Google's Scientific Approach to Work-Life Balance (and Much More)
J Thoendell stashed this in Tech
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.
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."
There's something coldly robotic about this approach.
I agree it kind of sucks the life out of things. It is like this article I read in which an author (Baumeister) was distinguishing between a happy life and a meaningful life, but he controlled for so much stuff to differentiate the two that it was unclear what exactly he was measuring in the end!
I love science but sometimes, to ensure proper quantitative research methods have been applied, it takes out all the wonderful nuances in life.
Well said, Patricia. Whatever we do needs to retain its inherent humanity.