What Is Data Governance?By Jill Dyché | Posted 2011-07-28 Print
Guidelines for defining data governance and formalizing it as a sustainable set of practices.
What Is Data Governance?
Part of the general wariness about data governance is due to the lack of a clear definition. Consider Figure 1, which includes the components of data governance.
The top portion of the figure conveys business ownership of corporate data, which encompasses the overarching definition of data governance, namely, the business-driven policy-making and oversight of corporate information. As such, data should be owned by the business, which circumscribes its definitions, rules, access and usage policies.
But IT has a role to play as well. The bottom portion of the figure, while conversationally part of data governance, is really data management: the tactical execution of data governance policies and decisions. Just as data governance is business-driven, data management is owned by IT.
“In health care, there’s a special urgency around information,” says Mike Nauman, corporate director and CIO at the Children’s Hospital and Health System of Wisconsin. “This is amplified in academic health care organizations that operate at the forefront of medicine.”
Nauman and his team recognized that data governance would be an organizational discipline, driven by the business but enabled by IT. “We knew that information was a shared asset, so we introduced a data management function in IT,” he explains. “The function encompasses new roles, new processes and specialized skills. As data governance evolves, we’ll be ready to support it.” vTogether, these two functions inform a workflow that defines, tracks, manages and deploys information across its life cycle at a company. After all, the extent to which data is shared across business processes and organizations is the extent to which it mandates formal management and policy decisions.
But how do you kick off a new data governance initiative? And how do you sustain it?
Launching Data Governance
A few years ago, when the early-adopter companies launched data governance, there were few examples to follow. Many of these organizations relied on a smattering of vendor and consultant advice, which admonished them to secure executive sponsorship and to “manage data as a corporate asset.”
That didn’t necessarily help deliver results. Often a visionary manager would convene like-minded people on both the business and IT sides to agree that data was an asset, that data quality was poor and that someone needed to clean it up. The natural next step was to convene a data governance council, the de facto decision-making body for data governance.
Then things got really quiet.
The main hurdle facing these pioneers is translating the all-too-real phenomenon of meaningless, unavailable, duplicated, siloed data into an information-cleansing, integration and deployment strategy that serves the greater good.
Absent a tactical plan for addressing key data needs, meetings of the data governance council degenerated into complaint sessions: The data on the ERP system is unusable. Marketing won’t share its data. No one in the C-suite understands how bad the company’s information really is. Who will fund the project?
The result? Data governance never transcends ownership discussions and priority debates. It is, instead, relegated to one more intellectual exercise at the company, with plenty of people sharing opinions but no one claiming accountability for fixing the problem.
At many of these companies, data governance has become a dirty word. An insurance executive recently invited us to help relaunch a moribund data governance effort. “Just don’t call it ‘data governance,’” he warned us. “You’ll lose credibility.”
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