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All I Want for Christmas is Better Data Quality


This holiday season has me thinking about gifts for family and friends and also for my friends and colleagues in the information management industry — like the many senior executives I’ve worked with over my 30+ years. What do you give the executive who has everything? Better quality data, of course.

Because data quality is that perfect present for today’s senior leaders, wouldn’t you agree? It may not be top of mind that they want it — or, perhaps, they quit asking for it years ago. But as they’re opening the package, I bet they’d exclaim, “Thanks! It’s what I always wanted.”

The Staggering Cost of Bad Data

If you keep up with industry news, you’ve seen the same stats that I have about the staggering cost of poor-quality data. My friend, Dr. Tom Redman (a.k.a. The Data Doc), recently wrote about the cost and estimated it to be 15% to 25% of revenue for most companies! (You can find his excellent MIT Sloan Management Review article here.) And IBM estimates the total cost of bad data to the U.S. economy to be $3.1 trillion a year!

This is a serious issue, folks, especially as companies are spending millions of dollars and man-hours going after the promised gifts of Big Data and the Internet of Things. What if they spent a fraction of those expenditures cleaning up their data? What a gift to their customers, vendors, employees, processes and their bottom line!

Underestimating Bad Data Problems

Indulge me a bit longer on the holiday theme: I know that a certain aunt will always gift me with new underwear. And, just as I know this for certain, I also know that nearly any organization I could ask will underestimate their data quality issues. Given a scale of 1 to 10 with 10 being the ultimate in bad data, I know from experience that many would give themselves a 3. But after digging deeper, we’ll see it’s more like a 6.

Sadly, companies have acculturated their bad data, are numb to the pain and are ignoring the problems this is causing their organization. And because they often have many people working full-time to clean up the data, they’ve put bad data in BAU (business as usual) mode and think (hope!) it’s being handled.

Tackling bad data is like eating an elephant. Take it one bite at a time. (@jladley talking about #dataquality)Click To Tweet

Tackle Bad Data a Bite at a Time

Honestly, it can be grueling work rolling up the collective sleeves of an organization to address bad data. It takes time, money and a dogged focus. So where, exactly, does one begin to tackle such a huge problem?

You know the answer to the “How do you eat an elephant?” question — right? (A bite at a time.) We must chip away at bad data one issue at a time.

If your organization isn’t proactively working to clean up its bad data, here are suggestions for how to begin:

  • Starting small is better than not starting at all. Tom Redman’s article includes an excellent idea that he calls Friday Afternoon Measurement — a quality review of the last 100 times an organization did a particular activity, like setting up a customer account. (Tom also published a video about this.) Could you take Tom Redman’s idea and give it a go at your organization — and derive benefit from it? Yes and yes!
  • Bring up the topic … and keep talking about it. Does your organization (or department or manager) avoid talking about data quality? If so, you’re in good (or bad, as it were) company. But not talking about bad data isn’t going to fix the problem. And, with avoidance, your data quality issues are guaranteed to get worse. Be “that person” who not only brings it up, but also proposes ideas for tackling data quality issues.
  • Educate yourself on how best to address data quality. There’s a lot of literature out there that can inspire an approach that’s right for your organization, including Tom’s writings over the years and that of another industry peer of mine, Danette McGilvray. (For example, see her book Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information.)
  • Be serious and strategic about remediation. Once you gain an awareness of bad data, then you need to get the organization to start addressing it. This means data remediation — that is, not only finding and fixing issues, but making sure they stay fixed.

Quality Data — the Gift That Keeps on Giving

Think of your data quality problems as a big holiday fruitcake, and maybe one that’s been sitting around unopened for a season or two. Do you want to re-gift it to someone as is — or chuck it and create something better? Remember how you felt when you received the same fruitcake you re-gifted earlier (a kind of a fruitcake karmic wheel)? Well, data quality is the same.

I encourage you to make data quality a focus for the new year. The Data Leaders group I’m working with asks that you think about being a data provocateur. (This can be daunting if you are not used to being one.) Data quality is a great starting point for the role. You gather the data, demonstrate good due diligence, and get management’s attention without undue political risks. Why not lead the charge or join an existing initiative — and just speak up. Quality data is a gift that keeps on giving, after all.


Article contributed by John Ladley. He is a business technology thought leader and recognized authority in all aspects of Enterprise Information Management. He has 30 years’ experience in planning, project management, improving IT organizations and successful implementation of information systems. John is widely published, co-authoring a well-known data warehouse methodology and a trademarked process for data strategy planning. His books, “Making EIM Work for Business – A Guide to Understanding Information as an Asset” and “Data Governance – How to Design, Deploy and Sustain an Effective Data Governance Program,” are recognized as authoritative sources in the EIM field.