Proposed Network Analysis of Food System Grantmaking

Julia Leis 

For DH217: Module 2, Social Networks in Organizations

Overview:  

Traditionally, philanthropic foundations have taken an independent approach to grantmaking, conducting charitable giving tied to an individual foundation’s strategic priorities, without connecting to other foundations or to a broader strategy for systemic change in a particular region.  Moreover, private and community foundations are not in the habit of collaborating closely with one another, or with government entities, both in terms of sharing information on 1) the level or amount of funding given to nonprofit organizations, 2) the type of grant/funding, and 3) the frequency of the grant (the number of years).  This is particularly evident in food and agriculture systems.

Given my background working with philanthropic foundations, I believe mapping foundation and government food system-related funding to nonprofit organizations may reveal current funding priorities as well as the potential for opportunities for foundations to collaborate more effectively in food system grantmaking.  These may be priority issue areas that are not necessarily food-specific, but that still intersect with the food system, such as workforce development, education, health and small business development. 

Funders are beginning to see the benefits and the imperative of collaborating with each other, especially given the decline in assets after the 2008 financial crisis. Many foundations are calling for targeted investments in certain sectors to achieve similar results.  Nonprofit organizations are also feeling the squeeze, as they are expected to produce the same level of impact with fewer dollars from foundations.

Utilizing a social network analysis (SNA) approach, I propose to map and visualize food-system grantmaking in a specific geographic region.  I plan to create a 2-mode network data set (the nodes would be foundations and non-profits), where the edges of the data would be whether funding exists between the nonprofit and the foundation (Yes/No) and the level of funding ($ amount).  By classifying the level ($ amount) and adding attribute data that would detail the type or purpose of the grant (organizational development, general operating support, program delivery, etc.), a network analysis would reveal which foundations are funding certain organizations as well as the nature of that funding.  The analysis may also reveal if there are any potential opportunities for more strategic collaboration between foundations.

Questions:  What kinds of patterns exist between foundations and funded food-related nonprofit organizations in a specific region? How much money, what types of grants and how frequent is the funding from foundations to these nonprofits? If there is funding overlap between foundations, could there be opportunities for more effective grantmaking?

Hypothesis:

By understanding the patterns of food-system grantmaking in a certain region, select nonprofits may be receiving more grant funding than others and there is most likely an uneven distribution of funding to these nonprofits. Further, there may be multiple foundations funding the same or similar organizations without coordinating with each other.

Network Measures:

The most important network measures will involve analyzing the centrality of certain foundations.  The larger the foundation’s grantmaking capabilities, the more likely it is that it will intersect with other smaller private and family foundations who are funding similar organizations and projects. 

It would also be possible to look at high in-degree scores of select nonprofit organizations that are receiving funding from multiple foundations.  There may be outliers that are only receiving funding from one or two foundations and/or one government entity in the three-year time period.

I plan to also analyze the strength of ties from foundations to nonprofit organizations, based on the amount of money given each year and if the funding is sustained.  Tie thickness could demonstrate the amount of money or the frequency of funding (2009-2011).

Finally, the network analysis might reveal if more foundations are trending towards funding certain issues like childhood obesity (related to an unhealthy food system) versus other programmatic areas like land conservation or beginning farmer training.

Data and Methodology:

The type of data required will be pulled from I-990 Forms for all major foundations in a specific region (approx. 10-15 foundations). Foundations are required to report on their charitable giving, including the name of the 501(c)3 nonprofit organization and the monetary amount. The total number of funded food-related nonprofit organizations is anticipated to be between 50 and 100.

Data limitations:

I will have access to a data set that includes certain foundations that conduct food-related grant funding. This would include information related to the type of grant. The attribute data may be more challenging to acquire, as it will require a combination of research (e.g., foundation and nonprofit websites and nonprofit I-990 forms).  Community foundations publish their grant lists (and even a grant map), to show their philanthropic investments in their region.  Government entities are also likely to issue press releases regarding major funding initiatives to community development or agriculture projects.

However, private and family foundations are less likely to disclose the purpose of their grantmaking (though the I-990 forms will detail the amount).  Acquiring this attribute data will require contacting the foundations directly, or the nonprofit organizations that received food system-related funding.

What type of foundation or government?

1 = Community Foundation 

2 = Private 

3 = Government

What are the foundation’s average grantmaking amounts? 

1 = $10,000-24,999

2 = $25,000-49,999

3 = $50,000-74,999

4 = $75,000-99,000

5 = $100,000+

What are the top three programmatic areas of each foundation’s grantmaking that intersect with the food system?

1 = Education (e.g. school food)

2 = Environment (e.g. land conservation)

3 = Health (e.g. childhood obesity)

4 = Community & Economic Development (e.g. community planning, green neighborhood zones)

5 = Basic Human Needs/Social Services (e.g. food banks)

Year of Funding:

1 = 2009

2 = 2010

3 = 2011

Attribute Data Set:

1 = Organizational Development/Strategic Planning

2 = Service or Program Delivery

3 = General Operating Support

4 = Staffing

5 = IT/Web Development

Other potential attributes:

-       Location in a select metropolitan area

-       Foundation budget

-       Nonprofit budget

-       Foundation staff size

-       Nonprofit staff size

-       Year of nonprofit inception

-       Outside funding (national foundations, non-local foundations)