In the past few years, numerous studies have indicated that on top of the social good it can do, diversity and inclusion has bottom-line benefits for organizations that invest in it. Research has found that diversity helps teams think better by disrupting conformity, that companies with more women in leadership make more money, and that businesses that engage in racial discrimination are more likely to fail. Our work at CEB, now Gartner, also finds that organizations tend to perform significantly better when they have more inclusive work environments. While some scholars have questioned a few of the links between diversity and performance or argued that this isn’t the right reason to invest in D&I, there is plenty of material out there with which to make the business case for it.
Another way of thinking about the value of diversity is in terms of the costs of homogeneity and exclusivity. MIT business professor Evan Apfelbaum recently dove into the specific ways diverse teams can improve teams’ decision making in an interview at the MIT Sloan Management Review. Apfelbaum’s research found that diverse teams spent more time deliberating important decisions, while more homogenous groups were prone to falling into a groupthink trap, where mistaken opinions are more likely to spread. Indeed, that’s one reason to think twice before recruiting for “culture fit.”
Previous studies on juries and student groups found that being on a racially diverse team changed how people approached legal issues and that people prepared more thoroughly when they knew they would be discussing things with a more diverse group. In both of Apfelbaum’s studies, this led to higher quality outcomes.
In this half-hour talk posted last week at re:Work, Google’s VP of People Operations Prasad Setty discusses his experience leading the development of the search giant’s talent analytics program, and about the key difference he discovered between having data make decisions for people, and using data to improve the way people make decisions:
When Prasad Setty joined Google ten years ago to build its People Analytics team, he envisioned a workplace where all people-related decisions would be made by data and analytics. If algorithms were spitting out search terms, why couldn’t we use them to make decisions for and about our people?
Setty soon discovered that this was the wrong approach. Despite the ability of analytics to objectively predict outcomes with high accuracy, people were reluctant to rely solely on formulas when it came to making important decisions — especially decisions that involved people, such as a promotion. And so, Setty shifted his vision for the People Analytics team. Rather than using data and analytics to make all decisions at Google, the team’s mission would be to educate Googlers on how they were making decisions and to help them make better decisions over time.
What really stands out about Google’s approach here is that they chose not to use a quantitative focus, even though they had the analytic sophistication necessary to do so. At one point, Setty mentions how HR was able to create a logistic predictive model that was able to accurately predict promotion decisions with an error rate of only 10 percent based on a few easily measurable attributes. Despite this, the engineers involved in the hiring process made it very clear that they did not want to outsource such an important task away to an algorithm.
This is an important lesson in how organizations can effectively use data in managing talent issues, particularly culture change.
Kelly Max, the CEO of Haufe USA, was elected to the job by Haufe’s employees in 2015 and must be re-elected each year to keep his position. Writing in Fast Company, Max retells how “corporate democracy” became the norm at his organization:
My company, Haufe, adopted leadership elections four years ago, when our founder, Hermann Arnold, realized he wasn’t the right candidate for global CEO as the company grew and expanded. Arnold stepped down from that post in 2011 and assumed the role of chairman. Then, rather than simply appoint someone, Arnold asked himself, “If we truly believe employees run companies—as our fundamental market approach says—what better way to prove it than to have our employees elect the next CEO and other top leaders?” So all 200 employees at the time were enfranchised, and they chose Marc Stoffel as the company’s CEO.
That set a pattern, which the company followed globally.
One rationale for Haufe’s democratic experiment is to prevent the emergence of “shadow organizations” within the company, he explains: