You may already have a formal Data Governance program in place. Then again, perhaps you don’t. Or … you are presently going through the process of trying to convince your Senior Leadership or stakeholders that a formal Data Governance program is necessary. Maybe you are going through the process of convincing the stakeholders that Data Governance is well worth the time and investment in terms of resources and time spent formalizing accountability for data across the organization. No matter what your situation is, you are probably spending significant effort conveying the message of why Data Governance is necessary and worth expending the energy.

Is this the best use of your time? You can answer “yes” and “no” to that question.

Yes, because if Leadership is not convinced that Data Governance is necessary, they may not allow you to pursue this as a discipline and data will continue to be managed the way it has always been managed. The very first best practice used in assessments by one-hundred percent of my clients reads that, “Senior Leadership supports, sponsors and understands the activities associated with the governance of data.” If you do not achieve this best practice, Data Governance will, at some point, be at risk of failure within your organization.

No, because the stakeholders have heard about the need for formal Data Governance too many times and from too many people in too many ways. Although we, as data practitioners, understand that analytics and improved decision-making is based on the confidence people have in the quality of the data, this does not mean that the stakeholders “get it” when it comes to the need to govern their data as a valued enterprise asset. This leaves many of us to repeatedly attempt to solve this burning problem and answer the questions stakeholders require to become thoroughly convinced that time and resources must be applied to Data Governance.

But fear no more. I can provide you with the three questions that, when answered thoroughly and honestly from a business and technical perspective, will provide the practitioners with the artillery they need to break down the barriers that are preventing the stakeholders and Data Scientists from being convinced that Data Governance is a necessity, rather than a nice to have.

Are you ready? Here we go … You may be surprised by the simplicity of the questions.

The three questions are:

1. What can’t you do, that you need to do, with data, because you don’t have the data, or trust the data, to do it?
2. What would you do, or could you do, if you had the data to do it?
3. What is the relationship between these “cannot do-s” and “would do-s” and data governance?

Let’s go through these questions one-by-one.

What Can’t You Do?

People that use data as part of their job (basically everybody) are typically glad to share their woes associated with the hoops they have to jump through to get the data they need the way they need it to perform their job function. These hoops often involve figuring out what data exists, gaining a solid understanding of that data, getting access to the data, understanding the rules associated with using that data, combining that data with other data (that they need to locate, understand, access, … by itself) which is a tiresome and repetitive problem that builds on itself. And my description minimizes the effort that these people go through.

Often times, the data consumers don’t have an inventory of the data available to them. The consumers don’t have business glossaries, data dictionaries and data catalogs that house information about the data that will improve their understanding of the data (and access to the metadata might be a problem even if it is available). They don’t immediately know who to reach out to to request access to the data (that they may not know exists in the first place). And the rules associated with the data (including classification and protection rules, business rules, ethical use rules and more) are not documented in resources that are available to data consumers, thus putting all of this effort, post hoop-jumping, at risk anyway.

If you ask data consumers, casual data users, and data scientists what causes delays and problems completing their normal job, you can expect to get answers listed in the previous paragraph, that will boggle your mind. At that point, you will begin to understand the often mentioned 80/20 rule. This rule states that eighty percent of their time is spent data wrangling and the other twenty percent is spent actually doing the analysis, meaningful reporting and answering questions that is truly a part of their job. This is what they are skilled at, why they were hired and why they like their job in the first place.

And these problems assume that the data they need, or that will really help them in their job, is even available to them in the first place. Often times, it is not available or the confidence that they have in the data is so low that they would not trust the data resources even if they were available. This is a sorry state and something that can and should be addressed in an environment where the data is governed.

What Would You Do?

This is another critical question because it plays out at the other end of the spectrum. This hypothetical question, when asked appropriately, can lead data consumers and data scientists to consider applying innovation and new ways of thinking (and certainly new ways to analyze the data and improved ways to make better decisions). Although this question is utopian and idealistic in nature, data scientists are getting better and better at hypothesizing about the things they could do differently if only they had the data to do those things.

If you ask this question, you can expect answers like:

1. model the data to produce predictive and improved forecasting analytics
2. combine data in ways that were never possible when less data and information about the data was available
3. enable improved machine learning capabilities, and
4. recognize patterns in the data that lead to more efficient and effective customer interaction, improved sales, risk assessments and fraud detection.

This question leads to improved ways of making the organization data-centric, data-enabled and data savvy.

The problem with asking this question is that the answers will point out things that indicate (or make you feel) that you have failed in your efforts thus far to become data-centric, enabled and savvy. But let’s look at the positive side of the answer. If the data consumers are not asked what they would do if they had the data to do it, you may never learn of all of the areas where you can improve as an organization. Blame should not be cast; opportunities for improvement have been brought to light. And then the question becomes…what are you going to do about it? Which leads to the final question I will address in this article.

What is the Relationship Between These Questions and Data Governance?

The relationship between the two questions and Data Governance can take many forms. There are complete books written on the subject including: The Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality by Lowell Fryman (former TDAN.com columnists), Gregory Lampshire and Dan Meers (Morgan Kaufmann 2016) and The Data Catalog: Sherlock Holmes Data Sleuthing for Analytics by Bonnie O’Neil (current TDAN.com columnist) and previously mentioned Mr. Fryman (Technics Publications 2020). The latter book is the subject of Steve Hoberman’s (my book’s publisher and the publisher of Lowell and Bonnie’s new book) present TDAN.com column The Book Look. However, I want to keep this article brief and to the point.

Organizations deliver Data Governance programs with the intention of

• improving access to data
• improving understanding of data
• improving the knowledge of the data that is available and the understanding of that data
• improving the knowledge of rules associated with protecting, sharing, and gaining value from data, and much more.

As I have been known to say, “The data and metadata will not govern themselves.” More simply put, it takes a resolute effort, effective management, capacity, resources, time, and money to put an effective Data Governance program in place and to sustain it for an extended period of time.

The relationship between the question “What can’t you do” and “What would you do” and the results of having a governed data environment, highlights opportunities that can be leveraged to convince stakeholders why it is necessary to put a formal Data Governance program in place. The relationship and the answers to the above questions may demonstrate some of the best reasons to put an effective Data Governance program in place.

In this day of heavy organizational investment in becoming data-centric organizations, practitioners have to start deploying effective data governance techniques, preferably in a non-invasive way, rather than spending the majority of their time trying to convince stakeholders and Data Scientists that Data Governance is necessary. Hopefully, this article shared practical techniques for proving the value of Data Governance to the people who will help make a difference for your organization.