Ever wondered why a mere 1% of nonprofits command 86% of the sector's revenue? We are about to unravel this mystery. Alongside our expert co-hosts, Ken Berger and Pete York, we dissect the profound nonprofit sector, its hurdles, and potential remedies. From discussing the scale of nonprofits to scrutinizing the disparities in resource accessibility, we unravel the layers of this intricate sector. We delve into the critical role foundations play in creating equitable solutions and how data can objectively demonstrate the collective impact of individual organizations.
As we progress, we shed light on the profound influence of nonprofits on community well-being. We investigate innovative measures and technologies to assess this impact. We discuss how data can illuminate the disparities between over-resourced and underserved communities, and we analyze the Area Deprivation Index—a measure of social determinants of health—to understand the relationship between nonprofit services and the well-being of a community.
Finally, we explore the exciting intersection of nonprofits and social impact businesses. We contemplate the potential of non-profit businesses, not just as a charitable sector, but as a model for businesses with a social impact. We discuss the transformative power of data in driving growth in the nonprofit sector, underlining the crucial need for data-driven decision-making. Join us as we conclude this enlightening episode by emphasizing the importance of empowering communities and making informed decisions in the nonprofit sector through data.
Ever wondered why a mere 1% of nonprofits command 86% of the sector's revenue? We are about to unravel this mystery. Alongside our expert co-hosts, Ken Berger and Pete York, we dissect the profound nonprofit sector, its hurdles, and potential remedies. From discussing the scale of nonprofits to scrutinizing the disparities in resource accessibility, we unravel the layers of this intricate sector. We delve into the critical role foundations play in creating equitable solutions and how data can objectively demonstrate the collective impact of individual organizations.
As we progress, we shed light on the profound influence of nonprofits on community well-being. We investigate innovative measures and technologies to assess this impact. We discuss how data can illuminate the disparities between over-resourced and underserved communities, and we analyze the Area Deprivation Index—a measure of social determinants of health—to understand the relationship between nonprofit services and the well-being of a community.
Finally, we explore the exciting intersection of nonprofits and social impact businesses. We contemplate the potential of non-profit businesses, not just as a charitable sector, but as a model for businesses with a social impact. We discuss the transformative power of data in driving growth in the nonprofit sector, underlining the crucial need for data-driven decision-making. Join us as we conclude this enlightening episode by emphasizing the importance of empowering communities and making informed decisions in the nonprofit sector through data.
This is For.
Speaker 2:Goodness' Sake. A podcast about the nonprofit sector where we talk openly and honestly about the many challenges that face the sector where we will discuss current and future solutions to those challenges where we explore how the nonprofit sector can have much more positive impact in the world a podcast where we believe that once we fix the nonprofit sector, we can much more dramatically help to fix our broken world.
Speaker 1:Hello everybody and welcome to episode two of, for Goodness' Sake, how we can fix the nonprofit sector to better help and fix the world. And in this episode I am joined by my colleague and co-host, peter York. Hi, peter, hey, ken, how are you? Good? Good, and we're today wanting to start by sort of framing the size and scope of the sector and some of the problems in even just communicating about it, and then in terms of some of the unique challenges based on size and scope that we see out there when we look at this. So let me just start off with a thought experiment for everybody.
Speaker 1:Back in the day, a few years back, there was something called the Occupy Wall Street Movement and feel free to Google that and regardless of your political perspective. They were protesting. They were mad because approximately 43% of US wealth at that time and probably even more so now, probably even more than that is in the hands of 1% of the US population. So concentration of wealth was really a problem. So imagine, as a thought experiment, if the amount of concentration was double that, if 86% of all the wealth in the country was in the hands of 1% of the people, there'd be a lot more people very upset and our country would be in deep, deep trouble. Well, the reason I mentioned that is because that is basically the nonprofit sector in a nutshell. In other words, approximately 1% of the nonprofits in this country going to garner approximately 86% of all of the revenues that come into the sector each year. So what that means another way to say that is, out of roughly 1.5 million charities in this country, only about 15,000 of them have the lion's share of the money.
Speaker 1:Who are these massive nonprofits? Well, the biggest part of the nonprofit sector, at least when it comes to public charities, which is another definition, it's the largest type of nonprofit public charities. The largest percent of the sector is made up of healthcare nonprofits, and those healthcare nonprofits garner about 60% of all the resources that come in. I think that's about $1.6 trillion in 2015, which is the last year. I think there are statistics on this. Education is the second largest $1.1 trillion come in, and then comes human services, at about 12%. I think education is somewhere in between 20%, 30%. So when you put all that together, everything else is single digits. Religious advocacy, environmental international all together are a mere 8% in terms of the revenues that come into the sector.
Speaker 1:So the reason that I belabor that for our conversations is when Peter and I are talking about the nonprofit sector. It's a very complex, multifaceted thing and it's sometimes hard to talk about it in general. I mean, I personally have worked in three of the largest parts healthcare, education and human services and that's not surprising, I guess in a sense because that's where most of the money is, most of the organizations that could afford somebody to run it so full time and to have a full time staff. If you want to hear more about these kind of statistics, you can go to the council on nonprofits and other resources like that to learn more about the sector. But so the problem that I think, one of the big problems that I think we have faith we face and it also is part of what prompted Peter and I to launch this podcast is that a lot of times when experts, consultants, academics talk about the sector, who they're typically talking to is the 1%, because those are the organizations that they typically consult with, that have the money for them to be consulting with, and so a lot of times what that means in practice is that the solutions that they're proposing really don't have resonance, don't have that much relevance for the vast majority of nonprofits Now and this is where I'm going to pass it over to Peter in a second.
Speaker 1:But one of the debates that I think there's no universal answer to that for sure is a pushback that some would say is well. So why is that necessarily a problem that 1% of the charities have that money? Maybe you need that kind of scale to have a meaningful impact. And the problem is more all these itsy-bitsy, teeny-weeny charities about, for example, over half the charities in this country get less than $50,000 a year in revenue, and so maybe the problem is not that they're too large, but perhaps there's just not enough revenues and there's not enough of those big ones and some of those that are smaller should be merging to get bigger to have the scale to have an impact.
Speaker 1:That's one perspective, but I will tell you one last thing before I pass it to Peter for some initial thoughts on this. One of the things that I've heard over the years is and especially I think this is from that 1%. They'll say the problem in this sector is there's just too many nonprofits. We have too many, and I really personally believe that's a bogus argument because since so many of these organizations are so small that it's almost like it's like a spec in terms of whether. In other words, if you got rid of those half the nonprofits, it almost wouldn't matter in the sense that there's so little revenue going to those organizations anyway. They're largely volunteer organizations, so I don't think that's a solution. But, peter, I'm going to inhale now and pass it over to you for your initial thoughts on this.
Speaker 2:Well, and what we're going to experience during these conversations that we have in these podcasts and these episodes is I'm going to come at it from an experience base that comes from data that is going to bring a perspective that is important to share, and that is I've been spending the past five years leveraging the data of the IRS 990 data and other community data from a resource that the US Census Bureau puts out it's a household survey every year called the American Community Survey and we've been spending the past five years myself and a number of my colleagues here, have been spending time building a platform that allows us to really understand more about what this sector looks like, even in terms of the communities they serve, where they're located. And so I bring that up because one of the things you talk about and I think I want to expand upon is this idea are there too many nonprofits? And there's many, and you are right that perceive there are too many nonprofits, and I've actually done evaluation work in my history as an evaluator of different efforts that funders have funded with the goal of addressing the problem of too many nonprofits through the use of mergers and strategic alliances and strategic restructuring, joint ventures, other types of efforts back office efforts to try to really condense all of this and to start to address what they perceive many perceive to be a too big problem. Well, it's really been enlightening to look at what the data show us, when we start to map where the nonprofits are located and really try to dig into this problem or challenge. And I would tell you that it's complicated, as with anything. When you have good data, when you have good big data, you begin to see that one of the biggest problems we have in the field is that there's a lot of us that are at the top of the food chain, so to speak, who over generalize and make statements based on just really generalized numbers without appreciating how complex the problem or the question is.
Speaker 2:Are there too many nonprofits? And so, specifically, let's dig into it a little bit more. And I think there's a part of the question that nobody's asking enough of. It's not that nobody's asking, but they're not putting it front and center. It's where are those nonprofits located and who do they serve? And that's another framing that I think is so important because the work that I know that I've been doing and the stuff that you and I have had many offline conversations and many that my colleagues in the field in this work is really appreciating that. You know. There's a fundamental question we need to understand and that is where are these nonprofits serving?
Speaker 2:And a lot of the big 1% you're describing. If you were to look at a map of the United States these a lot of the bigs, and some of them are scaled or multi-site, so let's acknowledge that. But you're gonna find them more centrally located in big cities. But if you look across the country, there are many, many small cities, metropolitan areas, communities, towns, villages, rural communities, especially where they are not going to be sitting, with a huge number of accessible local organizations that are in that 1% category. And then when we actually go into and look down to even census tract level so think the average community of 3,000 to 5,000 people in a census tract is the US Census Bureau's definition of a community, and there are over 70,000, actually with the new census there's over 80,000 census tracts in the United States.
Speaker 2:When you study these and look at them, even within major metropolitan areas, and ask a very important question which organizations are accessible to the most disadvantaged communities, the communities that are more people of color, more families and people of color, you begin to realize that that accessibility question, especially for service providers, there's a lot of inequities as well.
Speaker 2:And so if you ask the question about size and you say why should we have smaller organizations? Part of the reason is because in so many disadvantaged and excluded communities they are the grassroots, smaller and smaller nonprofit organizations that are in fact serving them. And if you were to get rid of a lot of the smalls, you'd probably be gutting those that already don't have enough nonprofit services and providers and organizations in their community. And then if you look across the United States and expand that conversation and investigation into rural communities and other places, you really begin to see that this question requires nuance. It requires a nuanced understanding of just where are these communities that these organizations are serving, and we need to ask questions through the lens of equity, exclusion and disadvantage.
Speaker 1:So let me take that a step further, and this is really I'm gonna pass it back to you because I remember a conversation we had a little while back I wanna share with the listeners. You had made the observation that from the work that you've been doing that there's evidence it's what I sort of we sort of called it the Goldilocks phenomena. By the way, that might be what we end up calling this podcast. Anyway, the Goldilocks phenomena that relates to the nonprofits, from your research seems to indicate that there's like three basic buckets. There's communities that you've described here that are really underserved. There are the communities in the middle, the Goldilocks ones, that are just. They have just about what they should have. And then there is this other group where they have an overabundance more than even arguably they need of resources and services from nonprofits. Why don't you share a little bit about that and those percentages and whatnot?
Speaker 2:Yeah, so from that standpoint. So a lot of the work that we're doing right now is with the data sets I was just describing is we're beginning to very much look at this issue of like who's got access, who doesn't have access, who's being included, who's being excluded, and with respect to the enough, not enough and too much element, we've been able to look at kind of programmatic output and the association that it has over time with improving or at least contributing to improving community well-being over time. And so what we're learning is that there are census tracks in the United States. If you were to look at it, everybody might think there's kind of a natural orientation. It's like either you don't have enough or you have enough. But the reality is there are many census tracks in the United States for which, if we were to model the data and we have and looked at those associations and relationships, we begin to see that there are certain communities in the United States that actually have access to more than enough healthcare and education services.
Speaker 2:There are those, to your point out, that have enough and they're just the right amount, and then there are those that don't have it and we see great inequities with respect to communities that are actually more poor, more people of color have, significantly are in a situation where they're much more likely to not have enough access to some of these core services you mentioned.
Speaker 2:Human services is a big area it really is, and in many cases our human services are our safety net issues, our safety net providers. And in those cases, if you look across the country and we've studied every census track across the country as to whether they have enough or not or too much we really do see that there's a distribution problem, meaning there are a lot of dollars going to nonprofits that when you look at geospatially, you look at who they're serving, and we can do this through understanding their commuting patterns, which is in the data as well. We know how far they commute to work, we know where they'll commute and with all the mapping technologies we can kind of see. And if you study those, you can begin to really realize that there's some really big problems in the sense that we actually have communities that have more resources, and they have. If you were to look at the thresholds of what predicts future wellbeing for a community, you really begin to see that there are communities that have more than enough.
Speaker 1:And so you're, but in those three buckets I gather that the bucket that has is the biggest bucket is underserved, that's like you know, 40, let's say 40% or something like that, are underserved.
Speaker 2:Are underserved. I don't know that it's 40%, but it's not 10% 30. So the point is I don't wanna quote it and then be quoted incorrectly, but the point is it's a significant amount. It's a significant amount. I can't remember where we fall, but I'll guesstimate right now and don't quote me is between probably 25 and 35% of you know, are literally communities that don't have access and, it's important to note, these are oftentimes in cities.
Speaker 2:These are oftentimes the cities of communities of color and already economically left out of a lot of the opportunities in their area and I also wanna emphasize it doesn't get enough airtime. It's also a lot of our rural communities, throughout the United States as well, that are really lacking access to what it is they need. They don't have enough, but yet we've got other places and other parts of the country that are flush, if you will, and you can see differences within major metropolitan areas. So it's not like you can just say and it would be wrong to say, oh well, if you're in the Bay Area or the New York City or in that area, you know everybody's flush. It's just not the case Because you have to remember when people access services, it has to be accessible, based on kind of the way they travel, commute and the socioeconomics that are within their respective communities.
Speaker 1:So I wanna dig a little deeper with you on this, but one off the tough sort of policy solution. Typically, when there are these kind of challenges, one of the things, one of the purposes typically of foundations, is to, you know, sort of be the first responders and taking the lead in trying to make policy change and resource distribution in a more fair and equitable manner. So this is an opportunity for foundations to take a look at this data on where the resources are and where the needs are and perhaps take the lead in making sure that those underserved communities are better served and in places where we're over-resourced, it may be time to do a little bit of an allocation change. And if those efforts you know, if they role model, those sorts of efforts, that's the kind of thing that ultimately could lead to policy changes at the government level, which could then in turn, really cause significant positive change. And that's what we here at, for Goodness' Sake, are trying to get to is solving some of these problems that are very, very serious. But so maybe I'll pivot for a minute, if I could, peter, on this, because I want to.
Speaker 1:One of the things that I think you and I both agree on is that currently and this is a theme that's probably gonna be you all are listening to us. You're gonna probably hear this over and over again One of the biggest challenges that we think the nonprofit sector faces, individual organizations face, is that the vast majority of them whatever their size, for that matter cannot objectively provide evidence of their outcomes. It's, you know most of them, just they're not there. And so the thing that intrigued me when you had first shared this information with me was that it sounds like and maybe you can explain it to everybody it sounds like, even though we don't yet have organization by organization evidence of their individual impact, we do have the ability, through the kind of data that you're compiling, to roll up and see which communities have a positive impact. You know adequate amount of services.
Speaker 2:So maybe if you could just tease that out a little, how we can know one thing while we don't know the other thing, yeah, well, and I've been referencing some of the work that we're doing and, for a listener's sake and I'll plug the company I'm at, bct partners, that's where a lot of this is. So, the study that you're referencing, that is helping us to understand this and, again, I'm referencing the data that we just talked about. What you're talking about, ken, is that? So I'm gonna try to do my best to explain the study that we did and then, and by the way, this report is coming out very shortly, but can you do me a favor and anytime I get too geeky, or whatever just let me know because we wanna make sure everybody understands.
Speaker 2:But here's so imagine this is what the study really has helped us to do. So we wanted to do a longitudinal study, looking over a four year period, just thinking that you know, and ask and answer the question does do nonprofit services contribute to community well-being? Not one organization at a time. But if the unit of analysis was the census tract, which is the US Census Bureau's definition of a community, by the way, it's important to note that it's a better measure of community than zip code, because it doesn't cross over rivers or other places where people don't tend to define their own quote communities by. So census tract is our unit of analysis and I told you that there's 70 to 80,000, the current census. There's over 80,000 census tracts of communities in the United States were studying.
Speaker 2:Imagine the question is could we figure out and use the data from the IRS as to program output by category of service? So think human services, think mental health. You know there's 18 different categories. Could we examine is there an association between the amount of accessible services and, over a four-year period, how much of that amount is needed to improve or contribute to community well-being? And we use a score called it's a social determinant of health, called the Area Deprivation Index. So it's a standardized, psychometrically developed measure using the Census Bureau's data. So we were following what researchers had already developed for a measure. So that's how we measure community well-being.
Speaker 2:So again the question is do we know what the right, you know, is that does? Do youth development, access to enough youth development programming, actually help communities improve some of their points of well-being? And the scores from one to 100? And imagine, well-being is 100 and seriously deprived is a one. So here's the thing. So what we found was this that the nonprofit sector in the way of programmatic output, so we know how much programmatic output every community in the United States has. Through geospatial algorithms and big data, we know how much everyone is getting of accessible output, programmatic output, dollars, of youth development, of healthcare, of education. So once we can figure that out, which was the hard part of building the database now we can ask the question okay, if we know that, do nonprofits, does access to services, really move the needle? And then, if so, and can we control for things that we know we want to control for? So we can kind of understand is it causal or not? Okay, so that's where we were investigating. So let's take an example.
Speaker 1:Wait a minute, wait a minute, wait a minute. Yeah, yeah, yeah. So it sounds like there is some good news here, which is that, although we have on an individual level, we still have most organizations not knowing exactly what their impact is. There's some good news here. That evidence is, whatever the heck that magic sauce is that they're doing, overall it's having a positive effect, and so the pitch that I just want to make, before you go a little deeper into this, is that we could. Part of what I said earlier was there could be a policy made here for foundations and then government to make sure that there's more of an equitable distribution of the resources to serve the communities. But the other thing that would really put this into the stratosphere is if the individual effects of each organization were known and could be they could be learning organizations that improve then we could dramatically move the needle even more than this kind of macro stuff we're talking about Exactly exactly we're looking at a macro level.
Speaker 2:I'm rolling up, like any census tract. It's a roll up of all accessible youth development programming across multiple organizations, but if we can at least go there and then go micro to your point, which is much more specifically about each individual organization's contribution to it. So the cool thing is, at any census tract, let's say, there's seven youth development organizations contributing $5 million worth of programmatic output and they're doing that on an annual basis to a particular local community. One of those might be providing 50% of that. It would be good to know that. It'd be good to know how they're doing.
Speaker 2:And then, obviously, if we can get more specific, granular information and we'll talk about this as well. Ken, you know we're doing a lot of work here with respect to actually being able to leverage program administrative data to even more better understand outcomes and what works for whom, and imagine that data were also available. We now get to a whole other place where we are in a place technologically, analytically and from the data standpoint that we can actually do a whole lot more than we ever could before. And yes, we can get to the answer to the question what can an individual programmer organization do and how does that contribute at a macro level to the larger piece?
Speaker 1:You just said something very profound. That's like a very, very, very big deal that we're able to do that, and this is relatively new ability in terms of getting.
Speaker 2:Yeah, it's been. For us we've been. You know the work that you'll probably hear on this that, ken, you and I have been talking about for a long time. We go back I mean, it's been 10 years that we've been working on some of this work. It's been the last five years. I think we've really gotten to a place where we begin really testing this across organizations, as well as this big data platform I'm describing which we call the equitable impact platform, all of this data and the potential we use machine learning, ai.
Speaker 2:There's a whole lot of discussion for other episodes, but, at the end of the day, we're getting to a place where we can no longer just continue to throw up our hands and go. We surrender outputs is the only way we can do this, or a rigorous randomized control trial is the only way we can kind of do this. I'm oversimplifying, but, at the end of the day, there's a lot more places, and let me just get to the conclusion, though, of the big data study. What we did see so back to that kind of thread of our conversation is that we did see that when you compare communities and you match them, so one of the things everybody wants to do is say well, if you're going to study this, it would just be correlational, it's not causal. So a lot of times there may be an association between two variables that seem like. As humans, we have this bias when we hear correlation, we think causation. So if somebody reads a data point, and it's true that the more ice cream people eat, the more murderers occur, and so if you draw, that's a, if you get in the way of my ice cream, that's a. So this is exactly right, so this is a. This is the classic case of a. Correlation is not causation, meaning it's just coincidental that that it's the ice cream. It's actually not the ice cream, that's the factor. So if we know that we have to control for other factors, right, the heat does you know? The heat is a factor we should have controlled for, because the heat would have been a factor that gets people out and maybe they're more irritable, and there's a whole lot of other factors. It's not the ice cream. And if you control, you have to control for those other things.
Speaker 2:So now take that example in order to get to causation, you have to, you have to, you have to do the kinds of experiments or study, use data in a way that controls for certain variables that we all know. Everybody would know. It's like, yeah, right, if it's not the ice cream, the general public. If we just had a conversation and said, do we really believe that ice cream causes murder, they'd all be like no, no, no, it's probably because and then they have these hypotheses it's probably because it's hot, it's probably because that's when everybody eats ice cream, or maybe somehow ice cream is when, you know, happens in certain places where there's certain conditions that that that make people more vulnerable to anger and angering and getting to a place of murder. Whatever the case may be, the point is we're going to raise those questions.
Speaker 2:So now get back to the example of the, of the, the big data study. If we just looked at the correlation between programmatic output, like how much, some communities have zero of youth development. Some communities have $100,000 access, some communities have $5 million access and some communities might have $100 million in access to youth development programming. Through all of that, they have Some city, some big metro areas or whatever. So because we have all that variance, most communities don't have any and there are plenty that do. Imagine matching all those communities again census tract on the variables. We know that we would be like, oh, but it could, because of this or that. Well, if we match them on their socioeconomics, we match them on their baseline community well-being. We match them on how much access they have to philanthropy, how much access they have philanthropic funding, government funding, individual contributions, how many volunteers are in their communities. We have all that data so we could control for that. So when I share with you that in fact, these, all these 18 different types of service providers youth development is one example when organizations have access to it, they actually have a statistically significantly higher over four years increase or change in their community well-being. So if they were 50 before and they're 60 and four years from now, some portion of those points, those 10-point jump that they took, could be attributed, can be attributed, to a particular type of service that is contributing a point, two points, three points to that community score. And we know it's statistically significant because we're comparing it counterfactually to the same matched communities. So in other words, apples to apples communities. We're not going to compare you, we're not going to compare a rural community with no access to philanthropic resources and government funding to a metropolitan with tons of it. We're not going to compare those.
Speaker 2:What is what? What is what is counterfactual? Counterfactual means basically that you have, like, an example of the same type of person that got something and somebody didn't, or the same community, the same type of community got something or didn't. Right, so it's, and that's what's the causal part of it, it's all. You can't really determine causality without having counterfactuals. Well, the cool thing is we have all these natural experiments that have happened across the United States, census tracks that are the same type of communities, same population density, same socioeconomic status, are very similar. We match them and then we go okay, there's 250 of these communities that all match. Guess what? A hundred of them had access to $10 million in youth development. A hundred of them had access to a million and 50 had access to none. I'm oversimplifying, I wouldn't say that.
Speaker 1:I wouldn't say that's cool, but it's helpful for the first time. Well, the reason that's important for all those that are the more.
Speaker 2:Correlation is not causation, and people like me, who like, really want to pay attention to this it's cool for data, but the bottom line the bottom line is that when we studied all 18 and allowed them to interact with each other and controlled for all these community factors, we know that there's a statistically significant difference when you have access to those, when communities have the right amount of access or not, and the key there is the total macro level of access to output. Programmatic output contributes to moving the needle. Now, that doesn't tell us about the individual programs and it doesn't tell us about anything more than output. So it's not a quote outcome. It's an output that is at least attributable to the contribution of change to well-being over four years.
Speaker 1:So let me just take this concept.
Speaker 2:You go ahead and finish that, but I want to get back to drawing the final conclusion about it, which is to say this that once we found out that things do make a difference, we then evaluated, because we never match communities based on factors that shouldn't be selection criteria, like the racial breakdown, the ethnic breakdown of the communities in terms of their population proportions, so we didn't match on that. Instead, we evaluated afterwards and what we found was that communities of color, in particular, were likely to have 50% less access to most of these services, regardless of being in the same types of communities, and so there's a real inequity with respect to this, and it comes back to some of the stuff we were talking about earlier.
Speaker 1:Yeah, and the big organizations go where the money is. The big organizations go where the affluent donors are. The big organizations tell the best stories. The little organizations are not as able to do so. They don't have the megaphone to be heard. All kinds of things like that are factors. But so let me just get back to Goldilocks for a moment, because you know we want to make sure she gets full and rest.
Speaker 1:full and rest, that's right, yeah, well, yeah, make sure it's just right. So you know, one of the things that I guess from that that we had talked about early on in terms of one of the visions that we kicked around, was this notion of having a larger nonprofit sector that has wider, potentially theoretically more positive impact if it's a larger part of the economy and whatnot. That's a for me that's a theoretical concept at this point. But but you know, it's almost like when I think about the percentages that we had kicked around informally before. It sounded like, you know, let's say, 20, some odd percent of the organizations are in communities that have more than enough and that if we could move some of those to the 25 to 35 percent that have less than enough, that in and of itself could be a game changer.
Speaker 1:And then part B that I said, where if all of these organizations, or a substantial number of these organizations, became more efficient and effective because they have metrics now to work with, to work toward and learn from their data to get better and better at serving people and communities, that those two things combined could be such a game changer that you could then conceivably get to a place in in, hopefully in the not too distant future where there is more equitable distribution of the resources and the communities are all. You're seeing the improvements in the communities, proportionally across the board. And so where? But so I guess the question is, couldn't the couldn't one result or one outcome of all of that be that you could say, well, the nonprofit sector is big enough, it doesn't need to become a bigger portion of the American economy. It's now efficient and effective and the evidence is showing it's doing what it's supposed to and now all of the communities are served adequately. Or is there something else? There's something else that I had a feeling. You were going to say that so go ahead.
Speaker 2:Well, and this is just okay, I'm going to come at it from my perspective there's something else that I care about that I would say that gets introduced here. So yes, technically speaking, if we envision what you're talking about, which is a better redistribution of dollars and, by the way, we also are studying the value of volunteers in that model as well, but that's a little messier.
Speaker 2:But nonetheless, as we start to think beyond that, we could envision that redistribution would take whatever dollars are already flowing and just put them and better distribute them, in which case it could stay the exact same size and we're fine. However, if the potential and we see it in our models if the potential is that the right amount is, it wouldn't necessarily get everybody the right amount. At some point you're going to need an equilibrium that basically says okay, at some point we may find out and I hypothesize that first of all, a that once we get to that point, that threshold, where if we could imagine the day, the utopian day, where all the dollars are getting to the communities that need it most and we also had some equity building in there and trying to through the equitable lens and everything else and everything was fair and we really saw that we could start to create a change, I think we'd end up in the next place, which is to realize it's still not getting us where we want to. On some of the just generalized metrics of success. Now, that's my theory that the, that the nonprofit sector, even with its dollars, is not quite there, given that the reason I'm saying this is because even then it only makes up, depending on your numbers, whether it's 5% of GDP, 10% of the US workforce, whatever it is, it's still not. If it's really a social good sector, it comes with some benefits of the business model that warrant another question Once we achieve that, or even in parallel to achieving that. And that question is this I think it's an interesting question because so many businesses in the private sector are just businesses that are really not.
Speaker 2:Let me back up a second and say it this way the non is the nonprofit business model, a model for a lot of services that are in the for-profit sector, that have a social impact benefit. Think of all those companies, the private sector companies, that are also measuring their social impact because what they do has a social impact. My question is because I believe and now I'm getting into a domain that I'm less expert on, but I have an opinion, which is but I'm at least semi-read on it is they start to look at some of the issues that we have, bigger issues we're facing, things like, for example, the influence of social media on our policy, our governance and other types of stuff. If we looked at that and said, well, what would happen if we start to translate companies that could have a social impact benefit, a social impact metric of success, and instead of saying they should be for-profit, where profit, shareholder-ship and therefore ads and everything else are driving a lot of the objectives of all these algorithms and everything else? What if it shifted to?
Speaker 2:What if we didn't? Just always we default in the United States as this idea. The ideal is to create a for-profit business, but a non-profit business will pay people salaries and bills and everything else, but what it does is it takes the ownership of that business out of the hands of shareholders, which is a rare small out of whatever percent of the population, and it gives it to the community, but not in the same way that a government the government problems sometimes come along with, but in a unique way. And so my question is ultimately, I believe it warrants at least investigating the idea. What if we got out of this mindset that the non-profit sector is the charitable sector that's there for safety net, and instead we said what could happen if we changed all of our for-profit impact businesses, or a number of them, into non-profit business models?
Speaker 1:So just a couple of just back up, a couple things. One is that the traditional theory back in the day, back in school, the theory is well, the purpose of the non-profit sector is to go where there's market failure, where the profit motive can't be you can't make a profit on this and there's a need, and so that's where the non-profit sector sort of fills that gap, those sorts of things. And I think when you look at our non-profit sector in the United States it's all over the parking lot. There are insurance companies that for business, strategic business advantage, not having to pay the same taxes as a for-profit insurance company, for example, they'll become a non-profit. And in many other ways they may seem similar. They may not have shareholders but they have very high paid leadership and so on, board members that get paid and so on. So it gets blurry. But that was one of the original concepts which has become blurred over time. Another place which I think you've touched on that also gets blurry and has been talked about more and more in recent years is social impact business and that, oh well, we may run a profit but we are very concerned about our social impact and making a positive impact on our communities. You have B corporations that are very overtly and very clearly especially if they're certified only a certain percent on profits and so forth. So the line between non-profit and for-profit also has become increasingly blurry over time.
Speaker 1:That was just sort of a that's not directly to your point, but that was just sort of a it relates to your point, but so I think one of the things I guess for our audience, just for me to say, is that when I think of my conservative friends, when they hear things like redistribution, they think redistribution of wealth, and then, if we talk about shareholders and wanting to sort of have a greater stake and more potential efficacy of nonprofits and so forth, I guess where I come from with all of this stuff is.
Speaker 1:At the end of the day, I think there's. We have a long road ahead of us before we can come to any kind of clear picture as to what mix of for-profit, nonprofit, in-between-y stuff is the best, the most ideal way for us to move forward as a society, and I suspect, from my understanding of the history of this country, that is an ongoing debate. The thing that excites me, though, about the work that you're doing in all of this is I do feel like we're getting more objective. What I think is objective information about where there are needs that are not being met, ways that the nonprofit sector can more thoughtfully help in those communities, and the redistribution that we're talking about here is the allocation of resources of nonprofits to serve those communities.
Speaker 2:Charitable resources.
Speaker 1:Charitable resources, right, charitable, so part of the Quote-a-quote charitable resources. But at the end of the day, I guess for me it's more of a question. I don't have any. I would wanna it's like what the Beatles used to say we'd all love to see the plans. It's kind of like we've got a ways to go yet before. I would wanna put a stake in the ground and say, oh, let's have a bigger nonprofit.
Speaker 2:Well, so, and I don't jump right to the end immediately, but where I'm gonna go is this is that one of the? I believe that one of the pain points that we're struggling from just societally is I think that there's an element. Look, I'm pro-business, I consider myself a capitalist, I really do. I believe in some of the principles of all that, but there's been just a lot of stuff, just like you're a fan oftentimes of reminding us, and I agree that there's corruption in the nonprofit sector, but it's not like there's not in the for-profit sector, what? But here's the thing. Let me come back to the point. First of all, the redistribution point that you were just making. Just let me put a really important, fine point on that. Anybody that's going to, if the word sounds loaded, you're reading into it the incorrect meaning. So for me it's the redistribution of what is already the philanthropic and government funding and individual donors. So if you're talking about, if you take an issue with my word, redistribution in that, context no, no, no, no, no, no, no, no, no, no, I know.
Speaker 2:I'm actually thinking of the audiences. I wanna clarify that my meaning is literally around charitable giving, sure, but also let me come back to the point about the for-profit and nonprofit and should the non. You're still asking a question and what I would say is this I still believe that one of the root causes of a lot of the pain that we're struggling from right now, economically and I don't mean economically, we're struggling people can you know, gonna throw different numbers out about what the economy looks like now, but I'm just talking about some of the inequities, some of the injustices and all that kind of stuff and how resources are really and where they are and who's got the assets and who doesn't. I believe that it's that our shareholder space, that the people that I always call have the passive income, the one or 5% or at the top, who don't need to work. Technically, they might work very hard, I get it, but they don't need to because they've got bank, so to speak. They're pulling on all of their shareholder value.
Speaker 2:My point is that, also, when it comes to shareholders, what they care about is profit, if you're a and so, and that's their motivation, it's really around profit which changes the dynamic with respect to one of the biggest costs in the world, which is human resources and human labor.
Speaker 2:Everybody wants to cut that.
Speaker 2:Automation comes in, ai comes in, there's all kinds of incentives when you're in a shareholder sector where, if you take the same service which rightfully so in the for-profit world you could say that a social media company that connects people to each other and allows them to give voice something like the Facebook analogy is easily identifiably could have a social impact metric of success.
Speaker 2:My point is what would it change, just in terms of the pain we're suffering, I think, where the shareholder kind of economy and model of the for-profit sector, if all you're doing is saying and this is one fundamental point, ken that really does make the nonprofit sector and please know, I know that we'd have to there's got to be regulations and there's corruption, I get it. But if you were just but just at a very simple level, the incentive structure of a nonprofit, not being about the shareholders and profit, is a very different for the same business model structure and of course, we'd have to go in and figure out what to do with it Grew to that size. But guess what and this is a very important point If we grew to that size because the value of the nonprofit sector and the nonprofit model of business was more valuable than our current what I call charitable volunteer model, handouts and volunteerism. Then, all of a sudden, what would that do to have an entire other business sector that is not got a shareholder?
Speaker 1:model. Well, let me just say this I've told you this before. I might have even mentioned this in the first episode and this may be something else we tease out in a future episode. But my observation of 40 something years doing the work direct service work in the nonprofit sector, one of the things that I've seen over and over again is that the theory is and you've heard me say this before theory is the for-profit sector, their metric is the profit motive, and the theory is that in the nonprofit sector, their purpose is the mission motive and we want to get it to become the outcome motive even further than that.
Speaker 1:But what I have seen over and over again in the incentive structure of the nonprofit sector is that, instead of the mission motive, the thing that wins out is what I call the growth motive, that the incentive structure is not necessarily about outcomes, better outcomes, but bigness.
Speaker 1:Get bigger, because the bigger you get, the bigger your salary is, the more awards, the more accolades, the more attention you get, and so it doesn't necessarily translate to that individual organization doing more good. As it gets bigger, it's getting bigger to for these other incentives, and the two things are not always combined. And so what I'm trying to say my last word on this. That's why I'm saying my attitude to all you're describing here is a question mark, whereas where I'm saying until such time as I see a nonprofit sector that's really humming and doing good that we can provide evidence of on an individual organization level, not this sort of macro, although I do think we need to redistribute as you described in the meanwhile. But until I see more evidence that the outcome motive or the mission motive is more front and center, more evidence of that, I would not want to make any kind of societal changes in terms of the size and scope of that sector until it gets its act together.
Speaker 2:I got you. I mean, I'm gonna address this in two levels. One can. This is where you and I are different, while I agree with you that there are many but it's a small, small slice who are motivated by growth and motivated not by them.
Speaker 1:Well, that's where you and I disagree. No, no, no, you can't.
Speaker 2:I'll tell you why you can't disagree with me Because of the. You said very few. Well, the reason I say this can is because of exactly statistics you cited earlier, which is, if only 1% are in charge of 86%, then I'm going to tell you it's a very small number. And if, of that 1% unless you're accusing 100% of them as only being driven by growth first and foremost and not their mission, which I don't agree with, I know you're not. So, from that standpoint, my point being is please, that's one of the things we do in our sector, and we do a disrespect to our sector by not understanding there's a big, long tail that is not being described by what you want. And also the second thing, the second thing you also have to.
Speaker 2:To me, part of the challenge we've had that I definitely want to confront through our podcast here is the idea that we have been living in what I call a super human driven sector and a human driven.
Speaker 2:You've got a lot of people with a lot of power and authority who are making decisions, some based on research and evaluation, most based on just anecdotes and stories, but at the end of the day, it is a human driven decision making.
Speaker 2:And a lot of times. When it comes down to that, it's in part because of its roots in history that doing good shouldn't be quantified, it shouldn't be data-fied. And what I'm gonna say, okay, is that for me to get where we need to go, where you and I would probably agree, requires it to be data-driven. It requires it to be more rigorous in how it's doing it. So my proposition that the nonprofit sector all I'm saying is it has a business model that removes the problem of shareholder profit driven motives that I think have created the advertising hell that we're in for all of the for-profit social media platforms that cause so many problems. The point being is that, to your point, we still have to get to I agree with this principle. If we get to it being data-driven at the program level, organizational level and community level and we know offense to all the humans out there making decisions humans have data-driven or data-supported recommendations and decisions based on data we would be in a better place because, as we know the human biases are just crazy, we agree.
Speaker 1:So let me just respond to your quoting me, to me and the seemingly contradictory remarks I might have appeared to make by implying this long tail does not have the same problem. Here's what I know, peter, from my 40 years. I've worked in organizations that had $50,000 in the bank and were extremely small, and I've worked with organizations that were in the 100 million plus category. So guess this is what my experience has been. Yes, peter, the teeny ones too. I have seen the teeny ones also very much measuring their success, largely on growth, getting more dollars, getting bigger.
Speaker 2:It is not just the larger organizations, but it's not just to be fair, and so I'm going to pull a different card on you, which is so OK, keep that. My card is this is that I understand that you've lived it? Let it been a part of it? I've probably consulted and studied and evaluated just hundreds and actually thousands and thousands of organizations.
Speaker 1:Many more, many more.
Speaker 2:And it's just to give a different perspective. And what I would tell you is this is, of course, organizations are motivated. Many organizations, smaller ones, are motivated to grow and that's because the incentive structure is such that, if they want to be able to sustain beyond volunteers and for the record we still do, and I don't have a problem with the fact that the roots and the origins and the foundation of what we do is serving people. So most people are motivated for growth, so they can serve more people.
Speaker 1:Oh yeah, so wait, wait, wait.
Speaker 2:So it's about serving more people and so that? No, but there's also. I get so to me, even when you say growth can and you make it sound like a root cause of the problem. It can be, I agree, but I think it's risky and not comprehensive. We shouldn't make a generalized statement, because I don't think growth is a problem it depends on are you growing to serve more and, ultimately, achieve better outcomes?
Speaker 1:OK. So I mean there's no. Well, actually and it's funny because it reminds me of the disclaimer that we've talked about, which is I certainly am not saying that it dwarfs the mission motive and the desire to have a positive impact to the point where it's an all-consuming focus. That's not what I mean by that. It's much more to your point and I agree it's more nuanced and complicated than that. However, let's maybe close this out using Goldilocks again, one last time for Goldilocks, which is the amount of focus on growth.
Speaker 1:The emphasis on growth can, if it becomes too all-consuming and too primary, it can damage the ability of an organization to meet its mission. You'll have mission drift, you'll get into things you shouldn't, you'll get too big too fast. There's a variety of things that can happen where, if that becomes the biggest part of the part, the hottest part that you can get, then it can be a problem that way. But yes, there are very small organizations that still are very much mission-driven, and mid-size and large where they're getting bigger in a more planned, thoughtful way and they don't let it subsume the mission. However, my point is, if I had to think about my experiences over the years, there's a lot of times that I've seen that growth phenomena in the too hot Goldilocks category as an emphasis point, and so I wanted to close my remarks today because I'm mindful of the time here by saying disclaimer-wise, I'm not talking about any particular organization I've worked for, or, for that matter, my current organization.
Speaker 1:It's not that, and there are exceptions there's some great work out there. There are many, many people in the sector care very much about the mission, and that is their primary focus. But sometimes even those of us who are well-intentioned, the allure sometimes it's like what is that? The frog with the heat goes up in the pot and it boils. It may not even be intentional, but it can. And I think at the end of the day, that's why I'm so hopeful and such a believer in your work, peter, because the more that we have the ability to have measurable metrics, tailored use of data and data analytics, the more it can keep us on track and keep us away from these kind of problems. And boy oh boy, I had no idea we were going to go here when we started this. But Goldilocks remains. So I would argue this is the Goldilocks phenomena episode. Yes, I agree Well thank you.
Speaker 2:So, tim, I think we can close out on that, and I just I like to just hopefully everybody walks away with. This is a very provocative conversation, I think to me. The only closing point I'd make is this is that when we talk about growth and you're going to hear this all the time from me it depends, and the point is that I do believe also in what you just said, and part of what we both so strongly agree in is that if we're going to get to solve this and achieve what at least I want, which is like a little bit more of a sector that's not just where it is right now I think it's going to be through the use of data, being data driven, and we're going to continue to infuse that into these conversations.
Speaker 1:Amen, ronald, amen. So, ken, it was wonderful.
Speaker 2:That is another episode of For Goodness' Sake, exclamation point, exclamation mark, and we look forward to the next episode. All right, thank you, thank you, thank you, it was great talking to you today.