A data analytics tool developed by PwC has revealed Sydney’s most active economic hotspots and shows that business is shifting away from the CBD.

The findings, powered by the Geospatial Economic Model (GEM), are a step change in how we understand the evolution of cities and plan to ensure they continue to thrive.

What makes the GEM analysis significant is that it looks at location-specific economic data for Australia’s global city.

Big City Analytics, a report produced in conjunction with the Committee for Sydney, shows that Sydney’s economic centre of gravity is not located in the CBD but in Concord, nine kilometres west of the CBD.

Furthermore, activity has been moving away from the CBD for the past 13 years, drifting to the North West, pulled by the growth of Western Sydney and locations to the north like Macquarie Park.

GEM’s findings have led to a call by Dr Tim Williams, the chief executive for the Committee for Sydney, for the city to improve public transport links connecting these emerging centres of economic value.

Why produce a new method for city data analysis?

Measuring the general performance of a city’s various functions by analysing data is nothing new.

The information is used to influence the planning of housing densities, public services and transport systems as well as identify the key skills and governance needed to manage and leverage growth.

However, until now there has been a lack of granular economic data to show how the wider economic trends that shape our country actually play out on the ground – where business and government operate.

The economy has, in the past, generally been analysed through the lens of industry or state, providing only high level perspectives. Yet there is a startling difference in the performance of industries depending on where they are situated.

Not all locations within CBDs, cities and regions perform the same, so they aren’t of equal economic importance. Each location has unique constraints and growth opportunities which need to flow into forecasts, targeted policies and evidence-based strategic plans.

This is the space in which GEM was developed.

What is the Geospatial Economic Model (GEM)?

PwC’s economics and analytics teams adopted the traditional method for calculating economic output (known as GDP: Income Method) but then applied this at a level of detail not previously achieved.

Economic output can now be calculated for 2,214 ‘locations’ that make up Australia – socially and economically distinct areas that have, on average, a population of 10,000 people.

Economic output can be separated further by 19 core industries including, for example mining, manufacturing, utilities, transport services, retail, financial services and health services.

To put the results of GEM into context, prior to its development it was only possible to understand the performance of the retail industry in Victoria by using Australian Bureau of Statistics publications, which offer analysis by state or industry.

GEM-Geospatial-Economic-ModelUsing GEM, it is now possible to zoom in and see how retail activity has shifted around the CBD of Melbourne, from the traditional city centre towards Southbank and Docklands, as these locations have developed.

This level of detail now exists across all locations in Australia, for all industries, across a time period reaching back to 2001 and forecasting up to 2030.

Putting economic activity into context

Economic data is just one of the dimensions of analysis that GEM provides. It can overlay information relating to social and demographic factors, customer preference, infrastructure access, crime, climate data and more, providing a holistic picture of a specific location.

For example, we can now see the impact that past manufacturing plant closures have had not only on the local economy, but social factors such as welfare payments, crime rates, demographic changes and education levels.

This holistic view provides the critical context required to understand the forces both shaping our economy and the impact that changes in the economy have on the business and social landscape. Policies and interventions can then be shaped accordingly.

Advances in data processing techniques, technology platforms and spatial visualisation made this mammoth task possible.

Why is this data significant?

As Australia looks beyond the resource investment boom it must plan for a future of sustainable growth in other industries.

The type of granular city analytics driven by the Geospatial Economic Model can identify new pockets of economic activity and those in need of stimulation. In turn, with the right planning, these can be supported by the right investment and policy environment.

Back in Sydney, this could mean that places like Macquarie Park – which the report shows has doubled its economic output in just over a decade – could soon become more of an economic powerhouse than the CBDs of Australia’s other capital cities.

Big city analytics supports big city thinking, which is essential to supporting the rising stars of Australia’s new business landscape.

 

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Contributor

Rob Tyson

Rob Tyson is a Director in PwC Australia’s Economics & Policy team.

Rob is an experienced economist, combining the practical experience gained from undertaking and managing a number of high studies with a strong theoretical background.

Rob leads the economic component of PwC’s Geospatial Economic Model (GEM) capabilities. This rich data platform provides clients with the opportunity to access unique insights about the local context of their business operations and customers. The platform is designed to integrate with our clients’ data, providing the opportunity for unparalleled clarity.

Since 2013, Rob has led a team that uses the GEM platform with government to better understand the growth of Australian cities, plan infrastructure to meet this growth and estimate the return and value capture potential from infrastructure.

He has also used GEM with a number of businesses looking to improve utility, retail and banking network investment decisions within cities to ensure they best capture potential growth.

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