An organization can gather data routinely, but what does the data indicate? Without direction or a process, the data may be meaningless or extraneous. HR analytics breaks down raw human-resources data into actionable insights, answering important questions in the process. These questions include:

• What patterns are revealed in turnover?
• How long does it take to hire?
  
• What amount of investment is needed to get employees up to a productive speed?
• Which employees are most likely to leave within a period of time?
• Are development initiatives having an impact on performance?

Simply put, HR analytics empowers organizations to unlock valuable insights from the vast sea of data they already possess. By delving into metrics spanning from recruitment timelines to employee turnover rates, HR analytics unveils patterns and trends crucial for informed decision-making. With analytics, organizations gain clarity on critical questions such as the effectiveness of recruitment processes, the impact of training programs on employee performance, and the identification of flight-risk employees.

Perhaps even more importantly, HR analytics acts as a shield against legal ramifications stemming from arbitrary, non–data-backed decisions. By grounding HR actions in reliable analysis, companies mitigate the risk of discrimination or bias, ensuring fair treatment across the workforce. This evidence-based approach does more than just safeguard the organization; it promotes a culture of transparency and accountability. 

For organizations striving to elevate their workforce management practices, effective HR analytics offers vital insights—ones that can be easily leveraged to drive meaningful change. Key benefits of incorporating HR analytics into your business strategy include: 

• Improved hiring

• Reduced attrition

• Enhanced experience

• Stronger workforce

• Optimized HR processes

• Increased employee and stakeholder trust

Transparent communication backed by data demonstrates that decisions are rooted in evidence rather than subjective judgment. The correct approach to HR analytics builds credibility and strengthens relationships across the organization.

HR analytics benefits for HR management

HR aggregates data to evaluate key practices, such as recruitment, talent management, performance, and training. The kind of data that is typically collected in HR analytics includes employee profiles, as well as data associated with performance, onboarding, demographics, retention, turnover, absenteeism, promotions, and salaries.

Given the range of responsibilities inherent in modern HR; the first step in HR analytics is to determine which metrics are most directly tied to success. Metrics are the yardsticks against which performance is measured, and in HR analytics, that means tracking, recording, and evaluating data in each of the following areas:

Revenue per employee

Revenue per employee is found by dividing revenue by the number of employees within an organization, indicating the average revenue generated by an employee. This metric provides a measure of workforce productivity and efficiency by assessing the revenue generated by each individual member of the workforce. It offers valuable insight into the organization's ability to leverage its human capital effectively to drive business outcomes. By benchmarking revenue per employee against industry standards and historical trends, businesses can gauge their workforce's contribution to overall profitability while also identifying opportunities for improvement.

Time to hire

Time to hire measures the duration it takes to fill vacant positions within the organization. A lengthy time to hire can lead to increased recruitment costs, productivity losses, and potential talent drain. HR teams use this metric to identify bottlenecks in the recruitment process, streamline workflows, and enhance candidate sourcing and selection strategies.

Absenteeism

Absenteeism quantifies the frequency and duration of employee absences from work— due to illness, personal reasons, or other factors. Satisfied, healthy, engaged employees are less likely to miss work; high absenteeism rates can indicate underlying issues such as low morale, workplace dissatisfaction, or inadequate employee support programs. By tracking absenteeism metrics, HR leaders can pinpoint trends, address root causes, and implement proactive measures to promote employee well-being and attendance.

Voluntary turnover rate

The percentage of employees who leave the organization voluntarily within a specific period contributes to the voluntary turnover rate. This is found by calculating the number of employees who were terminated involuntarily vs. the total number of employees within an organization. High voluntary turnover can signal dissatisfaction with job roles, organizational culture, or career development opportunities, etc. Analyzing turnover patterns and exit interview data helps HR enhance retention strategies and foster a more engaging and supportive work environment.

Involuntary turnover Rate

Involuntary turnover rate reflects the percentage of employees who are terminated or dismissed by the organization. While some level of involuntary turnover is inevitable, excessively high rates may indicate ineffective talent management practices or a misalignment between the workforce and the organization’s goals.

Offer acceptance rate

Whether or not a prospective hire accepts an offer of employment may depend on several factors—many of these relate directly to a company’s talent acquisition strategy. Offer acceptance rate measures the percentage of job offers extended by the organization that are accepted by candidates. A low offer acceptance rate may signify challenges in attracting and retaining top talent or discrepancies between job expectations and offered compensation or benefits. Insights gained from offer acceptance rates can be used to refine recruitment strategies, tailor job offers to candidate preferences, and enhance employer branding.

Time to fill

The duration that passes between posting a job opening and successfully hiring a candidate to fill the position is known as time to fill. A lengthy time to fill can lead to increased recruitment costs, prolonged vacancies, and heightened strain on existing staff.

Training efficiency

Training efficiency evaluates the effectiveness of employee training programs by assessing factors such as skill acquisition, knowledge retention, and performance improvement. Measuring metrics such as training completion rates, competency attainment, and post-training performance gives HR more understanding regarding the impact of training initiatives on employee development and organizational performance.

Training expenses per employee

Overly expensive training programs can be as problematic as ineffective ones. Measure the training expenses per employee by finding the total training expenses, and then dividing it by the total number of employees who participated in the training. Comparing training expenses to outcomes and business performance metrics, HR can optimize training budget allocation, prioritize investments in high-impact training programs, and ensure alignment with organizational goals and objectives.

To unlock the full potential of HR analytics, organizations need to leverage both internal and external data. This helps HR develop a holistic view of the workforce landscape, inform strategic decision-making, and drive sustainable business outcomes.

Internal data

Core HR systems have several data points for their analytics tools obtained from within their HR department—some metrics may include employee tenure, compensation, training records, performance appraisal, employee potential and value, disciplinary actions taken, and reporting structures.

An issue with these metrics is that the data may be disconnected and may not be entirely reliable, which is the point where data scientists play a significant role in organizing scattered data and grouping buckets of relevant points. 

External data

Data gathered externally involves working with other departments within an organization, which is essential for gathering a wider perspective. Vital external data metrics generally fall into the following categories.

• Financial: The cost of revenue per employee and the cost of hiring new employees. 

• Organization-specific: The organization and its core offerings which require HR to supplement varying analytics.

• Passive: Employees constantly provide data in an HRIS from the moment that they are contacted for a job. Data from their social media posts and shared feedback surveys are also important points to guide HR data analysis. 

• Historical: There are many external factors, like global economics, environmental, and political data that impact employee behavior. This data can provide insights that internal data cannot.

Broadly speaking, any process, initiative, or action that applies insights gained from HR data could be called a form of HR analytics. That said, most organizations that prioritize the improvement of workforce dynamics and performance see HR analytics as more of a journey made up of specific steps. These steps help direct the analytics process, providing a better foundation for achieving positive change.

Typically, the key stages in HR analytics include: 

Data collection

HR aggregates data to evaluate key practices, such as recruitment, talent management, performance, and training. The kind of data typically collected in HR analytics includes employee profiles, data associated with performance, onboarding, demographics, retention, turnover, absenteeism, promotions, and salaries.

Measurement

With the correct data on hand, it can now be placed under a microscope of continuous measurement and comparison. HR analytics compares the data to historical norms and standards, building from a constant stream (rather than a single-moment snapshot) of information, to develop an accurate, real-time picture of HR metrics. Effective use of HR metrics (such as those identified above) depends heavily on pre-established baselines, so that organizations can chart their progress.

Analysis

This stage analyzes the results from metrics gathered to find trends that may impact the organization as a whole, and can be broken down into three specific forms of analysis. Descriptive analytics help interpret and quantify historical data, predictive analytics uses statistical models to forecast future opportunities, and prescriptive analytics then focuses on using reliable information and insights to anticipate possible consequences and outcomes.

Application

The culmination of HR analytics lies in its application, informing organizational strategy and enhancing decision-making capabilities. By translating data-driven insights into actionable strategies, HR empowers organizations to optimize workforce management practices, improve employee engagement, and drive business performance. These insights inform critical HR decisions, such as recruitment strategies, talent development initiatives, and organizational restructuring efforts.

In terms of overall business value, the advantages of HR analytics can be thought of as falling into one of two categories:

Employee engagement

Employee engagement is a critical factor in driving organizational success, influencing productivity, retention, and customer satisfaction. HR analytics makes it possible for organizations to measure and improve their employee engagement through a variety of metrics and methodologies. Pulse surveys, sentiment analysis, employee net promoter score (eNPS), one-on-one meetings, and exit/stay interviews are among the key metrics utilized by HR teams to gauge employee sentiment, satisfaction, and overall engagement levels. 

Applying HR analytics to monitoring these metrics in real-time, organizations can more accurately identify potential problems and address employee concerns before they begin to spiral out of control.

HR analytics ROI

The return on investment derived from HR analytics initiatives directly contributes to overall business value by optimizing talent decisions and driving strategic outcomes. With clear data-driven insights, organizations can make more informed talent decisions throughout the employee lifecycle—from recruitment and onboarding to performance management and succession planning. At the same time, predictive analytics and modeling help HR teams identify high-potential talent, anticipate workforce trends, and align talent strategies with business objectives. 

The result is a more efficient and effective workforce that drives sustainable growth and competitive advantage. Typically, the ROI generated from HR analytics initiatives translates into tangible business value, demonstrating the impact of data-driven HR strategies on organizational success.

ust as HR analytics encompasses a wide scope of methodologies and metrics, it also covers an almost limitless range of use cases. Consider the following examples:

• Predictive analytics for talent acquisition 
  Predictive analytics enables organizations to forecast future hiring needs and identify high-potential candidates based on historical data and predictive modeling.

• Employee engagement surveys 
  Employee engagement surveys measure employee sentiment, satisfaction, and engagement levels within the organization. Conducting regular surveys and analyzing results helps identify drivers of engagement and any pain points or underlying issues.

• Retention analysis 
  Retention analysis involves analyzing turnover rates, exit interviews, and retention metrics to identify factors contributing to employee turnover and attrition.

• Learning and development evaluation 
  HR analytics evaluates the effectiveness of learning and development initiatives by tracking metrics such as training completion rates, competency attainment, and post-training performance metrics.

• Workforce planning and succession management 
  Workforce planning and succession management involve forecasting future workforce needs and identifying high-potential talent to fill key roles within the organization.

Getting started on the path to HR analytics is not difficult. With the right information, strategies, people, and buy-in, organizations will be able to enjoy actionable insight to optimize HR performance and processes. Consider the following best practices:

Develop a collective mindset

It’s crucial for HR leaders to prepare teams and organizations for workflows driven by analytics, which must occur before operational and mathematical aspects. Discussing the need for analytics and preparing your team to work with the data are two pieces that must operate in conjunction.

Employ data scientists

Data scientists are slowly becoming an integral aspect of HR teams. These key players assess analytics solutions and their viability—securing more-robust, more-detailed predictions and statistical models.

Focus first on quick wins

Implementing a successful small project can help convince stakeholders that HR analytics have important value to the business. These quick wins may deliver tangible, high-impact results in a shorter amount of time.

Listen to the legal team

Data collected by HR teams is heavily governed by compliance standards and laws. Some legal considerations include:

1. Employee privacy.
2. Location of HR analytics vendor.
3. Established a goal of data collection.
4. Consent from employees about the data being collected.
5. Security when using third-party software.

Choosing the right solution for your business

Although different organizations may have different HR analytics needs, effective HR analytics solutions tend to share certain commonalities:

1. They solve executive-level concerns.
2. They don’t require advanced data-science experience to use.
3. They are based in the cloud rather than on-premises.
4. They are built on advanced machine-learning technologies.
5. They incorporate predictive analytics, extracting information from existing data to identify patterns and accurately anticipate events.
6. They provide easy access to complex data through visualization, often in the form of charts and graphs.
7. They exist as SaaS solutions, cutting upfront expenses and ensuring up-to-date maintenance and patching.

Although analytics has helped revolutionize nearly every aspect of modern business, HR analytics is, in many ways, still in its infancy. This means that those companies who are able to fully embrace analytics within human resources processes and tasks may enjoy a clear advantage. In the book The Practical Guide to HR Analytics: Using Data to Inform, Transform and Empower HR Decisions, the authors identify four levels of HR analytics maturity:

Level 1 – operational reporting

The first level of HR analytics uses data to reflect on the events of the past, and draw conclusions about why those events played out. This level fundamentally understands data that is already available and eventually reconciles what the data means for the company.

Level 2 – advanced reporting

The difference between this level and Level 1 is how frequently data is reported. Level 2 involves proactive, routine, or automated reporting. The primary functionality is exploring relationships between variables.

Level 3 – strategic analytics

This level is the start of a more-thorough analysis. Casual models, data relationships, and more come into play, and their effect on outcomes is carefully evaluated.

Level 4 – Predictive Analytics

The final level is defined by predictive analytics. HR departments at Level 4 gather data and apply it to predict the future and make the right plans for it.

Unfortunately, most HR departments within organizations function entirely in Level 1, and only a third are capable of functioning at Level 2. However, for those HR departments that function at levels 3 and 4, increased efficiency, improved processes, and a greater role in business decision making are the natural result.

ServiceNow offers modern businesses the tools and analytics to optimize HR service delivery. Providing easy, comprehensive reporting and real-time visibility, ServiceNow Performance Analytics for HR Service Delivery integrates seamlessly across departments, for a consistent experience to improve employee satisfaction and business agility. Check out ServiceNow’s Performance Analytics Data Sheet for more information. 

ServiceNow makes it all possible, by applying intelligent workflows to help streamline the employee-HR experience. Track goals and gain insights into HR performance with best-practice KPIs and intuitive dashboards. Quickly identify and remediate HR bottlenecks and poor employee experiences. Employ advanced forecasting to predict and prepare for future trends. Provide self-service options to allow employees the freedom to take a more active role in their own satisfaction. With Performance Analytics for HR Service Delivery, you will always have the data you need, to provide the HR support your employees crave. Demo HR Service Delivery today!