Consider this situation- you are hiring for a sales position at your company. You have two equally impressive employees. Both candidates had identical GPAs in college. Both candidates have sales experience at a major company. Both candidates were friendly and professional during their interviews. Who do you hire?
This is where data and analytics come in. Big Data, as it is being called, is new to HR, but companies like Xerox, Lowe’s and ARAMARK are openly embracing a concrete approach to hiring and managing employees. Companies that use data in hiring decisions take time to compile statistics for turnover, performance and employee assessment results. This data is used to find trends that indicate which types of people will be successful at which types of jobs. If we had access to data in answering the situation in the opening paragraph, we would have identified personality traits that successful sales people in the organization have. We could have chosen the candidate that scored higher on those personality traits, with solid data to back up our selection.
Companies traditionally make hiring decisions based on skills listed on a resume, experience and intuition. This approach can and has worked, but there is no clear right or wrong answer. Although hiring decisions are supposed to be unbiased, life experiences and perceptions create natural biases. Considering that payroll is often the largest expense for a company, hiring decisions are not decisions to make major mistakes on. The cost of hiring and training employees today is too high for employers not to get it right the first time.
Josh Bersin, CEO of Bersin & Associates, recently wrote about a large service provider hiring sales people. The company used to believe that indicators of success were college major, GPA and reports from references. It turns out that none of that mattered. What did indicate sales success, as gathered from data the company analyzed, was a resume free of spelling errors, ability to perform under vague instructions and multi-tasking skills. The company began hiring salespeople with those skills, and achieved a $4.5 million increase in sales over only six months.
Xerox also had some commonly held misconceptions about hiring. They used to focus on hiring call center employees who had previous call center experience. Then Xerox solicited the services of Evolv, a startup that assists companies in selecting and managing hourly workers. Using Evolv’s tests and performance tracking tools, Xerox found that creative people tend to stay at call center jobs. Inquisitive people do not. After using this data in selecting employees, Xerox’s turnover rate dropped 20 percent.
“Data can be used to make incredible predictions,” said Daniel Enthoven, president of Evolv, but he added that “tons of data is used very poorly.” What is the right way to use HR data? Enthoven recommends using factors related to personality, aptitudes, work style, fit for the position and technical skills. Big Data will never work unless an organization has clear, specific job descriptions that prospective employees can be matched to.
Companies that use data in hiring decisions must be careful about unintentionally discriminating. When working with Xerox, Evolv found that workers who lived far from the call centers they work at are likely to quit. But that information was closely linked to race so Evolv did not use it in scoring employees.
Big Data is transforming the way companies hire. If done correctly, it makes the hiring field much more level for employees. Not every employee can afford to attend big name schools, but that does not mean they are not competent. Big data lets them stand out on the basis of factors that actually matter to the position. Employers also benefit. Big data removes much of the guessing from hiring decisions, allowing companies to hire smarter.
The use of Big Data calls for a reliable method to gather the data! The ProfileXT provides the data you need to make smart hiring decisions based on how well an individual fits a specific job at your company.
What do you think about Big Data coming to HR?