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Influencers with Andy Serwer: Sara Menker

In this article:
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In this episode of Influencers, Andy is joined by Gro Intelligence Founder and CEO, Sara Menker, as they discuss the challenges of food security, how Covid exposed the world’s agriculture system, and why Menker says we may be a few years away from a global food crisis.

Video Transcript

ANDY SERWER: Sara Menker left Wall Street in search of an answer to one of the most pressing questions facing the world today. What does the future of food look like? And where will our food come from? To find out, Menker is leveraging her experience in commodities trading and knowledge of data analytics to forecast everything from agriculture prices to the climate and its impact on our food supply.

But it's not just ones and zeros. These models are helping governments and business to predict food shortages and avoid disaster all over the world. In this episode of "Influencers," I'm joined by Gro Intelligence founder and CEO, Sara Menker, as we discuss food security, how COVID exposed our agriculture system, and why she says we may be just a few years away from a global food crisis.

[MUSIC PLAYING]

Hello, everyone, and welcome to "Influencers." I'm Andy Serwer. And welcome to our guest, Sara Menker, founder and CEO of a company called Gro Intelligence. Sara, welcome.

SARA MENKER: Thank you for having me, Andy.

ANDY SERWER: So I guess I want to start off by asking you, what is Gro Intelligence?

SARA MENKER: Gro Intelligence is an AI company that is really driven by a mission to help the world better understand our sort of food systems and our climate. And it's a platform that we've built over the past six years that harnesses vast amounts of data from various different sources to drive insights, both about sort of the understanding about our food systems as well as climate change.

ANDY SERWER: Right, and so is it a NGO or a for-profit company? Who are the customers? Tell us more about it.

SARA MENKER: Yeah, no, it's definitely a for profit company. We're a company that was founded in 2014. And we are a company that started actually in Nairobi, Kenya. And we're global now, and I'm based in New York. And so New York and Nairobi are our two co-headquarters. And our customers are really players across on the agriculture side, players across the food and agriculture supply chain.

So think of that as input companies that sell seed, fertilizer, crop protection to farmers, banks that lend money to farmers, insurance companies that insure farms, as well as those who purchase from farms and serve as intermediaries. So traders both in the financial markets as well as in the physical markets that move crops around the world, as well as food companies that use Gro to make decisions around procurement, supply chain planning, food safety detection, and then retailers who get food on our supermarket shelves. So we basically work across the entire supply chain in sort of the ecosystem.

ANDY SERWER: So are predictive models kind of at the core of this? And you mentioned AI. Talk about the actual products that you produce then.

SARA MENKER: Yeah, so, you know, we have one sort of-- we have one product that serves as a platform for the generation of many, many different products, right? And so, you know, the first part of our sort of company's journey was saying, how do we take very large disaggregated data sets that often come in very inconvenient formats and local languages and create a mechanism whereby we standardize that data and organize it so that people can just discover it, right?

So the first part of sort of the Gro journey was creating this massive dictionary of terms that have anything to do with global agriculture and classifying them in an automated way. So our sort of-- our platform currently classifies over 60 million terms related to global agriculture. So think of that as everything that can drive the supply side or the demand side, which means we have tons of environmental data, but we'll also have tons of demographic data because that drives a lot of sort of how we eat and what we eat, and the classification of it.

And there's a layer of AI there because, obviously, when you're processing hundreds of trillions of data points every day, classifying that data and understanding that, say, you take Canadian wheat exports as a number from a data set, you use neural networks to actually map that knowledge. So that's the first layer of AI.

The second part of sort of our journey then became when you have that much data, one, do you start creating new data about the world to tell us things we didn't know before? So you train models to create new data sets for parts of the world that don't have as much reporting. And then the second is, do you use that data to generate predictive models?

And so, our platform has raw data, lots of it-- almost too much of it. And where the power of the platform really emerges is in our predictive models forecasting supply or demand or price or climate models that then people use to sort of drive the decision-making. So we have thousands and thousands of predictive models that are built on top of the platform.

ANDY SERWER: How did you see the need for this? And maybe akin to that, what is the use case here? And can you give us some examples?

SARA MENKER: Yeah, absolutely. So how do I identify the need? So I used to be a trader. I used to be a commodities trader. I traded energy at Morgan Stanley. And I had seen the power that sort of access to data and better information had brought to the efficiency in the markets and the way in which we allocated capital and the way we drove innovation, you know?

We take sort of for granted that to drive the energy-- like, we talk about oil. We talk about gas today. And we talk about shale oil, shale gas. Those only became possibilities because there were mechanisms to finance those new innovations. Renewable energy-- it was possible because there was lots of money that went into it.

But a huge part of facilitating capital into markets and changing markets is information. And I had seen that there was huge information gaps that existed in the global agriculture ecosystem, which drives a lot of food insecurity around the world, et cetera, and also an understanding that unlike energy markets, where it's just a few products, agriculture's tens of thousands of different products. It's everything from vanilla and black pepper to corn and wheat, you know? And each one sort of has a very different set of biological rules that govern it.

So, for me, it was driven by a desire to say, if we're going to change a system, we first need to understand it. And we want to be the infrastructure and the highway to understanding, right? Like, so it is until we can facilitate that, then we're not going to drive any change. And so how can we be a change agent for industry and driving sort of decision making?

Now, to your question of use cases, it is sort of the beauty in what we do and the complexity in what we do. Because we have so much data and we have so many models, it is really a world where we say, tell us your problem and let us help you ask questions you didn't even need to know you needed to ask. So the system helps you ask questions differently. And it helps you sort of connect the dots.

So let me give you one example of how a single model we have can impact every single player across the vertical. So let's take something as simple as-- seemingly simple as what is the forecasted corn production in China today? Well, that has massive implications for everybody across the supply chain.

Let's start from the very top. If I am a seed company, I care about that question, and I care about the predictive models that we have around that because I need to know that, based off of the supply there, how much demand is there going to be for my seed the next season and the next season and the other parts of the world I'm selling. So for example, seed companies manufacture 1 and 1/2 years in advance, right? So they need to be able to predict the acres that US farmers and Brazilian farmers are going to have. And China plays a very big part of that. So they use it to-- they use that as an input to predict acreage.

Now if I'm a bank, I want to understand that because I want to understand farmers' abilities to repay my loans. If I'm a bank locally, it's about local repayment. If I'm a bank internationally, i.e. say, a US bank that lends to the agriculture-- to farmers in the US, I still care because farmers-- the amount of corn that China produces impacts the global corn price, which will impact the bottom line of the farmer in the US, which is how the farmer is going to repay my loan.

That same question now applied to sort of a trader-- you know, traders like to buy low, sell high, right? So that becomes a mechanism whereby I'm looking at what global supply is, and I compare that versus global demand. And all of a sudden, I'm making that decision. If I'm a food company, I use corn as an input as ingredients into my supply chain. So now that will drive both sort of the price at which I procure, and it will also drive how much I want to keep in reserves as a food company. Because that will give me a sense of what to do.

So that same sort of-- one model gets used in many different ways. So there's the model, and then there's the use case. And the use case of that model changes based on who you are and what type of organization you are. But the power in sort of what we do is unifying that decision making process, so people are working off of some baseline level of knowledge that allows them to have conversations that are somewhat aligned.

ANDY SERWER: Right, and so have there been companies that do this-- you mentioned you were an energy trader at Morgan Stanley. There are companies that do this for, say, oil and gas and for other kinds of commodities like silver and gold, precious metals, et cetera, et cetera, right? So but this is the first time it's really been done for agriculture? Or to this degree?

SARA MENKER: Yes, to this degree and at this level of automation, right? So that the power in what we do is-- and we say, you know, it's really about-- I always say the AI is only as good as the HU, which is the Human Intelligence behind it. And for us, it's about scaling Human Intelligence. And so what we did when we built the team was saying, how do we bring one or many of every kind of person that participates in the agricultural ecosystem?

That meant we brought in plant scientists and biologists and hydrologists, but then we bought in former hedge fund traders that traded agricultural products. We brought in people who built crushing plants and sugar refineries, and literally sort of got them to work side by side with world class engineers, and say, how do I automate that knowledge? How do I automate it? How do I scale? How do I-- how do we make that global? And how do we sort of rinse and repeat, rinse and repeat, right? Like, so that-- nobody's ever done that before.

ANDY SERWER: But you're finding lots of databases. I mean, that's the real key thing. So you're finding databases in different countries and different NGOs that track data as well and then integrating it all. So you must have a lot of computer science that you're bringing to bear here, right?

SARA MENKER: Absolutely, so we have a huge-- a huge part of our company is our engineering and data science organization, right? So we're ultimately a tech company. And but it is-- and I really do emphasize, though, the AI is only good as an HI because it's garbage in, garbage out, right? And so you have to make sure that you are trusted, that your models are trusted, that your data is trusted. And that part really requires human intelligence, especially in the early days.

ANDY SERWER: And how many people do you have working at Gro right now, Sara, and then also how does the business model work?

SARA MENKER: Yeah, so we have about 100 people. And we're going to be at least three times the size by the end of the year. So we're growing really fast. We just--

ANDY SERWER: Gro is growing.

SARA MENKER: Yes, Gro is growing, there you go. [LAUGHS]

ANDY SERWER: Is Gro an acronym, by the way? Or I see it's all caps. No, just Gro.

SARA MENKER: No, it's just Gro. It was my play on agro and growth, right?

ANDY SERWER: Got it.

SARA MENKER: How do we drive growth?

ANDY SERWER: Right.

SARA MENKER: And Gro is just a play on words. And so we're about 100 people, but growing really fast in a team. And how we work with companies in our business model is simple licensing model. So we have sort of three segments of customers we work with.

One segment of customers are corporates and financial institutions. So think of them as sort of the first segment that I mentioned, which is-- and it's a simple data licensing terminal C licensing model, where people buy subscriptions and they get access to different tiers of the product depending on, sort of, need.

The second is our sovereign business, where we work with governments. And there, we work much deeper in partnership around food security. And so how do you power food security decision-making for governments using a platform like this, right? And how do you think of National Reserve systems very differently? And so that is much more of a partnership-based model, where it's not just access to the data in the models, it's much more of an integrated solution that we provide, so we get very sort of deeply integrated.

The third is our capital markets business, where we are taking-- some of the models we have in the platform are a series of indices that we've built, so indices that measure very specific climate outcomes, so droughts, floods climate volatility. So we've created the VIX of climate. And so if you think equivalent in sort of equity land.

And what we're doing there is we're partnering with financial institutions to power climate as a whole new asset class and to think of how do we create financial instruments off of these indices that help us better manage the climate risk in our portfolios. And all of them are licensing.

ANDY SERWER: Right, but you can go there to your website and see a little bit of stuff, though, for free, right? If you're just a civilian.

SARA MENKER: Yeah. So we have-- and we're very much a mission-driven organization. We are very much about democratizing access. And so, we have a model that lets anybody sign up. And so we have lots of universities and NGOs that use our product. And we, as a company, also have an initiative internally where when we see specific, say, emergencies that we see emerge around the world that we feel like we can materially step in and add value, we just volunteer our time and our data scientists and help government solve for problem.

So last year, when we had a locust spread problem that emerged in Eastern Africa that was spreading to the Middle East and South Asia amidst a pandemic, that was going to be a very sort of large food security threat to a lot of countries that don't necessarily have the resources to sort of deploy a product like ours. And so we developed what we called our Locust Impact Toolkits, and we developed them for free. And these models basically predicted how locusts were going to spread, how much damage they were going to do. And we provided them to, I think over 300 NGOs.

ANDY SERWER: And speaking of threats, Sara, you've put out there that you think there is going to be food scarcity in the coming decades. And this is a critical issue. Why is that?

SARA MENKER: Well, so I think-- well, some of it we're already facing right now, unfortunately, right? And last year, we-- COVID exposed how fragile our food systems really are, how they're built on very short-term thinking, right? So the breaks that we saw in the supply chains were a function of the fact that, you know, if you think about food and agriculture, it's an industry that's been around for over 12,000 years.

However, if I find oil in the ground, and I want to go sell it 20 years forward, I can do that. If I want-- most food transactions are still done on a week to week, month to month, day to day basis. And so that means that something goes wrong, the system breaks. And so, you know, a huge part of the crisis we were warning against was going to-- was driven by the fact that it is a global market.

And so a global market means that you need-- you have sort of supply centers and you have demand centers. And if there's these deep imbalances that are built, you could have-- you know, that the areas where you have the largest growth and sort of demand could have a complete mismatch from the areas where you have the largest growth in supply or have the largest pools of supply. And the cost, right? So it's a function of trade, it's a function of demand growth, and then it's a function of cost.

And what we're seeing happening this year-- and it's a story that no one's really talking a lot about it. I think it's going to only manifest itself more and more, is that the local cost of food in so many economies has skyrocketed over the past year. Because, again, you have net exporting countries like the US and Brazil, Argentina, or Russia.

But outside of the US, every one of these net exporting countries are having currency crises due to COVID, right, and very weak macroeconomic structures. And what that is leading their governments to do is to start curbing exports as a mechanism for protecting local inflation because food inflation is your worst form of inflation.

And so, in a world where you have commodity prices and food prices that are going up, which is what's happened over the past year because of demand coming out of China-- Chinese demand hasn't slowed down-- you have countries that are exporting countries with currencies that are down 20%, which means that if your-- you know, the price of a product is up 15%, and then your local currency is down 20%, your, you know-- inflation is just skyrocketing. So you are having a lot of countries now curb, sort of, exports and lead to protectionist policies that I think can lead to all sorts of effects.

ANDY SERWER: What countries are you referring to, Sara?

SARA MENKER: So Russia, Ukraine. These are very large consequential economies that also play massive exporting roles-- and South American countries like Brazil and Argentina, right? So big countries play a very big role in agriculture, but actually play a large role in, like, global sort of economic dynamics as well.

ANDY SERWER: One thing you didn't mention is the threat. And I know your concern about this as well, is climate change. How does that factor into your thinking?

SARA MENKER: Well, it factors in a huge amount, right? So if you think of how we ended up with-- our platform currently ingests over 40,000 different data sources from around the world. Think of it as data that comes from public agencies, NGOs, companies that we partner with and license their data and we distribute their data, so it's a wide range, and then data we generate ourselves.

A huge amount of understanding agriculture means understanding your environment and ecology. Like, if you think of sort of the climate change conversation, there's this natural tension between ecology and economy, right? There's this tension. Like, economic growth has come at the cost of ecological decline.

And agriculture kind of sits in the middle of the two because agricultural demand is very much a function of economic growth and economy. And agriculture supply is very much about ecology. And because of that, our platform had tons of economic data and tons of climate data just naturally in it. And so we were able to sort of model and look at the role that climate change has in agricultural supply and then extend that to many, many other industries, everything from infrastructure to mining to utilities, et cetera.

And one of the things that we saw in a year like last year, the US alone experienced wildfires in the West Coast, experienced floods in the early part of the season, then drought, then, like, unprecedented derecho winds, in the same little microcosm of the Midwest, right? And so you're having multiple types of disruptions happening much faster than they ever did before.

And that's going to impact industry in sort of an unprecedented rate. And it is already, right? The number of billion dollar plus climate disasters that the US had last year was 22. It had $22 billion plus climate-related disasters. This is everything from hurricanes to droughts to wildfires to storms and whatnot.

Now, if you think of the trajectory in-- if you look at the last 40 years, the last five years have had record numbers year after year. The second record after the 22 we had last year is 17. The pace at which this is growing is just huge. And this is happening everywhere in the world.

ANDY SERWER: Does that all just mean higher prices for food? Along with other things, potentially, but.

SARA MENKER: It means-- it definitely can be tied to sort of food inflation, right? Because uncertainty means that you're going to drive-- because food inflation is driven by two things. One is supply and demand dynamics. One is if you constantly have supply disruptions, then food prices go up. Last year, we had supply and demand disruptions, which just caused huge skyrocketing of prices. And tons of disruptions mean more uncertainty, and more uncertainty means more protectionism, right? So you can also just by default drive more of that.

ANDY SERWER: I wanted-- that's a good segue, protectionism, because I want to ask about politics next and how that factors in. We have a changing of the guard here in the United States. I want to ask you the implications about that. But the bigger trend is towards protectionism around the world. Joe Biden notwithstanding, obviously, you can go around the whole globe and just point to nationalistic leaders. So, A, US, and B, global. What's the environment?

SARA MENKER: Yeah, so I mean, I think with the US with the changing of the guard, obviously, a very big change is around climate, right? Reentering the Paris Agreement, leading up to COP26, which is happening in November and December of this year. And, you know, the role sort of that the US is going to play and the prominent stage the US is going to take in sort of the climate change conversations, which are economic discussions and are conversations about tradeoffs that every country is going to have to make to sort of move to a world of net zero.

So I would say that that probably is the most consequential change as it sort of relates to the world that I live in, which is climate and agriculture. On the food side-- and just in general, I would say that, again, I always remind people food security is national security. Like, it really is. And we always forget it until there's something that reminds us, right? And last time, it was the Arab Spring.

And I-- like, watching sort of countries like Russia and Ukraine clamp down on exports-- I mean, think about it. You basically have a currency crisis. The way you solve for a currency crisis is by getting more foreign exchange reserves. You are sacrificing foreign exchange reserves by curbing exports because it is still more important to make sure your people are fed at the right price than it is to get more foreign exchange reserves in the country. And that's literally the world we're living in today, in many, many parts of the world. And so, it's-- I think there's a lot we're going to be on the lookout for this year.

ANDY SERWER: A quick follow-up question, Sara-- Arab Spring and food security? I missed that connection

SARA MENKER: Oh, Arab Spring, food security, it was-- a huge amount of it was driven by the price of bread and wheat. Right? And when you have large populations that can't afford the basics.

ANDY SERWER: Right, right. Oh, I thought it was a cause of the Arab Spring, rather than an effect of the Arab Spring.

SARA MENKER: Yeah, cause. Exactly.

ANDY SERWER: Let me turn and ask you about you and how you got to this place. And you were born and raised in Ethiopia. And tell us about your journey.

SARA MENKER: Yeah, so I was born and raised in Ethiopia. I came to the US for college, and I ended up on Wall Street after graduating. And so I-- like I said, I worked at Morgan Stanley, started there in commodities, was always a commodities person.

So I've only had two jobs in my life. I worked at Morgan Stanley, and I was CEO of my own company and sort of grew within Morgan Stanley and became an options trader, which is not a typical path. But it was fun. And at some point, I realized that I was good at it, but I didn't love it, which is when I left and then started this sort of new journey.

ANDY SERWER: But when you were growing up, were you connected to agriculture in any way? Did you live in a farm? Or what is it about-- how did you get connected to agriculture, I guess?

SARA MENKER: Well, you know, again, food security, national security, right? One is, I was raised in Ethiopia during, like, the famine that everybody still had associated Ethiopia with. That was my reality growing up, right? And that was sort of my perspective of what disaster looks like was driven by a communist government and country that rationed everything from fuel to food.

And the '08, '09 financial crisis happened. I had a lot of colleagues and a lot of people were like, oh my gosh, this is the end of the world. And I'm like, no, I kind of know what the world looks like. Like, Morgan Stanley stock going to zero sucks, but it's not the end of the world. Like, [LAUGHS] it's-- you know.

And that was actually what led me to start thinking about food security because I was like, well, hold on a second. If the world's coming to an end, I just want to eat. Like, I keep it basic. And it was sort of that that drove me down this journey of asking a lot of questions. And four years of asking why, I eventually realized I was so much more passionate asking these why's, but also realizing how broken our system was, that it was time for me to sort of go to the next adventure.

ANDY SERWER: There are not so many women of color who are leading well-funded startups. What were some barriers that you had? And how do we address them?

SARA MENKER: You know, I've been-- since we announced our series B fundraise, there have been-- I always say one of the most interesting things is when people take a headline or an article, and then they rewrite the story through a different lens. And it's been amazing to see the number of lenses that our story has been written by, right? Meaning there's the Africa lens. There was the female lens. There's the African-American lens.

There's the-- you know, there's multiple sort of lenses by which you look at it, and the stats suck for all of them, right? Like, you can't-- like, in a world where, you know, hundreds of millions of dollars of financings by companies get announced every day, to be the first of every kind is very bizarre to me in the sense that it's almost forced me to think about it differently than I had.

I always say that I think I was particularly lucky in that I had a successful career before I started the company. So I could afford to take a lot more personal risk in starting Gro. And I also came with a network of people that I left on very good terms. So the first people who funded my company were actually not VCs. The first people who funded the company for me were my former bosses and former clients.

And so the running joke is I never left Morgan Stanley because all of my old colleagues are investors in the company and continued to sort of support me. And so, I would like to see that change because half the struggle is, like, starting, right? And being able to sort of make those phone calls and get that initial financing and getting people that believe in you. And so, how do you change that? Like, it's hard. It's just hard. And I think you do by just maybe setting new examples, right?

Like, I have generally been against sort of doing a lot of press. But this has also made me realize that, like, people seeing you see themselves in-- you know, like, they see themselves in you in one way or another. And therefore, that makes it possible. So by virtue of telling more of these stories, I think we also just change some of the narrative around it.

ANDY SERWER: Gro is private right now, Sara. Do you have plans to do an IPO someday? Or where do you see this company in five years?

SARA MENKER: You know, many people ask me that question. I am much more focused on building the best business possible, meaning independence matters a lot to me. I'm not building this company to sell it. It is a company that we believe can be sort of a new industry standard, and we can be a neutral platform that really is-- like I said, if you are building infrastructure to change an industry you have to remain neutral. You have to work with all parties. You have to take in all perspectives.

And so I care a lot more about that versus sort of what's the end outcome. So I know the end outcome is not selling it to anybody. And then, from there, it's like you've got to just leave the rest to focusing on sort of growth and brand recognition and being trusted as an industry source.

ANDY SERWER: And last question, what are your personal goals then? What do you hope to achieve in your lifetime, Sara? Big questions.

SARA MENKER: Gosh, like, [LAUGHS] what do I hope to achieve in my lifetime? Building Gro the right way, because I think if we do it, then we solve for the very problem I left my job for, which is, how do we solve for food security? Like, you don't solve and you don't fix a system you don't understand. And if we become the mechanism for understanding, I think we stand a chance as a world to finally solve this problem that we've been trying to solve since the 1970s.

Like, to me, that was the most baffling thing, which is we've been saying, we can solve for food security since the 1970s, like literally when Henry Kissinger coined the term. And we still are talking about it. And we haven't changed it. So, like, I guess, in my lifetime is sort of that how do we become that mechanism, and how do we drive that change? Like, I feel like I'm doing my life's work in a very weird, convoluted way, right? [LAUGHS]

ANDY SERWER: Nothing wrong with that. That sounds great. OK, Sara Menker, CEO and founder of Gro Intelligence, thank you so much for your time.

SARA MENKER: Thank you, Andy.

ANDY SERWER: You've been watching "Influencers." I'm Andy Serwer. We'll see you next time.