Processes and Practices Around Meaningful Measurement: A Case Study

Processes and Practices Around Meaningful Measurement: A Case Study

Publication date: 
January, 2015

by Lisa Trahan, Director of Communications, St. David's Foundation, Austin, Texas

How do you know if the funds you are investing are actually making a difference in the lives of those you are trying to reach? The concept of outcomes-based philanthropy provides a framework for analysis and discussion. 

In a 2012 article for the Stanford Innovation Review, Paul Brest, former president of the William and Flora Hewlett Foundation writes that “outcome-oriented” is synonymous with “result-oriented,” “strategic,” and “effective.” 

Attendees at the recent Nonprofit Organizations Institute sponsored by Philanthropy Southwest and UT Law learned how a major foundation is approaching outcomes-based philanthropy. Semonti Basu of the Michael and Susan Dell Foundation (MSDF) says that in order to practice outcomes-based philanthropy, you must first ask a lot of questions, such as: What are outcomes? How do you get them? What data should you collect? What’s being done with it? What are other funders requesting?

With that in mind, MSDF embarked upon a data roadmap project to determine how to collect data to tell a story. The foundation’s donor analytics team looked at myriad of data they had collected from grantees, and analyzed what, if anything, was being done with the information. They had face to face meetings with each of their grantees to learn about the data being tracked by each agency. The team convened fellow funders to find out what metrics their organizations were requesting. They also met with data recipients - organizations who gather, track and map information- as well as data contributors, such as local health care systems, school districts, and police departments.

This research revealed several challenges with data collection. One was a lack of standardization across multiple outcomes. Another was the realization that multiple data sources had different reporting cycles, making it challenging to compare data sets across a specific timeframe.

It became clear that MSDF should focus on the information they considered most important as well as items that could be consistent from agency to agency. For MSDF, that meant basic organization information, demographics, project outputs, such as participation, attendance, cost per child, etc., and program outcomes, such as behavior changes, increased school attendance, etc.

Through this roadmap project, MSDF was able to reduce number of metrics collected by 30%. Eighty percent of their academic outcomes were standardized, and data fields were created for items that were previously narratives.

In addition, they set up a working group of funders who now meet regularly and are working towards aligning their reporting metrics. They have also set up cohorts of community groups to help standardize key community indicators.

For those considering moving toward an outcome focused model, Basu says that impact doesn’t have to be measured solely in the impact downstream. Throughout the process itself, the MSDF team has learned valuable lessons. Those include the importance of meeting people where they are and considering the program first and the solution second. It’s important to plan for the solution in context and get the right people on the job. Balance the small wins and the big ones. Don’t reinvent the wheel.

And once your metrics are determined, then you can become a benchmark data provider to help your grantees determine how to expand or extend services.

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