Stick to 'rubbish, roads, and rates' is a statement you might have heard bantered by disgruntled customers towards their local council. While these are critical services you might be surprised at the range of services that a local council provides. In the City of Casey in Melbourne’s south-east suburbs, over 60 services are provided to the local community. These include aged care, maternal child health, disease prevention, leisure facilities, libraries, aboriginal services, public art and, business regulation. With these broad services areas and over 300,000 residents located over 400 km2, the real challenge is how does the council provide relevant services to a diverse and fast-growing community? How do you create a service that isn’t just relevant but sophisticated, which has the ability to improve the customer experience while introducing efficiencies?
This can only be achieved by having a truly customer-centric approach. Our customers are not just data points or a list of transactions referred to as ‘big data’. We need to understand the person, who they are and why they do certain things. This is referred to as ‘thick data’. this is quite a challenge, however, as thick data is hard to obtain, especially a holistic view of all council residents. Residents can be surveyed, provided various feedback opportunities and have face-to-face community engagement events, but how can a government organization hope to gain data on all their residents?
The same way governments have always acquired information about its population through a census. An early example of a census is recorded in the Book of Numbers when Moses led the Israelites out of Egypt. More modern censuses are not just concerned with preparing for war and therefore contain a rich source of information. This is important for understanding who lives in a municipality and vital for the local government to provide effective services to enrich the lives of their residents.
Not only do we have a depth of data to investigate but the tools at our disposal to perform analytics have improved significantly. The City of Casey uses a business intelligence tool called Power BI and the following use cases are real examples of how the City has analyzed the recent Australian Bureau of Statistics Census to inform its services. Note this data is publicly available and anonymized and can be found at http://www.censusdata.abs.gov.au
Country flags for spatial analysis.
It is well known that Australia is one of the world’s most multicultural nations in the world and the City of Casey is no exception with 38.2% of its residents being born overseas. What would that look like spatially if world flags were used to represent areas with the highest representation of a birthplace in the City of Casey excluding Australia?
This map highlights the diversity of the City. We can see the high-density growth corridor dominated by Indian residents. The north and south of the city are low density older areas which are dominated by English residents. In Endeavour Hills there is a large concentration of Sri Lankan residents and a lot of Afghani residents coming from Greater Dandenong to the east. This is quite a unique way of understanding our municipality.
Understanding birthplace trends.
To gain insights into a data set, it is useful to look at the data from many different angles. Using the scatterplot below helps to understand the trend of Indian born residents.
The chart shows that the largest population of Indians are in the suburb Hampton Park as it has the highest dot. Although it has experienced minimum growth since 2011 (as it is just above the green area) compared to the Cranbourne suburbs which have seen the extraordinary growth of Indian customers. Understanding these cultural movements can really help shape our services, for example, where and what types of cultural festivals we host.
Use population pyramids to identify anomalies.
A population pyramid is a great way to understand the age and sex distribution of a population. This population pyramid is for the suburb of Doveton with females in purple and males in green.
Take note how it is skewed heavily towards males especially in the age range of 20 to 24. Identifying these types of anomalies helps inform where to target services delivered by the City or possibly just great information for single women to know!
How to effectively communicate to our community?
One question that was raised by our library staff was whether our highly valued Mandarin book collection was in the right facility?
Again the census provides an answer to such questions. Note the column chart shows that as a percentage the suburb on Endeavour Hills has the biggest proportion of Mandarin-speaking residents and this is exactly where the library books were held.
Understanding how we work.
The City of Casey is approximately 50km from Melbourne, the result is that 7 out of 10 working residents travel outside the municipality for work.
Due to a lack of public transport, 81.0% of people are forced to travel by their own car and 6.3% as seen on the treemap above. This has gone up since the last census and will continue to rise, really affecting the quality of life for residents. The City of Casey uses this type of analysis to advocate the state government to invest in infrastructure and an example can be seen here: https://www.caseyconversations.com.au/committocasey
What has changed over time
As the census was produced back in 1946, we can do longitudinal studies on arrival years from countries to highlight changes in trends.
This column chart not only highlights the growth of immigrants but also how the origin of the immigrants has changed. The 50’s to 80’s are dominated by United Kingdom immigrants with a change in the 90’s to Indian and Sri Lankan residents. This informs the type of facilities we provide. For example, we know Indians and Sri Lankans have a passion for cricket, do we have enough cricket facilities to cater to this kind of demand?
In summary, there are many ways we can use census data to gain a better view of our customers. Looking to the future, the value will be when we combine the census data with our own internal data sets. Perhaps we could identify correlations between dumped rubbish and languages spoken to identify what languages we should publish pamphlets for dumped rubbish education. Or use the data to encourage certain businesses to an area due to identifying a certain type of skilled migrant. There is no limit to the insights well sourced, thick data can provide.