By Teri Morse, vice president, Human Resources, Xerox
U.S. companies spend about $46,000 each year on training and developing new employees. It’s even more expensive when companies struggle to retain people.
If you want to improve employee retention, and reduce training costs, your recruiting process must change, even for hourly employees, so says the Corporate Learning Factbook 2013.
Cracking the Code
Some companies, including Xerox, have turned to big data to help with the hiring process. This is especially important to us in the customer care space.
Data and software programs can help crack the code of hiring the right employees, based on input gathered from tens of thousands of employee files on hourly workers.
Applicants are put through a series of tests and their job performance is tracked, which helps the technology learn about and identify the ideal customer care worker.
Those technologies, like the one we use from Evolv, help us assess all of our candidates (and we have a lot) and rank them from high to low potential for the job. Then we make the final decision on who to hire.
Not only does it help during the application process, but it also shows us where applicants have weaknesses. This provides recruiters areas to dive deeper into during the interview process, and it lets us know how we can focus training to enhance skills.
Less Guesswork, More Data
So who is the ideal customer care worker? The data tells us it’s someone who lives close to their place of work, has reliable transportation, uses social media (but not too much) and is creative.
This data has proven that when we hire people who are graded as “most likely to succeed,” they stay on the job longer and perform better. For one of our clients, it helped increase revenue by 10 percent because we were able to hire better people and keep them on the job longer.
This software helps take the guesswork out of the hiring process and replaces it with real, scientific, data. While hiring managers have the final say in who they bring on, instinct and intuition now play a much smaller (and more reliable) role in personnel decisions.
One thing we’ve learned from this process is that it’s not about the number of job applicants, it is about the quality of those applicants and how many we hire.
Employees that stay less than six months cause a loss for us, due to the expense of training them. Now our turnover is lower, which means less time and money spent on recruiting and training new hires.
Big data saves us time and money, and allows my team to focus on efficiency and customer satisfaction. What’s your team working on?
