Mass inspections are a means to a positive end

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One of the key principles of W.Edwards Deming in his drive for greater quality in the US manufacturing industry was:

“Cease dependence on inspection to achieve quality. Eliminate the need for massive inspection by building quality into the product in the first place.”

Quality purists will repeatedly quote this principle when faced with data quality practitioners who lay claim to the many benefits of data quality assessments, profiling and other "mass inspection" activities.

There is no doubt in my mind that data should be considered a "product" in the same mold as other manufactured products. We need to create quality data that delights customers in order to achieve business goals, so the term is a good fit. What we do have to be mindful of, though, is condemning mass inspections of the data quality kind as some form of outdated technique.

Deming’s principles stem from 1940s America, so there are important distinctions to be made. Mass inspections at that time would have been manual, extremely costly and obviously lengthy affairs. Inspections would also have been sample-based and therefore subject to a predictable level of inaccuracy.

Step forward to modern times and mass (data quality) inspections now are quite different. We have the ability to inspect entire data landscapes using automated tools at a relatively low cost, typically in hours or at most days.

I agree that we still need to apply the core principle and build quality in the first place, but modern information systems are incredibly complex and true change can take years to implement. Mass inspections therefore have a vital role to play. They help to channel often limited resources into improvement activities. We need these inspections to demonstrate the value of improvements. Given their relative low cost it makes sense to leave them in place, routinely monitoring and protecting our data assets.

I know this may sound contentious to quality purists, but mass inspections do have a positive role to play in modern data quality management. I feel a level of pragmatism is often lacking from some practitioners who scorn their use. No, they should not be used exclusively; prevention is still vital, but don’t discount them. You still need to put out the fires before you  practice fire prevention.

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Dylan Jones

Founder, Data Quality Pro and Data Migration Pro

Dylan Jones is the founder of Data Quality Pro and Data Migration Pro, popular online communities that provide a range of practical resources and support to their respective professions. Dylan has an extensive information management background and is a prolific publisher of expert articles and tutorials on all manner of data related initiatives.

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