Google’s Scientific Approach to Work-Life Balance (and Much More)
March 27, 2014 Editor 0
More than 65 years ago in Massachusetts, doctors began a longitudinal study that would transform our understanding of heart disease. The Framingham Heart Study, which started with more than 5,000 people and continues to this day, has become a data source for not just heart disease, but also for insights about weight loss (adjusting your social network helps people lose weight), genetics (inheritance patterns), and even happiness (living within a mile of a happy friend has a 25% chance of making you happier).
Upon reading about the study, I wondered if the idea of such long-term research could be attempted in another field that touches all of us: work. After more than a decade in People Operations, I believe that the experience of work can be — should be — so much better. We all have our opinions and case studies, but there is precious little scientific certainty around how to build great work environments, cultivate high performing teams, maximize productivity, or enhance happiness.
Inspired by the Framingham research, our People Innovation Lab developed gDNA, Google’s first major long-term study aimed at understanding work. Under the leadership of PhD Googlers Brian Welle and Jennifer Kurkoski, we’re two years into what we hope will be a century-long study. We’re already getting glimpses of the smart decisions today that can have profound impact on our future selves, and the future of work overall.
This isn’t your typical employee survey. Since we know that the way each employee experiences work is determined by innate characteristics (nature) and his or her surroundings (nurture), the gDNA survey collects information about both. Here’s how it works: a randomly selected and representative group of over 4,000 Googlers completes two in-depth surveys each year. The survey itself is built on scientifically validated questions and measurement scales. We ask about traits that are static, like personality; characteristics that change, like attitudes about culture, work projects, and co-workers; and how Googlers fit into the web of relationships around all of us. We then consider how all these factors interact, as well as with biographical characteristics like tenure, role and performance. Critically, participation is optional and confidential.
What do we hope to learn? In the short-term, how to improve wellbeing, how to cultivate better leaders, how to keep Googlers engaged for longer periods of time, how happiness impacts work and how work impacts happiness.
For example, much has been written about balancing work and personal life. But the idea that there is a perfect balance is a red herring. For most people work and life are practically inseparable. Technology makes us accessible at all hours (sorry about that!), and friendships and personal connections have always been a part of work.
Our first rounds of gDNA have revealed that only 31% of people are able to break free of this burden of blurring. We call them “Segmentors.” They draw a psychological line between work stress and the rest of their lives, and without a care for looming deadlines and floods of emails can fall gently asleep each night. Segmentors reported preferences like “I don’t like to have to think about work while I am at home.”
For “Integrators”, by contrast, work looms constantly in the background. They not only find themselves checking email all evening, but pressing refresh on gmail again and again to see if new work has come in. (To be precise, people fall on a continuum across these dimensions, so I’m simplifying a bit.)
Of these Integrators (69% of people), more than half want to get better at segmenting. This group expressed preferences like “It is often difficult to tell where my work life ends and my non-work life begins.”
The fact that such a large percentage of Google’s employees wish they could separate from work but aren’t able to is troubling, but also speaks to the potential for this kind of research. The existence of this group suggests that it is not enough to wish yourself into being a Segmentor. But by identifying where employees fall on this spectrum, we hope that Google can design environments that make it easier for employees to disconnect. Our Dublin office, for example, ran a program called “Dublin Goes Dark” which asked people to drop off their devices at the front desk before going home for the night. Googlers reported blissful, stressless evenings. Similarly, nudging Segmentors to ignore off-hour emails and use all their vacation days might improve well-being over time. The long-term nature of these questions suggests that the real value of gDNA will take years to realize.
Beyond work-life balance there are any number of fascinating puzzles that we hope this longitudinal approach can help solve. For a given type of problem, what diverse characteristics should a team possess to have the best chance of solving it? What are the biggest influencers of a satisfying and productive work experience? How can peak performance be sustained over decades? How are ideas born and how do they die? How do we maximize happiness and productivity at the same time?
The best part is that, just like the Framingham researchers, we don’t yet know what we’ll discover. They worked for 20 years before trends began to emerge, and today those findings are among the clearest risk factors of heart disease we’ve got–think cigarette smoking, lack of exercise, and obesity. gDNA is still in its infancy, and is inherently limited because we’re only including current and former Googlers. But already Googlers tell us that learning more about themselves has been eye-opening. In the future, we hope to find ways to share our data and findings more broadly. It’s thrilling not just to reimagine work at Google but to get to work with academics and other partners who can bring new perspectives to help us think beyond our ranks.
People Science needs to be adaptive. By analyzing behaviors, attitudes, personality traits and perception over time, we aim to identify the biggest influencers of a satisfying and productive work experience. The data from gDNA allows us to flex our people practices in anticipation of our peoples’ needs.
We have great luxuries at Google in our supportive leadership, curious employees who trust our efforts, and the resources to have our People Innovation Lab. But for any organization, there are four steps you can take to start your own exploration and move from hunches to science:
1. Ask yourself what your most pressing people issues are. Retention? Innovation? Efficiency? Or better yet, ask your people what those issues are.
2. Survey your people about how they think they are doing on those most pressing issues, and what they would do to improve.
3. Tell your people what you learned. If it’s about the company, they’ll have ideas to improve it. If it’s about themselves – like our gDNA work – they’ll be grateful.
4. Run experiments based on what your people tell you. Take two groups with the same problem, and try to fix it for just one. Most companies roll out change after change, and never really know why something worked, or if it did at all. By comparing between the groups, you’ll be able to learn what works and what doesn’t.
And in 100 years we can all compare notes.
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