From Data Overload to Data Impact with Ritavan

Speaker A: Hi everyone. It's Guy Spier here and I'm joined for an updated, uh, addition to my, uh, podcast with, uh, two people, Ritavan and Paras. Um, I'll start with Ritavan, who's the subject of this podcast. He's the guy who, in a way, uh, Paris and I are going to be interviewing and asking questions. And so I don't know how long ago this book arrives in my desk. And uh, uh, that's a book written by Ritavan. And I'm a big fan of anyone who writes a book. I think it's an enormously difficult and challenge and you put yourself out there. And so, uh, as I do, I glanced through the book and wrote a handwritten note, Ritavan saying something like, congratulations on writing a book. And the next thing I know, Ritavan's writing back to me and he's asking permission to post my handwritten note on LinkedIn, which I had no problem in doing. And so it created, created this like, cycle of, um, like, like, like reciprocation and love and all these things. And I haven't even met the guy. So, uh, so that's Rittervan. We'll get back to Rittavan in a second. And we have got Paris here. Paris is in Pune right now. He's an intern. The last time I saw him was at the Berkshire Hathaway meeting, uh, a long while ago. He knocked on our door and dropped off a resume and made a very, very good impression on, uh, Chantal, who works with me. And Chantal enthusiastically told me I need to pay attention to Paris. And at first I didn't, but the more I paid attention, uh, the more I realized what an amazing asset I have in having Paris an intern. So he's in Pune, just going back to Rittavan. I'm so. So the first time I met Ritavan was about two weeks ago. And um, you know, I, I couldn't quite place you. So first of all, I didn't realize that Ritavan was Indian. I didn't realize that he'd studied at the Col Normal Superior in Paris, which is a big deal. Uh, he now lives in Munich, so he's kind of like. But, uh, he's actually originally Indian. And so he's like part of this global tribe of world travelers, as is Paris, who was born in Switzerland. And so with that, uh, I'm going to pause because I've said a lot of things that both Paris and Ritavan will want to respond to. I'll let you just say hello, Ritavan, and then I'LL let Paris say hello. So, uh, why don't you correct anything that I've said wrong, Respond, say whatever you like to the audience, and then we'll go to Paris.

Speaker B: Uh, thanks, guy. I'll just add some depth. Uh, I think I read richer, wiser, happier. I read your book. I read Munish Pabrai's book, uh, about eight years ago and it left such a deep impression. And so the first thing that occurred to me when my book got, when I got my first author copies was just to send it over to you. And I never thought you'd respond. So, uh, yeah, it's really great to be on a podcast with you.

Speaker A: Yeah. So one of the lessons I learned from, uh, Tony Robbins amongst other people was you get more of what you focus on. So if you focus on the way people are persecuting you, you'll get more persecution. If you focus on people who are sending you books, you'll get more books sent to you. And it's kind of like just a weird way in which the world works. And um, I think in his seminars he talks about how in driving, if you just look in, in racing track type driving or in um, um, conditions where it's a slippery road, if you just look where you want to go. I don't know how it works, but, you know, it's important to you move towards what you focus on. So that's just an example of that, if you like. But, um, I'll stop. Then allows Paris to say hello to the audience. Paris, pass your message, I think, is what they say in, uh, in uh, um, in radios along the airwaves when you're flying airplanes. So, uh, any reactions? Hello.

Speaker C: Hi. Uh, so, uh, I'm Paris. I actually started listening to guys podcast perhaps six or seven years ago. So being on the podcast itself is, uh, uh, pretty wild for me right now. A bit about myself, myself perhaps. I've been interning with Akamarine for the past three months. I, uh, had first gone to the Aquamarine office back in 2023 when I was working in Germany, and then again in 2024. I think that put a pretty, uh, good impression on uh, Chantal and the rest of the team, which, uh, finally allowed me to have an internship in 2025. So it was a long process. But yeah, I'm really looking forward to the podcast. I read, uh, Ritavan's book. I really enjoyed it and I made some, uh, notes. I liked a lot of the ideas over there, so I'm really looking forward to this conversation.

Speaker A: Yeah. And I've read about half the book and flipped through the rest and Paris has read the whole book, which is great.

Speaker C: But.

Speaker A: So, um. Uh, well, Ritavan, how does somebody. And I'm going to. I'm going to. So questions that you've written down, unless I want to really steal them, I'm going to let Paris ask them. So, going to switch over to a question from you coming up in a minute. But just give us a sense of your life story. How did you end up studying in Paris at an elite school? How did you end up in Germany? Where is home? What's your background? Where have you worked?

Speaker B: Um, yeah, I think it's easier to connect the dots looking back. So it's a nice question to start out with. Um, Yeah, I was born and brought up on the southeast coast of India in a small town called Pondicherry in a relatively cosmopolitan environment. Uh, went to an alternative school. Um, and what that basically meant is you essentially owned your education as a teenager at around 15, uh, you got to pick exactly what you wanted to study with which teacher you wanted to study. And I think uh, that perfectly suited uh, my personality and that allowed me to explore widely but also uh, dig in deep, um, as and when I wanted. Um, and then came the challenge of what do you do for a formal education? Because after the age of 21 this environment uh, would kind of end. Um, and so I started freaking out a bit at about uh, 18, 19, uh, and started looking around, reaching out to people, uh, speaking with people. And that helped get uh, a better feel for formal education outside of alternative schools. Um, and then I decided to double down on mathematics because I felt it would keep all doors open because, because I wasn't really sure exactly what. I wasn't convinced enough to specialize into anything. Um, and I ended up then, um, doing a couple of internships and I, uh, think I ah, prepped a lot, I applied a lot, uh, but I think at the end it was still luck. I mean there was no other explanation of how I got a full scholarship to go and study at the Colonial Superior, uh, which is a very elite, uh, French, uh, math research institute. And I was kind of parachuted into their second year, so the first year of their masters basically. And it uh, was super hard. The first semester was brutal. I almost failed, uh, it completely. And then I didn't take. I took two weekends in a year I think, and just uh, it was just an insane but very rewarding grind. And I essentially had to make up for two years of prep school that um, uh, most French students or all French students, all classmates had gone through um, uh, and so that's what once I scoped the problem correctly, was all about putting my head down and working through it. And of course didn't reach the exact same level. But then it allowed me to complete the first year, get into a second year specialization, uh, which happened to be machine learning, which was just when the AI kind of one of the AI hype waves of that time was taking off because DeepMind had built an algorithm that beat one of the then Go, uh, world champions. And go was always considered a game that computers would struggle at because chess is kind of deterministic and you work backwards on a decision tree and all of that. And so chess with Casper or uh, had already been sort of worked on before and go was extremely exciting. That's when I graduated, um, when the financial crisis had really sort of scarred me as a teenager, even though it didn't affect me. But uh, just seeing the great financial crisis happening, following it closely was something that fascinated me. And so I ended up uh, doing a six month internship at the end of my master's at SocGen at their global headquarters in Paris, working on market risk models uh, that were data driven, that were machine learning based and yeah and then Brexit happened. I thought I'd go to a quant hedge fund and retire in London. Uh, and with Brexit that plan was deleted before I could even get started. And uh, yeah one thing led to another. I was uh, quite scary as an expat actually looking for a job at that point. Um, but then I got the best opportunity, uh, at an American hedge fund trading commodities in Berlin. And so I moved to Germany and finally got to speak German, which I grew up uh, speaking in India with my aunt was German. And um, and yeah and then after trading power I moved uh, to a consultancy and worked across a bunch of sectors, um, basically always around creating value with data. And um, and then uh, I wrote you know, Munich is home. And uh, last year I kind of decided to write this book based on a decade or so of operating, um, and uh, full of the scars and the battle scars and the ups and downs of what works, what doesn't work and what kind of focus matters. Um, so that's my story in British.

Speaker A: It's an amazing story and um, uh, just a few sort of follow ons from that before I cold call you Paras, is um. Well first of all just a general question. Why does France have the best mathematicians in the world? Uh, yeah, why so that's uh, actually

Speaker B: historically very interesting because you had the industrial revolution in England and then Germany industrialized later and France somehow really has dominated mathematics for centuries. Uh and I think to a large extent, I mean uh, yes, I think uh, the grand ecole system had just about started towards Louis XIV around that time before the French Revolution. Um um. But it's really Napoleon I think who laid the foundation because he himself was trained in mathematics and sort of was very much a first principles thinker. Uh in, in all his battles he would really even you know as, as a, as a marshal, as a, as a general a marshal and you know later on as emperor would really take the time to understand the battlefield, you know, do intel himself on the ground work from, you know, work back from these first principles. And so I think he really appreciated sort of a rigorous um, analytical approach to thinking and uh, sort of led to this grand ecal system which created a very sort of elitist track for any smart and ambitious person. And then you know that builds a nice flywheel over time.

Speaker A: In fact to the degree to which when I sort of glanced at pages of your book and I saw that you'd studied mathematics, I don't know if you remember in our call, I just assumed you'd studied at the um. Uh. Uh. A col. Poly technique. But I guess there are mathematicians that are good mathematicians that don't study technique. Ecopoly technique is, is a, is kind of a naval school in France. And basically you know if, if somebody has. They're called X. If you, if you're one of those, you uh. Anyway, you kind of like everybody knows to kind of make way for the. You intellectually type of deal. For me, ecolem nor m Mal si p is more literary actually. But I didn't even. It was only you. I realized it also has a maths uh, division if you like. And I'm sure that there are plenty of famous mathematicians who've graduated from the Ecolenombau Superior. Can you name one or two just for fun?

Speaker B: Um, yeah. I mean most field medalists uh, recently like uh, Wendell and Werner and uh, Cedric Villani and all of them are from the Economet Superior in, in. In Paris Rue d'. Ulm And I was in the Economade Superior used to be called Cachon, now it's called Paris Sacle. But they're basically three that are historic that were historically founded. The one in the center of Paris, the one in the outskirts of Paris and one in Lyon. And now there's a new one in Rennes and they, uh, all have their specializations. So the one in Paris, in the center of Paris, is very much theoretical. So a lot of literature, philosophy, et cetera, and pure math. Uh, the one I went to was, um, a lot more had the humanities, but also had the natural sciences and engineering sciences. And the one in Lyon is also pretty strong in physics and applied math.

Speaker A: I think that I've seen the guy Cedric lecture. He's just a very flamboyant, very, very unusual figure. They like sort of eccentric to the power of eccentric. But I, um, won't dwell on that. Uh, what I wanted to ask you for, just briefly. I mean, you grew up in Pondicherry, which I didn't even realize. It's a bit like Goa, but French, Goa being Portuguese and that, uh, and in, in English you have a very light. But you, you can tell that you, you speak with a kind of an Indian accent. When you're speaking French or German, how do you sound? And how long into a conversation with somebody in France or Germany do they say, where are you from? And then if you say, well, actually Paris or actually Berlin or actually Munich, they say, no, where are you really from?

Speaker B: Yeah, um, so the funny story is I learned French in kindergarten. So from the age of three, uh, speaking it in school m. And also at home. And a funny story, like my kindergarten teacher, uh, was, uh, Indian, but of, uh, but of Iraqi Jewish origin. So it was really insanely diverse. Like the, the kind of, uh, you know, the kind of environment I grew up in. Uh, it was really nice. And uh. So, yeah, my, My accent in English is very, is very Indian. My accent in French was pretty Indian until I landed in Paris. And you know, I'd read a lot of the French literary classics. Um, and so, you know, I have my Alexandre Dumas and etcetera, under my belt. My Jules Van. And I come with that, uh, vocabulary, the vocabulary of those times, uh, with a thick Indian accent. So that was very weird for people initially. And uh, one of my friends, uh, very smart guy who just, uh, completed his PhD at Polytechnic, he's, uh, now starting out as an assistant professor. And what he told me is, uh, look, you need to learn Parisian because if you want to be respected here on the street, you, you know, forget what you know, uh, you know, scrub that accent off. Learn slang, you know, learn Verlon, which is, you know, where you, where you invert, uh, vowels and syllables. Uh, and he gave me a playlist of, um, French rap. And so for me was really putting on French rap and Doing math proofs for a year and my accent was gone.

Speaker A: You need to share that playlist of French rap because I want to get into it and interestingly enough, so anyway, I don't want to dive into my personal stuff, but um, uh, so, so, so um, uh, if you had to choose between living exclusively nine months in the year in either France or Germany, because which would you choose?

Speaker B: Um, so the unfortunate thing is I haven't seen all of Germany, but if I had to choose between Paris and Munich, it would be Munich.

Speaker C: Huh.

Speaker A: Oh my God. Are you serious?

Speaker B: Yeah, I'm a small town guy.

Speaker A: Make sure that we, we delete that from all the French crowd, you know. That's amazing. That's, that's quite a statement.

Speaker C: Yeah.

Speaker A: Explain yourself.

Speaker B: Yeah, I think Paris is just too big. Paris, London, they're just way too big. I'm a small town guy. I, I like this cosmopolitan vibe which I think Munich has or I think Zurich would have too, but it's not too big. I think that's nice and it's very close to nature and uh, that suits me.

Speaker A: That's, that's fascinating. So Paris, I think I know what your first question is going to be, but you can go anywhere you like. So uh, go ahead.

Speaker C: So, um, I'm actually very curious. What do you think the first question would be?

Speaker A: I'm looking at your questions. So Paris has got like. He did a cheat sheet for me because he's. But I just thought it would end up being the first question. But feel free.

Speaker C: Uh, no, actually um, it was the third question that I was thinking about. But anyway, no, uh, go ahead because.

Speaker A: So just very briefly, um, I think I strongly believe that curiosity is much more than just your brain leading you astray. Uh, it's a seeking for something that is at the root. So go with your curiosity, not with what I expect you to ask. So I couldn't have of constrain you. I don't want to constrain you. Follow your curiosity, Paris.

Speaker C: Fair enough. Um, so I read the book. I really enjoyed reading the book. I read a lot of the examples that were in the book. So Data Impact, uh, is the book by Ritavan. Do have a look at it on Amazon. I think I'm allowed to say that already. But uh, um, when I went through the book I really liked a lot of the examples that you had noted. So there were a lot of different case studies from all across the world and it fairly unusual. So I had a business education and uh, I saw that you took uh, up a Lot of examples from all over the world. And at the end of the book, what surprised me the most was you said that, uh, you wrote the book in six weeks, which for me was like, oh, wow. So you probably had a lot of these ideas banging around in your head that were waiting to come out in, uh, written format somewhere or the other. So what was, uh, how long was the gestation period for the book actually? And what did it take to write the book in six weeks?

Speaker B: That's. That's a lovely question. So, um, yeah, I think the gestation period was a decade, like I said, at least, you know, as an adult, uh, in a decade of my adult life so far. Uh, and the six weeks was, you know, I joined a community of useful, uh, book writers. So these are nonfiction book writers, you know, who are trying to get, go through their first book. And the idea was to write this book like a recommendable product, right? So, like, you want it to be useful because someone is being nice to you by, you know, taking 90 minutes to read your book. You want to give them stuff that's useful, and you want to package it in a way that's easy to read, that's fun, and that's useful too. And, uh, and this is a methodology that Rob Fitzpatrick kind of, you know, pioneered. And what I realized was a lot of these writers were struggling. They're taking over a year, uh, uh, typically when I spoke with people who had written books, they had taken a year or more, as many people take several years. And for me, um, once I had sort of set my mind on it and I knew, uh, what kind of book I wanted it to be, then I, you know, I just wanted to push myself as hard as possible. You know, once you've kind of scoped your race and you're saying, you know, you're running a marathon or a half marathon, whatever, and that pain is there. I think the pain, the frustration, the drive, the learnings, the excitement, all of, you know, all that emotion is there. So you just want to compress it and then just let it out. And, and, uh, and so, you know, once I had this slash OG framework, I had the six step framework, uh, I knew that I could take all the complex ideas and package them in a way that's, um, that's good, that's coherent, that's cogent, and you know, that that can be read easily. And so I just, uh, pushed it through, um, you know, around Christmas, um, which is exhausting.

Speaker A: I have two follow clarifying questions just for the audience. So, um, uh, first of all, you talked about a kind of a summer mastermind group of people who are writing the first book. Non. First nonfiction book. Can you explain a little bit more about that and maybe even, um, name the group and how somebody else is listening to this who wants to write a book, maybe can tap into that group?

Speaker B: Yeah, um, of course. So, um, the author is Rob Fitzpatrick, who's famous for writing the Mom Test, which is, you know, how do you get feedback on something you've built? Because when you ask people, they will always say something nice.

Speaker A: And.

Speaker B: And, uh, and then he wrote another book on how to run effective workshops. And then his most recent book is how to Write Useful Books. And. And I like his approach because it's, uh, you know, he really worked back. He works backwards from anything being value delivered. Right. And, um, and so he then built a community where people who want to write a book could join. And he built a little video course, which helped speed up because, um, I think writing a book is, of course, the ideas, the packaging, the mental part, the feedback rounds that you want to do with beta readers. So that's all. The, um, let's say the purely intellectual part. I think the emotional part is brutal. I remember I would wake up every morning with massive imposter syndrome telling myself, who the hell do I think I am? Who am I to ever write a book and have anything meaningful to say to the world? And so I think just being part of this group, uh, joining the calls, you know, once a. One or two times a week, let's just go to Useful Books. Just Google Useful Books. Rob Fitzpatrick. You'll find the community, you'll find other resources. He's done podcasts with authors who speak about their journey. And I think just knowing that, you know, it's hard for everyone that, uh, there is no shortcut and that, you know, when you're trying to do something new, um, the mammalian response, I think, just evolutionarily is to tell you, you know, is to get the alarm, uh, lights going and to. And to tell you, don't do this. Um, and so that. That was emotionally very hard. And so that's why the. The first, you know, uh, validation from people I looked up to was so important and was so, uh, cathartic of sorts. Even if it was just a sentence, you know, two sentences. That's just, uh. And to anyone listening, I think any, you know, every review you write, every feedback you give is something for the. For the author, the creator, something that's just very nourishing because it's almost like, you know, you've given a part of yourself out there which uh, is very uncomfortable. But then, you know, you're really happy when, when people find it useful.

Speaker A: And so I actually Paris, I'm going to go to you for the question. So we'll give Ritavan a little bit of a break. And I mean, you know, I've not. I've read the first three or four chapters and uh, like you, I was so, so, you know, you have Amazon as an example, you have Netflix and as an example in the book. And then, and then you have Flipkart as an example. And then, and then Ritavan's talking about Napoleon and especially for example, Napoleon, which I know less about. And what Richavan said now, I mean, I didn't really. I just think thought of Napoleon as a very good commander and a bright guy from Corsica who would have never made it through in Austria, in Russia, because there was a sort of a class system there worse than any, any, uh, caste system you have in India. But now I want to like, learn more about this whole idea about Napoleon and, and um, uh, first principles thinking. But, but Paris, in addition to those, were there any other case studies or sort of global thinker type sort of examples in the book that strike you. Struck you either in addition to those or maybe you want to riff on the ones I've already mentioned.

Speaker C: So the. There are others, but just on Napoleon for a second. It was actually quite interesting. There was one section of the book that talked about communication and communicating very clearly. So a story that stuck with me was Napoleon would keep, uh, all the illiterate, uh, soldier around him and whenever there were to be new instructions to be issued or new, new, uh. And Riddle probably is going to tell the story better than I do, but, uh, whenever there were orders to be issued, they would first tell it to the old illiterate man. They'd read it out for him and then ask him to explain it. And if he was able to explain it, then the orders were a go. Otherwise they had to be rewritten because then nobody could understand it. So I thought that was a very useful way of looking at communicating in which you have to figure out if, uh, you can, um, understand the world. But other than that, there were a couple of other businesses that I thought were, or few others that were very interesting. So one was, uh, huk at 24. It's an insurer based out of Germany. I didn't know about this story despite having lived there for a couple of years. Then, uh, there was an example from uh, um, India, which was Bajaj Finance and I know about Bajaj Finance's domination of this uh, non banking financial lending space, uh, uh, in India. But I didn't know about their story very well, which uh, yeah, I mean it was very interesting to learn about how they grew over the past 15 years. And the last one was wise. So I've been a very proud, wise customer and uh, I didn't know their story as deeply as Rativan provided in Data Impact.

Speaker A: And I'm going to go. So Ritavan, thank you for those and I haven't, I hadn't come to those yet. Uh, the question that I thought Paris would start with, but now I'm going to ask is many people uh, uh, are curious about business, are smart, ah, enough to do the kind of analysis and thoughtfulness that you do. But you decided to write a book. Did you first of all, did you pick up Robert Fitzpatrick's book and then decide to write a book or. So those of you who are listening, Richavan just shook his head. So tell us about the process by which you came to decide that you wanted to write a book. If, or you can just uh, throw that question away and respond to something that Paris said. It's your choice really.

Speaker B: No, it's a very important question I think. So for me, if you zoom out, the book is basically a productized, uh, manner in which I can communicate something useful to someone without any additional investment of my time. And as I saw, you know, I would meet people and we would have the same discussions and I would end up saying the same things, uh, of course without the rigor and the structure that comes from writing a book. So it was more free flowing conversation and, and then the realization was, you know, I need to put it, I put, I need to go through the pain and the effort of kind of building it into a product. And uh, to be fair, you know, a book is a Gutenberg Time product. This is not uh, uh, it's not the most personalized, the most digital and the most advanced way to communicate. So I'm trying to now uh, flesh that out and provide other resources to readers, uh, you know, whether it's in the form of uh, short email courses or video courses or whatever. Uh, because as an author it's just impossible to put everything into the book because it would make it unreadable. So there's a lot of trade offs around how you structure and that is where Rob Fitzpatrick's book and the methodology and this thinking of a book as a product, um, that serves a certain purpose. I think all of that thinking flows in once you know why and once you've decided uh, why you want to write a book.

Speaker A: Ah, just to be clear, uh, and I, I would imagine, and if so for the audience, just that you know. So um, I actually got on the phone with Paras, with Ritavan two weeks ago because I discovered that he'd been in energy trading and I realized that he could teach me something about the energy trading business. And so we actually in a way, um, met Ritavan and did a vertical deep dive into the energy trading business and learned an awful lot about it, which I'm still uh, extremely grateful for. But uh, but I would imagine that that book is a kind of an introduction to a consulting business. But, and we have, I have a rule around me that I don't want people to sell from the stage, so to speak. But now I'm, but you are allowed to talk about your business model now that I'm asking you directly. So is, is the, is the goal to educate, sell books and courses or is the goal to sell consulting business? What is the product actually other than the book?

Speaker B: So the short answer is I'm um, I'm um, figuring it out as I'm doing it. But I think the mission I've set myself is to really drive data driven value creation for legacy businesses or businesses in legacy sectors. Let me just uh, kind of unpack that a bit. So uh, what we've seen over um, the last decades is the move from big mainframes that were essentially uh, in the domain of companies to uh, PCs etc. And that's the digital revolution. And then now we're seeing more and more data driven algorithms, let's just use the umbrella term AI even though it's not very rigorous but uh, just so that you know, everyone kind of has a feel for what it means. Um, and uh, but what's been happening is that legacy businesses, so traditionally non software businesses, looking at manufacturing, industrials, real, uh, estate, insurance, et cetera, their margins have been shrinking. And what's happened is in the name of being you know, at the forefront of technology, it's all been about buying, tooling, about, you know, upgrading infrastructure, et cetera, uh, computing infrastructure, you know, storage and other infrastructure. And so they've essentially increased their costs. But most companies have really not been able to generate value. And this is something I've seen time and again. And this is something that pains me uh, in a very deep way. And uh, and I wanted to change that. And one Challenge I see is that, you know, when you're trying to sell services too hard and it's easy to do it today, you know, because you just slap uh, a bit of hype on top and then you package, you know. And I have the expertise and the, the CV to do that. Uh, but, but that's why I wrote the book also a bit to draw a line and say, look, uh, I will only operate and do something if I see it creating value, not do it just because someone's paying me to do something. And there's a very interesting insight from, from Charlie munger stock at UC. Um, he was in um, at USC business school in California in 1994. And it's around this excitement around new technologies. And most people think, you know, when you, when you have a new technology off the shelf and you use it, you know, it'll increase efficiency and so you will be a better business. And uh, he uses an example, uh, from when Berkshire Hathaway owned textile mills and someone ran into their office and told Warren Buffett, we have textile mills that are 2x more efficient. And anyone would think, oh that's amazing, you know, we should buy them straight away and we will be a great business. And, and Warren Buffett apparently said, uh, gee, if that's true, we're going to have to exit this business. And I think the deep realization here is that when you have new tools, new technology, tools come in, even if there's a true increase in efficiency, that efficiency gets captured by the person selling the tooling and that efficiency gets passed on to the consumer because anyone can buy that tool. And so as the business, you know, trying to improve over time, what you end up doing is essentially just increasing your cost and becoming a worse business. And I call this sort of the entropy of commoditization. Right? And so you keep buying new technology, you keep chasing efficiency and you end up self destructing and you also end up being copy paste version. So like if you know just the word utility in the energy sector tells you that it's copy paste that's already been commoditized and then you have someone like an octopus energy that comes around and says, no, this is a completely unique concept and there's absolutely no way you could price compare them against someone. And if you think about the best companies, uh, sorry, I'm going to pause

Speaker A: you because you mentioned the name of the company and now you have to explain it. So you used ah, an um, example that is clear in your head and nobody else's. And so everybody's saying, what is octopus? And so now you can explain what's Octopus as opposed to a normal utility. I don't know myself that do very briefly.

Speaker B: So the idea is, uh, just Energy Markets 101, it's a B2B market, et cetera. And then as a consumer, you have some kind of utility that intermediates between you and the energy market. And what Octopus does is that they incentivize you to modify and match your consumption based on the price signal on the wholesale market. And so it essentially passes on the opportunity of making money to you directly. And that's very unique. Anyone could have done it. In theory, I think the technology was there for long enough. Uh, but it just takes a certain level of clarity of vision and of value you're delivering to your customer then to frame the problem like this, to build a business around it and to actually deliver that value. And the case I'm trying to make in the book is, look, this excitement around data, AI whatever is not about buying technology off the shelf, right? And just trying to plug it into your business or to drive efficiency. The point is, sharpen your value. Like what is your core value proposition to your customer? And I use the word value because the listeners are uh, value investors. So the value investing community is obsessed with value, but also the product tech, product development community understands the notion of value. And what I try to do is marry these two plus, uh, a smattering of military thinking and techniques. Uh, but the idea is really take your core value proposition and use data to sharpen that, to counter position to other players in the market based on your unique assets, right? Your unfair non digital advantages. So uh, I use Walmart as an example. You can either try to compete with Amazon, which doesn't have any physical stores, or you can say, look, we are special, we are Walmart precisely because we have stores. We don't just understand your needs based on your online shopping behavior, which you can go and shop on Walmart.com, but we also understand you based on how you shop in our physical stores. And so you want to take your unique, your circle of competence basically, right? You want to double down on that using data, right? And then counter position based on that to build your moat. And also sort of essentially to, you know, to monopolize in a good way the mind of your user, of your customer. Because, you know, there's just so much out there today if you want to stand out, you need to really have a unique, you know, even emotionally inspiring value proposition. And data allows you to do that. But data at the service of this mission is what's going to help you get there. Uh, right, just upgrading to, you know, getting a new, uh, moving to the cloud or buying a new CRM system or a new ERP system is not going to do that. Uh, those might be components to, you know, to actually execute on it. Right. But unless you have that clarity of, of vision and strategy, you will, you know, it's all going to be wasted money.

Speaker A: So I'm going to riff on that a little bit, if I may. So, first of all, another story that Warren Buffett's told is of the department store business where the one department store gets an elevator and the other store needs to get it right away. There's no choice. Or the one store invests in air conditioning and the other store needs to invest in air conditioning. And I'll segue, ah, from that to something that I used to do, which I've more or less stopped doing, which is great. That David, our cfo, uh, and you could call him our chief, Chief Technology Officer now, um, he used to joke that any software, um, uh, that was available for a business like ours to use. I'd already used the corporate email to try out the free version of the software. And he said that he hasn't come across. And that, in a sense, is on a very small scale, uh, for a very small business, me playing with software, playing with data, uh, uh, playing with signing up to cloud services of one kind or another. Uh, uh, an expression from Hebrew I like is full, full, gas and neutral. You know, so I'm doing all those things, trying all this, trying all those things out, but, but nothing's really changing the business at all. I mean, I'm having fun. You actually wrote it in the book somewhere. If you want to do it as a hobby, feel free, but don't, don't convince yourself that you're doing something useful for your clients and for your business that actually, I mean, this is fun to discuss. And there's nothing, I don't think there's anything that we can't, that I'm wrong in not sharing here. Is that so? Um, uh, Chantal comes along, who's a member of our team. So I had a Salesforce system, but she starts really using it to deliver, uh, value to, uh, either clients, potential clients, um, uh, you know, people that we've been doing due diligence with so very briefly. Because I'm just connecting dots in my head as I've read a bits of your book and I'm hearing you. Um, uh, Jeff, uh, Bezos, this famous expression that in business, focus on what is not changing, don't focus on what is changing. And then at the same time something that I figured out from the reciprocation Robert Cialdini stuff and. But I really sort of scaled up you and one of the early chapters talk about, you know, leverage your non digital assets. And I think that I was doing it at first. Chantal picked up on it. One of the non digital assets that we have here is just that we care more and that we humans and we're willing to go the extra mile to make person who has helped us feel better feel good. So you know, I, I spend every day writing. Uh, you know, sometimes it's half a dozen to a dozen, sometimes it's one or two personal notes to people and we're blown away that even on an email, I'll sometimes take a printed out email and I'd write a personal note and they get the uh. And this whole reaction interaction came from a personal note. So that in a way is leveraging your physical assets that um, uh, Chantal then went and she, she kind of a false multiplier and scaled up. So I found things in your book that, that I kind of reflect, I think what you have been saying right now. Um, and yeah, I mean. Richard Van, you mean that you can't just change your um, domain name to Dot AI and everything will become better for you right now?

Speaker B: You know, I could, but I don't want to.

Speaker A: But that, but it's a very interesting distinction and I'm going to. Well, I'll. If you raise your hand, Paris, you respond. And if not Ritavan will respond. But to say what actually am I trying to deliver? And then how can I use either innate resources or data resources that I can acquire to deliver that rather than just playing with the data and the data is there if you like and uh, you know, use my Salesforce database to deliver the thing that I define that I want to deliver to whatever um, focus or stakeholder group it is. It's a slight adjustment in my thinking, but changes a lot how you go about it. I don't know. Do you want to comment, Paris, and give Ritavan a chance to know he doesn't want to comment. Do you want to respond to that, Ritavan?

Speaker B: Um, no, it's exactly what you're saying. I think it's fun to experiment and try out new things. But like I say, it's a hobby and keep that a hobby. You know, when you're trying to improve your business, then you want to make sure that you are sharpening the value proposition to the value delivered to your customers. That's all that matters, right? Everything else, any kind of efficiency gain, like, you know, Charlie Munger's inside, that's all going to get passed on. And if Warren Buffett said, right, when someone gets an elevator, you have to get an elevator, that's a defensive strategy, right? You cannot be the compounder over a decade, uh, as a business, if you install the elevator, it's just a defensive tactic. And so, and so a lot of uh, technological tooling is very often just a defensive tactic to stay up to date. But it's not what's going to uh, create the winners. And I think that distinction is important.

Speaker A: So you clearly understand Netflix's business quite well. So they had some level of customer loyalty, uh, um, in the um, posted mail delivery of um, DVDs. But then that transition to, well, the transition to making their own content, um, was clearly a kind of a, I mean I don't know the business probably as better as well as you do, but it was bet the business kind of decision. So if, if it succeeded, it will succeed big, but you, the whole business could have failed as a result. And so maybe it's worthwhile. I mean, how, if you'd have been having a conversation with Reed Hastings as he contemplated this, how would your framework, uh, fit into that? Maybe that's a good way. Is that a good, is that a good question to ask you?

Speaker B: Actually, yeah, I think we can leave past the specifics of Netflix per se and just sort of abstract it out. You know, when do you bet the business and how do you bet the business? Uh, especially when there are these big pivotal opportunities. Right? Because doing a 1%, 2%, you know, fine tuning here and there is not going to make you compound and win over a decade. And I think the way I try to frame it is, and this is borrowed from, you know, from, from Mohnish's book, which is, think of it as an asymmetric bet. And then I add the leveraged part leverage not in the financial sense, but in the data driven sense. Like how do you use data specifically to get, you know, a, with a 20% investment and 80% return, um, or impact. And I think, um, when you do these bet the business, um, uh, bets, you want to take a step back and look at the entire distribution of future outcomes and then take the worst ones and find some way to put some kind of floor there. And it's usually Possible. And that's why it's very difficult for me to give a specific answer to a, uh, to this general approach because it's very contextual. Right? So it really depends on where you stand and you know, how the, it's really battle by battle that you need to fight this. Uh, but I think this framework of looking at all future scenarios, kind of assigning some sort of probability to them to get a feel for, you know, what is less and more likely and then trying to build mitigation strategies for the worst cases and then just executing with complete clarity, intent and just hammering it through I think is the way. Because you know, if you get into self doubt, like also the book at six weeks was, you know, because you wake up every morning with self doubt and the moment you bet your business on something you'll have 10x1000x more self doubt. And so I think thinking of it as a leveraged asymmetric bet. And that's where data is leveraged. Right. So I think what Tyro also argues, data is not something to be consumed. Data is not oil, you know, it's not a commodity. Uh, data is leverage. And so when you make these leverage bets earlier in the industrial paradigm you had opportunities that were available in the industrial paradigm. In the digital paradigm you had a new set of ways or layers you could build in into such asymmetric leverage bets. And now in the data driven paradigm you can again build in a whole bunch of other things. And once you understand these three paradigms, then you can bet your business even bigger, even better, you know, and then just keep compounding that and you have to take those bets, right? If you don't take those bets, you will flatline. It's guaranteed you will, you know, there

Speaker A: is, uh, so I want to, I guess I am going to personalize it. And so one thing I heard you say that strikes me as true, even though I don't know why it's true, is this idea that data is a commodity, data is a new oil is not a good way to look at data. But so that strikes me as true intuitively, but I don't fully understand it and I couldn't demonstrate why that is the case. And then the next thing you've said, which is just tantalizing to me but I haven't fully understood it, is you can use data as leverage. So I know mechanical leverage, which is where the word comes from. Uh, we all know financial leverage and the dangers of financial leverage. And now you've introduced me to an idea called using data as leverage. And I'm going to use an example that I think gets to what you're talking about, uh, which I think worked for a certain period of time, uh, and is less likely to work now. And I'm going to mention somebody, John Miljevic, who is about to have his Zurich project conference. And I used to spend a lot of time with him. He's got a, um, community called Manual of Ideas. And you know, he said something like, all I need is 100,000 subscribers to my mail list, mailing list. Because If I have 100,000 subscribers, you know, I can get a thousand true fans paying $1,000 a year from my community. And that's a perfectly good way to live. So, you know, the idea that 100 years ago somebody could have, well, selling books or having a book is a kind of a way to do leverage. Email is a way to do leverage. But can you help me to understand in more granular detail what you mean by using data as leverage and how it might apply to my business or any other business?

Speaker B: Yeah, um, so, yeah, I'm using the word leverage, but like you pointed out, mechanical leverage is Archimedes, uh, financial leverage, and now data leverage. And why I use the word leverage is because the idea is always with less effort, getting greater results, right? That's what is common to all three. Right now, um, when it comes to data leverage, I think I want to just introduce two key ideas quickly to kind of build this out rigorously. So, uh, the first idea is that I argue there are three value creation paradigms. There's the industrial paradigm, the digital paradigm, the data driven digital paradigm. And they're characterized by, in the industrial paradigm, replication costs are relatively constant and personalization costs are relatively constant, right? So if I make a coffee mug and I want to write your name on it, or Paris name, uh, every time I have the same cost to produce another cup and to personalize it. In the digital paradigm, you know, it gets much easier. Now replication costs are essentially zero, right? So if I have an ebook, I can, you know, you can, you need to create it once and then you have essentially infinite copies. Personalization, uh, costs remain, right? They remain relatively constant. If I want to write a personalized chapter for every person or write a personalized section that looks at their business, all of that, uh, has constant costs associated. Uh, in the data driven digital paradigm, now personalization costs start going towards zero. Because if I have enough context, enough data and the right kind of model, I can try to personalize without any additional investment. And once these three Paradigms are understood. Now comes the question, what does leverage mean in this data driven digital paradigm? And I like to use a framework that was created by someone in time management. Uh, the name is uh, Elizabeth Grace Saunders. So she initially came up with this idea of how do you allocate your time in a way that you get the most leverage out of it? And then uh, Shreya Stoshi, who's a thinker in tech product, sort of applied this uh, to tech product development. And I like that three bucket way of thinking, leverage, neutral overhead. And I sort of adapted it to this data setting. And the way I say uh, you should think about leverage is the following. Let's start with first overhead. So anything that has a one time payoff, right, Irrespective of the investment, anything that has a one time payoff, like a research report, like whatever, some analysis, that is an overhead task in the data driven paradigm. Because the next bucket is something that has a one time investment and a relatively constant payoff. So process improvement, uh, some kind of automation. So this neutral bucket is already better than the overhead one. And now the leverage bucket is something that has an increasing cash flow over time. When you think about data leverage, you look at these three buckets and ask yourself the question, when I do something, uh, is am I going to get a one time payoff, a relatively constant payoff over time or will I get increasing cash uh, flow over time or increasing payoffs? Right. And you can choose to monetize, not monetize those straight away. Like Amazon for example, right. Didn't create any profits, they kept reinvesting in the business. A lot of uh, businesses, you know, just give their profit back to their customers. And so you don't have to necessarily monetize it, but you need to create that value. And I think the data leverage bucket is really the highest kind of investment you can do. That will compound over time.

Speaker A: A few examples from my building, if you want to call it that, building my business. So a very, very simple example, um, if I collect uh, somebody's birthday, that's a one time collection cost, but I can then send them a birthday card once a year and deliver a little bit of a joy in a mailed birthday card once a year. But, but that is a one time, that is a, there is a certain cost to writing out the birthday card and putting it in the mail. But the most expensive thing is actually collecting that um, that mailing address and the birthday card. So that would be an example. Writing a book obviously is, is clearly, well it depends on what book it is. Some, some books depreciate in value over time because they don't get read very much. And if you're lucky, you've created a book that. But, but it at least has the opportunity to create kind of like recurrent revenue or recurrent interest or recurrent something. And so you're thinking what comes up for me is um, the tail to the. If I write a, I mean, um, if I write a research report and it's just internal for the business, as you said, it's an overhaul overhead. But maybe I can start thinking of the research report that I or somebody internally writes as first of all overhead and perhaps uh, contributing to investment decision. But then we can think of with maybe not zero cost but very low cost, repurposing it for some other content distribution, either in a newsletter or to personal delivery of the research report. And maybe we could discuss for hours my last sort of technical question, if you like. Um, and can you help me to understand. I know that it's something that is very clear for the um, television and movie business, content business, this concept of windows. And uh, you know, you want to capture along the demand curve, you want to capture as much of the consumer surplus for yourself. And so you have these release windows and you don't want to release the content in a way too soon to the people who don't pay for it. You want to release it last. So a movie, the reruns of the movies which are sold, uh, to be or in c television channels, uh, and make uh, revenue via advertising of the last place where you distribute the first place is first release cinema. And now that's changed slightly because sometimes a movie will be released to Netflix first and artists are playing with that as well. But I think that that's true. And I guess I'm thinking of the business in a way that I'm in, which is investment management and investment research that some people give their content away for free and that's wrong. And some people uh, build such a high wall around their content that nobody gets to see it. But, ah, I don't know. So I've kind of given you a potted analysis from my perspective. Can you help me to refine, uh, and understand better what I've just talked about?

Speaker B: No, I mean, I think the important thing you said was the same thing could end up in any of these buckets depending on how you like, you know, how it fits the bigger picture. Right. And what is your notion of the value it's supposed to deliver? And, and that's true. Right. So there's nothing that explicitly always falls in one bucket or the other. You can move it across the buckets if you, if you, if you, if you choose to. Um, and I think on, you know, what, what do you give for free and what do you pay? Well, and this is why I use the word leverage in the data context. Because if you look at most demand, you will have some sort of power law, right? You would, you don't have uniform demand. It's very rare. I've never seen in the real world, you know, like a uniform demand for anything. Right, so. And it's not Gaussian either, right? So you always have some kind of, you know, 80, 20 type of relationship, some kind of burrito, some kind of power law. And that's leverage again, right? Because you have 20%, you know, driving 80% of your revenue or your profits or whatever. And that allows you then to kind of produce the paywall stuff for that, for that 20%. But to the, to the rest you can, you can provide free resources. So this is how I also try to think when I do something. Because yes, you know, you have to monetize in some way to continue to grow, to create more value. Uh, but you also uh, want to uh, offer value for free. Especially uh, what is called product led, uh, growth in software businesses. Uh, but it's a bit like your free gym membership for a week or there are a whole bunch like try before you buy is something I think that's almost uh, mandatory today. And you want to create a portfolio offering that allows people to try out, get value and then sort of climb up this pyramid of value over time.

Speaker A: Uh, I find myself thinking of. So there was a, a big switch, um, in my little business. So I was a classic 1 in 20 guy. But I was going to lunch with Mohnish Pabrai and Warren Buffett and I didn't want to be a 1 in 20 guy. So I introduced this zero management fee share class. And what struck me is when you said, uh, demand follows a power law. And I think that we have a hard enough time thinking of just growth. Polynomial growth is already too hard for mind to understand. We think in terms of linear equations. But power law is a whole different thing. That if you have a hard time getting your mind around something like Y equals X squared something, something, something, you'll have even harder time following something where Y equals a number raised to the power X. And um, I think of Costco and Amazon, I think of my use of Kindle and Now I don't know how many books on Kindle I've bought, but now the highlights that I've put into my Kindle, I don't know how Amazon's going to monetize it or how. But, but it's, there's. I guess what I'm trying to say is, uh, and this comes from the Santa Fe Institute, more is different. So you can even imagine what will happen when you continue to sort of drive demand through a power law type framework if you like. But we could go on for hours on this. Tell me this, uh, because we're beyond an hour already. Um, do you do consulting? So you've written a book, you clearly do podcasts, uh, you creating courses online. But if somebody says, I want this guy, Rita Van to look at my specific situation, do you do work like that? Which of course in a way is not scalable unless you get to reuse the content.

Speaker B: No, but I'd love to do that kind of work. But I think like you said, you know, this 1 in 20 dilemma that you had, um, and I feel I'm at a stage in life where I'm having a similar churning, like I could just go out there and monetize my expertise, uh, based on hours worked or whatever as a consultant. And I have done that, uh, you know, in the past. But I want my compensation to be linked to value delivered. And if someone aligns with that, I'd love to work with them. Because the kind of opportunities I lay out in the book, the, the way I like to think and solve problems, I think requires this kind of alignment. And I want to move away from this 1 and 20 type of thing. I mean, of course I, uh, you know, I need like uh, some kind of retainer or some way, you know, just to cover the market mortgage. Right. I'm not, want to be, uh, naive and, or whatever. So I think that that component is there. I'm trying to get that component slowly over time covered through content. And then ideally, you know, I want to be like, I just want to get compensated for value delivered. And I, you know, and then, and I think that achieves amazing alignment, which as a typical, uh, professional services, you know, consulting vendor kind of person, you don't have. And I think this, this gives real meaning and this allows you to compound value creation over years and not think in terms of, oh, this year's budget, we have, you know, we have 50,000 left. Let's just do something right? Uh, and this, this is just wasteful. Like I don't want to Be stationary. You know, you have these stories of, of uh, of companies or government offices going and buying stationery because budget is left. You know, you get uh, 5,000 pens or something. And I don't what, what I find really sad and wasteful is it if data and algorithms are bought like stationary.

Speaker A: I mean, just again, what I'm going to do because, uh, time is short is I'm going to riff on that a little bit. Then I'm going to get Paris an opportunity to either both riff and maybe ask one or two questions. And then I'll, uh, give you, uh, Ritavan, a uh, final set of comments before we close this down. And um, now I need to reconnect to the thought that I wanted to riff on after having done some housekeeping. And um, it is going to come back to me. Yes. So if I was in the. So I think that something that motivates me is. And it's not got a dollar value, but I. So I'm in a place in my life where part of what I want to be able to do, uh, in 20 years time is to tell great stories about how I genuinely made a difference or even better enable other people to tell great stories about how I genuinely made a difference. And so, for example, this call, maybe in 10 years time your life has changed as a result of this call. And I will chalk that up as a win for me. That would be a beautiful thing if that were to happen. I'll keep trying that. That's upside measured in terms of stories told rather than any kind of monetary, uh, result. And I think that if I was, I mean I think that you have a unique, uh, a special knowledge set that can be sold on a consulting basis on a small scale as well as being taught to mass audiences like this will be, or on online courses. But I think that if I had. Bespoke is the word, if I had a company coming to me in your shoes and saying, we want you to consult to us one on one bespoke, my answer would be that's fine. And uh, I need to be rewarded for my time at some basic level. But part of your commitment to me is I'm allowed to tell the story of what happened. And obviously I'm not going to go and reveal data that you don't want revealed to your competitors or anything like that. But basically if it's a success, which I would only take the project if I think there's a high chance of success, I want to be able to tell the story of what happened and then Me, as your, um, future publisher, editor, book agent, will want the next book to be about how you actually had agency in all the stories that you told. So the stories that you're telling are beautiful stories in this book. And maybe later in the book it comes up, but the next book that you write will be how you had agency in the book. Just some ideas there. Uh, and I wouldn't work for somebody who said, under no circumstances can you ever talk about my work. I have a friend who shall remain nameless, who worked for household name pop artist, um, uh, on a show of hers in Vegas. Uh, it would have been transformative for him. And three days before the show was to start. This person has an enormous ego. The household name, you'd know who she is. And offline, I can tell you, I just can't tell it in public. Three days beforehand, she cancels the project, which she can do because she's that kind of person and she had a slight cold or something. And his contract said that he could not talk about it, and so he couldn't talk about it. And that part of the music industry is such that if you do talk about it, even though if it's a household name, your name is trash anyway, because confidentiality is everything. And, and it's just very frustrating for him because that would have been a breakthrough project for him that would have branded him as somebody who worked on xyz. Think of the police. Think of Queen. Think of, um, uh, the lead singer for Queen, something like that. So I just want that. But anyway, that's me, uh, and I heard loud and clear, if anybody's listening to this, Richard Van is open to consulting contracts, but paras last thoughts from you before going back to ritavan M.

Speaker C: Um, so the book itself, I think was great. The conversation has been even better because the two linking both of them together has clarified a lot of the questions that I really just had while reading the book. Uh, the case studies along with the discussion. Now I think I understand the ideas, uh, a lot better. So I guess with the courses, the email list, and all of, uh, the other things to go together, it probably would already start producing and providing a lot of value to people, even if not in business, just in personal life as well. There are a lot of ideas that can be implemented in one's own, uh, life through the book.

Speaker A: And for my part, thank you, Paris. I'll be reading the second half of the book and hoping that I didn't reveal my stupidity too much during the course of this podcast. But, uh, Ritavan it's a pleasure. First of all, thank you very much for the, uh, insight and knowledge that you gave to us on, uh, the energy trading industry. That was super valuable. I feel like you're a kindred spirit as being somebody who's, you know, third culture, kid, living, living from one culture, in another culture, in another culture. And I feel very similar. And you know, my children, when they finally, uh, having been in various different kinds of school, went to Zurich International School, in a way, they finally came home because they realized that they were just another version of an Afghan kid who had a German father and an Angolan mother and all sorts of crazy things. And in a way, I guess, uh, um, a former UK Prime Minister called us citizens of everywhere and nowhere. And you know, we accuse, all three of us would be accused in a way of being, by kind of sudden Trump, uh, direction politicians as being globalists. But I would say that I think that there's an aspect to all three of us which is very, very local. We care very, very much to be good citizens of the place that we're in and abide by the values of the place that we're in and, you know, pay taxes and to be a contributor to society. So my word to all you, um, uh, Nigel Farage, Donald Trump, all of those people, is that not all globalists are bad. Some are good, something like that. But, um, Richavan, uh, if somebody wants to follow you, get in touch. How do you do that? Is the book available on Amazon? Give, uh, us your how do if somebody wants to engage further. How do they do that?

Speaker B: I'm m only on LinkedIn and pretty active there, so I'd love to connect there on LinkedIn and, uh, otherwise on M ritvan.com, uh, I always try to have a whole bunch of, you know, podcasts and free material, um, that allows you to sort of familiarize yourself and uh, yeah, write to me on LinkedIn. I'd love to hear from you. If you read the book and like it, you know, write a review. I think any kind of feedback is always, uh, you know, makes me really happy.

Speaker A: Thank you, Ritavan. Um, thank you Paros. See you again. And we look forward to meeting you in person at the right moment.

Speaker B: Thank you guys.