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.

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