As a business leader, you may want to increase the diversity, strengths, and fairness of your organization, whether in terms of recruitment, promotion, teamwork, or other initiatives.
This is a key area and it matters a lot. For example, there is evidence that different teams perform better due to the integration of different skills and perspectives, and a fair system inspires employee loyalty by giving due trust. In addition, race, gender, and other prejudices in recruitment, promotion, and compensation have a significant legal impact on companies and other organizations.
The good news is that there is a new way to improve diversity, fairness, and value, and you already have data in your company. New technologies allow you to use data in an unprecedented sustainable way to reveal, understand and solve problems related to diversity and performance.
Professional woman with virtual assistant at her desk
Professional talking to the virtual assistant at her desk. GETTY
Here are three specific ways to achieve this goal.
Quantifying to correct stereotypes
Although stereotypes are often incorrect on a personal level, they affect how a person’s contribution is valued and recognized. In particular, stereotypes create a situation where “believing is seeing is believing.” In this case, people distort reality to fit their prejudices against specific groups. For example, gender stereotypes lead to degrading women in multiple settings. Contribution.
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To address this prejudice, the general idea is to create transparency around who contributes what and how to contribute, so that actual performance can be quantified fairly and visibly. Although it used to be expensive to collect comprehensive and accurate data that creates transparency, these data are now collected regularly and cheaply as a by-product of team collaboration platforms.
Popular technology collaboration platforms such as Slack, Dropbox, and Zoom carefully capture real-time performance information that can be extracted with AI to reveal an unprecedented window of organizational performance drivers: who leads thinking around specific projects, solves key issues, and starts important conversations , and many more.
These new data will not only give you the honor you deserve, but also promote effort and fairness. For example, if a factor affects performance, understand what is driving the result and take the necessary steps to resolve it.
For example, if you find that women’s brainstorming contributions can improve team performance when there is a formal shift structure rather than a freely competitive structure, it indicates that the teamwork process may be more relevant to the results than gender; and such processes are modifiable of. Therefore, you can use what you have learned to improve processes, make better evidence-based promotion decisions, correct misconceptions, and improve the overall trend of organizational performance.
From a team’s point of view, not from an individual’s point of view.
The well-known Moneyball team performance method shows that the team’s diversity in important indicators rather than star players drives success. Here, new data can help you understand the performance link between team and diversity.
Today, most businesses rely on teamwork. Thus, a basic question may no longer be whether all-men’s or all-women’s teams perform better, but whether teams with greater gender balance perform better than teams with greater weight of men or women. . For example, does a team of engineers with at least one woman reach a milestone faster than a team of men?
My survey of millions of biomedical research teams over the past 20 years found that a balanced team that monitors the individual’s past success is more likely to publish more influential ideas than a team of only men or women. And the gender-mixed team effect becomes more obvious as the team’s gender balance becomes more equal. Use this simple information to widely promote performance and fairness.
Innovative personnel policies
Data is essential to formulate effective and innovative personnel policies, especially when the labor market and work patterns change.
For example, a company recently used data to discover that their relocation policy prevented them from hiring good candidates, especially women: when they asked potential employees to move in the middle of the school year instead of the summer, women with children even if they wanted to This also tends to reject work because it disrupts the daily life of the family.
With this information and new options for remote work, the company can deliver better deals, strengthen the support culture, and increase the production of top talent without real cost increases.
Take a similar, open-minded approach, using smart data and assumptions to check your policies and practices, and you may be pleasantly surprised by the results you find.
I hope the ideas here inspire you to use data and artificial intelligence to contribute to the diversity, value, and fairness of your organization. Remember: Leadership plays a key role in these efforts, through advocacy initiatives and the smart use of data to quantify true relationships and promote important new insights.

By Peter

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