Can Improving Forecast Accuracy Address Our Demand Planning Woes?
If “the forecast is always wrong,” is improving forecast accuracy even the solution to our demand planning woes? In times that continue to defy our ability to predict them, the words of famous statistician George Box have never been more right: “All models are wrong, but some are useful.” So what can we do to make models more useful? Artificial intelligence and machine learning (AI/ML) can improve forecast accuracy, but a bigger problem is the failure to set accurate expectations around forecasting models, not the accuracy of the models themselves. For supply chains to get more use from their models, we need to “trust the box;” recognize that models are not the holy grail; and remember that a forecast is an input into making better decisions, not an end in and of itself.