Enhancing Human Flourishing: The Synergy between Data and a Systems Approach
In this contributor piece, Chris Mesiku, Research Fellow at The Australian National University’s School of Cybernetics, discusses the intersection of data and the for-purpose sector
There has been an increased call on the for-purpose sector to be data-driven.
In a recent opinion piece, Centre for Social Impact Research Fellow Dr Rhiannon Parker argued a measurement culture was necessary for the sector to maximise its impact by contributing to social policies through data-driven decision-making, prioritising evaluation, and fostering a learning mindset.
Services in the for-purpose sector – such as charities, social enterprises, community groups and not-for-profits – help society’s vulnerable in a multitude of ways, from identifying and supporting the homeless to providing financial assistance, counselling and accommodation for family members fleeing domestic violence.
Traditionally the for-purpose sector has been slow in adopting data intensive digital tools, due to cost as well as legal, policy and security compliance challenges. And the prospect of collecting, storing and managing large amounts of personal data sets from clients, donors and volunteers – to effectively feed these platforms – is understandably daunting.
Yet there are some who are increasingly relying on digital tools to collect personal and public data of those needing support. Low-code platforms, requiring little to no coding skills, and AI-enabled recommendation engines, where data analysis and machine learning algorithms help provide suggestions on how to support clients, are examples of tools being readily adopted.
But amassing more data is not enough. We need to supplement insights gained from datasets with insights from a systems approach. When the system is the unit of analysis, data-driven insights are one part of a holistic intervention. By thinking in systems, we’re ensuring that humans, technology and the physical environment are all taken into account. Context is crucial when developing support programs for the vulnerable.
An example of this would be service providers observing and assessing homelessness as resulting from, and impacting on, multiple interconnected and interacting elements of a person’s life such as the quality of social connections, mental health, financial stress, risk of exposure to violence and social isolation.
These factors are dynamic, requiring ongoing intervention and monitoring. Service providers who embrace an increasingly data-driven mindset may be at greater risk of devaluing the influence of multiple, shifting factors at play.
A systems approach could include consulting with several family members of an individual to ensure optimal service delivery, something many in the for-purpose sector already do. Data is inarguably critical in driving social change, but the approach must be one that supplements data collected with a whole-picture view.
Recent complex data projects and longitudinal studies have embraced this systems approach. One commendable example is 100 Families WA, a three-year research program designed to help understand the experiences of families living with high levels of long-term poverty, social exclusion and deprivation. Regular fortnightly interviews were held with 100 of the 400 families and comprehensive quantitative and qualitative data collection methods were deployed via surveys, interviews and focus groups. The lived experiences of participants and their family members were key; exploring what support they had received, what worked, what didn’t work, and suggestions for how their situation could be helped.
Relying on a version of the Ecological Systems Theory – a framework focusing on the impact of the surrounding environment and social interaction on human development – the project recognised a systems approach was necessary to try and understand the complexities around why exiting cycles of entrenched disadvantage is so difficult.
Quantitative data was pivotal, but researchers acknowledged no single data result or dataset could adequately represent each family member or family unit and their lived experiences.
The findings highlighted formal services helped some individuals and their families, yet others experienced barriers to entry being told they: ‘don’t fit the criteria’. Transport costs to access support with no guarantee of qualifying, was another real concern expressed by participants. Without a systems approach, it would have been difficult to reveal the depth of financial and emotional burden associated with trying to navigate a complex web of services.
Similarly, our data research at The Australian National University’s School of Cybernetics prioritises the system as the unit of analysis because history has shown when attempts to create change – whether it be the development of the steam engine, electricity or the internet – are enacted without considering the unintended consequences, the results may cause harm. The steam engine helped drive the Industrial Revolution, creating jobs and inspiring further innovations, but it also led to major pollution that has contributed to today’s climate crisis.
As the race to collect fine-grained data about individuals gathers momentum and a measurement culture begins to proliferate within for-purpose organisations, there might be a tendency to design, search for and privilege data while devaluing a systems approach. By having greater visibility of the dynamic influences on a person’s life, in addition to the data captured, we might stand a better chance of focusing on initiatives that will have the best possible impact, benefiting the people who need it the most.
Chris Mesiku is a Research Fellow at The Australian National University’s School of Cybernetics
