I thought my draft proposal was a great idea until my peer knocked it straight down to the ground- and for good reason. Coming from a different issue group, they were fresh eyes and provided interesting feedback. Their knowledge of housing affordability was similar to mine before the start of my research journey which was definitely full of assumptions, blame and the thought of hopelessness. However, that view was needed as my own views became more unrealistic.
What I thought was particularly useful was the chance to pitch the idea to my peers which made me realise how many problems it had. It was full of holes and every question asked about it left me agape for words. What my peer addressed was that I did not have a solid issue. What was the problem exactly? How was I going to design something for someone if I didn’t know what it was supposed to do or fix/help in the end? After identifying multiple pathways with my peer that I could take with the issue, the next hardest part solidifying my idea, which was by no means coherent or useful.
On the flip side, I listened to how my peer pitched their idea on an issue that I didn’t know about. It was interesting to hear how people interpreted their issue and the sub issue they identified within it.
Title: Is that Suburb Real?
Practice Type: Data Visualisation, Service Design
There is a lack of awareness of more affordable suburbs near high activity areas which contributes to young Australians putting off the search because they feel it’s futile to even look.
The Possible Change:
From my interviews and probes, I found that Young Australians are discouraged from searching for homes because all the ideal ‘cliche’ locations are too expensive and unaffordable. After I asked peers about their needs and preferences, I presented to them a suitable, cheaper alternative to which some responded “I didn’t even know that suburb existed!” What was also interesting was their facial expressions when they found out there was actually hope.
What I linked to this issue was the lack of awareness and information other than in media which can be quite skewed. We often hear about the ‘top 10 suburbs to live in’ or the ‘top 10 affordable suburbs’ but no information other than that.
The Design Action:
An interviewee stated that “Right now, the only way I’m looking for homes is along the train line. I don’t have time to do further research”. I want to tackle this issue using service design and data visualisation in the form of a website. The website will show a colour coded map that shows the activity levels of suburbs. For example, a high activity area like Sydney CBD or Macquarie Centre will be coloured red whilst surround areas will be coloured green. This will visually indicate to the user how far the suburb is from the activity hotspot whilst also being in a reasonable house price range just because it isn’t a hotspot. This is particularly useful for identifying unknown suburbs near places of high activity which are also generally transportation hubs to get where you want to go.
What will be innovative is how ‘activity’ is measured. There would be checkboxes and a very advanced search function for users to identify what contributes to the activity heat map. The activity from multiple criteria will be added up and displayed on a map. For example, couples who don’t want children or people living alone can uncheck the schools box so that school activity does not contribute to the map. There will be general selections like population or median house income but also more niche selections like crime rate or median age.
Once users have found a suburb that fits their needs and wants, they are able to click into it to find out more information. The website provides otherwise months of research in a visually interesting way for hopeful future homeowners to find those unknown unaffordable locations. It is designed as an assisting tool for users to work with on their search. As the activity levels change in real, it also affects the hotspots on the website, thus being an up to date, adaptable and self updating digital database.