At our first meeting, we instantly went into full case comp mode: here is the problem – people are not satisfied with waiting, they do not want to go see the doctor, and they speak different languages. Here was our solution – an AI chatbot that users can interact with; it would diagnose, triage, and send them to the right specialist. Seems pretty easy right? There was already a company doing this in the states and we could just recommend that the MICC contract them.
But we needed a little faith in the system. So we started gathering data:
I began taking photos of everything I could find – stores, hotels, clinics – not knowing what we would discover. After a while, I focused in on entrances. At first, I wasn’t paying attention to the characteristics of entrances, but after so many, you begin to see patterns. What kind of signage and how much of it, what style of lighting, employee visibility, etc. These things started to present themselves as potential variables for consideration.
At the same time, I started interviewing users. We tried to find recent immigrants because that matched with Southern Mississauga region’s demographics.
We ended up with more data then we had expected. And had no idea of how to deal with it all.
