Data Is Risky Business: The Opportunity Exists Between Keyboard and Chair

I’m doing some research work for a thing (more on that thing later in the column). My research has had me diving through all the published academic research in the field of data governance (DG) that deals with critical success factors for sustainable (as in: “not falling over and sinking into a swamp with all involved swearing to never speak of it again”) data governance change in organizations.

It took me most of a holiday weekend here in Ireland, using the full research library access of the two universities I’m engaged with as a lecturer and researcher. There isn’t a lot. At least, there isn’t a lot that isn’t a) looking at how the DAMA DMBoK can be reheated six ways from Sunday or b) isn’t identifying the relatively low priority of tools and technology for DG in the actual recipe for success. What there is precisely nothing on is anything that is really taking a long hard look at the root cause of all our problems. That critical failure factor that, if we could only get it corrected would make all our magical dreams come true and have our business glossaries sparkling like unicorns in the noon-day sun.

(New readers will by now be wondering what’s going on. Regular visitors, or those of you who’ve seen me on a panel at an event over the years, will recognise the frustrated cynicism and will be expecting something profound to turn up in about six paragraphs time.)

All Data Stuff Is People

Out of the hundred or so papers and articles I skimmed through as part of my first-pass literature review, none of them considered the “people” aspect of data governance and sustainable data change in any substantive way. In the academic literature, there are lots of references to people being an important pillar of data governance — just like there are extensive references to the importance of people in data governance and data quality in our practitioner publications. Heck, Tom Redman’s last book is called People and Data (Tom is renowned for his subtle hints to the profession about what he thinks is important to look at).

But what are we to look at when we are looking at the People Pillar for sustainable data governance and data quality practices?

The academic literature (and, dare I say it, many of the exceptionally good books on the disciplines of our profession) is almost singularly focused on the mechanics and methodologies of data governance and data management. There is a relative sufficiency of academic study of the scenarios where this stuff has delivered value (note the caveat there … there can never be enough study of value and success to help bolster the business case for data stuff).

However, there is an acknowledged absence in the academic literature of any real examination of the people factors in data governance and data management. And by people factors, I do not mean the low-hanging fruit of resistance to change, communication, and development of competencies and skills in data-related disciplines. What I mean is the nitty-gritty of what makes successful data people and sustainable data teams tick.

To take a sporting analogy: What sets the organizations that are the ultra-marathon runners of sustainable data transformation apart from the 100-meter sprint champions that shine bright, but fizzle out fast? If we assume that all data teams at least have access to the same methodologies and reference books, and if we assume that all data teams and data provocateurs will encounter similar barriers and resistance at different stages in the evolution of their organizations, the question we need to answer is simple.

What is the “secret sauce” that those who are sustaining progress and making it stick are bringing to the table? And how can we bottle that secret sauce and get it on the shelves so everyone can have some?

Seeking a Solution

The data management profession has, in the words of John Ladley and Tom Redman, failed. Of course, what we are looking at with that failure is a classic example of a “wicked problem,” a problem that is difficult or impossible to solve because of incomplete, contradictory, and changing requirements that are often difficult to recognize.

Other professions have gone through similar awakening moments. Recent years have seen an increasing focus in disciplines such as project management on the attributes of people and teams that are correlated with success and sustainable outcomes. There is a growing body of research into these factors that I believe data management professions can learn from.

But there is precisely zero research looking at these people factors in the context of data management.

Reading some of the research from other fields on this topic, several hunches I have had over the years about some of the critical people factors that we need to be considering seem to ring true. Other things I’m reading have given me pause for thought: perhaps we’re struggling at times in data because we’re simply doing it wrong and trying to, as a therapist friend of mine puts it, “Logic our way out of an emotion problem,” like Spock trying to win an argument with Dr. McCoy.

Of course, another characteristic of a wicked problem is that any solutions that are proposed, particularly those that are simple and elegant, are almost certainly wrong. But, we find ourselves at a juncture in the profession where we are failing to progress, and often struggle to hold the gains we’ve made (and I am having the same conversations with clients about data that I was having in my telco days 20 years ago, so we’re definitely not moving forward with pace). The volume of analysis of methodologies and “scaffolding” for data governance and data transformation in the academic literature, and the dearth of any meaningful or rigorous assessment of human factors in making those changes “sticky” and sustainable might well be a signpost to a symptom and a way forward to one part of the solution.

To paraphrase an old saying from my tech support contact center days: The opportunity exists between the keyboard and the chair. Even in this magical age of conversational AI tools, the key to putting data to work remains people.

Oh … the “thing” I was doing the review of the literature for is a doctorate I’ve started looking at these issues. I will be reaching out to ask the practitioner community for input as my research progresses. I look forward to hearing from you!

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Daragh O Brien

Daragh O Brien

Daragh O Brien is a data management consultant and educator based in Ireland. He’s the founder and managing director of Castlebridge. He also lectures on data protection and data governance at UCD Sutherland School of Law, the Smurfit Graduate School of Business, and at the Law Society of Ireland. He is a Fellow of the Irish Computer Society, a Fellow of Information Privacy with the IAPP, and has previously served on the boards of two international professional bodies. He also is a volunteer contributor to the Leaders’ Data Group ( and a member of the Strategic Advisory Council to the School of Business in NUI Maynooth. He is the co-author of Ethical Data & Information Management: Concepts, Tools, and Methods, published in 2018 by Kogan Page, as well as contributing to works such as the DAMA DMBOK and other books on various data management topics.

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