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Hello and welcome to tony martignetti non-profit radio big non-profit ideas for the other ninety five percent on your aptly named host. Oh, i’m glad you’re with me. I’d suffer the effects of depress opus. If you made me face the idea that you missed today’s show lean impact, your organization can adopt the lean innovation practices that helped fuel the rapid evolution of digital tech in silicon valley. And mae chang says you need to if you’re to do your best work in social change. She’s author of the new book lean impact on tony. Steak, too. Train. We’re sponsored by pursuant full service fund-raising data driven and technology enabled tony dahna slash pursuant bye weinger cps guiding you beyond the numbers. Wagner cps dot com bye. Tell us, tony. Credit card processing into your passive revenue stream. Tony dahna slash tony tello’s and by text to give mobile donations made easy text n pr to four four, four nine nine nine it’s a pleasure to welcome and may chang to the show. She’s the author of lean impact. How doe in innovate for radically greater social good. She’s worked as chief innovation officer at yusa idea and mercy corps and serve the u. S department of state as senior adviser for women and technology in the office of global women’s issues prior to her pivot to the public sector and may have more than twenty years experience as a technology executive at google apple and into it, as well as a range of startups. She’s at an mei and her book is at and made dot com. I’m very glad her book brings her to non-profit radio. Welcome to the show and may thank you so much for having me, tony. Real pleasure. Oh, you’re coming in loud and clear. Your your tech is you’re not surprising that your tech is awesome. Sound great. Thank you. Um, this lean impact process that you’ve evolved comes from the lean startup movement. Eric. I read his book, but i don’t know how to pronounce his last name. Is it? Reese? Isn’t eric reese? Yeah. Eric mary-jo k. Yeah. So within that, as a lean startup came from toyota manufacturing. Talk a little about just, you know, some little overview of lean startup and how you’ve morph this into the social change, social change, work and lean impact. Yeah, sure. So eric restore the book called lean startup about seven years ago now where he described a methodology for building products and services under conditions of extreme uncertainty. And this is certainly, you know, it’s it’s growing out of his work in silicon valley on dh, his own failures and what he learned from this failures about how we build products better on dh. You know, although it came out of silicon valley, it’s since then been highly papa popular and been adopted no, in business, both big and small and government and around the world. It’s been a new york times bestseller. It sold over a million copies and, you know, and this issue of extreme uncertainties really important. So if you’re building a product or service that is well understood and well defined, and you know exactly what you need to do, then what you care about is predictable execution. But if you’re trying to build something in a realm of high uncertainty, what you need is to figure out how to speed up your process of learning. And that is his court. Insight is that if we don’t know where we’re trying to get to what we need, to do is learn as quickly as possible to figure out the best way to get there. And why should i non-profits care about what came from lean startup, which now your book lean impact? Yeah, so, you know, if the lean startup was originally very focused on silicon valley, like i said in this branch out from there. But if you think about tech start ups, they work with high uncertain because they’re trying to build products and services no one has ever done before and not in the same way create new business models, new technologies and so forth in the nonprofit world. I would argue that we have at least a much if not more uncertainty, were generally working on challenges that are a big complex and entrench that have been around for ages and where the solutions we have are simply insufficient. Otherwise, we’d all be out of business. And so we give that we’re dealing with this incredible uncertainty both and not having interventions that are necessarily good enough. A cz well is not having one that can scale dramatically enough. That’s where techniques such a lean startup i become really appropriate. And yet you know the reality is that innovating and the social sector is much, much harder on. We can talk about all the reasons why, but, you know, from coming from silicon valley into the social sector. At first i thought i’d have it easier in some ways. But in fact it’s much, much harder because, you know, we have to deal with things like highly restrictive funding, you know, impact that can be difficult to measure. It may take years to realize that we worked with vulnerable populations for the whole notion of experimentation. Khun seem irresponsible you. In fact, you lay out some of this. I wantto i ripped out page sixty three from your book. I’m not gonna ask you to quote page sixty three. I doubt you haven’t memorized by page, but because i don’t bring, i’ll bring books to the into the studio, but i ripped out page sixty three and i wantto i’m going to read ah, paragraph. And i think this sets it up a cz just as well as you did. And and ask some very important questions that your book and this whole process set out to answer a grassroots community named lien impact sprang up several years ago as an offshoot of the lean startup movement, bringing together hundreds of practitioners. What has been missing is a framework that answers the common questions that arise when theory meets reality. How do i experiment when my funding is based on activities and deliver a bles that air predefined? How can i create a feedback loop? But it takes years for true impact to become evident. Is it responsible for us to experiment on people who are already vulnerable? Where do i find the resource is to test and iterated when i can barely make payroll? And i thought that was a really striking paragraph on dh. Set it up all very nicely on dh serves as some motivation for people in our non-profit community, too. Well, frankly, they’re gonna start with buying the book. I mean, that’s the first step you got. Tio got it by the book on then and then become acquainted with the practice of the impact. Yeah, and i think in that paragraph, really just try to call up some of the unique town does their face in the nonprofit sector who were trying to innovate. It’s not that we don’t want any of it. That’s not profit. Leaders very much care about these issues, care about their mission, want to figure out better solutions but worked within constraints that make it very hard to do so. I know many non-profit leaders that i’ve read the lean startup or similar types of books on the similar types of training and go back to the days you know their day job and just feel stuck because these these different impediments making much, much harder to innovate. And so, with the lean impact book, i’m not trying to come up with some new rocket science way of doing something. You know, most of the techniques i talked about are fairly common sense. But what i do try to do is look at how do we do this? Do these common sense things in the context of social good where we have to work within these kinds of strength, and i do so by bringing forward the stories of organizations that have been incredibly successful that has found ways to navigate these and other challenges. Ok, i agree. You did do that, and, uh, we’re gonna go out just, ah, moment early for our first break. And when we come back, you and i will talk about the way the book is organized around the three hypotheses. So first break pursuant they have to resource is to help you use data for improved fund-raising. The field guide for data driven fund-raising was riel world case studies of organizations using data to hit their fund-raising goals all data driven, just like pursuing typically is and the other is demystifying the donor experience revealing simple ways to develop relation a ll donordigital durney for your donors. You find them both at the listener landing page tony dot m a slash pursuing capital p for, please. And may you have these three hypotheses that the that the book is built around inspire, validate and transform. Can you? Ah, you sort of set these up for us and then we looked at, and then we’ll pedal through and we’ll touch down as much as we can. But, you know, we only have an hour. You just people got it by the book. I mean, that’s all there is to it. So go ahead, please. Yes, you’re i think you’re talking about the three parts of the book on the book is organized into three parts. The first part is inspire, and i think one of the biggest challenges in the social sector is that we tend to plan within constraints. We look at the amount of the money we have, amount of staff, we have the size and scope of grant and we think, what can we do with what’s in front of us with these? Resource is. And so i think the first line set shift is tio. Think big e also codify three principles really starts. A person would just think that that that we need to start thinking instead of what can we do with within the constraints we have, but what is needed in order to move the needle on the problems that we care about. And so the first part of the book is really looking at how do we expand our horizons? B’more ambitious about what we’re trying to do. Um, then the second part of the book, validate, is really the core of the book is what the lean startup is about is once, you know, have that you know, you’re thinking big, you have big aspirations. You have a potential solution that might work. How can you validate that solution to determine quickly, cheaply, a. Cz possible, whether it does deliver the things that you hope it will be. Too often we spend too much time heading down the wrong path on dh, wasting a lot of time and money before realizing some of the mistakes we’ve made. None of us a t least, not myself, can design something perfectly for such complex problems that we work on. And so figure out how we accelerate the pace of learning so that we can validate what you know. The risks that we are taking on by playing a new solution is essential to getting to a solution that works, and the third part of the book is called transform. And and that’s really looking at, you know, beyond sort of any individual organization and what they can do to both identify their problems. Think big, start small and experiment. How do we look at the broader system that we work in to transform the system to help us all be more effective? And that includes both with respect to solving problems the system change that is required. It also pertains to organizations. How do we change the culture of organizations? But it also applies to the sector at large. How do we change the dynamics of funding in the relationship between funders and non-profits so that we can all achieve more of what we’re looking for. Thanks. Excellent. Set up. And i see i understand my mistake. I called. I called these year your hypotheses, but you’re the hypotheses or value growth and impact, so thank you. Yeah, that’s well, we’ll get to those, but those are the three parts of the book. That was or not three hypotheses. I don’t want to confuse people who confuse our listeners. You you say that, you know, i i mean, i see i saw his like your objective, and this is the last last time i’m going to quote the book. Okay. I mean, i don’t i don’t read books backto authors who have written, but i just love this, too. If you want to find the most efficient path to deliver greatest social benefit at largest possible scale, that seems like, you know, that’s what you’re trying to help people do through lean impact. Most efficient, greatest social benefit at the largest possible scale. And my buy-in. Are you still there? You know, you cut out their part way through the quotes, so i didn’t quite hear the whole quote. Well, that’s a problem, okay? It’s if you want to find the most efficient path to deliver greatest social benefit at largest possible scale, that seems to me that’s what you’re trying to get get non-profits to to achieve. Yeah, exactly. I mean, i think that again because of a lot of systemic constraints we work in a lot of times what we’re doing is nibbling away at the edges. Were putting band aids on problems and doing some good on dh, making some difference, which is fantastic. But i think there’s a lot more we could do. And the reason that i wrote the book look at how can we bring some of these tools that have worked in other domains were squarely into the social sector so that we can deliver greater impacted skillsets. That’s ultimately what we’re all after. Andi. It’s just harder to do what one thing i would sort of add to that is, you know, in the business world, companies are expected to maximize shareholder value or maximize profits on dso everything, cos do you know all the decisions that they make day today? The metrics they collect, you know, sort of incentive they set up all around. How do we match my shareholder value? How do we maximize profits? And what i love to see is in the social sector. You know, whether you are a donor or whether you’re non-profit or whether your social enterprise that we hold ourselves that same standard to stay. We’re thinking impact. How do we maximize our impact? Not just how do we have some impact and sort of feel like we’ve done some good how we maximize that impact, and that’s really what the book is about is trying to put lord some tools that can help us magnify the impact that we’re having, because the things that we’re trying to solve are so grandiose, they’re so large, the problems with the problems that non-profit too devoted to our just so enormous. Yeah, absolutely. So starting with, you know, inspiration on dh listeners. I have heard many, many guests say the place to start is with your goals, you encourage you, you clamor for audacious goals. Yeah, absolutely. I think non-profits usually have audacious missions. The thing that i think is often missing, though, is that those missions are aspirational and their vague. There, you know, we’re going to end poverty, and instead what i want to encourage us to do is that much more concrete goals that are measurable, that our time down there geographically bound so that we know where we’re trying to get two more concretely and have those goals be goals that we don’t know how we’re going to get you yet. Because if you can achieve your goals with business as usual, there’s no reason to take risks or one potentially failing to innovate those cycles that really are a stretch but that are measurable so that we can tell whether we’re making enough progress towards wth um, um, and that sets the stage to orient everyone in the organization, as well as the other partners, to know exactly what we’re trying to get you. If you think of president kennedy’s call to send a man to the moon that galvanized the nation to try to figure out, how are we going to do this thing that we don’t yet know? How to do. And i think for non-profits, if we don’t set more concrete goals, it’s you know, if there’s a temple, it’s easy to fall into the trap of just moving in the right direction but not necessarily moving fast enough or deeply enough. Ah, part of what you point out is ah related to. This is a problem that we tend to fall in love with our solutions and you want us to fall in love with the problems. Yeah, i love the phrase fall in love with your problem, not your solution. I think this is a problem. Also in the business world that organizations can, companies can get very excited about their product or service. And and you get stuck to that and forget about what problem they’re trying to solve. I think it’s an even greater challenge in the social sector. I think that they’re there’s a tendency to fall in love. Are with our problems even more for a number of reasons. One is that whatever solution we have, we often it’s usually doing some good where that we don’t have a solution that’s doing some good. And so therefore we’ve seen it make a difference in real people’s lives on dso weaken become emotionally patch we wanted do whatever it is four more people even if it’s not the optimal thing to do even if there’s a potential to do something more it’s it’s easy to get stuck in that because we’ve seen it do some good and we don’t want to get it out because there’s a real need but there’s also i think because of the dynamics of social lt’s actor were constantly promoting our solutions. This is what you see on people’s websites. It’s what we’re pitching the thunder saying this is the best thing that you could possibly fund-raising dent if i with it becomes part of our organization als identity. And so it’s very hard to let go of any particular solution you have and what’s interesting to me. I talk to and work with a lot of different non-profits is that, you know, i can talk to ten different non-profits in the same sector, and they’ll all tell me that their solution is the best possible solution and out there, and i can’t imagine that that’s true. They can’t all possibly be right. Andi. Yet everyone has that we felt belief. So i think it’s important for us to have the data and look at the data, see what really is the best solution and of our solution isn’t the best recognised that and look at how we can improve it or look at how we can adopt. I’ve somebody else’s solution or elements of someone else’s solution or partner with someone else. And you know that kind of rigor behind delivering them. But most impact we ken will get us a lot further. You’re a computer scientist, you know. So you’re. Of course. That’s why you’re something stronger than encouraging your insisting that we be be data driven, your scientist. And so you’re bringing the rigor of the scientific method to this social change work. Um, we’ll get to, you know, it’s just that it’s tempting to talk about it now. You know, you thought of your book is how to make this change in your your in your organization that culturally. But i have to talk about it now, too, because we’re we’re talking about ego. This is this is difficult for people to abandon ego, put aside ego and recognize that their solution isn’t the best that there, that the work that they have been devoted to isn’t the best way the best way teo, to solve the problem that that that they’re attacking ego is because a tough thing to teo fiddle with toe get people to put aside yet. And organizations and an organization to put aside. Yeah, i mean, both individually and this organization’s again because we’re doingood. Our tendency is tio want encourage each other, pat each other on the back, you know, encourage each other. You’re doing good. Keep going. Keep doing this. You know you’re taking it a lower salary. You’re working long hours. Like who wants to discourage people who are doing that on dh. One of the things that i loved about coming into the social sector is, you know, just the culture. You know, people are so encouraging, so embracing, so supportive of each other. And yet i think something is also lost in that that we because we want to encourage each other. We often are reluctant to ask each other. The hard questions of, you know is working as well as it could. Could we do more, you know, kind of point out ways that maybe something is not quite meeting its full potential on when i said you’re a computer scientist, i didn’t mean to minimise the what? Two decades almost of work that you’ve been in non-profits as well. So i don’t know what the balances. But you’ve you’ve done quite a bit of work in the nonprofit community to i didn’t mean to say that. You’re you’re fresh to the non-profits. That’s not that’s not the case at all. All right. So you want us to think big with these audacious goals that are properly bounded? Think big, but start small. We’ll flush out. Out? Yes. So once you have that audacious goal, there’s a temptation to say i have a solution. That’s good enough. Let’s just execute and deliver as much of it as we can. But when we start small, it allows us to run experiments much more quickly and cheaply. If you’re working with five or ten or fifty people, you can be much more nimble. You can try things out. You, khun, learn much more quickly. You can adapt and change much more quickly than if you’re working with thousands of people. And so, by starting small allows us to accelerate that pace of learning again where we don’t have a solution that we know is good enough to fully solve the problems that we’re we’re trying to address. Okay, now this yeah. So this is ah, quite contrary to teo. What’s traditional and typical and quite a bit less efficient than than what you’re you’re promoting. What help people understand you mentioned these experiments. So what these experiments going to look like with ten people or fifty people instead of five thousand people. Yeah, sure. Let me give an example, maybe from from social enterprise in kenya. So there’s a a social enterprise called copia global in kenya that decided that that decided to focus on the issue, that people who are low income, the being in remote rural areas have a very limited choice of consumer goods. They can only really get this staples, and so they have a lot less choice of things that can enrich their lives. And so they set out this address this problem to give people much wider choice by, you know, sort of being the amazon, if you will, of rural kenya. And you know what some organizations might do is to go out, you know, build some warehouses, build transportation infrastructure, build some catalogue ordering system hyre a bunch of staff and so forth and roll out an offering. And i would take a lot of time and effort and money to do so. Instead, they decided to run an experiment minimum viable product, or m. V. P, which are these small experiments that eric talks about in the lead startup that allow us to validate our assumptions. First, until the case of copia global, their assumptions that they wanted to test were first would people order from a catalog was something people would find appealing. Second, what kinds of products would be most interested in? And third would agents cell from the catalogue could because they find agents that would help them sell in these different areas. And so what they did in their mvp was that the ceo at the time crispin went to the sort of walmart equivalent in the city and took photos of a bunch of different products, paste them into a handful of catalogs and gave them out to a potential agents and a few villages and step back to see what would happen. And now, when somebody came in and they want to place an order, the agent, we give him a call he would literally himself go run to the store, pick up that product just at the retail store by it, carry it to the village and deliver it. And certainly this is not something that was scalable at all, but it’s something that they could get up and running in the course of a few days, or a week and start to learn. And what did they learn? One. They learned that people were ordering from the catalog. It was appealing. People did have a demand for these products that were too hard for them to get, and so they validated demand. Second, they learned what products people were most interested in that help them figure out what things to put in their catalog when they actually wrapped up the business, what things to stock in the warehouse and so forth. And third, they had a surprise that people they thought would be the best agents who were the kiosk owners or the people who had these kind of corner stocked store equivalent that sold consumer staples. They thought that those would make the best agents, but they turned out to be terrible agents because there are far more interested in moving their own inventory in the store. But what they found out was that what made better agents were the people who ran complementary businesses, like a hair salon, where their customers were sitting around waiting to get their hair cut. They could flip through the catalogue order, things that they were looking for and it became a additional revenue stream for the business, and so do the m v. P. They were able to answer all sorts of questions very quickly, very cheaply. That helped them steer the next stage of their business in the far more effective erection. And so it’s it’s, you know, it’s experiments like these that that help us learn more quickly rather than focusing just on how do we roll out our program or our solution and the the the m v p. The minimum viable product? That’s that, that that’s at the at the root of all this. It’s it’s it’s smart because it’s you will avoid risk. You’re avoiding spending a lot of money and a lot of time on a solution that isn’t the best. Maybe based on assumptions that are invalid on dh, then is going is going to end up doing a disservice to the people you’re trying to serve to your employees, to your funders that flesh out more this and how non-profits could you apply the the minimum viable product to their work? Think, think through how to do that? Yeah, so that the way that you so the minimum viable product is really an experiment that test my hypothesis. So just step back a little bit when we think small. So when we have a solution and we know there’s some risks behind whether it will work or not, there’s some unknown. The first step is to identify that is unknown, so we contest that, and in the realm of social innovation, i think there’s three pillars of what makes a successful social innovation. And that is that it has to deliver value impacting growth. So value is something people want not only want, but we’ll demand will come back for will tell their friends about it. Fill a deeply felt need both by your beneficiary as well as by other stakeholders who need to buy-in is that people don’t want what you have. The offer. You’re going to be swimming upstream the whole time, the second once you have, you know, ascertain something people want. You have to ask, doesn’t have impact. Does this make a difference? Does it deliver the social benefit you’re looking for? In other words, does it work on guys? Too often we get far along and delivering something that people want, and that sounds good. To us but doesn’t necessarily deliver the social impact. And then the third pillar is growth, even if we’re delivery social impact from a few people, usually a scope of a problem, this huge there, maybe millions or hundreds of millions of people who have a particular need. And so how do we create an engine that will accelerate growth over time so that we can reach people enough people to really move the needle and sew? The m. V p is really the first step in what eric calls the build, measure learned feedback loop, which is essentially applying the scientific method to the risks that we identify. And each of these three categories that you identify a potential risk, for example, that people may not want to order from the catalog. You build an m p p, like copia did to test that assumption. Then you measure the results. You gathered data to see how many people ordered people engage, and then finally you learn. If you’re successful, then maybe it safe to double down. If you’re not successful like, for example, with copia, they’re there. They found out that the agents in the in these corner stores were not selling from the catalogue that they had to tweak their solution to to to look for other agents that might be more effective. And sometimes you find that, you know, you’re completely off base and you need to pivot and take a different direction altogether. And so it’s driving that bill measure learned feedback loop quickly as possible. That dr social innovation and, you know, we all do this in the bull court, of course, of time. Except that often the bill measure learned feedback loop. It can take years. By the time we deploy a program, you know, measure it, evaluate and learn from it. It can take years. And so what lean impact does is really asked. How do we move that learning cycle from an order of years to an order of days or weeks? All right, we gotta take another break when we come back and may and i, uh but also more stories about ah ah. Public school system, for instance, a cz. Great examples of this. This constant testing and learning iterating. And we’re talking about wagner sita is if you need help with your nine ninety, do you? I hope you hope you’re getting it out very soon. Are your books properly managed? Have you got the books? I do. Do you know how you’re doing financially? If you’ve got to see piela, maybe you’re thinking about a change in twenty nineteen. Talk to the wagner, the partner there. Eat huge tomb. You know him? He’s been a guest. You know him. Start out at wagner cps dot com and then pick up the phone. Talk to you. Check out regular cps dot com. Now time for tony’s take two training trains. I encourage you to invest in basic planned giving training for your fund-raising team, and i recognise your fund-raising team might be just you or you and the ceo that but get the basics of plan giving down. You want them to be you and your and your team. You want to be comfortable opening the door to conversations about a state plan. Gifts. That’s all that’s this’s not expertise. This is opening doors to conversations. You’re not talking about death like a lot of fundraisers. Think that complete misconception you’re talking about the long term value of your work and what what a long term gift is going to mean to keeping that work going beyond all of us. So that’s the that’s the essence of basic plan giving training. And in my video, i put a little holiday spin on training. So you check that out at tony martignetti dot com. Let’s go back to and mae chang and lean impact. Oh, and may you have this example of summat public schools. I felt like they were a good example of this iterating and was testing, learning and iterating. Yeah, one of the reasons that i think people struggled to look at how you can apply these tools in the social sector is that impact can take a long time to measure on dh, take a long time to fully realize and so you know. Example. Some of public schools is a great one because they work in education, where educational attainment is one of those things. Take a long time to fully realize that the founder of summat public schools, a woman named diane tavener, started out with this audacious goal that she wanted to start some schools that would serve a diverse student population, where one hundred percent of them would graduate from college. Now they brought in the best practices that they could find in education. Started up a couple charter schools, and eight years later, when they’re first cohort graduated from college, they they were highly successful. They beat out most of their peers and, you know, people were recognizing from this and encouraging her to just gail her solution. But but what diane recognised was that even though that they were doing well, they were doing better than any others. She believed they could do better, and she won’t had wanted to, you know, say she had set out with this goal of getting one hundred percent of students to graduate and they weren’t there yet. And so she she decided to invest instead and trying to figure out how to improve on the model. But she realized she didn’t want to wait another eight years for the next cohort to graduate. You know that that would be way too long in orderto see whether she was improving the models. Enough. So instead she decided to focus on building in a culture of of learning of it, aeration of innovation into their organization. And so what this looks like was they started out by running weeklong experiments for and did so over the course of fifty seven weeks, and each week they would bury the the structure of their classroom, the content of the classroom, the types of activities, whether it be, you know, kind of traditional lectures by teachers or south paste elearning on computers or small group project, or one on one tutoring. And they would look at all these different ways tools that they had and measure it each week by running student assessments, doing focus groups to see what the students are most engaged with interviewing teachers. And so each week they would gather this data marin what worked and didn’t work about what they had tried that week and that that’s what they’re doing and then try something slightly different the next. And so over the course of these this year, they essentially refined their model, a very transformative model for personalized learning and and, you know, have been highly successful. Their most recent cohort, ninety nine percent, got admitted to college. You know, they haven’t yet graduated from college. But now this model that they’ve developed has been adopted by over three hundred public schools around the country. So it shows that when you take a little bit more time up front to invest in improving what you’re doing to really maximizing the quality of what you’re able to deliver, then it’ll pay dividends over time. And and even in the case of education where you know, fully measuring educational attainment may take years and eventually get, they’ll get to looking at their graduation rates from college. There are often earlier indicators that can help you determine whether you’re on track or not and help you improve your solution along the way. And as you’re improving, you’re there’s a very good chance you’ll be. You may need to pivot at based on what you’re learning. I thought the the vision spring case in the book is a is a good example of multiple pivots. Can you talk about that one? Geever. Yeah. So a lot of times when we think about innovation, we think about the big, flashy new ideas and visions. Spring decided to focus on a seven hundred year old invention that has been proven teo. Increase productivity and improve learning potential and that i’d lost. And so, despite being seven hundred years old there’s an estimated two and a half billion people who need eyeglasses and don’t have them. Mental vision spring thought to bridge the gap you know we talked about earlier. They set out with an audacious goal that there’s two one a half billion people in need, and they started out of most non-profits would by looking, piloting in two locations in their case, elsalvador. In india, they recruited people they called vision entrepreneurs to go out to rule areas, division exams and provide eyeglasses and came back with really moving stories of people who weren’t able to work in a work again. Kids who weren’t able tto learn being latto learn more effectively, and many non-profits would be thrilled by that. You know, we’re making a big difference, but it wasn’t enough for vision spring. They recognized they were losing money with each person they reached, and they would never be able to scale to the degree that they needed teo achieve their goal. So they pivoted. Their second incarnation is that they set a vision centres in more urban areas that was serving more affluent population and took the profits from that too. Cross subsidize outreached into more rural areas. Through this mechanism, they were able to become financially self sustainable, also something that most non-profits would think. This is a huge success, not only doing good, we’re doing it in a financially self sustainable way. Prevision spring thought again it wasn’t enough because it would take them decades to be able to scale their infrastructure. To get to all the people around the world who could benefit, they pivoted again. They partnered with of organization in bangladesh called brac, who it which has community health care workers in every corner of the country and used their existing network to provide vision care. And through their partnership with brak, they’ve reached over a million people. Today on dh through other partnerships have not reached over four and a half million people. Well, that’s a pretty impressive number for a non-profits before and a half million people. But it still wasn’t enough provisions. Springbox kuze four and a half million is only a tiny fraction of two and a half billion, and they recognised that the problem here was really a systems problem that anyone organization could never reach. All of these people that we needed to figure out how to make marketsmart and how to make governments work better. And so they decided, instead of a public private partnership called the alliance that brought together eyeglass manufacturers, non-profits and local government to look at how they could work together to change the system. Tio encourage eyeglass manufacturers to manufacturer lower costs eyeglasses and distribute them to more remote areas, and to encourage governments to provide i care to their citizens. And one of their early successes was with the government of liberia. They find a mou where the government liberia agreed to work with, um, to provide vision care, do their national health care network as well as the public school system. Until you can imagine now, as they’re approaching this this problem from a more systems approach and working with making governments and businesses work for for people to provide vision, care to everyone that they can eventually get to this. This really audacious school they set out to, but it required them to be humble enough again, to your point, to put their ego aside to recognize when their solution wasn’t good enough and to be willing to pivot. Okay, i like that examples. Yeah. Thank you. Thank you. Alright, wait taking a break. Tell us. Start with the video at tony dot m a slash tony tello’s then think about this. What companies can you ask that would consider switching their credit card processing to tell us? Maybe it’s one owned by a boardmember. Maybe it’s one that’s already been supporting. You talk to them, have them watch the video. And if they switch, you get that long stream of passive revenue every single month. It’s it’s basically dahna unearned, but you’ve earned it. It’s that long stream, passive revenue that’s that’s the goal. And that’s what you can get through. Tello’s you’ll find this video and the intro at tony dot m a slash tony. Tell us now, back to and mae chang. Um and may the the tech industry has taken off well, not just recently, but has been able to grow so zoho so rapidly what you call the hockey stick growth growth curve. And a lot of that is explained by moore’s law. Ah, that dahna, eh? You know what? I think i know what it is, but you’re the computer scientists. You tell us just briefly what moore’s law is yes, the moore’s law was something that was defined by more. Who is that intel, i think almost fifty years ago now that said the number of transistors essentially, that the speed of computer chips would double every two years. I mean, tell true for almost fifty years now, and because of this, it’s driven this exponential growth in the computing industry, where computer that used to take up the whole building now fits in your pocket, and you can imagine all the things that that’s enabled us to do. And so, you know, it’s the underlying driver, a lot of the progress we see in the tech industry. So my question to you is, what is maize law going to be? There’s got to be. We have that. We need a maze law for the for the social change sector. Well, i think that, you know, moore’s law certainly has given the speed of computers, the advancement in the speed of computers. But what’s behind it in terms of like how how does that actually happen? You don’t just sit back and have more law takes place. Part of how that happened is because silicon valley is so competitive because there are are so many opportunities that people have really refined away to accelerate progress and accelerate innovation. And that’s what i think the lean startup captured so well. And it really is about having those audacious goals. You know, like how do you know? Doubling every two years is is a really fast pace of progress, and that requires organisations to take risks, to try different techniques, to try different approaches and figure out howto learn as quickly as possible. And that’s you know, where some of these innovation techniques i’ve really been home. But i do think that these techniques are just as important and justice needed for the social sector because we’re talking about solving, you know, real challenges, that where people are suffering, where there’s real needs. And so we need it more than ever. And i truly believe that the same techniques are equally ethical in the social sector. I’ve seen organizations, the success, sloan applying them and be able to dramatically magnify their impact. Andi so you know, i think there is a real translation there, but again, it’s not easy. It’s much harder in the social sector, and so you know, the lean impact book is really my attempt at looking at how do we adapt these tools for the realities of social good? Okay, i hope you believe in all this because that’s what the book is about. So you say you said you believe these tools apply. I hope you do. All right, but i’m challenging you. I want to see a maze law and maze low if you want. But i like the, you know, like the liberation of going from morris to maze, so yeah, i mean, are you, um i’m concerned, are you? I’m concerned. I guess i’m not really asking. I’m telling you. What about my concern? I’m i’m concerned about what i call legacy non-profits. Maybe i don’t catch if you use that in the book, but you know, the ones that are so big and bureaucratic that taking on new thinking like this and vast culture change just doesn’t seem likely. I mean, they just seem like dinosaurs that don’t know what their future is. Don’t know how bleak their future is. I don’t know. Are you more optimistic? And i am about those those types of legacy institutions. I am. I mean, maybe it’s in part because in my last job at uc, i’d e i worked at one of those dinosaur institutions, you know, on the underside here. But we also worked with a lot of large established non-profits that have been around for ages. You know, the yusa ideas, the us government’s foreign aid agency were one of the largest donors in the world. And we’re government. So you know, we are, ah, large, entrenched bureaucratic organization, andi. Even that yusa idea, we know with the vision of russia whose administrator, when i joined you, say i’d haye set up something called the global development lab that was recognizing that, you know, the world is changing, and we need to change with it if we want to stay relevant. So the lab was set up with this duel part mission teo identify innovations that could dramatically move the needle on our aim to fight global poverty as well as to look at how we could transform the development, the tools in our approach to development self to accelerate both our own work and those of our partners. And so so i saw through that how we could in a large established bureaucratic organization start planting the seeds of a new culture. It’s not easy. In our case, it was a separate team that kind of started out that was protected by the leaders shippen. But that ultimately, overtime made inroads across the whole agency by finding other people who really know saw the need, you know, felt felt, felt compelled to find better tools on dh were interesting partnering with us. And i thought, i’ve seen this happen at lots of large non-profits as well, that they know that they recognize that, you know, people work at non-profits, who they care about the mission. And even though some parts of organizations maybe entrench, there’s always some people there who, you know are restless and want to find better solutions and are just looking for the tools and opportunity to use. Um, yeah. All right, well, that was exactly we capitalize on that restlessness because, you know, doing well isn’t as good, is doing the best. And that’s what you know that’s that’s your that’s your that’s running through the book. That’s your thesis. You know, we wantto do it. Maximum scale, you know, as you say, greatest social benefit. Largest possible scale. Um, i so let’s let’s move over, too. Making this thiss transformation. You know what you call ah ri? Architecture of organizations? Ah, you say that, you know, we’re relying on nineteenth century institutions using twentieth century tools to address twenty first century problems. And we need to. The third part of your book is about the re architecture of not only the institutions that are doing the work, but also the funding institutions on the funding and their funding models. What did you you lead us into this one, i would you like to start this conversation about making this transformation? Yeah. So one of the biggest challenges that i heared over and over again across the over two hundred organizations i interviewed was funding that funding becomes an incredible impediment on one. The biggest issues of funding is that funding tend to be highly if under most thunders, wants to see you deliver very concrete short term delivery bubbles, that’s and that’s what how they measure you by and in your proposal, they expect you to layout in excruciating detail exactly how you’re going to do that, how you’re going to spend every penny, every person you’re goingto hyre and, you know, put together essentially what i call a grand master plan and then execute on that planet, sometimes over as many as five years. And those plans are quite rigid, and it prevents us from experimenting. Prevents us from taking risks. Potential prevents us from pivoting and taking different paths. When the status types of stories i heard over and over again, we’re from organizations who would get a grant from a foundation, start executing on that grant. Realized that it wasn’t working, but then continue doing it anyway. And of course, no one wants to go on the record about this buy-in tell you there’s lots of organizations that do this, but it’s just too hard to go back to your funder and say, this isn’t working. You’re worried you’re gonna lose the grants all together, then andi. So finding a different way, thiss kind of the existing relationship is one that seems like micro management to me, and we all know that people don’t do their best work when they’re micromanaged. So i think the first thing we need to do is we architect, the relationship between funders and non-profits that we need to have a relationship that’s a little bit more based on trust that allows for more risk that allows for more agility. And there’s a number of tools that we’ve tried to do this. The global development labbate use a. I. D. One of those is to tear funding. We have a mechanism called development innovation ventures that was modeled after venture capital where, rather than giving out the big, monolithic grants that yusa typically does, we would give out much smaller grant that we could take much more risk with and allow people to experiment. If they could show us that they had an idea where they thought they could develop a far more cost effective solution. What was that? So we give out these grants that were, like, typically about one hundred thousand dollars for them to try these things out. And if they were successful, they were able to get data back that showed that this thing had traction than we give them a larger grant of million dollars and then five million dollars. And so, just like in the startup world, where venture capitalist come in and they give you small amounts of money to test out your ideas and more money as you get more traction by funding this way in the non-profit space, we can allow people to take a lot more risks. We can allow funders to try a lot more different potential solutions, but without putting too much at stake. You know, because you know what you want to do. If you’re going to innovate, you need to fail. But what you want to do is fail small, not fail. Yes. All right, well, we got to take a break. And when we come back and may and i were going toe, continue this about making the change and talk some about within your own organisation. Now incentivizing and and hiring text to give. They have a five part email, many course which is debunking five myths. Do you think that all text donations or small the captain like five or ten or fifteen dollars? Not true. Do you think there’s a monthly or annual minimum? No, there doesn’t need to be. There’s a good amount of misinformation around text e-giving, and you can break through that with this five party male. Many course end up raising more money. You get the email men? Of course. You text npr to four, four, four, nine, nine, nine. And now we’ve got several more minutes for lean impact. So in may, um, anything just is there one more thing you wantto share with with us about lessons that you say i d before we turn it to the non-profits doing the work and some of the incentivizing there one more thing. You can you want to share with us a ride? Um, you know, i think we were just talking about tiered funding and other mechanism that can be really effective is paying for outcomes. You know, looking at how do we incentivize outcomes rather than center vise activities? Because outcomes is ultimately what matters. You know, eric and his book talks about something called vanity medicines that are these absolute numbers that we all used to say we’ve reached or touched or helped, you know, a million people on dh, you know, this is plastered all over mt profit and foundation web sites in terms of trying to give people some sense of what they’ve done. But those numbers are meaningless because it just says, like, we’ve done stuff, we’re good at raising money. It doesn’t say whether we made a big difference in those people’s lives. And it doesn’t say whether another organization with the same resource is could have done even more on. So you know what eric encourages us to do. It would mean impact talks about is moving away from these vanity metrics to actionable or innovation metrics that are at the unit level that look at what is our conversion rate. Are unit costs our success rate because when we can optimize for those types of those unit level metric. Those are the things that are going to make a big difference over time. All right, and this. So this creates thoughts, foreign fodder for conversation with you’re funders, potential funders. And also, of course, for foundations themselves to, you know, to try to rethink. I mean, maybe, you know, experiment yourselves for our foundation listeners with with an organization or two in some of these, some of these very different with with some of these different funding methods obviously more detail in the book, you gotta get the book. Let’s turn to the to the five a onesie three’s themselves. You talk a good bit about incentivizing around this around lean impact and the adoration and the testing and learning talk some about incentivizing. Sure, what i see is because innovation is hard in the social factor. I do see a lot of non-profits these days talking about innovation and wanting to innovate. And usually what ends up happening is that innovation is something that gets bolted on rather than built in on by bolted on. I mean, you know, organizations tend to, you know, either run a contest or a hackathon or a pilot, or they could, you know, hyre like an innovation person or a small innovation team, and these things are usually off to the side. They’re not part of the core operations of a non-profit, but something that they can kind of highlight in issue. Nice press releases about, but go on business as usual with ninety nine percent of what they’re doing. And so if if you really want teo, so what? The result is that we see all these kind of pilots and all these contests and flashy ideas, but very few of them making an appreciable difference over tonic. So if what we care about is getting to impact and transforming the culture and building a culture of innovation, we need to do that from the ground up. And i think that starts by establishing, you know, those ungracious goal something, you know, that we is measurable, that we continue to reference back to that we, you know, kind of reinforce, that is that is the north star for everyone in the organization to measure their own work against, you know, like vision spring to be. It asks the question. Is this going to get us to two and a half billion people. And so you need to start out with that goal because again, if you have a goal that is achievable with business as usual, there’s no reason for anyone to do anything different on then. Secondly, way need to create incentives that reinforced kruckel. Both reinforce the importance of taking risks and celebrate failure as well as reinforce progress towards that call, you know, on those innovation metrics. So if you’re able to reduce your costs, increase your success rate and so forth those air the metrics that really matter and get it into the goal on dso. Finding mechanisms that incentivize and incentives could be, you know, financial incentive. So they don’t have to be. They could be just you know what this leadership highlight when you have you know organization, you know, all all hands meeting. What? What do you highlight in your press releases? What are the you know who gets recognized? What are the things that you talk about in your weekly updates? So those incentives are incredibly important because they are what culture forms around. And then finally, once you have those goals and those incentives and you can look at where do you need to fill the gaps? In terms of talent? Do you need to bring in some other people who bring in a different skill set than you make might have the need to train your existing staff? Two. In some of these innovation techniques, that’s that’s sort of the last step into often. People make that the first and only step and don’t get a lot attraction. We gotta leave it there. Another book, another book you need. There’s so much more there you can follow and may she’s at and may its n n m e. I m not talking about ellie may from the beverly hillbillies and may so it’s not a y. It’s m e i on you find her book at and may dot com and may thank you so much. Thank you so much for having me on your show. Pleasure next week. Consultant sarah olivieri with admonition, but also, of course, encouragement for small and midsize non-profits. If you missed any part of today’s show, i beseech you, find it on tony martignetti dot com. We’re sponsored by pursuant online tools for small and midsize non-profits data driven and technology enabled twenty dahna slash pursuant we’re by wagner. Cps guiding you beyond the numbers wagner cps dot com bye. Tell us credit card and payment processing your passive revenue stream. Tony dahna slash tony tell us and by text to give mobile donations made. Easy text. Npr to four four four nine nine nine right. Our creative producers. Claire meyerhoff sam liebowitz is the line producer, but today it’s by chris shows, social media is by susan chavez. Mark silverman is our web guy and this music is by scots diner, brooklyn, new york do with me next week for non-profit radio big non-profit ideas for the other ninety five percent go out and be great. Buy-in. 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