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Recruiting is changing from candidate driven to employer driven searches

Recruiting is changing from candidate driven to employer driven searches

By Anthony Kaylin, courtesy of SBAM Approved Partner ASE

The shortage of qualified applicants and baby boomers and their knowledge fund retiring at a rate of about 10,000 per day continues to present recruitment challenges.

A typical recruitment process involves working with the hiring manager to identify the job requirements and then posting the position to various job boards, such as Indeed.  In addition, the recruiter will do a passive candidate search through LinkedIn, Facebook, various career sites, etc.

More innovative recruiters apply tools or bots that pull candidates for them, providing not only a profile of the candidate from publicly available sources but also a predictive analysis as to whether the candidate will be successful in the employer’s culture and environment.   Algorithms are used to determine if a candidate will perform well in a new job. The algorithms assess candidates’ chances of success in a position defined according to criteria such as aptitude, motivation, behavior, and even personality.

In fact, job boards will likely start to see impact on their revenues as the bot searches for candidates take over the active search, making it an employer driven search as opposed to the traditional candidate driven search.  LinkedIn, for example, has created objective, data-driven hiring profiles, allowing the company to target and surface high-fit candidates that competition never sees. LinkedIn college recruiting is walking away from college visits as their “smart” approach to college recruiting finds more suitable candidates. Tey Scott, Director of Global Talent Acquisition, said in 2016 that the goal is to never go to a campus again: “We’ve moved from schools to skills.”

Google is a leader in big data analysis of candidate potentials.  When Google analyzed actual job performance, they found that “GPAs are worthless as a criteria for hiring… we found that they don’t predict anything,” according to Laszlo Bock, their former SVP of People Operations. Instead, “We care a lot about soft skills – leadership, humility, collaboration, adaptability, and loving to learn and re-learn.” 

Recruiting is known as the leader of talent evaluation.  The cost of a bad hire is widely known and understood.   Professional sport teams understand this concept quite well.  They will use past performance, for example, baseball sabermetrics, to identify good fits for the team being built and then use candidate profile testing to determine fit.   Pro football uses the Wonderlic test.   

Most employers have enough data to create a model of a successful hire; the real issue is training recruiters how to use this data to better recruit.  The upfront cost will be high, but over time the costs will be lower, especially if the approach brings in quality hires.  Employers are recognizing the issues with live recruiters.  They are more likely to have biases which may impact selection.  That’s why bots are being used more and more for initial screening purposes, for example Fitbit and Evernote. 

Since technical requirements for jobs are found less and less among potential candidates, the soft skills are likely the skills to hire for, no matter what level in the organization.  Don’t think the trades or the factory floor, but also think accounting and purchasing.  Employers need to rethink degree versus certifications.  Too many positions are devaluing the college degree by requiring it for jobs that do not need it. 

In the end, employers have to rethink the recruitment process and develop internal training programs for those with the aptitude to learn in order to grow the internal talent base. Apprenticeship programs could be one of many initiatives used by the forward-looking employer.  Recruiters must lead this process or find their relevance and value to the organization questioned.  Employers that do not put resources into recruiting will experience the “same old same old,” impacting long-term profitability and viability.
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