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Speaker 1: Hey everybody. So a few weeks ago we did a

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Speaker 1: show with ce Me about the policies put in place

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Speaker 1: to accelerate e V adoption in China. The title was

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Speaker 1: Tesla Crushing it in Car Captain Trade Check it out.

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Speaker 1: In that episode I mentioned it was a trailer, a

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Speaker 1: sort of preview for what we'd do on BNF's flags

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Speaker 1: A report on transport, the Electric Vehicle Outlook, or EVO.

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Speaker 1: As I said then, the report looks at how electrification,

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Speaker 1: shared mobility, and autonomous driving impact road transport from now

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Speaker 1: out to twenty fifty. The reports out and the time

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Speaker 1: has come. This week we're lucky to be joined by

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Speaker 1: the lead author of EVO and head of Transport for BNF,

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Speaker 1: Colin mccarricker. I won't be labor the intro too much longer.

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Speaker 1: I just want to say, come for the findings, stay

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Speaker 1: for collins insightful opinions and observations. If you follow him

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Speaker 1: on Twitter you'll know what I mean. He has a

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Speaker 1: way of cutting right to what really matters in a

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Speaker 1: way that's easy to follow. Being if you just can

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Speaker 1: get the electric Vehicle out one on BNF, go on

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Speaker 1: the Bloomber terminal and BNF dot com as a reminder

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Speaker 1: of BENF does not provide investment strategy advice, and you

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Speaker 1: can hear the full disclaimer at the end of the show.

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Speaker 1: I'm Mark Taylor and you're listening to switch down to

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Speaker 1: BENF podcast. Colin, thanks for joining. Good to be here. Mark.

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Speaker 1: Always a pleasure to join you on the program. It's

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Speaker 1: always wonderful to have you on, Colin. We missed our

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Speaker 1: January ten Things to Watch this this year, and we'll

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Speaker 1: make up for it here. We will. We'll have a

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Speaker 1: good chat. I'm looking forward to it. Mark. So back

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Speaker 1: when I was an analyst and I was editing, you know,

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Speaker 1: my team's work and and the like, I always gave

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Speaker 1: the suggestion when I was editing to avoid what I

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Speaker 1: would call since the Dawn of Time statements you know,

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Speaker 1: and often begin with something like that. It was kind

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Speaker 1: of off putting, in a little bit too big for

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Speaker 1: the reports we were writing. But in Evil the Electric

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Speaker 1: Vehicle Outlook, you rightly start with quote mobility is at

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Speaker 1: the core of modern civilization and the way people in

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Speaker 1: goods move impacts many aspects of life. So definitely that's true.

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Speaker 1: This report is huge and far reaching. Can you tell

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Speaker 1: us a bit about it and the objectives behind it. Yeah,

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Speaker 1: happy too, And I like the leading of of that

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Speaker 1: opening line, and I did think about whether we shouldn't

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Speaker 1: fluid that, but I do think it's important when you're

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Speaker 1: talking about road transport just to recognize how personal it is. Right,

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Speaker 1: the power system isn't that personal for a lot of people.

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Speaker 1: They just want the lights to come on and and

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Speaker 1: it's as long as that happens there, okay, And as

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Speaker 1: long as it's not too expensive, it's okay. Mobility is

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Speaker 1: personal in a way that most other areas of the

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Speaker 1: energy transition and things that that being NEF works on

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Speaker 1: sometimes are not. So what is our electric vehicle outlook?

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Speaker 1: The kind of high level summary is that this is

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Speaker 1: our outlook for all of road transport, looking at how

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Speaker 1: people and goods move from now all the way out

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Speaker 1: to and then this year we actually extended it out

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Speaker 1: to to try and look a little bit at net

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Speaker 1: zero scenarios and what that means. And we can talk

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Speaker 1: about that in a bit, but that's kind of the

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Speaker 1: high level the high level picture. Despite the name, it's

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Speaker 1: not just an outlook for electric vehicles. It's an outlook

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Speaker 1: for everything to do with how people and goods move

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Speaker 1: on on roads around the world in different countries, and

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Speaker 1: what is the main objective with it. One of the

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Speaker 1: things we're trying to do is really investigate different scenarios

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Speaker 1: for how this might all play out, but also stitched

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Speaker 1: together a picture that draws in the breadth of research

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Speaker 1: that b an e F does. So it's we have

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Speaker 1: a team that's called the Electric Vehicle Team. This isn't

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Speaker 1: just the output of that team. It's the output of

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Speaker 1: that team, plus our intelligent Mobility team, plus the oil team,

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Speaker 1: plus the energy storage and batteries team, plus the metals

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Speaker 1: and mining team. So a lot of what we're trying

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Speaker 1: to do is present an integrated house view from Bloomberg

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Speaker 1: an EF about different possibilities for how how road transport

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Speaker 1: might might evolve. And this is actually the sixth iteration

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Speaker 1: we've done of this report. We started it back in

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Speaker 1: and really back then it was only oil companies kind

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Speaker 1: of commenting on the future of road transport, and in

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Speaker 1: our view, they were dramatically downplaying the changes that were

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Speaker 1: afoot that we were seeing on improvements in lithium ion

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Speaker 1: batteries and rapid drops in cost. And even though those

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Speaker 1: early stages, surging demand and real real consumer interest and

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Speaker 1: in electric vehicles. So at that point we thought, look,

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Speaker 1: there needs to be an independent voice digging into the

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Speaker 1: long term outlook for road transport and playing out what

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Speaker 1: it means across all these different areas that that we

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Speaker 1: were looking at, And that's kind of how the project

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Speaker 1: was was born, and it's evolved a lot since then.

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Speaker 1: Each year we're adding new segments. Each each year we're

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Speaker 1: adding new countries, we're looking at different impacts. So it

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Speaker 1: keeps evolving because we need to stay on top of

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Speaker 1: what types of questions are clients are asking us and

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Speaker 1: what types of things need answers. There's some things that

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Speaker 1: we know more about than we need five or six

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Speaker 1: years about, and others that are that are kind of

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Speaker 1: still unknowns. So it's really about kind of tying all

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Speaker 1: that stuff together, having an independent voice, and then playing

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Speaker 1: that out in across different across different areas. What were

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Speaker 1: you trying to answer this year that's new that you

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Speaker 1: weren't trying to answer in previous years. The big one

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Speaker 1: this year is our our net zero scenarios. So generally

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Speaker 1: what we've had is kind of our I won't call

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Speaker 1: it a base case view, because in economic modeling circles

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Speaker 1: and forecasting circles, base case is kind of this thing

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Speaker 1: people don't like to say. We call it our economic

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Speaker 1: transition scenario, which assumes no new policies are implemented. It's

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Speaker 1: a market lad transition. That's what we've generally done in

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Speaker 1: the past, sort of a techno economic analysis of adoption

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Speaker 1: potential in different segments. So the big difference this year

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Speaker 1: is we did a net zero scenario where we said, okay,

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Speaker 1: what do you have to do to get road transport

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Speaker 1: direct road transport emissions all the way to zero by

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Speaker 1: twenty fifty And it's important to note there that that's

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Speaker 1: direct tail pipe emissions. There are still possible upstream emissions

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Speaker 1: from generating electricity and and potentially generating hydrogen. Those are

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Speaker 1: covered in other areas of NF long term forecasting work.

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Speaker 1: So long term out looks like our New Energy or

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Speaker 1: New Energy outlook. So that's the big change this year

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Speaker 1: is to sort of say, let's do a bit more

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Speaker 1: of an exercise in working backwards to say what speed

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Speaker 1: do different segments have to go at, what has to

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Speaker 1: happen over the next five years, ten years, twenty years,

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Speaker 1: thirty years to stay on track for this net zero

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Speaker 1: scenario by and then look at policy or sorry by

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Speaker 1: and then look at policy recommendations that can help get

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Speaker 1: you closer to that. So before we get into those

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Speaker 1: scenarios a bit more and into the results of the report,

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Speaker 1: let's get into the how a little bit more. Thinking back,

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Speaker 1: one of my favorite episodes we've done actually was with

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Speaker 1: Ian Berryman and it was called Modeling the Energy Future, Ants,

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Speaker 1: Birds and Doctor Strange, And in that episode we just

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Speaker 1: talked about the only thing we talked about was his

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Speaker 1: approach to modeling Energy Forecast Model NEPHEM, the model that

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Speaker 1: powers the New Energy Outlook. So I know EVO is

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Speaker 1: a similarly complex task that you just mentioned with all

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Speaker 1: these teams collaborating and trying to get a coherent view

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Speaker 1: on something on the road Transport future. Can you tell

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Speaker 1: us a bit more about the approach and how you

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Speaker 1: actually got this thing done. One of the big things

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Speaker 1: we have to do is kind of start early. So

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Speaker 1: we we kind of start at the end of the

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Speaker 1: previous year saying what are all the things that we

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Speaker 1: want to include in it, and then work for a

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Speaker 1: big chunk of the first four or five six months

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Speaker 1: of one on it and to put it all together.

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Speaker 1: So there's there's definitely an element of planning and thinking

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Speaker 1: ahead about what you're gonna do. The summary is that

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Speaker 1: it's actually slightly different what we do depending on each segment.

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Speaker 1: So some segments have a very different architecture of the

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Speaker 1: way you model uptaking them. For example, when we're looking

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Speaker 1: at commercial vehicle it's really driven by total cost of

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Speaker 1: ownership of different competing drivetrain technologies. When we're modeling passenger vehicles,

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Speaker 1: it's much more driven by upfront prices and where did

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Speaker 1: those get to. But the one common theme that we

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Speaker 1: have across all of what we do is that we

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Speaker 1: actually start with again come back coming back to what

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Speaker 1: we open with, how do people in goods move? So

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Speaker 1: when when we try and forecast or do our outlooks

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Speaker 1: for the amount of vehicles that are going to be sold,

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Speaker 1: we actually start with kilometers of mobility how much do

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Speaker 1: people literally how much do people move around in a

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Speaker 1: different country, and freight time kilometers for how much goods

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Speaker 1: move around, And then we look at all the factors

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Speaker 1: that impact that over time. UH and those can be

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Speaker 1: some things that have been consistent or throughout the last

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Speaker 1: twenty years or other things that that are just starting

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Speaker 1: to come in. So something like e commerce changes the

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Speaker 1: distribution of kilometers of freight between whether they're heavier trucks

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Speaker 1: or lighter trucks, you might get more last mild delivery

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Speaker 1: going on, and that you just start to see that

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Speaker 1: in the data. So basically with with starting with kilometers,

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Speaker 1: it gives us a really good baseline for this is

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Speaker 1: how people in goods move, and then from there we

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Speaker 1: determine how many vehicles you need in order to satisfy

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Speaker 1: that demand for mobility for people and goods, and then

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Speaker 1: from fleet we get to sales. So a lot of

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Speaker 1: the and I think that's kind of something a bit

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Speaker 1: different about the way we approach it, is that a

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Speaker 1: lot of these a lot of the other exercise we've

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Speaker 1: seen generally think of sales as just sales, but but

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Speaker 1: people don't buy a car just to have a car.

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Speaker 1: It's it's to serve a purpose and that purpose is mobility.

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Speaker 1: So we kind of start with mobility and then work

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Speaker 1: our way down to sales, and then within sales in

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Speaker 1: each country, and each year we're creating an adoption outlook

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Speaker 1: for different drive trains. So the competing mix of different

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Speaker 1: drive trains can be is quite different between different segments.

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Speaker 1: So in trucks you might have C and G playing

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Speaker 1: a role, compressed natural gas playing a role, whereas in

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Speaker 1: the passenger cars it's really much more about um internal combustion, hybrid,

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Speaker 1: plug in hybrid, battery electric and maybe a bit a

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Speaker 1: few will sell that. We're a bit pessimistic on that.

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Speaker 1: So in each year, in each country, in each segment,

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Speaker 1: we're building a drive train outlook, and that factors in

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Speaker 1: all these different things around economics, but also other factors,

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Speaker 1: and there's a lot about the way we kind of

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Speaker 1: tie that all together in the long term outlook part.

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Speaker 1: And and again the exact mechanics differ a bit depending

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Speaker 1: on the segment you're looking at. So it actually does

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Speaker 1: sound a bit like power that you start with demand, right,

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Speaker 1: you know, in power, you'd start with demand as well,

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Speaker 1: and then you build some power plants to meet that

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Speaker 1: demand sales or drive trains, and then you start selling megawatts, right,

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Speaker 1: so you get individual unit sales. I guess one of

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Speaker 1: the things that was kind of, to be honest, controversial

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Speaker 1: when we started doing this was that you could use

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Speaker 1: consumer adoption modeling trends to actually forecast what was going

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Speaker 1: to happen. When we started doing it in twenty six

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Speaker 1: going and presenting a vast diffusion curve saying look it

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Speaker 1: is going to follow and ask curve that was quite

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Speaker 1: We've got a lot of skeptical looks at the time.

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Speaker 1: Now everyone kind of accepts that, accepts that, at least

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Speaker 1: on the passenger vehicle side, this probably will be a

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Speaker 1: tech knowledge adoption story, and it's just people debate over

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Speaker 1: which speed and in which segments and how fast it

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Speaker 1: goes in which country, but that that that that changeover

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Speaker 1: is coming. So when we look at that part, we

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Speaker 1: try and say, okay, here's here's what's happened in places

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Speaker 1: where adoption has gone quickly, and here's the parameters that

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Speaker 1: lead to that. And then we look at how that

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Speaker 1: might play out in other countries, and then we add

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Speaker 1: some kind of gating factors, and these are sometimes controversial.

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Speaker 1: So one of the things we do, for example, is

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Speaker 1: when we're again in the passenger vehicle segment, we have

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Speaker 1: a higher faster adoption rate for people who live in

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Speaker 1: single detached homes than in people who live in high

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Speaker 1: rise multi dwelling units. Because we think people who have

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Speaker 1: easy access to home charging infrastructure will probably go electric faster.

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Speaker 1: Now that it might not be the case. A government

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Speaker 1: may build its way out of that constraint and just

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Speaker 1: blanket a country and chargers, and then the adoption rate

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Speaker 1: might be the same. But those are some of the

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Speaker 1: things that we can play around within our model and

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Speaker 1: say do we think that's a thing, that we think

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Speaker 1: that's not a thing. I think it's a thing. I mean,

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Speaker 1: I am I'm living proof. Last year I bought a

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Speaker 1: car and I didn't buy one because I can't get

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Speaker 1: a you know, I live in a row house on

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Speaker 1: a on a London street, right, so I don't have

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Speaker 1: a charging option. And the deal was that the next

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Speaker 1: car we get will be an electric one because the

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Speaker 1: assumption is that there will be a charging network by then, hopefully.

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Speaker 1: I'm sure that's the calculus for a lot of people. Yeah,

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Speaker 1: And I think we're just getting to that point where,

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Speaker 1: I mean, you have more conversations about this with people, right,

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Speaker 1: that's a double edged sword. If you've been working on

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Speaker 1: this stuff for a decade, it means everybody wants to

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Speaker 1: chat about it, but it also means that you end

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Speaker 1: up talking about your work a lot at dinner, which

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Speaker 1: which maybe isn't a good thing. As you said, it

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Speaker 1: matters to everybody, right, So even if somebody is not

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Speaker 1: necessarily interested in the S curve, they're interested in their

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Speaker 1: mode of transportation. And then I guess whether that's even

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Speaker 1: public transportation two wheelers, cars, trucks, you, I mean, you

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Speaker 1: put all of it in. There. Is there different curves

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Speaker 1: for different types of technologies that you're seeing, Yeah, there is,

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Speaker 1: and and so for example, plug in hybrids in the

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Speaker 1: in the passenger vehicle segment, more and more they look

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Speaker 1: like a compliance strategy primarily by automakers to meet tightening

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Speaker 1: fuel economy regulations. And that's really why they've surged in Europe.

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Speaker 1: There about over half of all the plug in vehicle

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Speaker 1: sales in Europe right now are are our plug in hybrids.

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Speaker 1: The other half better electrics, of course, and that's really

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Speaker 1: because Europe tightened the screws on on the CEO two

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Speaker 1: regulations for cars this year or last year rather, and

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Speaker 1: it's a bit more again this year, and that has

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Speaker 1: really mend automakers who are skeptical of fully electric technology

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Speaker 1: or who don't have their platforms fully ready to go

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Speaker 1: are pushing a lot of plug in hybrids into the market,

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Speaker 1: but the dynamics of that are are kind of much

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Speaker 1: more predictable based on policy than they are or earth. Sorry,

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Speaker 1: the uptake of that technology is much more predicated on

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Speaker 1: on policy than it is on other sort of more

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Speaker 1: organic consumer demand factors. And that's that's kind of evident

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Speaker 1: in the data. So you don't get the same kind

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Speaker 1: of s curve for for plug in hybrids as you

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Speaker 1: do for better electrics. One, because they never get cheaper,

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Speaker 1: They never get cheaper on and upfront basis than comparable

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Speaker 1: internal combustion engine vehicles because they still have a combustion

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Speaker 1: engine on board. And in our model, which is looking

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Speaker 1: for the kind of cheapest path to do that, it

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Speaker 1: doesn't build a lot of those beyond what is required

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Speaker 1: by current compliance with with existing policies. So that's kind

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Speaker 1: of an example of a technology that adoption is going up,

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Speaker 1: but it's not going up. It's we don't think it's

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Speaker 1: going up on the same kind of ask curve that

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Speaker 1: you're going to get with fully electric vehicles. Makes sense, Yeah,

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Speaker 1: And I mean they just don't seem very interesting, right,

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Speaker 1: Like they don't seem like a big enough change to

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Speaker 1: really be all that enticing apart from a policy measure

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Speaker 1: or a policy incentive. That's just me speaking, And I

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Speaker 1: think for some consumers they are actually a good choice

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Speaker 1: if with the right needs. Maybe you just only want

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Speaker 1: to go on the odd long trip out out of

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Speaker 1: the weekend on the weekend, and and they're good fit

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Speaker 1: in that case. I think our our skepticism is more

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Speaker 1: that will automakers really build something that if there isn't

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Speaker 1: a policy push to do so, that can never get

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Speaker 1: cheaper than an internal combustion engine vehicle, because you do

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Speaker 1: have a lot of added costs. And so increasingly what

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Speaker 1: we're seeing is it automakers kind of they're going to

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Speaker 1: sell a bunch of peat plug in hybrids in the

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Speaker 1: next little while. But then the strategy starts to get

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Speaker 1: a bit more, a bit like a barbell. You go

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Speaker 1: fully electric, and then you do a bunch of mild hybrids,

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Speaker 1: non pluggable the lowest level of electrification you can, because

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Speaker 1: that's quite a cheap way to get the rest of

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Speaker 1: the emissions of the rest of your fleet down, and

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Speaker 1: then you sell a fair amount of fully electric vehicles

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Speaker 1: as well. This is actually one of the fascinating things that,

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Speaker 1: to be honest, makes this out look really hard to

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Speaker 1: do is that, for one, on the passenger vehicle side anyway,

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Speaker 1: right now, in some places you're in the middle of

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Speaker 1: a steep part of the curve. Right This isn't theoretical anymore.

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Speaker 1: In Germany, more than of auto sales have a plug

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Speaker 1: right now. China the latest data in June here around

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Speaker 1: fift that's the world's largest auto market. You're really hitting

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Speaker 1: kind of the steep part of the curve. So one

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Speaker 1: of the things that makes it tricky there is that

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Speaker 1: it's already kind of happening. This isn't something way in

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Speaker 1: the future. It's kind of happening now. The other thing

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Speaker 1: is course, is that there's still a lot of policy

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Speaker 1: in the mix. Like we're waiting kind of on tenter

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Speaker 1: hook right now to see what the Biden administration does

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Speaker 1: with fuel economy regulations in the US, because depending on

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Speaker 1: what they do with those, it could go faster or slower.

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Speaker 1: So this is where when you're doing these long term

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Speaker 1: out looks, you have to be really clear what the

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Speaker 1: exercises and what we're trying to do is saying here's

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Speaker 1: the policy or here's the outlook with no new policies,

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Speaker 1: and then here's the net zero outlook. If you want

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Speaker 1: to get to that, here's how how much further and

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Speaker 1: faster has to go. But we recognize that in the

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Speaker 1: near term there is going to be more policy, there

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Speaker 1: are going to be more changes, There's gonna be a

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Speaker 1: lot of different things that happened. So I think that's

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Speaker 1: maybe something we haven't explained as well as we could

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Speaker 1: have in the past, that that economic transition scenario assumes

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Speaker 1: no new policies, and therefore when there is a new policy,

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Speaker 1: it might change the curve. So an example I always

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Speaker 1: kind of give is, look, if you were building an

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Speaker 1: outlook model in the US last year and you somehow

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Speaker 1: knew that Biden was going to win the election, great

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Speaker 1: good on you. But we didn't know that, and we're

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Speaker 1: not in the business of a forecast election. So we

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Speaker 1: had to take sort of here's what the current policy is,

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Speaker 1: and here's what what that means for adoption. So that's

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Speaker 1: kind of one of the tricky things both to do

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Speaker 1: and to kind of communicate what it means overall. Okay,

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Speaker 1: so many different directions we could go down. There, so

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Speaker 1: many roads we could go down. Huh No, pun intended.

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Speaker 1: So much of our language is based on metaphors around transport.

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Speaker 1: Once you start to see them, notice them, you can't

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Speaker 1: stop seeing them everywhere. Oh sure, okay, so let's actually

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Speaker 1: do get into the results for a second, and then

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Speaker 1: we can go down a few different roads about you

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Speaker 1: know what some of the different markets are doing, some

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Speaker 1: of the policies that are in place, etcetera. But as

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Speaker 1: you said, your team has been doing this for six

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Speaker 1: years now. Is there anything that surprised you from doing

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Speaker 1: this year's EVO that you hadn't seen in previous years.

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Speaker 1: I think doing this net zero scenario was a bit

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Speaker 1: of an eye opener. Even been working on the stuff

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Speaker 1: for a long time, and you see how fast it's

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Speaker 1: all happening, and it feels like, wow, we're we're in

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Speaker 1: the middle of a huge transition. Things are really going

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Speaker 1: But at the same time, doing the net zero scenario

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Speaker 1: reminds you that it's still all has to go a

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Speaker 1: lot faster, and I think that was probably the biggest surprise.

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Speaker 1: I mean, you sort of know that intellectually, but then

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Speaker 1: you spend three months kind of in the data and

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Speaker 1: you're like, well, we we have to as a like globally,

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Speaker 1: you would have to phase out combustion vehicle sales um

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Speaker 1: completely to stay on track for the net zero scenario,

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Speaker 1: and even to do that, you need to do a

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Speaker 1: lot of early retirements of older vehicles in to even

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Speaker 1: do that. If you wanted to and if you wanted

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Speaker 1: to get to net zero without doing early retirements, you

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Speaker 1: almost have to stop selling to internal combustion engine vehicles

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Speaker 1: tomorrow because some vehicles that are sold now stay on

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Speaker 1: the road for a very long time. So so there's

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Speaker 1: just some reality of spending that time in the data

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Speaker 1: around the net zero scenario that makes you go, wow.

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Speaker 1: Road transport is especially personal. Road transport is probably one

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Speaker 1: of the areas that, um, we're most optimistic are in

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Speaker 1: the in the energy transition, because you have the solutions

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Speaker 1: today that can get you most of the way there

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Speaker 1: and yet still hard. So I think that's important kind

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Speaker 1: of kind of context in all of this that that

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Speaker 1: was maybe a bit surprising, again even though you might

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Speaker 1: intellectually know it. The other one that's kind of related

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Speaker 1: is that we did some investigations this year around reducing

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Speaker 1: demand from mobility. Everyone talks about changing over vehicles and

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Speaker 1: most of the government programs are aimed at at that,

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Speaker 1: at having different options to do the same amount of

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Speaker 1: driving and this sort of thing. But we are starting

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Speaker 1: to see some governments saying, actually, no, we need to

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Speaker 1: tackle how much people are driving around and we need

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Speaker 1: to reduce that. And that's through a combination of active travel,

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Speaker 1: more dense cities, better public transit. And I guess one

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Speaker 1: of the other kind of surprises that I'd like to

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Speaker 1: go into a bit more in the future, and and

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Speaker 1: and the sustainable transport advocates of course have been all

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Speaker 1: over this for a very long time, but is just

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Speaker 1: that if you can find a way to reduce demand

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Speaker 1: even a little bit, it makes the job of getting

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Speaker 1: to net zero a lot easier. So that means you

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Speaker 1: want to promote all those things. You want to promote

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Speaker 1: more cycling, you want to promote more public trends that

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Speaker 1: you want to promote more density and urban areas. You're

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Speaker 1: gonna need all of that, and you're also going to

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Speaker 1: need millions of electric vehicles in order to to stay

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Speaker 1: on track for the net zero scenario. So we're given

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Speaker 1: the sort of timing that we're all talking about all

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Speaker 1: around these climate targets. Were in the phase where you

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Speaker 1: have to do all of the above and you have

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Speaker 1: to do all of it very quickly, and that was

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Speaker 1: definitely one of the things that really stood out from

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Speaker 1: this year's exercise. The other thing that was interesting, again

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Speaker 1: from from the net zero scenario stuff, is that some

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Speaker 1: segments are are closer to on track than others. So

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Speaker 1: the main segments that we look at our passenger cars,

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Speaker 1: light commercial vehicles, medium commercial vehicles, heavy commercial vehicles, buses,

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Speaker 1: and two and three wheelers. And if you look at

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Speaker 1: two and three wheelers and buses, you're actually already at

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Speaker 1: pretty high rates of adoption of electric vehicles in those segments,

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Speaker 1: and those ones are already pretty close to on track

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Speaker 1: for the net zero scenarios. So two and three wheelers

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Speaker 1: globally of all vehicles sales last year were already electric.

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Speaker 1: Uh and bus is I think we're at almost most

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Speaker 1: of that is led out of China, but there's also

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Speaker 1: quite a bit of activity spreading in other countries as well.

434
00:20:08,960 --> 00:20:11,800
Speaker 1: So that was kind of another surprise is that, oh, actually,

435
00:20:11,800 --> 00:20:14,399
Speaker 1: in some of these segments of road transport, we're not

436
00:20:14,480 --> 00:20:17,240
Speaker 1: too far off the net zero scenario, and in others

437
00:20:17,240 --> 00:20:20,240
Speaker 1: were miles off, so the ones like heavy commercial vehicles,

438
00:20:20,520 --> 00:20:22,960
Speaker 1: the transition there has not even started and there's a

439
00:20:22,960 --> 00:20:25,160
Speaker 1: long way to go. That was really noticeable last time,

440
00:20:25,520 --> 00:20:27,960
Speaker 1: well last time we were in Shanghai for the b

441
00:20:28,040 --> 00:20:33,040
Speaker 1: NF Shanghai Summit. In they're electric scooters everywhere. It's just really, really,

442
00:20:33,040 --> 00:20:35,920
Speaker 1: really prevalent. I just gonna say that that I totally,

443
00:20:36,200 --> 00:20:39,000
Speaker 1: I totally totally agree with you that once you start

444
00:20:39,040 --> 00:20:41,040
Speaker 1: to look at how far there is to go, you

445
00:20:41,160 --> 00:20:45,120
Speaker 1: realize that we haven't even really started yet. I did

446
00:20:45,119 --> 00:20:47,760
Speaker 1: just back of the envelope calculations, you know, the day

447
00:20:48,440 --> 00:20:51,760
Speaker 1: looking at our New Energy Outlook scenarios, right, and I

448
00:20:51,840 --> 00:20:54,760
Speaker 1: just used some you know, average numbers for how big

449
00:20:54,800 --> 00:20:57,639
Speaker 1: a wind or solar farm would have to be or

450
00:20:57,680 --> 00:21:00,200
Speaker 1: would be. And it took me in the huns and

451
00:21:00,280 --> 00:21:02,520
Speaker 1: hundreds of thousands of projects to get to the point

452
00:21:02,560 --> 00:21:06,040
Speaker 1: that we lay out in the New Energy Outlook NEO.

453
00:21:06,400 --> 00:21:09,000
Speaker 1: And it makes you realize, Okay, we're not really even

454
00:21:09,040 --> 00:21:12,080
Speaker 1: started yet. So yeah, definitely a long way to go. Yeah,

455
00:21:12,080 --> 00:21:15,080
Speaker 1: And I think I think these long term targets are

456
00:21:16,080 --> 00:21:18,399
Speaker 1: it's good that they're stretched targets, right. We want to

457
00:21:18,520 --> 00:21:21,800
Speaker 1: keep pushing as to what's possible. And and to be honest,

458
00:21:21,840 --> 00:21:24,040
Speaker 1: this is kind of new turf for us at b

459
00:21:24,080 --> 00:21:26,560
Speaker 1: an F. We've we've spent much more time saying here's

460
00:21:26,560 --> 00:21:29,159
Speaker 1: what's happening, here's what we think it means, here's what

461
00:21:29,240 --> 00:21:31,280
Speaker 1: we think a sensible strategy is, and a lot less

462
00:21:31,280 --> 00:21:35,560
Speaker 1: time on what should happen, right because we're not advocates

463
00:21:35,560 --> 00:21:39,240
Speaker 1: were we're industry analysts. But this is kind of where

464
00:21:39,280 --> 00:21:42,879
Speaker 1: these long term exercises start to blend the two, because

465
00:21:42,920 --> 00:21:45,840
Speaker 1: you spend enough time in the data and you just

466
00:21:45,880 --> 00:21:48,000
Speaker 1: feel like, okay, well, then if we're going to do this, this,

467
00:21:48,000 --> 00:21:50,800
Speaker 1: this is what should happen, this is what has to happen.

468
00:21:51,280 --> 00:21:54,480
Speaker 1: And you find yourself using language that would be much

469
00:21:54,480 --> 00:21:58,680
Speaker 1: more associated with sort of activists or or advocates. And

470
00:21:59,240 --> 00:22:02,399
Speaker 1: I find that in an interesting sort of transition and

471
00:22:02,480 --> 00:22:05,080
Speaker 1: in in my analysts career to talk about that sort

472
00:22:05,119 --> 00:22:08,439
Speaker 1: of stuff. It also makes me uncomfortable sometimes too, because

473
00:22:09,280 --> 00:22:12,240
Speaker 1: it's not what I've thought my role is in the past.

474
00:22:13,359 --> 00:22:16,919
Speaker 1: I mean, we're at a juncture where, uh, where you

475
00:22:16,960 --> 00:22:19,000
Speaker 1: do have to accelerate all this stuff where you are

476
00:22:19,440 --> 00:22:21,080
Speaker 1: and even if you do accelerate all this stuff, you're

477
00:22:21,080 --> 00:22:23,800
Speaker 1: gonna deal with some pretty negative impacts from from climate

478
00:22:23,840 --> 00:22:27,040
Speaker 1: and we're we're seeing that right now. But that tension

479
00:22:27,119 --> 00:22:29,600
Speaker 1: is getting strong between are you are you an analyst

480
00:22:29,640 --> 00:22:32,359
Speaker 1: or are you advocating for a technology? And and I

481
00:22:32,680 --> 00:22:34,520
Speaker 1: think that's sort of one of the things you just

482
00:22:34,560 --> 00:22:36,800
Speaker 1: have to sit with as you're doing these long term outlooks.

483
00:22:36,920 --> 00:22:39,400
Speaker 1: I think you can be both, right. I actually really

484
00:22:39,440 --> 00:22:43,800
Speaker 1: listened to Um part of Fatty Bureau of the IDA

485
00:22:43,960 --> 00:22:47,119
Speaker 1: his speech from earlier last was it this year? Earlier

486
00:22:47,160 --> 00:22:49,240
Speaker 1: this year? Yeah, where he said that you know, new

487
00:22:49,680 --> 00:22:52,320
Speaker 1: exploration for for fossil fields just kind of has to stop, right,

488
00:22:52,800 --> 00:22:55,679
Speaker 1: and the I as you know, analysts but also advocates.

489
00:22:55,720 --> 00:22:57,480
Speaker 1: But really I think you can you could just rest

490
00:22:57,520 --> 00:23:01,000
Speaker 1: on saying if you want this to happen, you know,

491
00:23:01,080 --> 00:23:03,520
Speaker 1: for example, in net zero, then this has to happen. Right.

492
00:23:03,520 --> 00:23:05,480
Speaker 1: It doesn't have to be like we have to do this,

493
00:23:05,600 --> 00:23:07,480
Speaker 1: there's no necessary you don't necessarily have to say it

494
00:23:07,480 --> 00:23:09,000
Speaker 1: like that, but it's just if you want this, then

495
00:23:09,040 --> 00:23:11,439
Speaker 1: you gotta do this exactly. And that's that's how we

496
00:23:11,520 --> 00:23:13,480
Speaker 1: framed all of this, is look, if you if if

497
00:23:13,520 --> 00:23:15,639
Speaker 1: we take these targets seriously and we want to hit them.

498
00:23:15,680 --> 00:23:17,439
Speaker 1: Here's the trajectory you have to be on. And just

499
00:23:17,480 --> 00:23:18,840
Speaker 1: to give you an example, one of the things we

500
00:23:18,880 --> 00:23:20,680
Speaker 1: tried to do to highlight that is we said, okay,

501
00:23:20,680 --> 00:23:22,840
Speaker 1: what has to happen to passenger vehicle sales to stay

502
00:23:22,840 --> 00:23:25,879
Speaker 1: on track for the net zero scenario. They have to

503
00:23:25,880 --> 00:23:29,040
Speaker 1: get to about six fully electric share by So what

504
00:23:29,160 --> 00:23:31,480
Speaker 1: does that? What does that conceptually mean? How do you

505
00:23:31,520 --> 00:23:34,399
Speaker 1: try to bring that make that real? Norway, very small

506
00:23:34,440 --> 00:23:37,200
Speaker 1: market that's lad on evs, has gone from about three

507
00:23:37,280 --> 00:23:40,560
Speaker 1: or four percent to about six fully electric share over

508
00:23:40,800 --> 00:23:42,879
Speaker 1: roughly a ten year period. And what we're saying is

509
00:23:42,880 --> 00:23:44,840
Speaker 1: that the global auto market, which was about four percent

510
00:23:44,840 --> 00:23:46,719
Speaker 1: of sales are electric last year, has to go from

511
00:23:46,720 --> 00:23:49,080
Speaker 1: about four to about six over the next tent. So

512
00:23:49,119 --> 00:23:51,440
Speaker 1: the entire global auto market has to follow the same

513
00:23:51,440 --> 00:23:54,720
Speaker 1: trajectory over the next ten years that Norway followed over

514
00:23:54,760 --> 00:23:57,199
Speaker 1: the last tent. That's gonna be hard there. There are

515
00:23:57,200 --> 00:23:58,800
Speaker 1: going to be challenged with that. There are reasons to

516
00:23:58,840 --> 00:24:01,520
Speaker 1: be optimistic about that, things like the vehicles are a

517
00:24:01,560 --> 00:24:04,040
Speaker 1: lot better, there's more charging infrastructure, There's all sorts of

518
00:24:04,359 --> 00:24:06,240
Speaker 1: things that you can be optimistic about that. There's other

519
00:24:06,240 --> 00:24:08,120
Speaker 1: reasons to say, well, look, nor we had a very

520
00:24:08,119 --> 00:24:10,680
Speaker 1: specific tax structure. It also has a lot of single

521
00:24:10,720 --> 00:24:12,840
Speaker 1: detached homes and a and a really big spread between

522
00:24:12,880 --> 00:24:15,120
Speaker 1: the cost of petrol and the cost of electricity that's

523
00:24:15,160 --> 00:24:17,680
Speaker 1: quite favorable to ev s. That's hard to replicate elsewhere.

524
00:24:17,960 --> 00:24:19,280
Speaker 1: But so those are some of the types of things

525
00:24:19,280 --> 00:24:22,400
Speaker 1: we're trying to say. Okay, let's not just talk about

526
00:24:23,160 --> 00:24:26,080
Speaker 1: our net zero targets framed as let's talk about what

527
00:24:26,119 --> 00:24:27,560
Speaker 1: you have to do in the near term to stay

528
00:24:27,600 --> 00:24:29,960
Speaker 1: on track for those targets. And that leads you to

529
00:24:30,000 --> 00:24:32,600
Speaker 1: some of these more easy to relate to examples that

530
00:24:32,600 --> 00:24:34,880
Speaker 1: are in the report as well. Now for a very

531
00:24:34,880 --> 00:24:41,840
Speaker 1: short break, stay with us. So do you think net

532
00:24:41,920 --> 00:24:44,879
Speaker 1: zero is really the motivation for deployment? Like, I mean,

533
00:24:44,960 --> 00:24:47,960
Speaker 1: let's talk about deployment, right, So, like, are better cars

534
00:24:48,320 --> 00:24:50,880
Speaker 1: more of a motivator or is it charging network more

535
00:24:50,920 --> 00:24:52,959
Speaker 1: of a motivator? Or is it simply policy? You know?

536
00:24:53,040 --> 00:24:55,360
Speaker 1: And what are some of the things that other markets

537
00:24:55,400 --> 00:24:57,480
Speaker 1: can do, maybe that don't have a lot of single

538
00:24:57,520 --> 00:25:02,040
Speaker 1: family homes in the near term to encourage deployment. Yeah,

539
00:25:02,119 --> 00:25:06,320
Speaker 1: this kind of policy versus consumer demand poll is a

540
00:25:06,400 --> 00:25:08,840
Speaker 1: question that comes up a lot, and the detractors for

541
00:25:09,080 --> 00:25:13,320
Speaker 1: electric vehicle adoption will say, it's all just policy, it's

542
00:25:13,320 --> 00:25:16,600
Speaker 1: just pushed onto the market by governments, and it's it's

543
00:25:16,680 --> 00:25:21,040
Speaker 1: just it's yeah, there there isn't organic consumer demand. The

544
00:25:21,520 --> 00:25:23,560
Speaker 1: people who are really pro would often say, no, it's

545
00:25:23,560 --> 00:25:25,960
Speaker 1: all consumer demand and it's going to take off either way,

546
00:25:26,040 --> 00:25:28,680
Speaker 1: no matter what happens with policy. I think it's it's

547
00:25:28,720 --> 00:25:30,480
Speaker 1: it's a mix of those two. Write all the people

548
00:25:30,520 --> 00:25:33,000
Speaker 1: who drive evs love them, but also where there is

549
00:25:33,000 --> 00:25:35,960
Speaker 1: no policy support, there are no EV sales. Generally, to

550
00:25:36,040 --> 00:25:38,159
Speaker 1: come back to kind of the question, it is going

551
00:25:38,240 --> 00:25:41,000
Speaker 1: to take off because it's a cooler, better car. I

552
00:25:41,040 --> 00:25:43,960
Speaker 1: don't think there's very many things that have consumer products

553
00:25:43,960 --> 00:25:47,560
Speaker 1: that have taken off entirely based on their environmental attributes. Right.

554
00:25:47,640 --> 00:25:49,760
Speaker 1: That can get you a certain percentage of buyers, but

555
00:25:49,800 --> 00:25:51,960
Speaker 1: it can't get you all of them. Yeah, and it

556
00:25:52,000 --> 00:25:54,080
Speaker 1: probably can't get you more than four or five. It's

557
00:25:54,080 --> 00:25:57,359
Speaker 1: hard to get everyone on board with something purely based

558
00:25:57,359 --> 00:25:59,879
Speaker 1: on environmental metrics. But so so it is going to

559
00:26:00,040 --> 00:26:01,520
Speaker 1: They are going to take off because they're a better car,

560
00:26:01,600 --> 00:26:04,080
Speaker 1: and that's not a future statement. They're kind of getting

561
00:26:04,119 --> 00:26:06,240
Speaker 1: there now. But you do have to do a lot

562
00:26:06,280 --> 00:26:08,960
Speaker 1: to help enable that, right, And one of the things,

563
00:26:08,960 --> 00:26:13,160
Speaker 1: just as an example, I mentioned China sales data right now.

564
00:26:13,200 --> 00:26:16,080
Speaker 1: So China just in June about fifteen percent of sales

565
00:26:16,080 --> 00:26:18,439
Speaker 1: fully elect or fifteen percent of sales were electric. That's

566
00:26:18,480 --> 00:26:20,960
Speaker 1: in the world's largest autom market, a remarkable leap. Part

567
00:26:21,000 --> 00:26:23,560
Speaker 1: of that is driven because China started building charging infrastructure

568
00:26:23,560 --> 00:26:27,760
Speaker 1: way ahead of demand. So in December, China build over

569
00:26:27,800 --> 00:26:31,160
Speaker 1: a hundred thousand chargers, which is more than the size

570
00:26:31,160 --> 00:26:34,560
Speaker 1: of the entire US network built over twenty years. Depending

571
00:26:34,560 --> 00:26:35,879
Speaker 1: on when you start, want to start the clock in

572
00:26:35,920 --> 00:26:38,280
Speaker 1: one month. And so what they're doing is saying, look,

573
00:26:38,800 --> 00:26:41,560
Speaker 1: we we recognize as coming, so let's let's build the

574
00:26:41,600 --> 00:26:43,800
Speaker 1: network for it. And now they start seeing starting to

575
00:26:43,840 --> 00:26:45,760
Speaker 1: see much higher levels of adoption. So it's this kind

576
00:26:45,800 --> 00:26:48,199
Speaker 1: of if you build it, they will come. And that

577
00:26:48,359 --> 00:26:51,320
Speaker 1: is very true of charging infrastructure. But you need to

578
00:26:51,400 --> 00:26:54,680
Speaker 1: have the in some cases government support or certainly a

579
00:26:54,720 --> 00:26:57,000
Speaker 1: lot of buy in from from different groups in order

580
00:26:57,040 --> 00:26:58,840
Speaker 1: to get that level of build out. But they're also

581
00:26:58,880 --> 00:27:00,680
Speaker 1: kind of doucing it a bit. Right. We had seen

582
00:27:00,760 --> 00:27:04,639
Speaker 1: me on last week talking about some of the policy

583
00:27:04,800 --> 00:27:06,720
Speaker 1: mechanisms they got in place, like the cap and trade

584
00:27:06,760 --> 00:27:08,119
Speaker 1: for cars, what do they call it, the n e

585
00:27:08,200 --> 00:27:11,920
Speaker 1: V program. Basically that puts the onus on the manufacturers

586
00:27:11,960 --> 00:27:15,960
Speaker 1: to sell evs in that market. Is that working? Is

587
00:27:15,960 --> 00:27:17,879
Speaker 1: it going in other markets as well? Yeah, and I

588
00:27:17,880 --> 00:27:20,119
Speaker 1: didn't mean to imply that what's happening in China's entirely

589
00:27:20,200 --> 00:27:22,880
Speaker 1: organic consumer demand. Definitely, the policy still playing a big role.

590
00:27:23,240 --> 00:27:26,480
Speaker 1: China's fuel economy regulations, the ny V credit system, the

591
00:27:26,560 --> 00:27:28,920
Speaker 1: city level restrictions, those are also all a big part

592
00:27:28,960 --> 00:27:31,800
Speaker 1: of what's driving the Chinese market. The interesting thing is

593
00:27:31,800 --> 00:27:36,120
Speaker 1: is that's allowed there to be a number of uh, startup,

594
00:27:36,320 --> 00:27:38,119
Speaker 1: very well funded startups, but I guess we still call

595
00:27:38,200 --> 00:27:41,320
Speaker 1: them start up Chinese auto manufacturers that are producing models

596
00:27:41,320 --> 00:27:43,600
Speaker 1: that do seem to have some real organic consumer demand

597
00:27:43,640 --> 00:27:46,720
Speaker 1: to them, which is getting getting quite interesting. So this

598
00:27:46,760 --> 00:27:48,200
Speaker 1: is where it is. It is kind of a mix.

599
00:27:48,240 --> 00:27:50,240
Speaker 1: It is kind of a mix of the cooler car

600
00:27:50,760 --> 00:27:53,879
Speaker 1: that that that people love, but also the policy support

601
00:27:53,880 --> 00:27:57,200
Speaker 1: to help enable the supply to get there. There's a

602
00:27:57,200 --> 00:27:59,080
Speaker 1: podcast I listened to. I won't mention the name, but

603
00:27:59,400 --> 00:28:03,479
Speaker 1: it's fantas Sick, and the host often talks about the

604
00:28:03,560 --> 00:28:06,960
Speaker 1: pending Apple car and how he thinks that's gonna, you know,

605
00:28:07,080 --> 00:28:09,080
Speaker 1: just take over the market when it comes out. You know,

606
00:28:09,160 --> 00:28:11,480
Speaker 1: I don't know either way, But like, is there a

607
00:28:11,480 --> 00:28:15,480
Speaker 1: place for startup e V? Maybe you know, Apple would

608
00:28:15,520 --> 00:28:17,040
Speaker 1: be a startup in this case, but is there a

609
00:28:17,080 --> 00:28:20,160
Speaker 1: case where newcomers in this market? There are a lot

610
00:28:20,200 --> 00:28:22,440
Speaker 1: of newcomers, and in my view, there are too many

611
00:28:22,440 --> 00:28:24,480
Speaker 1: car companies. In my view, there were probably too many

612
00:28:24,480 --> 00:28:27,199
Speaker 1: car companies before all this happened. If you look at

613
00:28:27,200 --> 00:28:28,879
Speaker 1: how a lot of them just kind of replicate the

614
00:28:28,920 --> 00:28:31,720
Speaker 1: same the same R and D spending, And I wouldn't

615
00:28:31,720 --> 00:28:34,840
Speaker 1: say that's an especially efficient allocation of capital. You have.

616
00:28:35,440 --> 00:28:37,119
Speaker 1: As I said, you probably have too many car companies

617
00:28:37,119 --> 00:28:38,920
Speaker 1: before all this hit. Now you have have way too many,

618
00:28:39,320 --> 00:28:42,880
Speaker 1: I think. But having said that that those startups and

619
00:28:42,960 --> 00:28:45,440
Speaker 1: challengers are a big part of what is pushing the

620
00:28:45,480 --> 00:28:48,280
Speaker 1: market forward. I think the window on the startups is

621
00:28:48,280 --> 00:28:50,160
Speaker 1: closing a bit. So a bunch of them have made

622
00:28:50,160 --> 00:28:54,320
Speaker 1: it through. So obviously Tesla is very established now, other

623
00:28:54,320 --> 00:28:57,600
Speaker 1: ones like Chinese ones like Neo, x, Pung b y D,

624
00:28:58,560 --> 00:29:01,320
Speaker 1: upcoming ones like Rivian and Lucid. There's kind of a

625
00:29:01,360 --> 00:29:04,280
Speaker 1: top tier of these startups, and again I wouldn't put

626
00:29:04,280 --> 00:29:06,760
Speaker 1: Tesla in that category the very established. Now there's kind

627
00:29:06,800 --> 00:29:08,800
Speaker 1: of a top tier of this next group of startups,

628
00:29:09,000 --> 00:29:10,680
Speaker 1: then there's going to be a large list of kind

629
00:29:10,680 --> 00:29:13,520
Speaker 1: of also rans. I think if you're entering the v

630
00:29:13,640 --> 00:29:15,960
Speaker 1: market now, you have to be entering it with a

631
00:29:16,080 --> 00:29:18,960
Speaker 1: very different angle, which which I think would be Apple's angle.

632
00:29:19,000 --> 00:29:21,440
Speaker 1: They would they wouldn't try and manufacture their own vehicles,

633
00:29:21,440 --> 00:29:24,080
Speaker 1: they'd rely on external party. There would be some sort

634
00:29:24,120 --> 00:29:28,320
Speaker 1: of major software differentiation, whether that's some combination of connectivity

635
00:29:28,360 --> 00:29:31,240
Speaker 1: on autonomous driving, you would need something quite special, I

636
00:29:31,240 --> 00:29:33,520
Speaker 1: think to differentiate. I think this there was this there

637
00:29:33,600 --> 00:29:37,000
Speaker 1: is this window around electrification, but it's closing fast as

638
00:29:37,040 --> 00:29:39,840
Speaker 1: the established automakers really ramp up their spending and start

639
00:29:39,840 --> 00:29:43,120
Speaker 1: cranking out the models in the next few years. Okay, now,

640
00:29:43,760 --> 00:29:46,440
Speaker 1: speaking of also rans, we've got the Olympics going on

641
00:29:46,480 --> 00:29:49,120
Speaker 1: in Japan, and I know japan and Japanese companies have

642
00:29:49,160 --> 00:29:51,240
Speaker 1: had high hopes and put a lot of investment into

643
00:29:51,280 --> 00:29:55,960
Speaker 1: hydrogen fuel sale vehicles, but in the report they don't

644
00:29:55,960 --> 00:29:57,719
Speaker 1: really show up in a big way. Why is that?

645
00:29:58,000 --> 00:30:00,360
Speaker 1: There's been a lot of discussions on this over the years,

646
00:30:00,680 --> 00:30:02,560
Speaker 1: and I won't try and kind of rehash them all

647
00:30:03,160 --> 00:30:06,320
Speaker 1: over over here. If you want to UM, if you

648
00:30:06,360 --> 00:30:07,800
Speaker 1: want to have if you want to hear them all,

649
00:30:07,880 --> 00:30:10,600
Speaker 1: you can just go on Twitter and say something controversial

650
00:30:10,640 --> 00:30:12,800
Speaker 1: and people will pounce on it on either side and

651
00:30:12,800 --> 00:30:14,719
Speaker 1: you can get a great back and forth in your

652
00:30:14,720 --> 00:30:18,280
Speaker 1: Twitter mentions. But UM a couple of reasons they don't

653
00:30:18,280 --> 00:30:21,240
Speaker 1: play a big role in our economic transition scenario. One

654
00:30:21,240 --> 00:30:24,600
Speaker 1: of them is around the availability of green hydrogen. So

655
00:30:24,680 --> 00:30:26,360
Speaker 1: bn F has done a lot of work we on

656
00:30:26,640 --> 00:30:30,360
Speaker 1: green on hydrogen. We do think hydrogen produce for renewables

657
00:30:30,400 --> 00:30:32,160
Speaker 1: is going to get a lot cheaper over the next

658
00:30:32,400 --> 00:30:35,000
Speaker 1: few years, in the next decades, but it's still going

659
00:30:35,040 --> 00:30:36,960
Speaker 1: to be a scarce resource. There's still going to be

660
00:30:37,040 --> 00:30:41,360
Speaker 1: competition for its supply. And I think you can make

661
00:30:41,400 --> 00:30:44,959
Speaker 1: a case that you should use that green hydrogen in

662
00:30:45,200 --> 00:30:49,800
Speaker 1: areas where you don't have a viable alternative for decarbonization.

663
00:30:50,440 --> 00:30:53,120
Speaker 1: So that might be things like fertilizer, it might be

664
00:30:53,160 --> 00:30:57,800
Speaker 1: things like um shipping by ammonia, it might be aviation,

665
00:30:58,320 --> 00:31:01,280
Speaker 1: it might be heavy industry. You do have a route

666
00:31:01,280 --> 00:31:04,000
Speaker 1: to de carbonization for for passenger vehicles, so putting it

667
00:31:04,000 --> 00:31:06,640
Speaker 1: into passenger vehicles. I don't think it is a great

668
00:31:06,720 --> 00:31:09,280
Speaker 1: use of a scarce resource. So that's kind of the

669
00:31:09,400 --> 00:31:13,240
Speaker 1: from this perspective of like efficiency and designing a system

670
00:31:13,320 --> 00:31:15,960
Speaker 1: and all this sort of stuff. But of course there's

671
00:31:15,960 --> 00:31:19,120
Speaker 1: nobody orchestrating everything around how this plays out around the world.

672
00:31:19,800 --> 00:31:23,720
Speaker 1: The other reason is much more around just the numbers

673
00:31:23,800 --> 00:31:27,080
Speaker 1: about where we are today. So if you look at

674
00:31:27,840 --> 00:31:29,840
Speaker 1: the amount of fuel cell vehicles on the road today,

675
00:31:29,840 --> 00:31:31,880
Speaker 1: if you are to guest mark, there's a there's one

676
00:31:31,880 --> 00:31:34,000
Speaker 1: point to billion cars in the world. How many fuel

677
00:31:34,040 --> 00:31:39,160
Speaker 1: cell vehicles do you think there are? Mandod Yeah, order magnitude,

678
00:31:39,200 --> 00:31:43,160
Speaker 1: So all across all vehicle types, cumulative sales are around

679
00:31:43,160 --> 00:31:48,200
Speaker 1: thirty thousand. The actual fleet is smaller than that, so

680
00:31:48,320 --> 00:31:50,240
Speaker 1: not not not bad as as a as a guess,

681
00:31:50,680 --> 00:31:53,440
Speaker 1: the actual fleet is around thirty thousand, or the cumuli

682
00:31:53,440 --> 00:31:56,480
Speaker 1: of sales around thirty thousand, and the first generation of

683
00:31:56,520 --> 00:31:58,360
Speaker 1: Maras from Toyota, a lot of those are getting taken

684
00:31:58,360 --> 00:32:00,120
Speaker 1: back off Ley, so some are under thirty thou And

685
00:32:00,920 --> 00:32:03,560
Speaker 1: so if you just stay with that number for a second,

686
00:32:03,600 --> 00:32:06,640
Speaker 1: and again let's think about spending lots of time in

687
00:32:06,680 --> 00:32:09,400
Speaker 1: the numbers and orders of magnitude and these sorts of things.

688
00:32:10,120 --> 00:32:12,120
Speaker 1: If the number of fuel cell vehicles on the road

689
00:32:12,560 --> 00:32:17,719
Speaker 1: doubled every eighteen months, every eighteen months all the way

690
00:32:17,720 --> 00:32:21,760
Speaker 1: out to they would still only be about one to

691
00:32:21,840 --> 00:32:23,680
Speaker 1: one and a half percent of all the vehicles on

692
00:32:23,680 --> 00:32:27,320
Speaker 1: the road. So even if you believe that scenario and

693
00:32:27,360 --> 00:32:30,240
Speaker 1: it's really hard to double the fleet every eighteen months,

694
00:32:30,280 --> 00:32:33,240
Speaker 1: that would be incredibly rapid growth. But the starting point

695
00:32:33,280 --> 00:32:37,080
Speaker 1: really matters. And again, when we're looking at these these

696
00:32:37,200 --> 00:32:40,440
Speaker 1: kind of time scales were on you need you need

697
00:32:40,480 --> 00:32:42,440
Speaker 1: to somehow go even faster than that for them to

698
00:32:42,480 --> 00:32:45,040
Speaker 1: make a material impact in the passenger vehicle segment. So

699
00:32:45,080 --> 00:32:49,160
Speaker 1: there's all these other arguments about UH infrastructure and efficiency

700
00:32:49,200 --> 00:32:50,880
Speaker 1: and all those sorts of things that are hashed out

701
00:32:50,920 --> 00:32:54,520
Speaker 1: at nauseum elsewhere, But I think just the raw numbers

702
00:32:54,560 --> 00:32:56,560
Speaker 1: part is something that's underappreciated, is that even in the

703
00:32:56,600 --> 00:32:58,880
Speaker 1: scenario where these grow really rapidly, they're not a big

704
00:32:58,920 --> 00:33:01,320
Speaker 1: part of vehicles on the road, at least in the

705
00:33:01,320 --> 00:33:04,400
Speaker 1: passenger vehicle segment. And then there's this other thing around

706
00:33:04,640 --> 00:33:07,719
Speaker 1: There isn't a similar parallel industry that you saw with

707
00:33:07,960 --> 00:33:10,479
Speaker 1: lithium ion batteries in the form of consumer electronics that's

708
00:33:10,560 --> 00:33:13,280
Speaker 1: driving down the cost of fuel cell vehicle stacks, So

709
00:33:13,600 --> 00:33:15,160
Speaker 1: they don't play much of a role at all on

710
00:33:15,200 --> 00:33:18,240
Speaker 1: the passenger vehicle side in our in our outlook, they

711
00:33:18,320 --> 00:33:20,640
Speaker 1: might play a role in the heavy and heavy duty

712
00:33:20,640 --> 00:33:24,720
Speaker 1: long haul vehicles in the net zero scenario. So that's

713
00:33:24,760 --> 00:33:26,480
Speaker 1: kind of where we see. There's still a bit of

714
00:33:26,480 --> 00:33:30,560
Speaker 1: a technology question, but we're actually getting more optimistic on

715
00:33:30,600 --> 00:33:32,440
Speaker 1: the role the batteries are going to play in even

716
00:33:32,440 --> 00:33:37,000
Speaker 1: in heavy duty long haul. So definitely a participation award there,

717
00:33:38,520 --> 00:33:41,400
Speaker 1: not necessarily a medal. Okay, So where might we be

718
00:33:41,440 --> 00:33:44,440
Speaker 1: wrong in EVO? What are some of the potential blind

719
00:33:44,480 --> 00:33:48,160
Speaker 1: spots that came up. Yeah, one of them, as I mentioned,

720
00:33:48,200 --> 00:33:51,800
Speaker 1: is trucks. So there's a lot of different technologies competing

721
00:33:51,920 --> 00:33:55,320
Speaker 1: for for the heavy duty truck and parts. So we

722
00:33:55,440 --> 00:33:59,000
Speaker 1: think increasingly that fully electric trucks are going to going

723
00:33:59,040 --> 00:34:01,760
Speaker 1: to play a big role, and and some combination of

724
00:34:01,920 --> 00:34:05,880
Speaker 1: just fully electric or maybe overhead lines or overhead catinary

725
00:34:05,920 --> 00:34:08,839
Speaker 1: lines or battery swapping for trucks, those are all sort

726
00:34:08,840 --> 00:34:11,520
Speaker 1: of in the running, but that those that that can

727
00:34:11,560 --> 00:34:13,279
Speaker 1: play quite a big role. We might be wrong there,

728
00:34:13,320 --> 00:34:15,719
Speaker 1: there's this is at the very beginning of that transition.

729
00:34:15,719 --> 00:34:18,200
Speaker 1: There's a lot of money flying around, so that could

730
00:34:18,239 --> 00:34:21,120
Speaker 1: still we could still be wrong there. Another one is

731
00:34:21,160 --> 00:34:27,080
Speaker 1: that is autonomous vehicles, so and shared mobility more generally. Um,

732
00:34:27,120 --> 00:34:29,000
Speaker 1: this is still kind of a wild card. So we

733
00:34:29,080 --> 00:34:32,200
Speaker 1: do think shared mobility goes up a lot over the

734
00:34:32,440 --> 00:34:36,400
Speaker 1: over the next years. So right now, about three to

735
00:34:36,480 --> 00:34:40,920
Speaker 1: four of all kilometers traveled in cars anyway are in

736
00:34:40,960 --> 00:34:44,280
Speaker 1: some sort of shared mobility application, so that includes taxis

737
00:34:44,280 --> 00:34:46,280
Speaker 1: and things like that, and in some countries it's much higher,

738
00:34:46,440 --> 00:34:48,279
Speaker 1: but globally it's about that. We think that goes up

739
00:34:48,280 --> 00:34:53,680
Speaker 1: to about but there's a lot of unknowns in that.

740
00:34:53,760 --> 00:34:57,560
Speaker 1: Right if you really get fully autonomous vehicles that the

741
00:34:57,640 --> 00:34:59,880
Speaker 1: sort of robotaxi scenario, it could go up a lot

742
00:35:00,000 --> 00:35:02,760
Speaker 1: more than that. Um, we've been kind of skeptical about

743
00:35:02,800 --> 00:35:05,200
Speaker 1: that and and sort of said no, that's much more

744
00:35:05,239 --> 00:35:07,920
Speaker 1: of a late thirties story. Though you are going to

745
00:35:07,960 --> 00:35:10,800
Speaker 1: get some interesting city level experiments in the Indian interim.

746
00:35:11,360 --> 00:35:15,000
Speaker 1: Once you talk about global car markets and global energy picture,

747
00:35:15,440 --> 00:35:18,200
Speaker 1: it's probably not in the next ten years. But again

748
00:35:18,239 --> 00:35:20,399
Speaker 1: we might be wrong there, and that that's an interesting one,

749
00:35:20,840 --> 00:35:22,400
Speaker 1: and then the last one I would just say is

750
00:35:22,440 --> 00:35:26,080
Speaker 1: that it's very hard to know or quantify the pushback

751
00:35:26,200 --> 00:35:29,120
Speaker 1: that you might get on some of these transitions. So

752
00:35:30,440 --> 00:35:33,120
Speaker 1: if you think about I think about the last couple

753
00:35:33,120 --> 00:35:37,359
Speaker 1: of electoral cycles in the US where coal became this

754
00:35:37,440 --> 00:35:40,439
Speaker 1: really big issue, right like it became a sort of mark,

755
00:35:40,760 --> 00:35:43,520
Speaker 1: a signaling device and part of the kind of culture

756
00:35:43,560 --> 00:35:46,279
Speaker 1: wars and and all this sort of stuff. And I

757
00:35:46,320 --> 00:35:48,440
Speaker 1: think the day I'm this isn't my field, but I

758
00:35:48,440 --> 00:35:50,680
Speaker 1: think the data says that's somewhere around the number of

759
00:35:50,680 --> 00:35:52,520
Speaker 1: people who work in the US coal industry similar to

760
00:35:52,560 --> 00:35:55,200
Speaker 1: the number of people who work at Arby's, a mid

761
00:35:55,239 --> 00:35:58,279
Speaker 1: size fast food fast food chain in the US, not

762
00:35:58,480 --> 00:36:02,280
Speaker 1: a huge employer. A lot more people work in oil

763
00:36:02,320 --> 00:36:05,160
Speaker 1: and gas, and a lot more people work in in

764
00:36:05,160 --> 00:36:08,479
Speaker 1: in in different parts of the internal combustion engine value chain,

765
00:36:09,200 --> 00:36:12,880
Speaker 1: so in the supply chain. So there is going to

766
00:36:12,920 --> 00:36:15,080
Speaker 1: be pushback against a bunch of this stuff, and it's

767
00:36:15,120 --> 00:36:18,880
Speaker 1: just a question of what form it takes, how strong

768
00:36:18,920 --> 00:36:22,520
Speaker 1: it is, how long it lasts, and that's those are

769
00:36:22,560 --> 00:36:24,560
Speaker 1: things that are hard hard to quantify for us. We

770
00:36:24,600 --> 00:36:27,360
Speaker 1: don't assume anything on that right now. We don't assume

771
00:36:27,360 --> 00:36:29,759
Speaker 1: there's a big backlash or anything like that, because we

772
00:36:29,800 --> 00:36:33,400
Speaker 1: assume that the number of people who are driving electric

773
00:36:33,480 --> 00:36:36,439
Speaker 1: vehicles is they're enjoying their purchase and they become part

774
00:36:36,440 --> 00:36:38,920
Speaker 1: of the ones who are supporting that transition. But the

775
00:36:38,960 --> 00:36:41,200
Speaker 1: reality is this stuff may be messy in the interim.

776
00:36:41,520 --> 00:36:43,680
Speaker 1: You are both our outlooks in both the scenarios that

777
00:36:43,719 --> 00:36:47,480
Speaker 1: we run. Oil demand peaks within the ties and then

778
00:36:47,520 --> 00:36:50,920
Speaker 1: starts to decline. The politics of what happens then is

779
00:36:50,960 --> 00:36:53,919
Speaker 1: probably going to get quite complicated. And I think that's

780
00:36:53,960 --> 00:36:56,759
Speaker 1: something that we just don't know exactly how that's going

781
00:36:56,800 --> 00:36:59,200
Speaker 1: to play out, but we're watching it carefully. So that's

782
00:36:59,239 --> 00:37:01,799
Speaker 1: kind of another mind spot is that this is a

783
00:37:01,840 --> 00:37:05,919
Speaker 1: big transition involving big industries. The auto industry. Auto sales

784
00:37:05,920 --> 00:37:09,040
Speaker 1: are a couple of trillion dollars a year, Oil and

785
00:37:09,080 --> 00:37:12,759
Speaker 1: gas another big industry. How is that going to play out?

786
00:37:12,800 --> 00:37:15,480
Speaker 1: And I think I think you'd be sort of foolish

787
00:37:15,520 --> 00:37:17,560
Speaker 1: to think it's all just going to go very very smoothly.

788
00:37:17,640 --> 00:37:20,919
Speaker 1: I think we're we're going to have some there's gonna

789
00:37:20,920 --> 00:37:22,920
Speaker 1: be some battles there, and and and we don't know

790
00:37:22,960 --> 00:37:27,040
Speaker 1: exactly what's going to come from those. So will your

791
00:37:27,120 --> 00:37:29,560
Speaker 1: analysis be to show up some of those blind spots

792
00:37:29,560 --> 00:37:31,160
Speaker 1: to you know, factor in some of the battles that

793
00:37:31,239 --> 00:37:35,520
Speaker 1: might take place, or what are your plans to change

794
00:37:35,719 --> 00:37:38,760
Speaker 1: in the next iteration of this report? Yeah, I think unfortunately,

795
00:37:38,800 --> 00:37:40,520
Speaker 1: some of those blind spots are just gonna sit as

796
00:37:40,520 --> 00:37:42,560
Speaker 1: blind spots. I don't think this time next year we're

797
00:37:42,560 --> 00:37:45,240
Speaker 1: going to have a hugely better view on exact timelines

798
00:37:45,280 --> 00:37:48,040
Speaker 1: of a v S or how what what shapes some

799
00:37:48,080 --> 00:37:51,759
Speaker 1: pushback might might take. But I can say that we

800
00:37:51,800 --> 00:37:54,520
Speaker 1: want to start doing more on the roadmap for net zero.

801
00:37:54,680 --> 00:37:57,840
Speaker 1: So not just saying globally, here's what has to happen,

802
00:37:57,880 --> 00:37:59,960
Speaker 1: but start saying on a country basis, here's what has

803
00:38:00,000 --> 00:38:02,239
Speaker 1: to happen. Because our net zero scenario is actually a

804
00:38:02,719 --> 00:38:05,840
Speaker 1: global one, whereas the the other scenario and the report

805
00:38:05,920 --> 00:38:08,239
Speaker 1: is a country by country one built bottom up. So

806
00:38:08,280 --> 00:38:10,479
Speaker 1: we want to start doing a roadmap to net zero

807
00:38:10,560 --> 00:38:14,160
Speaker 1: four different countries and with specific policy recommendations on how

808
00:38:14,160 --> 00:38:16,440
Speaker 1: to get there. And then we also want to do

809
00:38:16,600 --> 00:38:20,040
Speaker 1: more on infrastructure costs. Right now, we have some high

810
00:38:20,120 --> 00:38:23,799
Speaker 1: level conclusions on the amount of investment needed in infrastructure,

811
00:38:24,239 --> 00:38:27,239
Speaker 1: but we want to do more on different deployment models, um,

812
00:38:27,280 --> 00:38:30,560
Speaker 1: different support models, because increasingly that's kind of one of

813
00:38:30,560 --> 00:38:32,680
Speaker 1: the areas that's really coming into focus as it becomes

814
00:38:32,680 --> 00:38:35,000
Speaker 1: clear that the demand is probably there, the cars are

815
00:38:35,040 --> 00:38:37,640
Speaker 1: probably there, the economics are getting good, all this sort

816
00:38:37,640 --> 00:38:40,080
Speaker 1: of stuff, Um, we want to zoom in on those

817
00:38:40,080 --> 00:38:42,759
Speaker 1: parts that still have some uncertainty around them. So that's

818
00:38:42,800 --> 00:38:45,239
Speaker 1: that's still around the infrastructure side, and that seems to

819
00:38:45,280 --> 00:38:47,359
Speaker 1: make a lot of sense with Top twenty six coming up.

820
00:38:47,400 --> 00:38:51,239
Speaker 1: You know, you have all these countries making pledges or not,

821
00:38:51,560 --> 00:38:53,560
Speaker 1: and you want to have a bit more clarity on

822
00:38:53,800 --> 00:38:56,879
Speaker 1: the country level. It seems yeah, definitely. You know, since

823
00:38:56,920 --> 00:39:00,759
Speaker 1: since we missed our ten predictions this year, is there

824
00:39:00,800 --> 00:39:03,080
Speaker 1: anything that we should be looking for, anything that you're

825
00:39:03,120 --> 00:39:08,600
Speaker 1: looking for? In h two of we're on pace for

826
00:39:08,640 --> 00:39:11,520
Speaker 1: a record year on ev adoption, So we're just kind

827
00:39:11,520 --> 00:39:13,680
Speaker 1: of watching the numbers there and I think you're gonna

828
00:39:13,800 --> 00:39:17,000
Speaker 1: probably exceed our expectations again for this year and probably

829
00:39:17,000 --> 00:39:21,560
Speaker 1: have over five million v sold. So that's that's important.

830
00:39:21,600 --> 00:39:24,040
Speaker 1: We just crossed one percent of all vehicles in the

831
00:39:24,040 --> 00:39:27,080
Speaker 1: world being electric, which is also important. One of the

832
00:39:27,120 --> 00:39:29,239
Speaker 1: things that I'm I'm kind of watching that I think

833
00:39:29,640 --> 00:39:31,759
Speaker 1: is going to be really neat in the next a

834
00:39:31,840 --> 00:39:34,160
Speaker 1: little more than just the next six months. But what

835
00:39:34,320 --> 00:39:37,520
Speaker 1: happens with um some of these Chinese ev companies that

836
00:39:37,560 --> 00:39:40,360
Speaker 1: are trying to sell levis in other markets outside of

837
00:39:40,400 --> 00:39:42,359
Speaker 1: their own, outside of their home market as well, so

838
00:39:42,400 --> 00:39:44,960
Speaker 1: some of them starting to export to Europe. And what

839
00:39:45,080 --> 00:39:48,839
Speaker 1: that's doing is kind of keeping established automakers from just

840
00:39:48,920 --> 00:39:51,480
Speaker 1: treating evs as a compliance only tool because there's these

841
00:39:51,520 --> 00:39:54,440
Speaker 1: other sort of pressure of someone else coming in and and saying, well,

842
00:39:54,600 --> 00:39:56,839
Speaker 1: I'm I'm willing to sell these things. I'm and I'm

843
00:39:56,840 --> 00:39:58,839
Speaker 1: going to take market share if you if you don't

844
00:39:59,239 --> 00:40:01,960
Speaker 1: ramp up your effort. So I think that I think

845
00:40:02,000 --> 00:40:05,880
Speaker 1: what that signals is that the competitive dynamics are getting interesting,

846
00:40:06,200 --> 00:40:10,680
Speaker 1: because for a while, some automakers were sort of saying, no,

847
00:40:10,760 --> 00:40:13,120
Speaker 1: this isn't the direction we're heading. That's kind of all gone.

848
00:40:13,160 --> 00:40:16,160
Speaker 1: Now everybody's saying, there, look, our our future is is electric.

849
00:40:16,320 --> 00:40:18,719
Speaker 1: It's just all a question of segments and timings, and

850
00:40:18,760 --> 00:40:21,280
Speaker 1: that's where you start to get much more interesting competitive dynamics.

851
00:40:21,280 --> 00:40:23,560
Speaker 1: So forward, for example, coming out and saying the F

852
00:40:23,640 --> 00:40:27,040
Speaker 1: one fifty lightning the base competitive base price is actually

853
00:40:27,040 --> 00:40:30,319
Speaker 1: pretty competitive with with the with the base price of

854
00:40:30,320 --> 00:40:33,640
Speaker 1: of a normal F one fifty in the US. That's

855
00:40:33,640 --> 00:40:35,560
Speaker 1: an example that they're saying, no, we're going to defend

856
00:40:35,640 --> 00:40:38,080
Speaker 1: market share in the full size pickup segments so that

857
00:40:38,120 --> 00:40:41,520
Speaker 1: electrification doesn't take anything away from our our our real

858
00:40:41,560 --> 00:40:44,479
Speaker 1: cash cow there. And again that's just those things about

859
00:40:44,560 --> 00:40:47,479
Speaker 1: Chinese evs, your Chinese automakers trying to enter Europe forward,

860
00:40:47,520 --> 00:40:49,960
Speaker 1: defending market share. It just shows that you're getting to

861
00:40:49,960 --> 00:40:52,239
Speaker 1: the next phase of adoption where it's much more about

862
00:40:52,320 --> 00:40:57,120
Speaker 1: competitive dynamics automaker strategies and less questions about oh do

863
00:40:57,200 --> 00:40:59,319
Speaker 1: people want these are not? And I think that's sort

864
00:40:59,360 --> 00:41:01,000
Speaker 1: of the one of the air is that we're we're

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00:41:01,000 --> 00:41:04,000
Speaker 1: pretty interested in. And then one other thing I'm kind

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00:41:04,000 --> 00:41:07,240
Speaker 1: of watching is is at b n F, we're also

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00:41:07,280 --> 00:41:10,319
Speaker 1: expanding our our scope of our transport team coverage, so

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00:41:10,800 --> 00:41:14,279
Speaker 1: we're doing more now on on shipping and aviation, so

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00:41:14,320 --> 00:41:17,200
Speaker 1: we're starting to look more at what are the pathways

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00:41:17,200 --> 00:41:20,319
Speaker 1: around decarbonizing some of these other parts of the transport ecosystem,

871
00:41:20,360 --> 00:41:24,120
Speaker 1: and and I think most of those are still much

872
00:41:24,160 --> 00:41:26,680
Speaker 1: further behind where we are on a road road transport,

873
00:41:26,920 --> 00:41:29,480
Speaker 1: but there are still really interesting things happening. So we're

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00:41:29,480 --> 00:41:33,480
Speaker 1: tracking everything from procurement of electric aircraft to the types

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00:41:33,520 --> 00:41:36,799
Speaker 1: of shipping vessels that are being procured, and that's that's

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00:41:36,800 --> 00:41:38,239
Speaker 1: going to be something we're keeping a close eye on

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00:41:38,280 --> 00:41:41,080
Speaker 1: in the next six eight months as well. One final question,

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00:41:41,280 --> 00:41:44,239
Speaker 1: along with the predictions, give me your take. Are you

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00:41:44,320 --> 00:41:47,399
Speaker 1: more or less optimistic on decarbonizing transport than you were

880
00:41:47,400 --> 00:41:50,560
Speaker 1: in the past. I think I'm much more optimistic on

881
00:41:51,480 --> 00:41:54,560
Speaker 1: the speed of adoption of some of these alternative drive trains.

882
00:41:54,560 --> 00:41:57,280
Speaker 1: Things are going really fast. There's a lot of reasons

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00:41:57,280 --> 00:42:01,640
Speaker 1: to be very optimistic on on that. I think I'm

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00:42:01,680 --> 00:42:05,880
Speaker 1: also more aware of the sheer scale of the challenge

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00:42:05,920 --> 00:42:08,120
Speaker 1: than I than I was in the past. And again,

886
00:42:08,160 --> 00:42:10,400
Speaker 1: digging into that data on the net Serah scenario shows

887
00:42:10,440 --> 00:42:13,000
Speaker 1: you that, yeah, you can be really optimistic about it

888
00:42:13,040 --> 00:42:15,240
Speaker 1: happening fast, and it probably has to happen even faster

889
00:42:15,320 --> 00:42:17,760
Speaker 1: than than you thought to stay on track for that scenario.

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00:42:17,880 --> 00:42:21,760
Speaker 1: So my optimism waxes and wanes a bit. It probably

891
00:42:21,760 --> 00:42:23,560
Speaker 1: depends a bit on whether I've had two cups of

892
00:42:23,560 --> 00:42:25,920
Speaker 1: coffee or on one when you ask me that question.

893
00:42:26,320 --> 00:42:28,439
Speaker 1: But yeah, I think I'm more optimistic on the speed

894
00:42:28,480 --> 00:42:31,439
Speaker 1: of adoption, but more aware of just how how big

895
00:42:31,440 --> 00:42:33,120
Speaker 1: the system is and how hard how long it takes

896
00:42:33,120 --> 00:42:35,680
Speaker 1: to change. Colin, always a pleasure having you on. We

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00:42:35,680 --> 00:42:38,040
Speaker 1: look forward to have many back soon. Great Thanks Mark.

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Speaker 1: This week's show was produced by Eva Gonzalez Visla and

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00:42:47,920 --> 00:42:50,920
Speaker 1: edited by Rex Warner of great Stoke Media. BLOOMBERGINNYA is

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00:42:50,960 --> 00:42:53,520
Speaker 1: a service provided by Bloomberg Finance LP and its avilion.

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00:42:53,760 --> 00:42:56,480
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00:42:56,520 --> 00:43:00,239
Speaker 1: as investment advice, investment recommendation, or a recommendation as to

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00:43:00,400 --> 00:43:02,959
Speaker 1: an investment or other strategy. Bloomberg an e F should

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00:43:03,000 --> 00:43:05,600
Speaker 1: not be considered as information sufficient upon which to base

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00:43:05,640 --> 00:43:09,160
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00:43:09,200 --> 00:43:12,200
Speaker 1: its affiliates makes any representation or warranty as to the

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00:43:12,239 --> 00:43:15,440
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00:43:15,520 --> 00:43:17,759
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00:43:17,880 --> 00:43:18,600
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