亞馬遜1997年上市以來，CEO貝佐斯每年都會(huì)發(fā)布致股東的公開信，在整個(gè)國(guó)際商界，貝佐斯的股東信始終都被追隨者奉為圭臬，是商業(yè)史上極為經(jīng)典的教材。如今，憑借長(zhǎng)期主義和以客戶為中心，貝佐斯成為世界首富，他歷年的股東信，建議大家抽半天時(shí)間集中學(xué)習(xí)。

亞馬遜致股東信2019 （全文）

以下是該信的全文（中文翻譯僅供參考）

To our shareowners:

Something strange and remarkable has happened over the last 20 years. Take a look at these numbers:

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:

Third-party sellers are kicking our first party butt. Badly.

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.

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:

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.

致我們的股東：

在過去的20年里，發(fā)生了一些奇怪而卓越的事情?？纯催@些數(shù)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%

這些百分比代表了獨(dú)立第三方賣家（主要是中小型企業(yè)）在亞馬遜上銷售的實(shí)際商品銷售份額，而不是亞馬遜零售業(yè)自己的第一方銷售。第三方銷售額從總數(shù)的3％增長(zhǎng)到58％。說穿了就是：

第三方賣家正在蠶食我們的市場(chǎng)份額。厲害了。

這也是一個(gè)很高的標(biāo)準(zhǔn)，因?yàn)槲覀冏鳛榈谝环降模ㄗ誀I(yíng)）業(yè)務(wù)在此期間大幅增長(zhǎng)，從1999年的16億美元增加到去年的1170億美元。我們?cè)谠撈陂g的第一方自營(yíng)業(yè)務(wù)的復(fù)合年增長(zhǎng)率為25％。但與此同時(shí)，第三方銷售額已從1億美元增長(zhǎng)到1,600億美元 - 復(fù)合年增長(zhǎng)率為52％。為了提供外部基準(zhǔn)作為比較，eBay在此期間的商品銷售總額增長(zhǎng)率為20％，從28億美元增長(zhǎng)到950億美元。

為什么獨(dú)立賣家在亞馬遜上賣得比在eBay上好得多？為什么獨(dú)立賣家能夠比亞馬遜高度組織的第一方銷售組織快得多？沒有一個(gè)空整的答案，但我們確實(shí)知道答案的一個(gè)非常重要的部分：

我們通過投資并向他們提供我們可以想象和構(gòu)建的最暢銷工具，幫助獨(dú)立賣家與我們的第一方自營(yíng)業(yè)務(wù)展開競(jìng)爭(zhēng)。有許多這樣的工具，包括幫助賣家管理庫存，處理付款，跟蹤貨物，創(chuàng)建報(bào)告和跨境銷售的工具 - 我們每年都在發(fā)明更多。但非常重要的是亞馬遜的履行和Prime會(huì)員計(jì)劃。結(jié)合起來，這兩個(gè)計(jì)劃有意義地改善了從獨(dú)立賣家購買的客戶體驗(yàn)。隨著這兩個(gè)項(xiàng)目的成功現(xiàn)已如此成熟，大多數(shù)人今天很難完全理解這兩個(gè)產(chǎn)品在我們推出它們時(shí)的激進(jìn)程度。我們?cè)谥卮筘?cái)務(wù)風(fēng)險(xiǎn)和經(jīng)過多次內(nèi)部辯論后投資了這兩個(gè)項(xiàng)目。隨著我們嘗試不同的想法和迭代，我們不得不繼續(xù)大量投資。我們無法肯定地預(yù)見到這些計(jì)劃最終會(huì)是什么樣的，更不用說它們是否會(huì)成功，但它們會(huì)以直覺和內(nèi)心向前推進(jìn)，并以樂觀的態(tài)度得到滋養(yǎng)。

Intuition, curiosity, and the power of wandering

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.

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.

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.

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.

直覺，好奇心和游蕩的力量

從亞馬遜生活的早期開始，我們就知道我們想要?jiǎng)?chuàng)造一種建筑者的文化 - 那些好奇的人，探險(xiǎn)家。他們喜歡發(fā)明。即使他們是專家，他們也是初學(xué)者的“新鮮”。他們看待我們做事的方式，就像我們現(xiàn)在做事一樣。建筑師的心態(tài)幫助我們以謙虛的信念接近巨大的，難以解決的機(jī)會(huì)，成功可以通過迭代來實(shí)現(xiàn)：發(fā)明，發(fā)射，重新發(fā)明，重新啟動(dòng)，重新開始，沖洗，重復(fù)，一次又一次。他們知道成功之路絕不是直截了當(dāng)?shù)摹?/p>

有時(shí)（通常實(shí)際上）在商業(yè)中，你確實(shí)知道你要去哪里，當(dāng)你做的時(shí)候，你就可以有效率。制定計(jì)劃并執(zhí)行。相比之下，在商業(yè)中徘徊并不高效......但它也不是隨機(jī)的。它的引導(dǎo) - 通過預(yù)感，直覺，直覺，好奇心，以及深刻的信念，即客戶的獎(jiǎng)勵(lì)足夠大，以至于找到我們的方式值得有點(diǎn)凌亂和切實(shí)。徘徊是效率的重要平衡。你需要同時(shí)使用兩者。超大的發(fā)現(xiàn) - “非線性”發(fā)現(xiàn) - 極有可能需要徘徊。

AWS的數(shù)百萬客戶包括初創(chuàng)公司，大型企業(yè)，政府機(jī)構(gòu)和非營(yíng)利組織，每個(gè)客戶都希望為最終用戶構(gòu)建更好的解決方案。我們花了很多時(shí)間思考這些組織想要什么以及他們內(nèi)部的人 - 開發(fā)人員，開發(fā)經(jīng)理，操作經(jīng)理，首席信息官，首席數(shù)字官，首席信息安全官等等 - 想要什么（需求）。

我們?cè)贏WS上構(gòu)建的大部分內(nèi)容都是基于傾聽客戶的意見。詢問客戶他們想要什么，仔細(xì)聆聽他們的答案，并制定計(jì)劃，以便周到快速地提供它（在業(yè)務(wù)中加快速度！）是至關(guān)重要的。沒有這種客戶的癡迷，任何企業(yè)都無法繁榮發(fā)展。但這還不夠。最大的推動(dòng)器將是客戶不知道要求的東西。我們必須代表他們發(fā)明。我們必須利用自己內(nèi)心的想象力來實(shí)現(xiàn)可能性。

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.

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.

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.

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.

網(wǎng)絡(luò)搜索結(jié)果

AWS本身 - 作為一個(gè)整體 - 就是一個(gè)例子。沒有人要求AWS。沒有人。事實(shí)證明，世界已經(jīng)準(zhǔn)備好并渴望獲得像AWS這樣的產(chǎn)品，但卻不知道。我們有一種預(yù)感，跟隨我們的好奇心，承擔(dān)了必要的財(cái)務(wù)風(fēng)險(xiǎn)，并開始建設(shè) - 在我們繼續(xù)進(jìn)行時(shí)無數(shù)次地進(jìn)行改造，試驗(yàn)和迭代。

在AWS中，相同的模式已多次重復(fù)出現(xiàn)。例如，我們發(fā)明了DynamoDB，這是一個(gè)高度可擴(kuò)展，低延遲的鍵值數(shù)據(jù)庫，現(xiàn)在已被數(shù)千名AWS客戶使用。在仔細(xì)聆聽客戶方面，我們大聲聽到公司感到受到商業(yè)數(shù)據(jù)庫選項(xiàng)的限制，并且?guī)资陙硪恢睂?duì)他們的數(shù)據(jù)庫提供商感到不滿 - 這些產(chǎn)品價(jià)格昂貴，專有，具有高鎖定性和懲罰性許可條款。我們花了幾年時(shí)間構(gòu)建我們自己的數(shù)據(jù)庫引擎，Amazon Aurora，一個(gè)完全托管的MySQL和PostgreSQL兼容服務(wù)，具有與商用引擎相同或更好的耐用性和可用性，但成本只有十分之一。當(dāng)這個(gè)工作時(shí)，我們并不感到驚訝。

但我們也對(duì)專業(yè)工作負(fù)載的專用數(shù)據(jù)庫持樂觀態(tài)度。在過去的20到30年中，公司使用關(guān)系數(shù)據(jù)庫運(yùn)行大部分工作負(fù)載。開發(fā)人員對(duì)關(guān)系數(shù)據(jù)庫的廣泛熟悉使這項(xiàng)技術(shù)成為最佳選擇，即使它不理想。雖然次優(yōu)，但數(shù)據(jù)集大小通常足夠小，可接受的查詢延遲足夠長(zhǎng)，您可以使其工作。但是今天，許多應(yīng)用程序存儲(chǔ)了大量的數(shù)據(jù) - 太字節(jié)和千兆字節(jié)。應(yīng)用程序的要求已經(jīng)改變?，F(xiàn)代應(yīng)用程序正在推動(dòng)對(duì)低延遲，實(shí)時(shí)處理以及每秒處理數(shù)百萬個(gè)請(qǐng)求的能力的需求。這不僅僅是關(guān)鍵值商店 DynamoDB，以及Amazon ElastiCache等內(nèi)存數(shù)據(jù)庫，Amazon Timestream等時(shí)間序列數(shù)據(jù)庫，以及Amazon Quantum Ledger數(shù)據(jù)庫等分類賬解決方案 - 正確工作的合適工具可以節(jié)省資金并更快地將產(chǎn)品推向市場(chǎng)。

我們也正在積極幫助公司利用機(jī)器學(xué)習(xí)。我們已經(jīng)在這方面工作了很長(zhǎng)時(shí)間，并且，與其他重要的進(jìn)展一樣，我們最初嘗試將我們?cè)缙诘囊恍﹥?nèi)部機(jī)器學(xué)習(xí)工具外部化是失敗的。經(jīng)過多年的漫游 - 實(shí)驗(yàn)，迭代和改進(jìn)，以及來自客戶的寶貴見解 - 使我們能夠找到僅在18個(gè)月前推出的SageMaker。 SageMaker消除了機(jī)器學(xué)習(xí)過程中每個(gè)步驟的繁重，復(fù)雜性和猜測(cè) - 使AI民主化。如今，成千上萬的客戶正在使用SageMaker在AWS之上構(gòu)建機(jī)器學(xué)習(xí)模型。我們繼續(xù)加強(qiáng)服務(wù)，包括增加新的強(qiáng)化學(xué)習(xí)能力。強(qiáng)化學(xué)習(xí)有著陡峭的學(xué)習(xí)曲線和許多活動(dòng)部分，直到現(xiàn)在，除了資金最充足的技術(shù)組織之外，其他所有部分都遠(yuǎn)遠(yuǎn)超出了它。如果沒有好奇心的文化以及愿意代表客戶嘗試全新的事物，這一切都不可能實(shí)現(xiàn)?？蛻粽陧憫?yīng)以客戶為中心的探索和傾聽 - 現(xiàn)在，AWS已經(jīng)實(shí)現(xiàn)了300億美元的年度運(yùn)營(yíng)業(yè)務(wù)收入并且增長(zhǎng)迅速。

Imagining the impossible

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.

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.

想象那些不可能的領(lǐng)域

亞馬遜今天仍然是全球零售業(yè)的小型企業(yè)。我們代表零售市場(chǎng)的低個(gè)位數(shù)百分比，而且我們經(jīng)營(yíng)的每個(gè)國(guó)家都有更大的零售商。這主要是因?yàn)榻?0％的零售業(yè)仍然在實(shí)體商店中（線下）。多年來，我們一直在考慮如何為實(shí)體店中的客戶提供服務(wù)，但我們認(rèn)為我們首先需要發(fā)明能夠真正讓客戶滿意的環(huán)境。通過亞馬遜Go，我們有一個(gè)清晰的愿景。擺脫實(shí)體零售最糟糕的事情：結(jié)賬線（收銀）。沒有人喜歡排隊(duì)等候。相反，我們想象一個(gè)商店，你可以走進(jìn)去，拿起你想要的東西，然后離開。

實(shí)現(xiàn)這些想象很難。技術(shù)上很難。它需要全世界數(shù)百名智能，專注的計(jì)算機(jī)科學(xué)家和工程師的努力。我們必須設(shè)計(jì)和構(gòu)建我們自己的專有相機(jī)和架子，并發(fā)明新的計(jì)算機(jī)視覺算法，包括將來自數(shù)百個(gè)合作相機(jī)的圖像拼接在一起的能力。而且我們必須以一種技術(shù)運(yùn)作良好的方式來實(shí)現(xiàn)它，它簡(jiǎn)單地退回到業(yè)務(wù)場(chǎng)景中。這個(gè)項(xiàng)目的回報(bào)則是客戶的回應(yīng)，他們將在亞馬遜Go購物的體驗(yàn)描述為“神奇的”。我們現(xiàn)在在芝加哥，舊金山和西雅圖擁有10家商店，并對(duì)未來感到興奮。

Failure needs to scale too

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.

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.

既便是失敗也需要擴(kuò)展

隨著公司的發(fā)展，一切都需要擴(kuò)展，包括失敗實(shí)驗(yàn)的規(guī)模。如果你的失敗的規(guī)模沒有增長(zhǎng)，你就不會(huì)有更多細(xì)致發(fā)明。如果偶爾有數(shù)十億美元的失敗，亞馬遜將以適當(dāng)?shù)囊?guī)模為我們規(guī)模的公司進(jìn)行試驗(yàn)。當(dāng)然，我們不會(huì)冒進(jìn)進(jìn)行這樣的實(shí)驗(yàn)。我們將努力使他們做出好的賭注，但并非所有好的賭注都會(huì)最終付出代價(jià)。這種大規(guī)模的風(fēng)險(xiǎn)承擔(dān)是我們作為大公司可以為我們的客戶和社會(huì)提供的服務(wù)的一部分。對(duì)于股東來說，好消息是，一次大贏的賭注可以彌補(bǔ)許多次失敗的成本。

Fire手機(jī)和Echo的開發(fā)大約在同一時(shí)間開始。雖然Fire手機(jī)失敗了，但我們能夠接受我們的學(xué)習(xí)（以及開發(fā)人員）并加快我們構(gòu)建Echo和Alexa的工作。 Echo和Alexa的愿景受到了星際迷航計(jì)算機(jī)的啟發(fā)。這個(gè)想法也起源于我們多年來一直在建設(shè)和徘徊的另外兩個(gè)領(lǐng)域：機(jī)器學(xué)習(xí)和云計(jì)算。從亞馬遜早期開始，機(jī)器學(xué)習(xí)是我們產(chǎn)品推薦的重要組成部分，AWS為我們提供了云端功能的前排座位。經(jīng)過多年的發(fā)展，Echo于2014年首次亮相，由AWS云中的Alexa提供支持。

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.”

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!

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.

沒有客戶具體要求Echo應(yīng)該如何。這絕對(duì)是我們自身的徘徊。市場(chǎng)研究并沒有多少幫助。如果你在2013年去過一位顧客并且說“你想在你的廚房里放一個(gè)黑色的，永遠(yuǎn)在線的圓筒，大小與Pringles一樣，你可以和他們交談并提出問題，這也會(huì)打開你的燈光并播放音樂“我向你保證他們會(huì)奇怪地看著你說”不，謝謝你。“

自第一代Echo以來，客戶已經(jīng)購買了超過1億臺(tái)支持Alexa的設(shè)備。去年，我們將Alexa理解請(qǐng)求和回答問題的能力提高了20％以上，同時(shí)增加了數(shù)十億的事實(shí)，使Alexa比以往任何時(shí)候都更有智能。開發(fā)人員將Alexa技能的數(shù)量翻了一番，達(dá)到80,000以上，與2017年相比，2018年客戶對(duì)Alexa的數(shù)量增加了數(shù)十億次。與2018年Alexa內(nèi)置的設(shè)備數(shù)量相比增加了一倍多?，F(xiàn)在有超過150種不同的產(chǎn)品內(nèi)置Alexa，從耳機(jī)和PC到汽車和智能家居設(shè)備。還有更多！

最后還有一個(gè)很重要的是，正如我在20多年前的第一份股東信中所說，我們的重點(diǎn)是雇傭和留住能夠像主人翁一樣思考的多才多藝的員工。實(shí)現(xiàn)這一目標(biāo)需要對(duì)我們的員工進(jìn)行投資，而且，與亞馬遜的許多其他事情一樣，我們不僅使用分析，還使用直覺和內(nèi)心來尋找前進(jìn)的方向。

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.

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.

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.

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.

去年，我們將全美所有全職，兼職，臨時(shí)和季節(jié)性員工的最低工資提高到每小時(shí)15美元。這項(xiàng)工資上漲使超過250,000名亞馬遜員工以及超過100,000名季節(jié)性員工受益。去年假期在全國(guó)各地的亞馬遜網(wǎng)站工作。我們堅(jiān)信，當(dāng)我們投資于員工時(shí)，這將有利于我們的業(yè)務(wù)。但這不是推動(dòng)決定的原因。我們一直提供有競(jìng)爭(zhēng)力的工資。但我們認(rèn)為是時(shí)候領(lǐng)導(dǎo) - 提供超出競(jìng)爭(zhēng)力的工資。我們這樣做是因?yàn)樗坪跏钦_的做法。

今天，我挑戰(zhàn)我們的頂級(jí)零售競(jìng)爭(zhēng)對(duì)手（你知道你是誰?。?，以匹配我們的員工福利和15美元的最低工資。做吧！更好的是，提高到16美元，然后向我們發(fā)出挑戰(zhàn)。這是一種有益于每個(gè)人的競(jìng)爭(zhēng)。

我們?yōu)閱T工介紹的許多其他計(jì)劃都是從頭腦中獲得的。我在職業(yè)選擇計(jì)劃之前已經(jīng)提到過，該計(jì)劃向合格的學(xué)習(xí)領(lǐng)域的證書或文憑支付高達(dá)95％的學(xué)費(fèi)和費(fèi)用，導(dǎo)致我們的員工需要職業(yè)生涯，即使這些職業(yè)將他們帶離亞馬遜。現(xiàn)在已有超過16,000名員工利用該計(jì)劃，該計(jì)劃將繼續(xù)增長(zhǎng)。同樣，我們的職業(yè)技能計(jì)劃包括培訓(xùn)關(guān)鍵工作技能，如簡(jiǎn)歷寫作，如何有效溝通和計(jì)算機(jī)基礎(chǔ)知識(shí)。去年10月，為了履行這些承諾，我們簽署了總統(tǒng)對(duì)美國(guó)工人的承諾，并宣布我們將通過我們的創(chuàng)新培訓(xùn)計(jì)劃提高50,000名美國(guó)員工的工資。

我們的投資不僅限于現(xiàn)有員工，甚至不限于現(xiàn)在。為了培訓(xùn)明天的員工隊(duì)伍，我們承諾提供5000萬美元，包括通過我們最近宣布的亞馬遜未來工程師計(jì)劃，支持全國(guó)各地的小學(xué)，高中和大學(xué)學(xué)生的STEM和CS教育，特別注重吸引更多女孩和少數(shù)民族對(duì)這些職業(yè)。我們還繼續(xù)利用退伍軍人的優(yōu)秀才能。我們正在努力履行我們?cè)?021年之前雇用25,000名退伍軍人和軍人配偶的承諾。通過亞馬遜技術(shù)退伍軍人學(xué)徒計(jì)劃，我們?yōu)樵朴?jì)算等領(lǐng)域的退伍軍人提供在職培訓(xùn)。

網(wǎng)絡(luò)搜索結(jié)果

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!

As always, I attach a copy of our original 1997 letter. It remains Day 1.

Sincerely,

Jeffrey P. Bezos

Founder and Chief Executive Officer

Amazon.com, Inc.

非常感謝我們的客戶，讓我們有機(jī)會(huì)為您提供服務(wù)，同時(shí)始終挑戰(zhàn)我們可以做得更好，感謝我們的股東所提供持續(xù)的支持，以及感謝我們?nèi)w員工的辛勤工作和開拓精神。亞馬遜各地的團(tuán)隊(duì)都在傾聽客戶的聲音，并為客戶而探索！

和往常一樣，我附上1997年原始信件的副本。它仍然是第1天。

此致

杰弗里P.貝索（佐）斯

創(chuàng)始人兼首席執(zhí)行官

亞馬遜公司