Episode #8: The Total Addressable Market for Micromobility

Oliver Bruce
Oct 19, 2018 · 28 min read

Welcome to Micromobility, a podcast exploring the disruptive potential of light weight utility vehicles. Using the history of computing as a framework we examine how these technologies will upend everything we thought we knew about the future of transport.

The host of the show is Horace Dediu, founder of Asymco.com and I’m his co-host Oliver Bruce.

Micromobility has an addressable market of more than $1.4 trillion dollars annually in the US alone, a figure that makes it more valuable than longer distance transport addressable by cars ($1.1 trillion).

That’s the message in this episode where we run through the talk ‘When Micromobility Attacks’ that Horace gave at the recent Micromobility Summit in Copenhagen. Be sure to check out the slides — have also included the relevant ones throughout the below transcript.

We look at:
- how US trip data typically exhibits log-normal disibutions (and an explanation of what this means!)
- how many of the 2 trillion vehicle trips taken in the US annually would potentially be served by micromobility
- how Marchetti’s constant (one hour of travel a day) relates to micromobility’s benefits
- how adoption of micromobility would impact car demand, and why this is relevant to automakers
- why these high volume, short trips are actually more valuable than average car trips on a dollar basis.
- how time spent travelling will actually drive adoption of micromobility in highly congested cities.
- Why 3 times more time is spent on short trips than longer trips in vehicles, and the implications for micromobility
- The impacts this explosion in micromobility might have on carbon emissions and how we can measure that

Be sure to let us know what you think at either @asymco or @oliverbruce on Twitter. Cheers!

___________________________________________________________________

[00:00:00] Welcome to Micromobility a podcast exploring the disruptive potential of lightweight utility vehicles. Using the history of computing as a framework we examine how these technologies will upend everything we thought we knew about the future of urban transport. The host of the show is Horace Dediu, founder of Asymco.com and his co-host is Oliver Bruce.

And welcome back to Micromobility. I’m Oliver and I have with me as always Horace. How you going today Horace?

I’m doing great. I’m in the San Francisco this time it’s been a few a few weeks of travel for me. I last week I was in Copenhagen for the Micromobility Summit. It was the second one we’ve run and would love to talk about what we learned there.

Yeah. Absolutely. [00:01:00] I was it was it was amazing watching the all this stuff come through on Twitter because it sounded like he had quite the collection of of leaders and thinkers in the space including Michal.

Yeah. Michael Naka was there, Steve Anderson was there and Winston Kwon was there. He’s an academic he’s a professor at the University of Edinburgh in Scotland and a few other people who are were we had on stage.

Then the audience, you know, was a pretty competent audience. We had we had a lot of people from the industry from either scooter sharing, bike-sharing. We had people from Europe, the US — it was a very very very good audience. Very [00:02:00] engaged.

Anderson gave a talk on safety that was really well received. We should probably talk about that at some point in more detail.

I’d love to. I think it’s probably valid given both of our histories of crashing things!

It was it was interesting because he has a physics perspective and he’s an engineer, but he looks at the dynamics and the physics of of micromobility. Last year he did a talk about how the physics of micromobility or electric drive in general favor the smaller and slower vehicle because you have, especially for a motorcycle, aerodynamic drag that really is so strong and therefore it [00:03:00] doesn’t make sense to go fast.

On these vehicles, you don’t have a lot of storage for battery and you have a lot of wasted energy for fighting the air and so on. It was it was interesting way to look at it. Anyway, we should do a safety show at some point in the future. But I also want to talk about some new material that I was able to present.

Yeah. Well some of the first thing I did was I defended the categorization of micromobility at the 500 kilogram weight or mass point of mass and and I did it by illustrating the weights of cars.

While I was preparing this I kind of learned one interesting point: although weights of cars have tended to grow out and go upward and you can do a before and after of [00:04:00] various brands like the mini the Mini of yesteryear and the Mini of today or something like a Volkswagen Beetle versus a low-end Volkswagen today or even the Toyota Tercel.

You can see how cars have gotten much heavier, bigger and also how we have the SUV or crossovers as the most popular form factor, along with pickup trucks as the most popular in the US.

As a result you can imagine cars are getting bigger and heavier. But one thing I learned was that there is a upper bound to vehicle weight.

This is because the regulations usually stipulate that if it’s above a certain weight, I think in the US it’s 6,000 pounds/3,000 kilograms, it’s classified as a truck. It’s classified as a [00:05:00] commercial vehicle.

So these classifications are global and and as a result also roads, and other infrastructure is limiting — you can’t cross certain Bridges, you can’t be accepted into certain facilities if you’re too heavy and so you have you have some upper bound constraint.

What’s happening is that while the lower bound is going up, the upper bound is fixed. The lower bound is simply that no one’s making anything light anymore.

This is why the 500 kilogram point is actually half of what typically a new car will weigh. In fact that the lightest vehicle I could find in production today is the smart Fourtwo from Daimler which is tiny. It’s only for two people and [00:06:00] it is about 750kg to 800 kilograms. It’s remarkable that it weighs more than a Fiat 500 did and that was a car for four people back in the 1950s and 60s and 70s there.

So, you know, it’s an interesting point that that I feel safe putting that weight down there. And in fact, it gives you probably at least 300 kilograms of gap to the nearest car. So it’s like the car can’t come down. If you say the limit is 500 and there’s no no real no real overlap at all with what cars are going to be in the future then I think that validates my premise.

I also looked at the [00:07:00] weights of people around the world. It turns out that actually it varies by continent. Americans are….

You don’t want to go into that Horace!

It’s true! The average weight of Asian people is about 60 kilograms. The average weight of Americans is closer to 80. So it really is a big difference and Europe is somewhere in between. I was trying to figure out what we should use is a global average are when you talk about weights of people.

It’s probably skewed towards the lighter persons because there’s more Asians, but generally the figure I stuck with is not just the person but maybe what they may have as things they want to bring into the car with them as well. So in your vehicle you have your bags, your groceries, [00:08:00] even a child you can consider sort of as an additional…

Accessory?

Exactly but it’s like, you know because you can’t just say that. Anyway, the average person is about 60 kilos but let’s say a hundred. Let’s say a hundred for a person plus other things they might need to bring along with them. Of course there’s going to be distribution, you know by some standard deviation but my assumption then is let’s say a hundred kilograms median is required to be transported.

Then the question is, why do you need something that’s a thousand kilograms to do that? That’s 10 times the weight of the power of the passenger and their accessories. It’s phenomenal why we have to build all of that. I was [00:09:00] standing around just watching cars just today and I was noticing how they’re all basically four passenger or more.

There’s very few cars that are less than that and and they’re all generally only occupied by one person. The car would be a lot lighter if it was designed for one person, but we design cars for four to six people.

It’s puzzling to me because the the why not have you know this micro vehicle for daily commuting which you might use 90% of the time and then you have a bigger vehicle that you’re going to use for these occasions when you need to carry people. It’s spectacularly wrong to me to think that we need to ship so much metal around and so much weight as a result. It’s so inefficient.

I completely agree. I think a lot of that is tied to the [00:10:00] business model [of the automaker] though right? I remember you doing the job to be done analysis on Asymcar and you were talking through the fact that you’re going to buy this car, and you’re making a one-off purchase that’s going to last for three years. You don’t want to be stuck three years in and realize that you needed the extra seat or whatever. So you end up defaulting to a larger vehicle.

I think there’s this really interesting intersection here of where you will see the business model evolution when we start doing more sharing. All of a sudden I think you’ll see a massive proliferation of vehicles that actually do that because you’ll just get the vehicle rightly size for you at the time that I need the job to be done because I don’t have to tie up heaps of capital, but anyway,

yeah, people will buy Six Sigma capacity. Six Sigma refers to six standard deviations away from the median. So they’re they’re going to buy something that is used one in a hundred thousand times. I’m [00:11:00] not saying it’s wrong, but what I’m saying is that there’s no viable alternative that you can substitute usually because if you’re going to purchase one vehicle for $35,000 you want it to cover all the possible cases of your transportation needs you may have over the lifespan that you think that vehicle is going to be in your possession.

We’ve gone over this before but what I was trying to do with the talk was sort of make it simple and easy to visualize.

You say okay, ‘We have an object needs to be transported — it’s a person and there things that weighs about a hundred kilograms’. Yep. No one’s making a car less than 10 times that person’s weight. That was the first talk

The second talk I gave that was to quantify the [00:12:00] opportunity that exists if we’re willing to create smaller vehicles for shorter distances.

This is going back to the log normal distribution and I you know, I hate to, I don’t hate it, that’s wrong word, but you know, there was a book A Brief History of Time written by Stephen Hawking that had a funny phrase right at the beginning of the book.

He said I’ve been advised by my editor that for every equation I insert in this book, I will lose half the audience. [00:13:00] So he said ‘I’m willing to take a chance. By actually writing this one equation now, I am very sorry for those half the people that are now going to stop reading this book, but I feel compelled to have to use this at least one equation’.

He reserved himself to one equation. Now, what I’m doing is I’m similarly introducing one mathematical function, which is this this log normal knowing possibly that I’m going to lose half the audience.

That’s okay. I will be very happy to be the layman to try and interpret this for the rest of the audience who don’t understand it because I think/hope I get it. So we’ll proceed on that basis and I’ll ask for clarification.

It’s a simple equation. [00:14:00] Just just to once again reintroduce it. Everyone is familiar with the normal distribution, which is or let’s say the Gaussian or the bell curve.

The Bell Curve. Yeah.

When you think about the bell curve, it is where the middle is the most common, let’s say the height of people or the weight of people. You’re going to have a middle point where the bell curve is highest and that’s that’s the most common, most popular or the most likely weight or or height.

With the Curve you’re going to see the probability or the likelihood of other weights that might occur and so it drops off. If you go far to the right, you’re going to see the, you know, very few people who are you know weigh twice the average and then in the other side you’re going to have very few [00:15:00] people who weigh half the average. That’s a normal distribution.

It’s used in all kinds of measurements of people and things in life. We kind of assume when someone gives us a figure that says, okay, the average speed is this or the average size of a house or whatever it is, you think of it as kind of shaped that way.

That means that the average is only the middle point, but guessing and putting in your head the assumption that there’s probably a shape to this curve. Average test scores, average all kinds of things. We’re a society that loves to have statistics to give as evidence.

So we usually get the one figure and the figure of averages. We assume in our heads that the shape of this [00:16:00] curve is somewhat symmetric around that average. So half is above and half is below.

The point I’m making, and this is why I’m belaboring this, is that when it comes to transportation and travel distances it isn’t like that. When someone gives you an average for travel distance, you’re not going to have half of the distance below that point and half of them above that.

Transport distance are skewed so far to one side that that the average is squashed so that it’s closer to zero. The peak on the curve is very close to 0.

I illustrate this in the talk ‘When Micromobility Attacks’. The idea behind it was [00:17:00] ‘let me show you the evidence’. Let me show you all of these modes from cycling to driving to walking to trains to buses to motorcycles to scooters to mopeds.

You can imagine 50 of these. I’ve collected them for different countries and they all have the same shape. They all look like this normal curve that’s been squashed up against zero or close to it. Now as a result, that means that the trips people take are predominantly short trips.

Then I started to ask ‘Okay, so of the trips in the United States how often do they travel, [00:18:00] how long are the trips and how many person miles are travelled and how many vehicle miles are there?

These are all statistics that are collected. If we take the actual figures and we know the distribution, that means that we can quantify the trillions of miles and trillions of trips that are being taken by Americans. Globally you can guess it’s a multiple of this — tens of trillions perhaps.

Now, If you if you imagine then that the the distances travelled are predominantly short distances and you multiply that probability by the actual number of trips, you can get something around the the total miles that are taken for short trips.

You can find out the point where let’s say half of the trips are short and [00:19:00] half of the trips are long, and say, if the car were used only for a certain long distances, and another vehicle was issued only for short distances at what point and how many miles is that threshold where half the trips or half the miles traveled are by the new vehicle versus the existing vehicle?

That’s called the parity — the point of parity where if you had a new vehicle and it was only good for short distances, not a very good vehicle, but only good for short distances, how many miles would be the threshold where the new vehicle would be used as much as the existing vehicle.

So just to clarify what you’re what you’re what you’re saying. You’re looking at all the trips that are taken [00:20:00] and at the moment the vast majority of them are taking the cars because that’s sort of the monoculture mode, especially in the US.

You’re looking at all trips and you’re saying of that what’s the sort of halfway point at which you would say actually a scooter would probably make more sense for us to use because it’s a short trip around town?

I’m thinking of a practical anecdote but say for example that you spend your entire time circling the entire block looking for parking when I’d actually be better off to go and use a scooter for that trip because it would be better to actually transport me that distance and then on the other half, there’s a sort of a point at which the distance for the scooter becomes too far so you’re better to use the car. Is that how you’d be thinking about it?

That’s how consumers are going to make the decision. Yeah. I’m trying to just take the numbers that we have and run with them. For example, in the [00:21:00] US there are four trillion person trips and two trillion vehicle trips taken.

Now, if you decided okay, I think scooters, bikes and quadricycles are going to be good at up to 15 miles, and let’s just call any distance under 15 miles addressable, that’s the addressable market.

These are no good above 15 miles, and in fact may be really tough to get to 15 miles at all. It’s a long distance to think about 15 miles, especially if you’re going slowly. Even walking you can do the same thing — any trip trip [00:22:00] below half a mile is probably comfortable walking, but anything above that is really uncomfortable, especially given that time budget.

yeah, I was going to ask how so if there a specific speed that you would expect those trips to be taken on those bikes.

I would because, in fact, we know that the speed e-bikes or pedelecs, are rated to about 30 miles an hour. In fact, it’s 45 kilometers an hour. So it’s about 28 miles an hour.

It may not sustain that for the entire journey and that overall speed limit may also creep up a little bit, but let’s assume that means that sustained 30 miles an hour. At half an hour, that’s around 15 miles.

We have [00:23:00] Marchetti’s Constant saying let’s say you take two trips a day then then your budget for time with the vehicle at that speed of 30 miles an hour is 30 miles. And so if you have a vehicle that can deliver 30 miles in one hour. Then I would say that it’s adequate at serving that point.

It’s hard to imagine that these vehicles are going to go 60 miles an hour. I just think micromobility ought to be limited. I’m not giving it that limit but I’m saying it’s likely that that they will be limited in speed but that means that the car is going to be just fine because it’s going to be hired for trips above 15mph.

So the question I was asking was if we make the cut off 15 miles, [00:24:00] then how many miles are being driven above 15 and below 15?

These are called vehicle miles traveled. We know the entire amount of available and because we know the distribution of those miles according to this function, we can start adding them up.

Here’s where it comes down to. Let me let me summarize it for you.

- 0 to 6 miles trips (scooters): 425 billion miles.

- 7 to 15 mile trips (e bikes): 612 billion miles

- over 15 miles: 1.06 trillion miles

Of course. This is a false precision I’m giving you.

Of the [00:25:00] more than 1 trillion trips over 15 miles, this is what the car is going to keep doing. The only question is what happens below 15 miles.

Right now, if you took those two buckets, I mentioned this if 425 and 612 you had them together. Yeah, you actually get approximately 1 trillion below 15 miles and about 1 trillion [00:26:00] above. That’s what I mean about parity at 15 miles. You have half the miles below that and half are done above it. That means that if you actually moved all those miles to micromobility they would have consumed about as many miles as the car.

Another way of thinking about it is that if all of these trips are done by car today, it stands to lose about half of the miles that it currently serves.

That’s an important question for an automaker or the entire auto industry. Are you seriously considering that short distances will be done by something other than a car? If so, then because of the distribution being a little bit lopsided towards zero, that means that only at 15 miles [00:27:00] we would lose half the market, and therefore half the dollars.

This is where it gets interesting because the talk continues, and we get into dollars by saying well not all miles cost the same. The reason for that is that if you get into a taxi or an Uber or a ride with the micromobility service, usually you have higher cost up front right?

You have a dollar to start or four dollars to start. The first mile is the most expensive mile. So you can put a function and sort of how quickly does the price per mile drop as the as the miles traveled increase by multiplying through with this function. You realize that actually this the shocking [00:28:00] thing.

The short distance — those below 15 miles — those will be the revenue for the provider of $1.4 trillion and the miles above that is reserved for the car because they’re long distance, and yet they’re only $1.1 trillion.

So just so I can contextualise this a but more, I went and did a little bit of math really quickly as as we were discussing.

So of the 0–6 miles and the 7–15 miles if you take that all together and then you divide it by the number by the number of people in the population in the US. It’s approximately about 3,000 miles a year per person which then is about 8.5 miles a day — that sounds about right like ballpark figure as a combination of all of the short trip done in a day.

From there you take that [00:29:00] and you’d say there’s $1.4 trillion. How did you calculate that number? How would that would be valued?

Okay. I apologize. I didn’t dig into that. But this is this is the data I used to to calibrate the cost per mile.

Yep. First of all, there’s a figure the Internal Revenue Service, uses for travel. It’s a figure that’s used for deductions. Regardless of the country, you’ll see that there’s a consistency around that number.

Also if you try to work out how much your car is actually costing you. It’s pretty similar to that number because you know, if you count all the depreciation, insurance, repairs, maintenance, [00:30:00] tires, all the consumables and everything that goes into that car ownership costs and you divide by the miles traveled you’ll get to that 50 cents a mile. So the 50 cents a mile is what the IRS uses. It goes up with inflation.

If you have a very economical car it might be cheaper. If you have an electric car, you probably will be cheaper. But but then if you have a truck it’s going to be more but so this is an average figure. But if you were to ask on a service basis, like look, I’m going to get in the taxi, how much are those miles going to cost me? Well theres data from New York City.

I actually pulled the data for taxis. I also pulled the data for citibike, which is the bike share system there. [00:31:00] I’ll give you an example: the first half a mile, if you’re only traveling a half a mile in your taxi, it costs $18. It’s very expensive for the per mile because you probably going to pay six dollars [as a flagfall]. But you know, we’re measuring per mile if you taking one mile is about twelve dollars again, because you’ve got the starting point and and then you’ve traveled one mile and that’s going to cost you $12 in New York City.

If you go to 1.5 miles, it goes down to about $10 if you go two miles around $9, if you go three miles it goes about $7–8. And so you see how the cost as the further you go, the miles get cheaper.

Citibike is actually a lot cheaper because it starts at three dollars if you go to half a mile. So I asked what does it what would be a micromobility average price for the [00:32:00] these first few miles? I’m guessing by mile six or seven, it’s going to go down to 50 cents, which is what the car costs. That’s going to stay at 50 cents all the way out to hundreds of miles.

So the whole point is what is the shape of the curve that drops? So I started three dollars because that’s the citibike in New York. Yep, and it drops to about a $1.50 after three miles, then after four miles drops to about a dollar and finally after six miles it’s on 65 cents and then gets to be 50 Cent’s about seven miles.

This was the the curve I used for pricing. This is the price curve. You multiply the curve by the miles so you get to dollars per mile so that Miles cancel out and you’re left the dollars. Yeah, so you [00:33:00] you multiply these two figures together to get again in the aggregate sense to get this this figure.

So what do what are all these buckets of miles going to be worth? The buckets of miles under 15, which again, we defined as potentially addressable by micromobility. Yep, that bucket of miles are going to be priced at $1.4 trillion based on the micromobility price curve starting a $3 a mile in there on dropping to 50c.

That 50c is still carried on beyond 15 miles for the car because that already is what what the price for a car mile is. So now we end up adding up those miles in the car bucket and thats $1.1 trillion. So already now just looking at $/mile and therefore the value of this addressable market, not just the number of trips, not just the number of miles, but the number of dollars that are going to be captured by micromobility is [00:34:00] about 30% higher than all the dollars that are going to be left with the car.

So here we are again asking this important question: are cars going to get half the market if you’re measuring miles, but going to less than half the market if you’re going to measure dollars?.

Again, it’s a big assumption that this 15 mile market will go to this new mode but it’s still an important provocation

Now the story continues, because beyond dollars and miles there’s also another way to think about value and that’s time.

I actually didn’t present this data. I thought about it afterwards and how to figure out the time spent.

We have speed, and if you divide the miles by the speed, then you get time and this is where it’s even more interesting. Now, of course, [00:35:00] how does time per mile change because again, the speed is low for short distances and it’s going to be high for very long distances.

Let’s say it goes up to 60–70 miles an hour an average for a long trip. Mostly short trips are at slow speed. If you think about the urban environment, I again devised the curve based on some some empirical data about about how city bikes and taxis are traversing through New York.

Again, this is very sketchy because I don’t have a lot of this data but if you draw the speed curve, if you go two miles in New York City in the taxi, you’re going to be an average of five [00:36:00] miles an hour. The city bike is eight miles an hour. These speeds go down as you get closer to the short distance trip. So if you going only half a mile the taxis at four miles an hour, which is barely above walking speed but that’s what people do in big cities.

Yeah interesting. I mean, obviously they solve other jobs to be done like it’s raining and I don’t want to be walking in the rain.

What I’m saying though, is that the curve begins at around five miles an hour and goes up to 60 miles an hour. The 60 miles an hour is achieved when your trip distance is about 25 miles. So at about 25 miles I’m assuming people are able to maintain 60 miles an hour which actually very improbable but [00:37:00] I’ll give it the benefit of the doubt to the high-speed there.

It turns out that the amount of time spent in the short distance trips by my calculation is about 90 billion hours in the United States, whereas the long-distance trips are 30 billion hours. And so here the the parities is even worse.

In other words, that 15 mile threshold is favoring micromobility by a ratio of 3 to 1. So 3 times more time is spent on trips that are 15 miles or less than trips that are over 15 miles.

This is important if your business model for micromobility is to engage the user during that Journey. [00:38:00] A lot of people think about autonomy who think about the future of automobile transport is about really how do we engage the user for doing their Journey because if they’re not driving they might be doing something else.

That’s I think this Marchetti’s constant of having an hour a day that is burned up staring out the window trying to not be frustrated by your driving work, now is suddenly you can use that time put more productively or in an entertaining way.

And so here’s the interesting premise. Although we you may not be eyes off the road in the microvehicle, these microvehicles are actually going to be used for three times more than the cocoon vehicle that you might go a long distance in.

When I presented this a lot of you [00:39:00] know, I don’t want to exaggerate, but there was a lot of commotion.

The crowd went wild?

Yeah I don’t know if it was that, but…

I mean this is this is amazing. It’s incredibly profound because it’s you know when you see people navigate through a city, most of it’s actually congestion. It harks back to that that graph from one of the earlier episodes about why people in Copenhagen bike. They bike not because it’s green or anything. No, it’s the quickest way across the city. Yeah.

The idea of saying okay, you’ve got parody in terms of miles but if you were to ask well, what is parity? Let’s try to move that 15 mile breakeven. to find out parity for dollars and parity for time?

[00:40:00] I didn’t calculate it for all of these but I think I think we’re the case of dollars it’s like 12 miles. So for the bucket of trips that are 12 mile or below there’s as much money there as there is 13 miles in above.

If you were to ask about time, I have to do that yet still to do that but I would guess it’s probably even less like 10 miles.

It just attracts so much. It attracts the miles. It attracts the usage. It attracts the dollars. It attracts the time.

The whole point of the [00:41:00] presentation is not a show — it’s in quantifying it in actual dollars and hours and kilometers and so on. And that’s just the United States. These figures are so big, you know, the digits are so long. You get these trillions and trillions, and they’re just kind of a shocking.

[In this world of high adoption micromobility], the car gets about 50% of the vehicle miles but only 30% of the time and 40% of the revenues.

And that’s you know again, assuming you can you can address this. The next stage of the discussion which I didn’t yet [00:42:00] prepare as of yet, will be just how quickly are we getting there? And this is therefore the rate of adoption, of miles, of dollars, of time as we are trying to reach these trillions that I’ve cited.

The good thing is Michal Naka’s work or rather his collaborator who is collecting data on how many trips Uber have, and how many trips does Lime and Bird and Lyft. So he’s collecting this data, and we’re starting to see how quickly these companies are sucking up miles.

You know initially you measure trips because that’s all they’re going to publish but then if you know something about the trip distance you can start to figure out, okay, this is how many miles they’re serving and then after that you’re going to calculate how many dollars they’re capturing and then how many hours [00:43:00] they’re capturing.

As you plot these trajectories ,and by the way these trajectories are exponential, you’re going to be able to forecast how long it’s going to take for the penetration of this market to occur.

This is the Holy Grail. Not only do we get an idea of how big it is, which is what I’m doing now. We’re also going to get an idea of how quickly we can capture this which is a very important indicator for capital, for policymakers, for entrepreneurs who say look you’ve got five years, or you’ve got eight years or you got 20 years.

Source: Asymco.com

We don’t quite know yet. Yeah, I’ll try to figure that out. But this is the beginning of understanding of the market potential and addressability.

I know many people I when I first posted this micromobility slides, [00:44:00] a lot of people were saying hang on a second, there’s a there’s a parity of 15 miles, but what are the chances that we’re going to capture any meaningful percent of those trillions and trillions of miles?

Well, that may be a valid concern because we’re not there yet. But again if you have something growing exponentially as scooters are, or bike systems in China are, [00:45:00] and perhaps e-bikes are going to follow — you’ve got the all of these things stack up on top of each other and they start to recraft the narrative that micromobility is not one company, one format or form factor.

Micromobility is going to be all of these things, swarming, stacking up and stealing miles.

One more thing, and this is important. A lot of this is about substitutions, and we’re going to try to capture a percentage of that, but as it turns out a lot of these new modes will create their own demand.

In other words, they’re going to not substitute but actually induce demand for trips that wouldn’t have otherwise been made. As we go forward, we may not see the incumbent, the car, actually lose all that many miles even though the entrants are just going gangbusters.

[00:46:00] So they’re going to be you know, just creating trillions of miles of travel and the incumbents are going to be like ‘well, so what?’

You’re going to see this in gas consumption. I’ve received a lot of inbounds saying ‘look at pollution statistics or oil consumption — it doesn’t seem like there’s any impact from these new alternatives?’

It will not be so. Over time, as you compete with non-consumption you’re seducing the incumbents and they’re saying ‘all this doesn’t affect us.’

This is like cordcutting. For years and years when we were switching to mobile telephony we just were not seeing the impact in terms of the number of land lines in use and then they just fell off a cliff.

We’re now seeing the same thing with cable [00:47:00] television versus streaming. People are watching Netflix and YouTube and doing all kinds of stuff online and all the cable companies are saying well, this is not affecting us. People still have subscription to cable and so they have kept raising their pricing and so on. Now we’re finally seeing the cliff-diving that happens.

This is typical of disruption. Disruption is painless for the incumbents for a long long time and therefore they don’t react. If it was painful, there would be a reaction.

They’re lulled into a sense of security by the lack of apparent erosion of their business. It’s important to get this analysis done in order to be able to quantify it but really what’s going to happen in the market [00:48:00] is that these this will create its own demand that will not really cause the incumbents to freak out, and there will be waiting and waiting and waiting. There’ll be a non-linearity to the whole process of response to this even though it seems like it’s going on very predictably.

It’s a little bit complicated but I would say, you know, check out the slides to understand what the basics are. When you think about what really is going to happen it’s a little bit more nuanced but we have to start somewhere. So that’s what this is about.

This is really interesting. I’m aware we’re right at the very end, but one part that I would love to at some stage go and explore is the environmental impact around that because you were saying we will [00:49:00] see an impact on oil or energy use and transport. Or at least, you won’t see one, you won’t see one, and then finally you might. I’m also just wondering how much of that could you forecast? If you look at somewhere like the Netherlands which already has, you know, 50% of its trips that are being done around Amsterdam or whatever and say what is the oil consumption? I’m just trying to think of how we could forecast that but that’s something we can come back to.

It’s so tricky to. One member of a panel at the Summit pointed out that the Danes, which are big users of cycling, actually have a very lousy carbon footprint as a per capita number. The reason was that they became wealthy enough that they would all go on holidays by hopping on an airplane and flying South. It’s shipping a whole [00:50:00] country by airplane down to Greece or Italy or Spain, which is not very good for the environment.

Of course, if you zoom out you might we might not see the environmental impact very quickly, but I think over time this has to make an impact. We have trillions and trillions of miles that will be converting to electric.

I’d like to you can certainly put the figure on the carbon savings. We will have a lot of fun with that. I can certainly see a forecast here coming up from trips, dollars, time and carbon all of these are going to fall out of this exercise. It’s still a question really because there are still secondary effects as [00:51:00] people create and displace demand and trips to something else.

So maybe we’ll have so many of these existing trips switching but people will feel that they have more leisure time and then they’ll go on.

Yeah, the Jevons Paradox.

Yeah, that’s the problem. But but I think it’s something worth doing anyway, so that’s it. What do you think?

Oh, no, I thought this was excellent. Super super profound. Especially the amount of time that micromobility could capture is crazy — when you really start to understand the implications of that and how it’ll shift our our cities move, I think it’s just going to be [00:52:00] profound. All right, excellent. Thanks for much for us and we’ll we’ll talk next time.

Excellent.

Micromobility

Micromobility is a podcast exploring the disruption from new electric, lightweight utility vehicles. Using the history of computing as a framework, we unpack what business models and impacts we’re likely to see in urban transport. Check us out at micromobility.io/podcast

Oliver Bruce

Written by

Now: Co-host of The Micromobility Podcast with @asymco. Climate tech investor. Edmund Hillary Fellow. Ex-@Uber ANZ Regional Ops/Strategic Projects.

Micromobility

Micromobility is a podcast exploring the disruption from new electric, lightweight utility vehicles. Using the history of computing as a framework, we unpack what business models and impacts we’re likely to see in urban transport. Check us out at micromobility.io/podcast