“Dr. Cab Driver”: High rates of over- and under-qualification, despite ‘progress’ in education.

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Does this situation seem familiar to you? On the Uber ride to the airport, you get caught up in a conversation with the driver and before you know it, you’re in the middle of a discussion about the potential of genetically modified bacteria to create cancer drugs. It quickly turns out that there is an extremely educated person in the driver’s seat who is currently putting his education to rather limited use. A new report from the International Labor Organization (ILO) on this matter now shows that only half of all workers worldwide have an occupation that matches their level of education. At the same time, many employers report difficulties in finding qualified personnel. This situation not only points to a significant gap between educational institutions and the working world but, depending on the facts, it also undermines the relevance of omnipresent keywords such as ‘upskilling’, the hype of which we have already questioned in the past.

 

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The Report

The main findings of the report published by the ILO in September reflect realities that we, at JANZZ, have been anticipating for some time. Despite improved access to education and an increased level of education, the overall match between workers’ level of education and the actual skill level required for their occupation is a sobering 50% worldwide. Breaking this mismatch down into its individual components results in over- and under-qualification situations. [1] In concrete terms, this means that oftentimes there is a gap between the work that people can or want to do, and the job profiles and qualifications for which there is an actual demand. Indeed, from our own data analysis, we can cite as an example the fact that, in Europe, there is currently a shortage of about 400,000 truck drivers, as well as hundreds of thousands of nursing and care workers and employees in the catering and hotel industry. The main problem here, however, is not a lack of skills but rather a lack of willingness to learn certain professions. The reality is that the previously mentioned occupational fields are often underpaid, thus, resulting in a general lack of interest to then remain in those positions for a longer period of time.

Accordingly, the ILO study found that while there is over- and under-skilling in all countries, the patterns differ depending on the income level of each country. The matching rate increases with progressively higher median income in a country, which means that in countries with lower wages, just one in four workers have a job that correlates with his or her level of education, like our opening example of the biotechnologist driving a cab. There is a tendency for undereducation to be more common in lower income countries, while overeducation is more common in high income countries. [1]

There are different reasons for both circumstances: Workers are sometimes overqualified for their jobs because they accepted them for motivations other than aspiration, for example because the position offered specific benefits such as shorter commute times, better work-life balance, or an experience opportunity for later, more demanding jobs. However, these people are only part of the workforce. Another part can be attributed to distortions in the labor market, according to which the supply of workers with higher levels of education exceeds their demand. In the case of undereducation, the main causes are in turn the relatively low completion rates and the lack of formal qualifications amongst a large workforce, which is more common in low-wage countries where educational opportunities tend to be poorer. [1] In addition, given the low chances of finding a job in their own level of education, many also take available jobs for which they are overqualified, but which provide them with an immediate source of income for their livelihood. From our own sources, we outline the example of Paraguay, where around six times more lawyers are trained than the labor market can accommodate after their graduation. Many of them end up in jobs in call centers, retail or administration, where there is hardly any connection to their legal skills and knowledge.

Among the inadequately trained employees, some can at best make up for the lack of qualifications by acquiring the necessary skills through on-the-job training or self-study. Overall, however, there are still numerous negative consequences of these mismatches due to over- or under-qualification that affect the workforce, the employer community, and society as a whole. For example, a high degree of overqualification can lead to a loss of motivation and suboptimal returns on investment in education and training. In addition, every overqualified person always occupies a position that could or should be held by someone more suitably qualified. On the other hand, many underqualified employees face difficulties in the transition from the informal to the formal economy, which can have negative consequences on productivity and innovation, as well as economic growth. Since the examples that we mentioned are rather longer-term phenomena, according to the ILO, systematic, i.e., political measures are usually required to solve them. [1]

The problem of upskilling and reskilling

Let us make a few more comments on one specific finding of the ILO study. Among other things, the report emphasizes that in countries with medium-high to high average incomes, about one-fifth of all workers today are overqualified [1]. In countries like Finland, where just under 75% of the population has a university degree but where there are considerably fewer jobs at this level of education, this rate is even higher [2]. At the same time, keywords like ‘upskilling’ and ‘reskilling’ are on the lips of everyone who talks about the development and future of labor markets. Such training processes can make sense within a company, but they are not automatic, especially not when it comes to the entire labor market of a state or region. As soon as experienced employees who are well established in their positions are moved or promoted to another function or activity because of upskilling, their old position must first be filled with someone suitable. This task alone can cause red flags for HR, as the assumption that all such ‘pre-upskilling’ positions will immediately cease to exist is misleading and incorrect. The situation may become even more convoluted when a country has a harsh migration policy and there is a lack of workers for low-wage jobs (often disdained by citizens), for instance, as can be observed nowadays in the nursing field in the UK [3].

Furthermore, in his or her new position, it is not certain that the promoted person will perform equally well or be as satisfied as before, or whether the promotion and the accompanying increased responsibility is a right fit for that person. Management literature knows the so-called Peter Principle, according to which a large part of the inefficiency on the labor market is due to the fact that in hierarchical structures, such as a labor market, every employee tends to rise to the point of incapacity. Although this theory has a satirical undertone, it nevertheless seems to be somewhat true, not least when considering the rather low downshifting rates [4]. When it comes to reskilling, the situation looks somewhat better in that it is conceivable in this process to be able to transfer and adapt at least so-called “core skills” from the old job to the new one.

Back to the findings of the ILO report: Even if none of the above problems occur, the fact remains that in our geographical location many people are overqualified for the work that they do on a daily basis. A prime example of this is the trend among medical students who seek to become a specialist, even though, depending on the area, the occupational demand for it can be rather limited and there is an existing deficit of family doctors. Moreover, one can also wonder, why at Swiss universities, efforts are being made to attract not only geography students but also lateral entrants from geology studies to train as geography teachers for secondary level II. What is problematic about this is that there is already no (increasing) demand for this profession, while at the same time, there is also a shortage of primary and lower secondary level teachers. Furthermore, data from an OECD survey indicates that, compared to EU/OECD countries, Swiss nationals are more often overqualified than immigrants, with the latter accounting for an above-average share of the workforce in the low-wage sector (60%) [5]. This also indirectly reflects where there is a real need for personnel…

Quo vadis?

Over- and under-skilling remain a current problem in most labor markets, despite considerable progress in global access to education. Both conditions reflect underutilization of human capital and can carry high economic and social costs. What needs to change?

To reduce such mismatches overall, it is first necessary to capture and assess the extent to which the level of education of workers in a labor market matches the level of education required for their jobs. This is done by means of analyses such as the ILO’s cited here. (See also our English-language contribution to a Nobel Prize-winning paper that systematically explains the asymmetry between the large number of unfilled jobs and simultaneous unemployment within a market). As a next step, this data would also need to be incorporated into a country’s education planning and human resource development, which may be complemented by policy measures. In countries with high rates of undereducation, the undereducation of those who already occupy highly skilled jobs or will do so in the future must be raised by qualitatively adequate means. It should be noted, however, that simply upskilling all job seekers in a labor market that offers many low-skilled positions will neither automatically eliminate the mismatch, nor lead to a reduction in the unemployment rate.

Furthermore, it would be important to actively create more transparency for the public about the actual demand of a labor market, especially in countries with a high rate of overqualification. Ideally, such information would motivate future workers to train in a ‘meaningful’ direction or at least to be aware of the suboptimal employment opportunities after graduation and to inquire about real (and often equal in terms of wages in German-speaking countries) alternatives, such as apprenticeships. What is therefore certainly not conducive is to propagate upskilling and reskilling towards trendy degrees and competencies as ‘the thing to do’, which unfortunately also happens regularly today due to published (and quoted) misinformation on this topic. The latter can have rather dangerous and far-reaching consequences for society, especially if done through governmental and political voices, because such false promises and forecasts will widen the skills gap more and more and possibly have global implications in areas such as migration.

Finally, more emphasis should be put on adequacy in the actual matching process between candidates and jobs. This requires, first and foremost, reliable and information-dense data collection, analysis and classification. Here at JANZZ, we gather just such information through a variety of projects, including collaborations with the Public Employment Services (PES) of countries around the world. This has allowed us to develop market-leading evidence-based solutions since 2010. Our systems are not only efficient, scalable and extremely powerful, they also rely on ontology-based semantic matching. Furthermore, our tools all deliver unbiased results according to the OECD principles on AI. We are keen to stimulate fact-based discussion on all issues related to labor markets and processes, and to raise social awareness about them. After reading this article you might think about how many people in your environment are working in a profession that truly corresponds to their degree (level)…

If you would like to learn more about our offerings, please contact us at info@janzz.technology or via contact form, or visit our product page for PES.

 

[1] ILO. 2021. Only half of workers worldwide hold jobs corresponding to their level of education. URL: https://ilostat.ilo.org/only-half-of-workers-worldwide-hold-jobs-corresponding-to-their-level-of-education/

[2] Clausnitzer, J. 2021. Population with educational qualification in Finland 2019, by level of education. https://www.statista.com/statistics/528083/finland-population-with-educational-qualification-by-education-level/

[3] Inman, Phillip. 2021. Does the UK have a wage problem? URL: https://www.theguardian.com/money/2021/oct/06/uk-wage-boris-johnson-skilled-skilled-economy

[4] Donzé, René. 2021. Mehr Leben, weniger Hamsterrad: Wieso die wenigsten einen beruflichen Neustart wagen. URL: https://nzzas.nzz.ch/spezial/downshifting-wieso-nur-wenige-einen-beruflichen-neustart-wagen-ld.1612299

[5] Loos, Melanie. 2018. Schweizer öfter überqualifiziert als Zuwanderer. URL: https://www.handelszeitung.ch/konjunktur/schweizer-ofter-uberqualifiziert-als-zuwanderer

 

Wanted: healthcare workers – but why aren’t these jobs being filled?

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Smiling female nurse holding senior woman’s hand. 

Despite improvement, there will still be a significant gap between supply and demand of healthcare staff by 2029 in Switzerland, according to the national 2021 report on future healthcare staff needs, published by the Swiss Health Observatory in September.

The report estimates that by 2029, the personnel demand in the healthcare sector may rise to 222,100. Compared to a base number of 185,600 recorded staff in 2019, an additional number of 36,500 staff will be required. To fill these additional positions, as well as to compensate for those who retire and leave the industry early, presents an enormous challenge to the next generation of health workers. The report further stated these jobs remain difficult to fill mainly due to demographic and epidemiological developments.

The growing need for qualified healthcare professionals is not specific to Switzerland, a trend can be seen around the globe, and it is not a recent trend. Back in 2016, World Bank published the research on Global Health Workforce Labor Market Projections for 2030. It predicts that global health workers’ demand will increase to 80 million, with a supply of 65 million health workers over the same period, resulting in a global shortage of 15 million health workers.

In a previous article, we have also discussed the shortage of healthcare professionals in the Swiss labor market (see Switzerland 2030: The risks and opportunities of digitization). Today, due to the effects of the global pandemic, it might have impacted the situation negatively. The pandemic has brought renewed attention to the frightening shortage of health workers, but remember, this extraordinary situation existed long before the Covid-19.

The same pattern is clearly evident in some other industries and occupations (see Free movement of skilled workers in the EU and beyond are more important than ever), with fewer and fewer young people willing to learn such skills. It is a basic problem and therefore, needs some fundamental changes to effect sustainable action. Share with us your thoughts and let us know your opinion on this topic.

Follow-Up on Equal Pay, or; The monster in our closet that we all ignore

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This is a follow-up post to our last article on the Gender Pay Gap (GPG), in which we suggested that focusing on a pay gap based on gender is not enough and that shifting the focus to the concept of performance would be useful. As a kind of continuation, we turn here to the topic of fast fashion and discuss this ubiquitous ‘monster’ in all our closets, including from the perspective of equal pay.

Lack of initiative despite well-known problems
We all know it,  » Read more about: Follow-Up on Equal Pay, or; The monster in our closet that we all ignore  »

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Building public services for a more resilient future

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When COVID-19 came last year, many countries scrambled to cope with the disruption to vital public services and the closure of schools and universities. However, a few countries such as Norway and Estonia, have managed to keep everything in place, thanks to their decade-long development in digital infrastructure. Today, Estonia has built one of the world’s most advanced digital societies.

Every two years, the United Nations Department of Economic and Social Affairs publishes the E-government rankings. The aspects considered in the rankings cover the range and quality of online services, the current state of the telecommunications infrastructure and available human resources. In the latest rankings, Estonia led the way in e-government among the 193 UN member states. How did this small Baltic country surpass powerful nations like the US and China and realize such an achievement?

Being ahead of the curve since the 1990s

After independence in 1991, Estonia quickly moved to take advantage of its technological prowess. In 1997, Estonia launched electronic-governance, followed by e-tax in 2000 and digital ID in 2001. In 2005, Estonia started i-voting, and three years later blockchain technology was introduced along with e-health. In 2014, Estonia aimed to create a country without borders and became the first country to offer electronic residency to people from outside of the country. The digital reforms that took place from the 1990s to the present known as the “e-Estonia model”, are well-known worldwide and its success inspires and intrigues many across the globe.

 

Source: Estonia: the most digitally advanced society in the world? (raconteur.net)

 

Estonia’s success is much more than technological innovation. In an interview with Tommas Hendrik IIves, the former president of Estonia with the International Monetary Fund (IMF), Mr Ilves stated that it’s not only the technology, but also political will, policies, laws and regulations that have made things happen in Estonia. The former president is recognized worldwide and has made Estonia today one of the most advanced countries in digital governance.

The decision to embrace digital life has certainly paid off during the lockdown. The e-Governance has ensured sustainability and continuity of the public sector services for citizens and enterprises in Estonia. Online options have already existed for a large number of daily procedures including civil and business registry, unemployment insurance registry, digital content management system to deliver learning materials, testing, assessment/evaluation and analytics to all students.

 Covid-19 pushes more government activities online

After the pandemic, more countries are pursuing the digital government strategies. According to the United Nations E Government Survey, a global trend in e-government development can be observed, for example, as a key indicator, the global average E-Government Development Index (EGDI) raised from 0.55 in 2018 to 0.60 in 2020.

 

Source: 2020 United Nations E-Government Survey

 

As a very important part for modern e-government, public employment services (PES) are embracing digital technology as well to better match people to jobs and to perform other new tasks such as providing career guidance and addressing skill gaps. According to the International Labor Organization (ILO), PES in 69 countries across all regions have the capacity to provide basic online services, such as publish open vacancies and register citizens for job matching. In these countries, one third of them has provided solutions with artificial intelligence (AI) for both job seekers and employers.

The Norwegian Labor and Welfare Administration (NAV) has implemented JANZZ’s AI-driven semantic search and match engine, multilingual and most comprehensive ontology as well as other solutions as SaaS/DaaS for its new job matching platform in 2019. Before the numbers of unemployment/registered people at NAV exploded during the pandemic, JANZZ’s robust system has extraordinarily prepared NAV with a volume of more than 10 times the planned volume and successfully managed any sudden increased load without incident.

Be prepared for the next unexpected moment

Worldwide, 50% of the population use the internet for various purposes including job searching. However, there are still wide disparities in digital government transformation including in PES across regions. Not all countries are sufficiently prepared to promote innovation and leverage digital technologies to provide accessible and reliable services.

It is as vital to tackle PES as it is to have other digital public services. As shown in the Estonia example, digital government transformation is not just about technology, it is also about political will. Today, in the context of pandemic, all countries should seize the opportunity and start their projects on digital technologies soon, before there is a new and again unexpected need for such services like 2020/2021.

To learn more about our AI-driven semantic search and match solutions, multilingual and most comprehensive ontology and other solutions for Public Employment Services (PES), please visit our product site for PES or contact us at info@janzz.technology.

Equal Pay – Let’s not fall into the gender pay trap…

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For some, Equal Pay Day marks the annual ‘free labor of women’, for others it is an ‘ideologically motivated lie’ – the truth is even more complicated. This article highlights the uselessness of many of the statistics surrounding ‘equal pay’ and explains why a focus on gender falls short when it comes to pay equity. Instead, we would do well to place more emphasis on actual, individual performance.

Is a focus on gender even justified?

First of all, let’s take a look at the terminology. Equal Pay Day (EPD) is generally understood as an international day of action for equal pay between women and men. The day is intended to draw attention to the so-called ‘gender pay gap’ (GPG), i.e. the gender-specific wage gap between the average gross hourly wage of women and men. The EPD is celebrated individually in each country, symbolically on the day up to which women would work for free if they were paid the same amount as men across society as a whole. In Switzerland, the EPD falls on February 20. So much for the definition.

Let us now turn to the methodology used to measure and prove the GPG. Two statistical approaches dominate here. Either the gross wages of women and men are compared by means of a regression analysis, without taking into account objective factors such as level of education, qualification, age, professional experience, overtime hours or the exercise of a management function. In the case of Switzerland, this led to the following result in 2018: Women earn on average a striking 19% less per hour than men [1].

Due to the fact that objective factors were neglected in the analysis this result is, however, questionable. Such a calculation literally compares apples with oranges. The other approach used concerns the calculation of the so-called ‘adjusted wage differential’, in which a distinction is made between ‘explained’ and ‘unexplained’ differences in pay. ‘Explained’ are those pay inequalities that exist due to objective reasons such as full-time/part-time employment or work experience. The ‘unexplained’ share refers to the pay gap that is potentially attributable to subjective inequality based on gender and amounted to 8.1% in Switzerland in 2018 – still a considerable, but nevertheless notably smaller figure than the result of the first calculation [1].

Although the first approach is now considered outdated, its results are regularly cited in the media to create politicized headlines (for example here) or to serve the often shouted slogan “equal pay for equal work.” But even the adjusted GPG omits important explanatory factors. For instance, comparisons are not made task-specifically but rather on an industry-wide basis, or projections are made nationwide despite very large regional differences in the cost of living. If all these relevant aspects were also included in the statistics, the explained difference would probably be even lower. A slightly different objection is that if such huge differences really existed despite equal qualifications, every profit-oriented company would actually have to hire only women, which definitely does not correspond to reality.

One real consequence of all this is a (media-driven) battle between the sexes, which unfortunately seems to lead nowhere except to diminished solidarity between men and women. A prime example of this is Switzerland’s Equality Act, which was amended in 2020. Since July of last year, the largest Swiss companies have had to monitor their wages for discrimination and fulfill their obligation to inform their employees about the findings. Apart from the fact that the law only obliges companies with more than 100 employees, which excludes a large part of Swiss SMEs, it does not provide for any sanctions [2]. Recently, the first evaluations of this federally mandated wage analysis were published – with surprising results for some. Only 5 percent of the analyzed companies do not meet the stipulated requirement, which on the one hand is below the granted tolerance threshold and on the other hand clearly contradicts the previous statistics of the federal government. Interestingly, the reactions of GPG critics to this result are either non-existent or skeptical [3]. One almost wants to say, because they do not fit their expectations or their world view…

The bureaucratic effort that is made today for the purpose of equal pay leads in the end not only to contradictory statistics and little real change. Moreover, the analyses also distort the representation of the actual economic situation of a non-negligible share of men who are below the average value of their gender, since male top earners statistically make all men appear to be better earners.

Focus should be on performance

The slogan “equal pay for equal work” quoted in the last section is therefore misleading, since the standard analytical methods used to examine gender pay inequality do not compare like with like. Another, even more important point in the discussion of equal pay concerns the concept of performance. Achievement can be divided into two components, the effort made and the result achieved within a given period of time. However, the first component is often equated with the second, or considered an equivalent substitute for the lack of the latter. An insistence on actually achieving results is sometimes even frowned upon as inappropriately exercised pressure to perform. And yet, in the end, it is the performance that matters. Let’s use an analogy to the world of sports: Recently, at the Summer Olympics in Tokyo, the on average smaller beach volleyball players from Japan played against the on average taller athletes from Germany. Although body size can definitely play a decisive role in this sport, neither the relative performance of the Japanese nor which team had trained x hours more, nor who had already participated five times more in the tournament counted for the final result, but only their performances in the match.

From the perspective of both fair and profit-oriented employers, the situation is similar. When it comes to salary, only the actual performance – measured by the contribution to a company’s income statement – of an employee counts or should count. Of course, this means that unchangeable attributes such as height, gender, ethnicity or social background should have absolutely no influence on a person’s salary. In radical economic terms, however, such a position would mean that even objective factors such as the type and duration of education would no longer have to be taken into account. Even if a completed degree means high education costs and temporary wage sacrifice, this qualification is sometimes not sufficient to outperform a naturally skilled or otherwise trained worker. If person A assembles twice as many parts in an hour on the assembly line as person B, then person A should also be paid more in the long run or be allowed better employment and advancement opportunities. Accordingly, fair hiring and compensation are ideally based on individually measurable and comparable performance – i.e., on the reason why a person is originally hired or should be hired. Thus, the well-known guiding principle can be rephrased as follows: Employers should not adhere to the slogan ‘equal pay for equal work’, but to ‘equal pay for equal performance‘. A deviation from this principle is therefore a genuine act of discrimination – including against women who perform measurably better and more consistently.

To return to the topic of equal pay in relation to gender, a marginal comment should be made here: If remuneration is to be based solely on a person’s contribution to economic success, the question arises at least as to why domestic work and child rearing in one’s own household/family, which is still mainly carried out by women, is not also considered to be work worthy of compensation. After all, it represents a significant pillar of our current economic and social system.  Or, if this work is ‘outsourced’ to a room attendant and a day care center, why are such important services are paid so low? We all tolerate this circumstance without a shred of bad conscience. This indicates that there would likely be no broad willingness to make a fair wage possible for people working in these sectors, for example by means of tax-financed subsidy payments. But more about this in the next section…

What counts as (equal) performance; or, The real problems

As alluded to, the principle of ‘equal pay for equal performance’ raises the question of what should actually count as equal – or rather equivalent – performance. Here, too, the comparison with the world of sports can be made: While the winner of the FedEx Cup golf tournament receives around 10 million US dollars in prize money, a ski jumper only gets one thousandth of this amount at the most for winning the competition. Both athletes perform exceptionally well (and entertain spectators), and yet the pay is set completely differently. Such gaps do indeed exist across the economy and cement specific sectors as high or low wage industries that often also correlate with gender. Of course, one can always appeal to women’s self-responsibility when it comes to career choice, à la ‘It’s your own fault if you choose a low-paying job that can be done part-time – no one is forced to start a family’. But we could also think about why so-called ‘female professions’ such as sales assistants, hairdressers or geriatric nurses are systematically paid less and whether this is fair. If the pandemic has shown us anything, it is that many of these professions are ‘essential’ for the functioning of our society. The prime case is nursing staff, who despite unpleasant working hours, stress and indispensable service provision earn much less than, for example, construction foremen. The real problem is therefore the wage inequality across sectors, which widens the gap between the rich and the poor and does not pay ‘equal’ performance equally.

For the individual, the consequences of choosing an occupation in the low-wage segment mean not only lower pay but also fewer opportunities for further training and promotion, as well as a lower pension in old age. But, to return to the GPG aspect: Discrimination can occur not only on the basis of gender, but along many lines, such as skin color, appearance, age, disability or religion. So why this focus on gender when solidarity and alliances can be formed much more broadly? On this point, one critic of the EPD suggests, “What would be really interesting would be a ‘social’ ‘Equal Pay Day’. […] The gender issue hides wealth and hides social inequality. The gender pay gap is […] a gender trap – a ‘gender pay trap’, so to speak” [4].

In summary, we as a society need to ask ourselves whether we are willing to accept the structural reasons for wage inequality as an unchangeable fact or whether we are willing to do our part to change the status quo. In terms of gender, one commentator summarizes that having children is not part of the plan in today’s economic model, as it often means being locked into a traditional role distribution and lower employment opportunities for women [5]. Here, a rethinking and a restructuring on different levels – individuals, large corporations, politicians – seems to be called for.

The examples of gastronomy and care can also be used to illustrate that social change requires everyone to take responsibility. Are we willing, provided we can afford it, to pay more for consumption in a restaurant or even higher health insurance contributions so that the waitress and the nurse are paid ‘more equally’ for their services, or do we prefer to be stingy so that we can keep more for ourselves? Do we elect policymakers who will advocate for better minimum wages in care, or do we think we’ve contributed enough by clapping from our home balcony? Or how about the next time you pick up your kid from daycare, you tip the caregiver a few hundreds to show that you appreciate their efforts and are aware of the wage disparities in the care sector?

At JANZZ, we are not satisfied with a couple of heart emojis posted on social media as extra pay for caregivers, but develop evidence-based solutions and have been using them successfully since 2010. Our job and skill matching solutions are fair and non-discriminatory and deliver completely unbiased results according to the OECD principles on AI. This ensures that the best performing candidates in all individual criteria receive the best match – regardless of employment status or other irrelevant characteristics such as origin, age, BMI or gender. This is one of the many reasons why we are a trusted partner for an ever-growing number of Public Employment Services (PES) around the world.

Want to take that first step to change the status quo and contribute to a more equitable labor market for all? Then contact us at info@janzz.technology or visit our product page for PES.

 

 

[1] Eidgenössisches Büro für die Gleichstellung von Mann und Frau. Plattform Lohngerechtigkeit. URL: https://www.ebg.admin.ch/ebg/de/home/themen/arbeit/lohngleichheit.html

[2] Tagesanzeiger. Ab Juli müssen Unternehmen die Lohngleichheit kontrollieren. URL: https://www.tagesanzeiger.ch/ab-juli-muessen-unternehmen-die-lohngleichheit-kontrollieren-711426685692

[3] Steck, Albert. Frauen werden kaum diskriminiert, wie die neue Überprüfung der Löhne zeigt. URL: https://nzzas.nzz.ch/wirtschaft/loehne-in-der-schweiz-frauen-werden-kaum-diskriminiert-ld.1640462

[4] Moser, Thomas. 2017. Ten Years Gender Pay Gap-Mistake – Ein Irrtum wird zehn Jahre alt. URL: https://www.heise.de/tp/features/Ten-Years-Gender-Pay-Gap-Mistake-Ein-Irrtum-wird-zehn-Jahre-alt-3652060.html?seite=all

[5] Zufferey, Marcel. Die Mär von den unfairen Frauenlöhnen. URL: https://blog.tagesanzeiger.ch/mamablog/index.php/10791/die-mar-von-den-unfairen-frauenlohnen/

Global Labor Market News: Despite strong vacancy recovery, long-term unemployment remains

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A new analysis of online job postings from the UK confirms that there has been a strong recovery of job vacancy rates this summer, well above the same period two years ago. The data, coming from one of the largest online job search engines in the UK shows:

  • New vacancies are mainly in IT, construction, trades or warehousing and logistics with 330,000 in total, nearly one-third of all vacancies.
  • The numbers of vacancies in healthcare, nursing and social work are reaching 130,000.
  • The numbers of vacancies in both sales and hospitality are nearly 75,000.

Despite the increasing job advertisements, what raised more concerns, however, is that the unemployment rate remains high. The long-term unemployment rate keeps rising at the fastest rate in a decade and the unemployment claims are still double the size compared to the time before the pandemic.

Not only in the UK, the same trend can also be seen in many other rich economies. A report released by the OECD in July warned that rich countries may face sustained growth in long-term unemployment. Their data shows, by the end of 2020, the number of people in OECD countries who have been unemployed for more than six months is 60% higher than the pre-pandemic level. This is because the low-skilled workers who are most likely to lose their jobs in the early stages of the crisis do not have the skills needed to enter the most extensively recruited industries.

To deal with the situation, governments are suggested to develop more targeted employment retention programs to ensure that they do not support businesses that are unlikely to survive in the open market. Meanwhile, they should better cooperate with employers to support reskilling and job matching.

Global Labor Market News: Will China get old before it gets rich?

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In May 2021, China announced that couples are allowed to have up to 3 children, due to a consecutive four-year decline in the population. In 2016, China abolished its one-child policy, replacing it with a two-child limit, which had little impact on its fertility rate. The Chinese government hopes to salvage the situation by further relaxation of birth control. However, the coming of the so-called “three-child policy” is responded to by most with just a shrug. The lack of social services to help families in both parenting and education was blamed for the reluctance to have more children.

A survey, conducted by the National Health Commission on the demand for childcare services for infants and toddlers under the age of 3 in urban families shows that more than 33% of such urban families expressed needs for childcare, and the demand among families without the help of grandparents is much higher reaching 43.1%. However, the actual enrollment rate of children aged 0 to 3 in 2020 was only 4.1% which indicates a huge shortage of supply. In OECD countries, about 25% of infants and toddlers aged 0 to 3 receive childcare services and the number even goes up to more than 50% in countries such as Denmark and Iceland.

Increasing spending on education is another reason for the lack of interest in having more children. According to research from a leading research and strategy consulting organization in China, the average annual expenditure on children’s education by urban families in China accounts for 30.1% of total family income and 35.1% of their total expenditure. In addition to the financial investment, the time and energy invested by Chinese parents in rushing their children to various training institutions tend to increase the burden on families.

It is widely believed that China will eventually drop the birth policy completely allowing couples to have as many children as they want, but is it already too late? Worldwide, we are experiencing a rapid aging population, with declining birth rates and increasing life spans. What is stopping us from having more children? Please share your thoughts with us.

Not entirely a “she-cession” but globally women are the key to economic recovery

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Advanced economies in Europe and North America are finally emerging after a year of COVID-19 lockdowns largely due to mass vaccinations, while populations in Africa and hard-hit South Asia and Latin America grapple with both vaccine access and labor informality. In a year mired by uncertainty, the economic and societal shocks of the pandemic impacted women and men differently—across the world, women were more likely to lose jobs, cut back paid hours worked, and became the default childcare providers in households.

In much of the world, women were left with no choice. In the United States, the pandemic erased the strides women had made in labor force participation rates since the 1960s.  By 2019, American women made up more of the workforce than men (approximately 50.04 percent of payrolls). [1]  Today, American women’s labor force participation stands at 57.4 percent which is lower than the pre-pandemic 59.2 percent in February 2020 and the lowest level since December 1988. [2] It is true that women’s employment suffered because many works in the services sector which witnessed hard hits in retail, healthcare and hospitality, while in developing countries women face high levels of informality which lack social safety nets to buttress the financial impact of a pandemic.

Last summer, an analysis by the McKinsey Global Institute showed that women comprise 39 percent of the global labor force but represented 54 percent of total job losses due to Covid-19. Many women’s choices disappeared as the pandemic created a childcare and education crisis with disruptions to everyday life.

Reactivating the economy with women in mind in a post-COVID world

Unemployment impacts men and women differently because society expects men to work and be the breadwinners, while women even with similar education levels as partners or husbands spend more time caring for the household. Perhaps it can be said that unemployment is shaped by gender, class, and social norms. While unemployment increased for those without university degrees or the ability to work from home, women and minority populations were disproportionately impacted. Even prior to the pandemic, gender inequality put women under greater financial pressure with unstable work contracts and less access to education and technology than their male peers.

The World Economic Forum’s Global Gender Gap 2021 report points out that the pandemic has increased the timeframe it would take to close the gender parity gap from 99.5 years to 135.6 years in terms of salary, education, and political empowerment. Overall, jobs provide people with earnings but more importantly they offer an identity that contributes to happiness and self-esteem. Covid-19 has left a void for women used to navigating a world of work instead of childcare.

The story of this pandemic is that women left the workforce independent of their education level or jobs held –at least in the United States, it appears this decision was based on whether children returned to in-person school. In Peru, children have yet to return to in-person schooling since March 2020, while other countries in the region have turned to hybrid models.  According to the International Labour Organization, approximately 13 million women in Latin America and the Caribbean witnessed their jobs vanish in 2020 due to the pandemic—with a regional total of 25 million women unemployed or out of the labor force. In developing countries, many women work informal jobs in vulnerable sectors usually earning daily wages with no sick leave or the safety net of unemployment insurance.

COVID-19 exacerbates digital biases and the gender pay gap

Additionally, women have dealt with digital biases (i.e., approximately 300 million fewer women have access to smartphones in low- and middle-income countries or 20 percent less than men according to the World Bank) in a world that overnight became more reliant on connectivity for survival coupled with the ever-present gender pay gap. Even today, in the United States women with school-aged children are slowly narrowing the gender divide and returning to work.

The pandemic accelerated the uptake of digital technologies by everyone from pre-school children to grandparents, from the “mom and pop” shop to women entrepreneurs turning to e-commerce platforms to sell goods and services, as well as the many other occupations that quickly adapted to a new normal for economic survival. With this faster than expected digital transformation, the workforce and especially women will have to adjust and gain new skills to remain competitive and stay employed.

A few years ago, McKinsey estimated that anywhere from 40 million to 160 million women would have to make occupational transitions due to automation. This holds truer today because the pandemic accelerated digitization of industries and services. Globally, policymakers are having discussions on the interplay between skills demand and the role of human capital to foster digital transformations across industries and firms.

In short, countries are reemerging at a time when technology and artificial intelligence (AI) are shaping how we live, work, and play at a faster rate than pre-pandemic levels.  Societies cannot afford to have women lag behind in terms of employment opportunities in both advanced and developing countries. In OECD countries, job growth pre-pandemic had been led by a demand surge for high skills benefitting women instead of men—partly because more women graduate with tertiary degrees than men.

In low- and middle-income countries, women entrepreneurs comprise a large percentage of the labor force. In Africa, women comprise about 50 percent of the continent’s self-employed workforce in the non-agricultural sector. [3] But the impacts of the pandemic stripped away sources of support from both high-skilled and low-skilled women essentially pushing many out of jobs and now preventing them from job seeking—limiting lifetime earnings and stunting a country’s economic growth.  Economic recovery depends on governments ensuring that women have equal access to jobs, digital connectivity, and digital skills.

JANZZ.technology is here to guide public employment services to navigate the post-COVID economic recovery by providing AI-driven digital solutions that empower women and the most vulnerable job seekers in the labor market to match their skills and talents with quality jobs.  Let’s rethink how we approach women’s labor force participation using actionable insights with non-discriminatory and unbiased jobs matching results by contacting info@janzz.technology and visiting our product site for PES.

 

 

[1] Time Magazine. Women are Now the Majority of the U.S. Workforce—But Working Women Still Face Serious Challenges. January 2020. https://time.com/5766787/women-workforce/

[2] National Women’s Law Center Factsheet. Ewing-Nelson and Tucker. April 2021. https://nwlc.org/wp-content/uploads/2021/04/March-Jobs-Day-2021-v1.pdf

[3] World Bank. Profiting from Parity: Unlocking the Potential of Women’s Business in Africa. 2019. https://openknowledge.worldbank.org/handle/10986/31421

When cloud meets COVID: How cloud computing is transforming across sectors – especially in public services

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By now we all know that when tech companies say that data is in the cloud, it has nothing to do with those white fluffy things in the sky. In fact, “cloud computing” is nothing more than a fancy marketing term designed to give users a magical feeling instead of telling them straightforward that their data is stored on the server in a data center. The use of the term first appeared in 2006 in an industry conference introduced by one of the largest tech companies. Since then, it has come into broader use. The idea of network-based computing, however, can be traced back to the 1960s. [1]

For a long time, the risks associated with using clouds have limited the widespread adoption of this technology. However, the pandemic has proven to be a strong driver for cloud adoption, as companies, especially government agencies, are increasingly investing in cloud solutions. But the risks remain. Companies and government agencies need to be aware that they could lose control of their strategic data and prepare for such circumstances. In some countries cloud service providers are required by law to allow government agencies to access data in the cloud, even if the data is located outside the country. An example of this is the U.S CLOUD Act aimed at US companies, the largest cloud providers in the market. Despite concerns about the security of information in the cloud, the latter presents itself as “the” solution that will help us through the crisis.

Online education

The Financial Times reports that more than 1.5 billion students worldwide have been kept out of classrooms by COVID-induced school and college closures. Thanks to cloud-based applications and tools, many of them have been able to continue with online lessons. Despite challenges such as insufficient access to online resources and lack of focus compared to traditional classroom situations, educators believe many of the new cloud technologies will remain post-pandemic. Hybrid approaches that mix onsite and online learning will most likely continue in the coming semesters.

Working from anywhere

Many of us have worked from home before and realized that cloud applications and services are the backbone of remote work. Nat Friedman, the CEO of GitHub, one of the largest open-source communities for software developers, explained in an interview that in the past, many of the world’s most ambitious software developers had to go to the West Coast of the U.S. to realize their dreams, but can now do so simply by going to the cloud. As he noted, GitHub’s developer community in the U.S. has shrunk by 10% in the last year, while other locations like Nigeria, Bangladesh, Egypt and Colombia have become the strongest growth areas.

This furthermore provides a novel way for companies to solve their talent shortage. Many developed countries have started hiring people from abroad for remote work, especially from countries where wages are lower on average. But the pandemic also highlighted the risks of offshoring: When call centers or data labeling companies in India closed, without computers, Internet access and security clearance employees could not work simply from home there.

Accelerated public sector investment

In many government departments, security concerns have been the main reason for reluctance to adopt clouds. However, the response to the pandemic and the increasing demand from the private sector and citizens for digital access to public services have increased the pressure to modernize applications and infrastructures. As a result, more openness and renewed interest in cloud adoption can be observed.

Government agencies use the cloud for its cost savings, scalability and rapid deployment. Gartner predicts that by 2025, 95% of new government IT investments will be as a service solution. Although COVID-19 posed a major opportunity for cloud providers, only those that are prepared can handle such unexpected spikes in demand.

At JANZZ.technology, we provide integrated labor market solutions for Public Employment Services (PES) via cloud. Through our robust and rich architecture, we can successfully manage any sudden increased load and deliver an uninterrupted user experience. By leveraging embedded machine learning (ML) and artificial intelligence (AI), PES can get powerful real-time analytics on labor markets with state-of-the-art solutions, even in countries with less infrastructure.

As a Swiss company, we have a different regulatory regime than most other major vendors in the market. At JANZZ.technology, our solutions are primarily offered as SaaS/DaaS in a strictly regulated, ISO 27001, CCPA and GDPR compliant private cloud environment, usually also on the territory of the country where we operate. Pandemic or not, we have long recognized the urgency of digitization transformation within public services, especially PES. And we are prepared to support PES of any size on this digitization journey.

To learn more about our cloud-based SaaS/DaaS solutions for Public Employment Services (PES), please visit our product site for PES or contact us at info@janzz.technology.

 

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[1] https://www.technologyreview.com/2011/10/31/257406/who-coined-cloud-computing/#:~:text=Part%20of%20the%20debate%20is,term%20to%20an%20industry%20conference

“No unemployed candidates will be considered at all” – the crux of unemployment.

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Back in 2008, when we first started developing our solutions, the work of Diamond, Mortenson and Pissarides provided the scientific basis for our job and skills matching technology. With their Nobel prize winning labor market theory and the DMP model, they provided a first coherent, complete framework to think about labor market dynamics in a structured way. In their theory, labor markets are viewed as markets with search frictions: workers look for suitable jobs and employers look for suitable workers, both investing considerable time and effort; search frictions are the process, or time factor, of matching the two.

The DMP model itself describes the search activity of the unemployed, the recruiting behavior of businesses and wage formation. When jobseekers and employers find each other, they negotiate wages based on the labor market situation: the number of unemployed workers and the number of vacancies, as well as other factors such as how long it will take to find that job, the workers’ unemployment benefits and what value the worker attributes to not having to work while searching. The model can thus be used to estimate the effects of different labor-market factors on unemployment, the average duration of unemployment, the number of vacancies and real wage. Such factors may include the level of unemployment benefits, the real interest rate, the efficiency of employment agencies, hiring and firing costs, etc.

On-the-job search and its effects on labor market dynamics

This framework significantly furthered understanding of how mismatch problems and a lack of symmetry between different search mechanisms and the resulting imbalance between supply and demand affect the functioning of the labor market. However, one key aspect of the labor market is completely ignored here, namely that not all jobseekers are unemployed. The majority of the literature since then typically also focused on the unemployed, not only because the standard DMP framework does not include on-the-job search, but also due to limited availability of on-the-job search data. More recently, however, research has begun to include on-the-job search and job ladders. The idea of a job ladder is that all workers agree on which jobs are more desirable in the sense of job and wage satisfaction and slowly climb the job ladder from “bad” or unsatisfactory jobs to “good” jobs through job-to-job transitions. Occasionally, negative shocks throw them off the ladder and back into unemployment. A growing number of studies have documented the importance of on-the-job search and its related job ladder dynamics for macroeconomic outcomes.[1] Some argue that the labor market is segmented in that employed and unemployed jobseekers are unlikely to directly compete with each other for jobs because they have different job-relevant characteristics and apply for different jobs. For example, Longhi and Taylor (2013) state that the unemployed only apply for “bad” jobs and the employed for “good” jobs and so they do not compete. However, they do not investigate the reasons for this behavior and it may well be that the cause is somehow tied to the search behavior of employed workers or related dynamics. For instance, they find that a larger proportion of the unemployed “prefer” a part-time job compared to the employed and state that this supports their claim of a segmented labor market, ignoring the fact that this may not be an inherent “preference”, but instead a higher flexibility on part of the unemployed based on their more pressing need to find any employment at all. Even though they note themselves that part-time workers are more likely to search on the job, probably because they are “unsatisfactory in terms of labor supply preferences”. Similarly, they find that the two groups tend to use different search methods, with the employed focusing more on using their networks and the unemployed relying more on job centers and employment agencies. They use this as another argument for their conclusion that they are not applying for the same jobs, apparently because the jobs available through these different channels differ. But this could instead have more to do with the fact that with increasing length of unemployment, jobseekers’ personal and professional networks decline and the unemployed become more reliant on institutional support. It does not necessarily imply that the unemployed actually want to apply for different jobs.

Indeed, the bulk of recent literature finds that on-the-job search has a clear effect on macroeconomic outcomes and the chances of unemployed jobseekers on the labor market. Moscarini and Postel-Vinay (2019) and Faccini and Melosi (2019) link on-the-job search to inflation, arguing that when employment is concentrated at the bottom of the job ladder, typically following a recession, employed workers search to find a better job. As workers climb the job ladder, the labor market tightens and generates inflation pressures through wage negotiations. Eeckhout and Lindenlaub (2019) provide an elegant theory where the search behavior of employed workers generates large labor market fluctuations even in the absence of other shocks through a strategic complementary between on-the-job search and vacancy posting. According to this theory, the labor market itself can generate cycles, contrary to the longstanding assumption (based on the DMP model) that such cycles can only be generated by exogenous shocks. The authors state that active on-the-job search improves the quality of the jobseeker pool, which encourages vacancy posting through firms, which makes on-the-job search more attractive. This corresponds to an economic boom with little mismatch, abundant job creation and low unemployment. On the other hand, during a recession, the jobseeker pool has a much lower proportion of on-the-job searchers. As a result, firms have less incentive to post vacancies, which generates a low matching rate for workers which cannot compensate the cost of on-the-job search, leading to high mismatch and high unemployment. The authors show that their theory, in particular the search behavior of the employed, can explain many important labor market phenomena, including large fluctuations in unemployment and the fact that unemployment rates take much longer to recover than vacancies and productivity, say, following a recession.

It may seem counterintuitive that the behavior of the employed could explain unemployment. But the employed typically have a share of over 90 percent of the labor force and apply for job openings in the same labor market as the unemployed. Therefore, any minor change in their behavior has deep aggregate implications for unemployment. Even if they search much less intensively than the unemployed, on average, almost half of the new jobs are filled by employed workers. Particularly at the end of a recession, the employed searchers crowd out the unemployed ones. As job creation picks up, jobs go disproportionately to the on-the-job searchers and not to the unemployed. All the renewed activity thus initially translates in better jobs for the employed, but not in improved prospects for the unemployed.

Based on a survey that focuses on job search behavior regardless of labor force status, Faberman et al. (2020) find evidence supporting Eeckhout and Lindenlaub’s theory in the following three facts: (1) on-the-job search is pervasive, and is more intense at the lower rungs of the job ladder; (2) the employed are about four times more efficient than the unemployed in job search [2]; and (3) the employed receive higher-quality job offers than the unemployed.

The stigma of unemployment

What these theoretical models and studies do not mention, is why the employed are more successful in job search and receive higher-quality job offers than the unemployed. Much of this may have to do with the stigma of unemployment – especially long-term unemployment [3]. The quote in the title of this article is from a job posting by Sony Ericsson, and they are not alone. Various studies (for example, the ones described here and here or here) have shown consistently over the years that hirers are biased against unemployed applicants, often assuming that the unemployed are lazy, less productive and less competent workers than employed applicants with otherwise equal characteristics. A 2019 study found that, based on stereotypical perception of unemployed applicants, hirers even condemn their character: unemployed job candidates are seen as less warm, less trustworthy, less well-intentioned, less friendly, and less sincere compared to employed job candidates. No wonder the unemployed are forced to settle for “bad jobs” – if they find employment at all.

And this biased perspective is not only found in hirers, it also seems to be widespread among researchers. For instance, at the core of Eeckhout and Lindenlaub’s theory is the implicit assumption that employed jobseekers are more attractive and valuable than unemployed ones (active on-the-job search improves the quality of the jobseeker pool). Even the DMP model takes a stigmatized view of unemployment: the result that higher unemployment benefits raise unemployment rates is rooted in the assumption that higher income through benefits decrease the unemployed worker’s motivation to search for a job and thus to successfully reenter the labor market. To put it bluntly, the model assumes that unemployed workers prefer leisure to work (are lazy) and puts the blame on them (a motivated unemployed person could find a job at any time).

This, together with the fact that research demonstrates that long-term unemployment also leads long-lasting damage such as to lifetime lower wages, increased health issues, lower quality of life and diminished lifespan as well as an increased risk of suicide, clearly shows that unemployed jobseekers should be protected and that efforts should be increased to prevent further unemployment and to mitigate long-term unemployment. One small but simple step is already apparent: promote solutions that prevent this bias, at least in the first steps of the candidate selection process, by using labor intermediation systems that mask labor force status. However, many current systems and platforms offered by PES only provide access to unemployed jobseekers. These systems are rarely successful, often barely frequented by companies and potential employers. And the stigma of unemployment is a key reason for this issue. To be sustainable in the long term and offer unemployed jobseekers a real chance to return to work, a good PES platform must include the whole universe of workers and specialists from all fields and industries and competences.

Of course – contrary to what some software providers claim – simply introducing the right software will neither fully solve the problem of discrimination against the unemployed, nor can it reduce unemployment on its own. This is a complex issue depending on many factors which needs to be tackled from multiple angles. Nevertheless, such solutions can serve as an effective component of well-designed labor market and anti-discrimination policies.

Here at JANZZ, we don’t just go with quick marketing headlines, we develop evidence-based solutions and  have already been deploying them successfully since 2010. Our job and skills matching solutions are fair and non-discriminatory, producing completely unbiased results according to the OECD principles on AI. This guarantees that the best candidate with the best aptitude in all individual criteria achieves the best match – regardless of labor force status or other non-relevant characteristics such as origin, age or gender. Which is one of the many reasons why we are a trusted partner of an ever-growing number of public employment services across the globe.

If you want to take this first step in breaking the cycle and contributing to a fairer labor market for the unemployed, contact us at info@janzz.technology or visit our product site for PES.

 

[1] Christensen et al., (2005), Cahuc, Postel-Vinay, and Robin (2006), and Bagger and Lentz (2019), among others,
[2] If they had relied only on transition rates – a common approach in the literature due to lack of data on job search effort – they would have found the opposite result of Fact (2), namely that the unemployed are about seven times more efficient.
[3] In the US, long-term unemployment is defined as (active) unemployment for longer than 6 months; in the EU for longer than 12 months.