The Human Resource Development Council of South Africa (HRDC) held its third Summit last week, focusing on the HRD strategy towards 2030. In any economy, the central aim of a human resource development strategy is to assist long term investment in the education sector. The scale of such investment can only be determined if skills needs are carefully identified. The problems of unemployment, changing technologies, skill requirements and knowledge obsolescence only heighten the need for forward looking tools for skills demand and supply. ADRS recently completed an international review of approaches to skills forecasting for the ILO. We classified and reviewed approaches and practices in various countries, including South Africa. The study revealed where SA stands relative to other countries in terms of skills forecasting techniques and utilisation.
Internationally, the main estimation methods used for forecasting skilled manpower can be grouped into three categories: quantitative, qualitative, and hybrid approaches. The quantitative approach is distinguished by its use of models and formal quantitative methods to produce projections of future skills needs. Practices that fall under qualitative approaches use ‘soft’ qualitative data alongside the ‘harder’ statistical information to anticipate future skills needs. They significantly rely on key experts and stakeholders for skills anticipation. Finally, and increasingly, countries are combining quantitative and qualitative approaches for their skills forecasting needs.
By far the quantitative approach based on large scale multi-sector macroeconomic models is considered ‘best practice’ worldwide for forecasting skills requirements. Statistical analysis of demand for skills relies heavily on the estimation of demand for occupations that are based on sector employment projections. Therefore, an important pre-requisite for credible skills forecasting is access to quantitative projections of industry level employment under alternative ‘what if’ scenarios for the economy and the education sector. The overall process of forecasting skills demand and supply, however, includes additional steps that systematically build on the outputs from a multi-sector macro model.
The South African quantitative approach to skills forecasting is centred on the Linked Macro-Education Model (LM-EM) which was built between 2012 and 2017 in response to a call by the then Minister of Higher Education and Training for instruments government and policy analysts could use for their strategic decision-making. In terms of approach and architecture, LM-EM is similar to the European Union’s skills demand model. Uniquely, however, it has a user friendly web-platform, which other countries lack. It is built to enable policy analysts to design economic and education policy scenarios, quantify their impact, and project future trends in economic indicators along with the demand for and supply of educational qualifications. The aim of LM-EM has always been to support skills planning and systematic decision making by providing credible foresight about the skill needs of future jobs.
In practice, governments across the world have relied on model projections to plan medium and long term manpower requirements. They typically have institutional mechanism to provide inputs into the generation of the model projections of manpower requirements and to engage in the final review and fine-tuning of projections prior to using the final results for budgeting and implementation. Thus, country officials combine a quantitative approach to forecasting skills requirements with quality control measures to establish forecasts that they can use for planning outputs from the education sector. For example, BLS in the US, Sector Councils in Canada (about 35 of them), Industry Skills Councils in Australia (10 of them), and Sector Skills Council in the UK (about 35 of them) all undertake verification of the skill forecasts produced by models.
Relative to countries that actively and systematically engage with and use model generated skills requirement forecasts, in South Africa a formal institutional arrangement to effectively interact with and utilise the LM-EM for skills planning is currently under consideration. In 2010, a key goal of the third National Skills Development Strategy (NSDS III) in South Africa was to establish a credible institutional mechanism for skills planning. At the time, the Strategy noted that there was no institutional mechanism that provided credible information and analysis with regard to the supply and demand for skills. While there were a number of disparate information databases and research initiatives, there was no standardised framework for determining skills supply, shortages and vacancies, and there was no integrated information system for skills supply and demand across government. Thanks to the support from the DHET, South Africa now has the necessary framework for determining future skills supply and demand requirements, what is missing is the institutional mechanism to effectively utilise the framework for its intended purposes.
We hope that you find this Did You Know/What If a useful and thought-provoking publication. Feel free to forward it to your colleagues. Please let us know if you have any comments or questions.
ADRS News Archive