Lean Startup

Назва книги: The Lean Startup

Автор: Eric Ries

Part 1. Vision

The five principles of Lean Startup

  1. Entrepreneurs are everywhere.
  2. Entrepreneurship is a management. A startup is an institution, not just a product, and so it requires a new kind of management specifically geared to its context of extreme uncertainty. In fact, as I will argue later, I believe “entrepreneur” should be considered a job title in all modern companies that depends on innovation for their future growth.
  3. Validated Learning. Startup exist not just to make staff, make money or serve customers. They exist to learn how to build sustainable business. The learning can be validated scientifically by running frequent experiments that allow entrepreneurs to test each element of their vision.
  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 preserve. All successful startup processes should be geared to accelerate that feedback loop.
  5. Innovation Accounting.

Entreprenurial Management

Building a startup is an exercise in institution building; thus, it necessarily involves management.

Unfortunately, too many startups business plans looks 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.

Products changes constantly through the process of optimization, what I call turning the engine. Less frequently, the strategy may have to change (called a pivot). However, the overarching vision rarely changes. Entrepreneurs are committed to seeing the startup through to that destination. Every setback is an opportunity for learning how to get what they want to go.

Startup Definition

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

Startups exist to learn how to build a sustainable business. This learning can be validated scientifically by running frequent experiments.

Startup are designed to confront situations of extreme uncertainty. To open up a new business that is an exact clone of an existing business all the way down to the business model, pricing, target customer, and product may be an attractive economic investment, but it is not a startup because its success depends only on execution – so much so that this success can be modeled with high accuracy. (This is why so many small business can be financed with simple bank loans, the level of risk and uncertainty is understood well enough that a loan office can assess its prospects).


True startup productivity: systematically figuring out the right things to build.

The question is not “Can this product be build?”. In the modern economy, almost any product that can be imagined can be built. The more pertinent questions are “Should this product be built?” and “Can we built a sustainable business model around this set of products and services?”.

Remember, planning is a tool that only works in the presence of a long and stable operating history. And yet, do any of us feel that the world around us is getting more and more stable every day? Changing such a mind-set is hard but critical to startup success.

Part 2: Steer (прискорення)

The products a startup builds are really experiment; the learning about how to build a sustainable business is the outcome of those experiments. For startups, that information is much more important that dollars, awards, or mentions in press, because it can influence and reshape the next set of ideas.

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 customers once they are using it. The growth hypothesis tests how new customers will discover a product or service.

The first challenge for an entrepreneur is to build an organization that can test these assumptions systematically. The second challenge, as in all entrepreneurial situations, is to perform that rigorous testing without loosing sight of company’s overall vision.


Early adopters are suspicious of something that is too polished: if it’s ready for everyone to adopt, how much advantage can one get by being early? As a result, additional features or polish beyond what early adopters demand is a form of wasted resources and time.

Deciding exactly how complex an MVP needs to be cannot be done formulaically. It requires judgement. Luckily, this judgement is not difficult to develop: most entrepreneurs and product development people dramatically overestimate how many features are needed in an MVP. When in doubt, simplify.

We must always ask: What if they (our customers) don’t care about design in the same way we do? We must be willing to set aside our traditional professional standards to start the process of validated learning as soon as possible.

As you consider building your own minimum viable product, let this simple rule suffice: remove any feature, process, or effort that doesn’t contribute directly to learning you seek.

Innovative Accounting (Measure)

The job of a startup is to:

  1. Build an MVP to measure where it is now.
  2. Experiment to improve the metrics.
  3. Decide whether to continue in the same direction or pivot in a new direction.

Defining the right metrics that actually matter to your business is critical. Before giving examples of good metrics, we’ll define common bad metrics startups choose.

Vanity Metrics

  • These common vanity metrics are all problematic:
  • Total number of anything – users, sales, actions in product
  • Money raised from investors
  • Press articles written about your company
  • Number of employees hired
  • Number of features added to product
  • Meetings scheduled
  • Emails written

Choosing Good Metrics

A good design is one that changes customer behavior for the better. You should establish metrics that can identify if you’re improving your product design (should it be a new feature or more intuitive UI).

You need to define metrics that really matter to your business, and measure improvements to that metric. The metrics that really matter vary from business to business. Often, they reflect your Value Hypothesis and your Growth Hypothesis.

For example, an app might aim for these metrics:

  • Value Hypothesis: Each new user will upload an average of 10 photos in the first week of using the app.
  • Growth Hypothesis: Every user who joins the app will refer 10 new visitors, 1 of whom will join as a new user (leading to virality).

The important part is that you need to believe these numbers are vital to the success of your business. Eric Ries suggests choosing the riskiest assumptions first – the metrics that you have the least confidence on, yet have the most impact to your business. For example, if your company is going to be supported by advertising, advertising rates are probably not the riskiest assumption – getting user engagement will be.


The goal of creating learning milestone is not to make the decision easy; it is to make sure that there is relevant data in the room when it comes time to decide.

It is not necessary to throw out everything that came before and start over. Instead, it’s about repurposing what has been built and what has ben learned to find a more positive direction.

Types of pivots

  1. Zoom-in Pivot- where a current feature becomes the new product. Votizen moved from voter social network to a voter contact product.
  2. Zoom-out Pivot – where the current product becomes a feature of the new product.
  3. Customer segment Pivot – where the target customers change.
  4. Customer needs Pivot – where the customer base remains the same, but the product changes to suit them more. Potbelly Sandwich shop started as an antique store in 1977. It decided to sell sandwiches to bolster traffic. It eventually pivoted to become a sandwich shop.
  5. Platform Pivot – where the product changes from a single use product to a platform for the other products.
  6. Business Architecture Pivot – Geoffrey Moore observed that most companies follow either a high margin, low volume model or a low margin, high volume product. Former is usually for B2B, and the latter is usually for B2C. A business architecture pivot is jumping from one to the other or vice-versa.
  7. Value Capture Pivot – where the way business makes money changes.
  8. The engine of Growth Pivot – where how business reaches new customers changes.
  9. Channel Pivot – where the distribution channel for the product changes.
  10. Technology Pivot – where the underlying technology to do the task changes.

Part 3. Accelerate

Todays companies must learn to master a management portfolio of sustainable and disruptive innovation. Modern companies must excel at doing multiple kinds of work in parallel.

Small Batches

It is counterintuitive, but smaller batches are much better for the lean startups. They appear inefficient but allow faster turnaround for the product leading to a more rapid iterative cycle. It helps in earlier detection of a problem as well as quick feedback from the customers. Toyota used the small-batch approach to compete with its much more capitalized American counterparts whose batch sizes were relatively bigger.

As soon as we formulate a hypothesis that we want to test, the product development team should be engineered to design and run this experiment as quickly as possible, using the smallest batch size that will get the job done. Remember that although we write 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 and then works backwards to see what product will work as an experiment to get that learning. Thus, it is not the customer, but rather our hypothesis about the customer, that pulls work from product development and other functions. Any other work is waste.

The wisdom of the Five Whys

The core idea of Five Whys is to tie investments directly to the prevention of the most problematic symptoms. The system takes its name from the investigative method of asking the question “Why?” Five times to understand what has happened (the root case).

At the root of every seemingly technical problem is human problem. Five Ways provides an opportunity to discover what that human problem might be. Taiichi Ohno gives the following example:

  1. Why did the machine stop? (There was an overload and the fuse blew)
  2. Why was there an overload? (The bearing was not sufficiently lubricated.)
  3. Why was is not lubricated sufficiently? (The lubrication pump was not pumping sufficiently).
  4. Why was is not pumping sufficiently? (Th shaft of the pump was worn and rattling)
  5. Why was the shaft worn out? (There was no strainer attached and metal scrap got in.).

Five Whys is a powerful organizational technique. Some of the engineers I have trained to use it believe that you can derive all the other Lean Startup techniques from the Five Whys. Coupled with working in small batches, it provides the foundation a company needs to respond quickly to problems as they appear, without over investing or overengineering.