The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses

by Eric Ries

It put itself in a position to interact with real customers and learn about their needs. For example, the business plan might call for discounted pricing, but how are customer perceptions o...

It allowed itself to be surprised when customers behaved in unexpected ways, revealing information Zappos might not have known to ask about. For exam...

Zappos’ initial experiment provided a clear, quantifiable outcome: either a sufficient number of customers would ...

It also put the company in a position to observe, interact with, and learn from rea...

Barlerin’s goal is to inspire her colleagues to make the world a better place. Looked at that way, her plan seems full of untested assumptions—and a lot of vision.

The first step would be to break down the grand vision into its component parts.

The two most important assumptions entrepreneurs make are what I call the value hypothesis and the growth hypothesis.

The value hypothesis tests whether a product or service really delivers value to custome...

the growth hypothesis, which tests how new customers will discover a product or service,

A likely way this program could expand is through viral growth. If that is true, the most important thing to measure is behavior: would the early participants actively spread the word to other employees?

The point is not to find the average customer but to find early adopters: the customers who feel the need for the product most acutely. Those customers tend to be more forgiving of mistakes and are especially eager to give feedback.

Put another way, what if all ten early adopters decline to volunteer again? That would be a highly significant—and very negative—result.

That doesn’t mean it’s time to give up; on the contrary, it means it’s time to get some immediate qualitative feedback about how to improve the program.

We don’t have to commission a survey or find new people to interview. We already have a cohort of people to talk to as well as knowledge about their actual behavior: the participants in the initial experiment.

In the Lean Startup model, an experiment is more than just a theoretical inquiry; it is also a first product.

Do consumers recognize that they have the problem you are trying to solve?

If there was a solution, would they buy it?

Would they buy it...

Can we build a solution for th...

The common tendency of product development is to skip straight to the fourth question and build a solution before confirmi...

“Until we could figure out how to sell and make the product, it wasn’t worth spending any engineering time on.”

The team assumed that customers would want to create the albums in the first place.

It assumed that event participants would upload photos to event albums created by friends or colleagues.

The Kodak Gallery team built a simple prototype of the event album. It lacked many features—so many, in fact, that the team wa...

What about features that were on the road map but that customers didn’t complain about? Maybe those features weren’t as important as they initially seemed.

“Success is not delivering a feature; success is learning how to solve the customer’s problem.”

Markets change all the time and our job is to change with them.”

As we’ve seen, even the seasoned managers and executives at the world’s best-run companies struggle to consistently develop and launch innovative new products.

At its heart, a startup is a catalyst that transforms ideas into products.

This Build-Measure-Learn feedback loop is at the core of the Lean Startup model.

The truth is that none of these activities by itself is of paramount importance. Instead, we need to focus our energies on minimizing the total time through this feedback loop.

To apply the scientific method to a startup, we need to identify which hypotheses to test.

I call the riskiest elements of a startup’s plan, the parts on which everything depends, leap-of-faith assumptions.

The two most important assumptions are the value hypothesis and t...

Once clear on these leap-of-faith assumptions, the first step is to enter the Build phase as quickly as possible with a minimum viable product (MVP).

The MVP is that version of the product that enables a full turn of the Build-Measure-Learn loop with a minimum amount of effort and the least amount of development time.

When we enter the Measure phase, the biggest challenge will be determining whether the product development efforts are leading to real progress. Remember, if we’re building something that nobody wants, it doesn’t much matter if we’re doing it on time and on budget.

Learning milestones are useful for entrepreneurs as a way of assessing their progress accurately and objectively; they are also invaluable to managers and investors who must hold entrepreneurs accountable.

Upon completing the Build-Measure-Learn loop, we confront the most difficult question any entrepreneur faces: whether to pivot the original strategy or persevere.

Although we write the feedback loop as Build-Measure-Learn because the activities happen in that order, our planning really works in the reverse order: we figure out what we need to learn, use innovation accounting to figure out what we need to measure to know if we are gaining validated learning, and then figure out what product we need to build to run that experiment and get that measurement.

Many things about it are remarkable, but I’d like to focus on only one: how Facebook was able to raise so much money when its actual usage was so small.1

By all accounts, what impressed investors the most were two facts about Facebook’s early growth. The first fact was the raw amount of time Facebook’s active users spent on the site.

This is an example of how a company can validate its value hypothesis—that customers find the product valuable.

The second impressive thing about Facebook’s early traction was the rate at which it had taken over its first few college campuses. The rate of growth was staggering:

In other words, Facebook also had validated its growth hypothesis. These two hypotheses represent two of the most important leap-of-faith questions any new startup faces.3

as we saw in Part One, startups need to conduct experiments that help determine what techniques will work in their unique circumstances.

For startups, the role of strategy is to help figure out the right questions to ask.

Every business plan begins with a set of assumptions.

Because the assumptions haven’t been proved to be true (they are assumptions, after all) and in fact are often erroneous, the goal of a startup’s early efforts should be to test them as quickly as possible.

The first challenge for an entrepreneur is to build an organization that can test these assumptions systematically.