The Lean Startup by Eric Ries
We were much more likely to run experiments on our customers than we were to cater to their whims.
The first problem is the allure of a good plan, a solid strategy, and thorough market research.
Build-Measure-Learn feedback loop.
For every success there are far too many failures:
The goal of a start-up is to figure out the right thing to build—the thing customers want and will pay for—as quickly as possible.
Instead of making complex plans that are based on a lot of assumptions, you can make constant adjustments with a steering wheel called the Build-Measure-Learn feedback loop. Through this process of steering, we can learn when and if it is time to make a sharp turn called a pivot or whether we should persevere along our current path.
A start-up is a human institution designed to create a new product or service under conditions of extreme uncertainty.
To open up a new business that is an exact clone of an existing business all the way down to the business model, pricing, target customer, and product may be an attractive economic investment, but it is not a start-up because its success depends only on execution—so much so that this success can be modelled with high accuracy. (This is why so many small businesses can be financed with simple bank loans; the level of risk and uncertainty is understood well enough that a loan officer can assess its prospects.)
Metcalfe’s law: the value of a network as a whole is proportional to the square of the number of participants.
Lean thinking defines value as providing benefit to the customer; anything else is waste.
Most of the time customers do not know what they want in advance.
The effort that is not absolutely necessary for learning what customers want can be eliminated. I call this validated learning because it is always demonstrated by positive improvements in the start-up’s core metrics.
We adopted the view that our job was to find a synthesis between our vision and what customers would accept; it was not to capitulate to what customers thought they wanted or to tell customers what they ought to want.
Zero invites imagination, but small numbers invite questions about whether large numbers will ever materialize.
Because we would have squandered precious resources on theatrics instead of progress, we would have been in real trouble.
Not every kind of customer will accept a low-quality prototype,
This is one of the most important lessons of the scientific method: if you cannot fail, you cannot learn.
It had more accurate data about customer demand because it was observing real customer behaviour, not asking hypothetical questions.
It put itself in a position to interact with real customers and learn about their needs. For example, the business plan might call for discounted pricing, but how are customer perceptions of the product affected by the discounting strategy?
It allowed itself to be surprised when customers behaved in unexpected ways, revealing information Zappos might not have known to ask about.
For Long-Term Change, experiment Immediately.
The value hypothesis tests whether a product or service really delivers value to customers once they are using it.
The point is not to find the average customer but to find early adopters: the customers who feel the need for the product most acutely. Those customers tend to be more forgiving of mistakes and are especially eager to give feedback.
If the numbers from such early experiments don’t look promising, there is clearly a problem with the strategy. That doesn’t mean it’s time to give up; on the contrary, it means it’s time to get some immediate qualitative feedback about how to improve the program. Here’s where this kind of experimentation has an advantage over traditional market research. We don’t have to commission a survey or find new people to interview. We already have a cohort of people to talk to as well as knowledge about their actual behaviour: the participants in the initial experiment.
Do consumers recognize that they have the problem you are trying to solve? If there was a solution, would they buy it? Would they buy it from us? Can we build a solution for that problem?”
The initial product—flaws and all—confirmed that users did have the desire to create event albums, which was extremely valuable information. Where customers complained about missing features, this suggested that the team was on the right track.
“Success is not delivering a feature; success is learning how to solve the customer’s problem.”
Once clear on these leap-of-faith assumptions, the first step is to enter the Build phase as quickly as possible with a minimum viable product (MVP). The MVP is that version of the product that enables a full turn of the Build-Measure-Learn loop with a minimum amount of effort and the least amount of development time. The minimum viable product lacks many features that may prove essential later on.
When we enter the Measure phase, the biggest challenge will be determining whether the product development efforts are leading to real progress. Remember, if we’re building something that nobody wants, it doesn’t much matter if we’re doing it on time and on budget.
For start-ups, the role of strategy is to help figure out the right questions to ask.
STRATEGY IS BASED ON ASSUMPTIONS
What differentiates the success stories from the failures is that the successful entrepreneurs had the foresight, the ability, and the tools to discover which parts of their plans were working brilliantly and which were misguided and adapt their strategies accordingly.
Whether I was in manufacturing, product development, sales, distribution, or public affairs. You cannot be sure you really understand any part of any business problem unless you go and see for yourself first-hand. It is unacceptable to take anything for granted or to rely on the reports of others.
It is common to think of selling to consumers as easier than selling to enterprises because customers lack the complexity of multiple departments and different people playing different roles in the purchasing process.
Those early conversations did not delve into the product features of a proposed solution; that attempt would have been foolish.
The goal of such early contact with customers is not to gain definitive answers. Instead, it is to clarify at a basic, coarse level that we understand our potential customer and what problems they have.
Unfortunately, because customers don’t really know what they want, it’s easy for these entrepreneurs to delude themselves that they are on the right path.
The problem with most entrepreneurs’ plans is generally not that they don’t follow sound strategic principles but that the facts upon which they are based are wrong.
Minimum viable product (MVP) helps entrepreneurs start the process of learning as quickly as possible. It is not necessarily the smallest product imaginable, though; it is simply the fastest way to get through the Build-Measure-Learn feedback loop with the minimum amount of effort.
Unlike a prototype or concept test, an MVP is designed not just to answer product design or technical questions. Its goal is to test fundamental business hypotheses.
The gross numbers were small because we were selling the product to visionary early customers called early adopters. Before new products can be sold successfully to the mass market, they have to be sold to early adopters. These people are a special breed of customer. They accept—in fact prefer—an 80 percent solution; you don’t need a perfect solution to capture their interest.
Early adopters use their imagination to fill in what a product is missing. They prefer that state of affairs, because what they care about above all is being the first to use or adopt a new product or technology.
Early adopters are suspicious of something that is too polished: if it’s ready for everyone to adopt, how much advantage can one get by being early?
When in doubt, simplify.
A critical question to consider is whether customers will in fact sign up for the free trial given a certain number of promised features (the value hypothesis).
How many features do we really need to include to appeal to early adopters? Every extra feature is a form of waste, and if we delay the test for these extra features, it comes with a tremendous potential cost in terms of learning and cycle time.
The lesson of the MVP is that any additional work beyond what was required to start learning is waste, no matter how important it might have seemed at the time.
But along the way, their product development team was always focused on scaling something that was working rather than trying to invent something that might work in the future. As a result, their development efforts involved far less waste than is typical for a venture of this kind.
The only way to know is to have tested the growth model systematically with real customers.
In a Wizard of Oz test, customers believe they are interacting with the actual product, but behind the scenes human beings are doing the work. Like the concierge MVP, this approach is incredibly inefficient.
If we do not know who the customer is, we do not know what quality is.
But we must always ask: what if they don’t care about design in the same way we do?
As you consider building your own minimum viable product, let this simple rule suffice remove any feature, process, or effort that does not contribute directly to the learning you seek.
Their challenge lies in prioritization and execution, and it is those challenges that give a start-up hope of surviving.
A head start is rarely large enough to matter, and time spent in stealth mode—away from customers—is unlikely to provide a head start. The only way to win is to learn faster than anyone else.
In addition, a long-term reputation is only at risk when companies engage in vocal launch activities such as PR and building hype.
Start-ups have the advantage of being obscure, having a pathetically small number of customers, and not having much exposure.
The rate of growth depends primarily on three things: the profitability of each customer, the cost of acquiring new customers, and the repeat purchase rate of existing customers. The higher these values are, the faster the company will grow and the more profitable it will be.
Use a minimum viable product to establish real data on where the company is right now. Without a clear-eyed picture of your current status—no matter how far from the goal you may be—you cannot begin to track your progress.
Second, start-ups must attempt to tune the engine from the baseline toward the ideal. This may take many attempts. After the start-up has made all the micro changes and product optimizations it can to move its baseline toward the ideal, the company reaches a decision point. That is the third step: pivot or persevere.
When good results are not forthcoming, business leaders assume that any discrepancy between what was planned and what was built is the cause and try to specify the next iteration in greater detail. As the specifications get more detailed, the planning process slows down, batch size increases, and feedback is delayed.
That which optimizes one part of the system necessarily undermines the system as a whole.
If you wanted to test a catalog design, you could send a new version of it to 50 percent of the customers and send the old standard catalog to the other 50 percent. To assure a scientific result, both catalogs would contain identical products; the only difference would be the changes to the design. To figure out if the new design was effective, all you would have to do was keep track of the sales figures for both groups of customers. (This technique is sometimes called A/B testing after the practice of assigning letter names to each variation.)
They were confident in this feature because lazy registration is considered one of the design best practices for online services. In this system, customers do not have to register for the service up front. Instead, they immediately begin using the service and are asked to register only after they have had a chance to experience the service’s benefit.
Companies that cannot bring themselves to pivot to a new direction on the basis of feedback from the marketplace can get stuck in the land of the living dead, neither growing enough nor dying, consuming resources and commitment from employees and other stakeholders but not moving ahead.
The more money, time, and creative energy that has been sunk into an idea, the harder it is to pivot.
Failure is a prerequisite to learning.
Pivot requires that we keep one foot rooted in what we’ve learned so far, while making a fundamental change in strategy in order to seek even greater validated learning.
Seasoned entrepreneurs often speak of the runway that their start-up has left: the amount of time remaining in which a start-up must either achieve lift-off or fail. This usually is defined as the remaining cash in the bank divided by the monthly burn rate, or net drain on that account balance.
Second, when an entrepreneur has an unclear hypothesis, it’s almost impossible to experience complete failure, and without failure there is usually no impetus to embark on the radical change a pivot requires.
More terrifying is the thought that the vision might be deemed wrong without having been given a real chance to prove itself.
We’ve discussed the tell-tale signs of the need to pivot: the decreasing effectiveness of product experiments and the general feeling that product development should be more productive.
Recommend that every start-up have a regular “pivot or persevere” meeting.
Each pivot or persevere meeting requires the participation of both the product development and business leadership teams.
This is also common with pivots; it is not necessary to throw out everything that came before and start over. Instead, it’s about repurposing what has been built and what has been learned to find a more positive direction.
Remember that the rationale for building low-quality MVP is that developing any features beyond what early adopters require is a form of waste.
Mainstream customers have different requirements and are much more demanding.
Mainstream customers are less forgiving of an early product.
Zoom-in Pivot In this case, what previously was considered a single feature in a product becomes the whole product.
Zoom-out PivotIn the reverse situation, sometimes a single feature is insufficient to support a whole product. In this type of pivot, what was considered the whole product becomes a single feature of a much larger product.
Customer Segment Pivot In this pivot, the company realizes that the product it is building solves a real problem for real customers but that they are not the type of customers it originally planned to serve. In other words, the product hypothesis is partially confirmed, solving the right problem, but for a different customer than originally anticipated.
Customer Need Pivot As a result of getting to know customers extremely well, it sometimes becomes clear that the problem we’re trying to solve for them is not very important. However, because of this customer intimacy, we often discover other related problems that are important and can be solved by our team.
Platform Pivot A platform pivot refers to a change from an application to a platform or vice versa. Most commonly, start-ups that aspire to create a new platform begin life by selling a single application, the so-called killer app, for their platform. Only later does the platform emerge as a vehicle for third parties to leverage as a way to create their own related products. However, this order is not always set in stone, and some companies have to execute this pivot multiple times.
Even after a company achieves initial success, it must continue to pivot.
How often should you release a product? Is there a reason to release weekly rather than daily or quarterly or annually? Product releases incur overhead, and so from an efficiency point of view, releasing often leaves less time to devote to building the product. However, waiting too long to release can lead to the ultimate waste: making something that nobody wants.
The one envelope at a time approach is called “single-piece flow” in lean manufacturing. It works because of the surprising power of small batches.
When we do work that proceeds in stages, the “batch size” refers to how much work moves from one stage to the next at a time.
The biggest advantage of working in small batches is that quality problems can be identified much sooner.
What can be built out of software can be modified much faster than a physical or mechanical device can.
Lean production solves the problem of stockouts with a technique called pull. When you bring a car into the dealership for repair, one blue 2011 Camry bumper gets used. This creates a “hole” in the dealer’s inventory, which automatically causes a signal to be sent to a local restocking facility called the Toyota Parts Distribution Center (PDC). The PDC sends the dealer a new bumper, which creates another hole in inventory. This sends a similar signal to a regional warehouse called the Toyota Parts Redistribution Center (PRC), where all parts suppliers ship their products. That warehouse signals the factory where the bumpers are made to produce one more bumper, which is manufactured and shipped to the PRC. The ideal goal is to achieve small batches all the way down to single-piece flow along the entire supply chain. Each step in the line pulls the parts it needs from the previous step. This is the famous Toyota just-in-time production method.
Work-in-progress (WIP) inventory
As soon as we formulate a hypothesis that we want to test, the product development team should be engineered to design and run this experiment as quickly as possible, using the smallest batch size that will get the job done.
Sustainable growth is characterized by one simple rule: New customers come from the actions of past customers.
There are four primary ways past customers drive sustainable growth:
1. Word of mouth. Embedded in most products is a natural level of growth that is caused by satisfied customers’ enthusiasm for the product.
2. As a side effect of product usage. Fashion or status, such as luxury goods products, drive awareness of themselves whenever they are used. When you see someone dressed in the latest clothes or driving a certain car, you may be influenced to buy that product. This is also true of so-called viral products such as Facebook and paypal. When a customer sends money to a friend using paypal, the friend is exposed automatically to the paypal product.
3. Through funded advertising. Most businesses employ advertising to entice new customers to use their products. For this to be a source of sustainable growth, the advertising must be paid for out of revenue, not one-time sources such as investment capital. As long as the cost of acquiring a new customer (the so-called marginal cost) is less than the revenue that customer generates (the marginal revenue), the excess (the marginal profit) can be used to acquire more customers. The more marginal profit, the faster the growth.
4. Through repeat purchase or use. Some products are designed to be purchased repeatedly either through a subscription plan (a cable company) or through voluntary repurchases (groceries or lightbulbs). By contrast, many products and services are intentionally designed as one-time events, such as wedding planning.
The Sticky Engine of Growth. The rules that govern the sticky engine of growth are pretty simple: if the rate of new customer acquisition exceeds the churn rate, the product will grow. The speed of growth is determined by what I call the rate of compounding, which is simply the natural growth rate minus the churn rate.
The Viral Engine of Growth. Customers are not intentionally acting as evangelists; they are not necessarily trying to spread the word about the product. Growth happens automatically as a side effect of customers using the product.
Wealthy consumers cost more to reach because they tend to become more profitable customers.
Every new engineer would be assigned a mentor, who would help the new employee work through a curriculum of systems, concepts, and techniques he or she would need to become productive
The performance of the mentor and mentee were linked, so the mentors took this education seriously.
Toyota proverb, “Stop production so that production never has to stop.”
The core idea of Five Whys is to tie investments directly to the prevention of the most problematic symptoms. When confronted with a problem, have you ever stopped and asked why five times? It is difficult to do even though it sounds easy. For example, suppose a machine stopped functioning: Why did the machine stop? (There was an overload and the fuse blew.) Why was there an overload? (The bearing was not sufficiently lubricated.) Why was it not lubricated sufficiently? (The lubrication pump was not pumping sufficiently.) Why was it not pumping sufficiently? (The shaft of the pump was worn and rattling.) Why was the shaft worn out? (There was no strainer attached and metal scrap got in.) Repeating “why” five times, like this, can help uncover the root problem and correct it. If this procedure were not carried through, one might simply replace the fuse or the pump shaft. In that case, the problem would recur within a few months. The Toyota production system has been built on the practice and evolution of this scientific approach. By asking and answering “why” five times, we can get to the real cause of the problem, which is often hidden behind more obvious symptoms.
I recommend several tactics for escaping the Five Blames. The first is to make sure that everyone affected by the problem is in the room during the analysis of the root cause. The meeting should include anyone who discovered or diagnosed the problem, including customer service representatives who fielded the calls, if possible. It should include anyone who tried to fix the symptom as well as anyone who worked on the subsystems or features involved. If the problem was escalated to senior management, the decision makers who were involved in the escalation should be present as well. This may make for a crowded room, but it’s essential. In my experience, whoever is left out of the discussion ends up being the target for blame.
When blame inevitably arises, the most senior people in the room should repeat this mantra: if a mistake happens, shame on us for making it so easy to make that mistake.
“If our production process is so fragile that you can break it on your very first day of work, shame on us for making it so easy to do so.” If they did manage to break it, we immediately would have them lead the effort to fix the problem as well as the effort to prevent the next person from repeating their mistake.
Be tolerant of all mistakes the first time. Never allow the same mistake to be made twice. The first rule encourages people to get used to being compassionate about mistakes, especially the mistakes of others. Remember, most mistakes are caused by flawed systems, not bad people. The second rule gets the team started making proportional investments in prevention.
You will need to be prepared for the fact that Five Whys is going to turn up unpleasant facts about your organization, especially at the beginning.
When the stakes are high, the Five Whys can devolve into the Five Blames quickly. It’s better to give the team a chance to learn how to do the process first and then expand into higher-stakes areas later.
If there are already too many complaints, pick a subset on which you want to focus.
To introduce Five Whys to an organization, it is necessary to hold Five Whys sessions as new problems come up. Since baggage issues are endemic, they naturally come up as part of the Five Whys analysis and you can take that opportunity to fix them incrementally. If they don’t come up organically, maybe they’re not as big as they seem. Everyone who is connected to a problem needs to be at the Five Whys session. Many organizations face the temptation to save time by sparing busy people from the root cause analysis. This is a false economy,
At the beginning of each Five Whys session, take a few minutes to explain what the process is for and how it works for the benefit of those who are new to it. If possible, use an example of a successful Five Whys session from the past.
Start-ups are different: too much budget is as harmful as too little.
Thus, start-ups are both easier and more demanding to run than traditional divisions: they require much less capital overall, but that capital must be absolutely secure from tampering.
“Financial incentives aside, I always felt that because my name was on the door, I had more to lose and more to prove than someone else. That sense of ownership is not insignificant.”
Taylor wrote: “In the past, the man has been first; in the future, the system must be first.”