Data Visualization for Humans: Visualizing Permanent Small Business Closures in Toronto from March — May
This visualization was difficult in both execution and subject matter. It was partially inspired by a conversation I had with my friend who is an ex-baker. We were were discussing the impact of COVID-19 on the Toronto job market and how hard it had become to find relevant roles.
“…and now the one thing I loved doing, the roles have been wiped down” she remarked sadly, in reference to the restaurant industry.
And she’s right. It’s hard to go on social media these days without a BlogTO or Narcity article proclaiming: “this is your last chance to try the iconic _______ at _______! Closing after ____ successful years in Toronto!” It seems like every week, I read new closure announcements and goodbye letters from institutions that had previously seemed untouchable (looking at you, Croc Rock).
I decided to create a data art piece dedicated to all of the incredible food & entertainment businesses that have permanently closed since March. One of the reasons I decided to do this is because I realized I actually had no idea what the total impact of COVID related closures was. I saw piecemeal headlines, but didn’t know the scale of the problem. Was the count of impacted businesses in the 10s? 20s? 100s?
Another reason I wanted to undertake this task was to see if there was any sort of relationship or trend in the type of business that is most likely to fold. Are trendy cafes that opened recently more likely to call it quits during these times? Or are large family legacies struggling due to higher rent and overhead?
One of the first trends you can see is that more businesses are closing with every month that passes. Only 2 businesses publicly announced they were closing due to impacts of COVID-19 in March, and this number grew over 6X to 13 by May (not including businesses that closed quietly with no announcement).
Another trend is that closures mostly impact sit-down restaurants, with 54%(12/22) of all public closures in this category. However, this overrepresentation may be due to the fact that there are more restaurants in general, compared to clubs or bakeries.
Additionally, it would appear that closures are as common across new venues as they are across long-established businesses. The average years of service across all impacted businesses is 18 years, with 54% (12/22) of the businesses previously thriving in Toronto for 10 or more years.
Perhaps most heartbreaking of all is the fact that almost every single one of these businesses was positively reviewed on Google Reviews, and loved by members of the community. The average rating for all 22 businesses is 4.3/5 stars on Google Reviews, with 3 businesses (Nishdish, Club 120, Plentea) having 5 stars at time of closure (or a rating that rounds up to 5 from the nearest .5).
I can personally speak to how saddened I was to see Plentea and Butter Avenue on the list of closed businesses. Plentea was just around the corner from my old office, and I would stop by at least 3 times a week to try a new delicious flavour of tea (okay let’s be real — I got Peach Breeze every time) or grab a warm pastry. Butter Avenue was where my friends bought a s’mores cake to surprise me for my 22nd birthday, and every meal for a week after November 23, I had cake for dessert.
There is no doubt in my mind that this visualization is an underrepresentation of the closures Toronto has suffered in the last 3 months. This is because a number of businesses may prefer to close in private, instead of publicly announcing and sharing with a publication (I used Daily Hive and Now Toronto as my key sources).
I’m not sure what the next step from here is. I am neither a public health specialist nor an expert on economics, so I feel unqualified to propose “next steps to solve the issue.” The only thing I can say is, this visualization has caused me to reflect on my favourite remaining businesses in Toronto, and wonder how long each of them have left. Maybe it wouldn’t be the worst thing in the world if I ordered Korean Fried Chicken from Burning Fridays twice this week.
If you would like to take a look at the data behind this visualization or even download it for your own analysis, please feel free to! Source here. If you end up doing your own analysis and want to share, tag me because I’d love to see it.
Bonus content: at the beginning of this article, I mentioned this was a tough visualization in execution and subject matter, but didn’t really touch on execution. Please enjoy my first draft of how this visualization looked, 12 hours ago.
