HR Analytics

What is HR Analytics?

HR analytics or people analytics is a process that uses data, statistical analysis, and data-driven insights to inform and optimize HR strategies, policies, and decision-making. It helps organizations achieve their goals by collecting, analyzing, and reporting HR data.

The key reason to conduct effective HR analytics is to conclusively show your business impact within the organization and actual cause-effect relationship among what you do and business outcomes and building a strategy based on that information, will allow you to make those terms a reality Mondore, S., Douthitt, S., & Carson, M. (2011)

HR analytics enables organizations to derive valuable insights from quantifiable HR data, which can be used for optimizing key performance indicators and enhancing employee productivity. Besides, it also allows organizations to achieve optimal performance and stay competitive.

Frequently asked questions (FAQs): 

1. What are the benefits of HR Analytics?

HR analytics provides descriptive, predictive, and perspective analyses of people management projects. It aims to support data-driven decision-making and eliminating unconscious or conscious bias.

Here are a few benefits of HR analytics that you need to know.

  • It helps in practicing evidence-based business decisions
  • It Improves recruitment and talent acquisition
  • It manages employee performance and productivity
  • It helps build equitable compensation and benefits packages
  • It enables effective workforce planning

2. What is the difference between HR Metrics and HR Analytics?

HR Metrics HR Analytics 
HR metrics are specific measurements used to track and evaluate various aspects of the human resources function. They provide a rapid and accessible tool to evaluate HR performance and make informed operational decisions. 

 

HR analytics is a more comprehensive practice involving collecting, analyzing, and interpreting large sets of HR-related data. It provides deeper insights and supports data-driven decision-making beyond intuition. 

 

Examples  

 

  • Looks into recruitment 
  • Calculates turnover 
  • Evaluates employee absenteeism. 
  • Indicates the investment in employee development. 

 

Examples 

 

  • Forecasting and predictive analytics 
  • Analyzing correlations between employee engagement and business outcomes. 
  • Suggest strategies to improve recruitment, retention, and performance. 

 

3. What are the 4 levels of HR Analytics?

The four levels of HR Analytics are:

  1. Descriptive Analytics: Descriptive analytics summarizes historical data and provides insights into what has happened.
  2. Diagnostic Analytics: Diagnostic analytics delves deeper into understanding why certain events occurred.
  3. Predictive Analytics: Predictive analytics uses statistical models to forecast future outcomes.
  4. Prescriptive Analytics: Prescriptive analytics recommends actions to optimize HR strategies.

4. What are the 7 pillars of HR Analytics?

  1. Workforce planning: Predicting future talent needs.
  2. Talent sourcing: Finding the best recruitment channels.
  3. Hiring: Optimizing the hiring process for quality and cost.
  4. Onboarding and engagement: Keeping new hires happy and productive.
  5. Performance and value: Identifying high performers and maximizing their impact.
  6. Retention: Reducing turnover and its costs.
  7. Well-being: Promoting employee health and safety.

Most importantly considering the modern workforce planning:

  • Focus on a data-driven culture: Train employees to interpret and leverage people analytics for better decision-making at all levels.
  • Invest in predictive analytics: Utilize data modeling to anticipate future trends, identify flight risks, and optimize talent strategies proactively.

 

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