Jim Harris hosted an excellent debate on his blog centred on Rick Sherman’s quote “Data quality is primarily about context not accuracy. Accuracy is part of the equation, but only a very small portion.”
From my experience, the bottom line from a business perspective is always that “just enough is good enough.” The challenge for the Data Quality profession is to make the business case for “just enough” to be clearly defined in terms of measurable dimensions.
Let me give you a simple analogy. Suppose there is a requirement to water a new lawn. The context is that 500 litres (or liters for our US friends) must be sprayed on the new lawn. One might assume that so long as the water is delivered, the requirement is met…
However, what if:
– A well had to be dug to provide the water?
– The water contains contaminants that will kill the new lawn?
– The hose contains many leaks, and leaks 5,000 litres in delivering 500 (incurring 10 times the water charges)
Watering a lawn is such an everyday occurrence, that one reasonably assumes that the required ‘plumbing’ is in place to deliver clean water in a cost effective manner. Similarly, business people have the right to assume that they can readily access the information they require. Business people have the right to assume that the required ‘plumbing’ is in place to deliver ‘clean’, ‘complete’, ‘accurate’ ‘timely’, ‘relevant’ ‘usable’ information in a cost effective manner.
Thus we need to split the “plumbing’, which should be standard across all applications, from the business specific, “bespoke by nature” part of data / information management. The business specific stuff, the ‘context’, the ‘really important stuff’ simply cannot happen if the ‘plumbing’ is not in place.
So, which is more important, the context or the accuracy? Which is more important, the chicken or the egg? Does the data plumbing in your Enterprise support a lush lawn of quality information? Or is your data plumbing so inadequate that your business users are left scratching around in a barren desert of information? To learn how to assess the data plumbing in your Enterprise click here: