Future of an Ageing Population
gs-16-10-future-of-an-ageing-population
gs-16-10-future-of-an-ageing-population
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Box 2.1: Special circumst<strong>an</strong>ces relating to Small <strong>an</strong>d<br />
Medium Enterprises (SMEs) <strong>an</strong>d older people<br />
Certain types <strong>of</strong> employment may be accomp<strong>an</strong>ied by specific challenges<br />
when addressing barriers to working longer. 41% <strong>of</strong> workers aged 65<br />
<strong>an</strong>d over are self-employed, compared to 15% across the whole working<br />
population 49 . A third <strong>of</strong> workers in SMEs are over 50 50 . Both are becoming<br />
more common types <strong>of</strong> employment across the whole population 51 . SMEs<br />
may lack the resources or scale needed to provide training 52 or support<br />
the ch<strong>an</strong>ging needs <strong>of</strong> older workers, for example to implement major<br />
health initiatives <strong>an</strong>d provide occupational health support 50 . Similarly the<br />
self-employed, particularly sole-traders, may face difficulties due to a lack<br />
<strong>of</strong> support services 32 .<br />
2.4 The import<strong>an</strong>ce <strong>of</strong> skills to the ageing workforce<br />
There are broader shifts in the labour market which are vital to underst<strong>an</strong>ding<br />
the implications <strong>of</strong> <strong>an</strong> ageing population for work <strong>an</strong>d productivity. Import<strong>an</strong>t<br />
trends include the growth <strong>of</strong> the service sector, computerisation, globalisation,<br />
<strong>an</strong>d increasing workforce diversity. Perhaps the most signific<strong>an</strong>t driver <strong>of</strong><br />
ch<strong>an</strong>ges to the future world <strong>of</strong> work will be adv<strong>an</strong>ces in technology, such as<br />
automation, machine learning, big data, the internet <strong>of</strong> things <strong>an</strong>d the digital<br />
economy 53 . These ch<strong>an</strong>ges may affect how people work, where they work <strong>an</strong>d,<br />
in cases where functions become fully automated, whether they work at all.<br />
Some <strong>an</strong>alysts suggest 35% <strong>of</strong> jobs in the UK are at risk from automation 54 ,<br />
with certain sectors particularly vulnerable (see Figure 2.7). The rates <strong>of</strong><br />
ch<strong>an</strong>ge, the types <strong>of</strong> jobs that are replaced <strong>an</strong>d the extent <strong>of</strong> job creation<br />
through new technologies are all uncertain. However, evidence suggests that<br />
lower paid jobs are five times more likely to be replaced th<strong>an</strong> those with higher<br />
pay. In a study <strong>of</strong> future employment in the USA, jobs requiring high levels <strong>of</strong><br />
creative or social intelligence were at much lower risk 54 .<br />
As working lives get longer <strong>an</strong>d the pace <strong>of</strong> ch<strong>an</strong>ge increases, it is likely that<br />
individuals will have to adapt to more frequent <strong>an</strong>d signific<strong>an</strong>t ch<strong>an</strong>ges during<br />
their working lives. One <strong>of</strong> the key determin<strong>an</strong>ts <strong>of</strong> older workers’ employment<br />
<strong>an</strong>d productivity will be their ability to adapt to these ch<strong>an</strong>ges, including retraining<br />
<strong>an</strong>d re-skilling H , particularly as early life education may not provide the<br />
skills to sustain longer <strong>an</strong>d fuller working lives.<br />
H For example, the Department for Work <strong>an</strong>d Pensions Fuller Working Lives strategy describes the<br />
import<strong>an</strong>ce <strong>of</strong> three Rs - Retain, Retrain, Recruit.<br />
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