Rewards Analytics: Demystifying the HR challenges

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“All people decisions at Google are based on data and analytics.”  – Google People Analytics

Analytics is the buzz word today and also in my view one of the most
trending but least understood topics. Though Analytics sounds to be complex, it has a very simple definition: “Converting available data into actionable intelligence for
deriving meaningful insights”.

“HR Analytics has a wide range of application right from employee engagement simulations to predictive recruiting models. However, a very interesting aspect is to explore and understand the use of Analytics in the field of Compensation and Benefits i.e., Rewards.”

The various HR processes generate huge amount of data in form of hiring metrics, engagement surveys, performance reviews, benchmarking, demographics and attrition trends, exit interviews, benefits utilization and costs etc. HR Analytics has a wide range of
application right from employee engagement simulations to predictive recruiting models. However, a very interesting aspect is to explore and understand the use of Analytics in the field of Compensation and Benefits i.e., Rewards.

Rewards Analytics: Overview

  • Almost every Compensation and Rewards Leaders needs to answer a
    few basic questions:
  • Is the reward strategy helpful in attracting, retaining and motivating
    the right talent?
  • What are the key drivers of engagement?
  • How to offer cost efficient, forward looking, sturdy and tailor made
    rewards solutions?

Traditionally, most of the answers to these questions were either based on the gut of the leaders or by leveraging backward looking historical data analysis. However, in the current VUCA world, Rewards professionals are expected to provide actionable insights rather than
just dashboards and metrics. They are expected to be forward looking in approach in order to build predictive talent models to help the business anticipate and prepare for the talent issues of future.

As per the various Data Analytics Maturity Models there are typically 3 stages:
1. Tracking & Operational Reporting
2. Advanced Reporting & Analytics
3. Predictive & Prescriptive Analytics

Most of the HR & Rewards function are at the 2nd stage of Advanced Analytics and the need of the hour is to move to the next stage by creating predictive models for producing proactive actionable insights.

Typical Application in Rewards function:

  • Correlation between Pay and Employee engagement: Establish
    how strongly factors like pay level, pay mix and the compensation
    delivery instruments are correlated with engagement and
    performance levels. The insights help in calibrating and fine tuning
    the compensation strategy and systems.
  • External vs Internal Competitiveness: Market surveys should always be reviewed in the organizational context to obtain a holistic view. Hence, analytical techniques come handy for pitting the market data against the various internal metrics for validation.
  • Retention analysis: By analyzing various aspects of compensation by segmenting workforce based on various factors like skills,qualification, demand etc. valuable insights can be obtained for building predictive retention models for critical talent.
  • Consumerization of Benefits: Employee benefits are no more onesize fits all. Preferences change with life stage, location, job profile, marital status etc. Hence, organizations need to keep a constant eye on the utilization trends, employee needs, external environment etc.Analytical techniques can help deciding on the benefits portfolio based on the customization insights and the cost-benefit analysis.

Focus Areas:
Based on the organization’s current stage in the maturity cycle, HR leaders should focus on the below-

  • Building or acquiring capability for performing analytics
  • Asking the right questions to seek the right answers
  • Quality and reliability of data sources
  • Compatibility with other HR systems to share data in real-time

Conclusion:
Rewards Analytics is a great tool for enabling business leaders make the right pay decisions. However, since human behavior is a complex subject, it cannot completely replace the human vision, gut and insights.

Having said that, for Rewards Analytics there is still a long ground to cover.

Keep the seat belts on, the journey has just started.

By- TUSHAR CHAUDHARI- Vice President-International Compensation & Benefits Specialist at BNY Mellon.

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