A company is only as good as the people it hires to work toward a specific goal. The process of recruitment is integral for all organizations. Everyone, of course, wants to hire the best of the best, the one that can help aid the company to become successful in its industry.
Cost of a Bad Hire
The cost of onboarding a new employee into a company, according to an expert, is about $240,000. Meanwhile, the U.S. The Department of Labor said that a bad hire can lose a company at least 30 percent of the employee’s earnings during their first year.
At the end of the day, the company wastes not just time and energy on a bad hire, it also suffers from financial consequences.
Moreover, bigger companies pay a higher price when they accept the wrong job applicant. Tony Hsieh, the CEO of Zappos, estimated that bad hires set the company back over a hundred million dollars.
In short, making a mistake in recruitment is very expensive but even the top hiring managers in the world are prone to choosing the wrong job applicant. How can the process be improved to minimize as much as possible the likelihood of bringing in an employee who is not fit for the role?
Set No Limits
An applicant’s educational background played a major role in determining whether a potential employer hires them or, in many cases, even considers their application. That still happens a lot today, but the biggest companies around the world have stopped looking at an applicant’s university and are focusing instead on their experience.
After all, Bill Gates and Mark Zuckerberg are famous dropouts who, despite not having a degree, went on to become billionaires.
A worker who graduated from a STEM senior high but has the capacity to fulfill their role and is willing to continue learning is not a bad hire. An applicant who relies on their degree and their university to get them through the door every time may be a waste of time and resources.
It does not matter whether the applicant has a degree or not from a reputable university. Whether they have the right skill set for the job and if they are a good fit for the company are the only factors that need to be considered in the hiring process.
Integrate New Tech
New technology exists to make the process of recruiting easier, faster, and more efficient.
There are great hiring managers who, through extensive experience, can immediately spot a promising candidate from the sea of applicants. They look beyond what is written on the resume. However, building the skills needed to become a great hiring manager takes time and, at the end of the day, they are still human. They are prone to errors.
A good way to minimize errors when it comes to hiring is by lightening their workload and allowing them instead to focus on hiring the right people.
Companies can automate tedious tasks that come with recruitment such as scheduling interviews, sending regular updates to candidates, and even source candidates whose credentials fit the role. An artificial intelligence tool reduces the amount of labor required in the hiring process. That way, humans can focus on the tasks that machines are not capable to do such as parsing through cover letters and responses during in-person interviews, vetting references, and assessing passion and professionalism.
Source on Social Media
Sometimes, the best people for the role are not actively looking for a new job. While they are open to better opportunities, they are not hanging around job application platforms, waiting for a potential employer who wants and is willing to pay for their expertise.
If companies want to hire the best, they need to go beyond LinkedIn. Recruiters should begin scouting for talents in places where like-minded people gather and interact: social media. Although websites such as Facebook, with its 2.7 billion users, are too broad, there are ways to find specific people. You can browse hashtags and read threads/discussions about interests relevant to the position you are hoping to fill.
Reddit, a community of over 400 million, has subreddits on almost any topic under the sun. A recruiter who is looking for a data scientist, for example, can look around r/datascience which has 400,000 members, or r/datasciencejobs with 15,000 members.
There is no process that is infallible. A company will, at some point, make the mistake of hiring the wrong applicant. However, minimizing the likelihood as much as possible mitigates potential financial disaster brought about by the bad hire and saves the company from other consequences such as wasting resources or losing opportunities.
