An enterprise can make the wrong AI demand forecasting technology decision even when it selects a capable product or builds an accurate model. A manufacturer may buy a respected planning platform, then discover that its configure-to-order workflow cannot fit the platform’s assumptions. A retailer may fund an internal machine-learning build, then spend the next year maintaining data pipelines instead of improving replenishment. A distributor may commission a fully custom syste

Every month, enterprise procurement teams across retail, supply chain, financial services, and manufacturing issue Requests for Proposals (RFPs) for predictive analytics and time series forecasting. The sales presentations look pristine. Vendors arrive with sleek dashboards, promises of "state-of-the-art AI," and claims of 98% forecast accuracy. Contracts are signed for $250,000 to $750,000. Eight months later, a familiar disaster unfolds: The vendor's model performs worse in