NFX partner James Currier talks with professor Tom Eisenmann about why, exactly, over 75% of startups fail. Tom has been teaching entrepreneurship at Harvard Business School for more than a decade and has uncovered patterns of startup failure that we want every Founder to hear -- so you can avoid making these same mistakes yourself.
James Currier (00:35):
Professor Tom Eisenmann, it's fantastic to have you here, you are a professor at HBS and you were there when I was there, you've been there now a total of 22 years, you've focused on technology startups, and over the years a lot of people have turned to you for studies on entrepreneurship and on network effects. This includes me and Scott Cook, your name came up in a recent NFX podcast with him. A lot of people, including you, have tried to capture why startups succeed, and now you're finishing up a book on covering the patterns of why startups fail. I think it's a fascinating topic, and let's talk about both of those today, both why startups fail and some network effects things. So thanks again for coming on, and...
Tom Eisenmann (01:15):
Yeah, thank you for having me.
James Currier (01:16):
What sparked you to focus on this topic of startup failure?
Tom Eisenmann (01:20):
I spent the first half of my time on the faculty at Harvard Business School studying platforms and network effects and I came up for tenure about halfway through, they've got a lot of leverage over you when you're facing that promotion, so they pointed out that I had never taught the core first year course on entrepreneurship. They said, "It'd be much easier to promote you if we could make the case that you're indispensable in several ways, not just some knowledge of network effects", and what could I say but, "Okay"? And I was wrapping up, having taught many years a course on network effects, so this was the first time I'd really taught the core of how you start a startup, and I just fell in love with it. It was a fantastic change, and pretty much that's what I've been doing for the last 11 years, is focusing on startup management.
Tom Eisenmann (02:09):
But what I found when I taught the first year course... so like most everything we did at Harvard Business School, that course is a required course on entrepreneurship and it's case-based, and we get feedback from the students at the end. Year after year, the students would say, "Hey, you told us along the way that something like three quarters of startups fail, but we just did 30 cases on these spectacular success stories. These founders march in, they spread their feathers like peacocks and everything sounds fantastic and of course that's inspiring, but what about the other three quarters of the time?"
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This transcript was exported on Sep 15, 2020 - view latest version here. James Currier (02:44):
Right, most of the HBS cases are, "I was brilliant and then I won".
Tom Eisenmann (02:48):
Yep. And it's fun to come back to school and tell the story of how all that happened and we do that a lot, and students can learn a lot from that of course. But I took that feedback seriously and I wrote a couple of cases about failures, they happened to be... we're allowed to invest in student startups after students graduate and I had done that and at least three quarters of my angel investments failed, so I had plenty to choose from. So I wrote a couple of cases on failed startups that had been led by former students and taught them, I would say classes were pretty wobbly, it was very hard for the students to figure out what happened and why.
Tom Eisenmann (03:29):
Some students were, as is often the case for MBAs, really good at analyzing by looking in the rear view mirror, "Well, isn't it obvious that they didn't do this or that?" And other students, a little more thoughtful, would say, "Yeah, but some really smart investors put money behind this idea and if it's a terrible idea that doesn't happen", so there were obviously a lot of contributing factors. It was hard to understand which, if any, were decisive. The students were really debating, we couldn't tell if it was death by a thousand cuts, there were a lot of things going on, or were some of the factors more central than others. So here I was, supposedly an expert on entrepreneurship, an educator, and I couldn't explain the most important phenomenon in my field, so that was a little sobering.
James Currier (04:13):
The most important phenomenon being that 75% of startups fail?
Tom Eisenmann (04:17):
Yeah, this is it. This is central. And the other thing that was going on then, I had recently discovered the Lean Startup ideas, I'd met Steve Blank and Eric Ries, this is 2009 or 10 before they got a lot of momentum, and absorbed all that and thought it was really powerful, and I was figuring out ways to bring it into the classroom at Harvard Business School. But when I matched those ideas and methods to what I was seeing in these cases, at least one of the cases that I wrote, they were textbook, pitch perfect application of the early part of a Lean Startup and minimum viable product test and so forth, and they still failed. So they'd found a great opportunity, they'd validated demand, they'd done everything they're supposed to do and yet they still failed, so that made me wonder if the playbook that I was starting to teach was incomplete.
Tom Eisenmann (05:08):
So the next step was, "Okay, what do other people have to say about this?", so I tracked down everything that practitioners had ever written. As you'll attest, a lot of venture capitalists are happy to explain why some startups fail and others succeed, and there was some academic work, it was not much and pretty thin. And a lot of what I read, both practitioner and academic, I would describe as oversimplified, read a lot about horse and jockey. I know you're a fan of psychology and it turns out that humans have a penchant to oversimplify, we take complicated things, "The team failed in August/September home stretch because the star pitcher tore a hamstring" or, "The presidential
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campaign failed because the candidate ignored a swing state", usually there's much, much more going
on than just those single simple causes.
Tom Eisenmann (06:00):
And the other psychological phenomenon I saw all over the place, psychologists have a name for something they call the fundamental attribution error, is basically when something goes wrong, if it happened to somebody else we're always inclined to blame dispositional factors; the individual wasn't very talented or they didn't work very hard, and if it happens to us, we blame the situation.
James Currier (06:25): The structural problems.
Tom Eisenmann (06:27):
Yeah. "The jerk cut me off in his BMW, he's a self centered..." I cut somebody off and, "There's a blind
spot that I've been trying to figure out what to do about it".
James Currier (06:36):
So as you've dug into this topic, the research has been a little bit thwarted by doing interviews with people who will give you fundamental attribution errors, both in the simplification and in the attribution errors, so that makes it hard for you to pick through why things have failed.
Tom Eisenmann (06:51):
Yeah, and that's where I realized a lot of people had done, the academic work in particular, they were just simple surveys. They would ask people like, "What are the top five reasons why startups fail?" And guess what, if you're talking to VCs they say "Well, weak team", if you're talking to a founder they say, "The market moved away from us in unexpected ways". And what I learned and realized was, the case method, the approach we actually use at Harvard Business School, because when a case is well done you've come at the problem from a lot of different directions and talked to a lot of different people, it actually was pretty good at triangulating what was going on in a failure situation.
Tom Eisenmann (07:27):
So I'd talk to the founder of course, but other team members and investors, look at other similar companies in the space and so forth, and when you surround the problem that way you'll get some attribution errors of course, but then you can make up your own mind about what's really going on. So the cases in the book I'm writing and the research I'm doing, the case studies have ended up actually being super important.
James Currier (07:47):
Right, having run four of these startups and invested in another hundred myself, I find there's this balance between playing to win and then playing not to lose. And a lot of companies need to... what they're doing at any one time, because if you don't pay attention to these failure modes then you're going to end up failing. It's also the case that with these startups, it seems as if 20 things often have to go right, you have to flip heads 20 times in a row in order for your startup to succeed in the end, so as you go back and look at the failure modes, there's so many triggers that could trigger failure, whereas everything has to add up to go right.
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This transcript was exported on Sep 15, 2020 - view latest version here. Tom Eisenmann (08:29):
Yep. And Paul Graham in one of his essays, he worked this very theme and basically said, "I'm going to tell you reasons why startups fail", it's a great list as a matter of fact, said, "Because it's easier for you to remember the things not to do than figure out all the things you have to do. You'll remember what not to do more easily than figuring out all the things you have to do".
James Currier (08:54):
And what you have to do is different in every age, in every company, in every market, it might be really different. Very interesting. So, do you actually have now... you've been doing this for what, two or three years? You've been looking at this in a systematic way, do you actually have a handle on why the vast majority, or 75% of startups fail? Particularly for early stage companies, most of our listeners are early stage, so I'd love to start there.
Tom Eisenmann (09:16):
So I get to be an academic. We like to define things, so one of the first things you have to do if you're studying entrepreneurial failure, you have to define who's an entrepreneur and I won't go there, but it won't surprise you to hear that people actually disagree about what is entrepreneurship, some people think it's anybody who runs a small business is an entrepreneur, or anybody who owns a company. And of course you also have to define failure, so that came home... I taught a course on entrepreneurial failure this past fall at Harvard Business School and we did a case on Jibo, the social robot out of the MIT media lab, a robot that could actually strike up a conversation with you and move and dance and stuff, it was a really remarkable product.
Tom Eisenmann (09:58):
It failed, it lost $61 million, but the question is, from whose perspective? So failure, is it from the founder's perspective? If the founder's goal was to build an amazing product that some people would love, which they did with Jibo, and prove... in this case the founder was Cynthia Breazeal, who's the pioneer of social robotics. She wanted to prove that people wanted a social robot in their home and she did. From society's perspective that venture didn't work, but the next generation of social robots are out there, working with autistic kids and the elderly and so forth. Investor's perspective, $61 million gone.
Tom Eisenmann (10:34):
And then when you look at failure, you also ask questions about what outcome, so does a company literally have to go out of business? Not every company fails of course, it's not an endearing term but a lot of investors will talk about "Zombies", companies in their portfolio that they know will never yield a return to the investor but they're making enough money to keep going, so is that a failure? Does something have to go bankrupt? I settled for the project on a definition of failure which I think will ring true to most venture capitalists, which is "early investors did not and never will make money", so that was the definition of failure.
James Currier (11:11):
So what we're talking about is how we define failure, and you've defined it narrowly as, "If the early investors haven't and will never make money". And that's a convenient way to describe it that gives us a hard line in the sand to then define the problem and then talk about it, makes sense.
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This transcript was exported on Sep 15, 2020 - view latest version here. Tom Eisenmann (11:27):
Yeah, and then to your question of, do I have a framework? That leads you in the direction of, okay, why? And there's an easy answer, proximate cause of death, if you're a forensic investigator, loss of blood. The company ran out of money trying to find a good opportunity and couldn't raise more. So, loss of blood. Why? Well, a gunshot wound. Okay, why? What's going on? Was it self-inflicted? Was it a jealous spouse? So really it's like Toyota Production System, five whys; when there's a problem in the factory you just have to keep asking why, and that doesn't lend itself to a single, simple, explanation to why startups fail.
Tom Eisenmann (12:12):
Some startups do not find the great opportunities, some don't have a great team, bad market, bad founder. There is a temptation I think for everybody, for academics in particular, to look for one theory that stretches across lots of situations. I think my colleague, the late Clayton Christensen was that kind of scholar, everywhere he looked he saw disruptive technology, you have a hammer and you can bash down on any problem that looked like a nail. The startup failure question really doesn't lend itself to that way of thinking, so no single cause, but there are patterns and I saw some patterns repeated with early stage failures.
Tom Eisenmann (13:01):
So I wouldn't say I have a framework, or at least not a newly invented one. When we teach MBAs at Harvard Business School how to diagnose the prospects for an early stage startup we use a framework we call "Diamond and square". There's a diamond that represents the opportunity and the four corners of the diamond if you will... it's a mnemonic device to help people remember, so the corners; customer value, proposition, the go to market strategy, technology and operations, so how are you going to build this thing and deliver it? And then the cash flow formula. And then surrounding the diamond is a square which represents the different folks who have to contribute resources; the founders themselves, the rest of the team, outside investors and strategic partners. And so we teach the students to ask, "How does the opportunity look, how do the resources look and are they in dynamic alignment? Do you have the right resources in the right quantities to actually pursue this opportunity?".
Tom Eisenmann (14:07):
And that's where the exploration of early stage failure gets really interesting, because what I found were some teams that had mobilized a great set of resources; strong founders, great team, supportive investors, but that team never managed to find an opportunity, a good opportunity. And then at the opposite end I found teams that really had, often through Lean Startup techniques, identified a great opportunity and validated a demand for a solution, but they weren't able to mobilize the resources to capture it. So those are two of the failure patterns that I saw, called one, "A false start" and the other "Bad bedfellows", we'll talk a little more about those. And then there's a third pattern which is, "False positive"; you get off to a start with early adopters and then it turns out that mainstream demand doesn't share the same needs and you've actually mobilized the wrong resources to pursue the mainstream market.
James Currier (15:11):
Got it, so these three patterns are the big, bulky patterns that stand out and within them, there must be
lots of different flavors?
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This transcript was exported on Sep 15, 2020 - view latest version here. Tom Eisenmann (15:21):
Yeah, exactly. The "False start" is a difficult and tricky one, what I've found and the... you may know Sunil Nagaraj, he's a HBS alum, started... before he became a venture capitalist, he now has his own seed fund, Ubiquity Ventures, and worked at Bessemer before that for many years, but straight out of business school he launched an online dating site called Triangulate. Sunil was an engineer, like a lot of engineers is great at building things, loved to build things, and so he dove headfirst into launching Triangulate without really studying the market, without getting a good sense for customer needs, without running what we would think of today as good minimum viable product tests.
Tom Eisenmann (16:11):
The first version of the product was off target and he spent several months building it and launching it before he figured that out. He had a fantastic team, they were really agile and could iterate and build new things fast, so he went through a couple of pivots, but the point is he'd only raised $750,000 and he only had time for a few pivots. Eric Ries actually in his book defines runway as not the number of months of cash you've got left before you exhaust your balance, but rather, how many pivots can you complete before you exhaust your cash balance?
James Currier (16:48):
Sure, that makes a ton of sense.
Tom Eisenmann (16:50):
And the "False start" is essentially, you get going too fast and you waste a pivot essentially, so you have less capital available and you can try fewer things. That's what happened to Sunil and Triangulate. It's very understandable, entrepreneurs have a bias for action, they love to build, they're told to launch early and often. There's actually a lot of the rhetoric of Lean Startup, I would say, pushes entrepreneurs in that direction [crosstalk 00:17:20].
James Currier (17:19):
I would agree, and another nuance to that, that I notice in working with myself and with other people in this space, is that, how much belief do you need in order to pursue an idea the 100%? And if someone needs to have a lot of belief before they'll really go at something, that gets them so that they often waste a pivot or two, because it takes them a long time to get revved up and a long time to get revved off of the idea, they get too attached to it. Whereas a lot of the more facile factors, the people with the personalities that really allow for the Lean methodology to work better, are people who can wake up every day, go 100% at their goal of that day and then immediately when they get the data that it's not working, they can move onto the next idea and then the next day get up with 100%. But a lot of people I find need to have a lot more belief before they can get revved up and that cause them to go slowly [crosstalk 00:18:12].
Tom Eisenmann (18:12):
Yeah, that point echos an important theme in the book about founders and storytelling and reality distortion fields, so that's a term originally from the 1960s Star Trek episodes, but co-opted to describe Steve Jobs and his ability to mesmerize people and get them to see his dream and work 90 hour weeks for months and months on end and help him put a dent in the universe. And when a founder invests that kind of ego in selling the concept, it does make it hard to be flexible in the way you just described,
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so I think there are two extremes; you described somebody who was ambivalent and needed a lot of validation and I think that's very much true, but the other extreme is somebody who's too headstrong and stubborn and just sees the future and is less willing to depart from that, so both extremes can be dangerous.
James Currier (19:16):
Unless the stubborn person just happens to be right with their first guess.
Tom Eisenmann (19:18): Yeah.
James Currier (19:20):
Which is where we get a lot of the decacorns and other companies that...
Tom Eisenmann (19:24):
Exactly. Federal Express 40 or 50 years ago in the 1970s was exactly that, Fred Smith was sure that the world needed a hub and spoke way to move packages around, and it then was the biggest venture capital launch in history and lots of people thought he was crazy, and he was as headstrong as they come.
James Currier (19:48):
Yep, he just happened to be right. Got it, so these are some of the frameworks for these early stage companies, or this is a way of looking at some of the... you've also mentioned the failure of false positives, so seduced by strong results with early adopters and then it doesn't hold with the mainstream companies; what happens there?
Tom Eisenmann (20:10):
If you create a product that's perfectly suited to the early adopters it often won't be the right product for the mainstream, so the example of that in the book, fab.com, e-commerce company, started off with a really highly curated set of funky, distinctive products that were sold to flash sales. So they'd put forward a chandelier made out of champagne glasses, they had rhinestone encrusted motorcycle helmets, things like that, and the early adopters were crazy about this stuff, this very distinctive vision of design that the Fab founders had, and bought a lot and referred their friends so it took off on social media. And the first cohorts that Fab recruited were just fantastic, some of the best that e-commerce has ever seen [crosstalk 00:21:12].
James Currier (21:12):
So the repeat purchase rate was high, and the average sales price was high, and they would take this deck to the venture capitalists and they would say, "I've never seen anything this great", it was there in Philadelphia and they raised what, $350 million or something?
Tom Eisenmann (21:25):
Yep, exactly. VCs pumped a lot of money in and the expectation was that they could go, go, go. Well, the next generation of customers, the next cohorts, weren't nearly as excited, they didn't repurchase. The first cohorts came through social medial referral, so the cost of customer acquisition was zero for them.
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You had to buy the next cohorts, so you have this LTV, lifetime value of a customer, CAC, customer acquisition cost, squeeze, where the customers became less valuable because they weren't repurchasing and they became much more costly to acquire. And so they burned through a ton of capital, mostly because the mainstream market didn't share the taste of the early adopters.
James Currier (22:13):
Talk to me about the aggregating resources and the catch 22 around that.
Tom Eisenmann (22:22):
You folks are all about network effects so you're very familiar with the catch 22. For the listeners, in case they should read the book, it's an amazing book, but a catch 22 is a logical impasse that takes the form, can't have A without B and can't have B without A, so you can't get a job without experience and you can't get experience without a job. Network effects in two sided markets have that flavor; side A won't come on board unless side B is there and vice versa. And so the catch 22 with an early stage startup is you can't get resource providers to commit, and by that I mean the rest of the team, strategic partners and crucially, outside investors, until you've resolved some risk. They're taking a risk by lending their time, their money to you, and you can't reduce risk until you've actually mobilized some resources. You can talk about it, but people will be looking for more validation and more proof. So the catch 22, you can't get resources without reducing risk, you can't reduce risk until you get started, and to get started you need resources.
James Currier (23:35):
Right. The founder kind of has to fake it until she makes it.
Tom Eisenmann (23:39):
That's part of it and I would say that's one of four tactics. When we talk about this at school we talk about storytelling and I think fake it 'til you make it is that, but in general we're looking for ways to either mitigate the risk and reduce it in some way, or reduce the resource requirements, if we can do one of those two things we've helped with the catch 22.
Tom Eisenmann (24:06):
So the four tactics; resolve risk, defer it, shift it to another party or get people to ignore it. Storytelling, fake it 'til you make it is basically a way to get people to ignore the risk, because you've faked them out essentially, or in the case of reality distortion field style storytelling, you've dazzled them. Partnering is another thing entrepreneurs always do, they don't have resources so let's go to somebody who's resource rich and borrow their resources and we'll shift the risk to them, but we have to persuade them that it's worth their while. Staging of course, when new ventures get funded inside big companies they don't come with seed, Series A, Series B, it's just next year's money, "Here's a big lump of capital". But VCs will stage, which essentially defers the risk until you've met some milestone; "If you haven't met the milestone we may not give you Series B". And then lastly, lean testing is a way to resolve the risk cheaply and still in a rigorous way before you have to commit too much in the way of resources.
Tom Eisenmann (25:15):
So those are the four ways you get around it, each of them has a dark side and you see some of that in
these failure stories. The dark side of lean testing is, people think they are doing it but they skip the
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upfront phase of essentially customer discovery, they go right to the building, "Let's build and put a product in customers' hands and then iterate as fast as we can", but they've skipped that first few weeks or maybe even couple of months of really interviewing customers and understanding their need and doing ethnography and so forth. Staging can go bad when you pick the wrong investors, partnering goes bad a lot basically because big players are hard to negotiate with, it's hard to align your interest with theirs, if you can get their attention at all. And then the risk with storytelling, reality distortion field and so forth, is that the reality distortion field folds back on itself and the founder is persuaded of the truth of what they're doing and doesn't hear the universe saying, "This idea really isn't working".
James Currier (26:23):
Yeah, it's interesting, you mentioned the dark side and I don't think people are very comfortable talking about that. I think that if you look at the percentage of traffic that was coming from the hookup area on Craigslist or... There's a lot of darkness that's driving the early stage of some of the companies we know and love that gets cleaned up later. I know that YouTube had to pay big copyright infringement payoffs after they were acquired by Google, because they had been infringing on copyright in order to get going.
James Currier (27:01):
It reminds me a little of Jean Valjean from Les Mis who does something wrong, he steals the silver candlesticks and if the vicar decides to rat on him, he's going to jail and will die in prison in the next year. He gets a pass and that lets him jumpstart his startup, but there was a dark side to Jean Valjean's beginning and then we as the audience have to decide, do we forgive them for that or not?
James Currier (27:27):
I think The Social Network, that movie, showed us the dark side of the beginning of Facebook, and many of these companies have those dark sides to them as they do something unusual, they do something out of the norm. Whether it's Airbnb, or Uber, or Lyft, or Lime, or Bird, looking at the gray area of what local states and cities have as their ordinances and pushing those boundaries and getting cease and desists. There's a tussle on the boundary, that if you put a bright light on it, it really doesn't look good.
Tom Eisenmann (28:01):
Yeah, better to ask for forgiveness than permission when it comes to all of these ventures that have got ambiguous legal standing, and then just a general problem that you point out of overstating, maybe in the extreme misrepresenting the progress you've made when you're selling the concept of [crosstalk 00:28:26].
James Currier (28:26):
Exactly, exactly, and there's this game between the venture people and the founders, and I was a founder for 20 years before I became a venture guy two and a half years ago, but now that I'm sitting on the other side I can see this game where we're trying to penetrate the exaggerations of the founders, and the founders need to exaggerate in order to get the confidence ball rolling and in order to attract resources into their company. So there's this culturally permitted boundary, that if you're not in the network and in the system, understanding where that boundary is, it's often easy for founders to cross the line into flat out misrepresentation versus what the community of investors and whatnot has come to understand as general exaggeration.
James Currier (29:13):
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I remember working at Battery Ventures as an associate in the '90s, and we would make an investment and it was my job to do a lot of the due diligence on the company, and we would make the investment and at the first board meeting we would always be surprised at how much worse things were than we thought before we made the investment, always. No matter how many people, no matter how many calls we made, no matter how many spreadsheets we looked at, things were always exaggerated, things were always hidden. And so there's this cat and mouse game between the investors and the founders now and this is the dark side of being on the cutting edge and trying to aggregate resources. This is the dark side of the founders trying to solve this catch 22.
Tom Eisenmann (29:49):
Yeah, it's out there. I wish I could say that we at Harvard Business School have figured out how to teach this to MBAs. We're acutely aware of the need to do that. There is essentially a business ethics course that all the MBAs take, but we've been, in my unit, wrestling with the question of whether entrepreneurship is somehow different; are these just business ethics problems that you would approach the same way as Johnson and Johnson figuring out what to do with all the tainted Tylenol bottles, or is this different? So a lot of smart folks, my counterpart at Stanford Engineering, Tom Byers, put a big push on to get entrepreneurship educators to think about ways to teach the next generation of founders how to approach these questions responsibly. We're getting there.
James Currier (30:43):
And when the system is rewarding the people who are the most aggressive, like in the Uber versus Lyft situation, it's hard to guide founders in a really clean way. One thing I've heard and I use myself with the founders I work with is, don't do anything you don't want on the cover of the Wall Street Journal.
Tom Eisenmann (31:01):
Yeah, that comes up in class discussions. People will draw a line between outright lying, and where it
gets gray and tricky is if they don't ask you, do you have an obligation to tell them?
James Currier (31:17): That's right.
Tom Eisenmann (31:19):
"We're about to lose a big customer and if you ask me I know you'd want to know the answer to this,
but you haven't asked me and so can I just sit here and let it go? What's my ethical responsibility?"
James Currier (31:31):
Yeah, it's tough. And then the founders will say, "Well, they're sophisticated investors, they should know
to ask the right questions".
Tom Eisenmann (31:38): Mm-hmm (affirmative).
James Currier (31:40):
I'm reminded of... but this is true in all of life, not just the startups. I know that my neighbor down in
Duxbury, we had some friends try to do a building project and they were declined, and then another guy
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bought the pieces of land and then he got the building project done. The first guy goes and asks this little town, "Why did he get to do it?" And he said, "Well, you didn't know what questions to ask". Spending time in the startup environment and learning the exact lines of these things I think benefits everybody, it's why network effects are even powerful within the network of people building startups, because you have to know all these little things. So is there anything that stands out as the most surprising thing you learned about startup failure at the early stage? Is there one thing that you're like, "Gee, I hadn't expected that"?
Tom Eisenmann (32:28):
Yeah, so the big surprise was the early adopter challenge. Most of us who've been in this business for a long time have read Geoffrey Moore's Crossing the Chasm book, and that book puts a spotlight on the difference between early adopters and mainstream customers, so I think I knew about it conceptually, but to see how hard it was for early stage founders to deal with this question of; do you build a product for the early adopters? Do you build a product for the mainstream? And how do you bridge from one to the other? And the mistakes you could make if you get that wrong and how it can tank your company, that was eye-opening.
James Currier (33:15):
That's interesting, that was very interesting. And what's the difference between the early stage and the
late stage startup failure?
Tom Eisenmann (33:22):
Well, the big difference is when a late stage startup fails, it leaves a giant steaming crater in the landscape, hundreds of millions of dollars and hundreds of employees and we read about it. Early stage things fail and you know about it if you've invested in it, but they don't quite have the impact, so the late stage failures can put your hair on end, some of them.
James Currier (33:52):
Now you've made the point maybe, that the failure rate of late stage is almost equal to the failure rate
of early stage, or am I misquoting?
Tom Eisenmann (33:59):
Yeah that's fair, if you use the definition we did before which is "investors didn't make money", then what happens with a lot of late stage startups is they've got momentum, the Series C investor buys in at a high share price and the thing goes sideways. And it doesn't necessarily fail, but there's a down round or even an up round, but a lot more capital comes in, in a different place in the liquidation stack and if the thing is sold, Series C might make some money but it isn't going to be the five or ten times they were hoping for and often they may lose money. So if that's the metric, not getting all your money back, then 75% is indeed the number.
James Currier (34:52):
That's incredible, Tom. That's super surprising to me, but I guess it makes sense because what we're seeing is that the capital markets are kind of efficient, meaning if there was one investing stage that was far outperforming the others then everyone would be doing it.
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I like that explanation. Never thought of it that way but I agree completely.
James Currier (35:14):
Okay, and so what are some of the differences with late stage? One is that it's a much bigger crater, many more people are affected, we hear about it in the press, you've got this great phrase, it's "cascading miracles", can you walk me through that?
Tom Eisenmann (35:28):
Yeah, so that's just one of three failure patterns that I'm looking at late stage, that one... I love the expression, it actually came... you'll remember who John Malone is, the entrepreneur who built TCI, Tele-Communications Inc, the biggest US cable company. He got it from a mentor of his, the phrase, and it basically, it's... you were making this point early in the podcast that it's often true that many things have to go right and if any one of them doesn't, the venture fails. It's a math equation where you multiply a bunch of outcomes and if any of them goes to zero the whole expression goes to zero. You used just 20 coin flips, if you just take five coin flips, so if there are five things that have to go right and there's 50/50 odds, the chances you're going to come up heads five times in a row is three percent, it's like spinning a roulette wheel and hoping you land on 31 or whatever.
Tom Eisenmann (36:34):
So that's the problem, and where you see this in particular, I reserve the expression for audaciously bold startups where there's this really ambitious innovation plan and often a founder who can sell that. Because of the scope of the innovation, it's going to take a long, long time to develop the product, because of the nature of these businesses you often have network effects in the background or high switching costs, attributes that are going to cause you to want to go fast once you actually do launch, and so there's a scaling imperative, there's a long development cycle, there are often partnerships, there's often government approvals, because again, ambiguous legal standing, and a whole bunch of things conspire. You've got a moving target, because you're not actually going to launch this thing for five years, seven years, of course the markets keep moving, technologies keep moving, you have to figure out whether you want to incorporate the new technology.
Tom Eisenmann (37:45):
And so examples of this, Jibo was a good example, it was a "cascading miracles". Iridium if you remember, satellite phones, $6 billion loss, satellite phone service anywhere on the planet. Segway was that kind of business, Silicone Valley veterans will remember GO Corp, which was pen and tablet computing back in the '80s, early '90s, and the case we use, SpaceX and Tesla, are probably examples of this working, flipped heads many times in a row, at least so far. But the case I use in the book is Better Place, Project Better Place, which was $900 million spent and lost on an effort to create a network of charging stations for electric vehicles, launched in 2007, went out of business in 2013.
Tom Eisenmann (38:47):
There's a tendency to overestimate demand, if you saw the original projections for Iridium or Segway, what they thought they were going to sell, and because of the delays you eventually cut some corners with the product, the costs, because of the delays and partners not carrying their end, the costs escalate, and so ultimately when you launch, it's disappointing, as it was for Jibo, as it was for Segway,
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as it was for Iridium, over and over again. And these things, when they go down, it's hundreds of millions
of dollars lost.
James Currier (39:20):
And for them to have worked, they would have had to have a series of cascading miracles for them to
work.
Tom Eisenmann (39:25): That's right.
James Currier (39:26):
And when people were investing in them, there was either a reality distortion field or there were some sort of metrics early on that allowed the investors to pour another, let's say $800 million, into Better Place, thinking that a lot of the risk had been taken out, thinking that the miracles had already happened in the past and now we just need it to scale.
Tom Eisenmann (39:47):
Yeah, and reality distortion field, Shai Agassi was the entrepreneur behind Better Place, positively Jobsian in his ability to dazzle an audience. And with Segway, Dean Kamen, same thing, really riveting, inspiring, presenter. Segway was backed by John Doerr of Kleiner Perkins, Steve Jobs himself wanted to put $50 million in and Dean Kamen wasn't comfortable with the amount of control that Jobs might want, Bezos wanted to invest. So yeah, some of these ventures get going in boom times, the height of a bubble, but not all of them.
James Currier (40:36):
It's interesting because the positive side of someone with a reality distortion field is that every company has financing risk, and if this person through their personality is really good at fundraising, then you as an investor think they'll attract more capital and will get more and more advanced with this.
Tom Eisenmann (40:55):
Yeah, exactly. And the financing risk is particularly acute because the development cycle is so long. If you're doing a... Better Place essentially was a clean tech startup, started in 2007 and launched in Israel in 2012, so you got to live with five years of financing risk and we went from boom time for clean tech investing to basically people deserting the sector.
James Currier (41:27):
Sure. And this was one of three failure modes you're seeing in later stage, these cascading miracles,
what are the other two?
Tom Eisenmann (41:36):
One of the others, I think, we've been talking about financing risk, I call... all of the failure patterns have names, so the name for this one is "Help wanted" and it's basically a late stage venture that still has product market fit; the customers love the product, the basic formula in terms of LTV/CAC is on track, but something on the resource front goes awry. It might be a mistake made, or it might just be... by the way, that's one of... with failure in general you've got to decide, are you only going to label this thing a
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failure if mistakes were made by the management team? Sometimes it's misfortune. We're in the middle of a pandemic and a lot of startups will fail not due to any fault, any bad decisions by the entrepreneurs.
Tom Eisenmann (42:32):
So Dot & Bo was the example in this chapter, it's an online retailer of home furnishings and the formula was working, the demand side was very strong, but two things went wrong; One, they got hit by, you'll remember this well James, circa 2013-14, big downdraft in spending on e-commerce, probably a 50% decline across the board and even in a downdraft like that, financing risk like that, even healthy companies can't raise more money. And so just as Dot & Bo was [crosstalk 00:43:15]
James Currier (43:14):
Hang on, what do you mean, the downdraft? You're talking about the downdraft from investors?
Tom Eisenmann (43:18): Yeah, exactly.
James Currier (43:18):
Not from buyers, consumers, but from investors.
Tom Eisenmann (43:23): Yeah, exactly.
James Currier (43:24): E-commerce fell out of favor.
Tom Eisenmann (43:25):
It did, and stayed out of favor for long enough that if you had just stepped on the accelerator as you were heading into that period of financing risks, you were in big trouble. It turned out Dot & Bo's demand model relied heavily on virality and social media, and it can be harder to turn that off than the kind of customer acquisition that relies on paid marketing, so that was one misfortune. I suppose you can always ask questions about whether management should plan for something like that, whether they could see it coming, but the other problem they had was shipping couches across the country is logistically and operationally intensive like nothing you've ever seen, except maybe apparel manufacturing. It took them the longest time to figure out how to do that and how to do it efficiently and effectively, and essentially they went through three vice presidents of operations before they found somebody that could get the logistics and operations and shipping under control.
Tom Eisenmann (44:33):
So they had strong demand, but they had poor margins because they were expediting things, because people were canceling orders, because there were all sorts of queries to customer service. And Anthony Soohoo, the entrepreneur, I think would say made a mistake in these hiring moves; first person he hired, because he knew he had these operationally intensive demands, he wanted a generalist, a chief operating officer type, and hired somebody who was good at that but had never really had e-commerce experience of shipping heavy things. Second person had more of that but had the kind of big company
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background we were talking about a little while ago and didn't work out, finally nailed it the third time
but by that point he'd burned through a lot of capital and then he hit the financing risk.
James Currier (45:28):
Got it, so incomplete team. So often I'll see [crosstalk 00:45:32]
Tom Eisenmann (45:31):
Exactly, missing manager, one single in a really decisive senior role, having the wrong person in there, so
"Help wanted".
James Currier (45:42):
Yeah, so often, as I said there with the founders, I finally conclude, I lean back and I say, "Well, we have
a recruiting problem don't we? We're missing someone".
Tom Eisenmann (45:51):
Yep, and again, it takes three months, six months to fill a position like that, and then you bring somebody on and it's three months or six months before you figure out whether it's working, so [crosstalk 00:46:02].
James Currier (46:01):
Yeah, it's 12 months of burns because you're missing one person. And if you've gotten everybody else in
place, then that just increases your burn every day.
Tom Eisenmann (46:12):
Yeah, exactly, that's what happened. And then the third pattern, I call it "Speed trap". I talked a bit about fab.com a minute ago, that's the case there. We can blame this one on the venture capitalists, although entrepreneurs can be complicit. So early momentum, VCs buy into a company that's growing fast at a high share price and expect more of the same, entrepreneur loves that, who doesn't want to grow the thing, so you step on the gas, the customers that arrive later aren't nearly as attractive as the ones who came in the beginning. If you're at all operationally intensive, if it's just a pure software business it's a little more forgiving, but if you've got to operate warehouses and call centers and so forth, you're now hiring legions of employees that you've got to train, you've got to layer in middle managers, you've got to create processes and so forth, and so you're going as fast as you can.
Tom Eisenmann (47:23):
You've got, often, chaos operationally, you've got problems culturally because you have old guard/new guard conflict; the new guard is jealous of the option gains that the old guard is sitting on, the old guard looks at these new people who don't understand the mission, who just see this is a job, the new guard are specialists and they think their skills aren't appreciated, the old guard are generalists and their jobs increasingly are, "What do we do with Fred? He's pretty good at a lot of things but he can't run performance marketing, he can't run the warehouse, he can't run the call center". And so you have all sorts of problem, and of course the right answer is to slow down and fix things, but you've got a lot of pressure to keep going and that's where the speed trap comes.
James Currier (48:19):
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So I want to switch gears and talk about startup success and network effects, because obviously NFX stands for network effects. We believe that network effects are the strongest, durable, competitive advantage and we see a strong correlation between network effects and success. And over the last few years we've done this research project where we've noted that 70% of the market cap in the tech industry comes from the 30% of companies with network effects at their core, so that underlies our thesis about how we invest. And you have been such a masterful contributor to the overall thinking about network effects over the last decade or more, and so it's always great to sit down and talk with you about this. Are you still teaching network effects to your HBS students?
Tom Eisenmann (49:03):
Do you mean me or my colleagues?
James Currier (49:04): You and your colleagues.
Tom Eisenmann (49:06):
I don't do it much anymore, two years ago I teamed up, I know you've met my colleague Scott Kominers, absolutely brilliant economist who's an expert on market design, marketplace design, protégé of Nobel Prize winner, and I helped him launch a course on marketplace design, so that was really the first time I've been back at it. And of course, in any kind of marketplace the network effects loom large, so that's the first time I've done it in years. Now I'm rusty. But it's all over our curriculum at Harvard Business School, I would say half of the required first year courses, the entrepreneurship course, the technology and operations course, marketing strategy, all of these courses teach some aspect of it, and plenty of the second year electives.
James Currier (49:56):
Interesting. Most people in the world don't get to go to HBS, and I was super lucky to get in and enjoyed my time there, and for those people who are listening who don't get to go, just knowing that you guys spend a lot of time studying it I think is helpful to know. That if they were going there and spending two years and spending their 140 or whatever it is thousand dollars, to...
Tom Eisenmann (50:18): That's the number.
James Currier (50:19):
To get the education, that they would be studying a lot about network effects, so certainly having the
syllabus is half the battle, so that's good.
Tom Eisenmann (50:28):
Well you guys have done a great... your website is the syllabus now, so thank you for [crosstalk
00:50:33]
James Currier (50:34):
Well thank you Tom, I appreciate that. So what do you think people are frequently getting wrong about
network effects?
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Less than in the past but still a lot, the definition even still. I know you're sensitive to this, there's a lot of people will point to virality and assume there's a network effect. Sometimes there is, but if it's just a word of mouth referral that's not a network effect, that's word of mouth referral. And the other place where it gets confusing and I think people, even experts on network effects, can have a reasonable debate about this, is a situation where density of the network, sheer traffic, scale of some sort, makes the product more valuable.
Tom Eisenmann (51:25):
I tend to reserve network effect for when the users of the network are actually interacting with each other, usually through a platform, and if there's no interaction I don't consider it a network effect. It is a scale economy, so you get into businesses like dockless bike sharing where the company buys a whole bunch of bikes and the more bikes there are, the more comfortable you are as a user going to be that there'll be a bike in the right place at the right time. It's not really a network effect.
Tom Eisenmann (52:00):
And Google in some ways is the same way, with a huge amount of search traffic they can draw better inferences about what the best listings are to serve up to you, so the product gets more valuable the more people use it, but they're not really interacting with each other through the product. So those definitions are an issue, I think it's easy for founders to wave their hands and say they're going to harness network effects without really understanding how strong they are, and i still see a lot mistakes assuming that network effects are stronger than they are.
James Currier (52:38):
Well Tom, it is a real pleasure to hear your voice and to talk with you about these things. When is the
book coming out?
Tom Eisenmann (52:44):
The book, I'm writing the conclusion right now. As you might guess, it takes a long time to go from there to a printed book on the bookshelves, so I think the target date is March or April, essentially 10 months from now.
James Currier (53:00):
Got it, and the name of the book will be?
Tom Eisenmann (53:02): Why Startups Fail.
James Currier (53:04):
I can't wait to read the whole thing. Tom, thank you so much.
Tom Eisenmann (53:07): Yeah, thanks James.