GLOBAL KNOWLEDGE CENTER
PREPARING STUDENTS FOR A DIGITAL WORLD MAY 20, 2019
PREMISE It’s common knowledge today that technology will drastically change the workforce of tomorrow. Companies will face changes to the way they do business as humans increasingly engage with automation and artificial intelligence in the workplace. Data literacy will be required in a range of industries and at all levels of employment. To remain relevant, we need to the refine soft skills that machines don’t have, but we must also learn how to work with the technologies we use. It will be crucial for individuals to understand and analyze large amounts of data to adequately manage the technologies of tomorrow.
New types of jobs are going to drastically change the workforce, labor market and education objectives This changing world of work requires us to re-think how the education system in the United States prepares students for the job market. Currently, high school students develop a range of skills in the arts and sciences, but most schools do not offer data literacy classes beyond basic computer science. The lack of focus on data-related skills in academic institutions will likely lead to two phenomena: • A substantial shortage of highly-skilled workers when technological jobs change the economic landscape • An increase in unemployment among graduates whose skills are no longer necessary due to the rise in automation Future students and graduates will not have the data analytical skills they need to manage the technologies they will use every day. Moreover, individuals already in the workforce may also lack the skills needed to excel at their jobs. To curb these problems, there must be a closer interaction between academic institutions and companies to prepare students for the work they will encounter upon graduation. Additionally, individuals at all levels of employment will need to develop some understanding of data literacy to succeed in an increasingly-automated world.
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DID YOU KNOW? 21% OF 16- TO 24-YEAR-OLDS RANK THEMSELVES AS DATA LITERATE.
Source: Lead with Data: How to Drive Data Literacy in the Enterprise, Qlik, 2018 This low percentage of data literate youth indicates that today’s young adults are not receiving enough training in how to read and analyze data. If this rate continues among youth in Generation Z, most of the future workforce will lack essential data analysis skills needed to work with machines and artificial intelligence in the next 10 to 15 years. Because data-dependent occupations will be among those with the highest productivity, the impact of data illiteracy will likely undermine the growth potential of the American economy.
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TRENDS As we move into a data-driven world, individuals of all levels of education and work experience should be prepared for a different kind of workplace. A 2018 survey by Censuswide and Qlik shows that young adults are not data confident and proficient despite having grown up in a digital world. 21% of 16- to 24-year-olds rank themselves as data literate. This low number indicates that most youth are unprepared to take on jobs that will require increasingly higher levels of data-related skills, which is due partly to a lack of academic and job training in data literacy. Being able to read, analyze and argue points derived from data is a pillar of today’s working world, and youth, as well as people who already employed, will need to develop a new level of comfort with data analysis and management to remain relevant in the workforce. The future of work will be influenced not only by automation but also by other six key trends, according to Pearson’s report “The Future of Skills – Employment in 2030” (check the exhibit below). Facing fears about the high risk of automation for 47% of U.S. workers’ jobs and also other trends like growing disparities in education and social services, it would be important to ensure that the youngest generation is provided with the proper education.
Exhibit 1: Key trends determining the future of work Environmental Sustainability
Globalisation
Increasing Inequality
Demographic Change
Political Uncertainty
Urbanisation
Technological Change Source: Bakhshi, Hasan, et al. “The future of skills: Employment in 2030”. Pearson, 2017
The question is this: Will the linear model of “Education – Employment – Career” be sufficient for the workforce of the future? The “Solving Future Skills Challenges” report by Universities UK provides a clear “No,” highlighting requirements for a new-and-improved education model: one that offers better collaboration between educators and employers and for efforts made by governments to adopt a wholeskills approach. As the demand for a high level of skills across a range of industries increases, there is a risk that there will be an insufficient supply of adequatelyskilled individuals to take up these jobs. NEWMARK KNIGHT FRANK
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THE FACTS It’s hard to disagree with John R. Allen’s statement that well-trained and educated youth will fuel the engines of future geopolitical success. In coming decades, people will greatly depend on the primacy of hi-technologies and artificial intelligence. This dependency underscores the need for improvement of skillsfocused courses taught in schools, universities, colleges and other academic institutions. Our increasing dependence on technology puts at risks lower-skilled and repetitive tasks that can be easily automated by machines. With this change also comes a greater demand for technical systems skills, higher-order cognitive skills and interpersonal skills. “The Future of Skills” report by Pearson made the following conclusions about future changes to the U.S. workforce:
Exhibit 2: The workforce composition according to future demand for occupations in United States 9.6%
18.7%
71.7%
9.6% of the current U.S. workforce is in the occupations that are most likely to grow as a share of the total workforce, 18.7% of employees are in occupations that will most probably reduce (i.e. probability of the growth is the lowest), For 71.7% of occupations the result is inconclusive – it suggests that the growth can be driven only by occupation redesign along with workforce retraining. Source: Bakhshi, Hasan, et al. “The future of skills: Employment in 2030”. Pearson, 2017
According to the report, the occupations that are projected to grow are teachers, personal care workers, business operations specialists, engineers and construction trades workers. Roles such as sales engineers and real estate agents are anticipated to increase as well, despite the predicted fall in general sales NEWMARK KNIGHT FRANK
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occupations which account for a high number of occupations in the United States. Followed by retail sales, the occupations that are most likely to decrease are those impacted by technological and digital changes such as woodworkers, rail transportation workers and production occupation workers. What is more, financial clerks are among the largest groups that are likely to decline; the reason being that the impact of automation is trespassing on more cognitively-advanced tasks. 71.7% of roles have no certain future at this time, which indicates that growth can be driven only by occupation re-design along with workforce training. Analysis of the relationship between skills and abilities as well as future demand for certain occupations in the United States demonstrates that the most important skills will be those related to decision-making and creativity, learning strategies and social perceptiveness, as well as the fluency of ideas and the clarity of speech. Subjects such as psychology and sociology will also become more important as value is increasingly placed on human-to-human communication and empathy.
Exhibit 2: The workforce composition according to future demand for occupations in United States Skills
Abilities
Knowledge
Learning Strategies
Originality
Psychology
Instructing
Fluency of Ideas
Sociology and Anthropology
Social Perceptiveness
Oral Expression
Education and Training
Coordination
Speech Clarity
Therapy and Counselling
Active Learning
Deductive Reasoning
Philosophy and Theology
Speaking
Oral Comprehension
Communications and Media
Service Orientation
Inductive Reasoning
English Language Knowledge
Active Listening
Speech Recognition
History and Archaeology
Complex Problem Solving
Problem Sensitivity
Administration and Management
Judgement and Decision-making
Memorization
Biology
Source: Bakhshi, Hasan, et al. “The future of skills: Employment in 2030�. Pearson, 2017
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POINT OF VIEW There are three important ways through which we can better prepare individuals for the labor market of tomorrow 1. Upskill teaching staff. Education facilitators will be the flywheel that initiates when it comes to reshaping the American education system in terms of data literacy. One example of how educators are successfully training students can be found at Lakeside Private School in Seattle, WA. The school reorganized its curriculum to prioritize teaching students to coexist with artificial intelligence and solve complex problems. Faculty and students are working together to develop a list of futureproof skills that will most benefit students. They will not only learn programming in math class but also soft and non-technical skills like creativity and adaptability which are in high demand by companies, according to a recent study “The Skills Companies Need Most in 2019” conducted by LinkedIn. This collaborative initiative will dispose of certain assignments, subjects and teaching styles that will not prepare students for the workforce. 2. Focus on the skills that are in high demand. Being data literate is crucial. Soft skills such as conscientiousness, creativity, teamwork and social skills, which have been largely underestimated in recent years, will have a substantial impact on the way people work in the future. XQ Institute, a nationwide group focused on transforming
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high school education in the United States, offers grants to schools that invent new ways of teaching. One such school is Tiger Ventures, based in Endicott, New York, that combines a high school and incubator space where students can work alongside start-ups to drive the community’s economic re-development. Through real-world cases, students have an opportunity to learn entrepreneurship. 3. Limit the increase of graduate unemployment. Academic institutions, such as colleges, universities, technical and vocational schools and laboratories, should develop initiatives that will re-train individuals to avoid digital exclusion of graduates, older age groups of employees and those whose work is most likely to be automated. Some institutions are already looking for potential tech workers among physical labor and gig-economy employees. Collaborations between academic institutions and businesses are crucial. Companies like Catalyte and Techtonic, which run data training programs and apprenticeships, screen applicants based on a person’s characteristics and interests rather than programming skills.
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BIBLIOGRAPHY
1. Universities UK. “Solving Future Skills Challenges”. August 2018. Available at: https://www.universitiesuk.ac.uk/policy-and-analysis/reports/Pages/solvingfuture-skills-challenges.aspx. 2. Qlik and Censuswide Survey. “How to Drive Data Literacy with the Enterprise: Data Literacy Report”. Qlik and Censuswide. 2018. Available at: https://www. qlik.com/us/bi/data-literacy-report. 3. Wadell, Kaveh. “Rebooting high school.” Axios. March 2019. Available at: https://www.axios.com/rebooting-high-schools-future-jobs-5366f9f5-1aed4878-81d6-77992281f205.html. 4. Bakhshi, Hasan, et al. “The future of skills: Employment in 2030”. Pearson, 2017. Available at: https://futureskills.pearson.com/research/assets/pdfs/ technical-report.pdf. 5. Allen, John R. “Why we need to rethink education in the artificial intelligence age”. Brookings Institute. January 2019. Available at: https://www.brookings. edu/research/why-we-need-to-rethink-education-in-the-artificial-intelligenceage/#footnote-1. 6. Petrone, Paul. “The Skills Companies Need Most in 2019 – And How to Learn Them”. Linkedin – The Learning Blog. January 2019. Available at: https:// learning.linkedin.com/blog/top-skills/the-skills-companies-need-most-in-2019-and-how-to-learn-them 7. Wadell, Kaveh. “Training unlikely techies. Axios. March 2019. Available at: https://www.axios.com/job-training-tech-catalyte-techtonic-b7451a9f-ea104126-8b02-4ecabf752e72.html
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RAJEEV THAKUR Executive Managing Director Head of Global Knowledge Center 571.230.0242 rthakur@ngkf.com
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