Transcript

HIBT Lab! Gro Intelligence: Sara Menker

Hello and welcome to How I Built This Lab. I'm Guy Roz. So have you ever wondered how a drought in one part of the world could impact the cost of food at your grocery store, or how extreme weather caused by climate change might change agriculture as we know it. Well, our global food markets are all incredibly connected and they require vast amounts of data to understand and analyze. Which is why Sarah Manker founded Grow Intelligence in twenty fourteen. Grow takes trillions of data points from a variety of sources and builds forecasts for thousands of unique agricultural products like chicken or wheat.

or corn or sunflower oil. Sarah's company helps clients like food suppliers and financial institutions navigate climate risk. understand supply models, predict the demand for crops, monitor conditions for farming around the world, and more. And as of this year, Grow has raised more than$125 million to support informed decision making in global food markets. Shermaker grew up in Ethiopia, where she saw the tragic consequences of food insecurity firsthand. Yeah, I mean it was you know, it was basically during what was known as sort of the Dirk regime, um, in Ethiopia and it was the communist regime.

And so it's a pretty dark time in the country. Uh, but everything was you know, run by the state and controlled by the state. So sugar Toilet paper, it was not even a rationing. With toilet paper wasn't even any rationing, it was an availability issue because most stuff was not imported. So it was all locally produced. Um

But you know, fuel, uh we couldn't drive on Sundays. You walked on Sundays or you took the bus. Um, and so it was just a it was a very it was a very different time. It was a very dark time in sort of the country's history. Yeah um You know, when you're sort of growing up in a in a world where It's not a world of abundance. It's a world of limited resources. Like everything is limited. Um, and it doesn't matter who you are. I think you just grow up with a sense of awareness of not taking anything for granted, if that makes sense. Like I don't know. I think

It's impacted me a lot, especially as I like I'm I've gotten older and you know, sort of experienced a lot in life. I think it it grounds you, right? It reminds you of what basic necessities and basic needs are in this life and And keeps you connected to those things.

Um you went to university in the US, I know you went to Mount Holyoke. Um and after college you decided to kind of enter the world of finance. You were you were at Morgan Stanley for a while and you you focused on commodities. Um tell me w wh why you had an interest in that space.

Yeah, I always say that, you know, I fell into finance after college. I didn't, you know, you know, there are people who grow up and are like I I dreamt of going to Wall Street. I didn't even know what Wall Street was. So um you know A lot of friends were doing these finance internships. And I didn't think I wanted to do that. I thought I actually wanted to do a PhD in economics.

And um and then I just You know sort of fell into the role in the sense that I met a recruiter. who convinced me to apply for a finance internship. I did that, um and I realized that

credit markets and credit default swaps and all these other sort of cool instruments were like the cool areas to work in. Like nobody wanted to work in commodities. Like it was always that division nobody understood. The reason I was attracted to it is that it was actually attached to some things that were so physical and necessary for life, you know, like oil markets, like things that still tied to like my academic interests, but also tied back to the real world in some way. Um, and so I think I just Loved the idea of Being part of a group. That dealt with the physical world.

While you were There. You spent I think um Eight years. um on Wall Street. you start to think about

an idea that would eventually become this business grow intelligence. Um I guess the idea really kind of began around two thousand eight during the financial crisis. What was going on and what led you to start to think about agricultural forecasting of what it would eventually become grow intelligence. It was the oh eight, oh nine financial crisis, which those of us that were there at that time will never forget. Um and I had a colleague

who um just thought the world was coming to an end in sort of a a genuine way. Like he was worried and he's like, Oh my gosh and and all I could think of was like, listen, like Honestly, if Morgan Stanley's stock went to zero, which at that time felt like Any of that was a possibility, like Lehman had gone under and everything else, like it would suck, but the world's not come to an end. You know, like I've seen. What

close to the end of the world looks like, which was sort of my upbringing. And going back to the comment I made earlier, which is it keeps you grounded and it gives you perspective, right? And so his his sort of way of hedging for that was buying as much gold as possible and and lots of guns. And um And I one day said to him, Like, What are you gonna do? Like trade a sack of potatoes for Bar of gold, like if you think the world's coming to an end, like that just gold seems like the worst investment idea.

Yeah. It was actually that that led me to look at agricultural investing. Coincidentally was also a time though. When land um in places like Ethiopia, actually, and and sub Saharan Africa more broadly, there was this really big push by governments to Um

Make arable land available for commercial farming purposes. And so I started looking at investing. in agricultural land. I'm not a farmer by any means, but I thought, you know It could be a great investment.

And uh and I by the time I went through the process of assessing what seemed like a good deal, it became clear that it was actually a near impossible deal to make the economics work. And it sort of like really baffled me that It was so interesting that every time I asked questions, I got more questions, or if I needed data, I got data that was like two years old. Or, you know, I'd ask about crop insurance and there was no crop insurance market. Like all the things that seemed like basic questions that one would ask to sort of set something like this up. The infrastructure for it sort of didn't exist and

And I just and I I just remember thinking, you know Gosh, like we're just not gonna solve. these big food security challenges. At some point it became clear to me we were like trying to fix a system we didn't even understand. And it was just uh I was just so curious about

it all sort of eventually just led me to say That I was really good at my job and I actually really liked the people I worked with at Morgan Stanley, but I just had no passion for it. Huh. So all right, so you

I guess you could decide to leave your job at Morgan Stanley and we'll get to that in a moment. But but help me understand a little bit mo more about the p the problems that you were starting to uncover. I mean essentially I guess you realize that there there just isn't enough data for investors and businesses and and and governments to understand what might happen to the price of different commodities, right? Especially uh in agriculture. And I guess that lack of information

uh can make problems like food insecurity even worse. Is that is that more or less What you started to realize. Well, yeah. I mean, uh, you know, when I was trading, I managed our natural gas options business. And if you think about sort of natural gas and and and any commodity, like the thing that drives the price of that product is like how much supply is there, how much demand is it, and what's the clearing price that clears the supply and the demand. You know, hurricane season constantly disrupted Production. So during hurricane season, you're using weather data and weather forecasts to sort of see the probability of a hurricane hitting some type of production or In the winter, how cold is it gonna be? Because that drives how much heating demand there is. So, you know, all of those are pieces of

That sort of drive w that the price of any commodity and um And and agriculture is one of them. So grow just became this idea to to do it for agriculture and that didn't exist at the time. All right, so you decide to leave your job.

at Morgan Stanley to pursue this idea and you found it uh this company grow intelligence, I think in in twenty fourteen, right? Yeah, I ended up leaving Morgan Stanley in 2012. So I spent two years. after I quit to when I sort of decided on exactly what grow what shape or form grow was gonna take. And so when I left in twenty twelve, My

explanation to my boss then, who I'm still very, very close to, and actually was one of my very early investors. was that listen. I love working with you guys. But this is not the place for me. I've fallen in love with this other problem and I need to move back to Africa. And I wanna do something that solves for sort of food security.

And he was like You've lost your mind. You've absolutely lost your mind. You like please like don't don't leave. Like maybe take a sabbatical. And I said, No, I don't want to take a sabbatical. Um and and he said, Why not? And I said, Well if I take a sabbatical Then I will

Wanna come back. Or you know, if something doesn't sort of fully work out. Um, then I'll have a fallback plan. I don't wanna have a fallback plan. Like what's the worst that can happen to me? I lose my life savings, fine, I'll get another job. Like I just for some reason I just thought the best way to do this was to

truly just sort of move on. And then I sort of embarked on this journey for two years, um, from 2012 to 14 of just defining. What the business was gonna be. Um let let's t let's talk a little bit about some of the challenges that you're trying to solve here. I mean the m the main issue is food security r and insecurity, right? Because

We know, right, that that um the amount of food produced in in the world is more than enough to feed people in the US alone, um, forty percent of food is wasted, right? Um so when we talk about this idea of food insecurity. What exactly does it mean if if there is Plenty of food available and

And there are still people who Don't have access to it. Yeah, well you you nailed it, which is Food insecurity is about access and affordability. Um

'Cause it's it's you can have a lot of food, but if you can't afford it, that's also not helpful. And so what we have as a world in terms of a challenge is both an access and an affordability problem. And it looks very different. depending on what part of the world you're looking at, right? So

If you're looking at food insecurity in sub Saharan Africa or in South Asia, It is An access issue. Um in the sense that not even enough is produced locally. So there is a a food insecurity that comes from the fact that domestic production is not sufficient to meet the local needs.

And then on top of that, there is an affordability issue, which is when you import it, obviously food is is more expensive. Um, and then if you look at food insecurity in a wealthy country like the US, it's very different, right? Like the US is feeds most of the world, right? Not just produces enough for itself. Um and um but in the US your challenge is affordability. And then to your point, you have a a massive food waste problem, which could be more food that could sort of go out to other parts of the world, right? So it's Different in in sort of different areas, but there's sort of that combination. So is there enough availability? And then can you get access to it when you need it? We're gonna take a short break, but when we come back, more from Sarah Menker, the founder of Grow Intelligence. Stay with us, I'm Guy Raz, and you're listening to How I Built This Lab.

Welcome back to how I built this lab. I'm Guy Raz, and my guest is Sarah Manker, founder of Grow Intelligence. It's a company that's using artificial intelligence to create forecasts for global food supply, demand, and pricing. So all right, so you launched grow intelligence in twenty fourteen, and now your clients include

uh food suppliers, um uh agricultural businesses, financial institutions Um H how do you provide forecasting models for them? What w what kind of data Points to you. Provide.

Yeah, so we so Taking a step back, what we did is the company's gone through sort of a journey, right, since 2014. The first set of challenges we dealt with was can we get enough data in our system? Like what data is out there? Like, do we even know what's out there? It's sort of, you know, one of the things that made agriculture so much more complicated than sort of the work that we did in the energy markets is that agriculture is not a single product, you know, oil is oil, natural gas is a natural gas. Agriculture is tens of thousands of different products. Every single one is sort of governed by a different set of biological.

rules that govern how it grows. Um supply is super fragmented. It can be in a half acre farm or a hundred thousand acre farm, right? So our first challenge was saying what data is even out there? And can we ingest it and come up with a a technology that can take that data and standardized it. and bring it in in any language in any format. So we shouldn't care if it's in PDF, we shouldn't care if it's images, we shouldn't care if it's in Mandarin or Portuguese or English. We should be able to take that automatically translate it. And also standardized the format. So what that then gives you is too much data, right? So we get data from 50,000 sources around the world. Um, they come in all these different formats, languages, but data on its own is not knowledge, right? It's just data. And so our our second challenge then became how do you take that and how do you develop insights and how do you develop models that tell people um, something they didn't know. And that's when we started building predictive models. And again, there we started

Simple. We started with modeling and forecasting in markets that everybody understood. So corn in the US. soybeans in the US, like really big markets before you start to go to Russia or India or Africa, where the data challenges are even bigger. So we essentially built This what we call our modeling frameworks. And so today we have twenty-eight modeling frameworks in the system. So think of those as Yield models. Climate indices.

food price indices very broadly defined, but they're essentially um, a combination of our data science team and our domain experts, people who actually understand these problems, design these models as templates that can then scale through sort of machine learning AI. And so today those 28 modelling frameworks actually develop two million unique models. Micro. So everything from forecasting the Um

The demand of pork in China to the supply of sugar in Brazil to the US. Africa, you name it. So what our clients want is for us to pick and choose these models to solve very specific problems for their business needs. So for example, if you're a seed company, you want to understand how profitable farmers are because you are selling all this product to the farmers, you need to know that they can pay for that product. And so that will use a combination of our yield models, what we call our planted area models, our demand models um and price data and combine that and actually give them a forecast for farmer profitability for every state or every district in Brazil or in China or in Argentina, right? But those same models get used by traders to just trade markets and those same models get used by governments.

To look at credit risk of farmers because b governments oftentimes backstop loans. So you know, you use these models differently, and the same models get used. slightly differently by a whole different set of constituents, which is What's been sort of cool and amazing about it. Yeah, um Right now there's a lot of

A coming. Grain crisis. because um because of the Russian Ukraine conflict. And I think Ukraine provides like a significant amount of grain to particularly to countries in the developing world.

Um What what does it mean for food security or insecurity, particularly in African countries and Asian countries that rely on on countries like Ukraine for for for wheat.

Yeah, so I you know, one of the one of the things that we've been emphasizing is that You know, the Russia Ukraine war. didn't start a food security crisis. It added fuel to an already like long burning fire. And I think it's really, really important to sort of highlight that because If the war went away tomorrow, the crisis we're in doesn't go away. Right. And that's really important context to sort of provide.

Really since the start of 2020, we'd been undergoing some pretty deep structural changes in agricultural markets that were sort of setting the stage for massive, massive price increases across different commodities. And what happened was in 2020, China, which has typically never been an importer. Of of um main core cereal grain. So China imports soybeans to feed its hogs and sort of pork production, but rice, wheat, corn, China's never been an importer of that stuff. In 2020, it turned into a structural importer of grains. That means that the world's sort of largest economy. Went from being self sufficient in some of these core grains.

To being insufficient. So that change happened irrespective of Covid. And irrespective of a Russia Ukraine war. Then you had Covid. Which disrupted supply chains. And drove up price changes. And they were not a simple shock that came and went when you know things sort of normalized in the world. They sort of

persisted. So that started driving prices up. Yeah. Then you also are now having an unprecedented number of Uh, supply side shocks due to climate change around the world. So major producing regions, the US, Brazil. China, Australia, I mean Year after year for the last Three years essentially have had one

climate catastrophe or another that has heavily impacted production. And so you rarely rarely actually have a confluence of supply and demand side shocks. Occurring. That was the backdrop of the start. Of the Russia Ukraine war. Right. And so that when you had that sort of already

happening, then what you end up with is a situation where now Russia and Ukraine over sort of the last 15 years had emerged as sort of the major growth areas of the world for agricultural production to fill sort of that demand gap that was coming from areas like sub-Saharan Africa, et cetera, where Economies were growing fast. They filled that. Right, so you just had this massive disruption to in particular wheat. Um corn to some extent, and then um sunflower oil.

really truly catastrophic because we're basically in year three of a crisis that existed despite this war. Yeah and and this is now weighing on sort of local economies more and more because how long can you actually withstand A persistent shock, right? Cause at some point A shock supposed to come in though not. Not stay. Hm.

Th there was a a speech that you gave to the UN Uh in May of twenty twenty two where you you basically talked about some of the major challenges that are facing the global food system. And and one of the things you mentioned was a lack of fertilizer. Why is there a shortage of fertilizer in the world right now? Yeah.

Oh gosh, that is actually the biggest Problem now. So you're touching on probably the the most terrifying challenge ahead of us for the next two years is fertilizer. So there are three types of fertilizer. Um there are nitrogen based fertilizers. Which would basically require natural gas. Uh, there are potash, which is mine, and then phosphate, which is mined. So

Let's start with the first nitrogen based fertilizers. It's dependent on natural gas. Well, Russia. Natural gas into Europe. energy crisis, right? It's all linked to the energy crisis. Um and Севенті та навіть процентов за кост.

Of producing nitrogen based fertilizer is the cost of natural gas. So when the cost of natural gas quadruples. Guess what happens to the price of fertilizer? So you basically have A massive sort of spike in fertilizer prices, but what you've also had is a lot of capacity being shut down in Europe as a result. So a lot of the producers just can't afford it. So that sort of cascaded, though, into challenges in places like Sub Saharan Africa, where people just already use little fertilizer to using none. Now going into sort of 2023, you have a major, major problem ahead of us because now you have an affordability and potentially an availability problem conflating the two. And we can model out

What that means to global food production. And we just finished rerunning a new analysis essentially as of November first. Um and what we see now is that basically Just the nitrogen problem alone. is going to lead to a reduction of two hundred sixteen trillion calories around the world. And that's just simply due to the fact that using less fertilizer is gonna lead to a reduction in yield. Yeah. So that is something that is a massive, massive sort of looming twenty twenty three, twenty twenty four problem that's even potentially bigger than it was before.

So if you can forecast this now, knowing what's happening with What Could your data lead to me could it could it Is it designed in in in theory to prompt

governments to take action to subsidize Fertilizer to I mean literally You know, to to ship fertilizer to countries that can't afford it? Um it's everything from uh central banks around the world looking at what that effect is gonna mean to sort of their national balance sheets, because some of these are countries that are actually typically exporters. So when you have

Exports go down, that means that you have a balance of payments issue that you need to manage. So you can plan in advance for like How do I mitigate this? Like do you Pre-purchase in the markets. Like how do you plan for this so that it's not an absolute catastrophe while it happens? We're telling you this that as you know, you're going into sort of twenty twenty three. It's being used by the likes of the World Found for emergency response. Where is it going to be the worst? Yeah. Where resource is gonna be needed, right? You start to think about sort of resource allocation. It's being used by a combination of companies around the world that wanna sort of think about donations for fertilizer. So you just plan for it, you know? It just It can either feel like all out chaos.

Or it can feel like planning. Um, and it's actually been amazing to sort of watch because we only launched um this tool this summer and and it's obviously the problem has gone sort of much worse, but it's it's been really powerful to see You know, really critical institutions relying on it and using it. We're gonna take another short break, but we'll have more from Grow Intelligence CEO and founder Sarah Maker in just a moment. Stay with us, I'm Guy Raz, and you're listening to how I built this lab. Welcome back to How I Built This Lab. I'm Guy Raz, and my guest is Sarah Manker, founder and CEO of Grow Intelligence. Um Sir you you grew up in Ethiopia at a time when I mean you've talked about this one, there were

images around the world of Ethiopian, you know, children in rural parts of the country dying of famine. You you of course did not experience that living in the capital, but Um that was something that was sort of was was a there was a clear image of that, right? Where we are today Right, what you're talking about it seems like a perfect storm.

That could result in a version of that in parts of the world, right? Lack of fertilizer. Obviously climate disruption. The Ukraine war.

Which is disrupting Grain supplies. supply chain challenges that are you know, that make it challenging to move things around the world. Are we are we looking at the possibility of

of you know significant Famine in parts of the world in the next year? Absolutely. So If you look at the price changes in local currency since the start of twenty twenty for major foods, so if you just look at Core grains and sort of your vegetable oils, like the basics, right? Like we're not looking at the fancy stuff. Um, like meat, as far as I'm concerned, is a luxury, you know? Um so the basics. If you look at the basket of basic food product around the world since the start of twenty twenty.

The price of a basket of basic products in Sudan is up. One thousand nine hundred percent. In Syria, it's up seven hundred percent. In Ethiopia, it's up one hundred seventy five percent. In Argentina, it's up three hundred percent. Even in the US, it's up sixty seven percent. Europe eighty percent. No part of the world is immune right now. And what's gonna come down to is which Economies have the resilience.

Which governments have the balance sheets to be able to deal. With this kind of neat. Right, and how you deal with it is gonna be different. So My sort of Concern is that

This is so widespread, and every country is busy fighting its own fire. Right. That that it actually becomes so overwhelming to think about collective action. Mm. Every country is sort of focus on its own. But We've got to

Do something. It's just really hard and and we've been spending a lot of time bringing as much attention as possible to the problem for that reason. Sir, let me ask you about about the business side of what you do. Um How did you you know, when you were setting setting up your

your organization, um, how did you begin to to gather team? How did you how did you find people to work with you. And to help you build this. Yeah, so you know, I always say I'm the least qualified ex until I find the best qualified person to do that job, right? Which is what it is like being an entrepreneur and starting a company from scratch, which is you're completely not prepared, you have no clue, you just have an idea and then you have to make it work. Um and so the first person I brought on who's um is our COO and and um

my co founder sweet and You know, she was a person that came from private equity um and finance, and I had known her for a long time from New York, but she'd moved to Kenya. And she was just somebody I just trusted, you know, like that was it. And she's really smart and you know, we'd have to raise capital and she's investing side, not on the the operational side. And so I asked her to leave her

cushy private equity job and and go on this wild ride with me. And I was lucky she agreed. So that was step one. And then with every other team member, it was sort of And this was the benefit I think of Taking time to sort of kick things off was as you're learning, as I, you know, I spent those two years from twenty twenty twelve to fourteen, like. I did so many crop tours around the world. I mean, I've done crop tours in the US and South America and Malaysia and China. I mean, I I traveled the world and I learned just the agricultural industry inside out. And in that process I was like, wait, I need geospatial scientists because like there's all the satellite data, and I know nothing about satellite data. Morgan Stanley, I had a meteorologist that told me stuff and I traded off of it, you know? Um, and so it was always just finding the people who were the domain experts. So

Before actually thinking of the technologists, we thought about the domain experts. Who are people who know agriculture? We need agronomists. We need people who traded agricultural markets. We need climate scientists. Yeah. We've really constructed the team with I would say a lot of intention. Um, to make sure that the team represents sort of the world we're trying to model.

Um how does your how does your business model work? Obviously there's I I'm assuming there's a subscription side to it, so companies pay a fee every year to to access this data. Correct. It's purely subscriptions. So um we have different types of subscriptions people can buy. Um so one of the things that's always mattered to us is sort of being able to serve really small companies as much as we serve really big companies. Um We work with financial institutions again, some of the smallest and some of the world's biggest. Um Governments, governments who can't afford to pay as much, and and those that can. Um, and so we've developed a really flexible business model that has allowed us to essentially scale up as organizations are are bigger, but also start small. But everything is subscription based and

And what we've developed is a is what we call our application store. So think of it as no different from the app store on your iPhone, where you go in and the app store is built on our platform that has all these models that I mentioned. Like when you have two million models, it's too overwhelming for one person to make use of them. So each application has a very specific use case and a very specific set of targeted sort of customers. And so there's a library of applications that people choose from and say, I want to buy this application. And one application can be$10,000 per seat, another one can be 15, another one's 50. Um, depends on the use case and then depends number of seats um or whether it's an enterprise license or not. And and so we've been able to sort of build out this this licensing model, but but one that sort of is relatively um inclusive. How are you able to differentiate your data? From what governments.

provide because there are government organizations that provide this information and and and it's available for For b for industry. Correct. Um So first of all If you think about governments

that report the sort of most extensive is the US government. The U SDA, namely. Everything else is Just Tiny, tiny, tiny order of magnitude of what the USDA does. So to give you some perspective, even in the US,

Our models are predictive and accurate. Four to six months. in advance of when the USDA comes out with its numbers. Um within Like ninety eight to ninety nine percent accuracy. Yeah.

In places like India and places like Russia and places like China and places like Africa. Our lead time for sort of our insights is One to two years. At times. So yes, governments report, but they oftentimes report way too late. And they're also not reporting the level of depth that we report. So a lot of countries will report at the national level. We actually go down to the district level. A lot of governments won't tell you where the crops are grown. We have our own algorithms that look at imagery to actually identify which fields are growing what crop because that's how you can then

determine how many acres are growing, and then use that acreage to determine the yield and all the stuff. So we Really have harnessed you know the depth of knowledge of actually public data sets, because that is necessary. Again, you need to train your models on something, you need a baseline, you need to compare it to something. Uh, but what we offer is fundamentally different, which is why we work with the public sector as well. How did you kind of develop the technology.

platform. Um I mean you're obviously super smart and come with incredible experience around Commodities. W was there a steep learning curve for you to figure out the the technology side of it?

It's a steep learning curve on every single one of it. Cause I was not a qualified agronomist. I'm not a qualified fertilizer trader. I'm not you know, I was only a com qu qualified energy trader. Like that was my qualification. Um Not a qualified CEO, right? Um building a team is so different than Than than trading a book. You know, everything was a steep learning curve for me, but one thing that I think has always driven me is that. I love this work, right? Like I really, really, really believe in the work that we're doing. And so that just has made me completely relentless in learning.

anything and everything required at that point in time to make sure that we're successful and that that I'm sort of doing right by the team and that I'm doing right by our investors, by the business, every you know, just it matters a lot to me. So I think I already had a deeply sort of technical mind in the sense that You know. I was always technical even growing up and even at Morgan Stanley I

you know, built my own options trading models and and and and built out sort of these things, but it was always by Teaching myself. And so I'm not sort of afraid to not know. I'm never afraid to like call people and say, like, I need to learn and I need to learn from you. So in the early days, I literally used to like, for example, there was this um this scientist at USGS out in um And Colorado and USGS is a government agency that produces tons of data around satellite imagery, but I just didn't even know what these things meant. I like emailed him and introduced myself and I was like, Do you mind like teaching me? And so he used to get on the phone and like

Sure. Months. I used to just Yeah. lessons from him on how to learn and understand interpret like satisf you know satellite imagery. And so then when I was recruiting the first person, I even knew what questions to ask, you know? That's the whole thing. Like you can't empathize what you're looking for unless you yourself has have experienced that one thing. So

Pretty much every role we've had in the company, whether it's technical. Like Or AWS. Account was set up by me. And I remember Googling what is AWS. I didn't know what AWS was. Um and sort of setting it up, right? I have been involved in data science, have been involved in design and marketing and sales. Like every one of these roles I've played at some point. It doesn't mean I was the best. In fact I'm not.

But I learned what it meant so that when we hire a team that like I knew exactly what we were looking for. Um, I mean as we're you know, as we face a more volatile Climate future. Um

How how will will the data that you provide Allow businesses. And farmers. to mitigate some of the effects.

of climate change. In other words Can this data help people Work around. The climate challenges. to continue to produce.

enough food. Oh absolutely. So um One of the things that makes Grow really unique is that we had to ingest tons and tons of environmental, weather, climate data into the platform. to use those as signals. into sort of forecasting production, right? And in doing it, we realize this data on its own is still quite messy. Like

Temperature alone doesn't tell you whether you're in drought or not. Um You know, uh rainfall alone doesn't really tell you whether it's a flooding event or not. Um, you know, so there's all these Components of sort of how weather translates into a climate impact itself that's really complex. And so what we did is do we developed a suite of climate indices. Now what these indices do is that they measure all of these different risks. So we have the grow drought index, the grow flood index, the tropical cyclone index, the fire index, heat index, et cetera Um what that means is that now you can look at real time risks.

Of all of these different perils. For every product everywhere in the world in a consistent defined way. But the next step that we took is we developed These forward looking models that under different Climate scenarios help you understand what the trajectory is. Of exactly these climate events for every crop everywhere around the world. Now, how does this translate to mitigating risk that you mentioned? Well, one of the applications that we have is called the land suitability application. So if you're a major

um, food or ag company, think about sort of one of your biggest risks is Not just procuring for today, but if you're building a new facility, where do you invest? Are the areas that grow coffee today gonna be the areas that are most suitable for growing tomorrow? And where will they be most suitable? Five years from now, ten years from now, fifteen years from now, twenty years from now, and you'll be surprised at how much land area is gonna have to shift. based on these sort of different climate scenarios.

That's Sarah Manker, founder and CEO of Grow Intelligence. Sarah, thank you so much. Thank you. Hey, thanks so much for listening to How I Built This Lab. Please do follow us on your podcast app so you always have the latest episode downloaded. If you want to follow us on Twitter, our account is at HowI Built This, and mine is at GuyRaz. And on Instagram, I'm at guy.ros. If you want to contact the team, our email address is hibt at id.wondery.com. This episode was produced by Chris Massini with editing by John Isabella.

Our audio engineer was Maggie Luthar. Our music was composed by Ramteen Arablui. Our production team at How I Built This includes Alex Chung, Carla Esteves, Casey Herman, JC Howard, Liz Metzger, Sam Paulson, Carrie Thompson, and Elaine Coates. Our intern is Susanna Brown. Niva Grant is our supervising editor, Beth Donovan is our executive producer. I'm Guy Raz, and you've been listening. How I built this.