Your complete guide to understanding HR analytics

What if you could predict which employees might leave next quarter, identify the factors dragging down team morale, or uncover the training programs that truly boost productivity?

HR analytics makes all of this possible. By turning raw employee data into actionable insights, HR analytics empowers organizations to address underlying workforce issues head-on and develop effective strategies for improvement.

In this guide, we’re diving deep into the world of HR analytics, exploring its fundamentals, importance, key HR metrics to track, and how it can transform your approach to human resource management. Get ready to unlock the potential hidden within your HR data and drive your organization forward.

What is HR Analytics?

HR analytics, also known as human resource analytics or people analytics, is the practice of collecting, analyzing, and interpreting employee data to improve organizational performance. It involves using statistical methods and data modeling to understand patterns and trends within the workforce, enabling HR professionals to make informed decisions based on empirical evidence rather than intuition.

By transforming raw HR data—such as recruitment metrics, performance evaluations, attendance records, and employee engagement scores—into actionable insights, HR analytics helps organizations address underlying workforce issues. This data-driven approach allows companies to optimize their HR functions, from hiring and training to retention and employee development.

What is HR analytics used for? 

HR analytics can be an invaluable tool for organizations aiming to optimize their human resource functions. By leveraging data-driven insights, companies can enhance decision-making across various HR domains. Here are some of the main use cases of HR metrics and analytics:

• Recruitment: Streamlines the hiring process by identifying the most effective recruitment channels, predicting candidate success, and reducing time-to-fill positions. Workforce analytics can assess the quality of hires and optimize talent acquisition strategies to keep your organization’s recruitment pipeline full.
• Employee engagement: Analyzes employee feedback, surveys, and engagement metrics to uncover factors influencing job satisfaction and commitment. This helps organizations implement initiatives that boost morale, enhance workplace culture, and reduce turnover rates.
• Workforce planning: Assists in forecasting future workforce needs based on business goals and market trends. Workforce analytics can identify skill gaps, plan for succession, and ensure the organization has the right talent to meet strategic objectives.
• Performance management: Evaluates employee performance data to identify high performers and those needing support. This facilitates objective appraisals, informs promotion and compensation decisions, and aids in designing effective training programs.
• Employee retention: Pinpoints reasons behind employee attrition by analyzing exit interviews, turnover rates, and satisfaction scores. Predictive analytics can identify employees at risk of leaving, allowing for proactive retention strategies.
• Training and development: Measures the impact of training programs on employee performance and career progression. HR analytics helps tailor learning initiatives to address specific skill gaps and improve overall productivity.
• Compliance and risk management: Tracks compliance-related data to ensure adherence to labor laws and regulations. HR analytics helps identify potential legal risks and implement measures to mitigate them.

The importance of HR analytics 

HR analytics transforms employee data into critical insights that enhance key HR functions like recruitment, performance management, and workforce planning. By analyzing this data, organizations can make informed decisions that improve hiring processes, objectively evaluate employee performance, and anticipate future staffing needs. HR analytics drives data-driven decision-making, ensuring that your overall HR strategies align with business goals and contribute to your ongoing organizational success.

Key HR analytics metrics to track 

Tracking the right HR metrics will help your human resources org gain valuable insights into your workforce and make informed decisions. Below are five types of HR metrics to monitor, along with specific metrics to track to help keep your finger on the pulse of each category.

1. Onboarding metrics

Effective onboarding is critical for integrating new employees and setting them up for success. Tracking onboarding metrics helps assess the efficiency of your onboarding process and its impact on new hires.

HR metrics to watch:

• Time to productivity: Measure the time it takes for a new employee to reach full productivity by comparing their start date to the date they meet predefined performance benchmarks.
• Onboarding satisfaction rate: Use surveys to gather feedback from new hires about their onboarding experience. Calculate the percentage of positive responses to gauge overall satisfaction.
• New hire retention rate: Divide the number of new employees who remain with the company after a certain period (e.g., six months) by the total number of new hires during that period, then multiply by 100 to get a percentage.

2. Employee engagement 

Employee engagement reflects how committed and motivated employees are toward their work and the organization. High engagement levels often lead to increased productivity and a reduced turnover rate.

HR metrics to watch:

• Engagement survey scores: Conduct regular employee engagement surveys and calculate the average scores across various dimensions like job satisfaction, alignment with company values, and willingness to recommend the company to others.
• Absenteeism: Calculate by dividing the total number of days missed by all employees by the total number of available workdays, then multiply by 100. Higher absenteeism may indicate lower engagement.

3. Growth and development 

Monitoring growth and development metrics can help evaluate the effectiveness of your training programs and the opportunities for career advancement within your organization.

HR metrics to watch:

• Training completion rate: Divide the number of employees who have completed a training program by the total number of employees assigned to it, then multiply by 100 to get a percentage.
• Internal promotion rate: Calculate by dividing the number of positions filled internally by the total number of open positions within a period, then multiply by 100.

4. Turnover trends

Understanding turnover trends can help your organization understand underlying issues that may be causing employees to leave, which allows you to develop strategies to improve retention.

HR metrics to watch:

• Overall turnover rate: Divide the number of employees who left during a specific period by the average number of employees during that period, then multiply by 100.
• Retention rate: Calculate by subtracting the turnover rate from 100%. A higher retention rate indicates better employee retention strategies.

5. Top performers

Recognizing and nurturing top performers will help you maintain a competitive edge and foster a culture of excellence within your organization.

HR metrics to watch: 

• Productivity metrics: Analyze key performance indicators (KPIs) relevant to each role, such as sales figures, revenue per employee, project completion rates, or customer satisfaction scores.
• Performance review scores: Use data from regular performance evaluations to identify employees who consistently receive high ratings.
• Promotion rate of high performers: Divide the number of top performers who have been promoted by the total number of top performers, then multiply by 100 to assess advancement opportunities.

6 effective HR analytics examples

Implementing HR analytics can significantly improve employee retention and address challenges like turnover, engagement, and productivity. Here are six actionable examples of how HR data analytics can make a difference in your organization:

Predicting employee turnover using HR analytics

Employee turnover is costly and disruptive. By leveraging people analytics, organizations can predict which employees are at risk of leaving. This involves analyzing data such as tenure, performance scores, engagement levels, compensation, and even external market trends.

Steps you can take:

• Gather historical data on employee departures, including reasons for leaving
• Use statistical models to identify common factors among employees who have left
• Develop a predictive model to assess current employees' likelihood of departure
• Implement targeted retention efforts like personalized career development plans or compensation adjustments for at-risk employees

Improving employee engagement through data insights

High employee engagement leads to increased productivity and lower turnover rates. HR analytics can pinpoint factors that influence engagement levels within your organization.

Steps you can take:

• Collect data from employee engagement surveys and feedback tools
• Analyze the data to find trends related to departments, managers, or job roles
• Implement initiatives to improve areas with low engagement, such as workload balance or recognition programs

Enhancing recruitment success for retention

Attracting and retaining the right talent starts with effective recruitment. People analytics can enhance recruitment and talent acquisition strategies to improve long-term retention.

Steps you can take:

• Analyze which talent acquisition strategies yield candidates who stay longer and perform better
• Identify characteristics of successful employees to refine job descriptions and candidate screening processes
• Streamline the recruitment process to reduce time-to-hire and improve candidate experience
• Correlate recruitment metrics with employee retention analytics to continually improve hiring strategies

Optimizing workforce planning through predictive analytics

Predictive analytics helps organizations anticipate future workforce needs and align them with business goals.

Steps you can take:

• Use historical data and business projections to predict staffing needs
• Identify current and future skill shortages within the organization
• Develop succession plans for critical roles based on performance and potential data
• Allocate resources for hiring or training initiatives to fill anticipated gaps

Increasing employee productivity with performance data

Analyzing performance data helps identify what drives productivity and how to replicate it across the organization.

Steps you can take:

• Determine which performance metrics are most indicative of productivity in each role
• Compare individual and team performance against these metrics
• Identify high-performing employees or teams to understand effective strategies or behaviors
• Implement training or process improvements based on insights gathered

Enhancing employee training and development programs

Effective training programs are key to both employee growth and satisfaction. HR analytics can optimize these programs to better serve your workforce.

Steps you can take:

• Measure employee performance before and after training sessions
• Evaluate which training programs lead to improved performance or promotion rates
• Use data to tailor training opportunities to individual employee needs and career goals
• Redirect investment toward programs with the highest impact on employee development and retention

How HR analytics enhances employee retention

HR analytics plays a crucial role in improving employee retention by turning employee data into actionable insights. By analyzing information from onboarding feedback, performance reviews, engagement surveys, and exit interviews, organizations can identify underlying issues that contribute to employee turnover.

For example, if your company notices an increase in departures within a specific department after a change in management, people analytics can uncover correlations between the new leadership style and employee dissatisfaction. By quantifying HR metrics like employee engagement and job satisfaction, you can predict which top performers might be at risk of leaving—often referred to as "flight risks."

By leveraging data-driven insights, HR professionals can move beyond relying solely on intuition or anecdotal evidence. This enables them to implement targeted strategies to enhance employee satisfaction, address areas of concern, and ultimately improve retention rates. Utilizing HR analytics not only reduces the costs associated with high turnover but also fosters a more engaged and committed workforce.

HR analytics best practices

Implementing HR analytics effectively takes careful planning and strategic execution. Here are some best practices to help you make the most of your HR analytics initiatives:

Choose the right tools for your analytics needs

The first step is to select the right tools to gather, analyze, and interpret HR data.

Start by assessing your organization's specific workforce analytics requirements, such as data visualization, predictive analytics, or real-time reporting capabilities. Make sure the tools you choose can seamlessly integrate with your existing HR systems like HRIS, ATS, or payroll software to facilitate smooth data flow. And opt for solutions with user-friendly interfaces so that HR professionals without extensive technical expertise can utilize them effectively.

Additionally, make sure you consider your tools’ scalability to accommodate increasing amounts of data and more complex workforce analytics as your organization grows. Data security is another essential concern—choose tools that offer robust security features to protect sensitive employee information and comply with data protection regulations.

Align HR analytics with organizational goals

For HR analytics to be truly effective, they need to directly support and enhance your company's strategic objectives.

Start by defining clear goals for your people analytics initiatives, whether it's reducing turnover, improving employee engagement, or enhancing recruitment efficiency. Focus on key performance indicators (KPIs) that align with both HR and organizational objectives.

Collaborate with other departments to understand how HR data can support broader business initiatives, fostering cross-functional synergy. Throughout the process, regularly review how your HR analytics efforts contribute to achieving organizational goals and make adjustments as needed to maintain alignment with other departments and the organization as a whole.

Collect feedback to continuously improve

Gathering feedback will help you refine your HR analytics processes so they remain effective and relevant. Ask for input from employees regarding HR initiatives informed by analytics to gauge their impact and acceptance, and involve managers and executives in reviewing analytics tool findings to foster their buy-in and collaboration. 

Use the feedback you collect to make iterative improvements to your analytics models. That way, they can evolve with the organization's needs. Providing ongoing training for HR staff can also enhance their analytical skills and ability to interpret data insights effectively.

HR analytics challenges

While HR analytics offers significant benefits, organizations often face challenges when implementing and leveraging their strategies and tools effectively. To maximize the value of your HR analytics initiatives, you need to understand the obstacles you may face. Here are some common challenges:

Data fragmentation across platforms

One of the primary hurdles in HR analytics is the fragmentation of data across multiple systems and platforms.

Employee data is often scattered in disparate systems—from payroll to recruitment, performance management, learning management and more. This fragmentation makes it difficult to consolidate data for comprehensive analysis.

Different platforms may also store data in various formats, leading to inconsistencies that complicate data integration and analysis.

With Rippling, your entire workforce management platform is built on a single source of truth for employee data, so it’s easy to access, connect, and visualize any analytics across your entire organization.

Lack of specialized analytical skills

Effective HR analytics requires a combination of HR knowledge and data analysis expertise, which can be lacking in traditional HR teams, who may not have training in data analytics, statistics, or the use of advanced analytical tools, limiting their ability to interpret complex data sets.

Looking for analytics software that’s user-friendly can bridge the skill gap. With Rippling, any user can point and click their way to reports with actionable insights that fuel better business decisions.

Resistance to data-driven culture

Shifting to a data-driven approach can encounter resistance from employees and management accustomed to traditional decision-making methods. Employees may be skeptical about relying on data analytics over personal experience or intuition, fearing that data might replace human judgment. Or, previous experiences with poor data quality can lead to distrust in analytics outputs, hindering adoption.

Fostering a data-driven culture involves clear communication about the benefits of people analytics. Providing training and involving HR leaders and other stakeholders in the implementation process can increase buy-in. Highlighting success stories where data analytics led to positive outcomes can also alleviate resistance.

Compliance and privacy concerns

Handling sensitive employee data raises significant compliance and privacy issues that organizations must navigate carefully.

Laws like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) impose strict guidelines on how personal data should be collected, stored, and used. Implement robust data governance policies that outline how data is handled and protected, and ensure compliance by staying updated with relevant laws and regulations. Invest in cybersecurity measures like encryption, access controls, and regular security audits to safeguard employee data.

How Rippling makes HR reporting simple

We’ve already hinted at the HR analytics solution that can help accelerate business impact for organizations of all sizes.

With Rippling, your data is centralized and easy to find so you always have real-time access to the data you need, helping you make informed business decisions with intuitive tools that transform trusted data into business insights.

Rippling’s data architecture connects any data from across HR, IT, payroll, and Spend without manual exports or messy spreadsheet joins. Rippling is also easy-to-use, with a point-and-click interface that empowers any user to create insightful reports with dynamic visuals, pivot tables, formula fields, and other advanced and intuitive tools.

Rippling’s hundreds of pre-built templates give you a head start to building reports, and you can still customize them to meet your exact needs. Or you can build reports from scratch. And Rippling offers 600+ integrations with your favorite apps so you can analyze, automate, and orchestrate anything.

HR analytics FAQs

What are the 4 types of HR analytics?

The four types of HR analytics are:

• Descriptive analytics: Answers the question, "What has happened?" It involves analyzing historical HR data to identify trends and patterns within the workforce, like employee turnover rates and employee demographics.
• Diagnostic analytics: Explores "Why did it happen?" This type delves deeper into data to uncover the root causes of workforce issues. For example, it might reveal that a spike in turnover is due to job dissatisfaction or lack of career advancement opportunities.
• Predictive analytics: Focuses on "What is likely to happen?" It uses historical data and statistical models to forecast future events, like predicting which employees are at risk of leaving or which candidates are likely to succeed in a role.
• Prescriptive analytics: Addresses "What should we do?" This advanced form of analytics provides recommendations for actions to achieve desired outcomes. For instance, it might suggest specific training programs to enhance employee performance or retention strategies to reduce turnover.

What are the 7 pillars of HR analytics?

The seven pillars of HR analytics provide a comprehensive framework for leveraging data to enhance human resource functions and contribute to organizational success. The pillars are:

1. Organizational culture: This pillar focuses on analyzing and understanding the company's values, beliefs, and behaviors that shape the work environment. HR analytics can measure cultural alignment, employee satisfaction, and the effectiveness of diversity and inclusion initiatives.
2. Talent management: Involves using data to optimize talent acquisition, development, and retention. Analytics helps identify skill gaps, predict future talent needs, and develop strategies for attracting and retaining top performers.
3. Leadership: Examines the impact of leadership on organizational performance. HR analytics assesses leadership effectiveness, succession planning, and the development of leadership competencies within the organization.
4. Workforce planning: Entails forecasting future staffing needs based on business goals and market trends. Analytics in this area aids in strategic decision-making regarding hiring, resource allocation, and succession planning.
5. Learning and development: Focuses on evaluating the effectiveness of training programs and professional development initiatives. HR analytics measures the return on investment (ROI) of learning programs and identifies areas for improvement to enhance employee skills and competencies.
6. Performance management: Involves analyzing employee performance data to improve productivity and achieve organizational objectives. This pillar uses analytics to set performance benchmarks, monitor progress, and provide actionable feedback.
7. Employee engagement: Measures the level of employee commitment, motivation, and satisfaction. HR analytics identifies factors influencing engagement and helps design interventions to boost morale, enhance workplace culture, and reduce employee turnover rates.

What skills are required for HR analytics?

Effective HR professionals need a blend of technical and interpersonal skills, including data analytics, HR knowledge, critical thinking, communication, and business acumen. Good HR analytics software can help close the skills gap when HR teams are missing some of these skills.

How does HRIS differ from HR analytics?

A Human Resource Information System (HRIS) is a digital platform that stores and manages employee data for HR purposes.

HR analytics, on the other hand, involves analyzing the data collected by HRIS and other sources to gain insights that inform HR strategies and decisions. While HRIS focuses on data management (and can be the foundation for process automation), HR analytics is about interpreting the data stored in an HRIS to solve problems, predict trends, and improve HR functions.

This blog is based on information available to Rippling as of September 25, 2024.

Rippling and its affiliates do not provide tax, accounting, or legal advice. This material has been prepared for informational purposes only, and is not intended to provide, and should not be relied on for tax, legal, or accounting advice. You should consult your own tax, legal, and accounting advisors before engaging in any related activities or transactions.