Watch Out for the Tail: Risk and Uncertainty in Agriculture

Risk has always been part of farming and agribusiness — but the way we understand and manage it has transformed dramatically over the past 60 years.

Today, hosts Sarah Mock and Trey Malone trace that evolution, from the irrational exuberance of 1970s American agriculture through the devastating farm financial crisis of the 1980s, and into today's high-stakes landscape of trade wars, AI disruption, and geopolitical uncertainty. Along the way, they dig into practical strategies that farmers and agribusiness managers can use right now — not just to survive the next crisis, but to find opportunity in it.

You'll walk away with a better understanding of:

• The difference between quantifiable risk (the thunderstorm you can forecast) and uncertainty (the tornado you can't) 
• How to use probabilistic thinking to score and rank the risks your business faces, and how to create a menu of options to help you react to both crises and opportunities
• And what all of this means for ag today, as the sector faces a Global Policy Uncertainty Index that has gone from 100 to 8,000

We'll go together on a journey through the history of risk in agriculture and the tools that have been built to help farmers manage everything from hailstorms to market downturns. And we'll explore a simple, practical framework for scoring your own risks — so that when the next crisis hits, you won't be making decisions in a panic. 

Agribusiness Blueprint is brought to you by Purdue Center for Food and Agricultural Business: agribusiness.purdue.edu. To learn more, follow, The Center for Food and Agribusiness on LinkedIn

Agribusiness Blueprint is supported in part by the USDA National Institute of Food and Agriculture (NIFA), Award No. 2022-68006-36433.

Transcript

SPEAKER_00 0:00

Talk to just about any farmer about risk, and the first word they'll probably mention is weather. From freak cold snaps to softball-sized hail to bin-flattening tornadoes, extreme weather gets the most news coverage, but the weather that many farmers remember best is a lot more ordinary. The years-long droughts, the washout rains, and the devastating duratios. But today, there's a lot more for farmers and agribusiness people to worry about than just weather. There's trade disputes, new technology, supply chain disruptions, policy changes, war. And just like today's weather, these threats are growing more severe and more unpredictable. Most days, uncertainty feels like agriculture's catchphrase. It just is everything.

SPEAKER_03 0:49

I mean agriculture. The global policy uncertainty index usually hovers around 100. The last I looked, it was at 8,000.

SPEAKER_00 0:58

So cool.

SPEAKER_03 1:01

Yeah, no. Mike was writing about uncertainty in the 2000s. That was the peak uncertainty. Oh no. This is a hold my beer level.

SPEAKER_04 1:11

That's great. That's right. It makes it a bit scary.

SPEAKER_00 1:17

Just like black clouds on the horizon, risk and uncertainty are bearing down on the farm economy. But luckily, we're not empty-handed. There are tools available to manage what's coming. And you can find them here on Agribusiness Blueprint. This is Agribusiness Blueprint, a limited series podcast about American agriculture's most impossible challenges and the agribusiness leaders who solved them. You're here with me, independent ag journalist Sarah Mock, and my co-host Trey Malone, Associate Professor of Agricultural Economics, and the Bulgy Chair at Purdue University. And today, we're talking about risk. Risk and uncertainty are nothing new in agriculture, but the way we understand and manage them has changed a lot over the last 60 years. That change was powered by advances in risk forecasting and motivated by the 1980s farm financial crisis. Since then, we've created many tools to mitigate risk, and today, those tools are being adapted to help operators deal with the likes of weather and marketing risks and unpredictable black swan events that seem to be becoming more frequent all the time. And today's conversation isn't just theoretical. We're going to dig into the details on strategies you can adopt right now to not only help you avoid the worst of the next crisis, but to set you up to seize the next unexpected opportunity coming down the pike. But before we can successfully wield today's risk and uncertainty management tools, we have to learn how and why they were created in the first place. To help us tackle that history, there's no one better than Mike Bolgi, the man who introduced agriculture to risk in the first place.

SPEAKER_03 3:18

At about 1972, 1973, all of a sudden it became one of the most popular words in the entire literature.

SPEAKER_00 3:25

Now, for anyone who knows anything about agriculture, you're probably thinking, how could this possibly be true? There was absolutely risk in agriculture before 1972. So why wasn't anyone talking about it? Mike has a theory. Last episode, we talked about the need for accurate measurements of movement to identify waste in the lean framework. And what Mike is talking about here is not so different. See, prior to the 1970s, researchers didn't have enough good data about risk to help people actually make decisions. They didn't have the right information to rigorously defend what risks might look like, when they're most likely to occur, or why. In other words, prior to the 1970s, we didn't have what we needed to forecast risk very well. But by the 1970s, our risk forecasting skills were about on par with our weather forecasting skills, which offers a good metaphor for how this all worked.

SPEAKER_04 4:33

When you had weather forecasting in the past, you'd say, well, weather's going to be good or not so good, high chance of rain, low chance of rain. We had all sorts of generic terms, but now weather forecasts have been very specific in terms of probabilities associated with rain in particular areas at particular times of the day. And so farmers now and agribusiness people really, I think, understand better. They change their behavior when they say, well, there's a 40% chance of rain versus a 10% chance of rain.

SPEAKER_00 5:06

This is why the 1970s was such an important era, because agribusiness researchers were finally accumulating enough knowledge and data to move from making generic forecasts like the price of corn might go up sometime soon, to forecasts like there's a 35% chance that corn prices will go up by 50 cents before the end of the year. And as Mike suggests, it's much easier to make a thoughtful decision about selling corn today based on that second forecast than the first. This was cutting-edge information in the 1970s. And the funny thing is, a lot of people weren't that interested in it. Mostly because they didn't need to be. After all, the 1970s were a golden era in American agriculture. Commodity prices were high, land prices were high, and they were even higher in places where recently discovered oil and gas deposits were helping farmers strike it rich. Everyone in agriculture seemed to be making money, and more and more people were setting their sights even beyond American markets. Looking to the billions of hungry mouths around the world who seemed likely to become buyers of American crops. In this era, the biggest risk on most people's minds was the risk of not dreaming big enough and missing out on this huge opportunity. Few examples capture the irrational exuberance of this era, quite like the lending practices of one Oklahoma financial institution called Penn Square Bank.

SPEAKER_03 6:38

That bank, when people would come to get a loan, a farmer would come get a loan to drill an oil well or whatever. That bank would say, Well, I know you asked for a million dollars, but we want to give you five. And then they would just give them money. And so at that point in time in Oklahoma, if you were a farmer interested in the oil and gas space, you could get a loan to buy a helicopter so that you could fly to Dallas for lunch. There are stories about people putting in private zoos. There are stories about these guys going to the top of buildings in Tulsa and throwing hundred dollar bills off the top of the building and shooting at them with guns.

SPEAKER_00 7:14

Penn Square Bank was an extreme example, but it wasn't as much of an outlier as it might seem. And it can be genuinely hard to wrap our minds around the amount of inflation that was occurring in this era as a result of this extreme lending. One telling figure, between 1970 and 1979, farmland values in some parts of Iowa rose by 10 times, from an average of around $200 an acre at the start of the decade to more than $2,000 an acre by the end of it. Thinking about these anecdotes feels ominous today. Of course, this level of exuberance couldn't last. But one of the critical challenges of the late 1970s and early 1980s was that no one was really paying attention to the big picture, to those storm clouds on the horizon, and this lack of awareness and thus lack of preparation meant that when the crisis arrived, it affected a lot more than just a few farmers who wanted to dig some oil wells.

SPEAKER_03 8:12

Did everybody put their eggs in the same basket at once? So all of the risks were correlated with each other in a way that created the systemic risk that would have been undervalued at the individual level. So these dollars kept flowing in, and it would have been fine had one of the farmers who were in oil and gas gone under whatever. But when the whole market shifted, they all went under at the same time.

SPEAKER_00 8:40

This was the risk that too few were paying attention to. Banks were aware of the individual risks, that a given oil well might not yield or that a single farmer might not repay their loan. But they hadn't really considered the systemic risk, that the price of oil might crash in the early 1980s, making all of this oil exploration unprofitable at the same time. In other words, they understood that each of these loans were delicate little eggs, but they hadn't reckoned with the risk that the basket they'd put them in was about to get hit with the baseball bat of international oil markets. A rash of farmers defaulting on loans was just the first wave of this crisis. Phase two involved Penn Square Bank, who'd lent so liberally for wildcat well drilling in Oklahoma, becoming insolvent. And then an even bigger bank, Continental Illinois National Bank, then the seventh largest in the country, which had lended hundreds of millions of dollars to Penn Square, was dragged towards failure as well. As the 1980s rolled on, the fallout from this and other simultaneous financial calamities came down on farms all at once. Land prices fell, leaving farmers all over the country overleveraged, at the same time that interest rates went sky high. By mid-decade, it wasn't just farmers who'd invested in energy projects that were hurting, it was farmers writ large who were struggling with a crisis on a scale that no one was expecting. With rural communities reeling from the impact of the crisis, agricultural leaders and lawmakers wanted to take action. It was clear that helping farmers better understand risk and take advantage of the latest risk management tools that had emerged alongside research like Mike Bolgi's could make the difference between farm survival and bankruptcy. But there was another problem. Communicating with farmers at this time was really, really hard.

SPEAKER_03 10:34

This isn't just the days before Google. This is the days before long-distance phone calls. There was a really famous program at Michigan State that was pioneering at the time called Telfarm. It still exists. That program was how to use telephones on the farm. We are not that far away from a time where like information could not spread quickly.

SPEAKER_00 10:57

But despite these limitations, U.S. farmers did have one powerful resource to lean on, the Agricultural Extension System. With agents on the ground in every county in America, the Extension Network sprang into action in the 1980s. Their goal? To help farmers understand the risks they were facing and help them find ways to manage that risk. One of the best-known extension agents of the era in the upper Midwest was a fresh-faced young graduate by the name of Jim Hilker.

SPEAKER_02 11:25

We put together these teams where we would go out at times to individual farms and put together a whole plan for them during this farm crisis.

SPEAKER_00 11:36

What Jim was doing at Michigan State University during this era was twofold. In some cases, he and his team were visiting farms and helping build custom farm management plans, but they were also teaching crash courses to hundreds of farmers and things like record keeping, commodity marketing, and risk management tools like federal farm programs, topics that most farmers were familiar with, but few had mastered.

SPEAKER_02 12:00

So they understood production risk. At the time there was crop insurance, not a lot used it, but a lot of times you could use the practical tools of having having three or four crops spreading your risk. Because you don't always have a bad corn yield and a bad soybean yield or a bad wheat yield. But the price risk, too many people were teaching them that you could beat the market. The average person can't beat the market.

SPEAKER_00 12:28

In Jim's experience, this was standard at the time. Farmers knew about the risk of losing a crop, and so they diversified their crop mix to reduce that risk. But price risk, the risk that the purchase price of a crop or input might suddenly change, that was different. To Jim, too many farmers in this era believed, like confident gamblers everywhere do, that they could beat the house, that they were going to be the lucky ones, and that if they weren't, well, there was nothing they could really have done about it. But one of Jim's key messages to farmers was that there are ways to minimize price risk, not by trying to predict the future and beat the market, but by using tools built specifically to make the future more predictable.

SPEAKER_02 13:12

There are forward contracts. I can lock in a price today and a little over later, whether it's something stored in my bin or whether it's something I'm going to deliver next year. The principle of hedging was out there. They could do it, but it was hard for them to do. Because then you have to have that extra fund and be able to work with a banker to have that happen.

SPEAKER_00 13:33

Another reason that adopting these risk management tools was difficult for farmers in the 1980s was simply because the tools and the problems they solved felt so new. In earlier decades, selling crops had been simpler. Farmers took their harvest to the local elevator and in return got a check that, at the very least, usually covered their bills. But the 1980s was the first crisis in a generation during which suddenly the spot price at the local elevator did not cover the cost of growing the crop. Again, Jim taught that risk management tools could help address this problem. But to use them successfully, farmers needed to know something they hadn't before. They needed to understand what the prices they were seeing at the elevator and the ones they were hearing about on the news were signaling about risk.

SPEAKER_02 14:24

There's several things going on in the commodity price. There's the futures price that the price the farmers getting is very closely tied to, but there's a basis, the spread between the two. And it's the interaction between those two, futures and basis, that gives you an awful lot of information on your next decision. Now, the basis tells you a lot of things. The basis tells you should you store it, should you not store it? You can be just in futures. You can store your commodity without being in futures. Then you you can hedge your crop. That's when you are both in the futures market and in the cash market. And it's a combination of the gains and losses because you tend to gain in one and lose the other that locks in this price. But you have to understand the basis in order to know whether you should hedge or you shouldn't hedge. And that information's there.

SPEAKER_00 15:21

Now, Jim is speedrunning here through material that could easily fill up a whole podcast of its own. But the takeaway is this for farmers in this era, it was possible to grow and sell a crop whose price was constantly changing and to do it profitably without putting the farm on the line. But to do it required farmers to learn a brand new language and to understand things like what the spread between the basis and future price was signaling about present and future demand and therefore risk. In other words, farmers could determine how likely the price was to go up or down in a given time period and by how much. By the 1980s, these weather forecasts like price predictions were possible to glean even from public information. If, of course, you understood the language of price and risk. But the challenge was, most farmers were learning in real time. From Jim's perspective, there was a reason why farmers were arriving late to the game here. It's because others in the industry were invested in them not understanding.

SPEAKER_02 16:24

Elevators didn't want farmers to understand it. I was given a marketing meeting at an elevator, and the elevator owner, no, no, base it's not important. Base is not important. Didn't let me talk. I ended up, he couldn't kick me out. I told him he was wrong and told him why he was wrong. Farmers need to know this information. Now, why did was that that's how elevators make money? They still do today, they're still gonna understand the basis better than farmers. And then there was a critical change that came along in the later 80s and really grew in the 90s.

SPEAKER_03 17:02

What's that?

SPEAKER_02 17:03

Anderson's the grain company. They decided okay, they were big, but they weren't the Cargills. And they're made a critical decision. And if my producers do better, I'm gonna do better. So they decided to have something called a hedge to arrive. Now, what's the problem with a hedge? If prices go up, you owe the futures money, but you make money on commodities. Anderson said, We're gonna do something they happen to call it a hedge to arrive. We will handle that money transaction, but you're locked into delivering to us. So now farmers could actually use a hedge and you're gonna pay for all your storage plus an extra 20 cents a bushel. Well, when prices are 240, 20 cents is your profit. Okay, whether prices go up or down. What I'm telling you here wasn't taught in a whole lot of places across the country.

SPEAKER_00 17:58

Anderson's new focus on helping farmers manage their price risk was indicative of the sea change in the agricultural industry that emerged from the 1980s crisis. Farmers that survived this era were no longer confident that they could beat the market, nor were they confident that the price at the elevator would reliably cover their costs. Plus, the surviving farmers were those who were the most hard-nosed in their pursuit of every penny per bushel they could get. And most found that the best strategy to achieve that was not to bet against the house, but to ruthlessly limit, transfer, or manage their downside price risk with any and every tool they could find. This is the history that shapes the way we understand and manage risk today. In the 1970s and 80s, danger lurked in the gaps in our knowledge and data and in our inability to access and share information quickly and efficiently. Since then, we've made huge strides on both those fronts. And today, farmers and their lenders have near instant access to one another and to up to the second information about prices, productivity, and supply and demand in every corner of the world. So there's no risk left in the system, right? Right? Despite the fire hose of data and information we have at our fingertips today, we still have our hands full dealing with risks. That's in part because of all the new information and interconnectivity, which has given us an increased awareness of the sheer scale of risks that could impact us, and it's actually increased agribusiness's exposure to risks from beyond our sector. The bad news is the tools we created and learned in the 1980s and 90s to manage that risk are not really enough to protect us anymore. But the good news is the principles that we learned back then are still helping us develop new tools to help us confront this growing raft of risk and uncertainties. So, how are these tools shaping up? That's after the break. This episode of Agribusiness Blueprint is brought to you by Purdue University's Center for Food and Agricultural Business. This year marks the center's 40th anniversary, and its mission remains the same: connecting evidence-based insights with the decisions agribusiness leaders make every day. From strategy and marketing to sales, finance, and risk management, the center helps organizations and professionals navigate what makes agribusiness fundamentally different. Learn more about the center's programs and research at agribusiness.purdue.edu. Now, back to the show. So I think it's safe to say that over the course of the last 60 years, we've learned a lot and we've gotten both smarter and savvier about how we manage risk in agriculture. It can also seem like over that same period, the risks that our industry faces have grown and evolved to match our skill. But that might not actually be true. We may be experiencing a kind of selection bias. In other words, we've minimized a lot of avoidable crises, so the unavoidable crises stand out more starkly. Or to really belabor my weather analogy here, now that we carry our umbrellas more often, we don't get soaked in as many thunderstorms. And so when a hail storm does rip through our umbrella's fabric, it's all the more devastating because we thought we were protected. The fact that we even can know this is a testament to our modern ability to track, quantify, and analyze the risks we're currently facing. This is the continuation of the work that Michael Bolgi started half a century ago. And today it's moved well beyond the early days of price forecasting and into a much more complete understanding of both possibilities and probabilities of any given outcome.

SPEAKER_04 21:51

Increasingly, now we focus on the distribution, and basically we become much more aware that the details. Really count. And it's not only that distribution that is important, but we also need to know the shape of that distribution. So do we have a high probability of getting very high prices? Or is it, on the other hand, skewed in the other direction where we're in a position where we're going to have very low course prices and have that for a long period of time?

SPEAKER_00 22:21

To explain what Mike means about the distribution of outcomes, imagine a bell-shaped curve on a graph. This is a normal distribution where there are very few low-end possibilities, a large number of possibilities in the middle, and a very low number of possibilities on the high end. But the range of outcomes for many things we care about, from crop yields to on for our revenue, do not necessarily have normal distributions. Say we were to plot all the data we have for a given farm's yearly income on a single graph. If most of the income figures fall in the middle with just a few outliers, that's a normal distribution. But if many of the data points instead skew towards the low end, we might well predict that future income will be skewed to the downside. Or if many more data points land on the high end, we might predict that future income will be skewed towards the upside. In other words, what Mike is saying here is that it's increasingly important to know whether a given risk is skewed one way or the other, because these skews can dramatically raise the chance of a seemingly unlikely event actually occurring. So with the distribution and the shape of the distribution of possible outcomes in mind, agribusiness managers today are focusing not just on understanding and managing the most likely future event, but on ensuring that decisions will be sound across a range of possible events.

SPEAKER_04 23:49

We don't just do our financial planning and our strategy development and our marketing plans, focus only on the average price or what we think is going to happen. Or we actually say, here's the high, here's the low possibility. We take that distribution, and maybe we do become conservative in the way we grow our business, how fast we try to grow it. So we're much more conservative in our investment strategy. We want to make sure we're protected so that we don't have the survivability of the business compromised if in fact that downside does occur.

SPEAKER_00 24:28

Now, in theory, this all sounds great, especially if you've been, I don't know, doing cutting-edge research on it since the 1970s. But what about for the rest of us? How should we, non-professional agribusiness researchers, be updating our thinking to include all these new insights? The good news is you don't need an MBA to start evolving the way you think about and manage risk. The probabilities and distributions that Mike is referencing here are not the result of advanced calculus. They're just as useful when they're mined from experience.

SPEAKER_03 25:01

Just thinking about what is the probability that blank happens. So identify whatever the things are that you think is a risk, and then you score it in terms of the likelihood that it happens. So scale one to five, how likely is this thing gonna happen? Five is almost definitely gonna happen, one is probably not. And then scale one to five, how big would the impact be if it does happen? Five being it would be catastrophic, one being it would be okay. So if you list out all of those risks that you think is on the board, and then you score them by those two things, multiply those two scores together, and then rank the risks that you've identified. So there are gonna be things, for example, back where I'm from, tornadoes. If the tornado hits a grain elevator, it'll be bad. But what's the probability that's gonna happen? Probably not super high, right? There are other things that are probably more likely to happen, even if that thing might not be as catastrophic as a tornado, maybe it's something that is worth taking more seriously.

SPEAKER_00 26:01

What Trey is describing here is a practice called probabilistic thinking, which can not only help you identify and quantify risks that might otherwise have fallen off your radar, it can also help you find the clarity and the tools you need to deal with them.

SPEAKER_03 26:17

So when it comes to commodity markets, we have a suite of options, but the data I've seen says that only about 15% of farms, like row crop farms, actually hedge. And so there is a very large percentage of farmers who just operate in the cash market. They might make more money actually than those that are hedged, but that is to say that their downside risk isn't covered. So we we actually have a paper that that we just finished where we looked at the probability that you're happy with your marketing outcome if you're using some of these risk management options. The probability that you're happy with the outcome more than doubles. I'm not saying you're gonna make more money, but you're probably gonna be able to sleep better at night if you know that your downside risk is covered.

SPEAKER_00 27:01

Probabilistic thinking and existing risk management tools go a long way towards helping farmers and agribusiness managers understand and mitigate risk, especially to the downside. Together, these two represent our weather forecast and our umbrella, two strategies that combine to help us avoid getting hosed. But now and again, tornadoes, Doratios, and hailstorms still strike. And unfortunately, our current forecasting tools aren't very good at predicting when or where these extreme events will hit. And our current risk management tools, our umbrellas, don't provide much protection in the face of these true crises. These wicked risks are a known problem, especially in agribusiness. In fact, we become so familiar with them, we don't call them risks at all.

SPEAKER_04 27:50

So when you we use the word risk and uncertainty in the agricultural industry, there is a difference between those two terms, actually.

SPEAKER_00 27:59

So far, our conversation has been focused on risk, on possibilities to which we can assign a specific probability of occurring based on historical data. Again, these risks are like thunderstorms. We have enough information from observing countless previous thunderstorms to have a very good idea of how likely another one is given our current conditions.

SPEAKER_04 28:23

Uncertainty, on the other hand, you can't have a probability distribution there because you don't have enough observations of that kind of event that you actually can put a probability distribution on it. It it happens so rarely, but it does have have the potential of happening.

SPEAKER_00 28:41

A growing awareness of uncertainty, especially at the systemic level, was one of the most important ideas to come out of the 1980s farm crisis. That's because that crisis was an uncertain event. Farm financial crises have happened before and almost certainly will happen again, but they have not occurred enough times for us to have a good understanding of how likely one is to occur at any given moment. Put another way, these uncertain events are captured in the tales of our distributions. They're events that are unlikely, but certainly not impossible.

SPEAKER_04 29:17

Because the tails drive a lot of stuff, right? I mean, the tales, whether it's a good positive tale or a really bad negative tale, they make a world of difference in terms of success. We have faced those recently in a number of cases. For example, COVID. And COVID was an event where people said, well, that can't occur. That will never occur. COVID did occur. And that was a good example of a black swan that people said never happened. We had similar types of attitudes to be frank about some of the political unrest we have, the geopolitical events occurring right now.

SPEAKER_00 29:59

Staying vigilant of these uncertain but possible events is hard. And to do it well, managers need to have a different strategy for managing uncertainty than they do for managing probabilistic risk. The first step in this new process is understanding the type of uncertainty you're dealing with.

SPEAKER_03 30:18

Usually you can group into three different uncertainties. So technological disruption is one regulatory and compliance uncertainty. This is one that we see in ag quite a bit, right? So what happens if all of a sudden the regulations change overnight or just the enforcement changes overnight? And then finally the macroeconomic and geopolitical risks.

SPEAKER_00 30:38

Once you've determined what kind of uncertainty you're facing, the next step is to imagine how that risk, whether it's the worst or the best case scenario, might actually play out.

SPEAKER_03 30:48

So with those uncertainty scenarios, this is where you really need to sit down and create a narrative. So what if this happens? What if I do end up with a postmaster general and I'm a hemp farmer and the postmaster general decides not to send on my stuff for testing? That's happened. So if that happens, what do I do? So long as we've identified that uncertainty or that what if scenario, we can write out a plan to attack that problem.

SPEAKER_00 31:15

Whether uncertainties come in the form of new regulations or global pandemics, they generally can't be dealt with like risks, which can be managed with market-based tools like insurance and forward contracting. In other words, pulling on our rain boots and carrying an umbrella won't protect us from a freak tornado or a bad hailstorm. Instead, we manage these uncertainties by identifying all our options. We have to be prepared to adjust our schedule, to wear layers, and to know the shortest route to the nearest tornado shelter. The best strategy for managing uncertainty isn't predicting uncertain events, but developing the most complete menu of options to choose from in the event that an uncertain event occurs.

SPEAKER_03 32:00

We can game plan and battle strategy this out. We can create consequences and options. Either you accept the risk, you could create a contingency plan, you could try to avoid the risk altogether. You could transfer the risk. Transferring risk is interesting, right? Is there a way that I can basically share that risk? Labor is a good example. If I'm concerned about some risk or uncertainty around labor, maybe I should hire a company to do that for me. Because then I've transferred the risk to somebody else. And in that regard, at least we've shared the risk to some extent.

SPEAKER_00 32:31

As Trey mentioned a few minutes ago, protecting against downside risk tends to be the top priority for agribusiness managers, or at least for those who like to sleep at night. But there are other benefits of adopting risk and uncertainty mitigation strategies. The biggest one, perhaps, being that they can help you unlock upside possibilities as well. After all, as Mike taught us, there are uncertain tales on both ends of our distribution. For every unpredictable trade war or pandemic, there's often an unexpected opportunity.

SPEAKER_03 33:04

That volatility can create a lot of pockets for opportunity for you. A good example is the organic chicken explosion. There was a time where people thought that organic chicken was hilarious. And maybe some still do. But a lot of the large firms were like, we're not going to make these investments in organic chicken. Well, there was one guy who was advising the organic chicken company, a guy named Ed Fryer, and he was like, you know what, we're going to do this. We're going to make an organic chicken company. Guy made a lot of money. The uncertainty around this new product development created enough hesitation from the large players that it created a pocket of opportunity for that other player. And so I think there are so many examples. In the corn and soybean world, you're operating in a razor-thin margin where what you're really trying to chase is achieving some larger economy of scale. Well, if everybody else is going bankrupt in your 1980s scenario, this might be the opportunity to push forward on your economies of scale strategy.

SPEAKER_00 34:04

As we think about continuing to prepare for an evolving world of risk and uncertainty, it bears repeating that the point of all of this is not to actually predict the future. We're really bad at predicting the future, and evidence suggests we might actually be getting worse at it. This is one reason why weather forecasts are useless more than two weeks out, why farmers in the 1980s and today have basically no shot at beating the market, and why regular people continue to be surprised by everything from headlines to microbes. And the fact that we're so bad at making predictions is exactly why thinking probabilistically about risk, by scoring risks on likelihood and impact, ranking them, and then building a game plan around top risks is such a powerful exercise.

SPEAKER_03 34:54

As an economist, they like to joke that we've predicted eight of the last seven recessions or whatever. And so yes, I think the concept of saying that tomorrow's weather forecast is blank is helpful. But I'll say in the world that we now live in, the value is less about predicting the future and more about designing the contingencies for what might happen. So it's more about thinking through this kind of optionality perspective that says that if these things happen, I maximize the choices that I have if the world does melt or if there is some type of change. And it's more about identifying the things that you need to be watching so that when you have to make a shift, you're available to do that. You have the option to shift. The biggest problem when you're playing chess is when you don't have any more options on the board. The best chess players are the ones who maximize the total number of options on the chess board. And if you are not thinking about these what-if scenarios, if you're not scoring your risks, if you're not trying to evaluate the uncertainties that exist that your business is confronting, you're probably not going to be able to maximize the number of options that you can take.

SPEAKER_00 36:05

Part of it is even just knowing that one day something is going to happen and you're going to be panicked. And don't leave it to that moment to think about what your options are because you're not going to think of them all, because you're going to be panicking. So it's good to have the options laid out for yourself before. So in your panic, you can at least look at all the options.

SPEAKER_03 36:26

Yeah, I think in our minds, think about the decisive leaders who just double down on whatever is the choice that they made and it works out. And that's great. I mean, that can happen sometimes. But in the current environment, in a high-risk, highly uncertain market, the thing that really separates the good strategists from the bad strategists are the people who are able to calculate and quantify the options and maximize the optionality in the decisions that they make. That's the key. How do I maximize my options? Full stop.

SPEAKER_00 37:14

In that time, we've experienced not just the run-up to the 1970s and the crash in the 80s. We've also weathered a number of other crises from dramatic farm and biofuel policy shifts to national economic crises, from a global pandemic to multiple market-moving conflicts. In that same time period, farmers, lenders, and agribusinesses at every level have gained a lot of skill at managing risk, especially thanks to the efforts of people like Mike Bolgy and Jim Helker. We've gone from making vague guesses about the future to carrying umbrellas to having sophisticated game plans to help us manage through the worst-case scenarios. But even as we've mastered parts of the risk and uncertainty landscape, the landscape itself has changed, consistently resisting our efforts to limit its impact on farms, agribusinesses, and the larger agri-food system. And these trends are not going away. Today, we're facing technology uncertainty around AI and robotics, changing global regulatory regimes, and growing conflicts at home and abroad. In response, the most important thing any manager can do is not bury your head in the sand. I know it can be time consuming to sit down and think about your business's risks and build plans to manage them, and it can be anxiety-inducing to strategize around your business's exposure to potentially devastating uncertainties. But those who are willing to put in the effort to draw up the most complete menu of options to have it the ready the moment the next crisis strikes, those are the managers who are most likely to not only avoid the worst of the next crash, they'll also be the best situated to find the opportunity in the downturn. The golden egg beneath the black swan's tail. But managing risk and uncertainty doesn't happen in a vacuum. Beyond our plans and strategies, other players in the system are dealing with their own demons.

SPEAKER_01 39:15

Wicked problems are, first of all, the ones we all hate to face because they're largely intractable.

SPEAKER_03 39:24

And I feel like in wicked problems, oftentimes there is nothing that you could do to change somebody's mind on whatever that thing is.

SPEAKER_00 39:33

The wicked problems of food and ag policy, next time on Agribusiness Blueprint. Agribusiness Blueprint is a production of Purdue University's Center for Food and Agribusiness. I'm your host, Sarah Mock, alongside my co-host Trey Malone. This show is produced and mixed by me, Sarah Mock, with editing support by Trey Malone and Mike Bolgi. Additional support from the wider team at the Center for Food and Agribusiness. To learn more about programs, classes, and continuing education opportunities through the Center for Food and Agribusiness, visit our website at agribusiness.purdue.edu and follow us on LinkedIn for the latest news and updates. For specific questions about the show, contact Trey Malone and the Department of Agricultural Economics at Purdue University. Agribusiness Blueprint is sponsored in part by the Agriculture and Food Research Initiative competitive program of the USDA National Institute of Food and Agriculture, NIFA, award number two zero two two six eight zero zero six three six four three three.