While most of the developed countries in the world are fighting against their aging populations by increasing the retirement age and welcoming migrants, other countries are worrying about how to fit large numbers of young people into the workplace. Deloitte’s Voice of Asia series reported that many countries in Asia have witnessed steady growth in their working age population, with more and more young men and women entering the labor markets each year. India is the top one country on the list.
According to the numbers from the World Economic Forum, half of India’s population is below the age of 25 and a quarter is below the age of 14. Bearing in mind that it is the second most populated country in the world, with 1.3 billion citizens, India makes up for a fifth of the world’s youth. As most economists predicted, India will benefit from the demographic dividend and will have a fast-growing economy.
To realize the demographic advantage, India will need to majorly accelerate job creation and investment in human capital to keep up with the growing working-age population. For currently, there are 17 million yearly entrants into the job market and only 5.5 million created jobs.  In a survey conducted by the OECD, over 30% of India’s youth aged from 15 to 29 are neither employed nor in education or training (NEETs). 
Isabelle Joumard, senior economist and head of the India desk at the OECD explained: “NEETs include all youth left outside paid employment and formal education and training systems. They are NEET because there are not enough quality jobs being created in the system and because they have little incentives or face too high constraints to be in the education and training systems.” 
Looking from a global point of view, youth unemployment rates remain above 20% in some European economies, the Middle East and North Africa have had youth unemployment rates close to 30% and things have continued to worsen over recent years. Nevertheless, the young people who have found work often have to content themselves with jobs that fail to meet their expectations  and 16.7% of working youth in emerging and developing economies live in extreme poverty .
Why are employment opportunities especially scarce in the least developed countries? Insufficient policy development, poor infrastructure and limited financing channels are among the many reasons for job shortages. According to the findings of e4e (an education for employment initiative driven by the International Finance Corporation and the Islamic Development Bank), the mismatch between education and the labor market demand is a major obstacle to job creation. 
As pointed out by several reports, developing an employability-driven skill ecosystem is key for leveraging India’s demographic potential. Rajasthan, the seventh most populated state in India, has a youth population aged below 25 that makes up nearly 55% of the state’s entire population. From 2012 to 2018, its unemployment rate increased from 4.5% to 7.7%. The problem of unemployment in Rajasthan is compounded with issues, such as the lack of quality trainers and the non-alignment of education and skilling. 
To tackle these problems, the state has continuously intensified the establishment of education infrastructure. In 2004 it became the first state in the country to implement a skill mission aiming to reduce the gap between demand and supply of skilled workforce and hence increase the employment rate. To further improve the quality of skilling, Rajasthan has founded skill universities, a pioneer project in the country. 
In Himachal Pradesh, located in northern India, a large share of employment is in agriculture. More than two thirds of its manpower are self-employed, and the amount of salaried jobs remains very low. In 2018, the Asian Development Bank (ADB) signed a loan with the Indian government to leverage the technical and vocational education and training (TVET) institutions and to scale up skilling ecosystems in Himachal Pradesh. The plans for the project include transforming 11 employment exchanges into model career centers, modernizing training equipment, employing a training information system and creating better access to quality market-relevant TVET for the state’s youth, in order to prepare them for the changing needs of the labor market. 
JANZZ.technology helps governments place workforce into labor markets with AI technology. In collaboration with MTESS and DGE, we have successfully implemented ParaEmpleo — a job matching solution in Paraguay. The collaboration between Paraguay and JANZZ.technology is within the framework of the Support Program for Labor Insertion which was supported by the Inter-American Development Bank (IDB) since 2011. The representative of IDB in Paraguay, María Florencia Attademo-Hirt, spoke highly of JANZZ’s technology, saying: “Innovative tools like this are what will improve the lives of Paraguayans, beyond the Mercosur and regional context”.  The innovative use of technology is the right way to solve today’s labor market problems. If you as a governmental organization are looking for solutions to fight against labor market issues in your country, please write now to email@example.com
 NASSCOM, FICCI and EY. 2017. Future of jobs in India – A 2022 perspective. URL: https://www.ey.com/Publication/vwLUAssets/ey-future-of-jobs-in-india/%24FILE/ey-future-of-jobs-in-india.pdf [2019.04.30]
 OECD. 2017. OECD Economic Surveys India. URL: https://www.oecd.org/eco/surveys/INDIA-2017-OECD-economic-survey-overview.pdf [2019.04.30]
 Guy Ryder. 2016. 3 ways we can tackle youth employment. URL: https://www.weforum.org/agenda/2016/01/3-ways-we-can-tackle-youth-employment/ [2019.04.30]
 ILO. 2017. Global employment trends for youth 2007. URL: https://www.ilo.org/wcmsp5/groups/public/—dgreports/—dcomm/—publ/documents/publication/wcms_598675.pdf [2019.04.30]
 Lars Thunell. 2012. How do we create more jobs for young people? URL: https://www.weforum.org/agenda/2012/01/how-do-we-create-more-jobs-for-the-youth/ [2019.04.30]
 Pwc and FICCI. 2019. Fast forward: relevant skills for a buoyant Indian economy. URL: http://ficci.in/spdocument/23062/FICCI-PwC-rajasthan-report.pdf [2019.04.30]
 ADB. 2018. ADB, India sign $80 million loan to help boost youth employability in Himachal. URL: https://www.adb.org/news/adb-india-sign-80-million-loan-help-boost-youth-employability-himachal [2019.04.30]
 IDB. 2019. Algorithms that get you a job in Paraguay. URL: https://www.iadb.org/en/improvinglives/algorithms-get-you-job-paraguay [2019.04.30]
Eric D. Beinhocker writes in his book The Origin of Wealth: Evolution, Complexity, and the Radical Remarking of Economics that, “over 97 percent of humanity’s wealth was created in just the last 0.01 percent of our history.” It is not until 250 years ago that humankind began to evolve into more prosperous and dynamic societies which offer an extraordinary variety of services.  Today our economic wealth is still growing, and the speed of this process has even been accelerated by the digitalization and automation of the 21st century.
A positive consequence of this development is the high standard of living provided by the increased productivity. However, we also need to live with the potentially negative consequences, which are challenging the security of our jobs. With the prospect of self-driving cars, how many drivers will remain employable in the next 5-10 years? When automated factories are combined with AI technology, how can workers keep up with the new skills required to complete their tasks?
In today’s world, quick and drastic changes make the promise of life-long security impossible. Powerful technology and automation pose a threat in almost every corner of business. Leaving us asking ourselves the question: will I still be employable in 10 years? The good news is that our jobs aren’t disappearing, they are changing. Still, in the era of digitalization and automation, our workforce constantly needs to keep reskilling and upskilling in order to stay up to date. It is time to take action.
More effort is required
increasingly discussing to foster a learning culture environment. Bersin by
Deloitte report that organizations with a strong culture of learning are 92%
more likely to innovate, they enjoy 37% greater employee productivity and are
58% more prepared to meet future demand. 
Stories such as Starbucks’ partnership with a local university to offer its employees an online college degree program are becoming more frequent. Jeff Bezos describes Amazon’s Career Choice program as follows: “For hourly associates with more than one year of tenure, we pre-pay 95 percent of tuition, fees, and textbooks (up to $12,000) for certificates and associate degrees in high-demand occupations”. 
In most of the cases, programs like these are only available in large international corporations with substantial financial capabilities. What about the workers in small and median sized companies who are not provided with these opportunities? Randstad’s Workmonitor survey indicates that more than one-third of American workers have not taken any steps to develop new skills within the past year. While it is sensible to expect employees to maintain up-to-date job skills and to actively seek training opportunities, this responsibility clearly shouldn’t fall solely on the individual’s shoulders. 
Barriers stopping companies
Companies have long been aware of the urgency to increase investment for reskilling and upskilling. In this issue, companies could potentially take the lead instead relying fully on governments. But what are the main barriers stopping them from taking action?
According to a recent McKinsey Global Institute report, rethinking and upgrading the current HR infrastructure is considered a priority by 1/3 of the respondent executives. In the US 42%, in Europe 24%, and in the rest of the world 31% of executives believe reskilling and upskilling is a primary concern. However, many companies lack the knowledge of how jobs are going to change, and they are struggling to figure out how digitalization and/or automation is going to change the future skill set needs. This unpredictability makes it hard to foresee which kind of talent they will be needing in the next five to ten years. Of the private-sector business leaders, only 16% have the confidence that they will be able to meet the future potential skill gaps on a large scale. 
Small to medium sized companies, as mentioned before, are lacking the capabilities to provide their employees with the necessary training, mostly due to financial inability. For many of them, there aren’t any extra resources available for planning and managing training programs. Even if some of them do offer such opportunities, they are confronted with a bigger risk, for well-trained employees might choose to leave for better employers.
As stated in the end of the McKinsey Global Institute report, the willingness of the large companies and senior executives to meet challenges lying ahead is strong despite obstacles. However, neither large corporations nor small to medium sized companies should be left alone in this matter, it is important to discuss the role of governments regarding the issue.
Closing the skill gap is an ecosystem task
Most job trainings are acquired on the job and some job positions are so unique that one cannot receive the right training from any institutional organization. Therefore, it would be efficient for governments to team up with companies to understand and identify skill gaps and to design and conduct training programs, thus preparing the workforce with position-ready skill sets.
Countries such as Germany and Switzerland attach great importance to their vocational training and apprenticeship models. Their outcome in procuring adult technical skills has shown great success and should be adjusted and expanded to an even larger scale.  There are several reasons why this model is especially significant today:
Firstly, due to the frequent updates of technology, the required skills for the jobs have to change more often than before. The model allows the workforce to learn on the job, which will notably minimize the skill gaps. Secondly, the Generation Z born in 1995 and onward have a more practical approach when it comes to education. They adapt to the economics of education and work, measuring their return on investment when choosing what and where to learn.  Therefore, the advantage of vocational education and learning while earning matches the learning attitude of today’s generation. Not to mention the economic benefit of having lower youth unemployment rates.
Low-skilled workers are often left behind by corporate trainings and are most likely to be affected by automation. To solve this issue, governments can provide subsidies to corporation programs to further educate the lower skilled workers. Governments need to ensure a broad-based reskilling, including bringing together different parties such as community colleges and social organizations to provide resources for the vulnerable and disadvantaged groups, such as people with disabilities, single mothers, and refugees. Small to medium sized companies should also be given some degree of financial support when conducting employment training programs. Financial supports could, for instance, come in the form of income tax deductions or public grants to subsidize trainings. 
The government of Singapore has taken the step ahead of many others. Singapore has been offering an outstanding program aiming to promote a culture and overall system of lifelong learning and skills mastery. Since 2016, Singapore has added $ 500 into the SkillsFuture account for every Singaporean aged above 25. This account intends to fund citizen approved courses that develop new and relevant skills for career development. The SkillsFuture Singapore Annual Report 2017-18 states that a significant number of Singaporeans have already benefited from this program since the launch.
Maximizing informal ways of learning
Recently, a 14-year-old American boy has been reported to have achieved nuclear fusion in an old playroom in the house of his parents with the assistance of an online amateur physicist’s forum. In its 2019 State of Software Engineers Report, by Hired, it’s claimed that 1 out of 5 software engineers are self-taught. As stated by Tim Cook, Apple is very proud that half of its US employees who were employed in 2018 do not have a formal four-year undergraduate degree. As the resources of knowledge are more open and easier to access, informal education is becoming even more important.
For adults who are already in the working environment, informal education is the most practical way to receive further education while still making a living. And a significant amount of adult learning is achieved through practical experience, interacting with customers and co-workers and online courses. Therefore, it is important to establish a system to certify the skills people have earned through such informal ways, not only to encourage a learning culture but also to sustain the motivation of learning.
Ironically, while everybody is talking about reskilling and upskilling and how technology is going to change our jobs, some of the fastest growing job fields, such as nursing, medical assistance, elderly care, plumbing and pipefitting, are the ones less affected by technology and automation and don’t need reskilling. However, those jobs are becoming less and less attractive. Perhaps it’s about time to talk less and act on solving feasible problems.
JANZZ.technology has been actively contributing and creating solutions for matching jobs and skills in the digital age such as the newly developed Realtime Labor Market Dashboard. We help corporations, organizations and governments cope with the challenges during the digital transformation and prepare the workforce to adapt to the new labor markets. At JANZZ.technology, we insist on knowing, not guessing. Our technology provides customers with real facts which help make the right decision. The semantic empowered JANZZ.technology is the right tool to rethink and upgrade the current HR infrastructure. For more information, please write now to firstname.lastname@example.org
 Eric D. Beinhocker. 2006. The origin of wealth evolution, complexity, and the radical remarking of economics. Boston, Masaachusetts: Harvard Business School Press.
 Deloitte. Leading in learning. URL: https://www2.deloitte.com/content/dam/Deloitte/global/Documents/HumanCapital/gx-cons-hc-learning-solutions-placemat.pdf [2019.04.01]
 Scott Mautz. 2018. Amazon is paying its employees $ 12,000 to train for a job at another company. And it’s brilliant. URL: https://www.inc.com/scott-mautz/amazon-is-paying-its-employees-12000-to-train-for-a-job-at-another-company-its-brilliant.html [2019.04.01]
 David W. Ballard. 2017. Managers aren’t doing enough to train employees for the future. URL: https://hbr.org/2017/11/managers-arent-doing-enough-to-train-employees-for-the-future[2019.04.01]
 Pablo Illanes, Susan Lund, Mona Mourshed, Scott Rutherford and Magnus Tyreman. 2018. Retraining and reskilling workers in the age of automation. URL: https://www.mckinsey.com/featured-insights/future-of-work/retraining-and-reskilling-workers-in-the-age-of-automation [2019.04.01]
 World Economic Forum. 2017. White paper: Accelerating workfore reskilling for the fourth industrial revolution. URL: http://www3.weforum.org/docs/WEF_EGW_White_Paper_Reskilling.pdf [2019.04.01]
 Jason Wingard. 2018. Training generation Z. URL: https://www.forbes.com/sites/jasonwingard/2018/11/21/training-generation-z/#74223a04bde0[2019.04.01]
- Do not use graphics or tables
- Follow the formatting rules
- Include unique keywords
Sound familiar? These are some of the tips which can help resumes get through an application tracking system (ATS) and eventually land them in front of an HR manager. However, when it comes to new AI technology used in the hiring process, these tips can no longer guarantee the resume getting past the ATS.
What is an ATS and how does it work?
Over 98% of fortune 500 companies, as well as an increasing number of small to mid-sized businesses, are using application tracking systems to filter resumes.  The ATS screens through a large number of resumes and passes the most qualified candidates on to the hiring managers. The principal at HR consulting firm Bersin by Deloitte says, “Most companies have thousands of resumes sitting in a database that they have never looked at.” Actually, 75 % of resumes get lost somewhere in the database and are never looked at by a human. 
When applicants apply for online jobs, their personal information, work experiences, skills, education and other relevant information is uploaded to the database. The ATS assists human resource personnel in managing the candidates throughout the whole hiring process, including sending applicants automated messages to let them know their applications have been received, giving online tests, scheduling interviews and sending rejection letters. 
The drawbacks of ATS
The biggest drawback of ATS is that many of the earlier systems are designed to look for specific keywords and titles in resumes that match with the advertised positions. Even though some ATS providers claim their system has AI capabilities, the search and match results are still very disappointing. This means that if a good candidate, who is switching careers, has a very similar skill set to the one required for the new position but doesn’t have the exact job title in their resume, the system would miss the candidate.
Sometimes recruiters search for candidates by combining multiple keywords, such as job titles, important skill sets and experiences. Even so, a keyword-based system is not capable of finding adequate candidates with an acceptable degree of accuracy and precision. Moreover, the majority of all searches look for terms that are common, such as “Java”, “Project Manager” or “MS Excel”. Unfortunately, this is not the right approach, for with keyword searching, the more trivial the keyword, the less effective the search and the broader the results.
Other drawbacks of an ATS are that it may not understand all abbreviations and that it can only read a certain format. According to a joint survey by CareerArc and Future Workplace, in 62% of companies using ATS, “some qualified candidates are likely being automatically filtered out of the vetting process by mistake.” 
The new technology to upgrade your current ATS
It would be pointless to discuss how to optimize resumes in order to “beat” the ATS. Instead, companies should implement the newest AI technology to optimize their application tracking system for a more efficient and accurate hiring process. JANZZ.technology offers the semantic technology which structures occupations, skills, experiences, functions and many more logically interlinked concepts, which deliver relevant search and match results to hiring managers.
With a semantic ATS, you will never miss talents simply because of wording. For example, when searching for a Chinese coach (e.g. for executive mangers who are going to China regularly to meet clients), a semantically powered system will show results including applicants whose job titles aren’t identical but related, such as, Chinese language tutor, Chinese instructor, Chinese teacher or language tutor specialized in Chinese and Japanese.
A semantic matching engine like JANZZsme! has the most comprehensive, multilingual knowledge graph of occupations and skills at its disposal. When the semantic matching engine does a query expansion, searches or matches job ads and resumes, it accesses the ontology concepts, lexical terms and synonyms, which may appear in CVs and job vacancies in up to 40 languages.
For instance, CEOs (US English) will match with Geschäftsführer (German), 首席执行官 (Chinese) and Managing Directors (UK English). Carpenters will be fully or partly matched with joiners and kitchen unit makers. Design illustrators, animation artists and film animation designers are all fully or partly connected.
Taking programing language as another example; let’s say you are looking for programmers to develop .NET. If programmer A has C# on his resume and programmer B knows Python, the smart matching engine JANZZsme! will successfully match programmer A to your open position, because it knows that C# is a programming language of .NET. This is achieved through the interlinked relationship of the concepts stored in JANZZon!.
Precision in matching is achieved through structure and context. However, neither CVs nor job offers are structured efficiently or consistently, which makes it difficult for a keyword search engine to identify the right data type. A matching engine such as JANZZsme! looks at the type of sought-for data and uses deep learning techniques to identify the correct match while disqualifying matches that are the wrong data type.
CV and job description keyword-based search systems and current CV Parsing technology do not have the same capability to produce high occurrences of accurate matches that contextualized semantic searching and matching has. While the results from a keyword-based search overwhelm hiring managers, a semantic matching engine produces a manageable volume of results, letting hiring managers focus on scanning questionable or unclear data and making the final decision. Thus, radically reducing the amount of needed time and effort.
Do you feel limited by your current ATS (e.g. Oracle Taleo, SAP or IBM Kenexa)? Do you want to optimize it with semantic technology and enjoy more advanced capabilities when searching for candidates, matching open positions and conducting skill gap analyses? To find out how to do so, please write now to email@example.com
 Jon Shields. 2017. Over 98% of fortune 500 companies use application tracking systems (ATS). URL: https://www.jobscan.co/blog/fortune-500-use-applicant-tracking-systems/
 Terena Bell. 2017. The secrets to beating an applicant tracking system (ATS). URL: https://www.cio.com/article/2398753/careers-staffing-5-insider-secrets-for-beating-applicant-tracking-systems.html
 Alison Doyle. 2019. How employers use application tracking systems (ATS). URL: https://www.thebalancecareers.com/what-is-an-applicant-tracking-systems-ats-2061926
 CareerArc. 2016. 23 surprising stats on candidate experience-infographic. URL: http://www.careerarc.com/blog/2016/06/candidate-experience-study-infographic/
Japanese society, one of the world’s oldest and most homogeneous, is about to change. In December 2018, Japan’s parliament passed an immigration bill that is intended to boost the economy and to tackle the country’s labor shortage.
More precisely, the law is designed to attract foreign “semiskilled workers.” These workers are to be employed in various industries, among others, construction, the hotel industry, agriculture and nursing care; in the latter case, shortages are most acute. Despite some protests from oppositional parties, Japan’s Prime Minister Shinzo Abe and his government put the bill through by a vote of 161 to 76. Over the course of five years the immigration bill, which is coming into effect in April 2019, aims to attract 345,000 foreign workers to Japan. 
Japanese cities worried about taking in more foreign workers
A survey conducted by Kyodo News in February this year shows that Japanese cities are concerned about the accommodation of more foreign workers. The issues cities seem to worry most about are of economic nature and include questions of how new foreign workers can be provided with livelihood support and with salaries on a par with local Japanese workers’. 
Both the oppositional protest and the concerns appear to be justified. In 1993, Japan has already once introduced a program concerned with foreign labor, the so-called Technical Intern Training Program. Its purpose was to attract interns from developing countries and to help them acquire technical skills which they could export to their countries of origin. Despite the good intentions behind it, the program has been abused. Many Japanese companies have misused it as a cheap way of employing foreign laborers. This translates to a majority of Japan’s young foreigners doing low-payed “3K jobs” (the three Ks are short for kitsui, kitanai and kiken, the words to describe work that is “dangerous, dirty and difficult”). Many of them receive less than half of the statutory minimum wage, which has a significant impact on the quality of their life and well-being. 
According to the Nikkei Asian Review, Japan wants to complement the new program with a range of measures to support foreign workers in adjusting to Japanese life and to encourage smaller cities to take in foreign laborers. Furthermore, foreign workers’ language proficiency will newly be tested with a focus on spoken Japanese. “People may have various arguments, but if Japan simply continued along the same path, we would find ourselves in a very difficult situation,” Chief Cabinet Secretary Yoshihide Suga says. 
Aging problem is forcing Europe to relax immigration regulation
The 2018 Aging Report, published by the European Commission, indicates that Europe’s population is continuing to age rapidly, with Germany having one of the oldest populations among European countries. The German population pyramid indicates a negative demographic growth and predicts the country’s arrival at a scary milestone this year: there will be fewer citizens under the age of 30 than such over 60.
To fight these current developments, Germany has taken action. In August and September 2015, the country opened its borders to welcome more than a million refugees. Last year’s employment figures show that since then 400,000 refugees have been integrated in work or training, which seems to vindicate Angela Merkel’s much-criticized approach. “After one year of instruction, most young migrants can speak German well enough to participate in vocational school classes,” the head of BDA (Confederation of German Employers’ Associations), Ingo Kramer, states. 
The aging problem also poses challenges for nursing care. Accordingly, many European countries, including Germany, Switzerland, the UK and Finland, are in great shortage of nurses and other professional care providers. To reduce their lack of skilled labor, these countries are introducing relevant policies.
In December 2018, the German government passed a skilled labor immigration law that will make it easier for employers to recruit workforce from outside the EU. In light of Brexit, the UK government is proposing a drastic overhaul of its immigration policy in order to henceforth prioritize high-skilled workers and treat non-EU citizens equally to EU citizens.
A war for skilled migrants
Evidence shows that immigration has played an important role in bringing significant economic benefits, including to the US and Canada. The two countries had the most welcoming immigration policies to attract skilled laborers that aid national businesses in becoming more agile, competitive and profitable in the “war for talent.” Their governments in exchange received more revenue and citizens profited from the momentum created by the influx of high-skilled migrants. 
More recently, other countries, too, have expressed their intent to attract skilled foreign workers, which increases the complexity of the skilled migration boom. The most important decision criteria for skilled workers’ choice of country are language and culture. The English-speaking countries of the US, the UK, Canada and Australia are the so-called “Big Four” of skilled migration and take 70% of all high-skilled migrants to OECD states.  Countries like Germany and Japan are therefore facing serious competition, even if they increase their policy efforts.
Negative aspects of migration
There are, however, also some negative aspects about large-scale migration. Although concerning a relatively small group of people, these negative consequences will have drastic effects. In essence, (im)migration can create unequal power balances. In John Stuart Mill’s words, it is big governments’ responsibility to ensure that the local and short-term social costs do not overshadow the role of (im)migration “as one of the primary sources of progress.” 
Another drawback of migration are the economic losses caused by the “brain drain” in the nations that high-skilled workers leave behind for countries offering higher salaries and better living standards. Most of these left-behind countries are less developed—the departure of their best-trained workers only perpetuates this: not only are they deprived of their high-skilled professionals, thereby they also lose the money invested in these people’s education.
On average, nurses earn 250 to 400 euros a month in Bosnia or Serbia. Compare this to a starting salary of about 1,500 euros in Germany. “We are losing our best experts,” says Zoran Savic, the president of Serbia’s medical workers’ trade union. “Younger doctors will fill in their places, but it takes a minimum of ten years to educate a specialist physician.” 
According to data supplied by POEA (Philippine Overseas Employment Administration), between 2012 and 2016 more than 92,277 nurses have left the Philippines. Low salaries have been one of the main push factors.  In the Philippines, a Bachelor of Science in Nursing program (BSN) takes four years to complete and costs about 30,000 pesos (576 USD) per semester. If only one third of the deployed nurses mentioned held a public BSN, the country has already lost 140,320,097 dollars that it invested in their education.
Similarly, a Kenyan study shows that in Kenya a doctor’s higher-level education costs are approximately 48,169 dollars. If one adds the preceding costs of primary (10,963 USD) and secondary education (6,868 USD), the total education cost for one single medical doctor amounts to 65,997 dollars.  For a country whose economy classifies as lower-middle-income the brain drain caused by the departure of expert workers such as doctors constitutes a major problem.
Migration, the only way to tackle labor shortage
According to the World Bank, developed countries could generate global economic gains of 356 billion dollars if they increased immigration by a margin of 3% of the workforce. Some economists predict that if borders were opened completely and labor forces could be allocated freely the world economy would produce gains of even 39 trillion dollars over the course of 25 years. 
Oxford University professor Ian Goldin indicates that ensuring a strong labor supply augment with foreign workers will become even more crucial in the future. Therefore, today’s governments need to prepare themselves for the labor market challenges laying ahead of them and they can do so by choosing the right tools and technologies to shape the future.
JANZZ.technology offers exactly what is needed to achieve this. With proven high-tech solutions such as the newly developed Realtime Labour Market Dashboard, its unique expertise in occupation and skills data and extensive know-how about the re-skilling and digitization of employment markets, JANZZ.technology provides an array of effective tools. These tools can be used to analyze and correctly predict both the potential and the demand for specific skills in labor markets, as well as provide policymakers and people in charge with the answers to make the right decisions at the right time.
Please write now to firstname.lastname@example.org
 Simon Denyer and Akiko Kashiwagi. 2018. Japan passes controversial new immigration bill to attract foreign workers. URL: https://www.washingtonpost.com/world/japan-passes-controversial-new-immigration-bill-to-attract-foreign-workers/2018/12/07/a76d8420-f9f3-11e8-863a-8972120646e0_story.html?utm_term=.1f730552bd5d [2019.02.26]
 KYODO. 2019. Japanese cities worried about taking in more foreign workers, survey finds. URL: https://www.japantimes.co.jp/news/2019/02/10/national/japanese-cities-worried-taking-foreign-workers-survey-finds/#.XGKdelxKiUk [2019.02.26]
 Christoph Neidhart. 2019. Zuwanderer verzweifelt gesucht. URL: https://www.tagesanzeiger.ch/ausland/asien-und-ozeanien/zuwanderer-verzweifelt-gesucht/story/19372917 [2019.02.26]
 Hiona Shiraiwa. 2018. Japan prepares support for incoming foreign workers. URL: https://asia.nikkei.com/Spotlight/Japan-Immigration/Japan-prepares-support-for-incoming-foreign-workers [2019.02.26]
 Jorg Luyken. 2018. Angela Merkel was right about refugee integration, says German business federation chief. URL: https://www.telegraph.co.uk/news/2018/12/14/angela-merkel-right-integration-figures-show-400000-refugees/ [2019.02.26]
 Ian Goldin. 2016. How immigration has changed the world for the better. URL: https://www.weforum.org/agenda/2016/01/how-immigration-has-changed-the-world-for-the-better/[2019.02.26]
 INTHEBLACK. 2016. Which countries are winning the global talent war? URL: https://www.intheblack.com/articles/2016/12/01/which-countries-are-winning-the-global-talent-war[2019.02.26]
 Daria Sito-Sucic. 2017. Nurses, doctors leave Balkans to work in Germany. URL: https://www.reuters.com/article/us-balkans-healthcare-germany/nurses-doctors-leave-balkans-to-work-in-germany-idUSKBN16G18X [2019.02.26]
 Don Kevin Hapal. 2017. Why our nurses are leaving. URL: https://www.rappler.com/move-ph/180918-why-nurses-leave-philippines [2019.02.26]
 Yusuf Abdu Misau, Nabilla Al-Sadat and Adamu Bakari Gerei. 2010. Brain-drain and health care delivery in developing countries. URL: https://www.researchgate.net/publication/46179307_Brain-drain_and_health_care_delivery_in_developing_countries [2019.02.26]
To many people, the word ‘ontology’ might sound abstract. It has its origin in Tim Berners-Lee’s dream of inventing the World Wide Web. This dream included the Web becoming capable of defining a so-called ‘Semantic Web’ by analyzing all Web data, including content, links and computer-person transaction. In the Semantic Web, the Resource Description Framework (RDF) and Web Ontology Language (OWL) have been established as standard formats for sharing and integrating both data and knowledge—the latter in the form of rich conceptual schemes called ontologies.  In this article the word ontology serves as the working definition, however it is worth mentioning that in today’s IT world there is also a broad use the term ‘knowledge graph’ to refer to this concept.
Why to care about ontology
With regard to artificial intelligence (AI), the terms ‘big data’, ‘machine learning’ and ‘deep learning’ are slowly replacing the usage of ‘AI’. However, to quote Adrian Bowles, “there is no machine intelligence without (knowledge) representation.” In other words, AI requires some elements of knowledge engineering, information architecture and a significant amount of human work to do its ‘magical neural work’. Fittingly, Alexander Wissner-Gross finds that, perhaps most importantly, we need to recognize that it is intelligent datasets—not algorithms—that are likely to be the key limiting factor in the development of human-level artificial intelligence.
“there is no machine intelligence without (knowledge) representation.”
An ontology is a structured and formal representation of relative knowledge in a certain domain. This is necessary, because unlike humans it cannot directly rely on human background knowledge about a term’s correct usage. What an ontology can do, however, is to “learn” about the semantic meaning of a term through the interlinks between the concepts in its system. Powerful ontologies already exist in specific domains, examples include the Financial Industry Business Ontology (FIBO) as well as numerous ontologies for healthcare, geography or occupations.
Another important part of AI is semantic reasoning. In addition to identifying potentially fraudulent transactions, determining users’ intent based on their browser history and making product recommendations, AI can also do the following: It can execute tasks that require explicit reasoning based on general and domain-specific knowledge, such as understanding news articles, preparing food or buying a car. Thus, such tasks require information that is not part of the input data but needs to be dynamically combined with knowledge. This type of machine reasoning can only be achieved with ontologies and the way their knowledge is modeled. 
Taxonomy and ontology are fundamentally different
Ontology is often confused with taxonomy. Apart from the fact that both belong to the fields of AI, the Semantic Web and system engineering, there is really not much that would characterize them as synonyms. Taxonomy classifications such as O*NET (Occupational Information Network) and ESCO (European Skills/Competences, qualifications and Occupations) simply cannot be compared to ontologies. They provide a much simpler approach to classifying objects, as they have a hierarchical structure and utilize only parent-child relations without any additional, more sophisticated links. Ontologies, on the other hand, are a much more complex form of categorization. Speaking metaphorically, a taxonomy equals a tree whereas an ontology comes closer to a forest.
For example: The term ‘golf’ could appear in several taxonomies. It might be located under a ‘Human Activities’ tree (human activities -> leisure activities -> sports -> golf). It could also be found under a taxonomy concerning apparel (apparel -> casual/active apparel -> sporting apparel -> golf clothing and accessories). It could even appear in something quite different, for example an automobile taxonomy (automobile -> Germany -> VW -> Golf). Each of these taxonomies can be considered a tree whose branches touch at their ‘golf’-related nodes. 
Put differently, taxonomies represent a collection of topics with ‘is-a’-relationships while ontologies allow for much more complex connections, such as ‘has-a’- and ‘use-a’-relations.  Hence, if we return to the classification example above, taxonomies lack the capability to compare child concepts.
In the classification of ESCO, almost all medical specialists are grouped under the heading ‘Specialist Medical Practitioners’. Furthermore, specialist skill sets are simply grouped in lists without any links to the respective specialist occupations. Why is that? One reason is that classifications are mainly used for statistical purposes. From this viewpoint there is no need to further classify all individual medical specialists according to their skill sets and training background. Therefore, according to taxonomies, specializations can only be recognized by their job title and one needs to refer to other sources to better understand their individual meaning.
Building an ontology of occupations, qualifications and skills makes it possible to automatically recognize similarities and differences between job titles. For example, pediatricians and neonatologists have similar jobs, both of which concern themselves with the medical care of newborn infants. With the ontology modeling approach, it is possible to determine that a pediatrician has a very high percentage of similar skills to those of a neonatologist. However, pediatricians can only take over the neonatologist’s job after further training. All this information can be represented in an ontology through the interrelationships between concepts. This goes beyond the capacity of a simple taxonomy.
Ontologies enable matching datasets
When it comes to matching, say the matching of CVs with vacancies, there is no better way than to use an ontology. All too often, simple keyword-based matching or fuzzy machine learning methods are used for this, which means that many similarities go undetected and cannot be matched, such as keyword variations, synonyms and alternative phrases. When matching, it is important to compare the semantics (the underlying meaning) of two items rather than the wording. This is where ontologies come into play. They can provide a semantic modeling that can detect the underlying meanings and similarities in CVs and job descriptions.
The ontology matching technique represents a fundamental technique in many areas, such as ontology merging. In domains with very complex rules (and complex interactions between rules) there’s no substitute for ontologies. This is shown, for instance, when you consider integrating disparate domains. Let’s say there are two separate ontologies, a weather ontology and a geographic ontology, when considering navigation or insurance risks, to create a third ontology which integrates and leverages the other two is a manageable proposition. 
True value of ontologies
The semantic system relies on explicit, human-understandable representations of concepts, relationships, and rules to develop the desired domain knowledge. It is impossible to rely solely on programmers to build such a system based on machine learning, as they lack the knowledge needed to define relationships between concepts in the specific domains. Therefore, the domain knowledge must be learned from domain experts with various backgrounds (e.g. intellectual property law, fluid dynamics, car repair, open-heart surgery, or educational and vocational systems). This process is crucial for creating a comprehensive knowledge representation.
For the multi-lingual JANZZ ontology language skills are a key point. In many cases, a one-to-one translation of a concept into multiple languages isn’t possible, however, thanks to Switzerland being small and integrated, all the JANZZ ontology curators are fluent in at least two languages and some even speak more than four (including Chinese and Arabic). This advantage guarantees the ontology’s consistency and quality across different languages.
About a decade ago, JANZZ started building its ontology on various occupation taxonomies, namely ISCO-08, ESCO and all country-specific classifications. Over the years, JANZZ has added thousands of new professions and functions (e.g. Market Research Data Miner, Millennial Generational Expert and Social Media Manager) to the JANZZ ontology, which didn’t exist before in any of the known taxonomies. Besides job titles, also up-to-date skills, education, experience and specializations have been included in the ontology. It is the right tool for HR and Public Employment Services, which recognizes the similarities and ambiguities among job titles, rather than being a collection of terms like a taxonomy. Today, the JANZZ ontology is by far the largest, most complicated and most complete occupation data ontology in the world.
For private corporations and public employment services trying to choose between a classification system based on a taxonomy and a classification system based on an ontology, we hope this article helps you make the right decision and helps you realize that investing in a non-semantic system (without content) will not get you any further. Luckily, some governments and corporations have chosen the right path and have already benefited from our newest technology. If you would like to know more about the JANZZ ontology, please write now to email@example.com
 Ian Horrocks. 2008. Ontologies and the Semantic Web. URL: http://www.cs.ox.ac.uk/ian.horrocks/Publications/download/2008/Horr08a.pdf [2019.02.01 ]
 Larry Lefkowitz. 2018. Semantic Reasoning: The (Almost) Forgotten Half of AI. URL: https://aibusiness.com/semantic-reasoning-ai/ [2019.02.01]
 New Idea Engineering. 2018. What’s the difference between Taxonomies and Ontologies? URL: http://www.ideaeng.com/taxonomies-ontologies-0602 [2019.02.01]
 Daniel Tunkelang. 2017. Taxonomies and Ontologies. URL: https://queryunderstanding.com/taxonomies-and-ontologies-8e4812a79cb2 [2019.02.01]
 Nathan Winant. 2014. What are the advantages of semantic reasoning over machine learning? URL: https://www.quora.com/What-are-the-advantages-of-semantic-reasoning-over-machine-learning [2019.02.01 ]
In Japan, one person in five is 70 or older. According to last year’s data of the Internal Affairs and Communications Ministry, 26.48 million people are 70 or older, which accounts for 20.7% of the total population . If you go to Japan, you will see many senior citizens still working in the shops or running around the streets in suits. There, the term “elderly” has been redefined. In fact, a group of academic societies suggested only considering people “elderly” as of age 75 and people from age 65 to 74 as “semi-elderly” who can actively contribute to society .
Due to the shrinking core labor force and the long lifespan of Japanese people, the number of employed senior citizens (65 and older) reached 8.07 million in 2017, which makes up 12.3% of the overall workforce . Currently, the statutory retirement age in Japan is 60, however, few people are taking their pensions at that age. Due to the fact that citizens are able to receive a pension anytime between 60 and 70 most Japanese seniors choose to work beyond the age of 60. Last year, the Japanese government approved plans to raise the optional age for receiving pensions to 71 and older and they are also considering raising the statutory retirement age to 65.
Aging problem is worldwide
Japan is not alone in this. The problem of population ageing is challenging governments worldwide. Many countries have carried out reforms aiming to increase the retirement age. According to the German federal government website, as of this year, the retirement age will increase from 62 to 65. Also, the Russian government has submitted a pension-reform legislation that proposes raising the retirement age from 60 to 65 by 2028 for men and from 55 to 63 by 2034 for women.
Some of the senior citizens are happy to continue working in order to help themselves stay mentally and physically fit. However, for those who have a hard-working life and are counting the days to retirement, the prospect of having to work until 70 is a dire one. Furthermore, this kind of development means that young graduates are worried about their job prospects.
Compared to young people, knowledge and experience are among the strengths of older workers. However, there are also many factors that make companies hesitate to employ them. Declining physical capacity prohibits seniors from continuing the kind of work that requires extreme physical fitness, such as fire fighting, construction work or gardening. What’s more, with the rapid changes in technology, it is especially difficult for the elderly to keep up with the newest developments.
The value of the “silver employees”
Certain companies have discovered the value of the “silver employees”. The Japanese cosmetics company Pola is one of them. Many Pola employees are in their seventies and older. For example, Miyoko Sugiyama, an 83-year-old store director of one of the Pola shops. She knows all the preferences, ages, health status and shopping habits of her 30-odd clients. When new products come out, she goes to visit her clients personally by bike or train to inform them about these products. Sugiyama is one of Pola’s 50,000 “beauty directors”. Among them, 5,500 are in their 70s, 2,500 are in their 80s, 250 are in their 90s and recently one of their salespeople turned 100. 
Manufacturing companies are staring to realize the value of older workers, too. There, passing on the skills of experienced workers to younger workers is key. At, bearing manufacturer Isoda Metal this is well understood. About a decade ago, the company started allowing skilled workers who have passed the statutory retirement age to continue working. Grinding bearings requires accuracy within a 100th of a millimeter which takes years of experience and intuition to manage. Today a quarter of the company’s workforce is in their 60s to 80s and many of them double as instructors of younger workers. 
Creating easy working environment for the elderly
As pointed out by Peter Cappelli, director of the Center for Human Resources at the Wharton School at the University of Pennsylvania, “in Japan, it’s now less about keeping people working at the same companies longer and more about trying to get them into alternate jobs and to do other kinds of things” . Furthermore, Professor Caitrin Lynch at Olin College of Engineering said that governments should create meaningful jobs for older workers that offer them satisfaction and a sense of meaning and of belonging, thus establishing a working environment and working conditions that keep them motivated for work. Even though this seems costly in the beginning, in the long run it pays off. 
For almost a decade, JANZZ.technology has been observing and working with many labor markets worldwide. Our matching engine “JANZZsme!” matches in a completely unprejudiced manner, as it is based on the relevance of competences, experiences, specializations, industries and more. It creates transparent and easy to understand gap analyses of the labor market. This will give you a clear idea of which skills are available and which ones should be expanded or redeveloped.
Write now to firstname.lastname@example.org
 The Japantimes. 2017. For the first time, 1 person in 5 in Japan is 70 or older. URL: https://www.japantimes.co.jp/news/2018/09/17/national/number-women-japan-aged-least-65-years-old-tops-20-million-first-time/#.XDR0PFxKiUk [2019.01.10].
 The Japantimes. 2017. Make is easier for elderly people to keep working. URL: https://www.japantimes.co.jp/opinion/2018/02/23/editorials/make-easier-elderly-people-keep-working/#.XDR9SFxKiUl [2019.01.10].
 Nippon. 2017. Senior-citizen workers in Japan top 8 million. URL: https://www.nippon.com/en/features/h00179/ [2019.01.10].
 Manabu Ito. 2016. Japan puts its seniors to work. URL: https://www.ft.com/content/7a879e66-6b78-11e6-a0b1-d87a9fea034f [2019.01.10].
 Richard Eisenberg. 2017. How these 3 countries embrace older workders. URL: https://www.forbes.com/sites/nextavenue/2018/05/10/how-these-3-countries-embrace-older-workers/#72b6c8171bd4 [2019.01.10].
 Caitrin Lynch. 2015. Create meaningful jobs for the elderly. URL: http://www.nira.or.jp/pdf/e_vision9.pdf [2019.01.10].
Due to digitization, jobs will disappear. This is old news to our ears. Yet, the predicted consequences made by the first comprehensive study on the effects of digitization by 2030 are devastating: In Switzerland alone at least 1 million jobs are said to disappear, which is a frightening figure for a population of about 9 million people. In fact, McKinsey & Company find that almost entire industries are affected – but they also anticipate that digitization enhances productivity and creates new jobs.
Especially manual and simple cognitive skills at risk
McKinsey & Company’s study “The future of work: Switzerland’s digital opportunity” predicts that 20 –25% of jobs in Switzerland are at risk of disappearing. Above all, it is manual and simple cognitive jobs such as cashiers, data collectors, warehouse clerks or production assistants that under digitization need no longer be performed by people. Thanks to a large number of small technological innovations, these jobs are already increasingly automatized today – this will increase considerably by 2030. Manual skills, too, will be increasingly less in demand, especially so-called low-skilled jobs. Statistical, reading and writing skills will also become highly automated by 2030. Likewise, there are already very good tools available for successful project management. This poses a particularly major challenge for the Swiss banking sector where many of these skills are crucial. There is already a growing number of bank customers who dispense with personal consulting and prefer instead the information portals of online banking. In numbers, the expected amounts of jobs that will disappear are about 50,000 jobs in the financial sector, 120,000 in the retail trade and 70,000–100,000 in the industrial sector.
New jobs in 2030
Of course, digitization also requires new skills, which is why there is a simultaneous generation of new jobs and positions, particularly with regard to technological, scientific and social skills. After all, digitalization has to be carried out by humans, hence its very implementation stimulates the growth of new job opportunities during the transition period. Unfortunately, the newly created 800,000 jobs in these areas will not coincide with those in which positions are currently disappearing. Rather, “Digital Transformation Officers” and “Project Managers Internal Digitization” are now in demand.
So, jobs cannot simply be redistributed: for example, a machine operator will not be able to become a project manager without great outlay. Neither will a cashier just assume the tasks of a nurse. Therefore, it is important to take measures in training at an early stage; partly because retraining is costly, partly because it is difficult to perform with broad sections of the population. The same goes for skills and soft skills: technological understanding, or the empathy and strength to provide for elderly and sick people are not natural givens to everyone.
Strong growth in health sector
The increase in new positions will not only be in the technological sector, but also in healthcare. One decisive factor in this area are social skills. An important contributor to this development is the fact that society is ageing: by 2030, 23% of the Swiss population will be over the age of 65, compared to 18% today. Accordingly, the demand for nursing staff is increasing considerably. In the health sector an additional demand of up to 85,000 employees is expected, especially of health and trained nursing professionals. This is in contrast to the fact that there are both already too few people being trained and many who leave their jobs after a while; among health professionals, it is as many as three out of four. Among registered nurses, about half remain in their profession. There are many reasons for this: shift work, hard physical labor as well as low wages.
This shortage in healthcare professionals cannot only be found in Switzerland, but worldwide. A study finds that in near future the United States’ lack of health staff will increase by some 2 million people, especially with regard to nursing care at home and in retirement homes. Yet, it is exactly these jobs which have an extremely low pay, with some of them being way below the median American income. Likewise, it is precisely these kinds of jobs that include physically challenging and inconvenient shift work. Under the current circumstances it is very unlikely that the necessary positions will be occupied.
How to finance and structure the future labor market
At first glance one would think that it is nice that especially physically challenging work will be made easier with the introduction of robots and other technological aids. Unfortunately, this also brings financial alleviation to health insurance funds. How, then, will we finance the future labor market, or, for that matter, road construction, schools or the necessary equipment for digitized world? Are we going to introduce a “digitization tax”? Will employers have to pay pension insurance “for” robots to compensate for the remaining human workforce?
The question also remains whether such a takeover by robots is even permitted. Changes that so far were monitored by human eyes will now be perceived by screens. Is this even legally defensible? Many procedures would furthermore require specific certificates. Thus, how can one secure a robot’s competence? Can robots, for example, pass driving tests?
The clarification of responsibilities is already difficult today, particularly when it comes to mistakes. Oftentimes, the determination of the responsible party requires months of assessment. Thus, will we soon be able to take out “robot insurance”?
The problems are the same worldwide
As indicated, it is not only Switzerland that is facing the outlined challenges. In Germany there is already a MINT staff shortage of 300,000. In the US, a large-scale study examined 702 jobs for their probability of automatization and concluded that 47% of the American working population is highly likely to be affected. Jobs requiring a high level of social intelligence (e.g. press spokespersons), creativity (fashion designer) as well as good comprehension and operation (surgeons) are hardly at risk. The situation looks similar if one looks elsewhere. The investment group CBRE finds that until 2025 50% of jobs in Asia will be at risk, especially in manual and cognitive areas.
In Germany the gravity of the situation has been recognized. The country is introducing a law that simplifies immigration for skilled workers, a measure to counteract the growing shortage, particularly in the health sector. The law applies to citizens of third countries, that is, non-EU countries that already benefit from the free movement of persons. This means that anyone with a sufficient qualification for an employment contract can immigrate. There will also be a six-month visa for the time necessary for job search. The current measure, namely the check whether an EU-citizen can perform the job, is cancelled. There are similar ideas developing in the UK, where in early 2019 a new start-up visa will be introduced. The UK’s intention behind this is to make it easier for foreign technology entrepreneurs to set up new businesses
Making transformation a success
How should these challenges be met? Digitization pushes two tasks to the foreground. Firstly, the transformation of the economy ought to be supported decisively but should not be done too quickly. Too rapid a transformation could lead to higher unemployment, if the situation arises that new skills have not been developed fast enough. Transformation also requires new processes and business models. For example, only 8% of trade in Switzerland takes place online, compared to 15% or 18% in Germany and the UK, respectively. If digitization succeeds, the Swiss economy in particular will be able to benefit considerably from the transformation and might increase productivity by up to one percent per year. Furthermore, higher real wages are likely to increase consumption and, in turn, to create new job positions.
Training instead of waiting
Concurrently, the focus must lie on the fundamental training of employees and learners in the skills of the future. To this end, teaching should have much more technological content. For example, trainees should be able to perform more office tasks on the computer. Today, the demand for technology graduates in Switzerland is far from being met; in the future, the 3,000 graduates now available would cover less than half of the positions to be filled.
Furthermore, it has been shown repeatedly that social skills are fundamentally underestimated: they play a major role in the long-term successful development of the labor market. This is another area in which companies and educational institutions should start to provide comprehensive training. Overall, thus, a fundamental rethinking of the development of skills is indispensable.
Clear, unprejudiced gap analysis for a successful transformation
For almost a decade, JANZZ.technology has been observing and working with many labor markets worldwide. Our matching engine “JANZZsme!” matches completely unprejudiced, as it is based on the relevance of competences, experiences, specializations, industries and more. It creates transparent and easy to understand gap analyses of your employees’ skills. This will give you a clear idea of which skills are available and which ones should be expanded or redeveloped. Contact us now for a consultation and we can accompany you with our know-how on your successful way to digitization.
Write now to email@example.com
 McKinsey Global Institute. 2018. The Future of Work: Switzerland’s Digital Opportunity. Zürich/Brüssel. URL: https://www.mckinsey.com/~/media/mckinsey/featured%20insights/
 Hug, Daniel. 2018. Bis 2030 fallen in der Schweiz eine Million Jobs weg. In: NZZ am Sonntag, 6.10.2018. URL: https://nzzas.nzz.ch/wirtschaft/bis-2030-fallen-in-schweiz-eine-million-jobs-weg-ld.1426280?reduced=true [2018.11.10].
 AsiaOne. 2016. Top 10 careers that are dying a slow death. URL: http://www.asiaone.com/business/top-10-careers-are-dying-slow-death [2018.11.08].
 Frey, Carl Benedikt, Osborne, Michael A. 2013. The Future of Employment: How Susceptible are Jobs to Computerisation?. Oxford. URL: https://www.oxfordmartin.ox.ac.uk/downloads/academic/future-of-employment.pdf [2018.11.10].
 Oh, Soo. 2017. The future of work is the low-wage health care job. URL: https://www.vox.com/2017/7/3/15872260/health-direct-care-jobs [2018.11.10].
 MAMK/DPA. 2018. Arbeitgeber melden Rekord beim Fachkräftemangel. In: KarriereSPIEGEL. URL: http://www.spiegel.de/karriere/fachkraeftemangel-arbeitgeber-klagen-ueber-fehlende-mint-kraefte-a-1207636.html [2018.11.08].
 Bauer, Karin. 2018. Welche Jobs bleiben, welche verschwinden. In: Der Standard. URL: https://derstandard.at/2000078804017/Welche-Jobs-bleiben-welche-verschwinden [2018.11.09].
 Walser, Rahel. 2017. Beruf Fachkraft Gesundheit – Nach der Lehre die grosse Ernüchterung. URL: https://www.srf.ch/news/schweiz/beruf-fachkraft-gesundheit-nach-der-lehre-die-grosse-ernuechterung [2018.12.03].
 Böcking, David. 2018. Einwanderungsgesetz für Fachkräfte. Wer darf künftig zum Arbeiten nach Deutschland kommen? In: Der Spiegel. URL: http://www.spiegel.de/wirtschaft/soziales/fachkraefte-die-offenen-fragen-beim-einwanderungsgesetz-a-1239722.html [2018.12.05].
 Hoock, Silke. 2018. Abschiebung nach Mazedonien. Wieder eine Krankenschwester weniger. In: Der Spiegel. URL: http://www.spiegel.de/wirtschaft/abschiebung-krankenschwester-amela-memedi-muss-nach-mazedonien-a-1239890.html [2018.12.05].
 The Government of United Kingdom. 2018. New start-up visa route announced by the Home Secretary. URL: https://www.gov.uk/government/news/new-start-up-visa-route-announced-by-the-home-secretary [2018.12.03].
Skimming over CVs (resumes, in the US) is an important part of HR managers’ job, but it can be a tedious task: at times, there is a need to go through thousands of documents in order to find the right candidate. Thanks to recent technological developments, today software can save HR the effort by recommending only the best matches between the contents of CVs and job ads. Although interpersonal aspects—for example, whether a candidate fits in with the company culture—still have to be considered by human judgement during interviews, » Read more about: We need to re-think the CV »
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