HR Analytics

Everything You Need to Know

Definition: What is HR analytics?

HR analytics is the application of statistics, modeling, and analysis of employee-related factors to improve business outcomes.

HR analytics is also often referred to as:

The below graph provided by Google Trends shows search interest for these terms since 2004. Both the terms HR analytics and people analytics have grown in popularity and continue to gain interest.

These terms are often used interchangeably, although some debate their differences. Definitions of HR analytics tend to encompass a broader scope of data, while people analytics and talent analytics refer to data points specific to people and their behavior. Some prefer the term workforce analytics because of the growing tendency to automate tasks with robots, which may be considered part of the workforce.

Overview

HR analytics enables HR professionals to make data-driven decisions to attract, manage, and retain employees, which improves ROI. It helps leaders make decisions to create better work environments and maximize employee productivity. It has a major impact on the bottom-line when used effectively.

HR professionals gather data points across the organization from sources like:

  • Employee surveys
  • Telemetric Data
  • Attendance records
  • Multi-rater reviews
  • Salary and promotion history
  • Employee work history
  • Demographic data
  • Personality/temperament data
  • Recruitment process
  • Employee databases

HR leaders must align HR data and initiatives to the organization’s strategic goals. For example, a tech company may want to improve collaboration across departments to increase the number of innovative ideas built into their software. HR initiatives like shared workspaces, company events, collaborative tools, and employee challenges can be implemented to achieve this goal. To determine how successful initiatives are, HR analytics can be utilized to examine correlations between initiatives and strategic goals.

Once data is gathered, HR analysts feed workforce data into sophisticated data models, algorithms, and tools to gain actionable insights. These tools provide insights in the form of dashboards, visualizations, and reports. An ongoing process should be put in place to ensure continued improvement:

Applications

Retention

The cost to replace an employee could be over 200% of their annual salary, according to AmericanProgress.org. The true cost might even be higher due to training/onboarding, lost productivity, recruitment, and decreased morale among other employees. Losing an employee that’s in the top 1% of performers could mean the difference between growth and decline. For this reason, decreased attrition and improved employee engagement are often top priorities for HR departments. HR analytics can help improve retention through a churn analysis that looks at data points like:

Through this data-driven approach, HR analytics can illuminate the major causes of attrition, and new policies, along with training programs, can be put in place to help mitigate the problem. For example, data might show that high-aspiration employees are not challenged or employees are frustrated with a certain management style. Human resources analysis will reveal these issues, and then it will be up to leadership to act. It’s also possible to spot an at-risk employee before they leave so preemptive actions can be taken to resolve issues. For example, a once high-performer may not be as productive because he feels he or she is underpaid. An analysis of productivity alongside a comparison of market-value salaries can help spot this.

Employee Performance

As qualified candidates become more difficult to find and retain, improvements in performance evaluation can prove to be tremendously valuable. HR analytics leverages your employee data to determine who your best and worst performers are, based on factors like past work experience, length of employment, and to whom they report. Common characteristics between groups of employees can emerge, which can be used to properly motivate employees and ensure they receive the right rewards. Career progression is an important component to monitor, as well, since employees are much more likely to leave if they’re not satisfied with their career trajectory. Analysis of promotion rates, promotion wait times, and qualitative data from employees will help HR meet employee expectations and keep them motivated. Leadership traits may emerge in some employees, and companies can determine which characteristics correlate with future leaders. HR can then foster this potential, resulting in long-term ROI for the organization.

Recruiting

Organizations need to first determine who their ideal candidate is and what skills are needed for the job. This can be discovered through discussions with hiring managers, analysis of previously successful hires, and available market data. Organizations can then match their need to where the largest pool of applicants with that skillset resides. For example, the best cities for PR jobs according to Forbes are Los Angeles, New York, and Washington D.C., so a recruiter may want to focus efforts in these cities if they aren’t able to find local talent for the job. Likewise, a recruiter may look at college graduate data to see where the best new talent is if they need to fill an entry-level position. Talent acquisition teams also need to adopt channel optimization strategies based on recruitment analytics. A continuous process of evaluating which channels drive the best candidates at the most efficient price is extremely important. Data analytics may reveal one source has a lower cost per applicant, while another may provide the best talent. HR analytics can also be used to craft the best recruitment message to the right candidate based on internal, open-source, and third-party data. This is all data that HR analytics platforms can consume and transform into easily digestible formats such as dashboards and charts. Recruitment relies heavily on metrics gathered during the interview process. Important metrics include:

Over time, HR analysts can also see which candidate characteristics predict the best employees. Pre-screen exams are often used to test candidates, and analytics can help determine what types of questions these exams should contain. For example, a candidate who applied for a Python developer role can be asked a series of questions to assess competence within the program.

Employee Development

Almost 40% of American employers say they cannot find people with the necessary skills for entry-level jobs and almost 60% say entry-level candidates are not prepared professionally.

HR analytics is also playing an increased role in evaluation of employee development (or workforce development) programs to close the skills gap. Analytics tools can help human resource management assess company needs, allocate resources to train employees most likely to fill those needs, and then evaluate the results. The goal is to close the skills gap so a company can compete with increasingly agile global competitors.

Data visualizations fed by employee and customer feedback data can show the evolution of employee professional growth. For example, a retail clothing chain may discover through customer feedback that sales associates are friendly, but have trouble providing excellent customer service when items are not in stock. An employee development program can be put in place to educate associates on the keys to customer success. This could take the form of a pilot training program for employees in the lowest-performing locations.

The best employee development and talent management programs align employee goals with business goals, and investment is often dependent on the ability to tie these to revenue. The process is successful when ROI is achieved, creating a feedback cycle where success increases revenue and investment in development.

Workforce Planning

Not only do organizations need to ensure they have employees with the right skills presently, but they also need to be able to anticipate future departures or changes in the organization’s needs, particularly for business growth. HR needs a data-driven approach to successfully navigate the ever-changing composition of organizational talent. This ensures that workforce and capacity planning are optimized.

For example, an electronics OEM may need to anticipate a greater need for call center support with the release of new products in the next quarter. Once again, HR needs to be aligned with the goals of the business and upcoming changes. Predictive analytics and data analytics platforms are changing the way HR can utilize and anticipate these changes.

Employee Engagement

An engaged workforce is critical to attracting and engaging talent. The challenge is determining which factors will result in revenue for the company. This makes employee engagement a very difficult metric to quantify and take action on.

How can HR analytics help with employee engagement?

Google is a perfect case study in how people analytics can be used to increase employee engagement. They’re one of the most data-driven cultures in the world. Its People Operations team utilizes a mix of quantitative and qualitative data to measure what employees value most and to keep them engaged.

They discovered, through a combination of employee surveys and productivity analytics, that great managers tend to have the following qualities:

  1. Coaching skills
  2. Does not micromanage
  3. Is genuinely concerned for well-being of employees and expresses this
  4. Results-oriented
  5. Excellent communicator (listens and shares)
  6. Develops employees
  7. Clear vision and strategy for team
  8. Possesses key technical skills to help guide team

Compensation and Incentive Programs

Compensation is often the largest business expense, which underlines its importance in organization decision-making. Data analytics platforms can help analyze large volumes of employee and market data to achieve a competitive advantage. Smart HR analysts will keep track of what competitors offer employees to ensure top talent is attracted to the company. They can also look at exit surveys during the recruiting process and declined offers to better understand the compensation and incentive landscape. HR analytics can provide:

What are the Benefits of HR Analytics?

In sum, HR analytics will move from an operational partner to a more strategic center of excellence. Companies are now realizing company success is built on people, and HR analytics can light the way from intangible theory-based decisions to real ROI through the following:

  • Better hiring practices
  • Decreased retention
  • Task automation
  • Process improvement
  • Improved employee experience
  • More productive workforce
  • Improved workforce planning through informed talent development

What are the Biggest Challenges of HR Analytics?

The road to actionable HR analytics is not always easy. There are several challenges organizations need to overcome so they can reap the rewards:

  • Finding people with the right skillset to gather, manage, and report on the data
  • Data cleansing
  • Data quality
  • Too much data to parse or not knowing what data is most important
  • Data privacy and compliance
  • Proving its worth to executive leadership
  • Tying actions and insight to ROI
  • Identifying the best HR technologies to keep track of the data

HR Analytics: A Brief History

The Future of HR Analytics

We’re experiencing seismic shifts in the HR landscape, and smart organizations realize they need to embrace a data-driven culture to compete and retain top talent. Data analysis is now a necessary tool to move beyond gut feeling, but challenges remain in selling its benefits to the C-Suite. Once consensus is gained, partners and human resource management solutions will need to be chosen with care to ensure goals are met.

Psychology is also playing an increasingly important role in HR analytics. Industrial-organizational psychology (I-O psychology) applies psychological principals to organizations. Its goal is to increase productivity and employee well-being. A common application is to match employees with the best-fit job within the organization, and analytics is one tool I-O practitioners use to make these decisions.

Ten disruptions identified by Josh Bersin from Deloitte should be on every CHRO’s mind as they move to incorporate analytics and the cloud systems that support it:

  1. Shift from automation to productivity
  2. Acceleration of HRMS and HCM cloud solutions
  3. Continuous performance management
  4. Feedback, engagement, and analytics tools
  5. Reinvention of corporate learning
  6. The recruiting market is thriving with innovation
  7. The well-being market is exploding
  8. People analytics matures and grows
  9. Intelligent self-service tools
  10. Innovation with HR itself

Tools for HR Analytics

Workday

Human resource information systems (HRIS) are one of the most important tools for HR analytics. These systems automate many of the core functions of HR, like benefit management, time and attendance, and applicant tracking. It functions very much like a database of your employees.

Workday is one of the leading HRIS tools on the market today due to its cloud-centric system architecture. It does an excellent job integrating finance and HR systems into one user-friendly platform.

Google Analytics

The most popular web analytics tool is Google Analytics, with well over 30 million websites taking advantage of its features. It’s a freemium tool that’s easy to implement and use. HR analysts can use Google Analytics to gain insights such as:

R

R is an open-source programming language for statistical computing and graphics. Analysts will require technical skills to work efficiently with this tool. It includes capabilities such as linear regression, non-liner modeling, and time-series tests. Use cases include:

Python

Python is a high-level programming language made for general programming. While R was built specifically for statistics, Python exceeds R when it comes to data mining, imaging, and data flow capabilities. It’s more versatile than R and more commonly used with other programs. Python is generally easier to learn than R, and is best used for task automation.

Microstrategy

MicroStrategy is an enterprise analytics and mobility platform which includes R, Python, and Google Analytics integration. It has 60+ data source connectors so analysts can gain insights by blending disparate data. This data can be output into data visualizations and dashboard reports to gain insights quickly, and can be easily shared throughout the organization. Some examples include:

Learn more: Digital Transformation of Human Resources with Microstrategy 10

Careers in HR Analytics

According to SHRM, 59% of organizations plan to increase positions over the next 5 years which require data analysis skills, with the most common functional areas include:

  • Accounting and finance: 71%
  • Human resources: 54%
  • Business and administration: 50%

The Bureau of Labor Statistics expects employment in HR to grow 21% and create 90,700 new jobs by 2020. While many companies know they need to apply analytics to HR, they often struggle to find the necessary blend of analytical talent and HR knowledge in candidates. Because of this, HR departments are either training existing employees in HR data analytics, utilizing analytical skillsets from other parts of the organization, or hiring data scientists and training them on HR principles.

Jobs in HR Data Analytics

Some job titles include:

  • HR Analyst
  • HRIS (Human Resources Information Systems) analyst
  • Analyst, people analytics
  • Analyst, people analytics and compensation
  • Corporate HR – workforce analytics
  • Strategic people analyst
  • Manager, HR workforce reporting analytics
  • Research, HR analytics
  • Talent analytics manager
  • HR data scientist

HR Analysts: What Skills Are Required?

  • People skills
  • Analytical skills
  • Detail-oriented
  • Data management
  • HR systems knowledge and experience

Salaries vary depending on a candidate’s background and the company’s need, but a background in data science will typically yield a higher starting salary because of a shortage in data science skills. Data scientists don’t necessarily need an HR background to make a huge impact in the HR department.

How Much Do HR Analysts Make?

How Much Do Sr. HR Analysts Make?

Data Scientist Starting Salary

FAQ

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