Tag Archives: Gert Maarsen

Knowing participants’ profiles is becoming increasingly important

The debate about a new pension system in the Netherlands is becoming more and more complicated because of issues including solidarity, labor market flexibility, indexation security and uncertainty about the level of pension income. These subjects are complicated. The question regarding whether pension income from retirement date is high enough in relation to income received in active employment or more relevant to the spending pattern is not often mentioned in this context. The questions about how long pension is to be paid out (life-long) and how much premium participants are willing to pay for their retirement is rarely discussed.

We suspect that one of the reasons that we find these questions so difficult to answer is because we do not really know about the (ex) participants (workers, retirees and former participants with vested pensions). As a consequence, the pension debate becomes an abstract compensation and benefits discussion focused on a complicated financing component.

Having relevant knowledge about our stakeholders could provide significant benefits. If we know and understand our participants well, then

• Pensions – even without specific customization – could be fitted to stakeholders more appropriately.
• Choosing the most appropriate financing (in terms of risk, duration and reservation) could be ensured.

Getting knowledge and information about our pension stakeholders can be accomplished in various ways. This may include:

• The pension stakeholders ask the right questions at the right level of knowledge-estimated by using available data (such as salary level and job title)-and in understandable language
• Combining knowledge of our pension stakeholders with external data to gain more insight and to better understand their needs.

A good example is the correlation between education level and life expectancy of participants. The Dutch Central Bureau of Statistics (CBS) regularly publishes that the life expectancy of a Dutch man with a highly qualified education at the academic level is much higher than that of a man who has enjoyed a maximum of elementary school education. Milliman calculated that the remaining life expectancy at the age of 68 for the more highly educated group was more than two years greater than for the other group.

In practice, it appears that data about the training of individual participants is often not available to pension funds. If this information were adequately collected and stored in the near future, then additional analyses could be performed using this data. This contributes to the necessary knowledge and insight into the needs of our pension stakeholders. As a result, not only the expected duration of benefits can be determined, but also by combining this data with other available data, we could estimate the individual’s income needs. The combination of data and analysis of connections between data can create even greater insight. For example, it makes a big difference whether a participant in a retirement scheme has a physically demanding occupation or a light one, whether he travels regularly or stays at home reading, and whether he maintains a healthy lifestyle or just the opposite.

Collecting knowledge about our participants and analyzing already available knowledge or information (big data) could ensure that we design better pension schemes and that their funding takes place in the most appropriate way.

Let’s start with that today. More knowledge and insight into participant profiles helps both the employer and the performer get better “demonstrable in control” information regarding their pension commitments, provisions, and HRM policies.