These are the best parts from the book Invent and Wander: the Collected Writings of Jeff Bezos. The book is a collection of the annual Amazon shareholder letters that Jeff Bezos has been sending out since 1997, and speeches he has given over time. It's a great source of business and management wisdom, some also applicable to daily life. The points on experimentation and decision making are especially relevant for data scientists. Enjoy!
Big winners pay for many failed experiments
To invent you have to experiment, and if you know in advance that it’s going to work, it’s not an experiment. Most large organizations embrace the idea of invention, but are not willing to suffer the string of failed experiments necessary to get there. Outsized returns often come from betting against conventional wisdom, and conventional wisdom is usually right. Given a ten percent chance of a 100 times payoff, you should take that bet every time. But you’re still going to be wrong nine times out of ten.
We all know that if you swing for the fences, you’re going to strike out a lot, but you’re also going to hit some home runs. The difference between baseball and business, however, is that baseball has a truncated outcome distribution. When you swing, no matter how well you connect with the ball, the most runs you can get is four. In business, every once in a while, when you step up to the plate, you can score 1,000 runs. This long-tailed distribution of returns is why it’s important to be bold. Big winners pay for so many experiments.
Many of the important decisions we make at Amazon can be made with data. There is a right answer or a wrong answer, a better answer or a worse answer, and math tells us which is which. These are our favorite kinds of decisions. Opening a new fulfillment center is an example. We use history from our existing fulfillment network to estimate seasonal peaks and to model alternatives for new capacity. We look at anticipated product mix, including product dimensions and weight, to decide how much space we need and whether we need a facility for smaller “sortable” items or for larger items that usually ship alone. To shorten delivery times and reduce outbound transportation costs, we analyze prospective locations based on proximity to customers, transportation hubs, and existing facilities. Quantitative analysis improves the customer’s experience and our cost structure. Similarly, most of our inventory purchase decisions can be numerically modeled and analyzed.
The above decisions require us to make some assumptions and judgments, but in such decisions, judgment and opinion come into play only as junior partners. The heavy lifting is done by the math. As you would expect, however, not all of our important decisions can be made in this enviable, math-based way. Sometimes we have little or no historical data to guide us and proactive experimentation is impossible, impractical.
As our shareholders know, we have made a decision to continuously and significantly lower prices for customers year after year as our efficiency and scale make it possible. This is an example of a very important decision that cannot be made in a math-based way. In fact, when we lower prices, we go against the math that we can do, which always says that the smart move is to raise prices. We have significant data related to price elasticity. With fair accuracy, we can predict that a price reduction of a certain percentage will result in an increase in units sold of a certain percentage. With rare exceptions, the volume increase in the short term is never enough to pay for the price decrease. However, our quantitative understanding of elasticity is short-term. We can estimate what a price reduction will do this week and this quarter. But we cannot numerically estimate the effect that consistently lowering prices will have on our business over five years or ten years or more. Our judgment is that relentlessly returning efficiency improvements and scale economies to customers in the form of lower prices creates a virtuous cycle that leads over the long term to a much larger dollar amount of free cash flow, and thereby to a much more valuable Amazon.
Type 1 and Type 2 decisions
Some decisions are consequential and irreversible or nearly irreversible – one-way doors – and these decisions must be made methodically, carefully, slowly, with great deliberation and consultation. If you walk through and don’t like what you see on the other side, you can’t get back to where you were before. We can call these Type 1 decisions. But most decisions aren’t like that – they are changeable, reversible – they’re two-way doors. If you’ve made a suboptimal Type 2 decision, you don’t have to live with the consequences for that long. You can reopen the door and go back through. Type 2 decisions can and should be made quickly by high judgment individuals or small groups.
As organizations get larger, there seems to be a tendency to use the heavy-weight Type 1 decision-making process on most decisions, including many Type 2 decisions. The end result of this is slowness, unthoughtful risk aversion, failure to experiment sufficiently, and consequently diminished invention. We’ll have to figure out how to fight that tendency.
High-Velocity decision making
Day 2 companies make high-quality decisions, but they make high-quality decisions slowly. To keep the energy and dynamism of Day 1, you have to somehow make high-quality, high-velocity decisions. Easy for start-ups and very challenging for large organizations. The senior team at Amazon is determined to keep our decision-making velocity high. Speed matters in business—plus a high-velocity decision-making environment is more fun too. We don’t know all the answers, but here are some thoughts.
First, never use a one-size-fits-all decision-making process. Many decisions are reversible, two-way doors. Those decisions can use a light-weight process. For those, so what if you’re wrong? I wrote about this in more detail in last year’s letter.
Second, most decisions should probably be made with somewhere around 70 percent of the information you wish you had. If you wait for 90 percent, in most cases, you’re probably being slow. Plus, either way, you need to be good at quickly recognizing and correcting bad decisions. If you’re good at course correcting, being wrong may be less costly than you think, whereas being slow is going to be expensive for sure.
Third, use the phrase “disagree and commit.” This phrase will save a lot of time. If you have conviction on a particular direction even though there’s no consensus, it’s helpful to say, “Look, I know we disagree on this, but will you gamble with me on it? Disagree and commit?” By the time you’re at this point, no one can know the answer for sure, and you’ll probably get a quick yes.
Metrics and measurements
We first measure ourselves in terms of the metrics most indicative of our market leadership: customer and revenue growth, the degree to which our customers continue to purchase from us on a repeat basis, and the strength of our brand. We have invested and will continue to invest aggressively to expand and leverage our customer base, brand, and infrastructure as we move to establish an enduring franchise.
Focus on the long term
Amazon will make bold rather than timid investment decisions where we see a sufficient probability of gaining market leadership advantages. Some of these investments will pay off, others will not, and we will have learned another valuable lesson in either case. When forced to choose between optimizing the appearance of our GAAP accounting and maximizing the present value of future cash flows, we’ll take the cash flows.
We will work hard to spend wisely and maintain our lean culture. We understand the importance of continually reinforcing a cost-conscious culture, particularly in a business incurring net losses. We will balance our focus on growth with emphasis on long-term profitability and capital management. At this stage, we choose to prioritize growth because we believe that scale is central to achieving the potential of our business model. We will continue to focus on hiring and retaining versatile and talented employees and continue to weight their compensation to stock options rather than cash. We know our success will be largely affected by our ability to attract and retain a motivated employee base, each of whom must think like, and therefore must actually be, an owner.
How to hire
Will you admire this person?If you think about the people you’ve admired in your life, they are probably people you’ve been able to learn from or take an example from. For myself, I’ve always tried hard to work only with people I admire, and I encourage folks here to be just as demanding. Life is definitely too short to do otherwise.
Will this person raise the average level of effectiveness of the group they’re entering? We want to fight entropy. The bar has to continuously go up. I ask people to visualize the company five years from now. At that point, each of us should look around and say, “The standards are so high now—boy, I’m glad I got in when I did!”
Along what dimension might this person be a superstar? Many people have unique skills, interests, and perspectives that enrich the work environment for all of us. It’s often something that’s not even related to their jobs.
Our pricing strategy does not attempt to maximize margin percentages, but instead seeks to drive maximum value for customers and thereby create a much larger bottom line—in the long term. For example, we’re targeting gross margins on our jewelry sales to be substantially lower than industry norms because we believe over time—customers figure these things out—this approach will produce more value for shareholders.
Missionaries and mercenaries
I’m always trying to figure one thing first and foremost: Is that person a missionary or mercenary? The mercenaries are trying to flip their stock. The missionaries love their product or their service and love their customers and are trying to build a great service.
By the way, the great paradox here is that it’s usually the missionaries who make more money.
“Working backward” from customer needs can be contrasted with a “skills-forward” approach where existing skills and competencies are used to drive business opportunities.
The skills-forward approach says, “We are really good at X. What else can we do with X?” That’s a useful and rewarding business approach. However, if used exclusively, the company employing it will never be driven to develop fresh skills. Eventually the existing skills will become outmoded.
Working backward from customer needs often demands that we acquire new competencies and exercise new muscles, never mind how uncomfortable and awkward-feeling those first steps might be. Kindle is a good example of our fundamental approach. More than four years ago, we began with a long-term vision: every book, ever printed, in any language, all available in less than sixty seconds. The customer experience we envisioned didn’t allow for any hard lines of demarcation between Kindle the device and Kindle the service—the two had to blend together seamlessly. Amazon had never designed or built a hardware device, but rather than change the vision to accommodate our then-existing skills, we hired a number of talented (and missionary!) hardware engineers and got started learning a new institutional skill, one that we needed to better serve readers in the future.
Customer focused vs competitor focused
Our energy at Amazon comes from the desire to impress customers rather than the zeal to best competitors. We don’t take a view on which of these approaches is more likely to maximize business success. There are pros and cons to both and many examples of highly successful competitor-focused companies. We do work to pay attention to competitors and be inspired by them, but it is a fact that the customer-centric way is at this point a defining element of our culture. One advantage—perhaps a somewhat subtle one—of a customer-driven focus is that it aids a certain type of proactivity. When we’re at our best, we don’t wait for external pressures. We are internally driven to improve our services, adding benefits and features, before we have to. We lower prices and increase value for customers before we have to. We invent before we have to. These investments are motivated by customer focus rather than by reaction to competition. We think this approach earns more trust with customers and drives rapid improvements in customer experience—importantly—even in those areas where we are already the leader.
Competition and zero-sum games
Zero-sum games are unbelievably rare. Sporting events are zero-sum games. Two teams enter an arena. One’s going to win; one’s going to lose. Elections are zero-sum games. One candidate is going to win; one candidate is going to lose. In business, however, several competitors can do well. That’s very normal.
The most important thing for doing well against competition—in business and also, I think, with military adversaries—is to be both robust and nimble. And it is scale. So it’s great to be in the US military because you’re big. Scale is a gigantic advantage because it gives you robustness. You can take a punch. But it’s also good if you can dodge a punch. And that’s the nimbleness. And as you get bigger, you grow more robust. The most important factor for nimbleness is decision-making speed.
The second-most important factor is being willing to be experimental. You have to be willing to take risks. You have to be willing to fail, and people don’t like failure. I always point out that there are two different kinds of failure. There’s experimental failure—that’s the kind of failure you should be happy with. And there’s operational failure. We’ve built hundreds of fulfillment centers at Amazon over the years, and we know how to do that. If we build a new fulfillment center and it’s a disaster, that’s just bad execution. That’s not good failure. But when we are developing a new product or service or experimenting in some way, and it doesn’t work, that’s okay. That’s great failure. And you need to distinguish between those two types of failure and really be seeking invention and innovation.
Embrace external trends
The outside world can push you into Day 2 if you won’t or can’t embrace powerful trends quickly. If you fight them, you’re probably fighting the future. Embrace them and you have a tailwind. These big trends are not that hard to spot (they get talked and written about a lot), but they can be strangely hard for large organizations to embrace. We’re in the middle of an obvious one right now: machine learning and artificial intelligence.
Fending off Day 2
“Jeff, what does Day 2 look like?” That’s a question I just got at our most recent all-hands meeting. I’ve been reminding people that it’s Day 1 for a couple of decades. I work in an Amazon building named Day 1, and when I moved buildings, I took the name with me. I spend time thinking about this topic. “Day 2 is stasis. Followed by irrelevance. Followed by excruciating, painful decline. Followed by death. And that is why it is always Day 1.” To be sure, this kind of decline would happen in extreme slow motion. An established company might harvest Day 2 for decades, but the final result would still come. I’m interested in the question “How do you fend off Day 2?” What are the techniques and tactics? How do you keep the vitality of Day 1, even inside a large organization? Such a question can’t have a simple answer. There will be many elements, multiple paths, and many traps. I don’t know the whole answer, but I may know bits of it. Here’s a starter pack of essentials for Day 1 defense: customer obsession, a skeptical view of proxies, the eager adoption of external trends, and high-velocity decision making.
There are many ways to center a business. You can be competitor focused, you can be product focused, you can be technology focused, you can be business model focused, and there are more. But in my view, obsessive customer focus is by far the most protective of Day 1 vitality.
Why? There are many advantages to a customer-centric approach, but here’s the big one: customers are always beautifully, wonderfully dissatisfied, even when they report being happy and business is great. Even when they don’t yet know it, customers want something better, and your desire to delight customers will drive you to invent on their behalf. No customer ever asked Amazon to create the Prime membership program, but it sure turns out they wanted it, and I could give you many such examples. Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight. A customer-obsessed culture best creates the conditions where all of that can happen.
As companies get larger and more complex, there’s a tendency to manage to proxies. This comes in many shapes and sizes, and it’s dangerous, subtle, and very Day 2. A common example is process as proxy. Good process serves you so you can serve customers. But if you’re not watchful, the process can become the thing. This can happen very easily in large organizations. The process becomes the proxy for the result you want. You stop looking at outcomes and just make sure you’re doing the process right. Gulp. It’s not that rare to hear a junior leader defend a bad outcome with something like, “Well, we followed the process.” A more experienced leader will use it as an opportunity to investigate and improve the process. The process is not the thing. It’s always worth asking, do we own the process or does the process own us? In a Day 2 company, you might find it’s the second. Another example: market research and customer surveys can become proxies for customers—something that’s especially dangerous when you’re inventing and designing products. “Fifty-five percent of beta testers report being satisfied with this feature. That is up from 47 percent in the first survey.” That’s hard to interpret and could unintentionally mislead. Good inventors and designers deeply understand their customer. They spend tremendous energy developing that intuition. They study and understand many anecdotes rather than only the averages you’ll find on surveys. They live with the design.
First, there’s a foundational question: are high standards intrinsic or teachable? If you take me on your basketball team, you can teach me many things, but you can’t teach me to be taller. Do we first and foremost need to select for “high standards” people? If so, this letter would need to be mostly about hiring practices, but I don’t think so. I believe high standards are teachable. In fact, people are pretty good at learning high standards simply through exposure. High standards are contagious. Bring a new person onto a high standards team, and they’ll quickly adapt. The opposite is also true. If low standards prevail, those too will quickly spread. And though exposure works well to teach high standards, I believe you can accelerate that rate of learning by articulating a few core principles of high standards, which I hope to share in this letter.
Another important question is whether high standards are universal or domain specific. In other words, if you have high standards in one area, do you automatically have high standards elsewhere? I believe high standards are domain specific, and that you have to learn high standards separately in every arena of interest. When I started Amazon, I had high standards on inventing, on customer care, and (thankfully) on hiring. But I didn’t have high standards on operational process: how to keep fixed problems fixed, how to eliminate defects at the root, how to inspect processes, and much more. I had to learn and develop high standards on all of that (my colleagues were my tutors). Understanding this point is important because it keeps you humble. You can consider yourself a person of high standards in general and still have debilitating blind spots. There can be whole arenas of endeavor where you may not even know that your standards are low or nonexistent, and certainly not world class. It’s critical to be open to that likelihood.
Perfect Handstands A close friend recently decided to learn to do a perfect free-standing handstand. No leaning against a wall. Not for just a few seconds. Instagram good. She decided to start her journey by taking a handstand workshop at her yoga studio. She then practiced for a while but wasn’t getting the results she wanted. So, she hired a handstand coach. Yes, I know what you’re thinking, but evidently this is an actual thing that exists. In the very first lesson, the coach gave her some wonderful advice. “Most people,” he said, “think that if they work hard, they should be able to master a handstand in about two weeks. The reality is that it takes about six months of daily practice. If you think you should be able to do it in two weeks, you’re just going to end up quitting.” Unrealistic beliefs on scope—often hidden and undiscussed—kill high standards. To achieve high standards yourself or as part of a team, you need to form and proactively communicate realistic beliefs about how hard something is going to be—something this coach understood well.
Time management for executives
I like to putter in the morning. I get up early. I go to bed early. I like to read the newspaper. I like to have coffee. I like to have breakfast with my kids before they go to school. So my puttering time is very important to me. That’s why I set my first meeting for ten o’clock. I like to do my high-IQ meetings before lunch. Anything that’s going to be really mentally challenging is a ten o’clock meeting because by 5 P.M., I’m, like, I can’t think more about this issue today. Let’s try this again tomorrow at 10 A.M.
Then on to eight hours of sleep. I prioritize sleep unless I’m traveling in different time zones. Sometimes getting eight hours is impossible, but I am very focused on it, and I need eight hours. I think better. I have more energy. My mood is better. And think about it: As a senior executive, what do you really get paid to do? You get paid to make a small number of high-quality decisions. Your job is not to make thousands of decisions every day. So let’s say I slept six hours a day, or let’s go really crazy and say I slept four hours a day. I’d get four so-called productive hours back. So if before I had, say, twelve hours of productive time during any waking day, now all of a sudden I have twelve plus four—I have sixteen productive hours. So I have 33 percent more time to make decisions. If I was going to make, say, one hundred decisions, I can now make thirty-three more. Is that really worth it if the quality of those decisions might be lower because you’re tired or grouchy or any number of things?
Now, it’s different if the company is a start-up. When Amazon was a hundred people, it was a different story, but Amazon’s not a start-up company, and all of our senior executives operate the same way I do. They work in the future. They live in the future. None of the people who report to me should really be focused on the current quarter. When I have a good quarterly conference call with Wall Street, people will stop me and say, “Congratulations on your quarter,” and I say, “Thank you,” but what I’m really thinking is that quarter was baked three years ago. Right now I’m working on a quarter that’s going to reveal itself in 2023 sometime, and that’s what you need to be doing. You need to be thinking two or three years in advance, and if you are, then why do I need to make a hundred decisions today? If I make, like, three good decisions a day, that’s enough, and they should just be as high quality as I can make them. Warren Buffet says he’s good if he makes three good decisions a year, and I really believe that.
The way you earn trust, the way you develop a reputation is by doing hard things well over and over and over. The reason, for example, that the US military, in all polls, has such high credibility and reputation is because, over and over again, decade after decade, it has done hard things well.
Questions for tomorrow
Tomorrow, in a very real sense, your life—the life you author from scratch on your own—begins. How will you use your gifts? What choices will you make? Will inertia be your guide, or will you follow your passions? Will you follow dogma, or will you be original? Will you choose a life of ease, or a life of service and adventure? Will you wilt under criticism, or will you follow your convictions? Will you bluff it out when you’re wrong, or will you apologize? Will you guard your heart against rejection, or will you act when you fall in love? Will you play it safe, or will you be a little bit swashbuckling? When it’s tough, will you give up, or will you be relentless? Will you be a cynic, or will you be a builder? Will you be clever at the expense of others, or will you be kind? I will hazard a prediction. When you are eighty years old and, in a quiet moment of reflection, narrating for only yourself the most personal version of your life story, the telling that will be most compact and meaningful will be the series of choices you have made. In the end, we are our choices. Build yourself a great story. Thank you, and good luck!