For employers looking to optimize their rewards programs, it’s not enough to just analyze employee preferences and compensation costs. Workforce data and taking an expanded view of total rewards are the keys to finding out which rewards truly drive retention, engagement and productivity.
Many organizations are finding the competition for talent to be fierce, as labor markets tighten globally and business strategies are upended by disruptive technologies changing the skill-sets needed for the future. Meanwhile, rewards budgets have been relatively stagnant over the last five years, leading workers to be increasingly dissatisfied with employee rewards programs and wanting more from their employer.
Mercer’s 2018 Global Talent Trends Study found that only two in five workers said their employer had a compelling employee value proposition – a concerning statistic given the current talent market.
That said, many employers are reviewing their total rewards strategy, as a way to strengthen their employee value proposition for both attracting and retaining employees.
Our recent Total Rewards survey of nearly 700 organizations found that 59% of employers are planning to revisit their total rewards strategy in the next six to 18 months for the entire organization, and another 18% are planning to reconsider their strategy for specific job families (e.g., sales, engineering).
A standard approach to getting started has been for employers to conduct a “total rewards optimization” analysis for developing a new employee rewards strategy. This method is often accompanied by a sleek modeling tool and utilizes two inputs to make rewards strategy decisions:
Based on these two inputs, an analysis is done to identify the “optimal” balance of compensation and benefits and employee preferences perceived to be of the most value.
On the surface, this approach seems to simply solve a complicated equation about how to allocate total rewards investments. But it all is predicated on the belief that what employees say they want is how rewards should be allocated – and is that the full picture?
This method and these tools are typically not enough to effectively evaluate total rewards programs for two main reasons:
1. There is a disconnect between employee preferences and business outcomes.
These tools often claim that if rewards are maximized based on employee preferences, this will, in turn, lead to better business outcomes such as employee retention, engagement and performance. However, our research shows there is often a disconnect between what employees “say” they value and what they “do”.
For example, compensation is nearly always rated #1 in employee preference surveys, but our client studies frequently show that the impact on business outcomes is not as strong as other reward elements. We recently worked with a client who found that an increase in base pay of $10,000 across their workforce had only a 3% reduction in turnover probability, but the autonomy of a manager (as measured by the span of control) had a 34% reduction in turnover probability.
2. “Optimization” typically only considers programs with readily quantifiable costs.
Typically, optimization tools require a “cost” for the reward program as an input. As a result, the optimization equation is limited to contractual rewards such as compensation and benefits. Missing from these tools is the capacity to evaluate the value of additional employee rewards, such as opportunities for career growth and flexible working policies. These elements of the employee value proposition while difficult to quantify, can often be the most effective differentiators for an organization.
True total rewards optimization cannot be narrowed down to a simple equation based on two inputs, as there are more factors to consider. Instead, we recommend using workforce data to help define the right approach to maximize value to the organization and create a compelling employee value proposition. Two ideas to consider:
HR has access to an abundance of historical data about their workforce and can track outcomes like retention, engagement and productivity. As a result, leaders no longer need to “guess” what will drive business outcomes. With sophisticated statistical models, we can use this data to prove this and also predict the impact of potential actions.
For example, what effect does receiving an above average merit increase have on engagement? Does offering a retirement program result in better retention? Making strategic rewards decisions based on evidence provides a stronger basis for changes in rewards investments.
The contractual elements of reward and recognition programs can only reach so far. Sure, these are table stakes to remain competitive, but they are expensive and easily replicated by competitors, so attempting to differentiate your employee value proposition on these elements alone is often ineffective.
Instead, organizations should consider a more holistic set of rewards, focusing on experiential and emotional rewards such as career development, wellbeing and purpose. These have proven to be more effective in creating a compelling experience to make the right talent want to join, stay and deliver their best performance for your organization.
Taking a fact-based, holistic approach to optimizing your rewards strategy will enhance the success of the program. This ensures that you have the right reward elements in place to drive the right business outcomes while also motivating and engaging employees.