We are at a regional university, and we are in the very infant stages of our data journey. We are launching our Data Governance Board, with the first meeting coming on Monday. Does anyone have a list of operating procedures, framework, etc. that they might be willing to share for me to look at?

Launching a Data Governance Board at your regional university is a strategic move that can significantly enhance institutional decision-making and data reliability. Below is a streamlined and practical framework outlining essential operating procedures and critical success metrics suitable for your initial phase:

Data Governance Board – Operating Procedures

1. Purpose & Scope

Mission Statement: Clearly articulate your purpose. For example:

"To establish policies, processes, and standards to improve institutional data quality, consistency, security, compliance, and usability in support of strategic goals."

Initial Scope: Define a manageable initial scope (e.g., student records, faculty data, financial aid).

2. Governance Structure

Membership & Roles:

Chairperson (Data Governance Lead)

Data Stewards (departmental representatives)

Data Custodians (technical support)

Executive Sponsor (senior leadership)

Meeting Frequency: Monthly initially, adjusting as needed.

Attendance Requirements: Set clear attendance expectations.

3. Meeting Protocol

Agenda Distribution: Send agenda at least three days before meetings.

Documentation: Maintain clear minutes outlining decisions and action items, distributed within five days.

Decision-Making: Establish transparent processes (consensus or majority voting).

4. Roles & Responsibilities

Role - Executive Sponsor
Responsibilities - Strategic guidance, resource allocation

Role - Chairperson
Responsibilities - Facilitate meetings, manage communication

Role - Data Stewards
Responsibilities - Ensure policy adherence, represent departments

Role -Data Custodians
Responsibilities - Implement decisions, manage technical aspects

5. Data Governance Framework

Policies: Data quality standards, security and privacy (FERPA), data lifecycle management, and classification.

Processes & Standards: Define clear data ownership, create data dictionary/glossary, establish issue resolution workflows.

Tools: Use shared documentation systems (e.g., SharePoint, Teams).

6. Communication & Training

Communicate regularly across campus.

Implement basic training for stakeholders on governance standards and processes.

Key Success Metrics to Track

Metric Category - Data Quality

Initial Metrics (first 12 months)-15-20% improvement in completeness and accuracy

Metric Category -Compliance & Risk

Initial Metrics (first 12 months)-Zero major compliance incidents

Metric Category - Adoption & Engagement

Initial Metrics (first 12 months)-90% attendance in board meetings

Metric Category - Issue Resolution

Initial Metrics (first 12 months)-Reduce issue resolution time by 25%

Metric Category -Training & Literacy

Initial Metrics (first 12 months)-50% stakeholder participation in training

Metric Category -Strategic Impact

Initial Metrics (first 12 months)-Document at least two tangible success stories

Implementation Tips:

Establish clear baselines to track improvement.

Regularly review metrics and communicate successes.

Adopting this structured yet flexible approach positions your Data Governance Board for early success, clearly demonstrates value to stakeholders, and provides a strong foundation for future growth.

In case you need more help , please DM me we can get into a video call and i am happy to walk you through in detail.

It depends on what you want the Governance Board to govern - is it data protection, is it a change control environment etc. Agree with other comments, it will need to be tailored to your needs. We set up a Board in our infancy 4 years ago and collapsed it, mainly as the Board member level of maturity was so low. So regardless of the Terms of Reference, make sure your Board members understand what you are considering and the relevant risks by developing a training programme alongside. We now have a Change Advisory Board, a Design Authority and Data Design Authority and a Business Operations performance sub committee. Good luck

Firstly, congratulations on recognising the importance of your data!
Operating procedures are very much org specific and probably need to be tailored to suit.
There are many frameworks - we have some fabulous frameworks, tested and proven but we'd need an engagement to share those and help tailor them.
One hint I'm happy to give away is the first step to good data governance is ownership - work out who in your org owns the data and work through principles, incentives, new roles you may need to create such as data stewards.