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This case study examines Unilever's approach to grounding global water risk assessments in local data. While using the Aqueduct Water Risk Atlas for initial screening across 300+ sites in 100 countries, Unilever validates results with local facility managers to correct discrepancies. The document highlights how global models can overestimate risk in the Great Lakes region due to unmodeled human engineering, or underestimate risk in São Paulo, Brazil, by ignoring water quality degradation and local transfers. The study concludes that global data should serve as a starting point, supplemented by documented local feedback and iterative reviews to ensure effective water stewardship.