[Short on time? Scroll down to read the TLDR version.]
I wrote last time that one way grant-making can fall short is through an accountability approach that thwarts learning and adaptation. But that’s not the only reason grants (or any strategic set of projects and programs) might have less impact than they could.
A recent Thoughts & Links note highlighted an article questioning whether measuring outcomes of individual programs and initiatives tells us much about their overall impact. Impact “is more associated with cumulative actions — where the whole is greater than its parts,” and so we must ask how to
build coherent narratives of impact ***across*** parts. In other words, we may have thousands of project-based assessments and evaluations but still have no real understanding of any change, or of the cumulative impact of all these projects. If that’s the case, then how do we really know that any of the activities are generating positive momentum in the desired direction of travel?
That’s particularly important for strategic endeavors like grant-making that seek to change things at a scale beyond the direct customers of a funded initiative.
Thus, we may fund building a highway, but we intend to improve connectivity or reduce traffic. We may fund services for people experiencing homelessness, but we intend that to be part of a larger effort to reduce homelessness and its impact on the community.
But how many organizations actually structure their grants and other initiatives to ensure that what they fund is meaningfully connected to what they intend?
To do that you must consider two distinct types of connection.
Linear Connections: The Chain
When we implement programs for strategic impact, we usually have in mind a kind of linear chain in which (1) the activities of the funded project bring about (2) customer outcomes, which in turn contribute to (3) progress toward a larger goal.
For example, Asheville nonprofit Eliada Homes works with youth aging out of the foster care system who are at risk of homelessness. They provide a combination of life skills training and individualized case management, with a focus on addressing their social determinants of health. Clients exit with core needs addressed, problem-solving skills, and a network of resources, reducing their individual likelihood of ending up homeless and thus contributing to reduced homelessness at the community level.
Organizations have gotten better about thinking through these connections, particularly from (1) to (2). The last section of the chain often gets shorter shrift.
While it would be inaccurate to say that ensuring impact on this level is “easy,” it is, in fact, largely a matter of discipline, as I discussed in the series on becoming a data-informed organization.
What is critical for improving impact on the larger scale from this chain perspective is to make sure you think through both proximate and ultimate goals and measures in order to connect (1) all the way through (3).
Nonlinear Connections: The Tangle
For the hardest challenges, a single funded project or program is a very small part of a very large system.
At minimum, that means the contribution at the community level will be small compared to the overall need. But that contribution may well also depend on how it relates to the other parts of the system.
One example where communities have begun to recognize this nonlinearity is gentrification. The development of an neighborhood amenity like a park or greenway that seems obviously of benefit to the people living there can potentially interact with market forces and cause displacement of the very people who were supposed to benefit. Many of us have become familiar with the tangle that happens around affordable housing.
But this kind of tangle happens with most of the hard problems communities face, from public safety to criminal justice, from housing to health, from economics to education. All of these are systems and can only be addressed as systems.
Simply implementing a collection of good programs doesn’t work on a tangle.
Some Steps Toward Improvement
We all wish there was a simple way to approach this. Unfortunately, nothing makes these hard, systemic problems not hard.
Nevertheless there are many ways to improve how we approach them and to make better progress by thinking across. I’ll briefly discuss two.
1. Use a people-centered community indicator framework
It’s easy to track affordable housing through simple metrics like cost ratios or vacancy rates. But those only capture one dimension of the issue. They must be embedded in a framework that is people-centered rather than issue-centered since it is through the experience of people that the issues organically interconnect.
One such framework is that of social determinants of health (SDOH), non-medical influences on human health outcomes across five key areas: healthcare access and quality, education access and quality, social and community context, economic stability, and neighborhood and built environment.
As at Eliada Homes above, SDOH is frequently used to address individual needs, but it also works quite well in the aggregate, whether for a community as a whole or for individual subgroups by race, gender, age, etc.
The value of such a framework is that it encourages thinking about individual programs’ impact across dimensions, as well as how those programs might interact with other quite different kinds of contributors to a given SDOH area.
There’s no magic to this, of course. Encouraging thinking doesn’t make it happen, but it does provide a structure to extend your data-informed decision-making practices in ways that constructively engage with the tangle of reality.
2. Set up structures for collaboration and coordination
Using a framework like SDOH internally can certainly improve the effectiveness of an organization’s investments, especially if that organization operates across multiple domains, as governments do. But even governments are just one player among many in their communities.
For the toughest problems it is critical to find ways to work together through formal and informal structures for collective governance.
There are many examples of this kind of structure. A couple that I’ve been involved with locally are a new community Continuum of Care for coordinating systems to address homelessness and the Buncombe County Justice Resource Advisory Council for systemic planning and coordination of criminal justice efforts. I am particularly excited about an upcoming opportunity to interconnect them.
Creating such structures is obviously well beyond the scope of this article but where they already exist they present some of the best opportunities to think across organizations and even across domains.
Most relevant from a data perspective is that applying indicator frameworks like those described above to the work of collective governance can both improve results within a specific domain and effectively connect those results to work happening in other domains.
Links & Thoughts
Room and Respect, inside edition. The ideas in last week’s article apply well beyond just grant-making. I was delighted to find them in this article on the HR function at Measures for Justice, a nonprofit focused on transparency and accountability in criminal justice.
Proxy measures, fast food edition. Many Texas Gulf Coast residents remained without power and facing a deadly heat wave days after being hit by Hurricane Beryl. Frustration with the local utility company lack of a way to inform customers of power outages led residents to devise an innovative proxy measure: gray icons, indicating closed stores, in the fast food franchise Whataburger app. HT Semafor.
tldr
Another way strategic efforts like grants can fall short is that they don’t think through how direct impact on clients connects to impact at the community level. To do that requires thinking about two types of connection.
The first is the linear chain from activities to customer outcomes and then beyond to the larger, ultimate goal. This is basically the discipline discussed in the series on becoming a data-informed organization.
The second is to think across contributors at the community level, including the ways that your program might interact with other factors. Just implementing a bunch of good programs doesn’t work on systemic issues that operate like a nonlinear tangle.
There is no simple way to handle such systemic problems, but there are a couple ways to improve our approach.
Use a people centered community indicator framework. Using a framework like the social determinants of health (SDOH) encourages thinking about individual programs’ impact across dimensions, as well as how those programs might interact with other quite different kinds of contributors to a given SDOH area.
Set up structures for collaboration and coordination. Formal and informal structures for collective governance present some of the best opportunities to think across organizations and even across domains. When these groups employ indicator frameworks like the above they improve their own results and better connect to work in other domains.
If you want to share thoughts on anything I’ve said here or have ideas about further questions or topics you’d like me to explore, please feel free to reply to the newsletter email or contact me here.