SOURCE-LINKED INTELLIGENCE
Accuracy Is Not Service: A Decision-Aware Benchmark for Intermittent-Demand Forecasting
A contract-logistics spare-parts operator is paid on order-level service: an order counts only if every requested line is fulfilled, yet forecasters are selected based on line-level forecast accuracy. This disconnect matters when demand is intermittent and lumpy, histories are short, and lead times span months. We benchmarked 38 forecasting methods spanning classical, intermittent-demand, machine-learning, deep-learning, and pretrained foundation models. A common decision-aware protocol evaluates them on an industrial panel drawn from a live contract and two public datasets. Forecast-accuracy
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-12T09:51:30.000Z
First collected: 2026-09-20T16:41:15.630Z. This is not the publication date.