The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses
Author: Ries, Eric
Ries, Eric. The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses. The Crown Publishing Group, 2011. Kindle file.
Notes by: Jacopo Perfetti.

Steve Blank
in 2004,
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
He called that methodology Customer Development,
the Lean Startup: the application of lean thinking to the process of innovation.
all three parts of this book, are as follows:
1. Entrepreneurs are everywhere.
The concept of entrepreneurship includes anyone who works within my definition of a startup:
2. Entrepreneurship is management.
3. Validated learning.
Startups exist
to learn how to build a sustainable business.
4. Build-Measure-Learn.
startup is to turn ideas into products, measure how customers respond, and then learn whether to pivot or persevere.
5. Innovation accounting.
we need to focus on the boring stuff: how to measure progress, how to set up milestones, and how to prioritize work.
Why Startups Fail
The first problem is the allure of a good plan, a solid strategy,
Startups do not yet know who their customer is or what their product should be.
it gets harder and harder to predict the future.
Part One: Vision

1. Start > 15/234
1. Start > 15/239
many entrepreneurs take a “just do it” attitude, avoiding all forms of management, process, and discipline. Unfortunately, this approach leads to chaos more often than it does to success.
1. Start > 16/244
There are more entrepreneurs operating today than at any previous time in history.
1. Start > 17/250
1. Start > 18/251
we lack a coherent management paradigm for new innovative ventures,
1. Start > 18/252
for every success there are far too many failures:
1. Start > 18/254
What makes these failures particularly painful is
1. Start > 18/255
a colossal waste of our civilization’s most precious resource: the time, passion, and skill of its people.
1. Start > 18/265
the Lean Startup uses a different unit of progress, called validated learning.
1. Start > 20/284
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.
1. Start > 20/285
the Lean Startup is a new way of looking at the development of innovative new products that emphasizes fast iteration and customer insight, a huge vision, and great ambition, all at the same time.
1. Start > 20/294
Startups have a similar engine that I call the engine of growth.
1. Start > 21/296
Every new version of a product, every new feature, and every new marketing program is an attempt to improve this engine of growth.
1. Start > 21/307
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.
1. Start > 22/314
The Lean Startup method, in contrast,
1. Start > 22/314
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.
1. Start > 22/316
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.
1. Start > 22/320
Startups also have a true north, a destination in mind:
1. Start > 22/321
I call that a startup’s vision.
1. Start > 22/321
To achieve that vision, startups employ a strategy,
1. Start > 22/322
The product is the end result of this strategy
1. Start > 23/324
Products change constantly through the process of optimization, what I call tuning the engine.
1. Start > 23/325
However, the overarching vision rarely changes.

2. Define > 25/345
general managers,
2. Define > 25/345
who are tasked with creating new ventures or product innovations.
2. Define > 25/347
they are visionaries. Like the startup founders
2. Define > 26/366
Entrepreneurs who operate inside an established organization sometimes are called “intrapreneurs”
2. Define > 27/374
what a startup is:
2. Define > 27/375
A startup is a human institution designed to create a new product or service under conditions of extreme uncertainty.
2. Define > 29/400
In 2009, a startup decided to try something really audacious. They wanted to liberate taxpayers from expensive tax stores by automating the process of collecting information typically found on W-2 forms
2. Define > 29/404
After numerous conversations with potential customers, the team lit upon the idea of having customers take photographs of the forms directly from their cell phone.
2. Define > 30/411
the new product—called SnapTax—provides a magical experience.
2. Define > 30/413
350,000 downloads in the first three weeks.
2. Define > 30/414
2. Define > 30/414
SnapTax was developed by Intuit, America’s largest producer of finance, tax, and accounting tools
2. Define > 30/418
Yet they are entrepreneurs.
2. Define > 30/420
Usually, companies like Intuit fall into the trap described in Clayton Christensten’s The Innovator’s Dilemma: they are very good at creating incremental improvements to existing products and serving existing customers, which Christensen called sustaining innovation, but struggle to create breakthrough new products—disruptive innovation—that can create new sustainable sources of growth.
2. Define > 31/427
they started with a team of five. What allowed the SnapTax team to innovate was
2. Define > 31/428
a process deliberately facilitated by Intuit’s senior management.
2. Define > 31/428
Innovation is a bottoms-up, decentralized, and unpredictable thing, but that doesn’t mean it cannot be managed.
2. Define > 31/431
cultivating entrepreneurship is the responsibility of senior management.
2. Define > 31/434
Intuit’s founder,
2. Define > 31/435
Scott Cook,
2. Define > 32/441
2. Define > 32/441
was frustrated.
2. Define > 32/442
too many of its new products were failing.
2. Define > 32/443
he came to a difficult conclusion: the prevailing management paradigm he and his company had been practicing was inadequate to the problem of continuous innovation in the modern economy.
2. Define > 33/450
They are working to build entrepreneurship and risk taking into all their divisions.
2. Define > 34/470
believe a company’s only sustainable path to long-term economic growth is to build an “innovation factory” that uses Lean Startup techniques to create disruptive innovations on a continuous basis.
2. Define > 35/486
Leadership requires creating conditions that enable employees to do the kinds of experimentation that entrepreneurship requires.

3. Learn > 37/497
I started to worry about measuring progress in this way. What if we found ourselves building something that nobody wanted?
3. Learn > 38/509
We must learn what customers really want, not what they say they want or what we think they should want.
3. Learn > 38/511
In the Lean Startup model, we are rehabilitating learning with a concept I call validated learning. Validated learning is not after-the-fact rationalization or a good story designed to hide failure. It is a rigorous method for demonstrating progress when one is embedded in the soil of extreme uncertainty in which startups grow.
3. Learn > 39/527
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.
3. Learn > 47/629
I had committed the biggest waste of all: building a product that our customers refused to use.
3. Learn > 47/638
Could we have learned those lessons earlier if I hadn’t been so focused on making the product “better” by adding features and fixing bugs?
3. Learn > 47/640
In other words, which of our efforts are value-creating and which are wasteful?
3. Learn > 48/651
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.
3. Learn > 48/652
Also consider all the waste caused by our incorrect strategic assumptions.
3. Learn > 49/657
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?
3. Learn > 49/659
that this is different from asking customers what they want. Most of the time customers don’t know what they want in advance.)
3. Learn > 49/664
learning is the essential unit of progress for startups.
3. Learn > 49/665
validated learning because it is always demonstrated by positive improvements in the startup’s core metrics.
3. Learn > 50/678
our job was to find a synthesis between our vision and what customers would accept;
3. Learn > 51/684
became magically more productive—not because we were working harder but because we were working smarter, aligned with our customers’ real needs.
3. Learn > 52/701
This is true startup productivity: systematically figuring out the right things to build.
3. Learn > 52/706
is often easier to raise money or acquire other resources when you have zero revenue, zero customers, and zero traction than when you have a small amount.
3. Learn > 52/707
Zero invites imagination, but small numbers invite questions about whether large numbers will ever materialize.
3. Learn > 54/735
the tactics it illustrates: launching a low-quality early prototype, charging customers from day one, and using low-volume revenue targets as a way to drive accountability.
3. Learn > 54/736
These are useful techniques, but they are not the moral of the story. There are too many exceptions.
3. Learn > 55/743
Instead, the way forward is to learn to see every startup in any industry as a grand experiment.
3. Learn > 55/743
The question is not “Can this product be built?”
3. Learn > 55/744
The more pertinent questions are “Should this product be built?” and “Can we build a sustainable business around this set of products and services?”
3. Learn > 55/747
In the Lean Startup model,
3. Learn > 55/747
everything a startup does—is understood to be an experiment designed to achieve validated learning.

4. Experiment > 56/754
they have followed the “let’s just ship a product and see what happens” plan. I call this the “just do it” school
4. Experiment > 56/758
if you cannot fail, you cannot learn.
4. Experiment > 57/763
Think Big, Start Small
4. Experiment > 57/771
Zappos began with a tiny, simple product. It was designed to answer one question above all: is there already sufficient demand for a superior online shopping experience for shoes?
4. Experiment > 58/774
To sell the shoes, Zappos had to interact with customers: taking payment, handling returns, and dealing with customer support. This is decidedly different from market research.
4. Experiment > 58/776
By building a product instead, albeit a simple one, the company learned much more:
4. Experiment > 58/777
1. It had more accurate data about customer demand because it was observing real customer behavior, not asking hypothetical questions.
4. Experiment > 58/778
2. It put itself in a position to interact with real customers and learn about their needs.
4. Experiment > 58/780
3. It allowed itself to be surprised when customers behaved in unexpected ways, revealing information Zappos might not have known to ask about.
4. Experiment > 61/817
Here’s what it might look like if
4. Experiment > 61/817
treat her project as an experiment.
4. Experiment > 61/818
Break It Down
4. Experiment > 61/819
break down the grand vision into its component parts.
4. Experiment > 61/819
The two most important assumptions entrepreneurs make are what I call the value hypothesis and the growth hypothesis.
4. Experiment > 61/820
The value hypothesis tests whether a product or service really delivers value to customers once they are using it.
4. Experiment > 61/826
the growth hypothesis, which tests how new customers will discover a product or service,
4. Experiment > 62/828
the most important thing to measure is behavior: would the early participants actively spread the word to other employees?
4. Experiment > 62/833
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.
4. Experiment > 62/834
Next, using a technique I call the concierge minimum viable product
4. Experiment > 62/835
could make sure the first few participants had an experience that was as good as she could make it, completely aligned with her vision.
4. Experiment > 63/848
This entire experiment could be conducted in a matter of weeks,
4. Experiment > 63/850
Even when experiments produce a negative result, those failures prove instructive and can influence the strategy.
4. Experiment > 63/850
what if no volunteers can be found who are experiencing
4. Experiment > 63/852
it’s time to pivot
4. Experiment > 63/853
4. Experiment > 63/855
If this or any other experiment is successful, it allows the manager to get started with his or her campaign: enlisting early adopters, adding employees to each further experiment or iteration, and eventually starting to build a product.
4. Experiment > 64/860
Mark Cook is Kodak Gallery’s vice president of products,
4. Experiment > 66/897
As Cook says, “Success is not delivering a feature; success is learning how to solve the customer’s problem.”
Part Two: Steer
How Vision Leads to Steering
As customers interact with those products, they generate feedback and data.
The feedback is both qualitative (such as what they like and don’t like) and quantitative (such as how many people use it and find it valuable).
For startups, that information is much more important
because it can influence and reshape the next set of ideas.
We can visualize this three-step process with this simple diagram:
This Build-Measure-Learn feedback loop is at the core of the Lean Startup model.
we need to focus our energies on minimizing the total time through this feedback loop.
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.
creating a MVP requires extra work: we must be able to measure its impact.
The method I recommend is called innovation accounting, a quantitative approach that allows us to see whether our engine-tuning efforts are bearing fruit.
It also allows us to create learning milestones,
Finally, and most important, there’s the pivot.
If we’ve discovered that one of our hypotheses is false, it is time to make a major change to a new strategic hypothesis.
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.

5. Leap > 81/1047
5. Leap > 81/1047
Every business plan begins with a set of assumptions.
5. Leap > 81/1049
the assumptions haven’t been proved to be true
5. Leap > 81/1049
and in fact are often erroneous, the goal of a startup’s early efforts should be to test them as quickly as possible.
5. Leap > 81/1053
Many assumptions in a typical business plan are unexceptional. These are well-established facts drawn from past industry experience
5. Leap > 81/1056
we assume that customers have a significant desire to use a product like ours,
5. Leap > 81/1057
Acting as if these assumptions are true is a classic entrepreneur superpower. They are called leaps of faith precisely because the success of the entire venture rests on them.
5. Leap > 82/1065
That is their goal: to make the business seem less risky. They are used to persuade investors, employees, or partners to sign on.
5. Leap > 83/1079
There is nothing intrinsically wrong with basing strategy on comparisons to other companies and industries.
5. Leap > 83/1081
Randy Komisar,
5. Leap > 83/1081
book Getting to Plan B
5. Leap > 83/1081
uses a framework of “analogs” and “antilogs” to plot strategy.
5. Leap > 83/1082
using the iPod as an example.
5. Leap > 83/1084
Will people listen to music in a public place using earphones?
5. Leap > 84/1085
Sony’s Walkman was the analog.
5. Leap > 84/1086
although people were willing to download music, they were not willing to pay for it. “Napster was an antilog.
5. Leap > 86/1116
Steve Blank’s famous phrase, “get out of the building” and start learning.
5. Leap > 86/1118
the Japanese term genchi gembutsu,
5. Leap > 86/1119
“go and see for yourself”
5. Leap > 86/1120
so that business decisions can be based on deep firsthand knowledge.
5. Leap > 88/1149
the facts that we need to gather about customers, markets, suppliers, and channels exist only “outside the building.”
5. Leap > 88/1151
The first step in this process is to confirm that your leap-of-faith questions are based in reality, that the customer has a significant problem worth solving.
5. Leap > 89/1164
The goal of such early contact with customers is
5. Leap > 89/1165
to clarify at a basic, coarse level that we understand our potential customer and what problems they have.
5. Leap > 89/1166
we can craft a customer archetype,
5. Leap > 90/1175
the customer archetype is a hypothesis, not a fact.
5. Leap > 90/1178
5. Leap > 90/1178
There are two ever-present dangers when entrepreneurs conduct market research and talk to customers.
5. Leap > 90/1179
Followers of the just-do-it school of entrepreneurship are impatient to get started and don’t want to spend time analyzing their strategy.
5. Leap > 90/1182
Other entrepreneurs can fall victim to analysis paralysis, endlessly refining their plans.
5. Leap > 91/1186
how do entrepreneurs know when to stop analyzing and start building?
5. Leap > 91/1186
The answer is a concept called the minimum viable product,

6. Test > 93/1208
A minimum viable product (MVP)
6. Test > 93/1210
is simply the fastest way to get through the Build-Measure-Learn feedback loop with the minimum amount of effort.
6. Test > 93/1212
the goal of the MVP is to begin the process of learning, not end it. Unlike a prototype or concept test, an MVP is designed not just to answer product design or technical questions. Its goal is to test fundamental business hypotheses.
6. Test > 94/1222
Before new products can be sold successfully to the mass market, they have to be sold to early adopters.
6. Test > 95/1228
Early adopters use their imagination to fill in what a product is missing.
6. Test > 95/1229
what they care about above all is being the first to use or adopt a new product or technology.
6. Test > 95/1231
Early adopters are suspicious of something that is too polished:
6. Test > 96/1241
how many features are needed in an MVP. When in doubt, simplify.
6. Test > 96/1253
Every extra feature is a form of waste, and if we delay the test for these extra features, it comes with a tremendous potential cost in terms of learning and cycle time.
6. Test > 96/1254
The lesson of the MVP is that any additional work beyond what was required to start learning is waste, no matter how important it might have seemed at the time.
6. Test > 97/1256
avoiding the temptation to overbuild and overpromise.
6. Test > 97/1257
6. Test > 97/1258
Drew Houston is the CEO of Dropbox,
6. Test > 98/1278
To avoid the risk of waking up after years of development with a product nobody wanted, Drew
6. Test > 98/1279
made a video.
6. Test > 98/1280
a simple three-minute demonstration of the technology as it is meant to work, but it was targeted at a community of technology early adopters.
6. Test > 99/1284
Our beta waiting list went from 5,000 people to 75,000 people literally overnight.
6. Test > 99/1288
6. Test > 99/1290
Manuel Rosso, the CEO of
6. Test > 99/1290
Food on the Table.
6. Test > 100/1302
Food on the Table (FotT) began life with a single customer.
6. Test > 100/1303
Instead of supporting thousands of grocery stores around the country as it does today, FotT supported just one.
6. Test > 102/1324
Each new customer got the concierge treatment: personal in-home visits, the works.
6. Test > 102/1324
after a few more customers,
6. Test > 102/1326
start to invest in automation in the form of product development.
6. Test > 106/1391
6. Test > 107/1401
If we do not know who the customer is, we do not know what quality is.
6. Test > 107/1403
MVPs sometimes are perceived as low-quality by customers. If so, we should use this as an opportunity to learn what attributes customers care about.
6. Test > 107/1405
Sometimes, however, customers react quite differently. Many famous products were released in a “low-quality” state, and customers loved them.
6. Test > 109/1427
So which version of the product is low-quality, again? MVPs require the courage to put one’s assumptions to the test. If customers react the way we expect, we can take that as confirmation that our assumptions are correct. If we release a poorly designed product and customers (even early adopters) cannot figure out how to use it, that will confirm our need to invest in superior design.
6. Test > 109/1432
We must be willing to set aside our traditional professional standards to start the process of validated learning as soon as possible.
6. Test > 110/1436
As you consider building your own minimum viable product, let this simple rule suffice: remove any feature, process, or effort that does not contribute directly to the learning you seek.
6. Test > 110/1438
6. Test > 110/1439
Building an MVP is not without risks,
6. Test > 110/1440
The most common speed bumps are legal issues, fears about competitors, branding risks, and the impact on morale.
6. Test > 110/1446
the patent risks of an MVP are minor compared with the learning benefits.
6. Test > 111/1449
building an MVP is fear of competitors—
6. Test > 111/1450
stealing a startup’s ideas.
6. Test > 111/1450
If only it were so easy to have a good idea stolen!
6. Test > 111/1463
there is an easy solution: launch the MVP under a different brand name.
6. Test > 112/1476
You have to commit to a locked-in agreement—ahead of time—that no matter what comes of testing the MVP, you will not give up hope.
6. Test > 113/1477
Successful entrepreneurs
6. Test > 113/1478
possess a unique combination of perseverance and flexibility.
6. Test > 113/1479
you may learn that some element of your product or strategy is flawed and decide it is time to make a change, which I call a pivot, to a different method for achieving your vision.
6. Test > 113/1488
We all need a disciplined, systematic approach to figuring out if we’re making progress and discovering if we’re actually achieving validated learning. I call this system innovation accounting,

7. Measure > 114/1497
One of the most dangerous outcomes for a startup is to bumble along in the land of the living dead.
7. Measure > 114/1498
We want to keep believing in our ideas even when the writing is on the wall.
7. Measure > 114/1499
This is why the myth of perseverance is so dangerous.
7. Measure > 115/1507
standard accounting is not helpful in evaluating entrepreneurs. Startups are too unpredictable for forecasts and milestones to be accurate.
7. Measure > 116/1519
a new kind of accounting geared specifically to disruptive innovation. That’s what innovation accounting is.
7. Measure > 116/1526
The rate of growth depends primarily on three things: the profitability of each customer, the cost of acquiring new customers, and the repeat purchase rate of existing customers.
7. Measure > 117/1538
Innovation accounting works in three steps:
7. Measure > 117/1539
first, use a minimum viable product to establish real data on where the company is right now.
7. Measure > 118/1541
Second, startups must attempt to tune the engine from the baseline toward the ideal.
7. Measure > 118/1542
move its baseline toward the ideal, the company reaches a decision point.
7. Measure > 118/1542
third step: pivot or persevere.
7. Measure > 118/1543
If the company is making good progress toward the ideal, that means it’s learning appropriately and using that learning effectively,
7. Measure > 118/1546
The sign of a successful pivot is that these engine-tuning activities are more productive after the pivot than before.
7. Measure > 118/1547
Establish the Baseline
7. Measure > 118/1548
a startup might create a complete prototype of its product
7. Measure > 118/1548
This single MVP would test most of the startup’s assumptions and establish baseline metrics for each assumption simultaneously. Alternatively, a startup might prefer to build separate MVPs that are aimed at getting feedback on one assumption at a time.
7. Measure > 119/1554
These MVPs provide the first example of a learning milestone.
7. Measure > 119/1557
it makes sense to test the riskiest assumptions first.
7. Measure > 119/1558
to mitigate these risks toward the ideal that is required for a sustainable business,
7. Measure > 119/1563
Tuning the Engine
7. Measure > 119/1563
Once the baseline has been established, the startup can work toward the second learning milestone: tuning the engine.
7. Measure > 119/1564
Every product development, marketing, or other initiative that a startup undertakes should be targeted at improving one of the drivers of its growth model.
7. Measure > 119/1567
To demonstrate validated learning, the
7. Measure > 119/1567
changes must improve the activation rate of new customers.
7. Measure > 120/1572
Pivot or Persevere
7. Measure > 120/1576
if we’re not moving the drivers of our business model, we’re not making progress. That becomes a sure sign that it’s time to pivot.
7. Measure > 125/1641
Each pivot unlocks new opportunities for further experimentation, and the cycle repeats.
7. Measure > 125/1641
repeat this simple rhythm: establish the baseline, tune the engine, and make a decision to pivot or persevere.
7. Measure > 128/1677
I call the traditional numbers used to judge startups “vanity metrics,” and innovation accounting requires us to avoid the temptation to use them.
7. Measure > 128/1679
the danger of vanity metrics
7. Measure > 129/1683
they give the rosiest possible picture.
7. Measure > 129/1684
You’ll see a traditional hockey stick graph (the ideal in a rapid-growth company).
7. Measure > 129/1684
As long as you focus on the top-line numbers
7. Measure > 129/1685
you’ll be forgiven for thinking this product development team is making great progress.
7. Measure > 129/1689
The engine is turning, but the efforts to tune the engine are not bearing much fruit.
7. Measure > 130/1692
The alternative is the kind of metrics we use to judge our business and our learning milestones, what I call actionable metrics.
7. Measure > 130/1693
7. Measure > 136/1778
A disciplined team may apply the wrong methodology but can shift gears quickly once it discovers its error. Most important, a disciplined team can experiment with its own working style and draw meaningful conclusions.
7. Measure > 137/1788
To figure out if the new design was effective, all you would have to do was keep track of the sales figures for both groups of customers. (This technique is sometimes called A/ B testing after the practice of assigning letter names to each variation.)
7. Measure > 143/1867
the three A’s of metrics: actionable, accessible, and auditable.
7. Measure > 143/1868
7. Measure > 143/1869
it must demonstrate clear cause and effect.
7. Measure > 144/1884
When cause and effect is clearly understood, people are better able to learn from their actions.
7. Measure > 144/1885
7. Measure > 144/1886
All too many reports are not understood by the employees and managers who are supposed to use them to guide their decision making.
7. Measure > 144/1889
There is an antidote to this misuse of data. First, make the reports as simple as possible so that everyone understands them.
7. Measure > 144/1891
use tangible, concrete units.
7. Measure > 145/1900
As the gross numbers get larger, accessibility becomes more and more important.
7. Measure > 145/1902
Accessibility also refers to widespread access to the reports.
7. Measure > 145/1903
Every day their system automatically generated a document containing the latest data for every single one of their split-test experiments and other leap-of-faith metrics. This document was mailed to every employee of the company: they all always had a fresh copy in their e-mail in-boxes.
7. Measure > 146/1912
7. Measure > 146/1914
We must ensure that the data is credible to employees.
7. Measure > 147/1922
First, remember that “Metrics are people, too.” We need to be able to test the data by hand, in the messy real world, by talking to customers.
7. Measure > 147/1923
This is the only way to be able to check if the reports contain true facts.
7. Measure > 147/1926
Second, those building reports must make sure the mechanisms that generate the reports are not too complex.
7. Measure > 148/1938
Only 5 percent of entrepreneurship is the big idea, the business model, the whiteboard strategizing, and the splitting up of the spoils. The other 95 percent is the gritty work that is measured by innovation accounting: product prioritization decisions, deciding which customers to target or listen to, and having the courage to subject a grand vision to constant testing and feedback.

8. Pivot (or Persevere) > 149/1947
pivot: a structured course correction designed to test a new fundamental hypothesis about the product, strategy, and engine of growth.
8. Pivot (or Persevere) > 149/1952
there is no bigger destroyer of creative potential than the misguided decision to persevere.
8. Pivot (or Persevere) > 149/1953
get stuck in the land of the living dead, neither growing enough nor dying,
8. Pivot (or Persevere) > 156/2055
what I call a customer segment pivot, keeping the functionality of the product the same but changing the audience focus.
8. Pivot (or Persevere) > 158/2086
Votizen’s story exhibits some common patterns.
8. Pivot (or Persevere) > 158/2086
One of the most important to note is the acceleration of MVPs. The first MVP took eight months, the next four months, then three, then one.
8. Pivot (or Persevere) > 159/2089
each time the company pivoted, it didn’t have to start from scratch.
8. Pivot (or Persevere) > 160/2106
8. Pivot (or Persevere) > 160/2107
the runway that their startup has left: the amount of time remaining in which a startup must either achieve lift-off or fail.
8. Pivot (or Persevere) > 160/2109
a startup with $ 1 million in the bank that is spending $ 100,000 per month has a projected runway of ten months.
8. Pivot (or Persevere) > 160/2110
they can extend the runway two ways: by cutting costs or by raising additional funds.
8. Pivot (or Persevere) > 160/2113
The true measure of runway is how many pivots a startup has left: the number of opportunities it has to make a fundamental change to its business strategy.
8. Pivot (or Persevere) > 161/2115
the startup has to find ways to achieve the same amount of validated learning at lower cost or in a shorter time.
8. Pivot (or Persevere) > 164/2158
the telltale signs of the need to pivot: the decreasing effectiveness of product experiments and the general feeling that product development should be more productive. Whenever you see those symptoms, consider a pivot.
8. Pivot (or Persevere) > 164/2161
schedule the meeting in advance. I recommend that every startup have a regular “pivot or persevere” meeting.
8. Pivot (or Persevere) > 172/2281
pivot is a special kind of change designed to test a new fundamental hypothesis about the product, business model, and engine of growth.
8. Pivot (or Persevere) > 173/2283
Zoom-in Pivot
8. Pivot (or Persevere) > 173/2283
single feature in a product becomes the whole product.
8. Pivot (or Persevere) > 173/2285
Zoom-out Pivot
8. Pivot (or Persevere) > 173/2286
the whole product becomes a single feature of a much larger product.
8. Pivot (or Persevere) > 173/2287
Customer Segment Pivot
8. Pivot (or Persevere) > 173/2290
solving the right problem, but for a different customer
8. Pivot (or Persevere) > 173/2290
Customer Need Pivot
8. Pivot (or Persevere) > 173/2292
the problem we’re trying to solve for them is not very important.
8. Pivot (or Persevere) > 173/2292
we often discover other related problems
8. Pivot (or Persevere) > 174/2294
it may require a completely new product.
8. Pivot (or Persevere) > 174/2296
example is the chain Potbelly Sandwich Shop, which today has over two hundred stores. It began as an antique store in 1977; the owners started to sell sandwiches as a way to bolster traffic to their stores.
8. Pivot (or Persevere) > 174/2298
Platform Pivot
8. Pivot (or Persevere) > 174/2299
a change from an application to a platform or vice versa.
8. Pivot (or Persevere) > 174/2302
Business Architecture Pivot
8. Pivot (or Persevere) > 174/2302
This pivot borrows a concept from Geoffrey Moore, who observed that companies generally follow one of two major business architectures: high margin, low volume (complex systems model) or low margin, high volume (volume operations model).
8. Pivot (or Persevere) > 174/2306
a startup switches architectures.
8. Pivot (or Persevere) > 175/2308
Value Capture Pivot
8. Pivot (or Persevere) > 175/2309
monetization or revenue models.
8. Pivot (or Persevere) > 175/2312
Engine of Growth Pivot
8. Pivot (or Persevere) > 175/2313
there are three primary engines of growth that power startups: the viral, sticky, and paid growth models.
8. Pivot (or Persevere) > 175/2314
a company changes its growth strategy to seek faster or more profitable growth.
8. Pivot (or Persevere) > 175/2316
Channel Pivot
8. Pivot (or Persevere) > 176/2320
a recognition that the same basic solution could be delivered through a different channel with greater effectiveness.
8. Pivot (or Persevere) > 176/2324
Technology Pivot
8. Pivot (or Persevere) > 176/2324
achieve the same solution by using a completely different technology.
Part Three: Accelerate

9. Batch > 184/2403
the one envelope at a time approach is a faster way of getting the job done even though it seems inefficient.
9. Batch > 184/2406
is called “single-piece flow” in lean manufacturing.
9. Batch > 185/2410
Because our intuition doesn’t take into account the extra time required to sort, stack, and move around the large piles of half-complete envelopes when it’s done the other way.
9. Batch > 185/2415
imagine that the letters didn’t fit in the envelopes. With the large-batch approach, we wouldn’t find that out until nearly the end.
9. Batch > 185/2417
In the large-batch approach, we’d have to unstuff all the envelopes, get new ones, and restuff them. In the small-batch approach, we’d find this out immediately and have no rework required.
9. Batch > 186/2434
Shigeo Shingo created the concept of SMED (Single-Minute Exchange of Die) in order to enable a smaller batch size of work in early Toyota factories.
9. Batch > 187/2436
He did this, not by asking workers to work faster, but by reimagining and restructuring the work that needed to be done.
9. Batch > 187/2442
The biggest advantage of working in small batches is that quality problems can be identified much sooner.
9. Batch > 188/2454
Working in small batches ensures that a startup can minimize the expenditure of time, money, and effort that ultimately turns out to have been wasted.
9. Batch > 191/2499
more and more industries are seeing their design process accelerated
9. Batch > 191/2500
There are three ways in which this is happening:
9. Batch > 191/2501
1. Hardware becoming software.
9. Batch > 191/2502
The latest phones and tablet computers are little more than a screen connected to the Internet. Almost all of their value is determined by their software.
9. Batch > 192/2505
2. Fast production changes.
9. Batch > 192/2506
many assembly lines are set up to allow each new product that comes off the line to be customized completely without sacrificing quality or cost-effectiveness.
9. Batch > 192/2510
3. 3D printing and rapid prototyping tools.
9. Batch > 192/2511
most products
9. Batch > 192/2511
today are mass produced using a technique called injection molding.
9. Batch > 192/2513
It is a classic large-batch production process.
9. Batch > 192/2514
However, new technologies are allowing entrepreneurs to build small batches of products
9. Batch > 200/2616
Lean production solves the problem of stockouts with a technique called pull.
9. Batch > 200/2621
The ideal goal is to achieve small batches all the way down to single-piece flow along the entire supply chain. Each step in the line pulls the parts it needs from the previous step. This is the famous Toyota just-in-time production method.
9. Batch > 200/2624
[called work-in-progress (WIP) inventory]
9. Batch > 201/2629
Almost every Lean Startup technique we’ve discussed so far works its magic in two ways: by converting push methods to pull and reducing batch size. Both have the net effect of reducing WIP.

10  GROW
10. Grow > 207/2710
Sustainable growth is characterized by one simple rule: New customers come from the actions of past customers.
10. Grow > 207/2712
There are four primary ways past customers drive sustainable growth:
10. Grow > 208/2712
1. Word of mouth.
10. Grow > 208/2715
2. As a side effect of product usage.
10. Grow > 208/2718
3. Through funded advertising.
10. Grow > 208/2722
4. Through repeat purchase or use.
10. Grow > 208/2725
Each is like a combustion engine, turning over and over. The faster the loop turns, the faster the company will grow.
10. Grow > 209/2727
10. Grow > 209/2734
There are always a zillion new ideas about how to make the product better floating around, but the hard truth is that most of those ideas make a difference only at the margins. They are mere optimizations. Startups have to focus on the big experiments that lead to validated learning.
10. Grow > 211/2754
The speed of growth is determined by what I call the rate of compounding, which is simply the natural growth rate minus the churn rate.
10. Grow > 211/2755
having a high rate of compounding will lead to extremely rapid growth—without advertising, viral growth, or publicity stunts.
10. Grow > 212/2771
The Viral Engine of Growth
10. Grow > 212/2775
Customers are not intentionally acting as evangelists;
10. Grow > 212/2776
Growth happens automatically as a side effect of customers using the product.
10. Grow > 212/2777
Hotmail. In 1996,
10. Grow > 212/2778
At first, growth was sluggish;
10. Grow > 212/2779
But everything changed when they made one small tweak to the product. They added to the bottom of every single e-mail the message “P.S. Get your free e-mail at Hotmail”
10. Grow > 213/2788
the viral engine is powered by a feedback loop that can be quantified. It is called the viral loop, and its speed is determined by a single mathematical term called the viral coefficient.
10. Grow > 213/2790
The viral coefficient measures how many new customers will use a product as a consequence of each new customer who signs up.
10. Grow > 213/2792
For a product with a viral coefficient of 0.1, one in every ten customers will recruit one of his or her friends. This is not a sustainable loop.
10. Grow > 214/2795
a viral loop with a coefficient that is greater than 1.0 will grow exponentially, because each person who signs up will bring, on average, more than one other person with him or her.
10. Grow > 215/2811
The Paid Engine of Growth
10. Grow > 216/2818
If either company wants to increase its rate of growth, it can do so in one of two ways: increase the revenue from each customer or drive down the cost of acquiring a new customer. That’s the paid engine of growth at work.
10. Grow > 216/2828
the paid engine of growth is powered by a feedback loop. Each customer pays a certain amount of money for the product over his or her “lifetime” as a customer. Once variable costs are deducted, this usually is called the customer lifetime value (LTV). This revenue can be invested in growth by buying advertising.
10. Grow > 217/2830
Suppose an advertisement costs $ 100 and causes fifty new customers to sign up for the service. This ad has a cost per acquisition (CPA) of $ 2.00.
10. Grow > 217/2832
if the product has an LTV that is greater than $ 2, the product will grow.
10. Grow > 219/2868
Marc Andreessen,
10. Grow > 219/2869
coined the term product/ market fit to describe the moment when a startup finally finds a widespread set of customers that resonate with its product: In a great market—a market with lots of real potential customers—the market pulls product out of the startup.
10. Grow > 222/2903
10. Grow > 222/2904
every engine of growth eventually runs out of gas.
10. Grow > 222/2915
The growth is all coming from an engine of growth that is working—running efficiently to bring in new customers—not from improvements driven by product development.
10. Grow > 223/2922
we need an organizational structure, culture, and discipline that can handle these rapid and often unexpected changes. I call this an adaptive organization,

11. Adapt > 225/2937
There are so many ways for a startup to fail.
11. Adapt > 225/2937
the overarchitecture failure, in which attempting to prevent all the various kinds of problems that could occur wound up delaying the company from putting out any product.
11. Adapt > 225/2939
Friendster effect, suffering a high-profile technical failure just when customer adoption is going wild.
11. Adapt > 226/2953
11. Adapt > 227/2962
an adaptive organization, one that automatically adjusts its process and performance to current conditions.
11. Adapt > 227/2965
focusing on speed alone would be destructive.
11. Adapt > 227/2966
To work, startups require built-in speed regulators that help teams find their optimal pace of work.
11. Adapt > 227/2967
with the use of the andon cord in systems such as continuous deployment.
11. Adapt > 227/2968
Toyota proverb, “Stop production so that production never has to stop.”
11. Adapt > 227/2970
you cannot trade quality for time. If you are causing (or missing) quality problems now, the resulting defects will slow you down later.
11. Adapt > 228/2979
On the one hand, the logic of validated learning and the minimum viable product says that we should get a product into customers’ hands as soon as possible and that any extra work we do beyond what is required to learn from customers is waste. On the other hand,
11. Adapt > 228/2987
Having a low-quality product can inhibit learning when the defects prevent customers from experiencing (and giving feedback on) the product’s benefits.
11. Adapt > 229/2989
Similarly, the more features we added to the product, the harder it became to add even more because of the risk that a new feature would interfere with an existing feature.
11. Adapt > 229/2992
11. Adapt > 229/2993
When you’re going too fast, you cause more problems. Adaptive processes force you to slow down and invest in preventing the kinds of problems that are currently wasting time.
11. Adapt > 229/3001
use a system called the Five Whys to make incremental investments and evolve a startup’s processes gradually.
11. Adapt > 230/3003
asking the question “Why?” five times to understand what has happened
11. Adapt > 230/3010
For example, suppose a machine stopped functioning: 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 it not lubricated sufficiently? (The lubrication pump was not pumping sufficiently.) 4. Why was it not pumping sufficiently? (The 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.)
11. Adapt > 231/3018
By asking and answering “why” five times, we can get to the real cause of the problem, which is often hidden behind more obvious symptoms.
11. Adapt > 232/3030
What began as a purely technical fault is revealed quickly to be a very human managerial issue.
11. Adapt > 232/3032
Here’s how to use Five Whys analysis to build an adaptive organization: consistently make a proportional investment at each of the five levels of the hierarchy.
11. Adapt > 232/3040
If the outage is a minor glitch, it’s essential that we make only a minor investment in fixing it.
11. Adapt > 233/3049
The more problems you have, the more you invest in solutions to those problems.
11. Adapt > 233/3052
The Five Whys ties the rate of progress to learning, not just execution.
11. Adapt > 234/3060
When the Five Whys approach goes awry, I call it the Five Blames.
11. Adapt > 234/3060
Instead of asking why repeatedly in an attempt to understand what went wrong, frustrated teammates start pointing fingers at each other, trying to decide who is at fault.
11. Adapt > 234/3062
managers and employees can fall into the trap of using the Five Blames as a means for venting their frustrations and calling out colleagues for systemic failures.
11. Adapt > 234/3065
I recommend several tactics for escaping the Five Blames.
11. Adapt > 234/3065
The first is to make sure that everyone affected by the problem is in the room during the analysis of the root cause.
11. Adapt > 236/3084
Here are a few tips on how to get started with the Five Whys
11. Adapt > 236/3089
1. Be tolerant of all mistakes the first time.
11. Adapt > 236/3089
2. Never allow the same mistake to be made twice.
11. Adapt > 238/3110
I recommend starting with a narrowly targeted class of symptoms.
11. Adapt > 238/3114
The more specific the symptoms are, the easier it will be for everyone to recognize when it’s time to schedule a Five Whys meeting.
11. Adapt > 239/3124
To facilitate learning, I have found it helpful to appoint a Five Whys master for each area in which the method is being used. This individual is tasked with being the moderator for each Five Whys meeting, making decisions about which prevention steps to take, and assigning the follow-up work from that meeting.

12. Innovate > 253/3314
As startups grow, entrepreneurs can build organizations that learn how to balance the needs of existing customers with the challenges of finding new customers to serve, managing existing lines of business, and exploring new business models—
12. Innovate > 253/3317
what I call portfolio thinking.
12. Innovate > 253/3318
12. Innovate > 253/3321
startup teams require three structural attributes: scarce but secure resources, independent authority to develop their business, and a personal stake in the outcome.
12. Innovate > 254/3329
too much budget is as harmful as too little—
12. Innovate > 254/3332
they require much less capital overall, but that capital must be absolutely secure from tampering.
12. Innovate > 255/3341
entrepreneurs need a personal stake in the outcome of their creations.
12. Innovate > 255/3343
I do not believe that a personal stake has to be financial.
12. Innovate > 255/3347
because my name was on the door, I had more to lose and more to prove than someone else.
12. Innovate > 256/3360
12. Innovate > 256/3360
focus on establishing the ground rules under which autonomous startup teams operate: how to protect the parent organization, how to hold entrepreneurial managers accountable, and how to reintegrate an innovation back into the parent organization if it is successful.
12. Innovate > 260/3410
Without the ability to experiment in a more agile manner, this company eventually would suffer the fate described in The Innovator’s Dilemma: ever-higher profits and margins year after year until the business suddenly collapsed.
12. Innovate > 260/3413
How can we protect the parent organization from the startup?
12. Innovate > 260/3417
Hiding from the parent organization can have long-term negative consequences.
12. Innovate > 261/3426
The challenge here is to create a mechanism for empowering innovation teams out in the open.
12. Innovate > 261/3428
My suggested solution is to create a sandbox for innovation that will contain the impact of the new innovation but not constrain the methods of the startup team. It works as follows:
12. Innovate > 261/3430
1. Any team can create a true split-test experiment that affects only the sandboxed parts of the product or service (for a multipart product) or only certain customer segments or territories (for a new product).
12. Innovate > 262/3431
2. One team must see the whole experiment through from end to end.
12. Innovate > 262/3432
3. No experiment can run longer than a specified amount of time
12. Innovate > 262/3433
4. No experiment can affect more than a specified number of customers
12. Innovate > 262/3435
5. Every experiment has to be evaluated on the basis of a single standard report of five to ten (no more) actionable metrics.
12. Innovate > 262/3436
6. Every team that works inside the sandbox and every product that is built must use the same metrics to evaluate success.
12. Innovate > 262/3437
7. Any team that creates an experiment must monitor the metrics and customer reactions
12. Innovate > 263/3455
Even if someone wants to sabotage the innovation team, he or she will have to learn all about actionable metrics and learning milestones to do it.
12. Innovate > 263/3456
The sandbox also promotes rapid iteration.
12. Innovate > 264/3461
the sandbox method allows teams to make cheap mistakes quickly and start learning.
12. Innovate > 264/3467
Operating in this framework, internal teams essentially act as startups.
12. Innovate > 264/3467
integrated into the company’s overall portfolio of products and services.
12. Innovate > 265/3476
This may require a different type of manager: one who excels in optimization, delegation, control, and execution.
12. Innovate > 266/3486
The problem for startups and large companies alike is that employees often follow the products they develop as they move from phase to phase.
12. Innovate > 266/3488
As a result, strong creative managers wind up getting stuck working on the growth and optimization of products rather than creating new ones.
12. Innovate > 266/3491
Entrepreneur Is a Job Title
12. Innovate > 266/3492
The way out of this dilemma is
12. Innovate > 266/3492
allowing strong cross-functional teams to develop around each area.
12. Innovate > 266/3493
When products move from phase to phase, they are handed off between teams.
12. Innovate > 267/3498
entrepreneurship should be considered a viable career path for innovators inside large organizations.
12. Innovate > 268/3513
Working in the innovation sandbox is like developing startup muscles. At first, the team will be able to take on only modest experiments.
12. Innovate > 268/3515
Over time, those teams are almost guaranteed to improve as long as they get the constant feedback of small-batch development and actionable metrics and are held accountable to learning milestones.
12. Innovate > 268/3518
When the product makes up the whole sandbox, it inevitably will become encumbered with the additional rules and controls needed for mission-critical operation.
12. Innovate > 268/3521
This last transition is especially hard for innovators to accept: their transformation from radical outsiders to the embodiment of the status quo.
12. Innovate > 271/3557
switching to validated learning feels worse before it feels better.

13. Epilogue: Waste Not > 272/3574
There is a reason all past management revolutions have been led by engineers: management is human systems engineering.
13. Epilogue: Waste Not > 273/3587
The big question of our time is not Can it be built? but Should it be built? This places us in an unusual historical moment: our future prosperity depends on the quality of our collective imaginations.
13. Epilogue: Waste Not > 274/3596
We of the twenty-first century are hyperaware of the importance of efficiency and the economic value of productivity gains.
13. Epilogue: Waste Not > 274/3599
our economy is still incredibly wasteful. This waste comes not from the inefficient organization of work but rather from working on the wrong things—
13. Epilogue: Waste Not > 274/3605
I consider this misuse of people’s time a criminally negligent waste of human creativity and potential.
13. Epilogue: Waste Not > 275/3616
We believe that most forms of waste in innovation are preventable once their causes are understood. All that is required is that we change our collective mind-set concerning how this work is to be done.
13. Epilogue: Waste Not > 275/3617
Our current problems are caused by trying too hard—at the wrong things.
13. Epilogue: Waste Not > 275/3618
By focusing on functional efficiency, we lose sight of the real goal of innovation: to learn that which is currently unknown.