Data Analytics
We define your organisation problem, then collate and analyse your data against a set of hypotheses. Our reports, predictive modelling, dashboards and datasets for machine learning, are designed to help you make informed decisions, with clear goals in mind.
  • Operational improvements  - use data to understand and address specific operational challenges (such as demand management, risk, performance, triage, and others).
  • Service optimisation - use insights from data to allocate resources and adjust service delivery in a more tailored way to meet individual client needs and maximise impact.
  • Efficient resource allocation - Look in more detail at client and cohort groups to allow staff to allocate their time and efforts where they are needed most, freeing up time.
  • Client-need insights - Understand - through quantitative as well as qualitative research - what drives risks and needs among client groups using that knowledge to adapt services and tailor solutions better to individuals.

Use cases for data analytics in social services

Social service use cases for data analytics
Social service use cases for data analytics

Case study: Using Clustering Analysis to improve services

We acknowledge all First Peoples of this land and celebrate their enduring connections to Country, knowledge and stories. We pay our respects to Elders and Ancestors who guide the Aboriginal and Torres Strait Islander community. We also  acknowledge the wisdom, dignity and lived experience of the people who benefit from social services.
Join the Data Impact Journey online community to learn , exchange ideas about using data for social impct