Importance of HR Analytics to Improve Employee Rewards System

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Importance of HR Analytics to Improve Employee Rewards System
Employee Rewards consists of - all the monetary, non-monetary and psychological payments that an organisation provides for its employees in exchange for the work they perform

AI and Machinery Learning Models are the most complicated when implemented on Employee Rewards System.

‘Employee Rewards consists of – all the monetary, non-monetary and psychological payments that an organisation provides for its employees in exchange for the work they perform.’

Crafting a Tailored Rewards Strategy is not as simple as these statistical equations

Simple Linear Equation

α ^ = y ¯ − ( β ^ x ¯ ) , β ^ = ∑ i = 1 n ( x i − x ¯ ) ( y i − y ¯ ) ∑ i = 1 n ( x i − x ¯ ) 2 = s x , y s x 2 = r x y s y s x . (A linear approach for modelling the relationship between a scalar response and one or more explanatory variables)

Or

Log-Logistic

b1 – ln (1 + b2 * exp (–b3 * x)) as need to deal with non-monetary and psychological need of employee apart from monetary demands.

Equation Vs Real challenges

The marketing department has the luxury of burning out the budget on customer acquisition and client retention by implementing the A/B Testing but this is not the case with HR department.

Getting back a lost client is possible but getting back your lost Talent is next to impossible with the ever-changing business dynamics.

“Underappreciation is the core cause and effect is employee quitting the organisation”

66% of employees say they would “likely leave their job if they didn’t feel appreciated.” Among millennials, the number of employees who’d leave if unappreciated jumps to 76%.

Millennials are becoming the dominant generation in the workforce, with a unique set of characteristics and needs.

Crafted by Data: A Tailored Rewards Strategy

Once you have all the blocks of the game, it is easier to craft the rewards that suit your employee. By clustering employees based on attributes such as age, income, life stage, career level, and certain preferences, HR can create distinct groups – or personas – that should be offered different combinations of rewards.

Understanding the matrix: Job Satisfaction and Environment

Big Questions

  1. Is your reward strategy really motivating best performers?
  2. Do you understand the critical drivers of employee engagement?
  3. How do you tailor made reward strategy under dynamic situation?

Role of Big Data

To answer all these questions and more, we need to understand the growing role of big data in reward strategies and how the use of such analytic techniques can help uncover stable correlations within particular populations.

Analysis of Cause and Effects

Understanding the correlation matrix will help you to focus on reward strategy in the right direction.  These will, in turn, help us to refine reward design to better achieve its objectives. Reward Strategies have a big impact on organizations as they influence who we recruit, how they behave, and thus impact the talent strategy, which in turn impacts business results.

Here are simple methods to establish the foundation of HR Analytics.

Engagement Drivers

What is the impact of financial and non-financial rewards on employee engagement?

As per the study done by WorldatWork with 6300 professionals across the United States, Canada, and Western Europe, it was found that base pay and benefits had the weakest relationship with the company’s ability to foster levels of employee engagement.

Whereas, Leadership quality has the strongest relationship with employee engagement.

Data Analytics

Data analytics helps in fine-tune pay packages to the right kind of drivers. The above theory reveals that appointing leaders who have the capability and demonstrated their ability to engage employees might be more important than just adjusting base pay to keep up with the competition.

Reward Theory

We need to understand the required different types of employee mix and required talents that will drive profitability for the organisation.

Performance Differential

Every organisation has its own tools and methods to calculate the value of performance and calculating the value of Top performer itself is the most challenging task itself.

Often, it is found that calculating performance differential between an exception and an average one was more than 100 times based on any given tool or method.

Important: Proving the value of top performers convinces executives to provide the resources necessary to hire, retain, and develop extraordinary talent.

Attrition Driver

Attrition rate or Employee turnover rate is only the gauge meter.

Slice and Dice Turnover- Key indicators to review turnover for critical jobs and employee tells the preferences for different types of benefits and reward structure required to stable the gauge meter.

Important: How can we slice and dice data to review turnover for critical jobs or groups of employees? Are we able to use data analytics to understand employee preferences for the types of benefits or reward structures that will lead to retention?

Benefits Analysis

Engagement measures, attrition, absenteeism, and employee surveys

Data-driven metrics- In this type of analysis, data-driven metrics such as engagement measures, attrition, absenteeism, and employee surveys are monitored together with benefit take-up rates over time so that the impact of benefits can be monitored and benefit spend justified.

Benefits of Data Analysis

# Economical – cost reduction

# Magnification of Employee Engagement

# ameliorate Communication strategies

Before you kick off your analytics expedition, begin with the most compelling business subject. Analytic techniques help you in finding the patterns and correlations for the given subject. This will help you better craft a reward and benefits package that will attract, retain and reward your top talents.

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