3 Feb 2026 · Assurance

When sampling fails integrity — and what to do next

A clean sample file can hide a dirty population. If your selections repeatedly land on low-risk, well-documented items while known problem vendors sit outside the frame, the design is comforting the team — not testing integrity.

Warning signs

  • Population definitions change after selections are drawn
  • High-risk strata are “too small to sample” every quarter
  • Exceptions are cleared with oral explanations and no ticket trail
  • Completeness of the population file is assumed, never tested

Reset by rewriting the population narrative first, then choosing method. Sometimes the honest answer is 100% testing for a week of postings or a vendor class. That is not failure; it is proportion.

Practice this reset in Sampling for Assurance.

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