Best practices for using recruitment analytics for successful hiring

4 mins, 21 secs read time

If you’d like to be more data driven in your recruiting practices, recruitment analytics can help you achieve that goal. You may have noticed that over the past few years, data is coming up in an increasing number of talent acquisition conversations. And for good reason – LinkedIn found that talent analytics roles have grown by 111% since 2014. Plus, talent acquisition teams with mature analytics are two times more likely to improve their recruiting efforts and three times more likely to see cost reductions and efficiency gains.

But what exactly is recruitment analytics and how can you apply it to your work? We caught up with Greenhouse’s Manager of Recruiting Operations Michelle Yoshihara to learn more about how talent acquisition professionals can use recruitment analytics to supercharge their work.

What is recruitment analytics?

Michelle says recruitment analytics is the process of using past data to forecast future performance and improve your hiring efforts. “Recruitment analytics involves looking at the information you have within your ATS or recruiting software – whether it’s from an old search or sourcing strategy – and using that to predict what might happen with future searches.”

This process helps you anticipate your workload and the time frame it will take to accomplish particular tasks. Using past data, you can come up with an educated guess about how long it will take to fill a specific role or how many people you need on your team to support making a given number of hires.

Why is it important to use data and keep track of recruitment analytics?

It’s simple, says Michelle: “If you want to be strategic, you need to look at the data you have.” Instead of relying on a feeling, data allows you to speak more accurately about what is happening right now and what is likely to happen in the future.

When you have access to data and can use it to tell a story, it becomes much easier to get the attention of your VP of HR, your executives and other company leaders. “It really helps to speak the language they’re speaking when you root the conversation in data,” says Michelle. This can be especially helpful if you’re trying to make the case for more resources for your team.

Plus, data helps you manage expectations. Have you ever felt like your hiring manager was asking for the impossible? If so, you’re in good company – 82% of recruiters say they’ve recently dealt with a hiring manager’s unrealistic expectations. Recruitment analytics can help you paint a clear picture of what your team is capable of.

You can also use recruitment analytics to evaluate your return on investment for different sources. Is your spending on certain job boards or events in line with the number and quality of candidates they bring you? Keeping an eye on your spending and the results might help you realize that it’s better to reallocate your budget. And spending less to achieve better results is always a win.

What should you use recruitment analytics to measure?

There’s no single answer here, says Michelle. “It will vary depending on your particular business and team goals.” But some of the common metrics recruiters track include cost per hire (the average amount of budget allocated toward making a single hire), offer acceptance rate (the percentage of extended offers that are accepted) and time to fill (the amount of time it takes to find and hire a candidate). We’ve compiled a list of the most common recruiting metrics and how to calculate them here.

What are some recruitment analytics best practices to keep in mind?

“Making things as automated as possible when setting up your system is going to set you up for success in the long run,” says Michelle. For example, Greenhouse makes it easy to track time to fill because the date the role was opened and the date a hire started are automatically tracked.

When using or creating templates, Michelle recommends keeping it simple with the fields you ask recruiters to fill out. And take the time to let recruiters know why this information is so important to put it in context. “Be sure to explain the value of each individual piece of data that’s being input.”

Michelle also recommends creating a regular cadence of reporting for your stakeholders. When you regularly check in on your data, you learn what to look out for and start to easily identify outliers. Plus, this gives your stakeholders regular insights into what’s happening and helps them prepare for the future. Michelle recommends the Pipeline History & Pass-through Rates and Candidate Quality by Source reports in Greenhouse.

If your team is lucky enough to have a recruiting operations manager (or someone in a similar role), they can also serve as a second set of eyes. Ask if they’d be willing to check up on your reports and flag anything that looks off. This can be especially helpful if your team is new to recruitment analytics and tracking data.

Curious to hear how other teams are making recruitment analytics part of their everyday processes? Check out this story about Tray.io’s data-driven approach to hiring.

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