Making AI Explainable in Demand Forecasting: Why It Matters More Than Ever

As AI in demand forecasting begins to gain traction, we must manage trade-offs between improvements in forecast accuracy and explainability. In this article I reveal the importance of being able to explain how a forecast is derived so executives can make informed decisions without relying on a black box approach. I provide a matrix revealing the trade-offs between performance, explainability, interpretability and accuracy for different forecasting methods of varying complexity. I also introduce three frameworks to explain statistical models, black models, and advanced AI models to facilitate understanding and adoption of your forecasts among ...