Information is Infinite

The breadth and depth of this information is infinite – we have but scratched the surface of what there is to know.  Every day, it seems, scientist discover some new particles within previously indivisible particles.  Atoms turn out to be made up of protons and neutrons.  Protons and Neutrons, we find, are made up of quarks.  Now we believe that Quarks are made up of Strings.  There was a time we thought our Solar system was the Universe.  Now we know there are many Solar Systems in the Universe. 

Data Governance = R:53 G:60 B:127

If you look on the internet, there are several definitions found for data governance...

"The exercise of decision making and authority for data-related matters."

"The overall management of the availability, usability, integrity and security of the data for an enterprise."

"A quality control discipline for assessing, managing, using, improving, monitoring, maintaining and protecting organizational information."

As a business professional reading these definitions I think - So what?

They sound like definitions for just about any organization in a business. Doesn't Business Process Management exercise decision making and authority for data-related matters? Doesn't Business Intelligence involve monitoring, using and improving organizational information?

True, data is pervasive and is an underlying element in almost everything we do. However, I think this is part of the reason there is some confusion about what Data Governance "is"; it sounds like a lot of other things that it isn't. It isn't BSM; it isn't BI (although it can work with those things to make them even more effective).

I want to take a different approach to defining data governance. In my opinion, data governance needs to move away from the ambiguous business definitions talking about principles, policies and usability and more into the scientific realm of metrology.

Data Governance is the establishment of measurement systems for the information in an enterprise and the management of data in accordance with those systems.

Data governance is about creating definition and measurement where there is assumption and ambiguity. It is about taking business subjects like customer or product and breaking them down into their minimal set of fundamental quantities by which they can be measured. Then, once defined and made quantitative, it becomes objective instead of subjective. Data governance makes the data in our applications measurable because it creates clear quantitative definitions about what the data needs to "be". Data governance creates and maintains definitive data.

When I was about seven, my mom told me that they were going to paint my room. She wanted to know what color I wanted it painted. I was ecstatic - Blue! Absolutely blue! My favorite color blue! I had visions of my american-flag blue room with one accent wall of multi-colored striped wallpaper and a contrasting color of curtains around the window. A bright bold room of blue.

What I got was a pale, sickly, powder blue room with flowery pale lemon yellow and light sky blue flowers. Ick! This wasn't at all what I had envisioned. This wasn't blue! But it was…

Think back years ago when you went to a paint store and they had that one guy who could match anything (I'll call him Bob). Bob understood things like for a warmer blue, add some red. For a teal green blue add some yellow. For an ugly, sickly powder blue add some white. Bob understood the fundamental quantities that made up color. Today, we have several standard definitions of color: CMYK and RGB are a couple of common ones. If only I had been able to tell my parents at seven that I wanted R:53, G:60 and B:127 things would have turned out so much better.

This is what data governance is about. It is about removing the ambiguity of the definition of something like color (blue) and making it something measurable, repeatable and objective (R:53, G:60, B:127). Today, nifty machines at any home improvement store can match any color because it can be broken down into its parts by a spectrophotometer and then quantities of the fundamental components calculated to create the end result: blue (american-flag blue, not sickly powder blue). Think of what could be enabled in our enterprises if we do for business data what RGB and CMYK did for paint?

Of course this is really just part of the picture - the data architecture side of data governance (and just a glimpse of it at that). Once it is defined, it has to be managed per that definition - the stewardship side of data governance. However, I will leave that for another discussion on another day.

Data Governance - An Executive Imperative

Trust! Kings have built empires on it. Generals have won un-winnable battles with it. CEO’s build their companies on it. You base Billion dollar decisions on the trusted input of your leadership teams. You make huge investments in marketing and public relations campaigns designed solely for the purpose of creating customer trust. It’s a powerful force. It can be the cornerstone of your empire or the Achilles heel of failure!

How do you decide where to place your trust, though? What do you do when you’re not sure? Do you guess? Do you go with your gut instinct? Many CEO’s report basing a significant number of key decisions on gut feel or a small number of factors because they don’t have sufficient trust; not in their advisors of course, but in the information used to make critical decisions. The human mind can only process seven to ten pieces of information at any one time. Most decisions CEO’s make require much more than seven to ten critical factors. As a CEO, you must trust your advisors to help process information and make good decisions. Success depends upon it.

However, with trust comes risk. Your advisors are using the same information you are. Do they all have the same perspective on the problem you’re trying to solve? Do they all have the same tools at their disposal? When you say “Net Revenue,” do they share your definition? How about the people they trust? How do they see the problem? Lurking behind every decision is a sea of facts, information and past experiences. We absorb that information to the best of our ability, draw conclusions and inferences and, eventually, make decisions. Unfortunately, facts are not always what they appear to be and while you trust those around you, do you trust the data they’re using to provide advice and guidance? Do they? Are they providing guidance based on their gut feel which is based on the gut feel of their trusted advisors?

Trust in your organization’s ability to provide you with good accurate facts on which to base decisions is a critical factor in your success. It must become an Executive Imperative to ensure that the information on which you base decisions is of the highest quality possible. We call this Data Governance and it’s not something CEO’s talk about. However, it is a core competency that every organization must develop if they are to maximize their competitive advantage in today’s market place. CEO’s sailing on instinct are likely to find themselves rounding Cape Horne in the middle of a perfect storm.

Every day your organization relegates the conversation of Data Governance to the IT break room, is a day of sailing without a solid grip on the rudder. The benefits of data governance transcend operational efficiencies and cost savings. Protecting and improving the integrity of the information on which you make key decisions will propel your organization to new levels of trust and agile decision making. It will allow you to transform the anarchy of disconnected operational functions into a cohesive trust-based team capable of delivering facts and analysis on which you can plot the fastest safest route to success. Data Governance creates trust. Trust creates success! Trust builds empires!