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Statistics-based hiring models present opportunity, challenges

Most Pennsylvania job-seekers are familiar with the disappointment of applying for a job that seems like a perfect fit, only to be summarily turned down without an interview. It can be hard to predict what makes the perfect applicant for a given job, especially without more insight into the basic duties and work environment.

Employers are seeking to standardize the hiring process, particularly for rank-and-file workers who do not make managerial decisions. Many different software models have emerged, placing emphasis on personality traits and values over education level and prior experience, which experts assert is a more accurate way to predict success on the job.

The companies that help implement and operate these types of statistical hiring models say that it can help eliminate certain types of biases, like those based on appearance, in the hiring process.

The software programs also track the people that are hired based on a certain set of criteria to see how successful they are and how long they stay with the company. Proponents of this method say that this can help avoid waste and make it easier to identify employees who will be a reliable investment for training dollars.

Still, there are some concerns that factors such as living close to the office and having reliable transportation could result in inadvertent bias against certain groups. Any practice that filters out applicants who belong to a protected class could be challenged as a discriminatory practice and could expose the companies to liability.

One concerning example is that some software programs ask applicants how long they have lived at their current address. For younger families or lower income people, this could put them at a disadvantage if they must move often for financial reasons. While the question is designed to find people who are prone to commitment, the unintended consequence could be discrimination.

More information about employment discrimination is available on our website.

Source: Wall Street Journal, "Meet the new boss: Big data" Joseph Walker, Sep. 20, 2012

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