Archive for October, 2013

Will Machines be our Next Hiring Managers?

October 18th, 2013

automated hiring managerWe are becoming increasingly reliant on machines to take care of so many tasks for us, with computers making suggestions for what next books we should buy online, or what movies we might want to watch next via a streaming video service. Robots assist workers putting together cars on the factory floor assembly line, and some of these cars may be eventually driving themselves rather than relying on humans for navigation and control.

It seems no industry is immune to the effects of computer automation, and this includes area of hiring and employee recruitment. A number of companies are now creating online questionnaires and even video games to help them measure attributes that they are seeking in potential job applicants, according to a recent article at Bloomberg.

With computers able to sift through massive amounts of information more quickly and efficiently than ever before, data mining is enabling companies to automate their processes when it comes to finding the right talent to fill jobs.

It may seem inevitable for us to rely more on automated systems to help us respond to the influx of job applicants. Constant access to mobile phones and the Internet has made it much easier for people to search for and apply to more jobs, which only increases the workload of human resources professionals.

Pros and Cons to the Machine Takeover

There are a number of benefits to using machines to help with the hiring process. For example, hiring managers need to use tools to help them manage the huge torrent of data unleashed by people applying for work, or they stand to miss out on finding the right candidate at the right time.

As many as 3.7 million jobs were not filled in July, the article notes, despite the fact that in excess of 11 million people were looking for work in the U.S., according to statistics from the Labor Department.

Erik Juhl, the head of talent at video advertising startup Vungle Inc. in San Francisco, will start using an online game to help track and record the actions of online players to measure how likely they will be a high performer at a new job.

Evolv is a human resources computer model that helps companies better evaluate their candidates for hourly positions with an online questionnaire.

Drawbacks to using “automated hiring” systems like this include substituting a computer algorithm for your own judgment when it comes to evaluating fresh talent. A program will not be able to determine how well a salesperson functions under high-pressure social situations,  while a seasoned recruiter can make such an evaluation during the course of an in-person interview.

Another problem is that automated systems haven’t been around enough for us to be able to track how well they can do at predicting the long-term performance of applicants, the article notes.

So, while completely automated software can help you filter job applicants for the ability to cover certain  tasks when recruiting to fill positions, these systems are not yet ready to completely replace such time-proven methods of evaluation as the face-to-face interview. This is especially the case for salaried positions that require some nuance, such as how well a candidate might ‘fit in’ with the rest of a team.

The future of hiring may not ever wind up being completely automated, but recruiters and hiring managers can still take advantage of some of these automated tools to assist them in their recruitment process.  The best of both worlds is likely the current solution; a live human being (recruiter or hiring manager) utilizing high tech recruitment software to make their job more efficient.  In this scenario, the software can best handle the data by efficiently finding, processing, organizing and checking on potential candidates, while the person can do what he/she does best – handle face-to-face interviews and provide a ‘human touch’ that could not currently be outsourced to a machine.  In a sense, a recruiting ‘android’ that utilizes the best assets of human and machine is an optimal solution.