Abstract
There are measurable factors that can predict growth in sectors and industries. One of these measurable
factors is skills. Skills relate to human capital, which is a known contributor to economies, businesses,
sectors etc. Technology evolves at a quick pace, skills are not unaffected by the change from technological advancements. Skills are dynamic and are a necessary metric to take note of. Skills
linkages, skills mismatches, and skills demand and supply are all factors to consider globally, skills
forecasting is a method to address these factors around skills.
The research questions in the study emphasise the context around skills, skills forecasting and the need for further perspective in the techniques which currently exist. The impact of technology on current and future skills is established. By identifying future skills, institutions are able to prepare graduates for
employment, and current skills aid in organisations training current employees effectively for the
current workforce. The aim is to connect technological evolution and future skills through the use of a systems thinking-based framework. The study proposes a systems thinking approach to address these limitations to advance digital forecasting. There are multiple layers involved in the systems thinking approach. A bibliometric analysis allows real-world context to the evolution of technology on skills from a sector to a sub-sector.
A cross-country analysis adds further perspective on the impact of technology on skills on a sector level. The bibliometric analysis, together with regression analysis, illustrates the technological evolution impacting skills in multiple sectors. The regression analysis illustrates the evolution of technology in
relation to skills publications. There is an increase in the percentage of publications per year for the
“skills AND technology” search string. This increase continues when a sector-by-sector analysis is conducted from the same database. The analysis provides real-world context, i.e., sharp increases in
publications from 2016 in the manufacturing sector due to technological advancements introduced to the sector, such as 3-D printing and IoT. Thus, illustrating technological evolution on a sector level.
The cross-country analysis extracts the job roles from a job website. This allows a comparison between
the healthcare sector in the USA and South Africa (SA), a developed and developing country, to provide further context. The top twenty roles are compared for their relevancy and perspective between the countries. This allows an overview of the jobs and skills requirements of each country. For example,
Job roles involving remote care, linked to the technological advancement of telehealth, appear more in USA data than in SA. This demonstrates the difference in permeation of technological advancements between developed and developing countries. This comparison allows an effective understanding of the progression and integration of technology in healthcare in the two countries, with the USA being more advanced than South Africa. As developing countries note changes in the developed countries for guidance when handling the impact of technological changes, this can assist in minimising risks.
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Technological leapfrogging can occur through the creation of roadmaps when comparing countries with
similar industries and skills needs.
The job descriptions from the data collected from the job website are fed into a networking tool to gain
further insight into the skills and technology by sector on a country level. By analysing the shape of the clusters of each diagram created, there is a significant difference between the shapes. The USA diagram and keywords indicate they are further along with the integration of digital technologies than SA.
Understanding the needs in the current sectors within countries can aid institutions and organisations in bridging the gaps for students graduating and moving into industry. Training can be developed to aid the transition, develop the necessary skills for graduates, and allow academia and industry to benefit
from this collaboration.
The combination utilised for the results of the study allows for a holistic perspective. The recommendations of the study include furthering the system thinking approach by expanding the databases for data collection and adding dimensions to a skill forecasting model for further contribution to decision-making.