Why Jeff Bezos recommends scaling failures and watching science fiction
Jeff Bezos, Amazon CEO, wrote an annual letter to shareholders , and RUSSOL startup school volunteers and Y Combinator initiatives translated it into Russian to answer these questions and inspire readers to create their Amazon.
Jeff Bezos, Amazon CEO Photo Source: flickr.com
Jeff Bezos, April 11, 2019
To our shareholders.
Something strange and important has happened in the last 20 years. Take a look at these numbers:
2015 51 %
Percentages show the share of gross sales of products on Amazon by independent third-party sellers. And these are mainly indicators of small and medium-sized businesses (the rest is from Amazon’s own retail sales). Independent sellers' sales grew from 3% to 58%.
Third-party sellers are robust so they kicked our ass
This is a high bar because our primary business has grown significantly: from $ 1.6 billion in 1999 to $ 117 billion last year. The total average annual growth rate (CAGR) of our business over this period amounted to 25%. At the same time, third-party sales increased from $ 0.1 billion to $ 160 billion - in their case, the combined average annual growth rate was 52%. To understand the scale: over the same period on eBay, with an increase in gross sales from $ 2.8 to $ 95 billion, CAGR grew by only 20%.
Why did third-party sellers on Amazon have an order of magnitude better dynamics than eBay? And why were their growth rates much higher than those of Amazon itself, with its level of sales organization? There is no definite answer to this question, but something will help us get closer to it.
We have helped independent sellers compete with our own business by offering them the best selling tools we could create. These are opportunities for sellers to manage inventory, process payments, track deliveries, create reports, and sell abroad — and we supplement them every year. The fulfillment (the complex of operations from order to delivery) and the Amazon Prime client program are of great importance. Together, these two programs have significantly improved the quality of services received by the client when purchasing from third parties.
Now that these two programs have become normal practice, it’s hard for people to fully realize how revolutionary they were at the time of launch. By investing in them, we went to great financial risks. The whole time we tested different ideas, the project required investments. We could not predict with certainty what these programs would turn out to be, but we moved forward, relying on intuition and promptings of the heart, helping our projects to come true with our optimism.
Intuition, curiosity and the influence of wanderings
Since Amazon was created, we have known that we want to build a culture of creators - a culture of curious people and researchers who like to invent. Even as experts, they are open to new experiences and think like beginners. They look at the situation as something temporary. A creative worldview helps us to approach great and difficult to solve opportunities. And we are convinced that the path to success lies through iteration: invention, launch, rethinking, restarting, repeating - again and again. Creators know that success can be achieved through a winding path.
Sometimes (or rather, often) in business you know what you are going to, in which case your actions will be effective. Develop a plan and follow it. Wandering in business is inefficient, but it is also not accidental. The search is guided by foreboding, intuition, curiosity and is fueled by a deep conviction that the benefits that customers will receive will be large enough to deviate slightly and wander on the way to it. This wandering is an important counterweight to efficiency. You need both. Large-scale discoveries, knocking out of the common “line”, are likely to require such wanderings.
Among the millions of customers of Amazon Web Services (AWS), there are both startups and corporations, both state-owned companies and non-profit organizations. Each of them wants to create the best solutions for their users. We spend a lot of time understanding what these organizations and their employees want - developers, operations managers, directors for digital technologies, directors for information security, etc.
The AWS we created is largely driven by customer feedback. It is important to ask customers what they need, carefully listen to their answers and plan a plan for thoughtful and quick (speed is important in business!) Work. No company can succeed without making the customer a priority. But this is not enough. Needs play a key role, but the customer does not know how to explain them. We must invent by putting ourselves in their place. Engage your imagination to understand what customers might need.
AWS itself as a whole serves as an example. No one asked us to run him. No one. But it turned out that such a service turned out to be necessary and in demand, just no one knew about it. We had guesses, we took upon ourselves financial risks and began to create - to process, experiment and try countless times.
In the case of AWS, the same scenario occurred several times. For example, we came up with DynamoDB - a well-scalable key-value database with a low degree of delay, which is now used by thousands of users of the service. Closely listening to the opinions of customers, we heard that companies have faced the limitations of their database providers and have worked for decades with inconvenient solutions: expensive, patented, tied to a supplier and penalties.
We spent several years creating our Amazon Aurora database engine, fully managed by MySQL, compatible with PostgreSQL. This service with stability and access conditions is not worse, or even better than commercial mechanisms, which, at the same time, was 10 times cheaper. No wonder our solution worked.
But we were also optimistic about specialized databases. Over the past 20-30 years, companies mainly solve their problems using relational databases. Due to the fact that developers are very familiar with relational databases, they were used everywhere: where possible and impossible. Although the sizes of the databases were not optimal and the query processing speed was high, you could make them work.
But today, many applications need to store huge amounts of data - terabytes and petabytes. Application requirements have also changed. Now applications are developing in the context of a short waiting period, real-time processing and the need to process millions of requests per second. And these are not only key-value stores like DynamoDB, but also RAM databases like Amazon ElastiCache, time series databases like Amazon Timestream, registry solutions like Amazon Quantum Ledger Database. All these are tools for effective work, saving money and quickly promoting your product on the market.
We also teach companies how to use machine learning technology. We have been working on this for a long time, but our attempts to make available some of the internal tools of machine learning have not been successful. It took years to search - we experimented, tried different versions, refined, listened to valuable insights from our customers, before we got SageMaker, which we launched a year and a half ago. SageMaker struggles with congestion, complexity and random movement at all levels - this is a democratic version of artificial intelligence.
Today, thousands of our customers build machine learning models in AWS using the SageMaker tool. We continue to improve the service - including by adding new training opportunities. Optimized learning involves a steep learning curve with lots of moving components. Until recently, such a tool was exclusively available only to technically advanced organizations with good funding. Change is made possible by a culture of curiosity and a willingness to try new things when we put ourselves in the shoes of our customers. Customer-oriented searches have received market feedback - AWS is now valued at $ 30 billion a year and continues to grow rapidly.
Presenting the unimaginable
Amazon today is still a small player in the global retail field. We occupy less than 10% of the retail market and in every country where we operate, there are retailers with most of the market. And, mainly, this is explained by the fact that 90% of sales are still ordinary offline stores. For many years, we thought we could do for people in ordinary stores, but it seemed to us that we first need to invent something that can really delight consumers. And with Amazon Go, we had a clear idea: to get rid of the worst that is in offline retail - from the line to the cash register. No one likes to stand in line. Instead, we imagined a store where you can go, take what you need and leave.
It was not easy to come to this. Technically difficult. This required the efforts of hundreds of talented single-minded computer specialists and engineers around the world. We needed to design and produce our own cameras and shelves, and create new computer vision algorithms, including the ability to form an image, combining data from hundreds of connected cameras. And this had to be done in such a way that technology faded into the shadows, became invisible. The reward was customer reviews, who described Amazon Go's shopping experience as a “miracle." We currently have 10 stores in Chicago, San Francisco and Seattle, and we are looking forward to the future with enthusiasm.
Failures must scale too
With the growth of the company, everything should be scaled, including your failed experiments. If the scale of your failures does not increase, you cannot create something significant enough to move forward. For an Amazon sized company, experimenting on the right scale means periodically incurring multi-billion dollar losses. Of course, we will not experiment so uncontrollably. Naturally, we will work hard to ensure that our bets are played, but in the end, not all bets are winning. To take on such large-scale risks is part of the services we provide to clients and society. The good news for shareholders is that even one such successful bid covers the cost of failure.
Frame from the movie Star Trek. Photo Source: redshirtsalwaysdie.com
The development of Fire phone and Echo began around the same time. Although the Fire phone was a failure, we were able to use our experience (and programmers) and strengthen the development of Echo and Alexa. At Echo and Alexa, we were inspired by a computer from Star Trek. The idea also originates from two other areas where we have been creating and experimenting for many years: machine learning and cloud services. From the start of Amazon, machine learning has been a key component of our recommendations to users, and AWS has given us the opportunity to be in the forefront of cloud use. After many years of development in 2014, we released Echo with integrated Alexa, who lives in the AWS cloud.
None of the customers requested Echo. This was an example of our “wandering”. Marketing research will not help here. If you came to a client in 2013 and asked: “Would you like to have in your kitchen there is always a working black speaker the size of a can of Pringles chips, with which you can talk, ask her questions, and which can turn on the light and play music ? " I’m sure that they would look at you strangely and answer “No, thank you not.”
Since that first-generation Echo, customers have bought over 100 million devices that support Alex. Last year, we improved Alexa's ability to understand queries and answer questions by 20%, adding billions of facts to improve Alexa's knowledge. The developers doubled the number of Alex's skills to more than 80,000, and customers talked to her tens of billions of times more in 2018 than in 2017. The number of devices with Alex in 2018 was doubled. Now on the market there are more than 150 different devices with Alex available, from headphones and computers to cars and components of a smart home. And there will be more!
And the last thing I would like to say. As I said in my first letter to shareholders more than 20 years ago, our focus is on attracting and retaining diverse and talented employees who think like owners. To achieve this, investments in personnel and, like in many ways in Amazon, help here not only statistics, but intuition and heart are needed.
Last year, we raised our minimum hourly wage to $ 15 throughout the United States (for all full-time employees, hourly workers, temporary and seasonal workers). This jump in pay has affected more than 250,000 Amazon employees, as well as more than 100,000 seasonal workers who worked at Amazon centers nationwide on past holidays. But that was not the main thing for us in making this decision. We have always offered competitive pay. But now we decided that we need to be a leader - to offer payment without regard to competition. We did this because we think it is right.
Now I offer this challenge to all competitors in the retail sector (they themselves know who they are) to answer our offer on remuneration of employees and minimum wages. Let's! Make $ 16 and answer us. Such competition will benefit everyone.
Many other programs that we proposed to our employees also came from the heart, not from the head. I mentioned the Career Choice program earlier, when we pay 95% of the total cost of obtaining a certificate or diploma in selected areas so that our employees receive the required education, even if this education takes them away from the company. Over 16,000 employees have taken advantage of the program, which continues to grow. Our Career Skills program also allows hourly workers to gain knowledge in writing resumes, communication, and basic computer skills. Last October, we signed the Pledge to America's Workers, initiated by the US President, and committed ourselves to raising the skills of 50,000 of our workers.
Our investments are connected not only with our current employees. To prepare the future workforce, we invested $ 50 million, including through the Future Engineer Program to support education in the field of exact sciences and computer science in primary and secondary schools, as well as in universities, with special emphasis on attracting girls and minorities to the data professions. We also continue to use the potential of our veterans. We are on track to fulfill our commitment to hire 25,000 military veterans and wives by 2021. With the help of a special program, we provide them with on-the-job training in areas such as computing in the cloud.
I would like to thank our customers for giving us the opportunity to work for them, while encouraging us to become better, our shareholders for their constant support and all our employees around the world for their hard work and leadership spirit. The Amazon team listens to customers and seeks new ones for them.
As always, I am enclosing a copy of our first letter of 1997. It is still Day 1.
Translators and proofreaders: D. Demidova, CathBa, Yu. Yartsev, I. Zvyagin, A. Litvin
And one more thing. Here are 4 insights that I saw in Bezos's letter:
- Failures and mistakes are important. This is one of the surest ways to learn and grow. No need to worry that if I fail, then the price is worthless to me and it’s better not to do it. On the contrary, more systematic approaches with fails lead to higher chances of success.
- Художественную и особенно научную фантастику стоит читать и смотреть всем, кто хочет стать технологическим предпринимателем или быть частью прогрессивного. В подобной литературе можно многое почерпнуть и вдохновиться, как это сделали Амазон с умной колонкой Echo
- Наличие открытого API у любого хорошего продукта всегда ведет к росту пользователей. Это сработало для Amazon, вконтакте, Яндекс и др. В ДНК создаваемго продукта нужно сразу предусмотреть использование платформы сторонними разработчками.
- Если у американцев меньшинства это мексиканцы, то у нас таджики и узбеки. Избавившись от предубеждений и больше вкладываясь в них получим другой взгляд на решаемые проблемы и создаваемые продукты. Странам выгоднее иметь сотни тысяч первоклассных ИТ специалистов, нежели первоклассных «дворников», передающих профессию по наследству.
Примечание от автора публикации: Я Юрий, основатель некоммерческой школы стартапов RUSSOL, координирую инициативу по переводу курса лекций школы стартапов Y Combinator. Вместе с волонтерами и фрилансерами мы перевели и субтитровали 36 часов видео о создании стартапов, начиная с поиска идеи и заканчивая инвестициями и международными продажами. Материалы 2018 года тут, 2017 года — там.
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