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The Work Issue

What Google Learned From Its Quest to Build the Perfect Team

New research reveals surprising truths about why some work groups thrive and others falter.

Credit... Illustration by James Graham

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By Charles Duhigg

• Feb. 25, 2016

L ike most 25-year-olds, Julia Rozovsky wasn’t sure what she wanted to do with her life. She had worked at a consulting firm, but it wasn’t a good match. Then she became a researcher for two professors at Harvard, which was interesting but lonely. Maybe a big corporation would be a better fit. Or perhaps a fast-growing start-up. All she knew for certain was that she wanted to find a job that was more social. ‘‘I wanted to be part of a community, part of something people were building together,’’ she told me. She thought about various opportunities — Internet companies, a Ph.D. program — but nothing seemed exactly right. So in 2009, she chose the path that allowed her to put off making a decision: She applied to business schools and was accepted by the Yale School of Management.

When Rozovsky arrived on campus, she was assigned to a study group carefully engineered by the school to foster tight bonds. Study groups have become a rite of passage at M.B.A. programs, a way for students to practice working in teams and a reflection of the increasing demand for employees who can adroitly navigate group dynamics. A worker today might start the morning by collaborating with a team of engineers, then send emails to colleagues marketing a new brand, then jump on a conference call planning an entirely different product line, while also juggling team meetings with accounting and the party-planning committee. To prepare students for that complex world, business schools around the country have revised their curriculums to emphasize team-focused learning.

Every day, between classes or after dinner, Rozovsky and her four teammates gathered to discuss homework assignments, compare spreadsheets and strategize for exams. Everyone was smart and curious, and they had a lot in common: They had gone to similar colleges and had worked at analogous firms. These shared experiences, Rozovsky hoped, would make it easy for them to work well together. But it didn’t turn out that way. ‘‘There are lots of people who say some of their best business-school friends come from their study groups,’’ Rozovsky told me. ‘‘It wasn’t like that for me.’’

Instead, Rozovsky’s study group was a source of stress. ‘‘I always felt like I had to prove myself,’’ she said. The team’s dynamics could put her on edge. When the group met, teammates sometimes jockeyed for the leadership position or criticized one another’s ideas. There were conflicts over who was in charge and who got to represent the group in class. ‘‘People would try to show authority by speaking louder or talking over each other,’’ Rozovsky told me. ‘‘I always felt like I had to be careful not to make mistakes around them.’’

So Rozovsky started looking for other groups she could join. A classmate mentioned that some students were putting together teams for ‘‘case competitions,’’ contests in which participants proposed solutions to real-world business problems that were evaluated by judges, who awarded trophies and cash. The competitions were voluntary, but the work wasn’t all that different from what Rozovsky did with her study group: conducting lots of research and financial analyses, writing reports and giving presentations. The members of her case-competition team had a variety of professional experiences: Army officer, researcher at a think tank, director of a health-education nonprofit organization and consultant to a refugee program. Despite their disparate backgrounds, however, everyone clicked. They emailed one another dumb jokes and usually spent the first 10 minutes of each meeting chatting. When it came time to brainstorm, ‘‘we had lots of crazy ideas,’’ Rozovsky said.

One of her favorite competitions asked teams to come up with a new business to replace a student-run snack store on Yale’s campus. Rozovsky proposed a nap room and selling earplugs and eyeshades to make money. Someone else suggested filling the space with old video games. There were ideas about clothing swaps. Most of the proposals were impractical, but ‘‘we all felt like we could say anything to each other,’’ Rozovsky told me. ‘‘No one worried that the rest of the team was judging them.’’ Eventually, the team settled on a plan for a micro­gym with a handful of exercise classes and a few weight machines. They won the competition. (The micro­gym — with two stationary bicycles and three treadmills — still exists.)

Rozovsky’s study group dissolved in her second semester (it was up to the students whether they wanted to continue). Her case team, however, stuck together for the two years she was at Yale.

It always struck Rozovsky as odd that her experiences with the two groups were dissimilar. Each was composed of people who were bright and outgoing. When she talked one on one with members of her study group, the exchanges were friendly and warm. It was only when they gathered as a team that things became fraught. By contrast, her case-competition team was always fun and easygoing. In some ways, the team’s members got along better as a group than as individual friends.

‘‘I couldn’t figure out why things had turned out so different,’’ Rozovsky told me. ‘‘It didn’t seem like it had to happen that way.’’

O ur data-saturated age enables us to examine our work habits and office quirks with a scrutiny that our cubicle-bound forebears could only dream of. Today, on corporate campuses and within university laboratories, psychologists, sociologists and statisticians are devoting themselves to studying everything from team composition to email patterns in order to figure out how to make employees into faster, better and more productive versions of themselves. ‘‘We’re living through a golden age of understanding personal productivity,’’ says Marshall Van Alstyne, a professor at Boston University who studies how people share information. ‘‘All of a sudden, we can pick apart the small choices that all of us make, decisions most of us don’t even notice, and figure out why some people are so much more effective than everyone else.’’

Yet many of today’s most valuable firms have come to realize that analyzing and improving individual workers ­— a practice known as ‘‘employee performance optimization’’ — isn’t enough. As commerce becomes increasingly global and complex, the bulk of modern work is more and more team-based. One study, published in The Harvard Business Review last month , found that ‘‘the time spent by managers and employees in collaborative activities has ballooned by 50 percent or more’’ over the last two decades and that, at many companies, more than three-quarters of an employee’s day is spent communicating with colleagues.

In Silicon Valley, software engineers are encouraged to work together, in part because studies show that groups tend to innovate faster, see mistakes more quickly and find better solutions to problems. Studies also show that people working in teams tend to achieve better results and report higher job satisfaction. In a 2015 study, executives said that profitability increases when workers are persuaded to collaborate more. Within companies and conglomerates, as well as in government agencies and schools, teams are now the fundamental unit of organization. If a company wants to outstrip its competitors, it needs to influence not only how people work but also how they work together .

Five years ago, Google — one of the most public proselytizers of how studying workers can transform productivity — became focused on building the perfect team. In the last decade, the tech giant has spent untold millions of dollars measuring nearly every aspect of its employees’ lives. Google’s People Operations department has scrutinized everything from how frequently particular people eat together (the most productive employees tend to build larger networks by rotating dining companions) to which traits the best managers share (unsurprisingly, good communication and avoiding micromanaging is critical; more shocking, this was news to many Google managers).

The company’s top executives long believed that building the best teams meant combining the best people. They embraced other bits of conventional wisdom as well, like ‘‘It’s better to put introverts together,’’ said Abeer Dubey, a manager in Google’s People Analytics division, or ‘‘Teams are more effective when everyone is friends away from work.’’ But, Dubey went on, ‘‘it turned out no one had really studied which of those were true.’’

In 2012, the company embarked on an initiative — code-named Project Aristotle — to study hundreds of Google’s teams and figure out why some stumbled while others soared. Dubey, a leader of the project, gathered some of the company’s best statisticians, organizational psychologists, sociologists and engineers. He also needed researchers. Rozovsky, by then, had decided that what she wanted to do with her life was study people’s habits and tendencies. After graduating from Yale, she was hired by Google and was soon assigned to Project Aristotle.

P roject Aristotle’s researchers began by reviewing a half-century of academic studies looking at how teams worked. Were the best teams made up of people with similar interests? Or did it matter more whether everyone was motivated by the same kinds of rewards? Based on those studies, the researchers scrutinized the composition of groups inside Google: How often did teammates socialize outside the office? Did they have the same hobbies? Were their educational backgrounds similar? Was it better for all teammates to be outgoing or for all of them to be shy? They drew diagrams showing which teams had overlapping memberships and which groups had exceeded their departments’ goals. They studied how long teams stuck together and if gender balance seemed to have an impact on a team’s success.

No matter how researchers arranged the data, though, it was almost impossible to find patterns — or any evidence that the composition of a team made any difference. ‘‘We looked at 180 teams from all over the company,’’ Dubey said. ‘‘We had lots of data, but there was nothing showing that a mix of specific personality types or skills or backgrounds made any difference. The ‘who’ part of the equation didn’t seem to matter.’’

Some groups that were ranked among Google’s most effective teams, for instance, were composed of friends who socialized outside work. Others were made up of people who were basically strangers away from the conference room. Some groups sought strong managers. Others preferred a less hierarchical structure. Most confounding of all, two teams might have nearly identical makeups, with overlapping memberships, but radically different levels of effectiveness. ‘‘At Google, we’re good at finding patterns,’’ Dubey said. ‘‘There weren’t strong patterns here.’’

As they struggled to figure out what made a team successful, Rozovsky and her colleagues kept coming across research by psychologists and sociologists that focused on what are known as ‘‘group norms.’’ Norms are the traditions, behavioral standards and unwritten rules that govern how we function when we gather: One team may come to a consensus that avoiding disagreement is more valuable than debate; another team might develop a culture that encourages vigorous arguments and spurns groupthink. Norms can be unspoken or openly acknowledged, but their influence is often profound. Team members may behave in certain ways as individuals — they may chafe against authority or prefer working independently — but when they gather, the group’s norms typically override individual proclivities and encourage deference to the team.

Project Aristotle’s researchers began searching through the data they had collected, looking for norms. They looked for instances when team members described a particular behavior as an ‘‘unwritten rule’’ or when they explained certain things as part of the ‘‘team’s culture.’’ Some groups said that teammates interrupted one another constantly and that team leaders reinforced that behavior by interrupting others themselves. On other teams, leaders enforced conversational order, and when someone cut off a teammate, group members would politely ask everyone to wait his or her turn. Some teams celebrated birthdays and began each meeting with informal chitchat about weekend plans. Other groups got right to business and discouraged gossip. There were teams that contained outsize personalities who hewed to their group’s sedate norms, and others in which introverts came out of their shells as soon as meetings began.

After looking at over a hundred groups for more than a year, Project Aristotle researchers concluded that understanding and influencing group norms were the keys to improving Google’s teams. But Rozovsky, now a lead researcher, needed to figure out which norms mattered most. Google’s research had identified dozens of behaviors that seemed important, except that sometimes the norms of one effective team contrasted sharply with those of another equally successful group. Was it better to let everyone speak as much as they wanted, or should strong leaders end meandering debates? Was it more effective for people to openly disagree with one another, or should conflicts be played down? The data didn’t offer clear verdicts. In fact, the data sometimes pointed in opposite directions. The only thing worse than not finding a pattern is finding too many of them. Which norms, Rozovsky and her colleagues wondered, were the ones that successful teams shared?

I magine you have been invited to join one of two groups.

Team A is composed of people who are all exceptionally smart and successful. When you watch a video of this group working, you see professionals who wait until a topic arises in which they are expert, and then they speak at length, explaining what the group ought to do. When someone makes a side comment, the speaker stops, reminds everyone of the agenda and pushes the meeting back on track. This team is efficient. There is no idle chitchat or long debates. The meeting ends as scheduled and disbands so everyone can get back to their desks.

Team B is different. It’s evenly divided between successful executives and middle managers with few professional accomplishments. Teammates jump in and out of discussions. People interject and complete one another’s thoughts. When a team member abruptly changes the topic, the rest of the group follows him off the agenda. At the end of the meeting, the meeting doesn’t actually end: Everyone sits around to gossip and talk about their lives.

Which group would you rather join?

In 2008, a group of psychologists from Carnegie Mellon, M.I.T. and Union College began to try to answer a question very much like this one. ‘‘Over the past century, psychologists made considerable progress in defining and systematically measuring intelligence in individuals,’’ the researchers wrote in the journal Science in 2010 . ‘‘We have used the statistical approach they developed for individual intelligence to systematically measure the intelligence of groups.’’ Put differently, the researchers wanted to know if there is a collective I. Q. that emerges within a team that is distinct from the smarts of any single member.

To accomplish this, the researchers recruited 699 people, divided them into small groups and gave each a series of assignments that required different kinds of cooperation. One assignment, for instance, asked participants to brainstorm possible uses for a brick. Some teams came up with dozens of clever uses; others kept describing the same ideas in different words. Another had the groups plan a shopping trip and gave each teammate a different list of groceries. The only way to maximize the group’s score was for each person to sacrifice an item they really wanted for something the team needed. Some groups easily divvied up the buying; others couldn’t fill their shopping carts because no one was willing to compromise.

What interested the researchers most, however, was that teams that did well on one assignment usually did well on all the others. Conversely, teams that failed at one thing seemed to fail at everything. The researchers eventually concluded that what distinguished the ‘‘good’’ teams from the dysfunctional groups was how teammates treated one another. The right norms, in other words, could raise a group’s collective intelligence, whereas the wrong norms could hobble a team, even if, individually, all the members were exceptionally bright.

But what was confusing was that not all the good teams appeared to behave in the same ways. ‘‘Some teams had a bunch of smart people who figured out how to break up work evenly,’’ said Anita Woolley, the study’s lead author. ‘‘Other groups had pretty average members, but they came up with ways to take advantage of everyone’s relative strengths. Some groups had one strong leader. Others were more fluid, and everyone took a leadership role.’’

As the researchers studied the groups, however, they noticed two behaviors that all the good teams generally shared. First, on the good teams, members spoke in roughly the same proportion, a phenomenon the researchers referred to as ‘‘equality in distribution of conversational turn-taking.’’ On some teams, everyone spoke during each task; on others, leadership shifted among teammates from assignment to assignment. But in each case, by the end of the day, everyone had spoken roughly the same amount. ‘‘As long as everyone got a chance to talk, the team did well,’’ Woolley said. ‘‘But if only one person or a small group spoke all the time, the collective intelligence declined.’’

Second, the good teams all had high ‘‘average social sensitivity’’ — a fancy way of saying they were skilled at intuiting how others felt based on their tone of voice, their expressions and other nonverbal cues. One of the easiest ways to gauge social sensitivity is to show someone photos of people’s eyes and ask him or her to describe what the people are thinking or feeling — an exam known as the Reading the Mind in the Eyes test. People on the more successful teams in Woolley’s experiment scored above average on the Reading the Mind in the Eyes test. They seemed to know when someone was feeling upset or left out. People on the ineffective teams, in contrast, scored below average. They seemed, as a group, to have less sensitivity toward their colleagues.

In other words, if you are given a choice between the serious-minded Team A or the free-flowing Team B, you should probably opt for Team B. Team A may be filled with smart people, all optimized for peak individual efficiency. But the group’s norms discourage equal speaking; there are few exchanges of the kind of personal information that lets teammates pick up on what people are feeling or leaving unsaid. There’s a good chance the members of Team A will continue to act like individuals once they come together, and there’s little to suggest that, as a group, they will become more collectively intelligent.

In contrast, on Team B, people may speak over one another, go on tangents and socialize instead of remaining focused on the agenda. The team may seem inefficient to a casual observer. But all the team members speak as much as they need to. They are sensitive to one another’s moods and share personal stories and emotions. While Team B might not contain as many individual stars, the sum will be greater than its parts.

Within psychology, researchers sometimes colloquially refer to traits like ‘‘conversational turn-taking’’ and ‘‘average social sensitivity’’ as aspects of what’s known as psychological safety — a group culture that the Harvard Business School professor Amy Edmondson defines as a ‘‘shared belief held by members of a team that the team is safe for interpersonal risk-taking.’’ Psychological safety is ‘‘a sense of confidence that the team will not embarrass, reject or punish someone for speaking up,’’ Edmondson wrote in a study published in 1999 . ‘‘It describes a team climate characterized by interpersonal trust and mutual respect in which people are comfortable being themselves.’’

When Rozovsky and her Google colleagues encountered the concept of psychological safety in academic papers, it was as if everything suddenly fell into place. One engineer, for instance, had told researchers that his team leader was ‘‘direct and straightforward, which creates a safe space for you to take risks.’’ That team, researchers estimated, was among Google’s accomplished groups. By contrast, another engineer had told the researchers that his ‘‘team leader has poor emotional control.’’ He added: ‘‘He panics over small issues and keeps trying to grab control. I would hate to be driving with him being in the passenger seat, because he would keep trying to grab the steering wheel and crash the car.’’ That team, researchers presumed, did not perform well.

Most of all, employees had talked about how various teams felt. ‘‘And that made a lot of sense to me, maybe because of my experiences at Yale,’’ Rozovsky said. ‘‘I’d been on some teams that left me feeling totally exhausted and others where I got so much energy from the group.’’ Rozovsky’s study group at Yale was draining because the norms — the fights over leadership, the tendency to critique — put her on guard. Whereas the norms of her case-competition team — enthusiasm for one another’s ideas, joking around and having fun — allowed everyone to feel relaxed and energized.

For Project Aristotle, research on psychological safety pointed to particular norms that are vital to success. There were other behaviors that seemed important as well — like making sure teams had clear goals and creating a culture of dependability. But Google’s data indicated that psychological safety, more than anything else, was critical to making a team work.

‘‘We had to get people to establish psychologically safe environments,’’ Rozovsky told me. But it wasn’t clear how to do that. ‘‘People here are really busy,’’ she said. ‘‘We needed clear guidelines.’’

However, establishing psychological safety is, by its very nature, somewhat messy and difficult to implement. You can tell people to take turns during a conversation and to listen to one another more. You can instruct employees to be sensitive to how their colleagues feel and to notice when someone seems upset. But the kinds of people who work at Google are often the ones who became software engineers because they wanted to avoid talking about feelings in the first place.

Rozovsky and her colleagues had figured out which norms were most critical. Now they had to find a way to make communication and empathy — the building blocks of forging real connections — into an algorithm they could easily scale.

I n late 2014, Rozovsky and her fellow Project Aristotle number-crunchers began sharing their findings with select groups of Google’s 51,000 employees. By then, they had been collecting surveys, conducting interviews and analyzing statistics for almost three years. They hadn’t yet figured out how to make psychological safety easy, but they hoped that publicizing their research within Google would prompt employees to come up with some ideas of their own.

After Rozovsky gave one presentation, a trim, athletic man named Matt Sakaguchi approached the Project Aristotle researchers. Sakaguchi had an unusual background for a Google employee. Twenty years earlier, he was a member of a SWAT team in Walnut Creek, Calif., but left to become an electronics salesman and eventually landed at Google as a midlevel manager, where he has overseen teams of engineers who respond when the company’s websites or servers go down.

‘‘I might be the luckiest individual on earth,’’ Sakaguchi told me. ‘‘I’m not really an engineer. I didn’t study computers in college. Everyone who works for me is much smarter than I am.’’ But he is talented at managing technical workers, and as a result, Sakaguchi has thrived at Google. He and his wife, a teacher, have a home in San Francisco and a weekend house in the Sonoma Valley wine country. ‘‘Most days, I feel like I’ve won the lottery,’’ he said.

Sakaguchi was particularly interested in Project Aristotle because the team he previously oversaw at Google hadn’t jelled particularly well. ‘‘There was one senior engineer who would just talk and talk, and everyone was scared to disagree with him,’’ Sakaguchi said. ‘‘The hardest part was that everyone liked this guy outside the group setting, but whenever they got together as a team, something happened that made the culture go wrong.’’

Sakaguchi had recently become the manager of a new team, and he wanted to make sure things went better this time. So he asked researchers at Project Aristotle if they could help. They provided him with a survey to gauge the group’s norms.

When Sakaguchi asked his new team to participate, he was greeted with skepticism. ‘‘It seemed like a total waste of time,’’ said Sean Laurent, an engineer. ‘‘But Matt was our new boss, and he was really into this questionnaire, and so we said, Sure, we’ll do it, whatever.’’

The team completed the survey, and a few weeks later, Sakaguchi received the results. He was surprised by what they revealed. He thought of the team as a strong unit. But the results indicated there were weaknesses: When asked to rate whether the role of the team was clearly understood and whether their work had impact, members of the team gave middling to poor scores. These responses troubled Sakaguchi, because he hadn’t picked up on this discontent. He wanted everyone to feel fulfilled by their work. He asked the team to gather, off site, to discuss the survey’s results. He began by asking everyone to share something personal about themselves. He went first.

‘‘I think one of the things most people don’t know about me,’’ he told the group, ‘‘is that I have Stage 4 cancer.’’ In 2001, he said, a doctor discovered a tumor in his kidney. By the time the cancer was detected, it had spread to his spine. For nearly half a decade, it had grown slowly as he underwent treatment while working at Google. Recently, however, doctors had found a new, worrisome spot on a scan of his liver. That was far more serious, he explained.

No one knew what to say. The team had been working with Sakaguchi for 10 months. They all liked him, just as they all liked one another. No one suspected that he was dealing with anything like this.

‘‘To have Matt stand there and tell us that he’s sick and he’s not going to get better and, you know, what that means,’’ Laurent said. ‘‘It was a really hard, really special moment.’’

After Sakaguchi spoke, another teammate stood and described some health issues of her own. Then another discussed a difficult breakup. Eventually, the team shifted its focus to the survey. They found it easier to speak honestly about the things that had been bothering them, their small frictions and everyday annoyances. They agreed to adopt some new norms: From now on, Sakaguchi would make an extra effort to let the team members know how their work fit into Google’s larger mission; they agreed to try harder to notice when someone on the team was feeling excluded or down.

There was nothing in the survey that instructed Sakaguchi to share his illness with the group. There was nothing in Project Aristotle’s research that said that getting people to open up about their struggles was critical to discussing a group’s norms. But to Sakaguchi, it made sense that psychological safety and emotional conversations were related. The behaviors that create psychological safety — conversational turn-taking and empathy — are part of the same unwritten rules we often turn to, as individuals, when we need to establish a bond. And those human bonds matter as much at work as anywhere else. In fact, they sometimes matter more.

‘‘I think, until the off-site, I had separated things in my head into work life and life life,’’ Laurent told me. ‘‘But the thing is, my work is my life. I spend the majority of my time working. Most of my friends I know through work. If I can’t be open and honest at work, then I’m not really living, am I?’’

What Project Aristotle has taught people within Google is that no one wants to put on a ‘‘work face’’ when they get to the office. No one wants to leave part of their personality and inner life at home. But to be fully present at work, to feel ‘‘psychologically safe,’’ we must know that we can be free enough, sometimes, to share the things that scare us without fear of recriminations. We must be able to talk about what is messy or sad, to have hard conversations with colleagues who are driving us crazy. We can’t be focused just on efficiency. Rather, when we start the morning by collaborating with a team of engineers and then send emails to our marketing colleagues and then jump on a conference call, we want to know that those people really hear us. We want to know that work is more than just labor.

Which isn’t to say that a team needs an ailing manager to come together. Any group can become Team B. Sakaguchi’s experiences underscore a core lesson of Google’s research into teamwork: By adopting the data-driven approach of Silicon Valley, Project Aristotle has encouraged emotional conversations and discussions of norms among people who might otherwise be uncomfortable talking about how they feel. ‘‘Googlers love data,’’ Sakaguchi told me. But it’s not only Google that loves numbers, or Silicon Valley that shies away from emotional conversations. Most work­places do. ‘‘By putting things like empathy and sensitivity into charts and data reports, it makes them easier to talk about,’’ Sakaguchi told me. ‘‘It’s easier to talk about our feelings when we can point to a number.’’

Sakaguchi knows that the spread of his cancer means he may not have much time left. His wife has asked him why he doesn’t quit Google. At some point, he probably will. But right now, helping his team succeed ‘‘is the most meaningful work I’ve ever done,’’ he told me. He encourages the group to think about the way work and life mesh. Part of that, he says, is recognizing how fulfilling work can be. Project Aristotle ‘‘proves how much a great team matters,’’ he said. ‘‘Why would I walk away from that? Why wouldn’t I spend time with people who care about me?’’

T he technology industry is not just one of the fastest growing parts of our economy; it is also increasingly the world’s dominant commercial culture. And at the core of Silicon Valley are certain self-mythologies and dictums: Everything is different now, data reigns supreme, today’s winners deserve to triumph because they are cleareyed enough to discard yesterday’s conventional wisdoms and search out the disruptive and the new.

The paradox, of course, is that Google’s intense data collection and number crunching have led it to the same conclusions that good managers have always known. In the best teams, members listen to one another and show sensitivity to feelings and needs.

The fact that these insights aren’t wholly original doesn’t mean Google’s contributions aren’t valuable. In fact, in some ways, the ‘‘employee performance optimization’’ movement has given us a method for talking about our insecurities, fears and aspirations in more constructive ways. It also has given us the tools to quickly teach lessons that once took managers decades to absorb. Google, in other words, in its race to build the perfect team, has perhaps unintentionally demonstrated the usefulness of imperfection and done what Silicon Valley does best: figure out how to create psychological safety faster, better and in more productive ways.

‘‘Just having data that proves to people that these things are worth paying attention to sometimes is the most important step in getting them to actually pay attention,’’ Rozovsky told me. ‘‘Don’t underestimate the power of giving people a common platform and operating language.’’

Project Aristotle is a reminder that when companies try to optimize everything, it’s sometimes easy to forget that success is often built on experiences — like emotional interactions and complicated conversations and discussions of who we want to be and how our teammates make us feel — that can’t really be optimized. Rozovsky herself was reminded of this midway through her work with the Project Aristotle team. ‘‘We were in a meeting where I made a mistake,’’ Rozovsky told me. She sent out a note afterward explaining how she was going to remedy the problem. ‘‘I got an email back from a team member that said, ‘Ouch,’ ’’ she recalled. ‘‘It was like a punch to the gut. I was already upset about making this mistake, and this note totally played on my insecurities.’’

If this had happened earlier in Rozovsky’s life — if it had occurred while she was at Yale, for instance, in her study group — she probably wouldn’t have known how to deal with those feelings. The email wasn’t a big enough affront to justify a response. But all the same, it really bothered her. It was something she felt she needed to address.

And thanks to Project Aristotle, she now had a vocabulary for explaining to herself what she was feeling and why it was important. She had graphs and charts telling her that she shouldn’t just let it go. And so she typed a quick response: ‘‘Nothing like a good ‘Ouch!’ to destroy psych safety in the morning.’’ Her teammate replied: ‘‘Just testing your resilience.’’

‘‘That could have been the wrong thing to say to someone else, but he knew it was exactly what I needed to hear,’’ Rozovsky said. ‘‘With one 30-second interaction, we defused the tension.’’ She wanted to be listened to. She wanted her teammate to be sensitive to what she was feeling. ‘‘And I had research telling me that it was O.K. to follow my gut,’’ she said. ‘‘So that’s what I did. The data helped me feel safe enough to do what I thought was right.’’

Charles Duhigg is a Pulitzer Prize-winning reporter for The New York Times and the paper’s senior editor of live journalism. He is the author of ‘‘The Power of Habit’’ and the forthcoming book ‘‘Smarter Faster Better: The Secrets of Productivity in Life and Business,’’ from which this article is adapted.

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How Google Sold Its Engineers on Management

• David A. Garvin

Hint: It’s all about the data.

Reprint: R1312D

High-performing knowledge workers often question whether managers actually contribute much, especially in a technical environment. Until recently, that was the case at Google, a company filled with self-starters who viewed management as more destructive than beneficial and as a distraction from “real work.” But when Google’s people analytics team examined the value of managers, applying the same rigorous research methods the company uses in its operations, it proved the skeptics wrong.

Mining data from employee surveys, performance reviews, and double-blind interviews, the team verified that managers indeed had a positive impact. It also pinpointed exactly how, identifying the eight key behaviors of great Google managers.

In this article, Harvard Business School professor Garvin describes how Google has incorporated the detailed findings from the research into highly specific, concrete guidelines; classes; and feedback reports that help managers hone their essential skills. Because these tools were built from the ground up, using the staff’s own input, they’ve been embraced by Google employees. Managers say that they’ve found their training to be invaluable, and managers’ ratings from direct reports have steadily risen across the company.

Since the early days of Google, people throughout the company have questioned the value of managers. That skepticism stems from a highly technocratic culture. As one software engineer, Eric Flatt, puts it, “We are a company built by engineers for engineers.” And most engineers, not just those at Google, want to spend their time designing and debugging, not communicating with bosses or supervising other workers’ progress. In their hearts they’ve long believed that management is more destructive than beneficial, a distraction from “real work” and tangible, goal-directed tasks.

A few years into the company’s life, founders Larry Page and Sergey Brin actually wondered whether Google needed any managers at all. In 2002 they experimented with a completely flat organization, eliminating engineering managers in an effort to break down barriers to rapid idea development and to replicate the collegial environment they’d enjoyed in graduate school. That experiment lasted only a few months: They relented when too many people went directly to Page with questions about expense reports, interpersonal conflicts, and other nitty-gritty issues. And as the company grew, the founders soon realized that managers contributed in many other, important ways—for instance, by communicating strategy, helping employees prioritize projects, facilitating collaboration, supporting career development, and ensuring that processes and systems aligned with company goals.

Google now has some layers but not as many as you might expect in an organization with more than 37,000 employees: just 5,000 managers, 1,000 directors, and 100 vice presidents. It’s not uncommon to find engineering managers with 30 direct reports. Flatt says that’s by design, to prevent micromanaging. “There is only so much you can meddle when you have 30 people on your team, so you have to focus on creating the best environment for engineers to make things happen,” he notes. Google gives its rank and file room to make decisions and innovate. Along with that freedom comes a greater respect for technical expertise, skillful problem solving, and good ideas than for titles and formal authority. Given the overall indifference to pecking order, anyone making a case for change at the company needs to provide compelling logic and rich supporting data. Seldom do employees accept top-down directives without question.

Google downplays hierarchy and emphasizes the power of the individual in its recruitment efforts, as well, to achieve the right cultural fit. Using a rigorous, data-driven hiring process, the company goes to great lengths to attract young, ambitious self-starters and original thinkers. It screens candidates’ résumés for markers that indicate potential to excel there—especially general cognitive ability. People who make that first cut are then carefully assessed for initiative, flexibility, collaborative spirit, evidence of being well-rounded, and other factors that make a candidate “Googley.”

So here’s the challenge Google faced: If your highly skilled, handpicked hires don’t value management, how can you run the place effectively? How do you turn doubters into believers, persuading them to spend time managing others? As it turns out, by applying the same analytical rigor and tools that you used to hire them in the first place—and that they set such store by in their own work. You use data to test your assumptions about management’s merits and then make your case.

Analyzing the Soft Stuff

To understand how Google set out to prove managers’ worth, let’s go back to 2006, when Page and Brin brought in Laszlo Bock to head up the human resources function—appropriately called people operations, or people ops. From the start, people ops managed performance reviews, which included annual 360-degree assessments. It also helped conduct and interpret the Googlegeist employee survey on career development goals, perks, benefits, and company culture. A year later, with that foundation in place, Bock hired Prasad Setty from Capital One to lead a people analytics group. He challenged Setty to approach HR with the same empirical discipline Google applied to its business operations.

Setty took him at his word, recruiting several PhDs with serious research chops. This new team was committed to leading organizational change. “I didn’t want our group to be simply a reporting house,” Setty recalls. “Organizations can get bogged down in all that data. Instead, I wanted us to be hypothesis-driven and help solve company problems and questions with data.”

People analytics then pulled together a small team to tackle issues relating to employee well-being and productivity. In early 2009 it presented its initial set of research questions to Setty. One question stood out, because it had come up again and again since the company’s founding: Do managers matter?

To find the answer, Google launched Project Oxygen, a multiyear research initiative. It has since grown into a comprehensive program that measures key management behaviors and cultivates them through communication and training. By November 2012, employees had widely adopted the program—and the company had shown statistically significant improvements in multiple areas of managerial effectiveness and performance.

Google is one of several companies that are applying analytics in new ways. Until recently, organizations used data-driven decision making mainly in product development, marketing, and pricing. But these days, Google, Procter & Gamble, Harrah’s, and others take that same approach in addressing human resources needs. (See “Competing on Talent Analytics,” by Thomas H. Davenport, Jeanne Harris, and Jeremy Shapiro, HBR October 2010.)

Unfortunately, scholars haven’t done enough to help these organizations understand and improve day-to-day management practice. Compared with leadership, managing remains understudied and undertaught—largely because it’s so difficult to describe, precisely and concretely, what managers actually do. We often say that they get things done through other people, yet we don’t usually spell out how in any detail. Project Oxygen, in contrast, was designed to offer granular, hands-on guidance. It didn’t just identify desirable management traits in the abstract; it pinpointed specific, measurable behaviors that brought those traits to life.

“Engineers hate being micromanaged on the technical side but love being closely managed on the career side.”

That’s why Google employees let go of their skepticism and got with the program. Project Oxygen mirrored their decision-making criteria, respected their need for rigorous analysis, and made it a priority to measure impact. Data-driven cultures, Google discovered, respond well to data-driven change.

Making the Case

Project Oxygen colead Neal Patel recalls, “We knew the team had to be careful. Google has high standards of proof, even for what, at other places, might be considered obvious truths. Simple correlations weren’t going to be enough. So we actually ended up trying to prove the opposite case—that managers don’t matter. Luckily, we failed.”

To begin, Patel and his team reviewed exit-interview data to see if employees cited management issues as a reason for leaving Google. Though they found some connections between turnover rates and low satisfaction with managers, those didn’t apply to the company more broadly, given the low turnover rates overall. Nor did the findings prove that managers caused attrition.

As a next step, Patel examined Googlegeist ratings and semiannual reviews, comparing managers on both satisfaction and performance. For both dimensions, he looked at the highest and lowest scorers (the top and bottom quartiles).

Essential Background

Evidence-based management.

• Jeffrey Pfeffer and Robert I. Sutton

“At first,” he says, “the numbers were not encouraging. Even the low-scoring managers were doing pretty well. How could we find evidence that better management mattered when all managers seemed so similar?” The solution came from applying sophisticated multivariate statistical techniques, which showed that even “the smallest incremental increases in manager quality were quite powerful.”

For example, in 2008, the high-scoring managers saw less turnover on their teams than the others did—and retention was related more strongly to manager quality than to seniority, performance, tenure, or promotions. The data also showed a tight connection between managers’ quality and workers’ happiness: Employees with high-scoring bosses consistently reported greater satisfaction in multiple areas, including innovation, work-life balance, and career development.

In light of this research, the Project Oxygen team concluded that managers indeed mattered. But to act on that finding, Google first had to figure out what its best managers did. So the researchers followed up with double-blind qualitative interviews, asking the high- and low-scoring managers questions such as “How often do you have career development discussions with your direct reports?” and “What do you do to develop a vision for your team?” Managers from Google’s three major functions (engineering, global business, and general and administrative) participated; they came from all levels and geographies. The team also studied thousands of qualitative comments from Googlegeist surveys, performance reviews, and submissions for the company’s Great Manager Award. (Each year, Google selects about 20 managers for this distinction, on the basis of employees’ nominations.) It took several months to code and process all this information.

After much review, Oxygen identified eight behaviors shared by high-scoring managers. (See the sidebar “What Google’s Best Managers Do” for the complete list.) Even though the behaviors weren’t terribly surprising, Patel’s colead, Michelle Donovan, says, “we hoped that the list would resonate because it was based on Google data. The attributes were about us, by us, and for us.”

What Google’s Best Managers Do

By examining data from employee surveys and performance reviews, Google’s people analytics team identified eight key behaviors demonstrated by the company’s most effective managers.

A good manager:

1. Is a good coach 2. Empowers the team and does not micromanage (See the sidebar “How Google Defines One Key Behavior”) 3. Expresses interest in and concern for team members’ success and personal well-being 4. Is productive and results-oriented 5. Is a good communicator—listens and shares information 6. Helps with career development 7. Has a clear vision and strategy for the team 8. Has key technical skills that help him or her advise the team

The key behaviors primarily describe leaders of small and medium-sized groups and teams and are especially relevant to first- and second-level managers. They involve developing and motivating direct reports, as well as communicating strategy and eliminating roadblocks—all vital activities that people tend to overlook in the press of their day-to-day responsibilities.

Putting the Findings into Practice

The list of behaviors has served three important functions at Google: giving employees a shared vocabulary for discussing management, offering them straightforward guidelines for improving it, and encapsulating the full range of management responsibilities. Though the list is simple and straightforward, it’s enriched by examples and descriptions of best practices—in survey participants’ own words. These details make the overarching principles, such as “empowers the team and does not micromanage,” more concrete and show managers different ways of enacting them. (See the exhibit “How Google Defines One Key Behavior.”)

How Google Defines One Key Behavior

Drawing on companywide survey responses, Google breaks down each essential management behavior into specific activities and best practices.

Best practice: Assign stretch assignments to empower the team to tackle big problems

“My manager was able to see my potential and gave me opportunities that allowed me to shine and grow. For example, early on in my role, she asked me to pull together a cross-functional team to develop a goal-setting process. I was new to the role, so she figured it would be a great way for me to get to know the team and also to create accountability and transparency. Once it was developed, she sent me to one of our Europe offices—on my own!—to deliver the training to people managers there.”

The descriptions of the eight behaviors also allow considerable tailoring. They’re inclusive guidelines, not rigid formulas. That said, it was clear early on that managers would need help adopting the new standards, so people ops built assessments and a training program around the Oxygen findings.

To improve the odds of acceptance, the group customized the survey instrument, creating an upward feedback survey (UFS) for employees in administrative and global business functions and a tech managers survey (TMS) for the engineers. Both assessments asked employees to evaluate their managers (using a five-point scale) on a core set of activities—such as giving actionable feedback regularly and communicating team goals clearly—all of which related directly to the key management behaviors.

The first surveys went out in June 2010—deliberately out of sync with performance reviews, which took place in April and September. (Google had initially considered linking the scores with performance reviews but decided that would increase resistance to the Oxygen program because employees would view it as a top-down imposition of standards.) People ops emphasized confidentiality and issued frequent reminders that the surveys were strictly for self-improvement. “Project Oxygen was always meant to be a developmental tool, not a performance metric,” says Mary Kate Stimmler, an analyst in the department. “We realized that anonymous surveys are not always fair, and there is often a context behind low scores.”

Though the surveys weren’t mandatory, the vast majority of employees completed them. Soon afterward, managers received reports with numerical scores and individual comments—feedback they were urged to share with their teams. (See the exhibit “One Manager’s Feedback” for a representative sample.) The reports explicitly tied individuals’ scores to the eight behaviors, included links to more information about best practices, and suggested actions each manager could take to improve. Someone with, say, unfavorable scores in coaching might get a recommendation to take a class on how to deliver personalized, balanced feedback.

People ops designed the training to be hands-on and immediately useful. In “vision” classes, for example, participants practiced writing vision statements for their departments or teams and bringing the ideas to life with compelling stories. In 2011, Google added Start Right, a two-hour workshop for new managers, and Manager Flagship courses on popular topics such as managing change, which were offered in three two-day modules over six months. “We have a team of instructors,” says people-development manager Kathrin O’Sullivan, “and we are piloting online Google Hangout classes so managers from around the world can participate.”

Managers have expressed few concerns about signing up for the courses and going public with the changes they need to make. Eric Clayberg, for one, has found his training invaluable. A seasoned software-engineering manager and serial entrepreneur, Clayberg had led teams for 18 years before Google bought his latest start-up. But he feels he learned more about management in six months of Oxygen surveys and people ops courses than in the previous two decades. “For instance,” he says, “I was worried about the flat organizational structure at Google; I knew it would be hard to help people on my team get promoted. I learned in the classes about how to provide career development beyond promotions. I now spend a third to half my time looking for ways to help my team members grow.” And to his surprise, his reports have welcomed his advice. “Engineers hate being micromanaged on the technical side,” he observes, “but they love being closely managed on the career side.”

Improving Management at Google: An Audio Interview

Harvard Business School professor David Garvin interviews Google software-engineering manager Eric Clayberg, a winner of the company’s Great Manager Award. They discuss how Clayberg and others at Google have benefitted from Project Oxygen, an internal research initiative that has evolved into a comprehensive management-feedback and -training program.

Download this podcast

To complement the training, the development team sets up panel discussions featuring high-scoring managers from each function. That way, employees get advice from colleagues they respect, not just from HR. People ops also sends new managers automated e-mail reminders with tips on how to succeed at Google, links to relevant Oxygen findings, and information about courses they haven’t taken.

And Google rewards the behaviors it’s working so hard to promote. The company has revamped its selection criteria for the Great Manager Award to reflect the eight Oxygen behaviors. Employees refer to the behaviors and cite specific examples when submitting nominations. Clayberg has received the award, and he believes it was largely because of the skills he acquired through his Oxygen training. The prize includes a weeklong trip to a destination such as Hawaii, where winners get to spend time with senior executives. Recipients go places in the company, too. “In the last round of promotions to vice president,” Laszlo Bock says, “10% of the directors promoted were winners of the Great Manager Award.”

Measuring Results

The people ops team has analyzed Oxygen’s impact by examining aggregate survey data and qualitative input from individuals. From 2010 through 2012, UFS and TMS median favorability scores rose from 83% to 88%. The lowest-scoring managers improved the most, particularly in the areas of coaching and career development. The improvements were consistent across functions, survey categories, management levels, spans of control, and geographic regions.

In an environment of top achievers, people take low scores seriously. Consider vice president Sebastien Marotte, who came to Google in 2011 from a senior sales role at Oracle. During his first six months at Google, Marotte focused on meeting his sales numbers (and did so successfully) while managing a global team of 150 people. Then he received his first UFS scores, which came as a shock. “I asked myself, ‘Am I right for this company? Should I go back to Oracle?’ There seemed to be a disconnect,” he says, “because my manager had rated me favorably in my first performance review, yet my UFS scores were terrible.” Then, with help from a people ops colleague, Marotte took a step back and thought about what changes he could make. He recalls, “We went through all the comments and came up with a plan. I fixed how I communicated with my team and provided more visibility on our long-term strategy. Within two survey cycles, I raised my favorability ratings from 46% to 86%. It’s been tough but very rewarding. I came here as a senior sales guy, but now I feel like a general manager.”

Overall, other managers took the feedback as constructively as Marotte did—and were especially grateful for its specificity. Here’s what Stephanie Davis, director of large-company sales and another winner of the Great Manager Award, says she learned from her first feedback report: “I was surprised that one person on my team didn’t think I had regularly scheduled one-on-one meetings. I saw this person every day, but the survey helped me realize that just seeing this person was different from having regularly scheduled individual meetings. My team also wanted me to spend more time sharing my vision. Personally, I have always been inspired by Eric [Schmidt], Larry, and Sergey; I thought my team was also getting a sense of the company’s vision from them. But this survey gave my team the opportunity to explain that they wanted me to interpret the higher-level vision for them. So I started listening to the company’s earnings call with a different ear. I didn’t just come back to my team with what was said; I also shared what it meant for them.”

Chris Loux, head of global enterprise renewals, remembers feeling frustrated with his low UFS scores. “I had received a performance review indicating that I was exceeding expectations,” he says, “yet one of my direct reports said on the UFS that he would not recommend me as a manager. That struck me, because people don’t quit companies—they quit managers.” At the same time, Loux struggled with the question of just how much to push the lower performers on his team. “It’s hard to give negative feedback to a type-A person who has never received bad feedback in his or her life,” he explains. “If someone gets 95% favorable on the UFS, I wonder if that manager is avoiding problems by not having tough conversations with reports on how they can get better.”

Loux isn’t the only Google executive to speculate about the connection between employees’ performance reviews and their managers’ feedback scores. That question came up multiple times during Oxygen’s rollout. To address it, the people analytics group fell back on a time-tested technique—going back to the data and conducting a formal analysis to determine whether a manager who gave someone a negative performance review would then receive a low feedback rating from that employee. After looking at two quarters’ worth of survey data from 2011, the group found that changes in employee performance ratings (both upward and downward) accounted for less than 1% of variability in corresponding manager ratings across all functions at Google.

“Managing to the test” doesn’t appear to be a big risk, either. Because the eight behaviors are rooted in action, it’s difficult for managers to fake them in pursuit of higher ratings. In the surveys, employees don’t assess their managers’ motivations, values, or beliefs; rather, they evaluate the extent to which their managers demonstrate each behavior. Either the manager has acted in the ways recommended—consistently and credibly—or she has not. There is very little room for grandstanding or dissembling.

This article also appears in:

HBR’s 10 Must Reads 2015

“We are not trying to change the nature of people who work at Google,” says Bock. “That would be presumptuous and dangerous. Instead, we are saying, ‘Here are a few things that will lead you to be perceived as a better manager.’ Our managers may not completely believe in the suggestions, but after they act on them and get better UFS and TMS scores, they may eventually internalize the behavior.”

Project Oxygen does have its limits. A commitment to managerial excellence can be hard to maintain over the long haul. One threat to sustainability is “evaluation overload.” The UFS and the TMS depend on employees’ goodwill. Googlers voluntarily respond on a semiannual basis, but they’re asked to complete many other surveys as well. What if they decide that they’re tired of filling out surveys? Will response rates bottom out? Sustainability also depends on the continued effectiveness of managers who excel at the eight behaviors, as well as those behaviors’ relevance to senior executive positions. A disproportionate number of recently promoted vice presidents had won the Great Manager Award, a reflection of how well they’d followed Oxygen’s guidelines. But what if other behaviors—those associated with leadership skills—matter more in senior positions?

Further, while survey scores gauge employees’ satisfaction and perceptions of the work environment, it’s unclear exactly what impact those intangibles have on such bottom-line measures as sales, productivity, and profitability. (Even for Google’s high-powered statisticians, those causal relationships are difficult to establish.) And if the eight behaviors do actually benefit organizational performance, they still might not give Google a lasting edge. Companies with similar competitive profiles—high-tech firms, for example, that are equally data-driven—can mimic Google’s approach, since the eight behaviors aren’t proprietary.

Because the eight behaviors are rooted in action, it’s difficult for managers to fake them.

Still, Project Oxygen has accomplished what it set out to do: It not only convinced its skeptical audience of Googlers that managers mattered but also identified, described, and institutionalized their most essential behaviors. Oxygen applied the concept of data-driven continuous improvement directly—and successfully—to the soft skills of management. Widespread adoption has had a significant impact on how employees perceive life at Google—particularly on how they rate the degree of collaboration, the transparency of performance evaluations, and their groups’ commitment to innovation and risk taking. At a company like Google, where the staff consists almost entirely of “A” players, managers have a complex, demanding role to play. They must go beyond overseeing the day-to-day work and support their employees’ personal needs, development, and career planning. That means providing smart, steady feedback to guide people to greater levels of achievement—but intervening judiciously and with a light touch, since high-performing knowledge workers place a premium on autonomy. It’s a delicate balancing act to keep employees happy and motivated through enthusiastic cheerleading while helping them grow through stretch assignments and carefully modulated feedback. When the process works well, it can yield extraordinary results.

That’s why Prasad Setty wants to keep building on Oxygen’s findings about effective management practice. “We will have to start thinking about what else drives people to go from good to great,” he says. His team has begun analyzing managers’ assessment scores by personality type, looking for patterns. “With Project Oxygen, we didn’t have these endogenous variables available to us,” he adds. “Now we can start to tease them out, using more of an ethnographic approach. It’s really about observations—staying with people and studying their interactions. We’re not going to have the capacity to follow tons of people, but what we’ll lose in terms of numbers, we’ll gain in a deeper understanding of what managers and their teams experience.”

That, in a nutshell, is the principle at the heart of Google’s approach: deploying disciplined data collection and rigorous analysis—the tools of science—to uncover deeper insights into the art and craft of management.

• DG David A. Garvin was the C. Roland Christensen Professor at Harvard Business School.

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Google Case Study: SWOT Analysis

Looking for a case study on Google? The essay below focuses on SWOT analysis of Google’s strategic management. Get inspired to make your own case study of Google company with us!

Google Case Study: Defining the Issue

Google business strategy analysis, swot analysis of google company, google case study: solution & recommendations.

Larry Page and Sergey Brin created Google in 1998 during their college days at Stanford University. Over the last one decade, Google has grown into a globally acknowledged market force for its service provision, business model, efforts in development of technology, and human life influence.

Since inception of internet and development of information technology, Google’s record is impressive in the way it has charmed people regardless of their ethnic, religious, and political affiliations.

The company has also reached out to different social and economic classes across the world through its numerous products.

Google identifies among the leading search engines available in the world market. Its reliability in terms of matching results and simple design of their website has attracted a respectable fraction of global population, which is increasingly warming up to the contemporary world of internet.

Some of the main competitors of Google are Yahoo, Amazon, MSN and Bing. Google has managed to fight off competition from these companies to command close to 85% of internet searches.

In 2005, Google’s search engine was the best performing product from the company ahead of email services. Other products by Google include Google profiles, Google maps, Google talk, Google gadgets and Google trends.

This essay will analyze Google’s strengths, weaknesses, opportunities and threats. It will also identify and discuss Google’s business strategy and organizational culture.

Google has demonstrated how fast a business can grow if it develops an effective operational strategy, and an inclusive corporate culture. In 2000, a company that started with two individuals grew fast to include a workforce of 60 workers.

Google has a business strategy that aims to help penetrate major global economies by providing products and services that meet primary needs of their customers. Google provides its services in America, Europe, Asia, and other parts of the world through ten other languages apart from English.

Google’s corporate values and business strategy help to promote innovation within its workforce, thus the company’s rapid growth.

Through innovations such as Google toolbar browser, keyword-targeted advertising, and expansion of search capabilities to include 28 languages, the company earned a annual revenue of $86 million for the 2001 fiscal year.

This figure was very high compared to their annual revenue of $220,000 two years earlier.

The company’s Chairperson and Chief Executive Officer, Eric Schmidt was definitely doing his job effectively. He managed to build a corporate culture for Google, which has made it a striking, favorable, fitting, and exquisite place to work.

It promotes cultural and talent diversity in its workforce. It also nurtures a spirit of togetherness among workers.

The inclusive nature of the work environment at Google motivates employees towards achieving organizational goals, as they develop a certain level of attachment to activities and processes within the company.

Google has developed its business model along this culture, thus the reason it stands out from its competitors. The focus of their business model is to improve access to information by providing quality, reliable and effective means of doing so.

This is a management tool used by organizations to make decisions through assessment of organizational structure and corporate culture. It entails identifying internal strengths and weaknesses of an organization, as well as external opportunities and threats.

The cardinal focus of applying SWOT analysis in an organization is to build on strengths, do away with weaknesses, take hold of available opportunities, and respond to possible threats.

Google has several internal strengths and weaknesses, as well as opportunities and threats from the external environment.

A strength that has enhanced Google’s fast growth is an effective market strategy. The market strategy applied by Google entails innovation, a large portfolio of products, broad market coverage, and effective marketing.

Google has created a global customer base covering various types of customers of varied age, social and economic class, as well as political and religious affiliations.

The second strength is good human resource planning and management strategies. Google has demonstrated strong ability to create a cohesive and inclusive work environment that helps maintain high employee morale.

They have effective employee motivation and retention strategies that include good remuneration packages and workplace benefits.

The third strength is effective change management strategies. Innovation creates need for regular change implementation at Google, and it has effectively managed to introduce without compromising its corporate culture.

Other notable strengths of Google include effective leadership and management strategies, financial stability, customer goodwill, and a strong corporate culture.

The first weakness is poor recruitment strategies. The human resource department at Google receives numerous applications from potential employees from various parts of the world.

Google ignores these applications because its owners prefer to hire graduates from Stanford University, their alma mater.

This strategy locks out very qualified and competent individuals who could bring a new dimension into Google’s way of conducting business.

The second weakness is poor implementation of employee retention strategies. Although the company has developed strategies for reducing employee turnover, poor implementation has forced some top managers to leave and join their competitors.

When employees leave and join a competitor, the competitor most likely counters their efforts in the market.

The third weakness is unreliable partnerships. Google formed numerous partnerships with many companies in a bid to increase its market share. Some of these partnerships failed to fulfill their desired potential, leading to poor management of some portfolios.

Opportunities

The outside environment offers Google numerous opportunities that can be exploited to improve stability in the market.

The first opportunity is to integrate its services with computer software in order to attract more users. This means that Google can form partnerships with computer software developers like Microsoft to have their products integrated during production.

Google plans to launch an operating system called chrome that will enable it compete effectively with companies such as Microsoft.

Although it will be challenging to convince people to try out a new operating system for their personal computers, Google can look up to its operating system for smart phones that has been a huge success. This will motivate them to go ahead with the launch.

The operating system is cost effective, reliable and its usability suits needs of many internet users. This is an opportunity Google can exploit and stamp its control of the internet service market.

Other opportunities include expansion of global market presence, integration of research and development skill in its activities, as well as development of new business partnerships for growth of its brand.

The first threat is Google’s inability to provide enough motivation to part time employees who work on various projects. Many of these employees do not receive allowances and this might derail their human resource development strategies.

The second threat is court battles instigated by its major competitors. Yahoo, Amazon, and Microsoft among other companies have filed a case to stop Google from digitizing and getting exclusive rights for the concept of online advertising.

The third threat faced by Google is the dynamic nature of competition in the industry. There is need for increased innovation to ensure that the company does not lose its market leadership to emerging competitors.

Google needs to apply certain approaches to ensure that it makes the best out of its strengths, do away with weaknesses, seize available opportunities, and eliminate all threats from the external environment.

The first recommendation is need for Google to further reflect on its mission statement and develop it. It is important for Google to know that all their competitors are seeking to provide the best services on the market. Thus, it needs to rethink how it can maintain its market leadership.

The second recommendation is that Google needs to reorient its organizational structure and culture to promote development of its brand. Google needs to develop effective strategies for change management, which is an effective tool for organizational success.

Thirdly, Google needs to revise its recruitment strategy to include graduates from other institutions who can provide an extra dimension to its organizational development.

Google currently applies a strategy that its founders started, of picking their employees from Stanford University, as they believe its graduates have the essential competencies.

Maintaining market leadership is a function of human resource management that involves applying effective recruitment strategies.

Employee recruitment entails developing an attractive remuneration and benefits package for all workers. This helps to reduce employee turnover because they will be satisfied and motivated to work.

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GOOGLE: a reflection of culture, leader, and management

• Sang Kim Tran 1 , 2  

International Journal of Corporate Social Responsibility volume  2 , Article number:  10 ( 2017 ) Cite this article

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This paper provides a viewpoint of the culture and subcultures at Google Inc., which is a famous global company, and has a huge engineering staff and many talented leaders. Through its history of development, it has had positive impacts on society; however; there have been management challenges. The Board of Directors (BoDs) developed and implemented a way to measure the abilities of their managers, which helped to identify problems. This paper will analyze the case study of Harvard Business Review, Oxygen Project, and clarify the management problem in Google’s organization. It will also compare Google with Zappos, a much smaller organization, and present how the BoDs of Zappos assesses its culture and subcultures. In this paper, we will recommend eight important points to building an organizational culture that is positive for stable growth of a company. We believe that much of what be learned could be useful to other business leaders, regardless of company scale.

Introduction

In a large society, each company is considered a miniature society (Mawere 2011 ). Similar to large societies with large cultures, small societies also need to build their own cultures. A culture is influenced by many factors and determines if it is a great culture. Corporate culture requires both the attention to the efficiency of production and business and to the relationship among people in the organization closely (Bhagat et al. 2012 ). Regardless if it is a large or a small organization, it must encounter issues of cooperation among individuals and groups. There are many factors leading to the success of business process re-engineering in higher education (BPR), the main four elements are culture, processes, structure, and technology. Culture is listed as number one (Ahmad et al. 2007 ). Hence, culture becomes the most important factor to the success of the development of a business. Organizational culture is the set of shared beliefs (Steiber and Alänge 2016 ), values, and norms that influence the way members think, feel, and behave. Culture is created by means of terminal and instrumental values, heroes, rites and rituals, and communication networks (Barman n.d. ). The primary methods of maintaining organizational culture are through the socialization process by which an individual learns the values, expected behaviors, and necessary social knowledge to assume their roles in the organization. In addition, (Gupta and Govindarajan 2000 ) and Fig.  1 in (Ismail Al-Alawi et al. 2007 ) illustrates that culture was established by six major factors, such as information systems, people, process, leadership, rewarding system, and organization structure. Therefore, there is a wide variety of combined and sophisticated cultures in the workplace, especially in big corporations like Google, Facebook, Proctor & Gamble, etc. Each organization tends to have a common goal, which is to create a culture that is different from other companies and to promote their teams to be creative in developing a distinctive culture (Stimpson and Farquharson 2014 ). Clearly, we can see that Google’s culture is different than others. What makes this company unique and different from others, as well as the dominant cultures and subcultures existing at this company? How do leadership behaviors impact the organizational culture? By operating a case study of a Harvard Business Review to analyze its organizational culture, subsequently, having compared it with Zappos’ culture, this paper will clarify the similarities and differences in managing organizational cultures between them and consider whether the solutions for the problems can be applied to other business models, and for tomorrow leaders or not?

Trends of using product by information searching

Company overview

This part shows how Google became famous in the world and its culture and subcultures made it a special case for others to take into consideration. Google is one of the few technology companies which continue to have one of the fastest growth rates in the world. It began by creating a search engine that combined PageRank system, developed by Larry Page (ranking the importance of websites based on external links), and Web search engine, created by Sergey Brin (accessing a website and recording its content), two co-founders of the company (Jarvis 2011 ; Downes 2007 ). Google’s achievements absolutely do not come from any luck. Google has made extra efforts in creating an index of a number of websites, which have been up to 25 billion websites. This also includes 17 million images and one billion messages to Usenet group (Downes 2007 ). Besides searching for websites, Google users are able to search for PDF files, PostScript, documents, as well as Microsoft, Lotus, PowerPoint and Shockwave files. Google processes nearly 50% of search queries all over the world. Moreover, it is the number one search option for web users and is one of the top five websites on the Internet, which have more than 380 million users and 28 billion visits every month, and more than 50% of access from countries outside the US (Desjardins 2017 ). Google’s technology is rather special: it can analyze millions of different variables of users and businesses who place advertisements. It then connects them with millions of potential advertisements and gives messages of advertisement, which is closest to objects in less than one second. Thus, Google has the higher rate of users clicking advertisements than its opponent Yahoo, from 50 to 100%, and it dominates over 70% market share of paid advertisements (Rosenberg 2016 ). Google’s self-stated mission: “to organize the world’s information and make it universally accessible and useful (Alves n.d. ).” Nowadays, it is believed that people in the world like “Google” with words “the useful-lively information storage”.

Predominant culture at Google

The dominant culture in the organization depends on the environment in which the company operates the organization’s objectives, the belief system of the employees, and the company’s management style. Therefore, there are many organizational cultures (Schein 2017 ). The Exhibit 3.1 at page 39 in (Schein 2009 ) provides what culture is about. For example, employee follows a standard procedure with a strict adherence to hierarchy and well-defined individual roles and responsibilities. Those in competitive environments, such as sales may forget strict hierarchies and follow a competitive culture where the focus is on maintaining strong relationships with external parties. In this instance, the strategy is to attain competitive advantages over the competition. The collaborative culture is yet another organizational way of life. This culture presents a decentralized workforce with integrated units working together to find solutions to problems or failure.

Why do many large companies buy its innovation? Because its dominant culture of 99% defect-free operational excellence squashes any attempts at innovation, just like a Sumo wrestler sitting on a small gymnast (Grossman-Kahn and Rosensweig 2012 ). They cannot accept failures. In fact, failure is a necessary part of innovation and Google took this change by Oxygen Project to measure the abilities of their multicultural managers. This means that Google itself possesses multiple different cultures (see Google’s clips). Like Zappos, Google had established a common, organizational culture for the whole offices that are distinctive from the others. The predominant culture aimed at Google is an open culture, where everybody and customer can freely contribute their ideas and opinions to create more comfortable and friendly working environment (Hsieh 2010a ).

The fig.  2 .1 in chapter two of (Schein 2009 ) and page 17 in part one of (Schein 2017 ) provide us three levels of culture which are Artifacts, Espoused values and Underlying assumptions helping us to understand the culture at Google. At page 84, in (Schein 2009 ), the “artifacts” are identified such as dress codes, level of formality in authority relationships, working hours, meeting (how often, how run, timing), how are decisions made, communication, social events, jargon, uniforms, identity symbols, rites and rituals, disagreements and conflicts, balance between work and family . It seems that Google is quite open in these artifacts by showing a respect for uniform and national culture of each staff individually and giving them the right to wear traditional clothes.

Ad Blocking Incidence

Working at Google, employees enjoy free food served throughout the day, a volleyball court, a swimming pool, a car wash, an oil change, a haircut, free health care, and many other benefits. The biggest benefit for the staff is to be picked up on the day of work. As assessed by many traffic experts, the system set up by Google is considered to be a great transport network. Tad Widby, a project manager and a traffic system researcher throughout the United States, said: “I have not seen any larger projects in the Bay Area as well as in urban areas across the country” (Helft 2007 ). Of course, it is impossible for Google to “cover up the sky”, so Yahoo also started implementing the bus project for employees in 2005. On peak days, Yahoo’s bus also took off. Pick up about 350 employees in San Francisco, as well as Berkeley, Oakland, etc. These buses run on biofuels and have Wi-Fi coverage. Yet, Danielle Bricker, the Yahoo bus coordinator of Yahoo, has also admitted that the program is “indirectly” inspired by Google’s initiative (Helft 2007 ). Along with that, eBay recently also piloted shuttle bus transfers at five points in San Francisco. Some other corporations are also emerging ideas for treatment of staff is equally unique. Facebook is an example, instead of facilitating employees far from the workplace; it helps people in the immediate neighborhood by offering an additional $10,000 for an employee to live close to the pillar within 10 miles, nearby the Palo Alto Department (Hall 2015 ).

When it comes to Google, people often ask what the formula for success is. The answer here is the employees of Google. They create their own unique workplace culture rules to create an effective work environment for their employees. And here are the most valuable things to learn from Google’s corporate culture (Scott 2008 ) that we should know:

Tolerate with mistakes and help staff correct

At Google, paying attention to how employees work and helping them correct mistakes is critical. Instead of pointing out the damage and blaming a person who caused the mistake, the company would be interested in what the cause of the problem was and how to fix it as quickly and efficiently as possible.

Also as its culture, we understand that if we want to make breakthroughs in the workplace, we need to have experimentation, failure and repeat the test. Therefore, mistakes and failures are not terrible there. We have the right to be wrong and have the opportunity to overcome failure in the support of our superiors and colleagues. Good ideas are always encouraged at Google. However, before it is accepted and put into use, there is a clear procedure to confirm whether it is a real new idea and practical or not?

Exponential thought

Google developed in the direction of a holding company - a company that does not directly produce products or provide services but simply invest in capital by buying back capital. In the company, the criteria for setting the ten exponential function in lieu of focusing only on the change in the general increase. This approach helps Google improve its technology and deliver great products to consumers continuously.

Of course, every company wants to hire talented people to work for them. However, being talented is an art in which there must be voluntary work and enthusiasm for the work of the devotees. At page 555 in (Saffold 1988 ) illustrated that distinctive cultures dramatically influencing performance do exist. Likewise, Google, Apple, Netflix, and Dell are 40% more productive than the average company which attracts top-tier employees and high performers (Vozza 2017 ). Recognizing this impact, Google created a distinctive corporate culture when the company attracted people from prestigious colleges around the world (West 2016 ; Lazear and Gibbs 2014 ).

Build a stimulating work environment

When it comes to the elements that create creativity and innovation, we can easily recognize that the working environment is one of the most important things. Google has succeeded in building an image of a creative working. Google offices are individually designed, not duplicated in any type of office. In fact, working environment at Google is so comfortable so that employees will not think of it as a working room, with a full area of ​​work, relaxation, exercise, reading, watching movies. Is the orientation of Google’s corporate culture to stimulate creativity and to show interest in the lives of employees so that volunteers contribute freely (Battelle 2011 )?

Subculture is also a culture, but for a smaller group or community in a big organization (Crosset and Beal 1997 ). Google, known as the global company with many more offices, so there are many subcultures created among groups of people who work together, from subcultures among work groups to subcultures among ethnic groups and nations, multi-national groups, as well as multiple occupations, functions, geographies, echelons in the hierarchy and product lines. For example, six years ago, when it bought 100 Huffys for employees to use around the sprawling campus, has since exploded into its own subculture. Google now has a seven-person staff of bicycle mechanics that maintains a fleet of about 1300 brightly-colored Google bikes. The company also encourages employees to cycle to work by providing locker rooms, showers and places to securely park bikes during working hours. And, for those who want to combine meetings with bike-riding, Googlers can use one of several seven-person (Crowley 2013 ).

Leadership influences on the culture at Google

From the definition of leadership and its influence on culture; so what does leader directly influence the culture existed? According to Schein, “culture and leadership are two sides of the same coin and one cannot understand one without the other”, page three in (Schein 2009 ). If one of us has never read the article “Google and the Quest to create a better boss” in the New York Times, it is listed in a priority reading. It breaks the notion that managers have no change. The manager really makes a difference (Axinn 1988 ; Carver 2011 ). In fact, a leader has a massive impact on the culture of the company, and Google is not an exception. The leaders of Google concerned more about the demands and abilities of each individual, the study of the nature of human being, an appreciation their employees as their customers. At Google, the founders thought they could create a company that people would want to work at when creating a home-like environment. It is real that they focus on the workplace brings the comfort to staff creatively and freely (Lebowitz 2013 ).

In my opinion, a successful business cannot be attributed solely from a single star; that needs the brightness of all employees. It depends very much on the capacity and ability to attract talented people. It is the way in which the leader manages these talents, is the cornerstone of corporate culture. One thing that no one can deny is that a good leader must be a creator of a corporate culture so that the employees can maximize capabilities themselves (Driscoll and McKee 2007 ; Kotter 2008 ).

To brief, through the view of Google’s culture, BoDs tended and designed to encourage loyalty and creativity, based on an unusual organizational culture because culture is not only able to create an environment, but it also adapts to diverse and changes circumstances (Bulygo 2013 ).

Company growth and its impact

“Rearrange information around the world, make them accessible everywhere and be useful.” This was one of the main purposes set by Larry Page and Sergey Brin when they first launched Google on September 4th, 1998, as a private company (Schmidt and Rosenberg 2014 ). Since then, Google has expanded its reach, stepped into the mobile operating system, provided mapping services and cloud computing applications, launched its own hardware, and prepared it to enter the wearable device market. However, no matter how varied and rich these products are, they are all about the one thing, the root of Google: online searching.

1998–2001: Focus on search

In its early years, Google.com was simply one with extreme iconic images: a colorful Google logo, a long text box in the middle of the screen, a button to execute. One button for searching and the other button are “I’m feeling lucky” to lead users to a random Google site. By May 2000, Google added ten additional languages to Google.com , including French, German, Italian, Swedish, Finnish, Spanish, Portuguese, Dutch, Norwegian and Danish, etc. This is one of the milestones in Google’s journey into the world. Google.com is available in over 150 languages (Scott 2008 ; Lee 2017 ).

2001–2007: Interface card

A very important event with Google around this time was the sale of shares to the public (IPO). In October 2003, Microsoft heard news of the IPO, so it quickly approached Google to discuss a buyout or business deal. Nevertheless, that intention was not materialized. In 2004, it was also the time when Google held a market share of 84.7% globally through collaboration with major Internet companies, such as Yahoo, AOL, and CNN. By February 2004, Yahoo stopped working with Google and separately stood out for engine search. This has led Google to lose some market share, but it has shown the importance and distinctness of Google. Nowadays, the term “Google” has been used as a verb just by visiting Google.com and doing an online search (Smith 2010 ). Not stopping at the homepage search, Google’s interface tag began to be brought to Gmail and Calendar with the links at the top of the page. Google homepage itself continues to use this style.

In 2006, Google also made an important acquisition to buy YouTube for $1.65 billion (Burgess and Green 2013 ). However, the company decided to keep YouTube as a separate brand and not to include it in Google Video search. Thanks to the backing of an Internet industry giant, YouTube has grown to become the world’s largest online video sharing service (Cha et al. 2007 ).

2007–2012: Navigation bar, Google menu, Google now

Google began to deploy a new navigation bar located at the edge of the screen. It includes links to a place where to look for photos, videos, news, maps, as well as buttons to switch to Gmail, Calendar, and other services developed by the company. In the upper left corner, Google added a box displaying Google + notifications and user accounts’ image. Google Now not only appeared on Android and it’s also brought to Chrome on a computer as well as iOS. All have the same operating principle, and the interface card still appears as Android it is.

2013–2014: Simplified interface

Google has moved all of the icons that lead to its other applications and services to an App Drawer button in the upper right hand, at the corner of the screen. In addition, Google.com also supports better voice search through the Chrome browser. Google has experimented with other markets, such as radio and print publications, and in selling advertisements from its advertisers within offline newspapers and magazines. As of November 2014, Google operates over 70 offices over 40 countries (Jarvis 2011 ; Vise 2007 ).

2014–2017: Chrome development and facing challenges

In 2015, Google would turn HTTPS into the default. The better website is, the more users will trust search engine. In 2016, Google announced Android version 7, introduced a new VR platform called Daydream, and its new virtual assistant, Google Assistant.

Most of Google’s revenue comes from advertising (Rosenberg 2016 ). However, this “golden” business is entering a difficult period with many warning signs of its future. Google Search is the dominant strength of Google and bringing great revenue for the company. Nonetheless, when Amazon surpassed Google to become the world’s leading product in the search engine in last December, this advantage began to wobble. This is considered a fatal blow to Google when iOS devices account for 75% of their mobile advertising revenue (Rosenberg 2016 ).

By 2016, the number of people installing software to block ads on phones has increased 102% from 2015. Figure  1 illustrates that by the year’s end, about 16% of smart phone users around the world blocked their ads whilst surfing the web. These were also two groups having the most time on the Internet, high-earners and young people; however, these people have disliked ads (see Fig. 1 ).

Figure  2 shows the young people have the highest ad blocking rates. It is drawing a gloomy picture for the sustainable development of the online advertising industry in general and Google in particular. Therefore, in early 2017, Google has strategies to build an ad blocking tool, built into the Chrome browser. This tool allows users to access ads that have passed the “Coalition for Better Ads” filter so as to limit the sense of discomfort (see Fig. 2 ).

For the company impact, the history shows that speedy development of Google creates both economic and social impacts to followers in a new way of people connection (Savitz 2013 ). In this modern world, it seems that people cannot spend a day without searching any information in Google (Chen et al. 2014 ; Fast and Campbell 2004 ), a tool serves human information seeking needs. Even though when addressing this paper, it is also in need the information from Google search and uses it as a supporting tool. Nobody can deny the convenience of Google as a fast and easy way to search (Schalkwyk et al. 2010 ; Jones 2001 ; Langville and Meyer 2011 ).

Research question and methodology

In order to get the most comprehensive data and information for this case analysis, a number of methods are used, including:

Research data and collect information were mostly from the Harvard Study (Project Oxygen), which has been selected because it is related to the purpose of our study.

Data collection and analysis has been taken from Google Scholar and various websites related researches. We look at the history of appearance, development, and recognize the impacts of this company, as well as the challenges and the way the Board of Directors measures the abilities of their manager when the problem is found.

Analyzing: It was begun by considering expectations from the Harvard Study. Subsequently, considering the smaller organization (Zappos) in comparison of how its cultures and subcultures are accessed as well. Since then, the paper has clarified the management problem that Google and Zappos confront and deal with it so as to help other businesses apply this theoretical practice and achieve its goal beyond expectations.

In our paper, we mainly use the inductive method approach by compiling and describing the other authors’ theories of corporate culture, especially Google and Zappos in merging and comparing, analyzing them and making our own results.

From the aspects of the research, the questions are suggested as below:

What is the most instrumental element found from the Harvard study?

Is there any difference and similarity between a huge company and a smaller enterprise in perspective of culture and subculture?

What makes Google different from others, the dominant cultures as well as subcultures existing? How do leadership behaviors impact on the organizational culture?

How organizational culture impacts on business achievements?

The Harvard study

Project oxygen summary.

This project began in 2009 known as “the manager project” with the People and Innovation Lab (PiLab) team researching questions, which helped the employee of Google become a better manager. The case study was conducted by Garvin (2013) about a behavior measurement to Google’s manager, why managers matter and what the best manager s do. In early days of Google, there are not many managers. In a flat structure, most employees are engineers and technical experts. In fact, in 2002 a few hundred engineers reported to only four managers. But over time and out of necessity, the number of managers increased. Then, in 2009, people and team culture at Google noticed a disturbing trend. Exit interview data cited low satisfaction with their manager as a reason for leaving Google. Because Google has accessed so much online data, Google’s statisticians are asked to analyze and identify the top attributes of a good manager mentioned with an unsolved question: “Do managers matter?” It always concerns all stakeholders at Google and requires a data-based survey project called Project Oxygen to clarify employees’ concern, to measure key management behaviors and cultivate staff through communication and training (Bryant 2011 ; Garvin et al. 2013 ). Research −1 Exit Interviews, ratings, and semiannual reviews. The purpose is to identify high-scoring managers and low-scoring managers resulted in the former, less turnover on their teams, and its connection (manager quality and employee’s happiness). As for “what the best managers do”, Research-2 is to interview high and low scoring managers and to review their performance. The findings with 8 key behaviors illustrated by the most effective managers.

The Oxygen Project mirrors the managers’ decision-making criteria, respects their needs for rigorous analysis, and makes it a priority to measure impact. In the case study, the findings prove that managers really have mattered. Google, initially, must figure out what the best manager is by asking high and low scoring managers such questions about communication, vision, etc. Its project identifies eight behaviors (Bulygo 2013 ; Garvin et al. 2013 ) of a good manager that considered as quite simple that the best manager at Google should have. In a case of management problem and solution, as well as discussing four- key theoretical concepts, they will be analyzed, including formal organizational training system, how culture influences behavior, the role of “flow” and building capacity for innovation, and the role of a leader and its difference from the manager.

Formal organizational training system to create a different culture: Ethical culture

If the organizational culture represents “how we do things around here,” the ethical culture represents “how we do things around here in relation to ethics and ethical behavior in the organization” (Key 1999 ). Alison Taylor (The Five Levels of an Ethical Culture, 2017) reported five levels of an ethical culture, from an individual, interpersonal, group, intergroup to inter-organizational (Taylor 2017 ). In (Nelson and Treviño 2004 ), ethical culture should be thought of in terms of a multi-system framework included formal and informal systems, which must be aligned to support ethical judgment and action. Leadership is essential to driving the ethical culture from a formal and informal perspective (Schwartz 2013 ; Trevino and Nelson 2011 ). Formally, a leader provides the resources to implement structures and programs that support ethics. More informally, through their own behaviors, leadership is a role model whose actions speak louder than their words, conveying “how we do things around here.” Other formal systems include selection systems, policies and codes, orientation and training programs, performance management systems, authority structures, and formal decision processes. On the informal side are the organization’s role models and heroes, the norms of daily behavior, organizational rituals that support or do not support ethical conduct, the stories people tell about the organization and their implications for conduct, and the language people use, etc. Is it okay to talk about ethics? Or is ethical fading the norm?

The formal and informal training is very important. The ethical context in organizations helps the organizational culture have a tendency to the positive or negative viewpoints (Treviño et al. 1998 ). The leader should focus on providing an understanding of the nature and reasons for the organization’s values and rules, on providing an opportunity for question and challenge values for sincerity/practicality, and on teaching ethical decision-making skills related to encountered issues commonly. The more specific and customized training, the more effective it is likely to be. Google seemed to apply this theory when addressed the Oxygen Project.

How culture influences behavior

Whenever we approach a new organization, there is no doubt that we will try to get more about the culture of that place, the way of thinking, working, as well as behavior. And it is likely that the more diverse culture of a place is, the more difficult for outsiders to assess its culture becomes (Mosakowski 2004 ).

Realizing culture in (Schein 2009 ) including artifacts, espoused valued and shared underlying assumptions. It is easier for outsiders to see the artifacts (visual objects) that a group uses as the symbol for a group; however, it does not express more about the espoused values, as well as tacit assumptions. In (Schein et al. 2010 ), the author stated: “For a culture assessment to be valuable, it must get to the assumptions level. If the client system does not get to assumptions, it cannot explain the discrepancies almost always surface between the espoused values and the observed behavioral artifacts” (Schein et al. 2010 ). Hence, in order to be able to assess other cultures well, it is necessary for us to learn each other’s languages, as well as adapt to a common language. Moreover, we also need to look at the context of working, the solution for shared problems because these will facilitate to understand the culture better.

According to the OCP (Organizational Culture Profile) framework (Saremi and Nejad 2013 ), an organization is with possessing the innovation of culture, flexible and adaptable with fresh ideas, which is figured by flat hierarchy and title. For instance, Gore-Tex is an innovative product of W. L. Gore & Associates Inc., considered as the company has the most impact on its innovative culture (Boudreau and Lakhani 2009 ). Looking at the examples of Fast Company, Genentech Inc., and Google, they also encourage their employees to take challenges or risks by allowing them to take 20% of their time to comprehend the projects of their own (Saremi and Nejad 2013 ). In (Aldrich n.d. ), it is recorded that 25%–55% of employees are fully encouraged and giving a maximum value.

The famous quote by Peter Drucker , “Culture eats strategy for Breakfast” at page 67 has created a lot of interest in (Manning and Bodine 2012 ; Coffman and Sorensen 2013 ; Bock 2015 ). Despite we all know how important culture is, we have successively failed to address it (O'Reilly et al. 1991 ). The organizational research change process from the view of Schein ( 2009 ); it is a fact that whenever an organization has the intention of changing the culture, it really takes time. As we all acknowledge, to build an organizational culture, both leader and subordinate spend most of their time on learning, relearning, experiencing, as well as considering the most appropriate features. Sometimes, some changes are inevitable in terms of economic, political, technological, legal and moral threats, as well as internal discomfort (Kavanagh and Ashkanasy 2006 ; Schein 1983 ). As the case in (Schein 2009 ), when a CEO would like to make an innovation which is proved no effective response, given that he did not get to know well about the tacit implications at the place he has just come. It is illustrated that whatsoever change should need time and a process to happen (Blog 2015 ; Makhlouk and Shevchuk 2008 ). In conclusion, a new culture can be learned (Schein 1984 ), but with an appropriate route and the profits for all stakeholders should be concerned by the change manager (Sathe 1983 ).

It is true that people’s behavior managed by their types of culture (Kollmuss and Agyeman 2002 ). All tacit assumptions of insiders are not easy for outsiders to grasp the meaning completely (Schein 2009 ). It is not also an exception at any organization. Google is an example of the multicultural organization coming from various regions of the world, and the national or regional cultures making this multicultural organization with an official culture for the whole company.

In this case, the organizational culture of Google has an influence on the behaviors of manager and employee. In addition, as for such a company specializes in information technology, all engineers prefer to work on everything with data-evidence to get them involved in the meaningful survey about manager (Davenport et al. 2010 ). Eventually, Google discovered 8 good behaviors of manager, which effect to the role of “flow” also (Bulygo 2013 ; Garvin et al. 2013 ).

The role of the “flow” and building capacity for innovation

More and more people are using the term of “patient flow”. This overview describes patient flow and links to theories about flow. Patient flow underpins many improvement tools and techniques. The term “flow” describes the progressive movement of products, information, and people through a sequence of the process. In simple terms, flow is about uninterrupted movement (Nave 2002 ), like driving steadily along the motorway without interruptions or being stuck in a traffic jam. In healthcare, flow is the movement of patients, information or equipment between departments, office groups or organizations as a part of a patient’s care pathway (Bessant and Maher 2009 ). In fact, flow plays a vital role in getting stakeholders involved in working creatively and innovatively (Adams 2005 ; Amabile 1997 ; Forest et al. 2011 ). An effective ethical leader must create flow in work before transfer it to employees for changing the best of their effort to maintain, keep and develop “flow” in an engineering job, which job be easier to get stress. Definitely, Google gets it done very well.

Acknowledgements

Thanks to the knowledge from my Master course, a credit of managing culture which helps me to write this paper. The author also gratefully acknowledges the helpful comments and suggestions of the reviewers and Associate Professor Khuong- Ho Van, who provided general technical help that all have improved the article.

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Sang Kim Tran

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Tran, S.K. GOOGLE: a reflection of culture, leader, and management. Int J Corporate Soc Responsibility 2 , 10 (2017). https://doi.org/10.1186/s40991-017-0021-0

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Received : 16 May 2017

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DOI : https://doi.org/10.1186/s40991-017-0021-0

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Case Study: How Google Boosts its Employees’ Engagement

You might have heard about this mantra: ‘happy employees produce better results.’ this is the mindset of google to keep its employees productive and satisfied. this article explains more..

Let’s say you’re a company providing software development services . If your developer’s team isn’t enthusiastic about their projects every day, you’re not going to achieve excellence. This is productivity’s power. But remember productivity is dependent on the company’s culture.

Why is everyone talking about Google’s culture or work environment? We know that Google is one of the most influential and powerful companies around the globe. The company follows a pretty well unique culture instead of corporate culture.

It has something that every big organisation needs to follow to level up their employees’ engagement or morale. The culture of any company is vital to its success and Google is perfectly right on the track.

It has one sole purpose:  Keep the employees happy and keep up the productivity.

Google has been at number ONE place from the past six years and featured on  Fortune’s  annual list of  ‘Best Companies to Work For.’  And this is not it. Google has also been named as the tech company with the best culture. (Reported by Forbes) Furthermore, Google has a 4.4 rating on  Glassdoor  based on 6000+ employees reviews.   

Google’s morale

This is what the employees of Google answered the questions asked about their work culture.

• Acknowledged for the efforts?

Yes: 61 % Employees

Get started for free today.

No: 39% Employees

• Job Security?

Very Secure: 34 % Employees

Neutral: 19% Employees

Insecure: 8% Employees

Very insecure: 5% Employees

• Work Environment?

Positive: 85% Employees

Negative: 15% Employees

• Excited about going to work daily?

Yes: 80% Employees

No: 20% Employees

So, without further ado, let’s move towards the ways Google uses to boost its employees’ engagement .

“There are way easier places to work, but nobody ever changed the world on 40 hours a week. But if you love what you do, it (mostly) doesn’t feel like work.”- Elon Musk.

How Google Keeps Its Employees Productive And Engaged?

Exclusive perks.

Today, employees want a job in a company that makes them love what they do. Never for financial benefit or intellectual recognition. Yet instead of chance to add to the common good.

The major differentiator is to make a real difference.

Google offers different perks to its employees to show them that they are not only investing in their overall health but their future as well.

• Chef-prepared free organic food (breakfast, lunch, and dinner);
• Free dental and health checkup;
• Free and unlimited dry cleaning;
• Subsidised massages;
• Several foosball, ping pong, video games stations;
• On-site physicians;
• Gyms/swimming pools memberships;
• Free haircuts from professional hairdressers;
• In-house nap pods;
• Death benefits to deceased employees’ families, and;
• Hybrid car subsidies.

Flexibility

Google has been one of the very first companies that had a vision of understanding the employees’ needs. It lets its workers have a flexible schedule so that they can work on their terms and enhance creativity and productivity. They have given their employees complete freedom to work in a way that is most suitable to them.

Knowing the employees well

Google had gone through a series of laboratory tests to figure out the productivity of their employees. They had four different experiments that included 700 participants. All the employees were treated to free drinks, fruits, and chocolates or shown a comedy movie clip.

They also enquired some of the participants about the family tragedies as a part of their assessment. After this, they found that happiness is the reason for 12% more productivity.

Google promotes an innovative and diverse organisational culture that has been a part of its employee’s life. A positive creative atmosphere and a safe working space offered by Google to its workers keep them comfortable and happy at work. The concept that being a part of Google is about being smart and wise encourages the employees to think openly and keeps them productive.

Nowadays, there are different creative coworking spaces which are known to be a perfect alternate to a workplace. These spaces are believed to deliver various advantages such as strong networking and increased engagement.

Google’s founders were researchers who had a belief in innovation and freedom of thinking. This is one of the main factors that influenced the style of Google’s leadership.

According to Brassfield, 2013, a positive leadership style stimulates inspiring and motivating employees to develop innovative ideas and inventions.

Keeping people inspired

Future Workplace, in 2017, demonstrated in a study that one of the biggest threats to employees’ engagement is employee burnout. It has also been found out that many proficient workers are often overburdened with the tasks that lead to halted innovation, incomplete work, etc.

What does Google do about keeping its employees productive, inspired, or motivated? Google’s strategy for this is  20% time . Every employee devours up to 20% of his time at work each week on ventures that inspire him.

This concept inspires employees as it allows them to concentrate on things they love or are passionate about. It can prevent burnout, decrease turnover, increase engagement.

Image: Pexels

Career development

Google provides an extensive professional growth program that is successful and creative and guarantees long-term performance for all the employees. The career development program of Google is one that ensures incentives are provided to employees to meet their professional and personal progression.

Google has adopted a unique way to promote the professional development of all its employees. CareerGuru  is a career coaching that provides all the details to the employees by Google’s leaders about working at a specific role in the company.

Creativity Encouragement

The companies that believe in fostering a culture of creativity have happy, satisfied, and motivated employees. Google leads the way in promoting creativity in their employees.

They are free to express their ideas as a solution to any problem. Moreover, employees are encouraged to work wherever they are comfortable in the workplace. Google has a set up where rather than just considering an applicant’s professional background, they look to recruit people who are normally inquisitive and fond of learning.

Trusting Employees

Google believes in trusting their workers because trusted employees feel more valuable. It can also boost the sense of job satisfaction and can also decrease the rate of staff turnover.

In a survey by PwC, reliable employees are 76% more engaged in their work than those in a low trusting environment. Trusted employees are happier and they have the urge to go the extra miles.

Culture based on qualitative data

Google has always been searching out different ways to optimise the performance of its employees while ensuring their happiness and satisfaction. Everything done at Google is based on real data. They use the qualitative and quantitative facts to set up processes and every single rule that is streamlined.

Google has additionally performed researches to discover how much paid time off new mothers would need and ways of building an improvised and better culture.

Fun workplace

Have you ever been allowed to design your own workstation at your company?

Probably not. But Google does it. It lets the employees design their desks or workstations.

When you see the pictures of the workplace, it seems an interesting adult play and work area and not a dull and lifeless space.

Google has always tried to push the boundaries of its workspace.

Collaboration of coworkers

At Google, the employees are urged to collaborate. They have a program called ‘Googler to Googler’ to keep them productive and promote skills such as management, public speaking, orientation, or extracurricular activities.

It is crucial to build a sense of community to create a positive culture. The company has arranged several micro kitchens around the whole workspace where coworkers can have a little chit-chat session. No one has to spend time on deciding where to eat because Google has various break-out spaces for lunch.

Google’s way of listening

Google employees have developed great software and projects that include Gmail, AdSense, Google News, etc. and all these big projects were originated because of its staff productivity approach. Google has a way of collecting employees’ feedback and listening to their suggestions that is  gDNA.

• The employees utilise a device ‘Google Moderator’ , the result of 20% time strategy, to inquire about something and vote on inquiries of others;
• The company holds a meeting, every Friday, where the managers react to the most famous inquiries of the week;
• Leaders or managers utilise a charting instrument called Google-O-Meter to measure the prominence of various worker bits of advice;
• Leaders likewise plan “Fixits” to comprehend huge, critical issues; and,
• Fixits are 24-hour runs where team members give their full focus around discovering solutions for explicit issues.

So, can Google teach us anything?

If you are planning to adopt these learnings at your organisation just like Google keeps its employees productive, it’s essential to test the progressions first and measure the results.

It’s a great deal of work, however, the engagement advantages will make the difficult function admirably justified.

About the Author

Usman Akram is a digital marketer and SEO specialist who’s passionate about experimenting and discovering new SEO tactics and strategies to dominate search rankings while bringing an unmatched user-experience. As of now Usman is serving Buzz Interactive , a leading digital marketing agency as the head of SEO.

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Summary of case studies

Acintyo uses Firebase to streamline and speed up app development by 25%.

View the Acintyo case study

Ahoy Games increases purchases by 13% with Firebase Remote Config personalization.

View the Ahoy Games case study

American Express

American Express reduced app test costs by 50% using Firebase Test Lab for Android.

View the American Express case study

CrazyLabs uses Firebase Remote Config to maximize revenue at scale.

View the CrazyLabs case study

Doodle increased user engagement by 42% with Firebase Crashlytics and Firebase Remote Config.

View the Doodle case study

eBay Motors uses Firebase ML to quickly categorize images, reduce costs, and improve user experience.

View the eBay case study

Gameloft uses Firebase Crashlytics to lower crash rates and increase player session duration by 16%.

View the Gameloft case study

GameNexa Studios

GameNexa Studios uses Firebase to double in-app purchase revenue and diversify its monetization strategy.

View the GameNexa Studios case study

Halfbrick increases revenue by 16% with Firebase Remote Config personalization.

View the Halfbrick case study

Hawkin Dynamics

Hawkin Dynamics levels up their product in 2 weeks instead of months.

View the Hawkin Dynamics case study

Hotstar scales with Firebase and increases engagement by 38%.

View the Hotstar case study

KCB Group lowers cost per install 24% with Google Analytics.

View the KCB Group case study

Le Figaro leverages Firebase to increase paid subscriptions across mobile and web apps.

View the Le Figaro case study

Mobills increases subscriptions by 15% with Firebase Remote Config.

View the Mobills case study

NPR gains valuable insights into user behavior with Google Analytics.

View the NPR case study

Onefootball

Onefootball increased users' sessions by 5% by testing features before releasing them.

View the Onefootball case study

Playbuzz marketing team easily wins independency to configure ads based on app insights.

View the Playbuzz case study

Pomelo Games

Pomelo Games uses Firebase to increase revenue by up to 35% without losing players.

View the Pomelo Games case study

STAGE uses Firebase and Flutter to cut release time in half

View the STAGE case study

Qtonz MBit Music

Qtonz uses Firebase to boost ad revenue by 4x and grow engagement.

View the Qtonz MBit Music case study

Tamedia increases subscriber conversion with custom alerts by using Google Analytics and Firebase In-App Messaging.

View the Tamedia case study

Tapple uses Firebase Remote Config to increase subscriptions by 8%.

View the Tapple case study

Tapps Games

Tapps Games increases crash-free user rate and improves ratings with Firebase Crashlytics and Firebase Remote Config.

View the Tapps Games case study

Vinwap increases ad revenue by 30% with Firebase A/B Testing and Firebase Remote Config.

View the Vinwap case study

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2024-05-10 UTC.

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Gender and Free Speech at Google (A)

• Format: Print
• | Language: English
• | Pages: 36

About The Author

Nien-he Hsieh

Related work.

• Faculty Research

Gender and Free Speech at Google (B)

• March 2019 (Revised June 2019)

Gender and Free Speech at Google (C)

Gender and free speech at google (a), (b), & (c).

• Gender and Free Speech at Google (B)  By: Nien-hê Hsieh and Sarah Mehta
• Gender and Free Speech at Google (C)  By: Nien-hê Hsieh and Sarah Mehta
• Gender and Free Speech at Google (A), (B), & (C)  By: Nien-hê Hsieh and Sarah Mehta
• Gender and Free Speech at Google (A)  By: Nien-hê Hsieh, Martha J. Crawford and Sarah Mehta

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Free Google Docs Case Study Templates

By Kate Eby | January 18, 2024

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We’ve collected several free, customizable case study templates in Google Docs format for marketing managers, content creators, sales reps, and product managers. Use these templates for customer stories, sales collateral, and product development.

On this page, you’ll find eight dynamic Google Docs case study templates, including a  case study report template , a  project case study template , a  marketing case study template , and a  one-page case study template .

Google Docs Simple Case Study Template

Download the Sample Simple Case Study Template for Google Docs Download the Blank Simple Case Study Template for Google Docs

When to Use This Template: Marketing managers and content creators can use this template — with or without sample data — to deliver clear and short case studies. First-time case study writers will appreciate the template’s straightforward approach. 

Notable Template Features:  This simple case study template focuses on the main points and results, so it's not overly detailed. You’ll find room to include an introduction, customer challenges, marketing strategies, and results.

See this selection of free marketing case studies available in PowerPoint format that are ready to use in presentations.

Google Docs Case Study Report Template

Download the Sample Case Study Report Template for Google Docs Download the Blank Case Study Report Template for Google Docs

When to Use This Template: Use this case study report template for Google Docs to make a detailed report. Download the version with sample text to get an idea of how to complete the template. It's perfect for marketing managers or product managers who want to dive deep into their analysis and show lots of data and insights. 

Notable Template Features: The report-style format of this template features a comprehensive layout with plenty of room to go into detail and depth. When complete, it helps you look closely at complex marketing issues, evaluate lots of data, and put together clear, professional reports. 

Check out these free marketing case study templates in various formats, ideal for highlighting marketing achievements and tactics.

Google Docs Project Case Study Template

Download the Sample Project Case Study Template for Google Docs Download the Blank Project Case Study Template for Google Docs

When to Use This Template:  Choose this project case study template when you want to show off how well you managed and executed your project. Project managers or content creators who need some guidance on how to complete this template should download the version with sample text. 

Notable Template Features:  The visually driven template format renders the content easier to grasp and effectively communicates the success of your marketing tactics. Use visuals such as line charts, pie charts, and bar charts to explain your project's success in a clear, easy-to-understand way. 

For additional sales tools, take a look at our selection of free case study templates available in Microsoft Word format.

Google Docs Marketing Case Study Template

Download the Sample Marketing Case Study Template for Google Docs Download the Blank Marketing Case Study Template for Google Docs

When to Use This Template:  Marketing managers, sales representatives, and content creators who want to demonstrate how their efforts have positively impacted the business should use this marketing case study template. Download the version with sample text for guidance on completing your own case study. 

Notable Template Features: This template includes additional sections specifically designed for marketing stories. You’ll find space to provide information about the company, challenge, solution, what happened, and benefits. Its visually appealing format helps explain complex marketing information simply.

Google Docs One-Page Case Study Template

Download the Sample One-Page Case Study Template for Google Docs Download the Blank One-Page Case Study Template for Google Docs

When to Use This Template:  Select this one-page case study template — with or without sample data — when you need to make a strong impression fast. It's great for sales representatives or marketing managers who want to grab the attention of busy decision-makers with a short, impactful summary. 

Notable Template Features: The template’s concise one-page format helps you get straight to the point. Add information about key results and any highlights and use it as part of a sales pitch or other business presentation.

Google Docs Problem-Solution-Impact Case Study Template

Download the Sample Problem-Solution-Impact Case Study Template for Google Docs Download the Blank Problem-Solution-Impact Case Study Template for Google Docs

When to Use This Template: Choose this problem-solution-impact case study template to outline a clear sequence of events. Download the version with sample text to see how to identify the problem and reveal the solution and its effects in a straightforward way.

Notable Template Features:  This template’s linear narrative structure sets it apart. Complete the  Problem, Solution , and  Impact  sections to end up with a straightforward, chronological approach to storytelling.

Google Docs Comparative Study Template

Download the Sample Comparative Study Template for Google Docs Download the Blank Comparative Study Template for Google Docs

When to Use This Template: Use this comparative study template to compare such items as marketing campaigns or strategies. Download the version with sample data to quickly see an example that highlights changes over time or how different approaches stack up against each other. 

Notable Template Features: This template layout is ideal for side-by-side comparisons. You can easily put two items next to each other to see how they compare, making it a useful tool for looking at changes and trends clearly.

Google Docs Case Study Storyboard Template

Download the Sample Case Study Storyboard Template for Google Docs Download the Blank Case Study Storyboard Template for Google Docs

When to Use This Template:  Pick this case study storyboard template when you want to present your case study like a visual story. It’s perfect for marketing teams that prefer using more pictures and fewer words in their case study.

Notable Template Features: This template focuses on storytelling with visuals. Unlike other templates, it uses images and graphics to walk through the case study, making it stand out for presentations.

Streamline and Collect All the Elements Needed for a Case Study with Smartsheet

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When teams have clarity into the work getting done, there’s no telling how much more they can accomplish in the same amount of time.  Try Smartsheet for free, today.

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From Assistant to Analyst: The Power of Gemini 1.5 Pro for Malware Analysis

Bernardo quintero, try gemini 1.5 pro.

Google's most advanced multimodal model in Vertex AI

Executive Summary

A growing amount of malware has naturally increased workloads for defenders and particularly malware analysts, creating a need for improved automation and approaches to dealing with this classic threat.

With the recent rise in generative AI tools, we decided to put our own Gemini 1.5 Pro to the test to see how it performed at analyzing malware. By providing code and using a simple prompt, we asked Gemini 1.5 Pro to determine if the file was malicious, and also to provide a list of activities and indicators of compromise.

We did this for multiple malware files, testing with both decompiled and disassembled code, and Gemini 1.5 Pro was notably accurate each time, generating summary reports in human-readable language. Gemini 1.5 Pro was even able to make an accurate determination of code that — at the time — was receiving zero detections on VirusTotal. 

In our testing with other similar gen AI tools, we were required to divide the code into chunks, which led to vague and non-specific outcomes, and affected the overall analysis. Gemini 1.5 Pro, however, processed the entire code in a single pass, and often in about 30 to 40 seconds.

Introduction

The explosive growth of malware continues to challenge traditional, manual analysis methods, underscoring the urgent need for improved automation and innovative approaches. Generative AI models have become invaluable in some aspects of malware analysis, yet their effectiveness in handling large and complex malware samples has been limited. The introduction of Gemini 1.5 Pro , capable of processing up to 1 million tokens, marks a significant breakthrough. This advancement not only empowers AI to function as a powerful assistant in automating the malware analysis workflow but also significantly scales up the automation of code analysis. By substantially increasing the processing capacity, Gemini 1.5 Pro paves the way for a more adaptive and robust approach to cybersecurity, helping analysts manage the asymmetric volume of threats more effectively and efficiently.

Traditional Techniques for Automated Malware Analysis

The foundation of automated malware analysis is built on a combination of static and dynamic analysis techniques, both of which play crucial roles in dissecting and understanding malware behavior. Static analysis involves examining the malware without executing it, providing insights into its code structure and unobfuscated logic. Dynamic analysis, on the other hand, involves observing the execution of the malware in a controlled environment to monitor its behavior, regardless of obfuscation. Together, these techniques are leveraged to gain a comprehensive understanding of malware.

Parallel to these techniques, AI and machine learning (ML) have increasingly been employed to classify and cluster malware based on behavioral patterns, signatures, and anomalies. These methodologies have ranged from supervised learning, where models are trained on labeled datasets, to unsupervised learning for clustering, which identifies patterns without predefined labels to group similar malware.

Despite technological advancements, the increasing complexity and volume of malware present substantial challenges. While ML enhances the detection of malware variants, it remains inadequate against completely new threats. This detection gap allows advanced attacks to slip through cybersecurity defenses, compromising system protection.

Generative AI as Malware Analysis Assistant 

Code Insight , unveiled at the RSA Conference 2023, marked a significant step forward in leveraging generative AI (gen AI) for malware analysis. This novel feature of Google's VirusTotal platform specializes in analyzing code snippets and generating reports in natural language, effectively emulating the approach of a malware analyst. Initially supporting PowerShell scripts, Code Insight later expanded to other scripting languages and file formats, including Batch, Shell, VBScript, and Office documents.

By processing the code and generating summary reports, Code Insight assists analysts in understanding the behavior of the code and identifying attack techniques. This includes uncovering hidden functionalities, malicious intent, and potential attack vectors that might be missed by traditional detection methods .

However, due to the inherent constraints of large language models (LLMs) and their limited token input capacity, the size of files that Code Insight could handle was restricted. Although there have been continuous improvements to increase the maximum file size limit and support more formats, analyzing binaries and executables still poses a significant challenge. When these files are disassembled or decompiled, their code size typically surpasses the processing capabilities of the LLMs available at the time. Consequently, gen AI models have functioned primarily as assistants to human analysts, enabling the analysis of specific code fragments from binaries rather than processing the entire code, which is often too voluminous for these models.

Reverse Engineering: The Human Face of Malware Analysis

Reverse engineering is arguably the most advanced malware analysis technique available to cybersecurity professionals. This process involves disassembling the binaries of malicious software and carrying out a meticulous examination of the code. Through reverse engineering, analysts can uncover the exact functionality of malware and understand its execution flow. However, this method is not without its challenges. It requires an immense amount of time, a deep level of expertise, and an analytical mindset to interpret each instruction, data structure, and function call to reconstruct the malware's logic and uncover its secrets.

Furthermore, scaling reverse engineering efforts poses a significant challenge. The scarcity of specialized talent in this field exacerbates the difficulty of conducting these analyses at scale. Given the intricate and time-consuming nature of reverse engineering, the cybersecurity community has long sought ways to augment this process, making it more efficient and accessible.

Gemini 1.5 Pro: Scalable Reverse Engineering for Malware Analysis

The ability to process prompts of up to 1 million tokens enables a qualitative leap in malware analysis, particularly in the realm of reverse engineering. This advancement finally brings the power of gen AI to the analysis of binaries and executables, a task previously reserved for highly skilled human analysts due to its complexity.

How does Gemini 1.5 Pro achieve this?

Increased capacity : With its expanded token limit, Gemini 1.5 Pro can entirely analyze some disassembled or decompiled executables in a single pass, eliminating the need to break down code into smaller fragments. This is crucial because fragmenting code can lead to a loss of context and important correlations between different parts of the program. When analyzing only small snippets, it is difficult to understand the overall functionality and behavior of the malware, potentially missing key insights into its purpose and operation. By analyzing the entire code at once, Gemini 1.5 Pro gains a holistic understanding of the malware, allowing for more accurate and comprehensive analysis.

Code interpretation : Gemini 1.5 Pro can interpret the intent and purpose of the code, not just identify patterns or similarities. This is possible due to its training on a massive dataset of code, encompassing assembly language from various architectures, high-level languages like C, and pseudo-code produced by decompilers. This extensive knowledge base, combined with its understanding of operating systems, networking, and cybersecurity principles, allows Gemini 1.5 Pro to effectively emulate the reasoning and judgment of a malware analyst. As a result, it can predict the malware's actions and provide valuable insights even for never-seen-before threats. For more information on this, see the zero day case study section later in this post.

Detailed analysis : Gemini 1.5 Pro can generate summary reports in human-readable language, making the analysis process more accessible and efficient. This goes far beyond the simple verdicts typically provided by traditional machine learning algorithms for classification and clustering. Gemini 1.5 Pro's reports can include detailed information about the malware's functionality, behavior, and potential attack vectors, as well as indicators of compromise (IOCs) that can be used to feed other security systems and improve threat detection and prevention capabilities.

Let's explore a practical case study to examine how Gemini 1.5 Pro performs in analyzing decompiled code with a representative malware sample. We processed two WannaCry binaries automatically using the Hex-Rays decompiler, without adding any annotations or additional context. This approach resulted in two C code files, one 268 KB and the other 231 KB in size, which together amount to more than 280,000 tokens for processing by the LLM.

In our testing with other similar gen AI tools, we faced the necessity of dividing the code into chunks. This fragmentation often compromised the comprehensiveness of the analysis, resulting in vague and non-specific outcomes. These limitations highlight the challenges of using such tools with complex code bases.

Gemini 1.5 Pro, however, marks a significant departure from these constraints. It processes the entire decompiled code in a single pass, taking just 34 seconds to deliver its analysis. The initial summary provided by Gemini 1.5 Pro is notably accurate, showcasing its ability to handle large and complex datasets seamlessly and effectively:

Issues a malicious verdict associated with ransomware

Identifies some files as IOCs (c.wnry and tasksche.exe)

Acknowledges the use of an algorithm to generate IP addresses and perform network scans to find targets on port 445/SMB to spread to other computers

Identifies URL/domain (WannaCry's "killswitch") and relevant registry key and mutex

While it might seem that Gemini 1.5 Pro's report of WannaCry is based on pre-trained knowledge of this specific malware, this isn't the case. The analysis comes from the model's ability to independently interpret the code. This will become even clearer as we look at the upcoming examples where Gemini 1.5 Pro analyzes unfamiliar malware samples, demonstrating its wide-ranging capabilities.

LLM on Code: Disassembled vs. Decompiled

In the previous example showcasing WannaCry analysis, there was a crucial step before feeding the code to the LLM: decompilation. This process, which transforms binary code into a higher-level representation like C, is fully automated and mirrors the initial steps taken by malware analysts when manually dissecting malicious software. But what is the difference between disassembled and decompiled code, and how does it impact LLM analysis?

Disassembly: This process converts binary code into assembly language, a low-level representation specific to the processor architecture. While human-readable, assembly code is still quite complex and requires significant expertise to understand. It is also much longer and more repetitive than the original source code.

Decompilation: This process attempts to reconstruct the original source code from the binary. While not always perfect, decompilation can significantly improve readability and conciseness compared to disassembled code. It achieves this by identifying high-level constructs like functions, loops, and variables, making the code easier to understand for analysts.

Given these factors, when using LLMs for binary analysis, decompilation offers several advantages on efficiency and scalability. The shorter and more structured output from decompilation fits more readily within the processing constraints of LLMs, allowing for a more efficient analysis of large or complex binaries. In fact, the output from a decompiler is five to 10 times more concise than that produced by a disassembler.

Disassembly is necessary to perform accurate decompilation and remains an invaluable tool in certain scenarios where detailed, low-level analysis is crucial. Given the structured and higher-level nature of decompiled output, there are specific circumstances where disassembly provides insights that decompilation cannot match.

Fortunately, Gemini 1.5 Pro demonstrates equal capability in processing both high-level languages and assembly across various architectures. Thus, our implementation for automating binary analysis can utilize both strategies or adopt a hybrid approach, as suited to the specific circumstances of each case. This flexibility allows us to tailor our analysis method to the nature of the binary in question, optimizing for efficiency, depth of insight, and the specific objectives of the analysis, whether that means dissecting the logic and flow of the program or diving into the intricate details of its low-level operations.

Next, we'll examine a case where we directly employ disassembly for analysis. This time, we're working with a more recent and unknown binary; in fact, the executable submitted to VirusTotal is flagged as malicious by only four out of the 70 VirusTotal anti-malware engines, and only in a generic sense, without providing any details about the malware family that could offer further clues about its behavior.

After automatic preprocessing with HexRays/IDA Pro, the 306.50 KB executable binary produces a 1.5 MB assembly file that Gemini 1.5 Pro can process in a single pass within 46 seconds , thanks to its large token window in the prompt. This capability allows for an analysis of the entire assembly output, offering detailed insights into the binary's operations.

This case of the unknown binary showcases the remarkable capabilities of Gemini 1.5 Pro. Despite only four out of 70 anti-malware engines on VirusTotal flagging the file as malicious—using only generic signatures—Gemini 1.5 Pro identified the file as malicious, providing a detailed explanation for its verdict. The file is likely a game cheat designed to inject a game hack dynamic-link library (DLL) into the Grand Theft Auto video game process. The designation of "malicious" may depend on perspective: deemed malicious by the game's developers or their security team focused on anti-cheating measures, yet potentially desirable for some players. Nevertheless, this automated first-pass analysis is not only impressive but also illuminating regarding the nature and intent of the binary.

Unveiling the Unknown: A Case Study in Zero-Day Detection

The true test of any malware analysis tool lies in its ability to identify never-before-seen threats undetected by traditional methods and proactively protecting systems from zero-day attacks. Here, we examine a case where an executable file is undetected by any anti-virus or sandbox on VirusTotal.

The 833 KB file, medui.exe, was decompiled into 189,080 tokens and subsequently processed by Gemini 1.5 Pro in a mere 27 seconds to produce a complete malware analysis report in a single pass.

This analysis revealed suspicious functionalities, leading Gemini 1.5 Pro to issue a malicious verdict. Based on its observations, it concluded that the primary goal of this malware is to steal cryptocurrency by hijacking Bitcoin transactions and evading detection through the disabling of security software.

This showcases Gemini's ability to go beyond simple pattern matching or ML classification and leverage its deep understanding of code behavior to identify malicious intent, even in previously unseen threats. This is a significant advancement in the field of malware analysis, as it allows us to proactively detect and respond to new and emerging threats that traditional methods might miss.

From Assistant to Analyst

Gemini 1.5 Pro unlocks impressive capabilities, enabling the analysis of large volumes of decompiled and disassembled code. It has the potential to significantly change our approach to fighting malware by enhancing efficiency, accuracy, and our ability to scale in response to a growing number of threats.

However, it's important to remember that this is just the beginning. While Gemini 1.5 Pro represents a significant leap forward, the field of gen AI is still in its infancy. There are several challenges that need to be addressed to achieve truly robust and reliable automated malware analysis:

Obfuscation and packing: Malware authors are constantly developing new techniques to obfuscate their code and evade detection. In response, there's a growing need to not only continuously improve gen AI models but also to enhance the preprocessing of binaries before analysis. Adopting dynamic approaches that utilize various preprocessing tools can more effectively unpack and deobfuscate malware. This preparatory step is crucial for enabling gen AI models to accurately analyze the underlying code, ensuring they keep pace with evolving obfuscation techniques and remain effective in detecting and understanding sophisticated malware threats.

Increasing binary size: The complexity of modern software is mirrored in the growing size of its binaries. This trend presents a significant challenge, as the majority of gen AI models are constrained by much lower token window limits. In contrast, Gemini 1.5 Pro stands out by supporting up to 1 million tokens—currently the highest known capacity in the field. Nevertheless, even with this remarkable capability, Gemini 1.5 Pro may encounter limitations when handling exceptionally large binaries. This underscores the ongoing need for advancements in AI technology to accommodate the analysis of increasingly large files, ensuring comprehensive and effective malware analysis as software complexity continues to escalate.

Evolving attack techniques: As attackers continuously innovate, crafting new methods to bypass security measures, the challenge for gen AI models extends beyond simple adaptability. These models must not only learn and recognize new threats but also evolve in conjunction with the efforts of researchers and developers. There's a need to devise new methods for automating the preprocessing of threat data, which would enrich the context provided to AI models. For instance, integrating additional data from static and dynamic analysis tools, such as sandbox reports, plus the decompiled and disassembled code, can significantly enhance the models' understanding and detection capabilities. 

The journey towards scaling automated malware analysis is ongoing, but Gemini 1.5 Pro marks a significant milestone. Give Gemini 1.5 Pro a try ; we look forward to seeing the innovative ways the community leverages it to enhance security operations.

At GSEC Malaga , we continue to research and develop ways to apply these models effectively in AI, pushing the boundaries of what's possible in cybersecurity and contributing to a safer digital future.  

Malware Details

The following table contains details on the malware samples discussed in this post.

The following is the exact prompt used in all the examples covered in the post. The only exception is the example where the word "disassembled" is used instead of "decompiled" because, as explained, we're working with disassembled code rather than decompiled code to show that Gemini 1.5 Pro can interpret both.

• Threat Intelligence
• Security & Identity

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Last updated 2024-05-02 UTC.