Abstract
Purpose
The constant and rapid change in technology is reshaping the nature of jobs across various sectors, leading to changes in skill demand. This study aims to identify and forecast skills that will be in demand in the future in the South African (SA) banking sector.
Design/methodology/approach
This study developed time series models to forecast future skill demand using job post data and conducted interviews with semistructured questions with seven technology experts to evaluate the relevance and usefulness of the models in predicting future skill demand.
Findings/results
The models indicate that there are stable or slight fluctuations in the future demand of skills within the banking sector. The interview findings align with the models’ forecasts, supporting their usefulness and relevance in forecasting skills demand.
Practical implications
This study can help firms with improved hiring practices of a workforce that can support organisations’ objectives and adapt to future changes in the workplace in terms of technologies and skill requirements. It demonstrates the relevance and practicality of skills demand forecasting models.
Originality/value
Identifying future skills is an ongoing challenge, especially given the rapid evolution and adoption of new technologies. This study demonstrates the application of skills demand forecasting models as a practical approach for managers to proactively address existing skills shortages and gaps.
Keywords – future skills, skill demand, skills forecasting, machine learning, time series forecasting
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1. Introduction
The rapid advancement and emergence of new digital technologies is changing the skills required for work across various industries, including the banking sector, and has resulted in an increase in the need for highly skilled workers (Ditse, 2020; Hlongwane, 2022). As banks worldwide adopt digital transformation strategies to address the changing needs of customers, they strive to increase their market share globally by offering banking services beyond borders (Nqala, 2021; World Economic Forum, 2020). Digital transformation not only enables global competitiveness among banks but also attracts and retains talented employees by offering growth and development opportunities (Nqala, 2021). This trend further increases the demand for specialised skills in areas such as data analysis, data science and cybersecurity within South Africa (SA) and the global banking sector (Hlongwane, 2022; World Economic Forum, 2020).
The South African banking sector is experiencing an increase in demand for skilled professionals and a workforce that possesses the skills required for adapting to changing customer needs and supporting data-driven decision making through digital technologies (Hlongwane, 2022; Mamela et al., 2020; Masheleni, 2022; Mishi & Mushonga, 2023; Naidoo, 2020). The rapid adoption of technologies within the banking sector and widening skills gap have made it challenging for banking firms to identify and anticipate the future skills they will need (Ditse, 2020; Masheleni, 2022; Mishi & Mushonga, 2023). This presents a problem for banks in that failure to align the skills of the workforce with changing demands could limit innovation, competitiveness and growth for banks in the sector (Naidoo, 2021; Naidoo, 2020; Thandray, 2020).
The adoption of digital technologies has a dual impact on employment in that it can lead to a reduction in certain jobs while also creating new and emerging job roles (Naidoo, 2021). The number of bank tellers has decreased as banks continue to automate back-end processes using new technology, but the number of digital banking specialists, data scientists, machine learning engineers and cybersecurity experts has increased to support the transition to more technology-driven banking operations (Ditse, 2020; Jacobs, 2020; Naidoo, 2021; Naidoo, 2020). Bank employees face the reality of a skills gap, in that the skills they possess and those that are in demand by bank employers could leave an enormous number of positions unfilled in the next years to come (Ditse, 2020; Garcia de Macedo et al., 2022; Mishi & Mushonga, 2023). Banks that do not possess a skilled workforce that can adapt to rapid changes in the market and technologies affect their ability to grow and offer innovative and competitive products and services to the market (Ditse, 2020; Naidoo, 2020). South African banks play a pivotal role in the South African economy by contributing 20% to GDP and being among the largest formal employers in the country (Ditse, 2020; Oluwajodu et al., 2015). The provision of financial services by banks contributes to the growth of businesses and household and personal accumulation of wealth, further driving economic growth for the country (Naidoo, 2021).
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As digital technologies have the ability to improve productivity among employees and introduce jobs into the economy, they also create a widening skill gap and shortage and displace a wide range of human tasks, which increases the already high unemployment rate experienced in South Africa (Hlongwane, 2022; Masheleni, 2022; Nqala, 2021). This can result in a slower adoption of digital technologies, which can have several implications for banks, such as reducing competitiveness, negatively impacting retention and attracting talent, and limiting innovation opportunities, which affects their contribution to economic development (Ditse, 2020; Mishi & Mushonga, 2023). Cognitive skills cannot be automated by technology, so such human skills are in high demand (Das et al., 2020). Some of the soft skills identified in the literature that graduates and middle to senior employees do not possess include leadership, communication, problem-solving, teamwork, and social and emotional intelligence (Abe et al., 2021; Bartaula, 2023; Fajaryati et al., 2020; Modise, 2019; Naidoo, 2020). This highlights that changes in digital tools and automation of human tasks are needed for more highly skilled individuals, but there is also a crucial need for human-centric skills to remain competitive and adapt to changes within the banking sector, further supporting the need to anticipate future skill requirements in the banking sector (Ditse, 2020; Naidoo, 2020; Samuel & Moagi, 2022).
This study makes an important contribution to the growing body of literature on skill demand analysis by demonstrating time series forecasting as an approach to analysing and predicting future skill demand. While previous studies have developed models that have effectively forecasted future skill demand, they have not evaluated its relevance to current industry needs in collaboration with experts (Das et al., 2020; Garcia de Macedo et al., 2022; Senthurvelautham & Senanayake, 2023; Vankevich & Kalinouskaya, 2020). This study addresses this gap by combining quantitative forecasting with qualitative validation by conducting semi-structured interviews with experts from the banking sector, ensuring that the findings are both data-driven and aligned with the skills demands of the South African banking sector. This evaluation also provided insights into the alignment between forecasted skill needs and workforce demands in the banking sector, helping to identify gaps between predicted and actual skills needs to enhance workforce planning. This study further highlights time series forecasting as a practical tool for banking firms to anticipate future skill demand, strengthen strategic workforce planning and implement targeted training initiatives to address skills shortages and gaps.