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How Technology is Changing the Job of Recruiters
Recruiters are constantly searching for employees who will be the best fit for an open position. The US Department of Labor estimates that up to 30 percent of an employee's annual salary is wasted on a bad hire which means the stakes are high for finding talented candidates. It's not always easy to identify poor candidates since it's hard to evaluate an employee until after they are fully trained. For example, it's estimated that sales representatives take 18 months to become fully effective, meaning a company might not realize there's a problem until well after a year of paying that person's salary. 
 
Those numbers are why recruiters are increasingly leaning on technology to fine-tune their recruiting efforts to minimize bad hires. 
 
Predictive Analytics 
Predictive analytics, or forming patterns based on large sets of past data, can help determine if an employee will succeed in a role long term. For example, Wells Fargo compiled data by giving assessments to 1,000 long-term employees ranging from low to high performance, reported Predictive Analytics World. The data sets included education and background information which was then compiled and compared to the employees' performance and duration of employment. Clear trends showed the best employees tended to have certain college degrees and work history. By giving new applicants a similar questionnaire, human resources managers can now find candidates with similar profiles to current top-performers which can help predict the new hire's eventual skill level and lead to higher retention rates. 
 
Artificial Intelligence (AI)
Predictive analysis helps provide data to new artificial intelligence programs that help screen candidates. AI recruiting assistants use complex algorithms to scour data on the internet and in job applications to help narrow down the pool of applicants that are presented to hiring managers, explained Fortune. They currently cannot replace their human counterparts, but they can increase the quality and diversity of the final applicant pool. Unlike a human, AI programs are not biased and can be programmed to hide religion, race and gender from recruiters, so no personal prejudices come into play before a face-to-face interview. The systems rove social media for things like language use (abundant use of "please" and "thank you" may indicate a person is more compassionate and better suited for customer service positions), facial expressions, negativity and more. 
 
Predictive analytics and artificial intelligence will continue to evolve how companies find and screen candidates to determine their next long-term high performing employee.  Will your company be next to incorporate them into your recruiting process? 
 
 
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