic dataset, but this approach is no longer effective.

Why are forecasts failing? Post-pandemic history is distorted, and 50% of SKUs are simply not forecastable using old methods.
What’s the new approach? Forecastability. Demand must be categorized into flows based on high, medium, and low forecastability.
How do we improve? Traditional metrics like WMAPE don’t drive better forecasts. Instead, we need Forecast Value Add (FVA) to measure the quality of forecast improvements over time.

With o9’s Graph Cube technology, businesses can store, analyze, and optimize complex data at scale—unlocking better demand planning in an uncertain world.

Learn more about the o9 Demand Planning software

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