Don’t Do Less Bad; Do Better Good

Oct 13, 2010 by Jim Harris in Data Governance, Data Quality

Implementing a data governance program is one of the most daunting endeavors an organization can undertake, especially a very large organization.

Most data governance maturity models describe an organization’s evolution through a series of stages intended to measure its capability and maturity, its tendency toward being reactive or proactive, and its inclination to be project-oriented or program-oriented.

For example, this is the Data Governance Maturity Model used by DataFlux:

When such a challenge is first being considered, many people express their doubts, often remarking that achieving a high level of data governance maturity sounds like an idyllic vision – and therefore an unrealistic goal for their organization.

It’s as if they are singing . . .

Over the Data Governance Rainbow

Somewhere, over the Data Governance Rainbow
Way up high
There’s an Organizational Maturity that I heard of
Once in a Data Lullaby

Somewhere, over the Data Governance Rainbow
Enterprise-Wide Collaboration grew
And the Data Dreams that you dare to dream
Really do come true

Way above the Data Silo tops
Where Data Quality problems melt like lemon drops
When all the petty politicking stops
The barriers to success have all been dropped

So, if other companies can fly
Over the Data Governance Rainbow
Then why, oh, why can’t mine?

 Do Less Bad

When some people look at a Data Governance Maturity Model with the labels Undisciplined, Reactive, Proactive and Governed, they see a Suckitude Scale with the labels We Suck, We Kinda Suck, We Don’t Suck and We’re Awesome.

Although we all want to be told we’re awesome, neither the organization nor its employees want to be told they suck.

Implementing data governance is about striving for continuous improvement, which requires a significant and sustained change management effort. Therefore, it’s not surprising that many organizations put off getting started until after they are confronted with a painfully obvious need for improvement. (In other words, the organization has to admit that “we kinda suck.”)

The primary reason that the change management efforts of data governance are resisted is because of an almost exclusive focus on why the organization sucks. In other words, the emphasis is on broken business and technical processes, as well as bad data-related employee behaviors.

The rallying cry of data governance often is bad people and bad processes are doing bad things, which are resulting in bad data, bad decisions and bad business. Therefore, the organization states that it needs to “do less bad.”

Although these problems are the root cause of some of the organization’s failures, an emphasis on doing less bad makes it sound like the organization is doing no good.

Don’t Do Less Bad; Do Better Good

Unheralded processes and employees are preventing other problems from happening, and these unsung heroes are the root cause of some of the organization’s successes.

Dedicate some time to analyzing the good that your organization is already doing, which will allow you to learn how to do even better. Additionally, by celebrating your unsung heroes, you also will be highlighting the grass roots advocates and peer level influencers who are leading by example.

It’s important to demonstrate that some of the data governance policies and procedures reflect existing best practices, which helps reduce resistance to change.

No matter how bad things may seem, your organization is definitely doing some good, and your organization definitely has the capability and maturity to do better.

Don’t Do Less Bad; Do Better Good.

Tags: Data Governance, Data Quality