Work Rules!: Insights from Inside Google That Will Transform How You Live and Lead

by Laszlo Bock

“When employees trust the leadership, they become brand ambassadors and in turn cause progressive change in their families, society, and environment. The return on investment to business is automatic, with greater productivity, business growth, and inspired customers.”

We deliberately take power and authority over employees away from managers.

Performance improved only when companies implemented programs to empower employees (for example, by taking decision-making authority away from managers and giving it to individuals or teams), provided learning opportunities that were outside what people needed to do their jobs, increased their reliance on teamwork (by giving teams more autonomy and allowing them to self-organize), or a combination of these.

All it takes is a belief that people are fundamentally good—and enough courage to treat your people like owners instead of machines. Machines do their jobs; owners do whatever is needed to make their companies and teams successful.

“All happy families resemble one another.”v All successful organizations resemble one another as well. They possess a shared sense not just of what they produce, but of who they are and want to be. In their vision (and perhaps hubris), they’ve thought through not just their origin, but also their destiny.

“People interpret strong cultures based on the artifacts, because they’re the most visible, but the values and assumptions underneath matter much more.”

Having workers meet the people they are helping is the greatest motivator, even if they only meet for a few minutes. It imbues one’s work with a significance that transcends careerism or money.

We all want our work to matter. Nothing is a more powerful motivator than to know that you are making a difference in the world.

If you believe people are good, you must be unafraid to share information with them

A few weeks into every quarter, our executive chairman, Eric Schmidt, walks the company through the same presentation that the board of directors saw just days before.

One of the serendipitous benefits of transparency is that simply by sharing data, performance improves.

Bridgewater Associates, the world’s largest hedge fund with $145 billion in assets,56 takes one such approach: Every meeting is recorded and made available to all employees. Bridgewater’s founder, Ray Dalio, explains: “My most important principle is that getting at the truth … is essential for getting better. We get at truth through radical transparency and putting aside our ego barriers in order to explore our mistakes and personal weaknesses so that we can improve.”

It’s almost impossibly difficult to take an average performer and through training turn them into a superstar.

One of the controversial insights. Not sure how I feel about it. Need to think/ analyze more.

Companies then turn vice into virtue by bragging about how much they spend on training. But since when is spending a measure of quality results? Do people boast, “I’m in great shape—I spent $500 on my gym membership this month?” The presence of a huge training budget is not evidence that you’re investing in your people. It’s evidence that you failed to hire the right people to begin with.

Only 10 percent of your applicants (at best!) will be top performers, so you go through far more applicants and interviews.

“A top-notch engineer is worth three hundred times or more than an average engineer. … I’d rather lose an entire incoming class of engineering graduates than one exceptional technologist.”

How can you tell if you have found someone exceptional? My simple rule of thumb—and the second big change to make in how you hire—is: “Only hire people who are better than you.”

“The broader failing of McKinsey and its acolytes at Enron is their assumption that an organization’s intelligence is simply a function of the intelligence of its employees. They believe in stars, because they don’t believe in systems.”

The lesson of “The Talent Myth” was not “Don’t hire smart people.” It was “Don’t hire exclusively for smarts.” Sound advice.

Interesting!

In the mid-2000s, interviewers could ask candidates any questions they wanted, but they didn’t follow any particular structure, so their feedback often lacked insight. The absence of coordination across interviewers also meant we often forgot to ask about some specific attribute, so the candidate had to come back for yet more interviews.

Our overreliance on referrals had simply started to exhaust Googlers’ networks. In response, we started introducing “aided recall” exercises.

Every interviewer sees a record of the interview scores they have given in the past and whether those people were hired or not.

The most common feedback from Larry is that a candidate might not meet our hiring bar or that the creativity shown in a portfolio might not be up to snuff.

Take power from your managers and trust your people to run things

Remember that the primary definition of “asylum” is “a place of refuge.” One of the nobler aspirations of a workplace should be that it’s a place of refuge where people are free to create, build, and grow.

In Japan there’s a saying: Deru kugi wa utareru. “The stake that sticks up gets hammered down.”

This is why we take as much power away from managers as we can. The less formal authority they have, the fewer carrots and sticks they have to lord over their teams, and the more latitude the teams have to innovate.

For example, as a practical matter there are really only four meaningful, visible levels at Google: individual contributor, manager, director, and vice president.

Our most senior executives receive only the same benefits, perquisites, and resources as our newest hires. There are no executive dining rooms, parking spots, or pensions.

That’s not fair, argued the engineers, because the first person received $20,000 in bonus, while the second had contributed the same impact but was paid only $18,000. So, at their request, we changed the basis for bonus calculation from actual salaries to the median salary of all people in that job.

innovation (maintaining an environment that values and encourages both relentlessly improving existing products and taking enormous, visionary bets), execution (launching high-quality products quickly), and retention (keeping the people we want to keep).

Edwin Locke and Gary Latham, in their 1990 book A Theory of Goal Setting & Task Performance, showed that difficult, specific goals (“Try to get more than 90 percent correct”) were not only more motivating than vague exhortations or low expectations (“Try your best”), but that they actually resulted in superior performance. It therefore makes sense to expect a lot of people.

“If you set a crazy, ambitious goal and miss it, you’ll still achieve something remarkable.”

Having goals improves performance.

The science on rating systems is inconclusive.115 There’s no strong evidence to suggest that having three or five or ten or fifty rating points makes a difference. Our 41-point scale came out of our engineering DNA. It felt satisfyingly precise to be able to draw a distinction between a 3.3 and a 3.4 performer. And when you averaged ratings over many quarters, you could calculate ratings finely enough to sort a 3.325 from a 3.350 performer.

For example, we polled Googlers about what to label our performance categories, and more than 4,200 votes were cast. The clearest trend was a desire for seriousness and clarity, not whimsy.

Calibration adds a step. But it is critical to ensure fairness. A manager’s assessments are compared to those of managers leading similar teams, and they review their employees collectively: A group of five to ten managers meet and project on a wall their fifty to a thousand employees, discuss individuals, and agree on a fair rating.

First, set goals correctly. Make them public. Make them ambitious. Second, gather peer feedback. There is a range of online tools, not the least of which is Google Sheets, that allows you to create surveys and compile the results.

Third, for evaluation, adopt some kind of calibration process. We prefer meetings where managers sit together and review people as a group. It takes more time, but it gives you a reliable, just process for assessment and decision-making.

Fourth, split reward conversations from development conversations. Combining the two kills learning. This holds true at companies of any size.

“instead of a massive group of average performers dominating … through sheer numbers, a small group of elite performers [dominate] through massive performance.”

Professor Boris Groysberg of Harvard Business School found that “star analysts suffer an immediate and lasting decline in performance” when they move to a new company.

Their prior success had been dependent on their coworkers, resources available to them, their fit with the company’s culture, and even the personal reputation or brand they had built up.

Googlers with the best managers did 5 to 18 percent better on a dozen Googlegeist dimensions when compared to those managed by the worst manager.

Training is, quite simply, one of the highest-leverage activities a manager can perform. Consider for a moment the possibility of your putting on a series of four lectures for members of your department.

In 1959, Donald Kirkpatrick, who was a professor at the University of Wisconsin and past president of the American Society for Training and Development, came up with a model that prescribed four levels of measurement in learning programs: reaction, learning, behavior, and results.

Robert Frank and Philip Cook predicted in their 1995 book The Winner-Take-All Society that more and more jobs would be characterized by growing compensation inequality, as the best people became increasingly discoverable and mobile, and therefore more able to claim a greater share of the value they create for their employers.

The biggest difference between a normal (also known as a Gaussian) and a power law distribution is that, for some phenomena, normal distributions massively underpredict the likelihood of extreme events.

At Google, we do have situations where two people doing the same work can have a hundred times difference in their impact, and in their rewards. For example, there have been situations where one person received a stock award of $10,000, and another working in the same area received $1,000,000. This isn’t the norm, but the range of rewards at almost any level can easily vary by 300 to 500 percent, and even then there is plenty of room for outliers. In fact, we have many cases where people at more “junior” levels make far more than average performers at more “senior” levels.

To make these kinds of extreme rewards work, you need two capabilities. One is a very clear understanding of what impact is derived from the role in question (which requires a complementary awareness of how much is due to context: Did the market move in a lucky way? How much of this was a result of a team effort or the brand of the company? Is the achievement a short-or long-term win?).