Forecast Quality and Recourse in Semantic Facility Placement

Forecasts guide the residency of service capabilities before demand is known, while compatible capacity may also be activated afterward at a recourse cost. We show that this distinction changes both the value of anticipation and the appropriate learning target. In the stated two-stage model, newly planned activations can be deferred without changing assignments, physical states, or total cost when emergency activation has no extra fee or delay. With paid recourse, a separable capability admits a Bayes one-step rule based on expected service savings clipped by capacity and activation cost. The conditional mean of demand generally does not determine that rule. A squared-loss calibration bound motivates learning the clipped value directly. On 12 matched generated conditions, selecting forecasts by local-search rollout cost reduces cost by 2.05% relative to EMA, but the improvement does not transfer to the same forecasts under MPC. A separate replay uses 104 structured API calls from 40 public annotated dialogues under 54 explicit cost mappings. The clipped target changes cost in only six mappings.