How effective is your company’s recruiting strategy—and your personal contributions to overall goals?

At face value, this question is a tough one to answer. That’s because recruiters often lack the HR analytics they need to connect the dots between efforts and outcomes. Whether you’re staffing hundreds of positions for a Fortune 50 company—or a few dozen roles for a small startup, you’re in perpetual context switching mode.

At any given time, you could be writing emails, creating job descriptions, updating applicant tracking systems (ATS), screening candidates, coordinating interviews with hiring managers, making offers, and reporting back into your team. It’s tough to know whether your efforts are making the right organizational impact.

Should you measure success based on how quickly you fill open roles? Should you be increasing the number of conversations you’re having in a day—or how many resumes you screen? Should you be looking at the ratio between extended and accepted offers?

These are trick questions. The answer all three questions is both yes and no.

Sometimes, the right metrics are also the wrong metrics to measure. Here’s why.

Data can have multiple, hidden meanings—and untold stories beneath the surface.

Consider the following scenarios:

  • Let’s say, for instance, that you’re a tech sourcer at a Fortune 50 company, and you’re responsible for filling hundreds of roles. You may be inclined to measure success based on how fast you bring on new teammates. Or, let’s say that you’re a recruiting generalist at a small, 30-person startup that has goals to double in size each year. In both situations, you may feel inclined to measure recruiting velocity as a function of the speed at which you’re placing candidates. But what if half those candidates leave your company within 18 months? Were your efforts still successful?
  • Maybe you’re reading hundreds of resumes a day to ensure that you’re not overlooking your highest-potential hires. But should you be spending your time, instead, on building relationships your highest potential candidates? Are you wasting hours in your day without realizing it?
  • If you’re recruiting talent for a startup, competing with larger entities for top talent, you may be happy to see a near 100% acceptance rate for the offers that you extend. But there are nuances beneath this surface-level picture. For one, the people you hire today may not represent the skills that your company needs in 1-2 years. Are you hiring people who have the potential to evolve with your company, or do you expect that they will leave as your organization evolves? Are you increasing the risk of employee churn, hiring for a role that a person may not want a year from now?

If you want to measure successes—and weaknesses—in your recruiting strategy, you need more than a one-dimensional set of metrics. That’s where the practice of data science enters the picture. The right key performance indicators (KPIs) will paint a picture of how your recruiting metrics influence your HR analytics—and how this cohesive quantitative picture influences long-term organizational outcomes.

As a recruiter, you wear many hats ranging from educator to communicator and even seller—your candidate interactions serve an important role in convincing people to take a job. An additional hat to consider wearing—to help you save time and improve performance—is data scientist. That means poking holes in your metrics, diving into the reasons behind a trend, and always seeking alternative explanations for what you observe.

“Good data scientists know that analyzing data is the easy part,” explains Jeff Bladt and Bob Filbin, two practicing data science leaders, for Harvard Business Review. “The hard part is deciding what data matters.”

Which HR analytics to measure

How Do You Know What Data Matters?

The answer to that question depends on the stories you’re seeking to learn.

The metrics you choose to track should tell a holistic, cohesive story about your business. The trickiest part about this process is that organizations are multidimensional. The success of a business incorporates several components — profits, people, processes, technology, and beyond. Effective recruiting metrics, as part of a larger HR analytics picture, communicate a story of how these elements relate to one another.

So what distinguishes “good” recruiting metrics from mediocre ones?

In an article for Towards Data Science, Filipe Rigueiro, founder of Uni Data, elaborates that good metrics are:

  • Comparative across time periods, groups of users, or competitors to facilitate an understanding of how things move.
  • Understandable and memorable enough to influence core business processes.
  • Consist of ratios or rates that are inherently comparative and intuitive to act upon.

In the HR realm, “good” recruiting metrics include data that:

  • Communicates whether teams are meeting goals in staffing urgent positions—as well as shedding insight into why or why not
  • Enables recruiters to identify sources for their best hires
  • Helps hiring managers, recruiters, and executives see the relationships between open reqs and company growth
  • Empowers functional leaders to identify areas or departments that need help

“Recruiting metrics allow everyone—recruiters, hiring managers, and executives—to take a step back from the day-to-day tasks of hiring to get an overview of the effectiveness of their hiring process,” explains an article from Hire by Google. “They ensure that every decision serves a broader company goal, with every dollar of recruiting spend translating into meaningful company growth.”

The right metrics will help recruiters align their individual-level actions to bigger-picture company outcomes.

HR analytics measurements and data points

So What HR Metrics Should You Measure?

Ultimately, recruiting is about people.

When you hire the right person for the right role, you create positive ripple effects in your business. But if you hire the wrong person? To use an analogy from the scientific community—Newton’s third law—every action has an equal and opposite reaction force.

Hire the right people, and they’ll attract fellow awesome candidates.

Hire the wrong person, and they’ll contribute to a toxic work culture—potentially forcing top performers out of your organization.

Capturing these stories on an individual-level process is the easy part. Over time, through a mix of feedback and observations, recruiters develop a strong sense of who makes an ideal hire—and who doesn’t.

Trend data aggregates these individual level stories into a higher-level strategic picture for your business. These HR analytics shed valuable insight into into line-item performance of your business. Consider the scenario of employee churn, for instance.

“The cost to replace an employee could be over 200% of their annual salary” explains an article from MicroStrategy, Inc and research from AmericanProgress.org. “The true cost might even be higher due to training/onboarding, lost productivity, recruitment, and decreased morale among other employees. Losing an employee that’s in the top 1% of performers could mean the difference between growth and decline.”

Aggregate-level data uncovers trends that you may not otherwise see from a partial, individual-level story. Here are some metrics that your team can consider measuring:

1. Hiring duration

This metric quantifies the time that elapses between the moment a recruiter posts a job to the point of making a hiring decision. There are two ways of looking at this metric.

Time to fill corresponds to the time it takes to find and hire a new candidate, assessed by the number of days between a req opening and a person accepting a role.

Time to hire refers to the time that passes between a candidate applying for a job and then accepting it. Quantifying this metric from both perspectives can help recruiters identify where to focus their efforts—between candidate sourcing and engagement, for instance.

2. Hiring effectiveness ratio

What you’re comparing, here, is the relationship between openings and filled positions. An ideal ratio will be a tiny number—less than zero. The bigger your company, the smaller this number should be. Over time, as your recruiting operations become more efficient, the number will become smaller. The tricky part of this calculation will be choosing a denominator to represent “filled positions.”

For instance, it won’t make sense to include all filled positions in your company, given the variety of time periods that employees stick around. When choosing “filled positions,” one approach is to examine multiple time horizons over a monthly, quarterly, and six month basis. With this comparative picture, your recruiting team can identify specific inflection points as to when effectiveness tends to increase—and decrease. You can use this metric to benchmark and eventually develop predictive capabilities into the speed at which critical roles get filled.

This level analysis gives recruiting, HR, and business teams the ability to forecast exactly how long it takes to staff different types of roles.

3. Selection ratio

You can calculate this metric by comparing the number of people you hire compared to the total number of candidates who apply for a role. At first, this metric will be exploratory—meaning that you’re gathering data simply to learn.

Over time, as you analyze your data, you’ll determine a baseline for what your ideal selection ratio will be. This metric will help you develop a greater sense of focus in your day-to-day. With it, for instance, you’ll be able to see how many reviewed resumes, screening calls, and outreach emails it should take to fill a role in a particular function.

And over time, a healthy selection ratio will be a steady number that is neither increasing nor decreasing. That’s because, as a recruiter, you want to cast your net just wide enough to find the right people. You don’t want to cast your net too wide or too narrowly. Your selection ratio will help you determine what that optimal balance is.

4. Applications and hires by source

How are people discovering open roles within your company? Which of those people consistently convert into your best hires?

Candidates discover job opportunities through a variety of channels—social

media, job boards, communication with talent sourcers, referrals, blogs, and

countless others.

As a recruiter, you need to determine where to invest your sourcing budget.

Which channels are yielding the highest volume of applications? More importantly, which of these sources are the best funnels to discovering your best candidates and hires? An understanding of these questions makes a recruiter’s job easier, more expedient, and more efficient—consequently yielding improvements to every other metric that you’re tracking to measure your impact on the overall business.

5. Retention rate

A placement is only as valuable as that candidate’s duration within your company. Given the high costs of replacing employees, it’s important to find people who are likely to stick around. Are there certain recruiting channels that open doors for teammates with longer tenures? Does the speed of the interview process correlate with the likelihood of the number of years that someone will stay with your company?

Employee retention and attrition are often the focal point of many HR analytic

Strategies. This metric articulates, exactly, how a first encounter with a

candidate influences that individual’s long-term tenure with your organization.

This quantitative connection sheds insight into your company’s profitability equation.

6. Applicants per opening

This metric sheds insight into the supply-side of your talent market. Some roles, for instance, require more specialized skills than others.

If you find that you’re receiving an abundance of applications for certain roles,

you may want to consider opening up another position—or tightening up your

requisites to attract candidates with more specific skills or types of experience. If

you’re not receiving enough applications, you may want to open up your job

description to attract a wider candidate pool. After all, your company can

always invest in education and training for the right hire.

7. Offer acceptance rate

This metric is a ratio between the number of offers made, compared to the number of accepted offers.

This metric communicates a few different perspectives. First of all, it paints a picture regarding the strength of your offer. Is your company competitive with others in the market? Secondly, this metric tells you how enthusiastic people are to work for your company.

Higher offer acceptance rates are an indicator of people being excited to work for your company. This metric is also indicative of whether you’re targeting the right talent pools in your recruiting efforts.

If your offer acceptance rates are low, you will want to investigate why. For instance, you can run a survey that examines the reasons behind candidates’ decisions to accept or turn down roles. Based on this information, you may consider changing your own internal processes—or expanding your hiring pool into new sources for talent.

8. Employee satisfaction rates

This metric enables recruiting and HR analytics team to join forces. Your recruiting team may be successful in getting candidates in the door and filling open positions. But who is happiest long-term? Who’s advancing? Who’s getting raises? Who finds the most meaning in their work?

An understanding of long-term outcomes will create a feedback loop into your talent sourcing strategy—as well as the candidate segmentation programs that you build.

What are the personality traits of your best employees? What makes people happiest at your company? Find more people who embody the traits of your most enthusiastic and passionate performers.

Conclusion: Analytics Help You Focus

All recruiters need more hours in their days. When you free up time from busy work, your better positioned to do what you love—talk to people, extend offers, and support individuals in finding their dream roles.

Every company is different, so we’d love to hear from you.

  • What recruiting metrics would you add to this list?
  • How are you aligning staff data with deeper HR analytics?
  • Which analytics will affect business outcomes?