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The best thing here is GM expects Chip supply shortages to ease, as does Tesla.
We know Tesla doesn't currently think they are cell constrained.
So if Berlin can get it's final permit, and both new factories ramp smoothly, Tesla production numbers in 2022 might be great.
When the chip supply problems ease, and vehicle production returns to normal, we will get a better read on relative demand.
Major problems for OEMs only happen if/when ICE demand drops rapidly, faster than they can build EV production.
IMO the key consideration is resale values for ICE vehicles as this impacts in multiple ways on ICE demand, resale of off-lease vehicles, and perhaps on the finance arm of many OEMs where the major debts. are held.
Lower sales volumes, mean less income from finance, and less income form service and parts, Indirect effects of lower ICE sales impact on dealers and gas stations. If dealers and gas stations start to close, that accelerates any transition.
So 2022-2024 might be the time interval when a clear trend emerges. If that clear trend is ICE sales dropping faster than expected, that is big trouble for many OEMs. If the other clear trend is Tesla, the Chinese and others ramping EV production faster than expected, that compounds the problem.
Up to now ICE has had the cushion of EVs only being available in low numbers and low public awareness.
IF IF IF everything goes against trend ....... then GM is in trouble.
The chip shortage will ease this year. But not end.
There is mounting pent up demand for not only trucks but vehicles in general. There is demand for ~21M vehicles this year in USA at MSRP but there will probably be 16M sales. Some will refuse to pay above MSRP or MSRP. And wait for things to "return to normal" with significant discounts on MSRP.
So far Chinese EV entries into North America are Volvo and Polestar. Plus some boutique players like Chery. You can special order an Imperium Skywell from Great Wall in Canada.
So the average US dealer has two franchises.
Can you give an indication of the number of :
- sales (per year) on the average franchise ;
- sales revenue per year per franchise;
- maintenance revenue per year per franchise;
That would allow us to start to compare with Tesla's numbers.
So the average US dealer has two franchises.
Can you give an indication of the number of :
- sales (per year) on the average franchise ;
- sales revenue per year per franchise;
- maintenance revenue per year per franchise;
That would allow us to start to compare with Tesla's numbers.
This consultancy, Urban Science, chose to put out that infographic to promote their business. Any more information is what they are selling to stakeholders.
That kind of chart continues to misunderstand what a market is.
New legacy EVs are not competition for Tesla- they're competition for legacy ICE vehicles.
There is no "EV market" there's just an "all vehicles" market.
Teslas share of "all EVS" will shrink as legacy converts some of their own sales from one to the other- which is both obvious and largely meaningless overall.
Teslas share of -all- cars sold keeps increasing though.
That's still the total car market. EV simply being a criteria for picking something in that market- just as someone who needs to tow is part of the total car market but would immediately eliminate most compact cars.
But nobody ever seriously talks about "the cars that can tow" market like that's a thing.
Did company X sell more, or less, cars this year than last seems a lot better "state of their competitors" measure than Did company X sell more of one specific powertrain or not.
Otherwise it might falsely gives you the impression each Mach E sale is somehow taking one away from Tesla, when clearly that's not the case (if it were Tesla wouldn't still have months of back orders on new cars and be massively up in sales YoY while Ford was down 6% YoY in the US).
Fords "ev market share" grew a ton YoY. Their total sales declined. Teslas "ev market share" shrunk YoY, but total sales increased massively.
There is not "ev market" there's just a "car market"
That's still the total car market. EV simply being a criteria for picking something in that market- just as someone who needs to tow is part of the total car market but would immediately eliminate most compact cars.
But nobody ever seriously talks about "the cars that can tow" market like that's a thing.
Yes, there is a towing market. PIckups and heavy duty trucks. We don't talk about here in that way much because this is a Tesla /EV forum. And cybertruck is not selling yet.
Nobody talks about mild hybrids in the same way people don't talk about vehicles that can only tow 1500 lbs. That is a minor feature in an other wise non-EV non-towing vehicle.
Not really though.
Did company X sell more, or less, cars this year than last seems a lot better "state of their competitors" measure than Did company X sell more of one specific powertrain or not.
Otherwise it might falsely gives you the impression each Mach E sale is somehow taking one away from Tesla, when clearly that's not the case (if it were Tesla wouldn't still have months of back orders on new cars and be massively up in sales YoY while Ford was down 6% YoY in the US).
Fords "ev market share" grew a ton YoY. Their total sales declined. Teslas "ev market share" shrunk YoY, but total sales increased massively.
There is not "ev market" there's just a "car market"
We should look at all the submarket market shares to give an accurate picture of what is going on.
IF Tesla has 2% of the overall market and 99% of the EV market it is a different relative competitive situation than if Tesla has 3% of the overall market and 10% of the EV market. In the first situation legacy automakers are ****ed and in the second situation the legacy automakers are not ****ed. Even though Tesla has 50% more overall market share.
Does Tesla have 90% EV market share in California but only 25% in the rest of the USA? Or does Tesla have 60% California EV share and 45% elsewhere in the USA?
Ford's EV market share and % of cars sold that are EVs matter. It tells us something about their business than simply overall market share.
There are some buyers that will consider a pickup and others that won't. There is a pickup market. Even though there are some buyers that may shift between the pickup market and non-pickup consideration market.
And also tons of cars that people tow things with.
The Model Y can be ordered with a hitch and it's a "heavy duty truck"
In the EU even the 3 can be ordered with one. There's folks who've said they did NOT consider the 3 in the US because there was no OEM tow hitch or rating. Others were fine with 3rd party solutions.
People look for cars that do what they want, not because they fit an artificially narrow sales category.
Such categories are often folks looking for ways to make specific brands look better or worse than reality.
Nobody talks about mild hybrids in the same way people don't talk about vehicles that can only tow 1500 lbs. That is a minor feature in an other wise non-EV non-towing vehicle.
You don't see much discussion of "sales in the iOS market" you see discussion of sales in the cell phone market.
It'd be accurate to write up a chart on exactly what % of each iphone model is in the market running iOS. It would not be nearly as useful as what % of all phones run it.
IF Tesla has 2% of the overall market and 99% of the EV market it is a different relative competitive situation than if Tesla has 3% of the overall market and 10% of the EV market. In the first situation legacy automakers are ****ed and in the second situation the legacy automakers are not ****ed. Even though Tesla has 50% more overall market share.
Does Tesla have 90% EV market share in California but only 25% in the rest of the USA? Or does Tesla have 60% California EV share and 45% elsewhere in the USA?
Teslas stated goal is to reach ~20 million cars by 2030.
That would be, worldwide, roughly 30% of the total market based on 2021 sales (nearer 20-25% based on pre-covid sales though)
And by 2030 it's likely the majority of ALL sales are EVs. As that becomes increasingly likely, continuing to artificially separate out "EV sales" rather than total car sales gets less and less useful in what was already not especially useful.
Because demand for good EVs is far greater than supply
So anybody who shows up with one can sell 100% of their production and take up some "ev market" share without providing especially useful info.
NONE of those sales are "taking" a sale from Tesla- they're taking a sale from an ICE vehicle. See again demand>supply for any good EV.
If Ford sees an 80% YoY growth in their EV market share... but a drop in total vehicle market share that's bad news for Ford. Even though with your narrow metric it'd look great.
Because it means more of their ICE sales are being replaced by someone elses EV. A problem Tesla doesn't have.
Whereas Tesla saw an 87% YoY growth in sales, but their "ev market" share shrank. Yet those are great results.
Market share shrinking in an artificial segmentation, where demand>supply for the segment and tons of folks are jumping into it but most only be canibalizing sales of their own ICE vehicles (and yet demand will KEEP outstripping supply for years to come) is not a useful measurement, especially without looking at total share.
BTW someone else just recently did a nice long (for twitter) thread on among other bits why total market share, not "ev share" is what matters- and how the "competition" for legacy EV sales is legacy ICE sales.
Which ought sound familiar They provide some data, charts, etc- good read for those interested.
I don't know why you think it needed. The transition to EV's will happen more quickly if legacy US Auto does fail. And the sooner they fail, the more quickly the EV transition will happen.
I would not be saying this if legacy auto was not in debt up to their eyeballs (relative to their earning power) but dragging all their legacy debt into the EV transition will slow things down, not speed them up. The existing capital assets of legacy auto (manufacturing plants) are not applicable to building EV's. Legacy auto doesn't want people to know this because they are trying to leverage ignorance on this matter to keep them relevant. Their high debt load and the ongoing expense of all their inefficient legacy departments and factories impairs their ability to invest in the required number of new facilities to transition to EV's in a timely manner.
Legacy auto resembles dead men walking. They think as long as they are wearing nice suits no one will notice they are already dead. Don't fall for that fake narrative. Keeping legacy auto alive will greatly slow down the transition to EV's.
Giving Tesla a 15-year head start was a bad idea
Being the first mover in a market has advantages and disadvantages. Advantages include economies of scale, brand positioning, patents, and supply chain relationships. Another underappreciated advantage is gaining knowledge and information in the early stage before others have gotten started, which can be leveraged in later stages of the game to accumulate yet more knowledge and information in a virtuous cycle. Wright’s Law is not just an industry-wide model; it also applies to individual firms. The game is actually a race down the Wright’s law learning curve, as well as a competition over whose curve has the steepest slope—that is, who extracts the most innovation potential out of each doubling of cumulative production. This is why pace of innovation is all that matters in the long run for any market in which there is still a significant cost delta between the best producers and their less successful competitors.
I think for the car market, this first mover advantage is strong for engineering, including supply chain, design, manufacturing, and servicing. Tesla’s head start is a gigantic and probably insurmountable barrier to competition in many ways. Today I want to focus on how it’s given them data and experience.
Apple and Foxconn, for instance, are formidable companies but they haven’t even started an attempt at EV mass production. New companies like Rivian and Lucid have been working longer but are much less capitalized and less known than Apple & Foxconn, and they still haven’t actually been shipping cars to customers for years. Apple coming to the car market would be like when Michael Jordan left basketball to play baseball in 1993. Despite being a world-class elite athlete at the peak of his athletic prime, he did not even make it to the Major Leagues as a baseball player. The obvious reason was that he had not practiced baseball since high school.
When engineers design a machine like a car, they have simulation models and physical test data showing that stuff should work in theory, but there's still significant uncertainty. Engineers also have models and test data for the manufacturing system and associated uncertainty. Automotive engineering has even more uncertainty than most machine designs because the duty cycle is intense, customer expectations are high, and the vehicle spends most of its time outside with all the accompanying stress from vibration, temperature, salt, moisture, even UV radiation. Plus, the expected service lifetime is more than a decade. Accelerated life testing is crucial for planning this but you just never really know until actually putting the cars in service and waiting for them to get old.
Any new car company has to learn all this from scratch. Sure, they can hire people who have worked in the car industry and they can do their best to copy industry best practices, and they can even buy all the latest commercial off-the-shelf software tools, but there's still a limit. Companies have institutional knowledge, policies and procedures, relationships between people, and habits that are hard to transfer over bit by bit to a new company. Tribal knowledge tends to be indigenous to the environment of the tribe. Companies also have critical data that they’re generally unwilling to share.
With greater design uncertainty, engineers need to apply bigger safety margins and sometimes need to add extra layers of redundancy in case of failure. All of this comes at a price: reduced vehicle performance on key design criteria like cost, range, acceleration, handling, safety, etc. Uncertainty also brings the risk of setting margins too thin and having a higher-than-anticipated failure rate in service, like Nissan's battery degradation in the first-generation Leaf, GM's spectacular f-up with the LG pouch cell partnership and Ford's melting high-current electrical contacts. In the fog of misunderstanding, mistakes happen, especially in organizations where decisions are made based on politics, deceit and confrontation instead of logic, honesty and cooperation.
Drew Baglino discussed this in his Stanford interview earlier this year, saying that a decade ago Tesla had been too pessimistic about Model S battery cell electrochemical degradation, but too optimistic about the other stuff like pack moisture sealing, battery management electronics, mechanical shock and vibration, and thermal cycling. Notably, Drew said that these things "don't show up until you've been in the field for ten years". Yikes. So even the big brains at Tesla were too conservative in some areas and too aggressive in others. It was only after years of vehicles being in the fleet and millions of cars produced that they’ve advanced this far in fixing these problems, making the cars with more reliability, more quality, and less design fat.
Tesla also gets the most data per car per unit time. because they actually had the foresight to design the car for remote data collection and cloud computing. Tesla has been putting electronic sensors on their BEVs since *2003*. One of the very first things they did as a startup was setting up vehicle data collection for trying to reverse engineer the AC Propulsion t-zero prototype. I heard Elon and a few other early Tesla employees talking about this in a panel interview from around the early Model S years (I can’t find it anymore, so no link). I think I recall Elon referring to it as trying to tease out “the ghost in the machine”, because the t-zero used custom analog power electronics and nobody really knew how the hand-crafted mule actually functioned.
All of this means Tesla alone has the luxury of running the tightest tolerances in the industry for their BEV designs, because no one has has produced 3 million BEVs over the last decade. This is like going camping in the wilderness. A novice might be a smart and conscientious planner, but their unawareness of the actual needs of the trip will inevitably result in worse selection of supplies to bring compared to a person going on the same trip who’s done it many times. The novice will bring along some stuff that’s unnecessary and not bring (or not bring enough of) other stuff that they actually do need. The expert also will have a better understanding of which equipment suppliers have the best options. The expert knows what to spend money on and what to go cheap on. The novice needs to spend more time researching and shopping and even then they will probably end up wasting money in some areas and get junky equipment for other items. The expert’s advantage is information and experience.
Novices can surpass experts in the long run. Tesla sucked at making cars 10 years ago, but that was with some prior learning on the original roadster and Tesla-level pace of innovation. This is not normal progress over the first decade of attempting to grow to being a mass manufacturer of cars. I don’t anticipate an iCar or any other competition having a meaningful negative impact on Tesla’s business for at least ten years.
Tesla’s data and expertise lets them get by with less stuff such as:
Structural material
Welds
Fasteners
Battery cell depth-of-discharge reserve
Warranty reserve
Tesla also gets performance gains, such as:
Range per kWh
Charging speed
Weight
More storage space and cabin interior space
Handling
More repeat sprints before power needs to be throttled
NVH (Noise, vibration & harshness)
Tesla's inventions compound each other's gains due to these feedback loops, augmenting Tesla's resultant lead.
Weight reduction and chassis stiffening, for example, reduces the power required to move the vehicle around, reduces NVH, and improves handling which makes the vehicle more efficient, which then enables reduction of the battery size needed for a given set of requirements for range and performance. Weight reduction also in many cases increases cabin storage space by opening up more room, as Tesla has shown with their masterful gigacasting design making for more spacious trunks and frunks. Better understanding of battery degradation and better thermal control means that a more aggressive charging curve can be allowed. And so on.
Example of tech with compound benefit:
Octovalve and integrated thermal management across all vehicle subsystems
Gigacastings with optimized new alloy
Structural battery with seats directly mounted on top
Cell-to-pack architecture
Motors best in the game according to Munro testing and cost accounting (kW/$, kW/kg, kW/cm^3)
I don't think it's physically possible for a competitor to try all of this stuff in their first BEV. They have a long road ahead of them to implement these technologies that are necessary to have a product that can compete with Tesla vehicles on specs, features and cost.
Even Tesla is still learning how to optimize their own inventions. Listen to remarks from the Q2 call:
The Rich Get Richer
All signs point towards acceleration of Tesla's pace of technological innovation. I think Tesla is in a runaway snowball effect situation now.
The EV market has an accumulative advantage dynamic with strong preferential attachment effects. Preferential attachment means a tendency within a competitive system for resources to be biased towards flowing to entities that already have more resources than other entities (i.e. "the rich get richer" / "success breeds success"). Preferential attachment was observed by Italian economist/engineer/sociologist Vilfred Pareto in his famous observation that 80% of the peas in his garden came from 20% of the plants and 80% of the wealth and land in Italy was owned by 20% of the families. The early advantage gained by some pea plants due to genetics or lucky position in the environment made them grow bigger more quickly as sprouts, and they leveraged this small advantage to consume more of the local sunshine, water and root space to grow even bigger, until a minority of plants dominated the garden. This relationship shows up in all kinds of phenomena like formation of stars and planets from dust after a supernova, crater size on the moon, frequency of words used in any language, and much more.
Preferential attachment usually results in a power law distribution, also known as a Pareto distribution. There are theoretical justifications for this and if you want to see the math I recommend reading the link. The stronger the preferential attachment effect, the steeper the Pareto curve is. Whenever there is a Pareto distribution in results of a competition, we can be pretty confident that some kind of preferential attachment effect exists.
In some cases, we observe power law rank relationships in which one or two outliers exist at the top, way off the trend line. This is called the king effect. Kings don’t conform to the statistical distribution of the rest, like how China and India have exceptionally large populations while all other nations fit neatly into a Pareto curve.
The EV industry in the US, Tesla's home turf, shows a typical Pareto distribution with one king, Tesla, which alone still holds most of the US BEV market share, and holds all of the profit. Soon enough they'll have more profit than all of the rest of the auto industry combined, including all cars, not just BEVs.
On a linear scale we can see just how far ahead Tesla is. Note that the pink colulmn is the grand total, the red column is Tesla, and the blue columns are the rest. On a logarithmic scale we can see that the power law model is a good fit, because all the data points fall appromixately in a line. All of them except Tesla, whose sales number comes in an order of magnitude higher than the power law rank relationship would predict. View attachment 850045 View attachment 850044
The dynamics that caused this result are not likely to change any time soon. The rank relationship for 2018 looks almost identical, again with Tesla an order of magnitude ahead of where the Pareto distribution of the rest of the market participants would predict Tesla to be. The numbers have gotten bigger and and the also-rans have shuffled around in the rankings, but in four years nobody has gotten any closer. In fact, if you look closely at the trend lines, Tesla’s deviation from the distribution has almost doubled since 2018, suggesting that indeed they are accumulating relative advantage over time.
I have a noob question. Is there anyone keeping track of total global deliveries/sales per car manufacturer and comparing that to Tesla? This would be a very stunning graph to follow in the coming decade, seeing Tesla rise from zero to hero.
I looked around on the internet but I find fragmented data and it is also hard to account for mergers (Stellantis for example).
I went back as far as 2017 and this is what I currently came up with:
The data behind this:
Company/Year
2017
2018
2019
2020
2021
BMW
2.030.331,00
2.494.276,00
2.520.146,00
2.324.778,00
2.521.596,00
Changan
1.759.971,00
2.003.663,00
2.314.547,00
Ford
5.953.122,00
5.734.217,00
5.385.972,00
4.231.549,00
3.942.755,00
Geely
1.245.055,00
1.500.458,00
1.361.556,00
1.320.471,00
1.328.029,00
General Motors
8.787.233,00
7.724.163,00
6.833.592,00
6.294.385,00
Honda
4.967.689,00
5.265.892,00
5.323.319,00
4.790.438,00
4.456.728,00
Hyundai Kia
3.951.176,00
7.437.209,00
7.189.893,00
6.353.514,00
6.668.037,00
Maruti Suzuki
2.891.415,00
3.212.984,00
1.563.297,00
1.457.861,00
1.652.653,00
Mazda
1.495.557,00
1.631.142,00
1.454.121,00
1.243.039,00
1.074.987,00
Mercedes
2.093.476,00
2.310.185,00
2.339.024,00
2.164.275,00
2.093.476,00
Nissan
4.834.694,00
5.653.743,00
5.176.211,00
4.029.174,00
4.064.999,00
Renault
2.275.227,00
3.883.987,00
3.749.815,00
2.949.871,00
2.689.454,00
Stellantis
8.091.825,00
6.205.996,00
6.142.200,00
Tesla
103.100,00
245.200,00
367.500,00
499.550,00
936.172,00
Toyota
7.843.423,00
10.521.134,00
10.741.556,00
9.528.753,00
9.562.783,00
Volkswagen
9.667.535,00
10.831.232,00
10.975.352,00
9.305.427,00
8.882.346,00
Before I delve deeper to go back to 2012 or I merge previous companies' delivery data (Stellantis for example) I'd like to ask if this is being recorded by anyone or if there is an internet resource for this. I had to combine this from very fragmented data. (It's a first quick draft using numbers from third party websites. If I were to double down I should go to the Investor Relations pages of each company but I don't need that amount of detail IMO).
Either way, if nothing is out there, I'm planning on adding future values to my existing data since the future data will be way more interesting for us TSLA investors then past data (= Tesla hugging the x-axis whilst the rest does whatever above it).
I have a noob question. Is there anyone keeping track of total global deliveries/sales per car manufacturer and comparing that to Tesla? This would be a very stunning graph to follow in the coming decade, seeing Tesla rise from zero to hero.
I looked around on the internet but I find fragmented data ...............
Either way, if nothing is out there, I'm planning on adding future values to my existing data since the future data will be way more interesting for us TSLA investors then past data (= Tesla hugging the x-axis whilst the rest does whatever above it).
At the beginning of each year (covering 2021, 2020, 2019) I try to crunch together a table of global annual BEV and PHEV sales by manufacturer group (e.g. VAG), and by brand (e.g. Skoda); and also of battery consumption in vehicles by both consumer (auto company) and by supplier (cell company). In order to do this I do a certain amount of model-level tracking as well. I put the results on TMC in this thread and they generally get put in the best-of thread as well. I generally do that effort in about Feb/Mar of each year for the preceding year, if that helps you look back for the relevant posts. There are a couple of commercial datasets that try to do this but most of us (inc me) don't get to see those. I also track global annual vehicle sales (all fuels), and BEV, PHEV and post those here (going back to approx 2000).
What I don't do is the intermediate level of fossil-cars/etc by manufacturer which is what you are trying to piece together. As you are finding that is quite difficult because a) some people are understandably coy for commercial reasons, b) some factories produce badged products for two different companies off one line, c) some factories, brands, etc change owners as the industry continuously restructures, d) some are white-label mfg for others (e.g. MagnaSteyr). Because of the restructuring issue it is quite difficult, and in any case I couldn't really see a burning need to do all the effort - really it is the aggregate decline that matters re dino juice; plus observing case-by-case when each major OEM goes sub-critical (my bets are on either BMW or JLR going belly-up first). So .... if you want to do this well then my advice is to carefully think through a database design before you start.
Does this help a bit ?
p.s. I give quite a lot of my sources in my posts, so find those posts ! Maybe put links to them all here to help others find them (and me)
At the beginning of each year (covering 2021, 2020, 2019) I try to crunch together a table of global annual BEV and PHEV sales by manufacturer group (e.g. VAG), and by brand (e.g. Skoda); and also of battery consumption in vehicles by both consumer (auto company) and by supplier (cell company). In order to do this I do a certain amount of model-level tracking as well. I put the results on TMC in this thread and they generally get put in the best-of thread as well. I generally do that effort in about Feb/Mar of each year for the preceding year, if that helps you look back for the relevant posts. There are a couple of commercial datasets that try to do this but most of us (inc me) don't get to see those. I also track global annual vehicle sales (all fuels), and BEV, PHEV and post those here (going back to approx 2000).
What I don't do is the intermediate level of fossil-cars/etc by manufacturer which is what you are trying to piece together. As you are finding that is quite difficult because a) some people are understandably coy for commercial reasons, b) some factories produce badged products for two different companies off one line, c) some factories, brands, etc change owners as the industry continuously restructures, d) some are white-label mfg for others (e.g. MagnaSteyr). Because of the restructuring issue it is quite difficult, and in any case I couldn't really see a burning need to do all the effort - really it is the aggregate decline that matters re dino juice; plus observing case-by-case when each major OEM goes sub-critical (my bets are on either BMW or JLR going belly-up first). So .... if you want to do this well then my advice is to carefully think through a database design before you start.
Does this help a bit ?
p.s. I give quite a lot of my sources in my posts, so find those posts ! Maybe put links to them all here to help others find them (and me)
Thanks a bunch. Will dig up your posts when I have some free time.
I understand the tendency to split up the data according to fuel type/PHEV/BEV/... but this data shows the (to me obvious) fact that ICE vehicle sales are in decline and EV sales are increasing.
The chart I'm also interested in, is an aggregate of all cars manufactured by a certain company/group (i.e. "the legacy OEMs") since I expect their sales to drop massively by 2030 whilst Tesla and for example BYD or another Chinese EV company become king of the charts.
In other words, I want to see the current "behemoths" become ghosts of their past selves in a nice chart to put on my wall .
