Free movement of skilled workers in the EU and beyond are more important than ever

Do you know how to build a house? If not, maybe you should consider learning it right now. In 2030 there is a high chance that we will have a critical shortage of construction workers. This is your opportunity to pick up the skills such as installing electrical wiring, carpentry, blockwork, waterproofing and plumbing.

According to the 2020 report by the Schweizerischer Baumeisterverband (Swiss Building Association)[1], the Swiss construction industry is facing massive problems: fewer and fewer young people are willing to learn a trade in construction, and many of the current skilled workers are about to retire. Compared to 2010, 40% less young people started a bricklayer apprenticeship in 2019. This will have a critical impact on the entire industry because the majority of construction foremen, supervisors, and construction managers are recruited from the bricklayer pool. On the other hand, the proportion of people aged over 50 in the main construction industry is up to 36%. The expected outcome of this combination is alarming.

In recent years, the level of professional qualifications on construction sites has risen sharply due to digitalization, leaving the typical unskilled worker now barely in demand and creating a skill gap between supply and demand of workforce in this sector. However, the drivers of skills shortages are much more complex.

Demographic trends

Lower birth rates and increasing life expectancy are the two key demographic trends in Switzerland and the European Union. An ageing population paired with a shrinking working-age population have intensified the situation in the labor market. According to data from Eurostat [2], the share of working-age population in the total EU population decreased by more than 2% from 2010 to 2018 and the median age increased by almost three years to 43.1 during the same period.

On top of this, the impact of baby boomers heading into retirement has yet to fully unfold. A study by Credit Suisse [3] states that a total number of around 1.1m people will reach retirement age in the next ten years and the younger generation will not be able to fill the vast number of highly skilled jobs vacated by this post-war baby boom generation. Studies from other Central European countries reveal similar expectancies concerning the impact of baby boomers on their labor markets.

However, multiple reports have indicated a shortage of skilled workers in the construction sector for countries that do not have this demographic shape, such as South Africa and India. Apparently, a more general factor is causing the skill shortage in construction on an international level.

Negative image

Many studies from around the globe show that the construction industry has a negative image, especially among the youth. For instance, in a study conducted in a high school by the national business employment weekly in South Africa, careers in construction came in at number 247 out of 250 potentially attractive career options [4]. CITB data in 2013 [5] found that in the UK, the overall appeal of the construction industry as a career option had fallen to only 4.2 out of 10 among adolescents aged 14 to 19, and the Union of Construction, Allied Trades and Technicians (UCATT) also reported a 14.6% fall in construction apprenticeship numbers in 2013. This was confirmed again in a 2017 poll. In the US, only 3% of youth aged 18-25 wanted to work in the construction trades in a 2017 survey [6].

Despite the bright prospects of a career in an in-demand field, the youth just can’t seem to get past the industry’s bad image: low wages and job security, health and safety concerns, low-quality work, and tough working conditions are the aspects that the youth most associate with jobs in construction and deter them from pursuing a career in this sector. Moreover, the rise of digitalization feeds a false fear that jobs in construction will fall victim to automation in the future.

Indeed, some occupations in construction have a higher potential for automation, but technically, it is not feasible to perform certain tasks with robots. Even physical work, which many assume most likely to be automated, can be too challenging for robots – especially physical tasks in unpredictable and changing environments.

Moreover, when referring to professions in construction, people mostly think only of on-site activities, often overlooking the professions related to sub-sectors such as real estate, procurement, architectural or engineering activities, which enjoy a higher social status and could be very attractive to both genders.

 Growing interest in the academic route

In the dual education system practiced most notably in Germany, Austria, and Switzerland (DACH), most career paths in the construction sector start with vocational training and apprenticeship. A long-standing tradition in these countries, the dual system was well received by parents, adolescents, and society at large. Lately, an increasing interest in university degrees has posed a direct challenge for the professions in the construction sector and for other skilled trades.

By the time university graduates are faced with making a career choice, it is far too late to attract them to the construction site. Research shows that timing is key for sparking interest in construction professions, and the highest success rates are reported when engaging school children at the primary level. Accomplishing this will require joint efforts to bring about fundamental changes to the education system and foster deeper collaboration between industry and educational institutions.

Indispensable free movement of skilled workers

This is certainly a promising strategy for the long term and future workforce generations. In the short and midterm, however, national economies – particularly in industrialized and industrializing countries – will highly depend on flows of skilled workers among countries all over the world to alleviate the workforce shortages. Indeed, as noted by the ILO [7], migrants are a vital source of skills and labor for industries such as construction. By nature, construction requires flexible teams with a variety of skills, and is thus often deeply dependent upon migrant workers due to their mobility and flexibility. Therefore, solutions contributing to the free movement of persons will rapidly grow in demand. However, to ensure true free movement of workers, an important issue needs to be addressed from the start: the recognition of qualifications among different countries and even regions.

Challenges in skills recognition

In the EU, the Professional Qualifications Directive (PQD), the European Qualifications Framework (EQF), and the European Credit System for Vocational Education and Training (ECVET) serve as the main instruments for the recognition of professional and academic qualifications to support workers’ mobility across Europe. However, despite significant efforts such as the launch of the European Skills, Competences, Qualifications and Occupations (ESCO) classification system, skills recognition and matching among the member countries are still very disappointing, not to mention internationally. Comparing skills across borders poses two significant challenges: first, many countries have their own classification systems or taxonomies, which each need to be mapped into a transnational system. But not all have already effectuated this. Second, not all skills and qualifications translate easily. For instance, a carpenter who completed an 18-month apprenticeship in the UK will have a different skill set than a carpenter with a three-year apprenticeship in Austria, even though both completed standardized training for the same skilled trade.

For this reason, more and more investments and expectations are placed on ontologies and semantic technologies as the solution to overcome these challenges. Currently, JANZZ’s ontology is the largest multilingual encyclopedic knowledge representation in the field of occupation data. Not only can it translate the many linguistic variations in occupational jargon into a common vocabulary, but more powerfully, by human expert curating, it can truly compare differences and similarities in education and qualifications across borders and language divides – thus delivering a meaningful contribution towards true free movement of skilled workers.

Contact us now to understand how JANZZ’s ontology can assist you in education and qualification recognition for your workforce.

 

 

[1] Zahlen und Fakten 2020, Schweizerischer Baumeisterverband SBV

[2] European Commission, Improving the human capital basis, Analytical Report (March 2020)

[3] Credit Suisse, Fear of recession exaggerated (September 2019)

[4] Makhene, D., Thwala, W.: Skilled labour shortages in construction contractors: a literature review

[5] UK Construction: An Economic Analysis of the Sector (July 2013)

[6] Young Adults & the Construction Trades, NAHB Economics and Housing Policy Group

[7] Buckley et al.: Migrant work and employment in the construction sector, Geneva: ILO, 2016

Hiring and managing a changing workforce

Remote working, temporary contracts and project-based employment have been shaping the traditional jobs, causing governments and corporations to rethink job offerings in short-term arrangements.

JANZZ.technology has been following the trends, shaping the future of work and collaborating with many labour markets worldwide. We are active in semantic parsing, searching and matching within occupation domain. Our technology can realize data-driven HR decision-making, speed up people analytics and use workforce data for business performance prediction. If you are looking for the right skilled employees or want to identify learning gaps to meet future business needs, contact us and we will explain to you how our products, consulting services and innovative solutions can help you.

Perhaps, this time, “working from anywhere” is here to stay

When people were still debating the future of flexible working and how technology and digitalization are going to change how we work, after COVID-19, that future has arrived much sooner than anticipated. Gartner stated in its report that 48% of employees will likely work remotely compared to 30% before the pandemic. [1]

How has the workplace changed over time?

Back in the days, the workplace was much less tech-oriented, and business conversations were conducted through landlines or in person. Documents and files were all hard copies. Employees were expected to work independently, and cubicles were present in the office. Since the 1950’s, major changes took place and the emergence of teamwork, computers, the internet, and business-oriented software has had a tremendous impact on how we work.

Over the past 20 years, one of the most significant workplace changes has been the technical transformation to a digital workplace. The workplace has undergone even greater revolutions such as telecommuting, zoom, co-working space, and flexible working. The elimination of fixed workplaces first appeared in Silicon Valley technology companies known as flexible working or the upgrade of activity-based working. Basically, employees want more freedom during work and their homes or even a café are gradually becoming their second “office”.

Remote work, who is ready or, more precisely, who is capable?

In an article published by Harvard Business Review, the robustness of digital services, internet infrastructure, and digital payment options were used to evaluate 42 significant global economies in terms of the readiness for remote work. [2] In the survey we can see that countries such as Singapore, UK, US, Netherlands, Norway, Canada, and Germany are placed in a better position while countries like India, Indonesia, Thailand, Chile, Philippines, and China are shown less prepared. However, the readiness of technology is only the external factor triggering the practice of remote work, and it can be influenced with the effort of country leaders by investing in infrastructure and technology.

The internal factor, thus the structure of different industries within a country is the key here. In countries where the main economic activities fall into the agriculture and manufacturing sectors, it is unlikely for its workforce to work remotely because farmers and blue-collar workers simply cannot work from home. On the other hand, countries whose service sectors produce a majority of their economic value, have a workforce, or more precisely a knowledge workforce, that is not attached to the workplace anymore. According to the knowledge economic index (KEI) from the World Bank Institute, countries such as Denmark, Sweden, Finland, Netherlands, Norway, Canada, and Switzerland, are among the top. [3]

The downsides of remote work

COVID-19 forced companies around the globe to practice full-time flexible working and some countries, where flexible working was not common, needed to adapt to the new situation quickly. For such countries, it is also important to understand the negative sides of flexible working when handled unproperly.

When the time spent in the office is no longer the key factor for being paid, flexible working must have a new pay-related appraisal criterion, hence performance is taken as the new measurement. In order to justify their efficiency and be seen as high-achieving and trustworthy, employees often agree to higher target agreements. This can lead to so-called “interested self-endangerment” causing the detriment of health. Therefore, companies should not ask too much of their employees or else they might risk the utility of flexible working. [4]

Digitalization shifts the boundaries between free time and work allowing people to spread their work across the whole day so they can better combine work and life. However, in a survey conducted in Germany, half of those surveyed said that digitalization increases the intensity of their work. They feel more stressed and their workload has piled up, and they also feel subjected to stricter supervision. [4]

The challenge in the gig economy era

Flexibility in jobs is no doubt one of the key features in the gig economy which is transforming our labor market drastically. The work today is changing towards being more cognitively complex, technology-dependent, collaborative, mobile, and border-crossing. This presents a huge challenge for governments and corporations today to match the right skills and qualified people with jobs and to identify the education and learning gaps to meet future business needs.

For almost a decade, JANZZ.technology has been following the trends shaping the future of work and working with many labor markets worldwide. We are active in semantic parsing, searching, and matching within occupation domains. Our technology can realize data-driven HR decision-making, speed up people analytics, and use workforce data for business performance prediction. To find out more about what we can do please contact sales@janzz.technology

 

 

 

[1] Gartner. 2020. 9 Future of Work Trends Post-COVID-19. URL: https://www.gartner.com/smarterwithgartner/9-future-of-work-trends-post-covid-19/

[2] Bhaskar Chakravorti and Ravi Shankar Chaturvedi. 2020. Which Countries Were (And Weren’t) Ready for Remote Work? URL: https://hbr.org/2020/04/which-countries-were-and-werent-ready-for-remote-work

[3] Wikipedia. Knowledge Economic Index. URL: https://en.wikipedia.org/wiki/Knowledge_Economic_Index

[4] UZH Magazin. 2018. Interview: “Working flat out”. URL: https://www.magazin.uzh.ch/en/issues/magazin-18-4/gesundarbeiten.html

Standard skill profiles – chasing white rabbits and other myths

Many employers struggle to articulate and communicate the skills they value most for a given position and this results in a myriad of variations in the vocabulary used for job postings. Today, with the possibilities opened up by (X)AI automation for recruiting processes, many globally positioned recruiting agencies or HR divisions are tempted to ask if AI could provide a quick fix to these struggles, say, by generating a one-size-fits-all skill profile for a given profession. The lack of a common vocabulary among stakeholders in the labor market is of course a hindrance: many job portals are based on keyword matching, which leads to missed opportunities for both jobseekers and recruiters due to differing vocabulary, and AI-based automation struggles with the wording of job postings written to attract talent. This issue can indeed be addressed by employing semantic technologies, which, in a sense, translate the many linguistic variations into a common vocabulary, significantly improving job-candidate matching. However, although such technology can generate standardized vocabulary, this does not mean that it can generate a standardized skill profile for job postings. The pertinent question is, does such a global skill profile even exist? Is there enough common ground in job postings around the globe for a given profession to define such a skill set? Or even in single countries?

JANZZ has analyzed millions of job postings over the years to investigate these questions. To illustrate our findings, let us explore skill profiles for two classical professions, carpenter and nurse. We randomly selected around 250 job postings for each of these professions from five countries in two language regions: United States, United Kingdom, Switzerland, Germany and Austria. Our evaluation shows that there is a vast amount of variation in skills required for individual positions, even in strongly regulated professions such as nurse.

Skills may define jobs. But who defines the skills? A business in one country may not be looking for the same person as a comparable business in another country because the skills depend not only on the specific work to be done, they also depend on cultural or regulatory factors, the educational system and many other aspects. In fact, in one country several people with distinct skills sets may be required to do a job that, in another country, just a single person may already be qualified to do. Strong variations in skill profiles can be observed even within the same region because different businesses position themselves differently in the market. This can be seen not only in the varying demand concerning professional skills, but also in required soft skills, which can reflect a company’s philosophy, team dynamics or client expectations.

Impact of education and work experience

Let us take a closer look at carpentry. Germany, Austria and Switzerland (DACH) have a dual education system, where students can train as apprentices in one of a given list of occupations, including carpentry. The precise (hard) skills and theory taught are strictly regulated and defined by national standards, including those for several specialties that can be chosen after basic training. Anyone seeking to train as a carpenter has little choice but to take this path in these countries. The United Kingdom has recently implemented a fully revised apprenticeship structure with national standards for a growing number of occupations and is developing incentives for employers to hire apprentices. However, even though apprenticeships exist for certain occupations, for any one of these there is an alternative route via college education, which is just as (if not at least as) widely accepted. In addition, as these structures are still very new, the majority of the workforce in such professions did not complete an apprenticeship.

The United States are at the other end of the spectrum in this regard. Apprenticeships do exist, but there is no single set of standards that all employers in the US must follow when designing their apprentice programs. This makes it difficult for employers to assess the training of a prospective employee and may be one of the reasons – apart from a lack of tradition for this type of training – why apprenticeships are still not nearly as widespread as in Europe. This is reflected in the numbers of apprentices per capita: in the UK, Germany and Austria around 2% of the working age population are currently in apprenticeship, and just under 4% in Switzerland – more than ten times the number for the US, which is less than 0.3%.1) So, what does this have to do with a skill profile for job postings? One aspect we observe is that in countries with standardized training, much more emphasis is placed on vocational education compared to work experience. This can be seen by taking a simple count of these criteria as required in job postings.

 

Education and experience – Carpenter

Outer ring: percentage of carpenter job postings requiring given criteria.
Inner ring: percentage of job postings listing at least one criterion in experience and in education.
Center: the number at the center of the chart is the ratio of required experience to required education. A number above one thus indicates more demand for experience than education, and vice versa for a number below one.

 

To state the obvious, if you have completed an apprenticeship, you also have work experience. And if very few workers have done an apprenticeship, then employers will ask for work experience instead. This is also confirmed by our data for nurses. This profession is highly regulated in all five countries, requiring training (practical and theory) according to predefined national standards, and with specific optional specialties. In all five countries, there is significantly less demand for work experience compared to education (see Fig. below). We also see that in postings for carpenters, experience in tools is much more often explicitly mentioned in the US. This may also be a result of the lack in standardized training, where experience in tools is a given.

 

Education and experience – Nurse

Outer ring: percentage of nurse job postings requiring given criteria.
Inner ring: percentage of job postings listing at least one criterion in experience and in education.
Center: the number at the center of the chart is the ratio of required experience to required education. A number above one thus indicates more demand for experience than education, and vice versa for a number below one.

 

Turning to craft skills for carpenters, i.e., hard skills directly related to the trade, we see marked differences in all categories. In the UK and US, demanded skills are scattered across all areas of carpentry, from general over construction and interiors to additional skills from other trades, whereas in DACH, the focus is clearly on general aspects of carpentry with little mention of specific skills. A fully trained carpenter is typically more diversely skilled than one who learnt on the job and thus employable for a wider variety of tasks, which do not need to be explicitly mentioned. By contrast, in countries with less standardized training, carpenters are often restricted to fewer, specific tasks within a job. Notably, apart from laminating, there is no demand for manufacturing skills in the US or UK in our data. This type of knowledge is highly specific to skilled carpentry and requisite in one in five DACH postings. On the other hand, we see some demand for skills from other trades in the US and UK, which is (almost) inexistent in DACH. This is not surprising if we consider that a trained carpenter is less likely to have learnt skills from other trades, whereas a worker who learnt on the job may have acquired any number of other such skills.

 

 

A similar effect can be seen for nurses: there is generally little mention of professional skills in all five countries, and particularly few offers detailing specific skills, ranging from 4 to 10 percent of job postings per country. The focus in this skill category is primarily on specialties and additional tasks, which are not part of standard training and/or experience.

 

Regional differences

There are also other factors that influence the skill profile. For instance, in the UK, soft skills appear to be of little importance in carpentry: less than half of job postings in the UK ask for any soft skills at all, compared to 76% in the US and around 90% in DACH. In the US, the top 3 demanded soft skills are physical fitness, flexibility and overtime, and teamwork (in this order). By contrast, the top 3 skills in DACH are teamwork, working without supervision, and reliability. This shows that employers in the US are typically looking for very different workers than those in DACH.

 

Interestingly, there are also significant differences regarding soft skills for nurses: in DACH, every single job posting demands at least one soft skill, with a median of five, whereas in the US and UK, only 70 and 80 percent of job postings ask for soft skills, with a respective median of one (US) and three (UK). The top 3 skills in Switzerland are teamwork (48%), responsibility (46%) and working without supervision (44%). In the UK, the top 3 are communication skills, a caring personality and motivation – but with much lower demand (40%, 26% and 26%, respectively). Again, we see very different criteria in different countries.

 

Another aspect to consider is regulatory matters and safety standards. In the US and UK, employers explicitly ask for knowledge of safety standards (OHSA and HSE/CSCS card) and a significant percentage expect employers to have their own tools. This is not seen at all in DACH and can be traced back to educational and regulatory differences. Similarly, three in four US job postings specifically ask for BLS or similar certifications for nurses, which are part of standard training in the other four countries and thus not mentioned.

 

Business/industry-specific differences

Suppose we still want to create a standard skill profile. The simplest strategy would be to include any criteria found in at least one job posting. Using our data for carpenters, this would result in a list of 103 requirements, most of which would be completely irrelevant to an individual opening: on average, seven skills are listed per posting, with individual numbers ranging from 2 to 21. For nurses, we would have 94 requirements, with an average of eight skills per posting and a range of 1 to 16.

Another strategy one may consider is to search for a common denominator, for instance, all skills required by at least 25% of job postings in each country. Taking another look at the data above, this leaves us with just two criteria for carpenters: work experience (of unspecified length) and a driving license. Most recruiters would find this unacceptable. In Switzerland, a completed apprenticeship is a must in a vast majority of job postings, whereas in most cases in Germany a driving license is not a requirement. Thus, such a profile would result in many unsuitable candidates in one country and in too few candidates and many missed opportunities in another.

Following this strategy for nurses again yields just two criteria: nursing certification and work experience (in any specialty). Not one soft skill is listed although there is a strong emphasis on this category, with at least 70% of job postings ask for such skills. Moreover, three in four job postings in Germany do not require work experience. Again, this would result in a significant mismatch of candidates to job openings.

Let us pursue the 25% strategy for a single country, say Switzerland. Our standard skill profile for nurses reads as follows:

  • nursing certification
  • work experience
  • care work
  • computer skills
  • responsible
  • stress-resistant
  • communication skills
  • empathy
  • social competence
  • teamwork
  • professional competence
  • flexibility and overtime
  • ability to work without supervision

At first glance, this seems acceptable. However, almost 70% of Swiss job postings ask for professional skills other than generic care work, with more than half demanding specialty knowledge not included in basic nurse training. This means that each individual job posting now needs to be fine-tuned according to the specific opening.

For carpenters in the US we also encounter such issues. Our strategy generates the following skill profile:

  • work experience
  • experience in tools
  • cabinetry and furniture
  • window and doors
  • teamwork
  • flexibility and overtime
  • physical fitness
  • ability to follow plans
  • math skills
  • knowledge of safety practices
  • driving license

As before, this seems adequate at first. However, focusing on craft skills, a worker skilled in cabinetry and furniture or windows and doors may not be experienced in drywalls, roof carpentry or other building structures as this requires a different skill set. Also, a full 80% of job postings require craft skills other than those listed in our profile, and 60% of job postings ask for other soft skills.

Similarly, the only craft skill listed in a thus standardized skill profile for Austria would be assembly and fitting. Yet, many carpentry jobs do not involve assembly and fitting at all, such as seven in ten of the job postings in Austria that require manufacturing skills. In this country, manufacturing techniques are learnt in an apprenticeship with a different specialization and thus, an average assembler/fitter will not have the necessary skills.

Back to square one

These are arguably basic strategies, and a sophisticated AI-based method may deliver slightly better results. Yet the key issue identified in our analysis remains unresolved: there is an immense amount of variation attributable to national and regional differences, and also resulting from differing requirements for positions across different industries and even within individual businesses. Our data show that any globally defined core profile must therefore be adapted to the country (e.g., to accommodate educational, regulatory and cultural factors), then to the industry (construction, manufacturing, etc.), to the individual business (e.g., company culture), and finally, to the individual position. Which brings us back to individual job postings. Thus, a standard skill profile simply does not exist.

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1) Own calculations based on figures from OECD and national statistics offices

 

Workers age 50+: ready for the scrap heap or worth their weight in gold?

Systematic discrimination against workers age 50+ in candidate selection – or why this is not the issue in the vast majority of cases.

Read on, the following article will not just repeat the same arguments as always on this particularly important topic, which are usually based on assumptions and politically deadlocked positions. We will provide you with new, statistically relevant and number-based arguments that allow you to take a different view on the challenges of older workers and, to the same extent, on our education policy. But let us start at the beginning.

The statistics bring it home…

Suppose we want to fill a new position. We already have 80 suitable applications and CVs, including ones from young professionals, experienced professionals and applicants age 50+. Let the selection process begin. We sort by relevant skills and competences, professional experience, education and training, language skills, specializations, industry knowledge and so on. We reduce first to five, then to three candidates, who we invite to an interview. Importantly, we hide all personal data during selection, or rather, we make a non-discriminatory first selection using XAI.

At the end of this not so fictitious example and after many long, personal interviews and assessments, we choose a 27-year-old, multilingual university graduate with almost three years of experience in the right industry and the best matching scores in the areas of hard skills/competences and soft skills, communication skills, appearance, etc. A surprising choice? Hardly. It is rather the logical result of a structured, transparent and above all fair selection procedure. Remember, the hiring HR professionals were not aware of age, gender or salary expectations for the first steps of the selection. It would have been more of a surprise if one of the 50+ candidates had won the race – for statistical reasons alone: in the total of 80 applications there were only seven more or less suitable 50+ candidates, i.e., less than 10%.

Imagine that a 54-year-old, less qualified candidate had been chosen, contrary to the robust findings of the structured selection process and results of the interviews, primarily because of his age. This would have been just as discriminatory as an inherent preference of male candidates or favoring the candidate with the necessary connections.

Let us explain in more detail why this choice is logical and fair, and why other, similar selection processes usually have just as little to do with age discrimination or with the argument that companies avoid recruiting 50+ candidates for financial reasons.

There are always better qualified candidates out there. No matter how good yours are.

Well-trained, enthusiastic and experienced engineer, 50 plus, seeking – this is a scenario that has become bitter reality for many older workers in recent years. In our example, by the way, six of the 80 applicants were ahead of the 50+ candidate, having even better qualifications, mostly just recently acquired or refreshed, and higher degrees. There was only one criterion, ‘relevant experience’, on which he came in fourth, just narrowly missing the interviews for the final selection round. In short, the candidate was not unsuitable or rejected just because he was over 50, there were simply better-suited and objectively better qualified candidates for the position.

By the way, according to some of the more serious statistics, jobseekers in many industries in Switzerland already start facing more difficulties when they reach their mid-40s. At this age, the chances of finding a suitable job fall significantly in more and more cases. Despite an exceedingly positive economic environment and stable labor market with an exceptionally low unemployment rate before Covid-19, even highly qualified older workers were concerned about potential, longer-lasting unemployment. The fact is that once the older generation have lost their job, it is difficult for them to find a new, equivalent position. This is primarily because, usually for the first time in many years, they will have to face up to the ever increasing, ever better educated, multilingual competition and keep pace with younger, highly motivated and equally ambitious applicants.

To be very clear at this point: The sad exceptions do exist, companies with a real prevailing ‘anti-50+ policy’. Such a policy makes no sense at all, economically or otherwise, but there have always been companies that could neither calculate nor had a reasonable and fair personnel strategy. However, the real reasons why people in their 50s are increasingly faced with unemployment are complex and found on both the employer and employee side.

Last relevant vocational training: commercial apprenticeship 1981

The current labor market is becoming more and more specialized and is exposed to ever-faster technological change in many sectors, not only because of advancing digitalization. There are several reliable surveys that consistently show that, by the age of 30, more than 60% of knowledge acquired up to that point is already outdated or no longer relevant for professional progress.

In recent years, digital technologies, channels and thus evolved processes have come to the fore, rendering tasks more demanding and complex, especially for older workers. For example, compare the top 20 required skills from 2008 and 2018, say, on LinkedIn or in similar surveys. The ongoing transformations and the digitalization of competitive skills are quite dramatic.

This is just one of the reasons why training is being invested in everywhere and more than ever. That is a good thing, we all fought for this privilege for a long time and have repeatedly stressed the importance of good, modern education for every economy. Access to education as affordable as possible for all. A whole variety of tailormade educational models, dual education, vocational baccalaureate, semester abroad, MBA, CAS and much more. Comparing the manifold possibilities of today’s educational landscape, not only in Switzerland, with the options that were available at the time of our 50-year-old engineer, there have been huge, mostly positive developments – consistently and in all areas and aspects that are key to a successful professional life. Moreover, ambitious young professionals will gladly pay, or rather invest, 60000 US dollars and a few months of their lives for an MBA or tens of thousands of francs for challenging advanced training, certifications or postgraduate studies in order to have a better chance in the competition, which is becoming tougher for younger workers as well. We must all be continuously willing to make such investments, including the time commitment and renunciation of family life and leisure time ensued. Lifelong learning and continuous training are more than just buzzwords.

To keep up with a constantly evolving labor market, it is absolutely necessary to continuously train and extend our skills and competences, on average every 5 to 7 years. Work experience is certainly valuable, but that value is diminishing in more and more areas because the businesses they are based on are often outdated after a few years or have disappeared completely from the market. The ever-accelerating cycles of innovation in basic processes, tools and market and production mechanisms render the by far largest asset of experienced workers increasingly obsolete in comparison with younger, often better trained co-applicants.

The problem for the 50+ generation is that their good education was completed many years ago. Their knowledge, should they need to transition from a familiar and well-known environment to a new field of work, is thus no longer up to date.

Also, many 50+ applicants list only a few, if any, current training courses on their CV. For instance, a TOEFL test from 1993 may be the last entry under ‘languages and communication’, hidden among an abundance of in-house courses and trainings with lavish certificates of little meaning or relevance to a new position. This can be confirmed statistically by parsing and carefully evaluating large quantities (several million) of anonymized CVs: on average, the last relevant qualified formal training was completed 11.2 years earlier for 50+ candidates in Switzerland. In cases of successful professional reorientation or re-entry into a profession, it was several years less. As a reminder, the iPhone as the first actual ‘smart phone’ was launched almost exactly 11 years ago. Several other, significant digital processes and tools have followed since – at ever-shorter intervals.

In such cases, companies cannot be blamed for not considering a 50+ applicant for the simple reason that younger applicants are statistically in the majority and are moreover better qualified or have more up-to-date competency profiles. It would therefore be particularly important for older jobseekers to continuously adapt their strengths and qualities to technological change (whether we like it, want it or not…) and to consider continuous, targeted further training or even reorientation. Self-commitment is called for and this is not the responsibility of employers.

Know-how and relevant competence profiles beat experience.

Another reason why older applicants’ dossiers often end up on the rejection pile is the number of years of service. Applicants who have worked in the same department, company and industry for 20 years have specific work experience but often lose touch with the rapidly changing professional world outside the company. However, this long-term, one-dimensional experience is not the main obstacle in itself: it is often more likely the fact that the applicants’ profile is strongly tailored to their former employer and their qualifications are too limited or they are too specialized, having spent many years in the same function with similar tasks. As a result, flexibility and new professional opportunities are often deemed difficult. A new employer would need to invest in thorough onboarding and possibly in retraining. Of course, this may be necessary for a younger applicant as well. However, it may greatly devalue the importance of acquired professional experience in the competition with other candidates. Even if relevant work experience is still very important in general, its importance has diminished in a fast-moving and even faster changing economy. Ten years of experience are no longer twice as good and meaningful as five. Or rather, only if the competence profile has been developed in parallel with experience gained and according to the latest requirements. Unfortunately, this is exceedingly rare, as the data from the many parsed CVs clearly show.

Protect a lack of qualifications?

Lately, there have been repeated discussions about special protection against termination or special quotas for over 50s, in the hope that this constantly growing problem will be mitigated in the long term. But are these ideas not extremely unfair and discriminatory towards younger and usually better qualified workers? Workers who are already severely disadvantaged when it comes to major topics such as retirement provision, and thus are already proving more than enough solidarity with older workers.

Such an approach leads to unacceptable discrimination against younger generations by protecting less-qualified applicants. Not only that, such a rule would also mean that current 50+ jobseekers may no longer be recruited because employers fear that they will not be able to dismiss them. This type of reaction can be widely observed in countries with rigid employee protection laws such as Germany and France, where, as a result, many employers strongly favor fixed-term over permanent contracts. Special protection against termination is thus not a solution, it is a fallacy.

Another idea aimed primarily at mitigating the consequences of systematic age discrimination is the bridging pension (rente-pont). But if that is not the driving factor behind long-term unemployment of older workers, then this will just amount to yet another instance of discrimination against younger jobseekers. Instead, older jobseekers should be trained – many of them barely know how to apply for an opening. Looking at their CVs, you immediately encounter the showcase syndrome: instead of listing relevant skills, the document is adorned with information of no relevance whatsoever such as obsolete programming languages learnt 20 years ago. As a consequence, such an applicant will often seem desperate and insecure, not like a proud, promising new employee who will support the department and enhance it.

So why hire over 50s at all?

Too expensive, too little professional expertise, too inflexible – these are classic stereotypes older employees are branded with. True, the younger generation is usually more flexible and mobile in terms of time and place of work. Sell my beloved house after twenty years and move far away to another city or canton? No thanks. The reality that wages automatically rise with increasing work experience and age is another fact that is never questioned and rarely discussed publicly. And yet, this is another point where performance should be assessed rather than age. Why not earn the most when we are at our most performant and our expertise is its most comprehensive and up to date?

And finally, young jobseekers often also boast more extensive language skills and are, for the most part, much more IT-savvy. However, a few arguments speak in favor of the older generation: they have a high sense of duty and responsibility, very often have a positive attitude to work and are usually regarded as balanced and notably more consistent.

Anyone who now thinks that these issues can be reduced with anonymized AI-based application procedures is completely wrong unfortunately. These procedures do not focus on the person, but on relevant skills, current education and training, language skills, industry knowledge and specializations. An evaluation of various applicant selection processes in a wide range of occupational groups and industries has shown that, in fact, (with the exception of select management positions) the pool for the next round usually contains a significantly smaller proportion of 50+ candidates than in conventional selection procedures. This in turn proves that it cannot be due to the age of the candidates because all personal characteristics such as age, gender, origin, etc., were fully disregarded in the selection process and thus played absolutely no role in the matching and ranking, which formed the basis for the interview invitations.

We must therefore find other strategies. The key is ‘to be found’ instead of ‘to search’. Positions tailored to over 50s are often not found in job postings. However, there are technological tools that ignore these common prejudices against older employees. Machines decide on the basis of matching data points. They do not know discrimination against age, gender, ethnicity, etc. Older applicants should utilize this opportunity, especially to find out what they can draw on to increase their chances. These tools also give very objective and sober answers to many questions such as how many matches do I really get with my current qualifications? Where are my personal skill gaps? In the mind of the machine, there is no ‘I didn’t get the job, wasn’t even shortlisted just because I’m over 50. Sure, that figures…’

Using these tools, employment services, recruiting companies, job portals and others can make attractive employment proposals to 50+ talents, but also pinpoint individual placement challenges. For a gap analysis, feel free to ask for help at info@janzz.technology

Welcoming Jimena Renée Luna as our new VP of Customer Integration, Emerging Markets

We are proud to announce that Jimena Renée Luna will be joining JANZZ.technology as our new VP of Customer Integration, Emerging Markets. She will be responsible for all accounts in LATAM, EMEA and Southeast Asia.

Jimena is well-established and highly experienced in advising client governments and international organizations on tech policy, job creation, and economic development. Throughout her career, she has worked 10+ years designing and implementing related projects with teams across Latin America, Europe and Africa. At the World Bank, she performed research on labor markets and launched innovative solutions for job creation. In addition, she has worked for the U.S. CIO at the White House on digital policies to improve how citizens and businesses interact with government – helping to close the gap between the public and private sector on technology and innovation. More recently, she has worked on projects in Africa to promote the digital economy and digital development.

Jimena is enthusiastic about the job matching products and digital solutions offered by Swiss-based JANZZ.technology to clients around the world. She is confident that digital platforms, big data, and AI will drive the economy of the future. At a time when the world is facing a digital transformation and changes to the labor market, she is excited by the opportunity to work directly with global clients to provide them with digital solutions for job creation.

Jimena will be joining us on May 15. She will start working from Washington, DC, and then transfer to our headquarters in Zurich at a later date. We look forward to seeing Jimena applying her experience, enthusiasm and professionalism to our mission to better serve our clients.

Feel free to reach out to Jimena via email at j.luna@janzz.technology . She is fluent in English, French, and Spanish and will be happy to answer any questions you might have.

What skills will be indispensable in the future labour market?

JANZZ.technology has been actively contributing and creating solutions for matching jobs and skills in the digital age, such as the recently launched Realtime Labor Market Dashboard.

We help corporations, organisations and governments deal with the challenges during the current digital transformation and prepare the workforce to adapt to the future labour markets. Our technology provides real facts and insights, to help you to make the right decision. If you need to rethink, to upgrade or to have a better understanding of your human resources and education infrastructure, JANZZ.technology has the right tools.

JANZZ.technology applies explainable AI solutions

Humans can hardly understand the algorithms used for machine learning and text-driven artificial intelligence applications: How and why decisions are made? Are the results fair, transparent and explainable enough? Are the results biased in one way or another?

 

Explainable Artificial Intelligence is fundamental for our clients and users to understand the results of our matching tools.

If you are interested to know more about how JANZZ.technology applies explainable AI solutions, please write now to sales@janzz.technology.

Guarantee fair opportunities for everyone

Today in 2020, still not a single country can claim to have achieved gender equality in the workplace. Unconscious bias, stereotypes and prejudices happen more frequently than we think. Studies show that when the recruiting process is anonymous the bias is effectively reduced. JANZZ.technology has always been devoted to inclusive hiring since its foundation in 2008.

The International Women’s day is the day to commemorate how far we have come towards gender equality, but also to remind us how far away we are from the goal.  If you too, think that there are still major changes to be done, please contact us. We have the right tools to help you fight for equal opportunities for everyone.

JANZZ.technology – providing semantic technologies powered by ontology

If we ask a computer to translate the English sentence “the box is in the pen” into other languages, it will most likely interpret the word “pen” as the object we use to write with, this being the more frequently used meaning. But then the sentence will be nonsensical because, as we know, a larger object cannot be inside a smaller one.

Language processing or natural language processing is a much bigger challenge in AI than, for instance, image processing. We humans realize that, for this sentence to make sense, the word “pen” must mean a small area surrounded by a fence. A computer, on the other hand, lacks contextual knowledge and thus the logical reasoning needed to translate the sentence correctly. Another example would be “John is flying to the Big Apple on Tuesday.” You can probably guess what the result would be.

This is where semantic technologies come in. Among the many available methods, semantic techniques aim to improve computers’ understanding in processing natural/conversational languages through knowledge representation. Semantic technology is powered by ontology: it relies on semantic information encoded in ontology to identify nodes (e.g., words) that are semantically related.

At JANZZ.technology, we offer superior semantic technologies including semantic extraction, searching and matching powered by our comprehensive ontology in the domain of occupation data. To illustrate, JANZZ.technology’s semantic solutions can realize the following smart applications:

-Job searching and matching on related concepts

Related concepts are not (necessarily) synonyms but concepts which share similarities, sometimes given in completely different words or even languages. For example, “Neonatology” and “Pediatrics” are related concepts. With the information stored in ontology, semantic technology can identify how closely these two terms/professions are related to each other and, importantly, what kind of training/certifications one of these professionals needs in order to perform the other one’s job. This can be extremely helpful when transforming workforce skills on a large scale such as public employment services.

As another example, “Creative Director” and “Web Designer” are also related concepts but to a much lower degree compared to “Neonatology” and “Pediatrics”. If you are looking for a “Web Designer”, our semantic technologies would also recommend someone with job title “Creative Director” combined with skills in CSS, HTML and UX, or suggest such skills. Of course, “Concepteur Web”, “Nettdesigner”, “مصمم على شبكة الإنترنت” or “网页设计师” will also be matched. Related concepts can also be skills or education. For example, if you are looking for someone experienced with ERP systems, our semantic technologies know that candidates whose CVs list SAP, JD Edwards and MS Dynamics are all good matches because these are all ERP systems.

– Job searching and matching on degrees of skills

Semantic technology is not only able to match job postings and CVs containing the same skills, but it can also compare the degree of skills. For instance, “MS office skills” is a broad term and listed in many CVs. If you are looking for a Spreadsheet pro, you don’t want to be matched with a myriad of CVs listing basic MS office or beginner’s level Excel skills.

Similarly, if you are searching for professional CAD software skills, our semantic technologies would match CVs with CATIA, OpenSCAD or Rhino rather than TinkerCAD or BlocksCAD because the different specificities of CAD software are also stored in our ontology. Moreover, our semantic techniques not only identify levels of skills, but also report any training necessary for candidates to transform skills from one CAD software to another.

– Concept identification through interpretation of the context

Semantic technologies help identify cryptic concepts through context. Job titles can be very challenging for computers to identify. In the sentence “Company X is looking for an RF System Engineer, Building 8, Menlo Park, CA,” our software is able to decode each part of the sentence with the information stored in our ontology, such as industry codes, company names and places of work. In this case, “Building 8” is not an address but instead a mysterious department for hardware development at Facebook, and the “RF System Engineer” refers to “Senior Radio Frequency Engineer”.

– Job matching on overall dimension of occupation data

Some job titles, such as dentist, pilot, carpenter and Android app developer, already contain a lot of information about the specific position. When matching these jobs, it is possible to match almost exclusively on job titles. However, other titles like teacher, consultant, assistant, engineer and coordinator are much less specific. In such cases, one needs to include other criteria such as industry, skills, education, experience, etc., in order to conduct an accurate and meaningful matching. Semantic solutions from JANZZ.technology can perform such tasks with the data linked in ontology.

– Identifying gaps in the information

In contrast to machine learning, which is proficient in pattern recognition and classification, an ontology models meaning. It helps a system to understand CVs and job postings and perform gap analyses, thus creating a more user-friendly experience. For example, when matching candidates and jobs, semantic technologies can recommend skills, education or training which a given candidate lacks and thus help candidates optimize their CV.

Are you a large international corporation, organization or public employment service? Do you want to have the right technology to prepare and accompany your labor force throughout the digital transformation? Do you want to improve user experience during the application process? Do you want to build a more powerful system which makes your products stand out from the HR tech crowd? To integrate the latest semantic extraction, searching and matching technologies powered by JANZZ’s ontology, please write now to  sales@janzz.technology and let JANZZ.technology assist you.