Empowering Europe's Data Economy: The Role of Skills and Talent
Francesco Tisiot
|RSS FeedHead of Developer Experience at Aiven
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The data economy may hinge on technology but it is being driven-forward by people. The fourth piece in our series explores this side of the data economy in detail looking at the evolution of digital skills required in today’s market. Featuring insight from Dojo, Atomico and WorkOrb, it looks at the challenges of finding people with the necessary skills and touches on what is required from a human capital perspective for companies to best achieve success in the data economy. If you’ve missed any of the earlier blogs, you can find them here
For all the advancements made in technology, none of it would be possible without humans. It’s why, in today’s dynamic, data-driven economy, talent has emerged as a critical factor in enhancing competitiveness.
Yet, for a resource as abundant as people, accessing the right skills is proving to be challenging. It poses the question as to whether the capabilities available in the market today are helping or hindering growth in the data economy.
Over the past decade, employment in the technology sector in Europe has grown exponentially, increasing by around 60% over that period, according to the European Commission. It also reports that this growth starkly contrasts with the 10% increase in overall job creation in the European economy.
This trend reflects a growing demand for digital professionals but volume alone only tells part of the story. The challenge is that technology is evolving faster than our ability to keep up. Each rotation of progress is taking us forward at one end and widening the digital skills gap at the other. It’s an issue that already costs the UK economy up to £63 billion a year.
Put simply, there are not enough people with the types of skills needed to work in the data economy. It’s an issue that is being exacerbated by the rise of Generative AI with companies intent on recruiting talent that will both differentiate themselves from the competition and provide a degree of sovereignty when it comes to the AI tooling that will drive the business forward. Because every company now entering the economy is data-based, the talent pool of those with the right type of skills diminishes. Unless something is done, it’s a race to the bottom.
It was a point made by Luca Eisenstecken, Partner, Atomico who recently told us,
Data and AI profiles are some of the most sought after skill sets currently by recruiters. Accordingly, there's a lot of demand for those types of profiles and some companies have been struggling to recruit people with the necessary skills.
This is because AI is distorting the skills market even further. Only a few years ago, those with coding and development skills were in high demand. They’re still highly sought after but, we’re also seeing AI begin to take programming work as it is used to enhance the pace of development for current programmers. Longer term, AI may or may not take more of this type of work but what is certain is that businesses will need people who at least have some element of technical understanding alongside capabilities relating to AI.
It’s why we’re seeing incentives for young people to get into such areas and a huge drive for STEM subject uptake for secondary school pupils. Unfortunately, the data economy cannot wait for today’s young adults to come of age. So how are businesses the data economy plugging this sills black hole?
One of the main issues businesses are facing is that ‘digital skills’ is a relatively amorphous term. It covers everything from basic spreadsheet capabilities to complex coding. There is no one-size-fits-all solution and answering it in the speed that is required needs strategic consideration from all sides. As explained by Jérémy Barneron, Senior Software Engineer at fintech start-up, Dojo, an innovative payments company, who said:
There are so many tools and technologies that people have experience with. Finding the right match when it comes to what your own company is using is incredibly difficult. It’s why we spend a lot of time going through candidates and making sure that they have the right mindset and foundational skills. Having adaptability and hunger to learn new skills is more valuable for us over the long term than an individual with deep knowledge in a limited space.
Individuals, too, also need to bear some degree of responsibility in terms of best equipping themselves with the type of skills and experiences that are being sought. It is one of the driving forces behind the Aiven Cluster Program, which offers early stage companies credits to use on any of the open source services available on the Aiven platform. This helps young companies grow but, by proxy, exposes those people working in them to the latest tools and platforms that will be the foundation to future businesses.
“Hard skills always matter more than logos on a resume,” says Luca Eisenstecken
The data economy is a manifestation of innovation. It exists because it solves problems - mostly this is for customers and citizens but, when it comes to skills, this is something that it needs to address for itself. It won’t happen overnight but as more and more data-based companies emerge, so too do the opportunities for people to work in a place that exposes them to the rigors needed to be successful in tomorrow's economy.
We also caught up with Nilesh Bansal, co-founder and CTO at [Workorb](https://www.workorb.com/, an AI and ML founded company poised to revolutionize the sales landscape, who shared some great insights into how his company is bridging the skills gap. He said,
Teams need to go beyond the skills that they have historically been using and move on to a new phase. One capable of ensuring data is accessible, resilient, reliable with the right governance controls in place. That's what will drive the data economy forward.
The rate at which technology advances means there’ll unlikely ever be an over-supply of skills and talent. However, today’s data-driven companies are far better positioned than their predecessors when it comes to upskilling and evolving their teams in an environment that encourages gradual improvement.
It’s this gradual improvement, brought about by every innovative entrant to the data economy, that will plug the skills gap.
