In today’s employee benefits landscape, cost control and talent management are top of mind for employers.

Balancing these goals requires employers to think holistically about how their benefit offerings will help produce desired workforce outcomes, such as retirement readiness and productivity.  

Benefits optimization is an approach to designing benefit plans and portfolios to maximize these outcomes against a given benefits budget — that is, it seeks the biggest “bang for the benefits buck.” Employers often have data at their fingertips that can provide insights into the drivers of employee behaviors, and help design plans that motivate employees to behave in a more cost-efficient way.

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The following examples explore how to optimize defined contribution plans and disability management programs to improve retirement readiness and productivity, respectively.   

Redesigning retirement plans

While many employers use defined contribution plans to help achieve retirement readiness objectives, it is up to the employees to enroll, save and invest.

To overcome employees’ inertia, employers can incorporate automatic enrollment and automatic contribution escalation. However, it’s important not to set the contribution bar too low.

The most common default deferral is 3 percent of pay, according to the Plan Sponsor Council of America, and many plans do not include automatic contribution escalation — sending a tacit signal that a 3 percent contribution level is adequate. A better approach may be automatic enrollment at a rate of at least 6 percent of pay, along with automatic escalation up to at least 10 percent, in annual increments of 1 percent. Employees would, of course, be eligible to opt out.

Employers who worry that automatic escalation increases the cost of matching contributions can help offset costs by customizing matching contributions to targeted employee populations, such as those nearing retirement age who have recently had their pension plans frozen. Companies with access to data analytics capabilities and actuarial expertise can be deliberate in allocating matching contributions in ways that optimize outcomes. 

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Companies with access to data analytics capabilities and actuarial expertise can be deliberate in allocating matching contributions in ways that optimize outcomes. (Thinkstock)

Re-thinking disability management programs

The cost of employee absence is significant, and is expected to increase.

Customized return-to-work programs can help reduce this cost and improve productivity by shortening disability leave durations. Such programs may involve making workplace modifications, designing jobs in less physically taxing ways, and partnering with physicians to develop transitional return-to-work plans.

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Data analytics can also provide the underpinnings of customized programs by identifying the most frequent and costly types of disability and durations by job title and type of work. For instance, a hospital with a high number of nurses retiring because of the physical nature of the job may develop knowledge transfer and mentoring programs that take advantage of the nurses’ expertise. This may increase talent retention and bridge the gap to retirement in a less physically taxing way that results in fewer disability leaves.

The examples above illustrate how employers might customize their plan designs to motivate desired workforce outcomes. Looking ahead, the ever-increasing availability and power of data analytics may help employers predict how their employee population will change over time, and design plans that meet employees’ needs and optimize outcomes down the road.

To learn more, read “Insights for Optimizing Your Employee Benefit Program.”

Vishal Jain is vice president of Strategy and Financial Wellness for Prudential Group Insurance. Snezana Zlatar is senior vice president and head of Product for Prudential Retirement’s Full Service Solutions business. Opinions expressed are their own.

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