Taming The Unicorn: Why Data Modernization Isn’t About Data

“Some cats, and rats and elephants, but sure as your born, Your never gonna see no unicorn.” – The Unicorn, The Irish Rovers

A series of six pictures (and yes, there was a unicorn) was posted on LinkedIn recently, posing the question: When it comes to Data Modernization, which pic best represents your organization?

The following statistic followed the above question: less than 5% of all data is analyzed—how do we fix it?

Besides being an obvious question, it is also a good one. However, the answer is not as clear-cut as one might think because data modernization doesn’t start with data—it begins with unicorns.

Besides reassuring you that we haven’t lost it here at the editorial desk, read on because data is the least of our problems when it comes to turning a vast sea of information into actional knowledge.

The Data Myth

The unicorn is a legendary or mythical horse-like creature with a twisted horn protruding from its forehead.

Do you know what else is mythical, like the unicorn? Organizations with a properly functioning data governance team and policy model.

The lack of data governance teams and policies reflects that when it comes to data modernization, we spend far too much time focusing on data and not enough on its management once collected. Or, as Herbert A. Simon put it, “a wealth of information creates a poverty of attention.”?

Another industry expert even went so far as to suggest that “we don’t need all data” and that “we collect too much of it” without knowing what we “need and want to achieve.”

Once again, our problem isn’t data but its governance.

The question is this: why are we so poor at managing our data beyond its capture and our awareness that it exists??

Easy Automation

Generally speaking, the answer to the previous question comes down to the ease at which we can automate processes without really understanding or knowing why we are doing it.

At first, this sounds ridiculous because automation is supposed to make things easier and more efficient. It is supposed to free us from the mundane tasks of our jobs and enable us to focus on more “strategic” activities.

But efficiency alone is not enough. We need to learn how to become strategic in our thinking. That’s right—we need to learn how to be strategic. Or, as one reader put it so well: while “realizing the importance of data,” a lot of organizations are “completely alienated to the concept [of data].”

Ownership and Trust

So, why are we alienated from our data? Why is data automation so easy, and why is data governance so hard?

A recent article on data governance challenges cites several reasons, including the existence of “disparate data systems” and “conflicting data flows.”?

Both are, of course, correct. However, we believe that the problem runs much deeper, starting with “a lack of data ownership” leading “to a lack of trust in information.”

Unfortunately, technology alone will not create the ownership and trust needed to turn our data into actionable insights. We need to surrender our belief in the mythical power of automation and take practical steps to harness and tame our data.