Working with his clients, the author has identified a set of practices that strongly align with success in the data governance world. The author recently launched a webinar series to share these must-do’s, with the first installment available here. As for now, here are five things you must do to find success with your Data Governance program.
1. Break Out of Governance Silos
Too often we see a data-centric and top down approach being taken; focusing on defining frameworks, policies, standards, definitions, and the likes. These efforts run out of steam eventually as the value is not in the data, but in the business application of that data. Do we need more data people defining more data artifacts, or do we want to start a meaningful dialogue with those communities applying the data?
We need to break out of the data silo and connect data artifacts to the people and processes that run the firm. You’re not maximizing the value of your work if you can’t give it relevance. Rather than defining a vertical, we should focus on exposing the data governance network of how we depend on one another and how data is being used in the firm.
2. Go Beyond Data Definitions
Good data governance ensures data is fit for purpose and used appropriately. To assess if data is fit for purpose, we need to understand its usage. To assess if data is managed appropriately, we need to understand context and locality. We need to go beyond the definitions and capture the context and diversity of its application in order to ensure any meaningful engagement.
We need to stop worshiping the purity of the models and reach out into the messy reality of today. Business glossaries are a great asset but will fail to drive alignment and adoption if not linked in with the wider organization; what Forrester calls “the context of data.”
3. Facilitate, Don’t Police
Policing works as long as the capacity to enforce law exceeds the volume of law breaking. In large firms, almost everybody is breaking governance laws, and often, areas are not too sure what their laws are. Without direct line management, what teeth do we really have to punish or correct lawbreaking? There always seems to be a good enough business case as to why non-compliance makes tactical sense.
The reality of large firms is that they are divided into a number of semi-independent states, and often in civil unrest from the data perspective. This unrest tends to only settle when communities are engaged, recognized, and heard, at which point they become powerful and active agents for good. Facilitation nurtures those communities and provides a platform for them to do well, for everyone to understand how they depend on one another, and how to problem solve, align, and reuse our data.
4. Embrace the Chaos
At an enterprise scale, there simply is no big bang solution to a leaner and cleaner data landscape. Even with the biggest budget in the world, in the time it takes to get from start to finish, the target has long moved on.
At most firms, dozens—if not hundreds—of active change programs are constantly transforming the organization: combining, overlapping, and bouncing off of each other. This level of change can be chaotic, but it brings with it huge amounts of energy and opportunity. Successful data governance initiatives harness that energy, and empower changing communities to expose the network, the locality, and the diversity to drive engagement and unlock value. Without understanding what is out there, we tend to only add to the chaos, adding layers of additional governance and complexity. The only way out is through it—together!
5. Do Less, Achieve More
Data is ubiquitous, and to become a data-savvy organization, we must transform the firm as a whole. The data governance function itself will never have enough direct reports to do all of the work, so enablement must be the objective. Data governance is less about doing, and more about empowering others to succeed.
Let’s empower everyone in the firm to make the right choices, at least most of the time. Leverage existing change, communities, knowledge, and control structures rather than only adding to them. When we encourage people to share and give them the freedom to share, sharing will be built into our culture. When we give our data citizens the platform to make sound decisions and trust them to do so, it cements into our culture.
