ultimate TOR template

Any working group, steering committee, strategy setting council and so on, will be more successful if it understands its purpose, responsibilities, and overall expectations. Outlining all these expectations will ensure a higher commitment and engagement rate from its members. This is also the case with a Data Governance Council (or however else you would like to name it). In this article, I’ll provide you with the ultimate Terms of Reference (TOR) template you can start using for your council’s meetings.

In a previous article, I’ve talked about what a TOR is and what its 4 crucial components are. In here, let’s outline how the document should be structured and what it should outline.

Spoiler: I’m offering a free template of a data sources inventory at the end of this article.

Document history

I start every document with outlining its versioning, what changes occurred and when they came into effect. Yes, most document management tools would have this as a built-in functionality, but having this outlined in the document itself helps ensure the most current document is being used and this metadata is agnostic of the document management platform.

Council’s roles and responsibilities

I’ve wrote in more detail about its purpose, roles and responsibilities in the Data governance council – what is it and why do you need one? article so I won’t cover this again here, but I’ll outline examples in the template provided below.

Organizational hierarchy

Since this group includes members from across the organization, it is important to explain where it lies within the organization. An organization hierarchy diagram fits perfectly here as it will visually outline who the group reports to and who reports back to the group. This is usually dependent on the data governance operating model you will adopt.


Include the criteria by which the members are appointed to take part in this group. Also outline the maximum number of members to take part.
Ideally the membership will be reviewed every 2 year or as membership spots become vacant, but whatever the number of years you choose to recommend, make sure it’s mentioned here.

Outline the names and titles they hold within the organization. It’s also best practice to outline their roles within this group. Typically you will have:

  • Chair (ex: Data Governance Lead)
  • Voting member (ex: VP Finance, VP HR)
  • Non-voting member (ex: note taker, program coordinator)
  • Guest member (ex: subject matter expert)

If you allow member substitutions, make sure you describe those terms. Ex:

  • Voting members can only appoint another person to attend X meetings/ year on their behalf
  • Special circumstances such as (vacation, sickness, unpaid/paid leave, etc.)
  • Voting privileges of member substitutions

Meeting expectations

Provide the expected meeting frequency and time commitment of these meetings. Typically, the meetings can occur as frequent as once every two weeks, especially in the early stages of the Data Governance program, to monthly or quarterly meetings.

It’s also worth noting that additional meetings may be called where there is extra demand for a review of projects, policies, or strategies due to new priorities.

The meeting time commitment is usually between 60-120 minutes, but you should mention that typically another 30-60 minutes is expected to be needed in order for members to prepare for the meetings (i.e. reading the agenda, reviewing the meeting notes from the previous one, delegation and communication of tasks, projects and program status to their own business units).

I recommend providing some clarity around the agenda. You can find more details around this in the template below and the 4 crucial TOR components article.

Consensus and voting

A quorum should consist of 50% of voting members plus one and should be required for all material decisions affecting project proposals and business cases. Make a note of which ones are the voting members (listed in the membership above), and how many votes each member receives – usually 1 per member, but there are cases where a heavier weight is provided to specific parts of the business.

Here you can also outline the voting procedure and who will conduct it (can be the chair or a program coordinator). Ex of voting procedure considerations:

  • Anonymous vs non-anonymous voting
  • In-person vs online voting
  • By proxy or by elected members only


Once a document is finalized or changes are made and come into effect, the final version of the document should be approved by the Data Governance lead and/ or Data Governance program sponsor.


This is optional, though I reserve this appendix section to provide some defined terms. If you’ve used any acronyms or terms which you believe would require further context, explanation, or a definition, here is the place where these should be outlined. I recommend defining the Data Governance program, key data governance roles and any technical terms with which the members might not be familiar with.

Free Terms of Reference template:

terms of reference template

Download “Data Governance Terms of Reference Template”

DG-Terms-of-Reference-Template.docx – Downloaded 4990 times – 148.84 KB


Here are some examples I found if you’d like to have some practical examples to inspire yourself from. In no particular order:


The contents of this document can sometimes be found in a Data Governance Charter document as well. Wherever you choose to outline this content, it is good to do so and have it available to the Data Governance council’s members, but also to all the stakeholders of the Data Governance program. Transparency and communication are underrated so contribute to them whenever you can.

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(more templates included)

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About the author 

George Firican

George Firican is the Director of Data Governance and Business Intelligence at the University of British Columbia, which is ranked among the top 20 public universities in the world. His passion for data led him towards award-winning program implementations in the data governance, data quality, and business intelligence fields. Due to his desire for continuous improvement and knowledge sharing, he founded LightsOnData, a website which offers free templates, definitions, best practices, articles and other useful resources to help with data governance and data management questions and challenges. He also has over twelve years of project management and business/technical analysis experience in the higher education, fundraising, software and web development, and e-commerce industries.

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