Build a Data-Quality Gate Before AI Recommendations
Assess supply chain data quality before trusting an AI recommendation.
The move: gate the data that drives the decision, not every field in the warehouse. Data quality is contextual. A supplier phone number may be irrelevant to a lead-time forecast. A supplier holiday calendar may be critical. The gate starts by asking which inputs materially influence the AI recommendation. Accuracy and validity Accuracy asks whether the value represents the real-world thing. Validity asks whether it follows the allowed format or range. For example, a lead time of 900 days may be valid as a number but invalid as a purchasing reality for the category. Completeness and consistency Completeness asks whether…
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