Book Notes #03: The Lean Startup by Eric Ries

Title: The Lean Startup
Author: Eric Ries
Year: 2011
Pages: 320

What if building a business didn’t have to feel like a giant leap into the dark?

That’s the question at the heart of The Lean Startup by Eric Ries. Instead of chasing perfection or gambling on hunches, this book offers something refreshingly different: a way to build smarter, learn faster, and waste a whole lot less time.

Whether you’re launching your own product, leading a team inside a big company, or just curious about how great ideas grow, this book gives you the tools—and the mindset—to stop guessing and start learning.

It’s not just about building things right; it’s about building the right things.

As a result, I gave this book a rating of 8.0/10.

For me, a book with a note 10 is one I consider reading again every year. Among the books I rank with 10, for example, are How to Win Friends and Influence People and Factfulness.

3 Reasons to Read The Lean Startup

Book Overview

What if everything we thought we knew about starting a business was wrong?

Most of us picture entrepreneurship as a mix of bold ideas, brilliant founders, sleepless nights, and maybe a little bit of luck. Build a great product, launch big, hope for the best. But what if that very process—the way we’ve been building companies for decades—is the reason so many startups fail?

That’s the question Eric Ries sets out to answer in The Lean Startup. And his answer flips the whole game.

Ries knows failure. His earlier venture had all the right ingredients—talented team, exciting product, even strong execution. But they were building something nobody actually wanted. So when he co-founded IMVU, he tried a radical shift. Instead of perfecting the product for months, they released it early—really early. It was buggy, incomplete, and honestly kind of embarrassing. But it gave them one thing they desperately needed: real customer feedback. And that changed everything.

That experience laid the foundation for what Ries calls the Lean Startup method. At its heart is a deceptively simple idea: instead of betting everything on a polished final product, start small with a Minimum Viable Product—a version just good enough to test whether your assumptions are even correct. Launch, learn, and improve through a fast feedback loop Ries calls Build-Measure-Learn. Each cycle gets you closer to what your customers actually need, not just what you think they want.

This book isn’t just about tech startups or Silicon Valley. It’s a wake-up call for anyone trying to build something new in uncertain conditions—whether you’re at a scrappy startup, a global corporation, or even a nonprofit. Ries argues that the biggest waste isn’t failed code or unsold inventory. It’s people spending time, energy, and passion building the wrong thing—beautifully and efficiently.

What makes The Lean Startup especially powerful is how it challenges traditional business logic. Most companies make long-term plans, set clear milestones, and measure success with metrics like revenue and headcount. Ries flips that. In the early days, your job isn’t to scale—it’s to learn. Is your idea viable? Do customers care? Will they come back? That’s what he calls validated learning, and it becomes the true measure of progress.

Along the way, Ries introduces concepts like pivoting—when you realize your current approach isn’t working and need to shift direction without abandoning your vision. He also shows how powerful continuous deployment and small batch releases can be, not just in software but in any industry where learning quickly can save you from disaster.

One of the best examples in the book is Zappos. Before it became a billion-dollar company, its founder simply posted photos of shoes from local stores online. When someone bought a pair, he went out, bought them retail, and shipped them himself. It wasn’t efficient, but it proved the business model before they spent a dime on inventory or warehousing. That’s the Lean Startup in action—testing assumptions before scaling effort.

But the book goes beyond tactics. It invites a deeper reflection on how we think about innovation itself. Ries warns about turning Lean into just another set of buzzwords. Terms like “pivot” and “MVP” can become empty jargon unless grounded in genuine curiosity, rigorous testing, and honest reflection. And perhaps most importantly, he reminds us that this approach isn’t about removing the human side of entrepreneurship—it’s about protecting it. Vision, creativity, and bold ideas still matter. The Lean Startup just gives them a better chance to survive.

Ries ends on a hopeful note. He believes we’re at a turning point—not in how we build products, but in how we build systems that let people do their best work. Imagine a world where companies invest in long-term innovation, where ideas are tested quickly and fairly, and where we stop wasting people’s time on the wrong things. That’s not just good for business. That’s good for people.

So, if you’ve ever wondered why your big launch flopped, or felt stuck building something that no one seems to care about, The Lean Startup offers a way out. It doesn’t promise instant success. But it does give you a map—and a mindset—for navigating the chaos of creation with purpose, humility, and speed.

And rather than adopting a static, product-centric approach, test your idea on your customers: respond to their feedback, and constantly be prepared to adjust your product, as well as your business.

The Lean Startup outlines key principles for successful startups, such as:

• Start with a clear vision and purpose.
• Test and validate ideas quickly.
• Use customer feedback to refine products and services.
• Focus on learning rather than achieving specific goals.
• Develop a culture of experimentation and continuous improvement.
• Measure progress and performance.

The point of a startup is to get through the Build-Measure-Learn cycle as quickly as possible to figure out what your customers will pay for. 

The Lean Startup also incorporates customer feedback into the productivity equation. After creating an initial product, further iterations must incorporate customer responses to the product.

1. Start Small and Iterate: Rather than aiming for perfection from the outset, entrepreneurs should focus on launching a minimum viable product and iterating based on customer feedback.
2. Measure What Matters: Instead of getting bogged down in vanity metrics, entrepreneurs should focus on measuring key metrics that indicate progress and success.
3. Experiment Often: Entrepreneurship is inherently risky, but by conducting frequent experiments and learning from both successes and failures, entrepreneurs can increase their chances of success.
4. Be Customer-Centric: Building a successful business requires a deep understanding of customer needs and preferences. By prioritizing customer feedback and engagement, entrepreneurs can create products and services that resonate with their target audience.

Strongly based on widespread practices such as Lean Thinking, Customer Development, Agile Methods, Business Model Generation, MVP, and many other concepts, Lean Startup refers to a group of scientific methods to reproduce the success of well-known startups instead of just developing a system and “seeing how it goes”.

The Lean Startup Method:

• Entrepreneurs are everywhere – Huge companies can (and should) have entrepreneurs
• Entrepreneurship is management
• Validated Learning – Startups exist to learn how to build a sustainable business
• Build-Measure-Learn – Run through this loop as fast as possible
• Innovation accounting – how to measure progress and prioritize work

Chapter by Chapter

Chapter 1 – Start

Entrepreneurship needs its own kind of management
Eric Ries kicks off the chapter by challenging a common misconception: that management has no place in startups. Many entrepreneurs reject traditional management styles, fearing bureaucracy and a loss of creativity. But without any structure, startups often fall into chaos. Ries argues that startups aren’t just a smaller version of a big company—they’re something different. They need a unique kind of management designed specifically for high uncertainty. He makes the case that entrepreneurship itself should be seen as a form of management.

A global wave of entrepreneurship—but a lot of waste
We’re living in what Ries calls an entrepreneurial renaissance. Thanks to technology and global shifts, it’s easier than ever to start something new. But with that ease comes risk. Without a solid framework, too many ventures waste time, talent, and energy on ideas that never get off the ground. Ries points out that while companies have become highly efficient at building things, they often don’t stop to ask: are we building something people actually want?

Lean thinking goes beyond factories
The Lean Startup takes inspiration from lean manufacturing, especially the approach developed at Toyota. In factories, lean thinking focused on reducing waste, accelerating cycles, and building quality from within. Ries takes those ideas and adapts them for startups, where instead of producing cars or widgets, you’re producing learning. He introduces the idea that the true measure of startup progress isn’t how much you build, but how much validated learning you achieve. This is what helps eliminate the waste of building something nobody wants.

Startups need feedback loops, not rigid plans
Ries uses a great metaphor here: startups are like cars, not rockets. A rocket requires precise plans upfront and has little room for correction mid-flight. A car, on the other hand, is steered continuously—you make small adjustments based on feedback as you drive. Startups should operate the same way. Ries introduces two kinds of feedback loops: the engine of growth (what powers the business) and the steering mechanism (how you adapt based on what you learn). He warns against the “achieving failure” trap—when teams execute a flawless plan that turns out to be based on the wrong assumptions.

Vision, strategy, and product: knowing what can change
Startups work toward a big vision. To get there, they develop a strategy, and from that, a product. The product might change often, and the strategy may need to pivot, but the vision usually stays steady. Ries emphasizes that setbacks should be seen as opportunities to learn and course-correct, not signs of defeat. The key is knowing when to pivot and when to persevere—something the Lean Startup method is built to help with.

In the end, Ries makes it clear that entrepreneurship isn’t a chaotic free-for-all, nor is it about rigid plans. It’s about managing uncertainty through fast cycles, constant learning, and thoughtful adjustment. This chapter lays the foundation for why we need a new way to build businesses—and how Lean Startup gives us a map for doing just that.

Chapter 2 – Define

Who, Exactly, Is an Entrepreneur?
In this chapter, Eric Ries expands the definition of “entrepreneur” beyond the typical image of young, garage-based innovators. He highlights that entrepreneurs exist everywhere, not just in startups, but within large companies as well. Ries emphasizes that entrepreneurs inside big companies—often referred to as “intrapreneurs”—face many of the same challenges as those in small startups. They need to foster innovation, take risks, and build something new in uncertain environments. He shares a story about Mark, a successful manager at a large corporation, who had all the traits of an entrepreneur but struggled to convert ideas into breakthrough innovations because he lacked a clear process. This shows that entrepreneurship isn’t limited by company size or resources—it’s about creating something new under uncertain conditions, which can apply to anyone, anywhere, whether in a startup or a large company.

If I’m an Entrepreneur, What’s a Startup?
Ries defines a startup as “a human institution designed to create a new product or service under conditions of extreme uncertainty.” This definition is broad, focusing not on the size or sector of the company but on the challenges it faces. The key here is that startups operate in environments where the future is unpredictable, and success cannot be determined purely through execution of a well-known plan. He explains that most tools from traditional management are inadequate for this context because they assume stability. Startups, whether in a garage or a corporation, thrive on experimentation, learning, and iteration.

The SnapTax Story
The chapter continues with the story of SnapTax, a product developed by Intuit—a large company—not a startup. The SnapTax team innovated by allowing users to take pictures of their tax forms with their phones, drastically simplifying the tax filing process. Even though Intuit is a large company with over 7,000 employees, the team worked like a startup, with little funding and a small team. The success of SnapTax wasn’t due to intuition or luck; it was a result of applying entrepreneurial principles within an established company. Ries uses this story to show that large organizations can cultivate innovation, but it requires a new management approach that allows for experimentation and risk-taking, much like what’s found in startups.

A Seven-Thousand-Person Lean Startup
The chapter wraps up by discussing how Intuit, under the leadership of Scott Cook, transformed its management culture to foster innovation. Even though Intuit had established products and a large customer base, Cook recognized that their innovation model wasn’t working as well as it should. He realized the company needed to create systems that allowed for rapid experimentation, much like the Lean Startup approach. By introducing more testing and iteration into their product development processes—like testing 500 different changes during tax season—Intuit was able to innovate faster and more effectively. This shift from rigid, slow-moving processes to fast, adaptable experimentation is what Cook believes will enable large companies to maintain their competitive edge.

In this chapter, Ries challenges us to think about entrepreneurship as a skill that can be applied in all environments, not just startups. Whether you’re in a big company or building a product from scratch, the principles of Lean Startup—experimentation, iteration, and rapid feedback—apply to everyone who is creating something new under conditions of uncertainty.

Chapter 3 – Learn

Validated Learning vs. Traditional Progress Measures
Eric Ries starts this chapter by addressing a fundamental issue every entrepreneur faces: how do you measure progress when you’re working under extreme uncertainty? Traditionally, businesses measure success by hitting milestones, staying on budget, and meeting quality standards. But Ries challenges this thinking. In startups, these measures don’t matter much if you end up building something nobody wants. Entrepreneurs often comfort themselves with the excuse of “learning” when things go wrong, but learning alone doesn’t pay the bills or build a business. The solution, according to Ries, is validated learning. Unlike traditional learning, validated learning is a rigorous, data-driven approach to measuring progress. It’s about proving that your team has discovered real, actionable insights about your business, based on real customer feedback, not just theoretical knowledge.

The IMVU Example: A Story of Learning from Failure
Ries shares a detailed example from his own experience with IMVU to illustrate the concept of validated learning. When they first launched the product, it didn’t perform as expected. Despite working hard to make the product better, customer engagement remained low, and the revenue was barely trickling in. The team had put a lot of effort into building a product that integrated with existing instant messaging networks, assuming that customers would appreciate the added value of an IM add-on. However, when they tested the product with real customers, they found out that their assumptions were wrong. Customers didn’t want an add-on; they wanted a standalone IM network. This was a painful realization, but it led them to pivot, adjusting the product to meet customers’ real needs. This was their first big lesson in validated learning.

Value vs. Waste
One of the most significant lessons from IMVU’s early days was realizing how much time and effort they had wasted on features that customers didn’t want. Ries discusses how lean manufacturing principles, which focus on eliminating waste, can be applied to startups. In the case of IMVU, building interoperability with many different IM clients turned out to be unnecessary. They could have learned the same things with much less effort if they had focused on fewer networks or even no networks at all. The goal, Ries argues, is to find the balance between value-creating activities and waste. Learning what your customers want and will use is the most valuable insight a startup can gain, and everything that doesn’t contribute to that learning is waste.

The Importance of Validation
Ries stresses that validated learning isn’t just about making educated guesses. It’s about testing those guesses with real customers and collecting data to see if they’re correct. At IMVU, the team eventually switched from guessing what customers wanted to experimenting with their product, changing it based on customer feedback and behavior. This process of continuous iteration and testing helped them improve their product and, eventually, their business metrics. Importantly, Ries notes that validated learning is not only about testing the product but also testing business assumptions, such as revenue models, customer segments, and marketing strategies.

The Audacity of Zero
Ries wraps up this chapter by discussing the “audacity of zero” in startup metrics. Early on, when a startup has no customers or revenue, it’s easier for investors and stakeholders to imagine the possibility of future success. But once a startup starts to generate small numbers, those small numbers can create doubts about whether the business will ever scale. Ries calls this the “audacity of zero” because, even though early numbers might be small, they provide a more accurate view of progress than relying on vague assumptions. He argues that the key to overcoming this challenge is to demonstrate that the startup’s development efforts are leading toward success, not through vanity metrics but through the validated learning that shows real customer engagement and progress toward product-market fit.

Lessons Beyond IMVU
Ries concludes by reflecting on how the lessons learned from IMVU apply to startups across industries. He warns against focusing too much on tactics—like building a low-quality prototype or using small revenue targets to drive accountability—without understanding the broader principles of Lean Startup. The real takeaway is that startups should be treated as experiments, where every action—whether building a product, running a marketing campaign, or testing a new feature—is part of a systematic process to learn what works and what doesn’t. By applying this scientific approach, startups can navigate uncertainty and increase their odds of success.

Chapter 4 – Experiment

The Importance of Experiments in Startups
In this chapter, Eric Ries underscores that startups should operate as ongoing experiments. Instead of relying on traditional business plans, which often fail to account for the high uncertainty in new ventures, startups need to think of each decision as a hypothesis to be tested. The goal is to figure out which aspects of a business model are working and which aren’t, to ultimately build a sustainable business. Ries compares the process to the scientific method, where each assumption is treated as a testable hypothesis. This approach shifts the focus from simply building a product to learning about what works, what doesn’t, and why.

From Alchemy to Science
Ries draws a parallel between old alchemical methods and traditional startup thinking, which often rely on hope and guesswork. In contrast, Lean Startup encourages a more rigorous approach akin to science. Every experiment starts with a hypothesis, which is then tested empirically. By gathering data and feedback from real customers, entrepreneurs can adjust their business model before committing too much time and money. This method not only helps startups avoid building things that nobody wants but also ensures that they learn as they go, adapting to customer needs.

Think Big, Start Small: The Zappos Example
One of the key examples in this chapter is Zappos, the massive online shoe retailer. Before becoming a billion-dollar business, Zappos’ founder, Nick Swinmurn, started with a very simple experiment. His hypothesis was that people were ready to buy shoes online. Instead of building a large e-commerce platform with warehouses, Swinmurn took pictures of shoes from local stores and posted them online, agreeing to buy the shoes at full price if a customer purchased them. This small-scale experiment provided valuable insights: it showed whether customers were willing to buy shoes online, whether they had the purchasing intent, and whether they cared about the service. The feedback gained from this experiment was crucial in validating the demand for Zappos’ model, and it allowed the company to scale rapidly once the assumptions were confirmed.

The Need for Immediate Experiments
Ries emphasizes that no matter the scale of your vision, the key to long-term success is to experiment immediately. Take a grand vision and break it down into testable assumptions. By doing this, you avoid wasting resources on features or strategies that may not work. The chapter highlights Caroline Barlerin, a director at Hewlett-Packard, who aimed to transform HP’s employee volunteer program. She used Lean Startup principles to quickly test whether employees were willing to volunteer, focusing on experimentation rather than long-term planning. Instead of waiting for months to execute her full plan, Barlerin started small by testing a few key assumptions about her project’s feasibility and employee willingness.

Experiment as a Product
Ries then introduces the idea that an experiment can be considered a product in itself. In Lean Startup, even early versions of a product or service should be seen as experiments. For example, at Kodak Gallery, Mark Cook shifted from traditional product development methods to an experimental approach, testing assumptions before committing significant resources. He led his team through a process of identifying risks and hypotheses before they built anything. By focusing on learning first, Kodak Gallery was able to test the viability of new features and make adjustments based on real feedback rather than theoretical predictions.

Learning from Failure: The Village Laundry Service Example
Ries closes the chapter with an example of Village Laundry Services (VLS), a business in India that began with a simple, low-cost experiment. By setting up a mobile laundry service, VLS was able to test assumptions about demand, customer behavior, and service viability. The experiment was small—just a mobile truck with a washing machine—but it provided valuable insights. As they iterated, VLS fine-tuned their approach based on real customer behavior. The experiment didn’t just validate the need for laundry services—it also revealed customer preferences, such as the desire for quicker returns and ironing services, which helped VLS refine its business model.

This chapter illustrates that the Lean Startup model isn’t about minimizing failure—it’s about learning quickly and efficiently. By treating each startup as an experiment, entrepreneurs can avoid wasting time and resources on ideas that don’t work. Instead of aiming for perfection from the start, the goal is to use rapid, small experiments to discover what resonates with customers and build from there.

Chapter 5 – Leap

Vision and Strategy: Understanding Leap-of-Faith Assumptions
In this chapter, Eric Ries focuses on how a startup’s strategy is rooted in a series of assumptions that must be tested quickly to avoid wasting time and money. He introduces the concept of leap-of-faith assumptions, which are the riskiest assumptions that a startup makes and that, if proven false, can lead to the failure of the venture. These assumptions are crucial because they determine whether the startup’s vision is grounded in reality. A startup’s strategy begins by identifying and testing these assumptions to refine and validate its business plan.

Facebook’s Early Success
Ries uses Facebook as a prime example to illustrate how leap-of-faith assumptions can shape the future of a startup. Despite being small and with limited revenue early on, Facebook attracted significant investor interest. What impressed investors was not just Facebook’s user growth but the engagement of its users. Facebook’s ability to prove its value hypothesis—that users found the platform valuable—and its growth hypothesis—that it could scale rapidly—was key to its success. These two hypotheses validated Facebook’s potential and led to substantial venture capital funding, despite Facebook’s modest revenue at the time.

Strategy and Assumptions
Ries explains that every business plan is based on assumptions that have not been proven. The success of a startup depends on how quickly these assumptions can be tested and validated. Traditional business plans focus on achieving the company’s vision, but they often overlook testing the underlying assumptions about customer demand, market behavior, or other factors that could make or break the business. In contrast, the Lean Startup method emphasizes testing these assumptions early and systematically, reducing risk and uncertainty in the process.

The Role of Analogies and Antilogies
Ries highlights how analogies—comparing a new business to an existing, successful one—can obscure the true risks involved. While analogies can provide comfort and a framework for strategy, they often gloss over the crucial leaps of faith that need to be tested. For example, entrepreneurs often compare their new technology to an existing one, believing that success in one area guarantees success in another. However, this approach ignores the unknowns that must be tested directly with real customer data. Ries urges entrepreneurs to move beyond analogies and focus on validating their hypotheses through experimentation.

From Vision to Testing: Customer Understanding
Ries advocates for the concept of genchi gembutsu, a Japanese term from Toyota that translates to “go and see for yourself.” This principle is crucial for understanding customer needs. Entrepreneurs must engage directly with customers to validate their assumptions, rather than relying solely on market research or second-hand information. Early engagement with customers helps identify what problems need solving and provides crucial insights into the real needs of the target audience.

Analysis Paralysis vs. Action
One of the key lessons in this chapter is that startups often fall into two traps: analysis paralysis and rushing into action without sufficient learning. Some entrepreneurs spend too much time refining their plans and gathering data, while others rush into building products based on superficial customer feedback. Ries emphasizes the importance of striking a balance—getting enough customer feedback and testing assumptions without waiting for perfect data. This is where the minimum viable product (MVP) comes into play, which will be covered in the next chapter. An MVP allows startups to begin testing assumptions quickly and with minimal investment.

This chapter stresses that the heart of entrepreneurship is testing assumptions and learning from real customer feedback. By focusing on leap-of-faith assumptions, startups can steer their efforts toward building something customers truly want, rather than relying on untested theories or analogies. The Lean Startup approach helps entrepreneurs avoid wasting time on ideas that don’t work by rapidly validating or invalidating assumptions through experimentation.

Chapter 6 – Test

The Power of the Minimum Viable Product (MVP)
In this chapter, Eric Ries discusses the concept of the Minimum Viable Product (MVP), a cornerstone of the Lean Startup method. The MVP is not about creating a fully fleshed-out product; it’s about quickly testing the most crucial assumptions of a business idea with minimal effort. The goal is to start the learning process as soon as possible, testing fundamental business hypotheses rather than perfecting the product itself. Ries introduces the story of Groupon, which began with a simple WordPress blog and basic coupon deals. This MVP wasn’t glamorous, but it validated the business concept and allowed Groupon to scale quickly, ultimately becoming one of the fastest-growing companies in history.

Why First Products Aren’t Perfect
Ries emphasizes that the MVP is not meant to be perfect. He shares his experience at IMVU, where their product was initially low-quality and not yet generating significant revenue. Despite these shortcomings, they were able to validate two crucial assumptions: the product offered value to customers, and they had a functioning growth engine. Early adopters, who are more willing to overlook imperfections in exchange for new technologies, are key to testing the viability of an MVP. These customers help entrepreneurs gauge whether the product is worth improving and expanding.

The Importance of Early Adopters
Early adopters are critical in the MVP process. They are willing to embrace an 80 percent solution, knowing that a product is not yet polished. They care more about being first to use a new product than about its perfection. Ries argues that over-polishing an MVP for the mainstream market is wasteful, as it doesn’t contribute to validated learning. Entrepreneurs often find that the features they think are essential may not be the ones that attract their early adopters. The lesson here is to keep it simple and focus on learning rather than perfection.

The Role of Testing in MVPs
The MVP is designed to test leap-of-faith assumptions—the critical elements of the business that could determine success or failure. For example, if your startup’s business model relies on a free trial to convert users, your MVP might test whether users will even sign up for the free trial. The key is to simplify and minimize features to focus on these core assumptions. Ries shares several techniques, such as video MVPs, where entrepreneurs can test interest before building the actual product, and concierge MVPs, where services are manually delivered to customers to test a business model before investing in automation.

Learning from MVP Feedback
Ries discusses how MVPs often involve delivering a less-than-perfect product to customers and learning from their reactions. He shares examples from companies like Dropbox, where the MVP was a video that demonstrated the product’s value rather than a fully working version. The goal is to measure customer behavior and feedback to validate the startup’s core hypotheses. In some cases, MVPs reveal that a product concept is not viable, and entrepreneurs must pivot, changing direction based on the lessons learned.

Quality and Design in MVPs
Another challenge for entrepreneurs is reconciling MVPs with traditional expectations of quality and design. While quality is essential, the MVP’s primary goal is learning—not perfection. Entrepreneurs must resist the temptation to overbuild or add unnecessary features to satisfy their own standards of quality. Ries stresses that the MVP should be just good enough to test the assumptions and gather data. Customers may not care about certain features as much as the entrepreneurs think, and focusing on these “nice-to-have” features is wasteful if they don’t contribute directly to the learning process.

Speed Bumps in Building an MVP
Building an MVP is not without its challenges. Ries identifies common fears, such as concerns over legal risks, branding, and competition. Entrepreneurs may fear that releasing an MVP will expose their ideas to competitors or harm their brand’s reputation. However, Ries advises that these concerns should not prevent entrepreneurs from testing their ideas early. Many startups benefit from launching under a different brand to reduce risks, especially when the MVP is still evolving. The MVP is a tool for learning, not for gaining immediate success or validation from external stakeholders.

From MVP to Innovation Accounting
The chapter concludes by discussing how MVPs are a starting point for the broader process of innovation accounting. Innovation accounting is a method for measuring progress in a startup, replacing traditional business metrics with learning milestones. By using MVPs, startups can validate their assumptions and move forward with clear, data-driven insights that inform future decisions. This process of learning and adapting is central to the Lean Startup methodology, helping entrepreneurs avoid wasting resources on ideas that don’t work.

In summary, Chapter 6 focuses on the importance of the MVP in the startup journey. The MVP allows entrepreneurs to test critical business assumptions, learn from real customer feedback, and adjust their strategies without overcommitting resources. The chapter reinforces the idea that startups should prioritize learning over perfection and embrace iteration as a path to success.

Chapter 7 – Measure

The Importance of Measurement in Startups
In this chapter, Eric Ries explains that one of the key challenges for any startup is measuring its progress in a meaningful way. At the beginning, many startups are simply an idea, a model on paper. The numbers in their business plans often represent ideal projections, far from what the startup can realistically achieve. To avoid becoming stagnant in the “land of the living dead,” where optimism clouds the harsh truths, startups must rigorously measure their actual performance and adjust their strategies based on real-world data. This is where innovation accounting becomes critical, offering a more useful framework than traditional financial accounting.

Innovation Accounting and Learning Milestones
Ries introduces innovation accounting, a new kind of measurement system specifically designed for startups. It focuses on tracking progress against clear milestones that allow startups to measure how much they are learning and whether they are moving toward building a sustainable business. Innovation accounting involves three key steps: establishing a baseline, tuning the engine, and deciding whether to pivot or persevere. The baseline is established by using an MVP to gather real customer data and measure the current state of the business. From there, startups must experiment to improve key metrics, eventually deciding if the business is on the right path or if a pivot is necessary.

The Danger of Vanity Metrics
Ries warns against the use of vanity metrics—numbers that look good but don’t provide meaningful insights into the startup’s true progress. Examples of vanity metrics include total registered users or total revenue. These metrics are often misleading because they fail to indicate whether the startup is actually solving a customer problem or if the business model is sustainable. Instead, startups should focus on actionable metrics, which clearly demonstrate cause and effect and provide actionable insights for decision-making. For instance, tracking conversion rates, customer retention, and lifetime value is more meaningful than simply counting website visits.

Actionable Metrics vs. Vanity Metrics
Actionable metrics, unlike vanity metrics, help startups make data-driven decisions by showing the direct effects of changes in the product or strategy. Ries illustrates this through the example of Grockit, an online test preparation startup. Despite initial growth and high engagement, Grockit was using vanity metrics like total customer numbers, which masked the deeper issue: they didn’t know which product changes truly impacted customer behavior. By shifting to actionable metrics, such as cohort-based metrics and split tests, Grockit was able to learn from customer behavior and optimize their product development process.

Cohort Analysis and Split Testing
Ries introduces the concepts of cohort analysis and split testing as crucial tools for measuring customer behavior in a way that offers real insights. Cohort analysis helps track the behavior of specific groups of customers over time, which is far more informative than simply looking at gross totals. For example, tracking the percentage of users who return to use a product after their first experience gives more useful data than counting total sign-ups. Split testing (A/B testing) is another important tool, where two versions of a product are tested simultaneously to determine which performs better. This helps teams identify the most effective changes and avoid wasting resources on features that don’t impact customer behavior.

Innovation Accounting at IMVU
Ries shares his experience with IMVU, a social network, to illustrate how innovation accounting played out in practice. At IMVU, despite numerous product improvements, they found that their metrics weren’t improving as expected. By focusing on the right metrics and tightening their feedback loop, they were able to pinpoint issues that required more profound changes, eventually leading to a pivot. The chapter highlights how consistent tracking of actionable metrics can help a startup stay focused on the right areas for improvement, ensuring that every effort is aligned with the goal of creating a sustainable business.

In summary, this chapter emphasizes the importance of using meaningful, actionable metrics rather than relying on vanity metrics. By focusing on learning milestones, startups can track their real progress and make informed decisions about whether to pivot or persevere. The chapter introduces the tools of innovation accounting, cohort analysis, and split testing, all designed to give startups a clearer understanding of their customer behavior and product development trajectory.

Chapter 8 – Pivot (or Persevere)

The Critical Decision: Pivot or Persevere
In this chapter, Eric Ries tackles one of the most difficult and pivotal decisions for any startup: knowing when to pivot and when to persevere. After testing a product, refining it, and gathering customer feedback, entrepreneurs must evaluate whether their original vision and strategy are still on track or if a significant course correction is needed. This decision is not always clear-cut, and it’s where human judgment—intuition and creativity—comes into play. Ries emphasizes that a rigid scientific approach can’t replace the judgment and vision of the entrepreneur. Instead, Lean Startup principles should be used to improve and test those judgments systematically.

Innovation Accounting Leads to Faster Pivots
The chapter highlights the importance of innovation accounting, which helps startups track their progress and decide whether to pivot or persevere. This method of accounting allows entrepreneurs to focus on actionable metrics rather than vanity metrics that can provide false reassurance. For instance, David Binetti, CEO of Votizen, used Lean Startup methods to pivot multiple times. Initially, his startup focused on creating a social network for verified voters, but after testing assumptions with his MVP, he realized that his vision needed to change. The data showed that the core customer engagement metrics, such as registration and referral rates, were not growing as expected, signaling that a pivot was necessary. Despite initial success, Votizen needed a new direction.

Pivots: A Special Kind of Change
A pivot is not just any change, but a structured course correction designed to test a new fundamental hypothesis about a product, business model, or engine of growth. The chapter explains several types of pivots, including:

• Zoom-in Pivot: Where a single feature becomes the main product.
• Zoom-out Pivot: Where what was initially the entire product becomes just one feature of a larger product.
• Customer Segment Pivot: A pivot in which the product still solves a real problem, but for a different customer than originally targeted.
• Platform Pivot: Moving from an application to a platform, or vice versa.
• Business Architecture Pivot: Changing from a high-margin, low-volume model to a low-margin, high-volume model (or the reverse).

The Runway of Pivots
Ries introduces a new way of thinking about a startup’s runway, which traditionally refers to the time a startup has left before it runs out of cash. Instead of measuring runway solely by cash, Ries suggests startups measure it by how many pivots they can still make. The idea is that a startup’s ability to pivot quickly is more important than simply stretching its time or resources. The faster a startup can test new ideas and pivot, the better its chances of finding the right path.

The Courage to Pivot
Pivoting can be difficult, especially for founders who may feel emotionally tied to their original idea. The chapter explores the psychological barriers to pivoting, such as the fear of failure, the pressure of vanity metrics, and the reluctance to abandon early investments. Ries notes that the courage to pivot is a vital characteristic of successful entrepreneurs. It requires being open to failure and recognizing that holding on to a failing idea only wastes valuable time and resources. The story of Path, a social networking startup, serves as an example where the team faced public criticism but remained focused on feedback from real customers instead of succumbing to the pressure of public opinion.

Learning from Failure and Pivots
Ries emphasizes that failure is a prerequisite to learning in startups. The traditional approach of launching a product and seeing what happens is unreliable because early feedback often remains ambiguous. The Lean Startup method encourages a deeper analysis of customer feedback, including negative feedback, to inform pivots. For example, the Wealthfront startup originally began as an online game for amateur investors (kaChing), but the team quickly realized that the business model wasn’t working. After several pivots, including refocusing their platform to provide professional investment management, Wealthfront succeeded by leveraging its learnings. The decision to pivot wasn’t easy, but it ultimately led to the creation of a profitable business.

A Catalog of Pivots
The chapter concludes with a list of various types of pivots that startups can pursue, depending on their specific needs and challenges. From zoom-in to customer need pivots, each pivot type represents a strategic change that tests a new hypothesis about the business. Ries explains that these pivots should not be seen as failures but as opportunities to refine and improve the product, business model, or growth engine.

Overall, this chapter illustrates the importance of flexibility, quick learning, and data-driven decision-making in startups. The ability to pivot, using innovation accounting and actionable metrics, helps startups avoid stagnation and stay on course toward a sustainable business model.

Chapter 9 – Batch

Startups and the Power of Small Batches
In this chapter, Eric Ries explains how startups can benefit from adopting the principle of small batches, a concept derived from lean manufacturing. Just as lean manufacturing uses small batches to eliminate waste and increase efficiency, Lean Startups use small batches to accelerate learning. The primary goal for startups isn’t necessarily to produce more efficiently but to validate assumptions and learn about customers as quickly as possible. By reducing the batch size of work—whether it’s product development, feature releases, or customer feedback loops—startups can test their hypotheses faster, identify problems early, and make adjustments more rapidly.

Learning from Toyota’s Production System
Ries draws parallels between the lean production techniques developed by Toyota and the Lean Startup methodology. Toyota’s use of small batches allowed them to identify defects and resolve issues quickly, improving product quality and efficiency. Similarly, in a startup, using small batches means that you can release a new feature, test it with real users, and measure the response without waiting too long or committing too many resources. This feedback loop helps startups avoid the danger of building something no one wants or that doesn’t work.

Small Batches at IMVU
At IMVU, the team applied the concept of small batches by releasing product changes on a very frequent basis—sometimes up to 50 changes per day. This continuous, rapid release cycle allowed them to gather immediate feedback from customers and adjust accordingly. Instead of waiting for months to roll out a perfect product, they tested small increments of new features, which helped them learn much faster. In fact, by reducing the batch size and focusing on incremental changes, IMVU could identify and fix problems immediately, which minimized the chances of building something that didn’t meet customer needs.

Why Small Batches Work
The key reason small batches are so effective is that they help avoid the waste of time and effort. For example, imagine you’re working on a product with a large batch process—building a major feature over several months. By the time you release it to customers, you might discover it’s not what they wanted. With small batches, you can detect that failure early, saving time and resources that would have been wasted. Moreover, small batches allow startups to maintain flexibility, iterate quickly, and respond to customer needs, ensuring the product evolves based on actual data rather than assumptions.

The Shift from Large to Small Batches
Ries discusses how traditional large-batch systems often lead to inefficiencies, such as excessive rework, delays, and missed opportunities. For example, a product designer may work on a batch of design changes, but once handed off to the engineering team, problems may arise that require the designer to revisit and revise work, causing delays. In contrast, the small-batch approach minimizes this risk by breaking tasks down into manageable chunks, allowing teams to work collaboratively and solve problems immediately as they arise.

Continuous Deployment and Small Batches
Ries introduces the concept of continuous deployment, where products are released in very small increments, sometimes several times a day. At IMVU, this practice allowed them to test assumptions and learn continuously. Every small feature or bug fix could be deployed immediately, and the team could assess its impact right away. This contrasts with the traditional model where product changes happen in large cycles, often causing delays and inefficiencies. The lean approach to product development—working in small batches and deploying continuously—allows startups to quickly iterate and learn, which is crucial for success in uncertain environments.

Beyond Software: Small Batches in Other Industries
While small batches are commonly associated with software development, Ries argues that other industries can also benefit from adopting this practice. He provides examples from manufacturing, like Toyota, and even hardware and clean-tech startups, showing how the principle of small batches accelerates learning and product development. For example, Alphabet Energy, a startup working in thermoelectrics, used small batch testing and rapid iterations to refine their product and pivot when their initial assumptions didn’t hold true. Instead of making massive investments upfront, they tested their hypotheses in small batches, minimizing risk and maximizing learning.

The Large-Batch Death Spiral
Ries warns about the dangers of working in large batches, a phenomenon he calls the large-batch death spiral. In large-batch systems, there’s a tendency to delay releases in favor of adding more features, refining designs, or addressing every possible problem before launch. However, this often leads to missed deadlines, increased anxiety, and a higher risk of failure when the product is eventually released. The chapter stresses the importance of staying lean and focused, avoiding the temptation to keep adding to a product without testing it with customers.

Pull Instead of Push
To conclude the chapter, Ries introduces the concept of pull, which is central to Lean manufacturing. In traditional systems, production is driven by forecasts or schedules, pushing products through the system regardless of customer demand. In contrast, pull systems respond directly to customer needs, ensuring that production is only triggered when there’s demand. Startups can apply this principle by focusing on customer feedback and data-driven experimentation rather than pushing products into the market based on assumptions.

Overall, Chapter 9 emphasizes the importance of small batches in startups, illustrating how this approach leads to faster learning, less waste, and a more agile business model. By reducing batch sizes, startups can experiment more efficiently, make data-driven decisions, and avoid the inefficiencies of large-batch development.

Chapter 10 – Grow

The Problem of Stalled Growth
Eric Ries begins this chapter with a story about two very different startups: one is developing a marketplace for collectible items, and the other is selling database software for enterprise customers. Despite their differences, both companies are experiencing the same problem: lack of growth. Even though they had early customer success, raised investment, and received positive feedback, they were no longer seeing the growth they anticipated. Both CEOs came to Ries asking whether they should invest more in advertising, marketing, product quality, or conversion rates to jump-start growth. The underlying issue was the same for both—neither company understood how to build a sustainable growth engine.

What Is an Engine of Growth?
The engine of growth is a critical concept for startups, referring to the mechanism that drives sustainable growth. Ries defines sustainable growth as growth that comes from the actions of past customers. This excludes short-term strategies like one-time advertising or publicity stunts. The goal is for new customers to come from the word of mouth, repeat usage, or funded advertising, all driven by existing customers. There are four primary ways past customers drive this growth:

1. Word of mouth: Customers who love the product tell others about it.
2. Product usage side effect: The product itself generates awareness when used in public (e.g., fashion or viral products like Facebook).
3. Funded advertising: Advertising paid for by revenue, not one-time capital.
4. Repeat purchase or usage: Products designed for repeated use, like subscriptions or consumer goods.

These engines of growth create feedback loops that power the business. The faster the loop turns, the faster the company grows.

Three Engines of Growth
Ries introduces three engines of growth that startups can focus on to achieve sustainable growth:

1. The Sticky Engine of Growth
   This engine focuses on customer retention. It works for businesses where the goal is to have customers come back repeatedly, like subscription services or products that offer long-term value. The key to success is minimizing the churn rate—the percentage of customers who stop using the product. Companies need to keep customers engaged, often by making the product more valuable or engaging over time.
2. The Viral Engine of Growth
   Products using this engine grow through viral loops, where each customer brings in new customers, usually without needing to actively promote the product. Examples of viral engines include social networks and products like Hotmail, where users get others to sign up through simple product features. This engine requires the viral coefficient to be greater than 1.0 to ensure exponential growth.
3. The Paid Engine of Growth
   The paid engine relies on paid advertising to acquire new customers. Companies using this engine have to balance the customer acquisition cost (CAC) with the lifetime value (LTV) of a customer. If the LTV exceeds the CAC, the business can reinvest profits into acquiring even more customers, leading to growth.

The Sticky Engine of Growth
Ries explains that businesses with a sticky engine of growth track their retention rates carefully. If customer retention is high, then the company will continue growing as long as new customer acquisition exceeds churn. For example, a collectible marketplace depends on customers returning often to see new products or trade. Similarly, database software for enterprise customers thrives on customer retention because switching to a new system is costly and difficult. These businesses need to focus on retaining customers and improving engagement to achieve sustainable growth.

The Viral Engine of Growth
In this section, Ries highlights how viral growth works differently from other forms of growth. A viral engine relies on automatic product usage transmission—each new customer naturally recruits others. Hotmail’s early growth came from a simple tweak in their product that encouraged users to spread the word by adding a message at the bottom of emails. In the case of Tupperware, customers hosted parties to sell products and recruit others to sell, creating a viral loop. For startups using viral growth, increasing the viral coefficient—the number of new users each customer brings—is essential for rapid scaling.

The Paid Engine of Growth
Ries wraps up this section by discussing the paid engine, which is driven by advertising or outbound sales efforts. For this engine to work, a startup must ensure that the cost of acquiring a customer (CAC) is less than the lifetime value of that customer (LTV). A case example from IMVU shows how they initially misjudged the viral potential of their product and had to rely on paid advertising to grow. Once they realized the need for paid acquisition, they focused on ensuring that their LTV was high enough to support sustained ad spending.

Engines of Growth and Product/Market Fit
Finally, Ries ties these engines of growth to the concept of product/market fit, which refers to the moment when a startup has found a customer segment that resonates deeply with its product. This is the point at which the engine of growth really starts to work. When the viral or sticky engine is running smoothly, the startup can focus on optimizing the product and scaling the business.

In this chapter, the focus is on understanding which engine of growth works best for the startup, tracking relevant metrics, and then scaling efforts based on which engine is most effective. Ultimately, this approach helps startups create sustainable growth that isn’t dependent on temporary bursts of success or capital investment.

Chapter 11 – Adapt

The Importance of Adaptability in Startups
Eric Ries begins this chapter by sharing a personal story about his experience as the CTO of IMVU. He explains the critical importance of adaptability in startups, particularly as they grow. Early on in his career at IMVU, Ries thought he was doing everything correctly—creating an agile engineering team and applying Lean Startup principles. However, he realized that as the company grew, his role and the processes that worked initially were no longer sufficient. The company had outgrown his previous approaches, and he was failing in his new role. This situation reflects the challenge every entrepreneur faces as their startup evolves. Adapting to new circumstances and scaling effectively requires a significant shift in thinking and actions, and it’s often difficult to recognize that change is necessary.

Building an Adaptive Organization
One of the main ideas in this chapter is the concept of building an adaptive organization. Initially, Ries believed that training programs and structured processes were unnecessary in a startup environment. However, as IMVU grew, the lack of these systems became a hindrance. They needed a formal training program to bring new employees up to speed quickly and effectively, so they began to create one. This training program evolved naturally as part of their process improvement efforts. Rather than stopping all other work to create a formal training program, the team integrated it into their continuous improvement approach, making it a part of the regular iteration and learning cycle.

Ries emphasizes that adaptability doesn’t mean moving away from systems or processes; it means continuously improving and adjusting them as the company grows. This adaptability should be built into the organization’s DNA, enabling it to adjust its processes automatically based on the current conditions.

Speed vs. Quality
While startups are focused on speed to avoid running out of resources, Ries highlights that focusing on speed alone can be detrimental. The chapter brings in the Toyota principle of andon cords, which allow workers to stop production immediately when an issue arises. This “stop to fix” principle ensures that quality doesn’t get sacrificed in the name of speed. Ries connects this concept to startups by stressing the importance of balance—moving quickly but also ensuring that quality is never compromised, as poor quality will inevitably slow down the process later on.

The Five Whys
A critical tool discussed in this chapter is the Five Whys method, which helps teams dig deeper into problems and understand their root causes. The method involves asking “why” five times to identify the underlying problem. Ries illustrates how this method can lead to meaningful insights and long-term improvements by uncovering not just the symptoms of a problem but its root causes. The Five Whys helps create an adaptive organization that can address issues incrementally, improving processes without overwhelming the team or over-investing resources.

Ries stresses that this method is about looking for systematic solutions to problems, not assigning blame to individuals. The process is about discovering the underlying systems that cause failures, which ultimately leads to long-term improvements. However, the process can be derailed if teams fall into the trap of “Five Blames”, where the focus shifts from problem-solving to finger-pointing. To avoid this, teams need to work together in a culture of trust and collaboration, with senior management supporting the process.

The Curse of the Five Blames
While the Five Whys is an incredibly powerful tool, Ries warns that it can easily devolve into finger-pointing, which he calls the “Five Blames.” This happens when the root cause analysis becomes a way for people to blame each other instead of focusing on process improvement. The solution, according to Ries, is to ensure that everyone involved in the issue is present during the analysis and that the goal is to solve the problem, not to assign blame. He also advocates for a “systems-level” view of problems, where the focus is on improving processes rather than criticizing individuals.

Practical Use of the Five Whys
Ries offers several strategies for successfully implementing the Five Whys in a startup, including starting with small problems and gradually scaling up as the team becomes more comfortable with the method. He also recommends appointing a Five Whys master to facilitate the sessions and ensure that the process stays on track. This person should be senior enough to take responsibility but also capable of guiding the team through the process without being bogged down by conflicting priorities.

Adapting the QuickBooks Process
In a case study involving QuickBooks, Ries demonstrates how the company adapted its processes to be more agile. Initially, QuickBooks followed a traditional waterfall development process, with long release cycles and extensive planning at the beginning of each year. This method led to poor customer feedback and delays in addressing issues. The team, led by Greg Wright, worked to shorten cycle times and bring customer feedback into the development process much earlier. This change was not easy, as the company had years of ingrained habits and systems that didn’t support the new approach. However, by focusing on smaller batches and involving customers from the start, they were able to iterate faster and improve customer satisfaction.

Ries concludes by reinforcing that an adaptive organization isn’t just about making quick changes; it’s about continuously improving processes and systems to support sustainable growth. Successful startups need to embrace both speed and quality, ensuring they evolve with their environment and maintain flexibility as they scale.

In summary, Chapter 11 focuses on the importance of building an adaptive organization that can learn, iterate, and grow continuously. By using tools like the Five Whys and adjusting processes incrementally, startups can stay responsive to customer needs and prevent major failures down the line.

Chapter 12 – Innovate

The Challenge of Innovation in Larger Companies
Eric Ries starts this chapter by addressing the common belief that as companies grow larger, they inevitably lose their ability to innovate. However, he argues that this is a misconception. With the right structure and mindset, even large organizations can innovate. Ries introduces the idea of portfolio thinking, which allows companies to balance the needs of existing customers while also exploring new business models and opportunities. Instead of accepting the decline of innovation as a given, large companies can design processes that foster innovation while continuing to manage established operations.

The Structure of Successful Innovation Teams
For innovation to succeed, the right team structure is critical. Ries identifies three key structural attributes for successful innovation teams:

1. Scarce but secure resources: Innovation teams need limited but secure resources. Too much budget can lead to complacency, while too little can be fatal. Startups thrive on a delicate balance where the capital is tight but protected.
2. Independent authority: Innovation teams must have the autonomy to make decisions and run experiments without constant approvals or interference from other departments. This freedom enables them to work quickly and learn from failure.
3. A personal stake in the outcome: Team members must have a personal connection to the success of the innovation. This can be achieved through stock options or other long-term incentives. A sense of ownership over the project motivates individuals to put in the effort necessary to succeed.

Ries stresses that structure alone doesn’t guarantee success, but getting it wrong can doom an innovation effort from the start.

The Sandbox for Innovation
Ries introduces the concept of an innovation sandbox, a controlled environment where new ideas can be tested without jeopardizing the main business. This “sandbox” provides the space for experimentation without the fear of disrupting the entire organization. It allows innovation teams to operate with the flexibility and speed of a startup while ensuring that the core operations of the parent company remain stable.

The sandbox approach enables teams to experiment in small, low-risk ways. By restricting experiments to certain customer segments, product features, or geographic areas, companies can limit the exposure of their innovations. The teams working in these sandboxes must use actionable metrics to measure success or failure. This helps ensure that the innovation process remains data-driven and transparent.

Protecting the Parent Organization from Innovation
While many traditional views emphasize protecting innovation teams from the parent organization, Ries flips this approach. He suggests that companies should instead focus on protecting the parent organization from the innovation process. When innovation teams operate secretly or outside the main company, it breeds mistrust and defensiveness. Established managers feel threatened when they are not included in the innovation process, leading to sabotage and inefficiency. The key is creating a supportive system where innovation teams are seen as partners, not threats.

Ries shares an example from a company that attempted to conduct a pricing experiment. The experiment was poorly executed and resulted in a lengthy and contentious meeting that ultimately led to no clear decision. The lack of alignment and trust among departments revealed how hidden innovation processes can harm the organization. By encouraging openness and collaboration, companies can better integrate innovation into their culture and reduce the risk of conflict.

Managing the Four Types of Work in Companies
Ries discusses the four types of work companies must manage as they scale:

1. Innovation: New ideas and disruptive products.
2. Growth: Expanding the market for existing products.
3. Optimization: Improving operational efficiency.
4. Efficiency: Ensuring that legacy products continue to run smoothly.

Each phase requires different management skills. As a product moves from innovation to optimization, the team managing it must adapt to the changing needs of the business. In many companies, innovators are asked to focus on growth or efficiency once their product becomes established. However, this can stifle future innovation. Ries recommends creating flexible teams that can shift between phases as needed.

Entrepreneur as a Career Path
Finally, Ries proposes that entrepreneurship should be considered a viable career path within large organizations. Innovators don’t have to leave their companies to pursue new ideas. By embedding Lean Startup principles into the organization, entrepreneurs within companies can lead the creation of new products while remaining part of the larger structure. This approach encourages companies to embrace a culture of innovation and supports the long-term career development of those driving change.

In summary, Chapter 12 outlines how large organizations can foster innovation by creating structures that support startup-like teams, providing autonomy, and using innovation sandboxes to protect both the new ventures and the parent company. Through proper management of the four phases of work, organizations can sustain innovation while continuing to optimize and grow. The chapter emphasizes that creating a culture of innovation is possible, even in large companies, as long as leaders embrace the principles of Lean Startup and foster cross-functional, empowered teams.

Waste Not

What Should Be Built, Not Just What Can Be Built
Eric Ries closes The Lean Startup with a powerful reflection on the idea of waste—not just of resources or materials, but of human effort, creativity, and time. He draws inspiration from Frederick Winslow Taylor’s The Principles of Scientific Management, published over a century ago, which revolutionized the way work was organized and studied. While Taylor’s legacy helped bring efficiency and structure to industrial work, Ries points out that many of his methods also dehumanized workers and overemphasized rigid systems. Still, the core idea that work can and should be improved scientifically remains valid and necessary today—especially in the world of innovation.

Ries argues that we’ve entered a new era where the challenge is not building products efficiently, but building the right things. We live in a world where the capacity to build exists almost without limit, but our biggest constraint is knowing what to build. The modern economy, he says, is still full of stories of failed products, wasted time, and misguided efforts. Ries believes that most of this waste is preventable—not through working harder or finding more brilliant individuals, but by shifting how we think about innovation itself. Innovation is not just about bold vision—it’s about testing that vision scientifically. He warns against the rise of pseudoscience in startups, where teams use vanity metrics or untested assumptions to justify their decisions, rather than relying on real customer feedback and validated learning.

From Superpowers to System Thinking
One of the most striking stories in this chapter comes from a junior employee who, after learning Lean Startup principles, found himself impressing corporate executives just by asking the right questions. Ries explains that what made this employee stand out wasn’t raw brilliance, but the use of a system—a framework for testing hypotheses and validating ideas. Yet, companies often misunderstand this and try to “find more brilliant people” instead of changing the system that leads to those insights. Ries’s message is clear: innovation should not rely on talent alone—it should be built into the structure and mindset of the organization.

He also warns the Lean Startup movement not to fall into the same trap as Taylorism, where the system becomes rigid and loses sight of the people. Lean principles should empower, not replace, individual creativity. It’s not about dogma or process for its own sake; it’s about creating organizations that are capable of continuous learning and sustainable growth. Ries calls for experimentation at scale, including startup labs, innovation accounting, and even a Long-Term Stock Exchange (LTSE)—a bold idea for restructuring how companies are evaluated and incentivized based on their ability to innovate over the long haul.

In Conclusion: Stop Wasting People’s Time
The epilogue ends with a hopeful, yet urgent call to action. Ries envisions a world where every employee has the tools and mindset of the Lean Startup—where assumptions are tested, failure is treated as a learning opportunity, and speed and quality work together in service of the customer. Most importantly, it’s a world where we stop wasting people’s time by asking them to build things that no one wants, using outdated processes and flawed assumptions. If we could eliminate that waste, Ries suggests, we might unlock an extraordinary amount of untapped human potential.

4 Key Ideas from The Lean Startup

6 Main Lessons from The Lean Startup

My Book Highlights & Quotes

This is one of the most important lessons of the scientific method: if you cannot fail, you cannot learn.

We must learn what customers really want, not what they say they want or what we think they should want.

The only way to win is to learn faster than anyone else.

What differentiates the success stories from the failures is that the successful entrepreneurs had the foresight, the ability, and the tools to discover which parts of their plans were working brilliantly and which were misguided, and adapt their strategies accordingly.

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.

We adopted the view that our job was to find a synthesis between our vision and what customers would accept; it wasn’t to capitulate to what customers thought they wanted or to tell customers what they ought to want.

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

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. In other words, 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.

Lean thinking defines value as providing benefit to the customer; anything else is waste

Validated learning is the process of demonstrating empirically that a team has discovered valuable truths about a startup’s present and future business prospects.

The value hypothesis tests whether a product or service really delivers value to customers once they are using it.

If we do not know who the customer is, we do not know what quality is.

Leadership requires creating conditions that enable employees to do the kinds of experimentation that entrepreneurship requires.

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.

Conclusion

The Lean Startup isn’t just for tech founders or startup junkies—it’s for anyone trying to create something new in a world full of uncertainty.

It gives you a way to move forward without needing all the answers upfront. It teaches you to ask better questions, listen harder, and treat every move as a chance to learn.

And maybe most importantly, it reminds you that building something great isn’t about being perfect—it’s about being brave enough to start, smart enough to learn, and humble enough to change.

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