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Through three industrial revolutions, technology has led to significant changes across economies, societies and businesses. Steam engines jump-started the transition of societies from agriculture to industrial production. The use of fossil fuels in engines and innovation in business models such as the assembly line rapidly scaled production. More recently, the digital revolution brought computing power and information technology. Each successive industrial revolution has involved significant shifts in the way people live and work, in how value is created in the economy, and demand for the highest-value skills.
As the Fourth Industrial Revolution unfolds, led by advances in technologies such as data science and artificial intelligence, the labour market is again changing in a fundamental fashion. In 2018 the Future of Jobs Survey and Report revealed that business leaders believe that by 2022, human workers and automated processes are set to share the workload of current tasks equally, while a range of new roles is expected to emerge simultaneously as digital innovation is absorbed across industries and regions. In particular, in many large advanced and emerging markets, growth is expected in sectors that will experience the bulk of these new roles, such as information technology, renewable energy, education and the care economy, and in occupations such as data science, healthcare work and human resources.
While the new labour market is changing at a rapid pace, emerging data sources are shedding light on its composition with a new depth and dynamism that has not previously existed. Online platforms and specialized insight firms are now offering new and complementary ways to understand how specific skills, tasks and occupations are changing across industries and geographies. While many of these remain limited to specific populations—and difficult to compare and contrast—when coupled with traditional and qualitative sources of data, they can help businesses, policymakers and workers have greater analytic capacity about the present and future of work and adopt better informed and coordinated business strategies and policies.
In this report, the authors look at three complementary ways in which leaders can understand the market for data science skills across the new economy: monitoring the demand for data science skills through job posting analysis from Burning Glass Technologies; the distribution and quality of data science talent across industries and regions based on learner skills insights from Coursera; and analysing the rising prevalence of data science skills within the core composition of selected roles through user profile analysis from LinkedIn. Finally, the authors conclude with a look towards the future demand for data science skills across industries, drawing from the insights of executives of the largest companies in the world surveyed through the World Economic Forum’s Future of Jobs Survey.
Key insights
Implications for decision-makers
Overall, the rapid growth and evolution of data science roles and skills stresses the need for appropriate business strategies and education and training policies that can match this demand, in quantity and quality, so that skills shortages do not hinder the transformation potential unveiled by vast sources of data and improved data analysis techniques. Industries and countries that fail to understand and address these dynamics risk slower growth and dynamism.
More precisely, the insights included in this report point to the following implications:
The sections that follow present three new metric scorecards that individually and collectively shed new light on data science roles and skills in the labour market of the Fourth Industrial Revolution. The collection provides one starting point to what could be further efforts aimed at tracking skills demand and capacity across emerging sectors such as renewable energy and the care economy. This exercise can set the foundations to analyse skills dynamics in other sectors, building on the potential of multi-source data collaboration to create coherent frames of analysis and common taxonomies that can provide business and policy leaders with a common frame of reference. Finally, this report presents a forecast on the importance of data analysis jobs across multiple industries.