The last twelve months have borne witness to some of the fastest and most profound changes to the workforce in decades. It’s been impossible to miss conversations about the short and medium-term impact of factors such as increasing automation, economic uncertainty and the COVID-19 pandemic on ways of working here in Britain, and around the world.
There’s little doubt these factors will be viewed as historical markers that provide context to the emergence of a set of new societal norms, particularly in terms of the way in which people work and develop their careers. But our fascination with discussing the future of work in this contemporary context belies the far more significant, long-term change to the UK workforce that has been well under way for at least a decade.
An ever-expanding skill gap
In 1975, Intel co-founder Gordon Moore predicted that computing power, speed and efficiency would grow exponentially year upon year, whilst also becoming equally more affordable. Known today as Moore’s Law, this time–proven theory explains how and why technological development has continually accelerated since the dawn of the computer age – to the point where the time between major technological eras has been cut from generations to a matter of years.
However, we are now reaching the stage where new technology is being developed and adopted faster than the skills needed to use them can be learned and applied. As a recent McKinsey report finds:
“The adoption of automation, along with technologies such as artificial intelligence (AI) and the Internet of Things, is likely to unleash profound structural shifts in the UK workforce—which will be amplified by other megatrends such as the aging population. As a result, demand for occupations such as managers, technology specialists, and health professionals could rise nearly 20 percent by 2030, while demand for administrative and manual roles could decline just as steeply.”
The report outlines two major looming issues facing the UK economy: a widening skills gap and an increase in redundancies due to employees lacking the required skills to fill these new jobs. For employers and employees alike, tackling both of these issues will require a major reconsideration of career development – one which takes into consideration the increasingly transient nature of demand for skills.
Present solutions to future problems
Today, companies typically recruit new staff either to fill existing job roles and provide the capacity required to sustain growth, or to fill new job roles and diversify the skillset of their workforces. Logistically, this approach makes sense, as it allows companies to be specific with what they are looking for and cherry-pick those with suitable traits. But is this an economically viable way to solve the problem? Perhaps not. Taking into account the time and money invested in conducting interviews, training new hires and administrative onboarding, the benefits of recruiting new talent begin to slowly ebb away. And that’s before you consider the costs that can be incurred from redundancies when employees’ skills no longer match those required to fulfil their employer’s current job roles.
To find real solutions to the UK’s talent shortage, a company need look no further than its existing workforce. They must review both its current level of skills, and the potential impact that new technology or other economic factors will have on it. Using this data, companies can then extrapolate a method by which employees can be transitioned out of roles that can be automated and into more relevant, in-demand roles. This process – also known as the ‘job corridor’ marks a new approach to career development – one focused on agility and adaptability, rather than linear progression.
Retain, retrain and redeploy
The effective use of job corridors to limit redundancies and address talent shortage issues relies on the three R’s: retain, retrain and redeploy. Crucially, these three actions are facilitated by data which companies already have access to, such as capacity planning, HR reports on productivity and efficiency and publicly available economic data, such as the UK Department for Business Innovation and Skills’ latest report on digital skills.
An example of the job corridor being used in practice was recently demonstrated by the UK offices of global insurance company Zurich. Comparing its current workforce to current economic and technological trends allowed the company to identify 270 jobs in robotics, data science and cybersecurity that could go unfilled by 2024 if employees were not reskilled to take those roles. Having anticipated the future impact of technology, Zurich invested almost £1 million into reskilling over 3,000 of its UK employees, using a precise approach that made best use of the skills that their existing talent possessed. For example, if demand arose for a new data engineer role to be filled, they now need look no further than within their existing workforce to find the perfect candidate.
A modern solution to a modern problem
With each historical era comes both problems and new technological solutions to address them. Every time a machine becomes capable of conducting tasks previous assigned to a human, it’s only natural to envisage long lines outside job centres and huge shortages in available talent to fill new roles.
However, history shows us that the workforce always adapts to advances in technology. To move forward, we mustn’t fall into the trap of viewing technology as the problem, but something to be incorporated into the solution. For example, intelligent analytics platforms to support the retain, retrain and redeploy process means this can also be done without the heavy lifting that would be normally required were it to be done manually.
As a result, not only can companies save themselves the costs of unnecessarily reducing their headcount, and their employees losing jobs, but they can also save a huge amount of time designing a targeted reskilling strategy. After all, talent shortages are some of the most pressing problems in the modern era; a modern solution was always going to be the answer.
