Data Governance: A Team Effort

By Kerry Young on Jul 17, 2020

Nearly all organizations, no matter the size, are placing greater emphasis on the quality and effectiveness of their data. And why not? Every single industry is getting more precise and personal. That’s where MDM Data Governance comes to the rescue.

Even if all stakeholders are on board with a more data-driven approach, efforts are often undermined by a lack of systematic governance. What organizations need is the foundation of MDM and a team effort.

It Takes a Data Governance Village

Because data governance is more of a company-wide philosophy than a siloed project, no one person can solely own the undertaking. It takes buy-in from staff and leaders at all levels.

While that level of buy-in has historically been hard to come by, in today’s environment, governed data is now seen as essential. As CIO.com notes, “Data governance used to be a nice to have, but due to the increasing focus and importance of data and analytics, it’s becoming a necessity that helps drive data management across the enterprise.”

Where in years past, companies would allocate a lone data analyst to the task of governing data, now many enterprises see the value in an established Data Governance team.

Functions of the Data Governance Team

As Ingryd Hernandez, Sr. Manager, Enterprise Data Governance at US Foods explains, the Data Governance team’s scope of responsibility typically divides into three primary functions:

Architect
Team members help design a strategy to build enterprise data capabilities while partnering with data operations teams. They educate stakeholders across multiple data domains about how systems are designed, how data is captured, and how it can be leveraged.

Investigator
The team also identifies gaps in existing data processes and technology to help build business cases to address. By digging into these cases and finding solutions, they improve processes and display measurable ROI.

Librarian
Lastly, they serve as librarians by cataloging data sources and business definitions. They also show how systems are connected through data linkage, which drives a better understanding of business intelligence metrics and reports.

While incorporating all of these functions may seem overwhelming, it’s important to remember that a Multi-Domain MDM solution can make these tasks more manageable.

The Data Governance Team

So, what does this team or department usually look like? It doesn’t need to be huge, just strategic. With an eye on continuous improvement, this team can grow as the organization’s emphasis on data management evolves. Typical they are comprised of:

Chief Data Officer or Sr. Manager – This is the person who spearheads data governance efforts for the organization. Responsibilities range from securing funding for the program and staffing it up to advocating for the program and monitoring its progress.

Data Managers – Often having ownership over individual data domains, these managers implement the strategic vision of the overall program.

Data Analysts or Business Analysts – Along with the rest of the data team, they develop and implement data standards. They also monitor the flow of data with an eye toward continuous improvement of data management processes and efficiencies.

Key Stakeholders Play Their Part

While the Data Governance team leads the way, the entire organization has to be on board with the program. Other stakeholders play a significant part in the success of the data initiative. These include:

Data Stewards or Champions – These are subject matter experts. They set up domain data and work to maintain the policies and processes established by the team. Members of this group often gather in monthly/regular tactical meetings.

SteerCo – An abbreviation for Steering Committee, this group is comprised of representatives across all organizational levels. They typically meet quarterly to discuss strategic data goals, provide cross-functional feedback, and make decisions on the direction of the program.

Third-Party Stakeholders – Data flows into a modern organization from multiple sources. Manufacturers, distributors, vendors – they all can help maintain the data quality. When business rules are disseminated to these parties, and the standards are upheld, it makes the job of the team easier.

MDM: The Data Governance MVP

Clearly, no data governance team can succeed without an organization-wide effort to plan, implement, and improve its data analytics.

When companies combine the power of MDM with a strong data governance program, they can finally make strides in the quality, standardization, and completeness of their data across any domain or channel. Some of the key benefits of MDM include:

  • Defining data policy aligned to business priorities
  • Customizing business rules and assigning workflow and owners
  • Establishing and configuring rights and policies for users and data ownership
  • Tracking actions of users in their respective roles with user-based auditing logs that are maintained for the entire content life cycle
  • Supporting data stewards with policy and procedure enablement

In our recent webinar series, Ingryd Hernandez of US Foods outlined how EnterWorks has been crucial in the evolution of their data governance initiatives. We invite you to listen to her advice and experience in the webinar here.

About the author

Kerry Young

Kerry Young joined EnterWorks in 2006 when Ennovative, Inc., the multi-channel publishing software company he co-founded, was acquired by EnterWorks. He directs EnterWorks’ operations and leads EnterWorks’ professional services and consulting organization, ensuring effective customer implementations and ongoing success. Mr. Young brings more than 25 years of technology and business management experience to EnterWorks, having served as CTO for a subsidiary of the Dow Chemical Company, and earlier as VP, Information Technology for Marshall Industries, a $1.7 billion industrial electronics distributor. He previously managed information systems for a subsidiary of McDonnell Douglas Corporation. Mr. Young holds a B.S. degree in Computer Science from Cal Poly, San Luis Obispo and an M.B.A. from California State University Fullerton.

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