Harnessing data to provide better outcomes for communities
Learn how different government agencies in Australia and internationally use predictive analytics to improve service delivery to their clients.
Predictive Analytics in the Public Sector
And its key benefits
With a massive volume of data at their disposal, many government agencies today leverage predictive analytics to be more efficient and responsive to the needs of their communities.
Governments are now operating in a more complex and interconnected world. More data is coming in from a variety of sources while citizens are expecting higher quality and faster service delivery at both state and local levels. By using predictive analytics, data-driven agencies can:
- Better understand their community’s needs;
- Improve the allocation of their resources;
- Improve the decision-making process of public employees;
- Enhance their risk-management; and
- Ultimately deliver better programs to the communities they serve.
Let’s look at some of the success stories of different government agencies in using predictive analytics to transform their operations.
Sustainability Victoria (SV) supports Victorians in transitioning to a circular, climate-resilient economy. Part of this mission is to lead state-wide waste and resource recovery planning. Through predictive analytics, SV’s analysts are able to understand the current and future waste amounts arising within the state’s hazardous waste system.
They also developed a projection model to take advantage of the huge volume of data coming from the Environmental Protection Authority Victoria. Allowing them to effectively map out waste generation, forecast industry trends and investigate opportunities to improve the management of hazardous waste in Victoria.
Australian Institute of Health and Welfare
The Australian Institute of Health and Welfare (AIHW) is known for providing authoritative information and statistics to support better policies on the health and welfare of all Australians.
AIHW uses predictive analytics to leverage their access to large data sets (e.g. national hospitals databases), and search for new insights and answer key policy questions including likely future scenarios.
For instance, AIHW used a projection model to forecast Australian health care expenditure. Combining various factors like population growth, the volume of services per treated case and excess health price inflation, AIHW’s model was able to provide projections for 20 disease groups. It also provided estimates of change in funding by the national and state governments as well as the private sector.
Department of Health and Human Services
The Department of Health and Human Services (DHHS) delivers policies and services to help improve the health and wellbeing of the Victorian community. They assist health services and researchers by applying their data and creating projection models, including:
- Supply and demand modelling of the health workforce;
- Hospital inpatient projection model; and
- Emergency department projection model.
These projection models allow DHHS to provide analytical insights to support service development, capital planning, and overall strategy development in the health sector.
Click here to learn how we helped DHHS become more client-centric and improve their service delivery to their clients.
Early Intervention for Youth Offenders
Hillingdon London Borough Council
Hillingdon Council’s AXIS Project is an award-winning initiative that supports the early identification of children at risk of criminal exploitation.
By collating and analysing data across different organisations such as the police and youth services, the AXIS project allows early intervention teams to identify at-risk youths more effectively. It enables them to flag high priority cases and to inform relevant agencies who can provide targeted support and keep more children safe.
Flood Emergency Planning
City of Ottawa
During the 2019 floods, Canada’s capital Ottawa used predictive analytics to optimise their emergency response. Using a mapping program, city officials were able to see the potential damage each additional centimetre of water could bring to their community.
Instead of relying on assumptions about where water was accessing properties, the city’s emergency planning team used the mapping tool to input different water levels and predict which areas would be affected.
Apply Your Data
And improve your agency’s operation
Want to learn more about how you can maximise the power of predictive analytics in your government agencies and departments? Talk to our data experts today.