The growing need for talent in data and analytics is no secret; research conducted in 2019 found that the demand for Data specialists had grown by 231 per cent since 2014. However, with the increase in use of analytics across businesses worldwide since the beginning of the COVID-19 pandemic, the requirement for this specialism has only increased.
As the pandemic reared its ugly head, businesses were left completely in the dark with very little knowledge of which route to take to survive. Decisions had to be made with clarity, no longer was it enough to take an educated guess and hope for the best – and the only way for many to be able to do this was with hard data.
Suddenly, businesses saw the value in Data and Analytics and the request for expertise skyrocketed and has continued to do so. In May 2021, there were, on average, 200,000 recorded data-focussed vacancies available in the UK alone. Delving into this in more detail, according to recent research we undertook, of 786 people, 33 per cent stated that the specialism within data they needed the most was programming/were programmers, followed closely (29 per cent) by AI specialists.
Nevertheless, despite the immense increase in demand, businesses have struggled to plug the gaps. Four in five (86 per cent) data leaders are struggling to recruit talent, with over half of these believing that skills shortages pose the biggest threat to being able to answer their own demand. This trend can be seen across all businesses, not just data-led ones, just under half (46 per cent) of businesses within the UK are struggling to recruit for data-led roles.
So, how exactly can business leaders look to solve the data skills gap?
Explore diverse talent pools
With two thirds of Britons saying that attending university is not viable/affordable, higher education is once again becoming an elitist system which creates a serious divide between those who can, and those who cannot. Diversity in the data science industry is poor, most workers are white and male. Black talent only represents 4 per cent of the industry and men make up well over half of the employee pool across all areas of the industry.
Much of this lack of diversity stems from where the talent pool is sourced. Most (56 per cent) are hired at undergraduate level; this drops significantly to only 5 per cent from college. Traditionally, the expertise needed for data scientists derived from undertaking an undergraduate or even master’s degree. However, this is no longer the case. With many colleges offering a variety of data science and data analyst apprenticeships, higher education does not need to be the only place for employers to source talent.
Additionally, apprentices will undoubtedly be more attractive to any employer due to the hands-on nature of the qualification. An apprentice can spend up to 80 per cent of their time on-site which means not only are the absorbing the ‘hard skills’, but also key business skills such as communication, time management and teamwork – skills which are not as easily obtained through higher education courses.
According to a survey by Accenture, only half of employees report that their skills are explored and documented by their employers. Much of the work undertaken by budding data scientists or analysts is outside of the 9-5, with many putting their knowledge to use outside of work as a hobby. Organisations, especially those on a larger scale, are likely to be shocked at the amount of untapped potential there is available within their existing workforce.
By harnessing these abilities and investing in training and upskilling in-house, leaders and hiring managers have the potential to build a few select individuals into a brilliant team of data specialists without even having to touch recruitment.
Encourage lifelong learning
Whether you’re hiring from different talent pools or looking to build skills in-house, it’s crucial that employers avoid a ‘one and done’ situation and look instead at data education as something that continues for the whole life of the business and its employees.
Data capabilities and technologies look very different to how they did only five years ago, and in another five years they will have evolved again; it has been predicted that 90 per cent of the data jobs for 2030 haven’t even been created yet.
It’s vital that, as a business owner, you regularly review the market and keep a close eye on data demand – this will help you spot any potential skills gaps before they arise and subsequently highlight to you where additional training is required. While it may seem like a large investment initially, maintaining a core focus on your teams’ data abilities will undoubtedly save you time, money and worry in the long-term.
Data and analytics is a booming industry, predicted to be worth $105bn by 2027 with a compound annual growth rate (CAGR) of 12.3 per cent and the COVID-19 pandemic has certainly played its part in this exponential growth. Employers must look at alternative ways to meet demand to ensure they aren’t left trailing behind their competition.