Improve on Key Performance Indicators
With HR Analytics Software
IndustryView | 2015
Human resources (HR) analytics falls under the umbrella of “big data,” a popular buzzword in the software and technology space. However, little research has been done on how analytics impacts key HR and recruiting metrics. To learn more, Software Advice spoke with experts and surveyed HR analytics users. This report will help small-business owners and recruiting and HR professionals determine how using data and analytics can improve a company’s hiring process.
Techopedia defines HR analytics as “applying analytic processes to the human resource department of an organization in the hope of improving employee performance and, therefore, getting a better return on investment.”
Obviously, this definition is rather broad. For less tech-savvy companies, HR analytics may be as simple as a formula in a spreadsheet. For example, a sales team manager might calculate the number of conversions the company receives per day to determine how many new salespeople need to be hired next quarter.
Alternatively, these analytics can be somewhat more sophisticated. For example, some companies may leverage data collected in their human resources information system (HRIS), which often includes completed trainings and performance reviews for individual employees. This data can help HR professionals identify common skills and attributes among the company’s strongest performers in order to look for similar candidates when hiring.
In both examples, HR analytics is used to improve a company’s bottom line. This occurs either by ensuring there are enough employees to bring in maximum revenue, or that new hires have similar skills and attributes to the company’s most successful current staff. The second example, however—which involves using software to aggregate data and identify trends—is the type of HR analytics our report will focus on.
For small businesses, this process can be especially important. Software Advice surveyed recruiters who use some type of HR analytics—both in the form of software or manual methods, such as self-created formulas—to determine whether HR analytics software can help businesses improve on departmental key performance indicators (KPIs).
Given the hype over the past few years about how HR is shifting from an administrative department to one that plays a crucial role in outlining business strategies, one would think HR analytics would be in widespread use across HR departments.
However, according to a 2013 assessment report by SHL, a leader in talent management solutions, less than half of global companies use analytics to make talent-related decisions.
This begs the question: Is HR analytics software worth the investment? And if so, how does the use of analytics impact hiring and other key metrics?
One of the best ways for HR departments—and businesses in general—to measure their success is to evaluate their performance against KPIs. In the world of HR, these KPIs often include the following:
Dave Weisbeck is the chief strategy officer at HR analytics software vendor Visier. When asked which HR KPIs analytics software is most likely to improve, his answer is simple: “All of them.”
Our survey data suggests Weisbeck is correct. We asked recruiters to rate their performance on HR KPIs on a scale of “very poor” to “very good,” and it’s apparent those using analytics software perform much better on KPIs across the board.
For instance, when it comes to the common recruiting metric of time to hire, those respondents using HR analytics software report significantly better performance than non-software users: a combined 86 percent report “good” or “very good” performance, while only 58 percent of non-software users report the same.
Respondents using HR analytics software also have many positive things to say about their experience. For instance, one recruiter in our sample notes that it has helped their company improve retention:
“We have successfully identified traits in our employees that will suggest their future willingness to remain with the company,” the respondent says. “Using this data, we try to recruit people with similar traits.”
Another respondent finds that, by using HR analytics software to help create more thorough and focused training initiatives, their company has been able to improve retention and lower training costs. Using HR analytics software, the respondent explains, helps the company tailor its training programs to each individual employee to focus on areas that will directly impact their job performance. This decreases training time and helps identify where in the organization certain individuals should be placed, which increases placement effectiveness.
Next, we wanted to learn which companies are actually experiencing the above benefits of HR analytics software. According to our survey data, small businesses of one to 100 employees are most likely to be using some form of an HR analytics solution (27 percent).
According to Brian Gaspar, senior director of product innovation at SumTotal Systems, this may be because using HR analytics in the hiring process is “more critical” for smaller businesses. For these firms, he explains, if even 5 percent of hires are not the right fit, this can have a disastrous effect on their bottom line.
On the other hand, if a larger company with thousands of employees has 5 percent of hires that are ineffective, “it’s not going to really impact them too much, because there’s enough workforce in there to mitigate that,” Gaspar says.
But this begs a key question: If HR analytics software clearly has a positive impact on a company’s hiring success, why don’t all companies use it?
The answer is perhaps not so surprising: the perceived cost of implementation. When we asked respondents who use manual methods for HR analytics (e.g., spreadsheets) why they choose not to invest in software, 53 percent cite cost as the reason.
However, it’s important to note that many of these respondents also say they have not verified that the cost is in fact out of their price range.
“We don't have it in the budget,” notes one respondent. “I honestly haven't looked into it, though, and assume it will be expensive.”
As Gaspar and Weisbeck note, despite the initial investment, HR analytics software can actually help smaller businesses save critical funds by making smarter hires. Thus, it may be in the best interests of smaller businesses that are growing their employee base to thoroughly evaluate the return on investment of purchasing an HR analytics solution.
After all, most systems in the HR software space are now cloud-based—and this deployment method is considerably less expensive than traditional, on-premise deployment when it comes to upfront costs. With cloud-based software, instead of paying for a license to install and operate the software on their own servers, businesses pay a monthly (or yearly) subscription fee to the vendor. In return, companies are able to access the software on any device with an Internet connection, and the software is secured and maintained by the vendor.
While we’ve seen that the use of HR analytics software can have an extremely positive impact on HR KPIs, Gaspar notes that adoption rates are still fairly low. Indeed, even among those respondents in our sample with the highest level of adoption (businesses with 100 or fewer employees), the adoption rate is still only 27 percent.
One reason may be due to confusion surrounding the topic: The term “HR analytics” can mean many things to different people. As such, we wanted to see if our respondents could agree on a definition of the term.
We provided a list with the correct definition (statistically modeling employee data) along with other definitions that are common misconceptions about the scope of HR analytics, asking respondents to choose the right one.
These other definitions include:
As it turns out, only 55 percent of respondents are able to identify the correct definition. The other 45 percent, combined, choose a definition that falls short. Therefore, the low adoption rate of HR analytics software may be partially due to ignorance of what can be accomplished with such systems.
Since it appears there is some confusion among recruiters about what exactly HR analytics entails, it’s logical there may also be confusion on how HR analytics software should be implemented.
Based on insight from our experts shared, here are a few steps companies should follow when getting started:
Track and record your data. For analytics to work, there first must be data to analyze. Most companies collect data through their HRIS, which tracks basic employee data collected during the onboarding process, such as hire date, department, job title etc.
But as Gaspar notes, “The more information that’s made available, the better.” Businesses may wish to create company-wide surveys asking employees about their professional ambitions and interests, and record that data in their HRIS as well.
Aggregate your data. The next step is integrating an HR analytics solution with your company’s other current software. Most HR analytics solutions will “bring together data from disparate systems: your HRIS, applicant tracking system, performance management, payroll and many other [systems],” Weisbeck says. By aggregating data from these solutions, he explains, you can identify valuable information, such as what hiring sources generally produce the best performers.
Decide which metrics matter most. Once a company has its HR analytics software up and running, the HR department may be overwhelmed by reporting options. This is because most software systems have a myriad of reports to choose from, which take time to learn and interpret. As such, Gaspar notes that it is important for companies to ease into using their system.
For companies that are just starting out, he recommends running a few basic reports as a first step—for instance, determining the average time to hire or employee turnover rates. Starting with the basics can help users become more comfortable with the abilities of their analytics software.
Use data to make more informed business decisions. Once comfortable with basic reporting, Gaspar says, companies can start using this data to make business decisions. For example, data on how many employees were hired and left in a given quarter, along with revenue and budget information, can be used to determine how many new employees to hire in the next quarter and how much to pay them.
In order to find the answers to these questions, an HR professional may need to synthesize data from basic reports that they’ve already run.
Let’s consider the following example scenario: A recruiter has three seemingly strong candidates in the pipeline for a single managerial position. Here’s how they might use HR analytics software to narrow down the competition:
Step 1: The recruiter analyzes the data available. Most analytics systems allow users to create reports evaluating employee performance. Using performance review information on current managers, the recruiter determines which traits and skill sets (e.g., strong communication skills and a background in Google Analytics) the most successful managers possess.
Step 2: The recruiter then checks for those characteristics in candidates and eliminates the ones who perform the weakest when their prior experience is compared against these criteria.
Step 3: Using compensation data from other managers at the company—their years of experience, level of education, skill set etc.—the recruiter determines a competitive salary for the open position.
Step 4: Comparing this salary figure to the candidates’ salary requirements, the recruiter sees that one candidate is out of the company’s price range, and eliminates them from the running. As a result, a single candidate is left who is the best fit for the role.
Visier’s solution tracks average compensation by position
Using the analytics reports that are often included even in basic HR software products—such as performance tracking and compensation trends reports—recruiters and HR professionals can make better, more informed hiring decisions.
In the end, the decision to invest in an HR analytics solution will depend on each company’s unique situation. But in order to make that decision, companies should first have all the facts.
As we’ve seen, the first step in successfully using HR analytics software is having a data collection process in place. Whether in spreadsheets or your HRIS system, this data is necessary to effectively use analytics.
After an HR analytics software solution is purchased, it then needs to be integrated with any current systems in place used to track employee data. Next, those businesses just starting out with analytics should go slow and initially use only basic reports to get a better feel for how everything works and get up to speed.
Once they gain confidence in the use of their reporting tools, companies can then begin to use their analytics software to make better business decisions—which, as our data shows, can have a very positive impact on key HR KPIs.
To collect the data in this report, we conducted a seven-day online survey of 12 questions, and gathered 105 responses from a random sample of recruiters at businesses within North America. We screened our sample to only include respondents who used some form of HR analytics—whether software, manual methods or a combination of the two. Software Advice performed and funded this research independently.
Results are representative of our survey sample, not necessarily the population as a whole. Sources attributed and products referenced in this article may or may not represent client vendors of Software Advice, but vendor status is never used as a basis for selection. Expert commentary solely represents the views of the individual. Chart values are rounded to the nearest whole number.
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