The Lean Startup Summary

Is there a method for success? Enter the lean mean startup machine.

The Lean Startup is a go-to guide for anyone wanting to enter the world of startups, or fine-tune their business. It takes us through understanding customers, testing the market, analyzing user experience, and most importantly, hustling to do all of this so that capital doesn't run out.

Eric Ries, a successful American entrepreneur, argues that hard work and passion don't guarantee success in startups. When it comes to business and entrepreneurship, Ries suggests a scientific approach with a focus on curiosity. Just as a scientist would, an entrepreneur starts with an idea. In business though, this is usually an assumption about what customers want, and what they're willing to pay.

As with a scientist, a successful entrepreneur creates an experiment, evaluates the data, and adapts accordingly. But, the trick is to do this quickly and cheaply before funds run out. Ries says we tend to rely on a vision or great leader to make the magic happen, or we over-analyze the product or service. Instead, innovation and entrepreneurship need a reliable methodology.

We'll briefly look at the sound scientific approach, which gives a framework to build a successful and sustainable business. What's more, we'll also look at how to be more resilient and confident when it comes to the uncertain world of the modern startup.

Let's Begin with a Familiar Story

We've all heard stories of a dream team of brilliant college kids who build a company from scratch. They hustle to get some funding, hire friends, and then dare anyone to stop them. They have a great product, a good team, the right technology, and the right idea at the right time. Despite all this, they somehow can't sustain success. The company fails, and disillusioned, they part ways. Promises to friends, family, and employees, all go unmet. So why is it that hard work and perseverance don't necessarily lead to success?

Ries understands failure firsthand, because he's one of the college kids, who tried to build a company, but failed. His story is universal and reiterates that promising startups often fail, and most ventures don't fulfill their potential.

Popular culture often leads us to believe that startups are easy. We believe that with a positive attitude and work ethic, anyone can make their dreams come true. Ries argues that startups are tough; they take time and a continuous effort. Sure, they need a great idea, a good team, and an innovative product, but ultimately, the execution is what's vital. How you run a startup is critical to sustainable success. Unfortunately, the boring stuff does matter.

Initial failure didn't stop Eric Ries though. In 2004, he co-founded another business called IMVU. You may have heard of it. It's an online social network, where people use 3D avatars to meet new people, chat with each other, create digital items, and play games. But, what was most innovative was that they went against the traditional business approach. This new process involved a speedy cycle time, a focus on what customers want, and what they're willing to pay. This strategy was all backed up by a scientific method, when making decisions.

This method worked for them. The company became a roaring success, with millions of users, and $50 million in annual revenues in 2011. Ries' practical knowledge, and experiences form the basis of this book. He highlights methods that he's validated, that we can all use to improve our chances of success.

Chaos and Uncertainty are the Only Certainties

Chaos and uncertainty are, in fact, the only certainties in a startup. Because of this, entrepreneurship requires skillful management, validated learning, scientific experimentation, and fast evaluation of product-market fit. All of these are critical. The author's model is a pragmatic solution that incorporates the Build-Measure-Learn feedback loop. This loop, he believes, will give us a dependable guideline and framework for successful entrepreneurship.

Reis argues that, a startup is an institution, not just a product. Therefore, they require a unique kind of management, that we specifically gear to an extremely uncertain context. A successful entrepreneur knows that if a startup doesn't work, they should quickly discover why, before their funds dry up. Here is where the science comes in. The Lean Startup approach prioritizes learning, above all else. But, learning requires the use of disciplined experiments, which Ries calls validated learning through scientific experimentation. This process brings order to the chaos, and eliminates uncertainty as much as possible. The key to creating a sustainable business is to understand quickly what customers want, and what they're willing to pay for what they want.

The reason startups typically fail, is because they build something that people don't want to pay for.

Ries says that too often we ask, 'Can we build this product?' Instead, we should be asking, 'Should we be making this product in the first place?' Hence, the Build-Measure-Learn feedback loop gives us a process that provides the answer to this critical question.

The 'Build-Measure-Learn' Feedback Loop

As with any scientific approach, it begins with a standard hypothesis. In the world of startups, hypotheses are opinions or assumptions about what our customers want, and are willing to pay. Once we've selected a hypothesis to test, we design an experiment. This approach means building what Ries calls a minimum viable product, or an MVP, which allows us to test our hypothesis quickly and cheaply.

The next step is measurement, where we run our experiment. We expose customers to the product, collect data based on their behavior, and then we analyze the data and learn from it. The questions that we ask about the success or failure of a hypothesis determine whether we pivot or persevere. And although metrics and specificity matters, so does speed. The faster we cycle through the loop, the quicker we learn. So the key aim is to shorten product development cycles, learn what's valuable to the customer, and work out if it's worth our time, our money, and the effort of our team.

This is a Learning Process

There are two initial questions we have to test when it comes to learning. Ries frames these as two critical hypotheses: the value hypothesis and the growth hypothesis.

In terms of value, the questions to ask are customer-focused. So, does the customer experience the problem we're trying to solve? Or, does the product deliver value to the customer? On the other hand, the growth hypothesis focuses on how the company will grow, once people start using the product.

Ries views every startup, as a grand experiment that attempts to answer these type of questions. Once we have formulated these two critical hypotheses, we can move on to the first step of the model, which is the Build step.

As an example, Zappos, an online shoe and clothing store, was founded by Nick Swinmurn. Swinmurn started the process by testing a simple value hypothesis. Would people be willing to buy shoes online? He took photographs of shoes in stores, and displayed the pictures on a simple website.

When people started buying the shoes online, he realized that his hypothesis was valid. And sure, he may have started with a manual, labor-intensive process, but it was quick, cheap, and easy to test. All of this was to validate his hypothesis. Amazon later acquired Zappos in an all-stock deal worth around $1.2 billion.

Swinmurn's story shows the value of developing a fast, cheap experiment to test a hypothesis. He built a minimum viable product, and this MVP helped him start learning about any potential opportunity, and growth, as quickly as possible. So unlike in typical product development, the aim isn't for product perfection. It's to test a hypothesis.

When it comes to building a product, it's human nature to overthink it and want perfection. Ries states that the Build step is where we tend to waste most of our time.

Three Ways to Develop Time and Cost Efficient MVPs

Before building a product, it can be a good idea first to make a video that only simulates the product. A famous example of this is the file synching software Dropbox. In 2007, founder Drew Houston, built an early prototype, but it wasn't ready to handle mass numbers. Before putting in more effort, he tested whether people wanted his product. He recorded a video that demonstrated the main features of the prototype. The sign-ups for his product went from 5000 to 75000 users overnight. This response proved to him that people needed a syncing file service, and Dropbox was the solution.

Next up, is the concierge MVP. This approach is to work directly with customers to solve a specific problem manually. This approach may require a lot of time, but it's an excellent way to test if there's an audience for your product. Concierge MVPs generally try to solve the problems of early adopters. Running before you can walk is a crucial thing to remember with this type of MVP. Focus on a slower process towards optimization, to build a steady customer base.

Finally, the Wizard of Oz MVP is where you give the illusion that you have a tech-savvy solution, but in reality, you're operating manually behind the scenes. Does that sound familiar? Swinmurn used this approach for Zappos.

The point of these three examples is to show that an MVP isn't an excuse to forgo quality. If we build something that doesn't accurately represent our product or service, we'll infer the wrong conclusion. We have to design an MVP that reliably tests our hypothesis. Crucially, we also have to be able to discern value from waste.

The Value of Split Testing and User Experience

Split testing is an experiment where you split your customers into two or more groups, and vary a set of variables between the groups. The variables can be quite straightforward. For example, on one version the button could be red, while on the other the button could be green. The point of the split testing experiment is to observe how the two customer groups respond. And then, using a valid metric, you can measure each version's impact, and decide which version offers more value.

But what makes a valid metric? In the next step in the loop, Ries argues that this is where we really start to learn what customers want. Metrics, according to Ries, help us learn what customers want. Not what they say they want, or what we think they want. His advice here is to avoid vanity metrics and choose actionable metrics, that genuinely show whether we're making progress.

As the term suggests, vanity metrics are flattering, but they don't measure any actual progress. So, while our Facebook advert might get lots of likes, it would be presumptuous to interpret this as a sign of success. Likes don't directly generate revenue. Furthermore, money raised from investors, the number of employees hired, or new features added, don't necessarily reflect actual progress. Another vanity metric might be measuring the hours of work we put in, which may have little correlation to actual outcomes.

Useful, Actionable Metrics Help Us to Make Informed Decisions

Each startup needs to define its core metrics as well as how to track them. Core metrics give a realistic view of progress. Ries goes into enlightening specifics about how to measure customer engagement, growth, and finances. But one crucial metric, that can help all of us in creating successful startups, is called cohort analysis.

What's often taken for granted, is how people interact with our products. So, don't look at global metrics like total revenues, or the total number of users. Ries suggests segmenting customers into cohorts. Customer cohorts are different groups with shared characteristics. This method makes it a lot easier to define customers and analyze how each group uses a product. We get, what Ries calls, independent report cards, that offer us a system to analyze and compare over time, and understand what's working and what's not.

Take Time to Reflect and Learn

Ries says that we shouldn't underestimate the importance of taking the time to reflect on the data, and to learn from it. It's only after this crucial step when we can then determine whether to pivot or persevere.

The decision to persevere, or to pivot, hinges a lot on our metrics. Persevering means continuing through the build-measure-learn loop, but pivoting involves a lot more critical thinking.

A pivot may mean a complete change in strategy. The question is, how do we know when to pivot? The solution that Ries proposes is to have regular pivot-or-persevere meetings involving both the leadership, and the product development team. It's important to remember that pivoting, doesn't mean failure.

Ries details various interesting pivots that you could take.

You could investigate whether a Zoom-In pivot, or a Zoom-Out pivot, could work for you. A Zoom-In Pivot, is when we find out what specific features of a product the customers like. We may then decide to zoom in and focus exclusively on this feature, to the exclusion of all else. Alternatively, a Zoom-Out Pivot is when the elements aren't enough on their own to meet the customers' needs, so we need to add more.

A customer segment pivot is when the initial group of customers is perhaps not as intrigued as we anticipated. But, maybe another group is very enthusiastic. Using this data it's easier to change the target customer focus.

Finally, a value capture pivot is when we may need to focus on revenue through advertising instead of charging for the actual product.

In Conclusion

The Lean Startup is a book that anyone wanting to start a business should read and engage with. Ries provides an easy to follow and highly accessible methodology that brings ideas to life, and optimizes the chances of success in the marketplace.

In a world where business can be intimidating, Ries makes entrepreneurship accessible to a whole new generation of founders, who are hungry to build the next big thing. According to Ries, success stories are not a consequence of good genes or being in the right place at the right time. Rather, success comes through following the right processes, being self-reflexive, and knowing that it can actually be taught.