It occurred to me the other day, when I was eating a slice of my daughter’s birthday cake, that I have an appointment next month for my annual check-up with my doctor. “Better lay off the sweets” was my next thought, followed by, “I better spend an extra 30 minutes on the bike tomorrow.”
The next day, as I was cranking down an imaginary road on the stationary bike, I thought about the effort many people put into ensuring we maintain good health, and how we work to improve it. However the same is not true as often in the business world with respect to ‘data health’ and the attention it receives from those responsible.
Maintaining the health of your data is akin to oral health. Your dentist provides a check of your oral health and fixes any problems (hopefully…ouch!) before they become serious. The same must be done to a company’s data. Regular check-ups ensure data quality issues don’t become the norm, and also provide the organization with assurance the data remains fit for purpose. In an ideal world, monitoring data quality and providing regular data quality reports help with this process, but in my experience, few companies are achieving this today on any reasonable scale.
Therefore it is a must to have the discipline to perform a data quality audit at least twice annually on any operational data that is providing significant financial leverage to your company. Utilizing a good data discovery tool makes this process painless (no pun intended…well, maybe a little). More importantly though, make sure you take action on the findings of the audit in accordance of your corporate data management policies, and actually review the data on the back end to ensure the data meets corporate goals for being ‘fit for the business’ task at hand.
I spoke with an IT manager at a prospect company just the other day who told me his business stakeholders couldn’t understand why they had so many data quality issues, especially since IT had implemented a data quality process years ago. This manager indicated they had a mature process for correcting the exceptions from the data quality tool and wanted to know what else they (meaning IT or the business) should do. Now I didn’t have enough information to answer this question, so I asked if they had audited the data recently and mapped the results to the business use of the data. I assumed the audit report would provide some insight into where to begin looking for trouble.
After the initial finger pointing stopped, it was clear no one knew who should have been responsible for the data review. And, it was also clear that nobody had ever actually looked at the data, only the exceptions report from the data quality process. Ah, now we know the cause of the health problems, not just the symptoms. A regular in-depth data quality checkup would have greatly benefited this organization just like it benefits our health.
No data management review policies in place? Well I’m afraid that’s a discussion topic for another time, kind of like why it’s important to eat your vegetables or else risk health problems later. For now, begin by evaluating the quality of your most important data several times a year, and fix as much as you can, as well as the source of the problem, so the issue doesn’t continue to manifest itself. Just like a dentist, fill the cavity, but then tell the patient to brush all the way in the back, and of course, lay off the sweets.



