Principles of Data Governance

Malcolm Chisolm, in a recent column in Information Management (A Principles-Based Approach to Data Governance) raises an excellent point. In 2006, when I attended my first Data Governance Conference, there was much discussion around a definition of DG. Implicit in this discussion was the need for something that was concise, yet comprehensive, and on top of that, engaging. The idea was that this definition could be used:

• As part of a sales pitch (like a slogan)
  
• To create synergy within the emerging discipline
  
• To provide focus for any ongoing methodology efforts

Some present may have had additional motivations, but I think these were the ones on most people’s minds.

The definition that emerged was acknowledged to be a work in progress. By the 2008 Conference, one of the tutorials quoted three definitions:

1. Data Governance refers to the organizational bodies, rules, decision rights and accountabilities of people and information systems as they perform information-related processes.


2. Data Governance is the practice of organizing and implementing policies, procedures and standards for the effective use of an organization’s structured/unstructured information assets.


3. Data Governance: The execution and enforcement of authority over the management of data assets and the performance of data functions.

These were troublesome to me then, probably for the very reason that Malcolm mentions. All seem to acknowledge a context based on an organization’s information assets, but their focus seems to be quite different. The feeling I have is that they are advocating a judicial, legislative and executive approach to governance.

In the U.S., a Constitution lays out these three perspectives and establishes the mechanics (framework, architecture) within which governance will be administered. Within the Constitution and before any of the mechanical parts are discussed, in fact, within the preamble, first principles are asserted. The writers tell us that what follows will be a system of governance for the purpose of

• Forming a more perfect union


• Establishing justice


• Insuring domestic tranquility


• Providing for the common defense


• Promoting the general welfare


• Securing the blessings of liberty to ourselves and our posterity

While this model would probably work on its own in establishing [data] governance, there are just a couple of nuances that will have to be accommodated because our system will not be working in a representative democracy but in a corporation.

Within the context of our system, leaders are appointed and serve at the pleasure of stockholders rather than the public. The principle of one-man-one-vote does not apply. One person may control sufficient votes to dictate to the Board of Directors. Within the day to day operations, the ability to dictate policy, direct activities and appoint deputies is granted at multiple levels, though always subject to the pleasure of the higher levels.

Having now established a context, it’s time to agree on some first principles for data governance. The candidates are:

• The entire corporation must agree to be subject to the system.
  While those placed higher may still, at their pleasure, appoint and dismiss deputies, they must agree that [data] governance operations will be a factor in those actions.


• It must be understood that within the corporation, domestic tranquility, the common defense and the general welfare are all dependent upon the information assets owned and managed by the corporation.
  When the system is followed, all processes will flow smoothly, problems are addressed at the process level, personal antipathies are secondary to process execution and process anomalies such as unplanned rework and delays are greatly reduced in number or even eliminated completely.


• Consistency is everyone’s goal.
  In a work context, surprises are almost always seen as negatives. Our goal must be to improve the consistency of our processes and their outputs such that surprises become exceedingly rare (six sigma has been suggested as a goal) and predictability becomes commonplace.

These principles should be the touchstone(s) of our efforts. Everything we do should be evaluated on the degree to which these principles are addressed.

I will suggest that these may also be the principles of the corporate Quality Assurance effort and remind everyone that they are also the basis of Deming’s 14 points as well as other quality improvement methods. No improvement is possible without first establishing a stable (consistent) process.

I leave you with one final principle: Data governance will not be implemented as a stand-alone initiative. If we cannot see data governance as part of a larger, comprehensive system of governance, we will not be able to address any of the three principles suggested above.