Data-Driven Hiring: Make Hiring Decisions Based on Stats

More and more talent acquisition professionals are realizing that collecting, tracking, and analyzing data can make them more effective. Data helps them:

Feel more empowered

Make better decisions

Identify opportunities for making improvements

Better align their efforts with business goals

Secure funding for new projects

But what do they measure? How do they measure? And what do they do with the data?

Data-driven hiring used to be about tracking these recruiting metrics:

Time to fill

Time to hire

Source of hire

Cost per hire

Quality of hire

Applicants per hire

Offer acceptance rate

Diversity and gender mix

Application completion / Application abandonment rate

As Lori Sylvia, founder and CEO of online recruitment marketing community Rally noted in the webinar Talent Analytics for Data-Driven Recruiting, these metrics all pertain to the bottom of the recruitment funnel, i.e. they start at the application stage.

But about what happens at the top of funnel, i.e. the awareness and interest stages? Lori argues that it’s equally important to track analytics from the 12-18 touchpoints used by candidates on average prior to the application. Not tracking them, she says, is a missed opportunity to connect with qualified candidates who may not complete the application for one reason or another.

New recruiting metrics on the rise

Many forward-thinking organizations have started tracking metrics related to employer branding initiatives, which pertain to the awareness and the interest stages of the recruitment funnel.

Cumberland Farms, a chain of convenience stores in Massachusetts, and Citizens Bank, an American bank that operates on the East Coast of the US, both track engagement for their online employer branding campaigns.

Additionally, Cumberland Farms continues to monitor the candidate after they are hired, specifically tracking retention, a key metric for their business.

How data is collected

Companies have various systems and tools for collecting and tracking data. Most use a combination of applicant tracking software (ATS) and Google Analytics. Some, such as Citizens Bank, outsource their recruiting analytics, receiving monthly reports about the candidate journey and the effectiveness of their campaigns.

To collect data about retention, Cumberland Farms sends out surveys and does exit interviews. Through them, they were able to identify drop-off points during the first year and create strategies for improving retention. One of the most effective of these strategies was to increase pay at the 60-day mark after the employees were fully trained.

Developing a data-based hiring strategy

Ready to improve your recruiting with data? Here are some tips to get started.

Identify what’s important to company leaders. Is there specific information senior management wants to see?

Invest in the right tools to get the data you need. Consider hiring an analytics specialist or educating yourself about analytics.

Use data to tell a story. Gregg Giambamco, from Cumberland Farms, stresses the importance of aligning metrics to business outcomes. When business leaders understand what the metrics mean for business, they are more willing to fund campaigns and projects.

What story does your data tell?

Consider your company’s business objectives and how you can use recruiting metrics to contribute to them. Decide how you will collect the data and report on each metric. And once you have the data, make sure to analyze it in context and apply what you know to make real improvements.

What metrics do you track and how?

For more about data-based hiring, check out Recruitment Analytics: The 9 Recruiting Metrics You Should Be Watching.