How Data Analytics Can Help You Make Retirement Plan Decisions

If you’re not using data analytics to help you make progress toward improving participant outcomes, then you could be missing out on a key component of plan governance. Data analytics are becoming a meaningful part of defined contribution plan governance for retirement plan fiduciaries.

Data analytics can provide detailed information on different participant segments and help sponsors recognize pain points in their plans.

Defining Pain Points

Think about using detailed analytics to break down plan data into specific employee segments based on key factors like age, job category and tenure. Analytics highlight the employees and groups most at risk of retirement savings shortfalls, giving you useful insight on the tools and strategies that could best help them. Once you assess the analytics, it's time to apply them to your plan.

Tactics for Retirement Readiness

Plan Design

Employers can use information from analytics to make changes or establish plan design features that can nudge participation at more impactful rates.

Plan Design options to consider:

  1. Low participant rate: Reenroll employees not participating
  2. Low deferral rate: Implement a higher automatic enrollment default rate
  3. Low deferral rate: Encourage auto-escalation of those enrolled but not saving enough
  4. Low deferral rate: Encourage participants to defer more by stretching the company match
  5. Improper asset allocation: Reenroll all participants into the plan's QDIA

Plan Tools

Positive employee behavior could be driven by using detailed analytics to help select plan tools and technology whether you want to increase participation, savings, tax efficiency, investing, budgeting or provide other education. With the help of your financial advisor, plan sponsors can develop tangible goals, scorecards, wellness programs and more to track progress going forward to improve plan governance and help participants achieving retirement readiness.

Plan Sponsor Take Away

In a recent white paper, Willis Watson Tower stated, "We believe plan-wide statistics on mean or median participation rates, balances or contributions rates measure aggregate data on all participants but offer little in the way of insight into retirement adequacy and meaningful benchmarks for individuals or segments of the population."(Emphasis added). Therefore, today, when most retirement plan committees look at roll-up 30,000 foot level data, data analytics will help you peek into the effectiveness of your plan.

With the proper analytics, plan sponsors can understand their employees' needs, then adjust and develop customized plans, enhanced plan features and communication strategies and provide tools and technology to engage employees in positive behaviors. Analytics highlight the employees and groups most at risk of retirement savings shortfalls, giving you useful insight on the tools and strategies that would best help them reach retirement.

1Willis Towers Watson. “The defined contribution plan proposition: Retirement readiness.” September 2018.

This information has been provided by 401k Marketing. The views expressed are those of the author, are subject to change and are not those of INTRUST Financial Corporation or its affiliates. The information is general in nature and is not intended to be, and should not be construed as legal or tax advice. In addition, the information is subject to change and although based upon information that INTRUST considers reliable, is not guaranteed as to accuracy or completeness. INTRUST makes no warranties with regard to the information or results obtained by its use and disclaims any liability arising out of your use of, or reliance on, the information. Past performance is no guarantee of future results.

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