Name: Insights: How Big Data Can Help Agriculture Respond To Climate Change
Uploaded: 2020-03-25
Duration: 6 min 26 s
Description: Land O’Lakes CEO Beth Ford is joined by Sara Menker, Gro Intelligence CEO, to discuss how tech is helping farmers work more efficiently and battle climate change. (July 2019)

[MUSIC PLAYING] BETH KOWITT: What kind of data are you collecting from those farmers? And how are they using it? Maybe you could give an example of that. BETH FORD: Yeah, we have applied research plots, for instance, where we're working with farmers to help them understand how they should plant, what kinds of things they should plant, different soil types. We also use predictive models. And we focus specifically on in-season technology or in-season models. And I think that that's really important this year. This year, many of you have seen we've had dramatic issues with weather across the country. Many farmers couldn't get planted. And that means that they have a huge issue with a gap in production. And more importantly, these farmers have been in a situation for multiple years where they have had low commodity prices. They have had struggles in the rural communities. They have had struggles on the acre. So these predictive models, this data that we're capturing-- and we're capturing farmer data, what they planted, what soil types, what their processes are on the acre. And we use that in conjunction with an alignment with our applied research platform to provide a model for them for what they may want to do, what they want to do in season. Do you want to apply some kind of a spray? Do you have an issue? Do we need to get a soil sample? Do we see a disease state? And so this model, we're using all sorts of imagery, analytics. But their data is their data. We capture their data in a data silo. We pair it with our applied research plots. We use predictive models. We use satellite technology. We use drone information. Many of these things that allow us to advantage a farmer. And never has that been more important in the United States, especially in this year, where we have had dramatic issues-- drastic issues with weather. BETH KOWITT: OK. Are farmers wary to give you their data? BETH FORD: You know, it's a great question. You know, nobody-- thankfully, we are a co-op. We are farmer owned. And the data is their data. And we make it very clear to them, while we will capture their data, we will not use their data unless we have permission to use their data. And we may use it from a modeling perspective. But they own their data. Of course they're reluctant, right? It's like all of us. Well, what are you going to do with the data? What kind of data? We've been using it and leveraging it by the way as well on sustainable production. We have a Truterra insight model that allows us to work with a farmer to improve their sustainable production. So are they wary? Yes. Do they understand the value of it? Yes. And we've been working with them for many, many years. And so we have a significant amount of data. And we make it clear to them that they own their data. BETH KOWITT: OK. So Sara, you have an interesting model. You work with everybody but the farmer. So explain why that is. That would be really helpful, I think. SARA MENKER: Yeah, well, we work with everyone but the farmer. But we definitely work for the farmer in the sense that the reason we exist as a company as grow intelligence is to make the system around the farm a lot more efficient. So what we do is we take large, disparate data sets that have anything to do with agriculture, that have been captured anywhere in the world. We transform and translate all of that data, normalize it, and essentially build a series of predictive models that let us you know forecast anything from supply to demand to price for any agricultural commodity anywhere in the world. One of the things that we have seen in the past couple of years is just the sheer volatility of climate events that occur everywhere in the world. So we're talking about floods in the US. But southern Africa, this year, had one of the worst droughts on record, right? And so you have these extreme shifts. So what it enables us to do is that we actually can look at a combination of satellite imagery with data that comes out of national statistical agencies to model real time-- model and build out real time indices on whether it's drought or flood. An index that, globally-- that lets people to start manage that risk. The thing is, we're not going to necessarily get away from the fact that it's happening right now, because we're just being confronted with it. But we can manage it better. That means if you are a food and beverage company or you're a retailer, you have massive supply chain risk that's tied to the way that you procure. So California drought, you know, 70% leafy greens come from one tiny portion of California. The next time there's a drought, where do you diversify that risk from? You can actually structure of financial instruments that let you do that and manage that risk, so you as a company can get paid out on a policy that then lets you use that money to go and essentially purchase product elsewhere in the world for potentially much higher prices. Because that's what happens, right? Markets react to a decline in supply by increasing price. And organizations need to be positioned to be able to react to that and manage that, so the consumer doesn't also suffer as a result of it. And so this is what I mean by that there needs to be a real re-architecting of the financial system that we have. And I think data can play a massive role in enabling that communication across organizations and the transfer of risk across organizations. BETH FORD: You know, to add on that, one of the things we're trying to do-- because change will happen in terms of building a robust and resilient food chain at the farm level. And so we've invested in something called the our Truterra insights engine, where we're working on the acre with the farmer. We're using their data. And we're using-- it's a over a trillion data points. And what we're trying to do is help a farmer understand what investment they can make to improve sustainable production on their farm while improving their profitability, so variable rate application of fertilizers or stabilizers or no-till or things like that that will improve the resilience of the acre on the farm on which they're working on, but at the same time, improve profitability. And I agree. What we need to understand is what are the incentive structures that we want to put in place to incentivize a farmer who wants to continue to improve production on their farm but at the same time is trying to make sure that they can be profitable in order to do that? So insights and data and analytics will help us. And at the same time, we're working with our master agronomists very directly with the farmer, with their data, to help them understand how they can improve work and production on their farm. [SOUND EFFECTS]

Insights: How Big Data Can Help Agriculture Respond To Climate Change

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Farmers work more efficiently and battle climate change.

How Big Data Can Help Agriculture Respond To Climate Change

Land O’Lakes CEO Beth Ford is joined by Sara Menker, Gro Intelligence CEO, to discuss how tech is helping farmers work more efficiently and battle climate change. (July 2019)

What kind of data are you collecting from those farmers and how are they using it? Maybe could give an example of that. Yeah, we have applied research plots, for instance, where we're working with farmers to help them understand how they should plant, what kinds of things planned different soil types. We also use predictive models, and we focus specifically on in season technology in season models. And I think that that's really important this year. This year, many of you have seen we've had dramatic issues with weather across the country. Many farmers couldn't get planted, and that means that they have a huge issue. We have a gap in production, and more importantly, these farmers have been in a situation for multiple years where they have had low commodity prices. They have had struggles in the rural community. They have had struggles on the acre. So these predictive models these the's, this data that we're capturing and we're capturing farmer data, what they planted, what soil types, what their processes are on the acre and we use that in conjunction with in alignment with our research, provide a model for them for what they may want to do what they want to do in season. Do you want to apply some kind of a spray? Do you have on issue? Do we need to get a soil sample? We see a disease state on dhe. So this model, we're using all sorts of imagery analytics, but their data Is there data? We captured their data in a data silo. We pair it with our applied research predictive models. We use satellite technology. We have drone information, many of these things that allow us to advantage. Ah, farmer. And never has that been more important in the United States of specialists in this year where we have had dramatic issues, drastic issues with with weather, our farmers wary to give you their data. You know, it's a great question. Nobody. Thankfully, we are co op. We are farmer owned and the data is there data and we make it very clear to them. While we will capture their day that we will not use their data unless we have permission to use their data. We need from a modeling perspective, but they own their data. Of course they're reluctant, right? It's like all of us. So what? You gonna do with the data? What kind of data? We've been using it in leveraging and by the way as well. On a sustainable production, we have a true terra Insight model that allows us to work with a farmer to improve their sustainable production. So are they wearing? Yes. Do they understand the value of it? Yes. And we've been working with them for many, many years. So we have a significant amount of data, and we make it clear to them that they own their data. Okay, Sarah, you have an interesting model. You work with everybody but the farmer, so explain why that is. That would be really helpful, I think. Yeah, well, we worked with everyone but the farmer, but we definitely work for the farmer in the sense that the reason we exist is a company, as grow intelligence is to, you know, make the system around the farm a lot more efficient. So what we do is we take large, disparate data sets that have anything to do with agriculture that have been captured anywhere in the world. We transform and translate all of that data, normalize it, and essentially build a series of predictive models that let us, you know, forecast anything from supply to demand to price for any agriculture commodity anywhere in the world. One of the things that we have seen, you know, the past couple of years is just the sheer volatility of climate events that occur everywhere in the world. So we're talking about floods in the US, but Southern Africa this year had one of the worst droughts on record, right? And so you have these extreme shift. So what it enables us to do is that we actually can look at that. A combination of satellite imagery with data that comes out of national statistical agencies to model riel time in a model and build out real time indices on whether it's drought or flood, an index that globally that lets people to start manage that risk, that the thing is, we're not going to necessarily get away from the fact that it's happening right now because we're just being confronted with it. But we can manage it better. That means if you are a food and beverage company or you're a retailer, you have massive supply chain risk. That's tied to the way that you procured California drought. You know 70% of leafy greens come from one tiny portion of California. The next time there's a drought, where do you diversify that risk from? You can actually structure financial instruments that let you do that and manage that risk. You as a company can get paid out on a policy that then let's use that money to go and essentially purchase product elsewhere in the world for potentially much higher prices. Because that's what happens, right? Markets react to a decline in supply by increasing price, and organizations need to be positioned to be able to react to that. I managed that so the consumer doesn't also suffer as a result of it, right? And so this is what I mean by you know, that there needs to be really kind of a really architect ing of the financial system that we have. And I think data complete a massive role in enabling that communication across organizations and the test for risk across organization. You know, to add on that one of the things we're trying to do because change will happen in terms of building a robust and resilient food chain at the farm level. And so we've invested in something called a true terror inside mention where we're working on the acre with the farmer were using their data, and we're using it over a trillion data points. And what we're trying to do was help a farmer understand what investment they could make to improve sustainable production on their farm while improving their profitability. So variable rate application of fertilizers or, um, stabilizers or no till, or things like that that will improve the resilience off of the acre on the farm in which they're working on but at the same time improve profitability. And I agree. What we need to understand is what is the incentive structures that we want to put in place to incentivize a farmer who wants to continue to improve production on their farm but at the same time is trying to make sure that they could be profitable in order to do that, so insights and data and analytics will help us. At the same time, we're working with our master of Rana's very directly with the farmer with their data to help them understand how they can improve work on and production on their farm