Kris Safarova  00:47

Welcome to the strategy skills podcast. I’m your host, Kris Safarova, and our podcast sponsor today is strategy training.com and we have some gifts for you. You can get five reasons why people ignore somebody in the meeting at f, i, r, M, S, consulting.com forward slash on the room. You can access episode one of how to build a consulting practice at firms, consulting.com forward slash build. And you can get the overall approach used in well managed strategy studies at firms, consulting.com forward slash overall approach. And today, we have with us mark canal, who is an MGI partner and leads research on global progress with a focus on productivity, demographics, human capital, technology. He is based in Barcelona. Now. A lot of listeners wish they were in your place, and we are going to talk about his work, his career, the new book that is coming out, century of plaintiff. And I hope you guys enjoy it. Mark, welcome. Thank you very

Marc Canal  01:51

much. It’s a pleasure to be here. I would

Kris Safarova  01:53

love to start with your career. Maybe you could start with giving us an overview of how you ended up where you at today? Yeah.

Marc Canal  02:01

So my only, the only place I’ve worked at is McKinsey, actually, but my career has been maybe slightly unusual, although I suspect that if you ask McKinsey people, they may all say the same thing. They all, everyone feels that their career has been quite unusual, because there are several paths. So in my case, I joined in 2014 in the Madrid office in Spain. I’m originally from Barcelona, and when I joined i I was attracted by the McKinsey Global Institute, which is the think tank. So I arrived the first day, and I said, Hey, what I want to do is this thing called the McKinsey Global Institute. And you know, the answer was, great. We love. We love that. You know that you have passion. But at the beginning, you know you have to learn the toolkit. You have to learn consulting. You have to do everything right, like the path. So basically, long story short, my career has been mix of consulting and the McKinsey Global Institute first. So for example, I did two years of consulting, first of integrative consulting. Then my third year, I could move to London, do one year at the McKinsey Global Institute on doing what we call a fellowship. Then I went back into consulting. I went all the all the way to engagement manager, and then finally, I transferred permanently to the McKinsey Global Institute, where I do research, basically. So I guess that you know what that shows is that, well, there’s a million paths within McKinsey, and I chose mine, and I actually was lucky enough that I could choose mine. And I’m still here. What is it like 12 years later? I’m still here and enjoying it more and more every day.

Kris Safarova  03:51

I’m so glad for you, because so many people are not happy in their careers. So it’s always amazing to speak to somebody who is happy in their career and learn from your experience as well, and for people to see how they can make adjustments. Do you remember when you just joined McKinsey? Was there anything that was different from what you expected?

Marc Canal  04:12

Different from what I expected? Yeah, I guess, um, what? What could that be? I think that maybe

Kris Safarova  04:23

something that you,

Marc Canal  04:26

yeah, like, I think that several things surprise you. I think that probably when you’re preparing for McKinsey or for these, like big strategy consulting firms, you’re very much focused on, you know, like preparing cases, and the analog, like the analytics side of the analytical side of it, and it feels like you’re solving some sort of mathematical puzzle. And what you realize when you join is that it’s like that is important. Of course, and it’s part of the value, but it’s a much more relationship based kind of job. I think that what strikes you most at the beginning is that, and as you grow in the firm, it becomes even more of that, right? A lot of what you do ends up being about so if you’re in consulting, for example, not on my side. Now on the research side, right? If you’re in consulting, you end up having to gain the trust of clients. And you know, all these sort of intangibles matter a lot more than than you would suspect, I guess, from the outside. But even in research like my side, which you may think, Well, no, but that is really, really about the research and the analytics. Actually, it is, of course, but it’s also about what are the the what are the messages, and what are the themes that will matter most of the world and will move the needle and will even make people sort of feel something different and get attracted to topics at the end of the day. That’s how the world works as well. So I guess that’s probably the, the one thing, the other one is, like, probably the, the massive, I would say, like the, I would describe McKinsey as the most formal and yet informal company in the world, right? And I don’t know whether that that’s the only company I’ve been to. So I guess, like, I cannot claim anything about in the world. I haven’t tried others. But my feeling is that it is a combination of very formal processes, very structured, you know, like things and committees, and how we evaluate and promote people and all that is, like, probably one of the most valuable things, for example, that we have. And at the same time, you build your own informal networks of Who are your buddies and who are your sponsors and who are the people you trust and who gives you feedback. And so that’s another one that really surprised me, that you really, you really create your own networks, and you really decide where you want to go and who you want to work with, and all this to an important extent that was also quite surprising.

Kris Safarova  07:09

What was most challenging when you joined?

Marc Canal  07:12

Honestly, I feel that. I feel that when I joined, I didn’t find anything challenging the in the sense that, you know, I joined when I was 23 right? So I was, I probably had an amount of energy that I don’t know. Maybe I still have it today, I don’t know, but I, I felt I could take on anything. And I was, I was sort of learning so much, and things were sort of like fat, like, the learning curve was so steep that the I honestly don’t recall, like, you know, like, this is extremely challenging. I guess there’s one thing, one thing that I would say is that you you need to get used to learning things fast. So maybe at the beginning, that is, that is actually the most challenging, probably. So the most, I would say the most challenging the beginning is that you come to a new topic, and you have to get smart on that topic quite quickly. That was before the age of AI, by the way, well before the age of AI, maybe today, it’s simpler in some ways, but you still need to learn, like the insights. So yeah, so I would say the learning curve at the beginning can feel quite stiff, steep. And yeah, that’s probably the most challenging part, Mark.

Kris Safarova  08:39

And for our listeners who are also in consulting, and let’s say they’ve just been promoted to partner, for example, or they’re trying to get promoted to partner, and they really need to learn how to be better building relationships with clients. What would be your advice?

Marc Canal  08:56

To be clear, I’m still not a partner, by the way, I’m an associate partner, so I’m on that process myself and but, but in any case, like my what I’m what, the way I think about it and, and what I would tell other people is, you know, like you, you can try to, there’s always more than You can do, right? There’s always more that you can grasp or achieve. So I think that while trying many things, and, you know, trying to be everywhere is maybe a tendency and sometimes a bit of an incentive, I think that building maybe a slightly smaller amount of good trust based solid relationships ends up counting more than you know, trying to be everywhere all the time, because that that that may have lower returns and also. Has a higher chance to to prove complex, basically at a personal level, so at least that’s how I think about it. I hope I’m right. If I’m not right, I may not make part of myself, but that’s also fine. I enjoy my job anyhow.

Kris Safarova  10:15

Well, you already did an associate partner, your junior partner, yeah. So, so, yeah, exactly so for somebody who is now in a position where they need to build a book of business, and that comes with being able to build relationships with clients, where people see as a trusted advisor, as someone who can be trusted, and someone who has something to bring to the table. How can someone improve in that data?

Marc Canal  10:43

Well, I think that look, this is very so I’ll go to the to the McKinsey Global Institute side, because the one that I experienced most, but I think that every consultant can can learn something from it. So basically, at the McKinsey Global Institute, what we do is try to analyze the most important trends in the world, so from geopolitics to demographics to technology, right and try to put facts in those most important things that are happening in the world. That means trying to understand them and trying to see what we can learn about them so that businesses can make better decisions, and not just businesses, also policymakers or society, society more broadly. So maybe I will say one underrated thing that one can do, and that clients value a lot, is having this broader view about what’s going on and how it can impact your business and decision making. I think that, of course, like as consultants, we tend to focus a lot where we may tend to focus on the specifics of an industry, or, you know, like getting very, you know, technically knowledgeable about something, but there are all those broader, trends that impact decision making significantly, and that we have the McKinsey Global Institute try to, you know, help with, and I think that that’s that’s probably one, one area that maybe sometimes by consultants, slightly underrated, and that At the end of the day, many clients, when someone they can ask a question to and feel that after the conversation, they are at least slightly smarter or have a bit more direction to make decisions,

Kris Safarova  12:36

definitely, 100% agree with you. Do you feel that there was something that you believed about how the world works, how business world works that changed over the course of your career. You realize, no, it works completely differently.

Marc Canal  12:52

Yeah, no, I, I do think I’ve changed. So I think one, one thing that you learn when you’ve seen many businesses is that and the world in general, by the way, like even when you study like economics and social and political trends as well. But just to focus on businesses, is that within businesses, things are messier than one may perceive from the outside, I think that you know, if you have not seen many businesses, you may even think that your own, like the place that you work at, is messy, but surely, like those competitors or those other industries, may be super well structured, like things you know work like a Swiss clock. And the reality is that that’s probably part of also, like the creative and innovation, innovative process that goes on in companies, and that, at the end of the day, we’re all humans, and we make mistakes and we correct and we go back and forth. And so I would say the and that’s part of the beauty, by the way. But I would say that what you get, what is counterintuitive, maybe, is that inside businesses are messier than they look, that there’s not a there’s not a single it’s hard to find someone that can actually you will never find someone that can run the business completely like that knows every every bit like if you talk to the CEO. Of course, the CEO will have a direction, but will really rely on many people to run many other small things that the CEO cannot control totally, and, you know, like that. And it’s what’s more interesting is that that messiness at the small detail amounts to some sort of emergent order that actually looks like it’s really, really planned, right? So from within, it looks less planned than what it ends up being, or what it what it ends up looking from the outside. And part of the of the consulting business, by the way, is to put some more structure to it. So of course, there is an element of structure that’s that’s very important, but still, you know, like there’s also some messiness within consulting.

Kris Safarova  14:58

Definitely, was it? Difficult to transition from being actually on the ground consultant, working with clients, and then switching to completely different type

Marc Canal  15:06

of role, not really. I think that within McKinsey, at least the as I told you, like the we, they so McKinsey still made me go through the process of consulting, and it’s a process where I learned a lot as well, and a lot of the skills are basically overlapping. So first of all, the type of job didn’t change it that much. Also, it was quite progressive. So I started doing some McKinsey Global Institute, then went back to McKinsey, then back to MDI. But also, most importantly, we the type of research that we do at the end of the day, we do it for the clients. So I still but it’s so basically, like it’s independent in the sense that we don’t ask clients or we don’t commission any research. Everything we do is, you know, publicly available and not influenced by a client or a set of clients, but what we learn, we do share with clients, and we learn from clients. So, you know, like at the other day, I’m in contact with clients. I see clients constantly and and so it feels very much part of the process. Yeah, no, it wasn’t hard at all.

Kris Safarova  16:17

Actually. It’s actually very nice, because you don’t need to worry about the sales piece, supporting the bit and so on.

Marc Canal  16:24

And you get to an extent, yes, that is true. That is true. I need to, I need to worry about my research being relevant, basically and correct, and that has an indirect effect. But it is true that I do not need to worry about sales directly. That is true.

Kris Safarova  16:43

Let’s talk about your recent book. What were some of the key things that you learned throughout the process that really changed the way you look at things?

Marc Canal  16:53

Well, I would say almost everything, actually. So it was a it was a book that we started knowing the first half of but the second half we didn’t know to begin with. So I would say, like most of what’s written in the second part I learned doing research as I as we wrote the book. So basically, like the first part is a look back to the so to give some context to the to the listeners, basically like the first part is 100 year look back at how much the world has progressed, basically between 1925 and today, that we had, of course, we knew quite a lot already. We do a lot of research ourselves. So, so we had a pretty good idea, although we still learned quite a bit, but we had a pretty good idea of what we wanted to write there. But then the second half of the book is, you know, we created a scenario for 2100 in which we say, let’s imagine a world of plenty, where the poorest country in the in the world today, Burundi, according to the World Bank, becomes as rich as Switzerland is today, and that will be the floor and everyone else above that. And what does that mean for the world? Basically, like, how can we what’s the best way to get there? What are the requirements to get there, in terms of energy, in terms of materials, in terms of food, in terms of technology, in terms of productivity, what happens to demographics and all of those we really didn’t know to begin with. So, so you know, like that was probably the, the part that I learned most about,

Kris Safarova  18:35

definitely, and you looked at admitted trends, of course, and as part of your work you do. And one question that all our listeners have is, What will likely happen now with the changes that are happening, especially when it comes to AI and automation, what are your thoughts on that

Marc Canal  18:53

so well, that’s that’s pretty broad. So we could, we could talk about AI for for hours from several angles, I would say that, or I view AI as the biggest opportunity that we have to create a productivity revolution that lifts us up and that improves living standards for everyone, actually. So basically, I think that we’re we’re now in a bit of an inflection point where, you know, like many things are happening, like demographics are changing, geopolitics are changing, the energy world is changing. And, for example, on the demographics front, we’re going to have a bit of a demographic drag. So we have pretty low fertility rates, you know, like some in some countries, or many countries actually are aging fast. So we have some things that wear tailwinds that are turning into headwinds. But at the end of the day, what has pushed us forward in history? Over the last 100 years, or even 200 years, have been technological revolutions, and AI is our best bet, of course, alongside many other technologies. So I don’t want to only focus on AI. There’s many things that will also be helpful and complementary to AI, but also on their own, are very important, from health and biotechnologies to energy related ones, etc, etc. But, yeah, but I would say, like AI, is our best bet to actually grow productivity very fast, and what we need in the future to lift living standards is growth and is productivity.

Kris Safarova  20:36

Many of our listeners are now in a situation where they are looking at the skill set, and they think, Okay, I’m great at writing, but AI can write. I’m great at this other skill, but AI can do that. And they’re starting to worry, what do you feel people can do? Our listeners can do to remain relevant.

Marc Canal  20:57

So I think we have pretty good research on that. Actually, we published a report in December, I think that’s called agents, robots on us, that I would tell people to go read, because it’s very good. And there we talk about skills a lot, actually, but a lot of the research on AI and technology, quote, unquote, automating jobs tends to focus on hours, right, like on hours worked, and tasks like, we can automate X percent of tasks, that’s a classic but we take we go one step further and say, Okay, but what about skills? Like, all these tasks are related to certain skills, and what we find is that there’s a very small percentage of skills that are purely that are purely AI or purely agent robot based, and most of them are shared. And actually, some of the ones that you were already mentioning are shared. So the fact that AI can write doesn’t mean that it will write on its own right, like that’s clearly a shared skill. And the fact that AI can help with analysis doesn’t mean that AI will make the decisions around how to do the analysis or how to apply that analysis to a certain situation or to another situation or etc, etc. So basically, I think that the key here is working with the machines, working with the AIS and not versus the AIS, and that’s what, what’s always happened in the past. So, and actually, let me go back to one more thing, which I think is very important, you remember. And of course, that was not, this will almost seem staged now, but I promise it isn’t earlier when you asked me about what surprises you about companies, what I said is they are messier than one would think, and that is really important for humans. All this messiness is much harder and again, like I don’t say messiness in a bad way, but all this messiness, all these bottlenecks, all these things that have to be solved, all this problem solving, all this conflict resolution, all this like that is there are things, these are things that humans need to resolve again, like in many cases, with the help of AI, which can provide good information. So I think that if you put together a that there are bottlenecks everywhere, that there are many things that need to be resolved and the world’s messy B that many skills that are human, and by the way, even more human than the ones that will get automated, are very complementary to AI and will grow and see probably, that many things will grow in demand so that AI makes them cheaper, so that, for example, coding may be may get easier. And so we need, quote, unquote, 20% of the coding effort per line of coding, or 10% but then coding multiplies by 20, so you end up needing more coders, not less or more computer engineers or whatever. If you put that together, I think you get to a potentially better world if we can work with the AIS.

Kris Safarova  24:09

Are there specific skills you think our listeners need to focus on now, strengthening, developing and many of our listeners, they are leaders within major organizations or their senior people in consulting,

Marc Canal  24:25

I think that probably there’s, there’s two. So if I had to say, like, two big groups, right? There are all the ones that have to do with relationships, management, etc. So you’re talking about, for example, like consulting, right? All of those are inherently very related to consulting, but also not just in consulting, right, in firms. And those are ones that I think are inherently human, really hard to automate, and not not just hard, like, technically hard, it’s also like, to what extent will we want to automate, even if. Could automate some parts. So I think that those are a very important set of skills. But then the other ones are the ones that have to do with AI. So you could call it AI literacy, right? Getting more AI literate is something that will make you not get replaced, of course, is substituted by AI. It will make you more valuable next to the AIS. And we have some data from from last year in the US. So if, like we did some search on like, what skills are growing faster in demand and and skill that has grown the most is indeed AI literacy, and it grew seven times only last year, so in the US. So I would say, like all the ones that are, again, that’s good news more human, right, because they’re very complementary with AIs. But also what you could call AI literacy more broadly, which is basically working with AI and taking all the potential from AI to maximize the return of the combined or the partnership between humans, agents and robots.

Kris Safarova  26:11

For listeners who feel they’re kind of a little bit behind because they have too much on their plate in terms of their own current obligations, and they’re kind of a little behind on AI literacy. What would you recommend they do to try to catch up?

Marc Canal  26:25

First of all, let me say it’s, it’s, it’s a quick transformation. But also, again, going back to the bottlenecks and the messiness of the world, it’s also, I think that it may be slightly overblown, and there’s some incentive to say, look like in six months, this will be completely different. The reality is that real life is slightly more complicated than that. So first of all, I would say there’s no point in panicking too much and listening to like. I mean, you should always listen right, but it is very easy to make the news by giving like a massive, you know, headline that makes everyone very nervous, right? And I think that, in general, life is a bit more complicated, so that some big claims are hard to believe in that sense, let’s put it that way. So that’s one part of it, just not panicking, but the other one is really about this is really about trying and experimenting and asking around and so forth. Just let me give you an example that we’ve done at the McKinsey Global Institute. We’ve created a small AI group, which I’m part of, and we organize things around AI. So, for example, I gather news and interesting articles and send them around once a month to all the colleagues that, you know, it’s hard to keep up with all the articles and all this. So I’ve taken this job and I just sent a bunch of articles every week. So someone, anyone can do that. And, you know, get a bunch of articles and send to their friends and whatever. But also, some people are, of course, much better and sort of at using AI at what’s called today, vibe coding and all that. So we organize small sessions in which anyone can join. It’s very friendly, and we get one person that is good at, for example, vibe coding, and they will teach everyone else, and we’ll do a session, and then people, you know, go away and try their own things and all that. So I think that in a large part it is experimenting and trying things and having fun. At the end of the day, it’s a it’s a fun thing

Kris Safarova  28:34

to try. Definitely. Do you have favorite publications that you go to in terms of getting news for what you’re going to send at the end of the month? Yeah, absolutely.

Marc Canal  28:45

I I follow many, I tend to follow quite a bit of sub stacks and and X accounts. I can even, I don’t know if you have, like, show notes or something, I can send you a bunch, and I’m happy to to share those. But I think that there are really, really good people basically like, okay, so books are very good, and there are some good ones, but I think that in a it’s it changes so fast that some books that have very good principles can be useful, but often books that want to be very precise get outdated quite fast. So I believe that in this area, it’s better to follow a bunch of substack accounts. And those tend to be really good and get updated very often. So basically, or they have new articles very often. And you know, like, there are this polemics, like, all of a sudden there’s a new article that says, I don’t know, like AI is going to take all our jobs, right? And then in like a day, there’s eight pieces that will answer to that one saying, Well, no, that is wrong because of this. That is wrong because of that, right? So there’s, there’s a whole debate. I think that, again, no one should feel. Uh, obliged to follow those debates in detail, as I do, because I enjoy it, but I think that there’s following, like, two or three sub stacks that that already gives you a lot of a lot of insight without, you know, getting extremely busy or devoting a lot of your life to that. Do you

Kris Safarova  30:18

personally feel concerned about AI and automation and what it is doing in terms of how it impacts people.

Marc Canal  30:27

No, I don’t feel concerned about it. I feel that so far, it’s made my work much better and more productive. It’s done my it’s made my teams work, also much better and more productive. Now I think that there are some things that are important to keep in mind. So, for example, one thing that so I write a lot right? Like I write reports, and the other day and I and my teams write reports. So one thing that I do when I insist my teams do, is, it’s very easy to just say, like, look, have a even if you have a very good prompt, right, like, but have a very good prompt, and then the AI will write something, right? And once you read what da has written, you know, like there’s some sort of confirmation bias, plus your prompt was already, of course, like in that direction. And so it’s very easy that you will not iterate it too much. You will just say, that’s good. That’s it, right? First, that in terms of style, tends to be a bit boring and not personal that. But second, even content wise, it can be improved substantially. And the reality is that that’s not how the process works, right? Like when we if you, if you forget about AI one second, we don’t normally like think, stop thinking, then Right? That this does not how it works, right? How it works is, you think, you start writing, but then the process of writing makes you iterate your thinking, and then you look at it, and then you think again and write a bit more, and then change the order. And then so I think that it’s important to find ways to not lose that process. And I’m using one example of writing, but I think that that cuts across many things, and I insist on my team, on my teams, to just make sure that they iterate their own writing that then if it’s through prompts, through prompts, I think that one advantage of AI is that you don’t have to write everything that nicely, so like you can be quicker at doing it, but still not losing This process of iterating and thinking about it, because to summarize it in a sentence, like writing is thinking, right? So, so, and part of your thinking happens through the writing. So just being careful about those things and trying to identify them and trying to act act upon them, is very important. So No, I’m not worried at all. I’m not concerned. I think that it’s almost all, or most of it upside, but I think that one has to be careful with certain things like this one,

Kris Safarova  33:11

and not to lose important skills, because if you’re not going to lose it, if you’re not doing the work. So for someone reading the book, and the book is very interesting. What are some of the key things you want people to take away after they close

Marc Canal  33:27

the book? The main things to take away are that a future of plenty, a century of plenty, is possible. It’s a real possibility that for that, we need substantial economic growth, and that economic growth is good, that there, that this is possible because there’s enough and we can generate enough of everything that we need for it, so we can generate enough energy. We can generate enough or we can extract enough materials and minerals in a in a clean and sustainable way, that we can generate enough food, that we can innovate enough, etc, but that this is a choice, I think that the most important message is that progress does not happen to you. Progress is a choice. So you have to choose it. You have to imagine it you and you have to build toward it. You have to invest in it. And that, I think that today, we’re a bit in the middle of a bit of a pessimistic mood. So I think that changing the narrative a little bit and moving toward or trying to be more optimistic about the future based on data, by the way, which is what we try to do in the book, and to prove why there’s more reasons for optimism than it may seem. That makes it more probable, not just possible, but probable that we choose this future. And. That we build toward it.

Kris Safarova  35:01

So you talk about the crisis of hope in the book. Have you had a certain period of time, or maybe just a few days in your own work, in your own life, when you personally felt that as well, and how you were able to pull yourself out

Marc Canal  35:18

of it? Well, I’m not, I’m not sure my ways will work for everyone. My in general, I would say I’m a, I’m a pretty rational person in the sense that facts can convince me and change my mood, so like, if I, if I feel, if I feel something is really wrong, or like the world is, I don’t know, like, let’s say that I felt that the world’s going to hell, and that, you know, like, we should all be in a real like, the crisis of hope is totally justified. When I look at the data, right, I can see that, you know, like, actually, the world has improved a lot, that the reasons why, or the ways in which it has improved depend on us, that some of them, like human capital, like technology, like are probably better and have bigger opportunities than ever before. So like, when I look at all this from a rational standpoint, it also makes my mood and my feeling change. Now I, I don’t mean to say that, like, maybe some people are just more emotional and, you know, like, basically, I’m also emotional in many ways, by the way, but, um, but, but. But I think that this, this is a way that works for me, basically, Now, having said that, another one that I think matters is perspective, right? So what, what writing about 100 years gives you is perspective. It shows you that every day, especially today, with so much access to information, every day, it feels like we’re living through a civilization changing event, right? Like every day, there’s something that will change us forever. And the reality is that when you take perspective and you look at 100 years, first of all, bad things happened in the past, too, and we overcame them. But also, second, there are many, many, many, many, many things that happen, and a very, very small percentage were that important or changed history forever, right? So I think that also having some perspective is really helps. Basically, do

Kris Safarova  37:38

you see certain mistakes we are repeating because we are not very familiar with the past.

Marc Canal  37:45

That’s a really good question. Well, I think, I think being the main one is probably being very pessimistic. I think we have a pessimism bias, right? So I think that we’re pessimistic bias. I think that if you take any decade over the last 100 years or 200 in which we have been improving. So let me actually, let’s, let’s put the numbers on the table, right? So like over the last 100 years, like global incomes and I’m counting every human on the planet multiplied by six. Life Expectancy went up by 40 years. Child mortality went down from like one in three children dying before the age of five to less than 5% globally and in advanced economies, it’s close to 0% maternal mortality. Same thing we did all that, by the way, working a lot less so like on average in the world, in or in the countries where we have decent data, 100 years ago, we worked 2300 hours per year, like the average worker today, it’s closer to like, I think it’s 18 or 1700 so it’s so we did all this working less, right? Because we got more productive and we got better at using resources, etc, etc, so, and with all that that happened over the last 100 years, right? And with all that you took any you take any decade, and it’s very easy to find headlines, to find that, you know, like things are getting worse, that that things are going badly, that we should completely change course, that. And of course, there’s always something to improve, right? Like I’m not, I’m not saying that, but I think that one quote, unquote mistake that we, that we probably make, to an extent, is, yeah, to lose this perspective, maybe, and always being it’s maybe part of not being complacent and just trying to get to the next level. I don’t know, or it’s a matter of expectation, but the reality is that we, we keep doing that. Probably the reason, by the way, and that stems from another mistake, is that we tend to, we tend to underrate human ingenuity. So I would say that, basically, humans are pretty. Good at being creative, at innovating, at adapting, and it’s very easy to see the problems of the present. It’s very easy to actually have sort of, how is it called, like nostalgia about the past, because we only remember the good things today, we only see the bad things, but it’s really hard to imagine the future. So even when we think and going back to AI, if you want, right, like it’s very easy to observe a task and say this by a robot, right? So that’s the negative side of it. It’s really hard because it hasn’t happened yet. So no one knows. It’s really hard to imagine how this task will complement something else, it will grow with it, or how another completely new task will emerge. So to an extent, it’s natural, but also mostly wrong, if you look at history. So, so, yeah, so that’s probably, that’s probably one other mistake that we do, which is underrating our capacity to create and to

Kris Safarova  41:04

adapt mark and what can all of us do in our individual capacity so that we can contribute towards the next 100 years being another center of plenty? I think

Marc Canal  41:17

we can do many things actually. So one is if, if you believe, like me, that there’s something about the narrative and that the narrative is self fulfilling. So one thing we can all do is try to be a bit more positive. Try to, you know, look at good things that happen and try to talk about them. And I know that, you know, like the news, have a negative bias, and that, you know, the algorithm chases us with with bad news and all that. But taking a step back, I think that there’s a I think everyone knows, like, it’s very funny, because if you ask people, is the algorithm feeding you bad news more than actually, you know, like that. They’re not representative of the world. Everyone knows that, right? Like everyone will say, yes, absolutely, that is true, right? And yet they will still look at those news like, read those news, and still be negative about the world. So one thing I try to do, by the way, is post good things about the world. So this morning, I posted on LinkedIn that that cancers adjusted by like, so cancer rates adjusted by age are down by more than 20% since 1980 we don’t hear about that, right? In general, actually, maybe the perception is, oh, no, cancer is going off, right? Like, I see more people that have cancer. Actually, the reality is that part of it is because we live more years and, you know, like so older people have more cancer, but at a given age, you’re at least 20% less likely to have cancer today than 50 years ago. So that’s a good piece of news that you know you can, you can also decide to focus on those so I think the one thing that people can do is try to, again, step back, get some perspective, and find but try to look for more positives. But then, at an individual level, there’s many more things we can do, like, for example, at the end of the day, when we talk about productivity, economic growth, like those things feel very high level. Feel very like things that the country does. But the reality is that it’s a sum of individuals, and it has to do with investment, using technology, growing your human capital, learning skills, being creative, creating new things, and all of that. And you know, like, again, this world is messy, but being playful with this messiness, and, you know, trying to thrive in it, I think, can get you a long way. So everything that feeds into esoteric concepts, if you will, like productivity or individual human decisions that we can all make, deciding what you want to invest your time on, you know, like deciding how you invest, if you’re, if you’re an individual, of course, but also if you’re a company, right? Like, if you’re, if you have some sort of decision on how on the portfolio of a company, right? Like, what kinds of products you’re investing, what kinds of services, so pretty much, not every decision we make. Of course, there are many individual decisions that are that have to do with other things than economic growth and economic progress, but a decent percentage actually influence that mark.

Kris Safarova  44:31

And in doing the research for the book, did you come across something that seemed almost unbelievable at first?

Marc Canal  44:39

Probably, yeah, there were, so there were some, I would say unbelievable, actually, what, what was, what was surprising to me is that most things were within very reasonable targets. So, like, I wouldn’t say that, like, was unbelievable. I. Um, but basically, when you do the numbers and you start looking at, okay, so how much more energy will we need? How many more materials will we need? You know, like, how much food and how much productive or, like, how, how much should the agricultural yields increase? Etc, what do you what is surprising maybe, is that all of it feels a challenge. Of course, it’s not easy, but it feels very doable. So I wouldn’t say anything surprised me massively in the sense that, oh, it’s totally unbelievable, but, but it was an extent of surprise, actually. No, I will say one thing that that I found very, very surprising and almost, quote unquote unbelievable, which is that when you look at the future right, when you think about the world, quote unquote, getting to Switzerland, as we as we put it right in the book, meaning every country at least as rich as Switzerland, if not above. What you see is that the rate of growth that you need for that is very similar to what we’ve experienced in the past. So at first I thought, okay, like it will look feasible, but it will require a very large acceleration of what we’ve experienced in the past, which is possible, you know, like I’m, you know, I’m very optimistic. I’m pro human. I think that with technology, we can do many more things with human capital tetra, but it will. And actually, what you find is that the accelerate, this is a very, very small acceleration, if at all. And and that was probably quite surprising when we looked at the past and our past lives and our grandparents lives, the amount of progress would have seemed completely unbelievable in 1925 right? Like so in 1925 you would have said, Oh my god, no. Like that. There’s it would have, it would have felt, probably much further than today, thinking, okay, like, let’s get, let’s get every human being to Swiss levels of prosperity. So one exercise that we did, for example, is like I and I did this one personally. I listed a bunch of things that the richest country on Earth, like the US in 1925 a bunch of things that the average person in the US did not have in 1925 and the list is absolutely insane like and of course, we tend to think about the big innovations. We tend to think about semiconductors and smartphones and which are obvious, right? But people did not have plastic bags. People did not have zippers. People did not have many things, of like normal hygiene that we have very close to us, right? People did not have, of course, all sorts of vaccines, most like, I think it’s about half of people did not have indoor plumbing. In rural areas, about 10% of people had access to electricity. That was, like 100 years ago. So actually, maybe what was most surprising is like this, when, when the amount of progress we did, we made in the last 100 years. Gets to a detailed example, like when we look at the details, that was probably what, what? What made it specific for me, and more, most surprising mark

Kris Safarova  48:33

and another question I wanted to ask you, so in your book, you write that someone from 1925 would see today’s technology as magic. What do you think are some of the ways we underusing technology right now that someone from 1925 would see it as magic? And I realize we only have few minutes, it could be very quick answer.

Marc Canal  48:53

I’m trying to think through some of the technologies that like but we have a so we have a piece of research that’s called arenas of competition, that basically looks at not just AI, but like the main technologies of today and the future. And so I think that many of them are probably today, still underused, because they’re developing, right? So that’s probably good answer. So like they’re in that in those categories, there’s a lot of around robotics that for now, I think, like, basically, so a good answer probably is, like, today, we still don’t see many robots around us. So, like, technically, probably we’re, quote, unquote, under using them, although you could, I mean, there’s, there’s a reason why, right? Like, because they still have to, like, scale and improve and decline in price and all that. So it’s always hard to say, like, we’re under using a technology, but in any case, like something that in very few years, probably we’re going to see a lot more of, is things like robotics. But then, like, there are others like space, for example, space technologies, like today, we are using more. In more space, but still not much. Probably like self driving cars, they’re thriving in like self driving cars would have looked completely like magic, right to someone in 1925 and today we are. We’re seeing them in some places, but they’re still very concentrated. And I would expect we see more of them in the future, but we also know that there’s all sorts of limitations, like our own self imposed limitations, like regulation, like all sorts of other things that may limit the usage as well. So again, I’m not sure we’re under using them today. I would say we may under use them a bit in the future, because of our own self imposed limitations. Yeah, and anyways, I could go on and on, like maybe within construction, for example, we haven’t improved productivity of construction for now several decades. We have some new techniques like modular construction and industrialized types of construction, and we’re still, probably still under using that a little bit, and I expect there will be a lot more of that. Anyways, I could, I could go on and on and on and on, like technology by technology, but those are some examples that come to mind.

Kris Safarova  51:11

Mark, thank you so much for being here. Such an incredible discussion. I really enjoyed it. Where can our listeners learn more about you? Buy your book, anything you want

Marc Canal  51:19

to share? Oh, thank you so much. Our book is on Amazon. It’s called a century of plenty, a story of progress for generations to come and in general. If you follow me on X, on LinkedIn, I post on all sorts of things. I don’t only post about my own book. I’m interested in many, many topics. I sometimes talk also about other things that I enjoy, that I love, like cinema, music, science, all sorts of things. I try to, I try to be, you know, not knowledgeable, but I try to enjoy other things as well, not just economics. So, yeah, all the above, just follow and interact also. That’s also fun. I try to answer when people interact. So yes,

Kris Safarova  52:04

that’s it. Thank you, Mark. Thank

52:06

you for being thank you so much pleasure.

Kris Safarova  52:09

Our guest today was Mark canal, and you can get his book. It is called a center of plenty. And our podcast sponsor today is strategy training.com you can get some gifts from us. You can get five reasons why somebody knows someone else in a meeting and you don’t want to be that someone else. So you can get it at terms consulting.com forward slash on the room. You can access episode one of how to build a consulting practice at firms, consulting.com forward slash build. And you can get the overall approach used in well managed strategy studies at firms consulting.com forward slash overall approach. Thank you so much for tuning in, and I’m looking forward to connect with you all next time.