Big Corporations: A Quarter of a Million Want to Leave

Career aspirations today are radically changing. Fifteen years ago, big corporations were the ultimate prestigious go-to for graduates but now they are seriously losing appeal for many young talents. People today want to build careers on their own terms.

The widening gap between people’s aspirations and what most professional jobs offer is leading to an epidemic of dissatisfaction, especially among employees in big corporations. The Escape the City initiative that has been working with disillusioned employees for over 5 years tried to identify the underlying issues of professional disaffection and to get behind the drivers of the changing career aspirations. According to the study, a quarter of a million workers in the UK want to leave big corporations in favor of companies that are more aligned with their values. Accenture, Ernst & Young and PWC are the corporates that most respondents want to leave, whereas companies like Airbnb, Uber and Virgin Galactic are at the top of people’s employer wish list.

Top Ten Companies to Escape and to Join

Source: Escape the City

But why is job dissatisfaction so high? And why does it culminate in big corporations like KPMG or Deloitte? The main issues that cause disaffection are the lack of personal freedom, a clear sense of purpose and a sense of positive social impact, worries about mental and physical health and the absence of creativity, innovation and entrepreneurialism at work. Half of the corporate employees that partook in the study feel that they cannot use their strengths or skills in their current jobs. Consequently, 54% cannot see themselves working in their organization in five years’ time.

Big corporations have failed to spot and catch up with the new ways of earning a living that are rapidly emerging. They still operate according to increasingly outdated paradigms that do not correspond to today’s working professionals’ values. The Escape the City survey admonishes corporates that their outdated attitude towards work is taking its toll on their image: “Perhaps, dear Corporates, you might wish to ask yourselves the questions that your employees are already answering: What is my purpose here? What difference am I making in the world? What positive mark will I leave behind after I’m gone? In a world where I could spend my days any way I choose — why should I spend them doing the work that I’m doing right now?”

It seems that big-named corporations have been living off old glory. Four of the top ten companies that workers want to escape are still to be found on the Times Top 100 Graduate Employers list, on which renowned corporations still hold 17 of the top 20 spots. While a host of talented graduates indeed flock to pursue a career within the corporate world, there is also a rapidly increasing movement away from the prestigious graduate schemes towards jobs in small businesses, start-ups and non-profit organizations. The growing importance of alternative careers is also highlighted by George Monbiot’s article in the Guardian warning students of entering a career in banking, finance or consulting rashly (How a Corporate Cult Captures and Destroys Our Best Graduates). There is indeed a trend of students moving away from these traditional career options; only 15% of Oxford graduates and 16% of Cambridge graduates now pursue finance and consultancy jobs when they leave university.

Furthermore, people’s aspirations to start their own business are increasing exponentially. Innovations in technology and communications make starting one’s own business easier and easier. And social media relentlessly celebrate every success, adventure and champagne moment creating ever higher entrepreneurial aspirations.

We find ourselves in a work revolution, in which the alignment of our own values and those of our workplace is becoming more and more important. – the job platform that works like a dating site – provides an efficient means to find our exact match. Using the latest semantic technologies, it precisely matches profiles of job seekers, employers, freelancers and companies.

Mapping Stereotypes: Immigrant Jobs in the US

Immigrants in the US are widely held to be employed in low-wage jobs such as gardening or housekeeping. A map created by Business Insider, showing the most common jobs held by immigrants across the United States, reinforces many stereotypes. However, a closer look reveals some surprising results.


The map largely offers an image of immigrants’ jobs corresponding to people’s prejudices, with immigrants holding down low-paying jobs in sectors such as agriculture on the West Coast and housekeeping and construction across much of the South. Yet, there are also four states in the East in which immigrants most commonly work as college professors, and in Delaware the predominant occupation among people born outside the US is software developer.
More importantly however, the map reveals that a significant number of immigrants work as health aides, nurses or personal care aides. Jobs in healthcare will be increasingly in demand with the aging of the population and the supply of workers will depend in part on the availability of immigrant workers.

Indeed, the distribution of immigrant jobs shown on map may lead to false conclusions regarding immigrant employment. The map suggests that most immigrants are employed in low-wage jobs, such as agricultural work or housekeeping. However, the Economic Policy Institute found in an extensive survey that, in the United States as a whole, there are almost as many immigrants in white-collar jobs (46%) as in all other occupations combined. Thus, the perception that all immigrants work in low-wage jobs is clearly inaccurate. While immigrants might be overrepresented in some occupations and underrepresented in others, the discrepancy between the US and foreign born population is not as dramatic as is often assumed. While immigrants are overrepresented in low-wage occupations, as the map shows, they also play a significant role in some high-wage and middle-wage jobs. An analysis of the Bureau of Labor Statistics data for example reveals that high-skilled immigrant workers are overrepresented in industries such as information technology, life sciences and high-tech manufacturing.

However, the fact many immigrants work in high-skilled and high-wage jobs offers little consolation for those at the bottom. Low-wage immigrant workers do not enjoy the benefits of employer-provided training programs as these are usually geared to managers or highly skilled employees. They are also outside the reach of government-sponsored job training programs that aim to inject more equality in the labor market. The data from the census that is represented on the map includes both documented and non-documented immigrants. While documented immigrants tend to hold higher skilled jobs, undocumented immigrants are relegated to menial work. The social gap is wide apart between immigrants at the top and at the bottom and it is not due to get any narrower soon.

In any case, foreign workers make up a large portion of the US work force and are vital to the US economy. An infographic that sums up data from the Immigration and Integration Initiative, as well as original AS/COA research shows just how big an impact immigrants both documented and undocumented have on prosperity in the United States. For example, immigrants started 28% of all new businesses in 2011, employing 1 in 10 US workers, while they only make up 13% of society as a whole.  On average, immigrants pay $1,800 more in taxes than they receive in benefits. They also produce significantly more consumer spending, thereby creating new jobs.

Both the insights from the map and from the infographic remain rather superficial because the statistical analyses do not go beyond job titles. For instance, it might be interesting to see, what skills or talents immgrants in the US bring with them exactly and how they could be put to use most efficiently. Also, an international comparison with other countries would offer valuable insights. An indepth investigation of immigrants’ occupations and skills would mean processing a wealth of data. More importantly however, it would require adequate tools that allow drawing significant conclusions. offers exactly that. Its semantic matching technology and its expertise in occupation and skills data provide an effective means to analyse the potential and shortages of immigrants’ skills. Furthermore, would allow to compare the immigrants within the US workforce to immigrants in other countries, as the ontology JANZZon! connects job titles, skills and qualifications across multiple languages and cultures. The ontology would also allow to assess the skills of immigrants better, showing them what skills exactly they lack in order to climb up the social and economic ladder. The tools by therefore offer a starting point in order to allocate immigrants to the best possible occupations and to learn from an international economic comparison.


The Rise of the Machines: The Disruptive Potential of Cognitive Computing

As cinematic representations of intelligent machines over the past decades have shown, the fascination with and the fear of artificial intelligence always inevitably mix. People enjoy the thrill of watching humans knocked off-balance by AI in Ex Machina, robots trying to take over the world in I Robot, or seeing an entire team of Marvel superheroes fighting Ultron in the latest Avengers movie. But also in real life, intelligent machines are rivalling with humans and many are afraid of automation and digitalization stealing away people’s jobs. Still, the quest for intelligent machines is relentless.

Thinking Robot --- Image by © Blutgruppe/Corbis

Thinking Robot — Image by © Blutgruppe/Corbis

Back in 1997 the Deep Blue computer picked grandmaster Garry Kasparov apart in a chess match. Three years ago, supercomputer Watson competed on Jeopardy! against two champions and defeated them by far. Now, Watson helps doctors make more accurate diagnoses using raw data from medical research and patient histories. In Japan, cuddly robot bears are hailed to be the future of elderly care. The ability to talk to one’s phone or tablet is not relegated to the imaginary space of films such as the science-fiction drama Her but is a reality. These and many more innovations in the field of artificial intelligence have profound implications for the relationship between man and machine.

Indeed, in our increasingly digitalized world with exponentially growing data volumes, complex issues are handled much more effectively by computers than by humans. Computers can process large volumes of data in a speed unattainable for humans. Not only is data increasing in volume but also in speed, variety and uncertainty. Most data is now supplied in unstructured forms such as images, videos, symbols and natural language – hence, computer systems needed to step up to the challenge in order to process this new kind of data. Cognitive computing aims to simulate human thought processes in a computerized model. Self-learning systems that use data mining, pattern recognition and natural language processing are trained to mimic the way the human brain works. Ultimately, cognitive computing strives to solve complex problems independently, without human assistance. According to Gartner, the era of cognitive computing, also called the smart machine era will be the most disruptive in the history of IT.

While AI capabilities such as natural language processing, speech recognition and machine learning algorithms were invented 30 years ago, it is only now that these technologies find significant application in business systems. More than 2’300 startups have been founded and venture capitalists have invested billions of dollars in the field of AI lately (a representation of the AI business landscape can be found here). Furthermore, major players like Amazon, Google, IBM, Microsoft, SAS and Yahoo are investing in the development of smarter applications.

Why now? The exponential growth of unstructured data not only offered a challenge to computer systems but also an effective means to train machines. Big data, along with improvements in the above mentioned disciplines, is what’s making the difference in machine learning. Sophisticated algorithms can only learn to solve problems independently by repeated training using big data. The success of smart applications thus depends largely on the quality of data that they are fed.

In healthcare, the finance industry, e-commerce, customer relationship management and search engines, cognitive computing is employed in order to support human experts in making faster and more accurate decisions. While machines have thus replaced human work in many fields, especially where manual work is concerned, artificial intelligence does not supersede human experts but rather acts as a catalyst. Cognitive computing systems can amplify the possibilities of what either machines or humans could do on their own. also supplies such a system in the field of employment, skills and talent. The ontology JANZZon! and the smart matching engine JANZZsme! make complex problems such as job and skills matching computable and completely change the way we think and go about job searching. As the applications of are structured semantically, that is, occupations, skills and qualifications etc. are interlinked logically; they can deliver meaningful results for complex searches for job vacancies, employees, freelancers etc. in real time, across multiple languages. Importantly, the applications are constantly fed with new data and therefore become more accurate over time. With the tools by, you don’t search for a job – you are found.

The high quality of’s tools stems from its specialization and expertise in occupation data. The ontology JANZZon! has been built with solid industry-specific expertise and years of experience in HR. Every day, a dedicated team of IT-supporters and engineers work on improving the quality and extent of the ontology JANZZon!. A myriad of connections between occupations, skills and other data stored in the knowledge base is established continuously – like synapses in a human brain – turning the unstructured occupation data into structured data. Big data is turned into smart data. The gist: Cognitive computing tools are only ever as good as the expertise of their human creators. Also the success of the supercomputers Deep Blue and Watson may be explained by looking at the specificity and quality of their training. Both were built for one particular purpose, to play chess and to compete in Jeopardy!. Also in a later stage, Watson needed to be fed with a wealth of medical research and patient histories in order to be able to supply doctors with accurate treatments. The assumption that smart applications are superhuman all-rounders is thus vehemently inaccurate.

The only ones to fear the rise of cognitive systems are those who perform menial tasks. Sure, cognitive systems can process volumes of information in real time that we couldn’t even dream of but they need to be nurtured by human experts in order to perform accurately. Hence, HR cracks and doctors need not fear their digital supporters but rather welcome their disruptive and amplifying potential.