Below are excerpts and a summary taken from the book.
Summary and Key Takeaways of The Lean Startup by Eric Ries
PART THREE: ACCELERATE
Start Your Engines
Most of the decisions startups face are not clear-cut. How much time should companies invest in infrastructure and planning early on in anticipation of success? What should employees spend their days doing? How do we hold people accountable for learning at an organizational level?
However, the critical first question of any lean transformation is: which activities create value and which are a form of waste? Once you understand this distinction, you can begin using lean techniques to drive out waste and increase the efficiency of the value-creating activities. For these techniques to be used in a startup, they must be adapted to the unique circumstances of entrepreneurship. The value in a startup is not the creation of stuff, but rather validated learning about how to build a sustainable business. What products do customers really want? How will our business grow? Who is our customer? Which customers should we listen to and which should we ignore? These are the questions that need answering as quickly as possible to maximize a startup’s chances of success. That is what creates value for a startup.
“Single-piece flow” is an approach in lean manufacturing when we attend to one product at a time, working on it start to finish. It works because of the surprising power of small batches. It is proven to be more efficient even if it appears to be counterintuitive since we simply don’t account for the extra time required to sort and stack. It seems more efficient to repeat the same task over and over but unfortunately, in process-oriented work like this, individual performance is not nearly as important as the overall performance of the system.
And even if the amount of time that each process took was exactly the same, the small batch production approach is still superior because it allows you to identify faulty parts or mismatching units almost immediately (instead of spending time on preparing all the parts only to find out they don’t go together). It is also more flexible. Instead of producing a large quantity at once, it produces one every few seconds. So in case customers decide they don’t want the product anymore, small-batch approach would allow the company to find this out sooner.
This approach is exactly what allowed Toyota to compete with many American automakers during post-WWII. Toyota perfected the process of rapid creation of many small batches and was able to produce a much greater diversity of products. Over time, that capability allowed Toyota to move successfully into larger and larger markets until it became the world’s largest automaker in 2008.
The biggest advantage of working in small batches is that quality problems can be identified much sooner. This is the origin of Toyota’s famous andon cord, which allows any worker to ask for help as soon as they notice any problem, such as a defect in a physical part, stopping the entire production line if it cannot be corrected immediately. This is another counterintuitive practice. The andon cord can interrupt the careful flow as the line is halted repeatedly. However, the benefits of finding and fixing problems faster outweigh this cost. The process of continuously driving out defects has been a win-win for Toyota and its customers.
Small Batches in Entrepreneurship
The theory that is the foundation of Toyota’s success can be used to dramatically improve the speed at which startups find validated learning. The goal of the Lean Startup is not to produce more stuff efficiently. It is to — as quickly as possible — learn how to build a sustainable business.
Much like in the car manufacturing process described above, finding out you’re building a product that a customer doesn’t want is better sooner than later.
Small Batches at IMVU
IMVU team applied these lessons from manufacturing to the way they work. They attempted to design, develop, and ship their new features one at a time, taking advantage of the power of small batches like so:
-engineers and designers work side by side on one feature at a time, instead of in separate departments
-a new feature was immediately released as soon as it was ready to be tested with customers (it would go live on the website for a relatively small number of people)
-the team immediately assessed the impact of their work, evaluated its effect on customers, and decided what to do next
On average, IMVU would make about fifty changes to its product every single day.
They key to being able to operate this quickly is to check for defects immediately. So the team had an extensive set of automated tests that assured that after every change the product still worked as designed (similar to the andon cord). The team even called this the product’s immune system because those automatic protections went beyond checking that the product behaved as expected. Once a problem is detected, a continuous deployment process sets into place:
- The defective change is removed immediately and automatically
- Everyone on the relevant team is notified of the problem
- The team is blocked from introducing any further changes, preventing the problem from being compounded by future mistakes…
- …until the root cause of the problem is found and fixed.
From the standpoint of individual efficiency, of a product designer, for example, producing designs one by one by yourself and then passing them onto the engineering team (in batches) makes sense. It promotes skill building, makes it easier to hold individuals accountable, and allows experts to work without interruption. Unfortunately, reality seldom works out that way.
Consider a hypothetical example: after passing thirty design drawings to engineering and they have questions about the drawings? Or what if something goes wrong when an engineer attempts to use the drawings? These problems turned into interruptions for the designer and are interfering with the next large batch he or she is supposed to be working on.
It is also very easy to fall into the large batch spiral. Moving a batch forward often results in additional work, rework delays, and interruptions so everyone has an incentive to do work in ever-larger batches, trying to minimise this overhead.
Pull, Don’t Push
In traditional mass production, the way to avoid stockouts — not having the product the customer wants — is to keep a large inventory of spares just in case. But this can be costly if you have many variations of products (such as Toyota car bumpers for each model). 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 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 product one more bumper, which is manufactured and shipped to the RPC.
The ideal goal is to achieve small batches all the way down to single-piece flow along the entire supply chain. This is the famous Toyota just-in-time production method.
This not only shrinks the size of the warehouse but also dramatically recudes the amount of just-in-case inventory.
It is hard to apply this to startup world because the work is intangible. So the right way to think about this is that the product development process is responding to pull requests in the form of experiments that need to be run.
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. Remember that although we write the feedback loop as Build-Measure-Learn because the activities happen in that order, our planning really works in the reverse order: we figure out what we need to learn and then work backwards to see what product will work as an experiment to get that learning. Thus, it is not the customer, but rather our hypothesis about the customer, that pulls work from product development and other functions. Any other work is waste.
Hypothesis Pull in Clean Tech
The Lean Startup works only if we are able to build an organization as adaptable and fast as the challenges it faces. This requires tackling the human challenges inherent in this new way of working.
A common problem many startups face is hitting an early growth flatline after validating and invalidating many hypotheses, executing against the product roadmap successfully, and getting a healthy mix of positive feedback. So how do you jump start your growth? Invest in more advertising or marketing? Focus on product quality or new features? Or try to improve conversion rates and pricing?
Where Does Growth Come From?
The engine of growth is the mechanism that startups use to achieve sustainable growth (not all the one-time activities that generate a surge of customers but have no long-term impact), that is characterized by one simple rule: new customers come from the actions of past customers, in one of the four ways.
- Word of mouth. This is caused by satisfied customers’ enthusiasm and urge to convince family and friends to also use the product.
- As a side effect of product usage. Luxury goods drive awareness of themselves so may compel others to buy that same product. Similarly with viral products, such as Facebook and PayPal where the both parties must have the product in order to use it.
- Through funded advertising. For this to be a source of sustainable growth, it has to be paid for out of revenue, not one-time sources such as investment capital. And the cost of acquiring a new customer (marginal cost) has to be less than the revenue that customer generates (marginal revenue).
- Through repeat purchase or use. Many products are subscription based or voluntarily repurchased (groceries, light bulbs) in contrast with intentional one-time services or events (weddings).
The faster the growth power feedback loop turns, the faster the company will grow.
The Three Engines of Growth
One of the most expensive forms of potential waste for a startup is spending time arguing about how to prioritize new development once it has a product on the market. Engines of growth are designed to give startups a relatively small set of metrics on which to focus their engines. As one of Ries’ mentors Shawn Carolan put it, “Startups don’t starve; they drown.”
There are millions of new ideas on how to make a certain product better. But they are mere optimizations. The engines of growth framework help startups stay focused on the metrics that matter.
The Sticky Engine of Growth
There are businesses that rely on high customer retention rate. This is based on the expectation that once you start using their product, you will continue to do so (e.g. mobile service provider). Then there are businesses where customer switching to a competitor’s product does not signal of dissatisfaction of the product but a fluctuation in taste (pepsi vs coke).
Therefore, companies using the sticky engine of growth track their attrition rate or churn rate very carefully. Churn rate is the fraction of customers in any period who fail to remain engaged with the company’s product. If the rate of new customer acquisition exceeds the churn rate, the product will grow. The speed of growing is determined by the rate of compounding or the natural growth rate minus the churn rate. Like a bank account that earns compounding interest, having a high rate of compounding will lead to extremely rapid growth — without advertising, viral growth, or publicity stunts.
Many would find that their compounding growth rate is almost zero, a typical number for companies struggling with growth. Once a company realises that there are plenty of new customers coming in the door, it focuses on the existing customers. Such companies will find growth by improving listings, sending direct messages about limited-time special offers, etc. and thus improving customer retention.
The Paid Engine of Growth
To predict how fast a company will grow, you need to know how much it costs to sing up a new customer. A company should always know how much percent of your revenue is available to reinvest in new customer acquisition. If a company wants to increase its rate of growth, it can do so in one of two ways: increase the revenue from each customer or drive down the cost of acquiring a new customer. That’s the paid engine of growth at work.
The paid engine of growth is also powered by a feedback loop called customer lifetime value or LTV. This is the amount each customer pays for a product over his or her “lifetime” as a customer. This revenue can be invested in growth by buying advertising.
Keep in mind that the outbound sales force and any advertising used for foot traffic are all costs that should also be factored into the cost per acquisition.
Over time, any source of customer acquisition will tend to have its CPA bid up by competition. Thus, the ability to grow in the long term by using the paid engine requires a differentiated ability to monetize a certain set of customers. In IMVU’s case, they allowed their non-lucrative customers to pay even though they didn’t have a credit card (send cash in mail or using mobile phones). They, therefore, could afford to pay more to acquire those customers than their competitors would.
A Technical Caveat
Eric Ries strongly recommends focusing on one engine at a time because the operations expertise requires to model all effects simultaneously is quite complicated. Only after pursuing one engine thoroughly should a startup consider a pivot to one of the others.
Engines Of Growth Determine Product/Market Fit
“In a great market — a market with lots of real potential customers — the market pulls the product out of the startup,” said Marc Andreessen, legendary entrepreneur, investor, and one of the fathers of the World Wide Web. When a startup finds its fit in a large market, there is no room for doubt. It’s the Ford’s Model T, Facebook, Lotus.
Another great tip, if you have to ask if you achieved product/market fit, you’re not there yet. The author argues that the concept of the engine of growth can put the idea of product/market fit on a more rigorous footing. Since each engine of growth can be defined quantitatively, each one also has a unique set of metrics that can be used to evaluate whether a startup is on the verge of achieving product/market fit. For example, a startup with a viral coefficient of 0.9 is on the verge of success.
A startup can evaluate whether it is getting closer to product/market fit by looking at the direction and degree of progress (and not raw numbers).
When Engines Run Out
Every engine will eventually run out as it is tied to an exhaustive set number of customers. It can take a long or short time. Keep in mind that transitioning to mainstream customers will require tremendous additional work. Don’t be fooled by the growing numbers and think that it’s because your product is getting better while having no impact on customer behavior. This growth is all coming from an engine of growth that is working and not from improvements driven by product development. Thus, when growth suddenly slows, it provokes a crisis.
Having no system at all is not an option. There are so many ways for a startup to fail. Many take the split-the-difference approach, as in “engage in a little planning, but not too much.” The problem with this is that it’s hard to give any rationale for why we should anticipate one particular problem and ignore the other.
Building an Adaptive Organization
Should a startup invest in a training program for new employees? The answer is absolutely yes. It requires huge effort to standardize the work process and prepare a curriculum of the concepts that new employees should learn. At IMVU, Ries assigned each new hire to a mentor and linked the performance, so it is taken seriously by both. The funny thing is that it was never Ries’ goal to build a great training program. This is what is called adaptive organization, one that automatically adjusts its process and performance to current conditions.
Can You Go Too Fast?
Focusing on just speed can be destructive for startups. To work, startups require built-in speed regulators that help teams find their optimal pace of work.
“Stop production so that production never has to stop.” They key to this andon cord philosophy is that it forces you to investigate the issue. Defects cause a lot of rework, low morale, and customer complaints, all of which slow progress and eat away valuable resources.
This is one of the hardest concepts of the Lean Startup to grasp. On the one hand, the logic of minimum viable product says you should get it into consumer’s hands as soon as possible and any work beyond that is a waste. On the other hand, any shortcuts taken in product quality, design, or infrastructure today may wind up slowing a company down tomorrow.
Once your learning allows you to build products that customers do want, you start to face slowdowns. The more features you add, the harder it becomes because of the risk that a new feature would interfere with an existing feature. That’s why you need to achieve scale and quality in a just-in-time fashion.
The Wisdom of the Five Whys
To accelerate, Lean Startups need a process that provides a natural feedback loop. When you’re going too fast, you cause more problems. Five Whys allows you to make incremental investments that will prevent most problematic symptoms and thus evolve a startup’s processes gradually. Asking “Why?” five times will let you understand the root cause.
At the room of every seemingly technical problem is a human problem. Taiichi Ohno, the developer of this technique and the father of the Toyota Production System, provides the following example:
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 no 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.)
If this procedure were not carried through, one might simply replace the fuse or the pump shaft. By doing this, you can get to the real cause of the problem, which is often hidden behind more obvious symptoms.
Make a Proportional Investment
This is how you build an adaptive organization: consistently make a proportional investment at each of the five levels of the hierarchy (the smaller the symptom, the smaller its investment).
If the outage is a minor glitch, it’s essential that we make only a minor investment fixing it. If, however, more and more problem occur because of the same reason (such as lack of training in new hires at IMVU), you might want to consider investing time in improving an engineering training program.
Automatic Speed Regulator
The Five Whys ties the rate of progress to learning, not just execution. Startup teams should go through the Five Whys whenever they encounter any kind of failure, including technical faults, failures to achieve business results or unexpected changes in customer behavior.
The Curse of the Five Blames
When the Five Whys approach goes awry, Ries calls it the Five Blames. Sometimes, frustrated managers teammates start pointing fingers at each other and using this as a means for venting their frustrations. In order to avoid this, make sure everyone affected by this problem is in the room including customer representatives who fielded the calls and anyone who tried to fix the symptoms as well as anyone who worked on the subsystems or features involved.
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.
For Five Whys to work properly, there are rules that must be followed.
- Be tolerant of all mistakes the first time. (they happen because of flawed systems, not bad people)
- Never allow the same mistake to be made twice. (make proportional investments in prevention)
Facing Unpleasant Truths
You will need to be prepared for the fact that Five Whys is going to turn up unpleasant facts about your organization. Under pressure, teams may feel that they don’t have time to waste on analyzing root causes even though it would give them more time in the long term. At all these junctures, it is essential that someone with sufficient authority be present to insist that the process be followed, that its recommendations be implemented, and to act as a referee if disagreements flare up.
Start Small, Be Specific
It is best to begin with a narrowly targeted class of symptoms. While it can be tempting to start with something large and important, it is also where the pressure is the greatest. For example, a customer complaint. If there are already too many complaints, pick a subset on which you want to focus, for example, every complaint involving a credit card transaction. Don’t pick a rule that is ambiguous. At first, keep the meetings short and pick a relatively simple change at each of the five levels of the inquiry.
Appoint a Five Whys Master
It is helpful to appoint a Five Whys master for each area in which the method is being used. This individual is the point person in terms of accountability and is the primary change agent who moderates, decides on which steps to take, as well as assigns follow-up work from that meeting. He or she also has to be senior enough to have the authority to do the above tasks.
As Lean Startups grow, they can use adaptive techniques to develop more complex processes without giving up their core advantage: speed through the Build-Measure-Learn feedback loop.
How to Nurture Disruptive Innovation
Successful innovation teams must be structured correctly in order to succeed. Startup teams require three structural attributes: scarce but secure resources, independent authority to develop their business, and a personal stake in the outcome.
-scarce but secure resources
Startups are different than established organizations in that too much budget is as harmful as too little; they are extremely sensitive to midcourse budgetary changes. Startups require much less capital overall, but that capital must be absolutely secure from tampering (it would be a fatal blow for a startup to lose 10 percent of its cash on hand suddenly).
-independent development authority
Startups need complete autonomy and thus have to be able to conceive and execute experiments without having to gain an excessive number of approvals. Startup teams should be completely cross-functional, that is, have full-time representation from every functional department in the company that will be involved in the creation of launch of their early products. Handoffs and approvals slow down the Build-Measure-Learn feedback loop.
-a personal stake in the outcome
Entrepreneurs need a personal stake in the outcome of their creations. And it doesn’t have to financial. The organization has to make it clear who the innovator is and make sure the innovator received credit for having brought the new product to live — if it is successful.
Creating A Platform For Experimentation
Next, it is important to focus on establishing the ground rules under which autonomous startup teams operate: how to protect the parent organization, how to hold entrepreneurial managers accountable, and how to reintegrate an innovation back into the parent organization if it is successful.
The Dangers of Hiding Innovation Inside the Black Box
The imperative to innovate is unrelenting. Without the ability to experiment in a more agile manner, this company eventually would suffer the fate of The Innovator’s Dilemma: ever-higher profits and margins year after year until the business suddenly collapsed.
Creating an Innovation Sandbox
The challenge here is to create a mechanism for empowering innovation teams out in the open. Ries suggests creating a sandbox for innovation that will contain the impact of the new innovation but not constrain the methods of the startup team as follows:
- Any team can create a true split-test experiment that affects only the sandboxed parts of the product or service or only certain customer segments or territories. However:
- One team must see the whole experiment through from end to end.
- No experiment can run longer than a specified amount of time.
- No experiment can affect more than a specified number of companies.
- Every experiment has to be evaluated on the basis of a single standard report to five to ten actionable metrics.
- Every team that works inside the sandbox and every product that is built must use the same metrics to evaluate success.
- Any team that creates an experiment must monitor the metrics and customer reactions while the experiment is in progress and abort it if something catastrophic happens.
At the beginning, the sandbox has to be quite small. Depending on the types of products the company makes, the size of the sandbox can be defined in different ways. For example, an online service might restrict it to certain pages of user flows. Similarly, a retail operation might restrict it to certain stores or geographic areas.
Unlike in a concept test or market test, customers in the sandbox are considered real and the innovation team is allowed to attempt to establish a long-term relationship with them.
True experiments are easy to classify as successes or failures because top-level metrics either move or they don’t. Either way, the team learns immediately whether its assumptions about how customers will behave are correct. By using the same metrics each time, the team builds literacy about those metrics across the company. Because the innovation team is reporting on its progress by using the system of innovation accounting, anyone who reads those reports is getting an implicit lesson in the power of actionable metrics. This effect is extremely powerful.
The sandbox also promotes rapid iteration. When people have a chance to see a project through from end to end and the work is done in small batches and delivers a clear verdict quickly, they benefit from the power of feedback. Thus, these teams tend to converge on optimal solutions rapidly even if they start out with really bad ideas.
Cultivating The Management Portfolio
There are major kinds of work that companies must manage. Scaling is the first one. As new mainstream customers are acquired and new markets are conquered, the product becomes part of the public face of the company, with important implications for PR, business development as well as copycats and imitators. This inevitable commoditization calls for certain procedures to become more routine and a different type of manager, one who excels in optimization. Company stock prices depend on this kind of predictable growth.
Another phase focuses on operating costs and legacy products. This is the domain of outsourcing, automation, and cost reduction. However, unlike the growth and optimization phase, investments in this area will not help the company achieve top-line growth. Managers of this suffer the fate of baseball umpires: get criticized when something goes wrong, unappreciated when things are going well.
Every new innovation competes for resources with established projects, and one of the scarcest resources is talent.
Entrepreneur Is a Job Title
The way out of this dilemma is to manage the four kinds of work differently, allowing strong cross-functional teams to develop around each area. All people should be allowed to find the kinds of jobs that suit them best.
Entrepreneurship should be considered a viable career path for innovators inside large organizations. After an entrepreneur has incubated a product in the innovation sandbox, it has to be reintegrated into the parent organization. A larger team eventually will be needed to grow it, commercialize it, and scale it.
Ideally, the sandbox will grow over time; that is, rather than move the team out of the sandbox and into company’s standard routines, there may be opportunities to enlarge the scope of the sandbox.
Working in the innovation sandbox is like developing startup muscles. At first, the team will be able to take only modest experiments. Over time, those teams are almost guaranteed to improve as long as they get constant feedback of small-batch development and actionable metrics and are held accountable to learning milestones. And will eventually need a new sandbox within which to play.
Becoming the Status Quo
This last transition is especially hard for innovators to accept: their transformation from radical outsiders to the embodiment of the status quo. It is very common to face these questions: how do we know that “your way” of building a company will work? What other companies are using it? Who has become rich and famous as a result? These questions are sensible. The titans of our industry are all working in a slower, more linear way. Why are we doing something different?
It is these questions that require the use of theory to answer. Those who look to adopt the Lean Startup as a defined steps or tactics will not succeed. In a startup situation, things constantly go wrong. When that happens, we face the age-old dilemma summarized by Deming: How do we know that the problem is due to special cause versus a systematic cause? If we’re in the middle of adopting a new way of working, the temptation will always be to blame the new system for the problems that arise. Sometimes that tendency is correct, sometimes not. Learning to tell the difference requires theory. You have to be able to predict the outcome of the changes you make to tell if the problems that result are really problems.
For example, changing the definition of productivity for a team from functional excellence to validated learning will cause problems. A programmer expects to be coding all day long. The constant interruption of meetings, explanations for endless numbers of bosses all act as a drag on efficiency. However, the goal of the Lean Startup is to work cross-functionally to achieve validated learning. Because it doesn’t matter how fast we can build or measure. What matters is how fast we can get through the entire loop.
There’s also a pattern to startups exhibit upon the switch: it feels worse before it feels better. Having the benefit of theory is the antidote to these challenges. If it is known that this loss of productivity is an inevitable part of the transition, it can be managed actively.
Ultimately, the Lean Startup is a framework, not a blueprint of steps to follow.
- Epilogue: Waste Not
In the twenty-first century, we face a set of problems where our productive capacity greatly exceeds our ability to know what to build. We have the capacity to build almost anything we can imagine. The big question of our time is not Can it be built? But Should it be built? This places us in an unusual historical moment: our future prosperity depends on the quality of our collective imaginations.
As a movement, the Lean Startup must avoid doctrines and rigid ideology. We must avoid the caricature that science means formula or lack of humanity at work. In fact, science is one of humanity’s most creative pursuits. I believe that applying it to entrepreneurship will unlock a vast storehouse of human potential.
What would an organization look like if all of its employees were armed with Lean Startup organizational superpower?
For one thing, everyone would insist that assumptions be stated explicitly and tested rigorously not as a stalling tactic or a form of make-work but out of a genuine desire to discover the truth that underlies every project’s vision.
We would not waste time on endless arguments between the defenders of quality and the cowboys of reckless advance; instead, we would recognize that speed and quality are allies in the pursuit of the customer’s long-term benefit. We would race to test our vision but not to abandon it.
We would respond to failures and setbacks with honesty and learning, not with recriminations and blame. More than that, we would shun the impulse to slow down, increase batch size, and indulge in the curse of prevention. Instead, we would achieve speed by bypassing the excess work that does not lead to learning. We would dedicate ourselves to the creation of new institutions with a long-term mission to build sustainable value and change the world for the better.
Most of all, we would stop wasting people’s time.
Compiled by: Aliya Serikpayeva