By 
By André Zitzke, Manager: SAS Global Academic Programs in Africa
The rapidly evolving digital landscape has had a massive impact on the public and private sectors, especially in terms of data science and analytics skills. A staggering 1.5 to 2 million global data science jobs remain unfilled. This gap is projected to widen, with an estimated need for 11.5 million roles by 2026 signalling an urgent demand for skilled professionals.
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Compounding the talent retention challenge, once study found that 33% of a departing employee’s annual salary is spent on recruiting a replacement. Given that the average tenure for a data scientist in a role is two years, there is significant work to be done if industry is to find an effective way of overcoming these challenges. In Africa, collaboration between all stakeholders will be essential in this regard.
The skills gap and talent shortage are significant. We need to facilitate what skills there are and the industries that need it most. But to do this, the funding shortage at universities must be addressed. The private sector must work closer with universities to make data science units sustainable. For instance, just as data scientists leave their jobs, so to do universities require funding to mitigate the risk of losing experienced faculty members. One of the benefits of stronger cross-industry partnerships for universities is that tertiary institutions will be able to produce graduates with the skills vital in the digital workforce.
Therefore, the connection between universities and business must be formalised and managed. Yet, many of these partnerships are left to chance. One of the most effective ways for stakeholders to think differently is to prioritise a brain gain – a proactive response to the brain drain often experienced – where knowledge is transferred, and collaboration is prioritised.
The power of AI
Artificial Intelligence (AI) is considered a game changer in social and economic development for several reasons. These include its potential to automate routine tasks, tailor products and services, and solve complex problems at scale. It can even be used in various social applications, from predicting and managing natural disasters to assisting in medical diagnoses and treatment recommendations, amongst others.
But if South Africa and the rest of the continent are to effectively inject AI into business processes, there needs to be a skilled resource to understand how to use this advanced technology. AI and machine learning are game changers when it comes to statistical analysis. If human capital is there with graduates having the skills to operate in the emerging data ecosystem, the opportunities to boost the African economy are significant.
Better private-public institutional arrangements for building data science and statistical capacity on the continent are vital as these harness the strengths of both sectors. While the public sector provides governance and broad reach, the private sector brings innovation and efficiency. Collaborative arrangements ensure the optimisation of resources, accelerate technology adoption, and facilitate skills transfer. Such synergies create a conducive environment for data-driven initiatives, maximising impact, and sustainability in Africa’s data landscape.
Embracing empowerment
Having a private and public sector dedicated to diversity and inclusion will be key in combating the high employee turnover rate of 33%. But beyond simply focusing on the numbers, connecting talent is about creating equitable opportunities for all.
This is where the potential for mentorship initiatives is significant. These have the potential to extend beyond traditional corporate roles to emphasise deep engagement with the community. Through personal mentorships, business leaders can provide graduates with the practical, real-world skills essential to enhance their data science training to not only grow as individuals but also have a broader societal impact.
Expanding data science skills
Much of this depends on how much investment businesses will make to ensure the requisite skills-building takes place and to align those with the growth they are predicting. There is no point in investing in new technologies that employees have not been skilled up to utilise, and no technology, no matter how good it is, will deliver a return on investment if people cannot – or will not – adopt it. By engaging with high school and university students, businesses can ensure a steady flow of skilled individuals prepared for the challenges and opportunities in data science and analytics.
All this requires a commitment by industry to foster a diverse and inclusive community, combined with a focus on nurturing future leaders in cybersecurity, data analytics, and digital transformation. And when that is in place, the skills gap will be reduced.
