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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is Bloomberg Intelligence

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Speaker 1: with Alex Steina and Paul'sweenye.

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Speaker 2: The real app performance has been the US corporate high yield.

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Speaker 3: Are the companies lean enough? Have they trimmed all the fats?

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Speaker 2: The semiconductor business is a really cyclical business.

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Speaker 1: Breaking market headlines and corporate news from across the globe.

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Speaker 3: Do investors like the M and A that we've seen?

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Speaker 2: These are two big time blue chip companies.

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Speaker 3: The window between the peak and cut changing super fast.

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Speaker 1: Bloomberg Intelligence with Alex Steinhall and Paul's Wheenye on Bloomberg Radio.

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Speaker 2: On Today's Bloomberg Intelligence Show, we dig inside the big

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Speaker 2: business stories impacting Wall Street and the global markets.

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Speaker 3: Each and every week we provide in depth research and

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Speaker 3: data on some of the two thousand companies and one

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Speaker 3: hundred and thirty industries our analysts cover worldwide.

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Speaker 2: Today, we'll look at how City Group is trying to

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Speaker 2: prevent a departure of wealth.

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Speaker 3: Bankers well as well look at why the tailor Best

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Speaker 3: Buy is warning of uneven demand for its electronics and appliances.

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Speaker 2: But first we begin with the tech media telecom space.

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Speaker 3: Recently, president like Donald Trump shows Brendan Carr as the

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Speaker 3: new chair of the Federal Communications Commission.

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Speaker 2: As Chair, cars priorities include raining in big tech, ensuring

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Speaker 2: broadcasters operate in the public interest, and unleashing economic growth.

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Speaker 3: For more and what to expect, we were joined by

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Speaker 3: Matthew Shettenhelm, Bloomberg Intelligence media litigation analyst.

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Speaker 2: We first asked Matthew about the scrutiny a big tech

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Speaker 2: will face under the new Trump administration.

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Speaker 4: I think in one sense, I think you'll see Congress

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Speaker 4: a little less aggressive, it moving forward with data privacy

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Speaker 4: type legislation that Democrats tended to promote. But where you're

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Speaker 4: going to see the risk and where I think I'm

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Speaker 4: prenominantly focused right off the bat is on big tech's

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Speaker 4: liability shield. This is a provision of law that's been

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Speaker 4: in place since nineteen ninety six that keeps Google and

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Speaker 4: Meta and other social media companies from being sued every

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Speaker 4: time someone posts something harmful on social media. What you're

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Speaker 4: seeing from the conservative side is increasing attacks on that,

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Speaker 4: and I think you could see a proceeding at the

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Speaker 4: FCC try to really focus and amplify those calls to

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Speaker 4: cut into the liability shield that's been so important for

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Speaker 4: those companies.

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Speaker 3: Does the FCD, FCC can they change it or can

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Speaker 3: they just sort of mold it on the sidelines.

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Speaker 5: Yeah, that's that's a great question.

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Speaker 4: The interesting thing is is this liability shield is tucked

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Speaker 4: into the Communications Act that the FCC administers. So during

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Speaker 4: the first Trump administration, the FCC took the position, hey,

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Speaker 4: we can make rules under this because it's it's.

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Speaker 5: In our law.

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Speaker 4: We can implement it, but they never got around to

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Speaker 4: doing it. I think the Trump administration this time is

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Speaker 4: going to try to move ahead with that and say, look,

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Speaker 4: we implement the Communications Act, the liability shield is tucked

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Speaker 4: in there.

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Speaker 5: We can make rules.

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Speaker 4: What's changed since then is that the Chevron doctrine has

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Speaker 4: been struck down, the Major Questions doctrine has arisen.

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Speaker 5: There's a real doubt.

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Speaker 4: I'm very skeptical that the FCC can bind the courts

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Speaker 4: in how to apply this liability shield. But in some

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Speaker 4: ways that's not the point. The point is sort of

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Speaker 4: to amplify the idea that courts or that Congress should

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Speaker 4: change the shield. And I think that's what you're going

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Speaker 4: to see a Brendan car Let FCC do is say, look,

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Speaker 4: even if we can't change the liability shield as an agency.

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Speaker 4: We're going to tell you how to do that and

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Speaker 4: amplify the momentum for Congress or the Supreme Court potentially

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Speaker 4: to do it itself.

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Speaker 2: So what do we know about the apparent FCC chair,

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Speaker 2: Brendan Carr, and what should we expect from a Republican

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Speaker 2: controlled FCC. What do we know about that, mister Carr.

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Speaker 4: Yeah, so Brendan Carr is the most senior Republican at

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Speaker 4: the FCC who knows communications law inside and out. But

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Speaker 4: he also knows how to play the politics around the

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Speaker 4: FCC better than anyone else there. And so he's going

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Speaker 4: to do his best to make sure that he's implementing

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Speaker 4: President Trump's agenda. And so while Brendan Carr is a

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Speaker 4: traditional sort of free market Republican, he's also very sympathetic

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Speaker 4: to the idea that there's sort of a bias against

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Speaker 4: conservatives among elite media, and he's very sympathetic to supporting

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Speaker 4: President Trump on that message. And so that's why you

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Speaker 4: see proceedings like this going after big tech companies, potentially

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Speaker 4: going after broadcasters and threatening to take away their licenses.

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Speaker 4: So there's going to be a little bit of this

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Speaker 4: sort of Okay, let's deregulate the democrats of regulator too much.

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Speaker 4: But there's also this concern about bias against conservatives and

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Speaker 4: that it's gone too much in that direction, and Brendan

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Speaker 4: Carr is going to support both.

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Speaker 3: So if I take a look at the actual equities

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Speaker 3: that are involved, what does it mean for them? If

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Speaker 3: I'm an investor and I'm looking at this, how do

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Speaker 3: I price it, how do I model it? How do

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Speaker 3: I think about it?

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Speaker 5: To me?

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Speaker 4: The I mean the biggest risk is you think about

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Speaker 4: the liability shield falling away if it goes you know,

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Speaker 4: in the most extreme approach, you're you're you're thinking about

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Speaker 4: the big social media companies. You're thinking about Meta, you're

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Speaker 4: thinking about alphabet, and you're thinking about creating a whole

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Speaker 4: new field of litigation with those companies as the targets.

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Speaker 4: And so you've seen a couple big settlements from those companies.

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Speaker 4: With the liability shield in place, you can think about

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Speaker 4: that being amplified many times over with class actions and

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Speaker 4: other suits.

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Speaker 5: Anytime content that's.

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Speaker 4: Posted on the social on social media causes harm in

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Speaker 4: the real world, you can think of limitless examples of

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Speaker 4: the harm it causes anytime that that there's harm, you

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Speaker 4: potentially have a lawsuit. And so I think it sort

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Speaker 4: of changes the equation in terms of the cost those

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Speaker 4: companies could fail in terms of potential liability if if

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Speaker 4: the liability shield were wiped away?

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Speaker 2: Will there be looser ownership riggish regulations on media? David

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Speaker 2: Zasov from Warner Brothers Discoveries asking.

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Speaker 5: Yeah, so, I absolutely So.

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Speaker 4: The Republicans at the FCC have historically been, you know,

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Speaker 4: they're tired of this idea of media ownership of broadcasters

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Speaker 4: that they said, look, there's so much new competition for broadcasters.

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Speaker 4: The problem is that there's first this political angle from

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Speaker 4: President Trump saying, look they edited my sixty minutes interview wrong,

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Speaker 4: And so Brendan Carr at first is kind of latching

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Speaker 4: onto that political arguments. Let's go after that first. So

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Speaker 4: I think media ownership sort of lurking in the background.

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Speaker 4: I think they'll get there after this political noise sort

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Speaker 4: of dies down.

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Speaker 5: Right.

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Speaker 3: Thanks to Matthew Shettenhelm, Bloomberg Intelligence media litigation analyst.

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Speaker 2: This week, we focused on a Bloomberg Big Take story

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Speaker 2: entitled Amazon prepares to go toe to toe with Nvidia

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Speaker 2: in AI hardware.

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Speaker 3: You can find it on Bloomberg dot Com and the Terminal,

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Speaker 3: and the story looks at how amaz On is loosening

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Speaker 3: and Video's grip on the one hundred million dollar plus

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Speaker 3: market for AI chips.

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Speaker 2: For more on this story, we are joined by Matt Day,

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Speaker 2: Bloomberg Technology reporter.

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Speaker 3: We first asked Matt for more context on the journey

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Speaker 3: that Amazon has gone on when it comes to innovation

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Speaker 3: and chips.

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Speaker 6: So Amazon gets a lot of credit for inventing the

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Speaker 6: cloud computing market and basically rented computing power, data storage

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Speaker 6: all over the Internet. What they don't get so much

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Speaker 6: credit for is building a lot of the hardware behind it.

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Speaker 6: So you go back fifteen years and they started building

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Speaker 6: their own servers, their own networking switches. Eventually they got

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Speaker 6: onto to silicon to chips themselves. That's where they find

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Speaker 6: themselves today is you know, they didn't set out to

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Speaker 6: necessarily try to upset in video, but because they've been

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Speaker 6: working on machine learning chips for the past you know,

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Speaker 6: call it five six years, they have a chip they

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Speaker 6: think is arriving at the right time.

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Speaker 2: Talk to us about what Amazon's folks in Austin, Texas

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Speaker 2: are doing what's going on that down.

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Speaker 6: There, So Austin, it's a tech mecha, especially for hardware,

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Speaker 6: dating back to IBM and Dell, and Amazon focuses there

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Speaker 6: machine learning chip testing there. They're chip engineering down there.

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Speaker 6: So myself a colleague paid a visit down there last

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Speaker 6: month and there it's really a scrappy vibe. The place

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Speaker 6: isn't isn't particularly pristine. There's just stuff strewn all over

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Speaker 6: the place, as the story notes. But that's a little

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Speaker 6: bit of the Amazon engineering ethos at work, right. They

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Speaker 6: don't have to push the limits of performance, they don't

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Speaker 6: have to make it real pretty. They just have to

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Speaker 6: build a part that works, a part. They can build

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Speaker 6: a whole lot of them in a pretty short period

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Speaker 6: of time. And so that's what they're trying to do

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Speaker 6: now is get those chips out to the data centers

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Speaker 6: before the end.

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Speaker 7: Of the year.

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Speaker 3: Now is the idea that, hey, in video, we don't

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Speaker 3: need you anymore at all? Or is it just sort

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Speaker 3: of like we can also do this and there's room

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Speaker 3: to everyone to play on different levels.

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Speaker 6: Yeah, no, not at all about replacing all of Nvidia.

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Speaker 6: And if you get any Amazon exec talking about it,

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Speaker 6: the first sentence out of their mouth is going to

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Speaker 6: be you know, we recognize in video has got a

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Speaker 6: great product and it's going to be around for a

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Speaker 6: long long time, you know, I said, And I don't

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Speaker 6: have any hard numbers in front of me, and Amazon

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Speaker 6: folks wouldn't speculate, but I think they'd consider this a

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Speaker 6: victory if they could just take some of that some

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Speaker 6: of that portion of the Nvidia demand. They already are

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Speaker 6: serving today with video chips in their data centers.

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Speaker 2: So in Vidia's biggest customers, they're big companies like Amazon,

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Speaker 2: like Microsoft, like Alphabet, and all of those customers are

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Speaker 2: trying to build their own chips. How is Amazon kind

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Speaker 2: of positioned relative to all those players.

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Speaker 6: I think one thing Amazon definitely has an advantage over

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Speaker 6: its its nearest cloud rival, Microsoft, and that they started

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Speaker 6: a lot earlier. Microsoft only started building its chips a

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Speaker 6: couple of years ago. Amazon's been doing this since twenty thirteen,

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Speaker 6: twenty fourteen, and they all kind of came to the

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Speaker 6: same realization, which is that you know, listen, ultimately, a

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Speaker 6: data center is just a big computer, right Like we

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Speaker 6: think of computers as laptops or maybe a single rack

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Speaker 6: of servers. But one of the things that the cloud

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Speaker 6: revolution has done is it's allowed these companies to say, Okay,

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Speaker 6: wait a minute, how is this going to work if

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Speaker 6: instead of one of them in a server, I have

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Speaker 6: one hundred thousand of them spread over a data center

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Speaker 6: or multiple buildings.

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Speaker 7: Right?

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Speaker 6: How does the computer work in that situation? And that's

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Speaker 6: one of the things that Generative AI and all these

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Speaker 6: real hard intensive training runs have kind of forced them

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Speaker 6: to do is think about these you know it, sprawling

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Speaker 6: data centers as computers in and of themselves.

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Speaker 3: Now, you guys went to some of these places where

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Speaker 3: they're trying to build these chips. Can you describe what

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Speaker 3: it's like, because we're looking at a bazillion dollar company

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Speaker 3: in Amazon, right, But the what you described is not that.

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Speaker 6: Oh yeah, I looked a little bit like a popour

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Speaker 6: rerac at a hardware store, right at a drill press

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Speaker 6: in a corner, they had a vacuum sealer and under

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Speaker 6: that was one of those slow ovens to kind of

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Speaker 6: dry things out dehumidifier.

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Speaker 7: Maybe that's not the right word.

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Speaker 6: But there's a lot of hardware sitting around, and a

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Speaker 6: lot of it's really high tech, a lot of it's

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Speaker 6: really expensive, you know, but the Vibe again, was just

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Speaker 6: an engineering crew trying to go as fast as they

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Speaker 6: can to put chips in the hand of their customers,

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Speaker 6: you know, an Amazon's case, that's their own data centers.

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Speaker 6: But there's a funny moment while we were there. The

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Speaker 6: guy who runs the lab, a guy called Romney Sino,

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Speaker 6: was yelling over to a colleague of his basically, what's

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Speaker 6: your job, and the job is to ship things to

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Speaker 6: data centers.

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Speaker 7: Right.

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Speaker 6: They're not there to push the limits of engineering. They're

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Speaker 6: there to reliably, you know, ship product out and get

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Speaker 6: it in the hands of their business customers.

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Speaker 2: What are the customers saying about the Amazon chips? How

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Speaker 2: are these Amazon chips performing in the market place?

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Speaker 6: And so the Amazon has only started just started rolling

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Speaker 6: out its latest chip. You know what we know from

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Speaker 6: the first version is you know, it's not as good

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Speaker 6: as in Nvidia. And that's particularly clear on the software level, right,

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Speaker 6: I mean, no matter how good a piece of hardware is,

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Speaker 6: if you can't access it with ease, that's going to

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Speaker 6: be a problem for you. And that's where Nvidia has

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Speaker 6: just a huge advantage. You know, they've got the open

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Speaker 6: source community behind them building libraries and tools so that

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Speaker 6: almost any AI thing you want to do, you can

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Speaker 6: accomplish it on an navidiate ship. And so that's what

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Speaker 6: customers have told us is the big hurdle for Amazon.

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Speaker 6: You know. Now, Amazon is offering it's early adopter some help.

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Speaker 6: They will, you know, send you engineers and help customize

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Speaker 6: your work for their chips, but that's not going to

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Speaker 6: scale in the long term. They're hoping they can build

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Speaker 6: a software package that makes it real easy to use

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Speaker 6: their hardware, but they're not there yet.

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Speaker 3: Who are the geniuses behind this in Amazon? Where the names?

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Speaker 6: So the main one who gets a lot of credit

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Speaker 6: for it, and probably doesn't get enough outside of tech

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Speaker 6: circles is James Hamilton. He's a longtime engineer at IBM

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Speaker 6: and at Microsoft who Amazon poached real early into their

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Speaker 6: cloud competing experiment back in two thousand and nine, and

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Speaker 6: it was partly his suggestion that the company should get

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Speaker 6: into the hardware business. Right He was looking at their

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Speaker 6: costs and saying, listen, why are we paying Dell HP

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Speaker 6: for all of these servers with a bunch of high

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Speaker 6: end functions we don't need. We could build a cheaper

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Speaker 6: mousetrap and if it's just good enough for us, then

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Speaker 6: we can pass those savings onto our customers. So it

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Speaker 6: really started this snowball of just Amazon getting into more

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Speaker 6: and more corners of hardware that previously, you know, they

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Speaker 6: hadn't really had much interest in, and that's really paid

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Speaker 6: off in terms of how profitable the cloud businesses for Amazon.

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Speaker 2: Our thanks to Matt Dave, Bloomberg Technology.

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Speaker 3: Reporter, coming up a conversation with the CEO of bloom Energy.

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Speaker 2: You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in

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Speaker 2: depth research and data on two thousand companies and one

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Speaker 2: hundred and thirty industries. You can access Bloomberg Intelligence via

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Speaker 2: bi Go on the terminal, Paul Sweet and.

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Speaker 3: A Malex Steel and this is Bloomberg.

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Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live

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Speaker 1: weekdays at ten am Eastern on applecarplaying nbroud Otto with

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Speaker 1: the Bloomberg Business app. Listen on demand wherever you get

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Speaker 1: your podcasts, or watch us live on YouTube.

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Speaker 3: We moved next to the Banking Space and Citygroup.

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Speaker 2: This week we looked at a story on the Bloomberg

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Speaker 2: Terminal and at Bloomberg dot Com entitled City Bonuses by

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Speaker 2: time for New Wealth boss rush to revamp.

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Speaker 3: And looked at how Citygroup's new CEO, Andy sigg Green

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Speaker 3: led special retention bonuses for dozens of personnel for more

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Speaker 3: and all of this means. We were drawn by Katherine Doherty,

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Speaker 3: Bloomberg Finance reporter.

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Speaker 2: We first asked Catherine how things are going now for

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Speaker 2: Citygroup and it's.

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Speaker 8: New CEO, Andy is one year into his new role,

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Speaker 8: and he came into it with a lot of difficulties.

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Speaker 3: And the basic.

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Speaker 8: Infrastructure that City was working with in their wealth division

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Speaker 8: was something that had been lagging peers. It was way

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Speaker 8: behind in terms of speed execution. And really that was

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Speaker 8: something that Andy had focused on right when he came in.

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Speaker 8: And upgrading the technology was one thing. Then bringing talent

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Speaker 8: was kind of the second pillar to improving the wealth division.

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Speaker 8: And keeping talent is the hardest part about building a

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Speaker 8: wealth business across Wall Street because it's a very competitive business.

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Speaker 8: The pay is oftentimes used as a way to lure

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Speaker 8: experienced advisors to competitors, and so not only are you

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Speaker 8: trying to focus on keeping that talent, the talent is

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Speaker 8: tied to the assets that they're managing for their clients.

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Speaker 8: So anytime you lose some big advisors with millions or

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Speaker 8: even billions in assets. That's going to affect your business

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Speaker 8: moving forward. So Andy had a very big agenda in

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Speaker 8: front of him in terms of having to clean up,

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Speaker 8: and not just clean up, but then improve cities wealth

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Speaker 8: business so that it could truly compete with the big

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Speaker 8: peers on Wall Street.

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Speaker 2: Yeah, because like when I think of Morgan Stanley, I

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Speaker 2: think of wealth management I use, and that's different. When

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Speaker 2: I grew up in the business, I thought about them

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Speaker 2: as sales and trading and investment banking City I don't

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Speaker 2: necessarily think of wealth as part as a kind of

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Speaker 2: a growth driver for them. But I know in their

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Speaker 2: private bank, which generates two point three billion dollars in revenue,

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Speaker 2: it is high touch service for the wealthiest clients, including

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Speaker 2: a quarter of the world's billionaires minimum net worth twenty

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Speaker 2: five million dollars. So is this a situation for City

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Speaker 2: that Jane Fraser has to just put a flag in

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Speaker 2: a ground say this is a core business for City

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Speaker 2: and we will invest Accordingly.

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Speaker 8: Private bank is definitely one of their money makers. You

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Speaker 8: can see that in the numbers. But also if you

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Speaker 8: think two tiers down, you have City Gold and this

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Speaker 8: is clients with avery average monthly balances of at least

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Speaker 8: two hundred thousand, So it's definitely not at the private

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Speaker 8: bank tier. The private bank tier. Why they're trying to

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Speaker 8: keep that part of the wealth business up is because

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Speaker 8: that's where the biggest assets are. That's where the revenue

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Speaker 8: really gets generated when you have the wealthiest and it's

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Speaker 8: not just Americans, it's oftentimes billionaires in Asia. They're really

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Speaker 8: focused on growing their business outside of the US, which

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Speaker 8: is different from some of the other big Wall Street

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Speaker 8: banks that are more US focused in terms of building

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Speaker 8: up their own private bank assets. And so City, their

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Speaker 8: private bank, I would say, was their strong suit and

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Speaker 8: continues to be their strong suit, but it doesn't mean

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Speaker 8: that that's going to stay that way. So they really

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Speaker 8: have to remain competitive keep their advisors that are catering

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Speaker 8: to the wealthiest individuals, not just in the US but

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Speaker 8: across the globe.

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Speaker 3: Did they lose advisors because they were posed or because

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Speaker 3: they let them go because they were revamping it and

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Speaker 3: it so it's a combination.

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Speaker 8: Just last week we reported that two of City's former

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Speaker 8: private bank advisors defected to go to Bank of America.

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Speaker 8: Actually in their private bank, which is interesting because that's

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Speaker 8: where Andy Sig had come. You worked in the Meryl division.

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Speaker 8: But still it's under the Bank of America umbrella and

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Speaker 8: those two advisors they brought seven billion of assets that

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Speaker 8: they managed. So that was a big kick to City.

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Speaker 8: And so when you see that, but it's not i

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Speaker 8: would say unique just to City. There's stories like that

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Speaker 8: all the time of some of these really big advisors

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Speaker 8: bringing their team to a competitor and oftentimes they're just

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Speaker 8: looking for it's opportunity and most of the time that

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Speaker 8: opportunity is translated and in pay all.

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Speaker 3: Right, our thanks to Catherine Doherty, Bloomberg Finance Reporter. We

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Speaker 3: move next to the energy space. The fuel cell maker

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Speaker 3: Bloom Energy recently signed a landmark supply agreement with American

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Speaker 3: Electric Power for up to one gigawatt of fuel cells

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Speaker 3: and this marks the latest commercial procurement of fuel cells globally.

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Speaker 2: For more and all of this, we were joined by

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Speaker 2: k R. Sweetheart, CEO of bloom Energy. We first asked

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Speaker 2: k Are how this deal came about.

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Speaker 7: So we have being more with data centers for a

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Speaker 7: very long time. Now we have over three hundred megawarts

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Speaker 7: in multiple data centers, across the country. These are the

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Speaker 7: smaller data centers called the edge data centers that are

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Speaker 7: located where customers are somewhere in the five to ten

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Speaker 7: megawat range in a particular site. So we have transacted

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Speaker 7: close to three hundred megawarts, so we are a known

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Speaker 7: player to data centers. Now with the hyperscalers, what's the difference,

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Speaker 7: it's a much larger data centers. These are now particularly

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Speaker 7: more important in terms of growth because of AI and

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Speaker 7: the amount of power they need. And currently these hyperscalers,

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Speaker 7: as they're growing very fast, the transmission distribution is not

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Speaker 7: able to keep up with providing those hundreds of megawarts

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Speaker 7: of power right at the site where you need it

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Speaker 7: within the time that you need it maybe five to

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Speaker 7: six years. They may be able to provide the power,

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Speaker 7: but the data center really wants it today, they want

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Speaker 7: it now. So we are perfectly under those circumstances because

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Speaker 7: our Bloom Energy servers can be deployed in a matter

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Speaker 7: of months right where the customer is, thereby not worrying

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Speaker 7: about the transmission distribution gridlock and providing that reliable, clean,

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Speaker 7: always on power to the data center. So that's the

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Speaker 7: reason this happened, and here what happened is the electricity

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Speaker 7: provider AEP said, we don't make nuclear power plants, we

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Speaker 7: don't make gas turbance, we don't make fuel cells. We're agnostic.

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Speaker 7: We'll buy your systems and similar to us using those

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Speaker 7: other power sources to provide power to the customer. Here

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Speaker 7: we can take your fuel cells and take the power

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Speaker 7: you produce and give it to the data center. However,

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Speaker 7: the big advantage here is we can put these fuel

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Speaker 7: cells right where the data center is, thereby avoiding the

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Speaker 7: transmission distribution issue.

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Speaker 2: So, Kerry, I mean, just you know, I didn't know

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Speaker 2: much about your company before, so just reading up here,

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Speaker 2: it's like right company, right place, at the right time,

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Speaker 2: with the right technology, and boom. Talk to us about

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Speaker 2: how good your fuel cells are. How would I know

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Speaker 2: whether your fuel cell is better more productive than say

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Speaker 2: a competitor.

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Speaker 7: That's a great question. So let me go away from

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Speaker 7: fuel cells, just into electricity for the customer. At the

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Speaker 7: end of the day, we all provide a service or

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Speaker 7: a product to our end customer. That electricity that a

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Speaker 7: data center takes has to be clean, it has to

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Speaker 7: be always on and reliable. Twenty four to seven. It

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Speaker 7: needs to have a pay as you grow characteristic, and

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Speaker 7: it needs to be future proofed in terms of sustainability.

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Speaker 7: Bloom Energy is one of those solutions that offer all

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Speaker 7: of the above no rs. It's the genius of end

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Speaker 7: So we are the most efficient way of taking natural

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Speaker 7: gas and making electricity out of it without combustone. Because

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Speaker 7: we don't compassed, there is no knock socks particulates anything

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Speaker 7: going into the atmosphere, so there is no local air pollution.

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Speaker 7: And if you look at our system they're like lego blocks.

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Speaker 7: You put many of these lego blocks, hundreds of them

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Speaker 7: to be able to provide power to a data center.

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Speaker 7: If any one of them has to be serviced, you

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Speaker 7: can just hot swap them in and out. So the

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Speaker 7: reliability and the resiliency of our systems are very high.

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Speaker 7: And then you and you can pay as you grow

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Speaker 7: data centers. Even though they build a big data center,

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Speaker 7: don't start that entire data center on day one. They

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Speaker 7: may do one third of the load, and then a

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Speaker 7: few months later they may add additional load. As they

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Speaker 7: are adding the load, they can add more and more

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Speaker 7: of our fuel cells. You can't do that to the

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Speaker 7: gas turbine. You can't do that to the nuclear power plant.

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Speaker 7: So we bring all these attributes in so I would

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Speaker 7: say we are ideally suited for this AI data center market.

441
00:21:56,880 --> 00:21:59,440
Speaker 3: Now, the financial terms were not disclosed. I appreciate that.

442
00:22:00,040 --> 00:22:02,280
Speaker 3: I'm gonna ask about the money a different way. How

443
00:22:02,480 --> 00:22:05,159
Speaker 3: easy was it or difficult was it to come to

444
00:22:05,240 --> 00:22:06,720
Speaker 3: an agreement on price.

445
00:22:06,560 --> 00:22:07,720
Speaker 5: With AEP.

446
00:22:09,080 --> 00:22:11,840
Speaker 7: In this particular case, it was fairly easy to come

447
00:22:11,880 --> 00:22:16,240
Speaker 7: to that agreement. Nothing is easy, but relatively speaking, And

448
00:22:16,359 --> 00:22:21,280
Speaker 7: here is why. There are three parties involved, actually four,

449
00:22:21,920 --> 00:22:27,920
Speaker 7: the data center customer, AP, the public at large where

450
00:22:28,040 --> 00:22:31,840
Speaker 7: this is being installed, and blow energy we were able

451
00:22:31,920 --> 00:22:36,520
Speaker 7: to put together When when for all four of these stakeholders,

452
00:22:36,800 --> 00:22:37,199
Speaker 7: why is.

453
00:22:37,240 --> 00:22:38,399
Speaker 1: That number one?

454
00:22:38,520 --> 00:22:42,440
Speaker 7: Let's start with the public at large with other kind

455
00:22:42,520 --> 00:22:46,920
Speaker 7: of provisions that were being contemplated. The fear of the

456
00:22:47,040 --> 00:22:50,119
Speaker 7: ratepayer was because the hyperscaler is going to get a

457
00:22:50,200 --> 00:22:54,040
Speaker 7: large amount of power from the transmission distribution company, they

458
00:22:54,119 --> 00:22:58,760
Speaker 7: will end up carrying the bill. In this construct, AEP

459
00:22:58,960 --> 00:23:02,520
Speaker 7: made sure none of the costs associated with putting these

460
00:23:02,560 --> 00:23:06,000
Speaker 7: fuel cells and providing that clean power to the data

461
00:23:06,080 --> 00:23:09,440
Speaker 7: center will cost the rate payer any money. So that

462
00:23:09,560 --> 00:23:12,040
Speaker 7: was a win for the ratepayer number two for the

463
00:23:12,160 --> 00:23:15,760
Speaker 7: data center. For the data center, the price of not

464
00:23:16,000 --> 00:23:19,800
Speaker 7: having power on time is significantly greater than the cost

465
00:23:19,880 --> 00:23:22,600
Speaker 7: of power. If you just think about the race in

466
00:23:22,720 --> 00:23:26,600
Speaker 7: AI and who has to get there competitively. So time

467
00:23:26,680 --> 00:23:29,800
Speaker 7: to power was the key metric and they would pay

468
00:23:29,840 --> 00:23:32,680
Speaker 7: a slight premium to be able to get that, and

469
00:23:32,840 --> 00:23:37,280
Speaker 7: that penciled out for AEP. They were able to grow

470
00:23:37,320 --> 00:23:42,080
Speaker 7: their customer base, give them their growth needs without dissenter

471
00:23:42,200 --> 00:23:44,960
Speaker 7: mediating them and having them go to some other state,

472
00:23:45,359 --> 00:23:48,120
Speaker 7: which is what has been happening in places like Virginia

473
00:23:48,440 --> 00:23:51,159
Speaker 7: where data centers are moving away from there because there

474
00:23:51,200 --> 00:23:53,119
Speaker 7: is not enough power. So it was a win for

475
00:23:53,240 --> 00:23:56,480
Speaker 7: AEP in retaining their customer and taking care of their

476
00:23:56,520 --> 00:24:00,480
Speaker 7: customer and making money for Bloom. Whether we in front

477
00:24:00,520 --> 00:24:02,520
Speaker 7: of the meter or behind the meter, it is the

478
00:24:02,600 --> 00:24:05,840
Speaker 7: same thing. Whether we sell it to AP who then

479
00:24:05,880 --> 00:24:08,360
Speaker 7: provides the power for the data center, or we sell

480
00:24:08,400 --> 00:24:11,119
Speaker 7: to the data center and they provide it and they

481
00:24:11,200 --> 00:24:13,560
Speaker 7: take their own power. You know, for us we are

482
00:24:13,560 --> 00:24:16,280
Speaker 7: agnostic because we get to make the sale and we

483
00:24:16,400 --> 00:24:17,879
Speaker 7: get the gross margins on the product.

484
00:24:18,160 --> 00:24:21,000
Speaker 3: All right. Thanks to k R. Shreedhar CEO Bloom Energy

485
00:24:21,240 --> 00:24:22,920
Speaker 3: all right, coming up a look at what's new in

486
00:24:22,960 --> 00:24:25,040
Speaker 3: the renewable fuels market in the US.

487
00:24:25,320 --> 00:24:28,280
Speaker 2: You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in

488
00:24:28,560 --> 00:24:31,080
Speaker 2: research and data on two thousand companies one hundred and

489
00:24:31,080 --> 00:24:33,840
Speaker 2: thirty industries. You can access Bloomberg Intelligence via p I

490
00:24:33,920 --> 00:24:34,639
Speaker 2: go on the terminal.

491
00:24:34,760 --> 00:24:36,640
Speaker 3: I'm Paul Sweeney and am Alex Steel.

492
00:24:36,400 --> 00:24:37,520
Speaker 9: And this is Bloomberg.

493
00:24:42,480 --> 00:24:46,320
Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live

494
00:24:46,440 --> 00:24:49,960
Speaker 1: weekdays at ten am Eastern on applecar Play and Android

495
00:24:50,000 --> 00:24:52,720
Speaker 1: Auto with the Bloomberg Business app. You can also listen

496
00:24:52,880 --> 00:24:55,960
Speaker 1: live on Amazon Alexa from our flagship New York station,

497
00:24:56,359 --> 00:24:59,080
Speaker 1: Just say Alexa play Bloomberg eleven thirty.

498
00:25:00,000 --> 00:25:02,439
Speaker 2: Each week we look at research from Bloomberg and EF

499
00:25:02,760 --> 00:25:04,919
Speaker 2: previously known as New Energy Finance.

500
00:25:05,080 --> 00:25:07,280
Speaker 3: They're the team at Bloomberg that tracks and analyzes the

501
00:25:07,359 --> 00:25:11,040
Speaker 3: energy transition from commodities to power, transport, industries, buildings, and

502
00:25:11,200 --> 00:25:11,920
Speaker 3: egg sectors.

503
00:25:12,240 --> 00:25:14,680
Speaker 2: This week we took a look at renewable fuels, and

504
00:25:14,760 --> 00:25:18,119
Speaker 2: we're joined by Anna Davies, bnef's head of renewable Fuels.

505
00:25:18,359 --> 00:25:20,920
Speaker 3: We first asked Anna what types of renewable fuel projects

506
00:25:21,040 --> 00:25:23,160
Speaker 3: now exist in the US, so there's.

507
00:25:23,400 --> 00:25:25,399
Speaker 9: A good number of projects in the US nice to

508
00:25:25,440 --> 00:25:28,520
Speaker 9: be here, and there's a wide range. The US is

509
00:25:28,520 --> 00:25:30,200
Speaker 9: the biggest market at the moment, so a lot of

510
00:25:30,240 --> 00:25:33,160
Speaker 9: the projects are based here. A lot of renewable fuels.

511
00:25:33,160 --> 00:25:35,080
Speaker 9: When we talk about renewable fuels, we're really talking about

512
00:25:35,080 --> 00:25:39,680
Speaker 9: basically biofuels at the moment, made from oils like soybean

513
00:25:39,720 --> 00:25:42,480
Speaker 9: oil or even use cooking oil like the excess grease

514
00:25:42,480 --> 00:25:46,080
Speaker 9: from your fryer. The key here is that unlike ethanol

515
00:25:46,160 --> 00:25:49,840
Speaker 9: or biodiesel or biofuels you usually think about, renewable fuels

516
00:25:49,840 --> 00:25:52,160
Speaker 9: are a special term for ones that are drop in ready,

517
00:25:52,240 --> 00:25:55,040
Speaker 9: which means they produce a diesel molecule or jet fuel

518
00:25:55,080 --> 00:25:58,480
Speaker 9: molecule that's basically the same as fossil dieseler jet fuel,

519
00:25:58,640 --> 00:26:00,240
Speaker 9: So you could just blend it one for one into

520
00:26:00,280 --> 00:26:04,280
Speaker 9: your dieseler jet fuel pool. There's no blending limit. It

521
00:26:04,560 --> 00:26:06,000
Speaker 9: can just go in however much you have, So it's

522
00:26:06,040 --> 00:26:08,439
Speaker 9: really cool in that regard. A lot of the projects

523
00:26:08,480 --> 00:26:11,480
Speaker 9: in the US are based, especially out of California. You

524
00:26:11,520 --> 00:26:14,200
Speaker 9: could take an old oil refinery and convert that to

525
00:26:14,640 --> 00:26:18,320
Speaker 9: produce a biooil like a biofeedstock instead of a crude feedstock,

526
00:26:18,400 --> 00:26:21,000
Speaker 9: so that's really common. There's also a lot of projects

527
00:26:21,040 --> 00:26:24,040
Speaker 9: being developed to use other feedstocks, things like corn ethanol,

528
00:26:24,320 --> 00:26:27,880
Speaker 9: because if you think about passenger vehicle fleet going electric,

529
00:26:28,280 --> 00:26:30,520
Speaker 9: you're going to have less demand for gasoline or ethanol,

530
00:26:30,840 --> 00:26:33,440
Speaker 9: so this could be another use for that ethanol in

531
00:26:33,520 --> 00:26:34,080
Speaker 9: the world today.

532
00:26:34,400 --> 00:26:36,639
Speaker 2: I gotta ask the question everybody wants to ask, how

533
00:26:36,680 --> 00:26:40,560
Speaker 2: will the Trump administration impact renewable fuel business?

534
00:26:41,000 --> 00:26:44,160
Speaker 9: That is the million dollar question probably for every clean

535
00:26:44,280 --> 00:26:48,040
Speaker 9: energy sector. I'd say that renewable fuels, compared to a

536
00:26:48,080 --> 00:26:50,639
Speaker 9: lot of the other sectors of clean energy, might be

537
00:26:50,680 --> 00:26:54,320
Speaker 9: a bit better insulated than most because this is a

538
00:26:54,400 --> 00:26:57,760
Speaker 9: sector where it really promotes the agriculture industry by using

539
00:26:57,880 --> 00:27:00,840
Speaker 9: biofuels as a new demand source. It also is a

540
00:27:00,880 --> 00:27:02,680
Speaker 9: way for the oil industry to get a second life

541
00:27:02,720 --> 00:27:05,000
Speaker 9: because they can't take this old refinery and convert it

542
00:27:05,040 --> 00:27:08,080
Speaker 9: into something new. So in that regard, I don't think

543
00:27:08,119 --> 00:27:10,719
Speaker 9: it's going to be completely in the crosshairs. There are ways, though,

544
00:27:10,720 --> 00:27:12,840
Speaker 9: that the Trump administration might have a big impact on

545
00:27:12,880 --> 00:27:14,440
Speaker 9: this sector. One of the big ones is if he

546
00:27:14,520 --> 00:27:17,360
Speaker 9: puts a tariff on used cooking oil from China.

547
00:27:17,320 --> 00:27:19,720
Speaker 2: Or some of the feets used cooking oil from China.

548
00:27:19,840 --> 00:27:20,040
Speaker 5: We do.

549
00:27:20,280 --> 00:27:22,000
Speaker 9: China produces a lot of use cooking oil, a lot

550
00:27:22,080 --> 00:27:25,679
Speaker 9: of fried food. They export the cooking oil to California

551
00:27:25,720 --> 00:27:28,000
Speaker 9: which they can then blend into these refineries. Used cooking

552
00:27:28,040 --> 00:27:31,679
Speaker 9: oil is a really popular feedstock for renewable fuels because

553
00:27:31,680 --> 00:27:34,040
Speaker 9: it has a low carbon intensity. Otherwise it's just wasted,

554
00:27:34,440 --> 00:27:35,960
Speaker 9: right you throw it out, it has to be collected.

555
00:27:38,600 --> 00:27:40,880
Speaker 9: It was collected into it dumped in probably a dump.

556
00:27:41,560 --> 00:27:43,760
Speaker 3: But so we don't have enough used cooking oil here

557
00:27:43,800 --> 00:27:46,840
Speaker 3: in the US as supplement if everything.

558
00:27:47,920 --> 00:27:50,000
Speaker 9: We have a lot. But if you think about replacing

559
00:27:50,080 --> 00:27:51,879
Speaker 9: you know, the diesel or the jet fuel pool, you

560
00:27:51,920 --> 00:27:52,760
Speaker 9: can always use more.

561
00:27:53,080 --> 00:27:55,560
Speaker 3: See So to that point, what is the price spread

562
00:27:55,600 --> 00:27:58,119
Speaker 3: between renewable fuels and traditional fuels? Right now?

563
00:27:58,520 --> 00:28:03,200
Speaker 9: Tie renewable fuel their cheapest are probably two to four times,

564
00:28:03,240 --> 00:28:05,680
Speaker 9: which is a big range, but cheaper than more expensive

565
00:28:05,720 --> 00:28:08,800
Speaker 9: sorry than fossil like jet fuel. And if you talk

566
00:28:08,840 --> 00:28:11,240
Speaker 9: about some of the novel technologies. So one of the

567
00:28:11,280 --> 00:28:14,720
Speaker 9: ways to make these renewable fuels is to take carbon

568
00:28:14,800 --> 00:28:17,320
Speaker 9: dioxide and green hydrogen, which is great because then you're

569
00:28:17,359 --> 00:28:20,040
Speaker 9: not using any biofeedstock that could be up to like

570
00:28:20,160 --> 00:28:22,399
Speaker 9: ten times as expensive as jet fuel. These are pricey

571
00:28:22,440 --> 00:28:24,040
Speaker 9: fuels and they're probably not going to get too much

572
00:28:24,119 --> 00:28:26,160
Speaker 9: cheaper because a lot of it is just the technology needed.

573
00:28:26,560 --> 00:28:30,000
Speaker 2: So but if as an airline, am I mandated to

574
00:28:30,160 --> 00:28:32,280
Speaker 2: use a certain percentage of clean fuel?

575
00:28:32,520 --> 00:28:35,240
Speaker 9: Depends where you are in Europe starting next year, yes

576
00:28:35,680 --> 00:28:38,160
Speaker 9: you are mandated to blend it in. In the US,

577
00:28:38,200 --> 00:28:40,840
Speaker 9: we don't have mandates yet. The biggest is we're doing

578
00:28:40,880 --> 00:28:43,440
Speaker 9: a lot of carrot incentives. So the Inflation Reduction Act

579
00:28:43,480 --> 00:28:47,600
Speaker 9: has a tax credit for producing renewable sustainable aviation fuel

580
00:28:47,880 --> 00:28:50,000
Speaker 9: that would give a discount of about a dollar dollar

581
00:28:50,080 --> 00:28:52,600
Speaker 9: twenty five to these producers. It's not enough to cover

582
00:28:52,720 --> 00:28:54,920
Speaker 9: that bridge that cost. It could bring it down closer.

583
00:28:54,720 --> 00:28:56,600
Speaker 3: Pences, and then if that goes away, then it makes

584
00:28:56,640 --> 00:28:59,920
Speaker 3: it even worse. So what's the best way to low

585
00:29:00,080 --> 00:29:03,080
Speaker 3: or that gap? Is it we need better technology, we

586
00:29:03,200 --> 00:29:05,720
Speaker 3: need scalable technology, or more sourcing.

587
00:29:06,800 --> 00:29:08,840
Speaker 9: I don't think technology is gonna come down too much

588
00:29:08,880 --> 00:29:10,680
Speaker 9: in cost because a lot of the cost technology is

589
00:29:10,680 --> 00:29:12,880
Speaker 9: a big component. But the feedstock is a big component too,

590
00:29:13,320 --> 00:29:16,760
Speaker 9: and it's hard to China exactly, so that could make

591
00:29:16,800 --> 00:29:19,360
Speaker 9: it worse. A lot of it is probably gonna be

592
00:29:19,440 --> 00:29:23,360
Speaker 9: a bit mix of mandates and subsidies. So if you

593
00:29:23,520 --> 00:29:25,160
Speaker 9: have a mandate, sayn you just have to blend a

594
00:29:25,160 --> 00:29:27,320
Speaker 9: certain amount, that's going to cause you know, maybe you

595
00:29:27,360 --> 00:29:29,760
Speaker 9: put a premium on the cost of jet fuel, a

596
00:29:29,880 --> 00:29:31,840
Speaker 9: tax on jet fuel that can cause that price gap

597
00:29:31,920 --> 00:29:35,960
Speaker 9: to close, or if you offer an incentive to produce

598
00:29:36,040 --> 00:29:38,040
Speaker 9: these fuels that can bring it down. There's a lot

599
00:29:38,080 --> 00:29:40,640
Speaker 9: of research being done on new feedstocks, like something like

600
00:29:40,720 --> 00:29:42,440
Speaker 9: cover crops. If you haven't a fueled you could just

601
00:29:42,480 --> 00:29:44,880
Speaker 9: plant a new oil crop in the off season that

602
00:29:44,960 --> 00:29:47,440
Speaker 9: can help retain the soil. You can use the same land.

603
00:29:47,520 --> 00:29:49,440
Speaker 9: You don't have to have this issue of food versus

604
00:29:49,480 --> 00:29:53,160
Speaker 9: fuel land use. But yeah, that's the question is how

605
00:29:53,200 --> 00:29:53,880
Speaker 9: cheap can you get it?

606
00:29:54,280 --> 00:29:57,840
Speaker 2: Our thanks to Annadavis, b n EFS, head of Renewable Fuels, we.

607
00:29:57,920 --> 00:29:59,800
Speaker 3: Move next to the retail space. This week we got

608
00:29:59,840 --> 00:30:01,720
Speaker 3: our from Best Buy and Dick Spoorting Goods.

609
00:30:02,000 --> 00:30:04,760
Speaker 2: Best Buy cut it's full year guidance on sluggish demand

610
00:30:04,840 --> 00:30:08,880
Speaker 2: for electronics and appliances. However, Dickboarding Goods increased its annual

611
00:30:08,920 --> 00:30:10,520
Speaker 2: projections for comparable sales and growth.

612
00:30:10,680 --> 00:30:12,080
Speaker 3: For more on all of this, we are joined by

613
00:30:12,120 --> 00:30:15,360
Speaker 3: Lindsay Dutch, Bloomberg Intelligence Consumer Hardline Senior Analyst.

614
00:30:15,760 --> 00:30:18,160
Speaker 2: We first asked Lindsay for her take on this week's

615
00:30:18,160 --> 00:30:19,480
Speaker 2: results from Dickboarding Goods.

616
00:30:19,760 --> 00:30:23,080
Speaker 10: I think Dick's had a strong quarter, you know, again

617
00:30:23,160 --> 00:30:26,160
Speaker 10: stronger than expected, sort of continuing the trend that we've

618
00:30:26,280 --> 00:30:29,680
Speaker 10: seen earlier this year. You know, they have you know,

619
00:30:29,960 --> 00:30:34,960
Speaker 10: the items that kids these days want in footwear, athletic apparel,

620
00:30:35,960 --> 00:30:39,440
Speaker 10: and their exclusive sort of vertical brands are also doing very,

621
00:30:39,600 --> 00:30:42,760
Speaker 10: very well and that really supported that back to school

622
00:30:43,000 --> 00:30:45,040
Speaker 10: and it gives a lot of optimism when we think

623
00:30:45,080 --> 00:30:47,000
Speaker 10: about holiday and the fourth quarter coming out.

624
00:30:47,320 --> 00:30:49,760
Speaker 3: So I realized that Best Buy and Dick's are different stores,

625
00:30:49,840 --> 00:30:52,960
Speaker 3: but the way you describe dick spoorting goods, it feels

626
00:30:52,960 --> 00:30:54,520
Speaker 3: like it should have been the same for Best Buy

627
00:30:54,680 --> 00:30:57,520
Speaker 3: right back to school. They do have some exclusive items,

628
00:30:57,560 --> 00:30:58,000
Speaker 3: et cetera.

629
00:30:58,160 --> 00:30:58,520
Speaker 6: Why not.

630
00:31:00,160 --> 00:31:02,720
Speaker 10: Yeah, So I think that's a great question, Alex. I think,

631
00:31:03,040 --> 00:31:05,480
Speaker 10: you know, when we think back three months ago, best

632
00:31:05,520 --> 00:31:09,520
Speaker 10: Buy had a great quarter and it was on back

633
00:31:09,600 --> 00:31:11,600
Speaker 10: to school for them. Back to school is a little

634
00:31:11,600 --> 00:31:13,920
Speaker 10: bit more college bias. It does hit a little bit

635
00:31:14,000 --> 00:31:18,680
Speaker 10: earlier in the year then Dix might benefit from and

636
00:31:19,120 --> 00:31:22,760
Speaker 10: the demand for laptops was very strong in the second quarter,

637
00:31:23,480 --> 00:31:25,960
Speaker 10: and you know, best Buy raised their guidance. There was

638
00:31:26,000 --> 00:31:27,960
Speaker 10: strong optimism that we were going to get back to

639
00:31:28,120 --> 00:31:31,560
Speaker 10: growth mode. I still think, you know, there's a possibility

640
00:31:31,640 --> 00:31:35,640
Speaker 10: for a strong holiday for Best Buy laptops did. They

641
00:31:35,680 --> 00:31:39,240
Speaker 10: were up comp sales seven percent in the third quarter,

642
00:31:39,800 --> 00:31:42,560
Speaker 10: but that was overridden by weakness in some of the

643
00:31:42,680 --> 00:31:48,880
Speaker 10: other categories, appliances, home theater being key ones. It sounds

644
00:31:49,160 --> 00:31:53,000
Speaker 10: like they're really leaning into promotions for the fourth quarter

645
00:31:53,520 --> 00:31:56,760
Speaker 10: and really looking to get aggressive with promotion, especially for

646
00:31:56,840 --> 00:32:00,560
Speaker 10: their premium product and things that are exclusive two best

647
00:32:00,720 --> 00:32:02,520
Speaker 10: Buy to really.

648
00:32:02,480 --> 00:32:05,560
Speaker 2: Draw that shopper in. How's it when you talk to

649
00:32:05,640 --> 00:32:08,640
Speaker 2: your retailer companies that you covered, lindsay, what are they

650
00:32:08,720 --> 00:32:11,600
Speaker 2: saying about just this whole holiday season when all is

651
00:32:11,600 --> 00:32:13,240
Speaker 2: said and done, how's it gonna? Are we gonna have

652
00:32:13,280 --> 00:32:15,840
Speaker 2: growth this year? So better than last year? How are

653
00:32:15,880 --> 00:32:16,560
Speaker 2: thy shaking out?

654
00:32:17,160 --> 00:32:17,440
Speaker 1: Really?

655
00:32:17,640 --> 00:32:17,840
Speaker 6: Yeah?

656
00:32:17,880 --> 00:32:21,320
Speaker 10: So growth looks pretty weak. I also think it's divergent

657
00:32:22,080 --> 00:32:25,120
Speaker 10: sort of like last year. So there's some categories that

658
00:32:25,240 --> 00:32:28,520
Speaker 10: are just in a better position. You know, beauty would

659
00:32:28,520 --> 00:32:31,160
Speaker 10: be one of those sports where you know, where Dix

660
00:32:31,280 --> 00:32:33,840
Speaker 10: is playing is also one of those where just demand

661
00:32:34,160 --> 00:32:36,880
Speaker 10: generally is a little bit stronger. And then we have

662
00:32:37,000 --> 00:32:41,440
Speaker 10: other categories that are still on the weaker side, home appliances,

663
00:32:42,040 --> 00:32:44,960
Speaker 10: and some of that still you know, obviously affects best Buy,

664
00:32:45,080 --> 00:32:49,080
Speaker 10: it also affects companies like william Sonoma RH. We also

665
00:32:49,160 --> 00:32:52,040
Speaker 10: have a bifurcation. I think in the consumer, you know,

666
00:32:52,120 --> 00:32:55,520
Speaker 10: a higher in consumer still seems to be holding up

667
00:32:55,560 --> 00:32:59,360
Speaker 10: pretty well. Dix is another benefactor there. You know, their

668
00:32:59,560 --> 00:33:03,240
Speaker 10: customer base is on the higher income side, whereas best

669
00:33:03,280 --> 00:33:05,959
Speaker 10: Buy is probably a little bit more like the average

670
00:33:06,000 --> 00:33:09,480
Speaker 10: of the overall country. So I think, you know, the

671
00:33:09,960 --> 00:33:13,120
Speaker 10: deal days that these companies are rolling out, you know,

672
00:33:13,160 --> 00:33:15,960
Speaker 10: they each have their own strategies on how they want

673
00:33:16,000 --> 00:33:19,320
Speaker 10: to manage that. But as I said, best Buy is

674
00:33:19,360 --> 00:33:21,920
Speaker 10: going to get very aggressive with those deals. The consumer

675
00:33:22,240 --> 00:33:26,040
Speaker 10: high or low income is very value focused, and we

676
00:33:26,160 --> 00:33:29,240
Speaker 10: may have seen a pause, you know, people holding back

677
00:33:29,360 --> 00:33:32,000
Speaker 10: waiting for those deals in the third quarter results.

678
00:33:32,480 --> 00:33:34,680
Speaker 3: Yeah, it's like she's describing me exactly.

679
00:33:35,360 --> 00:33:38,640
Speaker 2: Hey, lindsay, how about from an industry perspective, when I

680
00:33:38,920 --> 00:33:41,520
Speaker 2: if I ever find myself going into store which I

681
00:33:41,640 --> 00:33:43,640
Speaker 2: hope that doesn't happen. Am I going to find the

682
00:33:43,680 --> 00:33:44,480
Speaker 2: stuff I'm looking for?

683
00:33:44,680 --> 00:33:44,720
Speaker 9: Like?

684
00:33:44,800 --> 00:33:47,480
Speaker 2: Has everybody got the inventory they need?

685
00:33:47,560 --> 00:33:47,720
Speaker 9: Here?

686
00:33:47,800 --> 00:33:51,479
Speaker 2: I don't hear too many you know, supply chain stories anymore.

687
00:33:52,680 --> 00:33:56,840
Speaker 10: Yeah, So supply chain, the supply chain woes of COVID

688
00:33:57,000 --> 00:33:59,400
Speaker 10: have sort of gone away, you know. I think you know,

689
00:33:59,480 --> 00:34:02,480
Speaker 10: retailers you maybe a little over a year ago or

690
00:34:02,480 --> 00:34:06,000
Speaker 10: probably over inventoried. I think inventory is in a healthier

691
00:34:06,120 --> 00:34:08,880
Speaker 10: position this year, you know, for the retailer themselves, but

692
00:34:09,000 --> 00:34:12,160
Speaker 10: also for the shopper. And I think that the retailers

693
00:34:12,200 --> 00:34:15,760
Speaker 10: are working really hard to make that in store experience

694
00:34:16,040 --> 00:34:18,000
Speaker 10: a positive one for those that.

695
00:34:18,040 --> 00:34:18,560
Speaker 2: Go in store.

696
00:34:18,600 --> 00:34:21,040
Speaker 10: But there's also a lot of focus online, so that

697
00:34:21,200 --> 00:34:25,000
Speaker 10: online shopper, you know, best Buy is doing doorbusters again

698
00:34:25,120 --> 00:34:27,480
Speaker 10: this year, but it's it's for that in store shopper,

699
00:34:27,560 --> 00:34:29,799
Speaker 10: but also if you are a member and have the app,

700
00:34:29,880 --> 00:34:33,200
Speaker 10: you could also take advantage of that. So they're really

701
00:34:33,280 --> 00:34:36,799
Speaker 10: looking to you know, capitalize on that experience.

702
00:34:37,320 --> 00:34:40,520
Speaker 3: What about tariffs? What was the impact? How do they

703
00:34:40,600 --> 00:34:40,920
Speaker 3: manage it?

704
00:34:42,160 --> 00:34:46,279
Speaker 10: Yes, so best Buy they have talked about, you know,

705
00:34:46,520 --> 00:34:50,480
Speaker 10: as a big picture, as a percent of cogs, about

706
00:34:50,560 --> 00:34:55,880
Speaker 10: sixty percent of their inventory, you know, is manufactured in China.

707
00:34:56,480 --> 00:34:59,240
Speaker 10: That's about the same as where it was in eighteen

708
00:34:59,320 --> 00:35:04,640
Speaker 10: and nineteen. For the products that they have direct control over.

709
00:35:05,239 --> 00:35:08,480
Speaker 10: The exposure is low, and they've sort of managed that down,

710
00:35:09,440 --> 00:35:11,239
Speaker 10: and they discussed on the call that, you know, the

711
00:35:11,320 --> 00:35:14,000
Speaker 10: burden of that cost is really going to be shared

712
00:35:14,120 --> 00:35:19,880
Speaker 10: between the manufacturer, supplier, the retailer, and the possibly the

713
00:35:19,960 --> 00:35:24,160
Speaker 10: consumer if it comes to that. Dick's exposure is pretty low.

714
00:35:25,040 --> 00:35:27,760
Speaker 10: When I look across my coverage, you know, elf Beauty

715
00:35:28,200 --> 00:35:31,120
Speaker 10: stands out. They have eighty percent of their supply chain

716
00:35:31,400 --> 00:35:36,320
Speaker 10: is manufactured in China, very highly exposed. A company like

717
00:35:36,440 --> 00:35:39,439
Speaker 10: that is looking to lean on price increases to sort

718
00:35:39,480 --> 00:35:40,760
Speaker 10: of manage that type of cost.

719
00:35:41,200 --> 00:35:44,160
Speaker 3: All right. Thanks to Lindsay Dutch, Bloomberg Intelligence Consumer Hardline

720
00:35:44,200 --> 00:35:44,920
Speaker 3: Senior Analyst.

721
00:35:45,360 --> 00:35:49,880
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722
00:35:50,080 --> 00:35:53,239
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723
00:35:53,320 --> 00:35:56,480
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724
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