This article is the first of a five-part series on data governance from Robert S. Seiner of KIK Consulting & TDAN.com.

Three Types of Data Governance

There are three distinct approaches to implementing data governance in an organization.

The first approach is labeled as the “Command and Control”-approach and follows the notion that people must be assigned to be data stewards, immediately making the role feel like it is over-and-above the activities already called for in a person’s job description. But even still, people are told that they must govern the data, no matter what it takes.

The second approach is labeled as the “Traditional”-approach to data governance. I compare this approach to the movie “Field of Dreams” where the most memorable line is, “If you build it, he will come”. Organizations that follow the traditional approach build up their roles, processes, and data management style hoping that people in the organization will gravitate toward the roles and processes, but without a level of assurance that the people will actually adopt a governed environment. People are basically told that they should govern data better than they do already.

The third approach is labeled the “Non-Invasive”-approach to data governance and is built on the premise that people are already governing data, but they are governing data in an informal manner, leading to inefficiencies and ineffectiveness in the way data is managed. In the Non-Invasive Data Governance approach, people are shown that they already govern the data informally and are directed to the value they will receive from a more formal level of governance.

Removing the Stigma from Data Governance

Data governance sounds menacing enough from the start. Governance, like a word from the same derivation – government, sounds like it is focuses on control, supervision, and authority. Very few people or organizations want (or will accept) a method or system of government over their data. Further differences in the three approaches to data governance are described in the author’s popular article on The Data Administration Newsletter (TDAN.com) site, Comparing Approaches to Data Governance.

The comparison article focuses on the core components of a data governance program – roles, processes, communications, metrics, and tools – that are shared in the Non-Invasive Data Governance Framework from the perspective of each of the three approaches. Reading this article will demonstrate that the Command and Control approach is most invasive, the Traditional approach is middle of the road in terms of how invasive it is but also the least effective, and the Non-Invasive approach is … the least invasive while being effective when done properly. Non-Invasive Data Governance is only aggressive if the data stewards are not held formally accountable for their relationships to the data.

I define the data governance as, “the execution and enforcement of authority over the management of data and data-related assets.” With no mention of the approach I recommend for getting people to execute and enforce the authority, this definition sounds scary. When push comes to shove, the required result from governing your data is to get people to do the “right” thing at the “right” time with the “right” data required to improve decision-making, protection, quality, understanding and thus the value of the data. Besides, the “execution and enforcement” definition gets people to pay attention to what it will take to achieve the end game that is defined as your program’s purpose.

People Governance

This is why the selection of the appropriate approach to governing your data is so important. People naturally rebel against the idea of being governed. Data governance is known in some circles as “People Governance” because it is people’s behavior – how they define, produce and use data – that is being governed. In other words, the data will do what we tell it to do, so we must govern people’s behavior if we want to improve the quality, value, and understanding of the data. Therefore, the approach the organization takes to govern the data (and the people) can make or break whether the data governance program is accepted or rejected by the organization.

I have been known to say that, “the data will not govern itself.” Let me add to that with, “the documentation about the data, or the metadata, will not govern itself either.” Most of us have experienced data and metadata that has been left ungoverned. Why? Because people are not held responsible for the quality and/or value of the data or the documentation. As a result, there is no way to  improve the efficiency and effectiveness of the way data assets are being leveraged.

Ungoverned data is replicated many times over with many different versions of the “same” data. The data is siloed to the point that the answers to business-critical questions and the ability to gain value from the investments in analytical capabilities depend on where the data comes from and the confidence people have in that data. The data is protected only as well as people know how it is classified and understand the rules associated with handling it based on that classification.

Ungoverned metadata is inaccessible, incomplete, incoherent, and unavailable unless there are people in the organization that have the formal responsibility for defining, producing, and using metadata. One example of ungoverned metadata is what I call the “cheeseburger definition” rule. This rule results in metadata that defines the data with the words that make up the term. A cheeseburger is a “burger with cheese,” an account number is the “number for an account” and so on. Good data definition comes from governed metadata, which requires that people execute and enforce the rules associated with improving data definition.

The information about the data, most often collected in a Business Glossary, Data Dictionary and Data Catalog, will not govern itself and requires that people follow the “Bill of Rights”. The Alation Data Catalog is a terrific place to house the information about how the data is defined, produced, and used across the organization.

Formalize What is Already Being Done

Taking a non-invasive approach to governing data starts with the premise that your organization would not have survived and/or thrived if there had been no data governance whatsoever. Non-Invasive Data Governance starts with the idea that the governance of data, and perhaps the governance of metadata, have been less formal than the ideal situation. Therefore, it makes sense to apply formality to the level of governance in a non-invasive manner as a first approach to implementing effective data governance in your organization.

In the next blog, I will write about how data governance, and the approach you take, will impact the culture of data and governance in different types of organizations.

 

Data Governance White Paper