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Survey Finds Unbalanced Rewards Decision-Making

July 9, 2012

By Haig Nalbantian and Wendy Hirsch

Many organizations’ pay decisions may be unbalanced as they spend too much time focused on external comparisons and not enough time looking internally to measure and assess the actual workforce and business impact of their total reward practices.

According to new research by WorldatWork and Mercer:

• Most compensation professionals use internal and external benchmarking (95% and 90%, respectively) to make pay decisions in their organizations. Fewer are using more sophisticated analytical techniques such as projections, simulations and predictive modeling – 80%, 64% and 43%, respectively.
• Yet, more than two-thirds of participating respondents indicate that they possess the skill levels to perform sophisticated analytical techniques.
• And, three-fourths say their top executives and HR leaders have requested workforce analytics (e.g., projections, simulations, predictive modeling).

Undoubtedly, a disconnect exists between the abilities and outcomes of the compensation function – comp professionals are relying heavily on less sophisticated techniques for pay decisions, yet clearly have the know-how to use more involved methods. More sophisticated analytics allow organizations to make better, more fact-based decisions.

It’s ironic that a data-rich function like compensation would risk being ‘left behind’ as internal labor market analyses and fact-based decision-making become the norm in other areas of HR

In a true total rewards environment, key variables reflecting and affecting workforce capabilities like education levels, competencies, and training and development are absolutely necessary to determine the efficacy of rewards. Organizations focusing only on the motivational aspect of rewards and neglecting the broader effect rewards have on securing the right workforce – what economists refer to as the ‘selection effect’ – are being short-sighted about the role of rewards in driving talent development and business performance. They’re missing half of the equation, sometimes the most important half.

To effectively implement a total rewards philosophy, compensation practitioners must embrace a real culture of measurement – one that drives them to work with a broader set of data and utilize causal modeling methods powerful enough to address the complexity of the reward decisions with which they are charged.