Data interpretation hinges on the rationale for benchmarking project.
The size of the gap between performance and benchmark is a key guidepost. Balancing cost, quality, and speed aspects are at the heart of benchmarking. Just because data are less than perfect doesn't mean they should be discarded.
D019985:Benchmarking / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D017598:Efficiency, Organizational; D019983:Guideline Adherence; D006801:Humans; D019984:Quality Indicators, Health Care / Q000706:statistics & numerical data*; D014481:United States