The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses Audible Audiobook – Unabridged
Most startups fail. But many of those failures are preventable. The Lean Startup is a new approach being adopted across the globe, changing the way companies are built and new products are launched.
Eric Ries defines a startup as an organization dedicated to creating something new under conditions of extreme uncertainty. This is just as true for one person in a garage or a group of seasoned professionals in a Fortune 500 boardroom. What they have in common is a mission to penetrate that fog of uncertainty to discover a successful path to a sustainable business.
The Lean Startup approach fosters companies that are both more capital efficient and that leverage human creativity more effectively. Inspired by lessons from lean manufacturing, it relies on “validated learning”, rapid scientific experimentation, as well as a number of counter-intuitive practices that shorten product-development cycles, measure actual progress without resorting to vanity metrics, and learn what customers really want. It enables a company to shift directions with agility, altering plans inch by inch, minute by minute.
Rather than wasting time creating elaborate business plans, The Lean Startup offers entrepreneurs - in companies of all sizes - a way to test their vision continuously, to adapt and adjust before it’s too late. Ries provides a scientific approach to creating and managing successful startups in a age when companies need to innovate more than ever.
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|Listening Length||8 hours and 38 minutes|
|Audible.in Release Date||13 September 2011|
|Publisher||Random House Audio|
|Best Sellers Rank|| #87 in Audible Books & Originals (See Top 100 in Audible Books & Originals) |
#1 in New Business Enterprises
#2 in Small Businesses
#3 in Business Management
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Unfortunately, the book is hard to read, specifically the first half, which could be condensed to half its length, because there's too much repetition. The author leaves you to figure out what a term means from reading an anecdote spread over two pages rather than defining it explicitly and clearly defining it. Some chapter names are meaningless, like "Leap", and give you no indication of what to expect. Some case studies are not obviously connected to the point the author is trying to make — you scratch your head and try to figure out what it means, and what the point must have been, and what the moral of the story must have been.
But, stick with it, and you'll be rewarded with a solid, well thought-out, evidence-based method on running a startup with less risk, stress, time, money and effort.
Here's a summary of the book:
The lean startup method has five principles:
1) Entrepreneurs are everywhere.
2) Entrepreneurship is management, albeit a form of management that applies under the conditions of extreme uncertainty in a startup. If you think management is not cool and reject it, you'll have chaos and failure.
3) Validated Learning. Startups exist not to just make things, serve customers, or make money. They exist to learn how to build a sustainable business.
4) Build - measure - learn: Startups should go through this loop, as fast as possible.
5) Innovation Accounting is needed to measure a startup's progress, set up milestones, prioritise work, and for the people in it to hold themselves accountable.
- The lean startup draws from related fields like lean manufacturing and design thinking.
- If a company commits itself to the wrong plan and executes that plan excellently at a big scale, it may not be able to pivot in time, because it has committed all its resources and time to the wrong vision. It will achieve failure.
- Startups can exist as islands of independence within big companies.
Chapter 3: Learn:
- Which actions are value-creating and which are wasteful? This question is at the heart of lean manufacturing as well.
- Validate your assumptions more cheaply than building the entire product.
- But not by asking people what they want — most of the time, they don't know in advance.
- People who fail often give the excuse that they learnt a lot.
- It's easier to raise money when you have zero revenue and users. Zero invites imagination. A small number invites questions about whether big numbers will ever materialise.
- So, it's tempting to postpone getting any idea until you are sure of the success. But don't do that.
- Early in a startup's life, revenue growth happens slowly. But the real progress is in validated learning.
- Don't fall prey to vanity metrics, which are numbers that look good but are not the best indicators of your company's health. For example, if you have a web site that encourages people to download an app, page views on the web site is a vanity metric, because there are better metrics, like downloads of the app, signups, active users, etc.
- Don't waste money on PR and buying media attention and getting written up in magazines. Focus on learning.
Chapter 4: Experiment
- The founder of Zappos first tested his e-store for shoes by fulfilling orders manually — going to a nearby physical shop, buying the shoes, and shipping them. After a month, a thousand orders were placed, validating his idea.
- He observed real customer behaviour, interacted with them, and learnt about their needs, not asked hypothetical questions.
- Customers react in unexpected ways, revealing information you might not have known to ask about, like returning shoes.
- Startups have a value hypothesis and a growth hypothesis.
- The value hypothesis is that customers derive value from the product or service once they start using it.
- The growth hypothesis is about how new customers will discover a product or service.
- Give your first few users wonderful attention, as if you're a concierge.
- An experiment is actually a startup's first product, not just a theoretical enquiry.
- Startups have a build - measure - learn feedback loop.
- The learning is how to build a sustainable business.
- This learning is more important than revenue.
- Minimise the time it takes for you iterate through this loop.
- People are often trained and specialised in one aspect of this loop, like engineers trained to build. What matter is not one part, but how fast you can iterate through the entire loop.
- Startups should use a scientific method.
- To do so, they should know what hypotheses to test.
- The two most important hypotheses are the value hypothesis and the growth hypothesis.
- Every startup is based on assumptions, often not recognised as such by founders.
- Some assumptions are validated by the existence of other products. For example, when Apple built the iPod, one assumption was that people want to listen to music in public places using earphones. But the popularity of the walkman validated that assumption.
- "Leap of faith" assumptions are trickier, like saying that people want to pay $399 for a portable music player.
- You want to validate them ASAP.
- The riskiest ones first.
- You do so by building one or more MVPs. An MVP lacks features that are needed later, but its purpose is to validate assumptions with as little time and effort as possible.
- You should identify and list assumptions before, not after, building the MVP. Ideally give quantitative estimates like 20% of people will be interested in our service, and 5% will be willing to pay. That way, you can't claim later on that you succeeded, by defining the goal as what you actually achieved.
- You actually run the build - measure - learn loop in reverse: start with what you want to learn (assumptions to validate), then think about what to measure to validate those assumptions, and then build that MVP.
- Don't act as if your assumptions are true. Validate them. Otherwise your startup will fail.
- You can look for analogs and antilogs.
- An analog is a similar situation that validates your assumption, as with people listening to music in public using earphones.
- An antilog is something that goes against your assumption. For example, an assumption behind the iTunes Music Store was that people are willing to pay for music, but Napster was an antilog.
- Get out of the building and talk to users. Don't theorise.
Chapter 6: Test
- Start with a quick, crappy implementation.
- Groupon began as a themed Wordpress blog with the coupons being PDFs mailed by Apple's Mail app to 500 people.
- An MVP is not necessarily the smallest product to build, but the quickest to build.
- It's hard for entrepreneurs to launch an MVP, because the vision they have of themselves is launching high-quality, polished products, not crappy ones. Overcome that hesitation.
- If you don't know who the customer is, you don't know what quality is.
- Users may be fine with what you think is low-quality stuff, and may actually find it better, disagreeing with your opinion as to what constitutes high or low quality.
- Low quality is a problem only if it slows down the build - measure - learn feedback loop.
- An MVP can also be a marketing pitch accompanied by a sign up page to gauge interest.
- Or a video, in Dropbox's case.
- You can have humans substitute for an algorithm.
- Don't worry that an established company will copy your idea. Try pitching it to the managers there. They will do nothing, partly because they're already overwhelmed with good ideas.
- MVPs often result in bad news. Or, rather, they bring it out. You're better off facing reality.
Chapter 7: Measure
- If you're making changes to your product resulting in more users, that's not good enough. It's storytelling. How do you know that your changes are causing the results? How do you know that you're drawing the right lessons from your changes?
- You need innovation accounting.
- Innovation accounting works in three steps:
1) Use an MVP to establish real data on where you are. Without a clear-eyed picture of your current status — no matter how far from the goal you may be — you cannot begin to track your progress.
2) Tune the engine to move towards the ideal.
3) Decide whether to continue on your current course or pivot.
- An MVP gets you real baseline data — conversion rates, sign-up rates, trial rates, customer life-time value, and so on.
- Don't optimise something (like making your app easier for new users to use) until you know that it's a driver of growth and is less than what you'd like.
- Putting all these together, start with a baseline metric, then form a hypothesis as to what will improve that metric, and then perform a set of experiments designed to test that hypothesis.
- Metrics about the customer acquisition funnel are important.
- Running Adwords ads, even on a low budget is important, because it gives you critical data.
- Cohort analysis is important. Here, you define a cohort, such as people who signed up during a given week, or those who used a certain feature. Then you track the performance of your app for that group of users.
- Cohort analysis lets you prove or disprove theories like, if your number of users is declining, that people who signed up recently are abandoning the app while old users continue to use it.
- Cohort analysis can point out problems when other metrics are all up and to the right (hockey sticks).
- When you get poor quantitative results, they force you to declare failure and create the motivation, context and space for more qualitative research.
- If you pivot, and the experiments you run afterward are more productive than the ones before, that's the sign of a successful pivot.
- Don't focus on optimising, whether the conversion rate or the performance of your app, because you may be building the wrong thing, in which case no amount of optimisation will help.
- A startup has to measure progress against a high bar: evidence that a sustainable business can be built. This is possible only if you've made clear, verifiable predictions ahead of time.
- Sometimes, when you make changes and launch them, it's hard to look for cause-and-effect relationships after the fact. In that case, do an A/B test.
- A/B testing can also tell you things like whether the social features you've added to a product matter.
- Hypothesis testing can require you to build new infrastructure. For example, if you're testing delayed sign-up, you'll need to support a state where users have their data in the system but haven't yet signed up.
- Industry norms like delayed sign-up helping may not be true in your case.
- That may, in turn, reveal an insight, such as: customers were not basing their decision on whether to use your product on your demo. Maybe on positioning and marketing.
- Good metrics must follow the three As: Actionable, Accessible, and Auditable.
- Go by actionable metrics, not vanity metrics. Vanity metrics are those where the cause and effect relationship isn't clear. You don't know what change you made that led to an increase (or decrease) in this metric, like page views. Or maybe it has nothing to do with you, like a mention in a popular blog. An actionable metric is the number of customers. If it decreases by 50K, you know something is wrong. You can work on it and hopefully fix it. That's actionable.
- Accessible means that you can understand what it means, like a "customer" as opposed to a "hit on your web site".
- Auditable means that if a question arises as to the validity of the metrics, you should be able to verify it. The best way is to talk to customers, who will also tell you why something is happening, not just that it is. In addition, the mechanism that generates the results must not be too complex for the metric to be auditable.
Chapter 8: Pivot
- Companies that can't pivot may be stuck in the land of the living dead, neither growing quickly enough nor dying, consuming the time and money of the people involved.
- Launching early and iterating means that if you pivot, you waste less time, energy and money. If you drag it on, you won't want to pivot because of sunk costs.
- Go by actionable metrics, rather than vanity metrics that can give a feeling of false success.
- A startup's runway is conventionally defined as the number of months, but it should be defined as the number of pivots it can make.
- Don't cut costs by slowing down the build - measure - learn loop. Then you're just going out of business slowly.
- Two telltale signs that you need to pivot are the decreasing effectiveness of product experiments and the general feeling that product development should be more productive.
- Not having PR and media attention on you is good, because you can pivot without drama.
- Some types of pivots are:
+ Zoom-in pivot (where you focus on a subset of your original product)
+ Zoom-out pivot
+ Customer segment pivot (where you realise that you're more successful with different customers from the ones you expected)
+ Customer need pivot (where you discover that the customer has more important needs than the ones you thought they had)
+ Platform pivot (where an app becomes a platform or vice-versa)
+ Value capture pivot (commonly called monetisation, but monetisation is more like a feature while value capture is more central to the product)
+ Engine of Growth pivot (moving between viral, sticky and paid engines of growth)
+ Channel pivot (moving between sales channels)
+ Technology pivot
+ A pivot is a hypothesis; we don't know ahead of time whether it will succeed.
Chapter 9: Small Batch Sizes:
- Optimise the entire system, not a piece of it.
- Have a small batch size: deliver work in smaller units.
- Launch each feature independently.
- Continuous deployment. Launch many times a a day.
- Have lots of automated tests.
- Have your designer sit with the engineer and have them design and implement each screen together. As opposed to your designer working by herself for weeks and then delivering the entire result at once.
- Smaller batch sizes are actually more efficient, despite our intuition.
- Quality problems can be identified much sooner. If you make something no one wants, you'll learn sooner.
- Large-batch systems tend to malfunction, and when they do, people blame themselves.
- Large batches lead to multiple rounds of rework.
- ... and to still larger batches, which becomes a death spiral.
- And to interruptions, people being blocked on others, communication gaps, scheduling problems, and so on.
- The longer a project takes, the more bugs, problems and conflicts it has.
- Have minimum work in progress.
- Pull, don't push. Start from the hypothesis that needs to be validated or the experiment that needs to be run, and pull work from product development in the smallest batch size to validate that hypothesis.
- Small batches will also let you work with less capital.
- Companies can stay lean as they grow. They don't need to become bureaucratic.
Chapter 10: Engines of Growth:
- New customers come from the actions of past customers. This happens in four ways:
1) Word of mouth.
2) As a side effect of product usage
3) Through advertising
4) Through repeat purchases (sticky)
- Each of these engines has a feedback loop that leads to success.
- One of the most expensive forms of potential waste for a startup is spending time arguing about prioritisation of new features.
- The engines of growth help you prioritise better.
- There are always a zillion new ideas about how to make the product better floating around, but most make a difference only at the margins. They are merely optimisations.
- If you're using the sticky engine of growth, you will grow if the rate of new customer acquisition exceeds the churn rate. Track both.
- The metric to focus on is the compound growth rate. If it's high, you're doing well.
- Activation rate and revenue per customer have little impact on growth. (They're better suited to testing the value hypothesis)
- If the churn rate and customer acquisition rate are the same, then the standard intuition to invest in sales and marketing doesn't work, because you will lose your new customers as well.
- This is an example of vanity metrics misleading you.
- The viral engine of growth depends primarily on people sharing it with friends, as a central feature of the app, not an afterthought.
- The metric to focus on is the viral coefficient, which determines how quickly your app spreads. If it's 0.1, it means one of ten people using the app are referring a friend.
- If the coefficient is less than one, the cycle of growth fizzles: if you start with 100 users, they refer 10 more, who refer one more, at which point the loop ends.
- Exactly 1 gives you linear growth: if you gain 10 new users this week, you will gain 10 the week after that, 10 the third week, and so on. That's not good enough.
- The coefficient needs to be > 1 for exponential growth.
- Tiny changes in this number cause dramatic changes. If it's 1.01 per week, you end the year with twice as many users as you began.
- If it's 1.1, you end the year with 140 times as many users as you began.
- These are often free and ad-supported because being asked to pay comes in the way of viral growth.
- The paid engine of growth relies on more paid sales. It's different from the sticky engine, which relies on repeat sales to the same customers.
- If one company earns a revenue of ₹10 per user, and another earns ₹100, and they both reinvest their profit in acquiring new users, which one grows faster? A: It depends on the Cost Per Acquisition (CPA). If they are proportional, like ₹2 and ₹20, both grow at the same rate.
- For faster growth, you need to reduce CAC or increase revenue.
- The lifetime value (LTV) of a customer is the total revenue they generate over their lifetime, minus variable costs.
- If LTV > CPA, the company will grow.
- If < it won't, despite one-time tricks like using invested capital or publicity stunts.
- Don't pursue multiple engines of growth, since it's complex to model all these effects simultaneously. Startups usually focus on one.
- Product-market fit is the moment when a startup finally finds a widespread set of customers that resonate with its product.
- A great market — a market with lots of potential customers — pulls product out of the startup. In a terrible market, the best product and best team are going to fail.
- When you achieve product-market fit, it's exhilarating.
- If you have to ask, you're not there yet.
- Depending on which engine you're using, look at the appropriate metric, like viral coefficient for a viral engine. If it's 0.9 or more, you're on the verge of success.
- The number doesn't matter as much as the direction and degree of progress.
- Every engine eventually runs out of fuel.
- Moving from early adopters to mainstream users is not automatic. The engine may stop and may require tremendous additional effort.
- Be careful to not confuse growth coming from an engine already working efficiently for growth from product development. It's possible your work has no effect, in which case you can have a sudden stop.
- To prevent this, focus on actionable metrics rather than vanity metrics, and use innovation accounting rather than traditional accounting. In other words, are you making progress on your actionable metrics? Are you running experiments and building MVPs to improve them? Are you verifying that, if you ran an experiment to reduce the churn rate, for example, that it has actually reduced the churn rate, rather than assuming that it did from increased revenue?
The author introduces the readers to a framework Build-Measure-Learn feedback Loop—an agile product development technique that follows the concept of build faster and ship sooner which is commonly known as Minimum Viable Product (MVP) building methodology. MVP methodology is used to build faster with minimum but crucial features, test those to validate assumptions against the measurable feedback and inputs from the customers. These learnings are subsequently used to build next cycle of MVP by either persevering on the same path or pivoting to a new one. Each concept is further explained with real life experiences and instances from startups and corporate organizations alike, which makes this book very interesting and engaging.
The author has provided insightful learnings on identifying project wastages in terms of time, money and other vital resources. He has provided tools on measuring the feedback/data using what he calls 3 A’s metrics: Actionable, Accessible and Auditable, and warns against the pitfalls of vanity metrics that is loaded with unwanted and useless data. His wisdom on Pivot or Persevere is particularly very useful, he guides the reader on how to identify such stages but also provides an understanding of different flavors of change that can be adopted to redefine the strategy and continue with the loop.
He talks about how to accelerate and grow once we are on the path of perseverance, by fueling the growth engine at necessary intervals aiding us with several tools and framework like sticky, viral and paid engine of growth. He also emphasis on how the companies should continue to build an adaptive organization by continues learning, evolving ideas into innovations that results in developing new sources to fuel the growth engine.
The author is greatly inspired by The Toyota Way by Jeffery K. Liker and The Innovators Dilemma by Clayton Christensen. He has often listed examples and shared his learnings from these books that contributed to this technique. The section on wisdom of Five Why’s and Adapting to smaller batches can be adapted by anyone to quickly adjusts process and performance to grow more effective.
I recommend this book not just to entrepreneurs, but also to managers, leaders, innovators and people who are interested in personal growth. Even large organization can use these methodologies, Eric has very cleverly provided suggestions to build adaptive organization that can oil the growth engine and how to nurture disruptive innovation. One of the most likeable character of the author is that he is very candid on talking about his own failures and short sightedness during his early days as a CTO. And the lessons learnt from others mistakes can be priceless.
Top reviews from other countries
I really appreciated the book’s celebration that you don’t have all the answers and you shouldn’t if you’re a startup with an innovative solution. The major point, however, is that you shouldn’t pretend or act like you do but embrace the uncertainty and develop an experimental approach to delivering a Minimum Viable Product – build, measure, learn.
I found The Lean Startup not only great for advice, techniques and the analogous stories to help reinforce the approach, but it is an inspirational book that dares you to challenge everything and rationalise with customer validation that your vision is viable and scalable. When a book affects me it starts a chain reaction in my thought process so that I either gain a better understanding of where I need to go or may enable me to articulate what has been sitting just out of reach in my mind. This is one of those books.
Other books that reinforce this new startup environment and are worth reading include:
• Business Model Generation – Alexander Osterwalder
• Four Steps to the Epiphany – Steve Blank
• The Startup Owner’s Manual – Steve Blank
• Running Lean – Ash Maurya
Most important is the idea that you must prove your product or service innovation out in the market quickly.
There is so much uncertainty involved with developing an original product idea that traditional management techniques evolved in established businesses are inadequate in start-ups.
Instead, develop a minimum viable product (MVP) to test key elements of your business idea and get it out to potential customers. See what their response rates are compared with your expectations. Keep learning and innovating until you have a product that is proven and a marketing method that works effectively.
While I've spent more than 30 years studying marketing, I'm an accountant by training. I found the section on innovation accounting and cohort analysis to be an eye-opener.
This is an outstanding book. While its origins lie in software application development, the concepts have been proven in a vast range of different industries. In some ways, it echoes ideas in Michael Masterson excellent book "Ready, Fire, Aim" that also emphases the vital importance of early validation of a business idea in the market.
This is very highly recommended.
Paul Simister is a business coach who helps business owners who are stuck, get unstuck.
Im looking to eventually start my own business, and this was recommended to me by a friend who is a CEO of a big company as something that really helped him
Whilst it is slow to get started, its good because it used lots of contextual stories etc
Overall sso far a really interesting read but definitely a challenge to follow in its footsteps
I reckon it'll be 5 stars but seen as ive not yet got through it all yet which is why ive given it 4 at the moment
It is slightly biased towards tech companies, partculalrly the product refinement and testing, but there are some nice non-tech case studies that he works through methodically to demonstrate how the lean principles can be applied to any type of startup.