Working Backwards: Insights, Stories, and Secrets from Inside Amazon

by Colin Bryar

You’ll notice a pattern of trial and error with metrics in the points above, and this is an essential part of the process. The key is to persistently test and debate as you go.

A big mistake people make is not getting started. Most WBRs have humble beginnings and undergo substantial changes and improvement over time.

But the Analyze stage is all about developing a comprehensive understanding of what drives your metrics. Until you know all the external factors that impact the process, it will be difficult to implement positive changes.

When Amazon teams come across a surprise or a perplexing problem with the data, they are relentless until they discover the root cause. Perhaps the most widely used technique at Amazon for these situations is the Correction of Errors (COE) process, based upon the “Five Whys” method developed at Toyota and used by many companies worldwide.

Another thing that can happen in this stage is that you’ll identify processes that can be automated. Once a process is well understood and the decision-making logic can be encoded in software or hardware, it’s a potential candidate for automation. Forecasting and purchasing are two examples of processes that were eventually automated at Amazon. It took years of collaborative effort among category buyers and software engineers—and involving plenty of trial and error—to automate the forecasting and purchasing decisions across the hundreds of millions of products in Amazon’s catalog. But it’s now done with greater accuracy than even a large team of buyers could do manually.

Emerging patterns are a key point of focus. Individual data points can tell useful stories, especially when compared to other time periods. In the WBR, Amazon analyzes trend lines to highlight challenges as they emerge rather than waiting for them to be summed up in quarterly or yearly results.

Anecdotes and exception reporting are woven into the deck. One trait of an Amazon WBR deck that people often remark upon is the liberal use of two tools: anecdotes and exception reporting—that is, the description of an element that falls outside some standard or usual situation. Both tools enable you to dive into examples that contain something that doesn’t follow the natural or accustomed patterns and that can sometimes, but not always, reveal a defect, a broken process, or a problem with system logic. The use of anecdotes and exception reporting has enabled leaders to audit at scale in a very detailed way. This ability to flag, evaluate, examine, dig deep, and seek specific solutions for a wide range of issues in a very large organization is something we’ve noticed is uniquely Amazonian, and it’s helpful for small and large businesses alike.

Yes, executives know their output metrics backward and forward. But if they don’t continue to focus on inputs, they lose control over and visibility into the tools that generate output results. Therefore, at Amazon, everyone from the individual contributor to the CEO must have detailed knowledge of input metrics to know whether the organization is maximizing outputs.

Numerical data become more powerful when combined with real-life customer stories. The Dive Deep leadership principle states, “Leaders operate at all levels, stay connected to the details, audit frequently, and are skeptical when metrics and anecdotes differ. No task is beneath them.”

Controllable input metrics are a quantitative (diving deep with data) and qualitative (anecdotes) way of measuring how well the organization is satisfying these customer interests so that the output metrics trend the way the company desires. Properly evaluating your business and striving to improve each week requires a willingness to openly discuss failures, learn from them, and always look for inventions that will delight customers even more.

Bill gets an unwelcome assignment. Amazon’s move to digital as an example of Working Backwards. Can Amazon build hardware? To outsource, or not to outsource? Building a device that gets out of the reader’s way. The launch and a boost from Oprah.

Over our long march to building Amazon’s digital business, we proved a powerful lesson: it takes exceptionally patient and unwavering leadership to persevere through the prolonged process of building a new business and navigating through transformative times in an established industry with entrenched interests. The fact that we entered as total beginners and emerged as industry leaders is in no small part a result of our adherence to being Amazonian in our principles and our way of thinking, including thinking big, thinking long-term, being obsessed with customers, being willing to be misunderstood for long periods of time, and being frugal—principles that few companies are capable of maintaining in the face of quarterly reporting requirements and the daily gyrations of the stock market. Many companies with a lot more capital than Amazon had at the time tried and failed to build a digital business. Even if your company is smaller than your competitors, adhering to these principles will enable you to punch above your weight.

In other words, his first action was not a “what” decision, it was a “who” and “how” decision. This is an incredibly important difference. Jeff did not jump straight to focusing on what product to build, which seems like the straightest line from A to B. Instead, the choices he made suggest he believed that the scale of the opportunity was large and that the scope of the work required to achieve success was equally large and complex. He focused first on how to organize the team and who was the right leader to achieve the right result.

None of us, including Jeff, knew exactly what we would end up building; it’s more like we stuck with the process and surrendered to where it was taking us. Prime was a perfect example of the multicausal, nonlinear way in which business initiatives both major and minor got decided on and executed at Amazon. Correspondingly, we can’t tell a linear story of how we came up with Prime because there isn’t one. Instead, this chapter will reflect that there were a lot of little tributaries that emptied into the river of Prime.

A larger company might address its slowing-growth problem in a more dramatic way, perhaps by making an acquisition of another company, with the goal of creating a big jump in sales (though maybe not profit). But for Amazon at the time, there were few, if any, mergers or large acquisitions that made sense. All the e-tailers we might have bought were small, and their acquisition would not have moved our sales needle appreciably. Buying an offline retailer made no sense—although it might increase the number of customers, it would burden us with the brick-and-mortar costs and inefficiencies we wanted to avoid. Either of those actions carried the very real risk of becoming a resource-consuming internal distraction. We needed to make a move that would convince more customers to shop online with us.

Relying on promotions over the long term can be a slippery slope for any retailer, especially one-off promotions. There is danger in training your customers to delay purchases until the next deal comes along.

Customer expectations are not static. They rise over time, which means you cannot rest on your laurels.

The Kano Quality Model describes this well. https://asq.org/quality-resources/kano-model

We couldn’t even accurately estimate the cost, because our models could not really predict how customers would react, so we were relying more on judgment and educated guesses than on data.

The “October surprise” email arose out of his realization that you simply could not prove a priori that free shipping would work. You just had to try it.

world. Prime transformed Amazon from a fairly successful company in the e-commerce space to a top player in the retail space. And Prime changed the way people think about shopping online—and shopping, period.

At least I can say it embodied the “vocally self-critical” aspect of the Earn Trust leadership principle. In any other company, I probably would have been fired. Fortunately for me, Amazon’s commitment to long-term thinking includes its investment in people. They understand that when you innovate and build new things, you will frequently fail. If you fire the person, you lose the benefit of the learning that came along with that experience. Jeff would say something like this to a leader who had just laid an egg: “Why would I fire you now? I just made a million-dollar investment in you. Now you have an obligation to make that investment pay off. Figure out and clearly document where you went wrong. Share what you have learned with other leaders throughout the company. Be sure you don’t make the same mistake again, and help others avoid making it the first time.”

How? A streaming subscription service is a fixed-cost business. When Netflix licensed a movie or TV series from a studio, they paid a fixed fee. The amount was not based on usage. Netflix customers could watch the video once or ten million times, the costs were the same. Yes, there were some variable costs involved, for bandwidth and servers, but these costs amounted to pennies per view. And, as with most technology, those costs declined over time. The cost structure is very different from the DVD rental-by-mail business, where the costs—warehouses, wages, shipping, replacement discs—are variable. The major benefit of establishing a popular subscription service with a fixed-cost base is that once you exceed a certain number of subscribers, every new dollar of subscription revenue is pure profit. The hard parts of pulling off this strategy are (a) acquiring a large number of subscribers, and (b) building a catalog of must-see movies and TV series. By integrating Prime Video into the already large and growing Prime customer base we had a leg up on solving the first problem. We were less concerned about the poor initial selection because our time horizon for success was measured in years. We were confident that, given time, we could make the right investments and assemble a great selection of movies and TV series. If we did this well, customers would eventually be attracted to Prime, not only for the fast free shipping but also for the streaming videos included in the fee.

AWS A new class of customers. The origins of AWS in data sharing with affiliates. Colin gets “the call” from Jeff, who comes on board. Eight people attend the first software developer conference. How the Invent and Simplify leadership principle enabled Amazon to become the leader in web services. How we used the Working Backwards process to create AWS.

As we’ve already seen, in the early 2000s, the transformation from physical media to digital media posed an existential threat to Amazon’s business. Roughly 75 percent of Amazon’s business at that time consisted of selling physical books, CDs, and DVDs to customers. We had to invent or risk becoming an irrelevant has-been in media sales. Also, while hugely successful, Amazon Prime was essentially an extension (albeit a very large one) of our existing online physical media retail business.

In this chapter we will not provide a comprehensive story about the origins and history of AWS. That subject could fill a whole book in itself. Instead, we will attempt to answer the following two questions, which can help you incorporate key elements of being Amazonian into your organization: What elements of being Amazonian enabled Amazon to move into this completely separate line of business? Why was Amazon able to master cloud computing well before its potential competitors, including entrenched companies with large businesses to protect and well-capitalized web-based tech companies?

Being Amazonian Beyond Amazon Being Amazonian in your business. Being Amazonian means having to change habits and ways of doing things, deferring gratification, and persisting through challenging times, but also reaping distinct rewards. How to start being Amazonian wherever you are.

Even when a project does not achieve its goals or is deemed a failure, if the effort was admirable and adherent to Amazon practices and principles, the result for the individual is neither dismissal nor shame. Failure is almost always understood as the failure of a group, a process, a system, as much as that of a single person—many people have been involved, made comments, shaped the idea, and given approvals along the way. For the company, then, failure is typically viewed as an experiment from which a great deal can be learned that can lead to change and improvement. Very often, failure is temporary and eventually gives birth to success.