Working Backwards: Insights, Stories, and Secrets from Inside Amazon
Colin Bryar
Top 10 Best Quotes
“The best way to fail at inventing something is by making it somebody’s part-time job.”
“The NPI process was deflating for morale. But figuring out how to “boost morale” is not Amazonian. Other companies have morale-boosting projects and groups with names like “Fun Club” and “Culture Committee.” They view morale as a problem to be solved by company-sponsored entertainment and social interaction. Amazon’s approach to morale was to attract world-class talent and create an environment in which they had maximum latitude to invent and build things to delight customers”
“the Amazon hiring process has a flywheel effect—it pays greater and greater dividends the longer it is used. Ideally, the bar continues to be set higher, so much that, eventually, employees should be able to say to themselves, “I’m glad I joined when I did. If I interviewed for a job today, I’m not sure I’d be hired!”
“start by defining the customer experience, then iteratively work backwards from that point until the team achieves clarity of thought around what to build.”
“our explosive growth was slowing down our pace of innovation. We were spending more time coordinating and less time building. More features meant more software, written and supported by more software engineers, so both the code base and the technical staff grew continuously. Software engineers were once free to modify any section of the entire code base to independently develop, test, and immediately deploy any new features to the website. But as the number of software engineers grew, their work overlapped and intertwined until it was often difficult for teams to complete their work independently. Each overlap created one kind of dependency, which describes something one team needs but can’t supply for itself. If my team’s work requires effort from yours—whether it’s to build something new, participate, or review—you’re one of my dependencies. Conversely, if your team needs something from mine, I’m a dependency of yours. Managing dependencies requires coordination—two or more people sitting down to hash out a solution—and coordination takes time. As Amazon grew, we realized that despite our best efforts, we were spending too much time coordinating and not enough time building. That’s because, while the growth in employees was linear, the number of their possible lines of communication grew exponentially. Regardless of what form it takes—and we’ll get into the different forms in more detail shortly—every dependency creates drag. Amazon’s growing number of dependencies delayed results, increased frustration, and disempowered teams.”
“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.”
“every résumé received from a female applicant automatically led to a phone screen. It’s important to say that this solution did not lower the hiring bar, nor did it favor unqualified candidates on the basis of gender. If the candidate did not pass the phone screen, they would not move forward to the next step in the process. This technique made it clear that when a candidate’s name implied the gender as female, an unconscious bias had been affecting the résumé screening. The result was that well-qualified female candidates were apparently being rejected too early in the process.”
“every new hire should “raise the bar,” that is, be better in one important way (or more) than the other members of the team they join. The theory held that by raising the bar with each new hire, the team would get progressively stronger and produce increasingly powerful results.”
“With all other things being equal, the organization that moves faster will innovate more, simply because it will be able to conduct a higher number of experiments per unit of time.”
“When you encounter a problem, the probability you’re actually looking at the actual root cause of the problem in the initial 24 hours is pretty close to zero, because it turns out that behind every issue there’s a very interesting story.” In the end, if you stick with identifying the true root causes of variation and eliminating them, you’ll have a predictable, in-control process that you can optimize.”
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