48. Gina Lucarelli: Grassroots Innovations: UNDP Accelerator Lab Network

Gina built the world’s largest network of social innovation labs at the United Nations and currently teaches at Harvard University Graduate School of Design. 

The innovation lab network that she built was the United Nation's largest investment in sustainability innovation (115 countries). Her work is taught as a Harvard Business School Case Study (Fall 2022), received the Fast Company World Changing Ideas Award, the 2023 SXSW Innovation Award, Apolitical's Public Service Team of the Year (evidence-based policy-making) in 2019, was covered in the MIT Sloan Review (Summer 2020) and depicted in For Tomorrow, an award-winning documentary on grassroots innovation available on Amazon Prime.

A ride or die optimist, she has 20+ years of experience in the global sustainable development sector working on civic participation, human rights, entrepreneurship, reducing inequalities, climate action, food systems, informal economies and sustainable development across the board.

She writes, speaks and represents the United Nations on sustainability innovations regularly, including through a new course she designed for the Masters in Design Engineering program at the Harvard John A. Paulson School of Engineering and Applied Sciences and the Graduate School of Design (Integrative Frameworks: Innovation in Global Problem Solving).

Transcript

Intro 0:00

What's it worth it? Uh-oh. Uh-oh. Uh-oh.

Simon Hill 0:05

What's it worth it?

Intro 0:07

Uh-oh.

Simon Hill 0:08

Uh-oh. Welcome once again to the Total Innovation Podcast. As always, I'm your host, Simon Hill. When we talk about innovation in business, we tend to mean the same things: better software, faster products, smarter processes, a new feature, a new market, new model. And these things matter. But today's episode is about something a bit different. It's about what innovation looks like when the stakes aren't a quarterly target or a product roadmap, when the stakes are potentially survival. There's a scholar at MIT called Eric von Hippel, one of the world's leading thinkers on how innovation actually occurs, actually happens, whose life's work rests on exactly the idea I've just spoken about, that the best solutions to hard problems come from people living with those problems, not the experts flown in to fix them. It's an idea that changed the way that I think about innovation. And it's an idea that today's guests took and built something extraordinary with a global hub of innovation labs embedded inside the UN, working across hundreds of different countries in some of the most difficult and dangerous places on planet Earth. It's also where we met, MIT that being. She's one of the most remarkable people I've encountered in many years of thinking about how organizations create new value. Her work I should have known more about, but I didn't. And so, in my time at MIT and my time around MIT, talking to and speaking with her has been eye-opening for me as well, across the various communities, the various complex thematics, and the various complex settings in which she has worked. She's been studied by Harvard Business School, written about in MIT Sloan Review, and is also the subject of an award-winning documentary, or at least the work that she did, is narrated by Daisy Ridley, the premiered at the Lincoln Center in New York, and is available for everyone to see online. And now, alongside all of that busy repertoire, is also a teacher at Harvard Business School as well. And luckily, she's agreed to spend some time with us today. So for that, I'm very grateful and welcome to the podcast, Gina Lucarelli. Gina, welcome.

Gina Lucarelli 2:19

Thank you so much, Simon. What an introduction.

Simon Hill 2:22

Hopefully, it was all accurate as well. I think it was.

Gina Lucarelli 2:24

No, the only uh thing I would I'm teaching at Harvard, um, the Paulson School of Applied Sciences and Engineering and the Graduate School of Design. Yeah.

Simon Hill 2:33

She's at Harvard. Let's go with that.

Gina Lucarelli 2:36

Outside Boston. You know.

Simon Hill 2:39

So in that in that long introduction, and I know it's always slightly awkward when someone's introducing you and describing you, you know, I I talked a little bit about the the work that you've done inside the UN. Can you just just talk a little bit, introduce yourself now to the to the to the listeners um and the incredible things that you've been building at the UN?

Gina Lucarelli 2:59

Sure. Yeah, I mean, so I've been at the United Nations kind of a long time. Um, but for the past, uh, let's see, over 20 years, actually. Um, and for the past six years, um, my focus has been building uh what we dubbed the world's largest and fastest learning network on sustainable development challenges. Um, so basically, where it was, just to like dial back um a bit. So in 2015, the governments of the world, and I remember the Pope and Shakira and other dignitaries, came to New York City and promised to create a better world in very specific ways, um, to eliminate extreme poverty, to make sure that girls go to primary school at the same rate as boys, you know, to preserve biodiversity, to end HIV AIDS and other diseases, et cetera. So they made these sort of like target-based promises in 2015 called the Sustainable Development Goals. Um, and the promise was to do this all by 2030. So clocks ticking. Um, and the organization that I worked for, the United Nations Development Program, um, you know, has about 20,000 employees, works in 1, I don't know, 30 odd countries, um, has about a $5 billion budget a year. And they started to kind of notice that, you know, something uh, you know, sort of like the Bob Dylan song, you know, something's happening here and I can't really describe it kind of thing, Mr. Jones. That on the one hand, obviously, like innovation was infiltrating the public sector space, right? And there were new methods and you know, design thinking. And, you know, back then it wasn't yet, you know, generative AI, but big data and AI felt like, you know, this is a hammer and it can hit some nail, but we don't know which one. Um, and then on so on the other hand, people, regular people, were solving problems in a way that we as a global organization were not listening to enough, right? We were getting so caught up in our own strategies and programs that we weren't seeing, you know, the Sierra Leonean 16-year-old inventor who invented a new form of wind farming, right? Um, and we were just so locked in on delivering, you know, stewarding public funds in an effective way and delivering value and good that we promised to deliver that we were not that we just weren't paying attention. Um, so that's why we built this global network of innovation labs inside the United Nations development program, um, was to catch up with the pace of change, which was as much um human as it was technological, to be honest.

Simon Hill 5:51

Yeah, and I think it is quite good to wind back to where this all originated and frame it around it. I think it's and we'll get to where we got to, right? Which is real scale and real real deployment. Um but also the ethos that sits behind this. And I mentioned um Eric von Hippel in in my introduction. Maybe you know, as as we met in his lab, maybe you can just frame in your language some of the sort of the, I guess the academic thinking, but also the really applied thinking that that sits behind some of that design work that went into what was ultimately created.

Gina Lucarelli 6:28

Yeah, I mean, so Eric's Eric is just a feat of nature, uh, and and he's he's extraordinary and brilliant and has been for many, many years, and so inspiring. I think for for us, what he did was his work kind of is devoted to this idea that um it's not just experts in labs or in research and development teams inside businesses that innovate, right? Um it's everyday people, right? And that this is he he did some early work um kind of quantifying how much that happens. Um, in terms of they looked, you know, there are studies in the UK, in the US, in Russia, in China, in South Korea, um, among other countries. And they were trying to figure out like what percentage of the population solve problems in a novel way, not for their job. Um, and what they come up with might actually be useful for somebody else, right? So they started to look at this, and then they find a range of like between two and you know, on the extreme side, um, eight percent of the population are just kind of hacking their way through life, you know, and this has happened, you know. Eric von Hippel's thinking is this has happened all the time. You know, Sam O'Neill, who invented the wetsuit, just wanted to surf more. And he had a friend in refrigeration. So he's like, well, why can't I just wear the thing? You know, Candido Jacuzzi had a kid with arthritis, and instead of taking him to the hospital three times a week, it was like, wait, I'm an engineer. Why don't I just build this thing at home? So there was this extraordinarily empowering idea that, you know, sometimes in the face of global problems, it can feel like daunting, like we can never make a dent. There are all these invisible innovators out there that we're just not even seeing. Um in the early days, um, a colleague of mine, uh Julio Kwagiotto, did some work uh with others looking at um farms in Indonesia, basically. And with satellite footage, they, you know, like irrigational flooding is a problem in Indonesia regularly. Um, so with satellite footage, they started to look at like, okay, wait, who's actually doing better? Which farms are doing better? So they use the footage to zoom in and um some ethnographic methods to find, you know, farmers who were like doing better than their peers under the same circumstances. Um, and you know, they found um this guy, uh Mozaki Rafani, who um who basically was taking care of the environment of the black soldier fly, right? He really loved black soldier flies. You know, the the folklore goes he even looked like a black soldier fly. Um and he was just like obsessed with these bugs, and he was just like making sure that they were okay and they could recreate and they could have their homes and all this kind of stuff. And it turns out that the black soldier fly eats the irrigational waste in the canals and prevents flooding, right, of crops. So it's a bit of a crazy idea because um if you put all the agricultural experts in a in a workshop and pump them with coffee for days, they would never, and it was like, how are we gonna help the farms of Indonesia? They would never come up with give love to the black soldier fly, right? So this was like kind of the origin story of like uh this weird idea, which was you know a miracle in its time, to actually in um 90 labs that covered 115 countries around the world, have at least we had three people, but one person's full-time job, we called them the head of solutions mapping, was to learn from people what they were doing to make uh you know, to create livelihoods, to protect the environment, to advance all the kinds of things that you know world leaders had been promising for years. Um, so in it's a real shift for us because our usual like way of working is seeing people as beneficiaries, right? How we help them, right? We make their lives better. We come in from the top down and make their lives better. So here, this was a shift of like, you know, thanks to the government of Germany and the government of Qatar that believed in us in the initial stages, and honestly, Akeem Steiner, the former um head of UNDP, um, who, you know, let us run with this idea to have people's full-time jobs be learned from people in their own solutions, like this, you know, black soldier fly thing.

Simon Hill 11:01

Which is um, I mean, there's so much to unpack in all of that, right? But I think it's worth re-emphasizing some of the numbers as well, right? Sort of 90 plus labs across 115 countries and and and not not so many people either, right? Like real scale run on a very lean basis. Um, it's more than more than anything, it feels like a movement that was that was created across across all of it. Maybe before we get into some of the the sort of what was what what was the outcomes and what was built then um it feels to me like just building something at entrepreneurial pace inside any large organization is quite complicated. Then you've got it inside a a public organization, then you've got it inside a public organization that's dealing in not just 90 plus labs, not just 115 countries. Lots of them are quite complex uh countries as well, right? That you're that you're working across in and for a variety of different reasons. So you just talk a little bit around how that even came to how did you succeed how did you have success in that? And and and I'm sure it wasn't a straight line, so there's probably lots we can dig into there, but let's just talk about the origin story a little bit more in terms of you know those early days to that initial scale.

Gina Lucarelli 12:16

Yeah, I think I mean, so the there are a couple of things we did that that made this thing unique. Um, first, we so we hired about 300 people, and it was in a short amount of time. But one of the things we kind of broke the mold on was normally if you look for United Nations jobs, they are like almost in illegible to the outside world, right? They will like have really weird titles and 8,000 acronyms, and like you don't know what you're doing and why you're doing it. So we had these kind of lofty titles like the head of exploration, right? So you would apply to be the head of exploration of the United Nations Development Program in Zambia, right? Um, you know, and and that attracted a different kind of uh person, right? So basically, I think it was about 75% of the people we recruited were new to the UN, and about a third of them had been living or working abroad before they came back to their home country. So the head of exploration for the United Nations Development Program, Zambia, is from Zambia, is a Zambian citizen, right? Um, so they might have been studying or working in China or the UK and they came back, right? So it was this reverse brain drain, and that was kind of that was a big deal. The other thing was like we really from the beginning started with this, it was a weird dance between um, you know, it was a centrally funded initiative. We wanted global scale. So we wanted to build all these labs at once, um, which we all thought was bonkers, but the head of UNDP thought it was a good idea. And he turned out he was right. Uh, we were like, can't we just build 10 and see how it goes and another 10? And he was like, no, you know, everywhere all at once kind of thing, um, which helped because then you created a network of people who would just talk to each other. Um so, for example, early in the boot camps, um, you know, we were under enormous pressures to move like crazy fast and get this thing running and get in the media and be like, you know, cited as a great thing. Um, so we started these boot camps in Rwanda. And the very first one, um, you know, we we did our best to orient people and and bring them on board and everything. But the team from Mexico, as they were leaving, they knew other cohorts were going to come in this same room the following weeks. So they left these like messages on the wall and they were like, listen, I'm ahead of exploration in Mexico. Uh, you know, Gina and her colleague boss are really nice, but they've never done this job before. So if you want to talk to us, join this WhatsApp group. And so this knowledge exchange mechanism organically grew completely outside the organizational's like official communication channels, but we let it grow uh through these WhatsApp groups of the people in their different positions. So heads of exploration, heads of experimentation, and heads of solution mapping were the three rules. And they would just fire each other tips and questions all the time. So no matter how much we directed them to the like the official channels, they was always on WhatsApp. Later, fast forward, we ended up building, you know, a bit of a data model on top of that. So, because it became where knowledge is. Um, so we could see who's talking to who and figure out what they're talking about and you know, pick up on leads from there. But the third thing we did, I think, which was important was there was very much, you know, the UN development program is a very decentralized organization. It determines with national governments what it works on and how and when and where, and all of those things. So we needed it, this needed to be a very decentralized operation. Um, that being said, we were uh a global knowledge learning network, right? So we needed common protocols and ways of interacting and all that kind of thing. So we took some inspiration from um um a woman, an academic Yun Yung-an, who wrote a book about how China escaped the poverty trap. And she has this concept called directed improvisation. And basically the idea is don't I mean, I'm really like, you know, uh summarizing uh horribly inaccurately her book, but basically the central government of China told like the sub-national governments, just hit this target. How you hit it doesn't matter. Do whatever you want to do, right? So there was like this zone of like, here's a red line, don't cross this red line, right? We told the labs, no fraud, don't hurt people with your experiments, don't steal anybody's intellectual property, you know, nothing like that. And then there was a broader range, it was literally a visual we like taped on the floor and would stand around and be like, don't cross this red line. Do something like, you know, learn from people, advance evidence on what works in sustainable development. Everything in between in this circle, between the red dot, the red line and the you know, and the wider target, figure it out. Good luck, figure it out. Um, and then eventually we look back and and wrote that wrote that up, what that figure it out looked like.

Simon Hill 17:22

Which is a very entrepreneurial way, but not necessarily how many would imagine it might have ordinarily played out and uh in in the in a broader setting of where it was existing, existing in. Um can you can you make it a bit tangible for people? So at the scale we're talking about, you know, the and people will be familiar with the concepts of labs and they'll obviously understand what 91 of those could be, but what what what what what was it really within this thing that finally felt found its shape? And um and then we'll get into a little bit more of you know, not only what was it, but what was it capturing and what was the the knowledge network that was being developed as well.

Gina Lucarelli 18:03

Right. I mean, so basically, okay, let's zoom in on, you know, it was these are all uh global majority countries, quite a bit in Africa, some over over 40 on the continent of Africa. So, okay, if you zoom into like, I don't know, the team in Eswatini, right? Uh basically we hired three people, uh the head of solutions mapping who had a background in either sociology or ethnography or journalism, somebody who could like follow the trail, somebody who could sense what's going on, what's emerging and what's disappearing, um, a little bit of an ethnographic um background. We so that's the head of solutions mapping. Then we had the head of exploration, who would be kind of a data scientist or someone product developer in that space, and then a head of experimentation who would be could be like a straight-up scientist or uh or like a human-centered design expert, user, user-centered design, that kind of thing. Somebody who could take the intelligence from the ethnographic work and the exploratory, like signal sensing work, and you know, land it in experiments and tests that we could actually do with government and partners to see what works and what doesn't. So take the team in Eswatini. Um they one of the things they did is they the government, so basically in Rwanda, plastic bags are banned. Um, they have a plastic bag ban. And Eswatini wanted to say, you know, can we do this? You know, what would happen if we do this? But they didn't want to lock in on just banning plastic bags because they didn't know how it would affect their economy. So the Eswatini lab designed kind of like an experimental space and a, you know, and a campaign with supermarkets where they could test out what this would look like, right? Um, if we if they banned plastic bags. And what they did is over that time they saw new um economic opportunities, new jobs emerging for women who would, you know, make canvas bags and sell them to the supermarkets. So basically, with that experiential evidence, right, um, then the Eswartini government did indeed ban plastic bags. Um so that kind of that's kind of how it worked in a million different ways and spaces, um co-experimenting, often with government, um to kind of we would set like a learning question, you know, and we'd be like, you know, what happens to the economy in Estuatini if we ban plastic bags, right? And then actually get the answer to that question and then hope that the government would take up the evidence and and build it out from there.

Simon Hill 20:47

What what sort of, and thank you for that. I think it it helps to bring it to life for people. What sort of scale of um, I guess, need to solution or problem to solution areas were you guys able to gather then across the the multiple years of that this year.

Gina Lucarelli 21:04

What do you mean exactly?

Simon Hill 21:06

I guess how many, how many sort of different needs or or solutions have have have you been able to find and at what level of of verification and and understanding, or maybe how do you assess impacts? It's maybe the simpler way of asking that question. Yeah.

Gina Lucarelli 21:21

Yeah, yeah. Um, so I mean, there's sort of two different frames. One is this innovation scouting or grassroots innovation mapping, right? Which is like this sensory network. Like what are people actually doing to solve their problems? In that scale, um, we in our database, but you know, when you're building the plane and flying it in something like this, you know, a central database doesn't always suit every need. So there was a lot of data that didn't get captured. But what we did get capture globally was 2,500 solutions. Sorry, I'm sorry, 6,500 solutions. I don't know. 6,500 solutions.

Simon Hill 21:58

This is people just out there. So your solutions mapping people are just out in communities and mixing with people and just sort of really on the really grassroots level sort of finding things, or how did it be?

Gina Lucarelli 22:11

Yeah, exactly. Well, we you know, again, they figured it out, but basically what we kind of orientated them on was um and a method inspired by Anil Gupta um from the Honeybee Network. And they've really, they're he and uh Anamika Day are really the inventors of grassroots innovation for sustainable development work. They've they've done enormous work in in India and institutionalizing this. And basically what they do is they um they go on one of these innovation walks, Shodyatras, which is really random. It's like a random walk in a what they do is they go to the poorest part of the country, you know, the hottest part of the country in the hottest time of the year, and then they just walk. And then uh you just kind of stick your nose in somebody's shed and say, What's that thing? What does that do? Um, you know, and you find out. So that's what we told the labs to do. Um, sometimes they would do different things and be more methodical methodical about it, you know, because it is the UN and they had to convince their manager that this was a good use of time. They weren't just allowed to like roam around the countryside, but sometimes they were able to do that. So, you know, uh, I'm I'm thinking about Africa. So near Aswatini is another small country surrounded by South Africa, Losutu. Uh, they won one on one of these walks, and um, they were asking, you know, people in the village who's, you know, who's an inventor, who's got some ideas. And, you know, people would be like, Well, there's this crazy guy over there with his farm. I don't know what he's doing in that shed. So they go talk to this guy. Turns out they find somebody who um basically invented a pesticide from uh the pulverized bodies of dead bugs. So it was a weird loop where the problem became the solution. Um, so basically, when an elegant grasshopper, when you kill it, it emits a uh yellow pungent liquid, which smells really bad. And he stepped on it, serendipity discovery, uh, realized that like the little plot of land around that dead bug that he stepped on was less eaten than his other crops. So he started mixing it with water and pulverizing it and just using it as a pesticide because it was cheaper. Um, so then the accelerator lab in Lesotho came in and connected them with the National University of Lesotho, validated the repellent and morbidity claims, um, and and and kind of took it from there. So, so that's often how that would work. So, 6,500 solutions like that, of varying degrees of formality. That would be a really informal one. There'd be others that maybe someone has started a business around or something. Um, that's what we ended up mapping. We would also they also would do experiments which wouldn't necessarily be derived from the grassroots innovations that they mapped, right? They might just be like tests like the Espatini um plastic bag ban, right? Some some hypothesis that you want to test and and you run an experiment under under controlled conditions to figure out what would happen.

Simon Hill 25:08

Yeah. Um, I love these stories, by the way, like this. Every day I know we we exist in very similar worlds, and the the beauty and the honor of them is that you get to wake up and hear these incredible stories. Yeah, totally totally random things from totally random people that have totally random outcomes, but just to just you know, they're just poetic and and brilliant in in equal measure. Um what I there's kind of three different ways I want to take this question. So I'm picking picking which one I want to want to which thread I want to pull on next. Um what did you learn, right? So like how much we're what six years, more years down the road of this now? Um what did you what are your biggest learnings? And I, you know, I I I'm astounded how much you went with they figured it out and everything else. And I think it's brilliant. It's not a criticism. I think it's absolutely the way to go um without being overly prescriptive, because who the hell knows in in so many different settings. But what are the what are some of the biggest learnings, I guess, on the on the positive and the negative side that you can share and for reflection?

Gina Lucarelli 26:13

Well, I think we learned a lot about scaling and innovation diffusion. Um and I'm not an academic, so I don't know if like everybody already knows this, but we definitely learned it and we definitely saw it again and again. So on the one hand, this was already taking the idea of innovation labs to scale because there were so many of them globally, right? On the other hand, our investors, as as does happen, uh kept asking, you know, they wanted that viral thing that would just run, you know, from a small story to a, you know, to national impact or international impact or, you know, something that looks like like in the public sector, when we try and do good in the world, we're thinking about scaling the way it occurs in the private sector, which is for better or for worse, we basically are right. Where um it doesn't what we found is it doesn't actually work like that, but even better, I think we figured out how it maybe it does work. Um and so it's a lot more like it takes an ecosystem, you know, for an innovation to scale. Um and you it's a little counterintuitive. I mean, I spent many years in innovation in the UN, um, you know, a little bit like the main character in your book, uh, kind of researching an idea, pitching it, getting enough of uh, you know, backing to run with it, uh, coming back with the results and like presenting in a killer PowerPoint, you know, to a room of decision makers, what I thought would just totally change their life and their budgets and where they put their teams and whatever. Um and it really, really doesn't work like that, basically. What have it's not so the the people who have the money and the power are not going to be the first ones you interact with, right? So innovation happens in ecosystems and it happens in waves, right? The first thing that kind of happens is you find somebody and you know them by the light in their eyes, right? Like you're finally talking to someone, you know, as they did in Uganda. They find the one GIS specialist in the Ministry of Forestry who's like, I think we can do these land cover maps better and faster if we would just use this stuff and everyone thinks he's crazy. So you start working with that person, right? This is the kind of intrinsic motivation. They're like the mover, right? They're they're ready to roll. Eventually, things expand out to maybe like middle management in the government or entrepreneurs are big because they're will, once they start to see proof of concept, they're ready to move faster. Those are kind of like, you know, uh the ones who bring in the proof of concept and kind of expand it. And then only when there's momentum and action and there's already success to be claimed, then you get, you know, the decision makers in the room who can say, yep, let's put a law on this, let's put a budget behind it, whatever. So that's one thing I think we learned was innovation scaling in the social impact sector occurs in in waves and through ecosystems. Um, and so this whole idea that you can just sit in a room and design for scale, sure, you should try. You know, you shouldn't be remiss about thinking through what you can possibly imagine, but you should just get out there and do it and you know, work out loud and build the partnerships and all those things. Interestingly, this is kind of forthcoming, but we're working with some uh academics at University Um USC Marshall, and um and they work on serendipity, that's kind of the science of serendipity. Um, they ran a test in our lab network uh trying to measure the serendipity index of the people in the labs. And we then correlated that with the like scaling results of the labs. And interestingly, um, it looks like a higher serendipity index of a team correlates with more likelihood that an innovation is gonna scale in our work. So, like, isn't that interesting? So the the the like what looks like haphazard and kind of like all over the shop and random, as the kids would say, um is actually your scaling strategy, right? And it might actually be the one that you know that makes something take off.

Simon Hill 30:39

When you talk about scaling, um, and you've spoken, you know, we've spoken about the network and the virality as well. It is it is a very big challenge, regardless of sector, regardless of space, regardless of geography for for people. Did you did you manage to get not just scale within the context of a specific you know, region, whatever that might be, that you know, that could be the local community or or beyond or the country to actually cross-pollinate into other areas successfully?

Gina Lucarelli 31:14

Yes, definitely. I mean, so I think the we have the most data on how things scaled within country, right? Um, so somewhere along the line, one of the labs started actually measuring what percentage of their uh experiments scale, and then we scaled that method to the whole global network. Um, so we started to kind of, you know, speaking of you know, what is value, uh, we started to kind of define what scaling looks like within a country. And that within that definition, we were, you know, we were good at selling ourselves, we got to a 68% scaling rate. And what we mean by that is 68% of experiments um, you know, were um expanded geographically or and or uh instigated new partnerships, or um maybe the exact finding wasn't implemented, you know, the evidence wasn't taken to scale, but uh, but the method was embedded in uh you know in government or in UNDP as a way of working. Um, so under those kinds of a definition of scale, 68% of our experiments scaled um in country. Cross-country, we were less uh methodical about documenting it, though there was, I mean, it was a I, you know, we've all been in networks and we know the networks that are real and the ones that are just kind of curated by some you know ambitious facilitator who's trying to, you know, make connections. This was a real network, for sure. Uh, we met every Tuesday, uh 7 a.m. New York time, because that was globally what worked the best, even though it's not perfect for anybody. Um we, those WhatsApp groups were on fire. There were, you know, like hundreds of messages a day. Um, I know for a fact that like some work we did on um positive deviants, uh, positive deviants are like um people who under the same conditions as others are doing better, right? So whether it's like child nutrition, you know, somehow they're living in the same poor community, but somehow the children of this family have better nutrition than others, you call them a positive deviant, right? And you look at that. So we did some work in Niger and Somalia on positive deviants, and um, and that got picked up in India. So when uh Sweta Kuluri, the head of experimentation there, built a um climate agricultural data platform. She didn't just include a bunch of problem data, you know, what's wrong with the soil, what's wrong with humidity, what's wrong with this, what's wrong with that. She also included like positive deviant practices that are working for for for farmers. Um, so so that kind of stuff, it definitely traveled, it was more anecdotal, and we didn't necessarily have like uh data on what traveled where um and how much, but we knew it was happening. It was just um it was at a scale that we didn't keep track of.

Simon Hill 34:18

How did you how did you guys think about value then in the in this context? And I know it's something that you'll have spent a lot of time thinking about and it's very hard to track and measure in many ways, but also how maybe inside the team, but actually, you know, from a broader perspective, you know, the funding came from from a broader organization or sort of set of organizations as well. So, how how is that being reported back up? And I'm gonna use this question slightly to to preempt you as a as a hook into what we might learn from this nature, this type of innovation that could be applied in into you know the corporate world in that that maybe aspects of this feel very different to. I think they're very similar in many, many ways as well.

Gina Lucarelli 35:01

So yeah, I mean, I uh just thinking about like the I think okay, we're dealing with a context where there's a commitment to sustainable development, but budgets are stagnating, and the sit the context in which you make people less poor and protect the environment more is getting more and more complicated and complex. So it's very much a space where this whole initiative was like admitting we don't know, right? We don't know everything. We know some stuff, but we don't know everything, right? And so a lot of what we defined as value was creating intelligence, right? Creating finding out what works and what doesn't to make people less poor, to protect the environment better, to do this both of those things at the same time. Um, that was kind of what value was on the one hand. So this intelligence, right? Or learning or, you know. And then on the other hand, this like highly collaborative research and development that we did, um, not just as a global network, but also within each of the national ecosystems that that the labs worked, just creating kind of trust and belief in new ways of working, uh, seeing it firsthand, you know, doing not telling. Um that, you know, that has a ripple effect where many well-meaning governments around the world want their bureaucrats to be more entrepreneurial and they don't know how to help them, right? So this what we did is we kind of de-risked public sector experimentation, right? We would come in and be like, we're the United Nations generally, you know, you think of us as a legitimate actor. Uh, we're telling you you gotta experiment. We're telling you startups are people you should kind of think about working with, right? Um, I always remember in the early days in Zimbabwe, you know, the government was sort of like, wait, those people who hang out in the you know, internet cafes, aren't they just opposition parties? And we're like, well, they're businesses and they they might actually be advancing something that you want to do, and you should come up with a startup strategy and you should think about working with them, right? Seeing them and working with them as allies. So, yeah, so I think intelligence and kind of trust in a new way of working are like the um in a context where, frankly, we don't actually know, right? The best practices exist, but not on every problem. And the more that governments have to deal with complexity, you know, longer droughts, more frequent floods, how do you deal with that? Um, you know, uh, of course, the the the AI economy and and what that does to you, you know, how you should use technology, but also respect human rights. They're just like lists and lists of questions um that are unanswered and need RD.

Simon Hill 38:05

Yeah, exactly. And but I think also arguably that that the best innovators for some of those are exactly in the context and the settings that that that you guys were operating within as well, right? Um, back to some of Eric's thinking and back to other, you know, just other general principles as well, is that you know, the abundance of some of the settings that we try and do innovation in makes it harder for that innovation to scale and be successful by its very context and very nature, and that perhaps some of the more challenging settings, I'm not suggesting every single one of these countries is you know some backwater of nothingness, right? But like different settings than perhaps others might might have, is um is a is a is the perfect setting for a lot of the innovation that we're talking about, which is why I'm interested in the scaling side of it as much as anything, because it's a it's again it's this holistic problem everywhere. You know, I'm I'm really really brought into the the value side of things, not because I think everything should be measured to within an inch of its life of value, nor that I think it can be, but um because as we you know, whether this is directly related to this or not, that innovation teams have a very short lifespan inside corporates, right? And um part of my underlying thesis as to why that is, is because we find it very hard to quantify the value of the things that we are doing. And even though we know they're valuable, intrinsically and and extrinsically, even though there's a bunch of stories to get them to speak to the PL in a sense of, you know, we're we're we're we're driving value somewhere, right? I appreciate the PL inside uh the UN is different than the commercial organization, but still there's a financial, there's a PL and a balance sheet to work to, right? Um in every sense. And so this idea of how do you quantify and how do you get to really articulate the volume of work that is inherently hard to quantify and measure, but if you can't do it, is really reaches an end, is you know, potentially sadly, and it's public public knowledge, right? But these labs are being now pended, right? They're closing down. And so what's your reflection on that before before we get into it? Not necessarily on the closing down piece, but on on maybe you know the the longevity of innovation teams, the longevity of innovation initiatives, and this real challenge of speaking uh you know in a value-based language, right? I'm not even sure what my question is here, but it's because it's so big and profound in many ways. But what is your what is your observation and learning on it? And what can you talk about in terms of the context that you know your your amazing project now finds itself in?

Gina Lucarelli 40:44

Yeah, I mean, I I definitely I think that this the concept of expected value is incredibly useful. And I really like in your book the way you're like talking about like why do we not have real methods? We should be treated like a real team, you know, these innovation teams. And I I totally relate to that. Um, I mean, I think what we tried to do with this network, and one could argue to what extent we succeeded or failed, was to prove to a large global organization that just like accounting and HR are considered investments that are public goods, right? You need everybody needs those, right? Um, because we all need to hire and we all need to get paid and we need to manage our money, right? We tried to kind of prove to this big organization that you need innovation and research and development in the same way you need those. It's a public good, right? And so this wildly decentralized approach of like, I mean, it's insane to have a hundred and fifty million dollar investment over six years and say, we can't tell you what this thing is gonna bring, right? Um to say, we don't even know what problems these labs are gonna work on. That's all up to them, right? It was we don't even know what methods they're gonna use. That's all up to them. What innovation there? Is it tech? Is it grassroots innovation? Is it human-centered design? Is it foresight? Is it biomimicry? Is it whatever the long list is? No, it whatever it's happened. So it was this kind of wild thing. And what ended up happening to an extent, but again, it's always challenging, was that it the labs became a public good of the organization, which ended up driving corporate strategy, even though it was very bottom-up and distributed and not top-down. So 80% of the AI work came from the labs, 80% of the digital positioning work, uh, 60% of the digital positioning work came from the labs. Um, you know, even the organization was pushing on innovation portfolios, 80% of those. At least the labs could like handle the ambiguity involved in a portfolio and translate that to uh professionals who'd been in the organization longer and are deeper in their domain areas. So we really tried to get this idea, get forth this idea that this is a public good and you just got to invest in it, even though you don't know what's gonna come from it. On the other hand, I think we, you know, we toyed with the return on investment idea, and we, you know, in even internally within our own team, we had different thoughts on how much we should try and quantify that, right? Um and because these teams were designed, indeed, as labs are, as temporary teams meant to sort of model a certain kind of working and then, you know, infect the rest of the organization with that, you know, openness or excitement or at least awareness of a different way of doing things. We felt like we shouldn't be really vocal about the return on investment of the labs because what we're try what we were always trying to do was get somebody else to take credit for it, right? Like that was our big, you know, like let's just, if it works, just pretend you didn't even, this wasn't even our right. Yeah, you know, um, like so so there was this schizophrenic relationship with return on investment. On the one hand, basically we had leadership who protected this idea, who created the space for it, who raised the capital for it. Um, and under his leadership, it was okay, right? And it became this public good that you know created uh it brought in money, definitely. Um but we didn't focus on that because we always wanted to um, you know, give somebody else the credit for new business development. Um so yeah, so it's it's a tricky kind of thing when you're operating ahead of demand and you're not yet offering something that people know they want to buy and invite you know and spend money on. Um at least our approach was always if it works, if the thing ahead of demand works, let somebody else take the credit for it and just quietly slink away and start work. Anyway, we're innovators, we don't care, we're bored of that anyway. Move on to the next one, right? It was like totally worked for like the whole personality. Um, that was kind of how we how we approach that, uh, for better or worse.

Simon Hill 45:08

Yeah, and look, I think it was mostly for better, right? And and maybe we can talk, I know we're running tight on time now, but about what what next, right? Sort of from from from this perspective. And as I said up front, you're doing teaching now and and and pushing more on those side of things. So, like what do you see this as the foundation of going forward? Because I don't get the sense it's really the end, right? It's it's it's a part of a journey. Um, and it's an incredibly successful one with an incredibly rich data set that's sitting behind it as well.

Gina Lucarelli 45:38

Definitely. Yeah. So I mean, one of the outlets is um, you know, again, an idea from Eric von Hippel and others um is to build an Innovation Commons, right? And that, and and and Eric's work kind of shows that actually open source can be profitable, right? And so putting stuff out there is a is a really good idea. So we've built this database, the SDG, the Sustainable Development Goal, Innovation Commons. Sorry for the acronym. Um, uh, and it has 12,000 documents in it. And we've got a lot of interest uh from academic partners to mine that database, to supercharge it with AI, um, and to see, you know, what all of these insights and raw reflections from around the world might be able to generate, you know, in terms of uh an LLM. Um, so that's one output output is actually just to run off the intelligence. This was moving so fast in a way that we were generating intelligence, but we weren't generating like meta intelligence and thinking about it in that sense. So we can kind of run off that for a while. Um, and secondly, you you alluded to it. This was this was a movement, and it, regardless of the institutional home, it remains a movement. And and I say that in all sincerity. Um, I know there are you know 300 people in 90 countries who I can you know contact right now and get an answer on something uh that I need, right? Whether it's I'm looking for a job or whether it's you know, I'm trying to solve this problem, or whether I want to know if somebody else has ever tried this kind of innovation, like that is alive and kicking for sure. Um, and then thirdly, I think in in Africa in particular, we we did have you know over 40 labs on the continent of Africa. And um at least in the UN development program, they're pushing now a big effort to like uh for the startup revolution in Africa, right? To leverage a billion dollars for 10,000 startups um and create you know millions of jobs, um, and to kind of build out the RD agenda and pipeline of the continent um uh in new ways. So, so it definitely feels like that's an outgrowth um of this effort. They were kind of um just just having the capacity in in country uh for innovation, having earned reputations with innovation ecosystems, with startups, you know, speaking their language, all of that position the UN to now uh play this intermediary role um in the startup revolution in Africa. So there's definitely you know several, several outposts of it. For me myself, I and that's why I'm inspired by you as a writer. Um, I need to figure out which part of the day one writes in and what the ritual looks like. Because I think right now I'm I'm you know I'm expecting these perfect conditions of caffeination levels and lighting and inspiration and focus. And it's like everybody who writes just says you gotta get up and you gotta do it. And whether it's terrible or not, you just do it. Um, but I do want to write a book. I want to write a book about what sustainable development looks like when you take a research and development approach. Um, like what all this, you know, all the it's a little bit to your question of value, right? What did all what we learned from all this? What what the heck is different? Um, and and I've got kind of some hunches and some ideas and a ton of data. Um, so even if we were to just look at one of the things that was exciting about teaching at Harvard was I assigned the students to look at our database and I was like, what do you think? You know, and they're so smart. And they come back with like this one student came back with just like a fantastic frame for a research project to look at all of those 6,500 grassroots innovations and to kind of map the patterns in terms of the constraints they're overcoming, like intermittent electricity, abundance of waste, uh, you know, like all of those kinds of constraints, and then the design features that actually come up, right? So, like they're modular, they're lightweight, you can ship them, they work in tropical conditions, um, they're often communal in relationship and not individually owned. You know, like imagine how you could reinvent sustainable development from kind of like a policy-driven, top-down effort to something where it really learns from how people are solving their own problems. So those are some of the kind of pipe dreams I have.

Simon Hill 50:07

Yeah, and I think again, there's there's plenty you and I can and will keep pulling on on those on those threads as well. My one piece of of uh of advice on the book, by the way, is uh maybe not at the start, but if you're struggling for a start, take yourself somewhere different than home and and and and normal, right? Like so for me, I did a lot of work on it, but I was able to have the space and the time on a family holiday. I wasn't there to do it. It's better if you tell your family you're there to go do something like that rather than just doing it. But for me, this sudden moment of clarity came whilst I was removed from the day to day, and then I just disappeared for for hours and on a day, unfortunately, for the family, or maybe happily, but and just did the work that needed to come out at that point in time. But I think that change of context is um is quite important because otherwise the rest of the day just gets in the way. There's no other great lucidity or anything else. I mean, there's probably things you can take to help with that, but generally the um uh get yourself out of your normal drugs or something. Get yourself into a into a different setting is uh is quite is quite helpful advice. But listen, I I just want to say thank you, and and not just for today, but for the work that you've that you guys did on this, right? Like I appreciate that lots of other people were involved in doing it, but I think you took on something that was extraordinarily different and brave in the context of what was there. And there isn't a book yet. Maybe you'll write it that it can explain to other people how to do it. And so you just had to, as you said, multiple times, figure it out. Um, and rather than doing that in a command and control way, you just let people figure it out again, maybe partly by necessity because there was so much going on. And when you throw 90 different laps at something, like with not very many people and no playbook, good luck. If you can't, just let them do it. But the trust to let them just do that is, I think, advice that can follow through, not just from this setting, but into lots of different places. You know, you mentioned earlier, I don't know if there's, you know, if people know this and we just didn't. The academic literature doesn't agree on a lot of this stuff, right? There isn't an absolute playbook on decentralized, centralized, on command and control or whatever. But I think we all come with this from a very democratized lens of thinking about it and trust people with you know fairly broad corners and guardrails in place. Like you said, I love your little red line on the floor analogy. Um, but none of the people whose innovations you captured had any of that really, right? They were just out there just figuring something out, and and you guys helped to go and then try and figure out whether what they'd figured out is is was a there there or not for some level of scale. So congrats, right? And um, and I I would encourage people to go check it out. We'll share links to the to the work that you've done and to your profile and other things for for for for people to pick up on. But thank you very much for sharing your story. I look forward to spending more time together outside of this setting at at MIT in a few weeks' time as well. For for everybody else, thank you for listening. Um, as always, this is just one of a number of different stories that we're telling through the podcast, week in, week out. So please give me your feedback on this one. Please find and connect with Gina. I'm sure she'll be happy to take any questions or other things you've got outside of the podcast. Um, and check out all the other amazing um stories and very human-centered innovations that we bring you week in, week out. So, once again, Gina, thank you. Everyone else, thank you for listening. Until next time, this has been the Total Innovation Podcast. Goodbye.

Gina Lucarelli 53:26

Thank you, Simon. It's fun. What's up, Barthes? Uh uh.

Simon Hill 53:34

Uh oh. Uh oh. What's up, worth it? Uh uh, uh uh.