Brandon Donnelly — Daily insights for city builders. Published since 2013 by Toronto-based real estate developer Brandon Donnelly. — Page 1245

Toronto can’t make up its mind right now as to whether it would like to invest in additional cycling infrastructure. 

Of course, we have a history of vacillating on topics like this. And I think it’s because we’re at a tricky inflection point. We are weaning ourselves off of the car, but most parts of the city remain underserved by transit and heavily dependent on the car.

So today I thought I would share some numbers from a research study that was published last year by Stefan Gössling of Lund University and Andy S. Choi of the University of Queensland. It’s called, Transport transitions in Copenhagen: Comparing the cost of cars and bicycles .

Much of the focus of the paper is on the cost-benefit analysis that the City of Copenhagen uses to make its cycling investment decisions. Here is an excerpt from ScienceDaily :

“If the costs to society and the costs to private individuals are added together, the impact of the car is EUR 0.50 per kilometre and the impact of the bicycle is EUR 0.08 per kilometre.

The study by Stefan Gössling and his colleague also shows that if we only look at costs/benefits for society, one kilometre by car costs EUR 0.15, whereas society earns EUR 0.16 on every kilometre cycled.

“The cost-benefit analysis in Copenhagen shows that investments in cycling infrastructure and bike-friendly policies are economically sustainable and give high returns,” says Stefan Gössling.”

So there you have it. Now I thought we could debate this in the comment section. Your thoughts?

P.S. The images at the top of this post were taken by me using my new GoPro bicycle handlebar mount.

I have a bit of an obsession with my calendar, lists, and goals. On the home screen of my phone I have Wunderlist, Evernote, Google Drive, and 2 calendar apps (more on that in a second).

This obsession is probably one of the reasons I write this blog. I like writing, drawing, and documenting things. It helps me sort through my thoughts. I have everything from a list of cities I want to visit to a list of billion dollar business ideas (yes it’s really called that).

But the other reason I like to keep lists is because – as I said in this post – I’m trying to be cognizant about overcommitment. And when I write things down, it serves as a reminder of what I’m doing and what I’m allowed to focus on.

One of the ways I do that is through repeatable goals (or disciplines). These are non-negotiable things that I’ve committed myself to and that I just have to grind out – such as writing on this blog every day. I can tell you that some blog posts come out a lot easier than others. But I’m a firm believer that there are few substitutes for just showing up every day and putting in the work.

On that note, let me tell you why I have 2 calendar apps on my phone. I’ve been testing out the latest version of Google Calendar because of a new feature they rolled out this month called Goals .

What it does is automatically schedule repeatable goals. So for instance, you could tell it that you want to work out 3 times a week for 1.5 hours each time and that you prefer to work out in the evenings. It will then go and find 3 times for you to do it every week for all of eternity. 

If a conflict arises, that’s no problem. As soon as you enter another appointment, the app will automatically reshuffle your calendar goals to make sure that you still get your 3 workouts in. It’ll even learn your preferences as you make changes to these appointments over time. 

So far I’ve been finding this feature really useful. I used to do this for myself manually, but now I have a computer that does it for me. Even better.

It’s also a glimpse into the future that Sundar Pichai, CEO of Google, was talking about on a recent earnings call :

“We’ve been investing in machine learning and AI [artificial intelligence] for years, but I think we’re at an exceptionally interesting tipping point where these technologies are really taking off,” he said. “That is very, very applicable to businesses as well. So thoughtfully doing that externally we view as a big differentiator we have over others.”

“In the long run, I think we will evolve in computing from a mobile-first to an AI-first world,” Pichai said in closing. “And I do think we’re at the forefront of developments.”

For the past 5 years, it’s been  all about mobile . But now much of the tech community – including the CEO of a pretty big company – is saying that artificial intelligence is next. What do you think this will mean for cities?

One of the things you’ll often hear people deride at cocktail parties is the trend toward smaller urban dwellings. They get called “shoeboxes” and “cubby holes in the sky.” So let’s unpack that a bit today and try and better understand the economics behind it all.

When a new building is being developed, pretty much everything gets normalized to a per square foot (or square meter) number. 

This is important because saying that building X cost $50 million to build and building Y cost $100 million to build doesn’t tell you much if the buildings are completely different. 

However, saying that building X cost $500 per square foot to build and building Y cost $475 per square foot to build, tells you that building Y, despite being more expensive in absolute terms, was actually cheaper and/or more efficient.

The same is true on the revenue side. And typically, developers are looking (struggling) to meet a certain per square foot number in order to make the project financially feasible. 

For instance, let’s say you’re building a 100,000 sf condo building. Once you subtract the non revenue generating spaces, you might determine that you need 85,000 sf x $600 per square foot in revenue in order to make the project feasible.

But there’s a back and forth game that needs to be played here. You have to ask yourself: for the product that I’m hoping to build, does $600 psf translate into something that people can actually afford?

You might think: everyone keeps telling me at cocktail parties that condos in this city are too small. So I’m going to build a bunch of 1,800 sf, 3 bedroom condos. Based on the above, these homes would be priced at around $1.08 million (1,800 sf x $600 psf). Your on-site signage would read:  “Condos coming soon. From the low $1 millions.”

But wait a minute, how many families can afford a condo north of $1 million? Some could, but definitely not the majority. So then you determine through rigorous market analysis that $600,000 would be a better number. That is something that is within reach of more families.

But then you look at the math and realize that if you build that same 1,800 sf home, your per square foot revenue number now drops to $333 psf ($600,000 / 1,800 sf). 

Given that you bought the land for $100 psf buildable (market price in the area) and that your construction costs alone are going to be $250 psf, you realize that you’re now underwater ($100 + $250 psf > $333 psf) without even adding in any soft costs (consultant fees, city fees, and so on). If you showed this to your investors on the project, they would throw you out of the room.

So instead of building that 3 bedroom condo at 1,800 sf, you say to yourself: what if I made it 1,000 sf? You’re confident that your architect could lay out a terrific condo at that size and it now magically gets your per square foot revenue number back up to $600 psf. 

This solves two problems: it returns the project to positive feasibility and it keeps the total sale price within reach of more people. It promotes greater affordability. So you go ahead and do it. Boom – shrinking urban dwelling.

All of this is not to say that this is fair or unfair, good or bad. It is simply to say that this is the way it often is.