What to Do When IT Owns Data Governance

Daniel Teachey

For years, organizations had a curious view of the data. Employees within each line of business asked for high-quality, consistent and trusted information to make decisions and manage business processes. But, when it came time to actually manage that data, the business side was content to let IT take over. Data was viewed as a “byproduct” of the applications that IT also maintained.

As a result, IT was often in control of early data management programs. From the days of vacuum tubes and punch cards through the early 2000s, any project that had “data” in the title was destined for IT. Business staff would document requirements, attend meetings, and so forth. IT had to do much of the heavy lifting.

This dynamic has shifted in the past decade as the phrase “data governance” has emerged as a new framework for managing data. The “governance” term is a critical indicator that data – like vehicles, buildings, financial instruments and other assets – requires a coherent set of policies and processes to manage, maintain and optimize information.

The word “governance” also indicates a more business-focused approach to managing data. In many organizations, business professionals became more involved in data governance, often because the program has executive support. So, that led to more business involvement in data governance efforts.

But what happens when IT is still in control of data management programs, including data governance? This is not uncommon. Some companies established IT as a service organization within the enterprise, allowing IT to work on a variety of “as needed” projects. Other companies have more business-focused IT, where IT is very aligned with the needs of a certain division or department.

As a result, IT organizations can end up guiding a data governance effort. Because data governance requires so much interaction with the business – defining terms, outlining processes and optimizing procedures – this may seem to be a position of weakness for IT. How can IT lead a program where the impacts are felt more directly by the business side?

The good news is that there are several strategies to ensure that IT can lead a successful, impactful data governance program.

Open up the lines of communication

Any data governance effort is about communication. Data itself serves little to no purpose in a vacuum; the access, manipulation and consumption of data gives it true value. Data governance, then, must understand how data is used, how it applies to different business units, and what groups must be consulted for different sources of information.

With IT in control of the data governance effort, they are in a unique position. They aren’t a consumer or end user of the data, yet they have been the traditional “go to” resource for data problems. IT’s familiarity with data can help speed a data governance effort by streamlining the process of cataloging and presenting data. Then, while seeking consensus on how to manage data over time, IT can present this information to the business owners and consumers – and communicate more effectively the goals of the effort.

Define, define, define

Technology efforts have a tendency to grow beyond their original boundaries as the project uncovers new problems or finds new opportunities. For example, during an ERP implementation, a global paper manufacturer uncovered dozens of nomenclatures for its inventory. This not only delayed the ERP program, but they uncovered a huge barrier to just-in-time manufacturing practices. The ERP effort uncovered a significant data governance issue, and IT suddenly had two projects under way.

Like pulling a thread on a piece of fabric, uncovering problematic data can uncover similar problems elsewhere – and a small program quickly unravels into a bigger, thornier effort. A quick analysis of data can uncover problematic or inconsistent data before the program launches. That way, you get a more informed definition of the program, leading to more accurate budgeting and time estimates.

If IT is going to serve as a data governance driver, it first needs to define three things: the goals for the project, the sets of business policies and processes impacted, and the ways that they can measure success or failure. Without these, the IT organization won’t have a proper understanding of what the project is going to accomplish.

Establish timescales and short-term goals with the business side

With IT in control of a data governance program, they will be more effective as a facilitator than acting as a single point of control. To reflect a universe of business processes, the business side of the organization has to have a seat (or several seats) at the data governance table. IT can bring the parties together, but they must work closely with each line of business to establish what a successful program will look like.

Building off the previous phase, this phase requires IT to work with their business counterparts to uncover what can be accomplished in short order to test some of the initial business rules and processes. This not only provides feedback on near-term effectiveness, but it also establishes some momentum for future governance efforts.

IT has the tools to manage a complicated program like data governance. The staff knows key details about data management already, and they can work closely with IT to show what can and can’t be accomplished with the databases and toolsets already in use.

But, any data governance veteran will tell you that the effort will be collaborative. IT can be in the driver’s seat, but they cannot be the only one in the car.

Daniel Teachey is a managing editor in the SAS External Communications team, where he works closely with global marketing groups to promote SAS technologies, including analytics, information management and business intelligence. Prior to this, he managed marketing efforts for DataFlux, helping the company go from a niche data quality provider to a world leader in data management solutions. Daniel has also held positions in public relations and marketing with IBM, MicroMass Communications and Datastream Systems.

Add Comment      Leave a comment on this blog post
Mar 4, 2013 7:12 AM John John  says:
I like practical stuff, and this is an article that reflects reality. Two items are missing however. Defining a successful program needs to incorporate business goals into DG goals. Without this the DG effort will dissolve from lack of interest. Second, if IT is running the DG program they better have the skills mentioned in this article. Very often I have to train IT on some basic blocking and tackling because they have never stood up a program. That isn't a negative comment, its an experience thing. Reply
Mar 6, 2013 11:04 AM Madhu Nair Madhu Nair  says:
Great read Daniel. The trick is getting an incentive/penalty powerful enough to drive collaboration. Reply
Nov 12, 2016 8:22 AM Anthony Anthony  says:
Great article! The business and IT working together is always beneficial.Here is my take on data quality. https://anthonysmoak.com/2016/10/24/the-data-quality-face-off-who-owns-data-quality-the-business-or-it/ Reply

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