The Lean Startup: The Million Copy Bestseller Driving Entrepreneurs to Success

by Eric Ries

After more than ten years as an entrepreneur, I came to reject that line of thinking. I have learned from both my own successes and failures and those of many others that it’s the boring stuff that matters the most.

Entrepreneurship is a kind of management. No, you didn’t read that wrong. We have wildly divergent associations with these two words, entrepreneurship and management. Lately, it seems that one is cool, innovative, and exciting and the other is dull, serious, and bland. It is time to look past these preconceptions.

This was the frustration that led us to try a radical new approach at IMVU, one characterized by an extremely fast cycle time, a focus on what customers want (without asking them), and a scientific approach to making decisions.

Throughout my career, I kept having the experience of working incredibly hard on products that ultimately failed in the marketplace.

These supposed fixes led to still more failure. So I read everything I could get my hands on and was blessed to have had some of the top minds in Silicon Valley as my mentors.

Back in 2004, Steve had just begun preaching a new idea: the business and marketing functions of a startup should be considered as important as engineering and product development and therefore deserve an equally rigorous methodology to guide them. He called that methodology Customer Development, and it offered insight and guidance to my daily work as an entrepreneur.

I began to search outside entrepreneurship for ideas that could help me make sense of my experience. I began to study other industries, especially manufacturing, from which most modern theories of management derive. I studied lean manufacturing, a process that originated in Japan with the Toyota Production System, a completely new way of thinking about the manufacturing of physical goods. I found that by applying ideas from lean manufacturing to my own entrepreneurial challenges—with a few tweaks and changes—I had the beginnings of a framework for making sense of them.

This line of thought evolved into the Lean Startup: the application of lean thinking to the process of innovation.

I would describe my experiences at IMVU, I was often met with blank stares or extreme skepticism. The most common reply was “That could never work!” My experience so flew in the face of conventional thinking that most people, even in the innovation hub of Silicon Valley, could not wrap their minds around it. Then I started to write, first on a blog called Startup Lessons Learned, and speak—at conferences and to companies, startups, and venture capitalists—to anyone who would listen. In the process of being called on to defend and explain my insights and with the collaboration of other writers, thinkers, and entrepreneurs, I had a chance to refine and develop the theory of the Lean Startup beyond its rudimentary beginnings.

My hope all along was to find ways to eliminate the tremendous waste I saw all around me: startups that built products nobody wanted, new products pulled from the shelves, countless dreams unrealized.

4. Build-Measure-Learn. The fundamental activity of a startup is to turn ideas into products, measure how customers respond, and then learn whether to pivot or persevere. All successful startup processes should be geared to accelerate that feedback loop.

5. Innovation accounting. To improve entrepreneurial outcomes and hold innovators accountable, we need to focus on the boring stuff: how to measure progress, how to set up milestones, and how to prioritize work. This requires a new kind of accounting designed for startups—and the people who hold them accountable.

Startups do not yet know who their customer is or what their product should be. As the world becomes more uncertain, it gets harder and harder to predict the future. The old management methods are not up to the task. Planning and forecasting are only accurate when based on a long, stable operating history and a relatively static environment. Startups have neither.

The second problem is that after seeing traditional management fail to solve this problem, some entrepreneurs and investors have thrown up their hands and adopted the “Just Do It” school of startups. This school believes that if management is the problem, chaos is the answer. Unfortunately, as I can attest firsthand, this doesn’t work either.

It may seem counterintuitive to think that something as disruptive, innovative, and chaotic as a startup can be managed o...

I believe that entrepreneurship requires a managerial discipline to harness the entrepreneurial opportunity we have been given.

The Lean Startup adapts these ideas to the context of entrepreneurship, proposing that entrepreneurs judge their progress differently from the way other kinds of ventures do. Progress in manufacturing is measured by the production of high-quality physical goods. As we’ll see in Chapter 3, the Lean Startup uses a different unit of progress, called validated learning.

A comprehensive theory of entrepreneurship should address all the functions of an early-stage venture: vision and concept, product development, marketing and sales, scaling up, partnerships and distribution, and structure and organizational design. It has to provide a method for measuring progress in the context of extreme uncertainty. It can give entrepreneurs clear guidance on how to make the many trade-off decisions they face: whether and when to invest in process; formulating, planning, and creating infrastructure; when to go it alone and when to partner; when to respond to feedback and when to stick with vision; and how and when to invest in scaling the business. Most of all, it must allow entrepreneurs to make testable predictions.

The Lean Startup asks people to start measuring their productivity differently. Because startups often accidentally build something nobody wants, it doesn’t matter much if they do it on time and on budget. The goal of a startup is to figure out the right thing to build—the thing customers want and will pay for—as quickly as possible.

Unfortunately, too many startup business plans look more like they are planning to launch a rocket ship than drive a car. They prescribe the steps to take and the results to expect in excruciating detail, and as in planning to launch a rocket, they are set up in such a way that even tiny errors in assumptions can lead to catastrophic outcomes.

One company I worked with had the misfortune of forecasting significant customer adoption—in the millions—for one of its new products. Powered by a splashy launch, the company successfully executed its plan. Unfortunately, customers did not flock to the product in great numbers. Even worse, the company had invested in massive infrastructure, hiring, and support to handle the influx of customers it expected. When the customers failed to materialize, the company had committed itself so completely that they could not adapt in time. They had “achieved failure”—successfully, faithfully, and rigorously executing a plan that turned out to have been utterly flawed.

The Lean Startup method, in contrast, is designed to teach you how to drive a startup. Instead of making complex plans that are based on a lot of assumptions, you can make constant adjustments with a steering wheel called the Build-Measure-Learn feedback loop. Through this process of steering, we can learn when and if it’s time to make a sharp turn called a pivot or whether we should persevere along our current path. Once we have an ...

Throughout the process of driving, you always have a clear idea of where you’re going. If you’re commuting to work, you don’t give up because there’s a detour in the road or you made a wrong turn. You re...

Products change constantly through the process of optimization, what I call tuning the engine. Less frequently, the strategy may have to change (called a pivot).

In real life, a startup is a portfolio of activities. A lot is happening simultaneously: the engine is running, acquiring new customers and serving existing ones; we are tuning, trying to improve our product, marketing, and operations; and we are steering, deciding if and when to pivot. The challenge of entrepreneurship is to balance all these activities. Even the smallest startup faces the challenge of supporting existing customers while trying to innovate. Even the most established company faces the imperative to invest in innovation lest it become obsolete. As companies grow, what changes is the mix of these activities in the company’s portfolio of work.

Entrepreneurship is management. And yet, imagine a modern manager who is tasked with building a new product in the context of an established company. Imagine that she goes back to her company’s chief financial officer (CFO) a year later and says, “We have failed to meet the growth targets we predicted. In fact, we have almost no new customers and no new revenue. However, we have learned an incredible amount and are on the cusp of a breakthrough new line of business. All we need is another year.” Most of the time, this would be the last report this intrapreneur would give her employer. The reason is that in general management, a failure to deliver results is due to either a failure to plan adequately or a failure to execute properly. Both are significant lapses, yet new product development in our modern economy routinely requires exactly this kind of failure on the way to greatness. In the Lean Startup movement, we have come to realize that these internal innovators are actually entrepreneurs, too, and that entrepreneurial management can help them succeed; this is the subject of the next chapter.

A startup is a human institution designed to create a new product or service under conditions of extreme uncertainty.

After many years as an entrepreneur, I started to worry about measuring progress in this way. What if we found ourselves building something that nobody wanted? In that case what did it matter if we did it on time and on budget?

We must learn the truth about which elements of our strategy are working to realize our vision and which are just crazy. We must learn what customers really want, not what they say they want or what we think they should want. We must discover whether we are on a path that will lead to growing a sustainable business.

IM is an example of a market that involves strong network effects. Like most communication networks, IM is thought to follow Metcalfe’s law: the value of a network as a whole is proportional to the square of the number of participants. In other words, the more people in the network, the more valuable the network.

The common wisdom was that it was more or less impossible to bring a new IM network to market without spending an extraordinary amount of money on marketing. The reason for that wisdom is simple. Because of the power of network effects, IM products have high switching costs. To switch from one network to another, customers would have to convince their friends and colleagues to switch with them.

Because of the near impossibility of bringing a new IM network to market, we decided to build an IM add-on product that would interoperate with the existing networks.

I wish I could say that I was the one to realize our mistake and suggest the solution, but in truth, I was the last to admit the problem. In short, our entire strategic analysis of the market was utterly wrong.

We figured this out empirically, through experimentation, rather than through focus groups or market research. Customers could not tell us what they wanted; most, after all, had never heard of 3D avatars. Instead, they revealed the truth through their action or inaction as we struggled to make the product better.

We had a mental model for how people used software that was years out of date, and so eventually, painfully, after dozens of meetings like that, it started to dawn on us that the IM add-on concept was fundamentally flawed.3

Our customers did not want an IM add-on; they wanted a stand-alone IM network. They did not consider having to learn how to use a new IM program a barrier; on the contrary, our early adopters used many different IM programs simultaneously. Our customers were not intimidated by the idea of having to take their friends with them to a new IM network; it turned out that they enjoyed that challenge. Even more surprising, our assumption that customers would want to use avatar-based IM primarily with their existing friends was also wrong. They wanted to make new friends, an activity that 3D avatars are particularly well suited to facilitating. Bit by bit, customers tore apart our seemingly brilliant initial strategy.

When it came time to pivot and abandon that original strategy, almost all of my work—thousands of lines of code—was thrown out. I felt betrayed.

I had committed the biggest waste of all: building a product that our customers refused to use. That was really depressing.

Lean thinking defines value as providing benefit to the customer; anything else is waste.

Anything we had done during those months that did not contribute to our learning was a form of waste. Would it have been possible to learn the same things with less effort? Clearly, the answer is yes.

For one thing, think of all the debate and prioritization of effort that went into features that customers would never discover. If we had shipped sooner, we could have avoided that waste. Also consider all the waste caused by our incorrect strategic assumptions. I had built interoperability for more than a dozen different IM clients and networks. Was this really necessary to test our assumptions? Could we have gotten the same feedback from our customers with half as many networks? With only three? With only one? Since the customers of all IM networks found our product equally unattractive, the level of learning would have been the same, but our effort would have been dramatically less.

Here’s the thought that kept me up nights: did we have to support any networks at all? Is it possible that we could have discovered how flawed our assumptions were without building anything? For example, what if we simply had offered customers the opportunity to download the product from us solely on the basis of its proposed features before building anything? Remember, almost no customers were willing to use our original product, so we wouldn’t have had to do much apologizing when we failed to deliver. (Note that this is different from asking customers what they want. Most of the time customers don...

I’ve come to believe that learning is the essential unit of progress for startups. The effort that is not absolutely necessary for learning what customers want can be eliminated. I call this validated learning

As we’ve seen, it’s easy to kid yourself about what you think customers want. It’s also easy to learn things that are completely irrelevant. Thus, validated learning is backed up by empirical data collected from real customers.

Certainly our stories of failure were entertaining, and we had fascinating theories about what we had done wrong and what we needed to do to create a more successful product. However, the proof did not come until we put those theories into practice and built subsequent versions of the product that showed superior results with actual customers.

The next few months are where the true story of IMVU begins, not with our brilliant assumptions and strategies and whiteboard gamesmanship but with the hard work of discovering what customers really wanted and adjusting our product and strategy to meet those desires.

We adopted the view that our job was to find a synthesis between our vision and what customers would accept; it wasn’t to capitulate to what customers thought they wante...

Aligned with a superior strategy, our product development efforts became magically more productive—not because we were working harder but because we were working smarter, aligned with our customers’ real needs. Positive changes in metrics became the quantitative validation that our learning was real. This was critically important because we could show our stakeholders—employees, investors, and ourselves—that we were making genuine progress, not deluding ourselves.

It is also the right way to think about productivity in a startup: not in terms of how much stuff we are building but in terms of how much validated learning we’re getting for our efforts.4

For example, in one early experiment, we changed our entire website, home page, and product registration flow to replace “avatar chat” with “3D instant messaging.” New customers were split automatically between these two versions of the site; half saw one, and half saw the other. We were able to measure the difference in behavior between the two groups. Not only were the people in the experimental group more likely to sign up for the product, they were more likely to become long-term paying customers. We had plenty of failed experiments too. During one period in which we believed that customers weren’t using the product because they didn’t understand its many benefits, we went so far as to pay cu...