STEM Enterprises Seek High-Tech Solution to Hiring Bias Problem
They never get the chance to take on the right projects, lead the development team or otherwise pay their dues, and they leave because there's no future. Part of the problem with encouraging diversity and in the process easing the problem of hiring enough qualified people is that it's hard for a company to figure out what the problem is even when they want to solve it. In many companies, "the definition of 'qualified' seems to be white or Asian males of a certain age," said Gabriela Burlacu, human capital management researcher at SAP SuccessFactors. Burlacu said that maintaining the status quo has always been part of most organizations, and that leads to hiring practices that seek to maintain the status quo. "They believe certain demographic groups are going to be more successful," she explained.In May, SAP SuccessFactors announced plans to build data mining and analytics features into its Human Capital Management suite that will help improve workplace diversity. These features will be based on SAP's HANA in-memory database technology and will help companies review job descriptions, performance reviews and other personnel documents to discover potential bias and find ways to encourage workplace equality. SAP SuccessFactors hasn't announced when it will be ready to introduce these new features. The next step is using the information to find out where equality is impeded in the hiring and retention process. Unfortunately, in most companies, there's plenty of space for that. Hiring managers may want people who they predict will fit their culture, HR managers may worry about health care costs and lost work hours. Other managers may worry about someone simply not fitting in. Each of those when used as a prediction of suitability for a job brings a loss of diversity. Making matters worse, the bias in technology hiring and retention didn't start at the companies that are now finding themselves without qualified candidates. In fact, as I have observed, it starts much sooner as middle schoolers and high schoolers are encouraged to seek further education that fits their gender or place in society. This is the place where young girls are actively discouraged from math and science classes and where children from families that work in blue-collar jobs are pushed into trade classes, not colleges. The problem continues when students begin their college training, as I also observed when going with my daughters for college visits, only to hear the dean of a university tell me, "Girls can't do physics." Girls can do physics, and they can do engineering and software development. But it goes far beyond that because the same type of bias is preventing the hiring of people because of their race or their age. One has to wonder if the companies bemoaning the lack of qualified applicants are actually looking, because if they were we wouldn't see the vast populations of self-employed engineers and knowledge workers with decades of experience working as consultants.
"The starting point for organizations today is with workforce analytics being able to really dig into the data of their workforce," Burlacu said. "It helps them see where the problems lie and where the inequities might be. Now you have all these tools that enable you to slice and dice the data. But that's just the starting point."