In our latest AURIN Nimble Chat, we catch up with Michele Adair, Managing Director of the Housing Trust, Chair of Homes Tasmania and a member of AURIN’s Industry Advisory Committee.
In this chat, Michele discusses housing affordability in Australia, the importance of national standards for data related to this issue, how we can make effective planning decisions, and more.
Transcript
AURIN Nimble Chats: Michele Adair
My name is Michele Adair and I have two roles. I still have an executive role as the Managing Director of the Housing Trust. We’re a large community housing provider, building and acquiring and then managing social and affordable rental homes for people on low to moderate incomes, and our footprint is across the Illawarra and the Shoulhaven in New South Wales.
And I’m also the inaugural Chair of Homes Tasmania, and we’re relatively new. About two years ago established as a statutory authority responsible for supporting the government’s vision and delivery of a very ambitious housing strategy, which in addition to aiming to end homelessness within the next few years, to 2032, is also responsible for delivering an additional 10,000 social and affordable homes. Which is an enormous target for Tasmania.
What do you see as the biggest challenge Australia faces in managing its demographic transformation?
Look, without question the biggest social, and I would argue strongly economic, issue facing Australia today is what we are generally calling the housing crisis. So that is both a material shortfall in the number of homes that we need, as well as existing housing, and I’m afraid the likelihood of much of our future supply remaining unaffordable to people – even who are, you know, in households with full-time, double income working wages. That impacts, of course, all of the social determinants of health and community engagement and participation, educational completion, participation in the workforce, but it also has a very direct impact actually on productivity. And an increasing number of organisations, indeed like the Business Council of Australia, are backing in behind policy and investment initiatives to increase both the supply of affordable housing as well as the total supply.
So in my view the role that AURIN plays is being able to support a very wide range of actors across that housing system – to understand and to be able to model and forecast demographic changes. Clearly the one that we talk about most is probably the ageing population and the implications for redesigning homes that are not only safe, secure, affordable, but that are also fit for purpose in terms of people being able to afford to heat or cool them, people as they age in place being able to have safe mobility, access, entry points within their bathrooms and the like, and to be able to adapt the design and the architectural features of our homes to perhaps respond in real time to changes in household composition without necessarily requiring a person to move or result in either significant overcrowding or significant underutilisation, which is is a problem in in a lot of our our housing stock at the moment.
So on all of those things, AURIN has a a really wonderful contribution to make – where do we need homes, how quickly can we get them there, how do we track them and what are the implications. It’s a wonderful opportunity.
What role would you like to see AURIN play?
I still think that one of Australia’s greatest strengths, but also a consistent sticking point for us as a nation, frankly, is federation. And so AURIN’s ability to be able to establish and get buy-in and utilisation of national data sets and national standards around, simplistically: what is the definition of an affordable home? Now, we have talked about that in parts of the housing sector where I work for decades, and yet still, different jurisdictions have different understandings and we see new actors apply different language and different context as if the past hasn’t happened and as if we don’t know.
So I think things like national consistency around some of those things are vitally important. How do we nuance the detail of what is liveability? Does does that mean that homes are of a particular size or style, or what does it mean to be well located? All of these things are informed by spatial data, by the application of digital twin modelling, and the benefit’s there. So being able to understand what information might be helpful to be able to standardise the collection and the presentation of that, and then to be able to share it in a way that helps inform decisions, be that at board level, at policy level, is really exciting.
What possibility in the geospatial sector most excites you?
Probably the most exciting opportunities for me at an organisational level are around being able to understand both the drivers and the barriers to increasing affordable housing supply, and in particular to increasing the supply of affordable rental housing. Now, when I talk about affordable rental housing in this context, I mean both social or public housing for people on very low incomes, as well as affordable rental housing that is capped at 30% of household income.
So for me, it’s those things around understanding future transport corridors and links, what are the projections around availability and cost of capital, workforce, skill sets? So being able to bring together all of those dynamics and variables that would say, if I’m going to build 50 homes, if I’m going to build 500 homes, who is going to live in those – not just for the next 5 to 10 or 30 years, but intergenerationally? What does the composition look like, what are we going to do in relation to parking requirements? We still have local council regulations that mean, mostly, when you build an apartment building or a house you’ve got to have at least one motor vehicle per dwelling. How do we understand the future prospects of motor vehicles and public transport use and do away proactively with some of those barriers? It seems absurd, but actually building a parking space is just about the most expensive construction that you can undertake in Australia, usually because you have to build a basement and all sorts of other problems with it.
So, how do we use data to help us solve some of those problems reliably, in a way that is robustly evidence-based, that makes it, you know, much more reliable and much more difficult for people to dismiss.
END.

