Analyzing and Interpreting Workforce Age Demographics

“Most executives in developed nations are vaguely aware that a major demographic shift is about to transform their societies and their companies and assume there is little they can do about such a monumental change.” – Strack, Baier, Fahlender, Managing Demographic Risk, Harvard Business Review February 2008 

8 years after this article was published, it is fair to say that this demographic shift is well under way. Of course that’s the very nature of age, which is why analyzing this dimension of workforce demographics is worthy of frequent attention. As important as gender, race and (in some countries) religion are as subjects for analysis and action, with a few exceptions, those dimensions tend to change with employee turnover. Age, on the other hand, comes to us all… So what issues are affected by the demographics of your workforce? The one that immediately springs to mind, and forms the primary subject of the HBR article above, is the risk relating to an ageing workforce.

However, there are others – the difficulty of retaining talented young people in rapidly developing regions, the effect of property prices on employability in some cities, and so on. It’s not my intention here to discuss the global trends that give rise to these issues, nor to go into detail on the implications, but rather to talk about how you can look at the age demographics of your workforce to draw conclusions and take action.

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As with any business issue, the first step to taking effective action is having reliable data to interpret. One of the many benefits of implementing a global HCM solution is the immediate availability of demographic data to slice and dice. Some important dimensions to include in such a report are:

  • Location – an important factor but beware of assuming that issues relating to an ageing population are restricted to the so-called developed world – for example, research has shown that China’s manufacturing worker population over 50 will more than double in the next 15 years
  • Job profile/family – there can be particular problems with blue collar workers who, as they age, may not be able to perform more physically demanding jobs
  • Seniority level – often in companies (like Kainos) with a predominantly younger workforce, the smaller number of older workers tend to be concentrated in the top management positions. Is there a sufficient pipeline of younger talent coming through?
  • Line of business -– clearly, where a company has very different types of business, the motivations, economic situations and issues faced by staff in those will also differ – and hence the causes and effects of age demographics will differ

It’s also important to decide what groupings to use for your age categories. In a HCM system like Workday, you are able to define your own groupings, for example:

  • Under 20s
  • 20-35
  • 35-55
  • 55-65
  • Over 65

The flexibility provided means you can choose the categories based on the factors that particularly affect your business. For example, recent changes to personal pension rules in the UK mean that workers can access their pensions at any time from 55 on, whilst the evolution of the state pension age sees it rising over the next decade or so to 67 and may rise further in future. So a particular category for UK companies to keep an eye on might be those staff between 55 and 67 who may be considering early retirement if their pension entitlements enable them to do so.

Interpreting the data into actions

The first point to mention here is that it is critically important to consider the risk of age discrimination based on conclusions drawn from this data.  The purpose of this exercise is not to favour or disadvantage any employee or category of employee on the grounds of age, but simply to acknowledge the facts and mitigate any risks to the organisation. The second point is to ensure that external factors are taken into account – for example, if large numbers of young people are moving to an area that has experienced an ageing population and workforce, this could mitigate the risk, always assuming that they have skills and knowledge suitable to the nature of the work. Also to be considered are future business plans – it may not be a big problem to have an ageing workforce in a business which is declining and may close, whereas business plans to rapidly grow activities that are in high demand could be drastically affected by workforce demographics. Another consideration is the “time to effectiveness” of staff in particular jobs. Work that needs significant experience before the worker is fully effective or has a long qualification period requires longer term planning, and trends need to be identified earlier.

Workforce ageing is universal and unavoidable, but timely, considered action can mitigate its effects. Good quality demographic data from an HR system with powerful analytics capabilities provides a sound basis for interpretation and action.

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