Leveraging the power of data to improve the lives of young Australians

The rising cost of living is exacerbating the challenges faced by disadvantaged children who are already confronted by complex barriers that hinder their access to quality education and their ability to thrive in society.

As we look to disrupt these cycles of disadvantage, Australian governments are recognising the value of data and collaboration with the not-for-profit sector , as shown thee recently published reports.

The government recently released Measuring What Matters – a framework considered the first step in monitoring and tracking Australia’s wellbeing via 50 key indicators, moving beyond the traditional metrics of gross domestic product (GDP), inflation and unemployment.

The report is considered a beginning, and agencies will require further guidance to inform policy development and evaluation.

Federal Education Minister Jason Clare also recently announced the release of the Australian Universities Accord Interim Report – which found that Australian universities will need to make more places available for students from disadvantaged backgrounds and lower socio-economic communities in order to meet future labour demands.

The report calls for greater collaboration to improve student wellbeing and for greater emphasis on student pathways to tackle national priorities including economic productivity, clean energy transition and other Australian future needs.

The South Australian Royal Commission into Early Childhood Education and Care recently released its final report which highlighted the importance of upping data capture to help improve development milestone’s for disadvantaged children.

These initiatives reflect the growing acknowledgement of the critical role that vocational and tertiary education play in ensuring that all young people are part of the solutions to Australia’s challenges.

It's important that these solutions come from young people from all backgrounds, not just a minority or a privileged few.

However, to truly break cycles of disadvantage and ensure all young people have an opportunity to contribute, we must better harness the power of data, enhance collaboration and focus on interventions that can truly make a difference to young people.

Collaboration is key to breaking cycles of disadvantage

Across the government, not-for-profit, academic and business sector, we have seen some strong collaboration, but in order to overcome disadvantage, we must combine our efforts and resources and drive solutions more effectively.

Often, many interventions and projects have attempted to find solutions to the same problems, working in siloes to obtain similar findings.

This year, with the support of the Paul Ramsay Foundation, the Data Catalyst Network launched a data-driven network bringing together people from across the sector to break cycles of disadvantage through the innovative use of data.

As a collective, the network works to harness, use and mange data and knowledge from across all sectors to improve the lives of young Australians.

Like the Measuring What Matters framework, this network is just the beginning, and we’ve been challenged to find new routes to using and sharing data to drive more innovative solutions.

One of the crucial challenges we face is the complexity of the problem where multiple issues affect vulnerable children simultaneously. We also need to better understand and measure the quality of the services they can access to help them stay on clear pathways towards a brighter future.

To address these challenges effectively, we must abandon siloed approaches and foster collaboration among organisations and research institutes.

We have an opportunity to collectively advance our data maturity, share insights and form unique partnerships across sectors to tackle complex challenges together.

Crucially, we need to better understand service systems’ critical points of support.

Studies led by Mission Australia and The Smith Family, among others, have shed light on this.

They show, for example that financial assistance is key to successful housing outcomes for those seeking housing assistance.

They show evidence of the strong link between school by disadvantaged students, and post-school engagement in work and study.

By sharing and analysing these data-driven insights, we can develop stronger strategies that target the most critical areas and provide smoother pathways for those at risk.

Shining a light on intervention points to drive better solutions

Through better use of data and understanding of key intervention points, we can narrow our focus to the most critical areas to disrupt disadvantage.

Recent research from The Smith Family for example found that young people experiencing disadvantage want more individualised support to help them complete Year 12 and more intentional career development learning to better prepare them for life after school.

By assigning a unique student identifier (USI) to students on its long-term educational scholarship program, Learning for Life, The Smith Family has longitudinally tracked the school attendance, achievement, school completion and post-school engagement in employment, education and training, of thousands of disadvantaged children and young people.

The USI – which stays with each student regardless of which school they attend or state they live in – enables impactful data analysis, generating unique insights while protecting sensitive information about disadvantaged Australians.

In contrast, our current data collection and analysis abilities across the sector do not provide adequate visibility of who is or isn’t participating and receiving support.

Mission Australia, too, used data analysis to identify critical service intervention points for people experiencing a housing crisis.

It identified various individual and community-level factors that predicted early disengagement of people experiencing homelessness or at risk of homelessness – an issue central to disengagement from education, employment and training for many young people.

This helped the organisation tailor service provision toward these individuals and give more nuanced attention to certain people to ensure they remained engaged.

Mission Australia spent more than two years building an organisational data framework and developing its data infrastructure and capability so it could bring more than 500 variables together and then merge, clean and transform data into useful datasets for complex analysis.

As a result of this foundational work, Mission Australia identified three strong service predictors of a positive housing outcome for those experiencing homelessness: how long a person stayed in services; how much brokerage they accessed; and the intensity of support they received.

We know that investment in strengthening data and collaborating on findings can result in more useful lessons for the wider not-for-profit sector and improve our ability to find solutions to similar problems.