Chauncey grew up on a farm in rural northern California. At 18 he ran away and saw the world with a backpack and a credit card, discovering that the true value of any point or mile is the experience it facilitates. He remains most at home on a tracto.
Chauncey Crail ContributorChauncey grew up on a farm in rural northern California. At 18 he ran away and saw the world with a backpack and a credit card, discovering that the true value of any point or mile is the experience it facilitates. He remains most at home on a tracto.
Written By Chauncey Crail ContributorChauncey grew up on a farm in rural northern California. At 18 he ran away and saw the world with a backpack and a credit card, discovering that the true value of any point or mile is the experience it facilitates. He remains most at home on a tracto.
Chauncey Crail ContributorChauncey grew up on a farm in rural northern California. At 18 he ran away and saw the world with a backpack and a credit card, discovering that the true value of any point or mile is the experience it facilitates. He remains most at home on a tracto.
ContributorCassie is a deputy editor collaborating with teams around the world while living in the beautiful hills of Kentucky. Focusing on bringing growth to small businesses, she is passionate about economic development and has held positions on the boards of.
Cassie is a deputy editor collaborating with teams around the world while living in the beautiful hills of Kentucky. Focusing on bringing growth to small businesses, she is passionate about economic development and has held positions on the boards of.
Cassie is a deputy editor collaborating with teams around the world while living in the beautiful hills of Kentucky. Focusing on bringing growth to small businesses, she is passionate about economic development and has held positions on the boards of.
Cassie is a deputy editor collaborating with teams around the world while living in the beautiful hills of Kentucky. Focusing on bringing growth to small businesses, she is passionate about economic development and has held positions on the boards of.
Updated: Jul 9, 2024, 9:27am
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One of HR’s many functions is to act as an organization’s eyes, looking both internally and externally for information and comparisons that are useful to bettering a business. Human resource metrics are like an essential pair of glasses—without them, workplace data is visible but unintelligible. With the right lenses, patterns, trends and discrepancies come into focus and organizations can approach decision-making processes with a clearer picture of reality. Here are ten top HR metrics to consider when using a data-driven approach for talent management.
This tried-and-true HR hiring metric is as relevant in 2024 as ever. Cost per hire (CPH) shows how much a company spends on average to acquire a new employee. As with any value-per-person or “per capita” figure, a value can be reached by simply dividing costs by the number of people in question—here, total hiring dollars divided by total new hires within a given time period. The result is essentially a simplified cost-benefit ratio expressed in one easily comparable figure.
HR departments have long relied on CPH as one way to gauge the efficiency of the hiring process, as it’s more descriptive than simply adding up expenses. Importantly, this metric includes the costs incurred by outreach to all prospective employees, including those not ultimately hired. While this may seem counterintuitive, it’s less variable and more illuminating of cost-effectiveness, not to mention much more practical to calculate.
For consistency in comparison, the Society for Human Resource Management (SHRM) and the American National Standards Institute have created standardized definitions for what internal and external costs are to be included in the calculation. Included are rather obvious costs such as paying for recruiting staff, recruiting software and advertising, but the list also includes expenses such as health screenings, drug tests, sign-on bonuses and relocation fees the company must cover while preparing for a new hire. The SHRM estimates that in 2021, American organizations spent on average nearly $4,700 per hire and over $28,000 per executive-level hire.
Another essential metric for HR, “time to hire” measures the time from a prospective employee engaging with the recruiting process to their acceptance of a position. Similar to cost per hire, this is expressed as a per-person average and is used to assess the efficiency of the “talent acquisition” process. Investigating a lengthy time to hire may point to poor reach (job posting or advertising) or to underperformance of the hiring teams in charge of filtering candidates. Regardless, it’s a sign prospective employees aren’t being sufficiently engaged and may be lost to competitors or turned off by the company’s hiring process.
Many HR resources are vague or inconsistent in defining what exactly marks the start of the time-to-hire period. Some use first contact between the candidate and employer while others use the submission of a candidate’s application, which are sometimes different events. However it’s defined, time to hire is distinct from “time to fill,” which begins when a company makes an initial job request and ends when a candidate accepts your job offer.
Perhaps the broadest in scope of any metric on this list, “quality of hire” is something of a super-metric encompassing several different employee metrics (often called “indicators” in this context). The selection of these indicators will vary depending on the specific goals involved.
Unlike cost per hire and time to hire, quality of hire attempts to show the value an employee brings to a company, shedding light not on the efficiency of the hiring process itself but rather on its return on investment. The SHRM describes quality of hire as the “holy grail” of recruiting metrics due to how thoroughly it can address employee value compared to other, narrower metrics.
The general formula for quality of hire adds up the values from whatever employee indicators are being used and divides the result by the total number of indicators being used.
So what are the indicators that compose quality of hire? A 2017 SHRM survey found that “performance appraisal scores,” “retention rates” and “360-degree feedback scores” are the most popular inclusions. Other common inputs include “customer service scores,” “rate of salary increase” and “profit contribution.” While there are different ways to score quality of hire, it’s common for the indicators to be expressed as a percentage, meaning the resulting average will be expressed the same way.
An eNPS measures how much a group of employees would recommend or not recommend employment with their company to others. It’s relatively easy to measure and serves as a good, though general, proxy for overall employee satisfaction.
An employer surveys employees by asking, on a scale from zero to ten, how likely they are to recommend the company to others as a place to work. For calculation purposes, respondents who choose a nine or ten are categorized as “promoters,” those indicating a seven or eight are “passives” and those with a six or below are “detractors.” To calculate an eNPS, subtract the number of detractors from the number of promoters, divide the result by the total number of respondents and finally multiply this figure by 100.
A score of 40 to 50 is considered excellent and any score above 20 is still good, while the ten to 20 range is fair. An eNPS of below ten is considered indicative of more serious workplace satisfaction issues. Regardless of the outcome, employers may wish to include an opportunity for further comment on their survey to better understand what is driving satisfaction or dissatisfaction.
Results can be broken down by the respondents’ workplace characteristics (length of employment, position, department, etc.) and by broader demographics (age, gender, race, etc.). This can help HR teams learn more about issues such as employee burnout, satisfaction with department leadership and equitable treatment among employees of varied identities. For example, if women consistently respond less favorably than men, HR can investigate issues with workplace culture or gender-based discrimination. Using an eNPS in this way allows HR to build a picture of the workplace with only very general questioning, sidestepping loaded survey questions that employees may struggle to answer openly.
Absenteeism, which usually refers specifically to unscheduled absences from work, can have a variety of causes. It may indicate employees’ challenges with health and well-being, rather than with commitment or workplace dissatisfaction. Either way, collecting attendance data is important to HR, both for evaluating the costs and patterns of missed time and for better understanding employees’ needs.
To calculate an absenteeism rate, divide the number of unexcused absences by the total number of expected workdays within any set amount of time. Then, multiply the result by 100 to reach a percentage. The closer to zero, the better.
The equation works the same for a whole company as it does for a single employee and can be applied to time periods of any length. It can be calculated for individual departments within a company, too—so long as the inputs are adjusted accordingly. When calculating for a group, just remember that the “# of expected workdays” used in the equation represents the whole group’s individual workdays added together. In other words, there will be as many “expected workdays” in a single day as there are number of people. For example, a team of ten people working for five days will accrue 50 expected workdays in this context, not five.
Sometimes referred to as “company growth rate,” this metric indicates how much a company is either growing or shrinking its number of employees. It describes this change over any given period of time—perhaps a quarter, a year, five years—by using a headcount at the start of the period (“Point A”) and at the end (“Point B”).
To calculate employee growth rate, begin by subtracting the head count at Point A from the head count from Point B. (If there was a net loss in employees, this value will be expressed as a negative number, making the end result negative as well.) Next, divide this figure by the head count at Point A. Finally, multiply the result by 100 to represent it as a percentage.
Understanding a company’s rate of growth or contraction in terms of employee strength can be important for future planning. A simple head count can inform HR of certain company needs, but being able to predict how these needs will change in the future is critical for many workplaces. HR may also find it useful to compare growth rates between subsections of a company such as different departments or employee tiers, which can shed light on patterns in hiring practices. It may also be desirable to calculate separate employee growth rates for many sequential time periods and to compare the rate of change over time, which gives a more detailed picture than a single figure.
True to its name, employee turnover rate (ETR) reveals the number of employees who resign or are let go within a given time period (often a month or a year). At its core, the figure is simply a ratio comparing employee departures to total employees. As such, it can be calculated by dividing the number of departures by the number of employees at the outset of the time period in question and multiplying the result by 100 to reach a percentage.
An ETR is inversely proportional to the “employee retention rate,” so if 85% of a company’s employees stay on through a given time period, the ETR is 15%. Observable patterns in ETRs can indicate both the percentage of employees who can be expected to depart and also the average likelihood of departure for any one employee.
While most companies strive for the highest possible retention rate and the lowest possible turnover rate, some degree of employee turnover is usually healthy. It’s hard to put a number on ideal rates because turnover expectations can vary dramatically industry to industry, but in many cases, moderate ETRs don’t necessarily imply poor hiring practices.
Due to its very general nature, an ETR is often combined with other metrics to paint a more complete picture of workforce dynamics. Combining it with employee performance metrics, for example, can indicate whether being a top performer at a company increases retention prospects or alternatively increases the likelihood of departure in search of better opportunities. When combined with demographic data, high ETRs observed among specific identities can be one potential sign that workplace inequities or a troublesome company culture are driving away particular employees.
Salary averages can be used to describe relative compensation for virtually any category within a company. This includes subgroups of a company structure, such as different position levels or departments, as well as employees’ demographic groups. To calculate a salary average, begin by adding up the salaries for all members of the specified group. Then, divide that dollar amount by the total number of group members.
Salary averages can be useful both internally and externally. While cross-comparison within a company is important, these averages can also inform how employees at a certain position level are compensated compared to peers at competitor organizations, or when compared to a local or national average. For this, these averages are essential, but while simple and broadly applicable, salary averages by themselves provide minimal insight into the reasons behind any discrepancies, typically offering possible points of correlation but failing to deliver causation.
This metric describes how well an employee is currently being paid relative to an employer-determined salary range for a position. There are many reasons why an employee may be at the high or low end of an anticipated salary range. From an HR perspective, the important part is making sure the reasons for any variance between employees are appropriate.
To begin, identify the minimum and maximum values for the estimated salary range of an employee’s position. Subtract the range minimum from the employee’s current salary. Then divide this figure by the difference between the range maximum and minimum. Finally, multiply by 100.
The resulting percentage describes how far the employee has “penetrated” into an anticipated salary range, with 0% penetration being equal to the range minimum and 100% representing the maximum. For example, in a position with a salary range of $80,000 to $100,000, an employee making $90,000 has achieved 50% penetration; $95,000 would equal 75% penetration.
A figure such as this on its own can be useful at the individual level, but HR departments will likely want to compare salary range penetration statistics among groups of individuals within the company or even externally. Doing so can have many possible utilities, though particularly important is the ability to assess pay equity. For example, observing a pay gap based on salary averages offers less insight into company practices when factors such as position and hours worked are not controlled for—however, combining penetration figures with stats on gender representation in a company hierarchy can provide more targeted information about disparities.
A “diverse” group of employees can mean many things, though the language generally implies the inclusion of employees with varied gender, racial and cultural backgrounds, to name a few examples. As more companies push to include the language of “diversity, equity and inclusion” (DE&I) in company cultures and hiring processes, it’s important to have honest assessments of a company’s performance to back up the rhetoric. For HR departments, understanding representation often begins with employee diversity ratios.
To express diversity data as a ratio, the head counts for two groups being compared are commonly placed side by side. A three-to-one (3:1) ratio, for example, means that there are three employees in the first category for every one employee in the second category. For easy comparison, ratios take the totals (in this case, the employee head counts) of each group and divide them each by the largest factor they share (their “greatest common factor”), sometimes rounding if the groups are large.
For example, let’s say a company has 495 white employees and 163 employees of color. HR might want to know how this makeup compares to broader population metrics, smaller subsections within the company, internal data from the past or metrics from other similar companies. Expressing the ratio as 495:163 is not incorrect but it’s clunky and difficult to compare. However, divide the total of each group by 165 (an easy number very close to 163) and the resulting figures are 3 and 0.988. Because the latter figure is extremely close to 1, we can just say that there’s a 3:1 white to non-white ratio in the company’s workforce.
Comparisons such as these can prove essential to HR for simplifying the numbers and helping develop specific goals. Lumping all non-white employees into a single category, however, has obvious practical limits among other major ethical drawbacks, as does any act of overgeneralizing for easy comparison. Importantly, HR teams must also be aware that increasing head counts within certain categories only begins to address the first part of “DE&I.” The “equity and inclusion” aspects require much more work than simply hiring toward favorable ratios.
For HR teams, simply having data and employee metrics on hand is just the start, but it can be half the challenge to achieve. If your organization is light on data collection, look for ways to collect new data or to interpret existing, unused data through statistics. Collecting data doesn’t have to mean encroaching on employee privacy. It can be as simple as aggregating data on employee bonuses in one centralized place, for example, such that patterns can be tracked and more bonuses can be awarded where they’ll count. Another great place to start is the simple employee survey, which can be surprisingly illuminating.
Look for the areas where your company is most interested in seeking unknown information—evaluating candidates during the hiring process is usually a big one, as are the many factors that can boost or hinder employee productivity. Many companies are also more “in the dark” than one might assume about what factors drive retention and attrition. Whatever the case, a data-driven approach through HR metrics beats speculation.
One of the best ways to use HR metrics is by overlaying several of them to build a bigger picture. Many of the metrics listed here provide decent information by themselves but impart real insight and directives for change when combined. For instance, employee compensation metrics such as salary averages and salary range penetration simply allow HR to see who gets paid what. Compare this data side by side with employee satisfaction metrics such as eNPSs or turnover rates and patterns may emerge, answering questions about how effectively (or ineffectively) compensation tools are increasing retention and where raises can be most efficiently applied.
So long as the data are accurate, what we make of HR data and how we manipulate it to develop metrics for success determines how successful our analysis will be. For successful HR teams, the most important job is to put existing data to use and to look for new areas where uncollected data can be transformed into telling metrics. Advances in workplace technology and data management tools make this easier than ever.
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