Historically, data-driven recruiting has been synonymous with time to hire, aka speed to hire. But in 2020 companies are prioritizing these metrics.
What is Data-Driven Recruiting?
Data–driven recruiting is when you use tangible facts and stats to inform your hiring decisions, from selecting candidates to creating hiring plans. Recruiters and recruiting leaders that use data are more likely to be efficient, reduce costs and improve their hiring.
Benefits of Data-Driven Recruiting
Data-driven recruiting is taking off because it offers tangible business benefits:
- Overall: increased business performance, including higher revenue, higher customer retention, more upsells, higher NPS scores, higher referrals, and more. The nirvana state of getting it right is improved brand, which means commanding a premium for services and attracting and retaining the best talent available in the market.
- Improved quality of hire. This means hires ramp faster, stay longer, positively contribute to the culture of the company and perform well over time.
Conversely, getting the wrong fit means a negative impact on business performance, on the overall culture, on the brand itself – which can far outlast the departure of the hired person. And getting the wrong fit is shockingly common: 2/3 of newly hired employees say they’re in the wrong fit.
So what are the traditional points of data used to evaluate success in recruiting?
Until a few years ago, recruiting data was constrained to the sourcing, interviewing and “placement” metrics:
- Time to hire, measuring the overall velocity of the process
- Cost per candidate – usually because it was related to the above
- Source of hires – helping understand what candidate pools yield higher efficiencies (but can easily become self-fulfilling prophecies), and to understand referral rates
What limitations are being overcome?
While a candidate can be the most charming person you’ve ever met, that doesn’t mean they’re going to do well in your company. The technology that was previously available limited the organization’s ability to act on critical insights. That’s because:
- ATSes are great for the above – time and cost of hire, but the data pertaining to the performance traditionally lives in other systems. As a result recruiting has been siloed and recruiting efforts suffer from the limited feedback loop. This can also, over time, mean that business leaders trust less in their recruiting teams, as the lack of information handicaps the efforts and creates extra back-and-forth in determining what success looks like for a given role – and therefore, which candidates are most likely to fit the profile.
- Performance software such as CRMs show an organization what the performance is. Unfortunately, CRMs do not help identify what makes the individuals perform at their respective levels. The lack of insights make the siloed data problem that much worse when it comes to hiring, because there is no objective template of what good looks like. As a result, “what to look for” becomes an invisible goal in the interviewing panels’ heads that becomes difficult to reconcile for the recruiting teams.
What are the emerging sources of data critical to hiring?
As CHROs and business leaders look to align people and business objectives, the following metrics are now emerging:
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- FitScore – not just the % of hires that are “bad hires” and leave within 6 months, but FitScore to the success profile based on objective data for that role. Leaders use a fit-to-role platform to consistently evaluate and score both internal and external hires against objective performance metrics for the role.
- Quality of hire. This looks at the top attributes that will make someone successful in that role, and consistently evaluates all available talent pools against it. A secondary dimension being used is time to productivity. For example, in sales we see a faster time to pipeline, long before quota is met. But this isn’t your traditional subjective metric – this looks at the objective performance of candidates after they’re hired, and tracks their performance in their role. In other words, it closes the feedback loop on the employee journey. This can be achieved with a fit-to-role platform that connects the hiring evaluation to the performance metrics.
The above are rising because business leaders are looking to eliminate “gut-feeling” decision making. Such reliance on subjective evaluations has been proven to increase bias and lower diversity in a company, and negatively impacting business performance. In other words: there are now platforms to close the feedback loop between performance and drivers of performance, so that leaders can drive performance from hiring to onboarding.
Conclusion
2020 has seen 2019 trends accelerating, especially when it comes to the areas of remote hiring, addressing bias and breaking siloes. There is clearly a rise in revisiting recruiting practices based on performance. By tracking fit-t0-role and by leveraging a remote-friendly, digital behavioral interview, companies are breaking down siloes, improving performance and reducing bias.