We have a collection of computers at home spanning a range of operating systems and vendors. In recent months I’ve jumped ship from Windows and headed over to Apple and picked up a new Macbook. This event coincided with another major milestone in our household: my 3-year-old son decided to get tech-savvy and explore what these new “toys” could offer.

Working from home we normally have a couple of computers online throughout the day, the Mac and a Windows laptop. As a result, my son often tries to steal some free-time exploring his kids' website of choice on whichever machine has been left idle for a fleeting moment.

What has transpired through several months of casual observation is that my 3-year-old has become openly resistant to using Windows and is far happier on the Mac. As a result the line: “Can I watch cbeebies on the silver computer (Mac) Daddy, don’t want Mommie's (Windows)” - can be heard most days.

So where am I headed with this post and what does data quality have to do with the computing demands of a 3-year-old?

Well, at a recent event one of the members of Data Quality Pro talked about the challenge they faced in moving hundreds of managers and analysts off of their beloved spreadsheets and onto the corporate reporting platform they’ve been building out for the last two years.

Adoption rates had been lower than anticipated, so many of the data quality issues that are inherent in a poorly governed spreadsheet “free-for-all” were still occurring. A big driver for the new reporting platform was to manage data quality centrally, so they were struggling to demonstrate any real value until they could shift the culture away from spreadsheets.

This is a constant reminder that improving data quality is not really about changing data, it’s about changing habits. People are creatures of comfort and will actively take the path of least resistance:

• If we find it easier to create calculations and charts in Excel, unless we see an easier alternative that’s the path we’ll take.
• If we find it easier to use basic web forms without validation for data entry, that’s what we’ll do (forcing downstream teams figure out how to solve the resulting data defects).
• If we find it easier to pass reports to management with no assurance of quality, that’s what we’ll do (unless we’re given an easier way).

Of course we can wield the big stick of governance and say “You must adopt the corporate standard,” but that’s not enough. Data quality management and data governance must make our working lives easier, not more complex. Otherwise you’ll never transform the culture.

Look at the benefits your data quality team are creating. Are you making it easier for fellow workers to complete their tasks or are you adding extra processes and delays to their everyday tasks?

I personally feel that making working life simpler, easier and more rewarding are some of the core pillars on which a data quality strategy should be measured against. But what do you think?

Welcome your views in the comments below.