Top 5 Mistakes Made by Sales Hiring Managers and How to Avoid Them

A common criticism of sales hiring managers is that they act on gut instincts. Why is this such a bad thing? In short, they turn hiring into a crapshoot with a 50% failure rate.

Hiring has a 50% failure rateThe main problem with trusting your instincts is that they are often based on various cognitive biases learned through our experience. Cognitive biases are mental shortcuts that cause people to interpret information in a way that creates their own “subjective social reality,” which leads to inaccurate judgments and illogical behavior.

Inspired by this extensive list, here are the top 5 biases of hiring managers:

1. Overconfidence effect

This phenomenon describes when “someone’s subjective confidence in their judgments is reliably greater than their objective accuracy.” Case in point? When a person is (overly) confident that trusting their gut instincts leads to good hiring decisions. Overconfidence is often the result of confirmation bias, which causes people to remember the examples of when reliance on gut instincts led to a good hire while ignoring or forgetting the times it led to a disastrous one.

2. Halo effect

This bias occurs when “we assume that because people are good at doing A they will be good at doing B, C and D.” The halo effect often occurs when the hiring manager likes a candidate and uses that as a basis for assuming he or she will be good at the job rather than an objective analysis of their job-related skills and abilities.

3. Similarity attraction effect

This is the tendency for people to “seek out others who are just like them.” The adage “opposites attract” turns out to be a myth: We tend to like individuals who are similar to us. Research on hiring practices by Professor Rivera at the Kellogg School of Management found that “Employers sought candidates who were not only competent but also culturally similar to themselves in terms of leisure pursuits, experiences, and self-presentation styles.”

4. Confirmation bias

This bias occurs when people “favor information that confirms their beliefs or hypotheses” and ignore or discount disconfirming information. Confirmation bias is one of the reasons why hiring managers are inconsistent in the interview questions they ask across candidates. Because they tend to ask questions that confirm their unique beliefs about each candidate, this often results in a process of comparing apples to oranges.

5. Illusory correlation

This is the tendency to “perceive a relationship between variables (typically people, events, or behaviors) even when no such relationship exists.” Illusory correlation is the reason why hiring managers ask interview questions such as, “What kitchen utensil would you be?” These types of questions are believed to provide insight into a candidate’s personality even though there is no evidence that they actually predict job performance (or anything else for that matter).

The takeaways

The evidence shows that “trusting your intuition” doesn’t lead to better hiring results and in fact, based on Professor Dana’s research at the Yale School of Management, often leads to inferior outcomes. So what can you do to counteract these cognitive biases?

Although it’s impossible to eliminate their effects completely (we’re only human, after all), you can replace your reliance on subjective instincts by using objective data as the basis for making accurate hiring decisions. The best methods for collecting data on candidates that predict subsequent job performance include validated pre-hire psychometric assessments and well-designed structured interviews.

We’ve been “trusting our instincts” with inconsistent results for too long. It’s time to embrace the world of data analytics and “trust the data” instead.

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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 recruitment. She writes about trends and research in talent acquisition, HR tech, and people analytics.
Ji-A Min

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