What I Learned About Data Quality From Vacation

Over the 12 hours it took us to get from NY to the beaches of North Carolina, I had plenty of time to contemplate how our vacation was going to go. I mentally planned our week out and tried to anticipate what would be the best ways for us to ‘relax’ as a family. What relaxes me – is not having to clean up.  So to facilitate this, I set about implementing a few ‘business rules’ so that we could manage our mess in real-time, which I knew deep down, would be better for everyone.  The irony of this, as it relates to my role as the Director of Marketing for a Data Quality company did not escape me but I didn’t realize there would be fodder for a blog post in here until I realized business rules actually can work. Really and truly. This is how.

1. We Never Got Too Comfortable.

We were staying in someone else’s house and it wasn’t our stuff. So it dawned on me that we take much more liberty with our own things than we apparently do with someone else’s and I believe this applies to data as well. Some departments feel like they are the ‘owners’ of specific data. I know from direct experience that marketing, in many cases, takes responsibility for customer contact data, and as a result, we often take liberties knowing ‘we’ll ‘remember what we changed’ or ‘we can always deal with it later’. The reality is, there are lots of other people who use and interact with that data and each business user would benefit from following a “Treat It Like It’s Someone Else’s” approach.

2. Remember the Buck Stops With You.

In our rental, there was no daily cleaning lady and we didn’t have the freedom of leaving it messy when we left (in just a mere 7 days). So essentially, the buck stopped with us. Imagine how much cleaner your organization’s data would be if each person who touched it took responsibility for leaving it in good condition. Business rules that communicate to each user that they will be held accountable for the integrity of each data element along with clarity on what level of maintenance is expected, can help develop this sense of responsibility.

3. Maintain a Healthy Sense of Urgency.

On vacation, we had limited time before we’d have to atone for any messy indiscretions. None of us wanted to face a huge mess at the end of the week so it made us more diligent about dealing with it on the fly. To ‘assist’ the kids with this, we literally did room checks and constantly reminded each other that we had only a few days left – if they didn’t do it now, they’d have to do it later. Likewise, if users are aware that regular data audits will be performed and that they will be the ones responsible for cleaning up the mess, the instinct to proactively manage data may be just a tad stronger.

So when it comes to vacation (and data quality), there is good reason not to put off important cleansing activities that can be made more manageable by simply doing them regularly in small batches.

Why is Data Quality So Hard?

If you take a good look around the master data management (MDM) industry, data quality is the buzz word of the day. Blog posts, surveys, analyst briefings, white papers and testimonials are filled with commentary on the importance of good data quality. What is the importance? Well, if you’re paying attention, then you already know. Having accurate data (with no duplicates, correct addresses and the like) can save a company money, increase sales, facilitate positive customer experiences, streamline business processes and is the shining star of a strong brand.

So it’s really important to have good data right? Yes. Definitely. At least, that’s what everyone is saying.

But do they really mean it?

Yes. Of course they do. But each day helpIT systems still talks with clients, from marketers to SQL developers, who are having trouble making the case for a data quality solution. They know how important it is to keep a clean database. The marketing department is screaming for clean mailing lists. The customer relations team struggles to address client issues without a single customer view. Sales opportunities are flying out the window left and right. They get it. At any given time, at least one person in an organization gets how important this issue is. But the bottom line is, it’s still hard to sell.

Why? Here’s what we see…

  1. Data Quality is Elusive.
    Even with the best charts and examples, there is no brass ring to hand to your CEO after the installation is complete. It will take a while for true data quality to become a tangible element ? like cost savings or an additional sale. Selling the intangible requires stamina, planning and ammunition.
  2. Wanted: DQ Champions.
    Any new implementation requires one of two things, a direct order or a champion. If there is a direct order to improve data quality, it?s usually more about finding the right solution. But without that, data quality needs a hero – someone to bring it to the C-level team or the IT Director and show them what the value is. This is harder said than done.
  3. When Good Data Falls in a Forest?
    While a great database is the foundation of a strong MDM strategy, the true value will depend heavily on someone actually using the tools. Whether it?s batch cleansing or developing business rules, that champion we mentioned is likely to also be the poor soul who will need to see it through.
  4. First We Need Data (fill in the blank)
    You?re migrating data. You?re profiling data. Maybe you?re building a new data warehouse. There are lots of ?things? to do with, for and around your data. Isn?t cleaning it the last thing you do? Nope. It?s not. But some companies think so and just like cleaning the file cabinet, they put it off as long as possible.
  5. Connecting the Data Quality Dots.
    Do you have a ton of duplicates in your system already? Working with 7 databases on 2 platforms in multiple countries? Working with various data formats that you have no idea how to normalize? Sometimes a company’s current technology configuration can strangle the effort to integrate a data quality tool. It doesn’t have to, but every day we work with customers who have struggled to find a solution to work with their existing structure.

Are you a DQ champion? Facing some of these challenges yourself? Know of any other barriers worth addressing? Let us know if we can help you build the case for good data quality but most importantly, keep fighting the good fight until data quality becomes a priority in your organization.