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

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.

Improve your skills-based matching with JANZZsme!

In today’s digital world, computers can analyse competences and work experience faster and more effectively than humans. JANZZsme! powered by ontology transforms data about education, training, work experience and specialisation. Which helps governments and organisations to broaden their talent pool.

If you are in charge at a large international company organisation, institution, government or public employment service, contact  sales@janzz.technology and we will assist you with our unique AI based talent matching tool.

How can JANZZon! help your data?

To structure large amounts of data, JANZZ.technology combines its ontology (JANZZ.on!) with deep learning models.

JANZZ ontology is the largest and multilingual in the area of occupation data. Therefore, if you are a company, organisation, government/public employment service and would like to empower your data, please write to sales@janzz.technology.

Is reskilling and upskilling the real cure for today’s skills shortage?

Digitalization, automation and AI pose a great threat to today’s job market that requires constantly changing skills. However, some of the skills are not missing due to the evolution of technology, but rather due to a loss of attractiveness. This is especially the case for positions with an unusually high number of vacancies or such that remain vacant for a long time.


According to the Swiss Skills Shortage Index, “a skills shortage exists if there are more vacancies than job seekers in an occupation.” Last year, the Adecco Group compared in its Swiss Job Market Index job advertisements with the number of job seekers registered by the Vacancies and Job Market Statistics Information System (AVAM), which yielded the 2019 Swiss Skills Shortage Ranking.

As in previous years, in 2019 engineering occupations such as structural and electronics engineers are most wanted by Swiss employers. They are followed by technical occupations, fiduciary and IT professions. The ranking further indicates that compared to 2016, when the measurement was conducted for the first time, the skills shortage in 2019 is 22% higher across Switzerland. [1]

There are many reasons for the skills shortage. The rapidly changing skills requirements caused by technological innovation are believed to have the most profound impact on the risks of skills mismatch and shortage. Similarly, Hay’s Global Skills Index 2019/20 reported the highest talent mismatch since the index’ launch in 2012 and they, too, believe that technological development is one of the main contributing factors [2].

On the part of businesses, many companies facing the threat of talent shortages, which might damage their commercial success, prepare themselves for new technologies by upskilling their existing workforce, investing in training, encouraging lifelong learning and raising the retirement age.

There is no doubt that continuous upskilling throughout a career will become the new normal, but is this really the key to overcoming skills shortage? If it were, how come that the situation looks as if things are going in the opposite direction?

Another report published by a Swiss online job portal and Zurich University of Applied Sciences (ZHAW) provides further insight into the Swiss job market. The report compared more than 100,000 job advertisements with the number of clicks on Swiss job portals and, thus, reveals people’s interests in specific jobs in a more direct fashion.

In the German-speaking part of Switzerland, professions in administration, HR, consulting, sales and customer services, marketing, communication, and executive boards received more interest (clicks) than the job advertisements posted. However, jobs in areas like production, telecommunications, construction or nursing received less interest (clicks) compared to the job advertisements posted. [3] This suggests that economic incentives as well as social recognition are becoming increasingly important for people when it comes to choosing a profession.

Last year, there were over 6000 professional care vacancies in Switzerland. This number has doubled compared to five years ago.[4] Reporting on the healthcare workforce supply and demand in Switzerland shows that care workers graduating in the near future will only cover 56% of the demand until 2025.[5]

In the case described above, the problem doesn’t have to do with up-or reskilling. It is rather about the ways in which more people – especially younger ones – can be encouraged to pursue a career in jobs that are considered less attractive. What is even worse, evidence shows that due to bad working conditions (e.g. little income, long working hours, too much stress) a large share of young people has switched their working field either right after their apprenticeship or after a mere few years of professional experience. This includes professions in childcare, hospitality, catering services and handcrafts.

Today everyone is talking about automation, digitalization, AI, upskilling and reskilling. We must remember that there are still many jobs that are unlikely to be automated but essential to our daily lives. And these jobs are losing in popularity. It is important for governments and education systems to take action on increasing awareness and to promote such professions. As written in the OECD Employment Outlook 2019, the “future of work is in our hands and will largely depend on the policy decisions countries make.”

For almost a decade, JANZZ.technology has been observing and working with many labor markets worldwide. Our latest product JANZZdashboard! creates transparent and easy to understand gap analyses of the labor market. This will give governments a clear idea of which skills are available and which ones should be expanded or redeveloped. To learn more about our solutions please write now to sales@janzz.technology




[1] Spring. 2019. Swiss skills shortage index 2019. URL: file://srvgiga-adart/JANZZ.technology/JANZZ.technology/JANZZ.technology%20Company/JANZZ%20Business%20Development/JANZZ%20Social%20Media&Blogs/JANZZ%20Posts/2020/Swiss%20skills%20shortage%20index%202019/adecco-study-data.pdf [21.01.2020]

[2] Rachel Muller-Heyndyk. 2019. New technology causing skills gaps and stagnant wages. URL : https://hrmagazine.co.uk/article-details/new-technology-causing-skills-gaps-and-stagnant-wages [21.01.2020]

[3] Robert Mayer. 2019. Die meisten Stelleninserate, die geringste Nachfrage. URL : https://www.tagesanzeiger.ch/wirtschaft/in-diesen-berufen-herrscht-ein-mangel-an-fachkraeften/story/18953945 [21.01.2020]

[4] Albert Steck. 2019. Offene Stellen auf Höchststand. URL: http://jobs.nzz.ch/news/6/arbeitswelt/artikel/421/offene-stellen-auf-hochststand [21.01.2020]

[5] Veronica DeVore. 2016. When caring for patients gets competitive. URL : https://www.swissinfo.ch/eng/showing-off-skills_when-caring-for-patients-gets-competitive/42524090 [21.01.2020]