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  • >>Thomas Sharon: Hi everyone. Thanks for coming. My name is Thomas Sharon. I'm a UX Researcher

  • here.

  • And without further ado, I would like to introduce you to Eric Ries, the founder of the Lean

  • Startup movement. And thank you for coming.

  • [applause]

  • >>Eric Ries: See, I don't know. It's hard to know when you have an audience you don't

  • know.

  • It's hard to know what to say.

  • So, some of you maybe know the blog, Startup Lessons Learned. Anybody? Quick show of hands.

  • OK, good. We have true new people. So, thank you. Thank you for coming to check it out.

  • So my name is Eric Ries. I don't really want your undivided attention. So keep your laptops

  • on. That's fine. And in fact, if everyone do me a favor and take your phones out of

  • your pockets.

  • I mean, I'm sorry. I know I'm not supposed to have this one, but if can turn them on.

  • No, I'm not joking around. Out of the pockets, please. 'Cause this is gonna be a talk. You

  • might get bored and you might wanna tweet amongst yourselves.

  • Or I don't know, whatever special internal tools you guys use. Whatever it is, please

  • feel free. All I ask is that you use the Lean Startup hash tag, at least if you're on Twitter.

  • Okay. Is that fair? I won't tell anybody. Don't worry.

  • I'm in New York because I'm writing a book. So one of things you do when you're writing

  • a book is you have to go to tell as many people as possible that this book is coming out.

  • It'll come out in the fall. I thank you in advance for preordering it. You can do so

  • at lean.st.

  • That's my life now is as a professional expert selling books, which is a far cry from how

  • I started, which is as a programmer writing code.

  • So I'm one of those people that grew up writing code. I used to write code for a living, which

  • is a job I knew really well and understood. I was pretty good at it.

  • And then, I started doing startups and I started to have to manage people who wrote code for

  • a living. I knew that slightly less well.

  • And then I was managing people who managed people who write code for a living.

  • And now, I am this professional expert. And so I advise people who manage people who manage

  • people who write code. So I've become very far removed from the actual work of product

  • development.

  • But that journey has taken me from just writing code to doing this because I actually think

  • the way that we organize new product development is basically wrong. And that most of the energy

  • that we are investing into what is called 'entrepreneurship', when it's two guys in

  • a garage, or 'disruptive innovation' or something else buzzwordy when it's done inside a big

  • company, is wasting a lot of people's time. And I think we can do something about it.

  • So that's what I wanted to talk to you guys about. Thanks for coming.

  • So anyway, and this book, of course, will be available in stores everywhere in the fall.

  • So, if you read the book, you will learn five principles of the Lean Startup. And we'll

  • go through them today.

  • And I wanna invite you to ask questions either on Twitter, if you're not feeling that courageous,

  • or interrupt me at any time or we'll have time at the end. All right?

  • So, entrepreneurs are everywhere. The first thing is, especially in an audience like this,

  • I wanna be clear, that entrepreneurship is not just about two guys in a garage eating

  • Ramen noodles. In fact, what makes you an entrepreneur is not what kind of noodles you

  • eat, but the context in which you operate.

  • And as I've been travelling around talking about Lean Startup, what I have learned is

  • that there are entrepreneurs in all kinds of places you wouldn't necessarily expect.

  • And we have a lot more in common than people realize, because entrepreneurship is management.

  • But not the kind of general management we're teaching MBAs and that we have studied for

  • the last hundred years, something fundamentally different. It is management of a kind of work

  • that is measured by validated learning, rather than just making stuff.

  • We accelerate that learning through something called the 'build-measure-learn feedback loop'.

  • And then we measure and hold entrepreneurs accountable using a new accounting system

  • called 'innovation accounting'.

  • Now, I apologize. You came to a very, I'm sure, you saw the signs up here like, "Ooh,

  • an exciting talk about entrepreneurship and startups and that's gonna be cool." And what

  • did you get?

  • You got management and accounting, which are perhaps the two most boring topics on Earth.

  • So if anybody wants to leave now, I won't be offended. It's OK.

  • Because the truth is, what do people know about entrepreneurship? I feel like -- who

  • saw 'The Social Network'? OK. Right. I feel like that's probably the best modern example

  • of the entrepreneurship story we're all used to.

  • And you see this in magazines and you see it in 'The Social Network'. I noticed last

  • night that the story, 'Ghostbusters' -- remember 'Ghostbusters', the movie? It's an entrepreneurship

  • story. They start a business. They, Dave, everything's the same. It's like the same

  • plot structure as 'The Social Network', believe it or not, except it has a Stay Puft Marshmallow

  • Man, which is awesome.

  • In these entrepreneurship stories, what happens? It's a story in three parts.

  • Act One: The plucky protagonist, his character, his character flaws and how he came up with

  • his amazing idea.

  • Act Two: What I call the photo montage. It's usually about two minutes long. It goes from

  • "they finally get the thing to work". Then they're writing on whiteboards and drinking

  • some beer, pounding on some keyboards. And then they get their first customer. And then

  • that's pretty much it. No dialogue or anything in the photo montage.

  • And then Act Three: Now that we're on the cover of magazines, how do we divide up the

  • spoils? And who's in charge? And who's in Who's Who? And how do we deal with the EPA

  • and all that stuff? For fans of 'Ghostbusters'.

  • What I think is really interesting about these stories about entrepreneurship is that 95

  • percent of the time of the movie is spent in Acts One and Act Three, even though in

  • real life, all of the important work of entrepreneurship happens during the photo montage. But the

  • problem is, for a story-telling point of view, the photo montage, even though it has no dialogue

  • and only lasts two minutes, is it's unspeakably boring.

  • What do we do as entrepreneurs that actually makes a difference? We spend our time trying

  • to figure out which customers to listen to and who to ignore, how to product-prioritize

  • product features.

  • I mean you guys, how many product prioritization meetings do you go to? It's not exactly the

  • stuff of movies. It's unbelievably boring.

  • And how do we hold people accountable? How do we measure to figure out if we're actually

  • making progress or building something that nobody wants? See, watching somebody pretend

  • like they don't have anxiety that their vision is wrong, is not very good for movies. But

  • that's what most entrepreneurs do.

  • And so, we're gonna have to talk about stuff like management and accounting, 'cause it's

  • time to go inside the photo montage and try to figure out what can we do to make the actual

  • work of entrepreneurship more effective. So, entrepreneurs are everywhere.

  • My goal, my mission in doing this whole Lean Startup thing has been to try to put the practice

  • of entrepreneurship on a more rigorous footing. And so, I started out with a definition. Here's

  • mine: What is a startup? "A human institution designed to create something new under conditions

  • of extreme uncertainty."

  • So I think the most important part of this definition, and for our purposes today, a

  • very important part of our discussion is what it excludes. It doesn't say anything about

  • what the size of your company is. It could be five people, 5,000, or 50,000. It really

  • doesn't matter.

  • It doesn't matter what sector of the economy you work in. It really doesn't even matter

  • what industry you're in.

  • If you fundamentally are operating with extreme uncertainty about who is your customer, what

  • product do they actually want, and how do we build a sustainable business, then you

  • are an entrepreneur. And when I work with large companies, one of the things I have

  • been trying to do, is to get them to adopt entrepreneurship as a job title.

  • Entrepreneurship is a career. When you become an entrepreneur, you are no longer an engineer.

  • You are no longer a marketer. You are no longer a UX designer. Whatever it is you used to

  • do, all of a sudden now, you have a different job title and you've entered a new career

  • path.

  • But unfortunately, we don't get the memo that tells you that. So, it can be a little bit

  • confusing.

  • That's all a fancy way of saying a startup is an experiment. What I mean by "experiment"

  • is not just like let's ship it and see what happens, OK? That's not science. If you just

  • put some compounds in a beaker and heat it up, you might look like you're doing science.

  • But unless you have a hypothesis that you're trying to test, you have theory, it suggests

  • which experiments are gonna help you and then you make specific predictions, then, fundamentally,

  • you're not conducting an experiment.

  • And we mean, in a Lean Startup model, "experiment" in the scientific sense. We're trying to create

  • a science of entrepreneurship that will help us to stop waste people's time, because that's

  • what we're doing on an industrial scale.

  • And you guys know. Anyone's who's worked on new products knows that most of them are doomed

  • to failure. And when you get at the end of that product -- I mean as an engineer, I kept

  • having over and over again the experience of working on amazing technology that is today

  • sitting on a shelf or worse, that fundamentally nobody is using. And I kept looking for more

  • and more technical solutions to that problem. I thought, "If we could just get the right

  • development methodology, if we just had the right amount of unit tests or the right this

  • or the right that, then we could stop that happening."

  • But the biggest waste that product development faces today is not building things inefficiently,

  • but building things very efficiently that nobody wants. And I brought a demonstration.

  • We all know that most startups fail. Who remembers Web 2.0? Remember Web 2.0 when that was really

  • cool? At the height of Web 2.0, 2006, a graphic designer put together this graphic. Have you

  • seen this before? This was the like the logos of all the incredible Web 2.0 companies that

  • were gonna change the world.

  • And in just three years, in 2009, a different graphic designer was feeling a slightly different

  • set of emotions when they put together this graphic. Our three year report card in Web

  • 2.0. I mean, the blood red Xs, these are all companies that are just dead. I think for

  • our purposes today though, a much more important part of that chart to look at are the green

  • circles. I won't point at any of them in particular, but some of those green circles are supposed

  • to be the success stories of Web 2.0. But for this chart, what that means is there are

  • companies that were acquired by a larger company, including this one.

  • And listen, I'm all for people making money.

  • So when a company gets acquired by another company, usually investors and the founders

  • make some money and that's all good. But my question is which of these companies are actually

  • success stories? Success stories by the higher definition, not of "did anybody make money?"

  • But rather, which of these companies succeeded in living up to the aspirations, dreams, time,

  • talent, and energy of the founders and their investors? And more importantly, their employees.

  • See, look, we all know that when big companies buy startups, at least half the time, they

  • die afterwards. So we buy something for hundreds of millions of dollars. And then we wind up

  • selling it three years later for tens of millions of dollars.

  • That's not supposed to happen. In general management, that doesn't happen. When you

  • buy an asset, it depreciates in a predictable way. But when big companies buy startups,

  • it doesn't happen exactly like it's supposed to.

  • And I think the problems that corp-dev departments have when deciding how to buy startups and

  • which startups to buy and then how to integrate them into the parent company, are the exact

  • same problems that internal innovators who are trying to create brand new startups inside

  • big companies have. And they're the exact same problems that venture-backed entrepreneurs

  • have with their investors.

  • All of us lack a theory of entrepreneurship to guide our behavior and so we're falling

  • back on tools and methods that are not appropriate to entrepreneurship. That's my belief. So,

  • I don't think it has to be this way.

  • See, it's one thing if startups were failing because they were taking too much risk. If

  • one of these companies was working on teleportation and then it turned out to be too hard -- we

  • couldn't quite get the technology for quantum entanglement like we thought -- I accept that

  • kind of failure; that happens.

  • But I chose Web 2.0 for my demonstration, especially for you guys. You know. There's

  • not a single company on this chart where you would say, "Boy, I wonder if that can be built."

  • Right? "Geez, I wonder if that new social network -- is it possible to build it?" We

  • all know. Software companies, we can build anything we can imagine. Think about that

  • for a second.

  • The dominant question of our time is not can it be built, but should it be built. And the

  • issue is can we build a sustainable business around a particular product? So, the future

  • of our society, our economic growth in the future, the GDP growth of industrialized countries

  • in the future is going to be dependent on the quality and character of our collective

  • imaginations, which I think is a very strange place to be.

  • That is really different than the kinds of economic problems that general management

  • was designed to solve in the 20th Century. Now, most of my startups have failed. So I

  • know that's not how you're supposed start one of these talks, like, "Hi. I'm a professional

  • expert and I have had more failures than successes. So you can be just like me if you'll follow

  • my advice."

  • So, I'm sorry about that. But those of you who spend any time around entrepreneurship

  • know the truth that where there's startups, there's a lot of failure. And it has to be

  • somebody's fault in a talk like this and obviously it shouldn't be my fault 'cause I'm the expert.

  • And preferably, it should be the fault of someone who's dead so that they can't argue.

  • So I chose this guy.

  • [laughter]

  • This is Frederick Winslow Taylor. He died in 1915, which is very handy for the purpose

  • of this talk because it means he can't talk back. So, sorry, Fred.

  • Fred Taylor invented something called "scientific management" in the early 20th Century, which

  • today, we call "management". See, people don't really remember Fred Taylor.

  • And those who've studied scientific management in school probably remember him for some of

  • his outdated and really ridiculous ideas, like time and motion studies or the idea that

  • a worker is basically just an automaton and should be told what to do. The reason we don't

  • give Fred Taylor the credit he deserves is because he invented things that to us are

  • so obvious, we can't imagine them ever having been invented. It doesn't make sense.

  • Like, everybody knows that work should be done as efficiently as possible, right? And

  • that we should treat work like a system and that we should have managers organize that

  • system. That's just plain common sense.

  • And my favorite, Fred Taylor, invented something called "The Task and Bonus System", which

  • we just call "tasks". The idea was if you want to do a large project, the best thing

  • to do is decompose that project into a series of individual tasks, assign those tasks to

  • functional specialists. And everyone just does their part knowing that if everybody

  • does their part well and everybody else does their part, the whole will actually work out

  • like the manager said.

  • And here's the best part. If you do your task particularly well, better than expected, you

  • should be paid a bonus rather than being penalized. What could be more obvious? Except in the

  • 19th Century, the way work was organized is that if you did your task better than expected,

  • you were penalized.

  • [pause]

  • Why? Because that showed a lack of integrity. You obviously could have done it better before.

  • But you didn't. So that proves that you're a liar.

  • It gets worse. Not only are you a liar, but what about all your compatriots, your coworkers,

  • who do the same task the old, slow way? They're liars, too. All of you have been lying this

  • whole time and you should all be penalized.

  • Imagine working in a factory where if you can come up with a better way to do your repetitive

  • job, not only would you be penalized, so would all your coworkers. Can you imagine the culture

  • that would grow up around such a thing? That everybody is working really hard to make sure

  • that nobody ever does anything in any way better because then we'll all be in trouble.

  • That phenomenon was so widespread in the 19th Century, they had a name for it. They called

  • it "soldiering". That all the workers were intentionally soldiering on, trying to do

  • work as slow as possible so that nobody would get in trouble. Now, we laugh when we think

  • about that kind of thing happening in a factory. Because to us, the way that we manage physical

  • products, and just all regular general management, is light years beyond what was possible in

  • Fred Taylor's day.

  • But they also believed something else that I think maybe you'll find a little bit familiar.

  • They had this idea that what basically was the great man theory of work. That fundamentally,

  • the job of managers was to select the best possible person. Of course, this is the early

  • 20th Century.

  • So a great man of upstanding character with good integrity, the right attributes, put

  • them in the job and fundamentally leave them alone. Because if you just trust a great man

  • to figure out what needs to get done, they would figure it out.

  • Does that sound familiar? We still manage knowledge work and innovation work that exact

  • same way. We still believe in the great man theory of entrepreneurship and we believe

  • it especially about the great man software developers.

  • And yet, when we look back on this time, decades from now, I think we're gonna laugh at the

  • kinds of things that we do when we need to develop new products. It will seem as antique

  • to our future selves as Fred Taylor feels to us. Because I think that entrepreneurship

  • is management. It's just a different kind of management than the general management

  • that has been practiced since Fred Taylor's day.

  • So, we need to create a different paradigm for management that's not better than general

  • management. It's not worse than. It's simply a parallel discipline specifically for entrepreneurship.

  • And so, here's my attempt.

  • The first concept in the entrepreneurial management toolbox is this thing we call the "pivot".

  • Who's tired of hearing about pivots already? Anybody? OK, I apologize. In Silicon Valley,

  • everybody's hand is up, by the way. This word has become ridiculously overused. Believe

  • it or not, I saw this just the other day in the New Yorker magazine. Can you read this

  • caption? "I'm not leaving you. I'm pivoting to another man."

  • [laughter]

  • So this word started in Lean Startup and then it became this monster of an overused, overhyped

  • concept. Typical for Silicon Valley. We went from not knowing what the concept was to being

  • tired of hearing it and claiming that it's overhyped, without having passed through the

  • intervening stage of ever learning how to use it correctly. That's justthat's how

  • we operate with the hype-cycle in Silicon Valley. So, I'm sorry about that. I really

  • didn't intend.

  • But you can't understand anything about entrepreneurship unless you have a word for this concept, because

  • it is the universal constant of all successful startups. If you can get the real story of

  • what actually happened in the early stages of a company, you will find out that successful

  • startup founders do not, do not, have better ideas than the failed ones. Contrary to what

  • you see in the movies, most startup founders of successful companies had ludicrously bad

  • ideas at the beginning.

  • And what's amazing about the successful startup founders is not that they just persevered

  • indefinitely, but that they had this funny combination that when they run into difficulty,

  • it's not just that they gave up ship and went home. Neither did they persevere the plane

  • straight into the ground.

  • They do this thing we call the "pivot". By analogy to basketball, one foot firmly rooted

  • in what we've learned, changing one other thing about the business at a time. And the

  • premise of the Lean Startup is as follows: If we can reduce the time between pivots,

  • we can increase our odds of success before we run out of money.

  • See, the way you think about startup runway, is not how many months of burn do I have left?

  • It's fundamentally how many opportunities to pivot do I have left? And sure, we can

  • extend the runway by raising more money.

  • But we can also extend the runway by figuring out how to pivot sooner. And every day we

  • shave off that time is a magical extension of our runway by a proportional amount. Does

  • that make sense? OK, I'm getting at least a few nods. That's good.

  • So, to increase the odds of success, we need to figure out how can we pivot sooner. We

  • need to bring our focus to a validated learning. Anyone know this? This is the waterfall methodology

  • of software development. It's traditional in one of these talks when you're gonna beat

  • up on methodologies to call one the "waterfall methodology". So this is mine.

  • This is just Fred Taylor's idea as applied to software development. When I was trained

  • as an engineer in Silicon Valley, I was taught this as the manufacturing metaphor of software

  • development. You can imagine, incidentally, how pissed off I was when I found out that

  • they don't use this in manufacturing anymore. This is way obsolete.

  • So it's not clear to me what our excuse is in software development for copying an obsolete

  • model of manufacturing. But I understand why it's so appealing.

  • The idea is that since software is so intangible, we like to imagine our work travelling on

  • an assembly line, a virtual assembly line, from department to department. And if everybody

  • does their part and trusts everybody else to do their part, everything works out fine.

  • It's entertaining to beat up on the waterfall methodology because it has such a bad track

  • record. But it's important to understand that waterfall works as long as the solution

  • and the problem are both relatively well understood. So if we were building something that is fundamentally

  • similar as things we have built in the past, this works great.

  • If you're building a video game sequel, amen. If you're building the next iteration of a

  • product that zillions of people already use, that's fine. But entrepreneurship doesn't

  • deal with those circumstances. So it's basically a waste of time.

  • Now, when you do waterfall, you have this problem I call "achieving failure" where you

  • successfully build the wrong thing and you boast about how good you are at doing it.

  • My question is, if you go to a startup board meeting, or a milestone review meeting for

  • most new products, what do we talk about? Milestones, right. We are on track. We're

  • building features we said we were gonna build. We talk about our gross numbers likehey,

  • we have this many customers just like we said.

  • I remember being in a company once that was looking, had a plan. They said we were gonna

  • have this nice hockey stick-shaped growth. And we're on the nice, long flat part, and

  • everything's going according to plan. Sounds a little familiar, maybe.

  • And you're going to court like, the plan is genius. Like, nobody is using our product

  • as expected, as expected. But next week, it should turn up.

  • And how do you know if you were on the long, flat part and you're gonna just, or you're

  • on the hockey stick and you're gonna just coast indefinitely? I believe we can actually

  • answer those questions quantitatively. We'll get to that.

  • So, to me, we are bragging about how we're building a product that nobody wants. But

  • we're doing it on time and on budget. As if, I have this image of a general manager driving

  • a car off a cliff and while they're driving their like, "But I'm getting great gas mileage,"

  • right off the cliff. That's what startup failures mostly look like.

  • And I think that's true in big companies, too. Not that I would presume to talk about

  • you. But in other companies I've seen, for sure. So, in manufacturing, they abandoned

  • that linear way of working. That's why we call it Lean Startup by analogy to lean manufacturing.

  • These are two other unfortunately deceased men who made this possible. Deming is famous

  • for having said, "The customer is the most important part of the production line." By

  • which he meant everything that we do should be gauged to be decided by whether the customer

  • cares that we do it.

  • So if the thing is of high quality in the customer's eyes, that matters. But if we're

  • doing a lot of internal transport, with the meetings that we have, the specifications,

  • the customer doesn't care about any of that internal stuff. So let's try to eliminate

  • it.

  • When these ideas were handed down to me as a Silicon Valley engineer, they looked like

  • this. There's our very own guru of extreme programming, Kent Beck. You guys know Agile

  • very well, so I won't bother getting into it.

  • Suffice to say that all Agile methodologies have their origins inside the IT departments

  • of big companies. Every single one. And there's a reason for that. They are designed for situations

  • where it is the problem that's known, but the solution is unknown. And so, by building

  • something that is well-understood iteratively, we can increase the odds that the project

  • will be successful.

  • So, the classic -- Chrysler Corporation needs a new payroll system. Agile to the rescue.

  • But this isn't the world that we live in as startups either. If the customer is the most

  • important part of the assembly line, what do we do if we don't know who the customer

  • is? That in whose eyes should we judge our work? In extreme programming, which customer

  • should we sit down next to the engineers to tell them what to do?

  • The assumption of Agile and all previous management approaches is that there is somebody who can

  • give us an authoritative, definitive answer to design questions. And in entrepreneurship,

  • that assumption breaks down.

  • We are working on products where nobody knows what the customer wants. At best, we have

  • a theory, a hypothesis, a plan, a hope. And so, this is what Lean Startup looks like.

  • Now, at Lean Startup we have our own guru, Steve Blank. He's still alive, but I put him

  • in sepia tones just to be consistent.

  • [laughter]

  • Steve invented something called "customer development", which is an iterative process

  • of trying to figure out who your customer is, which we can merge in parallel with Agile

  • development to this company-wide feedback loop of learning and discovery. This changes

  • the unit of progress from making stuff to validated learning.

  • Let me try to illustrate what I mean. I created a company called IMVU in 2004. We make a 3-D

  • avatar instant messaging technology. And at that time, we wanted to be the next AOL back

  • when that was still cool. And we wanted to take over the hot, new social technology of

  • IM. We really thought that was the wave of the future.

  • Whoops. And here was our plan. See, everybody knows that instant messaging is a network

  • effects business, right? So, therefore, if you wanna get someone to switch from their

  • IM network to yours, it's kind of a pain 'cause they'd have to bring all their friends with

  • them. So there's high switching costs.

  • And therefore, IM isn't an industry characterized by high barriers to entry. That's the MBA

  • analysis of the instant messaging market. And we spent a lot of time figuring that out

  • at the whiteboard.

  • And we said, "Ah, we need a strategy. A strategy for avoiding that problem and here it is.

  • We'll create an instant messaging add-on that interoperates with all of the existing networks

  • and can bring 3-D avatar technology to your IM client. So we take your boring 2-D IM and

  • make it 3-D. Wow."

  • This is before 'Avatar' and the current 3-D craze. So we thought we were on to a real

  • trend. And so, here's the reason we got so excited about that strategy. It would be inherently

  • viral. Because when you would decide you wanna go 3D, you would have to be IM'ing with

  • somebody and they would automatically get a text link inserted into the chat stream

  • that they could just one-click, pick-up boom, IMVU installs. Now you're both in 3D.

  • Doesn't this seem like a good idea? Well, we met with investors at that time. The strategy

  • part of it, they're like, "That does sound very promising." And when I tell the stories

  • to MBAs now, I get a lot of nods, like "That is good stuff. I don't know what the hell

  • this guy's been talking about until now, but this I understand. This is strategy."

  • And the strategy actually is very good, except for the tiniest, tiniest problem, which is

  • that every single thing I just said is false. Customers actually don't have high switching

  • costs for IM. Their network effects are way overblown and our customers refused to invite

  • their friends. It was a total deal breaker.

  • We'd have customers come in an in-person usability test. We're paying them to be there. And we'd

  • be like, "OK, download our instant messaging add-on." The customer would be like, “What

  • is that?" "An instant messaging add-on. It interoperates with all your IM." And you gotta

  • picture of a 16- year old like, "What? Is it an IM client?" And we're like, "No, no.

  • You won't have to run a whole other IM client." They're like, "Why not?" Like, "Oh, it would

  • be so complicated to download." They're like, "Dude, I have like seven IM clients. What's

  • the big deal?" And we're like, "There are seven IM clients?"

  • [laughter]

  • So that was problem number one.

  • We're like, "Listen, we are paying you to be here. So how about you download this thing?

  • OK?" "All right. Fine." "Download the thing." OK. "Customize your avatar." They love this

  • part. "Like, ooh, that's really cool, interactive like that." Great. "OK, now you customize

  • your avatar. Invite one of your friends." "No way." "Why not?" "I don't know if this

  • thing is cool, yet and I'm not gonna invite my friends to something that turns out to

  • be lame."

  • See, I know people who are selling like business software are used to the concept of "mission

  • critical". We didn't understand that in our business, mission critical, like the law of

  • commandments of mission critical software, one of them needs to be like, "Do not make

  • teenager look lame in front of their friends." Total deal breaker.

  • They wouldn't do it. We were like, "We're paying you to be in this usability test."

  • And it's just like, "I'm not doing it. You can keep your money. I will not. It's not

  • worth it to me." And they kept saying things like, "Let me use it with -- let me try it

  • out first. And if it's cool, then I'll invite one of my friends." And we were like, "Oh,

  • OK." We're from the video game industry.

  • So we knew what that meant. That meant single-player mode. So we built another version of the product,

  • single-player mode. Allowed you to -- we had another teenager come in for a usability test.

  • "Hey, download this instant messaging add-on." "I don't know. What the hell is that?" "Just

  • do it." "OK." "Customize your avatar." "Oh, that's cool." "OK, try it by yourself."

  • And they could check out the avatar, dress it up, do the moves and the whole thing. Learn

  • how to use the chat bubbles. And then we're like, "OK, now invite one of your friends."

  • Teenager, "No way." "Why not?" "This thing is lame." And we're like, "But we told you

  • it was gonna be so lame."

  • I mean, we're supposed to be listening to customers, but they don't know what the hell

  • they want. And they told us to build this thing and we're like, "It'll be so cool once

  • you invite some of your friends." And they're like, "Listen, old man. I'm not doing it."

  • [laughter]

  • And we were really devastated. Okay.

  • So anyway, long story short, this was a total deal breaker. This strategy is completely

  • flawed in every respect because it's based on empirically incorrect facts.

  • Now, we wound up having to pivot the company and we created our own instant messaging network

  • and it all turned out fine. But I'd like you, if you would, just for a minute to sympathize

  • with me personally. OK? Because I was the engineer. I was the CTO of this company.

  • It was my job to write the software to do instant messaging interoperability. So I wrote,

  • I don't know, 25 thousand lines of code or something. I did it all Agile, refactored,

  • really elegantly structured if I do say so myself. Good unit test coverage, the whole

  • shebang. And all of my code got thrown out.

  • [pause]

  • The good code got thrown out and the bad code got thrown out. The well-factored code got

  • thrown out. The stuff I was proud to show my mom and the stuff that I wouldn't want

  • anyone to see at all was equally thrown out.

  • Because a [ ] of quality is if you don't know who the customer is then you don't know what

  • quality means. So failure is a great equalizer of quality. It all had to be thrown out.

  • And I was really depressed. Because you gotta understand, we had spent six months killing

  • ourselves to build this product. And we had spent I don't know how many hours of my life

  • that I can never get back arguing with each other about the following. Which bugs did

  • we absolutely, positively have to fix. And which ones could we live without? Sound familiar?

  • Which features just had to be in version one or which ones could we just maybe could maybe

  • postpone to a different release? That's what we spent all of our time doing.

  • And yet, we had this problem, which was that customers would not download our product.

  • Like, this product sucked. It was really buggy. It would crash your computer. I was really

  • embarrassed to have shipped it. And we almost didn't ship it, I was so embarrassed.

  • But then, I was actually relieved cause nobody found out how bad it was because nobody would

  • use it. And I was like, "Wait, something is not right here. Why am I relieved that nobody's

  • using the product? That doesn't seem right."

  • And long story short, my cofounders dragged me, kicking and screaming, to the realization

  • it was time to pivot. We had to throw that code away. And we created a standalone IM

  • network and we were much more successful, la di da.

  • But here's the thing. I had to make myself feel better somehow because I was like, "Gosh.

  • Would the company have been just as well off if I had spent the last six months on a beach

  • somewhere, having nice drinks and doing nothing?"

  • And I was, "Did I even need to be here given that all the work that I did was thrown away?"

  • Anyone feel like that's true? Anyone know what the excuse I used was to make myself

  • feel better?

  • You can shout it out. It's OK. I guess, yeah.

  • >>audience 1: You built a team.

  • >>Eric Ries: What's that?

  • >>audience 1: You built the team.

  • >>Eric Ries: We had the team at the beginning. What did they need me for? Why was it worth

  • having done this exercise in the first place? What's that?

  • [audience 2]: You learned something.

  • >>Eric Ries: Because I learned something. Thank you. The last excuse in the book. If

  • you've utterly failed to execute, you can always claim to have had a good learning experience.

  • At least you learned something. I mean, I don't tell you guys.

  • In general management, you claim to have learned something, you're likely to be fired. A general

  • manager who learned something -- one of two things is true. Either they didn't make a

  • very good plan, in which case, definitely should be fired. Or even worse, they made

  • a really good plan and failed to execute it. I'd definitely fire that guy.

  • So, I think it's natural that we have a little bit of an aversion to wanna just say

  • that we learned anything because that is very dangerous. But in entrepreneurship, failure

  • is, not only is failure an option, it's practically the only option. It's what happens when reality

  • intervenes with our plans.

  • >>audience 2: So, what did you learn?

  • >>Eric Ries: So here's what we learned specifically. We learned the hard way, that customers did

  • not wanna use our product to connect with their existing friends. They wanted to use

  • it to make new friends.

  • That doesn't seem like a very big deal. I mean, it's all a very modest change in semantics.

  • But from a code and product point of view, that is a radically different product. It

  • required a very different experience. And we didn't throw out every line of code. But

  • we had to throw out a lot.

  • The pivot was quite dramatic. And I made myself feel better with this whole learning story

  • until I asked myself the following question. I mean, literally, I was up nights once I

  • had this question asked to me.

  • Which was, "Wait a minute. If my goal of the last six months was to learn this important

  • thing about customers, why did it take six months? How come the word 'learning' is only

  • coming up now after we failed and we need an excuse? We never used the word 'learning',

  • not one time during those six months. All we ever did was argue about features and bugs."

  • And then I was like, "But would we have had the same learning if we'd built a slightly

  • different first product?" Like, for example, did we have to support all seven IM networks?

  • What if we'd supported only three? Would the learning value have been the same? Sure. Customers

  • won't download, so who cares? What if we'd supported only one network? Learning values

  • the same. Now, that's a lot of code between seven networks and one, that's a lot less

  • code that needed to be written.

  • But this is the thought that literally made me sick to my stomach. I'd say, "Wait a minute.

  • What if we had just created a single web page and in three hours created a photo mockup

  • of what the product was going to look like and said, 'Hey, download this amazing 3D avatar

  • instant messaging add-on.' And had a big download button. Would we even have had to create the

  • second page where we admit that we didn't build the product, or would a 404 have been

  • adequate?" Come on, it's the 404, obviously. Because nobody would download the product.

  • It was a deal breaker. Nobody wanted it. That meant that we didn't even need page two.

  • And that was really upsetting to me, personally. Why? Because I look at my business card and

  • what did it say? It said a lot of things, but all I saw was "guy who writes code." My

  • job is to make features.

  • So if I went home at the end of the day and I write good code, I had a good day. And now,

  • but if my goal is to learn this thing about customers, and I can do it without code, is

  • that my job?

  • Is it possible that something I could do in three hours is just as meritorious as something

  • that requires 25,000 lines of code? It didn't seem right.

  • But I think that's actually true. Fundamentally, startups exist to learn how to build a sustainable

  • business. We call it "validated learning" 'cause we have to back up that learning quantitatively.

  • Any old idiot can tell a good story.

  • But we need a system for rigorously assessing, "Are we actually learning how to build a sustainable

  • business?" And everything else is a complete and total waste of time, including our precious

  • code.

  • Now, in the lean manufacturing revolution, the first question they had to teach people

  • to ask was "what is the difference between value and waste"?

  • And in a factory, this is actually relatively straightforward. Value is the stuff that we

  • make. The customers want. And waste is everything else. But if our unit of progress is gonna

  • be learning, then our unit of value has become intangible and now we have an issue. Which

  • is -- OK, we can eliminate all the stuff that we do that doesn't contribute to learning.

  • So, we have this concept in Lean Startup called "minimum viable product", which is, what really

  • needs to be in that first version? And now we have a good answer. Only what is necessary

  • to learn whether our plan is correct or not. Everything else is extraneous.

  • But that's still a little bit vague. And so the next step in lean manufacturing was to

  • focus on cycle time. And so what that looks like is this. Very simple heuristic. This

  • is the flux capacitor of Lean Startup.

  • All we are as a software startup is a catalyst that turns ideas into code. When customers

  • interact with that code, they create data which we can choose to measure quantitatively

  • and qualitatively. And then if we want, we can learn impacting our next set of ideas.

  • This, we can use to put the concept of the pivot on a more rigorous foundation.

  • A pivot is one major turn through this feedback loop. And the heuristic for any kind of startup

  • advice that anyone wants to give you is really simple. Does it minimize total time through

  • this loop?

  • So I don't know about you, I go to a lot of startup talks, I read a lot of startup blogs.

  • All the advice is like this. "You know, it's really important to have great design. Design

  • always wins. Except craigslist didn't have very good design and neither did EBay. So

  • sometimes it's fine to have no design. But make sure its very scalable, cause you don't

  • want to be the next Friendster. Except that Facebook wasn't very scalable and it was fine.

  • So make sure you have good design and design doesn't matter. It's scalable, but not too

  • scalable."

  • It's not very helpful advice and if you go down the list, it's like make sure you raise

  • plenty of money, but not too much money. Make sure you have the right kind of people, but

  • not those other kind of people, but actually, sometimes those other kind of people are fine.

  • And we focus on all this contradictory stuff 'cause for any particular piece of advice,

  • I can find you somebody who followed that advice and then made a lot of money. I can

  • also find you somebody who didn't follow that advice and made a lot of money. I can find

  • you people who followed that advice and made no money and people who didn't follow that

  • advice. I can find you all four quadrants of a logical possibilities chart.

  • So, how do we know what advice to take and what not? I think this is the heuristic you

  • wanna use. If it gets us through this feedback loop on a sustainable basis faster, it's a

  • good idea. And if not, not.

  • There's a lot more, of course, to Lean Startup. There's a zillion things on this graph. You

  • can read them all on my blog, Startup Lessons Learned. Of course, you can buy a certain

  • book. I've heard it's coming out in the fall. It's really good.

  • All of these techniques, like continuous deployment, where we put software into production, like

  • 50 times a day on average. So, 20 minutes from the main trunk to production, no branches.

  • Things like net promoter score where we can evaluate in real time using a tracking survey,

  • what customers really think about our product. Everything you know about usability tests,

  • five whys, which is drawn from the Toyota production system.

  • Each of these techniques has -- they operate at one stage of the feedback loop, but they

  • have the net effect of minimizing total time. That's what the Lean Startup is about.

  • But I wanna mention one more really boring topic called "innovation accounting". See,

  • we've forgotten what accounting was designed for. I mean, we think of accounting as that

  • thing that the really boring people do to keep track of where the money goes, right?

  • That's pretty much what it is. It's just a ledger that says, "Where did all the money

  • go?"

  • But accounting was invented for a very different reason. It was invented to drive accountability

  • across departments. Because if you wanna have a large company with many different divisions,

  • you have to be able to hold the managers of those divisions accountable to some things

  • so that you know that they did a good job. General Motors, which invented most of our

  • modern management paraphernalia, had this concept.

  • When I first read this concept, I literally laughed out loud; I couldn't believe it. It

  • was called the Standard Volume. It was the ideal number of cars that General Motors should

  • sell, division by division, in an ideal year. And they actually had the math, and staff,

  • the macroeconomic staff to figure out, given all the macroeconomic data available, how

  • to translate the standard year into our coming actual year.

  • So they could go division by division and tell each manager, "Given that we're in a

  • recession, or the economy is booming, you should sell this number of Oldsmobiles. And

  • therefore, if you sell more than the standard number, you get a bonus. And if not, you failed."

  • And it's not fair if you didn't have that concept, then if it's a good year, all the

  • managers seem like they're doing well. And in a recession, everyone seems like they're

  • doing badly. You can't tell which manager actually made a difference.

  • Now when I read that concept, I laughed out loud because I was like, "Wait a minute. Are

  • you telling me there was a time when people could make forecasts about what was going

  • to happen in the future, and then it actually happened?"

  • I don't know about you. I have never in my whole life seen a forecast of anything that

  • turned out to be remotely accurate. No startup I have ever worked for has had a roadmap that

  • turned out to be remotely true. I have never seen a company say how many customers they

  • would have in the future and then deliver. Never seen it.

  • So to me, the idea of the standard volume is ridiculous. But I understand when you have

  • a sufficiently large company and you have a sufficiently long operating history, you

  • can do this. Maybe this sounds a little bit familiar.

  • So, if we're using accounting to drive accountability, but all of our accounting depends on having

  • a long operating history and a lot of customers, how do we drive accountability if there's

  • no customers yet?

  • If the CFO of a company, hypothetically speaking, gives a certain team a bunch of money and

  • sends them off to some remote location to do their work, like to Australia or something.

  • And then they hang out in Australia or whatever. And then a year later, they say, "What are

  • your results?" And the team says, "They're not very good, but we're on the brink of success."

  • How is the manager who gave them all that money supposed to know if A: They are in fact

  • on the brink of a success or they're just on the flat part of the hockey stick, or if

  • they've just been goofing off for a year? Or more likely, if they're just executing

  • a bad plan.

  • And at what kind of milestone should we hold them accountable to if we can't hold them

  • accountable to the gross numbers of customers? 'Cause that's fundamentally not fair. If we're

  • focusing on the gross numbers, incidentally, we might decide we're gonna do a lot of publicity

  • and PR and be like, "This thing is gonna be amazing," to drive customer awareness.

  • But we all know if you happen to find yourself on such a team, that that early awareness

  • is fundamentally lethal. But it's not fair to just say, "Well, just let them do whatever

  • and hope for the best." You guys know exactly how that turns out. So, what is the solution?

  • I think we can answer that question now with something I call "innovation accounting".

  • Here it is.

  • Instead of focusing on product milestones and gross numbers, we have three learning

  • milestones we can focus on. We have to take our attention away from the vanity metrics.

  • Vanity metrics are the numbers you put in a press release to make your competitors feel

  • bad. Like the total number of pages on the internet that you've indexed. I happen to

  • like that one a lot.

  • There was a time when we had a big index, number of in pages indexed battle. And it's

  • like, "We have four billion and you only have two billion." But like, what does that actually

  • tell you about the quality of somebody's business? Absolutely nothing.

  • They could be four billion really dumb pages. It could be one guy's website who's just really

  • excited about the number four billion. Or, it could be four billion people who each have

  • one crappy website.

  • If you read "TechCrunch", you're gonna see a zillion stories about "This company has

  • sent 400 messages through their platform." But is that 400 million people who are all

  • about to turn out, or one very excited customer? We don't know.

  • We used to have a competitor in IMVU that would report on the gross GDP of the value

  • of their whole user to user economy. And my CEO would sometimes come to me and be like,

  • "These guys have a four hundred million dollar GDP. What's our GDP?" I was like, "What does

  • that even mean in our context? If two users exchange some virtual currency, is that part

  • of the GDP? I don't know." It's a completely meaningless number, but it sure made us feel

  • bad.

  • I'm all for vanity metrics and press releases. Go to town. That's fine for making your competitors

  • feel bad.

  • But what happens when we use those numbers to guide our own business? Is that "when the

  • numbers go up, it's always because of what I was working on"? Everyone thinks I made

  • this feature last week and now the numbers went up. So obviously it's due to me. Of course,

  • the people in marketing feel like it's 'cause their new marketing campaign, etc. What happens

  • when the numbers go down?

  • Anyone ever been in that meeting? Oh, it's seasonal effects. Did anyone ever hear seasonal

  • effects used to describe numbers going up? Never in my career. It's always like, if it's

  • going up, it's features. If it's down, it's seasonal effects, or worse, those idiots in

  • marketing.

  • And over time, each us lives in our own private reality where the stuff I do makes numbers

  • go up and the stuff that those guys do make numbers go down. So is it any wonder that

  • we think each other are idiots?

  • Now, expand that organization larger and larger and larger as people are in ever more permanent

  • silos, speaking their own language, living in their own private reality. Is there any

  • wonder that they have trouble working together?

  • Maybe that sounds a little bit familiar. Okay. Just checking. So instead of that, we're gonna

  • use actionable metrics, which are about per customer behaviors, things that can be measured

  • at microscale.

  • And the first thing we're gonna do is establish the baseline. So now we can put the purpose

  • of the minimum viable product on a much more rigorous setting. Somewhere in our business

  • plan, there is a model that says, "Hey, if customers behave in this way, then we'll

  • have zillions of them over time." And we can't get into all the details on how to build those

  • models. Of course, there's a great book coming out. You can learn all about it.

  • In the meantime, what we wanna do is just figure out what are the real numbers for each

  • of those inputs at microscale? That's what the minimum viable product is for. So, if

  • there's some number, some spreadsheet somewhere, that says, "Hey, ten percent of customers

  • who come to our website should register for our product." Then we should have a big banner

  • in our office somewhere that's like, "We must have ten percent conversion or we die." And

  • then, we each have a minimum viable product as soon as possible to find out what that

  • number is today.

  • And most likely, when you do that experiment, the baseline will be horrible. Like, it'll

  • only be one percent and it's supposed to be ten percent. And like, oh my God. In general

  • management, that provokes a crisis cause now we failed and uh-oh. There's this thing called

  • the "audacity of zero", which is how much easier it is to raise money and get people

  • excited when you have no results. Or having zero dollars of revenue in a startup is a

  • great time to raise money. Having one dollar of revenue is a disaster. 'Cause with zero,

  • it's like, "Well, why is it zero?" "'Cause we haven't launched." So, obviously it should

  • be zero. Everyone's like, "Oh, that makes sense."

  • God forbid you have one dollar of revenue, 'cause then they'd say, "Why is it only one

  • dollar? I thought this thing was gonna be an overnight success and now you're proving

  • to me that it isn't." So with zero you can always be an overnight success. With any other

  • number you're screwed.

  • But we need to change that. We need to say, "Finding out the truth of where we are right

  • now is progress. It's a milestone that we should celebrate." And then we do step two,

  • which is we tune the engine. We make product development changes that are not designed

  • to drive huge gross numbers, but to make those conversion numbers go from the horrible baseline

  • to the ideal in our business plan.

  • And whenever I've done this with teams, I've only ever seen two cases. Case one, it's supposed

  • to be one percent. It's one percent but it's gotta be ten percent. So, a few iterations

  • in, it's one percent, three percent, six percent, six and a half percent, seven and a half percent.

  • Now, it's not ten percent yet. So the model isn't exactly working, but you can say, "Are

  • we gonna get there?" Yeah, probably. Each thing that we do seems to drive the number

  • up a little bit. We seem to be heading in the right direction. We're split testing to

  • make sure that the changes we're making are in fact driving the change. It's all good.

  • Here's situation number two. It's one percent, three percent, three and a half percent, 3.75

  • percent, 3.8 percent, 3.81 percent. Now, the numbers are going up every time. So it's not

  • like the numbers are going down. It's not like it's zero. But you might ask yourself

  • a question four, five, six months into hitting that asymptote. Are we ever gonna beat ten

  • percent? I think it's safe to conclude the answer is no.

  • Of course, theoretically, it is possible. The next iteration will be that magic one

  • more feature that gets you to ten percent. But in reality, that's not the case.

  • When the team gets to the point where hitting that diminishing returns, everybody knows

  • you're not gonna make it and you enter the land of death march. So instead, I recommend

  • we do three. We schedule the meeting in advance. That three months from now, six, whatever

  • it is, we're gonna have a meeting to decide whether to pivot or persevere.

  • And by that meeting, we will have the data about whether our efforts to tune the engine

  • are working or hitting diminishing returns. And so, we have all these concepts in entrepreneurship,

  • like product market fit, that are very vague. This system allows us to put those concepts

  • on a much more quantitative basis. We can't turn whether to pivot into a formula.

  • I can't tell you what to do. I still rely on human judgment, just like science does.

  • But if we make specific predictions, if we use innovation accounting as our accountability

  • model, then we can be training our judgment to get better over time, just like in science.

  • So, don't do product development astrology. Do product development science. I left a bunch

  • of questions unanswered 'cause we only have a short time together. Like, how do you know

  • specifically when to pivot?

  • What's the relationship between our vision, our strategy and our product? What exactly

  • should we measure in each of the engines of growth? How is it that products grow? How

  • do we know if we're on that hockey stick, or on the long, flat part forever? How do

  • we test if we're creating value?

  • What specific features should be in the MVP? Can we go faster? The answers to these questions

  • and so many more are in the new book coming out in the fall, called "The Lean Startup".

  • You can, of course, preorder it at lean.st.

  • Thank you very, very much for doing so. I'll just give you my contact information. Please

  • be in touch if I can be helpful in any way. We have a brand new website, which is itself

  • a minimum viable product about theleanstartup.com. Please check it out. We would love your feedback.

  • And you are all officially invited to the Startup Lessons Learned conference, which

  • is gonna be May 23rd in San Francisco, but we also simulcast. Last year, we were in 50

  • cities.

  • So presumably we'll be in New York, too. I hope if you can make it, you will drop me

  • a line. And if this proves in any way helpful, I hope you'll email me and tell me about it.

  • Thank you all very much.

  • [applause]

  • So we have time for a few questions? OK, let her rip. If I stumped all of Google, I'm gonna

  • be pretty proud of myself. That's going right on Twitter.

  • [pause]

  • Sweet.

  • [pause]

  • >>Female Audience Member #1: So, I just wanted to touch on something that you mentioned is

  • reviewed too many times; the pivot.

  • >>Eric Ries: Uh-huh.

  • >>Female Audience Member #1: I have trouble understanding exactly how much work to put

  • in for the first pivot. I think the second and the third might be a little bit more,

  • OK, maybe not. [laughs] But just starting off, like how much work should you really

  • put in for that first pivot?

  • >>Eric Ries: There's no way to answer that question in general, honestly.

  • You have to put yourself into a position where the team will know if it's working or not

  • working. And the problem is that most teams have a plan, which is basically to ship it

  • and see what happens.

  • And the problem with ship it and see what happens, you can feel like you're being very

  • agile, but you're guaranteed to succeed at seeing what happens. And so, you'll therefore

  • always feel like it was worth doing and you'll feel like you're on the right track no matter

  • what.

  • The only way to get yourself into a position where you have to pivot is to make specific,

  • concrete predictions ahead of time that if they turn out to be wrong, will actually call

  • your theory into doubt.

  • And the issue is that we all know that most projections for new products are complete

  • BS. You have to tell the CFO, or whoever, that you're gonna have a zillion trillion

  • customers in year five. Otherwise you won't get the money to do your project.

  • But we know that we just made those projections up. So when they don't prove to be correct,

  • we're like, "Well, that doesn't prove that our vision is wrong. It just proves that it

  • took longer than we expected." So, yeah, the hockey stick is still gonna happen, but it's

  • taking longer.

  • If we do innovation accounting and we make very specific per customer behavior predictions

  • -- like one thing we'll often have people do is sell the magic version of their product

  • on a landing page somewhere.

  • And it's like, don't even say what the product, like how it works. Just say the benefit that

  • it gives you and see if you can get people to sign up. If people won't sign up for the

  • magic, they're certainly not going to sign up for your product, 'cause magic is always

  • better.

  • And if magic isn't even good enough, if the conversion rate on magic is too low, then

  • you already know that you have a problem. Not that that means that therefore give up,

  • go home. It just means there isn't already enough latent demand for what you're doing.

  • And so you're gonna be in a different kind of market then maybe you expected. Does that

  • help? So the minimum viable product truly is the minimum, the least amount required,

  • to get that first information. It's not, "Oh, if it doesn't turn out into an overnight success,

  • we give up."

  • And if you release that pressure to get it right the first time, like, I feel like a

  • lot of us feel like we have to do this circus act to make it seem like we could predict

  • the future. Like, one of those brilliant visionary, the next Steve Jobs. Not even Steve Jobs is

  • as good as Steve Jobs. That's a story that we've all been told.

  • And every company I've worked with internally, there are these genius heroes who always seem

  • to be able to get it right on the first try and everyone else is trying to emulate. But

  • when you meet the hero, you're like, "How do you do it?" If they're being honest with

  • you, they're like, "I actually don't know."

  • Or, "Actually that's not how it happened and it wasn't as easy as everybody thinks. Now

  • I feel incredible pressure to replicate that success again." And so, you can imagine the

  • negotiation that happens with the superstar over their next project. They don't ever want

  • to be in a position where they do something and it doesn't work, or they'll have to quit

  • and go to convince some other company they're a superstar.

  • I hear that happened recently. Anyway. Is that helpful?

  • >>Female Audience Member #1: Yeah.

  • >>Eric Ries: OK. Any other questions?

  • [pause]

  • >>Male Audience Member #4: So most of the rapid feedback you're talking about seems

  • to be very applicable to consumer applications where the cost of trying something in the

  • amount of time it takes to try something is pretty low. I will or will not sign up for

  • Twitter or Facebook or whatever the next thing is.

  • >>Eric Ries: Yeah.

  • >>Male Audience Member #4: How does it apply if it's a bigger thing? If it's an enterprise

  • sale or if it's a bigger commitment, do you just basically take the same process, but

  • the time scale is longer because the commitment process is longer for each step?

  • >>Eric Ries: Yes. I mean, that's the short answer. I mean, the long answer is my background's

  • in consumer internet. So I talk that way just naturally about large sample sizes and split

  • tests. Just the way that I, I can't help it. That's my whole career.

  • What's funny is that Steve Blank, who I mentioned earlier, has a great book called "The Four

  • Steps to the Epiphany", that I hope you all read. When he talks, his background is in

  • enterprise software. He gets this question too, all the time. Except when he gets the

  • question, people say, "Well, of course, this will work in enterprise software. But how

  • will it work on consumer internet?"

  • Because we just assume that the tactics that have worked in one industry don't work in

  • another. So the answer is truly, it's the principles that matter, not the tactics.

  • And so, the principle of the build-measure-learn feedback loop is cross-industry. So for example,

  • in consumer internet, because we're used to having large numbers of customers, we do all

  • this analytic stuff as a crutch. It's actually, it's actually -- it's because we have it worse

  • than the enterprise people.

  • When you have a lot of customers, you can't get to know any of them particularly well.

  • In fact, you just have, you have to rely on archetypes and summaries and assumptions.

  • When you have a small number of customers, it's a huge asset because you can know each

  • of them extremely well and the experiments that you do can have much higher fidelity.

  • So like, physicists don't get to ask electrons what they're thinking about doing. They're

  • not available for comment.

  • But when you're studying something that can actually interact with you, it's a whole different,

  • whole different ballgame. Question over here? Yeah.

  • >>Male Audience Member #5: What product should Google be pivoting on right now?

  • >>Eric Ries: What? What product should Google be pivoting on right now? Listen, I would

  • never presume to tell Google anything about that. I mean, look.

  • >>Male Audience Member #5: You were invited.

  • >>Eric Ries: What's that?

  • >>Male Audience Member #5: You were invited.

  • >>Eric Ries: I was invited. But look, but seriously. Like, the outside expert doesn't

  • know anything. You guys know your business way better than I do. And you know what products

  • need to be pivoted. You know. You don't need me to tell you.

  • The better question is, how on Earth are we gonna get to pivot them? Because we're stuck

  • in a management and accountability framework where pivoting is failure is a problem. So

  • for example, a certain Google product that I know especially well because it was competing

  • with something that I was working on at the time, I won't get into too much detail.

  • One of our cofounders at IMVU went to work on this product for Google. So, you're Google

  • people. You can talk about this. So they had a lot of inside information about what we

  • were doing available to them. And at first, we were really nervous because it meant that

  • we were gonna face competition from Google.

  • Here's what happened. Google spent two years working on that product. Spent, I can't imagine

  • how much money developing it. And when it finally came out, they launched it with a

  • big bang, put the Google brand right on it. And then when some things didn't go as expected

  • and it turned out to be an embarrassment, like, it got pulled and killed.

  • And the whole time, we were like, "What is going on over there?" 'Cause we were iterating

  • and changing constantly over that whole two year period. By the time they launched the

  • product, we felt like they'd launched a product that did what our product did two years ago.

  • And by giving it the big launch hype, putting the Google stamp on it, the inevitable problems,

  • the same problems we had had when we launched, but we were able to pivot because we had a

  • pathetically small number of customers and no one had ever heard of us.

  • That's a huge asset. It's actually a relief. 'Cause it means you can screw up. Nobody knows.

  • Nobody cares. Obscurity is a benefit. By putting the Google name on it, by claiming it was

  • the next big thing, Google put that team, I assume, in a position where there was no

  • way for them to pivot. It became an embarrassment to corporate, or somebody, and the thing got

  • pulled.

  • Now, [pause] that product could have pivoted. It was a really good product. It had a lot

  • of really good things about it. There was no physical reason why it couldn't pivot.

  • But two million dollars, two years and millions of dollars in, with all these expectations

  • and the Google name, I can't imagine the pressure they were under. I felt bad.

  • So, the right question is, what could Google have done to build that same product and put

  • it in a position where it could have pivoted? I actually think that leadership in today's

  • economy means creating platforms for experimentation for your teams.

  • I borrow that phrase from Scott Cooks, founder of Intuit, who's been a big doctor of Lean

  • Startup.

  • So if you want to be a general manager in a big company like Google and you want Google

  • to be more entrepreneurial, my point of view is it's on you, not on your team, on you to

  • give them a safe sandbox for experimentation.

  • So for a risky new product, do not, I would never put the Google brand name on it. For

  • shame.

  • And I would never talk to the press about it at all, if you can avoid it. And I would

  • try to have it have as small a number of customers as humanly possible while still doing that

  • innovation accounting.

  • Then, teams will pivot just fine. Nothing wrong with Googlers. It's a management problem.

  • In my humble opinion. Yes.

  • >>Male Audience Member #6: So let me follow up with that directly.

  • >>Eric Ries: OK.

  • >>Male Audience Member #6: Let's say you write a new mobile application and you post it to

  • the--

  • >>Eric Ries: Hypothetically speaking.

  • >>Male Audience Member #6: Yeah, yeah. The app store or the market. If you do that at

  • Google, with the Google name in a blog post, you'll get a hundred thousand downloads no

  • matter what it is.

  • >>Eric Ries: Yeah.

  • >>Male Audience Member #6: It can be almost anything. But it's true. And by virtue of

  • that, you are now, when people browse to categories, shopping, personal finance?

  • >>Eric Ries: You'll be number one.

  • >>Male Audience member #6: you will be up there. You will have that visibility and those

  • will lead to clicks and you will be featured.

  • And you will jump start in a way that you can't do if you're nobody and you put up an

  • app out there. You may very well just be in the noise and you'll never break out of that

  • no matter how great the product is.

  • >>Eric Ries: Right.

  • >>Male Audience Member #6: So, I mean having done this twice--

  • >>Eric Ries: Entrepreneurs never ask hypothetical questions, by the way. So I understand.

  • >>Male Audience Member #6: Yeah. Yeah. So I can tell you there's real value. I mean,

  • I know the successes that I've had are in large part because of having that name attached

  • to it.

  • And that initial jumpfrog, the initial leapfrog made up for, was market that I couldn't have

  • bought.

  • >>Eric Ries: Yeah, look, you get free marketing, but so what? Free marketing is worth so much

  • less than we think. Like, yes, that accelerated your process of success, but only because

  • you had the right product and it worked for your customers.

  • So putting rocket fuel into a rocket that has problems with it is not a good idea, right?

  • You accelerate too fast. The thing blows up. Now, sometimes you achieve liftoff because

  • you actually do have the right product.

  • But marketing, marketing dollars are not as hard to come by as they used to be. The really

  • great products today have an engine of growth that allows them to grow organically anyway.

  • So, yes. Google has huge advantages of putting their brand name on it. It can get you a lot

  • of downloads. But also, there's a huge liability about that because--

  • >>Male Audience Member #6: Well, that's a good question then. So why is it not OK for

  • Google to fail? Why not take risks and just fall on your face?

  • >>Eric Ries: Listen.

  • >>Male Audience Member #6: and admit it quickly and move on?

  • >>Eric Ries: If it was me, I would be celebrating failures and I would make those people heroes.

  • If it was up to me, but that's the culture that I live in now.

  • But see, failure is not what we want to celebrate. We wanna celebrate successful pivots away

  • from failure. And that's challenging because it's easy.

  • If you're charismatic, you can get resources for anything and you can ship stuff and get

  • people to use it and then you can engage in a ton of what I call "Success Theater", to

  • try to make it seem like you're a big success. And so, those people tend to get the celebrations,

  • whether they actually add any value or not. They're like a cancer on most organizations,

  • in my opinion.

  • But what do we do instead? We don't want to celebrate those people. We don't wanna just

  • celebrate people who fail because they accomplished nothing. So we have to have a system for evaluating

  • which failures were actually instructive and then we have to celebrate the learning and

  • what the learning turned into in the next try.

  • So yeah, if Google corporate was fine with people failing and having the Google name

  • be associated with nasty stuff, that'd be fine. But I just think that's unrealistic.

  • I mean, I wouldn't be that comfortable.

  • If I was Google, I would be launching those things under a different brand name altogether.

  • I wouldn't tell anybody that they're made by Google until they're actually proven to

  • be viable.

  • How do you think Apple does it. The stuff that we all consume and wait in line for,

  • we're the first people -- the first person who buys an iPad at the Apple store is the

  • first person to have used the iPad? Come on. That's my humble opinion. Helpful?

  • >>Male Audience Member #6: I didn't follow the last line.

  • >>Eric Ries: Then maybe I shouldn't have said it.

  • [laughter]

  • Cancel that. I do think giving teams a platform for experimentation, having clear analytics

  • for testing whether they're making progress or not, and celebrating pivots is the answer.

  • Whatever Apple does, who knows?

  • >>Thomas Sharon: All right. Last question.

  • >>Eric Ries: Make it count.

  • >>Thomas Sharon: Or this was the last question.

  • >>Eric Ries: Too much pressure? It's a Google-branded official question. It's going on the internet.

  • [pause]

  • >>Thomas Sharon: All right then.

  • >>Eric Ries: Ok, thank you all very much. I appreciate it.

  • [applause]

>>Thomas Sharon: Hi everyone. Thanks for coming. My name is Thomas Sharon. I'm a UX Researcher

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