Summary-The Lean Startup - How Todays Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses - Eric Ries

Summary-The Lean Startup - How Todays Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses - Eric Ries



  • The author founded a startup company that failed ten years ago. Despite having promising ideas and a talented team, the company failed due to a lack of the proper process to turn insights into a sustainable company.

  • The common myth is that perseverance, brilliance, and timing inevitably lead to startup success. However, most startups fail. Success is not inevitable or based primarily on vision or ideas.

  • Instead, success is engineered through the proper management process. Startup success can be learned and taught. Entrepreneurship is management, not just vision and ideas.

  • There needs to be more than vision and ideas. Success is built through a mundane, tedious process of constant testing, measurement, and adaptation. Startups must validate their ideas through customer feedback, not just have faith in a vision.

  • The story of a 2004 startup called IMVU is shared. Despite their previous failure and Lack of credibility, their vision of avatars connecting people led to success. However, this was achieved through a relentless process of building products based on customer feedback, not just sticking to the vision. Success was built through experimentation, customer validation, and adapting based on measurement.

  • The overall message is that startups can succeed through a nimble management process of vision, experimentation, measurement, and adapting based on feedback. Success is built on this learning loop, not just vision, timing, or perseverance alone. Both vision and management rigor are needed.

The key ideas in the passage are:

  1. The Lean Startup method proposes a new approach to creating continuous innovation. It consists of quickly releasing a minimum viable product, constant experimentation, and scientific measurement of progress.

  2. The author developed the Lean Startup method based on his experiences co-founding IMVU, a startup that succeeded by following very short iteration cycles and constantly experimenting. Traditional thinking said their approach should work, but it led to success.

  3. The core principles of the Lean Startup are: entrepreneurs are everywhere, entrepreneurship is management, validated learning through experimentation, the build-measure-learn feedback loop, and innovation accounting.

  4. The Lean Startup aims to reduce waste and increase the success rate of new products by providing guidelines for efficient entrepreneurship and innovation. It has spread globally and benefited many startups as well as large companies.

  5. The Lean Startup proposes that startups exist to learn how to build a sustainable business, not just to make stuff and money or serve customers. Learning is validated through frequent experimentation to test different parts of the business vision.

The key takeaway is that the Lean Startup method offers a new approach to entrepreneurship and product development focused on accelerated learning through experimentation, rapid iteration and feedback. This method aims to improve success rates and reduce waste in startups and established companies.

The Lean Startup movement seeks to apply rigorous management to startups. Traditionally, startups have avoided management practices in the belief that they stifle creativity or invite bureaucracy. However, the "just do it" approach leads to chaos and failure. The Lean Startup adapts lean manufacturing concepts to startups. It uses "validated learning" as a measure of progress rather than the production of physical goods.

The Lean Startup addresses all functions of early startups: vision, product development, marketing, sales, scaling up, partnerships, and organizational design. It guides on making trade-off decisions in the face of uncertainty. It allows entrepreneurs to make testable predictions.

For example, the Lean Startup recommends cross-functional teams accountable for "learning milestones" rather than traditional functional departments. This may initially reduce perceived productivity, as people are used to evaluating productivity within their specialized roles. However, it leads to faster progress overall.

The Lean Startup is necessary because entrepreneurship has become more widespread, thanks to more significant economic opportunity and productivity. However, the Lack of a management framework for startups leads to many failures and waste. The Lean Startup aims to prevent such failures through scientific experimentation and learning.

Here is a summary:

  • The author used to measure productivity by the amount of programming code written. However, the Lean Startup method proposes measuring productivity differently for startups, focusing on learning and iteration rather than output.

  • The author compares startups to cars. The engine represents growth, and startups are constantly changing to improve the engine. The steering wheel represents the feedback loop with customers, allowing startups to pivot if needed. Startups have a vision of their destination but can adapt their route based on feedback.

  • In contrast, many startups have business plans like rocket ships requiring precise plans and assumptions. Any error can lead to catastrophe. One company the author worked with executed its plan precisely but failed because customers needed to adopt the product as expected.

  • Entrepreneurship requires balancing several activities: serving existing customers, improving the product, and deciding whether to pivot. Both startups and large companies have to balance innovation and existing operations.

  • However, entrepreneurial management is often not understood in large companies. Employees who spend a year developing a new product but fail to meet growth targets would often be fired, even if they learned a lot and were on the cusp of success. Entrepreneurial management is needed to support internal innovators in big companies.

  • The author has met many entrepreneurs within large companies adept at organizational politics and visionaries, like startup founders. For example, Mark leads a new division at a large company developing internet products. Mark already understood concepts like disruptive innovation and had a vision for the industry's future. He just needed entrepreneurial management to execute this vision.

  • In summary, the key traits of entrepreneurs are vision, the ability to navigate organizational challenges, and the need for entrepreneurial management to achieve their goals. This is true for both startup founders and internal innovators in large companies.

Here is a summary:

  • Mark has all the ingredients for innovation such as good team, vision, risk appetite but needs a process to achieve breakthrough success.

  • The Lean Startup methodology provides a process for innovation and success.

  • Entrepreneurs build new products under uncertainty, whether in a startup or an established organization. They need Lean Startup principles.

  • A startup is a human institution designed to create new products under extreme uncertainty. It is not defined by size, industry or sector. It involves building an organization, hiring, coordination and culture to deliver results.

  • Products refer broadly to any source of value for customers. Innovation also refers broadly to new scientific discoveries, new business models, reaching new customers, etc. Startups confront extreme uncertainty where the future is unpredictable and change is rapid.

  • The story of SnapTax by Intuit shows how even large companies can innovate like startups. They started small, with a simple product for a niche, and grew it into a thriving new offering. Though Intuit is large, the team was internal, without massive resources.

  • What enabled their success was a deliberate process facilitated by senior management. Innovation needs to be managed through a new discipline, not just by entrepreneurs but also those who support and guide them. Senior management is responsible for cultivating entrepreneurship.

Here is a summary:

  • Intuit is a large, established company that has succeeded through continuous innovation.

  • In the early 2000s, Intuit's founder Scott Cook realized that their traditional management approach could have resulted in successful new products.

  • Cook worked to change Intuit's culture to be more entrepreneurial and open to experimentation.

  • For example, Intuit's TurboTax team now runs up to 500 experiments during tax season and can get results and redesign experiments within a week. This approach develops an entrepreneurial mindset in employees.

  • Intuit's CEO has said that they measure innovation based on the percentage of revenue from offerings that did not exist three years ago. Under their old model, it took 5.5 years for a new product to generate $50 million in revenue; they have done that within 12 months.

  • Intuit's leadership realized that enabling fast experimentation and an entrepreneurial culture was vital. They invested in systems to speed up building, testing, and analyzing experiments.

  • Rather than top-down decision-making, Intuit's leadership aimed to implement a culture and systems that empower teams to experiment and innovate independently.

  • The author argues that more than measuring progress based on executing a plan and budget is required for entrepreneurial companies. Entrepreneurs need to make sure they are building something that customers want. Just "learning" from failures is not enough.

  • However, validating learning through experimentation and measurement is critical to entrepreneurial progress. This learning needs to be concrete and actionable, not just a story told after the fact.

The key themes are: adopting an experimental and entrepreneurial mindset; empowering teams to test ideas independently, and measuring real progress through validated learning about customers. The case of Intuit shows how these principles can work even in a large, established company.

Here is a summary:

  • The fundamental goal of entrepreneurship is an organization building under extreme uncertainty. The most vital function is learning. Entrepreneurs must learn the truth about what works rather than just executing a predetermined plan.

  • Validated learning is learning through empirical evidence that demonstrates real progress. It is more concrete and accurate than traditional business planning. It helps startups avoid "achieving failure" by executing plans that lead nowhere.

  • The author describes IMVU's mistakes in developing their first product. They wanted to be strategic thinkers, but their strategy needed to be revised. They entered the instant messaging market, hoping to leverage network effects. However, the IM market was dominated by a few big players, and hard for newcomers to enter.

  • IMVU's solution was to build an add-on product that would work with existing IM networks so users would not have to switch. They thought this would allow viral growth. They worked intensely to launch for six months, but the first version could have been better. They feared backlash but launched anyway to get feedback.

  • At first, nothing happened - no one even tried the product. They slowly improved it and got a few customers, but revenue and usage needed more significant. They started doing in-person customer interviews and usability tests, guided by their revenue targets. They realized their strategic analysis was utterly wrong. Customers could not need help articulating their wants - IMVU had to learn through experimentation.

  • Talking to customers, they found mainstream users thought IMVU was too weird. However, some target customers engaged with the product, like teens and early tech adopters. IMVU learned that their initial strategy needed to be revised and they had to pivot to focus on those specific customer segments. Validated learning through customer interaction led them to change direction.

In summary, the key lessons are: validated learning through experimentation is vital; customers cannot always tell you what they want, you have to observe their behavior; and startups must be willing to pivot based on what they learn, even if it means abandoning initial strategies and plans.

Here is a summary:

The author's team built an instant messaging add-on product based on some incorrect assumptions:

  1. Customers would want to use the product with existing friends and add them to their buddy lists. In reality, customers wanted to make new friends with the product.

  2. It would be difficult for customers to switch to a new instant messaging network or learn new software. In reality, customers were very comfortable using multiple networks and pieces of software.

  3. The team focused on building interoperability with many other networks to create network effects, but this needed to be a better strategy. Customers did not care about this and just wanted a standalone network.

The team learned these lessons slowly and painfully over many customer meetings. The author felt his work over the last six months had been wasted, but realized the value was in the learning rather than the actual product built. However, he wondered if they could have learned faster and with less waste.

Some sources of waste were:

  1. Debating and prioritizing features customers have yet to use. If they shipped sooner, this could have been avoided.

  2. The incorrect strategic assumptions themselves. Did they need to build interoperability with so many networks to get customer feedback, or could they have gotten it with less?

  3. The author wondered if they even needed to build anything to discover their flawed assumptions, or if they could have done it through other means like customer conversations.

The critical insight is that for startups, value is created through learning, not just building product. Anything that does not contribute to learning is waste. The team could have learned the same lessons with less effort and waste.

Here is a summary:

  • Early on, IMVU struggled to gain traction with customers. Very few people were using their initial product.

  • The author realized that learning customers' wants is the key to startup progress. He calls this "validated learning" - learning backed by data showing improvements in key metrics.

  • It is easy to think you understand what customers want. Validated learning comes from releasing a product, measuring how customers respond, and adjusting based on their behavior.

  • IMVU started gaining traction once they pivoted from their initial strategy and product based on customers' learning. Their metrics improved as they better understood and served their customers' needs.

  • Releasing a flawed product and learning from customers is better than delaying the release to try and build the perfect product. Delaying release increases the risk of building something nobody wants.

  • However, small numbers can also be damaging, as they invite questions about whether you will achieve scale. This can tempt startups to engage in "success theater" - superficial tactics to appear successful rather than focusing on actual progress.

  • IMVU raised funding despite small revenue numbers by demonstrating validated learning - showing investors that their product development efforts led to improvements, even if the absolute numbers were still small.

  • The critical lesson is that progress for startups should be measured by how much validated learning they can achieve from their efforts, not just by surface metrics like revenue or several customers. Validated learning is the way to build something people want.

In summary, the key points are:

  1. Focus on validated learning, not what you assume customers want

  2. Release a product and measure customer response, rather than delaying release

  3. Do not get distracted by "success theater" and surface numbers - focus on demonstrating real progress through validated learning

  4. Validated learning, not surface metrics, is the best measure of a startup's progress

Here is a summary:

The author teaches entrepreneurship and shares the story of IMVU, an early startup he co-founded. When teaching the IMVU case study, students often focus on the tactical details, like launching an early prototype, charging from day one, and using revenue targets to drive accountability. However, these tactics themselves are not the key lessons. The Lean Startup methodology is a principled approach to developing new products and can work across many industries.

The key is to view every startup as an experiment to test each part of the business plan systematically. Following the scientific method, startups should make predictions, test them empirically, and use the results to learn and adapt. The goal is to find a sustainable business model.

For example, Zappos started small by taking photos of local shoe stores' inventory and posting them online. If customers bought the shoes, Zappos would buy them at a total price. This tested the hypothesis that customers want to buy shoes online. It provided data on actual customer behavior and allowed Zappos to interact with and learn from customers. Despite starting small, Zappos grew into a hugely successful company.

Similarly, a director at HP is trying to encourage employees to volunteer in their communities. Although this seems suited to traditional management, it needs more certainty there than extensive planning; the Lean Startup approach suggests immediately running experiments to test key assumptions, like whether specific initiatives will inspire more employees to volunteer. The results can then inform next steps. The Lean Startup philosophy argues for starting small, testing hypotheses empirically, and accelerating that learning process.

Here is a summary:

  • The company traditionally valued community service but recently focused on short-term profits.

  • Longtime employees may want to reaffirm the company's values by volunteering.

  • It may be more satisfying for employees to volunteer using their work skills.

  • There are assumptions about employees' willingness and ability to volunteer.

  • The Lean Startup model offers a way to test assumptions through experiments.

  • Strategic planning takes months; experiments can start immediately.

  • Break down the vision into a value hypothesis (do customers find the product valuable?) and a growth hypothesis (how will new customers discover the product?).

  • Survey a small group of target customers (longtime employees) to gauge their volunteer interest. See how many volunteer again and recruit others.

  • Provide an excellent experience for initial volunteers to match the vision. Measure their actual behavior and feedback.

  • Experiments can influence the overall strategy. Negative results mean it is time to pivot.

  • An experiment is like an early product. It can find early adopters, gather feedback to build the complete product, and have customers ready when launched.

  • Kodak Gallery tested assumptions before building a new "event album" feature. Experiments showed that customers did not need help creating albums and wanted more features.

  • The negative feedback was demoralizing but helped avoid wasted effort. More experiments led to a successful product.

The key takeaway is that experiments that test vital assumptions and hypotheses can help validate or invalidate business ideas much faster than traditional strategic planning. Experiments turn assumptions into knowledge and save effort on ideas that will not work. Although negative results can be discouraging, they provide valuable learning to help create products that will succeed.

Here is a summary:

  • A team launched a product's beta version to create event albums. It was a success despite missing many planned features and receiving customer complaint success. They learned that users wanted the ability to arrange pictures, which was valuable information. They also learned that some planned features were not important to customers.

  • The CEO held off the marketing campaign so the team could improve the product based on feedback. This was a change for the company, which typically launched on pre-set dates. The CEO said success is learning to solve the customer's problem, not just delivering features.

  • In India, few people have washing machines. Most pay Dhobis to hand wash and air dry clothes, which takes ten days. Akshay Mehra saw an opportunity for affordable laundry service.

  • Village Laundry Service did experiments to test assumptions, starting with a basic setup that cost $8,000. They learned that customers would give them laundry and pay for same-day service. They improved based on feedback and now have 14 locations, serving over 10,000 customers.

  • The Consumer Financial Protection Bureau was tasked with protecting people from predatory lenders. Usually, a new government agency would make an expensive, time-consuming plan. However, the CFPB is considered a "lean startup" approach.

  • The assumption was that call volume would be high once Americans knew they could call about financial fraud. But this was an assumption, not a fact.

  • To test, the CFPB could start with a simple hotline in a small area, using targeted marketing. The MVP would give information via voice prompts, not caseworkers. This experiment would cost a few thousand dollars and provide invaluable learning about the types of problems people see as essential and the level of interest.

  • The CFPB could then improve and scale the service over time based on continuous learning and feedback. A scaled-up service would be much better than the MVP but also much more expensive. The MVP allows learning at low cost.

Here is a summary:

The o cial plan for the Consumer Financial Protection Bureau (CFPB) was ready for implementation. This early service could serve as a real-world template.

The CFPB is adopting an experimental approach. Instead of a limited rollout, it is segmenting its first products by use case, starting with credit cards. This experiment will allow the CFPB to monitor complaints and feedback in uence future o erings.

The CFPB aims to make it easy for citizens to report problems in the consumer financial marketplace. The CFPB can then react to this information. Markets are always changing, so the CFPB must also change.

Building innovative new products is challenging even for experienced managers. A mindset change is needed, from relying on well- researched plans to using experiments and feedback to steer startups.

The lean startup model relies on a build-measure-learn feedback loop. The loop starts with assumptions to test, builds a minimum viable product, measures progress and learns whether to pivot or persevere. Using this loop can save startups time and money.

Facebook showed how validating the value and growth hypotheses through a minimum viable product and early solid traction can attract investment, even without a transparent business model or revenue. Facebook had strong engagement and viral growth at colleges. This showed it had a different "engine of growth" than the failed dot-coms.

Here is a summary:

• Facebook succeeded by attracting massive customer attention and monetizing it through advertising. This validated the assumption that attention would be valuable to advertisers.

• Many entrepreneurs try to copy Facebook's success but get confused about the lessons. There are no universal rules; startups must run experiments to determine what will work for them.

• Strategy relies on assumptions that have not been proven. Startups should test assumptions quickly. They need a vision but also rigor in testing assumptions.

• Some assumptions are straightforward facts or deductions. However, some are "leaps of faith" that require courage to state, like assuming customers want your product. Arguments by analogy are often used to make leaps of faith seem less risky.

• It is essential to identify facts versus assumptions. Just because a previous technology enabled a market win does not mean your technology will. Test whether customers want your solution.

• "Analogs" are comparable companies or products. "Antilogs" are counterexamples. Use them to identify your assumptions and leaps of faith.

• Success depends on more than just being in the right place at the right time. Successful entrepreneurs adapt based on learning what is working and not working.

• The two most essential leaps of faith are the value creation hypothesis (whether your product creates value) and the growth hypothesis (whether and how you can grow). Some growth is "success theater" without real value.

• Innovation accounting, unlike traditional accounting, helps determine whether a startup is creating real value and growth. It requires a quantitative model but also getting out to learn from customers.

• Strategic plans early on will be based more on hunch and intuition. "Get out of the building" to start learning and turning intuitions into data.

Here is a summary:

• Genchi gembutsu is a core principle of Toyota's lean manufacturing approach. It means "go and see for yourself." Toyota believes decisions should be based on firsthand knowledge, not reports or assumptions.

• The chief engineer for Toyota's 2004 Sienna minivan, Yuji Yokoya, took a 53,000-mile road trip across North America to understand customers' needs better. This helped guide essential design decisions and led to a 60% increase in sales.

• Startups should "get out of the building" and talk to potential customers to test assumptions and find problems worth solving. Intuit's founder Scott Cook called random people to see if paying bills by hand was frustrating before building a solution.

• Early customer conversations should focus on clarifying the potential customer and their problems, not specific product features. This helps craft an accurate "customer archetype" to guide product development.

• Too much or too little customer analysis can be problematic. Endless analysis leads to "paralysis" while a lack of analysis leads to building solutions no one wants. Finding the right balance is critical.

• Groupon started as an activism platform called The Point but pivoted after early Lack of success. They built a minimum viable product, daily deals, that took off and led to Groupon's success. Simplicity and rapid experimentation were vital.

• The message is that startups should engage in iterative learning through direct customer contact. They should start simple, test assumptions, and make incremental improvements based on feedback. Success comes from discovering what customers truly want, not what entrepreneurs assume they want.

Here is a summary:

•A minimum viable product (MVP) is the fastest way for entrepreneurs to start the process of learning. It is not the most miniature product imaginable, but the fastest way to go through the Build-Measure-Learn feedback loop.

•Contrary to traditional product development which aims for perfection, the goal of an MVP is to start learning, not end it. An MVP tests key business hypotheses, not just product design or technical questions.

•First products are not meant to be perfect. Early adopters, the initial customers, prefer an 80% solution. They use their imagination to fill in the gaps. Additional features beyond what early adopters want is wasted time and money.

•The complexity of an MVP ranges from simple smoke tests (advertisements) to early prototypes with problems. In doubt, simplify. It is better to start simple and add complexity than start complex and cut features.

•Dropbox created a video MVP. The founders were engineers building a technical product, not marketers. However, they wanted customer feedback on their crucial question: would people want their product if they experienced it? They created a video showing how their product worked. The video demonstrated the concept and value, allowing them to get feedback without building the entire product first.

•The video MVP validated their leap-of-faith assumption, helped them raise money, and made their beta test far more successful. The video communicated the concept in a way that meetings and discussions could not.

•Other examples of MVPs include concierge services, landing pages, crowdfunding campaigns, and Wizard of Oz setups. The key is to start the learning process as quickly as possible.

Does this summary make sense? Let me know if you wantwant me to clarify or expand on any summary part.

Here is a summary:

  • Drew Houston, the founder of Dropbox, created a simple 3-minute video demonstrating the vision for his product to attract early adopters and get them to sign up for a beta. This minimum viable product (MVP) validated that customers wanted the product Drew was developing.

  • Manuel Rosso, CEO of Food on the Table, used a "concierge MVP" to validate his product. Instead of building software, hiring chefs, and partnering with grocery stores upfront, Manuel and his team found one customer and served them personally each week to learn what was required to make the product successful. They started scaling from there, automating parts of the process to serve more customers over time. This approach reduced waste and ensured they built something customers wanted.

  • Max Ventilla and Damon Horowitz wanted to build a new search engine to answer subjective questions that Google struggled with, like recommendations for places to go out in a city. They created an MVP with a "Wizard of Oz" technique: they had people behind the scenes quickly answering questions to simulate the experience of using their software. This helped them validate the product concept and gain insights to build the software.

  • The "Wizard of Oz" technique is proper when building a working prototype of a software product is challenging. Having people manually simulate the experience can be an effective way to gain customer feedback and validate ideas. But it requires acknowledging the "man behind the curtain" - being transparent that it's not real automation.

The key message is that MVPs, including low-tech approaches like videos, concierge services, and "Wizard of Oz" simulations, can be effective ways to validate ideas and gain insights to build successful products. They reduce waste by ensuring you build something customers genuinely want before investing heavily in development.

Here is a summary:

  • Max and Damon wanted to build a product to help people get answers to subjective questions by connecting them with friends and friends of friends.

  • Instead of diving into programming, they spent six months building a series of prototypes to test different ways of solving the problem.

  • Each prototype took 2-4 weeks to build and was tested on 100-200 people. All prototypes failed to engage customers until the sixth one, which became Aardvark.

  • Aardvark worked by allowing people to ask questions via instant messaging. The questions were then directed to friends and friends of friends who could provide the best answer.

  • To build Aardvark, Max and Damon used "Wizard of Oz" testing, where people thought they were interacting with an AI, but humans were providing the answers. This allowed them to see if people would use the product before investing in building the AI.

  • MVPs are often considered lower quality, but the quality is hard to determine if you do not know who your customer is and what they want. An MVP can help determine what quality means for your product.

  • For example, IMVU initially had avatars that could not move. They built an MVP that allowed avatars to "teleport" to different spots instead of walking. Despite feeling "lame," customers loved the teleportation feature. They cared more about the end result than how much effort it took to build.

In summary, Max and Damon spent 6 months testing different prototypes to find a product that resonated with customers before building the full technology to power it. By using Wizard of Oz testing and focusing on key features that provided value to customers, they could build Aardvark without first needing to solve complex technical challenges. Their experience shows that quality is hard to determine upfront and MVPs, even if seen as lower quality, can help startups learn what customers really want.

  • MVPs require testing assumptions about what customers want. Releasing an MVP helps startups get honest customer feedback to validate or invalidate their hypotheses.

  • The most common objections to building an MVP are fears about legal issues, competitors stealing ideas, damaging the brand, and morale impacts from bad results. However, these risks can be mitigated. Patents are often for defensive purposes. Competitors are unlikely to steal obscure startup ideas. MVPs can be launched under different brand names. Moreover, teams must commit to iteration, not giving up after an MVP fails.

  • Startups need a disciplined system to determine whether they are progressing and achieving validated learning. Innovation accounting is an alternative to traditional accounting tailored for startups.

  • A startup's job is to measure where it is rigorously, face the hard truths this reveals, and then design experiments to get closer to the ideal reflected in the business plan. Startups need to avoid "living dead" status and false optimism.

  • Most startups and products have some traction and positive results, not zero. However, startups must measure their progress and learn from it to achieve their vision. Perseverance without learning is dangerous.

The key points are: test assumptions, get customer feedback, commit to iteration, use innovation accounting to measure progress, face hard truths, and persevere based on learning, not false optimism. An MVP helps startups learn the truth about what customers want so they can work toward achieving their vision.

Here is a summary:

  • Epic entrepreneurs who persevered against immense odds are celebrated, but we rarely hear about the many who failed by persevering for too long.

  • Accounting is essential for large companies to set goals and evaluate progress, but standard accounting only works for predictable startups.

  • Startups need "innovation accounting" to objectively prove they are learning and progressing. It involves:

  1. Establishing a baseline by testing assumptions with a minimum viable product (MVP) and getting metrics on the current status.

  2. Tuning the engine by improving growth drivers and measuring progress. This may take many attempts.

  3. Reaching a decision point to pivot or persevere. Pivot means restarting the process with a new approach. Persevere means continuing the current approach if good progress is being made.

  • To establish the baseline, build MVPs to test risky assumptions, like whether customers will use a product. Get metrics on conversion rates, customer lifetime value, etc. Test the riskiest assumptions first.

  • When tuning the engine, target initiatives at improving the drivers of growth, like making the product easier to use to increase customer activation rates. Measure whether changes improve the metrics. If they did, they succeeded.

  • Two startups may make product changes, but the one with a clear baseline metric, the hypothesis of improvement, and experiments to test it is doing practical work and achieving accurate results.

The key elements are systematically testing assumptions, measuring progress against key metrics, and being willing to pivot when the current approach is not working. This "innovation accounting" framework provides accountability and validation of authentic learning and progress.

Here is a summary:

  • The numbers in a startup's model should improve over time and converge towards the ideal targets set in the business plan. If not, it indicates the startup is not progressing and it is time to pivot.

  • Innovation accounting at IMVU involved tracking key metrics like customer registration, trial usage, and purchases to measure progress. Despite constant product improvements over 7 months, their metrics were flat.

  • They used cohort analysis to analyze the metrics. This groups customer by the month they first used the product and tracks their behavior. It showed that while more new customers were trying the product, the percentage that paid remained flat at 1%.

  • This failure forced them to talk to customers to understand why their work was not paying off. They realized customers did not want to avoid using IMVU with existing friends, leading them to pivot to focus on meeting new friends.

  • Optimization involves incrementally improving a product, process or marketing campaign. This works for established companies executing a plan, but not for startups searching for a business model.

  • Startups need to focus on learning, not optimization. They need to test new assumptions and hypotheses about their business model. Each pivot unlocks new opportunities for experiments and learning.

  • The learning process is establishing a baseline, tuning the engine (making fake product improvements), and thdecidingide to pivot or persevere based on whether key metrics are improving. This cycle repeats.

  • Progress is measured by whether new experiments are more productive than old ones, indicating a successful pivot. Optimization can only yield incremental gains, while pivots unlock transformational changes.

The key takeaway is that startups must focus on learning rather than optimization. They discover a viable business model through experimentation, measuring results, and pivoting as needed based on whether key metrics are improving. Optimization has a limited impact until they have found product-market fit.

Here is a summary:

  • Success requires having a sustainable business model and meeting clear milestones, not just optimizing products or marketing.

  • Startups often need more precise predictions and metrics to measure progress. Instead, they rely on "vanity metrics" like several users or revenue that do not reflect whether the business model works.

  • The example of IMVU shows how vanity metrics can be misleading. While user numbers proliferated, cohort analysis showed a slight improvement in user retention or monetization.

  • In contrast, "actionable metrics" from innovation accounting provide the clarity needed to build a sustainable business. They measure progress against key milestones that reflect the business model's success.

  • The story of Grockit illustrates the difference. The founder started by teaching test prep online, generating $10-15K/month in revenue. However, he had a bigger vision for collaborative online learning. With VC funding, the company proliferated.

  • However, they needed help determining whether their new products and features contributed to the growth or just the result of momentum. They gained clarity and built a sustainable business by adopting actionable metrics and the lean startup methodology.

The key takeaway is that startups need clear metrics and predictions to guide them, not just growth or product optimization. Vanity metrics can be misleading, while actionable metrics provide the insight needed to build a sustainable business model. The examples show why this matters in practice.

Here is a summary:

Grockit, an online education startup, had an impressive debut but needed help to gain traction. They followed an agile development process with short development cycles and constant feedback. However, their metrics focused on vanity metrics like the total # of customers rather than actionable metrics.

The CEO realized this and made two fundamental changes:

  1. They switched to cohort-based metrics that tracked how specific groups of customers responded to new features. This allowed them to draw more apparent cause-and-effect relationships.

  2. They began launching new features as split-test experiments, offering different variations of a feature to different customer groups. By comparing how the groups responded, they could determine the impact of specific feature changes.

These new techniques gave much more precise insights into how their product worked and what customers value. The CEO gained confidence that they were building the right product for their customers.

The key takeaways are:

  1. Vanity metrics can be misleading. Focus on actionable metrics that provide clear feedback.

  2. Cohort-based metrics and split-testing allow you to understand cause and effect and make confident product decisions.

  3. Agile development needs to be combined with a learning mindset. Constant feedback and iteration are enough to validate that you are building the right product.

  4. Startups need to be willing to experiment not just with their product but also with their internal processes. Grockit improved by pivoting its metrics and development approach.

Here is a summary:

  • Split testing helps teams identify and eliminate work that does not add value to customers. Through split testing, Grockit's team learned that extra social features did not change customer behavior. This led them to seek a deeper understanding of what customers wanted, which turned out to be a combination of social and solo study features.

  • Grockit implemented a kanban system to constrain work in progress and ensure validation of new features. Under this system, work could only progress to the next stage when the current stage was packed. This forced the team to validate completed work before moving on to new work. At first, this process was frustrating, but the team realized it increased productivity by avoiding waste and ensuring validated learning.

  • Grockit tested one of their significant features, lazy registration, and found it did not impact customer behavior. This showed them that their customers' decisions were based more on Grockit's positioning and marketing than on their experience with the product. This insight allowed Grockit to focus on attracting new customers through marketing rather than building new features.

  • Grockit's metrics demonstrated the three A's:

  • Actionable: Their reports showed clear cause and effect, allowing the team to take action to replicate results. This differs from vanity metrics like website hits, which lack context.

  • Accessible: The metrics and reports were accessible to the whole team, allowing them to work together to interpret results and determine the next steps.

  • Auditable: The metrics were based on concrete data from split tests and customer research, allowing others to audit the results and understand the rationale behind decisions.

In summary, through disciplined experimentation, the constraint of work in progress, and metrics demonstrating validated learning, Grockit built a product that better met customer needs. Their story shows how focusing on continuous learning and improvement can help startups succeed.

  • Vanity metrics, like raw numbers that go up and down, often mislead teams and cause conflict. They prey on human tendencies to attribute changes to our actions.

  • Actionable metrics, which show clear cause and effect, counter this by giving objective feedback that helps teams learn from their actions.

  • Accessible metrics are simple, concrete, and understandable to all. They focus on people and their behaviors, not abstract data points. Cohort-based reports are ideal. They should be widely distributed and housed with product teams.

  • Auditable metrics can be checked in the real world. They are drawn directly from data and avoid complex intermediate systems. This builds confidence in the metrics and learning. Spot checks with customers also provide insights into the data.

  • Most stories about entrepreneurship focus on the idea and early success but gloss over the difficult work of innovation accounting: figuring out which customers to target, testing ideas, and deciding when to pivot or persevere.

  • The pivot is a structured course correction to test a new hypothesis. Building a startup is among the most challenging, time-consuming, and wasteful. However, it is critical to achieving product-market fit.

According to the passage, the summary outlines the characteristics of good metrics and the importance and difficulty of pivoting for startups. The key takeaway is that vanity metrics often mislead, while good metrics provide objective feedback to help entrepreneurs make the right choices in a landscape full of uncertainty. Pivoting is critical but complex.

Here is a summary:

The critical decisions for entrepreneurs are making pivot or persevere choices. However, removing human elements like vision, intuition and judgment from entrepreneurship is undesirable. Applying a scientific approach to startups aims to direct human creativity into its most productive form. To avoid stagnation, it is critical to pivot in the face of marketplace feedback.

While human judgment can be flawed, we can improve it through testing. Startup success is aligning efforts with a business model that creates value and growth. Successful pivots put startups on a path to building a sustainable business.

David Binetti, CEO of Votizen, wanted to refrain from betting everything on his vision. His first product was a social network for verified voters. It attracted early adopters but critical metrics needed to be higher to determine engagement or referral rates.

After optimizing and spending $20K over eight months, referral and retention rates improved slightly but were still low. Despite some success, the product was not needed to meet growth expectations. David had to decide whether to pivot or persevere. His measurable leap-of-faith questions and early launch helped him face this decision early, avoiding wasted resources.

David pivoted to @2gov, a "social lobbying platform" allowing voters to contact representatives via social media, translated into print. The updated MVP took four months and $30K. Metrics improved dramatically but few were willing to pay. The value per transaction was too low.

David's vision allowed him to persevere and optimize the initial product. However, concrete metrics revealed the need to pivot, even after some success and optimization. The pivot focused the product and improved metrics, though more work was still needed. Vision and judgment guided the decision to pivot, but were informed by testing and data.

Here is a summary:

David struggled to sustain a profitable business even after optimizing it. He pivoted multiple times:

  1. From targeting consumers to targeting businesses and nonprofits. He signed letters of intent but could not close sales.

  2. He reduced staff and pivoted to a self-serve platform where anyone could become a customer. This showed good metrics and a growth model. Votizen accelerated its product development through learning.

  3. Votizen is now doing well, having raised $1.5M. Its tools have enabled political campaigns and legislation.

David contrasts his failures in 2003 (despite investment) with his current success using the Lean Startup method. He produced four versions in 12 weeks and got early sales. Others who didn't pivot failed.

A startup's "runway" is the time until it achieves takeoff or fails. It is usually defined as cash on hand divided by the burn rate. Cutting costs indiscriminately slows learning and feedback. The actual runway is pivots left, so get to pivots faster through validated learning at a lower cost.

Pivots require courage for three reasons:

  1. Vanity metrics allow false conclusions and illusions. This prevents seeing the need to change.

  2. Unclear hypotheses mean no complete failure, so no impetus to radically change (pivot). "Launch and See" fails here.

  3. Fear of change and the unknown. However, the status quo is often scarier, it just seems safer. Pivoting increases the chance of success.

The summary highlights the key elements around David and Votizen's story, their struggles and pivots, the concepts of the runway and reasons pivots require courage and the failures of vanity metrics and unclear hypotheses. Please let me know if you want me to explain or expand on any part of this summary.

  • Entrepreneurs can succeed in several ways, including conducting experiments and making constant adjustments based on results. Early results can often be ambiguous, so it is essential to be willing to pivot or persevere as needed.

  • Many entrepreneurs fear failure, which can reduce morale and prevent them from testing hypotheses. The terrifying thought is that a vision is proven wrong before being given a real chance. Entrepreneurs must face their fears and be willing to fail publicly to avoid this fate. High-profile entrepreneurs especially struggle with this.

  • The startup Path faced public criticism after launching a minimum viable product, but they listened to customer feedback instead of critics and were able to make essential changes. Their experience shows the importance of testing theories and listening to honest feedback.

  • Pivot or persevere meetings should be held regularly to determine if a startup should change direction or stay the course. These meetings require product development and business leadership teams' participation, which should bring product experiments and customer conversation results.

  • Wealthfront was initially launched as an online trading game called kaChing to identify skilled amateur investors, with the goal of eventually allowing them to manage real money. However, after launching a paid product, only a few customers signed up and only seven gamers qualified to manage money. They had to determine a new strategy at their pivot or persevere meeting.

  • If Wealthfront only had the data showing their current strategy was not working, they would have been in trouble. However, they looked beyond the initial results at the meeting to find a path forward.

Here is a summary:

Wealthfront had to pivot from an amateur investment platform to partnering with professional money managers. They investigated alternatives by talking to money managers and consumers. They found:

  1. Successful money managers wanted to partner because transparency would validate them.

  2. Money managers needed help to scale their businesses and needed Wealthfront.

  3. Consumers needed clarification on the amateur platform.

The pivot abandoned the amateur platform and focused on professional money managers. Though dramatic, much stayed the same like the technology to evaluate managers. The pivot has been very successful.

Failure to pivot is common. IMVU failed to pivot for too long. They were very successful with early adopters but ignored mainstream customers. They should have done a customer segment pivot. They needed to be more focused on growth and learning. They needed to start over with innovation accounting. They developed a customer archetype and improved the product to make it easier. Though they pivoted late, their experimental skills helped them.

In summary, the key lessons are:

  1. Pivoting is critical but complex. You have to abandon assumptions and celebrate what you learned.

  2. Failure to pivot is common and happens when you focus too much on growth and success.

  3. You need to get back to basics with innovation accounting.

  4. Pivoting does not mean abandoning everything. Some things like skills and technology can be repurposed.

  5. A customer segment pivot is needed when you serve the wrong customers.

  6. Mainstream customers require dramatic product changes. Optimize for them, not just early adopters.

Here is a summary:

  • The company initially had a redesign that performed worse than the existing design. However, through continuous testing and improvement, the new design performed better. This redesign fueled the company's future growth and success.

  • Pivots are structured changes designed to test a new fundamental hypothesis about a product, business model, or growth engine. There are many types of pivots:

  • Zoom-in pivot: A single feature becomes the whole product.

  • Zoom-out pivot: A single feature cannot support a whole product.

  • Customer segment pivot: The product solves a real problem for a different customer segment than initially planned.

  • Customer need pivot: The problem the product is trying to solve is not that important to customers, but other related problems are discovered that can be solved.

  • Platform pivot: Shifting from an application to a platform or vice versa. Usually a "killer app" is first sold to gain traction.

  • Business architecture pivot: Switching between high margin/low volume and low margin/high volume business models.

  • Value capture pivot: Changing how a company makes money and captures value.

  • Engine of growth pivot: Changing growth strategies to seek faster or more profitable growth.

  • Channel pivot: Recognizing a solution could be delivered through a different channel.

  • Technology pivot: Achieving a solution through a completely different technology. More common for established businesses.

  • Pivots represent a strategic hypothesis that requires testing with a minimum viable product. Analogies to successful companies can be misleading. A pivot is a structured change, not just an exhortation to change.

  • Pivoting is a permanent fact of life for growing businesses. Even successful companies must continue to pivot to avoid disruption. The critical skill is knowing how and when to pivot.

Here is a summary:

Startups face many uncertainties and unclear choices. Some of the critical questions are:

  • How often to release a new product? Releasing too often reduces efficiency but waiting too long risks building something no one wants.

  • How much to invest in infrastructure and planning? Spending too much wastes time learning while spending too little fails to capitalize on success.

  • What employees should focus on and how to hold them accountable for learning? Traditional departments incentivize expertise in functions but cross-functional collaboration may better serve startups.

Lean manufacturing provides some answers that startups can adapt:

  • Identify value-creating activities and eliminate waste. For startups, value means validated learning about the business, customers, growth, etc. This learning creates value.

  • Use small batches. Like lean manufacturing reduces inventory through just-in-time, startups can do "just-in-time scalability" with small experiments rather than significant upfront investments.

  • Metrics for growth. Startups should track metrics to understand their growth engine (paid, viral, sticky) and pivot when growth may stall.

  • Build an adaptive organization. Use lean techniques like Five Whys to scale without bureaucracy—transition to operational excellence.

  • Invest in disruptive innovation. Successful startups can keep their entrepreneurial spirit. Companies need sustainable and disruptive innovation. Startups and big companies face similar pressures.

Small batches have surprising power. They:

  • Reduce time sorting and moving work in progress.

  • Identify problems earlier, minimizing rework.

  • Produce finished work frequently, allowing quick feedback and changes.

  • Suit startups that cannot compete on scale. Toyota used small batches and flexible machines instead of mass production's specialized machines and enormous scale.

Small batches provide benefits through faster feedback, less waste, and flexibility - all crucial for startups facing extreme uncertainty. Overall, lean startup techniques adapted from lean manufacturing can help startups accelerate their learning and make the most of scarce resources.

Here is a summary:

Toyota dramatically improved its productivity and quality by reducing changeover times and the time required to change a machine from making one part to another. By switching machines frequently to produce parts in small batches, Toyota gained several benefits:

  1. Higher diversity of products. Small batches allowed Toyota to produce more products to serve fragmented markets. Over time, this capability allowed Toyota to compete in larger markets.

  2. Faster feedback. Small batches enabled Toyota to detect quality problems much sooner. Workers could stop the production line as soon as a defect was spotted to fix the issue immediately. Although stopping the line reduced efficiency in the short term, it led to higher quality and lower costs over time.

  3. Continuous improvement. By resolving defects quickly, Toyota could continuously improve its production system. Each improvement led to the ability to work in even smaller batches.

The benefits of small batches also apply to entrepreneurship and startups. Working in small batches allows startups to accelerate learning and minimize wasted effort. If a product needs to be pivoted or a strategy changed, a startup will know sooner by releasing in small batches.

For example, IMVU, an online social network, deployed new features in small batches, sometimes updating their product 50 times per day. They also monitored the "health" of their key metrics to quickly detect any problems with new releases, allowing them to automatically roll back defective changes, halt further updates, and fix issues. Although controversial, this "continuous deployment" and feedback loop has been adopted by more startups to speed up innovation.

Beyond software, the principles of small batches and accelerated learning are spreading to other industries:

  1. Hardware is becoming software-centric. Many products like phones are now just screens connected to the Internet, with software determining most of their functionality and value. The software can be modified much faster than the hardware.

  2. Faster production changes. Lean manufacturing has enabled assembly lines to customize each product, allowing for faster design feedback and changes.

  3. Shortened product lifecycles. In many industries, the pace of change has accelerated, shortening product lifecycles and requiring faster learning and iteration. Startups' ability to operate at a high tempo is becoming essential for more established companies.

In summary, using small batches, rapid iteration, and accelerated learning is critical to innovation, productivity, and competitive advantage across many industries. Technologies and processes enabling startups to move at high speed will also impact established organizations.

  • New technologies like 3D printing and rapid prototyping allow for small batch production at low cost. This allows entrepreneurs to build small batches of high-quality products quickly and inexpensively.

  • Working in small batches allows for faster feedback loops and learning. This faster learning can provide a competitive advantage.

  • An example of small batch production in action is SGW Designworks, which designed and built a field x-ray system for the military in just 3.5 weeks using rapid prototyping and small batch production. They went through multiple design, prototyping, and review cycles to get feedback and make improvements.

  • Small batch production can be challenging in some areas like education where curriculum is typically designed in large batches. However, some startups like School of One enable small batch experimentation in education through personalized learning playlists and frequent assessments.

  • Large batch production often leads to a "death spiral" of rework, interruptions, and delays. It seems efficient for individuals to work in isolation on large batches, but then questions and problems arise, leading to interruptions and rework. This rework often has to be redone multiple times. Some managers work nights and weekends to avoid interruptions from emerging problems.

  • We tend to blame ourselves when significant batch systems malfunction, rather than recognizing the systemic issues with large batch production. People are instinctive to work in large batches even when a small batch approach may be better.

  • Alphabet Energy developed a thermoelectric material that can generate electricity from waste heat. Bringing clean tech products to market requires building solutions for specific use cases.

  • Unlike other clean tech companies, Alphabet Energy based their material on silicon wafers, allowing them to leverage existing manufacturing infrastructure and build products in small batches. This allowed them to go from concept to holding a physical product in just six weeks.

  • Their challenge has been finding the right combination of performance, price, and reliability to meet customer needs. They used the Lean Startup method, testing hypotheses through experiments to find the right product-market fit.

  • Rather than predicting what customers want, they designed experiments to test key assumptions and pull work from product development to run those experiments. Any other work was considered waste.

  • This "hypothesis pull" allowed them to reduce batch size, decrease waste, and speed up the build-measure-learn feedback loop. Through experimentation, they found that industrial facilities were most interested in their product.

  • Like with lean manufacturing, reducing the batch size and pull-based work decreased excess inventory (WIP). For startups, WIP includes unfinished designs, unvalidated assumptions, and unproven business plans. The Lean Startup techniques aim to reduce WIP through small batches, hypothesis pull, and fast experimentation.

  • In summary, the key to Alphabet Energy's success was framing progress around executing experiments to gain validated learning, rather than building products and hoping customers buy them. This allowed them to achieve product-market fit and scale.

  • The two startups were very different in industry and product but shared the same problem - Lack of growth. Though they had early customers and revenue, their growth had flattened.

  • Growth comes from past customers through four ways:

  1. Word of mouth: Satisfied customers tell others

  2. Side effect of usage: Products that convey status or luxury spread awareness when used. Viral products also spread this way.

  3. Funded advertising: Paid for by revenue, not one-time investments. Growth depends on the marginal cost to acquire a customer being less than the marginal revenue from that customer.

  4. Repeat purchase: Subscription or repeat buy models.

  • These sources of growth power feedback loops called "engines of growth". The faster the loop, the faster the growth. Each engine has metrics that determine how fast a company can grow with it.

  • The two startups used the "sticky engine of growth," where products attract and retain customers long-term. For the collectibles company, the goal is to become the top destination for collectors who will repeatedly use the product. For the database company, the goal is long-term enterprise contracts.

  • The metrics that matter for the sticky engine are customer retention and lifetime value. Optimizing them will restart growth.

  • Many startups fail by "drowning" in the many small ideas for optimizing their product instead of focusing on the extensive experiments that lead to real learning. The engines of growth framework provide the metrics for startups to focus on.

Here is a summary:

  • Two startups rely on repeat usage of their products by customers. Once customers start using the products, the companies expect them to continue using them. This is because switching to a competitor's product takes time and effort. These companies closely track their "churn rate," which is the percentage of customers who stop using the product in a given period. Their growth depends on new customer acquisition exceeding the churn rate.

  • The "viral engine of growth" relies on customers spreading awareness of the product to new potential customers, similar to how a virus spreads. Products that exhibit viral growth, like Hotmail and Tupperware, see awareness spread as a natural consequence of customers using the product, not because customers are intentionally promoting the product. These companies focus on increasing their "viral coefficient," which measures how many new customers each existing customer brings in—a viral coefficient over one leads to exponential growth.

  • The "paid engine of growth" relies on a company's ability to pay to acquire new customers. The speed of growth depends on how much it costs to acquire a new customer versus how much revenue that customer generates. Companies can pay to acquire new customers through advertising, sales efforts, opening new locations, etc. The lower the customer acquisition cost relative to customer lifetime value, the faster these companies can grow by spending more to get new customers.

  • In summary, companies rely on different "engines of growth": repeat usage and low churn (sticky), word-of-mouth and virality (viral), and paid customer acquisition (paid). Identifying which engine of growth drives a particular business is critical to understanding its key metrics and how to help it grow.

Here is a summary:

  • The paid engine of growth relies on using revenue from existing customers to acquire new customers through advertising and marketing. This engine requires that the lifetime value of customers exceed the cost of acquiring them.

  • IMVU initially thought it could grow virally as an add-on to instant messaging networks but ultimately had to pivot to paid growth. Customers wanted to avoid using IMVU with existing friends. They wanted to make new friends on the platform.

  • The ability to grow using the paid engine over the long term requires making more money from specific customers than competitors. IMVU did this by developing ways to get payments from customer segments that other companies, like teens, ignored or assumed would not pay.

  • Technically, companies can have more than one engine of growth operating at a time. However, in practice, the most successful startups usually focus on just one engine and optimize everything to make that engine work. Switching between engines or trying to operate multiple engines at once often confuses.

  • The concept of engines of growth helps provide a quantitative framework for determining whether a startup has achieved product/market fit. For the paid engine, key metrics are customer lifetime value and cost of customer acquisition. If a startup can determine it is achieving product/market fit with a particular engine, it can focus its efforts on optimizing that engine.

  • Continuous evaluation using the Build-Measure-Learn feedback loop and innovation accounting helps startups determine if they are getting closer to product/market fit. Raw numbers and "vanity metrics" matter less than the trend and whether metrics improve over time.

  • Achieving product/market fit does not mean a company will never have to pivot again. Companies may need to pivot to a new growth engine to spur a new wave of growth. The key is focusing on one engine at a time.

Here is a summary:

  • Two hypothetical companies have different compounding growth rates: 5% and 10%. Even though 10% seems better on the surface, Company A shows accelerating growth over time whereas Company B's growth is stagnating. Company A is the better bet.

  • Every growth engine eventually runs out of fuel as the target customer base is exhausted. Growth plateaus or stops. Startups need to build new engines of growth to continue accelerating.

  • Adaptive organizations automatically adjust their processes and performance to current conditions. They build speed regulators to find the optimal pace of work. An example is the andon cord which stops production immediately when quality problems surface, forcing investigation and fixing the root cause. Adaptive organizations evolve organically through constant experimentation and revision.

  • Going too fast can be destructive without speed regulators. Defects and quality problems slow progress, hurt morale, and waste resources. Service businesses also need playbooks to specify how to deliver service under different conditions. Complex rules and corner cases accumulate over time, slowing the organization.

  • Process guides and rules tend to become more complex over time in companies. This can make it hard for managers to experiment with new rules or procedures. A high-quality process guide is more accessible to evolve than a poor one.

  • The Lean Startup approach emphasizes quick learning and releasing a minimum viable product. However, the Build-Measure-Learn feedback loop is continuous, so shortcuts today can slow you down tomorrow. IMVU initially shipped a low-quality product but had to redo much of the work. As the product improved, defects and complexity made further changes harder.

  • The "Five Whys" technique provides a natural feedback loop for startups to adapt gradually. It ties investments to solving current problems, using incremental changes. You ask "Why?" five times to find the root cause of a problem, which is often human error.

  • IMVU used Five Whys to build an employee training program incrementally. They started with a small investment to fix an immediate issue, then expanded the program over time as more issues were revealed.

  • Five Whys acts as an "automatic speed regulator." As problems increase, you invest more in solutions, speed up again as improvements occur, and problems decrease. It balances speed and quality, tying progress to learning. Startups should use Five Whys for any failures or surprises.

  • Five Whys is a powerful technique that can help derive the right solution to complex problems by revealing their root causes. With practice, teams can become adept at using it.

In summary, the Five Whys technique helps startups gradually evolve effective processes and solutions through small, frequent investments targeting current problems. It maintains quality while enabling accelerating progress.

The Five Whys is a problem-solving technique used to identify the root cause of a problem. By repeatedly asking "why" five times, you can peel away the layers of symptoms to identify the root cause. This helps teams develop solutions that address the underlying problem instead of fixing the immediate symptoms.

The "Five Blames" refers to when teams misuse the Five Whys technique by pointing fingers and blaming each other instead of identifying the root cause. To avoid this, bring everyone affected by the problem into the discussion and have senior leaders emphasize that the goal is to fix the system, not blame individuals. Start with a simplified version of Five Whys before moving on to more complex problems.

Some tips for getting started with Five Whys:

  1. Create an environment of trust and empowerment. With this, the complexity of Five Whys can be manageable.

  2. Start with a simplified version, like "never allow the same mistake to happen twice." This helps build the habit before tackling more significant problems.

  3. Be prepared to face unpleasant truths. Five Whys will uncover problems in your systems and processes that require time and money to fix. Leadership support is needed to implement solutions.

  4. Start small and be specific. Pick a narrowly targeted problem to analyze before expanding to more significant, complex issues. Clearly define the types of issues that will trigger a Five Whys meeting.

  5. Appoint a "Five Whys master" to facilitate the meetings, determine solutions, and ensure follow-up. This person should have enough authority to drive change but still be able to participate in the meetings actively.

The example of IGN Entertainment shows how Five Whys can be used to analyze customer complaints in a structured way, determine the root cause, and implement effective solutions. By starting small and building up, Five Whys can help teams build the habit of continuous learning and improvement.

Here is a summary:

  • IGN is a significant gaming media company founded in the 1990s and acquired by News Corporation in 2005. It has hundreds of employees, including many engineers.

  • Recently, IGN's leadership wanted to accelerate innovation and improve their product development process. They decided to apply Lean Startup principles, but their first attempt at using the Five Whys technique was unsuccessful.

  • They appointed Tony Ford, a director of engineering, as their Five Whys master to lead the effort. After some initial struggles, Tony led a successful Five Whys session to analyze why their content management system returned errors. The session revealed several issues and led to proportional investments to fix them, including improving testing, automation, and deployment processes.

  • Tony said the Five Whys revealed information that brought the team together and strengthened their "cluster immune system." Without it, they may have just blamed the developer and moved on. The learnings were as valuable as the proportional investments.

  • Intuit's QuickBooks product used a traditional annual release cycle where months were spent planning before building features. When they got feedback, there was still time to make major changes. They wanted to move to shorter development cycles to get faster feedback.

  • Greg Wright, the director of product marketing, advocated for a switch to shorter sprints and iterations. Despite initial skepticism, a pilot project showed the benefits of faster iterations and customer feedback. The new process was adopted, and QuickBooks released updates every 4-6 weeks.

  • The new process allowed them to adjust based on customer data and ship higher quality updates. Customer satisfaction and retention improved as a result. The QuickBooks team overcame resistance to change by starting small, showing the benefits, and building on early wins.

Here is a summary:

  • Intuit's QuickBooks team used a traditional "waterfall" development methodology that relied on upfront planning and forecasting. This could have worked better in a fast-changing environment.

  • In 2009, the first year Greg was on the team, they shipped a new online banking feature that failed and took nine months to fix due to the slow process. Customer satisfaction dropped significantly.

  • Greg tried to improve the process by using smaller teams, shorter cycle times, faster customer feedback, and empowering teams. However, progress was slow due to "organizational muscle memory."

  • In Year 3, Greg and the product leader overhauled the process. They invested in new technologies, cross-functional teams, and involving customers from the start. This allowed much faster iteration and experimentation.

  • They had to overcome skepticism by explaining why the old process did not work and how startups were moving faster. Communication was key.

  • They reduced team size from 15+ people to 5 people and cycle time from 6 months to 6 weeks. Many small branches allowed more experiments.

  • They built new tools like a virtualization system to reduce risk and allow smaller batches, and enable faster releases.

  • The changes in mindset and culture were vital but had to be supported by changes to the technical systems and processes. Simply changing culture alone would not have been enough.

In summary, the QuickBooks team was able to overhaul its successfully development process by rethinking their approaches, redesigning their technical systems, forming cross-functional teams, and focusing on rapid customer feedback and experimentation. But driving this level of change required significant work to shift mindsets and address organizational challenges.

  • Intuit released multiple versions of QuickBooks to select customers to get feedback before the official release. This allowed them to test new versions on real customers in a controlled way without worrying about data corruption.

  • After three years of using this technique, QuickBooks released a version with significantly higher customer satisfaction that sold more units. Most QuickBooks users today use a version built using small batches and frequent customer feedback.

  • As startups grow into established companies, they can use lean techniques to develop complex processes while maintaining speed and agility. Startups that do this are well-positioned to achieve operational excellence based on lean principles.

  • However, established companies also need to pursue disruptive innovation to find new sources of growth. This requires "portfolio thinking" - managing existing business lines while exploring new opportunities.

  • Successful innovation teams, whether in startups or established companies, require:

  1. Scarce but secure resources: Limited budgets protected from tampering. Too much or too little budget is harmful.

  2. Independent authority: Autonomy to develop and market new products without excessive approvals. Cross-functional teams with the ability to build and ship products, not just prototypes.

  3. A personal stake: Equity, bonuses tied to long-term success, recognition, and credibility. This motivates innovation teams to take risks and achieve success.

  • To enable internal startups, companies need to establish a "platform for experimentation":
  1. Protect the parent organization: Ensure accountability, oversight and the ability to reintegrate successful innovations. Do more than just protect the startup team.

  2. Use accountability mechanisms: Objective metrics, reviews, and milestones. However, minimize handoffs, approvals and interference.

  3. Reintegrate successful startups: Have the plan to scale innovations and transition them to the main company structure. Address cultural/structural issues.

  • The end goal is to achieve speed and agility through small teams and frequent iteration, while leveraging the resources and stability of an established organization. Portfolio thinking and platforms for experimentation are critical to this.

Here is a summary:

  • The company struggled and needed help interpreting the results of an experiment to grow its consumer business segment.

  • There were many issues with the experiment including:

› Using vague metrics instead of actionable ones. › an extended period which made it hard to determine what led to results. › Unclear hypotheses and weak experimental design.
› Lack of team ownership and accountability.

  • The meeting to discuss the results became arguments as each department interpreted the data to support their agenda.

  • The executives ended up making decisions based on persuasiveness rather than data.

  • The root cause of the issues was a rational fear that changes to help the consumer segment would hurt their core B2B segment.

  • Hiding innovation teams and experiments often does not lead to sustainable change and can breed distrust and politics.

  • The suggested solution is creating an "innovation sandbox" with strict rules to contain the impact, including:

› Only allowing split-test experiments in the sandbox. › Requiring one team to own each experiment end-to-end. › Putting time limits on experiments.
› Capping the number of customers affected. › Using the same few metrics to evaluate all experiments. › Requiring close monitoring and the ability to abort experiments if needed. › Starting small and gradually expanding the sandbox.

  • The sandbox allows for open innovation in a controlled way that addresses fears and gains trust over time.

  • Long-term relationships with customers are essential for innovation teams. They need time to experiment, learn, and achieve milestones.

  • Cross-functional innovation teams with clear leaders, like Toyota's shusa, are most effective. They should have autonomy to build, market, and deploy without prior approval, but report on progress using metrics.

  • This approach works even for teams new to cross-functional work. Early experiments do not only require a little engineering but coordination across departments. Productivity is measured by creating customer value, not just activity.

  • Real experiments are easily judged as successes or failures based on metrics. Teams learn if assumptions are correct. Using the same metrics builds company-wide understanding. Even critics have to learn the metrics to undermine the team.

  • Rapid iteration from end-to-end work in small batches provides quick feedback and helps teams converge on optimal solutions. This manifests the principle of small batches, unlike functional teams' large batches that bog down good ideas.

  • Like startups, internal teams should be held accountable to an ideal disruption model, establish a baseline, tune to get closer to ideal. As they succeed, they integrate into the company's portfolio.

  • Companies do four kinds of work: creating new products, growing and optimizing them, maintaining infrastructure, and reducing costs. Employees often follow the products they develop through these phases, but some suit certain phases better. Allowing people to choose leads to better fits.

  • Entrepreneur should be a viable internal career path with accountability via innovative accounting and rewards. Entrepreneurs incubate products and then hand them off to larger teams to commercialize and scale, training them in new methods.

  • The innovation sandbox can grow over time by adding new product features or customers. However, senior management must consider if the team can handle the politics. Teams improve with constant feedback and milestones. Success leads to an innovation cycle as former innovators become guardians of the status quo.

Here is a summary:

  • The Lean Startup approach inevitably becomes part of the status quo as companies adopt it. This is hard for innovators to accept as their radical ideas become mainstream.

  • As the ideas become standard practice, new employees must be indoctrinated. However, the ideas have become the status quo for longtime employees, leading them to suggest radical changes in the opposite direction.

  • Considering these suggestions seriously and scientifically is essential to determine whether they have merit. Blindly compromising or dismissing them is not helpful. The Lean Startup is a framework, not a set of steps to follow, so it needs to be adapted to each company.

  • Switching to validated learning often feels worse before it feels better because the problems of the new approach are tangible while the problems of the old approach were intangible. However, with the benefit of theory, this transition can be managed by setting expectations upfront.

  • The Lean Startup community allows people to explore and master these ideas. The approaches must be tailored to each company rather than copied from others.

  • Frederick Taylor pioneered scientific management 100 years ago. His ideas led to tremendous prosperity but were also taken to an extreme, treating workers like automatons. Subsequent management theories corrected this.

  • Today we face new problems Taylor could not imagine. Our ability to produce exceeds our ability to determine what to produce. Prosperity depends on imagination rather than just efficiency. While Taylor focused on efficiency and productivity, today we must determine if things should be built.

  • Taylor pointed out that we fail to appreciate the enormous waste of human effort from inefficiency and blundering. We can see and feel more tangible wastes but these less visible wastes persist.

Here is a summary:

The passage discusses the waste and inefficiency that results from the misuse of human effort and time. While we have become much more efficient in producing material goods, we need to be more wasteful regarding how we direct human energy and creativity. The author estimates that much of this waste is preventable if we change how we think about innovation and adopt a more scientific approach.

The Lean Startup movement aims to bring more rigor and scientific thinking to entrepreneurship and new product development. By focusing on validated learning and building a sustainable business model, the Lean Startup can help reduce waste and increase the odds of success. However, we must avoid making the same mistakes as scientific management, emphasizing efficiency and system over human judgment and adaptability. The key is finding the right balance between planning and flexibility, vision and experimentation.

Much of current product development practices amount to pseudoscience. Teams routinely approve new projects based on intuition rather than facts. They engage in "success theater" by selectively using data to confirm their beliefs and avoiding external feedback. Real learning and progress can only be demonstrated through building models of customer behavior and then using new products and services to change that behavior systematically. Overall, the passage argues for bringing more scientific rigor and experimental thinking to the work of innovation and entrepreneurship. However, this should not come at the cost of the human elements that are equally vital to success.

Here is a summary:

  • The Lean Startup movement should avoid becoming rigid or doctrinaire. We must avoid portraying science as formulaic or lacking in humanity. Science is a creative human pursuit that can unlock human potential if applied to entrepreneurship.

  • An organization using Lean Startup principles would explicitly state and test assumptions, value speed, and quality, learn from failures, avoid unnecessary work, and focus on creating long-term value.

  • People's time would be well-spent. Arguments would be avoided in favor of testing visions quickly while maintaining quality. Waste would be eliminated to achieve agility and results, not perfectionism.

  • Setbacks would be met with learning, not blame. Speed would come from skipping unnecessary work, not increasing batch sizes, or avoiding risks. The focus would be on building sustainable value and positive change.

  • The Lean Startup movement has spread globally. Many resources are now available, but local communities and ecosystems remain essential. The author's website contains more information and resources. Reading is good, but taking action is better.

  • In conclusion, the success of the Lean Startup movement must not lead to a new pseudoscience around concepts like pivots, MVPs, and validated learning. Scientific management's early success bred similar problems, setting it back for decades. We must question our assumptions and prejudices to avoid the same fate. Research into productivity, accountability, and how to nurture innovation is needed. A "Long-Term Stock Exchange" could also help companies focus on innovation.

Here is a summary:

  • There are many Lean Startup communities and resources to tap into, including:

  • Lean Startup Meetup groups in over 100 cities

  • The Lean Startup Wiki, which lists events and resources

  • The Lean Startup Circle, an online community with thousands of members sharing tips and stories

  • The Startup Lessons Learned Conference

  • Required reading includes The Four Steps to the Epiphany, The Entrepreneur's Guide to Customer Development, and several recommended blogs

  • Further reading recommendations cover topics like disruptive innovation, startup metrics, product development, Lean thinking, and more

  • The key ideas in the Lean Startup methodology are: build-measure-learn feedback loops, validated learning, and pivoting when necessary based on customer insight

  • Examples of companies that have employed Lean Startup principles include Intuit (with SnapTax), IMVU, HP, Kodak, and Village Laundry Services in India.

The summary touches on the available Lean Startup resources and communities, the core ideas of the methodology, recommended books and blogs on related topics, and examples of companies that have used the Lean Startup approach. The details on the specific companies and their experiments are omitted from the high-level summary. Please let me know if you want me to clarify or expand the summary in any way.

The Consumer Financial Protection Bureau (CFPB) opened its doors on July 21, 2011 but will only accept consumer complaints about financial products and services later this year. The CFPB was created by the Dodd-Frank financial reform law to protect consumers from unfair practices. However, it is still in a "beta testing" phase and is not ready to handle complaints. The agency will first focus on handling credit card complaints and later expand to other financial products.

The key points are:

  1. The Consumer Financial Protection Bureau launched on July 21, 2011.

  2. However, the CFPB is still testing its systems and is still waiting to be ready to accept consumer complaints. It will start by handling only credit card complaints.

  3. The CFPB was created by the Dodd-Frank law to protect consumers from unfair financial practices.

  4. The CFPB's complaint system is still in "beta testing," The full rollout will happen in stages over the coming months.

  5. Many public servants have worked hard under President Obama's leadership to set up the CFPB. The author thanks several of them by name for their efforts.

The summary is high-level but captures the essence and critical details of the source article. Please let me know if you want me to clarify or expand the summary in any way.

Here is a summary of the key ideas from the passages:

  1. The story of Hotmail's viral growth is discussed in the book Viral Loop by Adam Penenberg.

  2. The four essential resources customers can provide to a business are time, money, skill, and passion.

  3. According to Geoffrey Moore's Crossing the Chasm, businesses should focus on dominating a niche market before expanding to new segments.

  4. The Toyota Production System by Taiichi Ohno discusses lean manufacturing principles like minimizing waste.

  5. Net Promoter Score is a tool for measuring customer satisfaction and loyalty. It is discussed in The Ultimate Question by Fred Reichheld.

  6. QuickBooks is an accounting software product. The passages mention interviews with QuickBooks as a source of information.

  7. Japanese companies like Toyota are known for their technology management practices, especially around lean production and continuous improvement.

  8. Geoffrey Moore's Dealing with Darwin discusses strategies for established companies to adapt to disruptive innovations.

  9. There are quotes from Peter Drucker and the Tao Te Ching about efficiency, waste reduction, and flexibility.

  10. The author has worked with or had investments in Aardvark, Dropbox, Food on the Table, Grockit, IMVU, Intuit, Votizen, Wealthfront, 500 Startups, Floodgate, Greylock Partners, Kleiner Perkins Caufield & Byers. So, he may have a conflict of interest in discussing those companies.

  11. The author thanks many collaborators, mentors, researchers, entrepreneurs, investors, and publishers who provided feedback and support in developing the ideas presented in the book.

Does this summary accurately reflect the key ideas and highlights from the passages? Let me know if you wantwant me to clarify or expand on any summary part.

The author expresses gratitude toward his grandparents, Andrew Ries, and k, for their constant love and support. They believed in the power of writing and supported his interests in technology and entrepreneurship.

He also expresses gratitude toward his sisters, Nicole and Amanda, and brother-in-law, Dov, for supporting him through the years.

Finally, he expresses deep appreciation and gratitude toward his wife, Tara Sophia Mohr, for being by his side through every struggle and success. He says she is incredibly brilliant, strong, and compassionate and grateful for her steadfast support, love, and their life together.



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