This section considers the difficulty of finding work from the perspective of the individual. It considers how hard it may be for an unemployed person to get a job based on their past occupation and current advertised vacancies, and what this looks like from a skills cluster perspective.

Data from the Australian Taxation Office indicate that when people change jobs, they most frequently change employers but remain in the same occupation. It is likely that, for many job seekers, the default option is to seek work in the occupation they have most recently held. Unfortunately, the vacancy profile can make this challenging. Figure 46 shows, at the national level, the most common previous occupations of unemployed people compared with the most frequently advertised vacancies.

Occupations in high demand are more likely to be specialised and require higher level skills and formal qualifications. These include occupations such as ‘registered nurse’, ‘software and applications programmers’, and ‘advertising and sales managers’.

Unemployed people tend to have experience in lower skilled or entry level jobs such as labourer, cleaner, storeperson or checkout operator. Even in occupations that make both the ‘recent occupations of unemployed’ and ‘online jobs’ lists in Figure 46, such as sales assistant and general clerk, the supply of unemployed workers outstrips the number of vacancies.

That said, caution should be taken when using internet vacancies as a measure of demand. Not all jobs are advertised on the internet and some are not advertised at all ⁴⁷. The NSC uses a range of inputs to measure skills shortages and surpluses; hence the charts in this section provide only one indication of the difficulties faced by unemployed people seeking jobs.

Taking this analysis from the occupation to the skills cluster level shows there is a difference between the skills profile of the unemployed and the jobs that are frequently advertised. Figure 47 shows the average amount of time currently advertised roles require for a skills cluster family compared with that of unemployed people’s previous occupations.

Figure 47: Skill intensity by skills cluster family for unemployed people and current vacancies

Vacancies for jobs requiring skills from the health and care family made much more intensive use of these skills than the occupations that unemployed people had come from. In total, vacancies required 10% of time to be spent on using these skills compared with 5% of time in the previous occupations of unemployed people. Vacancies also require a slightly higher proportion of time spent on health skills than is found in the employed population (9%) indicating that demand for health skills is increasing across the labour market. There is more discussion of this point in the section on ‘Trending and emerging skills’ in Chapter 7.

Drilling down into the health and care family reveals that the skills most in demand are related to management in thehealth sector, and high-level patient management. Skills in demand in management in the health sector include: ‘managing health care operations’, ‘collecting, documenting and communicating medical information’ and ‘creating health care documentation’. Skills in demand in high level patient management include ‘developing treatment plans’ and ‘monitoring and evaluating patient treatment’.

Few unemployed people have recently worked in occupations that have the required level of expertise in these areas. Unemployed people are more likely to have acquired skills from their previous occupation in direct patient care, such as ‘assisting and supporting clients’, ‘caring for patients’, and ‘administering medical treatments’.

Work which involves significant use of skills from the health and care skills cluster family is heavily regulated and subject to accreditation and licensing requirements. Strategies to address shortages of specific skills, such as those mentioned above, would need to take these frameworks into account. However, the trend for vacancies to demand more technical, supervisory and strategic skills than are typical among some unemployed people is also reflected in other skills cluster families.

Although many unemployed people have skills from the business operations and financial activities family, they tend to be in more entry level clusters, such as ‘conducting financial transactions’, ‘maintaining inventory’, and ‘estimating costs of goods or services’. Employers are more often seeking skills in management-related clusters, such as ‘manage and monitor financial activities’, ‘managing services, staff or activities’, and ‘establishing organisational policies or programs’.

The Australian Skills Classification (ASC) expands the possibilities for job seekers by identifying skills which are transferable across occupations. For example, although the number of unemployed sales assistants appears to greatly outstrip the number of job openings in most states, many of the skills they are likely to have acquired in their last role could be applied to occupations such as ‘beauty therapist’, ‘model and sales demonstrator’, ‘motor vehicle salesperson’ and ‘real estate sales agents’.

Figure 48 sets out the intensity of use for skills in common between ‘sales assistant’ and ‘real estate sales agent’. Most sales assistants would already have more than enough experience in ‘providing customer service and communicating information’, as sales assistants typically spend 19% of their time using skills from this cluster, whereas real estate agents tend to spend about 7% of their time on them. In contrast, a sales assistant may need to extend their current skills in ‘negotiating purchases or contracts’, because this skills cluster takes up more of a ‘real estate sales agent’s’ time than it does sales assistants (10% compared to 8%). In addition, sales assistants looking to move into real estate may need to build skills in ‘appraising or evaluating properties’, ‘analysing market data and trends’ and ‘developing marketing material’ which are not typically used in their current occupation. The number of real estate agents in Australia is projected by the NSC to grow by 8.5% over the next five years, and the move to such a job would bring the additional benefit of higher pay.

Figure 48: Transferable skills of sales assistants and real estate sales agents, percentage of transferable skill

Transition opportunities can also be mapped systematically across the labour market. Figure 49 shows the most common previous occupations of unemployed people, with the number of unemployed people in each category represented by the size of the bubble. The x-axis gives the number of current vacancies for the occupation and the y-axis shows the number of vacancies for similar occupations based on their underlying skills profile.

Unemployed retail managers face quite steep competition for roles in their own field, but many of their skills are transferable to other occupations with vacancies, making them relatively competitive in the overall labour market if they are prepared to consider other roles. General clerks both have a comfortable number of vacancies in their own field and many viable transition options. Checkout operators and office cashiers face the double disadvantage of few openings and a lack of skills that are transferable to occupations that are in higher demand.

Figure 49: Transition options for unemployed into wider labour market opportunities Transition options for unemployed into wider labour market opportunities

The VNDA offers insights into qualifications and training provider outcomes

The NSC is developing better ways to monitor the effectiveness of the vocational education and training (VET) sector to meet labour market needs.

The NSC is working in partnership with the Australian Bureau of Statistics (ABS) to create the VET National Data Asset (VNDA). This will allow us to assess the performance of the VET system with greater depth and accuracy. The VNDA will link Total VET Activity (TVA) data – showing who has participated in accredited training,
whether they completed the course and their background characteristics – to the Multi-Agency Data Integration Project (MADIP).

To date, the ability to monitor the outcomes of VET courses in the labour market has been limited by the data available. The Australian VET system is fragmented and this introduces further difficulties. There are more than 1,200 nationally recognised qualifications and 600 accredited courses, delivered by more than 4,000 registered training organisations (RTOs). Each state and territory has responsibility for its own system of subsidised delivery, introducing a further source of variation. Until now, the primary data source for student outcomes was surveys, which are costly to administer and often have low response rates, potential response bias and reporting lags.

A robust assessment of the performance of the Australian VET system must overcome a number of challenges. The impacts of education and training can only be observed after training has ended, and sometimes years after. Disentangling the effects of the training from other factors, such as the student’s aptitude, attitude, background characteristics and labour market experience as well as general community and economic effects, requires careful use of statistical techniques.

There are five outcomes of interest from this research. They have been chosen because they address the most pertinent areas of interest, and the required data for analysis appear to be already available. The outcomes of interest are:

• employment income
• employment status
• personal income tax payable
• social security payments received
• business income.

The NSC will develop a risk-adjusted methodology, based on stakeholder feedback, expert input, and the quality and usefulness of the data. It will be particularly important to ensure that the final assessment of qualification performance adequately focuses on the value add of the training. The methodology must also control for the range of student characteristics and local economic factors that have a large influence on individuals’ labour market outcomes. In all cases the research is testing whether training in a course is a turning point in the private and public circumstances of the cohort.