5 Steps to Strengthen Your Grantmaking Organization’s Data Governance

A grant management system is no place for your garbage.

And yet, many grantmakers leave duplicate records, incomplete contacts, and incorrectly formatted information littered throughout their GMS, waiting to be scooped up in reports. Garbage in. Garbage out.

Without good data management examples and expectations, your team may not be aware they are making these mistakes. A strong data governance framework helps you build confidence in your data so you can make more informed decisions and be prepared for unexpected changes.

In our webinar with grantmaking consultant Lisa Tacker, she highlighted the importance of data governance for grantmakers and how to incorporate it into your organization.

Why is Data Governance Important for Grantmakers? 

Data governance is the cornerstone of data management. It outlines how your organization’s data should be managed responsibly, securely, and aligned with your overall goals.

It is the framework that ensures data is managed effectively throughout its lifecycle, from creation to deletion.

The core principles of strong data governance include:

  • Ownership: When people with domain expertise own their data, they are more likely to know the data creation process and what good data looks like.
  • Data Quality: Set expectations and rules to ensure that your data is accurate, consistent, and complete.
  • Security: Protect your data from unauthorized access, use, disclosure, disruption, modification, or destruction.

When you have strong data governance in place, it boosts data quality because there is an expectation of completeness. It also improves accuracy and minimizes inconsistencies.

With more accurate data, you can make more data-driven decisions because you have confidence and a better understanding of the needs. And more consistent controls improve security, which builds trust and fosters transparency with your stakeholders. 

Here are five best practices when establishing and managing your grantmaking organization’s data governance.

1. Identify Critical Data

You can’t manage data you don’t know you have, or don’t know where it’s located.

Conduct an inventory to locate all data sources. This includes spreadsheets, marketing materials, and customer information that might live in emails or forms. What information is coming into your organization and where is it being stored?

Evaluate each data asset based on three factors:

  • Data sensitivity: What is the confidentiality level of the data? Does it include financial information or personally identifiable data? What would the potential impact be if an unauthorized user accessed this information?
  • Regulatory requirements: Certain data types might fall under regulations, like health care data. Know the regulations that apply to your industry and identify the data that might be applicable to those regulations.
  • Business value: You don’t have to worry about data you don’t store. Make sure all the information in your system supports critical decision-making or strategic goals. If it doesn’t, delete it.

2. Standardize data collection formats and processes

Define how you want information collected and stored so it can be pulled accurately into reports.

For demographic data, standardize field inputs like titles, genders, and dates so users choose from a list or are prompted to use a specific format. Use your system to confirm email addresses have an @ symbol, for example. Match organization names to a database like Candid so The Animal Shelter of Springfield doesn’t accidentally get a second entry under Springfield Animal Shelter.

Take advantage of integrations and bulk data uploads whenever possible. For example, have your grant application automatically pull data into your CRM instead of having to manually enter or update contact records each grant cycle. This will make sure the data is always in the same format.

Schedule time on a regular basis—monthly or quarterly—for data cleaning tasks. Run reports to identify outliers, duplicates, and other potential issues.

3. Leverage technology solutions

Your grantmaking technology stack can take a lot of the data governance heavy lifting off your plate. Lean on your grant management solution and other systems to automate and streamline your data entry and validation processes. 

The first step is making sure you know and use any applicable automation available in your system, such as creating contact records from applications. If you aren’t sure what functionality your GMS has, look for on-demand training or talk with your account manager.

Your system should also help you merge data from diverse formats into a single place to create reports for holistic analysis. Whether it’s payouts from your fund accounting system or contact updates from your email marketing tool, find ways to integrate your GMS to limit manual data entry.

4. Establish clear data ownership and access protocols

The people who are closest to the point of entry should own the data governance for that set of information.  

Make it clear who owns which data pools. Database managers should be a resource, but different parts of the organization are going to know their data and what they want more than the database manager. You can look at a donor record and know if a field is empty, but you won’t know if what is in there is incorrect.

How seriously an individual may take data ownership will depend on how much it impacts them. Show them how accurate data can impact the reports that drive decisions and how they can get a more holistic picture when the data set includes all records—instead of missing incomplete records.

Along with establishing clear data ownership, you also want to define data access protocols. Who can view certain data and who can change certain data? Create role-based permissions based on the principle of least privilege—each person has the access to do their job and nothing more. If they need more as their role changes, that should be reviewed on a role-by-role basis.

5. Prepare for the future of data analysis

Artificial intelligence and machine learning have the potential to streamline and supercharge your grantmaking data analysis.

Through AI, we are redefining how data can be used to create more impactful outcomes. Soon, you can expect tools that incorporate AI to be able to automatically flag incomplete applications, and not just where fields are incomplete but where an applicant may not have answered a question fully. It will help you allocate resources more effectively and analyze large data sets faster so you can better forecast the needs of your community one, three, and five years in the future.

But we are still in the beginning stages of its application. AI and machine learning are tools. They need human oversight. AI won’t take your grantmaking job, but as more AI tools become mainstream, you need to be prepared for how it can help you manage your grantmaking processes more effectively.

If your organization doesn’t have one already, create a cohesive and widespread policy about AI adoption and implementation. Grantmakers need to be aware of potential bias in the AI-enhanced tools you may be adopting. Understand that something is on the other end “teaching” this technology, and that “something” might have bias that can alter the output.

Your policy also must outline how you are articulating to stakeholders how you are using this technology. The goal is to be very transparent. Explain how you are using this technology, and how it might impact any decisions you make. It could be as simple as identifying potential gaps the grantee can address prior to finalizing their application to providing summaries to reviewers as part of the application review process.

Visit associations like TAG to find best practices and guidelines for creating an AI policy.

The Human Is at the Center of Good Data Governance 

Ultimately, it’s important to keep the human touch in your grantmaking processes. Yes, you are using technology, but ultimately a human is going to look at the data and make a final decision. It will always be important to maintain the relationship with the community, maintain connection with the people you are helping, and establish and grow the human connection as you use technology ethically

Grantmaking decisions affect real lives. Strong data governance helps confirm that the data we make our decisions on is accurate and fair. To learn more about the importance of data governance for grantmakers, check out our webinar, Unlocking the Power of Data: Data Governance for Strategic Grantmaking.