20VC: Redpoint's Tom Tunguz on Winning with Data: How To Gain A Competitive Advantage & Dominate Markets with Data and 5 Steps To Create A Data Driven Company

Tom Tunguz is a Partner @ Redpoint Ventures, where he has invested in the likes of Axial, Dremio, Expensify, Electric Imp, Looker, and ThredUP. Tomasz is also the co-author of Winning with Data: Transform Your Culture, Empower Your People, and Shape the Future, which explores the cultural changes big data brings to business, and shows you how to adapt your organization to leverage data to maximum effect. Before joining Redpoint, Tomasz was the product manager for Google’s AdSense social-media products and AdSense internationalization. In Today’s Episode You Will Learn: 1.) When did Tom perceive the true power of data for the first time? 2.) What is the biggest difference between a company that is data driven and one that is not? What are the inherent benefits and how can non data driven businesses become data driven? 3.) What are the best data driven teams doing to operationalise their data today? 4.) Adam Grant: 8% of job interviews are productive. So what structure can management use to ensure higher efficiency in the hiring process? 5.) What are the complexities and skills required for strong data analysis in today's environment? 6.) Data often leads to over confidence in decision making, how do you prevent illusion bias once data has been obtained? Items Mentioned In Today’s Show: Tom’s Most Recent Investment: Dremio As always you can follow Harry, The Twenty Minute VC and Tom on Twitter here! Likewise, you can follow Harry on Snapchat here for mojito madness and all things 20VC. Eve make 1 perfect mattress – made with 3 layer technology and next generation memory foam. It comes packaged in a beautiful box and arrives the day after you order. You get 100 nights to try it with free return pick-up – it really is the perfect mattress for everyone. Just go online to evemattress.co.uk and enter the code 20VC for £50 off. Everybody deserves the perfect start with Eve. Cooley are the global law firm built around startups and venture capital. Since forming the first venture fund in Silicon Valley, Cooley has formed more venture capital funds than any other law firm in the world, with 50+ years working with VCs. They help VCs form and manage funds, make investments and handle the myriad issues that arise through a fund’s lifetime. So to learn more about the #1 most active law firm representing VC-backed companies going public. Head over to cooley.com and also at cooleygo.com.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Harry Stebbings?

  Hello and welcome to the 20 Minute VC with your host Harry Stebbings and you can add me at H Stebbings on Snapchat. And for the show this week, we have a very special feature week as we feature one of the Valley's leading VC funds, Redpoint. And joining me today from Redpoint, we have none other than Tom Tunguz, partner at Redpoint, and many of you might have read his incredible blog, but I really wanted to have him on the show today. First, because he is really one of the best minds in SAS, and second, because he's recently released a book titled Winning With Data. Now, for long time listeners of the show, you will know that books are not usually my thing, but this book absolutely had me from start to finish, really was an absolutely incredible read, and so today we'll be picking a couple of strands from the book and deep diving on them. I also have to say a huge thanks to Tom, it was such a fun interview to record and

• 0:45Harry Stebbings?

  a real pleasure to have him on the show again. But before we meet Tom today, it's very easy to see VCs with the books, the blogs, the podcasts, but what about backstage and how they operate and function? Well, that's where Cooley come in. Cooley are the global law firm built around startups and venture capital. Since forming the first venture fund in Silicon Valley, Cooley has formed more venture capital funds than any other law firm in the world, with more than 50 years' experience working with VCs. They also help VCs form and manage funds, make investments, and handle the myriad of issues that arise through a fund's lifetime. So to learn more about the number one most active law firm representing VC-backed companies going public, head over to Cooley.com and also go to Cooleygo.com to check out more.

• 1:28Harry Stebbings?

  And with all the operational support behind the scenes, it is imperative to get a good night's sleep, and that's where Eve come in. Eve is the UK's number one direct-to-consumer mattress company. Because they don't sell through high street stores, they can cut out 70% of traditional costs and pass those savings on to you, the consumer. Developed over four years with thousands of prototypes, Eve are so confident of their product, they give customers 100 nights to try it at home before committing. So what's the risk? For those who don't love it, they even do a free return pickup with full refund. So head over to evemattress.co.uk, enter 20VC, and the kind folks at Eve will give you £50 off, and it'll be with you by the next day. However, it's now time for me to hand over to the main man himself, Tom Tunguz, partner at Redpoint.

• 2:17Speaker 01

  You have now arrived at your destination.

• 2:20Harry Stebbings?

  Tom, so fantastic to have you on the show for a second time. This obviously makes you a very special guest and very special Red Point Week. So, thank you so much for joining me again today.

• 2:29Speaker 02

  Oh, thanks for inviting me, Harry. I really appreciate it. Great doing this with you again.

• 2:33Harry Stebbings?

  Now, I'd love to start off today with the book and we'll deep dive on it a bit later in terms of the elements of the book in greater detail. But the book's called Winning with Data. And I want to start with, when did you first perceive the true power of data? Let's start with that. When was your aha moment of data's importance?

• 2:49Speaker 02

  Yeah, well, so it's more of a sequence of aha moments. But the very first one was when I was 17. I was living in Santiago in Chile and I was working for a law firm at the time. And the managing partner said, hey, we're three months behind in our bills. And so one thing led to another and I ended up founding a company with my dad. I remember sitting down on this like one Tuesday afternoon with the managing partner of the law firm and I told him, I said, here are your top performing attorneys. You're the ones I don't think are doing so well. And he got up in the middle of the meeting and he walked me into another senior partner. And he said, this 17 year old knows exactly who our best performing attorneys are. And he's been here for four weeks. And I was like, wow, with just a little bit of data, the stuff that we were collecting

• 3:30Speaker 02

  about who was billing hours and the interactions between the attorneys and the clients, we knew a whole lot. That's when I was like, maybe there's something to this. And then I remember Google, you know, I started in Google in 2005 and it was kind of the center of the world for data at that point, right? It was crawling all the world's information. And I was working in the AdSense team and we were kind of neck and neck early 2005. We were neck and neck with Yahoo, which was the big competitor trying to run ads on other people's websites. And we were trying to figure out who had the lead and which sites would be a good list to target for us to compete for that business. And so a friend of mine, a friend of mine in the engineering team named Sanjeev, he and I built a tool using the Google search index to figure out exactly where Yahoo ads were running, where Google ads were running.

• 4:15Speaker 02

  And basically every day we could tell you exactly what the competitive market share would be. And so those are probably the two big points. Data really kind of changed the way. We operated.

• 4:23Harry Stebbings?

  Now, now, Tom, for anyone that knows you, they know that you obviously write the incredible newsletter, which is really my must read every day. So, so I have to ask, without being rude, why does it take so long to write the book? You've done incredible array of newsletters. Why now for the book and why did you decide to write it?

• 4:42Speaker 02

  Yeah, we wrote it because, like you said before, this data driven theme, I've really been excited about data for a long time. And one of the benefits of working at Redpoint is I've been able to see the differences between data driven companies and not and companies that are less data driven. The biggest difference among them is that data driven companies tend to iterate faster. Like, you know, I was talking to an angel investor the other day and I was asking him, this is a SaaS angel investor, and I asked him, if you had one question to determine whether or not you would invest in a software company, what would it be? He had this amazing response. He said, I would ask the CEO, how many meetings the sales team needs to set up so that the company hits its bookings number next month? He asked that question because it shows a really deep understanding of the way that a company works. That kind of insight, that's when you know you have a data driven business.

• 5:27Speaker 02

  And so that's really attractive. And in 2012, we were talking about this data driven theme for a while, next generation BI. And we were lucky enough to partner with a company called Looker, which is a next generation BI company. It's going incredibly fast. And because they work with hundreds of companies now, we, we hear all these wonderful stories about the way that different leaders transform their businesses using data. And so when Wiley, which is the publisher of the book, reached out and said, hey, would you be interested in writing a book? We had all this wonderful material to kind of illustrate and narrate the way that all these transformational companies are, are, are really changing their industries.

• 6:07Harry Stebbings?

  I do love that narrative because there's a lot of case studies in there, you know, be it from Venetian, uh, transfer of business models in the 15th, 16th century, selling like silk, uh, second hand.

• 6:18Speaker 02

  Yeah.

• 6:19Harry Stebbings?

  Brilliant. Uh, so, so, you know, absolutely love that narrative. But I do want to deep dive on some elements today then. Uh, and so starting with a simple one, we said about data driven teams there. Uh, and ones really know the power. Power of data. So what are the best in class doing to operationalize their data today? What have you found that they're all doing in terms of commonalities?

• 6:41Speaker 02

  There are three things they do. The first is they have a data team and there's this data and that this exists at Facebook, it exists at Zendesk and these data teams, they're structured a little bit differently, but they all basically do the same thing. They're the experts. They know where the data is stored. They understand how to perform analysis, but their main function is really education. They go around educating people with like office hours and tech talks and that kind of thing. The second thing is a product of the data team. It's this data dictionary and it was the head data scientist at Warby Parker that came up with this idea and he found when he was doing a bunch of analysis internally, two different teams internally, they had the same metric, but they had defined it differently. In talking to a bunch of different people, we found that this is a really common problem. Like in the software world, a marketing

• 7:25Speaker 02

  qualified lead and a sales qualified lead, well, the sales team might define each of those differently than the marketing team. And so you have a communication breakdown. So the second common characteristic is there's a single person or team that creates this data dictionary that defines all the key metrics for the business once and for all. And then the third thing is what we call in the book a data pipeline, which is a way of getting the data from the deep recesses of the business out to the front lines. And what we found is a lot of the data pipelines in businesses today are creaking under the load. There's this notion Lloyd Tab, who's the founder of Looker, came up with this notion of the data breadline. It's an invisible breadline, but there are all these people inside of a company who really would like some data in order to help them with their

• 8:06Speaker 02

  questions, but they can't. And a funny story, I was talking to, I was telling this to my wife when we were writing the book. It was over the Christmas holiday and I was asking her, because she's, we met at Google and she works at Google still. And I was asking her, you know, how do you get access to data when you need it? And you know, Google's like 50, 60,000 employees. And she said, well, I work with a data analyst on my team, but oftentimes we need to get access to the data and that takes, it can take days or weeks or sometimes longer. And so what you have to do is you have to go and curry favor with people on that team. And so you can trade things back and forth. And that's a really great example of somebody who's on an invisible Data breadline, right? Like she needs to answer a question and she's got to figure out exactly how to get it. And so if you have the right data supply chain, then you can solve that problem.

• 8:51Speaker 02

  So those are the three characteristics, a data team, data dictionary, data supply chain.

• 8:55Harry Stebbings?

  I guess in terms of data supply chain, then it all comes down to kind of management and the ethos that they instill at the company. So, so I mean, before we jump into the next question, how do you instill a sense of transparency around data within the firm without causing internal problems, do you think?

• 9:12Harry Stebbings?

  Is that a very, very hard question?

• 9:13Speaker 02

  It's a really hard question. I think the companies that are really data driven, they have cultures, they have a questioning culture. There's this famous quote that said, it basically said, if we have data, let's go with the data, but if we have opinions, let's go with mine.

• 9:26Harry Stebbings?

  Absolutely. So, okay, well then let, let, let me rephrase that then, kind of on, on the management theme. With regards to kind of setting the right culture, you, you say, stating the book that it all starts with curiosity and changing the culture. So how does one change a company's culture to become more data driven?

• 9:43Speaker 02

  I think the first thing is the leadership decides to start asking questions and they ask open ended questions. So they ask things like, how can we improve sales? How can we increase our price point? How can we differentiate relative to this competitor? How can we hire better? How can we retain people? Questions have this unbelievably empowering aspect to them, which is if you ask one of your lieutenants an open ended question, they feel a sense of responsibility and they're going to rise to the occasion. And the best way to answer those questions, a lot of times people answer it with opinions, but the best way to answer it is finding data and building a case and making an argument. And so that's going to create the need and the volition inside the company to use data to answer questions. I think that's how it starts. What ends up happening then is that the senior leadership of the company infuses the whole company bottoms up with data.

• 10:28Speaker 02

  Sometimes it happens that there's a couple of individuals at the, who come in and say, hey, this is, you know, we need to use data in order to solve this problem. But it has to come both from the top and from the bottom in order to be successful.

• 10:37Harry Stebbings?

  And you said about in the book that you should stop listening to your boss.

• 10:43Harry Stebbings?

  So, so, so why do you say that then? Obviously the importance of data, but is it not still important to have a very much authoritative figure who instills the data upon you as a team?

• 10:53Speaker 02

  It is, yeah. But the important thing about not listening to your boss is really coming to your own conclusions, using data to support your conclusions and then having a point of view. That's the catchy headline and that's the, that's the takeaway.

• 11:03Harry Stebbings?

  It's a great catchy headline. And on the hiring front then with regards to kind of data-driven professionals, Adam Grant states that eight percent of job interviews are productive. Love Adam Grant, by the way. So talk to me. What structure can we use to ensure higher efficiency with regards to the archaic process of hiring these data-driven people? How can we source them?

• 11:25Speaker 02

  Yeah, so I was stunned to hear this. I remember going for a walk in San Francisco and this product manager at a SaaS company told me that only that unstructured interviews, which is when we interview people by asking just kind of the typical questions, can only predict success in about eight percent of the cases, which is far worse than a coin flip. And so what Adam Grant, who's a professor in this field, recommends is the first thing you do is you perform a structured interview. Everybody asks the same set of questions and those questions are based upon the characteristics that are going to define success in this role. So the right way to recruit somebody is first you define the role, you define what success looks like, and then you create a set of structured questions that the four or five people are going to be interviewing this person all ask and all rank on the same scale.

• 12:07Speaker 02

  And then Professor Grant also recommends doing actually basically a standardized test, like an IQ test. If you do those two things, then you go from about eight percent predictive capability to more than, I think it's fifty-four percent, which is a huge increase. Also in the book, there's this company in New York called Greenhouse, which is a really fast-growing applicant tracking system.

• 12:25Harry Stebbings?

  Daniel.

• 12:26Speaker 02

  Yes, yeah.

• 12:27Harry Stebbings?

  I interviewed Daniel.

• 12:29Speaker 02

  Oh, you did? Okay, yeah.

• 12:30Harry Stebbings?

  There are a few people, Tom, that I haven't interviewed.

• 12:32Speaker 02

  I believe it. And his head of VP and strategy is a friend of mine from college. Her name's Maya. She's a skydiver, amazing background, world traveler. She has these like five key metrics that all recruiting teams should use. We had her at office hours at the Red Point San Francisco office. And the most interesting one, or the most surprising one for me was basically the recruiting sales cycle. How many days from first contact to offer letter? Basically, she said, if you can minimize that, and there's this sub thirty days at Greenhouse, then you have a far more effective recruiting cycle. And so if you can take a really structured interviewing process plus a metrics-driven recruiting platform, then she said, you know, and I believe it, they're incredibly successful with recruiting.

• 13:10Harry Stebbings?

  So I have to be honest, there's one slight element of the data-driven approach, which always Not concerns me, but just always comes into my mind and it's to what extent do we actually allow human emotion in to drive our decisions too, particularly with hiring. I find it interesting when we talk about kind of infusing the right culture in a company. Because necessarily the best data driven employee may not actually be the best cultural fit. So how do you find the balance between the counter that's best in terms of data and the counter that actually might be the best in terms of personality and culture?

• 13:44Speaker 02

  Yeah, so there was this guy in Germany who was struck by lightning and the part of his brain that created emotions was destroyed. And so there are all these psychiatry-

• 13:52Harry Stebbings?

  And he turned into Jason Lampkin.

• 13:54Speaker 02

  Yeah.

• 14:00Harry Stebbings?

  Jason, if you're listening, you know how much we love you. I'm just kidding.

• 14:03Speaker 02

  So all these psychologists really wanted to study him because they thought he was going to be an unbelievable decision maker because here was basically a human computer, right? There was no fuzzy element to his decision making. The inverse turned out to be true. He actually couldn't make a single decision. And what they realized is that we never have perfect information and the way that we get from not making a decision to making a decision is we use our emotions. So emotions are a really important part of the decision making process. That's kind of the moral of the story. And I remember at Google, when we were interviewing product managers, we would take these packets and we would have all these different, we were doing structured interviews at the time. It was on a 4.0 scale. You need to score above a 3.5 and if you had a 3.9, it was really terrific. But during these calibration sessions, people would argue. And I think that's when the, you know, you're not hiring exclusively based upon the metrics

• 14:47Speaker 02

  that are coming out of the interviews. There needs to be an advocate inside of the hiring committee and people need to argue back and forth. And I think that's where the emotional component definitely comes in.

• 14:56Harry Stebbings?

  And hopefully with this process that we just discussed, we've hired some truly talented individuals with great data evaluation skills. So I want to dive into the data analysis process then, once we have them. So what are the complexities and skills required then for strong data analysis in today's environment, would you say?

• 15:15Speaker 02

  Yeah, so numbers can be really confusing. There was this woman who wrote about the Monty Hall game. Well, the Monty Hall game is a game where you pretend you're on a game show and the host is called Monty Hall and there are three doors in front of you and behind two of the doors, there's a goat and behind the third door, there's a prize. And so the game show contestant, Monty, asks you, Harry, to pick a door. And let's say you pick door number two. And so Monty goes and he opens up door number three and he reveals to you that there's a goat. And so now you know that between door number one and door number two, there's a prize and there's a goat. And he asks you whether or not you want to change your number. Should you or should you not? And so there is this journalist who posed this question in a magazine article and she posted the answer and the answer

• 15:56Speaker 02

  is you should change, which is completely counterintuitive. And so she received 10,000 letters berating her and telling her that she was wrong, including several hundred from PhDs in statistics from some of the finest universities in the world. And it turns out, you know, she went back and forth, back and forth that it's actually right. And so it tells you that, you know, having that discipline is really, really important and even some experts can be wrong. Getting to the point of the question, you know, the most important one, and I think that the skill that most often comes up in data analysis is correlation versus causation, right? Like, there's this great website that shows spurious correlations and causations, like the number of Nick Cage movies released in years highly correlated with swimming pool accidents.

• 16:39Harry Stebbings?

  Well, I think they're highly correlated, actually. I think a Nick Cage movie would make me want to jump in the pool. But let's say they are uncorrelated. Okay, absolutely. Yeah.

• 16:49Speaker 02

  Yeah. And then the second one is this notion of anchoring bias. And anchoring bias is, you know, if I ask you, Harry, a question like, how much are you willing to pay for this map listed at $20? Telling you that number and having, putting a number in your mind ahead of time, you're already thinking around that number and that kind of biases you. And it can either bias you higher or it could bias you low.

• 17:10Harry Stebbings?

  Talk to me about the availability bias. I was really intrigued when I read about that one in the book.

• 17:14Speaker 02

  Yeah, the viability bias is basically, this is founded by Daniel Kahneman. It's basically if you can, if it's something that's easily remembered, then you perceive it to be more likely. So, there's a reason that when somebody wins a Powerball lottery, which is, tends to be the biggest lotteries in the US, or like El Gordo in Spain, that there's as many camera crews as possible, there's a person who's got a ludicrously large cheque, who comes to the front door and hands it, and then this person is celebrated all over the place. And that's because, that gets everybody who's playing the lottery to remember that moment and imagine themselves as receiving that cheque. And because they, because it's so easily remembered, people perceive it to be far more likely than it actually is.

• 17:59Harry Stebbings?

  And then there's the final one, which is illusion of validity, I seem to remember. So, talk me through that one, and then we'll dive into the quickfire.

• 18:06Speaker 02

  Yeah, yeah, so the illusion of validity is, okay, so Daniel Kahneman, Harvard academic, he goes to West Point, and he looks at all the different cadets, and he and his colleague, they go in with the goal of identifying who will be the leaders of the brigade, three or four years from now, by looking at the cadets during the first couple of weeks. They take 12 cadets, and they give them an enormous log, and they put a six-foot wall on a grass field, they tell the cadets, "Your goal is to lift this log and get it up and over the wall, without it touching the ground, or without it touching the wall. And in either case, if it touches the ground or the wall, you have to bring it back." And so they watch how this group of cadet self-organizers, there's two or three people who negotiate a strategy, then they kind of tell the other people what to do, and so they get it over.

• 18:48Speaker 02

  And so the whole time Kahneman and his assistant are taking notes, and they basically stack, rank all these different cadets to kind of predict who is going to be a leader. It turns out they're dead wrong. All of them. They couldn't predict at all. And so, the illusion of validity in this case is that Kahneman and his assistant thought they could predict, when in fact, they couldn't, right? They had no idea.

• 19:09Harry Stebbings?

  Is there a way to prevent this kind of false sense of knowledge that's probably inherent within most C-suite level execs, in terms of now they've got the data, they've got the knowledge? How do you prevent that kind of illusion bias?

• 19:23Speaker 02

  Yeah, I think that what you do is you do what Google does or did when I was there, which is you create a hypothesis and you say, let's run a small scale experiment just to make sure that it's true. Because basically what you want to do is you want to test your assumptions. And most of the time, your assumptions are probably right. Like, you know, like, if you look at it, um, most of the time, your assumptions are probably right, but you definitely want to certify them. And that's the way you get rid of that illusion of validity.

• 19:47Harry Stebbings?

  And I'd love to dive into a quick fire round now.

• 19:49Speaker 02

  Yeah, sounds great.

• 19:50Harry Stebbings?

  You've done it before, so you're aware. Sixty seconds per one max, and I'm much stricter now. So let's start with the biggest challenge in writing the book.

• 20:00Speaker 02

  Yeah, it's much different than writing a blog post. The way I thought about it was, it's a 50,000 word book, so it was about, it is about 100 blog posts, yeah. The biggest challenge was trying to figure out, how do you go deep enough into a topic to be interesting to the reader, but not so deep that you're bored? And you don't have instant feedback, like a blog, and you can't correct it, so you just don't know.

• 20:18Harry Stebbings?

  How long did it take to write and what tools did you use?

• 20:21Speaker 02

  I had 90 days to write it.

• 20:23Harry Stebbings?

  You said this?

• 20:24Speaker 02

  Yeah.

• 20:25Harry Stebbings?

  Did you do any work as well?

• 20:26Speaker 02

  Yeah, I wrote it from, uh, we wrote it from November 1st to February 1st.

• 20:30Harry Stebbings?

  That is unbelievable.

• 20:31Speaker 02

  Nights and weekends, yeah, my lovely wife watched our boys.

• 20:34Harry Stebbings?

  I'm sure she did. Um, so, okay, so it took three months, and what tools did you use?

• 20:39Speaker 02

  You know, there's this great software called Scrivener.

• 20:41Harry Stebbings?

  Okay, I use Hemingway, because I can't spell or use punctuation in any way.

• 20:46Speaker 02

  Hemingway's great, too. The great, the great part about Scrivener is it breaks things down into individual blog posts, and then it kind of, kind of compiles them up. And so you're like, you can reorganize a table of contents changes, you can do indexing.

• 20:58Harry Stebbings?

  And then what was your biggest kind of learning from writing the book? Obviously, you had to do a massive research, anyone that reads it will see. So what was your biggest takeaway from writing the book?

• 21:08Speaker 02

  Uh, my biggest takeaway is, nobody knows how to do all this stuff right. And it's always changing. Like, that's the thing that kind of stunned me. Like, I was reading, there's one story about, uh, in the Second World War, the Americans were losing all these planes because the Germans were shooting them down. And these planes were coming back and only armored them on a certain pieces of the plane. And so the colonels, uh, of the air force said, well, why don't we just armor it where all the bullet holes are? And then you had this guy named Wald, who Came in and said, no, that's the whole point. The planes that come back have holes in the places where the planes can survive with those holes. And the planes that don't come back are the ones that have bullet holes in all the other places. So, you know, the planes that were coming back had holes in the fuselage. And so you don't need to armor the fuselage, you need to armor the wings or whatever it was. And that was in the 50s, right?

• 21:51Speaker 02

  And so statistics is really only like 50 or 60 years old. And even this world of like business intelligence and data analysis is, you know, only that old. And nobody really knows how to do it inside of companies. So that was the most exciting part for me.

• 22:02Harry Stebbings?

  Who's doing data driven the best today? Which company are you most impressed with how they operationalize and use data?

• 22:10Speaker 02

  Yeah, I think company that I work with that that meets that is a company called Threadup, which is the world's largest secondhand clothing store. And they process 20 to 30,000 items of clothing per day that go into four distribution centers. And the people who built it, uh, the people who built the DVD facilities at Netflix are building the same things at Threadup. I first got introduced to Looker because during one of the board meetings, James, who's the CEO at Threadup, one of the board members asked him a question and he pulled up Looker and he answered the question on the spot in 45 seconds. And literally everything at Threadup is, uh, is measured. A piece of clothing coming off a FedEx truck to being categorized, itemized, photographed through the facility, then back out and being shipped, everything, everything is data driven. And the incredible part there is the impact on the financials of the business,

• 22:55Speaker 02

  particularly the margin structure is, I can't disclose it, but it is impossible to overstate.

• 23:00Harry Stebbings?

  It makes absolute sense, I can see. And then who would you like to see innovate with data? Who's not, you know, your traditional corporates of America? Who do you think has the most potential to innovate with data?

• 23:11Speaker 02

  You know, we've been looking a lot at software companies in the human resources world. And it used to be that the two people inside of a board meeting that that didn't have data at the board meetings were the head of marketing and the head of people. And now the head of marketing and the marketing team's been fully instrumented. And so the last, the next great opportunity is helping the head of people with data.

• 23:31Harry Stebbings?

  And then talking of kind of opportunities that have arisen, most recent investment for you and why you said yes?

• 23:36Speaker 02

  Yeah, the last public investment is a company called Dremio. It's a data middleware company founded by the chief architect and the head of product from MapR, which is in the Hadoop world. They basically allow you to move data in really beautiful and seamless ways and they allow people inside of companies to find the data they need access to. I'm really excited about them because they solve this data discovery problem, not the analysis and exploration part, which companies like Looker and Tableau and others are solving, but it's the next step. It's, hey, within this company, we have 10,000 different data sets and I'm looking for this particular one. I'm looking to understand which customers came from which marketing campaign, how do I connect the two? And so they're solving that problem.

• 24:16Harry Stebbings?

  Well, Tom, I can't tell you how much of a pleasure it's been. As I said, I loved, loved, loved the book. I'm going to say this on the show, actually, because I said I wouldn't say it, but I haven't read a book, as I said, in about two years, genuinely from start to finish, and yours was the first. So thank you, A, for breaking that one.

• 24:33Speaker 02

  I'm honoured. Thank you so much. Harry, thanks so much. Yeah, it's been great fun.

• 24:39Harry Stebbings?

  What a top man. And I have to say, that episode was just fantastic fun to record and a huge thank you to Tom for giving up his time today to appear on the show. And if you love the episode, then head over to the 20min VC dot com, where you can find the links to purchase the book. It really is a must read, as I said, one of the first books in two years, but let's keep that between us. And also, if you'd like to stay in the world of the 20 minute VC, then you can add me on Snapchat at H Stebbings or add Tom on Twitter at T Tunguz. And do not forget what I said earlier, funds would be nothing without operational support behind them. And in this case, there's no one better than Cooley, the global law firm built around startups and venture capital funds.

• 25:20Harry Stebbings?

  Since forming the first VC fund in Silicon Valley in the late 50s, Cooley's formed more venture capital funds than any other law firm in the world with more than 50 years working with VCs. They also help VCs form and manage their funds, make investments and handle the myriad of issues that arise through a fund's life cycle. So to learn more about the number one most active law firm. Representing VC-backed companies going public. Head over to cooley.com or you can also check them out at cooleygo.com. But whether you're a VC or a lawyer or even a podcaster, getting that shut eye is so important. And that's where Eve can help. Eve is the UK's number one direct-to-consumer mattress company. Because they don't sell through high-street stores, they cut out 70% of traditional costs and pass those on to you, the customer.

• 26:05Harry Stebbings?

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