Brandon Donnelly
Daily insights for city builders. Published since 2013 by Toronto-based real estate developer Brandon Donnelly.
Brandon Donnelly
Daily insights for city builders. Published since 2013 by Toronto-based real estate developer Brandon Donnelly.
Since we're on the topic of large-scale data collection, I thought some of you may be interested in Uber Movement's new "Speeds" product.
First launched in 2017, Uber Movement aggregates anonymized data from their ride-sharing business to create data sets and tools that can help cities make better transportation decisions.
Below is a (hex cluster) map of Toronto showing average travel times from downtown. I dropped the pin at Toronto City Hall. What is shown is the average for all days of the week during the month of January 2018.

Uber Movement's new Speeds product looks at how specific streets are performing relative to their "free-flow speed." Uber defines this as "the average speed of traffic in the absence of congestion or other adverse conditions." (The 85th percentile of all speed values.)
As of right now, Speeds is only available in 5 cities: New York City, Seattle, Cincinnati, Nairobi, and London. Here is a snapshot of London during the same time period as above, January 2018:

In comparison to what we were talking about yesterday, I have few concerns with the fact that my Uber rides around town have likely contributed to these mappings. With these use cases, the value really only emerges once you aggregate the data.

The average salary of a teacher in the United States was approximately $61,730 last year. This can make homeownership in high cost areas a challenge.
Here is a chart from Curbed:

Landed is trying to solve this problem by offering downpayment assistance to "essential professionals" -- starting first with teachers -- so that they can buy homes in and near the communities that they serve.
The way it works is pretty simple.
They'll contribute up to half of a traditional 20% downpayment -- so 10% of the value of the home -- in exchange for a 25% share in any future gains, or losses.
Put differently, for every 1% that Landed contributes, it takes 2.5% of any future appreciation (or depreciation). However, on an equity basis, they are actually putting up 50% of the required cash (in the maximum scenario) in order to get 25% of any future gains.
There's no monthly payment associated with Landed's money, but it does need to be repaid at the end of 30 years or when the homeowner exits the agreement, whichever comes first. Homeowners are free to repay Landed at any time should they decide to sell the property or they just want to pay them out.
Landed pitches the service as another version of "the bank of mom and dad." And for many prospective homeowners, I am sure that it makes all the difference in the world.
At first glance, it would seem that each homeowner also benefits from a kind of positive leverage. They only put up 50% of the required equity, but they get to enjoy 75% of the potential gains. However, each homeowner is also responsible for 100% of the carrying costs.
I ran a couple of quick return scenarios, assuming a $500,000 purchase price and a 10 year hold, in order to test whether Landed or the homeowner would receive a higher IRR once the property gets sold.
I didn't carry any transaction costs, but I did factor in principal recapture, as well as utilities, insurance, and maintenance.
My rough numbers suggest that it depends on the annual rate of appreciation. If appreciation stays close to the rate of inflation, it could tip in favor of Landed because they don't put out any money after t = 0.
But at higher rates of appreciation, the homeowner starts to benefit from the favorable 75/25 split at the end of the hold period.
Either way, Landed is providing a service to people who may not otherwise be able to afford to buy a home. That has value. Here's some more information on how it works, in case you're interested.
Since we're on the topic of large-scale data collection, I thought some of you may be interested in Uber Movement's new "Speeds" product.
First launched in 2017, Uber Movement aggregates anonymized data from their ride-sharing business to create data sets and tools that can help cities make better transportation decisions.
Below is a (hex cluster) map of Toronto showing average travel times from downtown. I dropped the pin at Toronto City Hall. What is shown is the average for all days of the week during the month of January 2018.

Uber Movement's new Speeds product looks at how specific streets are performing relative to their "free-flow speed." Uber defines this as "the average speed of traffic in the absence of congestion or other adverse conditions." (The 85th percentile of all speed values.)
As of right now, Speeds is only available in 5 cities: New York City, Seattle, Cincinnati, Nairobi, and London. Here is a snapshot of London during the same time period as above, January 2018:

In comparison to what we were talking about yesterday, I have few concerns with the fact that my Uber rides around town have likely contributed to these mappings. With these use cases, the value really only emerges once you aggregate the data.

The average salary of a teacher in the United States was approximately $61,730 last year. This can make homeownership in high cost areas a challenge.
Here is a chart from Curbed:

Landed is trying to solve this problem by offering downpayment assistance to "essential professionals" -- starting first with teachers -- so that they can buy homes in and near the communities that they serve.
The way it works is pretty simple.
They'll contribute up to half of a traditional 20% downpayment -- so 10% of the value of the home -- in exchange for a 25% share in any future gains, or losses.
Put differently, for every 1% that Landed contributes, it takes 2.5% of any future appreciation (or depreciation). However, on an equity basis, they are actually putting up 50% of the required cash (in the maximum scenario) in order to get 25% of any future gains.
There's no monthly payment associated with Landed's money, but it does need to be repaid at the end of 30 years or when the homeowner exits the agreement, whichever comes first. Homeowners are free to repay Landed at any time should they decide to sell the property or they just want to pay them out.
Landed pitches the service as another version of "the bank of mom and dad." And for many prospective homeowners, I am sure that it makes all the difference in the world.
At first glance, it would seem that each homeowner also benefits from a kind of positive leverage. They only put up 50% of the required equity, but they get to enjoy 75% of the potential gains. However, each homeowner is also responsible for 100% of the carrying costs.
I ran a couple of quick return scenarios, assuming a $500,000 purchase price and a 10 year hold, in order to test whether Landed or the homeowner would receive a higher IRR once the property gets sold.
I didn't carry any transaction costs, but I did factor in principal recapture, as well as utilities, insurance, and maintenance.
My rough numbers suggest that it depends on the annual rate of appreciation. If appreciation stays close to the rate of inflation, it could tip in favor of Landed because they don't put out any money after t = 0.
But at higher rates of appreciation, the homeowner starts to benefit from the favorable 75/25 split at the end of the hold period.
Either way, Landed is providing a service to people who may not otherwise be able to afford to buy a home. That has value. Here's some more information on how it works, in case you're interested.
San Francisco recently became the first city in the US to ban the use of facial recognition software by city agencies. (There's a second vote next week, but it is considered just a formality.) A similar ban is also making its way through the system in Boston.
I thought the following quote by Aaron Peskin in the New York Times was an interesting one, because it speaks to some of the growing tensions between tech, policy, and city building:
“I think part of San Francisco being the real and perceived headquarters for all things tech also comes with a responsibility for its local legislators,” Mr. Peskin said. “We have an outsize responsibility to regulate the excesses of technology precisely because they are headquartered here.”
I can appreciate both sides of this argument.
For those concerned about crime and safety, facial recognition promises more effective policing. That's why this technology is already used at many airports, including SFO. (Because it's under federal jurisdiction, it won't be impacted by this ban.)
At the same time, there are legitimate concerns related to the large-scale collection of personally identifiable data. And it is this same concern that is fueling the debates here in Toronto around what Sidewalk Labs is up to along the waterfront.
I am not an expert on this particular topic (or many topics for that matter). But if you're a regular reader of this blog, you will know that I believe in innovation and I believe in progress.
However, I also believe that it is important and healthy for us to be having these debates. Because what I do know is that I wouldn't want Toronto to become Shenzhen. I wouldn't want to jaywalk across the street and have facial recognition software automatically send a ticket to my phone and post my photo to a "wall of shame."
That doesn't sound like a very fun city.
Photo by Chris Leipelt on Unsplash
San Francisco recently became the first city in the US to ban the use of facial recognition software by city agencies. (There's a second vote next week, but it is considered just a formality.) A similar ban is also making its way through the system in Boston.
I thought the following quote by Aaron Peskin in the New York Times was an interesting one, because it speaks to some of the growing tensions between tech, policy, and city building:
“I think part of San Francisco being the real and perceived headquarters for all things tech also comes with a responsibility for its local legislators,” Mr. Peskin said. “We have an outsize responsibility to regulate the excesses of technology precisely because they are headquartered here.”
I can appreciate both sides of this argument.
For those concerned about crime and safety, facial recognition promises more effective policing. That's why this technology is already used at many airports, including SFO. (Because it's under federal jurisdiction, it won't be impacted by this ban.)
At the same time, there are legitimate concerns related to the large-scale collection of personally identifiable data. And it is this same concern that is fueling the debates here in Toronto around what Sidewalk Labs is up to along the waterfront.
I am not an expert on this particular topic (or many topics for that matter). But if you're a regular reader of this blog, you will know that I believe in innovation and I believe in progress.
However, I also believe that it is important and healthy for us to be having these debates. Because what I do know is that I wouldn't want Toronto to become Shenzhen. I wouldn't want to jaywalk across the street and have facial recognition software automatically send a ticket to my phone and post my photo to a "wall of shame."
That doesn't sound like a very fun city.
Photo by Chris Leipelt on Unsplash
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