David speaks with Luca Dellanna, a management advisor and author.

Luca is the author of multiple books, including "Ergodicity" and "Best Practices for Operational Excellence".

His work emphasizes the importance of understanding risk, maximizing longevity, and making high-quality decisions in various domains.

They talked about:

๐Ÿ’ก The concept of ergodicity: The lesson is that survival matters more than performance, and irreversible losses can absorb future gains.

๐ŸŒŸ The importance of avoiding extremes: Finding a balance between extremes is crucial to minimize risks and maintain well-being.

๐Ÿ“Š Optimise for average: Consistently being average over time can lead to being above average in the long run.

๐Ÿ“‹ The role of good coaches and managers in providing actionable feedback: Maintaining skills, culture, and reducing risk through regular maintenance is crucial for long-term success in organizations, even if it may not maximize short-term results.

๐ŸŽ™ Listen in your favourite podcast player

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๐Ÿ“น Watch on Youtube

๐Ÿ‘ค Connect with Luca:

Twitter: @DellAnnaLuca

Books: Ergodicity | https://amzn.to/42K6Z3j

Best Practices for Operational Excellence | https://amzn.to/3qI5WDW

Website: http://luca-dellanna.com/

๐Ÿ“„ Show notes:

0:00 | Intro

2:49 | What is ergodicity and why is it important

7:35 | An example of ergodicity in action

8:55 | How ergodicity can manifest in our lives and work

11:34 | Optimizing for opportunities, not just outcomes

15:42 | Avoiding extremes in all areas of life

16:00 | How to avoid arguments in relationships

20:06 | The compound effect of being average

25:41 | How to create a culture of excellence

26:50 | DuPont's culture of safety

29:44 | The importance of near-miss incident investigation

34:11 | How to identify and mitigate risks in your life

43:43 | How to help your employees improve

44:25 | The danger of judging decisions based on outcomes

51:52 | When to make the best statistical play, and when to trust your gut

54:06 | Why does Luca write so many books

58:45 | Luca's writing process

1:01:41 | Books that have inspired Luca

๐Ÿ—ฃ Mentioned in the show:

Elizabeth Swaney | https://www.theknowledge.io/issue66/#:~:text=Exceptional mediocrity

Freestyle World Ski Championships | https://en.wikipedia.org/wiki/FIS Freestyle World Ski Championships

Elon Musk | https://en.wikipedia.org/wiki/Elon Musk

The Success Equation | https://amzn.to/3p38kog

Michael J. Mauboussin | https://en.wikipedia.org/wiki/Michael J. Mauboussin

The 22 Immutable Laws of Marketing | https://amzn.to/43FgNwS

DuPont | https://en.wikipedia.org/wiki/DuPont

David Epstein | https://twitter.com/DavidEpstein

Range | https://amzn.to/43UpH9C

Annie Duke | https://en.wikipedia.org/wiki/Annie_Duke

Thinking in Bets | https://amzn.to/3X5z04k

Steve Carroll | https://en.wikipedia.org/wiki/Steve_Carell

Greg Popovich | https://en.wikipedia.org/wiki/Gregg_Popovich

Nasim Taleb | https://en.wikipedia.org/wiki/Nassim_Nicholas_Taleb

Antifragile | https://amzn.to/45Zw5yf

Scaling People | https://amzn.to/43EhmHh

Claire Hughes Johnson | https://twitter.com/chughesjohnson

Bent Flyvbjerg | https://en.wikipedia.org/wiki/Bent_Flyvbjerg

How Big Things Get Done | https://amzn.to/3X8uCBO

Full episode transcript below

๐Ÿ‘จ๐Ÿพโ€๐Ÿ’ป About David Elikwu:

David Elikwu FRSA is a serial entrepreneur, strategist, and writer. David is the founder of The Knowledge, a platform helping people think deeper and work smarter.

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๐Ÿ“œFull transcript:

Luca Dellanna: For the organization, they don't really care if 10%, for example of the employees churn each year because they just substitute them. But you as an employee, you care very much if you burn out or if you lose your health other kind of things. And you can see the difference in incentives. Another typical example is with startups, venture capitalists like a big investment fund. They invest in hundreds of startups with a hope that one of them is the next Google or the next Facebook. And to get such an extreme outcome being the next Google, you need to push your funders to take extreme risks to work a lot. And maybe there would be 90 companies that fail, 9 that kind of make it and 1 that becomes the next Google. You as an investor, you will be extremely happy because the one Google makes it for hundreds of failure.

David Elikwu: Hey, I'm David Elikwu. And this is The Knowledge. A podcast for anyone looking to think deeper and work smarter. In every episode I speak with makers, thinkers, and innovators to help you get more out of life.

This week I'm speaking with Luca Dellana. So Luca is a management advisor and an author of multiple books. I think he's written nine, he's already about to publish a 10th, and we primarily focused on two of his books, one Ergodicity and the other Best Practices for Operational Excellence.

And so you'll hear us talking about this concept of Ergodicity what is it? What does it mean? How can you factor it into your thinking to make higher quality decisions and start realizing what you might be optimizing for?

Then we talked about management and some of the principles and best practices for managers.

And then we talked about decision making writ large and how we can wrap all of the different concepts that we touched on into making high quality decisions on a consistent basis, particularly when the stakes are high and when time is short. So that part was really, really interesting.

And then finally, we talked about Luca's career as a writer. his journey so far and his writing practice, how he manages to write so many books? How he manages his time? What his routine is like? Et cetera.

You can find Luca on Twitter @dellanaluca and his website is luca-dellana.com.

You can get the full show notes transcript and read my newsletter @theknowledge.io.

Every week, I share some of the best tools, ideas, and frameworks that I come across from business psychology, philosophy and productivity. So if you want the best that I have to share, you can get that in the newsletter at theknowledge.io.

And you can find the video version of this podcast on YouTube.

And most importantly, please don't forget to leave a review ideally on Apple Podcast because it helps us tremendously to reach other people just like you.

Awesome. So I thought we'd probably start with the book Ergodicity. It's probably the strangest term out of all the books you've written a few books actually, and we'll come to that in a moment. But maybe you could explain this strange word that not everyone might have heard of and why you think it's so important.

Luca Dellanna: Yes, usually I always begin with an example because it's much easier to understand and I begin with the example of my cousin, who very younger was excellent at skiing, made it to the world championship for his age bracket, and then suddenly he had the an injury to the leg, another injury, and then he suddenly had to stop professional skiing even before he reached 18 years old.

And from him, I learned the lesson that it's not the fastest skier who wins races, but it's the fastest one of those that who make it to the finish line. And so already you can see a principle, which is that survival matters more than performance. Now when I say that, usually people say, Yes, look, I understand that survival matters, but are you sure that it matters more than performance? And so in the first chapter of the book, I run an example with some numbers and imagine that my cousin, brilliant skier, he has a 20% chance of winning each race, but he also takes a lot of risks and he has a 20% chance of breaking his leg. How many races does he expect to win in a championship made of 10 races? And the naive answer would be two races because we say there are 10 races. Here's a 20% chance of winning each, 10 times 20% makes two. The actual answer is, 0. 71, less than half of that. And the reason is because if he breaks his leg in the first race, he cannot participate in the second one and he cannot win it.

He only has an 80% chance of participating to the second race, the expected number of wins is not 20%, but it's 20% times 80% makes 16%. He has even fewer chances of participating to the third race, and so on. So if you run the numbers to discover that the expected number of races that he wins is 0.71.

Which is much lesser of 0.2, and that's because the big principle is irreversible losses absorb the future gains. In this case, the problem if you break your leg is not just that you lose the current race, but you lose all following races as well. And we can see this in career, for example, if you break the law or you break the trust of your clients, you lose the chances of working with them in the future.

In a relationship, usually the most time you spend with a person, the more you build trust. But if at any point you break the trust of the other person they want, they will not want to spend time with you anymore, which means that you will not be able to rebuild trust. And so the thing is, whenever we hear about the average outcome of an action or the average outcome of a strategy, that's usually related to the average if we get to continue playing the strategy infinite times, or very long time. But if we cannot do that, the average outcome will be very low. And that's why we should, in our everyday life, try to maximize the chances that we can play as long as possible, or that we can stay in a career as long as possible in a relationship, as long as possible, and so on. And basically, Ergodicity is the name of the studies of this kind of phenomena.

David Elikwu: Yeah, even as you're describing it, I'm sure people will be hearing what you're saying and not fully grasping it, because I think it's very underrated the way that the principal works, and you've done a great job of explaining it. But I think it's one of those things that someone could just say to you one day, like, oh, you know, it's not so much the average outcome, but it's the individual outcome. Like the individual outcome doesn't always match average outcome and people might not fully grasp exactly what that means for them.

And I think you've also used the Russian roulette analogy, which I think also makes a lot of sense, which is essentially that, you know, you might have the statistical odds of how likely you are to survive a game of Russian roulette. It sounds like, oh, you put one bullet in the chamber of a gun and there's five empty ones. If there's six chambers. You know, there's five empty slots and there's only one bullet. So it seems like, oh, your odds are likely that you'll survive. But actually as soon as you miss once, then that's the end of the game. You don't actually get to play out the rest of the odds, so you don't actually get to enjoy the rest of it.

And the skiing analogy that you gave is quite funny because it reminds me of something I wrote about not long ago, actually, probably a while ago, which is about a skier. I'm not sure if you've heard of Elizabeth Swaney.

Luca Dellanna: No.

David Elikwu: Okay, good cause that was the point. The point is almost no one has heard of this girl and she managed to become an Olympian and all she did is very boring skiing. So she figured out there's certain rules for the Freestyle World Ski Championships where you are scored in certain ways, and she figured out how to game the system. All she did was she turned up to as many events with a small amount of people as possible, so she would only go to events with less people, so the competition wouldn't be too high. And she didn't do any tricks. She just did the most boring ski runs you could imagine. So she did no tricks, but what it meant is that, she just racked up the points because everyone else that was doing the fancy jumps and actually optimizing for coming first would get injured over the course of the qualification period.

So people would get injured or people would take time off or all kinds of things would happen to them and all she did. And so when she actually turned up at the Olympics people were booing because they didn't necessarily, you know, the way that she skied might not have been the best to look at, but that's how she made it this far. Simply by not optimizing for being first.

Luca Dellanna: Exactly. That's a great example. And I love it because it's a strategy that it's easy to reproduce. Oh, not necessarily easy because it takes a lot of effort, but it's likely that if you put the effort, it'll yield the results. Whereas there are a lot of other strategies where even if you put a lot of effort, you are still not guaranteed the results. And that's another very important point.

David Elikwu: Yeah, so maybe we can talk about some real life examples of how this concept of Ergodicity can start to manifest in our lives or maybe in our work. So I know that you've talked about how it can influence organizations so you can have, So I used to work in corporate law and I think, an analogous example to one that you gave was that you have some companies that might optimize for just getting as much out of their young associates as possible and so you know, you are overworking a lot of your junior employees and the junior employees might churn before you as the organization. Your odds don't change because if you just replace those workers like over a certain number of runs or over a certain period of time, you can still get the same outcome, but the outcome for you as an organization is then different from the outcome of the individual employee. So maybe you can explain more about that.

Luca Dellanna: Yes, exactly. So in this case, we have different incentives. For the organization, they don't really care if 10%, for example of the employees churn each year because they just substitute them. But you as an employee, you care very much if you burn out or if you lose your health other kind of things. And you can see the difference in incentives.

Another typical example is with startups, venture capitalists like a big investment fund. They invest in hundreds of startups with a hope that one of them is the next Google or the next Facebook. And to get such an extreme outcome being the next Google, you need to push your funders to take extreme risks to work a lot. And maybe there would be 90 companies that fail, 9 that kind of make it and 1 that becomes the next Google. You as an investor, you will be extremely happy because the one Google makes it for hundreds of failure.

On the other hand, If you are a founder, you don't care about the average returns of your investors, you care about your company succeeding, which means that you should take much less risks than what is optimal for your investors. And this is an example of like how we should be aware of the fact that there is no optimal strategy. The optimal strategy depends on whether we are gamblers. For example, the investment fund, which spreads of multiple gambles. Or if we are a single gamble, for example, we are the founder and it's just us.

We have one chance and we want to make the most out of it. And in the latter case, you shouldn't do what's optimal for an investor. You should do what's optimal for you, which means taking less risk, focusing on staying in the game as long as possible. And so on.

David Elikwu: Yeah. But there's also another level to the investing analogy, which I think you've touched on in the past as well, which again is something I have definitely failed to appreciate in the past, which is that you are not just maybe the first layer you're optimizing for how many pulls of the trigger you get. So if I have. 50,000 pounds and I could invest 1000 pounds into 50 companies, then you could have a great outcome. But that is assuming that in that type of scenario, the amount that you invest you never end up with an outcome that is worse than what you put in. You can only go back to zero.

But there's other forms of investing where if you're investing in the stock market, the return that you get can be negative. And so if I'm investing in using the similar example in 50 stocks, instead of say 50 companies, if I invest in 50 companies, if they lose my money, then I just lose the amount that I invested. If I invest in 50 stocks. Some of those stocks could end up being worth significantly less than what I invested into them. And so what it means is that there's a potential that some of your investments could actually wipe you out, or some of your investments can have a much bigger negative impact. That means that you don't actually get to, the numbers don't work out anymore, like you don't get to keep playing the rest of the averages. If I thought that I had maybe 50 investments that I could make, and the third investment goes down completely, and it becomes a huge negative on my portfolio, then I actually can't afford to play out the rest of those scenarios.

Luca Dellanna: Yeah, I think that what you mean is like if you invest in different types of investments, like some where they have a limited drawdown and some which have like, which they can go to zero like all the way. And indeed you should be very careful of the second type because, once they go to zero, they cannot go back up.

So for example, even if you read that the average I don't know, very risk that the average startup investments has a positive gain. You should consider that if you invest in one single startup and it goes to zero. Then you will not get to the average positive gain. And that's why usually the advice is never to invest everything you have, but always to keep some cushion, even if the cushion sits in your bank account or in a very low return fund because if part of your investments go down, then with that cushion you can try to invest it and grab some of the future gains. Whereas if you don't have the cushion, if things go down, you need to disinvest maybe or you cannot anyway grab the upside.

David Elikwu: Sure that makes sense. And I think there's probably a ton of other applications as well. I'm thinking even in a personal life, you made an earlier reference to just the idea that I think it can be very easy to default to only thinking about maybe something like compounding. Where, you know, it can be an easy frame might be, oh, I would like to do more exercise because when I'm 50 or when I'm, let's say like 70, I would love to be in great shape. And so if I start exercising a little bit, then by the time I'm 70, I can be in good shape. But I think, sometimes you can also have the incentive that, oh, actually 70 is still a long time away. Maybe I have some time and I can wait.

But I think when you think of the concept of Ergodicity, it's the fact that you know, if you get injuries at any of these points, you know, let's say you don't have a great posture and so it might seem like, oh, you have all of these years up until the point at which, okay, if I quickly do some exercise now, then I can get in good shape. But actually there's the negative compounding effect of, oh, actually if you have good posture or you have some kind of injury at an earlier stage, then you've already decreased the quality for later on. And so you don't get to, you don't get to keep playing the game effectively.

And the same, let's say in relationships. It might be the case, let's say that, oh, you could have five arguments with your wife before she wants to divorce you, but actually, if the first argument is particularly bad, or the third argument is particularly bad, you don't get to have those future chances. And so you can't just work out the law of averages for the long term. You have to think about the variance or the variability of how bad each of the chances could be.

Luca Dellanna: Yes. I think that the point is that you have extremes at both ends. So for example, your exercise is too much, you might have an injury. You don't exercise, you become weak and that also increases your chances of injury. And so the point is to try to exercise as much as you can without causing injuries.

Same thing with relationships. On one side, it's true that if you always have arguments very easy that at some point there will be an argument, which is so big that you break up. But if you never have arguments, it's also possible that some problems stay unspoken, they keep going until there is a big argument. And so the idea would be try to talk about things, but never in a way that which the relationship at risk, for example.

And same thing with work. If you work super hard, you burn out. But if you don't work hard, you get fired or, or you don't advance your career, which can be bad as well, because then you don't get to enjoy your life and so the idea is work as much as you can without endangering your health, your family, your life, and so on.

David Elikwu: Yeah, but like you said, I think it's important to remember that the worst outcome and worst scenario is not as bad as the worst average outcome. So, you know, if every night you work hard on average, it might be the case that, oh, you just don't have great sleep and you don't feel great in the morning, but you think you can just continue and every night I can just continue working late and the sacrifice or the penalty that I pay is only the average penalty, which is that I wake up tired and I'm not in a good mood.

But actually there's a great variance in some of the effects that it could have because you see some people, like you say, burnout or overwork. And so actually the worst possible outcome is worse than the average outcome. And so if you hit that point, then suddenly maybe it's affecting your mental health and suddenly you are in a much worse position than what you assumed was just the average outcome for each additional night.

Luca Dellanna: Exactly. And on this there is also a subler point, which is the fact that people who burn out, they tended to leave the company maybe or move to another job and so you don't see them and because you don't see them, you tend to under rate the chances that burnouts actually occurs. Whereas imagine that in a company you could take a record of everyone who burns out. You will notice that for example, burnout rates are much higher and you can see that in lot of kind of sports.

For example, I like the NBA. And you watch, if you watch NBA games, you can think, wow, there are some injuries. And then you can think, you should think that the players that you're seeing, that you've seen in the games, they've already been selected for a world class injury resistance.

Almost all of them, because otherwise they wouldn't be playing at those levels. So you also have this considerations.

David Elikwu: Yeah, that's a really good point actually. And I think this goes to some of what you've talked about, which is the idea that, the survival bias that is naturally already baked into what you see, because the companies that you see doing having a particular habit or the NBA players that you see having particular routines are already the most resilient, the highest skilled basketball players, all the other people that got injured along the way, they didn't even get to this point. And so actually, you know, it can help you to get a better appreciation of the base rate because what you see on the highest stage is not the real base rate when you're looking at NBA players and you're trying to guess, oh, if I play basketball every day, how likely is it that I get injured? If you just watch NBA players, that's not the real likelihood of getting injured. That is the likelihood of getting injured for the people that have already played at the highest level of the game. Everyone else that was more likely to get injured has already been injured. They're already not playing anymore, they already bombed out. Whether it was in college or whether, you know, it was at some earlier point in their career, they didn't even get to that level.

Luca Dellanna: Exactly, and that goes back to the point that you made previously with the skier you mentioned. Just by going like, average but being average for a very long time, you usually get very much above average returns.

David Elikwu: Yeah. Okay. So maybe let's talk about that, because I think for most people, they might not think I want to be average, and most people don't think, I just want, you know, average or slightly above average returns. People often want to optimize for being the best or getting the best.

How do you think we can better start to think about, you know, how we approach what we optimize for when we account for concepts like Ergodicity?

Luca Dellanna: I think that you need to consider two phenomenon. So the first one is what I was mentioning before, if you are average for a very long time, the benefits of being average, they compound and if you manage to make them compound for much longer than everyone else, you end up as very good.

I make two examples. One, investing money. If you invest money for 20 years at exactly the average returns of the stock market, you will become probably richer than 80% of the people who invest. Because a lot of other people, maybe they have a great year, but then they lose a lot of money and so on. And that averages to something lower than you.

Second example, if you are an average professional but you stayed for 20 years in the profession. You will start having people referring to you, you are very reliable, you start knowing people that they refer you other clients, you are there when another person that maybe was a bit more performing that you, but maybe because they work very late, they cannot make it that day, or they have extra work and then the client calls you because you're more reliable and so on. You will probably have a very good career anyway, an excellent career, probably not, but you will have a better career than average, which for some people having a better career than average is already enough.

And then the second phenomenon you want to consider is, I always take the example of Elon Musk. Elon Musk, great entrepreneur also great risk taker. He's the richest person in the world. How much of his fortune is due to luck? Usually the reasoning is he's very skilled. The four most of his fortune is due to skill. That's false. Even if he's very skilled, most of his fortune is due to luck. How do we know that? So Elon Musk, I think, like I checked the numbers sometime ago. I think that he was like 160 billions. Now I don't remember the exact numbers, but imagine that he has $160 billion. Imagine that you take 20 parallel words where Elon Musk is still grows up the same, in the same family, goes to the same college, funds PayPal, and then we check how those 20 parallel worlds evolve.

Probably in all 20 of this world, Elon Musk, he will become a millionaire. Maybe he will have much more than a million, but will he have 160 billions? Probably not. Maybe in some world he has 10 billions, maybe in some he has 200 millions, maybe in one world he has 50 billions, but the average will maybe go to something around 10 billion. So Elon Musk, in the current world, he has 160 billions, but the average in 20 parallel worlds will be 10 billion. That means that almost 90% of his fortune is due to luck. Even if he's extremely skilled. So once you realize that, you realize that the fact that you are skilled doesn't mean that luck doesn't play a huge role first.

Second, if you want to aim to be the richest person in the world, you need to take extreme risks because if you are the best at something, there will be still someone which has better results than you just because they got luckier and because they took more risks. So to get the, a chance of being the richest person in the world, you also need to take a lot of risks. But the more risks you take, the more you increase your extreme outcomes, but the more you reduce your average outcomes. Because at some point you will take a lot of risk that when you close to bankruptcy. For example, Elon Musk, his companies have been close to bankruptcy multiple times and so on.

So once you realize that if you want to be the best, you lower your average outcome then you can think about, do I really want to be the best or do I want to have the best average outcome for me. For me, For example, I don't care about being the best. I care the fact that, in 100 parallel world, I am happy in all 100 of them, and that is a very different strategy than if I wanted to excel in any of those.

David Elikwu: Sure. That makes a lot of sense. Optimizing for the best average outcome is a really good paradigm. Part of what you were saying reminds me of a book that I had started reading but hadn't finished, which is The success Equation by Mauboussin. And I think one of the things that he talked about is how, and you see this, especially if you read a lot of books. When you read, like, I think there's a book called The 22 Immutable Laws of Marketing or something like that. You know, any of these old business books, they give loads of examples and they say, oh, look at what this company's doing. This company does this, this startup founder does that. And I think what Michael was pointing out is the fact that well, it's two things when you look at a longer time horizon than just the window that book was looking at, very often people revert to the mean. And so actually you might have a company that outperforms within a two year window or a five year window, or even a 10 year window, but on a longer term, let's say you look at 20 years, they revert to the mean. And so actually that company didn't outperform at all.

So then, if you start making inferences based on, oh, I see this company within this two year time window is doing incredible. Wow. What business methodologies do they use? How do they operate? How do their teams work, et cetera. And you take a carbon copy of all the principles that they run on, but actually on a much longer time horizon they revert to the means. So actually they didn't outperform anyone, now you are running off with this whole strategy of lots of different things that might not actually perform better than anything else.

Luca Dellanna: Exactly. This is a great point. When you observe excellent results, you don't know how much of it is due to skill, how much of it is due to luck, and how much of this is due to external conditions like, I don't know, a bull market for example.

And that's why you should never like, blindly copy. You should always ask yourself some good questions about, What are they doing? Does it make sense? Is it something that it makes sense for me to imitate and so on.

And then the other thing is also like, my job is I consult for companies. And something that I always need to remind people is you need to dedicate a little bit of time every week to maintenance. To maintaining the skills of your people, to maintaining the culture of your company and so on. And of course, if you want to maximize results in the current year, the answer is do not work on maintenance just work on creating value. But if you want to have the maximum performance over 10 years, then you need to spend a bit of time on maintenance, on reducing risk, on building culture, on building skills, and so on.

David Elikwu: Sure. And so you've mentioned that some of these principles map to your background in working at DuPont and other industries. And I know that you gave a really interesting example about their culture of safety as well. Could you talk more about that?

Luca Dellanna: Yeah, so I've worked for a few years at the DuPont, the chemical and manufacturing company. And one of the things that struck me was that they were obsessed about safety. I remember the day that I went at the office for the job interview. I'm clamping the stairs and there was some random employee that was going down the stairs telling me that I should put my hand on the handrail, and they really care about safety. And there is good reason why they care about safety.

So one reason is because, non-safety has a lot of costs because an injury means that you cannot work that you stop production. Maybe a project gets stopped and so on. But it's also because once you teach people how to be safe, you've learned how to teach them any other habit.

And for example, DuPont had safety ingrained in the culture since the very beginning of their foundation. DuPont started as a gunpowder company and gun powder companies, they have the problem that they have lots of explosions. And the way that the founder managed this risk was that he had two principles. The first one was that he the CEO lived with his family inside the premises of the company, which means that if there was an explosion, there would be a chance that he would be affected. Number two, he had the principle that every time that a new machine was installed in the plant, one of the directors had to operate for the first day so that if the machine was unsafe. Then the director will be the first one suffering from it. This is great because it's a perfect incentive to keep things safe.

And that made the company not just safer, but also much more productive because the fewer incidents you have the more you can produce. But also because if you ask the manager to operate the machine during the first day, it automatically means that the manager will have a better knowledge of the operations, will know much better what is going on, what are the problems of the workers, which means that he will just be able to do his job much better. I'll give you another example.

There was this case study of a consulting engagement that the company had in which they were asked to improve the safety of a very big construction site. And what DuPont did was that they only worked on safety. They taught the managers, the four men and so on, they trained them on safety. What happened is not only that the incidents went down, but also all the projects were delivered on time, on schedule, and on budget. And the reason is because, when you teach safety, you teach everything else.

I'll give you an example.

Core principle of safety is incident investigation. There is an incident, you try to understand what happened, you try to understand the root cause and you take an action to prevent it. And that's something that's transferrable to another domain because you can transfer it to quality incident to customer satisfaction incidents, to ethical incidents and so on. Not only. If you only make incident investigations on bad thing that happened, you will always have new problems because there are always things which can go wrong. And the problem is that sometimes things go wrong 10 times without creating an incident, and then they go along the 11 time and there is the incident.

For example, when we drive with a car, it might happen that we crossed with a red light once, because we were checking our phone. We crossed the red light another time, and maybe we crossed the red light nine times and nothing happens, and then the 10 times the incident happened. So if you only do the incident investigation after the incident happens, what happened will be that you will visit the hospital a lot of times. Instead, you need to make the incident investigation when the near miss happened. So you cross with the red light once, you should immediately make the incident investigation. What caused me to cross with the red light? Was it because I was checking the phone? Then I should not check the phone. How can I not check the phone while I drive?

For example, I don't put it on the seat next to me. I put it in my pants. And this is the mentality and once you teach people to make incident investigation on near misses, they will start do it for quality, they will start do it for all kind of incidents and you will increase the productivity of the company.

David Elikwu: Yeah, that makes a lot of sense. Perhaps even in personal lives, I'm just thinking of how many people perhaps might not even appreciate all the near misses. I'm thinking of the example you gave of, you know, going past the stoplight or performing some kind of maneuver, you know, where you take a corner early in a way that isn't the most safe, but you just do it anyway. And actually you've done it before, and once you've done it a few times, you think it's safe.

And I guess there's two parts of it. One part, which I think is maybe even before making the decision. One thing that I talk about in a slightly different context but on this course that I run, is just this idea of when you are thinking about the decision that you make, it goes back to the concept of variance that we discussed earlier, where you think about the people like to use pros and cons. I don't know if that's the best paradigm actually. I think you should think of, you know, what's the variance between the high and low mean? Like the best median outcome and the worst median outcome.

So on an average day or for an average person, if they, let's say, okay, you'd use the example of crossing through a traffic light going through a red light, the average good outcome for that is nothing happens. You just go straight through, it's a narrow miss, nothing necessarily bad happens. The average bad outcome might be there's some kind of camera and you get a ticket. The best good outcome might be actually, there's no narrow miss, there's no, no one was actually at the intersection at all, and you get to your destination early, that's like the best possible outcome. But in that scenario, you can see there's not much difference between the best possible outcome and the median good outcome. The average good outcome you can get and the best good outcome you can get is very similar. But the worst bad outcome you can get is there is another car that is coming across that intersection and you have a car crash and you're dead, right? So the distance between the average bad outcome and the worst possible bad outcome is much bigger. And so if you are thinking of that decision normally then, because you can see the difference between, okay, the good and the best and the bad and the worst, then that should tell you this is a bad decision. So I guess that's one frame to think about before you even make the decision that should help you to make the better decision in the first place.

But then I think the other side, which you touch on, which I think is still really important is, being able to appreciate when you have already had near misses and some people because of maybe confirmation bias, or you have the bias of your own experience. You've done something before where maybe you didn't appreciate the risk the first time. The question for you might be, how can we get better at learning to appreciate those kind of risks? Where, going back to something we touched on before, you now don't appreciate the base rate. So because you've survived and five of your friends can tell you, oh, I ran that stop light, there's no camera there, nothing happens. You're getting the survivorship bias of, you can only speak to people that didn't die in a car crash doing that thing. So how do you suggest we adjust for that?

Luca Dellanna: No, exactly. I think that these are two good frameworks. And if I can add one more like, I always suggest everyone to make the following risk analysis. You think questions such as, let's imagine that tomorrow I end up in the hospital, I wake up in the hospital. What could be the reason? The most likely reason, and for example for me, and it's a habit that I'm working on, is that I'm crossing the street while looking at my smartphone. And at least that helps me bringing awareness on this and to take steps on that.

For example, other good question is if you're in a relationship, you can think, let's imagine that tomorrow my partner breaks up with me. You don't think whether it's likely or not, you just assume that it happened and you ask yourself what could have made it happen?

Oh, let's imagine that tomorrow I'm fired. Likely or unlikely, let's just imagine that it happens. What's the most likely reason? And you get with, with a good list of three or four problems in your life that didn't seem urgent, but they're actually very good to work on.

David Elikwu: Oh, I really love this. So I have a question that is a much more basic version of this question. I mean, it's a similar analog, but I just think of it in terms of when you are making a hypothesis or when you're making an argument. I just think, how can I be wrong?

If I find out tomorrow that I'm wrong, what would be the reason that I was wrong? And that helps me to revisit my assumptions and say, okay, this assumption has the highest possibility of being wrong, maybe I should investigate that a bit more. And you know, what are the knock-on consequences of that if I am wrong, what ends up happening? But I think the way that you've expanded that to cover all aspects of life, I really love, and I guess maybe this goes back to what you were talking about in terms of having like a the check-ins.

I'd love the idea of having like a regular check-in where you can have this as part of your routine where maybe every month or every quarter you just ask yourself this question in a few different areas of your life. You know, if I ended up in the hospital, why would that have been? If my partner broke up with me, why would that have happened? If I got fired from my job, why would that have happened? And that will help you to highlight in advance all the near misses. So I think that's a really, really good framework that you've shared there.

Luca Dellanna: I just wanted to say it also works on the positive side, like something that I always ask myself when I'm writing a book is, let's imagine that this book becomes a New York Time best seller. What's the one thing that made it go there? You can also do it in, on the positive side and very useful.

David Elikwu: Awesome. Okay, that makes a lot of sense. So I was gonna ask, maybe just sticking with the work paradigm, what are common mistakes that you see leaders make, whether it's in leadership or management or people that are maybe solo operators that are trying to build businesses where they fail to account for some of these principles?

Luca Dellanna: So one big problem is failing to make this kind of analysis. Like, don't ask yourself, let's imagine that the company fails, let's imagine that this project fails, let's imagine that my star employee quits and so on. And you are ignoring the biggest risks that are waiting on your business, maybe because you are too busy in the day to day, or maybe because you're trying to maximize growth. And then those risks happen and you are in a very bad situation.

The other thing which I see that's a very common problem that lot of time managers don't try to set up their people for success. And by this I mean, mainly one growing their skills. Like lot of time what happens is that we hire someone and somehow we assume that they have the skills needed for the job, and we just train them on the very specific procedures or software tools that we have in our company and that's it. And I understand that, you can argue that there is not much time to do training, but lot of time a little bit of training could go a very long way. And I'm talking about the very basic things, things such as writing emails. For a lot of jobs, writing emails is 20, 30% of the job, some jobs even 50%. And people have not received a single training on how to write emails. I'm not saying anything, pick just five minutes on what does a good email look like? Lot of times it doesn't happen. Or even just you put them in front of two emails, one which is a good email, one which is a bad email and you explain, this is a good email because of 1, 2, 3. This is a bad email because of 1, 2, 3.

Same thing, meetings, we spend lot of time in meetings. I know very few companies that train people on how to be in meetings except maybe sales meetings. For example, when I worked in my former company few times per week we will have project updates meetings. No one ever explained to me what was a good project update. Takes three minutes, you just say a good project update has this characteristics. Now make a random example in 20 seconds, you just remind us of what your project is about and then you mention the biggest obstacle on the project. And then you, you either tell us what's the solution to that problem, or you ask us the rest of the room, how we can work on it? And that makes for a good project update. Whereas a bad project update, you speak for five minutes and you only mention things that go well and nothing happens. Takes three minutes, you already increase the effectiveness of your employee by a lot. Very few people are doing it. That's one thing.

And then the last thing is, managers are not very often some managers do it, but lot of time other managers are not giving feedback on how people are doing things. They just give feedbacks on the results.

But that's a bit absurd. Imagine that you are a sports coach, imagine that you're a soccer coach. And imagine that you don't watch your people training, you don't watch your players playing. You just receive a scorecard at the end of the match, and then you give feedback to your people in your office. You will be a terrible soccer coach. Instead to be a good soccer coach, you need to watch how your people play and you need to suggest them how they can play better. You need to give them feedback at the very least. This movement that you make is wrong, this movement that you made was great to do it more often. And lot of times there are some managers do it, but there are a lot of other managers who don't do it.

And my advice for them would be, be a little bit more like a soccer coach. Watch how your people do things and give them feedback on that. Like not on the result of their work, but on how they do the work.

David Elikwu: Yep. That makes a lot of sense. One thing I wanted to flag, just going back a step to what we were talking about before, this is only for people listening, is just the nuance in exactly what you were saying, that there's a difference between the pre-mortem, which is something that maybe a lot of companies might do, where you are about to start a new project and you say, how might this go wrong? How might this fail? I think it's a separate. What you were suggesting is slightly different from that cause it's not just for a new project that you're starting, but it's also looking at existing things you are already doing and saying if something was to fail, if something was to go wrong or if something was to go right, you know, what would cause that. And so you are taking that moment of introspection to examine you know, your existing habits, your existing tools. So I just wanted to flag that for people listening.

And then I love this other part that you were talking about, which is this concept of feedback as well. I think it's not just the quality of feedback, but the type of feedback that you get. And like you were saying, it's not just having a scorecard that says, was this right or was this wrong? But it's also the quality of, okay, you know, how the technique and how can you do this better? What does it look like to do this better or to get this wrong.

I think David Epstein talks a little bit about something along these lines in his book Range, but I can't remember the exact framing that he used. I know that one frame he had was like strong link and weak link, but I don't think that was it, it was something else. But it was essentially about the idea that there are, you know, let's say different type of games or different types of activities that you can do and some where the type of feedback that you get is predictable and immediate. And I think he was talking about like how easy it is to learn different skills or to pick up things. So for example, there are, you know, you could play a game of chess or maybe even golf, where as soon as you hit the ball you know the answer was wrong. The ball didn't go into the hole and all you know is this didn't go right, but it doesn't actually tell you what you should do to fix it. It just tells you something went wrong and the bullet is not in the hole. So there's a problem, there's something we need to fix here, but there are other types of activities that you can do where the response is spontaneous and immediate and it tells you exactly what you got wrong. And so some of those simpler domains that I think it's important to make that distinction and I guess maybe have a different strategy for how you deal with those different things

Luca Dellanna: Yeah, exactly. And on this, I have an example for, I used to play basketball for a few years. When I was in high school, I had lot of coaches and there was a big difference between bad coach, good coach, and great coach. Bad coach will be the one that I shoot, and then gives me feedback depending on whether the ball goes in. So if the ball goes in, he tells me good shot. And if the ball goes out, he tells a bad shot. That's terrible feedback because it doesn't give me information that I don't have, and it doesn't tell me how to improve.

Then good coaches, instead, they look at the movement of your arms while you shoot or your legs like, they look at how you move at your body and if you did the right movement, they will tell you good job, regardless of whether the ball goes in, because they know that if you keep doing the right movement enough times you will make a lot of baskets.

And then great coaches, They give you feedback on what you should do differently in the movement. For example, they tell you, you should jump a little bit higher, these kind of things. And that's extremely actionable. And the difference is that with the bad coaches, you don't know what to improve. With good coaches, you have a guess on what you should improve. And with great coaches, they tell you what you need to improve and you just need to do it.

And the same applies to managers. There are some managers that just give feedback on performance, which is not terrible, but it's not good either.

The managers who give you feedback on the small things you do, like this presentation was great, I like that slide. And then there are great managers, which tell you, I like the color in the slide. You should smile a little bit more. Language in that document should be a bit more technical. Anything, but they give you very actionable feedback.

David Elikwu: Yeah, I think two things that stood out to me from what you were just saying. So one is the concept you were talking about earlier. Reminds me of resulting, which Annie Duke talks about in her book, Thinking in Bets, which is this idea that a lot of people, when they're making decisions, look at the outcome first and say, so they make a decision and they see what the outcome was. So let's say I decided to stay up late and I wake up in the morning and I say, do I feel tired? Did it feel good? And actually I feel fine. And then you use that to say, oh, that was a good decision in that case. But actually you know, over time on a longer time horizon. Just going back to the concept of Ergodicity, that's not always going to be the outcome. So even though that's the average outcome, the worst possible version of that is a lot worse than maybe that average outcome.

And then I think also the other part of that, that I was thinking is, and maybe you can tell me more about how you think this interplay should change our behavior. Where I'm thinking of you were given the example of the basketball coach, the first basketball coach example you mentioned, he is only looking to see if the shot goes in and depending on whether or not the shot goes in, he will then just give you the feedback on, okay, oh, that was good. If it went in bad, if it didn't. And then the second coach, which is a better coach, objectively, is saying, okay, based on your form, if you had good form, that was a good shot. If you didn't have good form, that was a bad shot. But I'm interested in how this interplay changes because in a game, for example, you can have situations where someone that is shooting well objectively form wise might be missing, they might be having like a bad streak. But when you're playing, the time is limited and so you don't have time for someone, you know, if someone is shooting well, then on a long time horizon, if they take 10 shots, eventually they'll start shooting better. Like the outcome will start matching their form. The number of shots that they actually make will start to match the form that they have. But in a game, you don't have time to watch someone miss 10 shots just to get into the rhythm because you know, the other team could be scoring and sometimes it might be better to pass the ball to the other person who has terrible form, but seems to be on a hot streak. And it might seem like even though they don't have the best process right now, they're making the shots and maybe if we're just optimizing for winning this game, we should pass it to the other guy. There might be an analog of that in some businesses or in some organizations or in some processes where sometimes people could see that type of situation play out and assume that because we're optimizing for some form of success, we have an objective, we have a goal. For now, it may be better to choose this suboptimal route and do the bad process, do the process that doesn't always work out well because for now we can get some outcome versus picking something that is the better process overall, but right now might not give us the best outcome that we need.

How do you think of that dynamic and how people might relate to it?

Luca Dellanna: I don't know I think that In the case of for example, the player with bad form, which is suddenly making more baskets could be just due to luck, like maybe how he's shooting warrants I don't know 40% baskets and tonight he's by chance he's taking 10 shots and he put seven and he looks at he's performing better. And then there is the other one who shoots, who a better form shoots 50%, but tonight only put three because of bad luck. And I think that part of the job of the coach is to recognize that the first one is just shooting well because of good luck and to keep insisting passing on the other one.

This applies when you as a coach, you are 100% sure of what it means to have a good technique and maybe you observe those players for hundred of games, tons of practice, and you know that the guy that has a better form is a better shooter and he just had a bit of bad luck. In real life, often we don't have this luxury. Like, sometimes there are some careers in which you make very few projects, you make couple of projects a year. So in this case you have a much higher like variance, like you only observing few people for very little, maybe the condition change. You maybe you don't even know what is good for. And in that case it goes a lot on the skill of the manager to know what good form is and to be able to observe someone which looks like their bad form and is receiving some success and observing it closely and think like, oh, maybe his form is not so bad after all, or understanding whether maybe, oh, he just got lucky.

But it's something that you can only do if you observe closely, and it's not something that you can do if you just Talk to your people once a month in your office, and that's why it's important to observe your people working so that you can know which one is really a better employee or who is really doing things well.

David Elikwu: But, so the point that I was going to make, going off the back of what you were saying, I guess there's two pieces to it. One is, I think the point I was making was just in general, this difference between how things work in training and how things work in practice, which is that once you introduce maybe a time constraint or a deadline or an objective, sometimes that can change or tweak the way people then make decisions, sometimes inducing people to make a suboptimal decision because of the time pressure.

And so in the example that I was giving, it was more so let's say you are in the last, the last 10 seconds of a game and you have one player on the left who is objectively your best player. They have the best technique, the best shooter on your team, they shoot the highest percentage. But tonight they've missed their last five shots. Do you pass it to that player or do you pass it to the player that is having a hot streak right now, they do not have the best technique, they are not the best shooter on your team, but right now they're performing. And I think what can happen is that in organizations as a parallel, but also maybe even in our lives, let's say with our habits. We can default to deciding, let's go with the suboptimal decision, because right now it seems like it might give us the best outcome, even though we know objectively there's something better that we should be doing. But actually right now it seems like this other thing is working.

And I think the second part of what you were saying reminded me of, again, going back to Annie Duke, she talks about in Thinking in Bets, the example of Steve Carroll, who was the offensive coordinator for, or the manager for the Seattle Seahawks. They played in the Super Bowl a number of years ago and in, I think the last, less than a minute to go, something like 26 seconds on the clock and they have to make a play. And the best play for the majority of people watching is to pass the ball Marshall Lynch, you have this running back who is very talented, very highly renowned, you know, you can just trust in this person's ability to just go through and score, and score the ball, right? You are gonna trust this one person. But statistically, that's not the best decision, that's not the best choice. Statistically, the best choice, which is what Steve Carroll chose, was to toss the ball to someone else because on a toss, you are less likely to lose the ball. It's less likely it's going to be intercepted. it's a high probability play. The issue is that he made that play and it was intercepted, even though the likelihood that it would be intercepted on a play like that is very low, it happened. And so, they lost the Super Bowl and everyone said, oh my gosh, this is the worst play in Super Bowl history. This is terrible, you know, it was a terrible decision that he made, et cetera, et cetera.

And so I guess the underlying question is, was that a good decision or not? And I think in Annie Duke's book, or in her opinion, what she was saying is that actually this was the good decision because you made the best statistical play, the best statistical decision. However, and I'm interested in your take on this, considering a lot of what we've just talked about. Should you still make the optimal decision in this kind of scenario, like a time pressure scenario or a scenario where you're optimizing for a particular outcome? Or is it the case that actually maybe the crowd was right and actually you should just trust in this one player that has a high amount of skill, which is technically, you know, from a statistical perspective, it's the suboptimal decision, but it's the equivalent of passing the ball to the player that is having a hot streak, even though he's not your best shooter in the final seconds of a game.

Luca Dellanna: Well, I think that in general, the principle is to judge the decision based on the information available at the time of the decision. So if you take something that based on what you know is the best decision, and then it goes badly, just because you got unlucky, that doesn't make like a good decision, a bad decision.

On the crowd reactions there is something true in that, enough about American football but in the example you made before in basketball where you have two players, one which is generally a better player, but today he's performing worse. The big question that you want to ask yourself is, is he performing worse because of bad luck or is he performing worse because maybe there is some tactical condition on the field in which today he's facing the best defender in the league, or today, every time he gets the ball, he gets two defenders on him. And so in that case, that's something that you should account for. But if instead it's only bad luck, then you should probably keep giving the ball to him.

So I think that, that's very much about considering all the conditions, both those that applied in the past and the ones that maybe are only applying in the now. And then you take a decision based on what you know, and then if you get bad luck, that doesn't make a bad decision.

David Elikwu: Okay. That makes sense. Fair. Thank you for answering my, my highly specific question. So I wanted to talk more about, you know, you've written a bunch of different books and you've covered a lot of different ground. Maybe the best question to ask you is, What of these areas you are most interested in? Because I could run through, I think you've written like nine, nine books, so maybe actually a precursor question is why do you write so many books? What does your life look like at the moment? And you know, how do you make the time to be this prolific?

Luca Dellanna: So the reason I write so many books is because of how my career evolved. I used to work for a few years in a corporation as a management consultant. Then I decided to quit the job to start working by myself. And then I discovered that even though I had all the competencies to do that, I still didn't have the clients to work full-time on projects every single day. So suddenly I had half of my week, which was free. And I decided to spend this time to write books and since then it's been great because a lot of people read the book and then they call me to consult for them.

And going to your question of which books I'm more passionate about, these are the books on management. Mostly because I really care about everyone having good managers. I think that's something that's extremely important, it really affects the quality of life of people. If you have a bad manager, you come home, you're in a worse mood you are tired, you're exhausted, you have less time for your family. And then it's also important as a society because the better the managers that work in our company, the more our societies are prosper.

And so I really believe in the importance of having great managers for our companies. And that's what really gets me out of bed and makes me love my work. I'm really trying to give people better managers.

David Elikwu: I love them. And earlier in terms of advice for managers, we talked about this concept of feedback in giving people high quality feedback and how to give that aside from maybe some of the things we've touched on already, what would you say are maybe the one or two highest leverage things that a manager could do to either perform better for themselves or to increase the quality of the experience for their team.

Luca Dellanna: To increase the quality of experience for the teams. I think that two things you can do is, one, have a weekly or at most biweekly one-on-ones with your people. And while you have them, dedicate at least five minutes and discussing something that's not on the to-do list, that's not a project that they're working on, but just something like, skill of theirs, what problems are they facing on their job? What small change could make their job better? Like, had to have these kind of conversations.

And then the second small change that could make a big impact is when you delegate something, ask the other person to rephrase what they understood because it happens so many times that you delegate something and maybe they misunderstood, but maybe more often you have not been clear. And then the other person, not just because you are the boss, or just because they don't want to look bad, like saying, I didn't understand. Then they go back at the desk and they discover that they don't really know what they're supposed to do. Like maybe they know the task, but they have lot of questions of what exactly you mean, and therefore they waste a lot of time trying to figure out what you meant. Maybe they work on three different things because they don't know which one of the three you really care about and so much effort will go to waste.

Instead, there is a solution is you delegate something and then you immediately ask them to rephrase. You don't ask them as in, please repeat because I want to catch if you misunderstood something because that sounds very bad, but you want to say something along the lines of, I'm just want to make sure that I didn't forget anything. Can you just repeat what's your understanding of the task? Something like that or can you just repeat what I just told you. And the moment that I repeat, you will discover either that they misunderstood something or that you didn't say something that was important. Because maybe you thought that they would have the same beliefs and knowledge, assumptions as you, but they not to have it. And you will save yourself so much time and you will prevent so much problems and you will just make your people's life so much easier.

A lot of times people say, oh, but rephrasing, that's something that amateurs do. And that's completely false because the professions where people ask the other person to rephrase are very prestigious professions. Surgeons, pilots like, jet pilots, military, these are high stakes and very prestigious professions in which they have the habit of rephrasing. So just do it also yourself.

David Elikwu: That makes a lot of sense. I'd love to ask you a few questions about your, your writing craft. I heard you mention at one point, maybe on a previous podcast, that you start your days with a croissant. I'd love to know more about your writing process, like how do you go about identifying what to write about and then on a day-to-day basis, how do you actually sit down and actually make sure the output happens?

Luca Dellanna: Yeah, so basically I have two kind of days, the ones in which I'm working on some client project and the days in which I'm not. And the days in which I'm not, I usually begin getting my nice breakfast, the coffee, I get the croissant and the cappuccino. And then I try to usually answer some question, which could either be a question that some client asked me or maybe some people on Twitter had, or maybe it's a question about something that seems weird to me or something that I don't really understand. I try to answer that question really not superficially, but trying to really understand what's going on.

And that's usually how the books start actually.

David Elikwu: Do you find that once you start, the words just flow or do you have to go through some kind of routine in order to, I guess, some people might say, okay, I'm gonna lock myself in this room. I'm gonna write 500 words before I come out.

Do you maybe structure your argument in advance and then fill in the gaps or, you know, is there a particular process that you use?

Luca Dellanna: It really depends. There are some topics that flow very easily, which are usually the topics that I've already like, worked on or that I've already taught in some of my courses. And then we said there are the topics, which might take very long, but the good thing of having done very often is that I know that it'll come. It's just a question of thinking or researching long enough.

There is basketball coach Greg Popovich, which has a very good metaphor on this. He calls it like, Pounding the Rock. And that's the idea that, when you want to break a rock into halves, you need to hammer it many times and maybe it will requires 100 hits, and the first 99 hits will not show any sign of progress. And then you hit the 100th time and it breaks the stone into, but the 100 time require that the other 99 times to break. And the thing is, at the beginning you don't really know about it. At the beginning, you don't even know whether you have the right technique. But after you break, you've broken enough stones, you know what's the technique, you know that if you keep doing it at some point, results will show and you just keep doing it. 1, 2, 5, 10 times and you shouldn't mistake the lack of visible progress with the lack of progress.

David Elikwu: Sure that makes sense. I think the last question that I'll ask you, I know that you've mentioned that some of the work you've done has been inspired or based on, you know, some books by Nasim Taleb and some of his work around the Anti-fragile. I would love to know maybe beyond that, are there any particular books, maybe two or three, that either have inspired a lot of your thinking and a lot of your work or books that you just find yourself recommending quite often to friends and people that you speak to quite regularly?

Luca Dellanna: Yeah, so Taleb is definitely my biggest influence and the number one person I would recommend to read. Two books that I've liked, particularly in the last years. One, if you're interested in management, is Scaling People by Claire Hughes Johnson. I believe the former CEO of Stripe.

And the other one, which instead I recommend to everyone is how big things are built or how to build big things by Bent Flyvbjerg. And it's a book on the surface, it's about project management, really it's for everyone because all of us, at some point of our life, we will be project managers, be it because we will be organizing our wedding or because we will be renovating our house. And even if we will be project managers only twice in our life, those will be relatively high stakes projects.

For example, renovating our house will be very big project. Very expensive if you did it wrong, same thing, our wedding or something like that. And the really recommended book, it's not technical at all and it really tells you that three, five things that you should do to nail any kind of project, and it's just so important. And I really recommend it.

David Elikwu: Okay, amazing. Thank you so much Luca, for making the time and for everything that you've shared. I've really loved the conversation.

Luca Dellanna: Thank you, David for having me. Thank you so much.

David Elikwu: Thank you so much for tuning in. Please do stay tuned for more. Don't forget to rate, review and subscribe. It really helps the podcast and follow me on Twitter feel free to shoot me any thoughts. See you next time.

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