By David Diviny

Is it just me or does it feel like in 2019 we have reached “Peak Future of Work”? I am not sure if anyone needs convincing that the world of work is changing. Technological disruption is already changing the jobs and career paths of people at an unprecedented scale and pace, and the skills required to succeed in these jobs have already changed.

The unresolved challenge is what to do in response. This challenge is faced by current and future workers, employers, policy-makers and education providers. Many have begun tackling it. Notably, the Foundation for Young Australians’ New Work Order research series has analysed how disruption to the world of work has significant implications for young Australians. These disruptions include automation, the reduction in entry-level jobs and changes in the skills required for a successful career. FYA has re-conceptualised traditional occupations as clusters of work that demand similar skill sets.

Nous’ recent work extends this thinking from clusters to networks. We explored how social network analysis might offer a new way to think about career development and transitions in the labour market. This analysis unlocked new ways to explore career development for individuals and to reskill workers transitioning to a new job.

Social network analysis, a powerful new field, examines the relationship between the nodes in a network (e.g. individuals or things) and the ties between them (e.g. links or relationships). Ideas underpinning social network analysis may be familiar through “Six Degrees of Kevin Bacon”, an early internet phenomenon. At a personal level, social media networks like Facebook and Twitter make our own social networks an inherent part of the experience.

We combined this analytical technique with a rich dataset of about 7.4 million unique Australian job advertisements, drawing on real-time job data from Burning Glass Technologies. For each occupation we identified the top 10 most frequently advertised skills, providing a profile enabling identification of career progression opportunities based on common skills.

To construct the ties in the network, we defined pairs of occupations (i.e. the nodes) that shared five or more of the top 10 enterprise skills and five or more of the top 10 specialised skills. (Enterprise skills are generic skills transferable across jobs and specialised skills are particular to an occupation.) These represent the common skills that theoretically enable an individual to move from one occupation to the other with limited further development. For example, the common skills between checkout operator and retail supervisor is shown here:

Network analysis can provide deep insight into different occupations in the network of occupations. This insight can be into the connectedness of different occupations (i.e. how many jobs can you get to in one career transition), the pivotability of a job (i.e. how many career paths is it on) and the structure of the entire labour market. Curiously, the principle of six degrees of separation (and six degrees of Kevin Bacon) applies to our analysis of the labour market – the average length of the pathway between any two connected occupations is also six job transitions!

The number of occupations available for career change or progressions differs between occupations. The connectedness of different occupations is not uniformly distributed. Approximately 10 per cent of jobs connect to more than eight occupations and most occupations are connected with two or fewer occupations.

These well-connected occupations, shown below, are predominantly management, sales or labouring and trades occupations. The skills advertised for these occupations are typically a mix of enterprise skills and specialised skills that are transferrable across industries and occupations.

Interestingly, analysis of the network, together with advertised salaries for jobs, shows returns to specialisation. Very few high-salary occupations are also highly connected to other occupations:

Insight mined from networks can help us support workers to navigate the labour market. Highly connected occupations can provide routes for career development for young people, together with reskilling pathways for workers who need to transition or reskill because of automation.

Nous recently delivered to the NSW Department of Industry a prototype of a consumer information tool for current and future workers: a dynamic digital platform that allows users to understand the connections between career paths. At a glance, users can see the relationships between occupations, along with education requirements, salaries and entry-level opportunities.

This example shows a route for career development through skill acquisition from checkout operator to CEO in three occupation transitions:

This analysis just scratches the surface for combining new data with advanced analytical techniques. This analysis of the labour market has a range of potential applications, including:

• Employers can apply this analytical technique to their own workforce to help reshape it in response to digital disruption.
• Universities can use this analysis to inform the design of new courses and to identify opportunities for short courses that can support viable career pathways.
• Policy-makers can use this analysis to rethink the design and funding of our education and training system.

Get in touch to find out how Nous can use advanced analytics to creatively solve problems and deliver value to your organisation.