HR analytics has become a hot topic in many companies. And it’s only growing more popular by the day. But despite all the hype, few HR departments know how to “do” analytics well.
Good analysis are central to talent management. Tomorrow’s HR will find analytics even more indispensable. So, let’s discuss exactly what it means and how to get started.
Table of Contents
2. HR Analytics Stats and Facts
3. How HR Analytics Help Businesses
6. Getting Started with HR Analytics
What Are HR Analytics
HR analytics are “data-driven insights to inform talent decisions, improve workforce processes and promote positive employee experiences,” writes Gartner. They inform decisions on every aspect of talent management, leveraging big data to draw conclusions.
Are analytics different from metrics? Yes. Metrics measure easily identifiable benchmarks. For example, they show whether you’ve made your sales quota. But the former take a deeper dive into more complex data. By exploring relationships between variables, they unearth insights that aren’t visible at first glance.
But analytics leverage metrics. Some of the variables they deal with are metrics that HR measures. They can compute the complex relationships between them. In doing so, they distil complicated information into easy-to-understand insights.
HR Analytics Stats and Facts
Let’s review some telling facts about the need for increased use of analytics. Then, we’ll look at emerging areas in the field.
The State of Analytics at a Glance
Only 1 in 4 organizations feel their HR has good data literacy. And just 9% say they understand which aspects of talent drive performance. Yet more than 70% identify people analytics as a top priority.
But how to prioritize this type of HR analysis remains a challenge. “Most companies still face critical obstacles in the early stages of building their people analytics capabilities, preventing real progress,” says McKinsey.
Emerging HR Analytics Specialties
New HR analytics roles are emerging to fill this gap, Deloitte asserts. For example, algorithm management roles can understand and translate how programs actually work. They can also design and select the best people data and algorithms. Meanwhile, data scientists can take charge of understanding and disseminating insights.
In larger organizations, data scientists may have specialized backgrounds. Some may focus on natural-language processing or quantitative psychometrics, notes McKinsey. Others may be data generalists. Bigger orgs may also hire data “translators” to help leaders and technical experts communicate.
Further, the field of relational analytics is emerging, says HBR. This involves studying how people interact, where silos exist, and which interactions are most fruitful. Relationships as well as individual attributes affect performance, this discipline holds. Relational analysis can also study who actually holds the most influence—which can be surprising.
How HR Analytics Help Businesses
HR analytics can help businesses stay competitive through strong talent management. Today’s HR teams can benefit from in many ways.
For example, data on your people can make sense of issues like these:
- Why a high percentage of employees quit at a particular time in their careers.
- Why fewer strong candidates are applying.
- How they can make better use of their talent.
- Why the company struggles with diversity—and how to improve.
- Which employees are most likely to succeed as leaders.
- How employees are interacting and collaborating, and how this could improve.
“Talent is the largest, most significant, ongoing investment made by successful organizations,” writes SHRM. “However, most people decisions are made based on intuition and instinct. With the amount of information available in today’s workplaces, HR professionals are now able to leverage people-related data and analytics to drive business decisions and make data-based recommendations.”
Importantly, this kind of analysis entails passive collection of data. This can be very cost-effective, as HBR notes. Rather than conducting long interviews or questionnaires, you’re automatically generating insights. And these insights have a high level of accuracy since they’re based on observations.
Investing in HR Analytics
HR analytics are a wise investment for any company. But are there any drawbacks?
Some people caution against relying too heavily on data analysis for hiring or advancement decisions. That’s especially important if you don’t know exactly how the software’s algorithm works. You don’t want to rely heavily on a program you don’t understand to make choices affecting people’s careers.
“Implementing predictive analytics in the context of employee selection, development, or engagement decisions requires a substantially scaled-up data-science operation, massive amounts of highly accurate data (“very big data”), cutting-edge algorithmic technology, and organizational comfort with how to address the impact on fairness and bias,” writes McKinsey. Using cloud-based services is essential at this level of complexity, they add.
However, the technical skills of many HR staff are advancing as well. So, you could hire—or upskill—staff who understand how such programs work. This will safeguard your decision-making processes while giving you access to quality insights.
Keep in mind that analytics shouldn’t replace human assessment completely. Rather, they can complement it.
Further, they’re invaluable for daily performance management. They’ll help you support employees’ growth and improve productivity.
How to Use HR Analytics
Using analytics is a multi-step process. According to Northeastern University, it looks like this:
- Benchmark current performance. For any issue you’re seeking to address, first define the current state of affairs.
- Make observations and draw conclusions, determining potential solutions.
- Enact a change intended to address the problem. You might do so at a small scale first to test the concept.
- Monitor results to understand whether the change is working. Roll it out at scale or adapt your solution as needed.
Types of HR Analytics
SHRM has identified four levels of HR analytics:
- Operational reporting. This uses data to understand past events.
- Advanced reporting. This is basically the same concept as operational reporting but is used continuously.
- Strategic. This involves a more in-depth analysis of the relationships between different variables.
- Predictive. This uses data to predict and plan for what may happen in the future. It involves synthesizing a high volume of data. It can also make use of machine learning.
When we speak of analytics, we’re primarily referring to the more advanced types. In particular, predictive analysis has the power to shape HR decisions in profound ways. Today’s software doesn’t just allow you to understand the past—it helps you predict the future.
Examples of Strong HR Analytics
Here is an assortment of ways in which analytics can be used. This is by no means an exhaustive list.
Improving Recruitment
HR analytics can improve recruitment. For instance, HR can learn which strategies attract the most qualified candidates. They can also determine which demographics they reach through particular platforms. Or, they can learn which channels draw candidates who are likely to stay for years.
By assessing a range of factors, they can help enhance their recruitment plan.
Analytics might also be used to predict which candidates have the best chance of success. HR shouldn’t rely solely on data to make hires, of course. But when data predictions and human assessments align, a company can feel more confident in its decisions, SHRM notes.
Reducing Bias in Hiring
Analytics can reduce bias in the hiring process. For example, an app called Blendoor can determine the most qualified job candidates through a blind review of data. According to Knowledge@Wharton, this can help solve a critical problem companies are facing: How to improve diversity despite their unconscious bias.
Pinpointing Performance Issues
HR analytics can illustrate why an employee is experiencing poor (or strong) performance. For example, is a bad relationship with a past manager still affecting the employee today? By tracking patterns, data can reveal causes that might have gone unnoticed otherwise.
Studying Productivity Influences
Organizations can track time worked and tasks completed to study productivity and teamwork. “For example, time-sheet data could be transformed and loaded into a graph database and linked by activity or project codes to allow better analysis of teamwork and collaboration,” says McKinsey.
Examining Collaboration Patterns
Companies can study collaboration patterns to identify strengths and gaps. “Fortunately, the raw material for relational analytics already exists in companies,” says HBR. “It’s the data created by e-mail exchanges, chats, and file transfers—the digital exhaust of a company. By mining it, firms can build good relational analytics models.”
Tracking ROI
HR analytics can determine the ROI of performance management programs. They can shine a light on what is working and what isn’t.
Understanding Patterns of Influence
Using relational analytics, HR can determine who holds the greatest influence. Leaders can then get these individuals on board with new ideas, as HBR says. The organization can implement changes more effectively using this strategy.
Detecting and Addressing Bias
Data analysis in HR can shine a light on bias within managers’ assessments. Data can show whether they’re fairly evaluating each employee’s performance. Then, HR can work with the managers to help them overcome any bias.
As you can see, analytics can enhance everything from hiring to performance management. Now, let’s explore how to begin.
Getting Started with HR Analytics
What features does a good HR analytics solution have? Ideally, you’ll use a comprehensive software that includes the following:
- HR analytics dashboard. This dashboard places insights at managers’ fingertips. By doing so, it empowers them to act on data in real-time. They can easily view insights on various topics that apply to them.
- Performance management software. This provides a wealth of data for analysis. Data can automatically be drawn from this software and used for analysis.
- The ability to glean additional data from surveys. Finding out how employees feel about various issues will enrich your insights.
Primalogik’s reporting and analytics module provides all of these features. Leaders can use the analytics dashboard to make talent management decisions. Through this user-friendly software, they can easily visualize data on numerous topics.
Ready to upgrade your knowledge of analytics—or that of your HR staff? Take a course or certification program to upskill. Here are some valuable HR analytics resources to choose from:
- HR Analytics: Cornell Certificate Program
- SHRM People Analytics Specialty Credential
- Rutgers’ Certificate in Human Resources Analytics
- Harvard’s People Analytics: Maximizing Human Capital with Data
- Wharton’s HR Management and Analytics
When choosing a course, consider your learning style. Do you work best in a group setting? Or do you prefer a self-paced program? A variety of formats exist today to meet everyone’s needs.
Advanced learning in data analytics will prepare you for the next level. You’ll have a wealth of data at your fingertips and know how to use it! As a result, you’ll make stronger talent management decisions.
Ready to explore how HR analytics can enhance your success? Request a demo of our software today!
