Occupational classification systems in the digital age

People have long been monitoring the economic activities of our society. It is said that during the Chinese Tang Dynasty (618-907) there were 36 different job types. Fittingly, the period marks the origin of the famous Chinese saying that ‘every trade has its master’ (san shi liu hang, hang hang chu zhuang yuan).

Today, jobs are changing at such a speed that it is almost impossible to give an exact number of the occupations that affect our daily life. Compiling statistical records of occupations is also becoming complicated since jobs are changing, disappearing and emerging. There used to be only ‘the’ manager, but now there is a PI manager, an IT manager, a project manager, an intergenerational engagement manager, you name it.

Thus, other than listing simply all occupations for statistical purposes, job descriptions, skill and experience requirements, education levels and more aspects are integrated, too, in occupation-related databases. That way, we can not only better understand the jobs of today but also develop more sophisticated systems that are able to perform more complex services with occupation data. For example, this enables performing the tasks of career planning, job searching, identifying trends or guiding policy design.

US-based classification systems

The United States Department of Commerce released the Standard Occupational Classification (SOC) in 1977. Back then, many programs by the US government began collecting statistics which is why the federal government needed a unified occupational classification system. SOC entails a short description and illustrative examples for each job. It is classified based on the type of work performed, but rarely on the level of skills and education needed for a specific position [1]. The latest version of SOC was published in 2018.

 The online database O*Net is an expansion of SOC and was created during the mid-1990s by the US Department of Labor’s Employment and Training Administration. O*Net can be freely accessed and downloaded by job seekers, students, businesses researchers and workforce development professionals alike. Compared to SOC, it is a much more sophisticated system with more detailed information such as tasks, technology skills, knowledge, abilities, education level and work style.

 Europe-based classification systems

The international Standard Classification of Occupations (ISCO) is maintained and managed by the International Labour Office (ILO). ISCO is the main international classification of occupation-related data and used for international exchange, reporting and comparison. It also serves countries and regions that want to either further develop their own occupational classifications or directly adapt one from ISCO-08. Examples include Ö-ISCO in Austria, Styrk-08 in Norway, COCR-2011 in Costa Rica, NOC 2016 in Canada and most national occupational classifications in Asia.

In July 2017, the European Union launched the first version of a European multilingual classification of skills, competencies, qualifications and occupations (ESCO) that is also based on ISCO-08. ESCO aims to create a common understanding of occupations, skills, knowledge and qualifications across the EU’s official 24 languages that enables employers, employees and educational institutions to better understand needs and requirements. Under freedom of movement ESCO could aid in making up for skill gaps and unemployment in the different member states, as the President of the European Commission Jean-Claude Juncker states [2].

Industry classifications

Industry classifications or industry taxonomies group companies by industry and in terms of production processes, products or job positions. They serve national and international statistical agencies for the analysis, comparison and summarization of economic conditions. Well-known industry taxonomies include NAICS, ISIC, GICS, NAF 2015 and MUPCS.

Furthermore, a shift from occupational classifications towards skills classification has been observed. This shift is linked to an attempt of improving classifications’ ability to aid in career guidance and the conduction of upskilling and reskilling. The United Kingdom and the innovation foundation Nesta have built the UK’s first data-driven skills taxonomy. It allows for measuring the country’s supply and demand of skills and for preventing skill shortages. The social media platform LinkedIn has also built a skills taxonomy for its users.

Chinese classification systems

China started to create its occupational classification in 1995. After four years, the country released its first version. Currently in use is a version from 2015 that aims to keep pace with the fast-changing employment sector. The Chinese classification has 4 digits with 1838 professions in total.

Compared to O*Net, which was created during about the same time period, there is still much room for improvement in the Chinese occupational classification. Specifically, it could be improved with regard to accessibility, continuous data updating and the provision of guidance for students and job seekers [3]. However, the problem of lacking in updated data is not unique to the Chinese occupational classification. This issue is shared with many other classifications, including O*Net.

A new concept for occupational classification systems

The creation of a traditional expert consultation taxonomy is time-consuming, costly and, most importantly, will lack the ability to continuously adapt to the world’s fast-changing working environment.  Therefore, a new solution is needed. One that can inform the labor market constantly and make job seekers, students, education providers, employers and policy-makers alert for change and empowered to react.

With digitalization, a data-based information collection methodology can revolutionize the way classification systems are created. At JANZZ.technology, we have mapped all international occupational classification systems and others in our ontology. (If you would like to learn about the difference between taxonomy and ontology, please check https://janzz.technology/ontology-and-taxonomy-stop-comparing-things-that-are-incomparable/).

This mapping allows us to analyze complex sets of occupational data and to annotate it with intelligent and standardized meta-data, which makes the data comparable in further processes like benchmarking, matching or statistical analyses. Our JANZZclassifier! is a product for everyone who has large volumes of (unstandardized) occupation-related data such as job titles, hard and soft skills and, particularly, training/qualifications. It enables you to simply run your data through our API and will return more meaningful data and, if desired, one of the standard classifications.

Above all, we are using real-time data, both from our users, our partners and the labor market in order to constantly update our database. It is the new way to develop classification systems in the digital age. Please write now to sales@janzz.technology if you wish to learn how our ontology may assist you.

 

[1] Jeffrey H. Greenhaus and Gerard A. Encyclopedia of career development.

[2] ESCO (2015). ESCO strategic framework. Vision, mission, position, added value and guiding principles. Brüssel.

[3] LI Wen – Dong and SHI Kan. 2006. A brief introduction to the development of the U.S. national standard occupational classification system and its implications to China. URL: https://www.docin.com/p-1479318301.html [2019.06.24]