$1.$ Case Study $1$: $$Project Oxygen$$ Resuscitates Google$$s Poor$-$Performing Bosses

When it comes to gathering data and analyzing it to build new and better products, few companies do it as well as Google. Recently, Google decided to use its info$-$tech expertise to answer an important question: Since people make the difference between good and great companies, could a data$-$driven, analytical approach be used to improve Google$$s human resources management function? Such an approach worked for Billy Beane, so surely it could work for Google, couldn$$t it$?$ Recall from Chapter $1$ that Beane, the manager of the Oakland A$$s$,$ dramatically improved players and the team using data and statistics. $($Actor Brad Pitt dramatized Beane$$s efforts in the movie Moneyball.$)$

One thing Google wanted to know was if it could $$build$$ better bosses. Why? Because despite the many job perks Google$$s workers get, the company$$s employee turnover rate was surprisingly high. It$$s been said that the number $1$ reason people leave their jobs is because of their bosses. Could this be true at Google? And if so$,$ could the behaviors of good bosses be pinpointed and used to improve the performance of not$-$so$-$good bosses? The researchers at Google wanted to find out. They also wanted to answer these questions using data from their own organization to find out precisely what would work for Google rather than other organizations.

To answers these questions, a team of $25-$plus Google researchers and scientists began studying the company$$s supervisors using their performance reviews, surveys from their employees, interviews, and observations of their behaviors. Over $10,000$ observations were collected on $100$ variables to determine how well the supervisors were performing. Initially, not all supervisors were thrilled to be evaluated by their subordinates and $$put under the microscope.$$ Consequently, the effort took some $$selling$$ to Google$$s top management. The fact that the researchers could point to dramatic differences in the overall ratings employees gave different managers and that some teams performed much better than others helped fuel the fire to get $$Project Oxygen$$ off the ground. $($Presumably$,$ a good boss gives you room to breathe, whereas a bad boss can suck the life right out of you, hence the project$$s name.$)$

Once concluded, Project Oxygen yielded a wealth of information, some which mirrored conventional wisdom and some which did not: Teams with higher$-$rated managers performed better, the employees in them were happier, and they stayed with the company longer. Their managers had more impact on how the employees felt about their jobs than any other factor. However, it turned out that best bosses weren$$t the ones with the greatest technical expertise, as Google had anticipated. Instead, they were those who are even tempered, help their employees think through problems without micromanaging them, and care about them as people. Google then used the information it gathered to implement training and coaching programs to quickly improve the managerial skills of its worst$-$performing managers.

Specifically, Google identified eight behaviors you should engage in if you want to be a good boss$$at least at Google:

$1.$ be a good coach

$2.$ empower your team and don$$t micromanage

$3.$ express interest in team members$$ success and personal well$-$being

$4.$ be productive and results oriented

$5.$ be a good communicator and listen to your team

$6.$ help your employees with career development

$7.$ have a clear vision and strategy for the team

$8.$ have key technical skills so you can help advise the team

According to the case, successful Google managers are leaders and coaches. If all Google managers were measured on technical performance standards, but not on their coaching or leadership abilities, this would result in:

criterion contamination.

strategic irrelevance.

criterion deficiency.

unreliability.