Team Name:
Millennial Snowflakes
Team Members:
Millennial Snowflakes
People and businesses are struggling with the cost-of-living crisis – but how can we find them and support those in need?
Community Needs Navigator (CNN) is a tool to assist governments and charities allocate resources to the areas that need it the most.
CNN leverages ABS and Regional Data Hub data to segment the Australian population into 9 distinct groups which differ in terms of age, household income, socio-economic status, cultural background and more. These groups can be used to identify areas in need quickly and efficiently. In addition, the segments are combined with unemployment rate data and industry employment information for a comprehensive view of each area.
The tool includes tables and charts highlighting the differences between segments so that individuals can gain a detailed understanding of the characteristics of each group, and which segments are ones to focus attention on.
Once segments of interest are identified, the Suburb Identifier section can be used to find all relevant postcodes so that action can be taken. For example, if you are a charity operating in Victoria and Tasmania, you can select VIC and TAS from the state dropdown menu, and the population segments of interest in the segment dropdown menu. The table will then display all relevant postcodes and associated information so that action can be taken.
The CNN tool includes three components:
Geographies: This section shows a colour-coded map of Australian postcodes, where each colour represents a different segment of society. By clicking on a particular area, you can drill down and retrieve location-specific information such as average rent payments, household income and most common industry of employment, as well as the area’s unemployment rate and number of businesses employing staff in each industry.
Segment Analysis: Here you can build a more detailed understanding of each segment by exploring how they vary by variable and comparing them. For example, if you select segments 4 and 9 and view the Household Income tab, you can see that these segments are almost completely opposite in income – segment 4 primarily high incomes, and segment 9 generally has lower incomes.
Suburb Identifier: Use this section to search for states and segments of interest to find all the relevant postcodes, and view information about those areas.
We join location, demographic and industry information from the ABS and Regional Data Hub to create nine distinct segments using k-means clustering. Some data is only available at the Statistical Area Level 2 level, so data is joined to postcodes to provide information at the suburb level. ABS postal area shapefiles are used to show locations on a map, and data is joined to the shapefiles to display additional information interactively.
Description of Use Matched to postcodes and used to plot the number of businesses employing staff in each industry when a specific suburb is clicked on the map
Description of Use Used to plot unemployment rate by suburb, and unemployment changes over time are input into a machine learning model
Description of Use Used in a machine learning model to segment the Australian population and display relative socio-economic scores to help allocation of government spending and charity activities.
Description of Use Used in a machine learning model to segment the Australian population. Also used to link Statistical Area Level 2 codes to Postcodes.
Description of Use Used to extract the suburb name(s) of each postcode for display, as well as identify the postcode centroids in latitude and longitude for the "search postcode" feature
Description of Use Used to plot the boundaries of each area on a map
Go to Challenge | 33 teams have entered this challenge.
Go to Challenge | 10 teams have entered this challenge.
Go to Challenge | 4 teams have entered this challenge.
Go to Challenge | 7 teams have entered this challenge.
