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0:00:15 at any investors or potential investors in any A16Z fund. For more details, please see
0:00:21 a16z.com/disclosures. Hi, and welcome to the A16Z podcast. I’m
0:00:27 Doss, and this episode is all about what the numbers, both financials and KPIs, do and
0:00:32 don’t tell you about your business. Our guests for this episode are A16Z General Partner and
0:00:37 Managing Partner Jeff Jordan, who previously ran several businesses and took a company
0:00:42 public right after the 2008 financial crisis. David George, who runs our late-stage venture
0:00:47 operation, and Caroline Moon, who leads our financial operations practice and helps companies
0:00:54 with their own best practices. She’s also a former CFO. In our conversation, we cover
0:00:58 the most common mistakes people make when it comes to understanding numbers. When investors
0:01:03 think when they look at a company’s profit and loss statement and why, how investors
0:01:07 use metrics to determine if a business is healthy, and how some founders may use them
0:01:13 to navigate times of crisis. We begin, though, with the basics of the three core financial
0:01:18 statements, the income or PNL statement, the balance sheet, and the cash flow statement.
0:01:24 The first voice you’ll hear after Caroline’s and mine is Jeff’s, followed by David’s.
0:01:28 Especially in the early days of a startup, they’re just going to do cash accounting,
0:01:30 and that’s just literally how much cash you had in the beginning of the period and how
0:01:35 much you had cash at the end of the month. That’s not the same thing as what a PNL really
0:01:41 should show, because your PNL paints the picture of how your business did in a particular period
0:01:46 of time and measurement, whether that’s quarterly or yearly, or the cash statement then reconciles
0:01:49 that with what did you actually collect. Everything that happens on that cash flow
0:01:52 statement then ends up on your balance sheet.
0:01:57 The reason why it’s important to be able to present it in that fashion, it’s called generally
0:02:03 accepted accounting principles, so GAP accounting, is because that’s how everyone understands
0:02:08 that the comparisons are apples to apples when you look across companies.
0:02:12 When you are trying to figure out how a business is doing, what are the financials that you
0:02:13 look at?
0:02:20 Typically, the early investing, you don’t emphasize financial metrics that much, because
0:02:24 usually, there isn’t a mature go-to-market organization. I tend to focus much more on
0:02:31 KPI-type metrics, users, daily to monthly users, engagement, and things on those lines,
0:02:34 and then the financials tend to emerge over time.
0:02:40 Yeah, I would say I care most about two very high-level topics at the later stage. The
0:02:47 first is, can you demonstrate that you can have very persistent growth? Secondly, how
0:02:53 profitable will you be when you reach scale? I spend less time for later-stage high-growth
0:02:58 companies staring at their balance sheet than I do KPIs, income statements, and cash flow.
0:03:02 The main thing I look for in the balance sheet is the comparison for how much traction they
0:03:06 have on the income statement and the cash flow documents relative to the amount that’s
0:03:10 been invested in the company. For me, the most important balance sheet metric early
0:03:15 is how much capital is the company deployed to get to where they’re going.
0:03:19 How do you guys know when a business is truly profitable?
0:03:24 I do think you go to the unit economics and really understand them, but this is often
0:03:29 a lot of art as well as a good amount of science. Some of the most frustrating interactions
0:03:34 I’ve had with companies are where they’re presenting that their unit economics work,
0:03:38 but the business isn’t working. And so I had one where, okay, we’re capital efficient,
0:03:43 the unit economics are working, we acquire users, they’re profitable in three months,
0:03:48 and the company was hemorrhaging cash. It turns out the unit economics actually weren’t working.
0:03:53 The cash flow statement was the arbiter of truth and the analysis that the company had
0:03:57 done on unit economics was wrong. Yeah, I agree. I think lifetime value is one
0:04:01 of those traps that people fall into. They’re assuming, oh, our customers are going to stay
0:04:05 with us for five years, three years, so we’ve got plenty of time to do the payback,
0:04:09 but that’s a key driver to whether or not your unit economics work.
0:04:14 There’s nothing that’s less consistent in the market than how lifetime value to
0:04:20 cost of acquisition of the customer. LTV to CAC is defined. What I always counsel companies and I
0:04:26 like to see is very transparent calculations of what goes into the LTV side and the CAC side.
0:04:33 So the LTV to CAC metric that I like to look at is for the LTV, so the lifetime value side,
0:04:38 I always use gross profit, not revenue. And then I like to use a shorter duration than
0:04:43 founders typically like to use. So I like to use three years. Often founders present five years,
0:04:47 and the point I make on that is that five years is too uncertain and long of a period of time,
0:04:52 whereas three years is much more visible, and then use actual retention statistics that you’ve
0:04:57 experienced in the past to project those three years. The thing that I really try to emphasize
0:05:03 to founders when they talk about these kinds of metrics is, look, this is not about necessarily
0:05:07 showing investors. This is how you have to run your business. What am I spending on sales and
0:05:12 marketing? What am I spending on my R&D? And how much am I spending on G&A? And is that
0:05:17 the right level of investment that I should be making in my company? So you need to be as honest
0:05:21 with yourself as possible as to what all these things cost you and what you’re really generating
0:05:25 in terms of revenue, because if you can’t be honest with yourself, you can’t run your business.
0:05:30 What are some of the other really common mistakes or things that founders do in presenting numbers
0:05:34 that you’d want to help them correct or you’d like to see them do differently?
0:05:39 You know, one tell for me where business is probably struggling is when they come up with
0:05:46 North Star metrics, you know, KPIs, and then when they come back to report on them a quarter later,
0:05:50 they’ve changed. And then they come back a quarter later and they’ve changed again. And what I found
0:05:55 a little bit of pattern recognition is when the KPIs change all the time, it’s largely because
0:06:01 they’re not working. And the company’s trying to navigate through it. For me, you pick your metric,
0:06:07 you report on it. And ideally, your understanding of the business improves over time as your metric
0:06:12 and your models are either validated or unvalidated. That leads this interesting question, I think,
0:06:18 of the psychology and how you look at your numbers. So how do you manage your own psychology
0:06:21 so that the numbers are a tool, not this obsession where it’s like,
0:06:26 my obsession is I want to reach my KPIs. So I’m going to keep adjusting my KPIs. So I do.
0:06:30 You know, the reason they’ve so defined the three financial statements is it’s kind of truth-seeking
0:06:36 and trying to fool your investors or lack of better word or your board. You know,
0:06:42 I don’t want to let them know how bad things are. By not telling the truth to your key constituents,
0:06:47 you often run the risk of not telling the truth to yourself. And so I’ve had a couple founders
0:06:53 where sometimes they fall prey to it themselves, where they believe their own machination,
0:06:57 and then the board and investors can’t help them based on the truth.
0:07:03 What do the best founders do, especially in challenging moments, like when the finances
0:07:07 and the numbers maybe aren’t going your way, or you know that you do have to tell a difficult truth?
0:07:13 They typically acknowledge it. They take it as, okay, the truth isn’t what I wanted it to be.
0:07:17 So now, what can I do to change the business to improve the truth?
0:07:21 The only thing I would add to that that I’ve observed from some of the best founders of
0:07:28 later stage companies is they’re very careful not to drown themselves in KPIs. So you can actually
0:07:34 inundate yourself with KPIs, but the very best ones pick out a very few handful of metrics that
0:07:39 they think are the most important drivers of their business. And if they see those divert from where
0:07:44 they would like them to be, they dig in from there. So for example, Ali from Databricks always
0:07:50 focuses on the productivity of a sales rep because he believes that indicates health
0:07:55 of the business in many different ways. So how well is the sales organization actually functioning?
0:07:58 What are the market dynamics? What’s competition? How is the product performing?
0:08:03 And you do get a real force for the trees. I have companies that will present you 50 pages
0:08:09 of metrics based on the last quarter and you just drown versus what in here is really important?
0:08:13 What are the key ones? Are the one or two that matter the same for every company or does it
0:08:18 depend on the nature of the company and the stage that they’re at? I think to some degree,
0:08:22 some of them are the same. For instance, retention should matter to any business model.
0:08:26 You spent money to acquire your customer base. How long are you hanging on to them?
0:08:31 Yeah, I find they are consistent by type of business. So marketplace metrics typically
0:08:36 have a lot in common with each other, but they’re very, very different than e-commerce metrics.
0:08:40 The key e-commerce metrics typically center around the efficiency of customer acquisition
0:08:46 and LTB to CAC. A lot of marketplaces I work with don’t spend a penny on customer acquisition.
0:08:52 And so it’s got organic distribution or something like that. So comparing across models can be
0:08:58 challenging. Comparing within models can be very helpful. So for B2B companies, for example,
0:09:03 the efficiency with which you spend a sales dollar, whether it’s on a rep or marketing
0:09:07 or bottoms-up sales, inside sales, outside sales, is always one of the most important things that
0:09:12 you look to. Things change. Markets are unpredictable, which is something I think we’re seeing now
0:09:18 more than ever. How do you use finances to make better, faster decisions, especially in uncertain
0:09:24 times? You know, I started my career in finance. I ended up as CFO at the Disney Store. So it’s
0:09:28 near and dear to my heart. The typical finance function is conceived of as kind of keeping score,
0:09:34 the accounting control function, just reporting back. For me, that was necessary but not sufficient.
0:09:39 The finance function has access to all of the key data. And so I look at them not only to keep
0:09:45 score, but to score points to make the business better by leveraging their access to the information
0:09:49 and to the trends and to the unit economics to improve the business.
0:09:57 A good finance leader needs to work with the CEO to make sure that the company has
0:10:04 enough money to not just survive but thrive. So that is becoming super intimately familiar
0:10:08 with the business, not the financial statements, not the accounting that goes into developing
0:10:11 these things, because those just represent what’s happening at the business level.
0:10:17 They really need to understand how everything works and then where are the levers that you can
0:10:22 change, that you can pull on, that you can push on to accomplish the things that you want to do
0:10:27 as a business in the timeframe that you need it all backs up with the cash that you have on hand.
0:10:32 When I was managing businesses, I always had a mental model of how the business should work.
0:10:37 And that mental model typically, ideally, was consistent with the financial model.
0:10:43 eBay, back when I managed it, was a perfect economy. And eBay as a platform attracted every
0:10:48 leading finance professional who was into micro because it was one of the most pure examples
0:10:54 of a perfect economy. If there was an increase in supply, prices fell. If you change the fee
0:11:00 structure, behavior changed. And so it’s when businesses diverge from my mental model that
0:11:05 you really needed to pay attention. It’s like, why is the conversion rate going down? My god,
0:11:10 I’ve never seen it go down like that. That’s a big warning indicator for me. So I would
0:11:15 typically be pretty comfortable running the business until anomalies emerge. And then I just
0:11:19 would need to understand the driver of the anomaly. And I can’t emphasize enough how important it is
0:11:24 for companies to understand their bottoms up for how revenue is generated. I see a lot of people do
0:11:30 tops down forecasting. So the last quarter, we had whatever, a million dollars in revenue, 10
0:11:35 million dollars revenue. And then you go, okay, and historically, we’ve grown 50% or 100%. And so
0:11:41 we’re going to model something similar to that for the next year. And so that’s our number.
0:11:45 And that’s got no intelligence built into it whatsoever. What you have to do is double click
0:11:50 on that and go, okay, so we made whatever $10 million last year, how was it made? What was the
0:11:55 makeup of that customer base? Who’s likely to still be here? Who’s going to spend more? Who’s
0:12:00 not going to spend more? Who’s going to completely leave the platform? In marketplaces, you often
0:12:05 get two shots at bottoms up because you typically can build a model based on the supply,
0:12:09 or you can build a model based on the demand. Get an example at eBay. We would look at the
0:12:15 behavior of sellers and we had this many sellers growing this fast, doing this kind of behavior,
0:12:20 and then you just kind of roll them together and come up with a revenue estimate. Then we’d sanity
0:12:26 check it with, we have this many buyers buying this frequently, spending this much and coming onto the
0:12:31 platform at this rate. And then you’d run up that number. And ideally, the two would inform each
0:12:37 other. So one of the best CEOs who I worked with, who I partnered with was George Kurtz from Crowdstrike.
0:12:42 He had an exceptional business. One of the things when we were working together that we came to
0:12:48 realize was his gross margins were a little lower than most other software companies that we were
0:12:54 working with. He actually made the decision in one quarter based on that to try and experiment
0:13:00 where he made gross margin actually be part of the calculus for sales compensation for the reps
0:13:06 in that quarter. And his gross margins over the last three years have actually gone from 35% to 70%.
0:13:12 So a very operational tactical decision that can have a massive impact on the value of the business.
0:13:17 So I wanted to go back to a point, I think, Jeff, that you brought up of having this mental model
0:13:22 of your business and hoping that that matches the financials and how then you have those red flag
0:13:27 moments. And I think a lot of companies right now are having a red flag moment because of a
0:13:32 lot of circumstances very beyond their control. I’d love to hear, what are you telling founders
0:13:37 right now when it comes to how to think about their financials? This is one of the most significant
0:13:41 disruptions I’ve experienced. I’ve had a long enough career that I’ve experienced a bunch of them,
0:13:47 the bubble bursting in 99, 2000, the financial crisis of 2008, 2009, which by the way, we took
0:13:54 OpenTable public in May 2009. So the future isn’t dictated. But a couple of things come to mind.
0:13:59 One is cash is king. The income statement, throw it away. Just look at the cash flow statement.
0:14:03 How much cash do you have? How’s the burn? How are you adding or using cash over time? So
0:14:08 cash becomes completely king. Throw out your forecast because the forecast is now meaningless.
0:14:13 It was based on a bunch of assumptions that no longer hold. So throw the financial print out
0:14:17 and start looking really hard at things like year over year, which typically doesn’t lie.
0:14:23 And then just do tons of sensitivities. And you got to do it decisively. I always like this thought
0:14:31 exercise of how bad could this possibly get? Just let’s take the absolute worst. How bad could it
0:14:37 get? Because I think people tend to do the opposite. They iterate down of like, okay, I’m going to,
0:14:42 we’re down 5%. I’m going to plan down 10%. But if it’s going down 5% per day,
0:14:47 plenty down 10% just met your plans out late in two days. And so I found it helpful both from a
0:14:52 business, prudent cash management perspective, also from a mental perspective. Don’t let this
0:14:57 just continue to erode. And I get more and more depressed every day. Get really depressed one
0:15:02 day, look at reality and then try to change it. Yeah, I agree. So I was a CFO at a company
0:15:07 called Adbride in 2008. And I think that at first we didn’t want to believe that it could get that
0:15:12 bad. But we were an advertising network. And so unless you were Google and even they were impacted
0:15:16 by this, your customers weren’t going to advertise anymore. The marketing departments were decimated.
0:15:21 So there were situations where we were like, some of this is just going to become zero.
0:15:26 Contracts that were signed are now just getting outright canceled. So we made the decision to
0:15:31 cut really deep and as quickly as possible. Because we knew that even if we got it wrong,
0:15:37 at least we could then rebuild the company and do it only once. And then your employees then
0:15:41 are told, hey, we’ve made this big decision. Here’s what we based it on. Here’s our cash
0:15:45 position. Here’s what we’ve sort of expecting in terms of worst case scenario. You bring them
0:15:50 into that circle of trust of what’s happening at the company. But there’s asymmetric potential
0:15:57 issues. If you underestimate how bad it’s going to get and don’t deal with the situation quickly,
0:16:01 the outcome is very well be you lose your company. Yeah, death by a thousand cuts.
0:16:05 Yeah. And if you overreact and it doesn’t end up being as bad as it would have been,
0:16:11 you might have suboptimized your company for some period of time, but it’s alive.
0:16:16 So for me, the mistake is to underestimate the potential versus overestimating.
0:16:20 Yeah, I want to go back to something Jeff said, which was this notion of throwing your forecast
0:16:26 out the window. Very much agree with that on the top line on your revenue. But you have this whole
0:16:30 base of costs that are under your control, those are your operating expenses. And so
0:16:36 we’ve spent a lot of time focused with our companies running sensitivities of, hey, this is
0:16:41 your operating expense budget. And what’s an operating expenses are your salespeople, your
0:16:47 marketing people, your CFO function, your HR function, your engineer’s product. Those are all
0:16:54 people and costs that you have as a base. What happens to that cost base in order to preserve
0:17:00 cash under various scenarios of revenue decline? And so I think that’s the way that you have to
0:17:05 be managing your business on a very, very granular level. And especially since companies,
0:17:10 especially startups, they staff in advance of growth. And so you have to really be honest with
0:17:16 yourself. I want to just also chime in and just say, look, these are all very, very hard decisions.
0:17:22 And I think Caroline and Jeff, especially because you’ve been in the seat of operators
0:17:27 during really, really trying times, you’re probably pretty diagnostic about it. But suffice
0:17:32 to say it’s hard decisions, you know, people’s jobs, decisions not to be taken lightly.
0:17:37 And that’s why there are cases where it is a death by a thousand cuts because people are reluctant
0:17:43 to do those layoffs, make those cuts. And believe me, you don’t sleep when you have to make these
0:17:48 decisions. It’s so tough. So I don’t take that lightly at all. But when you’re running a company,
0:17:53 number one is making sure the company can make it through to the other side. And so you have to
0:17:58 make these really tough decisions. And believe me, I understand how difficult that can be.
0:18:00 But you can’t kick the can down the road on some of these things.
0:18:06 Everyone in the organization knows that the proverbial shit is at the fan. And so if the
0:18:13 leader is unwilling to acknowledge that with the team, that for me creates a crisis of confidence.
0:18:20 I always found it way better just to call it what it is, share it, try to enlist the team. And
0:18:24 do you agree with this version of reality and try to get agreement? And then it’s like, okay,
0:18:29 what do we do? But denial and trying to hide it from your team is a failing strategy completely.
0:18:34 And I understand the human psychology around that because I think people don’t like to give
0:18:39 bad news. And so I think the natural impulse is to hide those things. But these are the moments
0:18:44 where you have to actually be the most transparent. Talk about why you’re doing what you’re doing,
0:18:48 how much cash you’ve got left, how much you want to preserve. And what I find is when you do that,
0:18:52 when you bring everybody into the fold, they all become part of the solution. So they understand
0:18:58 that cash is king, and they’ll figure out ways to be even scrappier than they might have been
0:19:03 otherwise. Jeff, you’ve lived through some crises already. Go back to a time when you were facing
0:19:07 a crisis where things were rapidly changing. You were having to make some of these difficult
0:19:13 decisions. What was a day in a life like then? And what were you doing, especially with regards to
0:19:20 the financials? I got a good one for you. So OpenTable in mid-2008, the board decided it’s
0:19:25 time. Let’s go public. The market wasn’t good. But for a variety of internal reasons for the
0:19:29 company, we decided, okay, we have to, quote unquote, get the puck on the ice. And so we got
0:19:36 ready for the IPO. And we did our bake-off in, I think it was August 2008 and did it like on a
0:19:42 Thursday. And Friday, we informed the six banks whether they got on the offer or not.
0:19:46 We told Lehman on Friday they didn’t get the offer. They went out of business on Saturday.
0:19:51 We told Merrill Lynch, they did get the assignment to take OpenTable public,
0:19:57 and they traded to Bank of America on Sunday. So over that weekend, the number of people dining
0:20:03 in fine dining restaurants in America went down by 15% in one weekend. So we had the org meeting
0:20:07 Monday morning. I walk in, sit down, all the bankers there, all the lawyers there, and this is not
0:20:15 going well. Our business is in free fall. The bank just changed. The consumers terrified. And so
0:20:20 it was pretty clear we could not proceed with the IPO at that point because we couldn’t predict it.
0:20:25 But then we just said, okay, what can we predict? And so we put it on hold for three or four months.
0:20:30 And it turned out that the consumer kept dining in restaurants at 85% of what they had the prior
0:20:34 year. And all of a sudden, we got confident that the business was predictable at that point. And we
0:20:38 restarted the process and went out. And it ended up being a successful offering.
0:20:42 How were you looking at the financials during that time? How did those come into play as you went
0:20:47 through that? We were watching the year-over-year change in reservations of people dining and
0:20:52 reservations made daily, just like, okay, where’s this business going? Because if it kept falling,
0:20:57 one of the scenarios we were concerned by is more and more people would stop eating as they got more
0:21:03 and more nervous about the economy. And we’d go from revenue of X to revenue of like 0.3X. And the
0:21:08 business would have been hugely stressed at revenue of 0.3X. So we were watching that the
0:21:15 one key North Star metric of diners per night, year-over-year, maniacally. And that ended up
0:21:19 giving us the confidence to restart the offering. How does a startup or a founder right now approach
0:21:24 contingency planning around their finances, especially if you’re a high growth startup that’s
0:21:29 been going through cash quickly and been pretty aggressive with your risk taking until now?
0:21:36 For me, you don’t scenario plan constantly. But when a shock hits the system like this shock has
0:21:44 hit this system, hit the world, is you want to plan quickly, even if it’s bluntly. If I was running a
0:21:50 business in this environment, I would get the expected outcome. Maybe it won’t go there quickly,
0:21:55 outcomes are slightly better, but also just what is the worst case? Where could this go? And then
0:22:02 you build your response if each of those comes true. And for me, you put much more time into the
0:22:08 plan, what if, than you do in the building the sensitivity scenarios. One of the less productive
0:22:14 activities is making that sensitivity beautiful and accurate. And it takes two months to come out
0:22:19 with and the company’s out of business. Yeah, just take the bluntest assessment. David and his team
0:22:24 has done this for a few of our internal companies. Yeah, what we did is we basically took every
0:22:30 company’s financials and started with revenue and said, okay, let’s start with your budget.
0:22:36 And then let’s run sensitivity analyses for your revenue. Let’s assume you hit your budget,
0:22:42 that you’re flat, that you don’t grow, that you declined by 25% or that you declined by 50%.
0:22:48 And then we compared that with a company’s operating expense budget. And across all those
0:22:54 different scenarios, if you run your current budget of operating expenses, if you assume you
0:22:59 don’t grow your operating expenses, and then if you assume you decline your operating expenses by
0:23:05 25% or 50%, what is your cash runway in each of those scenarios? And we plug that in for each of
0:23:11 our companies and gave it to them. And I think it’s just a helpful way for them to put some parameters
0:23:17 around, hey, if things get really bad, this is what our runway is. And often it helps them just to
0:23:23 start thinking about, okay, how do I contingency plan in the event of flat revenue? I had never
0:23:27 even thought about that before. If that happens, I only have this much runway. Maybe I should take
0:23:32 action. And another thing that I would say to you, a lot of times companies are building things as the
0:23:37 plane is in the air, and they solve their problems linearly by throwing bodies at it. This is an
0:23:42 opportunity to be able to potentially refactor your code base, to shore up infrastructure,
0:23:48 to build internal tools to make your teams more efficient, so that when you do come out on the
0:23:53 other side, that you are primed and ready to just hit the ground running and run in a million miles
0:23:57 an hour, because you have now built the foundation that you need to be able to really scale your
0:24:02 business, a company called AdBright. We were an ad network. This was before Amazon Web Services was
0:24:07 really a big thing. And so you had to have your own data centers, which means you had to buy
0:24:13 equipment. So we were a very capital intensive business. And what we realized was that we weren’t
0:24:17 going to be able to afford anymore to be constantly replacing our servers, because we just did not
0:24:24 have the money to do it. And our CTO had been playing around with this thing called AWS and
0:24:29 brought it to us and said, one, we can’t afford to upgrade our servers, even though we need to.
0:24:34 And two, this is going to probably in some ways improve our gross margins, because now
0:24:39 we can flex up and down when we need the capacity. So can we give it a try?
0:24:46 This was cloud-based. Anything was still pretty new. This was 2008, I think, AWS launch in 2006.
0:24:50 So we became a data customer of theirs. At the end of the day, when we came out of the crisis,
0:24:56 we were pretty much a cloud-based ad serving company. We deprecated all of our data centers
0:25:01 when we just moved everything to AWS. So what bottom line advice right now are you giving to
0:25:07 founders? One anecdote about the 2008 credit crisis, when housing prices dropped like 30
0:25:11 to 40%, if you were to interview people on the street who owned homes, you asked them, hey,
0:25:15 what do you think the US residential market has done in terms of real estate values?
0:25:20 They would across the board say, oh, it’s down 30 to 40%. And then they would be asked,
0:25:25 all right, what do you think happened to the value of your own home? And they say, oh, nothing,
0:25:28 nothing at all. It’s still fine. It’s not down at all. And it’s like, well, that’s not how averages
0:25:33 actually work. And so no one believes that it’s going to happen to them. But believe me, it is
0:25:39 happening to them. And that is the thing that I want founders to understand. You are not going to
0:25:43 be impacted asymmetrically compared to everybody else. You’re not going to be that outlier more
0:25:49 likely than not. So we’ve had a lot of advice in here on confront reality decisively, plan for
0:25:56 the worst case, scenario plan the worst case. And psychologically, that is pretty darn challenging
0:26:01 on the founder. I mean, I’ve lived it, I understand there. So that brings the point that it’s just
0:26:06 incredibly important for the founder to manage their own psychology. And I think probably the
0:26:10 best resource I’ve read on that is Ben’s book, The Hard Things About Hard Things. You flip from
0:26:17 peacetime to wartime, people are looking for you to lead, and you’ve just got to take the horn.
0:26:23 But I always was most uncomfortable with my personal psyche when things were going great.
0:26:30 I mean, when OpenTable was trading for like 21 times forward revenues, which is an absurd valuation,
0:26:36 I was jumping out of my skin. But once you confront the fact that, okay, we’re in one of those
0:26:42 moments and I need to lead out of it, I actually found it after an absolutely miserable X hours.
0:26:48 I found it motivating. We can get over this, let’s show them what we can do. For me, the CEO and
0:26:54 founder needs to confront reality quickly and then they need to lead. And you can lead your company
0:26:58 through these things and get to the other side, then things will get better again. But the biggest
0:27:03 thing is manage your psychology actively. I just want to thank you, David. Thank you, Jeff. Thank
0:27:07 you, Caroline, for joining us on the podcast today. Thank you. Thank you.