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Data interpretation hinges on the rationale for benchmarking project
Abstract:
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.