18 HR Data Analytics Examples (2025)

Human resources management is all about people, but that can make things tricky. It isn’t uncommon for managers and HR professionals to fall victim to the halo and horn effect. HR and managers can easily come to incorrect conclusions, like assuming low engagement is the reason for poor performance when in fact a lack of targeted training is the problem.

HR data analytics is the best way to uncover what’s really going on. You can gather accurate, unbiased information with measurable data so you can make informed decisions that not only support business operations, but they also support your employees.

As a data-driven performance management platform, we know how powerful the right information can be when implementing strategies for increased performance and engagement.

Here’s everything you need to know about HR data analytics, along with real-world HR data analytics examples that you can use to drive better performance, increase employee engagement, and achieve company-wide goals.

The Four Types of HR Data Analytics 

Numbers are at the heart of the HR data analytics examples you’ll see below, but those numbers can uncover very different things about your business and how its employees work. It’s important to understand the four different types of HR data analytics so you can figure out which one is best according to what you want to measure.

They include:

• Descriptive
• Diagnostic
• Predictive
• Prescriptive

Descriptive

Descriptive analytics is an HR data analytics example that focuses on what happened. It allows you to uncover historical data to better understand what happened in the past.

For example, you might collect historical data on how many employees left the company within a certain time period. This type of data can also be an effective way to measure attendance and employee engagement trends over time.

Diagnostic

Diagnostic analytics is an HR data analytics example that focuses on why something happened. It gets to the root of behaviors, which is where real change can take place. You can understand the cause of a specific outcome or the reason for trends in the workplace. Data points can be especially effective when trying to determine the reasons why employees leave the company or some employees aren’t engaged.

What is the difference between descriptive analytics and diagnostic analytics?

Descriptive analytics allows you to measure what happened in the past. Diagnostic analytics illuminates the reason behind the descriptive data point that was uncovered. For example, descriptive analytics will tell you how many employees left the company within a certain time period. Diagnostic analytics can help you identify the factors that contributed to a high turnover rate.

Predictive

Predictive analytics is an HR data analytics example that analyzes current and historical data to predict future outcomes. It utilizes innovative technologies like machine learning to create predictive models that highlight correlations in past data in order to predict what might happen next.

It’s an effective way to predict employee turnover, talent needs, and other workforce trends. For example, predictive analytics can help you identify which employees are most at risk of leaving the company within a certain time period based on specific factors like job satisfaction and engagement level.

Prescriptive

Prescriptive analytics is an HR data analytics example that identifies the best actions to take in order to improve future outcomes. It goes beyond current and historical data and crunches the numbers to analyze potential outcomes and scenarios for the future. It gives HR departments the power to design OD interventions by uncovering actual things you can do to increase employee satisfaction, reduce turnover, and enhance performance.

For example, prescriptive analytics can determine whether you should offer a promotion, a pay raise, or a professional development opportunity if you have identified an employee who is at a high risk of leaving the company.

What is the difference between predictive analytics and prescriptive analytics?

Predictive analytics uses current and historical data to predict what is likely to happen in the future. Prescriptive analytics identifies the best actions to take in order to achieve the best outcome. For example, predictive analytics can help predict which employees are at the highest risk of leaving the company. Prescriptive analytics can help you determine whether a pay raise or professional development would be a better strategy for retaining an employee according to their unique risk factors.

18 HR Data Analytics Examples 

Seeing actual HR data analytics examples can help you see exactly how they fit into a broader workforce analytics strategy. Each of the 18 examples below is broken down according to each of the four data types so you can zero in on which one to use and when.

Descriptive analytics examples

The first step in gathering data points is to focus on historical data with descriptive analytics. The HR data analytics examples in this category include:

1. Employee turnover data
2. Diversity metric
3. Recruitment metrics
4. Employee engagement results
5. Performance review scores

1. Employee turnover data

Employee turnover data includes the total number of employees who left the organization within a specific category. Categorizing them by department, role, and tenure can illuminate your findings. If you want to dive deeper, exit interviews can illuminate the reasons why employees choose to leave your company.

2. Diversity metric

Some statistics point out that racial and ethnically diverse companies regularly outperform less inclusive companies, so you can see why it’s important to investigate why certain demographics might be underrepresented in your workplace. You can analyze hiring patterns, promotion rates, and internal mobility trends.

3. Recruitment metrics

Recruitment metrics can help you uncover the effectiveness of your recruitment methods. Some examples include the time-to-fill for open positions and cost-per-hire. Counting the number of applications received is important, but you can glean even more from this data point if you divide applications based on department, experience, and other factors.

4. Employee engagement results

Aggregating employee data in a survey that measures engagement scores using a behaviorally anchored rating scale can illuminate overall engagement levels. Create unique scores for different teams and departments, and you can identify more accurate trends in employee satisfaction.

5. Performance review scores

Analyzing average performance review scores over time can help you learn more about an employee’s performance level over time. You can also measure the average performance review scores of teams and departments. Information can be used to identify high performers as well as those who may need additional support.

Diagnostic analytics examples

Diagnostic HR data analytics examples can illuminate the descriptive analytics you uncovered and show you how best to make improvements. They include:

6. Recruitment effectiveness
7. Diversity gaps
8. Declining employee engagement
9. Performance issues

6. Recruitment effectiveness

HR leaders and managers can analyze why certain job postings fail to attract qualified candidates by evaluating job descriptions, sourcing channels, and measuring application conversion rates.

7. Diversity gaps

With eye-opening HR statistics like the fact that racial and ethnically diverse companies regularly outperform less inclusive companies, you can see why it’s important to investigate why certain demographics might be underrepresented in your workplace. You can analyze hiring patterns, promotion rates, and internal mobility trends.

8. Declining employee engagement

If you notice that employee engagement levels have dropped, you can correlate survey feedback with recent organizational changes like restructuring, policy changes, and workload increases. An employee engagement survey can also uncover additional concerns, like the lack of autonomy or a lack of professional development opportunities.

9. Performance issues

In this HR data analytics example, you can examine why certain individuals or teams consistently underperform. You can analyze factors like workload, training availability, job fit, and leadership effectiveness.

Predictive analytics examples

You can correlate past data and forecast future outcomes with predictive analytics examples that include:

10. Turnover prediction
11. Recruitment success forecasting
12. Future workforce needs
13. Engagement and productivity trends
14. Performance outcomes

10. Turnover prediction

Replacing an employee can cost as much as two times their annual salary, which makes predicting turnover a valuable metric to measure. With engagement scores, tenure, performance trends, and compensation benchmarks, you can predict which employees are at the highest risk of leaving.

11. Recruitment success forecasting

Because talent acquisition can be so expensive, it’s important to make sure your recruitment process is as successful as possible. You can predict the likelihood of a candidate accepting a job offer based on historical data, such as time taken to extend offers, industry averages, and candidate feedback to optimize recruitment.

12. Future workforce needs

You can anticipate future hiring needs by analyzing trends in organizational growth, project demand, and employee attrition rates. You can hire someone for a brand-new position or hire extra hands to avoid the stress of being understaffed.

13. Engagement and productivity trends

Instead of waiting until there’s a drop in engagement and productivity before taking action, you can forecast employee engagement levels over the next quarter based on historical survey data, recent management changes, and workload trends.

14. Performance outcomes

Predicting the future performance of employees can help you provide proactive support instead of offering reactionary support after performance has already dropped. You can do this with skills assessments, past review data, and training program participation.

Prescriptive analytics examples

Prescriptive analytics can help you take the right action when you've uncovered a predictive data point you would like to improve. Some prescriptive HR data analytics examples include:

15. Turnover reduction strategies
16. Optimizing recruitment channels
17. Engagement improvement plans
18. Training and development recommendations

15. Turnover reduction strategies

If you predict turnover could be an issue in the near future, you can develop data-driven turnover reduction strategies. They can include increased training, salary adjustments, and mentorship programs according to the specific predictive analytics you uncovered.

16. Optimizing recruitment channels

Based on the potential recruitment needs you have uncovered, you can optimize your recruitment channels. You can discover the most effective sourcing platforms or job boards based on past data and the predicted success of different channels for specific roles.

17. Engagement improvement plans

Engagement improvement plans can provide you with actionable recommendations to boost engagement based on predictive trends that show declining satisfaction on certain teams or roles. This data can also be incorporated into SMART HR goals that help provide employees with actionable steps to increase their engagement levels.

18. Training and development recommendations

Prescriptive analytics can provide you with precise training and development recommendations that enable employees to enhance certain skills. Recommended targeted training programs can focus on improving future performance or prepare employees for an internal promotion.

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Real-World Data Analytics Examples

Here are three real-life HR data analytics examples. The organizations used HR analytics to transition from general processes and metrics to quantifiable, data-driven goals and insights.

Dominion Due Diligence Group

Dominion Due Diligence Group (D3G) is a full-service environmental, engineering, and energy due diligence firm. The firm’s HR department wanted to shift from general performance management metrics and processes to specific, practical measures.

D3G transitioned from using paper-based performance processes and evaluations to digitizing them with HR data analytics tools like PerformYard. From there, they drill down into the elements that determine job success.

D3G was able to set specific, quantifiable objectives like a professional goal, an operational goal, and a personal goal. Managers could track them, and employees could use them for development. They can now tie performance to measurable metrics.

Cline Family Centers

Cline Family Cellars is a family-owned winery business. The business owns multiple vineyards, tasting rooms, and olive oil subsidiaries.

Cline Cellars went through a restructuring to better enable long-term growth. Previously, the team conducted employee performance reviews on an ad-hoc basis, and employees weren’t clear about how higher-ups evaluated them.

Thanks to a new HR director and partnership with PerformYard, Cline Cellars created a standardized performance management process that tied employee goals to organizational objectives.

VCC Construction

VCC Construction is a general contracting/construction management firm licensed in 50 states. The firm wanted more robust performance management processes than the simplistic annual review process they already had.

With PerformYard, they evolved their processes to an annual review and a mid-year check-in. The yearly review gives a 360 review, a manager review, and a self-review. The reviews could now include factors like technical skills, interpersonal skills, and areas for improvement (among others).

Managers can use the data to track employee goal progress and see who has potential for advancement. Beyond individual goals, the team has visibility and insight into how well the company accomplishes organizational goals.

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HR Data Analytics Tools That Help You Maximize Your Team’s Potential 

Digging into the data is nearly impossible if you're trying to do it manually and you’re keeping track of the numbers in an Excel file. You can get so much more from your HR data analytics when you use the right software tools.

Here are a few of our favorite HR data analytics software examples.

PerformYard 

PerformYard is a completely customizable performance management platform that offers a wide range of features that can make using the HR data analytics examples in this article a lot easier.

Here are the basics to know about PerformYard.

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Primary functionality

PerformYard offers a complete performance management toolkit. It includes performance reviews that can be personalized for different time frames, teams, and individuals. It has goal-tracking capabilities baked right into the platform with feedback management tools that support employee recognition, manager input, and feedback requests in real time.

The platform also includes dedicated employee engagement features. You can design your own engagement survey, view results in your engagement trends dashboard, and dive deep with dynamic employee cohorting to uncover insights that might otherwise be overlooked.

Integration capabilities

Data is most powerful when it’s integrated across all areas of your business. PerformYard integrates with some of the most popular platforms so you can keep employee data up to date without manually updating information from your HRIS platform. It also integrates with SSO platforms to streamline the sign-on process, as well as collaboration platforms so communications regarding performance are quick and easy to find.

Insights and reporting

Robust reporting and analytics capabilities are included on the platform so you can track performance, identify trends, and generate reports to make data-driven decisions in your organization. Reports are customized according to your unique data with highly visual displays that make it easy to understand exactly what the numbers mean.

Want to learn more? Check out PerformYard’s HR performance management software and get a free demo today!

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Python

Python isn’t technically a software platform. Instead, it’s a popular programming language that can make crunching numbers fast and easy.

Here’s a brief overview of how you can integrate Python into your HR processes.

Primary functionality

Because Python isn’t an actual platform, it can be a bit tricky to get started. But once you learn the ropes, you can use Python’s programming language to superpower your data analytics.

It enables you to use large datasets to automate reporting, which increases accuracy while saving you time. It uses machine learning and can help you generate interactive reports to spot trends. Python makes it easy to process data and create predictive models, regardless of the exact software you use.

Integration capabilities

Python has been an open-source, cross-platform for over 20 years. It works on all operating systems and easily integrates with other programming languages. It runs within existing application programming interfaces (APIs) and HRIS systems.

It also supports a vast library of over 85,000 scripts and modules within the Python environment, regardless of where it's being used. There isn't anything Python can't do and anywhere it can't run once you've learned how to use it.

Insights and reporting

If you don't want to be limited to the reports offered within existing software platforms, integrating Python into your data analytics strategy can be hugely helpful.

It gives you the ability to create your own reports and predictive models with scripting abilities that can be used to automate specific tasks over and over again. Its flexibility enables you to analyze an unending range of employee data that includes predicting employee turnover, identifying high performers, learning what factors impact job performance, and much more.

ADP Workforce Now

ADP is a popular HR and payroll platform that aims to integrate a wide array of HR systems. That can be handy if you want a single platform that does it all.

Here’s what you need to know about ADP Workforce Now.

Primary functionality

ADP Workforce Now is an all-in-one software platform for HR with functionalities that support:

• Payroll
• Time and attendance
• Benefits administration
• Talent acquisition
• Talent management
• Reporting and analytics

You can add dedicated performance management capabilities to your plan that will help you dig deeper into your analytics. That’s especially true in regards to performance, as the platform focuses on supporting continuous improvement as a way to align employee goals to the strategic objectives of the organization.

Integration capabilities

ADP integrates with a wide variety of platforms so it truly can become an all-in-one platform that contains all the data sources and information HR needs to function efficiently. Integrations include accounting software like QuickBooks, time-tracking platforms like ClockShark, compliance platforms like G-P, and benefits software like Wex.

Insights and reporting

Because ADP contains so much information across a spectrum of HR tasks, it can be an especially powerful option when it comes to getting the most out of the HR data analytics examples in this article. You can pull data from any area and compare it to data from others to create dashboards, custom reports, and insights that provide you with a complete picture of your HR processes, workforce planning, and more.

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Complete and Accurate Data is the Best Way to Get the Most Out of Your Analytics

The HR data analytics examples in this article have the potential to elevate employee engagement and supercharge their performance. Knowing the different types of data analytics and ways to crunch the numbers is important, but the quality of the data you use is even more important. You have to use complete and accurate data in order to get actionable insights that address the unique nature of your business and its workforce.

It doesn't matter if you want to illuminate HR's role in performance management within your company, figure out what to do about a rising turnover rate, or encourage more engagement among your workforce; PerformYard can make sure you have the data analytics capabilities you need to implement strategies that support your employees and the overall growth of your business.

Learn more about PerformYard and see our demo to see our HR data analytics examples in action.

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