How to Get Better at Hiring



Wharton Prof. Peter Cappelli, in his newest article in Harvard Business Review, declares in the title no less, “Your Approach to Hiring Is All Wrong.” He follows up on this bold statement with further indictments:


“Businesses have never done as much hiring as they do today. They’ve never spent as much money doing it. And they’ve never done a worse job of it.”


Status Quo: How Companies Recruit

Prof. Capelli first describes modern corporate recruiting practices:


“The recruiting and hiring function has been eviscerated. Many U.S. companies—about 40%, according to research by Korn Ferry—have outsourced much if not all of the hiring process to “recruitment process outsourcers,” which in turn often use subcontractors, typically in India and the Philippines. The subcontractors scour LinkedIn and social media to find potential candidates. They sometimes contact them directly to see whether they can be persuaded to apply for a position and negotiate the salary they’re willing to accept…”


“At companies that still do their own recruitment and hiring, managers trying to fill open positions are largely left to figure out what the jobs require and what the ads should say. When applications come—always electronically—applicant-tracking software sifts through them for key words that the hiring managers want to see. Then the process moves into the Wild West, where a new industry of vendors offer an astonishing array of smart-sounding tools that claim to predict who will be a good hire. They use voice recognition, body language, clues on social media, and especially machine learning algorithms—everything but tea leaves.”


Why the Status Quo is Unsustainable


These modern recruitment practices are problematic because they expensive (companies “spend an average of $4,129 per job in the U.S. and many times that for managerial roles) and companies have no idea whether these investments are “actually produc[ing] satisfactory hires.” Considering that “the United States fills a staggering 66 million jobs a year,” these unjustified costs add up.


This mystery of the quality of modern recruitment practices is due to the fact that “[o]nly about a third of U.S. companies report that they monitor whether their hiring practices lead to good employees; few of them do so carefully….”


Why the Status Quo Persists


Prof. Capelli posits that there are 2 reason that companies adopt these expensive hiring practices of unknown quality:


1. Importance of Poaching: Less than a third of job vacancies are filled by internal candidates so that companies have to aggressively collect and target experienced candidates who are working at other firms and who seem like they should be able to do a good job.


2. Poor Retention: Poor employee retention as employees leave for advancement with competitors is constantly causing vacancies so that again, companies have to aggressively collect and target experienced candidates who are working at other firms and who seem like they should be able to do a good job.


Ultimately, the lack of investment in training and career development for existing employees is causing firms to invest in poaching from a large pool of experienced external workers.


Solution Step 1: Make Recruitment Efforts Internally


Companies need to make use of their own valuable pool of internal human capital; a pool of candidates about which firms have all the data on internal job performance and over which firms have the power to steward development of skills and experience.


In order to start internal recruiting campaigns, the first step is to measure and track the percentage of openings that are filled from within. After all, “[a]n adage of business is that we manage what we measure.”


Next, companies need to require that all openings are posted internally.

Finally, companies need to start understanding the cost of outside hiring. Only when companies understand the costs of outside hiring can they truly begin to track hiring return on investment.


Considering that “outside hires take three years to perform as well as internal hires in the same job, while internal hires take seven years to earn as much as outside hires are paid,” firms that track their outside hiring return on investment might naturally be led to invest more in training and career development of internal employees.


Moreover, “[o]utside hiring also causes current employees to spend time and energy positioning themselves for jobs elsewhere. It disrupts the culture and burdens peers who must help new hires figure out how things work.”


Solution Step 2: Track Quality of Recruitment


Once recruitment pipelines are properly set up to collect and develop more internal candidates, the next step is to improve the actual hiring and quality-tracking processes. Prof. Capelli has provided 10 pointers to achieving these goals:


1. Don’t waste resources on posting “phantom jobs” on career portals – these though these phantom jobs may funnel a large volume of online applications into a “recruitment pipeline,” they divert attention and resources away from quality hiring practices.


2. Design hiring criteria with realistic requirements (i.e. having internal recruiters push back on the unrealistic “wish list” of job qualifications) so that resume-sorting software does not filter out nearly all applicants.


3. Stop focusing so much on passive candidates who would only leave their current employers for higher salary, and focus instead on active job seekers who, according to surveys, “are more passionate about their work, engaged in improving theirs skills, and are reasonably satisfied with their current jobs,” and also, looking for higher quality work and career development.


4. Rely less on referrals: apart from leading to a homogenous workforce, the results indicate that referral candidates aren’t necessarily better worker. Research by Castilla et al. demonstrates that “when referrals work out better than other hires, it’s because their referrers look after them and essentially onboard them. If a referrer leaves before the new hire begins, the latter’s performance is no better than that of nonreferrals, which is why it makes sense to pay referral bonuses six months or so after the person is hired—if he or she is still there.”


5. Measure the hiring results: Specifically, at a minimum, measure which channels “send employees who perform the best, stay the longest, and are paid the lowest starting wage.”


6. Create a smaller but better qualified applicant pool to improve yield: Considering that “every applicant costs you money—especially now, in a labor market where applicants have started to ‘ghost’ employers, abandoning their applications midway through the process. Every application also exposes a company to legal risk, because the company has obligations to candidates (not to discriminate, for example) just as it does to employees. And collecting lots of applicants in a wide funnel means that a great many of them won’t fit the job or the company, so employers have to rely on the next step of the hiring process—selection—to weed them out.


Moreover, employers aren’t good at weeding bad applicants out because “they may not be completely honest about their skills or interests.” Rather employees should find a way to creatively preview “what is difficult and challenging about the work as well as why it’s fun so that candidates who don’t fit won’t apply.”


7. Test candidates’ standard skills: Test for the presence of job-relevant objective skills such as ability to do simple programming tasks, IQ tests, language fluency, etc.


8. Be wary of machine-learning tools to filter and test employees: there is a lack of data on the job performance of applicants that are recommended by these tools and applicants can take advantage of some of these tools (a cottage industry has sprung up in teaching applicants how to game these programs).


9. Conduct interviews with the same job performance questions across candidatesdon’t focus on subjective characteristics like “fit with culture”; instead attempt to ask objective questions focused on job performance


10. Use machine-learning models that examine current-employee job performance to find correlations between objective-non-discriminatory characteristics and job performance.

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