Learn how to manage valuable data every day at your nonprofit.

Director of Data and Systems at the Greater Washington Community Foundation in Washington DC, Jenn Walen, discusses her role in managing data policies and training and supporting nonprofit staff in keeping data clean and organized.

Jenn stresses that you need a single source of truth, standards for data entry, and policies. Spending the time to decrease the time spent pulling reports and seeing the whole picture is extremely valuable in this moment. Jenn shares advice and experiences in getting your nonprofit’s data where you want it to be.

Everybody wants to look good. Good data helps everyone at your organization look good – to your board, your executives, your donors, your constituents. And good data saves everyone time.

Additionally, nonprofits looking for one thing they can do to protect themselves in this political environment should look to their data governance and standards. This project doesn’t have to involve highly paid consultants or new expensive tools. It just takes prioritization, time, and good change management.

Recommendations: 

Be consistent. Create standards and uphold them. No exceptions.

If you need data governance documentation, templates and assistance are available online. You don’t have to start from scratch, ask your colleagues. 

Kindness along the way is important. This is not easy. Data clean up is a pain. Everyone lending a hand can help create solidarity and a culture of accuracy. Support your colleagues!

People learn in multiple ways and with multiple styles. Provide training and support to meet them where they are.

Get support from leadership to emphasize data clean up priorities.

It is so satisfying when the data is in good shape. The rewards for doing the hard work are great.

Is there an AI tool that can do this for you? 

AI tools are helpful. Start with education and training on the tools you plan to use. The tools you can use will depend on your database. Get the training from your vendor on the AI that is being incorporated into your tool. Work with a data consultant to understand implementing AI to understand the implications, the security, and matching the tool to your needs and use policies.

Every output from AI needs to have a human review. Don’t expect to give AI your data and have it sort and clean it for you with minimum input from humans. 

Be careful. Respect confidentiality and follow your organization’s data governance policies. Think about how you would want an organization to handle your own data.

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