In a past life, I worked on projects that explored how people interact with and experience hospitals. Traditionally, when hospitals were built, senior doctors collaborated with architects to design the space. The result? Hospitals optimised for doctors, not patients - centralised workspaces for medical staff, but confusing layouts, long corridors and frustrating experiences for patients and families.
Modern hospital design flipped this approach. Instead of prioritising doctor convenience, architects started designing for patient experience. A great example is the Royal Children’s Hospital in Melbourne, which features family-friendly overnight accommodations and even a mini zoo in the atrium with meerkats to engage young patients.
Data systems in social services - stuck in the old paradigm
Data in the social sector is much like the old hospital model - designed around the needs of funders and commissioners, rather than the organisations delivering services or the clients receiving them. Reporting requirements dictate what’s collected, often leaving frontline teams stuck gathering data they don’t use, while the insights they do need are missing.
It’s time to flip the script. Data systems should be designed to improve service delivery, support staff and drive better outcomes. Reporting to funders should be a byproduct, not the primary goal.
At Latitude Network, we often workshop a 'data vision' with our clients, helping them reimagine how data could work for them.
Here are some key elements to consider:
A future-focused data vision
Imagine a world where -
1. Dynamic service models drive best practice
Every program has clear, structured documentation - service models, decision criteria, checklists and training resources - all stored in a version-controlled space that staff can access in real time. This "single source of truth" aligns frontline practice with the latest evidence, ensuring consistency and continuous improvement. It is based on:
✔ External research and best practices
✔ Internal service data and outcomes evidence
✔ Practitioner wisdom and real-world experience
2. Metrics matter and are aligned with service models
Data collection should work for frontline teams, not just funders. A well structured Monitoring, Evaluation & Learning (MEL) framework ensures:
✔ Staff collect only data that is useful and practical
✔ Metrics align with service models and track progressive success
✔ Data feeds directly into dashboards that help decision making at all levels
3. Data tools support day-to-day decisions
Dashboards should be built for action. When designed well, data tools become an essential part of daily operations:
✔ Frontline teams use data for client triage and service planning
✔ Managers track staff capacity and caseloads, matching resources to demand
✔ Executives use outcomes data to guide strategy and investment
4. There is a culture of learning & continuous improvement
Data isn’t just for reporting - it should drive real change. Social services can apply evidence-based learning to refine service models and test new ideas. They allow teams to:
✔ Identify what’s working (and what’s not)
✔ Run A/B tests to compare new interventions against the status quo
✔ Use data to enhance staff training and professional development
What happens when data works?
When teams have clear, actionable data, it drives motivation and improves performance. One organisation in a Latitude Network data collaboration project increased team performance by 50%, without increasing staff hours - simply by using better data to track outcomes and focus efforts where they mattered most.
The social sector has an opportunity to move away from compliance driven data and embrace systems that empower teams and improve services.
What is your organisation’s data vision?
Comments