Nonprofit leaders often grapple with the question of how large their organization must become to have the impact they desire. Inevitably, that question is coupled with the question of where the money will come from to support that growth.

A new study by The Bridgespan Group explores the funding strategies of large US-based nonprofits and reveals two key findings. First, we found that over 90 percent of these “really big” nonprofits (those with $50M or more in annual revenue) raised the bulk of their money from a single category of funding (such as government or program revenue). Second, we found that an increasing share of these organizations now rely on philanthropy as their primary source of funding.

Read more about what we found in our Stanford Social Innovation Review article “A New Look at How US Nonprofits Get Really Big.” 

(While you’re at it, check out our new related research on nonprofits in Kenya, Nigeria, and South Africa in “How African NGOs Grow.”)

Funding Categories At-A-Glance

The assets and capabilities required to effectively pursue a revenue category such as government, philanthropy, or individual giving can vary greatly from one category to the next. The chart below provides an overview of some of the most significant characteristics, assets, and capabilities associated with each type of revenue, based on our data and experiences in the United States. Consider it a starting point in asking critical questions about what is the most plausible, effective, and sustainable revenue mix for your organization. (You can also download a PDF copy of the table.)

* “Examples of Natural Match Domains” refers to common domains of work for “really big” organizations that relied upon a given funding category. “Really big” nonprofits are defined for this work as organizations found in our research of nonprofits that, as of 2021, had grown to $50 million or more in annual revenue within 30 years of founding. See “A New Look at How US Nonprofits Get Really Big” for more detail. These examples are a starting place for organizations to consider high-potential funding categories; they should not deter organizations from pursuing other promising opportunities based on their own analysis and circumstances.

Research Methodology

Because we sought to compare current revenue results to those from our 2007 study, we adopted a similar methodology. We:

Looked at US-based nonprofits founded since 1990 that have grown to annual revenues of $50 million or more. As in the 2007 study, this represents roughly a maximum 30-year timespan between an organization’s founding and its most recently available revenue data. As before, limiting the age of nonprofits in our data set ensured we were able to identify instances where organizations identified their funding model and scaled relatively rapidly. It also established a clear starting point from which revenue growth could be measured.

Examined the most recent publicly available audited financial statement (or IRS form 990) for each organization. For about 80 percent of the organizations this was 2021, but for the remainder we looked at 2020 or, when available, 2022.

Kept the $50 million revenue threshold rather than adjusting for inflation. Even today, $50 million is a lot of revenue, and we were happy to have a larger data set to explore.

To remain consistent with the methodology of the 2007 study, excluded several categories of nonprofits, including hospitals and universities (whose sources of funding are well understood) and affiliates of national networks founded before 1990 (in which case these newer affiliates had access to a variety of supports from a pre-existing organization).

Grouped revenue into six categories—government, program service fees, corporate, philanthropy (foundation grants as well as individual gifts of $10,000 or more), individual giving under $10,000, and investment income.

To gather data on CEO/executive director racial and ethnic identity, we emailed inquiring about the leader’s identity to all organizations with publicly listed email addresses. In instances when we could not find an email address or did not hear a response, we looked at self-identifying information from Guidestar, LinkedIn, biographies, keynote speeches, press releases, professional associations, etc. If there was no clear indicator of identity, then those leaders were excluded from the overall count. Overall, we were able to learn the racial/ethnic identity of CEOs and executive directors at 290 of the 297 organizations.