As a plan sponsor, you probably spend a fair amount of time dealing with it one way or another — whether you’re gathering, analyzing, or reporting it.
And for good reason, given the intrinsic value of data-driven decision making.
Much of this data exists on a macro level, including market trends, economic reports, white papers published by asset managers, and industry benchmarks. But how well are you leveraging small data available right within your own organization?
Small Data, Big Opportunities
Data doesn’t have to be big to be meaningful. Plan-level insights derived from participation and deferral rates or financial wellness utilization metrics are likely to be more relevant and actionable to you than broad industry statistics like the median U.S. retirement account balance. After all, your participant data may differ significantly from industry or national averages, and it’s what matters most to you as a plan sponsor.
But what about even more specific data? Take, for example, the employee who tells an HR rep they adjusted their contributions after a financial wellness seminar, or the retiree who informs a benefits manager that they keep assets in the plan because of strong service? While a single comment shouldn’t dictate major plan decisions, evaluating participant-level qualitative data can reveal not just what is happening with plan performance, but why it’s happening.
Where Can You Uncover Small Data?
Small data is often hiding in plain sight, embedded within everyday interactions and operational details. Key sources, keeping in mind anonymous collection to protect privacy, might include:
- Utilization metrics, such as the most-read financial education blogs or most-accessed online retirement planning tools.
- Employee feedback collected from HR and benefits surveys, onboarding sessions, and exit interviews.
- Questions employees ask during retirement planning sessions. Even casual encounters can yield meaningful information, such as when an employee mentions delaying retirement due to worries about inflation or expresses confusion about their investment choices.
Using Small Data
Small data can help you form hypotheses about new type(s) of financial education and support to offer. It can also help shape participant “personas” or cohorts based on shared financial needs or attitudes rather than broad generational labels. If you notice a trend in small data, the next step could be conducting micro-surveys – or brief one-question pulse surveys — to get real-time feedback from a larger subset of employees. Insights from these assessments, combined with other small data points, can help you refine messaging, adjust plan features, and develop targeted interventions to boost engagement.
Plan sponsors should also consider sharing small data with their retirement plan advisor, who can then explore findings more directly in group and individual sessions. Advisors can provide additional context, validate trends, and suggest adjustments that may be beneficial. By thinking beyond benchmarks and zooming in on small data, organizations can better gauge participant needs and take relevant, meaningful action to help improve plan outcomes.
