Electorate analysis
Seats as data. Federal and state results down to the booth, joined to census demographics on the ABS spine, across boundary sets that keep changing.
Industries
Government and public affairs
Cut any program, grant or exposure by electorate or local government area, briefing-ready — for departmental analysts, ministerial offices, government relations firms and peak bodies.
Departments have the mandate for location-based analysis and rarely the capacity. The request that arrives on a policy analyst's desk is almost always the same shape — take this program, this grant round, this exposure, and show it by electorate or by council area, by Thursday — and the answer takes three days of manual geocoding and joining that nobody has budgeted.
The same request arrives at government relations firms, peak bodies and think tanks, usually pointed at somebody else's program.
The join is the product
Commonwealth grant awards and contracts are published, and they are published with recipient names and address strings rather than geography. Regional statistics are published by statistical area and local government area. Electoral boundaries are published separately again and move on their own cycle.
Resolving award addresses against the national address file, then to a parcel, a council area and a division, is the unglamorous step that makes everything downstream possible. It is also where hand-built analyses fail — a match rate nobody measured, records silently dropped, and a distribution map that is confidently wrong about the seats with the messiest address strings. Here the unmatched records come back as a list with a count, and the match rate is stated in the output.
Take this grants program's awards, geocode the recipients, and show total value and recipient count by federal division with population and socioeconomic index alongside.
What comes back is a table by division with award value, recipient count, value per capita, and the demographic and socioeconomic context that makes it interpretable — plus the count of records that could not be resolved and why, which is the first question any competent reviewer asks.
Regional briefs
The other standing request is the electorate or council profile: population and its trend, age structure, income, industry of employment, socioeconomic index, housing, and increasingly hazard and climate exposure. Dwellings inside a flood planning area, bushfire prone land share, canopy cover and heat, projected hot days. Those layers are live now and can be cut by council area today, which covers a large share of what a regional brief actually needs.
Give me a ten-chart profile of this local government area: population change, age structure, income distribution, industry mix, housing tenure, and flood and bushfire exposure.
What this is not
It does not have an opinion. It produces the numbers, the map and the source list; the framing, the recommendation and the political judgement stay with whoever signs the brief. Every figure names its dataset, vintage and custodian, which matters more here than almost anywhere else — a number in a ministerial brief will eventually be asked about in an estimates hearing, and the answer needs to be a citation rather than a recollection.
Sequencing
Local government area analysis over census, socioeconomic, population, land, infrastructure and hazard data works today. Grant and contract data with the address geocoding, and the electorate join that lets everything be cut by division, are being built now alongside the electoral results work. If you have a specific program or portfolio in mind, that is useful input into the order it gets built in.
Frequently asked
What does a request typically look like?
Some version of "cut this by electorate". A program's recipients, a grant round's distribution, an infrastructure pipeline, an exposure or a service gap, mapped against divisions or council areas with the demographic context that makes it briefable. The mechanical part is the geocoding and the join; the analysis is yours.
Why is geocoding grant recipients hard?
Awards are published with a recipient name and often an address string, not a coordinate or an electorate. Resolving those strings against the national address file, then to a division and a council area, is the step that turns a spreadsheet of awards into a distribution you can map. It is also where hand-built attempts quietly lose records — unmatched rows dropped without anyone counting them.
Is this available now?
The ABS spine, census, socioeconomic indices, population series, and the hazard, land and infrastructure layers are live today, so anything cut by local government area works now. Grants, contracts and the electorate join are being built, sharing the electoral data work described on the electorate analysis page.
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