2019-04-11 Jeff Bezos’s Letters to Amazon Shareholders
To our shareowners:
Something strange and remarkable has happened over the last 20 years. Take a look at these numbers:
在过去的20年里，发生了一些奇怪而非凡的事情。 看看这些数字：
1999 3%
2000 3%
2001 6%
2002 17%
2003 22%
2004 25%
2005 28%
2006 28%
2007 29%
2008 30%
2009 31%
2010 34%
2011 38%
2012 42%
2013 46%
2014 49%
2015 51%
2016 54%
2017 56%
2018 58%
The percentages represent the share of physical gross merchandise sales sold on Amazon by independent third-party sellers – mostly small- and medium-sized businesses – as opposed to Amazon retail’s own first party sales. Third-party sales have grown from 3% of the total to 58%. To put it bluntly:
这些百分比表示在亚马逊上由独立的第三方卖家——主要是中小型企业——销售的实体商品总额所占份额，而不是亚马逊自营的一方销售。第三方销售额已从总体的 3% 增长到 58%。直截了当地说：
Third-party sellers are kicking our first party butt. Badly.
第三方卖家正在狠狠地打败我们的自营业务。
And it’s a high bar too because our first-party business has grown dramatically over that period, from \$1.6 billion in 1999 to \$117 billion this past year. The compound annual growth rate for our first-party business in that time period is 25%. But in that same time, third-party sales have grown from \$0.1 billion to \$160 billion – a compound annual growth rate of 52%. To provide an external benchmark, eBay’s gross merchandise sales in that period have grown at a compound rate of 20%, from \$2.8 billion to \$95 billion.
这还是一个很高的门槛，因为同期我们的自营业务也实现了大幅增长，从 1999 年的 16 亿美元增加到去年刚刚过去的 1,170 亿美元。这段期间自营业务的复合年增长率为 25%。但在同一时期，第三方销售额从 1 亿美元飙升至 1,600 亿美元——复合年增长率达到 52%。作为外部对照，eBay 在同一时期的商品成交总额从 28 亿美元增至 950 亿美元，复合年增长率为 20%。
Why did independent sellers do so much better selling on Amazon than they did on eBay? And why were independent sellers able to grow so much faster than Amazon’s own highly organized first-party sales organization? There isn’t one answer, but we do know one extremely important part of the answer:
为什么独立卖家在亚马逊上的表现远胜于他们在 eBay 上的表现？又为什么独立卖家的增长速度能远超亚马逊自己高度组织化的自营销售团队？这一问题并没有唯一答案，但我们知道其中一个极其重要的原因：
We helped independent sellers compete against our first-party business by investing in and offering them the very best selling tools we could imagine and build. There are many such tools, including tools that help sellers manage inventory, process payments, track shipments, create reports, and sell across borders – and we’re inventing more every year. But of great importance are Fulfillment by Amazon and the Prime membership program. In combination, these two programs meaningfully improved the customer experience of buying from independent sellers. With the success of these two programs now so well established, it’s difficult for most people to fully appreciate today just how radical those two offerings were at the time we launched them. We invested in both of these programs at significant financial risk and after much internal debate. We had to continue investing significantly over time as we experimented with different ideas and iterations. We could not foresee with certainty what those programs would eventually look like, let alone whether they would succeed, but they were pushed forward with intuition and heart, and nourished with optimism.
我们通过投资并为独立卖家提供我们能够想象并打造的最佳销售工具，帮助他们与我们的自营业务竞争。此类工具多种多样，包括帮助卖家管理库存、处理支付、追踪运输、生成报告以及跨境销售的工具——而且我们每年都在推出更多新工具。但最重要的要数“亚马逊物流”（FBA）和“Prime 会员计划”。这两大项目结合在一起，显著改善了消费者从独立卖家处购物的体验。如今，这两项计划的成功已无可争议，但大多数人很难充分体会当年它们推出时究竟有多么激进。我们在这两个项目上投入了巨大的资金并承担了重大风险，且经历了大量内部辩论。在不断试验不同理念和迭代方案的过程中，我们不得不持续进行大量投资。当时我们无法确定这些项目最终会呈现什么样子，更无法确定它们会否成功，但它们是在直觉与热情的推动下前进，并由乐观精神不断滋养。
Intuition, curiosity, and the power of wandering
直觉、好奇心与漫游的力量
From very early on in Amazon’s life, we knew we wanted to create a culture of builders – people who are curious, explorers. They like to invent. Even when they’re experts, they are “fresh” with a beginner’s mind. They see the way we do things as just the way we do things now. A builder’s mentality helps us approach big, hard-to-solve opportunities with a humble conviction that success can come through iteration: invent, launch, reinvent, relaunch, start over, rinse, repeat, again and again. They know the path to success is anything but straight.
早在亚马逊创立之初，我们就知道要打造一种“建设者文化”——这群人好奇、爱探索，乐于发明。即便已是专家，他们仍保持“初心者”的新鲜视角，把我们现在的做法仅视为“暂时”的做法。建设者心态让我们以谦逊而笃信迭代能带来成功的方式去面对那些庞大且难解的机遇：发明、推出、再造、再推出、从头来过，洗牌、重复，一遍又一遍。他们深知通往成功的道路绝非直线。
Sometimes (often actually) in business, you do know where you’re going, and when you do, you can be efficient. Put in place a plan and execute. In contrast, wandering in business is not efficient … but it’s also not random. It’s guided – by hunch, gut, intuition, curiosity, and powered by a deep conviction that the prize for customers is big enough that it’s worth being a little messy and tangential to find our way there. Wandering is an essential counter-balance to efficiency. You need to employ both. The outsized discoveries – the “non-linear” ones – are highly likely to require wandering.
在商业中，有时（事实上常常）你确实知道目标，于是可以高效行事：制定计划并执行。相比之下，商业中的“漫游”效率不高……但它并非随机，而是由预感、直觉、好奇心引导，并被一种深信——为客户创造的价值足够巨大，值得我们在摸索中稍显杂乱和偏离正途——所驱动。漫游是对效率的重要平衡，两者缺一不可。那些超常发现——“非线性”成果——往往需要漫游才能获得。
不怕失败是个优点。
AWS’s millions of customers range from startups to large enterprises, government entities to nonprofits, each looking to build better solutions for their end users. We spend a lot of time thinking about what those organizations want and what the people inside them – developers, dev managers, ops managers, CIOs, chief digital officers, chief information security officers, etc. – want.
AWS 拥有数百万客户，涵盖初创公司到大型企业、政府机构到非营利组织，他们都在为终端用户构建更优方案。我们花大量时间思考这些组织以及其中的开发者、开发经理、运维经理、CIO、首席数字官、首席信息安全官等人真正想要什么。
Much of what we build at AWS is based on listening to customers. It’s critical to ask customers what they want, listen carefully to their answers, and figure out a plan to provide it thoughtfully and quickly (speed matters in business!). No business could thrive without that kind of customer obsession. But it’s also not enough. The biggest needle movers will be things that customers don’t know to ask for. We must invent on their behalf. We have to tap into our own inner imagination about what’s possible.
AWS 的很多产品都是基于倾听客户需求而构建的。询问客户想要什么、认真倾听反馈并迅速且周到地制定方案至关重要（商业讲求速度！）。没有这种对客户的执着，任何业务都难以繁荣。但这仍不足以推动最大突破。最大的杠杆往往是客户不知道如何提出的需求。我们必须代表他们进行发明，挖掘自身对可能性的内在想象力。
AWS itself – as a whole – is an example. No one asked for AWS. No one. Turns out the world was in fact ready and hungry for an offering like AWS but didn’t know it. We had a hunch, followed our curiosity, took the necessary financial risks, and began building – reworking, experimenting, and iterating countless times as we proceeded.
AWS 整体就是一个例子。没有人要求过 AWS，真的没有人。然而事实证明，世界早已准备好并渴望这样的服务，只是不自知。我们凭直觉行事，顺着好奇心，承担必要的财务风险开始构建——在推进过程中无数次重做、实验与迭代。
Within AWS, that same pattern has recurred many times. For example, we invented DynamoDB, a highly scalable, low latency key-value database now used by thousands of AWS customers. And on the listening carefully-to-customers side, we heard loudly that companies felt constrained by their commercial database options and had been unhappy with their database providers for decades – these offerings are expensive, proprietary, have high-lock-in and punitive licensing terms. We spent several years building our own database engine, Amazon Aurora, a fully-managed MySQL and PostgreSQL-compatible service with the same or better durability and availability as the commercial engines, but at one-tenth of the cost. We were not surprised when this worked.
在 AWS 内部，这种模式屡次上演。例如，我们发明了 DynamoDB——一款高度可扩展、低延迟的键值数据库，如今被数千家 AWS 客户使用。在倾听客户方面，我们也清楚听到企业长期受限于商用数据库，几十年来对供应商不满——价格昂贵、封闭、锁定高且许可条款苛刻。于是我们花费数年打造自己的数据库引擎 Amazon Aurora，这是一项完全托管且兼容 MySQL 与 PostgreSQL 的服务，具备与商用引擎同等或更优的持久性和可用性，但成本只有十分之一。当它成功时，我们一点也不感到意外。
这类产品的质量值得怀疑。
But we’re also optimistic about specialized databases for specialized workloads. Over the past 20 to 30 years, companies ran most of their workloads using relational databases. The broad familiarity with relational databases among developers made this technology the go-to even when it wasn’t ideal. Though sub-optimal, the data set sizes were often small enough and the acceptable query latencies long enough that you could make it work. But today, many applications are storing very large amounts of data – terabytes and petabytes. And the requirements for apps have changed. Modern applications are driving the need for low latencies, real-time processing, and the ability to process millions of requests per second. It’s not just key-value stores like DynamoDB, but also in-memory databases like Amazon ElastiCache, time series databases like Amazon Timestream, and ledger solutions like Amazon Quantum Ledger Database – the right tool for the right job saves money and gets your product to market faster.
但我们也对专门为特定工作负载设计的专业数据库持乐观态度。在过去的 20 到 30 年中，公司大多使用关系型数据库来运行其工作负载。开发者对关系型数据库的广泛熟悉使得这种技术成为默认选择，即使它并非理想方案。虽然并不完美，但当时的数据集规模通常足够小，可接受的查询延迟足够长，因此仍能运作。然而如今，许多应用程序存储着大量数据——从 TB 级到 PB 级。应用需求也发生了变化。现代应用驱动着对低延迟、实时处理以及每秒处理数百万请求能力的需求。现在需要的不仅仅是像 DynamoDB 这样的键值存储，还有如 Amazon ElastiCache 这样的内存数据库、Amazon Timestream 这样的时序数据库，以及 Amazon Quantum Ledger Database 这样的分类账解决方案——为合适的工作选择合适的工具可节省成本并让产品更快上市。
We’re also plunging into helping companies harness Machine Learning. We’ve been working on this for a long time, and, as with other important advances, our initial attempts to externalize some of our early internal Machine Learning tools were failures. It took years of wandering – experimentation, iteration, and refinement, as well as valuable insights from our customers – to enable us to find SageMaker, which launched just 18 months ago. SageMaker removes the heavy lifting, complexity, and guesswork from each step of the machine learning process – democratizing AI. Today, thousands of customers are building machine learning models on top of AWS with SageMaker. We continue to enhance the service, including by adding new reinforcement learning capabilities. Reinforcement learning has a steep learning curve and many moving parts, which has largely put it out of reach of all but the most well-funded and technical organizations, until now. None of this would be possible without a culture of curiosity and a willingness to try totally new things on behalf of customers. And customers are responding to our customer-centric wandering and listening – AWS is now a \$30 billion annual run rate business and growing fast.
我们也正全力帮助企业利用机器学习。我们在这方面已深耕多年，和其他重要突破一样，我们最初尝试将一些早期内部机器学习工具外部化时并未成功。经历了多年的漫游——实验、迭代与完善，以及来自客户的宝贵洞见——我们才找到 SageMaker，并在 18 个月前推出。SageMaker 消除了机器学习过程每个环节中的繁重工作、复杂性和猜测，实现了 AI 的大众化。如今，成千上万的客户在 AWS 之上使用 SageMaker 构建机器学习模型。我们持续增强该服务，包括新增强化学习功能。强化学习有着陡峭的学习曲线且涉及众多组件，这在此之前基本让除最富资金和技术的机构外无人问津。若无好奇文化以及代表客户尝试全新事物的意愿，这一切都不可能实现。客户也对我们以客户为中心的探索与倾听做出了回应——AWS 目前的年度营收运行率已达到 300 亿美元，并保持快速增长。
Imagining the impossible
想象不可能
Amazon today remains a small player in global retail. We represent a low single-digit percentage of the retail market, and there are much larger retailers in every country where we operate. And that’s largely because nearly 90% of retail remains offline, in brick and mortar stores. For many years, we considered how we might serve customers in physical stores, but felt we needed first to invent something that would really delight customers in that environment. With Amazon Go, we had a clear vision. Get rid of the worst thing about physical retail: checkout lines. No one likes to wait in line. Instead, we imagined a store where you could walk in, pick up what you wanted, and leave.
如今的亚马逊在全球零售业仍只是一个小角色。我们在零售市场所占份额不足百分之几，而在我们经营的每个国家，都有规模更大的零售商。这主要是因为近 90% 的零售仍然在线下实体店。多年间，我们一直考虑如何在线下门店服务客户，但认为首先需要发明真正能在该场景中令客户惊喜的东西。借助 Amazon Go，我们有了清晰愿景：消除实体零售中最糟糕的一点——排队结账。没有人喜欢排队。我们想象的是这样一家店：你走进来，拿起想要的商品，然后离开。
Getting there was hard. Technically hard. It required the efforts of hundreds of smart, dedicated computer scientists and engineers around the world. We had to design and build our own proprietary cameras and shelves and invent new computer vision algorithms, including the ability to stitch together imagery from hundreds of cooperating cameras. And we had to do it in a way where the technology worked so well that it simply receded into the background, invisible. The reward has been the response from customers, who’ve described the experience of shopping at Amazon Go as “magical.” We now have 10 stores in Chicago, San Francisco, and Seattle, and are excited about the future.
实现这一目标并不容易。从技术上讲非常难。这需要世界各地数百名聪明而专注的计算机科学家和工程师的努力。我们必须设计并构建自有的摄像头和货架，并发明新的计算机视觉算法，包括将数百个协同摄像头的图像拼接起来的能力。并且我们必须以一种方式做到，让技术发挥作用却又悄然隐身于背后。回报是客户的反馈，他们形容在 Amazon Go 购物的体验“如同魔法”。我们目前在芝加哥、旧金山和西雅图拥有 10 家门店，并对未来充满期待。
Failure needs to scale too
失败也需要与规模相匹配
As a company grows, everything needs to scale, including the size of your failed experiments. If the size of your failures isn’t growing, you’re not going to be inventing at a size that can actually move the needle. Amazon will be experimenting at the right scale for a company of our size if we occasionally have multibillion-dollar failures. Of course, we won’t undertake such experiments cavalierly. We will work hard to make them good bets, but not all good bets will ultimately pay out. This kind of large-scale risk taking is part of the service we as a large company can provide to our customers and to society. The good news for shareowners is that a single big winning bet can more than cover the cost of many losers.
随着公司成长，一切都必须扩张，包括失败实验的规模。如果失败的规模没有增长，你就不可能在真正能够产生影响的层面进行创新。对于亚马逊这样的公司而言，如果我们偶尔出现数十亿美元级别的失败，说明我们在合适的规模上进行实验。当然，我们不会轻率地启动此类实验。我们会努力使之成为高概率的下注，但并非所有好下注最终都会奏效。这种大规模承担风险的做法，是我们作为大型企业能够为客户和社会提供的服务的一部分。对股东来说，好消息是，一个重大成功的下注就足以弥补许多失败的成本。
Development of the Fire phone and Echo was started around the same time. While the Fire phone was a failure, we were able to take our learnings (as well as the developers) and accelerate our efforts building Echo and Alexa. The vision for Echo and Alexa was inspired by the Star Trek computer. The idea also had origins in two other arenas where we’d been building and wandering for years: machine learning and the cloud. From Amazon’s early days, machine learning was an essential part of our product recommendations, and AWS gave us a front row seat to the capabilities of the cloud. After many years of development, Echo debuted in 2014, powered by Alexa, who lives in the AWS cloud.
Fire Phone 和 Echo 的开发几乎在同一时间启动。虽然 Fire Phone 以失败告终，但我们从中吸取了经验（也保留了开发人员），并加速了 Echo 与 Alexa 的构建。Echo 和 Alexa 的愿景来源于《星际迷航》中的电脑。同时，这个想法还起源于我们多年探索的另外两个领域：机器学习和云计算。自亚马逊早期起，机器学习就是我们产品推荐的核心部分，而 AWS 则让我们近距离见证了云端能力。经过多年开发，Echo 于 2014 年问世，其背后的 Alexa 运行在 AWS 云上。
No customer was asking for Echo. This was definitely us wandering. Market research doesn’t help. If you had gone to a customer in 2013 and said “Would you like a black, always-on cylinder in your kitchen about the size of a Pringles can that you can talk to and ask questions, that also turns on your lights and plays music?” I guarantee you they’d have looked at you strangely and said “No, thank you.”
没有客户要求我们推出 Echo。这绝对是我们的“漫游”。市场调研对此无济于事。如果你在 2013 年去问顾客：“您想在厨房里放一个黑色常亮、大小如品客薯片罐的圆柱体，能跟它对话提问，还能开灯放音乐吗？”我敢保证他们会奇怪地看着你，然后说：“不用了，谢谢。”
Since that first-generation Echo, customers have purchased more than 100 million Alexa-enabled devices. Last year, we improved Alexa’s ability to understand requests and answer questions by more than 20%, while adding billions of facts to make Alexa more knowledgeable than ever. Developers doubled the number of Alexa skills to over 80,000, and customers spoke to Alexa tens of billions more times in 2018 compared to 2017. The number of devices with Alexa built-in more than doubled in 2018. There are now more than 150 different products available with Alexa built-in, from headphones and PCs to cars and smart home devices. Much more to come!
自第一代 Echo 发布以来，客户已购买了超过 1 亿台支持 Alexa 的设备。去年，我们将 Alexa 的请求理解和答复能力提升了 20% 以上，并新增了数十亿条知识，让 Alexa 比以往更加博学。开发者将 Alexa 技能数量翻倍至 8 万多个，用户在 2018 年与 Alexa 对话的次数比 2017 年多出数百亿次。2018 年内置 Alexa 的设备数量也增长超过一倍。目前已有超过 150 款不同产品内置 Alexa，从耳机、电脑到汽车及智能家居设备。不止于此，未来还有更多！
One last thing before closing. As I said in the first shareholder letter more than 20 years ago, our focus is on hiring and retaining versatile and talented employees who can think like owners. Achieving that requires investing in our employees, and, as with so many other things at Amazon, we use not just analysis but also intuition and heart to find our way forward.
结束前再说一点。正如 20 多年前我在第一封股东信中所说，我们致力于招聘并留住能够像所有者一样思考的多才多艺人才。要实现这一点，就必须投资于员工。与亚马逊的许多其他事情一样，我们前进的方式不仅依靠分析，也依靠直觉与热忱。
Last year, we raised our minimum wage to \$15-an-hour for all full-time, part-time, temporary, and seasonal employees across the U.S. This wage hike benefitted more than 250,000 Amazon employees, as well as over 100,000 seasonal employees who worked at Amazon sites across the country last holiday. We strongly believe that this will benefit our business as we invest in our employees. But that is not what drove the decision. We had always offered competitive wages. But we decided it was time to lead – to offer wages that went beyond competitive. We did it because it seemed like the right thing to do.
去年，我们将美国境内所有全职、兼职、临时及季节性员工的最低时薪提高至 15 美元。这一加薪惠及了超过 25 万名亚马逊员工，以及去年假期期间在全国各地站点工作的 10 多万季节性员工。我们坚信，投资员工将惠及我们的业务。但这并不是驱动我们决定的原因。我们一直提供具有竞争力的薪酬，但我们认为是时候起到引领作用——提供超越竞争水平的工资。我们这样做，是因为这看起来是正确的事情。
Today I challenge our top retail competitors (you know who you are!) to match our employee benefits and our \$15 minimum wage. Do it! Better yet, go to \$16 and throw the gauntlet back at us. It’s a kind of competition that will benefit everyone.
今天，我向我们的主要零售竞争对手（你们知道我说的是谁！）发出挑战：请把你们的员工福利和我们的 15 美元最低时薪看齐。行动吧！更好的是，把时薪提高到 16 美元，然后把战书再抛回给我们。这种竞争将惠及所有人。
长期处于竞争和挑战的处境中不会有好的结果。
Many of the other programs we have introduced for our employees came as much from the heart as the head. I’ve mentioned before the Career Choice program, which pays up to 95% of tuition and fees towards a certificate or diploma in qualified fields of study, leading to in-demand careers for our associates, even if those careers take them away from Amazon. More than 16,000 employees have now taken advantage of the program, which continues to grow. Similarly, our Career Skills program trains hourly associates in critical job skills like resume writing, how to communicate effectively, and computer basics. In October of last year, in continuation of these commitments, we signed the President’s Pledge to America’s Workers and announced we will be upskilling 50,000 U.S. employees through our range of innovative training programs.
我们为员工推出的许多其他项目，同样源于感性与理性并重。我之前提到过 Career Choice 计划，该计划为符合条件的学习领域证书或文凭支付最高 95% 的学费和费用，帮助员工获得市场紧缺的职业，即便这些职业会让他们离开亚马逊。目前已有超过 16,000 名员工受益于该计划，而且仍在持续增长。类似地，我们的 Career Skills 计划为计时员工提供关键工作技能培训，例如撰写简历、有效沟通以及计算机基础知识。去年 10 月，为延续这些承诺，我们签署了总统的《美国工人承诺》，并宣布将通过一系列创新培训项目为 50,000 名美国员工提升技能。
Our investments are not limited to our current employees or even to the present. To train tomorrow’s workforce, we have pledged \$50 million, including through our recently announced Amazon Future Engineer program, to support STEM and CS education around the country for elementary, high school, and university students, with a particular focus on attracting more girls and minorities to these professions. We also continue to take advantage of the incredible talents of our veterans. We are well on our way to meeting our pledge to hire 25,000 veterans and military spouses by 2021. And through the Amazon Technical Veterans Apprenticeship program, we are providing veterans on-the-job training in fields like cloud computing.
我们的投资不仅限于当前员工，甚至也不限于当下。为了培养未来的劳动力，我们承诺投入 5,000 万美元，其中包括最近宣布的 Amazon Future Engineer 计划，支持全国小学、中学和大学阶段的 STEM 与计算机科学教育，尤其关注吸引更多女孩和少数族裔进入这些领域。我们也继续发挥退伍军人的非凡才能。我们正稳步实现到 2021 年雇用 25,000 名退伍军人及军属的承诺。通过 Amazon Technical Veterans Apprenticeship 计划，我们为退伍军人在云计算等领域提供在职培训。
A huge thank you to our customers for allowing us to serve you while always challenging us to do even better, to our shareowners for your continuing support, and to all our employees worldwide for your hard work and pioneering spirit. Teams all across Amazon are listening to customers and wandering on their behalf!
衷心感谢我们的客户，感谢你们让我们得以为你们服务，并不断激励我们做得更好；感谢股东们的持续支持；同时感谢全球所有员工的辛勤付出和开拓精神。亚马逊各个团队都在倾听客户，并代表他们不断探索！
As always, I attach a copy of our original 1997 letter. It remains Day 1.
一如既往，我随信附上我们 1997 年最初股东信的副本。对我们而言，仍然是 Day 1。
Sincerely,
Jeffrey P. Bezos
Founder and Chief Executive Officer
Amazon.com, Inc.
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