Don’t Go With Your Gut: 3 Ways Data Can Improve Recruiting Outcomes
Recruiters and hiring managers used to rely solely on their gut feelings for hiring decisions. It was mostly about whether you had a connection with someone and whether they “seemed” like a good fit for the company.
Today, we know that first impressions are generally unreliable predictors of success. Gut instinct can be useful when hiring data is absent, but recruiters and hiring managers now have access to a wealth of information about their candidates. They know their personality types, key factors like commuting distance, and more.
Just like a bad hire has a negative ROI, a good hire has a strong positive ROI. When recruitment data can indicate the potential fit between a candidate and company, it can be used to make a rough estimation of the hire’s ROI.
However, this recruitment data is often underutilized. Research shows that many recruiters still prefer to rely on gut feelings. No algorithm, they would argue, can substitute for a veteran’s knowledge.
By not fully utilizing their recruitment data, these recruiters are missing out on key hires — better business outcomes. Here are three examples of how recruitment data can lead to better business results:
1. Leveraging Performance Data for Future Hires
Every company wants to attract high-performing employees, but what drives performance is still hotly debated. Several personal characteristics are likely involved, including conscientiousness and IQ, among others.
How can recruiters and hiring managers be certain candidates are high-performers before they are even hired? The best approach is to look at the high performers already at work within your company. That way, you can determine the characteristics shared by your organization’s top talent. Once you understand what drives performance in the context of your own operations, you can look out for candidates with similar characteristics in the future. This ensures you recruit candidates who are likeliest to produce significant ROI.
2. Stopping Turnover Before It Happens
If a candidate leaves within three months of being hired, you can’t consider it a good hire — no matter how well they performed before leaving. Having to do the entire hiring process all over again means unnecessary costs for the business and a missed opportunity for a better hire.
Therefore, it is paramount to look at turnover risk when making hiring decisions. As with performance, you have to understand the key indicators of turnover among previous employees of your company. Taking these key indicators into account when making new hires can help you surface candidate who are less likely to leave.
According to a 2000 meta-analysis, several metrics are predictive of employee turnover. These include some obvious signs, but also some less obvious ones:
- Age: We have all read that millennials are hard to please and switch jobs frequently. The fact is that age in general is negatively associated with turnover. In other words, younger people tend to leave their jobs more frequently than older people, regardless of what generation they belong to.
- Commute distance: People who have longer commutes are more likely to leave.
- Ability to cope with stress: Stress is an important factor that drives employee turnover. A candidate who has healthy coping mechanisms is less likely to leave after being hired.
3. Building a More Diverse Workforce
While diversity was once considered a box to check, companies today know that increased diversity immediately impacts business performance. Diversity has therefore become a business strategy — one in which recruiting plays a key role.
It is quite common, especially in the US, to track candidate and employee demographic data in order to measure progress toward diversity targets. However, data can be leveraged in more robust ways as well. For example, tracking the kinds of candidates returned by different recruitment channels can help organizations uncover audiences their current channels may not be reaching at all (the so-called “pipeline problem”). Similarly, gendered language in job descriptions could be discouraging women from applying for particular roles. Using data to uncover and counteract these biases can help you achieve a more diverse workforce in less time.
It is a shame that managers often underutilize the data they have at their disposal. Improving your recruitment process with data can help you make better hiring decisions. Not fully utilizing this potential is a costly mistake for organizations.