Shabana Barshaj Jul 26, 2024

Leveraging HR Analytics in Decision-Making: Evaluating Pay Raise Requests

Leveraging HR Analytics in Decision-Making can provide data-driven insights that ensure fairness and transparency. 

As a Human Resource professional, you can make more informed decisions about salary adjustments by analysing employee performance metrics, market salary data, and organisation budgets. This approach helps you in identifying high performers and aligning compensation strategies with business goals.

In this blog, I will explain to you how HR analytics can guide decision-making processes, particularly in scenarios such as evaluating employee pay raise requests. We will also explore the methodologies and tools that HR professionals (you) can use to make evidence-based decisions that align with organisational goals.

Also Read: Top HR Certifications for Career Growth

What is HR Analytics? 

HR analytics, also known as people analytics, is the process of gathering, examining, and presenting HR data to improve business operations. It helps companies make well-informed choices, cut expenses, and streamline procedures while adhering to legal regulations.

HR analytics can improve a range of internal operations, such as payroll, benefits, recruitment, orientation, performance evaluation, and employee satisfaction. Generative AI is still in the experimental phase.

Check out: How to become a Successful HR professional

How to evaluate a Pay Raise Request in different scenarios?

Let's consider a scenario where an employee requests a pay raise. Here’s how HR analytics can assist in making an informed decision:

  • Data Collection: The first step is to gather relevant data. This includes the employee's performance metrics, tenure, current salary, market salary benchmarks, and the organization's compensation policies. Data can be extracted from the Human Resources Information System (HRIS) and other relevant databases.
  • Performance Analysis: Using performance data, HR can evaluate the employee's contributions against set Key Performance Indicators (KPIs). Tools like regression analysis can help determine the correlation between the employee's performance and their current pay level.
  • Market Benchmarking: It’s essential to compare the employee’s current salary with market standards. Conjoint analysis can be used to assess if the employee’s compensation is competitive within the industry.
  • Predictive Modeling: HR analytics can employ predictive models to forecast the potential impact of a pay raise on employee retention and motivation. For instance, by analysing historical data, HR can predict whether a salary increase is likely to enhance employee retention and productivity.
  • Decision Trees: Decision trees are useful for visualizing different decision pathways and their potential outcomes. For instance, a decision tree can help illustrate the potential costs and benefits of approving the pay raise versus rejecting it.
  • ROI Analysis: Finally, HR can perform a Return on Investment (ROI) analysis to evaluate the financial implications of the pay raise. This involves comparing the cost of the salary increase against the expected gains in productivity and employee satisfaction. 
Flow chart showing evaluation of pay raise request in different scenarios

Analysis of HR Analytics Scenarios Through Example

Let's put the above concepts into practice with a simplified example.

  • Employee Data:
    • Tenure: 3 years
    • Current Salary: AED 120,000 per year
    • Performance Rating: 4.5/5
    • Market Salary Benchmark: AED 130,000 per year
  • Performance Analysis: Regression analysis indicates that high performers (rating above 4) in similar roles are typically in the 75th percentile of the salary range.
  • Market Benchmarking: Conjoint analysis shows that the employee's current salary is slightly below the market average.
  • Predictive Modeling: Historical data suggests that a salary increase of 10% reduces turnover risk by 15% among high performers.
  • Decision Tree:
    • Approve Raise: Increased retention, higher motivation, cost AED 12,000 annually.
    • Deny Raise: Potential turnover, loss of productivity, cost of replacing employee approximately AED 50,000.
  • ROI Analysis: The cost of the raise (AED 12,000) is significantly lower than the cost of turnover (AED 50,000), indicating a positive ROI.

This analysis ensures that the decision to approve the pay raise is aligned with both employee satisfaction and organisational goals.

Conclusion

HR analytics provides a solid framework for making data-informed decisions about employee compensation. By using performance analysis, market comparisons, predictive modeling, and return on investment (ROI) analysis, HR professionals can make fair and strategic choices. This approach helps retain top talent and ensures that HR strategies are aligned with the broader goals of the business.

By integrating HR analytics into decision-making processes, organisations in the UAE can optimise their talent management strategies and ensure a motivated and productive workforce. For more insights on how to leverage HR analytics for your organisation, consider enrolling in HR courses offered by Edoxi Training Institute.

You might also be interested: Power of HR Analytics in the UAE

HR Trainer

Shabana Barshaj is a passionate and versatile HR trainer specializing in communication and soft skills development, with over a decade of experience in the UAE's training landscape. HR Analytics, KPI, Performance Management, Recruitment and Talent Acquisition are her areas of expertise. Her ability to bridge the gap between technology and soft skills makes her a valuable asset. She also conducts training workshops on MS Office Suite applications time management and stress management.

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