Developing Talents vis-à-vis Fourth Industrial Revolution

Developing Talents vis-à-vis Fourth Industrial Revolution

Muhammad Anshari (Universiti Brunei Darussalam, Brunei), Mohammad Nabil Almunawar (Universiti Brunei Darussalam, Brunei) and Abdur Razzaq (Universitas Islam Negeri Raden Fatah Palembang, Indonesia)
Copyright: © 2021 |Pages: 13
DOI: 10.4018/IJABIM.20211001.oa2
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The growing numbers of unemployment raises concerns around the world. With the arrival of the Fourth Industrial Revolution (4IR) many believed that 4IR might increase the unemployment rate by replacing the current jobs with automated machines such as robots whereas some argued that 4IR might reduce the unemployment rate by creating millions of new jobs. The paper aims to share the scenario of Industry 4.0 processes that affect future talent management, in determining which jobs will be severely affected, and that will be less affected. The talent mapping is a conceptual framework of job landscapes and the following four clusters examine job characteristics: machine-centric to human-centric, routine to complex, and optimization to identity. A qualitative method was deployed to extracts primary data from educators' perspectives in developing talents required for 4IR through Education 4.0. The adoption of Education 4.0 will be advantageous for developing talent in keeping up with the progressive and demanding talents in 4IR. The proposed model defined that clusters of machine-centric are jobs performed routinely on an application basis and usually structured and do not require any compassion or emotions. While developing talents for clusters in human-centric jobs, it may be difficult to replace humans due to complexities in the decision-making process and required compassion for task completion.
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Advancement in technology has reshaped the structure of jobs affecting the workforce both positively and negatively. Previous research shows that this growing trend could reduce the unemployment rate by creating thousands or even millions of new jobs or increasing the unemployment rate by displacement of the current jobs by smart machines or robots (Balliester and Elsheikhi, 2018; Ford, 2009; Görmüş, 2019; Kergroach, 2017). While others believed that 4IR will create millions of new jobs (Ford, 2009; Görmüş, 2019; Kergroach, 2017) due to new innovation and economic growth that is supported by the advancement of technology (Ford, 2009).

Furthermore, the Fourth Industrial Revolution (4IR) describes the current trend of integrating physical technologies with concepts such as the Internet of Things (IoT), Big Data, Artificial Intelligence (AI), Robotics, 3D printing, and Cyber-Physical Systems (CPS) with the aim to reduce both job-related risks and costs especially in the manufacturing sector (Heinrich, 2019; Sumer, 2018; Anshari et al., 2017).

It is important to note that 4IR is not only limited to the manufacturing and production sector, but also other sectors including healthcare, retails, agriculture, education, etc. 4IR emerged not just due to the swift growth of technologies, but also due to the social and economic factors of a current globalized and interconnected world. The economic and social factors include Telecommuting, technologically-enabled freelance and consulting services, and people becoming used to work that are more flexible leading to interdependency in regards to work relationships.

Talent development in 4IR is important discussion highlighting issues concerning who is the talent to be developed, what competencies should be developed, who drives development, what is the appropriate pace of development and what is the architecture to support the development (Ziegler et al., 2019; Garavan, Carbery, & Rock, 2012; Bloom, & Sosniak, 1981).

Since there are not many studies discusses talent development in regards to 4IR, whether talent development processes should focus on the development of technical or generic competencies or both. The paper proposes a significant debating point of the conceptual model in developing talents and skills required in Industry 4.0. The aim of the paper is to propose a conceptual model of the job matrix of 4IR which has highlighted the nature and characteristics of a job and talent development.

The research distinguished the talent management should be developed into four clusters. These are combinations of human and machine interactions. Human and Human-to-Human Interaction is complex involving emotion, feelings, and compassion as human identity. It also emphasizes as non-routinized tasks that need human interaction and task discretion is difficult to automate. As numerous routinized tasks are automated in the workplace, non-routinized tasks that need human interaction and task discretion are difficult to automate (Koleva, 2018). While Machine-to-Machine Interaction is noted as an important aspect as most production processes will highly depend on automation for the purpose of optimization, encompassing high-tech robotic machines.

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