Hiring Data You Need to Be Tracking

4 Kinds Of Hiring Data You Need To Be Tracking

Hiring today looks a lot different than it did 10 or 20 years ago. What used to rely on a piece of paper and a gut feeling now relies on recommendations, evidence, and data. And it’s all thanks to recent advances made in technology.  

Of these factors, hiring data is particularly important, as it can essentially reveal how well (or not well) a job candidate will perform in a role, if hired. Rather than taking a candidate’s word for it, hiring data can provide the much-needed evidence hiring professionals need to make an informed decision.

So, to help you better identify top talent, here are four things to take into consideration when it comes to hiring data:

1. Start with a rubric.

Before you even begin gathering candidate data, you need a streamlined evaluation process. That’s why we advocate for using interview rubrics to eliminate emotional biases and conduct a more efficient recruiting process.

A rubric can prevent you from jumping to conclusions by replacing emotional judgment with bite-sized factors — helping you make objective, micro-evaluations about each candidate.

Great candidates come in different forms. A rubric will help you compare different profiles and resolve differences in strengths and weaknesses.

Jordan Wan, founder and CEO, CloserIQ

2. Focus on predictive data…

Hiring managers should focus on data metrics that have evidence of being predictive of on-the-job success, such as a pre-hire assessment score, a company culture fit score, a job test score, and a structured interview score.

Using these types of data metrics will increase the likelihood of hiring the right candidate, but it won’t guarantee it. This is because there are many on-the-job contextual factors (e.g. your supervisor, your co-workers) that also determine how successful someone is at work.

The best ways to use these data metrics when evaluating potential new hires is to put in place a standardized, objective system for every candidate.

My biggest tip for effectively using this data when hiring is to use software tools that automate and standardize the process for you: software that assesses every resume for you, software that tests candidates’ job-related knowledge, software that helps you interview candidates, etc.

Using software will not only allow hiring managers to accurately use data to compare candidates to each other, it significantly reduces the amount of time and administrative burden it takes to collect and analyze this data.

Ji-A Min, Head Data Scientist, Ideal

3. …as well as what can be measured.

Our experience shows that the most reliable metrics are the ones that can be properly and objectively measured. It is easier and less subjective to focus on hard skills. Skills such as “how well somebody can use Excel” can be a reliable metric, especially when it comes to productivity at the workplace, so it can be hard to ignore.

Everybody knows that soft skills are really important. However, it is so hard to measure them, let alone to get honest responses from candidates, that the attempt to get any metrics usually is not worthwhile.



Stelios Lambropoulos, Product Manager, TEST4U

4. Rethink “time to hire.”

We’ve been using “time to hire” for a while, until we found ourselves in this situation: “OK, this job takes longer to fill than the other job. But why?” Often, it’s by the end of the hiring process. Thirty days have gone by and we honestly didn’t know where to dig up the reasons for the slowness. So, we found a better metric to use: interview to hire.

We track both the time and the reason “why” the hiring decision is made. The time tracking starts the moment a candidate is tagged with “interview stage” and it ends the moment they sign the contract. Then, we track why the candidate gets the job offer.

Since the implementation of this metric, we have seen two improvements in our hiring process: we close candidates faster and we are more aware of why we choose some candidates over others.

Perry Oostdam, co-founder and CEO, Recruitee

What hiring data metrics do you measure? Let us know in the comments below!