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Speaker 1: This is Bloomberg Business Wait inside from the reporters and

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Speaker 1: editors who bring you America's most trusted business magazine, plus

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Speaker 1: global business finance and tech news. The Bloomberg Business Week

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Speaker 1: Podcast with Carol Messer and Tim Stenebeck from Bloomberg Radio.

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Speaker 2: So global MNA activity is gearing up for a spring renaissance,

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Speaker 2: with more than twenty billion of potential transactions emerging since

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Speaker 2: the weekend, the latest charge being led by merk which

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Speaker 2: agreed yesterday to buy Prometheus Biosciences for about ten point

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Speaker 2: eight billion works out to about two hundred in cash,

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Speaker 2: continuing a theme of large biotechs looking for ways to

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Speaker 2: boost pipelines and portfolios of new drugs. It's an old story,

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Speaker 2: We've seen this before. It is also the latest boost

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Speaker 2: for deal makers in healthcare, which is one of the

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Speaker 2: few sectors justice to fight.

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Speaker 3: The global slump.

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Speaker 2: At M and A.

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Speaker 3: We are seeing activity here.

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Speaker 4: And with more on that, we do have Sam Fazelli,

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Speaker 4: who's the senior pharmaceutical analyst at Bloomberg Intelligence on Zoo

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Speaker 4: from London and Sam, I'm looking at shares of Prometheus Biosciences.

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Speaker 4: That's tickersible. Rx DX is about seventy percent on peace

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Speaker 4: Sport's best day since early December. Breakdown this deal for us.

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Speaker 5: Yeah, Hi, So basically what we've got is merk is

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Speaker 5: going after a drug that has shown which is the

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Speaker 5: key asset that Prometheus has, that has shown very good

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Speaker 5: at efficacy, accepting that his cross trial comparisons or either

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Speaker 5: not being competitive to head, it seems to be the

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Speaker 5: best efficacy that we've seen so far in treating inflammatory

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Speaker 5: bowel disease, and that's a big market.

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Speaker 6: J and J alone has a drug called Stellara.

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Speaker 5: Where of course it's used in other indications too, and

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Speaker 5: that could be the same for Prometheus's drug is doing

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Speaker 5: close to ten billion.

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Speaker 6: Dollars expectation this year. So you know, then when you put.

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Speaker 5: That into context, ten point eighty billion dollars doesn't stand

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Speaker 5: like a lot at least from this basic assessment. But

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Speaker 5: of course commercial dynamics could be very different when this

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Speaker 5: drug comes to market in twenty twenty six.

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Speaker 2: Yeah, I'm just going to say, right, that's a few

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Speaker 2: years from now, and you know better than most sam

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Speaker 2: about the you know, drug trial process. You know there

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Speaker 2: could be some stumbling blocks. So but you would assume

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Speaker 2: that Mark has done its homework in a big way here.

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Speaker 5: Sure, but this is a this is an early stage trial.

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Speaker 5: When you go into larger base three trials.

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Speaker 6: Different kinds of things can surface. But I'm not necessarily

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Speaker 6: worried about spiderfecks.

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Speaker 5: I mean that is a risk that drug companies take

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Speaker 5: day in, day out, or the efficause it doesn't pan

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Speaker 5: out as well as it did in the smaller trial.

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Speaker 5: What I think is interesting going to be interesting is

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Speaker 5: that the same drug that I mentioned earlier, Johnson and

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Speaker 5: Johnson's drug.

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Speaker 6: Stillara, is going off patent imminently.

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Speaker 5: So this is this peak year and in twenty twenty

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Speaker 5: four it's going to be going losing.

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Speaker 6: Market share to buy a similar drugs it will be cheaper.

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Speaker 5: So when Mark comes to market with this drug, where

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Speaker 5: will it be positioned? Will you people be forced to

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Speaker 5: use the Laura first and if they fail, then they

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Speaker 5: use permifew drug, which would then take longer to ramp

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Speaker 5: up sales.

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Speaker 4: Sam, I know MRK is really focused when it comes

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Speaker 4: to oncology, but I know it's key drug, key Truda.

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Speaker 4: It's estimated to bring in around forty three percent of

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Speaker 4: its revenues by the end of twenty twenty four. Now,

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Speaker 4: as far as the expiration is concerned, it's still wilder.

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Speaker 4: But is this really a key play as far as

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Speaker 4: the patent front, as far as what it can do

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Speaker 4: to still boost those revenues once that patent does expire.

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Speaker 5: Yeah, So the patent expires in twenty twenty eight, and

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Speaker 5: we don't think that they're going to be able to

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Speaker 5: push that much further.

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Speaker 6: Of course, it doesn't.

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Speaker 5: Expire everywhere at the same time, so it's going to

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Speaker 5: be a relatively speaking, at that point, expectations are about

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Speaker 5: thirty three billion dollars of sales, but we think that

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Speaker 5: it could lose about seventeen over the next two years,

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Speaker 5: and that's what consensus has in their expects.

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Speaker 6: So will you be able to replace seventeen billion? That's

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Speaker 6: a big ask.

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Speaker 5: There are other drugs in this pipeline that are looking

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Speaker 5: really good from previous acquisitions and this will help, but

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Speaker 5: we don't think that it's going to be quite enough

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Speaker 5: to make up that difference. That therefore they'll need more

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Speaker 5: deals or at least more drugs coming out of their

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Speaker 5: own pipeline.

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Speaker 2: Hey, Sam, I mean we've seen this movie before, right,

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Speaker 2: you know, the big pharmaceutical companies have drugs coming off

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Speaker 2: patent and then they got to figure out how to

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Speaker 2: beef up their patent pipeline. I mean, is that what

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Speaker 2: is at this point once again driving so the acquisition

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Speaker 2: mode if you will, among the big drug companies.

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Speaker 6: Yes, it is exactly that.

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Speaker 5: You know, we've got estimates of over three hundred billion

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Speaker 5: dollars worth of drugs exposed to pattern the experience by

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Speaker 5: twenty thirty.

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Speaker 6: Now that doesn't mean that's the sales that lose, but

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Speaker 6: that's a big number. Over some period of time post

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Speaker 6: twenty thirty.

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Speaker 5: They will lose some of those sales to competition, So

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Speaker 5: they're going to have to be able to replace.

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Speaker 6: Is that some people will do a better job of

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Speaker 6: replacing than others.

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Speaker 5: Time will tell, but they certainly need this and there's

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Speaker 5: going to be more in Mana to get through this.

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Speaker 2: I am also curious Sam that kind of what's on

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Speaker 2: everybody's radar. We talk to various folks in the medical

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Speaker 2: community and just in the innovative space and disruptive space,

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Speaker 2: and they talk about the human genome and you personalized,

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Speaker 2: individualized drugs, and I'm thinking, also, we're coming off the

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Speaker 2: pandemic and I'm thinking about what we might need next

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Speaker 2: and messenger RNA right, that led to the development of

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Speaker 2: those drugs. What are some of the things that are

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Speaker 2: on your radar that you think are probably on the

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Speaker 2: radar of you know, a mercer, a Pfizer and others

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Speaker 2: out there.

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Speaker 6: Yeah, I mean there are. There's so much going on

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Speaker 6: in science. Prometheus is an example of that. This is

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Speaker 6: a completely new target.

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Speaker 5: Being developed for this inflammatory disease, which has seen quite

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Speaker 5: a lot of innovation.

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Speaker 6: There are patients with psoriasis, which is pretty bad.

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Speaker 5: Disorder that that see one diseaser mission or skin clearance

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Speaker 5: with some of these newer drugs. So immunology is exploding.

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Speaker 5: Our understanding of immunology is exploding, which frankly touches every

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Speaker 5: disease that there is. And so the more in depth

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Speaker 5: understanding of immunology will have, the better we'll be able

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Speaker 5: to target some of these diseases. At the same time,

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Speaker 5: the modalities that we can do it with are expanding

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Speaker 5: protein degraders, things that can downregulate the amount of a protein.

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Speaker 6: That's produced, even if it's not a standard way of

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Speaker 6: doing pharmacology. So there's that element. There's the modern a vaccines,

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Speaker 6: there are the gene editing technologies all targeted at trying

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Speaker 6: to stall single gene diseases.

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Speaker 5: Or targeting immune system disorders, which, as I said, is

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Speaker 5: involved in every pretty much every disease that there is.

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Speaker 4: And Sam I was curious about what you think this

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Speaker 4: says about the macro and the economy as far as

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Speaker 4: a sign of confidence if you have these c suite

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Speaker 4: executives that want to put more money to work, and

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Speaker 4: particularly obviously when we're talking about the pharmaceutical.

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Speaker 6: Industry, yep.

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Speaker 5: I mean, look at the end of the day, when

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Speaker 5: you have that drug that's been become such a success,

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Speaker 5: not just for your P and L, but also for patients.

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Speaker 5: And I'm talking about Key Truder here as an example,

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Speaker 5: you need to do something.

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Speaker 6: You can't just sit back.

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Speaker 5: And let's not forget pharmaceutical companies are not impacted by

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Speaker 5: the macro environment as much as consumer stocks or tech

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Speaker 5: or etc.

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Speaker 6: They are less.

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Speaker 5: Sensitive to interest rate rises because they're very high cash generative,

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Speaker 5: highly cash generative, so they're in a position to exercise

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Speaker 5: this power. And thank god, because at the end of

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Speaker 5: the day, we do need the drugs that they're bringing

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Speaker 5: into market, and they are making a difference, putting the

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Speaker 5: pricing discussion aside, because that's a whole different kettle of fish.

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Speaker 2: Yeah, it's pretty remarkable though you think about what Pfizer

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Speaker 2: was it last month bought Siegen for forty three billion.

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Speaker 2: I mean, there's so much going on in the space. Hey,

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Speaker 2: any thoughts if you will, Sam, on Prometheus, it's trained

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Speaker 2: below two hundred. We know that two hundred in cash

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Speaker 2: was what Mark put out for it. Does that mean

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Speaker 2: anything significantly to you just quickly?

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Speaker 6: Not really? Not really.

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Speaker 5: I mean if you look at Merk's current areas of

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Speaker 5: activity in this disease area.

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Speaker 6: There really don't. I don't really think there's much competition.

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Speaker 6: The drug is early stage, is high risk.

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Speaker 5: I think this is just six months of waiting for

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Speaker 5: it to close, or a few months of waiting for

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Speaker 5: it to close on that gap will likely close.

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Speaker 6: So I don't read too much into this.

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Speaker 2: Okay, well, good, good to get some perspective and fun

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Speaker 2: to have kind of another m and a Monday, which

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Speaker 2: we don't always have, or it has it feels like

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Speaker 2: we haven't in a while.

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Speaker 3: Hey, Sam, thank you so much.

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Speaker 2: I know it's a little bit later out there in London,

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Speaker 2: so appreciate you hanging around so we could talk with you.

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Speaker 2: Sam Fazzelli, he's Bloomberg Intelligence senior pharmaceutical analyst, as we said,

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Speaker 2: joining us zoom from London. Check out Bloomberg dot com

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Speaker 2: for some of the additional research by Sam and the

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Speaker 2: team and some of the other reporting when it comes

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Speaker 2: to this acquisition. But it is typically you know about

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Speaker 2: the pipeline, Jess. That's what it's about for these big

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Speaker 2: pharmaceutical companies. You know, if you know covering business news

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Speaker 2: a lot, you see this, these cycles that go through

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Speaker 2: for these companies that have these blockbusters that bring in

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Speaker 2: so much money, and then they go off patent and

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Speaker 2: then they've got to think about, okay, what brings in

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Speaker 2: revenues from right?

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Speaker 4: And when you think about how much cash these companies

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Speaker 4: were sitting on in the pandemic, Carol, and then wondering

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Speaker 4: what do we do with the money? Well, particularly with

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Speaker 4: the pharmaceutical giants, maybe more M and.

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Speaker 2: A yeah, exactly, and we've seen a fair amount already

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Speaker 2: this year.

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Speaker 1: You're listening to the Bloomberg Business Week podcast. Catch us

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Speaker 7: It's not easy being green, having to spend each day

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Speaker 7: the color of the leaves.

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Speaker 2: All right, everybody, a little kermit for you, because we're

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Speaker 2: all talking about being green, We're going to talk about

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Speaker 2: farming and growing green something. This next company knows a

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Speaker 2: lot about it, and I've got to say, you know,

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Speaker 2: we've been talking about this a lot here Jess on air.

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Speaker 2: We recently caught up with the founder and CEO of

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Speaker 2: the ag tech company Regrow, and a lot is going

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Speaker 2: on when it comes to farming, food and the AG space,

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Speaker 2: which is really seeing some disruption and also growth in

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Speaker 2: terms of the market size. So let's get into it

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Speaker 2: with someone who's well versed and embedded in the agg

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Speaker 2: and farming space. We welcome Irving Fine, founder and CEO

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Speaker 2: Barry Farming, which is backed by GV formerly Google Ventures.

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Speaker 2: He joins us via zoom in New York City. Irving,

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Speaker 2: I've been looking forward to having you on air. Welcome

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Speaker 2: and good to have you here. First of all, how

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Speaker 2: should do you think the world think about modern arming?

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Speaker 8: You know, it's it's an important question, and I imagine

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Speaker 8: at some point you all have talked about. You know,

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Speaker 8: we have a big and important farm bill that is

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Speaker 8: coming up again quite soon, and so not only does

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Speaker 8: the world need to be thinking about farming, but this

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Speaker 8: country is very specifically thinking about farming. And you know,

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Speaker 8: one of the statistics that I think a lot of

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Speaker 8: people always find surprising or often find surprising, is that

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Speaker 8: agriculture is actually the second largest source of global greenhouse

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Speaker 8: gas emissions, right after the production of electricity and heat.

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Speaker 8: So it actually accounts for a bigger slice of greenhouse

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Speaker 8: gas emissions than the transportation sector, which you all were

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Speaker 8: just talking about. And so when you think about what

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Speaker 8: does modern farming need to look like, one of the

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Speaker 8: critical recognition that we all need to have is there

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Speaker 8: is no path to that zero. There is no path

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Speaker 8: to decarbonization that doesn't lead directly through all of agriculture.

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Speaker 8: And so the question you're asking is an extraordinarily important

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Speaker 8: question for all of us to answer, not only in

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Speaker 8: the next few years, but in the next few decades,

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Speaker 8: as we need to transition to a more sustainable system

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Speaker 8: that needs to feed a lot more people.

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Speaker 2: Are we doing it yet? I mean, I feel like

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Speaker 2: you're involved in it. There's definitely pockets. But I also

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Speaker 2: think about industrial farming. It's massive and controls a lot.

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Speaker 3: So where are we in.

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Speaker 2: Not only thinking about it, but doing something differently that's

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Speaker 2: better for our world?

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Speaker 8: So massive it is, and changing a system that is

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Speaker 8: as large and embedded as sort of broad based industrial

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Speaker 8: agriculture is is not something that happens overnight. And I

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Speaker 8: think you can just look towards the energy sector, the

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Speaker 8: transportation sector, which are in many ways far ahead of

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Speaker 8: where we are agriculturally, to see how long real transformational

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Speaker 8: change takes. And you know, I think there's an interesting

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Speaker 8: statistic that really answers your question more effectively than anything

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Speaker 8: I can say, which is, for every gigaton of CO

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Speaker 8: two that's generated annually by the combined global energy and

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Speaker 8: transportation sectors, fifty one billion dollars was invested in low

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Speaker 8: carbon energy transition in twenty twenty two. So for every

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Speaker 8: gigaton of CO two that was generated from energy and transportation,

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Speaker 8: there's fifty one billion spent for low carbon transition in

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Speaker 8: twenty twenty two. At the same period, the transition to

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Speaker 8: cleaner and more efficient agriculture got two billion dollars of

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Speaker 8: investment for every gig aton, so twenty five time difference.

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Speaker 8: And so are we moving, Yes, we're moving, and yes

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Speaker 8: there's a lot of innovation, there's a lot of excitement,

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Speaker 8: but what is very clear is we're not moving as

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Speaker 8: quickly and as aggressively enough as we really need to.

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Speaker 8: When you think about how substantial the food and agriculture

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Speaker 8: ecosystem is for the entirety of the global population.

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Speaker 4: Irving take a step back and talk to us more

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Speaker 4: specifically about Bowery Farming and specifically what your company does.

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Speaker 8: Absolutely so, our belief at Bowery is that wherever food

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Speaker 8: is needed, we can grow it, and we do that

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Speaker 8: by growing in warehouse scale smart growing environments. We stack

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Speaker 8: our crops from the floor all the way up to

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Speaker 8: the ceiling. We grow under lights that mimic the spectrum

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Speaker 8: of the sun, and we grow in a totally controlled

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Speaker 8: and contained environment, so we can grow three hundred and

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Speaker 8: sixty five days of the year, independent of weather, independent

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Speaker 8: of seasonality, so it's reliable, consistent supply of pure produce

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Speaker 8: year round. On top of it, we grow completely pesticide

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Speaker 8: free and agrochemical free food. And whereas in the field

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Speaker 8: that not only hurts your quality and productivity in our case.

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Speaker 8: First of all, our produce is really the purest expression

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Speaker 8: of what you would imagine came out of your grandmother's garden,

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Speaker 8: and it's one hundred times more productive than a square

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Speaker 8: foot of farmland, all the while using a very small

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Speaker 8: fraction of water compared to traditional.

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Speaker 2: Agriculture packed on the environment, the footprint much smaller. Forgive

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Speaker 2: me for interrupting, but so absolutely, how does it compare.

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Speaker 2: I'm just thinking for people who are listening, how does

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Speaker 2: it compare from traditional in terms of the impact.

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Speaker 8: It is fractional, so ninety percent plus less water than

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Speaker 8: traditional farming, uses no pesticides, no herbicides, no fungicides, no insecticides.

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Speaker 8: And there's even more benefits beyond this, because number one,

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Speaker 8: we locate our farms close to the actual points of consumption,

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Speaker 8: so our product is harvested and delivered within twenty four

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Speaker 8: to thirty six hours versus weeks of time in the

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Speaker 8: traditional agricultural supply chain, and oftentimes even months. That means

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Speaker 8: you're wasting less food, it's fresher when it shows up,

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Speaker 8: and it's more nutritious. You also are reducing all the

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Speaker 8: transportation miles that are required in today's existing supply chain.

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Speaker 8: So in many respects, what we are doing is actually

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Speaker 8: reinventing the fresh food supply chain, and we're building a

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Speaker 8: supply chain it's simpler, it's safe, it has much more

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Speaker 8: surety of supply, and it's a lot more sustainable than

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Speaker 8: the existing system today.

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Speaker 4: How does this exactly reshape the food patterns if we're

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Speaker 4: talking about either gen Z or millennials.

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Speaker 8: In a number of ways. I think this is meeting

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Speaker 8: consumers where they are and what they're looking for. So

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Speaker 8: Number one, what allows us to do what we do

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Speaker 8: at Ballery is leveraging an enormous amount of technological innovation

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Speaker 8: that's occurred over the last decade or so. We certainly

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Speaker 8: leverage improvements in lighting and LEDs, but it's also leveraging

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Speaker 8: artificial intelligence, computer vision, software, center and control systems, automation

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Speaker 8: and robotics. It forms the intelligence layer across our farm

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Speaker 8: and allows us to automate the entire process from when

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Speaker 8: we plant the seed to when we harvest the product

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Speaker 8: and put it into a package. And the reason that's

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Speaker 8: important is it both allows us to be more sustainable,

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Speaker 8: it allows the product to be safer, and it's using

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Speaker 8: technology and smart and effective ways to produce a more

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Speaker 8: sustainable system that we sell a product today at or

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Speaker 8: below the cost of field grown organic and so consumers

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Speaker 8: are looking for that sustainable solution. They're looking for technological

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Speaker 8: solutions to age old problems and systems that we've lived in.

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Speaker 8: But they don't want those solutions to cause them to

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Speaker 8: have to bend their lifestyles an excessive amount. And that's

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Speaker 8: where and how we can use technology effectively to deliver

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Speaker 8: the solution. We do about and cost.

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Speaker 2: Remind us about cost differentials between what you guys are

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Speaker 2: doing and what kind of the rest of the are

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Speaker 2: much of the ag space is doing.

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Speaker 8: We are selling at or below the cost of field

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Speaker 8: grown organic products today, and we sell across We are

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Speaker 8: the largest into vertical farming company in the US now

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Speaker 8: eighteen hundred plus retail doors. We work with Amazon and

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Speaker 8: Whole Foods and Walmart and safe Way, Albertson's, and I'll

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Speaker 8: hold so many of the grocery stores that you all

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Speaker 8: shop and.

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Speaker 2: Know and Irving. I know I've had the benefit of

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Speaker 2: talking with you earlier this year at this incredible dinner

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Speaker 2: that you and your team hosted and you brought together

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Speaker 2: you know, people from different walks of life, I feel like,

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Speaker 2: and it was just a really rich conversation about what's

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Speaker 2: going on in terms of food, food production and how

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Speaker 2: we think about wellness and the importance of food production

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Speaker 2: in our wellness.

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Speaker 3: So when you think about.

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Speaker 2: What's going on in the food space, it's going to

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Speaker 2: require a lot of parties right in order to get

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Speaker 2: it right.

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Speaker 8: Absolutely, And you know, like any large scale system that's

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Speaker 8: global in nature and that in essence touches every person

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Speaker 8: on the planet, the notion that there's a single silver bullet,

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Speaker 8: a single industry, you know, let alone a single company,

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Speaker 8: is of course false and would never be the case.

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Speaker 8: And so again not the point to the energy decarbonization

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Speaker 8: and transition. But there are so many different companies and

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Speaker 8: approaches that we're seeing play out in that space. And similarly,

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Speaker 8: we are going to need many different ways to approach

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Speaker 8: the new agricultural ecosystem. We're going to need lots of

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Speaker 8: different solutions, and we're gonna need to look at every

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Speaker 8: aspect of the agricultural ecosystem as well. And you know,

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Speaker 8: we're talking today about farming and fresh food production, but

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Speaker 8: equally we have to look very closely at animal agriculture

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Speaker 8: and how that is transpiring and taking place. We need

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Speaker 8: to look at food waste in general and how that's handled.

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Speaker 8: We need to look at developing countries across the world

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Speaker 8: and the way they're farming, their actual availability of not

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Speaker 8: only capital but actual tools, and the types of understanding

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Speaker 8: that we have and the access to equipment and to

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Speaker 8: inputs and things that we have in the developing world

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Speaker 8: that they may not have access to which can raise yields.

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Speaker 8: It is a large scale problem that will need many people,

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Speaker 8: lots of capital and a lot a lot of focus

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Speaker 8: and attention in the coming decades.

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Speaker 5: Well, and what I.

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Speaker 2: Wonder too, and I think this came up at the

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Speaker 2: dinner that you guys hosted, is that when we talked

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Speaker 2: about plant based proteins which haven't necessarily lived up to

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Speaker 2: what thought they were going to be and they're ten years,

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Speaker 2: you know, right old and counting whether it's beyond impossible

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Speaker 2: and a lot of other players. Everybody was so excited,

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Speaker 2: but it hasn't quite worked out how we thought. Is

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Speaker 2: there going to still be you know, a really important

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Speaker 2: role for plant based protein in your view, because I

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Speaker 2: know you reach out and really are looking at things

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Speaker 2: on a bigger level.

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Speaker 8: So you know, I don't in some ways there was

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Speaker 8: a structural disadvantage that plant based protein had, and you

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Speaker 8: could argue whether or not they created this on their own,

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Speaker 8: but this notion that they themselves and the set of

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Speaker 8: companies were going to be able to displace the entirety

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Speaker 8: or even a huge portion of the traditional meat industry,

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Speaker 8: that's a really tall task. That's difficult, and more importantly,

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Speaker 8: is it possible. Absolutely, But something like that will take

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Speaker 8: time no matter what. And so what plant based proteins

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Speaker 8: absolutely have been able to do is they've shined the

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Speaker 8: light and they've brought into the forefront the conversation about

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Speaker 8: how animal agriculture is affecting the planet, how it's affecting

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Speaker 8: our health. I mean, we spoke about this at that dinner.

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Speaker 8: But the calorie calculation is about ten calories in for

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Speaker 8: one calorie out when it comes to meat. So if

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Speaker 8: I said to you, Carol, hey, listen, I'm going to

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Speaker 8: give you a dollar and you give me ten dollars,

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Speaker 8: I think that that would not be a trade that

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Speaker 8: you would want to make. And that is essentially our

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Speaker 8: current trade in the industrial agriculture system when it comes

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Speaker 8: to meat, and plant based proteins are helping people realize

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Speaker 8: whether it's animal welfare, whether it's the environmental impact, and

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Speaker 8: it's not just the animals themselves, it's all of the

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Speaker 8: crops that we have to grow to feed the animals,

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Speaker 8: many of which we grow in this country and we

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Speaker 8: end up sending overseas to support ecosystems in other countries

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Speaker 8: and other regions. There are better ways to do this.

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Speaker 8: Plant based proteins are shining a light on it. And

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Speaker 8: what you're going to see now, in my view, is

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Speaker 8: cell based agriculture is really beginning to grow. It's beginning

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Speaker 8: to take shape. It's very early stages, but it's the

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Speaker 8: ability to essentially grow animal protein in a laboratory that

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Speaker 8: is in many ways indistinguishable from an actual animal protein

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Speaker 8: that comes from an animal. It just has a fractional

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Speaker 8: environmental footprint and actually doesn't require the land, the feed

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Speaker 8: and everything else that we need today. Is this a

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Speaker 8: next year's solution, right? Absolutely not, but this is coming

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Speaker 8: absolutely irving.

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Speaker 2: Having said that, then do you envision a world and

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Speaker 2: I don't know whether it's five years, ten years, twenty years,

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Speaker 2: where most of our food is produced inside in labs

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Speaker 2: in you know, gardens like you guys have hydroponic inside

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Speaker 2: because climate change is unstable and in terms of just

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Speaker 2: productivity demands that we're going to have to be you know,

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Speaker 2: making everything kind of inside.

441
00:22:52,520 --> 00:22:54,960
Speaker 8: So it's a great question, and I think it's worth

442
00:22:55,040 --> 00:22:57,040
Speaker 8: just taking a step back for a second and realizing

443
00:22:57,840 --> 00:23:01,280
Speaker 8: the problem that we are solving ultimately is that the

444
00:23:01,320 --> 00:23:04,480
Speaker 8: world around us, in particularly our climate, is becoming increasingly

445
00:23:04,560 --> 00:23:07,960
Speaker 8: unreliable and unstable. And all you have to do is

446
00:23:08,040 --> 00:23:09,639
Speaker 8: look at what's happening on the west coast of the

447
00:23:09,720 --> 00:23:12,760
Speaker 8: US right now. We were talking about the twelve hundred

448
00:23:12,840 --> 00:23:16,480
Speaker 8: year mega drought in California and the southwest of the US,

449
00:23:16,800 --> 00:23:20,560
Speaker 8: which still very much is present, had very real impacts

450
00:23:20,560 --> 00:23:24,000
Speaker 8: on agricultural output over the past three years. Now, over

451
00:23:24,000 --> 00:23:27,080
Speaker 8: this winter, we have these atmospheric river events, and we

452
00:23:27,119 --> 00:23:30,160
Speaker 8: have record snowpack in the Sierras, and we've gone from

453
00:23:30,359 --> 00:23:33,560
Speaker 8: heavy drought conditions to enormous flooding in the fields of

454
00:23:33,560 --> 00:23:36,479
Speaker 8: the Central Valley where the majority of our food, our

455
00:23:36,520 --> 00:23:38,800
Speaker 8: fresh food comes from, over the course of the next

456
00:23:38,800 --> 00:23:43,080
Speaker 8: six eight months. It is a different problem and a

457
00:23:43,160 --> 00:23:45,840
Speaker 8: different extreme on the other side of the spectrum, and

458
00:23:46,040 --> 00:23:49,000
Speaker 8: meteorologists and experts in this area say we're not done

459
00:23:49,000 --> 00:23:51,880
Speaker 8: with the drought that will be back, and so this

460
00:23:52,080 --> 00:23:55,679
Speaker 8: increasing amount of unreliable and uncertainty is going to demand

461
00:23:55,840 --> 00:23:59,760
Speaker 8: that we put systems in place that can actually much

462
00:23:59,800 --> 00:24:03,119
Speaker 8: more effectively hedge against that. What we're doing at Bowery

463
00:24:03,160 --> 00:24:06,720
Speaker 8: and indoor agriculture is absolutely important and will be a

464
00:24:06,880 --> 00:24:10,480
Speaker 8: very large part of the agricultural ecosystem moving forward. But

465
00:24:10,560 --> 00:24:12,760
Speaker 8: I would never tell you that all food will be

466
00:24:12,800 --> 00:24:15,679
Speaker 8: grown indoors. It is too large of the industry, it

467
00:24:15,760 --> 00:24:18,520
Speaker 8: is too broad. We're talking about a global industry, a

468
00:24:18,560 --> 00:24:23,760
Speaker 8: global problem, and there is places for outdoor agriculture, indoor agriculture,

469
00:24:24,000 --> 00:24:28,480
Speaker 8: traditional animal proteins, cell based proteins, plant based meat. This

470
00:24:28,560 --> 00:24:32,119
Speaker 8: is a many lead bullets and no silver bullet problem,

471
00:24:32,200 --> 00:24:32,800
Speaker 8: without question.

472
00:24:33,359 --> 00:24:36,080
Speaker 4: So is it easier to do this as a private

473
00:24:36,160 --> 00:24:39,680
Speaker 4: company or is it make more sense to go public.

474
00:24:41,280 --> 00:24:44,200
Speaker 8: I think what's exciting about what we're doing is food

475
00:24:44,280 --> 00:24:47,560
Speaker 8: and the opportunity that we're going after is enormous and

476
00:24:47,560 --> 00:24:51,159
Speaker 8: it's durable and irrespective of what's going on cyclically in

477
00:24:51,200 --> 00:24:54,159
Speaker 8: an economy, people need to eat and this is important.

478
00:24:54,440 --> 00:24:57,280
Speaker 8: And when we look at our opportunity just for crops

479
00:24:57,280 --> 00:25:00,760
Speaker 8: that are good candidates for us at Bowery a trillion

480
00:25:00,840 --> 00:25:03,399
Speaker 8: dollar plus a year global opportunity. So there is an

481
00:25:03,560 --> 00:25:06,919
Speaker 8: enormous amount of to growth. Still, we are fractional compared

482
00:25:07,119 --> 00:25:09,879
Speaker 8: to the opportunity in front of us. And so right now,

483
00:25:09,960 --> 00:25:13,159
Speaker 8: as a private company, investing in innovation, investing in the

484
00:25:13,200 --> 00:25:16,840
Speaker 8: foundational technology that we need to develop to do this

485
00:25:16,880 --> 00:25:19,800
Speaker 8: effectively is the right decision for us. But you can

486
00:25:19,880 --> 00:25:22,480
Speaker 8: absolutely see what we're doing at Bowery as a standalone

487
00:25:22,520 --> 00:25:23,600
Speaker 8: public business. At some point.

488
00:25:23,640 --> 00:25:24,840
Speaker 3: Hey, you know one thing I'm thinking about.

489
00:25:24,840 --> 00:25:27,280
Speaker 2: We're getting ready to head out to Milkin and they are,

490
00:25:27,600 --> 00:25:30,359
Speaker 2: you know, the Milk and Global Institute, their annual big event,

491
00:25:30,840 --> 00:25:34,119
Speaker 2: and it really is this cross section between finance and wellness,

492
00:25:34,160 --> 00:25:38,960
Speaker 2: and they often I've monitored moderated panels out there about

493
00:25:39,000 --> 00:25:43,560
Speaker 2: food and food production in particular. Is the money flowing

494
00:25:43,680 --> 00:25:45,639
Speaker 2: in too where it kind of needs to do to

495
00:25:45,720 --> 00:25:47,480
Speaker 2: get to a food system that we're going to need

496
00:25:47,480 --> 00:25:50,159
Speaker 2: in the future, that is better for the environment, that

497
00:25:50,280 --> 00:25:53,120
Speaker 2: is much more productive and also healthier.

498
00:25:54,359 --> 00:25:57,040
Speaker 8: I think this points to the stat I mentioned earlier.

499
00:25:57,280 --> 00:26:00,760
Speaker 8: Is there money flowing absolutely, But when you think about

500
00:26:00,760 --> 00:26:04,120
Speaker 8: the fact that twenty five times more investment is going

501
00:26:04,119 --> 00:26:08,399
Speaker 8: towards in twenty twenty two energy and transportation decarbonization, and

502
00:26:08,480 --> 00:26:13,040
Speaker 8: yet agriculture is the second large green gas by a

503
00:26:13,280 --> 00:26:17,680
Speaker 8: very not far behind that twenty five times delta. To me,

504
00:26:17,960 --> 00:26:22,560
Speaker 8: doesn't speak to a recognition and acknowledgment of the urgency

505
00:26:22,960 --> 00:26:25,560
Speaker 8: and size of the opportunity in front of us.

506
00:26:25,600 --> 00:26:27,880
Speaker 2: What's holding it back thirty seconds? Serving do we need,

507
00:26:27,880 --> 00:26:29,680
Speaker 2: like an Elon musk to just kind of rip off

508
00:26:29,680 --> 00:26:30,240
Speaker 2: the band aid?

509
00:26:30,240 --> 00:26:30,920
Speaker 3: What do we need?

510
00:26:32,800 --> 00:26:36,240
Speaker 8: Strangely, we all interact with the food system every single

511
00:26:36,280 --> 00:26:40,199
Speaker 8: day of our lives. Yet I'm often amazed it just

512
00:26:40,240 --> 00:26:43,840
Speaker 8: people don't know a lot about what's underneath the products buy.

513
00:26:43,920 --> 00:26:45,920
Speaker 8: We go into the grocery store, we pick something off

514
00:26:45,920 --> 00:26:48,280
Speaker 8: the shelf. I mean, you think about early COVID, when

515
00:26:48,280 --> 00:26:50,320
Speaker 8: we were all shocked that our grocery store shelves are

516
00:26:50,320 --> 00:26:52,720
Speaker 8: empty because we'd taken for granted that when we needed

517
00:26:52,720 --> 00:26:55,040
Speaker 8: a product that would be there. But in fact, it's

518
00:26:55,080 --> 00:26:58,359
Speaker 8: this long, complicated global supply chain that allows that to

519
00:26:58,400 --> 00:27:01,960
Speaker 8: be a reality. And people are beginning to understand really

520
00:27:02,000 --> 00:27:04,760
Speaker 8: what allows our food system and our agricultural ecosystem to

521
00:27:04,840 --> 00:27:08,240
Speaker 8: exist in the way that it does. But increased knowledge

522
00:27:08,280 --> 00:27:11,840
Speaker 8: and increased awareness and increased understanding will only lead to

523
00:27:12,240 --> 00:27:16,800
Speaker 8: more investment, more entrepreneurs focusing problem and the returns are there.

524
00:27:17,119 --> 00:27:17,840
Speaker 8: It's about that.

525
00:27:17,960 --> 00:27:19,720
Speaker 2: Well, so glad we got to catch up and I

526
00:27:19,760 --> 00:27:22,560
Speaker 2: look forward to next time already Irving Fain, Founder and

527
00:27:22,640 --> 00:27:26,040
Speaker 2: chief executive Officer Barry Farming joining us via zoom from

528
00:27:26,119 --> 00:27:26,879
Speaker 2: New York City.

529
00:27:28,600 --> 00:27:32,200
Speaker 1: You're listening to the Bloomberg Business Week podcast. Catch us

530
00:27:32,240 --> 00:27:36,240
Speaker 1: live weekday afternoons from three to six Eastern on Bloomberg Radio,

531
00:27:36,440 --> 00:27:39,720
Speaker 1: the Bloomberg Business app, and YouTube. You can also listen

532
00:27:39,800 --> 00:27:42,920
Speaker 1: live on Amazon Alexa from our flagship New York station.

533
00:27:43,359 --> 00:27:47,800
Speaker 1: Just say Alexa, play Bloomberg eleven thirty.

534
00:27:47,680 --> 00:27:50,920
Speaker 2: Here's some data points for everybody. According to the latest estimates,

535
00:27:51,160 --> 00:27:54,000
Speaker 2: nearly three hundred and twenty nine million terabytes of data

536
00:27:54,080 --> 00:27:57,720
Speaker 2: are created each day. It's a lot, and no doubt

537
00:27:57,760 --> 00:28:00,000
Speaker 2: about it, Chess. We're living in a data centric world.

538
00:28:00,240 --> 00:28:00,880
Speaker 3: We get that.

539
00:28:00,920 --> 00:28:04,360
Speaker 2: We talk about it constantly. We talk about retail using it,

540
00:28:04,440 --> 00:28:07,440
Speaker 2: you know, to learn more about us and our buying habits.

541
00:28:07,520 --> 00:28:09,959
Speaker 2: We talk about, you know, all the search giants they

542
00:28:10,040 --> 00:28:11,880
Speaker 2: use it in terms of advertising, right it is kind

543
00:28:11,880 --> 00:28:13,080
Speaker 2: of everywhere.

544
00:28:12,760 --> 00:28:15,480
Speaker 4: It does, it follows us and obviously are different types

545
00:28:15,480 --> 00:28:18,600
Speaker 4: of patterns, so you can't really escape it at this point, Carol.

546
00:28:18,840 --> 00:28:20,920
Speaker 2: No, and it can be put to really good use

547
00:28:20,920 --> 00:28:22,840
Speaker 2: when it comes to maybe creating better software.

548
00:28:22,840 --> 00:28:23,440
Speaker 5: And we know that.

549
00:28:23,480 --> 00:28:25,640
Speaker 2: And so that's where our next guest comes in. Whose

550
00:28:25,640 --> 00:28:28,520
Speaker 2: company just raised fifty million in a series dfunding. So

551
00:28:28,600 --> 00:28:30,760
Speaker 2: let's get to it. Christine Yan is co founder and

552
00:28:30,840 --> 00:28:34,600
Speaker 2: CEO of Honeycomb. She joins us via zoom from Rena Reno.

553
00:28:34,720 --> 00:28:37,760
Speaker 2: Excuse me, Reno, Nevada. I always say Nevada wrong, and

554
00:28:37,800 --> 00:28:40,360
Speaker 2: I always have all my friends Christine yelling at me like,

555
00:28:40,440 --> 00:28:42,440
Speaker 2: don't you know how to say it? And so instead

556
00:28:42,480 --> 00:28:44,959
Speaker 2: I scribed Reno, Reno, Reno. I can't believe that.

557
00:28:45,640 --> 00:28:47,000
Speaker 3: Welcome, Welcome, How are you?

558
00:28:48,120 --> 00:28:49,520
Speaker 9: I'm excellent, happy Monday?

559
00:28:49,560 --> 00:28:52,960
Speaker 2: How are you happy Monday? I'm doing okay too. Tell

560
00:28:53,040 --> 00:28:55,280
Speaker 2: us about your company and how like kind of tapping

561
00:28:55,280 --> 00:28:58,680
Speaker 2: into your time at Facebook specifically maybe helped you create

562
00:28:58,840 --> 00:29:01,200
Speaker 2: I feel like almost a face book for tech engineers

563
00:29:01,200 --> 00:29:04,000
Speaker 2: to kind of work together and create better code.

564
00:29:04,080 --> 00:29:05,160
Speaker 3: So talk to us about it.

565
00:29:06,160 --> 00:29:08,600
Speaker 9: Yeah, in a nutshell, my co founder and I met

566
00:29:08,720 --> 00:29:13,239
Speaker 9: actually had a company before Facebook, and we were, you know,

567
00:29:13,360 --> 00:29:17,000
Speaker 9: two engineers on opposite sides of sort of the spectrum

568
00:29:17,040 --> 00:29:19,360
Speaker 9: of engineering, if that makes sense. She was very focused

569
00:29:19,360 --> 00:29:22,560
Speaker 9: on back end infrastructure. I was building our analytics product.

570
00:29:23,120 --> 00:29:28,480
Speaker 9: And you know, this company that we were employees at,

571
00:29:29,000 --> 00:29:32,120
Speaker 9: we're building this very complex software system. We beating the

572
00:29:32,120 --> 00:29:35,600
Speaker 9: engineer supporting that had to all the time figure out

573
00:29:35,640 --> 00:29:37,760
Speaker 9: what was going on, why our software was not behaving

574
00:29:37,760 --> 00:29:41,520
Speaker 9: the way that we expected. And you know, when when

575
00:29:41,560 --> 00:29:44,920
Speaker 9: smaller companies get up by bigger companies, it's coming for

576
00:29:44,920 --> 00:29:47,360
Speaker 9: the bigger company to push all the big company tools

577
00:29:47,360 --> 00:29:49,240
Speaker 9: on a smaller company and say here, here are the

578
00:29:49,240 --> 00:29:53,040
Speaker 9: big kid toys. And for the most part, we were

579
00:29:53,120 --> 00:29:56,400
Speaker 9: skeptical that, you know, Facebook built for Facebook would make

580
00:29:56,440 --> 00:30:00,520
Speaker 9: sense for our system. But there was one and this

581
00:30:00,600 --> 00:30:05,480
Speaker 9: one tool that sort of shed all of the typical

582
00:30:05,520 --> 00:30:07,920
Speaker 9: patterns that we'd seen in how tools can work with

583
00:30:07,960 --> 00:30:10,360
Speaker 9: data to help engineering teams make sense of why is

584
00:30:10,400 --> 00:30:15,520
Speaker 9: the software misbehaving? And despite being skeptics to begin with,

585
00:30:16,280 --> 00:30:20,920
Speaker 9: we found that this internal tool changed changed how we

586
00:30:20,960 --> 00:30:23,760
Speaker 9: thought about software, changed how we thought about what it

587
00:30:23,800 --> 00:30:26,560
Speaker 9: meant for code to go life, and when each of

588
00:30:26,640 --> 00:30:29,920
Speaker 9: us were thinking about leaving Facebook. You know, we both

589
00:30:29,960 --> 00:30:31,800
Speaker 9: had the thought of I don't want to have to

590
00:30:31,960 --> 00:30:36,040
Speaker 9: do that thing again without this internal tool. And so

591
00:30:36,120 --> 00:30:38,200
Speaker 9: really what brought us together is wanting to bring this

592
00:30:38,280 --> 00:30:43,680
Speaker 9: tool to the masses through the lens of folks who

593
00:30:43,680 --> 00:30:45,160
Speaker 9: are skeptical about it to begin with.

594
00:30:45,560 --> 00:30:47,520
Speaker 3: So how does the tool actually work.

595
00:30:48,800 --> 00:30:49,040
Speaker 5: Well?

596
00:30:49,400 --> 00:30:51,560
Speaker 9: With any of these data tools, we take in massive

597
00:30:51,560 --> 00:30:54,560
Speaker 9: amounts of data and really effect in the end we

598
00:30:54,640 --> 00:30:58,120
Speaker 9: allow users to ask questions of that data. What's special

599
00:30:58,120 --> 00:31:01,800
Speaker 9: about this particular UH this problem space, and then I'll

600
00:31:01,840 --> 00:31:02,520
Speaker 9: talk about the tool.

601
00:31:03,160 --> 00:31:03,800
Speaker 5: Is that.

602
00:31:05,480 --> 00:31:07,840
Speaker 9: Some of the examples of data use that you described

603
00:31:07,840 --> 00:31:10,760
Speaker 9: and the lead into this segment are all you know,

604
00:31:10,960 --> 00:31:13,880
Speaker 9: on the business side, they are all assuming that the

605
00:31:13,920 --> 00:31:16,080
Speaker 9: software is doing what the software does, that if you

606
00:31:16,120 --> 00:31:19,160
Speaker 9: click check out on your shopping cart, that you actually,

607
00:31:19,600 --> 00:31:21,520
Speaker 9: you know, you're able to check out with that item.

608
00:31:21,800 --> 00:31:25,520
Speaker 9: Our software UH is intended more for the software engineering

609
00:31:25,560 --> 00:31:28,200
Speaker 9: teams who are on the hook when you click check

610
00:31:28,200 --> 00:31:31,240
Speaker 9: out and you can't actually check out with your with

611
00:31:31,280 --> 00:31:35,520
Speaker 9: your purchase. When that happens, the engineering teams go, oh, no,

612
00:31:36,680 --> 00:31:40,120
Speaker 9: you know, what assumptions do we make that we're wrong?

613
00:31:40,720 --> 00:31:44,040
Speaker 9: Do we have a logical error somewhere, is the person

614
00:31:44,440 --> 00:31:45,960
Speaker 9: is the you know, is it not actually a person

615
00:31:46,040 --> 00:31:46,600
Speaker 9: clicking checkout?

616
00:31:46,680 --> 00:31:47,200
Speaker 5: Is it a bot?

617
00:31:47,400 --> 00:31:48,080
Speaker 6: It should should?

618
00:31:48,440 --> 00:31:51,760
Speaker 9: Is it behaving correctly and not letting the bot check out?

619
00:31:52,440 --> 00:31:56,880
Speaker 9: All of these questions rely on a massive amount of

620
00:31:56,920 --> 00:32:01,000
Speaker 9: data as you touched on, but really that really quick

621
00:32:01,080 --> 00:32:05,000
Speaker 9: response times. You know, if your e commerce site not

622
00:32:05,040 --> 00:32:07,520
Speaker 9: able to let your customers check out, those are real

623
00:32:07,560 --> 00:32:12,240
Speaker 9: dollars flying out the window and speed really really matters.

624
00:32:13,560 --> 00:32:17,680
Speaker 2: So this tool brings people together, engineers specifically, right too, Okay,

625
00:32:17,840 --> 00:32:19,880
Speaker 2: there's a bug or something or I can't check out.

626
00:32:19,920 --> 00:32:21,480
Speaker 2: Oh my god, Carol's got to be really ticked off,

627
00:32:21,480 --> 00:32:23,040
Speaker 2: but we got to fix this, you know what I mean? Like,

628
00:32:23,400 --> 00:32:25,560
Speaker 2: So that's what your tool does.

629
00:32:25,480 --> 00:32:28,840
Speaker 9: Right exactly exactly, And what.

630
00:32:28,800 --> 00:32:31,920
Speaker 4: Does this mean exactly for the growth in your business?

631
00:32:31,960 --> 00:32:33,560
Speaker 4: How's it spurred more of that?

632
00:32:35,320 --> 00:32:35,640
Speaker 3: Well?

633
00:32:35,920 --> 00:32:37,960
Speaker 9: One of the things that seems to always be true

634
00:32:37,960 --> 00:32:40,840
Speaker 9: with engineers is we want to build bigger and better things,

635
00:32:41,440 --> 00:32:43,160
Speaker 9: and as new technologies come out, we want to play

636
00:32:43,160 --> 00:32:47,240
Speaker 9: with these new technologies. And many of the recent changes

637
00:32:47,320 --> 00:32:50,240
Speaker 9: in this in our software space have made the systems

638
00:32:50,240 --> 00:32:53,280
Speaker 9: that we've built more complicated. And when when the building

639
00:32:53,320 --> 00:32:56,320
Speaker 9: blocks that you're using are more complicated. The tools that

640
00:32:56,360 --> 00:32:59,120
Speaker 9: you use like Honeycomb to make sense of are these

641
00:32:59,160 --> 00:33:02,360
Speaker 9: building blocks put together in the right way? Also need

642
00:33:02,440 --> 00:33:05,880
Speaker 9: to need to be also more flexible to manage that complexity.

643
00:33:06,320 --> 00:33:09,000
Speaker 9: And so, you know, we've all seen the world as

644
00:33:09,040 --> 00:33:13,160
Speaker 9: moving online as consumer, I know my expectations of you know,

645
00:33:13,160 --> 00:33:16,240
Speaker 9: how fast and reliable a piece of software have increased.

646
00:33:16,880 --> 00:33:19,120
Speaker 9: That shifts a lot of the expectations onto these engineering

647
00:33:19,160 --> 00:33:21,920
Speaker 9: teams that need to ensure that their software is behaving

648
00:33:22,480 --> 00:33:26,200
Speaker 9: in the face of all this increased complexity and increased expectation.

649
00:33:26,320 --> 00:33:29,640
Speaker 2: Christine, you guys shared some numbers. Momentum in twenty twenty

650
00:33:29,640 --> 00:33:32,760
Speaker 2: two achieved another consecutive year of two times revenue growth,

651
00:33:32,920 --> 00:33:35,360
Speaker 2: drove over one hundred and sixty percent net revenue retention

652
00:33:35,720 --> 00:33:40,320
Speaker 2: for six hundred plus customers globally. Has Generative AI changed that, like,

653
00:33:40,440 --> 00:33:44,680
Speaker 2: are you even in more demand? Because this is complicated

654
00:33:44,800 --> 00:33:48,640
Speaker 2: stuff and you're going to need those engineers really working together.

655
00:33:48,680 --> 00:33:52,240
Speaker 2: And just got about a minute or so left short answers.

656
00:33:52,320 --> 00:33:54,320
Speaker 9: Yes, I think that we're just on the cusp. We

657
00:33:54,360 --> 00:33:58,120
Speaker 9: haven't seen you know, right now, engineering teams everywhere are

658
00:33:58,320 --> 00:34:02,200
Speaker 9: thinking about how to incorporate generated AI. But absolutely, anytime

659
00:34:02,520 --> 00:34:05,680
Speaker 9: you incorporate a black box into your system, you know

660
00:34:05,720 --> 00:34:09,160
Speaker 9: that the AI is making decisions, engineering teams needed. Are

661
00:34:09,200 --> 00:34:10,880
Speaker 9: the humans are going to be on the hook to

662
00:34:10,920 --> 00:34:12,960
Speaker 9: figure out why they made those decisions and what are

663
00:34:12,960 --> 00:34:15,400
Speaker 9: those are the right things? So absolutely I think that

664
00:34:15,400 --> 00:34:18,720
Speaker 9: this space is only it has only just begun.

665
00:34:19,360 --> 00:34:23,160
Speaker 2: So your space of this observability which I had never

666
00:34:23,200 --> 00:34:26,839
Speaker 2: heard of, this concept, you know, how is that thing

667
00:34:26,920 --> 00:34:29,120
Speaker 2: or not? When you create, you know that is going

668
00:34:29,160 --> 00:34:31,600
Speaker 2: to be something even more important in this more kind

669
00:34:31,600 --> 00:34:33,839
Speaker 2: of complicated AI space. And I'm just curious, does that

670
00:34:33,880 --> 00:34:36,200
Speaker 2: mean you are already seeing more demand for your products?

671
00:34:36,239 --> 00:34:38,080
Speaker 2: And just get about thirty forty seconds.

672
00:34:38,840 --> 00:34:41,440
Speaker 9: I think the demand for our products is correlated with

673
00:34:41,560 --> 00:34:46,439
Speaker 9: just general instant interest in cloud generative AI. Absolutely is increasing,

674
00:34:47,000 --> 00:34:50,400
Speaker 9: you know, cloud commitments and clouds to spend across the board,

675
00:34:50,719 --> 00:34:54,040
Speaker 9: but it's still early and absolutely I think that there's

676
00:34:54,160 --> 00:34:55,480
Speaker 9: a lot of exciting times ahead of us.

677
00:34:55,560 --> 00:34:55,680
Speaker 5: Now.

678
00:34:55,680 --> 00:34:57,879
Speaker 2: It makes sense and in terms of a space where

679
00:34:57,880 --> 00:35:00,160
Speaker 2: these guys can work or these you know, women and

680
00:35:00,440 --> 00:35:04,759
Speaker 2: men everybody kind of work together on a program really

681
00:35:04,840 --> 00:35:08,440
Speaker 2: makes sense. Christine very cool, Christin Yah, Chief executive officer

682
00:35:08,440 --> 00:35:14,719
Speaker 2: co founder of Honeycomb. Joining us from Reno, Nevada by zoom.

683
00:35:14,760 --> 00:35:19,120
Speaker 1: This is Bloomberg Business Wait inside from the reporters and

684
00:35:19,280 --> 00:35:22,840
Speaker 1: editors who bring you America's most trusted business magazine, plus

685
00:35:22,920 --> 00:35:27,080
Speaker 1: global business, finance and tech news. The Bloomberg Business Week

686
00:35:27,120 --> 00:35:32,279
Speaker 1: Podcast with Carol Messer and Tim Stenebek from Bloomberg Radio.

687
00:35:34,520 --> 00:35:37,480
Speaker 7: Bomarcle.

688
00:35:37,920 --> 00:35:40,600
Speaker 6: The Journal. Now about you, let me drive?

689
00:35:41,120 --> 00:35:45,000
Speaker 1: No no, no, no, honey, please.

690
00:35:47,000 --> 00:35:51,320
Speaker 6: Wait, I want to drive. It's a good question.

691
00:35:55,080 --> 00:35:57,680
Speaker 7: This is the Drive to the Clothes dot Com.

692
00:35:58,440 --> 00:36:01,480
Speaker 1: Well by around each other down on Bloomberg Radio.

693
00:36:01,719 --> 00:36:03,640
Speaker 2: All right, everybody, just got about eighteen minutes left in

694
00:36:03,680 --> 00:36:04,960
Speaker 2: today's trading session.

695
00:36:05,080 --> 00:36:05,880
Speaker 3: We've got stocks hit.

696
00:36:05,920 --> 00:36:07,680
Speaker 2: We're in the green, so we're off our worst levels

697
00:36:07,680 --> 00:36:09,400
Speaker 2: of the session, as you just heard from Charlie. But

698
00:36:10,239 --> 00:36:12,520
Speaker 2: just call it a little changed on the day. We

699
00:36:12,560 --> 00:36:14,799
Speaker 2: really are just getting into the thick of earnings and

700
00:36:15,000 --> 00:36:18,200
Speaker 2: trying to make sense and just on guard about any

701
00:36:18,239 --> 00:36:19,800
Speaker 2: other problems in the banking sector.

702
00:36:19,960 --> 00:36:22,720
Speaker 3: So, I mean, Jess, volume, what's volume like today?

703
00:36:22,880 --> 00:36:25,080
Speaker 4: I mean, still it's not as high as you would

704
00:36:25,120 --> 00:36:27,399
Speaker 4: think relative to the last twenty days, and I think

705
00:36:27,440 --> 00:36:28,879
Speaker 4: a lot of that is just the same things we've

706
00:36:28,880 --> 00:36:32,040
Speaker 4: been talking about, Carol waiting on those more regional banks.

707
00:36:32,080 --> 00:36:34,399
Speaker 4: Let's say on Thursday we're going to get clear Third

708
00:36:35,040 --> 00:36:37,200
Speaker 4: Key Corp as well US Bank. So I think that's

709
00:36:37,239 --> 00:36:38,959
Speaker 4: really more of the focus leader on this week.

710
00:36:39,000 --> 00:36:40,640
Speaker 2: All right, So let's get to it with our guests.

711
00:36:40,640 --> 00:36:43,400
Speaker 2: Back with us is Doug Cioka, CEO and partner at

712
00:36:43,440 --> 00:36:46,240
Speaker 2: Kavar Capital Partners. They've got over a billion in assets

713
00:36:46,280 --> 00:36:49,400
Speaker 2: under management, based as you know, in Leewood, Kansas and

714
00:36:49,520 --> 00:36:51,760
Speaker 2: joining us on the phone once again actually.

715
00:36:51,800 --> 00:36:54,520
Speaker 3: Via zoom via zoom, Hey we can see you. How

716
00:36:54,560 --> 00:36:54,880
Speaker 3: are you?

717
00:36:55,960 --> 00:36:57,719
Speaker 10: I'm great? How are you do it?

718
00:36:57,760 --> 00:36:58,120
Speaker 3: Okay?

719
00:36:58,200 --> 00:37:00,640
Speaker 2: Trying to keep up with the flow here and trying

720
00:37:00,680 --> 00:37:02,880
Speaker 2: to make sense. You know, it's funny. I wanted to

721
00:37:02,920 --> 00:37:04,880
Speaker 2: kind of kick it off with you, Doug. Earlier with

722
00:37:04,960 --> 00:37:07,840
Speaker 2: Romayne and Scarlett, the four of us were talking about

723
00:37:07,920 --> 00:37:09,799
Speaker 2: and Scarlet brought up what's going on with the VIX

724
00:37:09,880 --> 00:37:12,640
Speaker 2: and it's what below eighteen? I think seventeen and change.

725
00:37:12,880 --> 00:37:15,839
Speaker 2: I don't quite get it. Sixteen ninety seven. Do you

726
00:37:15,920 --> 00:37:17,760
Speaker 2: care about the VIX? Do you think it's a reliable

727
00:37:17,760 --> 00:37:20,480
Speaker 2: indicator of something? Because it just feels like we're in

728
00:37:20,480 --> 00:37:23,440
Speaker 2: this market environment where we're not quite sure what's next,

729
00:37:23,480 --> 00:37:25,799
Speaker 2: and yet there feels like a fair amount of complacency.

730
00:37:26,520 --> 00:37:28,560
Speaker 11: Yeah, and we may have used a little bit of

731
00:37:29,000 --> 00:37:31,560
Speaker 11: maybe pulled forward some of this year's last year, Carol.

732
00:37:31,600 --> 00:37:33,359
Speaker 10: I think last year there were forty.

733
00:37:33,040 --> 00:37:36,560
Speaker 11: Six different trading days with two percent moves up or down,

734
00:37:37,320 --> 00:37:40,000
Speaker 11: and actually it was twenty three and twenty three equally divided,

735
00:37:40,000 --> 00:37:41,040
Speaker 11: which is pretty fantastic.

736
00:37:41,360 --> 00:37:42,560
Speaker 10: And this year I think we've had two.

737
00:37:43,160 --> 00:37:48,080
Speaker 11: So I think we saw so much fitful trading, indecision obviously,

738
00:37:48,200 --> 00:37:52,080
Speaker 11: credit exported equity volatility, and this year, even though you

739
00:37:52,120 --> 00:37:54,120
Speaker 11: know what, the Fed may have one more hike and

740
00:37:54,160 --> 00:37:56,160
Speaker 11: maybe they won't cut as much as the markets and

741
00:37:56,239 --> 00:37:59,319
Speaker 11: pricing in, I think there is a set of a

742
00:37:59,320 --> 00:38:01,080
Speaker 11: bit of complacency that's setting in.

743
00:38:01,280 --> 00:38:02,000
Speaker 10: I think more than.

744
00:38:01,920 --> 00:38:05,439
Speaker 11: Anything, it's just that an exhaustion with the type better

745
00:38:05,520 --> 00:38:08,520
Speaker 11: day training activity that become the norm throughout twenty twenty two.

746
00:38:08,800 --> 00:38:11,759
Speaker 2: Is it exhaustion or is it signs of we're kind

747
00:38:11,760 --> 00:38:13,680
Speaker 2: of finishing up or getting near the end of this

748
00:38:13,920 --> 00:38:14,680
Speaker 2: market cycle.

749
00:38:15,280 --> 00:38:17,439
Speaker 11: Yeah, I think nothing's been as bad as had been

750
00:38:17,640 --> 00:38:21,120
Speaker 11: anticipated going into twenty twenty three, even when you throw

751
00:38:21,200 --> 00:38:25,759
Speaker 11: in the issues that had transpired with the banking mini crisis, right,

752
00:38:25,800 --> 00:38:28,920
Speaker 11: And I think when you saw what had transpired with

753
00:38:28,960 --> 00:38:33,160
Speaker 11: this fear of contagion, that very anxious weekend, weren't sure

754
00:38:33,239 --> 00:38:35,399
Speaker 11: what if any additional deposits are going to be covered

755
00:38:35,400 --> 00:38:36,600
Speaker 11: by the FDIC of the FED.

756
00:38:37,040 --> 00:38:38,640
Speaker 10: And then it just kind of played.

757
00:38:38,440 --> 00:38:41,080
Speaker 11: Itself out and we realized that some of the additional

758
00:38:41,080 --> 00:38:43,840
Speaker 11: liquidity could be a bit of a sav or otherwise

759
00:38:43,880 --> 00:38:47,040
Speaker 11: deeper wounds that could have transpired, even though it may

760
00:38:47,080 --> 00:38:49,920
Speaker 11: have been kind of the sword that caused the affliction

761
00:38:49,960 --> 00:38:50,440
Speaker 11: to begin with.

762
00:38:50,920 --> 00:38:53,920
Speaker 4: Doug, let's talk about earning seasons. We've gotten a number

763
00:38:53,960 --> 00:38:56,359
Speaker 4: of these bigger banks as well as regional banks. Now,

764
00:38:56,520 --> 00:38:59,680
Speaker 4: I know you're thinking more this is obviously more backward looking,

765
00:38:59,680 --> 00:39:01,680
Speaker 4: but you look a year out, earnings growth is supposed

766
00:39:01,680 --> 00:39:04,759
Speaker 4: to be back to double digits. What are you expecting?

767
00:39:04,840 --> 00:39:06,359
Speaker 4: And is that why you might have a little bit

768
00:39:06,360 --> 00:39:08,480
Speaker 4: more of an optimistic look when you are seeing earnings

769
00:39:08,480 --> 00:39:09,520
Speaker 4: improving a year from now.

770
00:39:10,400 --> 00:39:11,760
Speaker 10: Yeah, it's a great question, Jessin.

771
00:39:11,760 --> 00:39:13,880
Speaker 11: I think one of the things that's been so pronounced

772
00:39:13,880 --> 00:39:16,800
Speaker 11: this year and it's only been one quarter, but patience

773
00:39:16,840 --> 00:39:18,480
Speaker 11: has been kind of the enemy of performance.

774
00:39:18,600 --> 00:39:18,759
Speaker 5: Right.

775
00:39:18,840 --> 00:39:22,760
Speaker 11: The valuation gap going into twenty twenty three between international

776
00:39:22,920 --> 00:39:26,640
Speaker 11: and domestic closed very quickly. High tech sector went from

777
00:39:26,680 --> 00:39:31,040
Speaker 11: like incredible laggard to darling leader. The banking issues pulled

778
00:39:31,040 --> 00:39:32,560
Speaker 11: for the bulk of the Bond movie that we'd hope

779
00:39:32,560 --> 00:39:35,680
Speaker 11: we'd see throughout all of twenty twenty three. So when

780
00:39:35,680 --> 00:39:38,480
Speaker 11: you consider what's happening in earnings, we try to overlay

781
00:39:38,520 --> 00:39:41,520
Speaker 11: this whole concept of a rolling recession, right, And that's

782
00:39:41,560 --> 00:39:46,080
Speaker 11: just another way of characterizing right relative value of certain

783
00:39:46,200 --> 00:39:49,880
Speaker 11: sectors based upon a few things correlation with interest rates,

784
00:39:49,880 --> 00:39:52,719
Speaker 11: with underlying economic growth, and with sentiment. So when you're

785
00:39:52,719 --> 00:39:55,360
Speaker 11: an environment for which we think is going to be

786
00:39:55,440 --> 00:39:59,440
Speaker 11: higher for longer interest rates, slowish economic growth, sectors that

787
00:39:59,600 --> 00:40:05,880
Speaker 11: benefit from scale, from inelastic demand, from low leverage from

788
00:40:06,120 --> 00:40:09,759
Speaker 11: multinational distribution networks, those should hold investors' interest, and we're

789
00:40:09,800 --> 00:40:12,719
Speaker 11: starting to see that as they're coming to kind of

790
00:40:12,719 --> 00:40:17,480
Speaker 11: the earnings reporting table in healthcare, staples, communication services, and

791
00:40:17,520 --> 00:40:20,879
Speaker 11: then even outside of those within the royal recession camp,

792
00:40:21,239 --> 00:40:25,239
Speaker 11: you have idiosyncratic sort of tackle opportunities and sectors like

793
00:40:25,440 --> 00:40:29,040
Speaker 11: energy and IT sectors like agriculture, because even those supply

794
00:40:29,120 --> 00:40:33,160
Speaker 11: lines have improved supply hasn't. So we're seeing that an

795
00:40:33,239 --> 00:40:37,080
Speaker 11: overestimation of just how negative kind of the economic client

796
00:40:37,120 --> 00:40:39,359
Speaker 11: twenty twenty two is going to have and impacting their

797
00:40:39,360 --> 00:40:41,520
Speaker 11: profit models and it's just not materialized.

798
00:40:41,600 --> 00:40:43,360
Speaker 2: So is this a market where we can kind of

799
00:40:43,360 --> 00:40:47,600
Speaker 2: make smart decisions, Doug, based on fundamentals versus kind of

800
00:40:47,600 --> 00:40:49,000
Speaker 2: a technical trade?

801
00:40:49,080 --> 00:40:51,680
Speaker 11: I think so, right everyone, It's probably overused expression on

802
00:40:51,680 --> 00:40:54,560
Speaker 11: every program of our biggest stock pickers market, but I

803
00:40:54,600 --> 00:40:56,480
Speaker 11: do think, right if you look at the last.

804
00:40:56,239 --> 00:41:01,320
Speaker 10: Three years, what's underperformed quality company has been left behind.

805
00:41:01,320 --> 00:41:04,280
Speaker 11: What's underporting more than quality sort of a subcategory dividend

806
00:41:04,280 --> 00:41:04,960
Speaker 11: paying stocks.

807
00:41:05,320 --> 00:41:08,040
Speaker 10: So if you have those two subsets that.

808
00:41:08,160 --> 00:41:12,840
Speaker 11: Are providing comfort in balot sheet income statement and valuations,

809
00:41:13,040 --> 00:41:15,280
Speaker 11: then yeah, I do think there can be specific spots

810
00:41:15,280 --> 00:41:18,960
Speaker 11: where you can actually see identifiable alpha generating opportunities.

811
00:41:19,000 --> 00:41:19,960
Speaker 10: No question, Doug.

812
00:41:20,000 --> 00:41:23,040
Speaker 4: You're talking about quality companies and dividend paying stocks. What

813
00:41:23,200 --> 00:41:27,080
Speaker 4: specific sectors or some industries are you recommending clients by

814
00:41:27,160 --> 00:41:27,560
Speaker 4: right now?

815
00:41:28,200 --> 00:41:32,280
Speaker 11: Yeah, So, going back to healthcare, staples, communication services, definitely

816
00:41:32,360 --> 00:41:34,880
Speaker 11: dipping our toe into some financial services companies where we

817
00:41:34,920 --> 00:41:37,880
Speaker 11: think just the valuation we're just blown out way beyond

818
00:41:37,880 --> 00:41:40,120
Speaker 11: anything that could have been deserved because of the expected

819
00:41:40,160 --> 00:41:42,799
Speaker 11: contagion with Silicon Value Bank and Signature Bank, and then

820
00:41:42,880 --> 00:41:45,160
Speaker 11: even like in places like agriculture, we think there's a

821
00:41:45,160 --> 00:41:45,960
Speaker 11: lot of opportunity.

822
00:41:46,239 --> 00:41:47,320
Speaker 3: Yeah, no, it's interesting.

823
00:41:47,320 --> 00:41:48,719
Speaker 2: You know, we've been spending a lot of time here,

824
00:41:48,760 --> 00:41:52,840
Speaker 2: Doug talking about kind of agriculture, what's going on, disruption, innovation.

825
00:41:52,960 --> 00:41:54,839
Speaker 2: We're going to have somebody on from Bowery Farming later,

826
00:41:54,920 --> 00:41:56,880
Speaker 2: but just there's a lot going on in that space

827
00:41:57,000 --> 00:41:59,520
Speaker 2: as the world tries to make sure there's enough food

828
00:41:59,520 --> 00:42:03,440
Speaker 2: for everybody where. Don't you want to be in this

829
00:42:03,520 --> 00:42:04,840
Speaker 2: fee That's a good.

830
00:42:04,719 --> 00:42:08,520
Speaker 10: Question, I think. You know, we were excited about extending duration.

831
00:42:08,280 --> 00:42:11,040
Speaker 11: Are fixed income portfolios, and then with the massive rally

832
00:42:11,040 --> 00:42:13,680
Speaker 11: we saw coming out of that second week in March,

833
00:42:14,160 --> 00:42:17,160
Speaker 11: issues with the financial with the banking sector, that was

834
00:42:17,239 --> 00:42:19,480
Speaker 11: kind of arbitraged away. So we don't want to be

835
00:42:19,520 --> 00:42:21,520
Speaker 11: too long in our duration right now in our fixed

836
00:42:21,520 --> 00:42:23,759
Speaker 11: income portfolios. You know, we don't want to be too

837
00:42:23,880 --> 00:42:26,560
Speaker 11: aggressive in growth sectors of the market because we just

838
00:42:26,560 --> 00:42:30,719
Speaker 11: don't think there's going to be any type of multiple expansion,

839
00:42:31,040 --> 00:42:31,560
Speaker 11: not when you.

840
00:42:31,520 --> 00:42:33,560
Speaker 10: Have a slower growing ecconomy and higher interest rates.

841
00:42:33,640 --> 00:42:35,720
Speaker 11: So even though it's been exciting to see what's happened

842
00:42:35,719 --> 00:42:37,520
Speaker 11: in tech, I think it could provide an opportunity to

843
00:42:37,560 --> 00:42:39,880
Speaker 11: take some profits in that area, particularly if you're in

844
00:42:39,960 --> 00:42:42,760
Speaker 11: a sector or a company that's seeing a pretty significant expansion.

845
00:42:42,800 --> 00:42:45,759
Speaker 2: They're multiple, all right, So more optimistic or more pessimistic

846
00:42:45,760 --> 00:42:50,360
Speaker 2: bottom line about the outlook sounds like optimisticistic.

847
00:42:49,320 --> 00:42:51,399
Speaker 11: Oh my gosh, but by a lot, right. I think

848
00:42:51,400 --> 00:42:53,879
Speaker 11: there are some interesting lessons we learned from the FED

849
00:42:54,000 --> 00:42:56,480
Speaker 11: coming out of this little banking crisis. Right, you can't

850
00:42:56,520 --> 00:42:59,240
Speaker 11: live in the lab and I think regulators are really

851
00:42:59,239 --> 00:43:02,040
Speaker 11: good and in plenting implementing policies to prevent.

852
00:43:01,800 --> 00:43:02,880
Speaker 10: The previous crisis.

853
00:43:03,239 --> 00:43:06,160
Speaker 11: And because of that, the messaging really really matters when

854
00:43:06,200 --> 00:43:09,160
Speaker 11: it gets convoluted, and when you see sort of babies

855
00:43:09,160 --> 00:43:12,759
Speaker 11: and bathwater indiscriminately sold and thrown out, that's where opportunity

856
00:43:12,800 --> 00:43:15,239
Speaker 11: really really lies very heavily with us. There's a really

857
00:43:15,239 --> 00:43:17,200
Speaker 11: cool piece you guys price over the weekend. It came

858
00:43:17,200 --> 00:43:21,040
Speaker 11: from Bloomberg Intelligence talking about this regime model. Yeah, it's

859
00:43:21,200 --> 00:43:23,759
Speaker 11: so obsessed about how we going to a recession, how

860
00:43:23,760 --> 00:43:25,719
Speaker 11: deep recession is going to be twenty three to twenty four,

861
00:43:26,160 --> 00:43:28,759
Speaker 11: What they talk about with really liable inputs is we

862
00:43:28,840 --> 00:43:29,399
Speaker 11: may have been in.

863
00:43:29,440 --> 00:43:31,879
Speaker 6: One yeah, and we really have to creating a lot.

864
00:43:31,800 --> 00:43:34,480
Speaker 10: Of reasons for being optimistic, which is depicting games.

865
00:43:35,160 --> 00:43:37,400
Speaker 2: I love the new quote the next story.

866
00:43:37,520 --> 00:43:38,399
Speaker 3: I wrote that love story.

867
00:43:38,560 --> 00:43:39,600
Speaker 2: Oh Jess wrote it?

868
00:43:40,040 --> 00:43:41,680
Speaker 3: Dogdoka? How great is that?

869
00:43:42,120 --> 00:43:42,400
Speaker 7: All right?

870
00:43:42,440 --> 00:43:44,680
Speaker 2: Doug b Well. Doug is CEO and partner at Kavar

871
00:43:44,760 --> 00:43:47,320
Speaker 2: Capital Partners, joining us from lee Wick, Kansas.

872
00:43:48,560 --> 00:43:53,440
Speaker 1: This is the Bloomberg Business Week Podcast Apple, Spotify, and

873
00:43:53,600 --> 00:43:57,080
Speaker 1: anywhere else you can get your podcast. Listen live weekday

874
00:43:57,080 --> 00:44:00,720
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875
00:44:00,719 --> 00:44:04,080
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876
00:44:04,120 --> 00:44:07,080
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877
00:44:07,280 --> 00:44:09,320
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