Moulding a future-ready workforce

Shaping tomorrow’s workers for a fast-changing world The educators and workplaces need to evolve to a new method of instruction and training to enable tomorrow’s workers to perform

The main task of education and research is to train people to perform in future economic and technological environments with many unknowns, tackling unknown problems using instruments yet to be developed.

In truth, we know embarrassingly little about tomorrow’s jobs. Interdisciplinary and holistic education and research are indispensable as the workplace combines cognitive skills with teamwork and debate with focus on adaptability, replacing silo thinking with a flexible approach that applies knowledge from multiple sectors that at first appearances may not seem relevant.

In many industries and countries, the most in-demand occupations or specialties did not exist 10 years ago, and the pace of change will only accelerate. On average, by 2020, more than a third of the desired core skill sets of most occupations will be comprised of skills not considered crucial to the job today. In essence, technical skills must be supplemented with strong social and collaboration skills.

Education and research are increasingly out of touch with demand for these skills. The tendency to focus on cognitive skills, including the ”STEM” topics of science, technology, engineering and mathematics, cannot preclude the productivity benefit of soft skills, including applying knowledge and finding opportunities offered by technology. In recent decades most countries have fallen into the trap of overextending cost-benefit analyses while training students to solve yesterday’s problems. Governments enforce short-term fiscal planning on education programs, but measuring social skills is not as easy as calculating STEM competences.

Much attention is devoted to high calibre education and research, and for good reason, but demand trends suggest that human factors may be more essential than normally assumed. For example, health, nonstop improving of skills and entertainment may prove to be the growth sectors of the future — and the main job providers. Human maintenance will grow almost exponentially, steered by demographics and a growing proportion of elderly citizens.

Human improvement, the ability to try new technologies, should not be overlooked, because the higher productivity promised by new technology blossoms only if humans have the skill to manage that technology. Entertainment will also be a growth sector, owing to shorter work lives and longer retirements. Today’s elderly are more active than previous generations’, and they demand health care, entertainment, social networks and communication.

For students to learn to adapt requires motivation and self-confidence via autonomy, mastery and purpose. Autonomy means that students learn how to learn, to perform and to do research on their own without seeking instructions or guidance. In the industrial world, guidance was normal, because those societies were not evolving very fast. The ”We used to do it this way” approach was useful for the previous era, but is obstructionist today.

Students today must prepare to work for situations with no paradigms. Mastery requires an individual to feel in control of a subject or craft, ready to renew his/her abilities to win respect and acquiescence from others when canvassing for new paradigms. Purpose demands understanding of what must be done, why and how. Enterprises must communicate purpose to their staffs and expect two-way feedback: Employees must show initiative, informing managers of improvements and new methods, while managers must inform their staffs about objectives while keeping an open mind.

Modern workplaces constantly challenge the notion of ”This is how we have always done it.” Autonomy, mastery and purpose are rarely practiced in education or in research, yet these are indispensable for coping with change. The new workplace requires trust among leaders and staff alike. The key is sharing knowledge, allowing technology, research and innovation to fulfil potential. Sharing takes place only if individuals feel that they operate in a reciprocal system.

Colleges must catch up. Amid chatter about the impact of artificial intelligence, quantum computing and the internet of things, the transition from the industrial to the technological age includes moving from narrow disciplines and specific approaches, delivering reproducible scientific results, to options and the possibility of comparing different options, which entails searching for solutions across disciplines. Waiting for results must give way to a focus on asking the right questions.

This is a shift from more than 200 years of deduction to induction as the foundation of education and research. Formerly deduction was the preferred method, which required forming a theory and, from there, working to solve a problem and seek an answer. Today, however, big data, quantum computing and artificial intelligence enable complex systems that may require emphasis on correlations, interactions and interrelationships without the need for theories as such. More than one best solution may be possible, and the end goal should be systems and language models that adapt themselves. This is induction.

European universities use two basic models to confront this massive change. The Anglo-American model is the analytic pattern of moving from the parts to the whole, assuming that the whole is the sum of its parts. The Continental model prefers to move from the whole to the parts, and then from parts to the whole, in a cyclical process to understand a system.

Asia’s universities, apart from the top layer, are relatively new, so Asia has the chance to start from scratch in forging its own university model. It is by no means certain that, despite the race for top spots on international-ranking lists, Asia will be best served by universities in the mould of Europe and the United States.

Interdisciplinary, holistic education and research call for a new paradigm. Technology opens many windows, but human skills determine how it is used. Instead of digging deeper to understand a narrow discipline, individuals can grasp interactions. Societies must understand that what worked well until a few decades ago, in education, research or business alike, may not work anymore. Universities must play a more direct role in forging societies and interact more with government, business and society.

So far universities have welcomed interdisciplinary and holistic thinking, but within limits — via special courses or a small subset to existing curricula. This is better than nothing, but still reflects an industrial-age response. Barriers among disciplines must be torn down, and students must give thought to how their skills can be applied in any area.

Among the lessons for educators and workplaces: focusing on the ability to use knowledge and how to adapt, questioning cost-benefit analyses based on fiscal results here and now, engaging in long-term thinking, emphasizing the need to meet human needs rather than materialistic demands, providing feedback to education and research on how to interact with other human beings while resisting the trend of dehumanisation, and relying on a combination of individualism, creativity and teamwork to develop societies.

(This article is condensed from an article written for the Asian-Europe Foundation Rectors’ Conference & Students’ Forum, held in Singapore in October. Joergen Oerstroem Moeller, an adjunct professor at the Singapore Management University & Copenhagen Business School, is a visiting senior fellow at the Institute of Southeast Asian Studies in Singapore.)

Quick Bytes

1
On average, by 2020, more than a third of the desired core skill sets of most occupations will be comprised of skills not considered crucial to the job today.
2
Big data, quantum computing and artificial intelligence enable complex systems that may require more emphasis on correlations, interactions and interrelationships rather than on theories.
3
On average, by 2020, more than a third of the desired core skill sets of most occupations will be comprised of skills not considered crucial to the job today.
4
Big data, quantum computing and artificial intelligence enable complex systems that may require more emphasis on correlations, interactions and interrelationships rather than on theories.