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As organizations look to audit and optimize their tech hiring processes, these hiring metrics are essential for learning how to do more with less
It’s easy to understand the value of a data-driven recruitment process. However, it’s not always clear precisely which hiring metrics to track.
For example, in our most recent tech hiring trends report, we asked talent and engineering leaders which metrics they use to evaluate software engineer candidates at their organizations.
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We found that each group responded differently, with engineering leaders more likely to focus on interviewer performance and the technical interview passthrough rate, and talent leaders more likely to focus on time spent in the technical hiring process.
Neither of these groups is necessarily right or wrong. But it’s important to note that the hiring metrics you track (and how much weight you give them) can lead to different insights and outcomes.
In this article, we’ll list some of our preferred hiring metrics and discuss the benefits of tracking each of them.
Here are some of the hiring KPIs we suggest considering as you formulate your data-driven hiring strategy:
Even if you use structured and standardized interviewing techniques to ensure fair and honest evaluations of candidates, there will still be differences between individual interviewers.
Which interviewers are leading to the highest-quality hires, and which are underperforming?
If you can answer that question, you can drill down and solve the problem. For example, an interviewer may be underperforming due to not following your standard process or by letting their personal biases impact their results.
How many days elapse between a job opening becoming available to when a candidate accepts the role?
This commonly tracked metric is useful for two key reasons.
First, it enables more accurate forecasting of capacity based on current staffing levels.
Second, it’s a great metric to track the effectiveness of improvements to the hiring process over time. Ideally, improvements should result in increased efficiency, which reduces time to fill.
Lower time to fill usually correlates with time saved, reduced resource usage, and increased candidate satisfaction.
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Time to hire is slightly different from time to fill. Rather than measuring the entire process from job opening to offer acceptance, it focuses on the time the eventual hire spends in the hiring pipeline.
In other words, how many days elapsed between when the candidate applied and when they accepted an offer?
Time to hire is strongly correlated with candidate satisfaction with the hiring process, and low time to hire can be a differentiator in competitive fields such as software engineering.
For technical job roles, it’s smart to measure the number of candidates that make it through the technical interview stage of the process.
Low passthrough rates may be indicative of issues with your sourcing/talent acquisition or with the technical interviewing process itself.
For example, many of the organizations we work with find that too few of their candidates are making it through the technical interview round, limiting the talent pool. Improvements to the process (such as offering redo interviews) have been shown to increase passthrough rates and total hires.
Diversity in recruiting is essential to getting the best talent on your team. Unfortunately, in many organizations, diverse candidates end up missing out on opportunities due to biases in the hiring pipeline.
While assessing the demographics of your hires is the obvious way to track diversity, you can also use candidate surveys and anonymous interview feedback to identify diversity, equity, and inclusion issues.
Negative experiences in the hiring process due to poor communication, biases, or overly arduous requirements can reduce the quality of your talent pool. The last thing you want is for great-fit candidates to go another direction because they were unsatisfied with the hiring process.
Collecting feedback from candidates at different stages of the hiring process can help you calculate satisfaction scores and work to improve the candidate experience over time.
How many candidates that were interviewed eventually received a job offer?
This metric is indicative of the accuracy and efficiency of the early stages of your hiring process. It’s important to track because a low interview to offer ratio means you’re likely wasting resources interviewing unqualified candidates.
An even more specific version of this hiring metric is the “onsite to offer” ratio, which measures the efficiency of the most time-consuming and intensive step in most organizations’ hiring processes.
Of the candidates that receive a job offer, how many accept?
This metric is a great indicator of the competitiveness of your offers. If your offer acceptance rate starts slipping, it may be time to reassess your compensation or employee perks.
In addition, tracking offer acceptance rate alongside candidate satisfaction can help you identify if candidates are passing on offers because they have a negative impression of your organization during the interview process.
Hiring metrics don’t stop when a candidate steps into their new role on the team. To truly close the loop, it’s necessary to track whether that employee meets the expectations and requirements of the job, how long they stay employed, and their overall productivity. For many engineering leaders, this corresponds directly with engineering performance on the job.
Is there a correlation between the quality of your hires and the source of their application?
This is helpful to guide your recruitment efforts and allocate resources toward the highest-quality talent sources. It can vary based on factors like geographic location, school, industry, prior employer, and more.
While the exact hiring funnel metrics you should be tracking depend on your industry, priorities, and the strengths and weaknesses of your hiring process, there are a few rules of thumb:
Regardless of which hiring metrics you select, tracking them can help you find opportunities for improvements in the hiring process, which can ultimately lead to you filling more positions with great candidates faster.
Looking for a data-driven hiring process for software engineering talent? Karat can help. Request a demo.
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