No matter how many research studies show that using a data-based method for hiring sales reps is more objective, fair, and accurate compared to using subjective judgment, people still have a tendency to prefer a human touch when it comes to hiring.
Only a human being, and not a cold and impersonal algorithm, can truly understand a fellow human being. Right?
What happens when you hire with a human touch
- Do you have a single typo on your resume? ELIMINATED
- Do you have a different job title than the job you’re applying for? ELIMINATED
- Have you been out of work for more than 6 months? ELIMINATED
- Have you left a job before a year of tenure? ELIMINATED
- Have you have more than 5 jobs within a 10-year span? ELIMINATED
- Are you over 40 years old? ELIMINATED
- Do you have a non-White name? ELIMINATED
- Are you self-employed or an independent consultant? ELIMINATED
- Are you not already employed? ELIMINATED
- Are you “overqualified“? ELIMINATED
But when the average job posting attracts hundreds of applications, we need something to help us narrow down the candidate pool.
So what’s wrong with eliminating job candidates based on these criteria?
Mostly, that they’re wrong: they’re just not valid methods for assessing the quality of a job candidate.
What the data tell us
Research finds that there are no differences in performance for employees with a history of long-term unemployment (i.e., greater than 6 months) and those without.
A study of over 100,000 job applicants found that there were there was no differences in an employee’s loyalty regardless of how many jobs he or she had previously: Job hoppers and non-job hoppers are equally likely to stay in their jobs.
Overqualified employees not only outperform their colleagues, but they are also less likely to quit as long as their needs are met otherwise.
Employers who are smart enough to tap into these neglected talent pools will create a huge competitive advantage. Let everyone else fight over the same passive, already-working-at-a-competitor job candidates.
The better alternative for sales hiring
Use data-based methods to assess sales job candidates. Surveys reveal that 49% of people lie on their resumes. Research tells us job interviews are a poor predictor of future job performance. Everyone knows resumes and interviews are unreliable but everyone uses them anyway.
Instead of guessing and being led astray by unsubstantiated “red flags,” why not allow the data do the job of predicting who the best salespeople are likely to be?
Research featured on the Harvard Business Review found that compared to human judgment, an algorithm increases the accuracy of selecting productive job candidates by more than 50%.
These data-based hiring methods include psychometric assessment of personal characteristics, which can account for 25% of the differences in job performance (that’s a lot!) and structured interviews, which are up to twice as effective at predicting job performance than unstructured ones.
The bottom line
Hiring with a human touch unfortunately often means hiring with a human bias.
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