The proliferation of big data has changed the way businesses and the world work. I see it all the time with some of my clients — innovators who have tapped into this phenomenon to generate higher revenues and increase production. These groups embody the expression “work smarter, not harder,” and data-driven decision-making processes are the key.

So how do we leverage this idea and these technologies to make our retirement plans smarter? It all starts with measurables — that is, the metrics and statistics that detail your plan, such as average savings rates, participant age breakdowns, investment allocation by various demographic groups, match rates and so on. These measurables give plan sponsors a snapshot in time of their plan.

With this snapshot in place, it’s now time to leverage data. Comparing to the industry and retirement plan space as a whole can show a plan sponsor where their plan meets, exceeds or fails standards. From a business perspective, this information is invaluable. Not only is a sponsored retirement plan a benefit to reward loyal employees, but also to attract valuable innovators who can contribute to and drive business processes forward in an increasingly competitive global marketplace — and ultimately drive more revenue to the firm. Competitive businesses must know the benefit packages they need to offer desired candidates.

Holistic point of view

That being said, a reader might suggest that relating a benefit package to the industry isn’t exactly innovative. Let’s take it a step further and approach it from a holistic point of view. In an effort to have a best-in-class benefit package, sometimes plan sponsors can, in a sense, miss the forest for the trees. Rather, they miss the overarching goal of having a retirement plan, which is to help facilitate successful participant retirement outcomes. A plan can be best-in-class from an industry standpoint, but if your participants aren’t on track to meet their goals, the plan can’t be considered a success. Again, data mining, big data and measurables can point plan sponsors in the right direction.

Also see: "6 best practices to implement auto-escalation in retirement plans."

Referring to the snapshot of a plan, plan sponsors and their consultants can identify areas of need and then develop a strategy to correct those needs. For example, the plan’s millennial demographic may not be contributing enough or at all. Perhaps a tweak to plan design that includes auto enrollment and auto escalation is the answer. Or perhaps the data reveals that an older demographic that is on track to a reasonable income replacement ratio may be invested too aggressively and are putting their retirement at risk to a market downturn. In this case, a revised education plan teaching this group about appropriate investment strategies may prove corrective.

By understanding the measurables of their plan and leveraging data, plan sponsors will make smarter, more informed decisions to create competitive benefit packages while addressing plan-specific needs with actionable insights. These same measurables combined with a targeted action plan can then be used to track progress over time. With these improvements, plan sponsors can welcome their plans to the data age.

Ludwig, ChFC, AIF, CRPS, is an LPL Financial adviser with LHD Retirement. He can be reached at jludwig@lhdretirement.com.

This information was developed as a general guide to educate plan sponsors, but is not intended as authoritative guidance or tax or legal advice. Each plan has unique requirements, and you should consult your attorney or tax adviser for guidance on your specific situation. In no way does adviser assure that, by using the information provided, plan sponsor will be in compliance with ERISA regulations.

Securities and Advisory services offered through LPL Financial, a Registered Investment Advisor. Member FINRA/SIPC.

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