Disha Gupta
What is HR Analytics? (+34 Examples)
- Published: July 1, 2022
- Updated: January 4, 2024
Human resources is a people-oriented function. But the HR contribution isn’t just limited to extending offer letters and onboarding new hires. HR professionals are responsible for developing and sustaining a people and workforce management strategy.
In today’s data-driven world, HR leaders are increasingly turning to HR analytics to make informed decisions and drive strategic initiatives. When used strategically, workforce analytics transforms the way HR operates, providing them insights and allowing them to contribute to the organization’s bottom line in an active and meaningful way.
This article explores the significance of HR analytics, its key benefits, and how organizations can leverage it to unlock the potential of their workforce.
What Is HR Analytics?
HR analytics, also known as people analytics, refers to the practice of using data, statistical analysis, and data-driven insights to inform and optimize HR strategies, policies, and decision-making.
HR analytics involves collecting, analyzing, and interpreting data related to various HR functions, including recruitment, talent management, employee engagement, performance management, learning and development, onboardinging, training, and workforce planning. Organizations leverage HR analytics to gain deeper insights into their workforce, identify people-related trends, make data-driven decisions to improve employee productivity, and align HR initiatives with organizational goals.
Types of HR Analytics
There are four main types of HR analytics; descriptive, diagnostic, predictive, and prescriptive. Let’s explain each category of HR analytics further
1. Descriptive analytics
Descriptive analytics involves analyzing historical HR data to understand past trends and patterns. It provides a retrospective view of workforce metrics, such as headcount, turnover rates, diversity ratios, and employee demographics. Descriptive analytics helps organizations identify areas of improvement and establish benchmarks for future analysis.
2. Diagnostic analytics
Diagnostic analytics goes beyond descriptive analytics to uncover the reasons behind trends or issues within the workforce. Diagnostic analytics aims to answer “why” questions by exploring relationships between different HR metrics and identifying the drivers or predictors of specific outcomes. By conducting diagnostic analytics, HR professionals can gain deeper insights into the factors influencing employee engagement, turnover, performance, or other HR-related phenomena. This understanding allows organizations to address root causes, develop targeted interventions, and make informed decisions to improve HR practices and outcomes.
3. Predictive analytics
Predictive analytics uses statistical models and algorithms to forecast future outcomes and trends based on historical data. It involves analyzing factors that impact workforce behavior and performance to predict attrition risks, identify high-potential employees, and anticipate talent needs. Predictive analytics helps organizations proactively address challenges and make informed decisions.
4. Prescriptive analytics
Prescriptive analytics takes predictive analytics a step further by recommending specific actions or interventions to optimize outcomes. It uses advanced algorithms and modeling techniques to simulate different scenarios and predict the impact of different HR strategies. Prescriptive analytics assists in making evidence-based decisions by providing insights into the most effective courses of action.
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4 HR Areas to Improve With HR Analytics
Here are some examples of how to incorporate HR analytics in your organization.
1. Employee turnover
An employee leaving to join another organization they feel is a better fit for them is not an ideal scenario for an employer – and turns out to be costly in terms of lost time and profit too. To prevent turnover from becoming an ongoing problem, organizations need to understand the overarching reason or trends for the turnover.
HR analytics provides relevant data and information collected from employee engagement levels, employee satisfaction index, exit interviews, etc., for HR leaders to study turnover rates and make better decisions to improve employee retention in the future.
HR analytics help prevent employee turnover by:
- Collecting and analyzing historical employee churn data to identify trends and patterns that indicate why employees leave.
- Collecting data and identifying patterns of employee productivity and engagement to understand the job satisfaction rates of current employees.
- Creating a predictive model to track employees who may fall into the category of employees that might quit.
- Developing retention strategies and making decisions to improve employees’ work environment and engagement levels.
2. Employee recruitment
HR teams are constantly looking for candidates with the right skills and attributes that match the organization’s performance requirements and latest industry trends. However, sifting through stacks of resumes daily, shortlisting, and making recruitment decisions on fundamental information is an overwhelming job that might result in overlooking potential candidates.
Talent acquisition is a key area in which HR analytics can provide valuable insights, helping to streamline the recruitment process, improve the quality of hires, and reduce hiring costs.
HR analytics helps optimize the recruitment and selection process by analyzing data related to sourcing channels, candidate profiles, and hiring outcomes. It identifies the most effective recruitment strategies, improves candidate screening, and enhances the quality of hires, resulting in better talent acquisition outcomes.
HR analytics help streamline the employee recruitment process by:
- Enabling fast, automated collection of candidate data from multiple sources including public search records for background checks and other critical information.
- Helping recruiters write better job postings to attract the right people using HR tech and skills data.
- Helping recruiters narrow down the list of universities to visit or partner with to save time and resources.
- Providing historical data on the periods of over-hiring and under-hiring, enabling organizations to develop efficient long-term hiring plans.
- Determining where the recruiters need to post job openings.
- Identifying candidates with attributes comparable to the current top-performing employees in the organization.
- Comparing hiring costs among regions versus a benchmark.
3. Workforce planning
As HR professionals confront new challenges in finding and retaining the right employees, workforce planning has become a key focus point. Strategic workforce planning starts with gaining insights on organization imperatives and talent implications for the company, followed by a measurement of talent gap risks, talent demand, and talent supply.
HR analytics helps with workforce planning by:
- Performing a skills gap analysis to understand individual employee’s skill set and creating training programs for upskilling and reskilling.
- Analyzing, forecasting, and planning workforce supply and demand.
- Providing performance management, tenure, and payroll data for CFOs to identify talent gaps, burnout, or high attrition levels.
- Providing employee engagement or satisfaction survey data for HR and finance leaders to assess current workforce conditions and build a plan to boost employee engagement, satisfaction, and retention rates.
- Providing performance management data, financial data, demographics, employee movement, and training history for better workforce management.
- Answering workforce-related questions quickly.
4. Employee performance
To stay on top of growth, companies need to improve employee performance and turn their workforce into valuable assets and high-performing team members. HR analytics provides HR teams with insights into employee engagement and overall performance to discover ways to improve their impact.
HR analytics help boost employee performance by:
- Helping organizations collect and analyze employee data efficiently to drive business productivity using talent data as a key input.
- Using performance prediction to measure business performance and hand out benefits.
- Identifying better performers and incentivizing them by deriving insights from employee data.
- Providing accurate and actionable insights for decision-making.
- Identifying engagement activities that directly or indirectly impact employee performance.
- Using HR appraisal and performance data for succession planning – anticipating promotions, transfers, and professional break-ups beforehand.
5. Employee engagement
For the area of employee engagement, HR analytics enables human resources professionals with the data to understand what motivates employees, how engaged they are, and can provide data that can help to increase satisfaction and productivity.
By analyzing employee feedback, sentiment analysis, and other factors influencing engagement, HR analytics identifies key employee engagement drivers and helps develop strategies to improve it.
6. Learning & development
HR analytics enable organizations to implement effective training programs by collecting big data and learning from historical patterns.
Training analytics determine which employees need the most help by looking at turnover rates for each role, exit interviews that consistently mention a lack of training, and key performance indicators (KPIs) that aren’t being met in a particular employee group. These insights highlight a significant skill gap and enable HR teams to create a training plan accordingly.
HR analytics also helps identify if employees are making full use of the knowledge provided during training programs by measuring training effectiveness. Training effectiveness can be measured via post-training evaluations or implementing digital adoption platforms that collect real-time data on how employees are engaging with the learning flows.
All these insights into learning and training programs empower HR teams to understand the training results better, readjust plans, and correct courses throughout the learning process.
Examples of HR Analytics
To better understand what type of data and insights your team can extract from an HR analytics strategy, let’s explore different types of data points and survey analysis that can be done with HR analytics software or an HR analytics framework:
HR Analytics Examples for Employee Engagement
- Engagement Surveys: These are one of the most common ways to measure employee engagement. HR analytics can help gather and interpret this data, identifying patterns, trends, and areas for improvement.
- Pulse Surveys: Unlike engagement surveys, pulse surveys are brief and conducted more frequently to gauge employee feelings and engagement levels in real-time. The data generated can give quick insights into the impact of recent changes or initiatives.
- Productivity Metrics: HR analytics can track metrics like output per hour or quality of work to assess engagement. Highly engaged employees are often more productive.
- Employee Net Promoter Score (eNPS): This is a measure of how likely employees are to recommend their workplace to others. This can be a valuable measure of overall engagement.
- Social Network Analysis: This involves analyzing the communication and collaboration networks within an organization. Strong networks can indicate high engagement.
- Exit Interviews: Analyzing data from exit interviews can provide insights into reasons for employee disengagement and areas for improvement.
- Performance Metrics Analysis: Comparing engagement survey results with performance metrics can give a deeper understanding of the relationship between engagement and performance.
HR Analytics Examples for Hiring & Recruiting
- Time to Hire: This metric measures how long it takes to fill a vacancy from the moment the job is posted to when an offer is accepted. Analyzing this can help identify bottlenecks in the hiring process and improve efficiency.
- Quality of Hire: This involves evaluating the performance of new hires after a certain period. It can be determined through factors like job performance ratings, turnover rates, and feedback from managers and peers.
- Source of Hire: Tracking where successful candidates are coming from (e.g., job boards, social media, employee referrals) can help refine recruitment marketing strategies.
- Applicant Drop-off Rate: By analyzing at which stage applicants drop out of the process, HR can identify and fix issues in the recruitment process.
- Candidate Experience: Surveys can be used to collect data on candidates’ experiences during the recruitment process. This can provide insights to improve the overall experience, enhancing the employer’s brand.
- Cost per Hire: This metric measures the total cost associated with hiring a new employee. By reducing this cost, companies can achieve significant savings.
- Offer Acceptance Rate: This measures how often job offers are accepted. A low rate may indicate issues with salary, benefits, company culture, or the way offers are presented.
- Diversity Metrics: Analytics can be used to evaluate diversity in hiring practices. This can be crucial for companies committed to diversity and inclusion.
- Skill Gap Analysis: By comparing the skills of successful employees with those of applicants, HR can identify any gaps and adjust their hiring criteria accordingly.
- Employee Referral Rate: Analytics can help determine how many candidates are coming from employee referrals, which can be a valuable source of qualified candidates.
HR Analytics Examples for Employee Retention & Turnover
- Turnover Rate: This is the percentage of employees who leave the company during a certain time period. It can be calculated overall or broken down by department, role, tenure, etc.
- Voluntary vs. Involuntary Turnover: Analyzing the reasons behind employee departures (voluntary or involuntary) can help identify potential issues within the organization.
- Turnover Cost: This metric includes costs associated with recruiting, onboarding, training, learning and development, and lost productivity. Understanding these costs can motivate strategies to increase retention.
- Exit Interview Data Analysis: Through analysis of exit interview responses, HR teams can gain insights into the reasons employees are leaving, which can inform strategies to improve retention.
- Retention Rate by Manager: If a particular manager has a high turnover rate in their team, it could indicate issues with management style or team dynamics.
- Absenteeism Rate: High absenteeism can be a predictor of turnover, as it may indicate employee disengagement or dissatisfaction.
- Promotion Rate: Understanding the rate of promotions within the organization can also be useful. A low promotion rate might indicate a lack of career development opportunities, which could lead to increased turnover.
HR Analytics on Learning & Development
- Training Completion Rate: This measures how many employees complete their training programs within a specified time period. A low rate might indicate that the training content or format is not engaging or accessible.
- Pre- and Post-Training Assessments: These assessments measure the knowledge and skills of employees before and after training. Comparing these results can demonstrate the impact of training on employee knowledge and skill levels.
- Learning Application: Surveys or interviews can be used to determine how much of the training content employees apply in their work. This can provide valuable information on the practical relevance of the training programs.
- Training Cost per Employee: This measures the total cost of training divided by the number of employees trained. It can be useful for budgeting and deciding whether to develop in-house training or hire external vendors.
- Return on Investment (ROI): By comparing the cost of training programs with the benefits they deliver (increased productivity, reduced errors, etc.), companies can calculate the ROI of their training initiatives.
- Time to Proficiency: This metric tracks how long it takes for an employee to reach a defined level of competence after starting a training program.
- Employee Satisfaction with Training: Employee feedback can provide insights into how training programs are received and what improvements might be needed.
- Career Progression Post-Training: Tracking promotions or increased responsibilities post-training can provide insight into the effectiveness of training in terms of career development.
- Attrition Rate Post-Training: If attrition rates are high following specific training programs, this could indicate a problem with the training content, delivery, or relevancy.
- Performance Metrics Post-Training: Tracking changes in performance metrics after training can provide insights into the effectiveness of the training programs.
How DAPs Empower HR Teams & Drive HR Transformation
How to Get Started With HR Analytics
Here are the steps to help you get started with HR analytics in your organization.
1. Define your objectives
Clarify the specific HR challenges or areas of focus where analytics can provide insights and solutions. Determine the goals you want to achieve through HR analytics, such as improving recruitment, optimizing workforce planning, or enhancing employee engagement. This way, you’ll be able to gain actionable takeaways and measure the effectiveness of your actions.
2. Identify relevant HR metrics
Determine the KPIs and metrics that align with your HR objectives. This could include metrics related to employee turnover, time-to-fill vacancies, training effectiveness, or diversity and inclusion.
3. Assess data availability and quality
Collecting and tracking high-quality data is a crucial component of HR analytics as it provides insights into a lot of information and knowledge for the HR teams.
The kind of data collected for HR analytics includes:
- Employee performance data including low and high performers
- Salary and promotion history
- Demographics
- Onboarding and training engagement
- Overall employee engagement
- Employee retention and turnover
- Employee absenteeism
The data can be gathered from HR systems, learning & development systems, cloud-based systems, or data scientists can be hired to sort and organize the data. A data scientist is best suited to assess the viability of an analytics solution, ensure the robustness of the statistical modeling and predictions, monitor the quality and accuracy of the data, and help HR professionals implement the data to their benefit.
4. Build analytical capabilities
Develop the necessary skills and expertise within your HR team to conduct HR analytics. This may involve upskilling team members in data analysis, statistical techniques, and data visualization tools. Alternatively, consider partnering with experts or leveraging external resources for support.
5. Select appropriate analytics tools
Identify and implement suitable HR analytics tools and technologies. This could include data visualization software, statistical analysis tools, or specialized HR analytics platforms.
Here are some key features to look for in your HR analytics solution:
- They must answer any business questions asked by the C-suite.
- They must be easy to use by individuals who are not data scientists.
- A cloud-based solution aids accessibility without heavy IT integration.
- They must be powered with statistical analysis and machine learning technology.
- A solution with a subscription model is beneficial because they allow easy access to the latest upgrades in technology.
6. Analyze and interpret data
With HR analytics, informed decisions are made based on data rather than assumptions, which is why it’s important to understand the significance of these insights and take action accordingly.
The collected data could be used to build various forms of reports, graphs, and charts. Here are a few formats that can be used:
- HR dashboard – a visual representation of data that enables key stakeholders to easily monitor HR analytics and build it in the right way. It provides benchmark data such as turnover, headcount, sickness absence, time to hire, quality of hire, etc.
- HR scorecard – a mechanism used to describe and measure how people create value in a company.
- Document report – a simple document with key performance metrics and narrative.
7. Application
With the data at hand, start developing and implementing a strategy for addressing the outlined problem. The HR department must work with the management team to discuss the findings and devise a solution.
For example, if a lack of employee training and development opportunities is identified as contributing to employee turnover, then the HR department needs to take immediate action to invest in development and upskilling training programs for the workforce.
8. Communicate findings
Present the insights and recommendations derived from the HR analytics to relevant stakeholders, such as HR leadership, managers, or executives. Clearly communicate the implications and potential benefits of the analytics findings and collaborate on implementing actionable strategies.
9. Monitor and refine
Continuously monitor and assess the impact of your HR analytics initiatives. Collect feedback, evaluate the outcomes, and refine your analytics approach as needed. This iterative process helps improve the effectiveness and value of HR analytics within your organization.
5 HR Analytics Software
While there are many HR analytics solutions on the market, here are five we recommend exploring:
1. Whatfix
Whatfix is a digital adoption platform and user behavior analytics tool that enables organizations to drive software adoption with in-app guidance, self-help support, and adoption analytics.
Whatfix enables HR, L&D, and IT teams to understand how employees are engaging and adopting digital processes and software with capabilities such as custom event tracking, user journey flows, employee cohorts, and more.
Whatfix also collects data on how employees are engaging with your in-app guidance and employee help content, allowing you to understand gaps in your training content and friction points in your digital employee experience.
Unlock the full potential of your workforce with better support training and content, embedded directly in your enterprise applications.
2. intelliHR
intelliHR is a performance analysis human capital management (HCM) tool that helps organizations create useful reports on employee performance and satisfaction metrics. The software offers analytics features for HR teams to align their efforts with the organization’s strategic business objectives.
The software offers a variety of data collection solutions such as employee satisfaction surveys, employee net promoter score, performance and productivity data through self-review, peer review, and task completion statistics.
3. Qualtrics
Qualtrics HR analytics software is a user-friendly simple-to-use tool suited for medium and large enterprises. It sorts the collected HR metrics in graphs and reports that are easy to digest. The tool provides a survey feature for collecting self-reported workforce data around culture and performance.
Qualtrics leverages machine learning and native language processing to interpret data from open text responses, which are much more flexible and informative than numerical ratings or multiple-choice questions.
4. ADP Workforce Now
ADP Workforce Now is an all-in-one cloud-based HR suite. The software features HR management, payroll, benefits, talent management, labor management, and learning and analytics capabilities.
ADP Workforce Now helps manage the workforce and make data-driven decisions informed by insights from the richest and most robust workforce database in the business. The software also seamlessly integrates with leading third-party solutions.
5. Hibob HR
Hibob HR platform simplifies people management and helps drive engagement, culture, and productivity. It is configurable for the way you operate – onsite, remote, or hybrid.
The tool empowers HR managers to increase performance and retention, and streamline core HR processes such as onboarding, performance management, and compensation management using automated workflows to increase efficiency.
Future Trends in HR Analytics
Here are some HR trends that your team can focus on moving forward.
1. AI and machine learning
Organizations used an average of 3.8 AI capabilities in 2022, that is double the 1.9 used in 2018.
AI and machine learning technologies are poised to play a significant role in HR analytics. These technologies can automate data analysis, identify patterns, and make predictive recommendations, enabling more accurate and proactive decision-making.
For example, AI and ML can be used to predict employee turnover, identify high-potential candidates, and forecast future workforce needs.
2. Sentiment Analysis and employee experience
HR analytics will increasingly focus on analyzing employee sentiment and feedback to understand the employee experience. This includes leveraging natural language processing (NLP) that enables machines to understand, interpret and generate human language. NLP can be used to analyze employee feedback from various sources, such as surveys, performance reviews, and social media, to identify insights and trends that can help organizations improve their HR practices.
3. Predictive analytics
The focus will shift from reactive to predictive analytics, where organizations can anticipate future workforce needs, identify high-potential employees, and forecast talent gaps. Predictive analytics will enable HR professionals to take proactive measures to address talent requirements and optimize workforce planning.
For example, predictive analytics can be used to identify which employees are at risk of leaving the company, or to identify which job candidates are most likely to succeed in a given role.
Make the most of your HR analytics software with Whatfix
Unlock the full potential of your workforce with better support training and support content, embedded directly in your enterprise applications with Whatfix digital adoption platform.
Witness a 1.25x increase in employee productivity, as Whatfix enables you to:
- Provide a personalized in-app onboarding and training experience on your HR analytics software to get the maximum ROI.
- Deliver an elevated employee experience by reducing support tickets and eliminating employee frustration across enterprise applications.
- Empower employees to find answers to their own questions with a self-help knowledge base.
- Enhance user experience through comprehensive user journey analysis.
Schedule a free demo with us to learn more about how Whatfix DAP supports HR teams!
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