Our new measure emphasizes criteria that plan officials can control.
Plan sponsors and providers understandably want to measure the effectiveness of the defined-contribution plans they offer; plan participants should want to monitor their plans all the more. But not all evaluation methodologies measure up. A retirement plan should be evaluated on criteria over which those responsible have some authority or opportunity for influence. For example, if a team of 55-year-olds enters a plan with zero retirement savings, that shouldn’t say anything about how well the plan is run or has prepared its participants for retirement.
But the most common defined-contribution-plan measures in use do just that, allowing two factors in particular—participant age and plan tenure—to have a significant impact on analyses of plan effectiveness.
In today’s dynamic workplace, the average employee tenure is approximately five years. Tenure, which plan officials have little if any control over, has a significant impact on the perceived success of a plan and its participants. For example, a plan with a high savings rate but low tenure may appear to be ineffective if participant balances were especially low when employees joined the company. Judging the plan on what its administrators can influence (the high saving rate) instead of what they cannot control (turnover) would yield a much more meaningful rating.
To address these shortcomings, we created a methodology for estimating the effectiveness of a plan at the individual participant level, which in turn can be rolled up into what we call a Retirement Plan Effectiveness Score. We use robust estimation techniques to determine the appropriate retirement plan “target balance” based not only on age and plan tenure but also gender, compensation, and other variables. Comparing the participant’s current balance to a customized target balance yields the relative funded status, and combining these individual participant metrics produces the Retirement Plan Effectiveness Score.
Our approach overcomes the weakness of the most common approach to evaluating retirement plan effectiveness—estimating the probability of a participant successfully accomplishing his or her retirement goal—by focusing on factors that plan administrators can influence and controlling for factors such as age and plan tenure. The new framework allows for meaningful comparisons across plans and through time.
Tenure, Age, and Out-of-Plan Assets
Using widely available tools, plan sponsors cannot accurately answer the basic question, “Will our participants have a successful retirement?” Common “success” metrics—such as retirement replacement rates, which is the percentage of a participant’s income he or she will be able to replace at retirement, and a success analysis, which estimates the probability the participant will be able to maintain the same standard living for retirement—require a significant number of assumptions that are beyond the influence, and knowledge, of the plan sponsor. A variety of inputs are required to estimate retirement readiness, some of which the plan sponsor has information on (such as current plan balance, compensation, plan savings, etc.); however, most plan sponsors have no information about a participant’s savings or assets outside the plan.
Tenure, which varies significantly across employers, plays a key role in measuring plans. According to the Bureau of Labor Statistics, the median tenure for wage and salary workers in the United States was 4.6 years in January 2014. Although not perfectly equal, employment tenure and plan tenure tend to be similar.
To study the effects of tenure on retirement plans, we obtained data for 186 401(k) plans with at least 50 active participants, representing 135,322 participants. This dataset came from one record-keeper, but there is nothing to suggest any unique biases or that it is not a representative sample of typical plans and participants. Analyzing this data, we found the median and average years of participation are eight and six years, respectively. The average is greater than the median due to the positive skewness of the distribution. (When people stay, they stay longer than would be expected in a normal distribution.) There is clearly a significant deviation in employee tenure across plans, with a standard deviation of approximately three years.