Top Five Lessons from Leading Analytics at Facebook and Data Science at Sequoia Capital

Thank you so much, Harry. It’s really my honor. I love this show. I would say this is my favorite podcast show, and I’ve listened to so many amazing people saying amazing things. And I I’ve learned so much from the show, so

an honor.

Yeah. So Rohan was my manager, and I I think he went on to lead a bunch of different teams at PayPal. And I was working in at PayPal and was primarily on risk management and doing a bunch of different analysis. And I actually got caught in a crossfire between two senior leaders. And what ended up happening was it became really, really frustrating for me, and I couldn’t actually do my work. Basically, what I did at that point was I was so frustrated that I wanted to quit.

Rather than address the problem, I wanted to quit. And I went and told Rohan and said, you know what? I don’t wanna stay here. I actually wanted to quit. And for which he basically said, you know what? You never want to be a quitter. Set things right, fix things, and then when you’re in a better state of mind, come back to me, and I’ll see what I can do. So I stayed on for another six to nine months. At that point, I got into a much better state of mind, fixed all the issues I had with the senior management, and then fixed the problems there was and and actually got the PayPal trajectory back on track.

And then I went back to Rohan six to nine months later and then basically told him, okay, man. I fixed a bunch of different stuff. I still feel like PayPal is not the right place for me for several reasons. And I told him, I want to go to a different company. And he actually reached out to Facebook and literally got me a job there.

Yeah. You know, I mentor a lot of high school kids and undergraduates, and I tell them the number one most important thing that you need to learn as a kid, especially at their ages, because they’re extremely talented where they’re very smart, they can do things is character building. To me, I think it was a character building exercise. Not quitting is a character building exercise. I mean, as we are a child, we are being told don’t lie, which I think is a character building exercise. Just crossing any line that you want to that you think you shouldn’t is basically a character building exercise.

And I I think it is a very strong character building exercise for me. So, yes, specifically how long it takes, at some point or the day, it’s gonna hit you if you don’t build character. So I think two years would have been a very long time, but I think six to nine months, I think it is worthwhile because otherwise, I might never have done it. And that has helped me so much later because when it became very tough situations at Facebook, I knew how to handle it.

I didn’t back away. I didn’t say I would run away from a problem. I stayed on with it, and it was a very, very good six to nine months time spent. What was

I think the hardest part for me was when I was managing a bunch of analytics teams and Integrity being one of them. And it turned out that the kind of data that we were actually providing was there were people in the organization that want didn’t wanna see the truth, and I was trying to be a truth seeker and say the truth there. And it ended up being that the senior leadership there did not like what I was saying, and I almost got fired for it. But that’s when I think people like Javier and Alex at Facebook actually backed me up, and the trust they had in me was amazing.

And the fact that I didn’t actually run away from it and stayed on helped me, and the fact that there were people who are willing to back me up to the hilt helped me a lot.

The couple of biggest lessons is, I think, one is, focus on impact, especially after I went to Sequoia Capital and saw so many companies. And then I found out what was the thing that was so different than Facebook than any other company. It ended up being it was really the fact that Facebook focused on impact and many other companies did not.

The impact is essentially the thing that you’re doing, is it a needle mover? That’s basically what it is. Is that does it move the needle? Are you always prioritizing on the most important things all the time? And if you’re able to do that, you’re actually focused on impact. Now how do you measure that and how do you do that? So in my own framework and I I talked to companies about it, I also did that internally at Facebook is that I think of impact measured in three different ways.

One is you move a metric. If you take a specific metric that you have in mind, which is maybe a North Star metric and you wanna move that, that essentially is one way to create impact. The second is influence a product decision that could be, like, you’re doing things to identify an opportunity to help set a road map or a strategy. Those would be another way of creating impact. And the third was influencing and changing a process, which is be like, hey. It’s something that they do being done manual, and I can now automate it, and that would also relate to create impact.

And I tell I used to tell people at Facebook that if you’re not doing one of this, if something you’re doing, an activity doesn’t come into one of these things, you’re probably not having impact. Then what ends up happening is that you confuse motion with progress. And so there’s a lot of motion. You do a lot of different work, and you find out that it’s not prioritizing on the right thing. Essentially, impact is saying you shouldn’t be confusing motion with progress.

Yeah. Motion is about doing tons of work, and I re recall when I used to be younger, I would say I worked twenty four hours. I didn’t sleep three nights in a row, and that’s just basically saying you did a bunch of different things, lots of activity. But if you ask those three days of activity, what was the impact? What is the value of the activity? And you can’t actually say much. Oh, I did 2,000 things. And I think it’s the right of passage. I think at the at the earlier phase of life, you like that you actually work hard and you feel good about it, and working hard is the most important thing.

I still think it’s the most important thing, by by the way. But if you work hard and don’t work on the right things and you don’t prioritize it, that doesn’t lead to impact. And so the idea is that the motion is all about activity. Lots of different activity. And it’s kinda like a vanity metric. I mean, it’s like saying, I have these millions of billions of installs where I the the retention is, one percent. Right? It’s

Yes. So I have a framework for this. In terms of if you take a completely new activity, right, you’re actually learning up in a in a curve, and then you start a flat note. Right? I mean, if you look at it, you go down straight line, you keep growing as you go along, and then after a point of time, you asymptote. Either you don’t grow anymore. Let’s take, for example, basically, this thing brushing your teeth. I mean, brushing your teeth is now second nature. You can’t say that if I spend two hours on it, you’re gonna get that much better.

Probably not incremental. There’s opportunity cost to it. So in terms of activity, if every single activity that you do were on the straight line that every single hour that you spend, every single day you spend, it improves or increases or you’re better each day, then I think you should be spending time on all kinds of different types of activity and you’d be okay. But I think if you spend 80% of your time actually saying that you’re all you’re trying to do is provide a a basically, traffic ticket at the New Jersey Turnpike and you’re handing it out, that can’t be if 80% of your time is just doing that, you can’t say I’m getting better and better at it.

So I think it’s a kind of activity to do whether you are on the growth curve of the activity or in the or you are in the asymptote of the activity. And I think if you maximize that, then you’re probably in a much better shape. Mark once said in a q and a in internal to Facebook that he said that he and a lot of the reasons why we do that is because of how secure we are as people.

And he would basically say that something like I I don’t remember the exact number, but he said, like, 80% of his time, he does activity that’s outside his comfort zone, which basically means that he’s trying to be on this sloping growth curve rather than the flat curve. I think most people can’t do that because they are not secure enough to do it. But if you are able to do that, I think you’ll have the greatest impact you can in the shortest amount of time. An impact also is if you think about the total amount impact is impact over time.

Right? The total amount of impact you can divide by the time that you spend.

I think at the highest level, you know you have so many things in terms of the data team that you are at Sequoia that you can actually do. For example, you could be spending time on on sourcing. There are three types of activities that we did. Basically, we I would spend time on sourcing, which is trying to identify companies that investors can go talk to. Second is due diligence. Once the company comes in and they give us the data room, we basically need to make a recommendation on whether this company is doing well or not.

And the third is company portfolio building, which is like go to the companies that are trending well and basically try to spend your time and try to see how you can make a good company great. And that’s the third thing. Now if you were to spend the time, it’s again come come back to what how you spend your time. If you were to spend the time that is a company that is likely not going to go up onto the right and you spend all your time on that, you can imagine how much of impact the company would have.

The same thing would be true with the sourcing. If you give an investor 200 different leads rather than a top five leads that matter, I think it makes a material difference to how it is. It’s also the due diligence. What we realized on the due diligence part, in particular, what we realized even through the way we prioritize was that how quickly can we say no? And that was primarily what we arrived to because that was the fastest way. What is the one signal in every company that would say no rather than say yes?

What we would find is that there was a company where we would actually find out that they were growing really well. Everything was going right, to the right, and then we would find out we ask them for the marketing spends, and we would find the marketing spends the reach of the marketing. When we look at the marketing reach, it was very close to the addressable market. So, basically, they already talked to everyone, in which case we realized that that one thing is not.

Another company, find out that the reason why we did not invest was we realized that there are all the older cohorts who are doing really, really well, retaining well, and engaging well, but we found that the more recent cohorts were actually starting to decline, and we could see it in the data. And that is the one reason that we did not invest in them. So these are just two examples. But every time that we would look at, we will stress it and saying, how can I say no to the company?

So two things. I think if you look at it from a funnel perspective and from the time perspective, if you think about it, if you think about the funnel and saying the investors talk to, let’s say, 2,000 companies and all per year, probably it’s more, but let’s say it’s 2,000 to 5,000 companies and all. And then you have this bucket of let’s say, there are only 50 great companies and all every year that you can even invest into, then you wanna catch those 50. And the thing is that if you make wrong investments and many of this, by the way, that we stop Sequoia from investing where things they would have otherwise invested.

It is so close to investment. So then you’re gonna spend so much more companies. So think about every investor. If you have 10 companies in your portfolio, every investor has ten ten companies in the portfolio. If eight of them are not so good and two are great, they spend all their time on that too, but they can’t do anything, but they they still need to talk to them. If you can make it, like, out of the 10, you have five good and five bad, you’re in so much better place in terms of where you are.

So I actually think that it really helps the investors themselves because you do you do want fewer and fewer bad. So I actually think that good investments are relatively I mean, there may be this one great investment that nobody knows about, and those are hard, and I agree with that. But if you think about the good investment, very quickly, everyone knows about it. It’s not that hard for good investment. It’s only the bad investment that you may end up investing, I believe, is where most of the opportunity lies.

Time is a big one for Sequoia because in each investor, they would rather be spending on five good investments out of eight than two good investments out of 10.

I think it’s first, I think the quality of investors themselves are exceptional. I actually think their brand for several several years, I mean, nobody doesn’t talk to them. Right? I mean, you have everyone talking to Sequoia, which actually gets them all the leads that they want to. The third is a diversity of the people that are in the group. You have all the way from, you know, during those times, Mike Moritz and Jim Getz and Ruloff and Pat and, of course, so many other people. And they have this diversity people with different types of skills.

And I think their collaborative decision making is also excellent in the way that the collaborative decision making. I think the process that they take in terms of how they go from the one pages, from the time that they actually source the deal to going through the due diligence process to get into the one pages and getting to actually talk about it and then going through the decision making process. I love the way that they do that process. They keep talking about one thing. Everyone going to the room, they talk about this prepared mind.

I keep talking about it since to my team and so on. It’s like, people who go into the room, there’s already if you have a Monday morning meeting, they circulate the entire memo on a Friday. And when people go into that room and make a collective decision, they go with a prepared mind, which basically means you better have read your memo. You come in knowing everything. We’re not gonna talk to you about the basics. We’ll go deep into the investment itself.

I think the second one I would say is I learned what it meant to build a world class organization or a world class team that was happy. Again, this came a lot from the growth team at Facebook. I I think both I would attribute Alex Schills and Javier to it. They get a very, very high bar. At their first, I think high bar in terms of the people that they had, the high bar and expectations about them, and in the way that they cared. I think it’s the impart per capita.

So the way think about it is, like, impact is equal to impact per capita or impact divided by number of people times the number of people. They always cat over the impart per capita. How much can each person do? Then multiply it by the number of people. So as a result, what they would have is the growth marketing team, Alex ran, had Brian Hale, which who was on the show, and it was like a seven people team or a six people team. And I would think, like, how can six or seven or eight people have such enormous output and enormous scent of this?

And it’s his camaraderie, the way he built teams, the way that he would make sure that every single person who came in would be incredible and never try to grow very, very fast. And so it is impact per capita. I think what we get confused a lot of time is total impact. This, like, total impact can be gained by lots of people.

I would say when I first joined Facebook, and I remember an engineer, Harry, who worked on the payments team, told me once, the way we think about the impact here is basically take our market cap, which I think was 10,000,000,000 then, and there were probably for the sake of math, I’m just going to say thousand engineers, I think it was far fewer. But it just for math, I’m just saying it’s a thousand engineers. So that would be, like, 10,000,000 per engineer if I’m doing my math right.

So, essentially, you’re saying every single engineer contributes 10,000,000 to this. I think it was more like 20 or 50,000,000. So every new engineer that comes in will have to contribute so much. Otherwise, if you can’t find something that they can do that can be of that type of impact, don’t hire. And I think it’s the same sort of mindset that Alex and Javier and everyone else had, which is like, do not add more people. One thing if you add more people, what happens is you the a plus players becomes a and so on.

And very fast, you need to get to grow very slowly so you can reach equilibriums very slowly and then keep the value of the entire team high. So do not hire very fast. And so that that was one thing. I would also say that the way you may measure it, yes, it’s harder in in many things, but you kinda know. In many ways, you you can think about is, like, if you basically say, I can only have x number of engineers, and then essentially peg your engineers to every other part of the team.

So it’s 20 to one, let’s say, engineer to PM ratio, or from PM to data scientists, a one to one ratio. But, essentially, if you’re saying engineers are building stuff and you have a market cap or some value there, you can actually say what the value of everyone should be.

Yeah. So growth is basically about identifying methods, approaches that scale product market fit in a scalable way. The way you do that is by identifying a notch or metric and moving that metric. In order to move the metric, you need to basically identify and prioritize the most important opportunities that move the metric.

For your specific company, there’s a mission, and it needs to tie to something in your mission. For example, at Facebook, at that time that we were there, it was like making the world open and connected. Naturally, it was you wanted to get everyone in the world on it. So it just naturally meant that you wanted to get the largest number of people to use a product. So MAU made a ton of sense in terms of what you’re trying to do.

100%. So I actually think that at Facebook, you could actually move the DAU metric too by multiple ways or DAU, MAU metrics. But for example, if you’re trying to move, let’s say, the number of friends, for example, that could be more of an input metric. So I actually think that the goal itself that you have, the goal that you have needs to be movable, and you could move it through multiple different ways in terms of what you can do. But I actually think that, yes, if you choose a metric that can’t be moved, that’s not a good metric.

For example, I’ll take the example of advertiser growth. In advertiser growth at Facebook, in the advertisers, we decided not to move the revenue metric, but decided to move the advertiser growth metric because that’s a metric that we actually could tangibly move. But as we didn’t have the levers to move the revenue metric. But I I do believe from an active user perspective or DAU or MAU perspective, we actually could move the metric in terms of what those metrics were.

I think a lot of your North Star metrics changes Instagram as a case. Right? When Instagram came along to Facebook, we still had the MAU as our goal. When we had the MAU as a goal, I mean, basically, Kevin’s system was like, what? We’re now in the mobile world. People use the phones all the time. We do DAUs. We don’t do MAU. MAUs. It makes sense sense because, essentially, people are using the product every single day. Why are you still caught up in the MAUs? And that made us start a thing because we were still in the web world, which is fine, where people weren’t using the product every day.

So in that sense, as a company starts transitioning, let’s say, from a web world to a mobile world, you need to change. That is one reason why you would actually change your metric is, like, move from a MAU goaling metric to a a DAU goaling metric. That that’s just an example, but I I think the market is one reason. The second reason is actually the world changing on you itself. And third, I mean, you may have just picked the bad metrics. Sometimes in companies, it’s just hard.

It takes a lot of iteration to get to the right metric.

I know, man. I think the problem, as you point out, the biggest problem for anything with your intuition led is bias. It’s bias and how the world will change around you. Those are the ones that you need to guard against. But, honestly, that’s the best you got at that point. So if you actually have to make a decision and I actually think that the cost of not making the decision, in my opinion, is far worse than making a wrong one as long as you can iterate fast.

But you’re right. You’re not gonna get it. The intuition is not fail safe for sure, But even data is not fail safe. Data also works under certain assumptions that you have, and those assumptions can just get ripped off.

If you wanna make great decisions, you need to understand a phenomenon very deeply. That’s my thesis. If you wanna make a great decision, you need to understand that phenomena that you’re trying to make a decision very well. If you want to understand that, you basically need to analyze that problem very well. In order for you to construct the story around the phenomena, it turns out the data has a lot of things. I think of data as a manifestation of you have a story that you care about, and then it’s manifested in the data that you have.

So the data itself is manifested in a ton of different metrics, for example. You understand and say, okay. Active users went up or new users went up or you find that ad spend went up and so on and so forth. And what ends up happening is that you need to come up with a bunch of hypothesis of why they went up or down. And generally, these type of hypothesis for example, if you look at active users going up or something, the primarily, the reasons are either seasonality or it’s a product change or it’s a sales change or the there’s a marketing change or competition or things like that or and it’s manifested as behavioral change in customers, and that’s how it is manifested.

And then, ultimately, you see it in the data. So to me, if you wanna deeply understand a phenomena and make great decisions, you need to understand the story behind it really well. If you want to understand the story behind it very well, you have to go into metrics and see how they changed, identify them, and then be able to come up with right hypothesis of why they changed. And then if you do that, you can make great decisions.

In terms of how you do the hypothesis, you need to stress test it, which means you come up with hypothesis and then you need to look at data to validate the hypothesis. So you just can’t do a hypothesis and say this is it and so on. So the way that you do this and I’ll tell you a quick example that we did, for example, at PayPal in fraud. I mean, we wanted to reduce fraud, which is the most important metric for the risk management, probably the most important for even PayPal in terms of the metric that they carried over.

So what we did was we said, okay. We made a hypothesis, and we basically said, hey. People, if they use the same cookie, which is a web cookie, if more than five people use the same cookie on the same day, there’s something wrong with it, which bay basically, we are saying that people were using a single computer. They were taking over other people’s accounts and do a bunch of different activity on it, and then there is something bad about it. So we basically started with the hypothesis and saying, hey.

This is wrong. So so then you go into the data and try to validate it and saying, okay. Is it really true? And when you go into data, you say, yeah. Many of them actually fraud. So you look at good use cases and a bad use case. The bad use cases are, yeah, the many of them are fraudulent. Then you look at the good use case for the same person who’s using the same computer. It turned out that a bunch of them were family members, or they were using an Internet cafe logging in out of the product.

So what you end up doing is that you need to go back from data to hypothesis and back to data and basically solve the problem that way. Now there may be still things that you don’t know that you don’t know, and your story still may be wrong, but you still want to get to the point of getting from data to hypothesis and back and then be able to tell what the story around it and then hypothesis what story it is. If you can do that, you can make great decisions.

Yeah. I think there are multiple problems here. One is I think when you have the data, it is possible I mean, you have a hypothesis, you can’t even check it. For example, at Facebook, we’d have saying that, hey. By the way, we would wanna know why advertisers churning, and there’s no easy way to find it. I mean, you actually need to do a survey. It takes a long time, and then they would basically say ROI. When they say ROI, we still wanna understand what ROI meant to them because we don’t actually know the data behind it.

To validate the hypothesis many, many times, you can’t do it through just data. You need to do it through, essentially, user experience research. There is a problem of just being able to validate your hypothesis because there’s a lot of time you don’t have the data. The flip side is also true. You may not even be able to come up with the right hypothesis, and I’ve seen that happen too. It’s like you don’t know what went on and suddenly you realize what happened. For example, what happened at Facebook and it happened became with a hypothesis very, very much, much later is, like, we found that there’s certain parts of America which had an increase in time spent, and we didn’t know what happened.

And we kept looking and say, what is all this? And we kept digging deep, and it ended up being very cold winters. People staying at home, and they use a product a lot more, and the times went went up. And if you look at just time spent across US on extremely cold days, you see an increase in times went not.

Yeah. You don’t want to hire anyone before product market fit. Because at the end of it, I think, as I mentioned to you, I think growth is about scaling that product market fit in a sustainable way. It basically means that if you’re not able to grow, if you’re not even reached the point where you can actually scale it, no point getting your first hire. So product market fit.

If it’s a consumer product, people wanna come back. They wanna keep using the product. They seem to love the product. And you’re not throwing more money at it, which means that’s why I mean by sustainable. It’s not like you’re throwing huge amount of marketing dollars to just keep them on, and there is some they’re actually being able to provide a value that other companies don’t. And I think with the product market fit, it doesn’t mean the product market fit, you can actually scale it because the moment you start charging, for example, it’s a free product.

And maybe just the people are only using it because it’s a free product. The moment you charge it and charge the same amount as a competitor, it may just go away. So it’s not that it’s guaranteed that you’re gonna go from product market fit, scaling product market fit, unit economics, scaling unit economics. I think those are all four different steps in my opinion. You can get to product market fit, but you may not be able to scale it for several reasons. And if you get to scaling product market fit, you may not get to unit economics.

And if you do, we get to unit economics, you’ll now be able to scale it.

Yeah. The first hire, I’m not sure if you just hire one single person that’s gonna be that valuable to you. Meaning that what would that one single person do? It probably is a team that you need to hire. And if you think about the one single person that you’re trying to hire, if you are thinking about the one single person you’re trying to hire is probably the leader of the team who can then get everyone else, such as getting you the designer and the growth marketing person and the analytics person, the product manager, and the engineer, all of them on board.

If you don’t have that, I am not sure how you can actually function because you can have someone. They won’t have and, of course, the marketing spends the dollars too for it. And so if you don’t have that, I don’t know what they would do if you had just one person. But I would basically say that if you had to hire only one person, it’d probably be someone who’s relatively senior, who can hire everyone else, or be part of the team and so that you can actually get a team that can actually work and move a metric.

I think there are two answers to this. I think the answer at an earlier stage of your growth, they should be a standalone team for two reasons. One is I think it’s the is for the best practices, meaning that they can learn from each other, and then they can go solve problems across the company. Suddenly, you separate this team and put them into the different parts. I don’t know if they’ll be able to build the same culture of the know all. A lot of it is knowing how to do this really, really well.

I worked on many parts of this from pages growth to games growth to advertiser growth to and then when you have all of these types of growth, what ends up happening is that these sort of knowledge does translate. And imagine that all this was not part of one single team and they were separated all over. I actually don’t think the learnings will be there. So my feeling at the earlier stage, you should all be centralized. Now once you get a large enough team, if you get to a large enough team, I actually think that it can start to be decentralized and work go into product teams, but I actually think that early on, it should be centralized.

So the more important thing is that somewhere in the interim, you probably have a a role where you embed people into team, but you still have a centralized organization. And then at some point, you move completely decentralized.

Yeah. At the end of it, to think about it, you’re at a series a. Are you gonna do 20 things? Are you gonna do two things, three things, four things for the front of the growth team? So there are fewer things that you’re actually gonna do. And for that, a small team will just suffice. You’re doing very, very few things. And for that, those five people that I talked about just do, And you’ll work on one, and you’ll go work on the second, and you’ll work on the third, and you’ll actually work on multiple types of problems.

At any time, you probably don’t work on more than two or three because the surface area can’t be that large. If you’re gonna spend that much time on everything, you’re probably gonna do nothing right. So I think at a smaller phase of your company, you don’t need. It’s the surface area narrows, so you can actually do it with just a centralized team. But, actually, when the surface area grows, you can actually start to spread your wings out. So I actually think it works out.

Again, this comes back to the product growth. Right? So this I’ll give you an example. When I joined Facebook, analytics was all about counting numbers, and then it was creating dashboards, and then it was doing AB testing, and then going towards goals, road map, and strategy. So, initially, the types of person that we needed to hire were basically people who can just count numbers. And secondly, so it was bunch of people who can create infra to create dashboards. The third was people who actually were statisticians who could do AB testing.

Finally, it was people who could influence. And even now, I think it’s Facebook is like the analytics team is largely about influence even inside the growth team and so on. Throughout, it’s about influence. So the point is that if I’d actually hired three years earlier and said I’m gonna hire people for influence, what would ended up happening was people wouldn’t have been able to do the same people who do the AB testing who needs stats background are not the ones who can actually influence. And what would happen is that you wouldn’t have actually taken the journey in the right way.

So what ended up happening was that we build a dashboard, we automated it. AB testing, we built something called Delta. It automated it. And then when we could automate all of this stuff, it will became easier for us to move towards what we think was the most valuable thing that analytics teams could do is influence. So, again, we would even in the growth team, you’d actually understand, identify opportunities, influence the road map of products, of the road map of what we need to build. So my point is that I think it depends on the growth of your company and where you are at.

At a later stage, I started to build for much, much longer, eighteen months and so on. But the earliest stages, I actually hired for what I needed right now because there’s no point in hiring someone who will be so valuable for you in eighteen months and who can influence everything but can’t build your dashboard. Advised a bunch of different companies. Now I changed my answer based on who I’m talking to. If I’m thinking this company is in a rocket ship, for example, a company like OpenAI.

In fact, I did that. And when I talked to OpenAI, they asked me who should be hiring for the head of analytics and head of growth and so on. I said, oh, someone who’s look looking at a rocket ship, don’t worry whether they are statisticians or they’re this. Influence is the most important thing for them. But if I were to be at a early stage Series A company, would say hire for someone now because it’s just as a early part of your product market fit. If you reach certain levels of scale, I think it’s a very different thing.

So I think it’s a lot to do with the stage at which you are at, and I think your answer is either very short term or long term. But keep in mind, it’s gonna become long term. The company goes into a rocket ship, you do need to hire for the long term.

Great question. I think influence is a hard problem. So I think influence is obviously an art, not a science. And so if people are very receptive about what you’re gonna say, it’s actually very easy. So people who are very data informed, who actually want to embrace data, it’s actually very easy. There’s also what and how there, which means, like, what do you wanna say and how you say it. If you actually are not doing that very well so one thing is, like, I may just not do a good job of influencing.

Say, if you have the right data and be able to influence, I think there are multiple reasons. One is the person that you’re talking to. If they’re not receptive, it’s very hard for you to influence. Second, if you’re not doing a good job, you may not be able to influence. Third is that the answer may be right, but if you don’t have the right data to convince people, you may not be able to. And the fourth, think, is just biases all around. I think if people have strong biases about what they want to see and don’t wanna see, I think it’s very hard.

For me, I think in particular, in my earlier time, I had Facebook, I think I struggled with influence largely because of the fact that I I I actually think that there were specific leaders, and this probably what Alex is talking about, who are not receptive to what I was saying. As a result, it became very hard for me to influence them. It both hurt me and I think the company a bit.

Yeah. It’s patent recognition, Harry. I I actually think that over a period of time, you do so much of it because that’s all I practiced. At Facebook, if you think about what I did the most was influence over a period of time. And then you have so many different characters, and each of them just becomes a cast of characters, and you start to understand what ticks with them and what does not. And once you do that, there is a way of approaching influence. So I actually think it’s an art.

You have an idea and say, oh, this type of person, they can be influenced through data. You need to be really good at storytelling. For example, Harvey. You go to try to influence Harvey. You just throw the data. Don’t give me anything other than just data. Just tell me the data. Don’t tell me the story. You go to Chris Cox. Don’t just throw data at me. Tell me the story, please. Both are extremely well meaning, but there are multiple different spectrum of people that you work with, and you have to understand who they are.

I also found that while I worked at Sequoia, I think I found four different types of founders, people who love data and knew data and wanted to embrace. That’s one. There are people who love data, thought they knew a lot, but would not listen to you because they knew thought they knew more than you. And then there was a third who did not know data, but said there is something out there. Come help me. And that was fine too. And there are people like, this is crazy.

This is so stupid. I don’t believe in data. It’s all should be designed. This is crazy. So you have all of these types of founders, and some of them you just can’t. The people who are like, I’m gonna be closed, have a wall in front of me. You just can’t influence. There’s no way to influence. But the people who are like, I don’t know much, but I am hungry, you can. The people that are that know data, but they say, wanna know more because I wanna learn from people around me, those you can.

The people who are adamant and saying, know more than you. Very difficult. And I’ve had all these four. So you got to judge that of who are you talking to and then how you tell the story. You tell the story. Do you just show data? How much of data do you show? Do you go deep into storytelling and tell them every small thing or just peel layer after layer after layer? And you need to learn that while you’re talking to them. And then on the fly, be ready to influence, and that’s a very hard thing.

What are the biggest mistakes people make when trying to influence people have

The biggest one I used to make and I think most people make is confusing the what and the how. What message do you want to deliver, and how do you deliver the message? When you deliver the message, we are all human beings. And so if you can do it in a way that is easier for that person to handle, I think or they it can resonate with them or all the influencing skills I talked to you about, then I think it makes your job much more easier.

I’ve seen many, many people try the influence, but they fail. I mean, for example, I knew a very senior leader at at Facebook who they’d be so blunt and say, this is it. Take it or leave it. And it will never resonate because they didn’t try hard to influence. They just wanted to say the facts. I mean, at the end of it, influence is not about just saying. It’s about having the impact, making sure you’re able to influence into making a change in the direction that you think should be the right way to do it.

It’s not just about saying things. It’s actually making the change. For that, you need to go far more than just saying things in any way you want. So you gotta start to understand people and psychologies and all these things.

I I think very dimensionally, which basically means that I don’t think about a person as a person. I think of them as a body of skills. So what that basically means that are they peaking in one or two or three different things and not a liability in the others? That’s kinda how I think about every person. So if that’s what it is, I would think, like, I say, oh, this person, the ex exception in a b c, they can bring a lot to the table. At the end of it, what you’re trying to do is hire a bunch of different people who are excellent what they do that they can learn from each other and become better each day.

So what you’re really trying to assemble is if you think about why anyone comes to work, it’s for four different reasons. One is they love what they do. Number two, they love the people they work with. Number three, they feel like they can learn from the people that they work with. And four, the company is going up into the right. If one of these four does not work, they will leave. Essentially, what you mean is if you add the people with the same skills, all of them being exactly the same skills, they’re not gonna learn from each other.

Other. If you’re gonna have people that you feel like you don’t love working with and they’re all jerks, how are you gonna stay? If the company’s not doing very well, it’s actually a company that was great fifty years back and doing nothing now, are you gonna stay? No. The company’s gotta go up and to the right. Finally, do you love what you do? You come in to do something. You came to do design or you came to do growth marketing or you came to do analysis or you do something.

Do you actually enjoy your job? And if all four of them fit, you do a great job.

I agree with you that there are reasons why people may stay, but you ask me for the kind of person that I wanna hire and what I wanna have in the team and what really makes them come every day. The thing about the Morgan Stanley guy who you’re talking about, they’re probably working out of fear, or they’re working because of some boss. If you ask the same question of, are you getting the best out of that person, him or her? I don’t think you are. It’s hard for me to think over a long period of time.

Maybe over a week or two, you can. For a period of a year, I don’t think you’re gonna get the best out of the person. So if you wanna get to the best of the person, they really need to enjoy what they do. It’s about making sure that they don’t come to work with fear. They come with loving what they do and building up a bottom of culture that they can be happy and wonderful at. You said

I think there are a few things. One is I think from an analytical perspective, I I’ll talk about the body of skills, and then I’ll talk about outcomes. The body of the skills would be, like, are they able to break a problem down? That’s becomes an important thing, which if you give them a complex problem, are they able to simplify it and make it convert into a a business question into a technical question? And then from the technical question, can they convert into a data question?

And then from a data question, are they able to do the right type of analysis? And then from the analysis, can they derive the right type of insights? And then from those insights, can they convert into the actionable insights? From the actionable insights, can you convert it to opportunities and decisions? So there’s an entire flow to that. The first few skills that you have is breaking it down is more like a consulting skill. It’s like a mindset that you need to have. The second skill is a technical skill which requires some amount of coding, etcetera.

The third is analysis skill. And the fourth is basically a lot of it has to do with in in terms of synthesis skills and influencing skills that you need to have. And if you did all that, you can do great at that in terms of analyzing a funnel or analyzing retention or analyzing any sort of problem that you want and identify opportunities, set road maps with it, and trying to move the thing forward. I’d also say that in terms of analytics itself, there are literally only two things you need to do.

One is indexing. You wanna see if things are under indexed or over indexed in anything you’re comparing and benchmarking. And the second thing is asking the so what question. The only two things. So for example, over indexing and under indexing means that if New York is going up, you’re asking if Chicago also is going up. You need to benchmark to something. And if if New York is going much more up, it’s over indexed, and so then you want to provide there’s an opportunity of some kind.

I’m just simplifying it. And then if New York went up by point 001%, is it material? And that’s a so what question. And that helps you prioritize. So, essentially, analytics, literally, you need to know only how to index and how to ask a so what question. If you do that really well, that’s really the two skills that you need. But in order for you to even get that, you need technical skills. You need all the other kinds of skill because you need to munch data. And then being able to tell the story, put it together, and influence.

Right? That’s the other part that he said. You can actually do this, so I’ll do that, but if you don’t know how to influence it, it’s a problem. That’s a slightly different dimension. Technical is a different dimension, but the analysis itself, the core to it is basically only two things.

Let me give you an example. Right? I I worked with MongoDB while I was Sequoia. So at Mongo, what we basically did was we basically were looking at the pay payment conversion rates. And I went in there and they had a data science team and they had an analytics team and they had worked on it for, I don’t know, how long, but I went in there, took a quick look, and found out that Germany had a very low conversion rates compared to its neighbors like France or the rest of Western Europe.

It had a far lower payment conversion rate. And I was like, it shouldn’t be. It should be similar to the other European countries. Why is it so low? And that’s the benchmark. It doesn’t have to be the average. It has to be what you think is a similar country or similar something. And so in this case, what ended up happening was that they turned out that Germany is very different. That’s such it’s it’s a very bank country. It’s an ACH country, so they use banks a lot, whereas the rest of the country use credit cards a lot.

And it turned out that MongoDB did not have a way for people to pay using a financial instruments using banks. They only had a credit card. People would go try, look at bank. There was no bank available, so they would just not convert. And so what I did was I told them, hey, guys. Go and change that. I I think it materially changed the top line of the companies. I think they told me I don’t I don’t know whether it’s true, but it’s a few percentage increase overall increase in terms of conversion because Germany was a big country, and it was converting at abysmally low rates.

The so what is all asking the question of, okay. This thing increased by point 1% or point 5% or 1%. So what? And if you ask a so what question, you are basically saying, so what? Yes. If I do that, it’ll increase my wow, my north star metric or my north star metric by a 100,000 users or by 200 users. So if it’s 200 users, you’re still like, duh. It’s no value to me. But if it’s 100,000 users, wow. That’s super cool. That’s what I wanna know.

So when you look at the so what, you have to have a sense of something is material or not. And material basically means you have to have a sense of what your overall goal is. If you have an overall goal, is this the highest opportunity you can have or one of the high opportunities that you can? So you gotta tie whatever you’re trying to do back to something into a North Star metric. Even if it’s not this goes to the art and science part. Even if it’s not an exact, you should have a sense of how much you’re gonna drive.

Without asking the so what question, that’s a problem. And what I realized was the difference between good analytical people who can be good at insights, but the ones that are good at actionable insight, the muscle is really the so what question. It’s not the analysis. They can be great at coming out with lots of indexing and analysis, but coming on, they don’t ask so what questions enough. That’s And what I’ve seen differentiate very, very good analytical leaders and not and who can take basically data into action better because they can they know how to go from insights to actionable insights.

Yeah. More and more senior you get. The number one and probably the only thing I care about is their ability to simplify. Chris Cox once told me that I asked him, what is the one single thing that senior people can do? Is it simplified? And that’s the same thing I have is, like, can you actually simplify? When you look at a very senior person, I look at if they can simplify. Simplify shows clarity of thought. Clarity of thought shows your first principle’s thinking. So if you have great first principle thinking, you have higher degrees of clarity of thought, which leads to simplification.

And so the more senior you are, the kind of skills that I look for is can you actually simplify, which basically means that you can take very complex problems, break it down, and you can actually take on harder and harder problems because you’re thinking first principles.

So what I do is I actually have a blog. And when I did the series of blogs, I wrote one on sustainable growth. And on the sustainable growth, I have them read it. I send them and say, go read it. And there are things in there which is not quite right. There are things in there that make sense. And I basically first question I generally ask them is synthesize. What are the primary takeaways? So those are the kinds of things I go through every single day, and it’s not just that I go deep into retention.

I go deep into growth itself. I ask them things like you ask me. It’s like, what is product market fit? And I see how they think. I can have a dialogue with them because it’s when you are interviewing for these people, I mean, I know what’s on their resume. I mean, it tells you me a bunch of different things about their resume, like, oh, they can code or they can do this or they can do that. I just take that for granted. On top of that, I’m trying to think, in a working environment, when I’m talking to you and I’m discussing with you, can I actually have a conversation with you?

And then in the moment, can you think deeply? And that’s what I’m trying to look for.

Exactly. And that’s what I do. I tell them also upfront in the interview. Tell them, look. No answer is wrong wrong answer. I only care about how you think. If you are on the wrong track, I’ll immediately tell you because some of them are objective. So I say I’ll immediately tell you what is, but I won’t judge you on it. It’s fine. All I wanna do is that if you’re giving giving me 10 ideas and eight of them are good and two are absurd, I won’t judge you on it because inside a great company, those two will be weeded out anyway.

But I don’t want those eight not to be there. So say whatever you want.

Early on, the big mistakes that I I used to make and I make less of it now, I think I’d probably still make them, is I think about slope and asymptote. Asymptote is how good are you? Slope is how fast are you growing. And so what I would hire more for is people with asymptote, which basically means that, oh, they have such a good profile, etcetera. They’ve done so much, etcetera. But they wouldn’t look at the growth, and they may actually flatten out on the growth part.

And that is probably much of my mistakes, you go back to it, one big one would be the hiring for asymptote rather than slope. Now I don’t mind. You can imagine what it it’s just a matter of catch up. Right? People with the slower as in total, the faster growth are gonna overtake. And I generally tend to invest in people over a very long period of time, but within reason, within two people, within slope and this, I know that basically the effect of compounding will just overtake the person.

And if you’re willing to invest over time, you could.

If you’re below a certain age, you do you’re not institutionalized. Let’s say you’re below 27, 30, whatever those ages are, you’re probably not institutionalized. Until that, I think it’s very easy to mold anyone. But beyond a certain age, it’s so much harder. If you are actually in a certain type of company, you’re set in your ways, you have certain ways of thinking, it’s that much harder for you to change. I don’t think it’s impossible that’s not hard. But I would say that if you have developed the growth mindset very early on, which means that even if you’re 31, 35, and you’ve developed a growth mindset where you are then and your mind is nimble and flexible, you can take on almost anything.

It’s like how early did you develop a growth mindset? And if you did, I think you can continue to challenge yourself on anything. But if you didn’t, I think you need to cast them young.

Yeah. I think if you look at my career, I am an oceanographer by training. I was a professor and went into high performance computing. And then I did weather forecasting. Then I went to climate change. I was a is in risk management at Facebook. Then I moved to analytics at Facebook and led many of the teams there, went to venture capital and did a bunch of different things, and now I’m doing a startup. I think my journey has been one which has always been, like, trying to disrupt myself, to be honest with you.

The biggest challenge now I have is essentially I I think two things. One is growing the company itself, and I think growing a remote team in India. The remote team in India had its own challenges partly because of cultural reasons of India and the fact that I think not being able to role model easily because we were in The US and they were in India, the rest of the team was in India. That has been a challenge in itself.

Yeah. So what I’ve started to develop while at Facebook was creating frameworks to think. So when you start to develop frameworks like formulas of framework. Right? And at Facebook, we used to dev dev formulas like you have a formula for the entire company, which is if you look at revenue as the driving metric that you care about, you have number of users and then you have time spent per user and then you have ads per time spent is formula. So those are ways actually to think in terms of frameworks.

So if you think about things in frameworks, you don’t need that much of data. What you really need to think about is in terms of that, which is why when I went to Sequoia, there’s so little data compared to Facebook. There’s so little data. And then I needed to kind of think about abstractions. How do you create abstractions and frameworks? So then what we realized what all the companies at Sequoia, for example, we classify for the types of companies phase that Sequoia had was eight different types of companies, ecommerce, two sided marketplaces, consumer subscription, consumer ads, SaaS, obviously, and so on.

So there are these seven or eight different types of companies, eight formulas, And then what tends to happen is that then you don’t need to have a lot of data. You all you really need to do have is a way of thinking. And for that, you need to have a way of thinking from first principles. And if you can do that really well, you don’t need a huge amount of data. I always have believed every large data problem can be brought down to a small data problem.

Every large data problem can be brought down to I’m being extreme here. Obviously, nothing in general AI is like that. But in terms of analytics, I think it’s actually true. It’s like most large data problem can be reduced to small data problems, and then you’re solving small data problems. So, essentially, if you think of it that way, you don’t need large data to solve problems. You need the right data for solving the right problem, and you need to tease it out. That’s the art.

I would say there are three things I look for. One is I think you look at skill gap, knowledge gap, and value slash culture gap. Those are the three things I expect. If somebody is not doing well, performance not doing well, because somebody is not performing, that can be easily found out. More easily found out if someone is not performing in terms of how they’re delivering, you can found out. But not all people who are not performing will do badly. It may be that they’re in the wrong role, or it may just be that they’re deep thinkers.

I’ve seen that too. Or they may just not be good at what they’re trying to do and so on. So for that, you need to analyze three things. One is is the problem that they’re trying to do is the skill problem. They graded Python, but this is a c plus plus problem. They can’t do it. Okay. That’s why they’re slowing down. Second is, like, knowledge problem. It’s a Python problem. They know Python really well, but this space is security, and they don’t wanna change security, so they can’t do it really Values is like, are they not working hard or any other cultural things that may be.

You have to first identify what the problem is. And as soon as you identify it, if you think it is fixable, then you need put them on the right track and see what happens. So I think identifying whether or not they’re performing is an easier problem, which you can actually do, not just talk to us. Just look at the productivity and see what’s going on. But to diagnose what the reason is is the one that you need to go after.

Often, many, many times, I found that the reason why they’re not doing well is because they’re not in the right team or not in the right role or in the right thing, and you just need to shift them, and then suddenly, they become a force multiplier.

I think when you put up someone in a performance plan, it’s three months too late. Three months before you should have intervened and tried to do the right thing. What happens most of the times is that people put them on the improvement plan when they’ve already decided there’s no chance of success, and that is why it doesn’t work. If you think there’s a seventy percent chance of there or sixty percent chance of them succeeding and you put them on a performance plan, then it might work.

But what ends up happening is that we time it so badly. We time it at 10% or 5% or not even 1%. And I think it’s the timing which is a problem. Most managers take too late to interview, and they’re not willing to have honest direct conversations. And because they don’t have direct conversations, it becomes that much harder largely because most of us are conflict of us, and we won’t have those conversation. And it becomes too late. And then what do you do? Try to go into a performance plan.

I think it’s less about the performance plan is when you time it. But, regardless, I don’t think you need to call it that. Just why do you call it? The label is not great anyway. Just go help them out. If you can’t help them out, make sure that you they can see reason. Almost everyone, I would say, barring a couple of people who have left my team or company, I’m still very good friends with, and largely because I could make them see reason it’s best for us and best for you.

And it’s most times, is that. Because at the end of it, think about it. It’s a two way thing. If I knew what I knew two months later, would have done? Hiring is a terrible process. I know you ask a ton of questions of what do you look for? What do you look for? I can say all I want. It’s useless. At the end of it, it’s easiest when they work with you or you ask referrals from people you really care about. That’s the only one that really, really works.

You can do something in the interview, judge a few things, and even I said this, like, oh, simplicity and all this nonsense. But, honestly, you just don’t know until they join. There is so many unknowns here. They really don’t know. Before we move into a quick fire,

I’d say two different answers to it. One answer is that I think what I’ve noticed is that this happened even at Facebook, and while I worked with over a 100 portfolio companies, I think of it as from an exec perspective, I think there are three types of execs. People who know how to take companies from bad to okay and people who know how to go from okay to good, and there are people who are good at going from good to great. I mean, Chris Cox, excellent exec at Facebook.

Chris Cox is excellent at good to great. I don’t think he was good at okay to bad to okay, which means that bad to okay requires a lot of fighting. This whole thing is bad. Turn them around. Get a completely new. You have to have a different type of mindset to be able to do that. The good to great are people who are superb at being visionaries, who are able to bring everyone along. Everything’s already in a decent place. They can know what kind of products you need to be dreaming for the next stage of evolution of the company, they’re fantastic at it.

What ends up happening is that at least at the levels at which I have seen newer execs, even chief product officers, etcetera, whatever execs you look at, what ends up being is that you just go by resume and say, oh, let’s do this. You don’t actually ask a question of what does the company actually need, and it ends up being that it’s not the same type of person who can do all three or four of these things. And at Facebook, I knew that there were and I will name them, but there are exec who is superb at.

They were superb at good to great like I pointed out. And so knowing that is a huge thing. So that’s one reason I think execs fail is just not. Second is just the fact that I I think they have very strong opinions of what they think they need to be doing. I mean, for example, when I came to Facebook from PayPal, the first week or two, I I I mean, I had worked on risk for so many years, and I said, okay. I was an expert.

I must know more than these guys. I’ve done this for so many years. So this arrogant me went and basically the first week or two went and told them, hey. Do this or do that or do this. And I remember Dan Levy, who was my manager there at Facebook, told me, you know what? You may be right, but you need to bring these people along. By the way, you should be listening more. You’re just actually talking as though you know everything. The thing that is that obviously took the feedback to heart and have been trying to change it across almost anything in life, but I actually that’s what it is.

You you think you know, and you’ve done this before. You know what it is. You come in there. You have notions of how what works, what doesn’t work. That’s not reality on the floor.

The good to great are, as I mentioned, great at strategy, great at vision, not that great, not necessarily great at execution, great at bringing people along and making people feeling great about it, empowering the next set of leaders to be amazing, all the kinds of thing that you want. The bad to okay is, like, essentially firing their entire squad, giving very hard messages, saying everything is crazy, having a center set set of loyal groups of people that they can bring on who can completely change everything and then have very strong execution mode.

I wanna get shit done. I need to go to okay. That’s all I care about. They’re like a machine, and they don’t care that much about how how do people feel. Should I make people, everyone happy, culture, none of that actually matters. It matters only when you get to okay. But in the process, you don’t need to be so you’re so much tougher in how you handle it. And you need both. You’d actually need to go inside a company. You need to do both. But not the same person can do it.

You can’t get the same person to do both. They don’t even think like that.

Basically, looking at a lot of it has got to do with the with looking at asymptote versus slope. I actually think that not the right person you have to find the right person for your company, not look at this amazing profile as someone who’s done some amazing stuff in some amazing company that doesn’t work for you.

Occasionally, I meditate a lot. I have different tones to my voice, which basically for example, the last two months in my company, I’ve I consciously told them my tone’s gonna change. I expect far far more from everyone. And my son realized it pretty early and that I have different tones to my voice, but I’m still under control. I’m under control, but I actually can have a very calm demeanor. I can not necessarily scream, but I can amplify my tone to a point of showing sense of urgency.

Yeah. So a quick story on that. I used to stutter a lot until I was in my ninth grade back in India, and I used to stutter a lot. And one of my uncles basically was in a hypnosis group, and he hypnotized me and then taught me self hypnosis. And I couldn’t finish one sentence. And during the process hypnosis, which I don’t know, but he recorded it on tape. And he asked me to say multiple sentences, and I never stuttered. And so he taught me self hypnosis, and I started hypnotize myself.

And within six months, I stopped stuttering. And then I realized self hypnosis was the same as meditation, so I call it meditation now. So I don’t even know what form it does. I haven’t formally learned it in any form, but I just close my eyes, relax. A lot of times, I just may meditate even unconsciously. Like, you would be in in a in a flow, so I just go into the flow when I’m go deep into things. I don’t even know what I’m doing, and I’m I actually may meditate without knowledge.

Yeah. I try to observe myself and see the stream of thoughts and try to see whether I can see myself as a third person. And then while I do that, I try to see whether I can take the thought back to its origin and see it as a third person. And if I’m able to do that, my mind gets less and less cluttered and then at some point goes blank. But I don’t know that it went blank until I can look at the clock an hour or two later and then see that two hours passed and I didn’t sleep.

I must have meditated. What’s

So many, but I think the hardest part is it’s keeping your customers happy. I I think the customers are happy, but if I have such a high bar for them, constantly feel like there’s more to do. There’s so much more to do with our customers. The hardest part is to build an amazing product that makes our customers so happy. What would you most like to change about the world of growth? One of the things that we don’t do enough is counter metrics, and I saw that at PayPal and at Facebook where you would grow a metric.

Like, at PayPal, for example, there were two teams. One was growing revenue, and then one was actually stopping revenue, which is fraud. And neither team had the other as a counter metric. So PayPal’s growth team would keep increasing revenue, and the fraud team would keep stopping them, but neither wanted the other to succeed, or they didn’t put it as a counter metric. And if the two teams can work together at two different metrics, which can actually fight with each other, you know, and be in conflict is a big problem.

So you should have counter metrics.

I think growth is much, much harder problem than I initially thought it was. And I think partly because if you wanna do growth really, really well, you need a great infra. You need to have great people with high talent density. You you need to have people that can identify opportunities and execute and have the right process for it like we had at Facebook is understand, identify, execute. Then you need to have the leadership buying and making sure that you can have the right leadership to be able to evangelize for growth.

And if you don’t, it’s that. The fifth one is the one I talked about impact. I think if you don’t focus on impact, it’s hard. And to get all of them right is super hard. And I I realized that when I worked with so many companies now is that some of this or one of this fails, either they don’t have the great talent density or they don’t have the right infrastructure. They don’t have a infrastructure in terms of doing AB testing or if they don’t have the right leadership in place to basically say that this is really important or set the wrong goals, which also is a big problem that you can actually set the wrong goals.

All these can be problems.

His ability to go all the way from highest level being able to up level to the highest level and go to, you know, the 10 feet level is incredible. So he would be able to say, here, we are gonna be a mobile first company. And that’s essentially what he wants us to do. And then he will outline a five page document on every single widest, and then he’ll talk about the strategy. And then why does that important pardon? Then he talk about the strategy. Then he’ll talk about every single team and the road map for each team.

He won’t get to the level of which person does what, but he gets to the level of road map and then even initiatives inside of it. He may not get to the specific tactics and so on, but his ability to go all the way from the top, take a big problem, break it down all the way down to initiatives for such a large problem in a five page document, which I think he writes in such short time. I mean, I think he wrote his s one in one sitting on a mobile phone.

It’s astonishing.

Thank you so much, Harry. It is actually so much, so much fun. I’m delighted and great chatting with you.