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Can bias in the workplace ever be eliminated?

October 25, 2017

 

It’s hard to believe that in 2017 we are still having a conversation about workplace bias, but the topic seems more relevant now than ever. With new allegations surfacing every day about Harvey Weinstein, we have to ask ourselves if we are really making any significant progress towards workplace equality?  Although most discrimination is not as obvious as overt sexual harassment, some recent studies prove that bias is still rampant and not only affects women but many minorities as well. For example, in an article written by Anne Loehr, she cited a study that was conducted by Cambridge-based National Bureau of Economic Research. In their study, they created two comparable dummy resumes, half of which had “African-American sounding” names and half of which had “white-sounding” names.  They then responded to 1,300 classified ads and found that “African-American sounding” names were 50 percent less likely to get a callback than “white-sounding” names.   

 

In another study, conducted by Michael I. McDonald, a professor of management at the University of Texas at San Antonio, he found that following the appointment of a female or minority CEO, white male managers often felt less respected and valued.  They also “identified” less closely with their company which resulted in a lack of engagement.  This behavior certainly doesn’t seem logical and may even point to the fact that bias can often be rooted in insecurity and the perceived threat from “others”. 

 

So how can this situation be turned around?  As the U.S. population continues to diversify, we need to find a way to do more than simply coexist in the workplace.  We need to find solutions that will treat diversity as an advantage and not a threat. Can big data provide some answers?

 

Big data certainly is not the only solution but it can be used to extrapolate some valuable insight. However, “insight” is the key word because collecting the data is only useful if your organization is going to analyze the information and actually do something with it.  For example, one useful data point might be to track the length of tenure and upward mobility of minorities and women and compare that to their white male counterparts.  Are there any trends that can be detected such as higher turnover of one group vs the other?  If so, how can that data be further analyzed to make predictions about who is at the greatest risk for resigning and can programs be put in place to mitigate that churn?

 

Data can also be used to identify personality traits that can help to predict candidates that will do the best within a given team. It is not enough for companies to attract diverse talent. They also have to retain that talent and ensure that new hires have the best chance of success within their organization. If companies can nurture new employees through the first few months, which can be the most challenging, there is a much greater possibility that those employees will end up thriving and remaining with the organization for a longer period of time.

 

One final example of how data can be mined for insights is to compare customer and employee data. Studies show that by hiring employees that more closely mirror their customers, businesses can more effectively market to consumers from different backgrounds. This not only means that businesses will be hiring more diverse employees but they will also be ensuring that their customers viewpoints will be better represented. 

 

The lack of diversity especially in senior management and board positions will not be a problem that is solved immediately.  However, companies can begin to use data to help them make better decisions about how to address the issue.  It is not only the right thing to do but businesses will be stronger as a result.  Census data points to the fact that by 2050, there will be no racial or ethnic majority in our country.  Therefore, if companies do not make an effort to recruit the best and brightest from all backgrounds, they will not be able to compete in a global economy.

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