The Lean Startup
Tags: #business #entrepreneurship #startups #innovation #agile #lean startup
Authors: Eric Ries
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Overview
This book, “The Lean Startup,” introduces a new approach to building successful companies and products. It rejects the traditional notion that success comes from having the ‘right stuff’ or being in the right place at the right time. Instead, it emphasizes the importance of process, learning, and experimentation. It argues that entrepreneurship is a form of management, and like any management science, can be learned and improved. The book details a set of practical techniques for quickly testing business hypotheses, iterating products based on customer feedback, and pivoting when necessary. It introduces the concept of “validated learning,” which involves proving with data from real customers that a team has discovered valuable truths about their business. Central to this approach is the “Build-Measure-Learn” feedback loop, which emphasizes fast iteration and feedback from real customers. It also advocates for working in “small batches” and creating “innovation sandboxes” to accelerate learning and reduce waste. The book draws heavily on principles of lean manufacturing and agile development but adapts them to the unique circumstances of entrepreneurship. It argues that traditional accounting metrics are insufficient for evaluating startup progress and instead proposes a new system of “innovation accounting.” Ultimately, the Lean Startup aims to empower entrepreneurs and managers to create successful, sustainable companies by providing them with the tools to navigate the uncertainty inherent in building something new.
Book Outline
1. START
Entrepreneurship is a management science that can be learned. We can’t depend on ‘just do it’ intuition, or large corporations’ playbooks to deal with uncertainty. Instead, we need a new discipline of ‘entrepreneurial management’.
Key concept: A startup is a human institution designed to create a new product or service under conditions of extreme uncertainty.
2. DEFINE
Entrepreneurs don’t only exist in garages. Anyone creating something new under conditions of high uncertainty can benefit from entrepreneurial management. This definition of entrepreneurship includes not only tech startups, but also innovators in large organizations and public institutions.
Key concept: A startup is a human institution designed to create a new product or service under conditions of extreme uncertainty.
3. LEARN
Instead of merely “learning” as an excuse for failure, startups need to focus on validated learning, proving with data from real customers that a team has discovered valuable truths about their business. Validated learning provides a much faster and more accurate feedback loop than traditional business planning.
Key concept: “Learning” is the oldest excuse in the book for a failure of execution. It’s what managers fall back on when they fail to achieve the results we promised.
4. EXPERIMENT
Startups should treat their work as experiments designed to gain validated learning. Like scientific experiments, startups should have a clear hypothesis, predict the results, and then rigorously test those predictions with real data from customers.
Key concept: If you cannot fail, you cannot learn.
5. LEAP
The Build-Measure-Learn feedback loop emphasizes fast iteration and feedback from real customers. Rather than spending years building a product in hopes of ‘getting it right,’ launch early with a minimum viable product (MVP). Gather data from customer interactions to learn, and use those learnings to rapidly iterate the product.
Key concept: The Build-Measure-Learn Feedback Loop
6. TEST
The goal of the MVP is not to ship a perfect product, but rather to begin the cycle of learning. It’s not a prototype built only to answer technical questions, but a tool to test fundamental business hypotheses. It can take many forms, from a simple ‘smoke test’ or landing page, to a functioning early version of the product.
Key concept: 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.
7. MEASURE
Innovation accounting is a new kind of accounting, specifically for startups, that uses actionable metrics to assess real progress. This system uses cohort analysis to track how groups of customers behave over time, and split-testing to systematically evaluate the impact of product changes on customer behavior. This allows teams to make data-driven decisions, even under conditions of high uncertainty.
Key concept: Cohort Analysis
8. PIVOT (OR PERSEVERE)
A pivot is a structured course correction that involves changing one or more fundamental hypotheses about the product, strategy, or engine of growth. After going through the build-measure-learn feedback loop, teams should assess if they are making sufficient progress and use that data to decide to pivot or persevere.
Key concept: A pivot is a structured course correction designed to test a new fundamental hypothesis about the product, strategy, and engine of growth.
9. BATCH
By working in small batches, startups can increase their speed and agility. Small batches allow for more rapid iteration and faster learning, as well as less wasted effort. They also increase quality by making problems more visible early in the development process.
Key concept: The one envelope at a time approach is called “single-piece flow” in lean manufacturing. It works because of the surprising power of small batches.
10. GROW
Startups operate using one of three ‘engines of growth’: sticky, viral, or paid. Each engine has a unique set of dynamics and success metrics. Startups should focus on maximizing the effectiveness of their chosen engine, and when they encounter growth challenges, use this framework to identify potential solutions.
Key concept: New customers come from the actions of past customers.
11. ADAPT
Adaptive processes are essential for startups to grow successfully. Using a technique called the Five Whys, startup teams can identify the root causes of problems, make proportional investments in prevention, and continuously improve their operating model. This technique can be adapted to create a variety of internal systems and processes.
Key concept: If a mistake happens, shame on us for making it so easy to make that mistake.
12. INNOVATE
Large organizations can regain their capacity for innovation by building ‘innovation sandboxes’, and cultivating entrepreneurial talent within. By giving innovation teams clear constraints, a personal stake in the outcome, and the autonomy to build, ship, and learn, large organizations can capture the same benefits of speed and learning that are available to startups.
Key concept: Entrepreneur Is a Job Title
13. EPILOGUE: WASTE NOT
The goal of entrepreneurship is not efficiency, but rather effectiveness. To avoid the waste of building things no one wants, we must focus on building a learning organization that uses the scientific method to rigorously test its vision. This approach allows us to harness our creative potential to create value and drive progress.
Key concept: “There is surely nothing quite so useless as doing with great efficiency what should not be done at all.”
14. JOIN THE MOVEMENT
The Lean Startup movement has gone global! Resources and communities for Lean Startup practitioners are springing up all over the world. This chapter provides links to some of the best books, blogs, and online communities. Reading is good; action is better.
Key concept: I maintain an official website for The Lean Startup at http://theleanstartup.com, where you can find additional resources, including case studies and links to further reading.
Essential Questions
1. Why do most startups fail, and how does the Lean Startup method propose to improve their chances of success?
The Lean Startup methodology aims to address the high failure rate of startups and new product launches. It does this by providing a scientific approach to entrepreneurship, emphasizing validated learning, rapid iteration, and continuous innovation. The book argues that traditional business planning methods are ill-suited for the uncertainty inherent in startups. Instead, it advocates for building minimum viable products (MVPs) to test hypotheses, using innovation accounting to track progress, and pivoting when necessary. The Lean Startup approach is designed to be adaptable and can be applied in any industry or sector.
2. What is a startup according to the Lean Startup, and who is an entrepreneur?
The Lean Startup defines a startup as a human institution designed to create a new product or service under conditions of extreme uncertainty. This definition emphasizes that entrepreneurship is not limited to tech startups in garages but can exist within any organization or industry where new products or services are being developed under uncertain conditions. This includes intrapreneurs working within large companies, social entrepreneurs tackling social problems, and even government agencies launching new initiatives.
3. What is validated learning, and how does it differentiate the Lean Startup from traditional business planning?
Validated learning is the process of demonstrating empirically that a team has discovered valuable truths about a startup’s present and future business prospects. It is more concrete, accurate, and faster than market forecasting or traditional business planning. It involves testing key hypotheses with MVPs and using data from real customers to validate or invalidate those hypotheses. This approach helps startups avoid the common pitfall of ‘achieving failure’ – successfully executing a plan that leads nowhere.
4. How does the Lean Startup approach use the scientific method to improve the odds of building a successful company?
The Lean Startup encourages entrepreneurs to treat their work as experiments designed to gain validated learning. This involves formulating a clear hypothesis, predicting the results, and then rigorously testing those predictions with real data from customers. The process is iterative and data-driven, emphasizing fast feedback cycles and continuous learning. This scientific approach helps startups avoid the common pitfall of ‘just do it’ entrepreneurship, where teams build products without a clear understanding of customer needs or a systematic way to test their assumptions.
5. What is the Build-Measure-Learn feedback loop, and how does it help startups create value?
The Build-Measure-Learn feedback loop is a core principle of the Lean Startup. It involves building a minimum viable product (MVP) to test a key hypothesis, measuring customer response to the MVP, and then learning from that data to inform the next iteration. This iterative process emphasizes speed and learning over perfection, encouraging startups to get their product in front of customers as quickly as possible to gather feedback and iterate. This approach helps startups avoid the waste of building products nobody wants.
Key Takeaways
1. Build Minimum Viable Products (MVPs)
A Minimum Viable Product (MVP) allows startups to test their key assumptions with minimal effort and quickly gather feedback from real users. It helps validate the product’s value proposition and engine of growth before significant resources are invested in building a full-featured product. The MVP doesn’t need to be perfect; it simply needs to be good enough to learn from early adopters.
Practical Application:
An AI product team could apply this by launching a simple chatbot that only handles a narrow range of user queries. By measuring user engagement and iteratively improving the chatbot’s responses, the team can gain valuable insights before investing in a more complex and fully-featured AI assistant.
2. Test hypotheses with Split-Testing
Split-testing, a technique where different versions of a product are offered to customers simultaneously, allows startups to systematically evaluate the impact of product changes on customer behavior. By measuring the difference in key metrics between the two groups, teams can make data-driven decisions about what changes to keep and which to discard.
Practical Application:
A team developing a new AI-powered marketing automation platform could use split-testing to evaluate the effectiveness of different email subject lines, ad copy, or landing page designs. By measuring conversion rates for each variation, they can identify the most effective approach.
3. Identify root causes with Five Whys
The Five Whys is a problem-solving technique that helps teams identify the root causes of problems by repeatedly asking “Why?” at least five times. This approach forces teams to look beyond superficial symptoms and understand the underlying human and systemic factors contributing to the problem. By addressing the root cause, teams can implement more effective solutions and prevent the problem from recurring.
Practical Application:
An AI team struggling to improve the accuracy of their machine learning model could use the Five Whys to understand the root causes of errors. By repeatedly asking “Why?” they might uncover underlying issues with data quality, feature selection, or model architecture, leading to more effective solutions.
Suggested Deep Dive
Chapter: Chapter 13: Epilogue: Waste Not
This chapter delves into the dangers of mistaking efficiency for effectiveness, a crucial concept for AI engineers working on complex projects where the ‘right thing to build’ might not be obvious. It also introduces the thought-provoking concept of a Long-Term Stock Exchange (LTSE), which could have significant implications for funding and incentivizing long-term AI research.
Memorable Quotes
Introduction. 10
“The mundane details, the boring stuff, the small individual choices don’t matter. If we build it, they will come. When we fail, as so many of us do, we have a ready-made excuse: we didn’t have the right stuff.”
Why Startups Fail. 16
“Planning and forecasting are only accurate when based on a long, stable operating history and a relatively static environment. Startups have neither.”
VALIDATED LEARNING AT IMVU. 41
“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.”
WHY FIRST PRODUCTS AREN’T MEANT TO BE PERFECT. 90
“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.”
OPTIMIZATION VERSUS LEARNING. 115
“If you are building the wrong thing, optimizing the product or its marketing will not yield significant results.”
Comparative Analysis
This book presents a unique contribution to the field of entrepreneurship and product development. While other books like Steve Blank’s ‘The Four Steps to the Epiphany’ focus on customer development, and Clayton Christensen’s ‘The Innovator’s Dilemma’ analyzes disruptive innovation, ‘The Lean Startup’ provides a holistic framework, integrating these concepts with agile development and lean manufacturing principles. It offers a practical methodology applicable across industries, unlike books that primarily focus on specific sectors like tech. Notably, Ries’ emphasis on ‘validated learning’ and the Build-Measure-Learn loop contrasts with the traditional emphasis on extensive planning and big upfront investments. This data-driven approach encourages faster iteration and reduces the risk of building products nobody wants.
Reflection
This book serves as a powerful antidote to the ‘gut feeling’ approach to entrepreneurship, urging a scientific rigor that can be valuable not just for startups, but for any organization facing high uncertainty. However, the book’s focus on rapid iteration and MVPs might lead some to neglect the importance of long-term vision and deep technical innovation. While Ries acknowledges that not all ideas are suitable for MVP testing (especially those reliant on scientific breakthroughs), he doesn’t delve deeply into this. The risk is that an overemphasis on rapid iteration might lead to incremental improvements at the expense of truly disruptive innovations. Despite this, the Lean Startup’s emphasis on validated learning and data-driven decision-making offers a valuable framework for navigating the unpredictable world of innovation, helping teams build not just products, but sustainable businesses.
Flashcards
What is validated learning?
The process of demonstrating empirically that a team has discovered valuable truths about a startup’s present and future business prospects.
What is a startup, according to the Lean Startup?
A human institution designed to create a new product or service under conditions of extreme uncertainty.
What is a minimum viable product (MVP)?
The version of a 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.
What is innovation accounting?
Turning the leap-of-faith assumptions into a quantitative financial model and using actionable metrics to track progress.
What is a pivot?
A structured course correction designed to test a new fundamental hypothesis about the product, strategy, and engine of growth.
What is the fundamental rule of sustainable growth?
New customers come from the actions of past customers.
What are the three engines of growth?
Sticky, viral, and paid.
What is the Five Whys method?
A technique for identifying the root cause of problems by repeatedly asking “Why?” at least five times.