Chicago Booth Magazine Measuring Success to Maximize Impact

Social sector organizations worldwide wrestle with one fundamental issue: How do they know they are having an impact? That’s the sector’s $64 million question, and it was at the center of an insightful and thought-provoking panel discussion.

Hosted by Chicago Booth’s London campus, the event marked the Rustandy Center for Social Sector Innovation’s first visit there following the announcement of a $20 million gift from Tandean Rustandy, ’07 (AXP-6). Moderator Robert H. Gertner, John Edwardson Faculty Director of the Rustandy Center and Joel F. Gemunder Professor of Strategy, opened the event by remarking, “Nonprofits must focus on measuring impact in a way that maximizes success and induces governments and funders to make smart decisions.” 

Such measurement is proving difficult. Those same funders increasingly want proof of an intervention’s effectiveness before investing in it. Governments struggle to decide where to allocate support. For Julia Grant, CEO of Pro Bono Economics (PBE), a good place to start is focusing on impact management, rather than measurement. “Measurement implies a passive observer without real accountability,” she suggested. “Management is about identifying and driving impact throughout a whole journey of learning and improvement.”

Naturally, though, there’s no fairy-dust solution. Instead, it was suggested during the debate that organizations should assess their needs and resources, and act accordingly. Just ask Katherine Mathieson, chief executive of the British Science Association, a UK nonprofit that seeks to inspire more young people to consider science and engineering careers and was, itself, assisted on its own impact journey by Grant’s PBE. 

Initially, Mathieson’s organization considered randomized control trials (RCTs) with students. “These are great but expensive,” Mathieson said, “and the control group gets all the hassle but none of the benefits.” Eventually she sought PBE’s help in analyzing multiple external datasets to uncover what really influences attainment and interest in science. This allowed the organization to deliver a more evidence-based approach to funders and sharpen decisions about how to target the program’s interventions.

And with that determination came a new question: If RCTs aren’t always a cost- or time-effective option—and there’s the added issue of their inability to capture unobservable mechanisms and motivations—then could big data provide the answer instead?

“Big data will be transformational and can be especially helpful when deciding who to target with social interventions,” said Marianne Bertrand, faculty codirector of the Rustandy Center and Chris P. Dialynas Distinguished Service Professor of Economics. “But if you’re using past data to predict the future, it may contain the exact historical biases you’re trying to eliminate.”

And therein lies the rub. For social sector organizations, life is increasingly a balancing act: they must know when to turn to science and when to invoke more-human instincts. At the same time, they must reconcile funders’ demands for up-front evidence with their unwillingness to invest in major data projects rather than on-the-ground interventions.

For Grant, the key is to keep sight of the ultimate goal. “It’s critical to understand your logic model and how your mission links to the outcomes you want,” she said. “That’s the only way to determine whether your interventions are actually making a difference to those who need them.”

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