Published by Martin Willis on
Estimated reading time: 6 minutes
But it is, not only will supporting employees in saving for retirement assist with recruitment and retention and improve their financial wellbeing but it also helps ensure they can retire when they want to. If they can’t do that it certainly raises some challenges for both parties.
Delivering good outcomes for individuals will always be the focus of any pension arrangement, and an individual’s saving journey for retirement effectively becomes a path that runs parallel to and mirrors their career. Job, pay and life changes becoming the key turning points.
What this means though, is that analysis of pensions data can have uses that reach far beyond simply working out if an individual is on track to reach their retirement goals – it can be used to gain a much wider understanding of a workforce and what it looks like now and in the future. This in turn will assist with workforce planning and support.
Pension data can reflect a number of key life decisions for an individual. The most obvious of these are how and when they are likely to retire:
Whilst this data is most useful for employees with long service or relatively early on in their career (there’s no way of telling what benefits individuals have from previous employment), it gives an idea of whether an individual will draw a lump sum (smaller projected fund values) or take a secured income for life (medium fund values). The FCA’s Retirement Outcomes Review confirms that the majority of pots fully withdrawn are less than £10,000 (59%) or between £10,000 and £29,000 (29%). Large fund values are more likely to be drawn on over time.
From this it follows that individuals with smaller fund values are potentially likely to continue working either part time or beyond state pension age to supplement income. Those with large fund values are more likely to stop working earlier.
Analysis of scheme data can show what the average fund value for people retiring might be, and in turn the income that will be generated depending on how it is taken. This will help inform how and when people will retire.
Many pension providers allow members to select investment options that target taking benefits in a certain way. This gives a clear indication of how a member might draw benefits. That said, this is more of a target – the project fund value is more likely to dictate reality.
This seems like an obvious one – confirming when an individual will retire, but it can be a red herring as there is no requirement for an individual to adhere to this. Furthermore, it often is just a default, which leads us on to our five tips:
These ‘selections’ will give a good indication of how and when an individual might take their benefits, but only if actively made. One of the challenges of auto-enrolment and the defaults that it brings is that it is reduces the likelihood of decisions being made. Active engagement is preferable not just for the employees (as it will increase their chances of an outcome that meets their objectives) but it also makes data more relevant to employers.
It is worth considering the effectiveness of any engagement strategies in place to ensure that they target the specific needs of a workforce and monitoring the extent to which they drive positive or negative actions. Again, reference to data is important– it can identify areas whereby there are a lack of decisions (such as contribution choices) or potentially poor decisions (such as opting-out).
Monitoring changes in these data sets over time will evidence changing member behaviours and the effectiveness of any strategies. Once members are engaged the data will paint a much more accurate picture and become particularly useful.
Building on the idea of engagement, how do you encourage individuals to consider these matters? Pensions are by their very nature (as a future focused benefit) never going to be at the top of everyone’s agenda, but ‘teachable moments’ (points in time where someone will consider and take action in relation to their wider circumstances) provide an opportunity to make an impact.
As an example, starting a new job is a time of fundamental change, and individuals may consider their current (e.g. living circumstances, debt, savings, and health/protection benefits) and also future position (savings, health/protection benefits and pension savings). This makes it a great time to promote pension offerings and the options available to individuals, as they are more likely to consider take action in relation to joining a plan, selecting a contribution level or making an investment choice.
Auto-enrolment creates a mechanism where anyone who has opted out of pension saving has made an active decision. If people are doing this, the question is why? The obvious answer is affordability, and if individuals feel that they cannot contribute to such an arrangement there may well be wider financial concerns such as debt issues. If this situation is unaddressed, the employment of these individuals is may be unsustainable.
To a lesser degree members not taking advantage of higher matching contribution rates also gives an indication of this. Analysis of this data can inform a review and any re-design of the scheme contribution structure. It is important to ensure contributions are adequate (if an individual isn’t saving this is likely to generate problems around succession planning in the future), so increased employer contribution rates may be worth considering.
Freedom and choice (the pension flexibilities) have been in place for over three years now, and this gives us a good idea of how people are actually using their benefits, including how and perhaps more importantly when they are taking them. Providers will be able to collate information in this regard, and this will allow employers to identify trends and understand how benefits might be taken in the future. This can also be supplemented by in-house data collation in respect of when and how employees start to take retirement (including whether phased). This will help identify future turnover and allow for appropriate succession plans to be made. This can help inform and define an organisation’s whole working structure, from working from home policies to job sharing.
The pensions industry loves data analysis and drawing conclusions from this, but focusing on this relies heavily on assuming individuals make rational choices. Behavioural economics tells us this is not always the case, and the lack of understanding around pensions suggests that even if people do make rational choices these may be based on insufficient understanding of the consequences. For example, although the majority of the lump sums taken are relatively small, 12% are over £30,000 and may incur significant amounts of tax. This suggests that members are either not aware of the consequences or perhaps more likely are happy to accept them.
A workforce survey that considers employees’ views on saving for and taking benefits at retirement will provide a complementary perspective through qualitative data that gives an insight into what they actually think and why decisions are being made.