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Robust layers on inventory models are costly to build, calibrate and explain, yet whether one changes decisions, or the data support its protection, is rarely asked. Two pre-adoption diagnostics become five ordered gates, exercised in a controlled study and a retrospective plant-level coal benchmark over 35 rolling origins. For a cost-form type-1 Wasserstein program with hinge loss on unbounded support, the worst case adds a decision-free term, leaving prescriptions unchanged; relocating robustness into the service constraint restores sensitivity. Under a common conditional residual law, a uniform cushion minimizes average expected shortfall at a matched budget; a closed-form example shows targeting can win. The layer changed prescriptions yet matched a quantile-plus-cushion policy at equal inventory, and most pile-build targets had no precedent; the controlled study found it worse on both criteria. The gates demonstrate stopping specificity, not sensitivity. Changed prescriptions need not add value; planners should ask these questions before adoption.
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Shao et al. (2026) studied this question.
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