導讀
這封信是2018年Amazon的第22封致股東信。
我們都知道「執行力」對於個人發展、團隊發展和組織發展很重要。
制定計畫，然後專注執行，化計畫為現實。這是很有效率的做事方式，我個人也很喜歡這樣有板有眼的做事原則。
然而，有時候你沒辦法很明確知道「要達到目標具體要做什麼是情」，這時你就需要稍微偏離正軌，讓直覺和好奇心引領自己，犧牲一點效率才能成就真正有意義的事。
放在Amazon的例子，就是需要「圍繞著客戶漫步」。不斷試驗、失敗、更新、迭代，直到推出對客戶真正有意義的產品。
Amazon剛開始推出第三方賣家服務時，並不是很清楚第三方賣家需要什麼服務。於是，漫步開始。他們不斷試錯，直到遇到Amazon配送服務和Prime會員。
賓果！繞了好多彎子，總算碰上有意義的非線性發明！
好了，導讀結束，以下致股東信正文開始。
正文
To our shareowners:
致我們的股東：
Something strange and remarkable has happened over the last 20 years. Take a look at these numbers:
過去的20年裡，發生了一些奇怪而令人驚訝的事情。請看這些數字：
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 thirdparty 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:
百分比數字代表第三方賣家（主要是中小型企業）在Amazon上銷售的總銷售額百分比。第三方銷售額從總銷售額的3％增長到58％。說清楚一點就是：
Third-party sellers are kicking our first party butt. Badly.
第三方賣家正全方位地擊敗作為官方的Amazon，他們大大勝出。
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.
這建立起很高的門檻，因為在此期間，我們的官方業務也急劇增長，從1999年的16億美元增長到去年的1170億美元，複合年增長率為25％。與此同時，第三方銷售額從1億美元增長到1600億美元，複合年增長率為52％。提供一個對標的外部基準，eBay在同時期的商品銷售總額以20％的複合增長率增長，從28億美元增長到950億美元。
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:
為什麼第三方賣家在Amazon上的銷售成績比在eBay上好得多？為什麼第三方賣家能夠比Amazon官方增長得更快？沒有一個確切答案，但是我們對答案略知一二。
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.
我們提供最好的銷售工具給第三方賣家，幫助第三方賣家可以跟官方競爭。這樣的工具提供的服務包括庫存管理、付款流程、物流追蹤、報告生成和跨境銷售，而且還在持續發明新工具。然而，更重要的是Amazon配送服務和Prime會員服務。結合這兩項服務，可以大大改善和第三方賣家購買商品的客戶體驗。如今這兩項服務已經很成功，因此大家很難想像當初推出它們時，這兩種產品的發展有多麼艱難。經過內部成員大量討論之後，我們投資於這兩項具有重大財務風險的服務。在我們嘗試不同的想法並多次迭代後，我們繼續加碼大筆投資。我們無法預見這些服務最終會長成什麼樣子，更不用說它們會不會成功。這兩項服務被直覺推動，被樂觀滋潤。
Intuition, curiosity, and the power of wandering
直覺、好奇心和漫步的力量
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.
從一開始，我們就知道我們想營造一種創造者文化，也就是一種屬於好奇者、探險者的文化。他們喜歡發明。即使已經是專家，他們還是具備初學者的好奇心。他們看待做事的價值觀，正是我們現做事的原則。創造者心態能幫助我們以謙虛來把握重大的機會和難以解決的問題。我們相信成功可以透過迭代來實現：發明、推出、再發明、再推出、從頭來過、一次又一次重複。他們知道成功的道路絕不可能一帆風順。
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.
有時（通常是實際上）在業務中，你確實清楚自己要的是什麼，於是你可以很有效率地往前邁進。制定計劃，然後執行。相比之下，在企業中漫步不前（Wandering）並不高效。漫步不是隨機的，而是受預感、直覺和好奇心引導，堅信一點混亂和偏離正軌能帶給客戶更大的好處。漫步是必要的平衡，你需要同時兼顧效率和漫步。大的發明－尤其是「非線性」的發明，極需要漫步才有機會出現。
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.
數百萬名AWS客戶遍及新創公司到大企業，從政府到非營利組織，每名客戶都希望提供終端消費者更好的解決方案。我們花費大量時間思考這些組織的需求以及組織內部人員的需求－開發人員、開發經理、運營經理、CIO、首席數位長和首席資訊安全長想要的東西。
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的大部分功能都奠基於客戶的意見。詢問客戶他們想要什麼是至關重要的事，認真聽他們的回答，並製定出計劃，周到且迅速提供服務（速度是關鍵！）。沒有這種對客戶的專注，任何企業都無法蓬勃發展。但這樣還不夠，最大的推動力是那些客戶不知道怎麼提出需求的事情。我們必須為他們發明。我們必須從想像出發，化可能為真實。
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本身就是一個例子。沒有客戶要求AWS這樣的東西。沒有任何一名客戶。事實證明，世界已經做好了準備並渴望AWS的出現，只是世界並不知道這件事。我們有預感並跟隨好奇心，承擔必要的財務風險，然後開始建構、重來、試驗和迭代，就這樣進行了無數次。
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 listeningcarefully-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.
這樣的模式已經在AWS重複多次。例如，我們發明了DynamoDB，這是一種可擴展、低延遲的鍵值（Key-Value）數據庫，已經有成千上萬名AWS客戶在使用。認真聆聽客戶需求，我們聽到許多公司對自己使用的商業數據庫感到束縛，數十年來一直對數據庫提供商感到不滿意－這些產品昂貴、專用、高度限制，又經常帶有懲罰授權使用條款。我們花費了數年時間，構建自己的數據庫引擎Amazon Aurora，這是一種全託管的服務，兼容MySQL和PostgreSQL，擁有和其他商用引擎相同，甚至更好的耐用性和可用性，但成本僅為商用引擎的十分之一。當AWS表現得很好時，我們並不感到訝異。
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.
我們也對用於特殊工作的專用數據庫的前景感到樂觀。在過去的20到30年間，企業使用關係數據庫來處理大部分業務需求。開發人員對關係數據庫的選擇，主要取決於他們是否了解該技術，而不是技術本身是否優異。儘管沒那麼好，但因為數據集的大小通常很小，所以查詢等待時間還是在可接受的範疇。但是今天，許多應用程序的數據量級在TB和PB，而且需要滿足低延遲、實時處理以及併發處理的需求。每秒處理數百萬個請求是常見的需求。它需要是DynamoDB這樣的鍵值資料庫，而且也要是Amazon ElastiCache這樣的內存數據庫、Amazon Timestream這樣的時間序列數據庫、Amazon Quantum Ledger Database這樣的分類帳解決方案－用上正確的工具可以節省金錢，提升產品推向市場的速度。
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.
我們也致力於幫助其他公司利用機器學習。我們已經為機器學習進行了長時間的研究，與其他重要進展一樣，我們最初嘗試將內部學習工具向外推廣的嘗試是失敗的。經過數年的漫步－實驗、迭代、優化，以及來自客戶的寶貴建議，我們找到SageMaker，並在18個月前正式推出。SageMaker減少了機器學習過程中的繁重複雜的工作，從而使AI能夠普及。如今，成千上萬名客戶使用SageMaker在AWS上建構機器學習模型，我們將繼續加強服務，添加新的強化學習功能（Reinforcement learning）。強化學習的學習曲線陡峭，並不容易掌握。目前為止，除資金最雄厚的技術組織外，其他人都無法接觸它。出於好奇心文化，以及樂意為客戶嘗試新事物，我們開始以客戶為中心進行漫步和聆聽－AWS現在是年營業額300億美元的業務，而且還在快速增長。
Imagining the impossible
想像那些不可能的事
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，Amazon在全球零售業中仍然只是小人物。我們在零售市場中所佔的比例較低，而且我們開站的每個國家裡都有規模更大的零售商，近90％的零售仍然發生在線下。多年以來，我們一直在思考如何在實體店中提供服務，但我們認為首先需要一款讓客戶真正滿意的產品。有了Amazon Go，我們有了明確的願景－擺脫實體零售最糟糕的事情：結帳台。沒有人喜歡排隊等候結帳。我們設想了一家商店，你可以走進去，拿起想要的東西，然後直接離開。
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.
要實現真的很難，技術上很難。需要全球數百名聰明敬業的計算機科學家和工程師的努力。必須設計和製造專用相機和架子，發明新的計算機視覺算法，合併數百個協作相機中的圖像。而且必須以一種運行良好的方式實現，讓技術退入背景，客戶看不見也無須看見。成就感來自於客戶的回應，他們稱Amazon Go的購物經歷為「神奇」。我們在芝加哥、舊金山和西雅圖有10家Amazon Go，我們對未來感到興奮。
Failure needs to scale too
就算練習失敗，也需要放大規模
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.
隨著公司的成長，一切都需要擴張，也包括失敗實驗的規模。如果失敗的規模沒有跟著長大，就無法取得真正有進展的進步。如果我們偶爾遇到數十億美元的失敗，我們還是會持續進行適當規模的試驗。當然，我們不會輕蔑地低估試驗。我們會努力使他們成為好賭注，但並非所有好賭注最終都能得到回報。作為一家大公司，這種大規模試驗是我們可以為客戶和社會提供的服務。對於股東來說，好消息是，一個成功的大賭注可以彌補許許多多失敗的損失。
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的開發始於同一時期。Fire Phone失敗後，我們（包括開發人員）吸取教訓，因此加快了Echo和Alexa的工作。Echo和Alexa的構想受到《Star Trek》中計算機的啟發。這個想法起源於我們已經耕耘多年的另外兩個領域：機器學習和雲技術。 從Amazon成立之初，機器學習就成為產品推薦功能必不可少的一部分，而AWS使我們在雲技術領域處於領先位置。經過多年的研發，Echo於2014年首次亮相，並可使用透過Echo使用Alexa服務。
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.”
沒有客戶直接提出他們需要Echo。這是我們漫步的結果，市場調查無濟於事。如果你在2013年去問任何一位客戶：「你是否想在廚房裡使用一個不斷運轉的黑色圓筒，差不多是一罐品客的尺寸。你可以與之交談或要求它打開燈光和播音樂。」我向你保證，他們會用奇怪的眼神看著你說：「不用了，謝謝。」
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!
自從第一代Echo以來，客戶已經購買了超過1億個支援Alexa的設備。去年，我們將Alexa的理解請求和回答問題的能力提高20％，同時增加了數十億個知識點，使Alexa比以往任何時候都更加知識淵博。開發人員將Alexa的技能數量增加一倍，達到8萬項技能。與2017年相比，客戶在2018年與Alexa交流的次數增加了數百億次。內建Alexa的設備數量在2018年增加一倍以上。現在有150多種產品內建Alexa，從耳機、PC到汽車和智能家居設備。未來還會更多！
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.
結束前的最後一件事。正如我在20多年前的第一封股東信中所說，我們的重點是招聘和留住能像主人一樣思考的人才。要做到這一點，需要向員工進行投資。和Amazon的其他事情一樣，我們不僅分析，也會使用直覺和毅力來尋找前進的道路。
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，我們將全美所有全職、兼職、臨時和季節性僱員的最低工資提高到每小時15美元。這次加薪使超過25萬名Amazon員工以超過10萬名季節性員工受益。我們堅信投資在員工身上有利於我們的業務。但這不是決定的原因。我們一直提供有競爭力的薪資，但是我們現在認為是時候站出來－提供超乎其他人才競爭公司的薪資。我們這樣做，是因為我們認為這是正確的。
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，我挑戰頂級零售競爭對手（你知道我們在說誰！），提供和我們一樣的員工福利和15美元最低工資。來吧！最好能給16美元，再把挑戰拋回來給我們。這是一場使所有人受益的競爭。
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.
我們為員工推出的許多計劃。我之前提到過職業選擇計劃，此計劃預付最高95％的學雜費，讓員工可以取得學習領域的證書或文憑，從而給他們嘗試新職業的機會，即使這些職業會不在Amazon。現在已有超過1.6萬名員工從此計劃中受益且人數持續。同樣的，我們的職業技能計劃（Career Skills）對員工進行關鍵工作技能的短期培訓，例如簡歷寫作、有效溝通和計算機基礎知識。去年10月，為兌現這些承諾，我們簽署了《President’s Pledge to America’s Workers》，宣布將透過一系列培訓計劃，提高5萬名美國員工的技能。
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.
我們的投資不僅限於現有員工，甚至不局限於當下。為了培訓明天的勞動力，我們已承諾投資5000萬美元，包括Amazon未來工程師計劃，這是一項支持全國小學、高中和大學生STEM和CS教育的計畫，將會特別著重於吸引更多女孩和少數民族。我們將繼續招聘退伍軍人，讓他們發揮絕佳的才能。我們正在努力實現承諾，在2021年前僱用2.5萬名退伍軍人及其配偶。透過Amazon的退伍軍人技術培訓計劃（Technical Veterans Apprenticeship），我們將在雲計算等領域提供退伍軍人在職培訓。
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!
非常感謝我們的客戶，在為你們提供服務時，你們始終敦促我們做得更好。非常感謝我們的股東，謝謝你們持續給予我們支持。感謝全球Amazon員工的辛勤工作和開拓精神。Amazon各地的團隊都在傾聽客戶的意見，並以客戶為中心尋求提供更好的服務！
As always, I attach a copy of our original 1997 letter. It remains Day 1.
如同往常，我把我們在1997年寫的致股東信附在文末。我們的價值觀依然不變，今天依舊是Day 1。
Sincerely,
Jeffrey P. Bezos
真誠的
傑夫·貝佐斯
Jeffrey P. Bezos
Founder and Chief Executive Officer
Amazon.com, Inc.
傑夫·貝佐斯
Amazon創始人暨CEO
以上就是2018年Amazon致股東信。
想看隔年的Amazon致股東信，請至《2019年Amazon致股東信：疫情之下，任重道遠》。
想看全系列導讀目錄，請至《Amazon 1997–2019年致股東信導讀目錄》。
