Despite the letters being written for 20 years, 2 decades, there were some themes that held consistent:
1997: Window of opportunity…
We have a window of opportunity as larger players marshal the resources to pursue the online opportunity and as customers, new to purchasing online, are receptive to forming new relationships… Our goal is to move quickly to solidify and extend our current position while we begin to pursue the online commerce opportunities in other areas.
1997: Long term focussed on cash flows
We will continue to make investment decisions in light of long-term market leadership considerations rather than short-term profitability considerations or short-term Wall Street reactions… 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.
1997: Sense of urgency
Though we are optimistic, we must remain vigilant and maintain a sense of urgency. The challenges and hurdles we will face to make our long-term vision for Amazon.com a reality are several: aggressive, capable, well-funded competition; considerable growth challenges and execution risk; the risks of product and geographic expansion; and the need for large continuing investments to meet an expanding market opportunity.
1998: Bigger challenges ahead
Given what’s happened, it may be difficult to conceive, but we think the opportunities and risks ahead of us are even greater than those behind us. We will have to make many conscious and deliberate choices, some of which will be bold and unconventional.
1998: Hiring
During our hiring meetings, we ask people to consider three questions before making a decision:
2000: Long term focus
So, if the company is better positioned today than it was a year ago, why is the stock price so much lower than it was a year ago? As the famed investor Benjamin Graham said, “In the short term, the stock market is a voting machine; in the long term, it’s a weighing machine.” Clearly there was a lot of voting going on in the boom year of ’99—and much less weighing. We’re a company that wants to be weighed, and over time, we will be—over the long term, all companies are. In the meantime, we have our heads down working to build a heavier and heavier company.
2000: Real estate does not obey Moore’s Law
Price performance of processing power is doubling about every 18 months (Moore’s Law), price performance of disk space is doubling about every 12 months, and price performance of bandwidth is doubling about every 9 months. Given that last doubling rate, Amazon.com will be able to use 60 times as much bandwidth per customer 5 years from now while holding our bandwidth cost per customer constant. Similarly, price performance improvements in disk space and processing power will allow us to, for example, do ever more and better real-time personalization of our Web site.
2001: Customer focus elaborated
Amazon.com had been primarily built on two pillars of customer experience: selection and convenience. In July, as I already discussed, we added a third customer experience pillar: relentlessly lowering prices.
2004: Inventory turnover 7%!
We have a cash generative operating cycle because we turn our inventory quickly, collecting payments from our customers before payments are due to suppliers. Our high inventory turnover means we maintain relatively low levels of investment in inventory—$480 million at year end on a sales base of nearly $7 billion.
2005: Making decisions with numbers
Many of the important decisions we make at Amazon.com 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.
2005: Making decisions with judgement
Sometimes we have little or no historical data to guide us and proactive experimentation is impossible, impractical, or tantamount to a decision to proceed. Though data, analysis, and math play a role, the prime ingredient in these decisions is judgment.
2005: Math-based decisions vs judgement-based devisions
Math-based decisions command wide agreement, whereas judgment-based decisions are rightly debated and often controversial, at least until put into practice and demonstrated. Any institution unwilling to endure controversy must limit itself to decisions of the first type. In our view, doing so would not only limit controversy —it would also significantly limit innovation and long-term value creation.
2005: Strong quantitative and analytical culture
You can count on us to combine a strong quantitative and analytical culture with a willingness to make bold decisions. As we do so, we’ll start with the customer and work backwards. In our judgment, that is the best way to create shareholder value.
2006: Growing businesses within
We have many people at our company who have watched multiple $10 million seeds turn into billion dollar businesses. That first-hand experience and the culture that has grown up around those successes is, in my opinion, a big part of why we can start businesses from scratch. The culture demands that these new businesses be high potential and that they be innovative and differentiated, but it does not demand that they be large on the day that they are borns.
2009: customers and long term
Taken as a whole, the set of goals is indicative of our fundamental approach. Start with customers, and work backwards. Listen to customers, but don’t just listen to customers – also invent on their behalf. We can’t assure you that we’ll meet all of this year’s goals. We haven’t in past years. However, we can assure you that we’ll continue to obsess over customers. We have strong conviction that that approach – in the long term – is every bit as good for owners as it is for customers.
2010: No textbook solution
And while many of our systems are based on the latest in computer science research, this often hasn’t been sufficient: our architects and engineers have had to advance research in directions that no academic had yet taken. Many of the problems we face have no textbook solutions, and so we – happily – invent new approaches.
2010: Inter-operability
Our technologies are almost exclusively implemented as services: bits of logic that encapsulate the data they operate on and provide hardened interfaces as the only way to access their functionality. This approach reduces side effects and allows services to evolve at their own pace without impacting the other components of the overall system. Service-oriented architecture – or SOA – is the fundamental building abstraction for Amazon technologies.
2010: Machine learning
Rule- based systems can be used successfully, but they can be hard to maintain and can become brittle over time. In many cases, advanced machine learning techniques provide more accurate classification and can self-heal to adapt to changing conditions.
2010: R&D integrated
All the effort we put into technology might not matter that much if we kept technology off to the side in some sort of R&D department, but we don’t take that approach. Technology infuses all of our teams, all of our processes, our decision-making, and our approach to innovation in each of our businesses. It is deeply integrated into everything we do.
2015: Company culture
You can write down your corporate culture, but when you do so, you’re discovering it, uncovering it – not creating it. It is created slowly over time by the people and by events – by the stories of past success and failure that become a deep part of the company lore.
2016: Process as a 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.
2016: 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…
2016: 70% info
Second, most decisions should probably be made with somewhere around 70% of the information you wish you had. If you wait for 90%, 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.
2016: Disagree and commit
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.