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?

Let’s examine the common job candiBruceSpringsteen-Ideal-Candidate-Salespeopledate red flags that recruiters and hiring managers use and assess how well this claim holds up.

What happens when you hire with a human touch

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.

We need to acknowledge that long-term unemployment and “job hopping” merely reflect the realities of today’s workplace – these circumstances are often completely out of the job seekers’ control.

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.

Interested in finding out what the monetary benefits of using a data-based sales hiring system are? Read this.


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Ji-A Min

Ji-A Min

Head Data Scientist at Ideal
Ji-A Min is the Head Data Scientist at Ideal. With a Master’s in Industrial-Organizational Psychology, Ji-A promotes best practices and data-based HR. She writes about trends and research in talent acquisition, people analytics, and workplace diversity.
Ji-A Min