Employers are increasingly interested in financial wellness programs—and the expertise retirement advisors have to offer. Combining that expertise with data provides a valuable means for advisors to help an employer understand its employees and uncover their specific financial wellness needs.

While introducing this type of workforce analysis to an already overwhelmed benefits committee may raise some eyebrows, it’s not as complicated as it sounds.

Champion the Value of Employee Data

For an employer who wants to begin providing financial wellness benefits to its employees, existing workforce data provides the perfect starting point when they don’t know where to begin. By analyzing the data, and segmenting a workforce, a picture is created of that company’s unique employee base. Fortune 500 companies have long utilized internal data to improve career pathing initiatives, customer service programs, logistics, internal reporting, and human capital financial wellness programs.

Because basic employee data may come from the company’s payroll provider, insurance carrier, and 401(k) record keeper, some employers may be hesitant to share it. Talk to them about how critical they find it to have information about their clients and competitors for use in making business decisions. This same process allows for the use of anonymized employee data for making informed decisions about the financial wellness benefits they want to offer their employees.

Capitalize on Company-specific Data

Employers have access to all sorts of information about the financial well-being of their employees. They’ll have details about employees’ 401(k) participation rates, average contributions, and matching contributions, as well as health information such as prescription drug use and number and types of claims.

Depending on the company, it will likely be able to share other data about its employees such as age and stages of life, company tenure, location, salaries, and education level. This type of information will provide insight into life events that can be overlaid across the workforce—the likelihood of marriage, children, home ownership, the need for caregiving services, and years to retirement. This information can be used to better understand the financial challenges facing employees.

Supplement with External Data

Even if a company doesn’t have a lot of data internally, there are data sets available that provide information on employees with similar demographics that can be used to supplement company-specific data.

National and regional information can be leveraged to learn even more about a workforce—the cost of living in a certain market, what the averages are in student loan debt, years to retirement, percentages of homeownership, when people buy homes, and percentages around when people typically get divorced.

Big data has evolved to a point where you can take the concepts used to work with larger, more complex data sets and apply them to smaller data sets. For example, an employer with a college-educated workforce can reasonably assume that on average 34 percent of 18- to 29-year-olds have student loan debt and that 35-year-olds have an average student loan debt of $42,600.¹ Having information like this points directly to financial wellness solutions that can help those employees.

Complete Workforce Segmentation and Develop Personas

Gathering and extrapolating the relevant internal and external data will allow an employer to segment its workforce and provide a more targeted approach to benefits delivery.

From this segmentation, personas can be built for each particular type of employee. The attributes assigned to these personas can be used by the employer to help predict their needs and preferences. Done with enough detail, these personas can be used by the employer beyond the determination of benefits to improve other aspects of employer-employee relations.

To think about the use of personas in action, let’s look again at the example above regarding student loan debt. An employer with a young, college-educated workforce can reasonably assume that a student loan repayment plan would appeal to its employee base and serve as a valuable perk for recruiting and retention.

Insights into Advisor Involvement

The prevalence of generalized data does make it tempting to skip the work that would enable an employer to optimize solutions using their own readily available data, technology, and expertise. But committing to the initial investment of gathering current employer-based data allows for an opportunity to be prescriptive to the specific employee base and their family.

While this type of work is mostly being done at the largest U.S. companies today, there are steps retirement plan advisors can take to bring it to smaller markets.

• Help employers get comfortable in understanding that they—not the various vendors—own their data to use as they see fit and commit to gathering and using all the data elements necessary to make optimal program decisions.
• Assist in breaking down the walls that exist in human capital consulting. Aid employers in making intelligent plan design decisions by gaining an understanding of their entire compensation and benefits package. This commitment to data allows retirement plan advisors to ensure individuals are optimizing their benefits and discretionary income. Not knowing the employee and their dependents’ current and future health spend makes it difficult to advise them on their HSA contributions and therefore on their 401k. Compensation and financial wellness programs cannot be based on specific benefit silos and product outcomes alone.
• Remind employers that data from deployed programs needs to be collected so its effectiveness can be measured against the specific area being addressed as well as evaluated for other benefits or unintended consequences.

Data as a Differentiator

When I started on this journey to help employers improve the financial wellness of their employees, nobody had the technology, access to data, or understanding that exists today. I’m encouraged by the number of clients who are using the holistic application of data to drive new designs and better outcomes every day. While penetration is still quite low, advisors can differentiate themselves by embracing this new role and encouraging employers to embrace these techniques as well.

Data alone won’t provide everything an employer wants to know about the best financial wellness options for their employees—that’s where you come in. It takes a human element combined with the data and tools to provide the financial wellness benefits that will make a difference to employers and employees.

Financial technology and data are poised to help employers better understand their employee base—where they are struggling, and what solutions are best for them. Retirement advisors can serve as the conduit to helping employers make the most of these tools while at the same time provide a tactical means of expanding your practice beyond being a source for retirement plans.

DISCLAIMER: The eMoney Advisor Blog is meant as an educational and informative resource for financial professionals and individuals alike. It is not meant to be, and should not be taken as financial, legal, tax or other professional advice. Those seeking professional advice may do so by consulting with a professional advisor. eMoney Advisor will not be liable for any actions you may take based on the content of this blog.

The views and opinions expressed by this blog post guest are solely those of the guest and do not necessarily reflect the opinions of eMoney Advisor, LLC. eMoney Advisor is not responsible for the content, views or opinions presented by our guest, nor may eMoney Advisor be held liable for any actions taken by you based on the content, views or opinions of the guest.

Source:

¹ Hanson, Melanie. “Student Loan Debt by Age.” Education Data Initiative, 2022. April 19. https://educationdata.org/student-loan-debt-by-age#:~:text=1%2Din%2D3%20adults%20under,group%20to%20have%20student%20debt.

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