The Integrated Data Infrastructure (IDI) is starting to give us deeper insights into the supply of skills in the New Zealand labour market. Here we look at the origin of new entrants into industry workforces.

By tracking the labour market status of individuals over time we can look at new entrants to an industry workforce in any given year and identify their status in the previous year. This tells us whether a new entrant was a school leaver, a tertiary education graduate, a migrant from overseas, someone who was already in work but in a different industry (we call these career changers), or a beneficiary.

This new entrant data is a game changer. When an industry is expanding its workforce, we can now identify the skills supply sources that this industry will most likely draw workers from. We can look at whether these pipelines are sustainable and think about how we might want to change them – for example if we wanted to reduce an industry’s reliance on overseas workers and increase its intake of tertiary education graduates.

First a note of caution. These data should be interpreted broadly. Don’t get bogged down in the details. A lot of thought has gone in to how a new entrant to an industry workforce should be defined, and how their status in the previous year should be determined. There’s a fair degree of noise in the data and small changes to definitions change the results.

Crucially, we created a hierarchy of sources for people who fall into multiple categories. The hierarchy from top to bottom is as follows: secondary school leavers, tertiary education graduates, migrants from overseas, career changers and beneficiaries. We also have data that does not apply a hierarchy so new entrants can come from multiple sources. Comparing the two datasets, unsurprisingly we find that the hierarchy weights the results towards sources at the top, so more school leavers and tertiary education graduates and fewer career changers. But relativities across industries remain more or less the same. So, the industries that rely more on school leavers for example, do so regardless of whether the hierarchy is imposed or not.

So, what does the data tell us? Reassuringly, it tells us a few things we expected.

• School leavers make up a relatively large proportion of new entrants in retail and hospitality. These sectors tend to offer stepping-stone jobs for young people before they embark on their careers.
• Tertiary education graduates make up a relatively large proportion of new entrants in education, professional services, healthcare, the arts and recreation, IT, and public administration (central government). Employers in these sectors tend to require new entrants to have post-school qualifications.
• Migrants from overseas make up a relatively large proportion of new entrants in agriculture, hospitality, and administrative services (food packaging, labour hire services, travel agents, cleaners and call centre staff).
• Beneficiaries make up a relatively large proportion of new entrants in administrative services (cleaners, call centre operators) and healthcare (allied health, social assistance and aged care).

We were a little surprised to see how much all industries rely on career changers – albeit to differing degrees.

• Most industries source at least 40% of new entrants from other industries. For sectors such as mining and utilities, it is over 70%.

Part of why this is surprising is that we simply haven’t seen this kind of data before. When sector bodies develop skills strategies, they often focus on attracting tertiary education graduates, migrants and maybe school leavers. There’s nothing wrong with this, but it arguably inflates the importance of these sources of new skills when industries are growing and/or facing labour shortages. Understanding that the majority of your new workers are already in the workforce and are working in other industries really changes how you view attraction and retention.

We will investigate career changers in more detail. If most industries draw the majority of their new entrants from other industries, we want to know what the industries are. With this information we can start to understand how growth in one industry can cause labour shortages in other industries as workers transition to jobs in the growth industry. We can look at workers transitioning between similar industries within the same broad sector and workers who transition between broad sectors.

The data on migrants is only for migrants who have arrived in New Zealand 12 months prior. We want to look at the industries migrants transition between in the years after their arrival.

We want to look at qualification pathways to better understand which qualifications people achieve prior to entering work and after they have entered the workforce.

We want to focus in on school leavers and what they do in the years after leaving school: what education or training they get involved in, what jobs they do, and whether they move between regions.

We will also look at people exiting from sector workforces to see where they go to.

We also want to enable our clients to analyse this skills supply data alongside our employment forecasts in an online interactive dashboard. Currently our Regional Skills Outlook online, interactive dashboard includes our employment forecasts alongside data about school leavers, tertiary education graduates and migrants. But the latter are all separate datasets from different sources. What’s exciting about the IDI data is that it enables us to see all the skills supply sources together, and understand which sources are more or less important to different industries.

If you have any questions about the labour market that you think can be answered using IDI data, please get in touch.