What is HR analytics?

Human resources analytics is a series of processes that collect and analyze HR data to improve organizations and the performance of their workforce.

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?

  • Improve hiring
  • Reduce attrition
  • Enhance experience
  • Strengthen workforce
  • Improve processes
  • Gain trust
Graphic showing the benefits of HR analytics.

Collecting data

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.

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 off of a constraint stream (rather than a single-moment snapshot) of information, to develop an accurate, real-time picture of HR metrics. Effective use of HR metrics in HR analysis depends heavily on pre-established baselines, so that organizations can chart their progress.

Important HR analytic metrics include:

  • Times to hire: How long it takes to post jobs to the finalized hiring stage.
  • Recruitment costs: The cost associated with the locating and hiring of employees.
  • Turnover: The rate of employees quitting their jobs after a specific amount of time.
  • Absenteeism: The frequency with which employees miss work.
  • Engagement: Measuring employee productivity and their satisfaction with their assigned job and related tasks.

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

With data collected, quantified, and analyzed, the resultant insights are then used to inform organizational strategy and improve decision-making capabilities.

  • Make better data-driven decisions
  • Justify necessary HR intervention
  • Effectively evaluate the effectiveness of interventions
  • Increase tactical and strategic role within an organization

Employee engagement

The data useful for an HR team is a measure of employee performance, experience, and business outcomes. Metrics include pulse surveys, sentiment analysis, employee net promoter score, one-on-one meetings, and exit/stay interviews.

HR analytics ‘ROI’

The return on investment increases the business value derived from making better talent decisions.

Absenteeism

Satisfied, healthy, engaged employees are less likely to miss work. By tracking absenteeism, organizations can gain insight into employee health and happiness.

Involuntary turnover rate

Involuntary turnover tracks the rate at which employees are terminated from their positions within the organization. This is found by calculating the number of employees who were terminated involuntarily vs. the number of employees within an organization. The involuntary turnover rate can also provide information on the recruitment strategy to analyze the quality of hires.

Offer acceptance rate

Whether or not a prospective hire accepts an offer of employment may depend on a number of deciding factors. However, many of these factors relate directly to a company’s talent acquisition strategy. A low offer acceptance rate may indicate critical problems in the hiring process. Acceptance rate is found by taking the number of formal job offers divided by the number of open job positions.

Revenue per employee

This metric is found by dividing revenue by the number of employees within an organization, which indicates the average revenue generated by an employee. This is a measurement of operational efficiency and how effective an organization is at generating revenue through employees.

Time to hire

Time to hire describes the amount of time that it takes to find and bring in new talent. A longer time to hire may indicate inefficiencies or bottlenecks on the hiring process, while a shorter time to hire can help deliver a more satisfying experience for future employees.

Training efficiency

Training efficiency is determined by analyses of multiple data points, such as performance improvement, upward transition of employee roles, and test scores after training. Measuring training efficiency can provide better insights into the effectiveness of company training programs.

Training expenses per employee

Overly expensive training programs can be nearly 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.

Voluntary turnover rate

The rate at which employees choose to quit their jobs, voluntary turnover rate helps identify any issues in the employee experience. This is calculated by dividing the number of employees who have left their jobs by the number of total employees.

Time to fill

Time to fill describes the length of time between first advertising a job opportunity and conclusively hiring a new employee to fill the position. Organizations benefit when positions are filled quickly, and this metric can help refine strategies for a more efficient process.

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 an important 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 requires 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.

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.

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’ll always have the data you need, to provide the HR support your employees crave.

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