Adaptability of skills
Human adaptability, or rather its shortcomings, was a running theme of a recent speech by the Conservative MP Robert Halfon. He was speaking about a different type of challenge; how to equip young people with the skills they will ultimately need in the workforce.
Halfon argues that the way we educate young people in the UK has failed to keep pace with the digital economy. Young people simply do not possess the skills to adapt during a period of seismic change.
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Throughout history, technology has disrupted the workplace, forcing us to adapt accordingly. Highly specialised skills become obsolete, or they become commoditised as part of a core set of skills every employee is expected to possess. For example, the typing pool has long since been consigned to history and we all need to be able to pick our way around a keyboard. PowerPoint has made us all ‘have a go’ slide designers.
The fact that workers have been able to adapt to these changes suggests that any forecasts predicting the end of work might be premature. Technology destroys jobs, but it also creates them. And the jobs it creates tend to be higher value and more rewarding. That’s the good news. The bad news is that the pace of technological change is pretty much unprecedented. Human adaptability is undergoing a significant examination.
Like many industry leaders, Halfon believes the current education system, with its narrow focus and emphasis on functional learning creates inflexibility. Human ingenuity may well find a way to adapt to these changes in the long-term. But in the short-term we risk putting a generation of young people in unfair direct competition with increasingly capable machines.
Adapting to rapid change requires a broad and flexible skillset. The government’s own Employer Skills Survey points resoundingly to two areas of focus: first, technical and practical skills and second, interpersonal, teamworking and problem-solving skills.
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My own field of data analytics provides a good example of why this mix of skills is increasingly vital and urgent. Technology might be consigning data entry clerks and other roles the way of the typing pool, but even the most advanced systems struggle to extract genuine value from data.
That means two things. First, demand for highly qualified data scientists and analytics professionals is skyrocketing. Second, everyone from the reception desk to the boardroom is increasingly expected to be comfortable using data to derive insight and inform decision making.
Most organisations employ a spectrum of technical and non-technical people. Exciting things happen when these diverse groups are able to meet somewhere in the middle of this spectrum and share ideas. Modern data analytics tools facilitate this exchange by being highly intuitive and easy to use for both technical and non-technical employees.
But better tools only take you so far. If technology is breaking down barriers between technical and non-technical teams, then all employees need to be able to adapt to that journey. As data becomes more ubiquitous, everyone must be able to read, understand and above all, communicate data.
If a data scientist describes design and communication as a ‘soft skill’ then it indicates to me that they have missed the point of what the role entails. Similarly, if an HR professional dismisses data as too technical, then they might as well put their computer, or the internet into the same bracket.
Breaking down these prejudices is tough, particularly when narrow education pathways seem intent on reinforcing them. My young daughter came home the other day having been asked to manually enter a data set into an excel spreadsheet in a school technology project. Not only is that not how we would collect data anymore, it’s also a great way to put a young person off data analytics for life!
Better tools only take you so far. If technology is breaking down barriers between technical and non-technical teams, then all employees need to be able to adapt to that journey.
I can accept that the specifics of what we teach will always be playing catch-up with rapidly changing innovations in the workplace. But there is no reason why the core principles of how we teach should be so far away from the requirements of the workplace.
As working with data becomes more ubiquitous, it is increasingly bizarre that we hive off the teaching of data analytics into technical subjects. The Royal Society’s Curriculum Review, published last year, makes a compelling case for incorporating elements of data science into primary and secondary education across a broad range of data rich subjects such as history and geography. Teaching data skills should not be limited to STEM subjects but be a core competency in every subject.
Progressive teaching methods in subjects like design and technology show that it is possible to break down siloes between technical and creative disciplines, while also encouraging students to collaborate to solve problems. It is depressing then that school performance indicators like English Baccalaureate (Ebacc), which prioritises so-called ‘traditional’ academic subjects, have led to a 57% reduction in design and technology GCSE entries since 2010.
The acquisition of knowledge is important. But it is not enough. The truth is that knowledge is only useful where individuals have the skills to interpret and communicate it, and skills are only useful where young people have a core knowledge to draw on.
All young people need the opportunity to develop the knowledge and the skills that they need for future employment. This requires a broad and relevant curriculum that links explicitly to the real world. Get the balance right and the so-called rise of the machines looks less like competition, and more like a springboard for employees to challenge the old ways, deliver more value, and do work which is ultimately more rewarding.