It is a critical area with high stakes. For example, there is evidence that different groups perform better, because of the integration of different skills and perspectives, and that fair systems create employee loyalty by giving credit where credit is due. In addition, racial, ethnic, and other biases in hiring, promotion, and compensation have significant legal implications for businesses and other organizations.
The good news is that there are new ways to improve diversity, equity and value — with the data already available in your business. New technology enables you to use data to visualize, understand and address diversity and performance issues in unprecedented and sustainable ways.
Here are three specific ways to make this happen.
Quantify to correct stereotypes
Although stereotypes are usually wrong on any individual basis, they affect how a person’s contributions are valued and recognized. Specifically, stereotypes create a situation of “believing what you see” where people distort reality to fit their preconceived view of a given group, such as the contribution of gender stereotypes to devaluing the contributions of women in multiple settings.
To resolve such biases, the broad idea is to create transparency about who is contributing what and how, so that real performance is quantified – fairly – and visible. While it was previously expensive to collect comprehensive, accurate data that creates transparency, such data is now commonly collected cheaply as a byproduct of team-based collaboration platforms.
Popular tech collaboration platforms like Slack, Dropbox, and Zoom discreetly capture real-time performance information that can be mined with artificial intelligence to reveal unprecedented windows into the drivers of organizational performance: who is driving the thinking around a particular project, solving key problems, starts important discussions, and so on.
This new data can not only give credit, but can promote effort and justice. For example, if a given factor affects performance, understand what is driving that effect and take steps to address it. For example, if you find that women’s brainstorming contributions increase team performance when there is a formal structure for turn-taking rather than an unstructured free-for-all, this suggests that teamwork processes, rather than gender, are likely to correlate with outcomes and such processes are modifiable. So you can use what you’ve learned to improve processes, make better, evidence-based decisions about people advancement, correct misconceptions, and improve overall organizational performance.
Look through the lens of groups, not individuals
The famous ones Moneyball The approach to team performance showed that team diversity in important metrics, not star players, drives success. Here, new data can help you understand the performance relationship between teams and diversity.
Many things today depend on teamwork. Thus, a key question may no longer be whether all-male or all-female teams perform better, but whether more gender-balanced teams perform better than male- or female-heavy ones. For example, does an engineering team with at least one woman reach milestones faster than an all-male team?
My previous research on millions of teams of biomedical researchers over a 20-year period found that controlling for past individual success, mixed-gender, balanced teams are more likely to publish more influential ideas than all-male or all-female teams, and that the result of the mixed-sex group becomes even more pronounced as the gender balance of the group becomes more equal. Use this simple image to widely promote efficiency and fairness.
Innovate your people policies
Data is critical to creating effective, innovative policies for people, especially as labor markets and work settings change.
For example, a company recently used data to find that their relocation policy prevented them from hiring strong candidates, especially women: when they asked job candidates to relocate in the middle of the school year rather than the summer, women with children were prone to rejecting the offer because it disrupted family routines , even though they wanted the job. With this knowledge and new options for remote work, the company is able to make better offers, strengthen the culture of support and increase the performance of top talent, without a real increase in costs.
Take a similar, open-minded approach to examining your policies and practices using data and smart assumptions, and you may be pleasantly surprised by what you find.
I hope the ideas here inspire you to leverage data and AI in service of diversity, value and equity in your organization. Remember: leadership plays a critical role in these efforts, through advocacy initiatives and intelligent exploitation of data to quantify true relationships and drive meaningful new insights.
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This article originally appeared in Forbes.
