Understanding the Future as it Unfolds: The Power of Megatrends - Mark Esposito, at USI

Good morning and thank you for joining me today while we're having this conversation on the future. There is always fascination when we think about the future. Most likely it's because we don't really know what the future looks like and we did not try to attempt this with the exercise in the book that we have released. A few months ago in March. The question that we were trying to really engage today in, which is really captured by what the book has tried to do, is do we have any way to determine what are the trajectories that the future will actually look like? The question is not really forecasting the future, but is looking at those trajectory that over time will lead to what we call a certain future, or future that is now unfolding because now is a large-scale driver that over time will actually occur. So in the quest for this, we started the journey that started in 2015. They led to this, this book, which was actually released in March, and they collected about 80 interviews with senior executives, CEOs, governments, asking the question, can we have any sense of empowerment about today if we want to really change the future? To give you a sense of this, if you do an exercise by asking, "What type of present do we have?" you're going to have a specific set of answers. We're going to talk about technology, we're going to talk about geopolitics becoming difficult or different, we're going to talk about the rise or fall of democracy depending on where you are in the world. You might talk about a number of different trends. And then if you ask the same question about what type of future would you like to have, we tend to have very aspirational and idyllic perspective. We always think about the future as something that is going to be to some extent better, or at least what type of future we would like to have, which naturally is wishful. But if you try to understand whether the present is matching in the progressive itinerary the future, you always find there is a glitch. It looks like the type of future we'd like to have never matches the type of present we currently have. And so that journey was the primary trigger in understanding what is really that we have to study if we want to have a sense of empowerment into the future and the megatrends. So we started to observe that for most of modern history, we got really obsessed with growth. At first, this journey was to, to help organizations to find new growth. It became a way to find new growth as well, but it was not necessarily the proxy. The proxy had changed to a different, to an entirely different set of imperatives. And then we start to look at the data, and we noticed that for most of history, we haven't really aggregated that much. This is the global GDP until we could actually measure this. You notice that we have a trend that is incremental, but it's not exponentially incremental. And then when you're looking at the GDP now, you notice that we have significantly changed the variables. In other words, we are facing for the first time an increased acceleration in the way we aggregate growth. So this, bearing in mind, brings us to a question: what type of world will we have if we continue to aggregate like this? So we started to think, what is the wiring of our society? And what is universally accepted to the point in which every society on Earth, regardless of where you're coming from or what type of governance structure you have, will be equally comfortable in understanding trends? Now, we can call them, as a cliché, megatrends, but we're really looking at these large driving forces, these driving plots that are really unfolding as we speak. So we came up with an acronym that was easy for everyone to remember. It's called DRIVE. Which was the subtitle of our work. And I'm going to tell you more about each one of these. The purpose of this session with you is to show you what has been the journey with the specific megatrends and how we find there are interesting, interesting inklings on how we can possibly empower the future to unfold the way we'd like to. We started to look at that in this hypothetical framework, which is non-exhaustive, naturally. Demographics is playing a primary role. We noticed that the way the chemistry of the world is really defined is through its people. And we are dealing for the first time with a degree of human interaction that we never had before. We never had so much migratory corridors as we have right now. We have a huge amount of people that are despairing in terms of life expectancy. We have life expectation— expectancy in some countries raising to a median which is very high, and in other countries, we're still very, very young. We do have a gap between the rich or those who have and those who don't have that is significant in terms of demographic output. And then, of course, all of this is related to the access to resources. So— and I'm going to go deeper in detail in each one of the different letters of the acronym, but for you to have a sense of the comprehensive nature that we're trying to have with something that we could work with. We realize that the way we are currently moving on the territory is impacting our resources. So we noticed that we were actually experiencing a reverted effect from abundance, which defined most of economic model in which country would actually compete on comparative advantage. We now start having scarcity, and now more and more of some of the resources are either becoming non-renewable, or if they are renewable, our pace of consumption is faster than every replenishment rate we actually can allow the stocks to fulfill. So we're dealing with one of these paradoxes: how do we reconcile growth when we aggregate so much? At the same time, resources are no longer part of this abundant stock, but they're shifting to scarce. And then we realize that because of the relationship between demographic and resources, or the access or no access to resources, naturally and unfortunately, the gap is increasing. And it's not only one gap, it's several gaps. We have inequalities, intentionally in plurals, because we think that inequality is now a number of series of multiple issues that we're dealing with, and we realized that if we're not addressing this, after a period of time, we'll start having with structural inertia, or something that will possibly start slowing down, decelerating, eventually dysfunction, the way in which we're currently distributing wealth in our society. And from there, we were quite pessimistic. After we have done this work collecting data from a number of different senior executive, we're thinking, are we writing a book that has no hope whatsoever? And then as we were collecting our data, we fell into what we call our hope net. We decided that V and E were really where we are harnessing the hope. So yes, in many cases volatility, scale, and complexity is considered to be bad, but we actually consider it the opportunity to rewire and reorganize our society today. We noticed that, yes, predictability is becoming more of crystal balling than anything scientific, but at the same time, can we readjust our system to measure things differently so that volatile systems define performance rather than systems that tend to pretend to be structured, symmetrical, organized, slow, steady? And naturally, the answer is, if we're shifting our expectation on how we're going to measure this, if we're measuring our economic activity not in terms of what we call the normal distribution or the normal progression, but we start looking differently, maybe this entire new way of thinking can really allow us to thrive and eventually move forward. And then the final part of our work was coming from understanding that plethora of innovation coming from country that were not historically innovative. We start to notice that most innovation is no longer coming from the traditional R&D labs, but it's coming from the streets, from where people are inventing, innovating at different pace. From countries that were never really allowed to have so many resources to possibly innovate beyond their capacity. And so we discovered, little by little, that innovation has shifted from the transatlantic order in which the rich countries were defining innovation for more, for more, to countries where now, with very little, innovation and solutions were becoming extremely effective. So we were actually excited. We found a number of really difficult stories, but we found equally great ways to move forward. So the journey of today is really looking at that numbers, making sure that we have an engaged conversation with this, but at the same time determining that all of this, if it's becoming a compass on how we're redefining and reconsidering our economic and social compacts, then maybe we stand a chance to understand how the future will unfold. And maybe we're going to be able to have a future that matches the expectation we'd like the future to have rather than making it very disconnected from our reality. So let's start the journey. In demographics, we discover naturally that aging is the number one factor. We are aging across the spectrum, every single part of the world, even in countries that age from 16 to 17, or countries in which the aging goes from 45 to 50. Yes, the disparity is important, but what's really happening is that we're changing our population pyramid. How are we changing this? This is the population stock in 2000. You see that we already have a specific imbalance going into a specific direction, divided by age, and this is the population stock as we are actually accelerating the clock and looking at 2050. Now, most of our social welfare system is not designed to capture this type of demographic imbalance. I call it imbalance in the perspective of what was a historical legacy. You have to bear in mind that our population pyramid has been stable for about 300 years. The first inklings of a population pyramid that looks like kids at the bottom of the pyramid more than, of course, people at the top of the pyramid is in 1700 in the UK. So we really had the sense that kids are the most, and as we get older, of course, the population stock is decreasing. But you're noticing now that kids are no longer the most. We are going to live in a world in which the kids are becoming the least numerous part of our population. Now, as a father, I do have an issue with this, because I have discovered that the other side of life happens when you become a father, but this is, of course, a personal story that I can share when I'm talking. But this is personal. It does not necessarily have an economic driver. But I'm always very worried that we are changing dramatically the composition of our society. But on the other hand, as an economist, I need to engage into what has happened and in which way can we now design our social economic system to capture this anomaly. Again, it's anomaly in terms of what we expect it to be. It's not an anomaly in terms of the new norm. But this is exactly what we have to figure out. Is our social welfare system designed to capture this tendency? Is our pension system designed to deal with this? You know by the way I asked the question, it's not. In America, life expectancy, when it was 63, coincided with the time in which Social Security was actually introduced. So we haven't really updated our stocks in terms of our cultural stocks in the same way. But if we don't, if we're not capable of understanding that increase in aging in a specific part of the population will change the variables that are coming from it, then naturally we're going to find ourselves in the next 15 years with a number of issues that we have never experienced before. Why? Because for the first time the past does not match the future. Why? Because the aggregation is not the same. We don't have the same ability for the aggregation to happen by providing the same spectrum of comparative analysis. On the contrary, what we're noticing more and more is that we're dealing every single day with a new scenario. There's very little that we can really learn from experience other than emotional fitness. So that we feel comfortable in dealing with the degree of uncertainty. But in terms of using the data of the past that applies comparably to the future, the ability for us to do that is not really very high, mainly because we are changing too fast for any of this data to be extracted into a norm that we can actually use as a rule. So how do we design our society dealing with that specific set of issues? The next conversation, of course, is, in some countries, we're really going to get really old. This is some of the extrapolated data that shows you the countries that are going to get the oldest. Some of these are not too far away from where we are. Of course, we've got Japan that's been dealing with this specific anomaly for a number of years. The question around aging is not aging per se, it's productivity. How will we be able to be as productive when we are decreasing the number of people in the younger part of the population distribution And of course we're aging. We're shifting the aging stock to the top. There is not an issue in terms of efficiency. You can replicate now a lot of the efficiency that used to be manual labor with computer and robotics and AI. We'll talk about this. But our, again, social system are not designed for AI to produce taxes that will then eventually be redistributed back into welfare. Not yet. Well, Bill Gates is arguing that we should do that. But then the question is, are we capable of understanding the input on productivity that we might have into this specific scenario. So this is empowering us to think about— hold on a second, there is a change that is currently happening that will profoundly transform everything. Now, how does the future unfold? If we continue business as usual, demography will actually push us against the wall. We won't be able to deal with the same agility of our social economic system by dealing with an anomaly in the way we expect it to be And of course it's not. So reality will outsmart our expectation or our prediction. And this is the first type of set that we're going to share today in terms of demographics. Demographic is related to where we live. So as we are shifting more and more from non-urbanized area to urbanized area, we're also going to impact with our behavior specific set that are coming together, almost like the strings attached to urbanization. The energy, resources, traffic and mobility, and of course productivity is related to that. How do we actually manage waste? One year ago on this stage, I was talking about the circular economy as being an opportunity to recycle, reutilize, reintegrate material at the end of their life cycle. But this is only one part of the conversation that needs to be done to determine how this specific impact will actually generate the ability for us to live harmoniously in cities. And naturally, as we are shifting towards cities, the access to resources is becoming more critical. So we are not too worried about energy. I think we have been taught a lesson in the last few years that we can actually accelerate transition to different type of energy. About 10 years ago, I would have never believed that renewable could ever be an alternative, not because they were not there, but I could never imagine that this could actually scale. But now, because of the drop in the price of oil, because of the awareness, because of the large energy companies themselves investing in energy, we're having every single day records in terms of how much renewable energy is now being utilized to support our needs, which is good news. I was not able to share this good news maybe even 5 years ago. But now I find that in energy we're trying to address it quicker than what we think. Eventually even the US will figure that out. After that, we decided to look at urbanization, and the, the example I'm going to bring to you is the country that is now defining most of our agenda— China. So imagine what will happen to a country like China if the urbanization ratio will shift to actually 60%. In this simulation, you're going to see the city— they're currently below 50%. This means that these are cities that have not fully urbanized yet. You can imagine with the population stock of China what it means in terms of the input on resources. The next are the cities that are urbanized between 50 and 79%, and only the one in red are the cities that urbanized over 80%. So China is still a long way to urbanize itself. But naturally, when you're urbanizing, you're increasing your, of course, CO2 emission. The materiality, which basically is how much material do you use to create $1 of GDP, will naturally increase unless we're shifting to green energy in that country. But this shows you that we are dealing, again, in the next 15 years, with a type of future that will unfold with even more environmental crisis. Why? Because demographic— when you're having this stock of population moving into cities, it's not coming by itself, it's coming with associated collaterals. Not always bad. You can call them positive and negative externalities. But it's coming with some factors that we have to consider. From there, the conversation on resources becomes even more critical. So will we have enough? Yes, but water is where we have to worry. According to the projection, if we continue to grow as we have grown so far, not only are we going to have an impact in terms of the weather— you see in blue what will still be partially habitable with arable land, You see in red what, if we get into 4 degrees warmer, might become not habitable or difficult to grow food. So not only are we going to have scarcity of water, but we're also going to have imbalance in the way in which actually the balance of the geopolitics or the economic geography is currently designed. And this is, of course, a picture I would never like to see. Not because the Earth will matter, because the Earth is a biological system that will constantly evolve, I'm not sure that we as society are ready to deal with the level of impact in our economic structure. But where I'm, of course, a little bit worried is the consumption of water and this potential expectation in the years to come. This is the overall consumption of water. You see the different years. And this is the performance in terms of percentage. So on a global level, business as usual— this is how I call it in "Future as It Unfolds"— if we're not changing anything, we will need more, 37% of water. Do we have it? Not under current standards. Under current standards, we're currently struggling with that. Can we change it? Of course. We can be smart about water. We can replenish stocks in a different way. We can collect rainwater differently. We can maybe desalinate. Maybe we can use alternative energy to decrease the use of water. But according to this projection, If we're not changing our traditional way of procuring water, then we are in trouble. So how do we forecast the future? We start forecasting what will happen for a fact, unless we're capable of transitioning. So the conversation today is about how do we empower us, ourselves, how do I empower you to think that if you want to have a different future, you have to change the way we think now. The future is nothing more than a compound of many small todays. It's the choice that we're making today that will define the type of future we're going to have tomorrow. But if we're not changing this, or if we're shifting the responsibility to the next generation, not only might it be a bit irresponsible, but we might not have the ability to game this. This is too difficult and too challenging for us to take a bet or gambling into the future, hoping that someone in the future will do it for us. It will also be a bit irresponsible in terms of our kids. So we have to think, how do we change water supply differently right now because I cannot afford business as usual? And here is where inequality is becoming even more visible. This entire new redefinition of demographic and resources is changing the way we're having access to resources from, of course, from a human perspective. So inequality is looking a little bit like this these days. It's not only in terms of income, but we're going to look at a number of different inequalities, but it's actually really impacting a number of different spectra that we were going to look at together. So yes, we do have an issue with the fact that digitalization has increased in many ways corporate profits, but it has not really matched the same in terms of wages as a percentage of GDP. So we have what we call the decoupling. We were able in the last few years to decouple productivity with actually wages. In a better slide that will allow you to see the overall evolution of this, why are we a bit worried about this? Well, look at this. This is actually the evolution of labor productivity. This is the real GDP per capita. You have the private employment, and then in blue, you have the family income. You notice that we have really an interesting decoupling. Now, productivity grew by 4 times what it used to be in 1947, But the wages, which is somehow what is holding us together as a society, in which the collective benefit is actually experienced by everyone being able to participate in the economy, spending their money— consumption, of course, is an invention of the 20th century to allow the economy to aggregate. That's why GDP is so high. All of these factors that really define our legacy and inherit the system in the 20th century have not really worked that well. And you notice that we were quite okay until 1995, and then we start to talk about different languages. So the worry we have to figure out is what is not really working in our redistributive system. Is it that the fact that when you are digitalizing labor productivity, yes, you maximize shareholder values, but that value is not naturally redistributed back into jobs? That might be one answer. And if that is the case, how do we make sure that we have access to redistribution, not from a top-down perspective, but to normal organic grassroots perspective in which growth is proportional to everyone. No matter where you are, you can make a very small proportion of benefit in comparison maybe to someone else, but the, the correlation is positive. What we're noticing right now is that we have a negative correlation between labor productivity from a perspective of maximizing the assets and median income of a family. And that's something we need to correct. If we're not correcting this— and it's not only calling for a social, political action, it's not my orientation, it's just that it's not functional. That degree of dispersion of value is not functional to the economy. It will be very difficult for us to eventually recover because we are somehow eroding what really holds us together. Just to show you why this conversation needs to happen: business as usual, free market hypothesis, and under current terms, would not work anymore. So it's not about empowering yourself to go somewhere else. It's not about empowering communism or any of this. It's about saying the original model of capital system or capitalism is no longer yielding the same expected result as we were thinking before. So how do we possibly correct this? How do we understand that the trajectory— that's what we call these megatrends, the plots— are not going in the direction which we actually want to? Ahead of us could only be troubles unless we are able to correct them or understand them or immerse ourselves in what really has been the major reason for that. The same happens for life expectancy. We have differences in life expectancy between men and women. We notice that richer people live longer, and most of this data is only extracted by countries where you have really good access. So what is to do? Well, we have gone from a sick care, where we're always looking at people when they are sick, to a preventative care that only very few people can afford. So most of the medical breakthrough, or the type of scientific breakthrough that we see ahead of us, are coming with a price that only very few people are able to afford. So one more time, unless we're changing the ability for this technology to become scaled, we're going to have even more that degree of inequality through the gap in between those who can afford to be preventative and those can only afford to go to the ER when they really need it. The same is for women. We have a slightly better ratio between men and women, so the numbers show that the richest 10% live 12 years older in men and 8 years older in women. So we have to think that even the specific level of distribution of quality of life is not as equal as we were thinking before. And then we're moving into the part that I like the most. Yes, we are volatile, but maybe some of this is a way for us to redesign some of our stories so we can engage in entirely different collective rationale. And so in volatility, we notice that we have an unprecedented degree of connection or connectivity. We have more money in infrastructure today than in military expenses, which is great. The world has become an integrated model. It has become A global network society in many ways. But are we capable to match our governance system, our political system, our economic measurement to the nature of the world we have become? Not really and not yet. This is an example of jobs that most likely will be replaced in the next few years. Have we really engaged at the societal level on how the replacement of the job will be okay if you're shifting to a new economic platform? Because if we're not, Naturally, we're going to create a crack where many of these people that currently have a job might not be able to find a job anymore, not because they're not qualified, but because the economic infrastructure is not prepared for them to go anywhere else. We have not created the sense of social mobility that is required for them to eventually move on. This is some of the impacts that the job will have. We're naturally going to have jobs that we've never seen before, but many of these jobs, they do not employ as many people as we need. One of the issues we have with the ability of thinking that we're going to simply create new jobs is that some of the jobs that we will create, because of the fact the system has become more efficient, won't require as many people as before. So the engagement on how do we think about distribution of value, not only in terms of what I mentioned to you before, redistributing back through the social compact, but also engaging into a conversation that is allowing us to see that replacement of the job is not coming at the number, that is desirable. So how can we move that low-skilled labor elsewhere? This is when, of course, artificial intelligence is not going to help us in the short term, but it might really help us in the long term if we engage it not as a negative technology but something that really becomes a way to harness hope. We have lost all possibility to redefine probability. Statistics is no longer following the same principle as before. Mainly because we're no longer capable of gaming it. We noticed that the idea of bell curve is now being, most of the time, not respected because we're having too much oscillation and fluctuation of the bell curve. We do have example that, you know, we should have within distribution of behavior within the two different variable that is expected to be about 7%, but actually rather than happening only once every 300,000 years as we were expecting from the distribution, In the last few— in the 20th century, it happened 48 times. It shows you that we're dealing with a way for reality and the variable around reality to go faster and now smarter in most of our predictions in many ways. So what I'm trying to share with you is that we can no longer forecast the way we did before. We can no longer use statistics in the same way in which we're thinking that we're going to have an independent variable, maybe a dependent one, and try to think about the way in which they can correlate. We can no longer think about gaming it by defining the frequency, by thinking that the fluctuation will only happen within a specific spectrum. Why? Because the spectrum is a moving pendulum. It's constantly shifting. So how do we measure when we're no longer capable to stop, synthesize, capture, extrapolate, normalize, and create a rule? That's the question. It's not about feeling powerless. It's about how do we integrate from the educational system to the labor force to the workplace ways to measure that are different, not because we are simply becoming too geek, but because we have to honor the fact that we have transitioned to an entirely different type of society. And from there, again, AI. AI is currently getting smarter than what we think. This is actually quite a funny article. I like funny because it's talking about how computer-based personality judgments are more accurate than those made by humans. You see here what they call the famous fight trait, and this is the performance that we have by a number of different stakeholders in our life, but the computer would not go that far from the spouse, which still holds the, you know, the pole position, as they call it. It looks like we are capable more and more with artificial intelligence to replicate accuracy at the level in which we've never seen before. So why don't we use it? Why don't we use this technology not to disempower people or to replace, you know, labor force. But why don't we use it to create new economic infrastructure that will allow this mobility to actually be in place? And it's necessary for us to think this way, unless, as a society, we're going to be happy in thinking about degrowth as a standard, unless we're deciding to decrease our standard of living, which I'm not sure is going to be possible, especially when so many emerging economies are emerging right now. So all I'm trying to share with you is that we have to understand that this technology is not neutral. We make it what we want it to be. If our understanding is that the D, R, and I are showing us symptoms of anomaly, can we use these driving forces to change today? Rather than having conversation how disempowering it could be to lose a job to an algorithm, how do we think about algorithm allowing us to find new economic opportunities? It's what we make of it that will determine the future. It's not something that is divine intervention coming from the top. That's the type of conversation I want to have with you. We empower ourselves by understanding what will happen, studying this safe or certain future, but at the same time, we have to empower decision right now. As you are thinking about what should I do with that specific choice, think not only in terms of the transaction, but think about the impact it will have, the first-order effect, the second-order effect, and the third one, what we call the inception. The ability for us to think in terms of multiple dimensions, the unintended consequences, thinking in terms of reinforcing loops, is how do we shift that specific thinking. But there is more. We have innovation coming from countries that we have never experienced before, and we can learn from them. Many of my colleagues working in the whole frugal innovation, jugaad innovation, they teach me everyday lesson that country with very little resources are really capable of shifting from a specific model of incremental more for more results to less for more. So the example that we're gonna see today, specifically in this presentation, is from the traditional 4 types of innovation, what we call the customer-focused one, in which the customer is driving, the efficiency one, in which we're simply improving our ratio of efficiency because the inputs and outputs need to be put into better process, the engineering-based, when we're simply incrementally doing iPhone 2, iPhone 3, iPhone 4, iPhone 5. We're thinking about that level of evolution constantly coming by tweaking and improving little by little the products we have. Or science-based, when we're having breakthrough. This is now being completely overshadowed by frugal and relatively inexpensive innovation that is coming from countries that were not historically capable of innovating. One more time, the example of China, because it's one of those recurring topics. That we always have to talk about, teaches us the lesson. This is how— a question— we're never taught that China is an innovative country. But when you're going into the distribution of technologies and you're looking at the overall spectrum in many of this, you notice that the U.S. has historical legacy but also historical leadership. The U.S. has been a country that has been able to innovate fast. Because of their patents, their innovation culture, their ability to destigmatize risk. And China, which is not a country that has started from that specific point in time, have they caught up? Not in every way. If you look at the performance of China, in some dimensions China is truly outsmarting the U.S. But they don't do it by more, by more. They did it by contextualizing what is already out there and use it. You could argue they copied some of our technology. Maybe. But even if they did, they use it differently. They were able to find a way to trick it to the point in which we're now able to say China's innovation is coming into our homes with something that is so different from what we're seeing from the traditional innovators. You know what? We need this. We need to have this competition between, you know, high-end country innovation in which more creates more to countries that will less create more, because this is how we're going to decrease the dependency on resources, the example we were having before. So all of this conversation really leads us to think, how do we redefine a spectrum of action for us to move into the future? This is what we actually talk about, the opportunities. So towards the end of our book, we talk about all of this can be used It's now how do we empower you to make sure that this conversation is happening in a way in which you can bring it back to work, in which you're going to ask the question, "What are the megatrends that matter to me? What has been the impact of resources—energy, electricity, water—into my business? How have my business changed because of rising aging? How do I ensure people when the inequality gap is becoming larger?" How do I define social contract and the relationship with unions when digitalization and robotics are threatening to make a number of people redundant? All of this conversation needs to be made at your level. You need to bring what we call drive back into your life, thinking, how have these megatrends impacted? And then once you do this, you start thinking about how do we find new growth now that I understand it? Because of course we want this to be a process of triggering economic opportunity. And we think about 3 lenses that might help you, and that's kind of where my takeaway for this session could be. After having done the study on what we define to be the megatrends, try to determine what are the macro forces that really matter to you. Ask yourself the question: "Has access to specific resources impacted my business line?" Did I suffer a lot because I was expecting return from oil, but oil became less profitable? Have I paid more in electricity because now our source of electricity is becoming more expensive because it's attached to water? Whatever is the story, bring it back. Make a DRI framework for yourself. Define what is important for you in terms of the macro one. Define the macro picture so you're not disconnecting from the big picture. You don't have to always get the overwhelming feeling of the big picture. You have to empower yourself to bring the big picture somewhere else. We argue that if you bring it down to these 3 proxies, it will help you. What's been your experience? What have you noticed? What has been the ability for you to connect to the reality and feel that we have maybe changed? The field witnesses. How do we notice that something is different now? We have realized that there has been a change. How do I look at this certain future by knowing that yes, water will become scarce if we continue business as usual? So we can't continue business as usual. Or how has climate change impacted your production if you're in agriculture? In which way the increase in temperature will constantly push you to a specific limit? And then, have you noticed any pain point? Have you noticed that there are areas where we are struggling because we are not capable? If you're a bank, have you asked yourself whether you are banking everyone, if you're underbanking them. And if you're underbanking them, why? Is it because your services don't match their reality? What is their reality? Bear in mind that every pain point is a dormant demand. If you're capable of understanding how a pain point is structured, it's a demand that's never been expressed. But if you're understanding that it's a dormant demand, you can address it with a business model. You can go to that demand and help. This is why this social entrepreneurship Revolution works so well because they start by understanding what's going on rather than having this expectation of what's going on, which is very desktop-driven. They have this field feeling for things. And then from there, you bring it down to the micro. You try to determine in which way the micro matters to you, in which way your everyday action not only will empower you to simply find growth, but you're finding growth will have emerged from understanding how the future unfolds. That's the story of the book. We want you to think that the future is nothing more than what we make of it, but we have to understand this large-scale integrated network of things— demographic, resource scarcity, inequality, volatility, enterprise and dynamics— for us to determine in which way all of this makes sense for us, then organize it down to proxies, make it something you can work with, Define the proxy yourself. Define that what matters to you as a filter to get to the specific point is actually those 3 elements. In our case, those 3 elements emerged from the most frequently reported elements. So we collected from data, but they are non-exhaustive. If we had more time and more life, we probably would find even more. It doesn't matter. It's the idea that matters, how you transfer this to yourself. And once you do this, Empower your micro, empower your decision, go back to the board and talk to them and say, "There is an impact we have in aging versus a specific experience we have versus the dormant demand that we have never addressed where we might have an opportunity." See, I do believe that business can really be a force for good, but we have to understand what's happening in the world. We have to engage much more than now. Before, the world was mainly what we made of it, but it was really more about the perspective that was where I am, and you could have a really narrow spectrum or peripheral vision, and you could still make enough living because the market was out there, and we only need to basically open business and be there. Now it's a little bit more complicated. Why? We are changing this composition. The chemistry of the world is changing in many ways. So are you going to feel empowered or powerless about this? My conversation with you today is that you should feel actually empowered. You should finish this session— and we're going to have now a few questions— but try to think, "How do I empower myself from the macro trends that seems to be so far away from me, but if I understand them, encapsulate them, bring them into my own core, I am empowering myself to be a 21st century organization?" You are creating that match between these large-scale forces and where you really are. So to finish, Can we forecast the future? Not really. We can see those trajectories that will unfold themselves over time because they're safe, they're large-scale, they're above micro-performances. But then, once I see them, if I don't like what I see, bring it down to a level in which you can elaborate them, work them. Define a process that will allow you to figure this out so that you're creating this special link between the macro trends, the understanding we have, and your behavior. In this way, we probably will be able to understand how the future unfolds. Thank you very much.