Data science can help close the ‘digital skills’ gap, or so it seems

A ‘digital skills’ gap is harming employer productivity and growth, according to a survey by engineering body IET. But the ‘digital skills’ that are needed sound a lot like data science skills: statistical understanding, data analytics, AI and machine learning.

Machine learning
Data analytics

Brian Tarran


February 14, 2023

Digital skills. We all need them. Employers say they want them, but there aren’t enough to go around. Supply can’t meet demand, so we’re left with a gap – a digital skills gap. But what are digital skills exactly?

This is a question that was asked repeatedly, in various different constructions, by Stephen Metcalfe MP, chairing a meeting of the Parliamentary and Scientific Committee on Tuesday, February 7. I went along to the meeting as an observer, hoping to hear an answer to that very question.

What I got was several different answers – no single solid definition, but a reasonable sense that boosting data science skills would go a long way towards closing the digital skills gap.

Survey says…

The committee meeting was sponsored by the Institution of Engineering and Technology (IET), and the main focus of discussion was the results of IET’s skills for a digital future survey, based on a YouGov poll of 1,235 respondents drawn from engineering employers (defined as “employers who employ at least one engineering and technology employee in the UK”).

Woman painting while wearing virtual reality headset. Photo by Billetto Editorial on Unsplash.

Digital skills, including AI skills, are not only required of engineers, says the IET’s Graham Herries. Generative AI tools like Stable Diffusion threaten to shake-up the creative industries. (Photo by Billetto Editorial on Unsplash)

Kicking off the discussion was Graham Herries, an engineering director and chair of the IET’s Innovation and Skills Panel, who drew attention to the harms that the digital skills gap is reportedly having. Of those respondents who identified skills gaps in their own organisations, 49% pointed to a reduction in productivity, while 35% said skills shortages were restricting company growth.

As the hot topic of the day, ChatGPT inevitably came up during the discussion. Herries sees it as a disruptive force, and 36% of all respondents believe artificial intelligence (AI) skills will be important for their engineers to have within five years (24% say they are important now). But AI skills are important for non-engineers too, argued Herries, as he pointed to stirrings in the creative industries caused by generative art tools such as Stable Diffusion.

Herries therefore puts AI skills under the broad umbrella of “digital skills”. But, to him, it’s not enough to simply be able to use AI technology; rather, users should know enough to be able to ask the right questions about the provenance of the data used to train the AI, its quality and biases, etc. This was a point developed further by Yvonne Baker, an engineer and the CEO of STEM Learning. Baker talked about digital skills as being both the ability to use digital technology and also to understand its limitations. Yet another perspective was offered by Rab Scott, director of industrial digitalisation at the University of Sheffield’s Advanced Manufacturing Research Centre. Scott defined digital skills in the context of quality control systems in industry 4.0: it’s about knowing how and where to place a sensor to collect data about the manufacturing process, to feed that data into a data collection system, analyse the data for insights, and use those insights to inform decision-making.

Closing the gap

Further definitions of “digital skills” are to be found in the IET’s published report. Survey respondents were encouraged to describe the term in their own words, so we see things like:

  • “the ability to understand, process and analyse data.”

  • “Coding, programming, software design, use of social media for marketing and communicating with stakeholders, data visualisation, work that relies solely on the use [of] online systems.”

When respondents were asked what skills were lacking in both the external labour market and their internal workforce, around a fifth cited “more complex numerical/statistical skills and understanding”. And when looking to the future and to the skills anticipated to be important areas for growth in the next five years, 39% of respondents picked “data analytics” while 31% said “artificial intelligence and machine learning”.

So, perhaps you now understand why I left the meeting with the feeling that more data science skills, more data science training, could help address the shortfall in “digital skills”.

But how exactly can we equip more people with the right skills? At one point during the discussion, Metcalfe told the meeting that he was still looking for a key takeaway, something he could take to the Secretary of State and say, ‘This is what we need to embed in the curriculum’. What was offered instead was a range of possible solutions.

The IET survey found broad backing for government support for reskilling: 40% of respondents favoured grants or loans for training (and retraining) programmes, 39% would like more funding for apprenticeships, while 33% think there should be better carers advice and guidance in schools and colleges.

Baker also made the case for digital skills to be taught in schools as part of every subject, not just in computer science lessons, and that teachers would need to be supported to deliver this.

But how would you close the “digital skills” gap, if given the chance?

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Copyright and licence
© 2023 Royal Statistical Society

This work is licensed under a Creative Commons Attribution 4.0 (CC BY 4.0) International licence, except where otherwise noted.

How to cite
Tarran, Brian. 2023. “Data science can help close the ‘digital skills’ gap, or so it seems.” Real World Data Science, February 14, 2023. URL