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The Future of Automation and AI with Honeywell CEO Vimal Kapur · Masters in Business

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Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. This is Masters in
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Speaker 1: Business with Barry Ritholt on Bloomberg Radio.
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Speaker 2: This week on the podcast, yet another extra special guest.
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Speaker 2: Vimal Kapoor is CEO and chairman of Honeywell. He's worked
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Speaker 2: there for the past thirty seven years, and not only
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Speaker 2: has he been overseeing a fascinating transition, Honeywell is in
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Speaker 2: the midst of breaking itself up into three distinct parts.
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Speaker 2: I thought this conversation was fascinating and I think you
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Speaker 2: will also with no further ado, my conversation with Honeywell's
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Speaker 2: Vimal Kapoor.
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Speaker 3: Pleasure Berry, thanks for hosting me.
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Speaker 2: Well, my pleasure to have you here. It's not very
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Speaker 2: often we get a member of the down industrials as
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Speaker 2: part of our guests. Let's start out a little bit
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Speaker 2: with your background. You received a degree in electronics engineering
1:07
Speaker 2: from the the par Institute of Engineering in in India.
1:10
Speaker 2: What was the original career plan?
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Speaker 3: Original carrier plan was to work then get a job.
1:16
Speaker 3: That that was a carrier plan. Yeah, that was a
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Speaker 3: carrier plan. And then you know, first I did two
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Speaker 3: small stints of a job and then I joined Honeywell
1:24
Speaker 3: in early eighty nine. It was a new company in India,
1:27
Speaker 3: so set up. So I ended up joining a startup
1:31
Speaker 3: because it was set up as a joint venture between
1:33
Speaker 3: two large companies. There's a large Indian company called Tata Group.
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Speaker 3: They joined the automobiles everything, so they invested in this venture.
1:42
Speaker 3: It's a big Honeywell with a lot of tech, and
1:44
Speaker 3: then they created this joint venture in which you show
1:47
Speaker 3: up and it's basically creating something from scratch. We had
1:51
Speaker 3: no revenue when I started. Our revenue was zero points
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Speaker 3: zero zero. So you learn how to build a company,
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Speaker 3: how you scale, You wear much people hats like in
2:00
Speaker 3: a startup, you don't have a very defined role. So
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Speaker 3: thenk that early experience of high flexibility and you know,
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Speaker 3: going through a very high pace in a short period
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Speaker 3: of time. That laid some very strong foundations. You know.
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Speaker 2: So in the United States, out in Silicon Valley, we
2:18
Speaker 2: noticed a lot of these startups. Where they end up
2:22
Speaker 2: certainly isn't where they began. There's usually a pivot or
2:26
Speaker 2: three or four. What was the original idea and the
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Speaker 2: joint venture and what did that eventually turn into?
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Speaker 3: They turned into what it was planned for because Honeywell,
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Speaker 3: they did not have its automation business footprint in India
2:38
Speaker 3: at that time you're talking forty years back. So they
2:40
Speaker 3: partnered with the local company to scale the business. They
2:43
Speaker 3: already had those products and capabilities in US and they
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Speaker 3: were trying to get into Asia and they formed partnerships
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Speaker 3: in few countries, India being one of them. And the
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Speaker 3: strategy was to penetrate the local market, develop the local capability,
2:55
Speaker 3: and we were able to do that quite well. So
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Speaker 3: it's not that we have to change our product strategy,
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Speaker 3: but we have to run learn as we go through.
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Speaker 3: We had intense local competition. How do you beat that?
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Speaker 3: How we create our own our own avenue stream there.
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Speaker 3: So it was a very successful story.
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Speaker 2: So you come up through the operating side, not so
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Speaker 2: much the Harvard Business School DeVos theory side. How much
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Speaker 2: of an advantage has that been as your career clicked
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Speaker 2: through all these different divisions.
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Speaker 3: I mean, I think it's an advantage to in a
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Speaker 3: way to work in a practical business because you have
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Speaker 3: to deal with actual problems which the business deal with.
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Speaker 3: And having worked in different businesses gave me an opportunity
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Speaker 3: to deal with a different customer situation, different end markets,
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Speaker 3: operational issue, commercial issue, product development issue, supply chain. So
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Speaker 3: I would say, I mean, there's no replacement of formal education. One.
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Speaker 3: I'm not suggesting that having a higher degree is a disadvantage,
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Speaker 3: but I would say that it is amount of advantage
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Speaker 3: to get practical experience. And I was benefiting from a
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Speaker 3: variety of experiences I got in my long career in Honeywell.
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Speaker 2: And you ran three very different businesses before becoming CEO
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Speaker 2: Process Solutions, Building Technologies, Performance Materials. Tell us, I mean
4:21
Speaker 2: those names seem sort of ambiguous, right, tell us a
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Speaker 2: little bit about what each of those three divisions get.
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Speaker 3: So process solution business is. You know, it provides automation
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Speaker 3: system in the energy sector. So energy sector, think about it, refining,
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Speaker 3: petrochemical plants, other oil and gas facilities, pipeline terminals, even
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Speaker 3: I would say facilities like which may paper metals and mining.
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Speaker 3: So these facilities are very complex in terms of their
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Speaker 3: operating procedures, and if they're not automated, it's nearly impossible
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Speaker 3: to run them. So this business provides a sophisticated automation
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Speaker 3: system to these large companies. So think about Axon and
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Speaker 3: Shell and BP as kind of a typical customer or
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Speaker 3: a Ramco in Middle East and at NOx, so this
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Speaker 3: serving these customer So this business was very global, is
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Speaker 3: very global even today the business still is very successful.
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Speaker 3: And I became CEO in twenty fourteen of this business
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Speaker 3: and Oil Downtown happened within six months of I becoming
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Speaker 3: the leader of the business. So you learn through tough experiences.
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Speaker 3: Oil price was from whatever one hundred and forty hundred
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Speaker 3: and fifty dollars to like a big nose dive, and
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Speaker 3: we did a lot of work in that downturn. Learned
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Speaker 3: a lot, but primarily or question, this business is all
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Speaker 3: of our sophisticated automation and complex facilities. And then I
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Speaker 3: moved to the building automation business, where we still do automation,
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Speaker 3: but now in this case buildings of different type hospitals, airports, schools,
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Speaker 3: university campuses, data centers. There the business model was very different.
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Speaker 3: Now you serve multiple building through variety of channel partners
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Speaker 3: across the world, and so our strength comes through product innovation,
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Speaker 3: our strength comes through channel management. Way different business model
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Speaker 3: compared to what I did in you know, in my
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Speaker 3: in my process automation days. And then performance material and technology,
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Speaker 3: very interesting business. They build technology. They build energy infrastructure.
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Speaker 3: So if you want to build a UH, if you
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Speaker 3: are a refiner, you buy crude, which we all hear
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Speaker 3: a lot about today to do you know, ongoing around conflict.
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Speaker 3: You don't sell crude, you sell product. You sell gasoline,
6:43
Speaker 3: you sell diesel, you sell jet fuel. So they have
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Speaker 3: options to make multiple products, and as the input changes
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Speaker 3: on a market needs changes, they need to decide what
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Speaker 3: are the options they have to build different offering. From
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Speaker 3: their perspective, this business provides technology to energy company to
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Speaker 3: build energy infrastructure. Because it's a molecule transformation converting one
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Speaker 3: molecule to another molecule. That's heavy technology involved behind it.
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Speaker 3: So performance material and technology provides technology to the customer
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Speaker 3: to build tech energy infrastructure. So very high technology or
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Speaker 3: research oriented business. You have a lot of chemical engineers
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Speaker 3: who are going to invent the next best technology and
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Speaker 3: you provide their technology to some very large companies. And
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Speaker 3: that was fascinating to lead that business, to see that
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Speaker 3: cycle of nomination and work in that business. So you
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Speaker 3: have very diverse experiences in variety of sectors, different business models,
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Speaker 3: which I'm benefiting today because now I have experience of
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Speaker 3: dealing with different markets in different situations, and that practical
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Speaker 3: experience helps you a lot as you really get into
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Speaker 3: your CEO job.
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Speaker 2: So in twenty twenty two, you were name chiefing officer.
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Speaker 2: We were just coming out of the pandemic. What was
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Speaker 2: that environment like? How did you take your experience at
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Speaker 2: these three prior divisions where you were either president or
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Speaker 2: president and CEO? Howd that affect running operations?
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Speaker 3: I mean, I think at that time. The biggest challenge
8:21
Speaker 3: that time actually was the chip shortages and how do
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Speaker 3: we really redesign our products because chips are simply not available,
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Speaker 3: So we really had to learn how do we redesign
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Speaker 3: our products in a much shorter period of time. So
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Speaker 3: think about if we designed a product in one year,
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Speaker 3: we had to do that in two months because there's
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Speaker 3: no other option. If we don't do that, we can't
8:40
Speaker 3: have an alternative source of supply and we can't shape
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Speaker 3: our product. So I use a lot of experiences on
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Speaker 3: dealing with such a different scenario in earlier jobs, and
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Speaker 3: we were able to successfully deal with that. That was
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Speaker 3: also a job. I also got exposure to the businesses
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Speaker 3: of Honeyweale, which I hadn't done before. Aerospace being the
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Speaker 3: biggest one, so that goll ed into my responsibility. So
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Speaker 3: there was a sort of learning there on how that
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Speaker 3: industry works, which is totally different from everything else I
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Speaker 3: had done.
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Speaker 2: Is there a through put through materials, processes, technologies and
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Speaker 2: aerospace or are these all completely different animals?
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Speaker 3: Different animals in the sense of the n market says
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Speaker 3: Serve right, there are some commonality of the business models,
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Speaker 3: and you know there there's a common denominator, but there
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Speaker 3: are differences which really led me to think about whether
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Speaker 3: we are good to be one company or multiple companies
9:37
Speaker 3: when I started as a CEO, and part of it
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Speaker 3: was the differences between them, but part of it was
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Speaker 3: opportunities which is ahead of us, that how these businesses
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Speaker 3: independently could shape or scale much differently versus when we
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Speaker 3: are together, which led us to do a lot of
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Speaker 3: work to think about optionality and pros and cons of
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Speaker 3: each option, which led us to make a decision that
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Speaker 3: we are better off to split into three companies, and.
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Speaker 2: We're going to spend some time delving into those three
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Speaker 2: companies and the thinking behind it. Before we get to that,
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Speaker 2: I want to ask you a couple of more general
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Speaker 2: questions about the firm. You've been there so long since
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Speaker 2: the nineteen eighties. I'm curious, how has the culture of
10:25
Speaker 2: Honeywell changed. It's almost forty years, three and a half decades.
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Speaker 2: Is it still essentially the same company or has everything
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Speaker 2: changed like so many other companies.
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Speaker 3: Yeah, it evolved a lot, I would say. You know,
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Speaker 3: there was a big change moment in early two thousand
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Speaker 3: and when Honeywell and a Light Signal merged together. Recall yep,
10:48
Speaker 3: so a little bit of fun fact, A Light Signal
10:52
Speaker 3: acquired Honeywell and changed its name to Honeywell, which doesn't
10:56
Speaker 3: happen the acquator keeps name because they figured Honeywell brand
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Speaker 3: was so powerful, i was more impactful, so they changed
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Speaker 3: their own name. So that was a big moment to
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Speaker 3: your queshion on cultural assimilation of two large companies. It
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Speaker 3: was kind of merger of equals, and it did go
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Speaker 3: through its own motion of ups and downs. And that's
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Speaker 3: when Dave Cody came in as chairman and CEO of Honeywell,
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Speaker 3: and Dave did a great job to rebuild the County
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Speaker 3: Honeywell culture, which was much more one company mindset. We
11:25
Speaker 3: are not two companies. We have one company. We're going
11:28
Speaker 3: to work towards one stock, one Honeywell mindset, put a
11:31
Speaker 3: lot of operational culture in the organization. So that was
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Speaker 3: one phase of you know, under her leadership. Then my predecessor,
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Speaker 3: Darius Ademchek, he became CEO in twenty seventeen. He further
11:47
Speaker 3: enhanced our operational excellent skill. He invested a lot of
11:49
Speaker 3: effort to build more digital backbone of the company, simplifying
11:53
Speaker 3: Honeywell in terms of internal systems we have. Darius was
11:57
Speaker 3: very passionate about digital on how to mind data and
12:00
Speaker 3: create more capability for our customers. So he created a
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Speaker 3: culture of more operational excellence, more operational rigor, while Dave
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Speaker 3: was much more focused on one Honeymoon mindset, cultural integration,
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Speaker 3: not multiple companies. And as my tenure comes in over
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Speaker 3: the last no two plus years, we are not pivoting
12:19
Speaker 3: from the more growth oriented company. And the reason that's
12:23
Speaker 3: important is that over a period of time, our margin
12:26
Speaker 3: rates have grown up and we were sub ten percent
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Speaker 3: margin company in two thousand and five, two thand and
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Speaker 3: six last day to us twenty three percent. So our
12:35
Speaker 3: earnings growth is going to come more from the top
12:37
Speaker 3: line growth versus margin expansion. Not that we want to
12:40
Speaker 3: do margin expansion, but we can't get from another fifteen percent.
12:44
Speaker 3: There's no headroom. So growth culture is important, which means
12:48
Speaker 3: we have to be more externally focused. Now we need
12:50
Speaker 3: to understand our markets. We need to understand our customers,
12:53
Speaker 3: what's changing, need to understand our competition. So our company,
12:57
Speaker 3: even though name preserves it sell as a heriitage, but
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Speaker 3: it has been constantly evolving itself. And that's one of
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Speaker 3: the reasons this company has survived on hundred and twenty
13:07
Speaker 3: years because it has courage to reinvent itself versus being
13:11
Speaker 3: inward looking and always saying that Okay, we are what
13:14
Speaker 3: we are and we aren't going to change.
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Speaker 2: Really really interesting. So I used to hear people talk
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Speaker 2: about automation pretty regularly as just the process of moving
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Speaker 2: more and more things to machines. We kind of hear
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Speaker 2: people using the phrase artificial intelligence and AI the same way.
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Speaker 2: Kind of bluntly. I'm curious from the Honeywell perspective when
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Speaker 2: it comes to automation and AI, what are the customers buying?
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Speaker 2: Is it productivity gains, is it safety improvements? Is it
13:48
Speaker 2: cheaper labor or substitute for labor? What is the key
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Speaker 2: selling point for your customers.
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Speaker 3: So I would say the we have to go back
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Speaker 3: to where the automation industry started from to better appreciate
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Speaker 3: how will AI impact automation offerings or automation products. Go
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Speaker 3: back to mid seventies when this industry got created. Somewhere
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Speaker 3: in mid seventy five timeframe, when computing was invented, chips
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Speaker 3: were invented. There came the need to say, the word
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Speaker 3: has a lot of these expensive assets. Those assets are
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Speaker 3: not running very efficiently. So can we move from the
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Speaker 3: older technologies which were kind of World War one Word
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Speaker 3: War two war era to more modern digital technologies. And
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Speaker 3: the way automation system was created was that you sense
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Speaker 3: a set of properties on how a particular equipment or
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Speaker 3: a machine or a processor is running, and then you
14:44
Speaker 3: have a software program running in a computer which is
14:48
Speaker 3: going to make sure that it gets back to the
14:50
Speaker 3: desired condition what it wants it to be. So just
14:52
Speaker 3: a logic based, pre defined system, and the assumption was
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Speaker 3: most of the time this will work in a normal situation.
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Speaker 3: When exception occur, human will take a call. So automation
15:06
Speaker 3: systems were always designed with the human in the loop,
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Speaker 3: and human was supposed to take care of change in
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Speaker 3: input condition, change in output conditions. Maintain the equipment, take
15:17
Speaker 3: care of maintenance requirement down the line. Now you fast
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Speaker 3: forward fifty years before AI and data science came in.
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Speaker 3: The people who were running these equipment or automation system
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Speaker 3: or different facilities in different environment think of a former
15:33
Speaker 3: manufacturing facility or a data center. They acquired in knowledge
15:37
Speaker 3: on the exceptions which were occurring in those operating conditions.
15:41
Speaker 3: But when they retire or they move on, their knowledge
15:44
Speaker 3: went along with them. So when the next set of
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Speaker 3: people came in, they kind of have the same learning cycle.
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Speaker 3: Maybe some of it was captured in some documents and manuals,
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Speaker 3: but not a lot. So what AI is solving for
15:56
Speaker 3: is our systems have no intelligence layer on top of
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Speaker 3: the core automation layer, so that when the next human
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Speaker 3: being comes in, they're not starting from scratch. They have
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Speaker 3: an advantage of all the learning over the last twenty
16:08
Speaker 3: five years all built in, so they get to say,
16:11
Speaker 3: when this condition occurred, nine out of ten times this
16:15
Speaker 3: was done, it always worked. So you are the human
16:17
Speaker 3: being and say, okay, I think I will choose this
16:19
Speaker 3: logic mix. So human still needs to make a decision
16:22
Speaker 3: so I think it's a changing the human and making
16:25
Speaker 3: them more capable at the heart of it. And the
16:29
Speaker 3: reason it becomes even more compelling now is the shortage
16:32
Speaker 3: of skills which are happening in the industrial sector for
16:35
Speaker 3: performing these kind of tasks. So I would say it's
16:38
Speaker 3: a perfect convergence of the situation that more capability is
16:43
Speaker 3: coming into our system because of availability of data science,
16:48
Speaker 3: and at the same time, situation requires this capability to
16:52
Speaker 3: be there because less people are available to do this work,
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Speaker 3: and that's going to create more capability in automation system.
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Speaker 3: Animasion system remains Intelligencelyer is on top of it, so
17:03
Speaker 3: it makes its automation system better in terms of what
17:07
Speaker 3: it can do by preserving its capability.
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Speaker 2: Coming up, we continue our conversation with vim L. Kapoor,
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Speaker 2: CEO of Honeywell, discussing turning Honeywell into three standalone companies.
17:21
Speaker 2: I'm Barry Ridults. You're listening to Masters in Business. I'm
17:25
Speaker 2: Bloomberg Radio. I'm Barry Ridults. You're listening to Masters in
17:41
Speaker 2: Business on Bloomberg Radio. My extra special guest this week
17:44
Speaker 2: is vim Al Kapoor. He is CEO and chairman of
17:49
Speaker 2: Honeywell International, he's been with the firm for thirty seven years.
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Speaker 2: Honeywell is a highly regarded automation and industrial company. So
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Speaker 2: let's start out with plans to break the firm up.
18:04
Speaker 2: You have three distinct entities Honeywell Automation, Honeywell Aerospace, and
18:12
Speaker 2: then Solstice Advanced Materials. So let's talk about that split.
18:18
Speaker 2: That sounds fairly natural, breakup based on industry. Tell us
18:24
Speaker 2: a little bit about the thinking behind that.
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Speaker 3: So thinking behind that was when I started as a CEO.
18:29
Speaker 3: My incoming thesis was that we have to simplify this company.
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Speaker 3: It's performed extremely well, greater return to shareholder, great service
18:37
Speaker 3: to our customer, but what will we do for the
18:39
Speaker 3: next twenty five to thirty years? Are we set up
18:41
Speaker 3: for that? And my thesis was that we need to
18:45
Speaker 3: simplify this into few things where we have a scale.
18:49
Speaker 3: But I started the job in middle of twenty three
18:51
Speaker 3: as the CEO of the company. Two things happened in
18:54
Speaker 3: the year of twenty three, which is good to kind
18:55
Speaker 3: of reflect back just three years back. That was the
18:58
Speaker 3: first year when the aerospace cycle really became very strong.
19:01
Speaker 3: That was a year one where everybody said, oh, this
19:04
Speaker 3: industry is growing a lot, let's pay more attention to it.
19:07
Speaker 3: And this was also the first year when something called
19:10
Speaker 3: AI was talcked, right, So if we were sitting here
19:13
Speaker 3: three years back, we wouldn't be talking AI. So it's
19:15
Speaker 3: that recent phenomena. So the question we had to really
19:18
Speaker 3: ask ourselves that if we have to simplify as a
19:21
Speaker 3: company and these two external drivers are occurring simultaneously a
19:26
Speaker 3: huge demand in our largest business, which is aerospace, automation,
19:30
Speaker 3: which is core to Honeywell, is going to probably redefine
19:33
Speaker 3: itself with AI. Should we do it as one company
19:38
Speaker 3: or should we do it as in a different construct,
19:42
Speaker 3: And that question get into a problem solving by early
19:47
Speaker 3: twenty four, to say, let's look at all the scenarios,
19:49
Speaker 3: what's possibilities, what others are doing. And as we did
19:53
Speaker 3: the work over twenty twenty four, we got more and
19:56
Speaker 3: more conviction it's better to separate automation and aerospace into
20:00
Speaker 3: two separate companies. But we ended up making three decisions
20:04
Speaker 3: because specialty chemical is extremely good business which neither fitted
20:08
Speaker 3: in any one of these two, and we said it's
20:11
Speaker 3: compelling to also spin that off as a separate company.
20:14
Speaker 3: So rather than you know, two ended up becoming three.
20:18
Speaker 3: So they became a standalone business in October of last year,
20:21
Speaker 3: doing extremely well since we spun it off now for
20:24
Speaker 3: six months. Very proud of the management team and the
20:27
Speaker 3: board which is running this company. Aerospace will become a
20:30
Speaker 3: standalone company in about six to eight weeks from now.
20:33
Speaker 3: Six weeks actually as we speak today, twenty nine is
20:36
Speaker 3: a date and data is firm. We quite committed to
20:39
Speaker 3: that and it's going to be a leader in its
20:42
Speaker 3: segment in aerospace. And the remain core will be a
20:45
Speaker 3: pure play automation company which will be probably one of
20:48
Speaker 3: the largest, if not the largest automation company in the world.
20:51
Speaker 2: So advanced materials does that include building technologies.
20:57
Speaker 3: It's a pure play chemicals business, straight up chemical chemical business.
21:00
Speaker 3: They make refrigerant which goes into your car, which goes
21:03
Speaker 3: into your home. They have some other technologies which are
21:06
Speaker 3: related to chemicals. That business is doing extremely well as
21:10
Speaker 3: a standalone company. The automation which you mentioned building automation
21:14
Speaker 3: or automation of industrial facilities, that's part of the remaining Honeywell,
21:19
Speaker 3: which is Honeywell Automation. Now we won'll not be called
21:21
Speaker 3: Honeywell Automation. We're using as just as an equal descriptor
21:25
Speaker 3: on what the business will be. We will reimagine our
21:28
Speaker 3: name as we go by in a couple of weeks
21:30
Speaker 3: from now and will reveal that name what it should be.
21:34
Speaker 3: But for sake of simplicity, a chemicals business, an aerospace business,
21:38
Speaker 3: and an automation business.
21:39
Speaker 2: And performance materials and technology.
21:42
Speaker 3: Is so part of it became into Advanced Material Advanced
21:45
Speaker 3: Material Solstice, and then part of it is retained within Honeywell,
21:49
Speaker 3: so it split into kind of two.
21:51
Speaker 2: Because this is really everybody thinks of these very broadly,
21:55
Speaker 2: but there are some really narrow specific use cases for
21:59
Speaker 2: different groups. So I was trying to figure out what
22:03
Speaker 2: would align with what.
22:05
Speaker 3: So so think about. Automation business serves three large end markets,
22:10
Speaker 3: all types of buildings, all types of energy facilities, and
22:13
Speaker 3: all types of industrial facilities. That's what we have kept
22:17
Speaker 3: in the automation and we also are conscious that we
22:20
Speaker 3: should not make automation business serving so many segments that
22:23
Speaker 3: it becomes confusing again, so we want to narrow down
22:27
Speaker 3: to a few very large and impactful segments. The market
22:30
Speaker 3: size is about two hundred billion dollars. We will be
22:33
Speaker 3: just shy off twenty billion of revenues, we have a
22:35
Speaker 3: lot of runway to think about creatively, what more we
22:38
Speaker 3: can do, how do we grow more so we're not
22:40
Speaker 3: shortage off runway. Secularly, automation is a naturally high growth
22:47
Speaker 3: segment because it's something which is so basic to existence
22:51
Speaker 3: of an industrial facility or on an asset, and then
22:54
Speaker 3: when you add the AI story coming on top of it,
22:58
Speaker 3: it's going to have increasingly more growth momentum. So all
23:02
Speaker 3: things being said, yeah, it's very well positioned for a
23:04
Speaker 3: compelling future.
23:05
Speaker 2: And what does the Aerospace Group do? Not unlike GE,
23:09
Speaker 2: you're not making aircraft eins.
23:11
Speaker 3: Right, So we do make aircraft engine for the business jet,
23:14
Speaker 3: some more mid size, smaller and smaller engine the business
23:17
Speaker 3: jet engines make. We don't make the big engines. But
23:19
Speaker 3: we are a systems company. We make different components from
23:22
Speaker 3: the nose to tail of the plane, so our components
23:26
Speaker 3: are right in the cockpit. Our components. We make radars,
23:31
Speaker 3: we make navigation system we make brakes for the plane,
23:34
Speaker 3: we make environmental controls in the plane. So we are
23:37
Speaker 3: a systems company. We make engines, we make APUs, so
23:41
Speaker 3: our approach is system designed for a new platform. So
23:46
Speaker 3: every platform comes in and it could be a commercial plane,
23:49
Speaker 3: could be a business jet, could be a defense platform.
23:52
Speaker 3: We will pitch in different components and systems of honeywere
23:55
Speaker 3: customers will select many of them, some of them. Then
23:58
Speaker 3: that will become part of that you know that fleet
24:02
Speaker 3: for decades and decades. So it's a multi product business,
24:08
Speaker 3: not constrained to one particular product line. And the business
24:11
Speaker 3: model is more powerful because it's a system's approach and
24:15
Speaker 3: not a component approach. So you're right in the heart
24:18
Speaker 3: of the systems. You understand how the whole mechanics work
24:21
Speaker 3: and really add more value for our customers.
24:23
Speaker 2: So over the past let's call it ten years, there
24:26
Speaker 2: have been a number of activist investors like Alliott Management
24:31
Speaker 2: that not just Honeywell, but lots and lots of other
24:34
Speaker 2: large conglomerates. They often agitate for share buybacks or increased dividends,
24:41
Speaker 2: or sometimes just break the company into pieces. You seem
24:46
Speaker 2: to have landed pretty much in a similar space as
24:50
Speaker 2: some of these activists. First, were they at all influential
24:55
Speaker 2: in your thinking or was this something that Hey, these
24:59
Speaker 2: are such diferent businesses, is no longer scale advantages of
25:03
Speaker 2: having them under one room.
25:05
Speaker 3: I would say the situation in art case was a
25:07
Speaker 3: bit unique because we started doing work to investigate our
25:11
Speaker 3: future optionality early twenty twenty four and did a lot
25:14
Speaker 3: of work and actually even announced the separation of chemicals business.
25:18
Speaker 3: In October. Elliott wrote a letter which was in public
25:22
Speaker 3: domain and I got to see it at the same time,
25:24
Speaker 3: and if everybody else saw it to say we should
25:26
Speaker 3: further split aerospace and rest of Honeywell too. That was
25:29
Speaker 3: their argument, is a more value to be created. The
25:33
Speaker 3: good news was that we already had done the work
25:35
Speaker 3: and we were convinced that's the right thing to do,
25:37
Speaker 3: but we had not announced anything, so we treated them
25:42
Speaker 3: as another shareholder who has a point of view and
25:45
Speaker 3: we have to articulate our strategy. So there were strong
25:47
Speaker 3: convergence on the thinking, and I think we worked with
25:51
Speaker 3: them very collaboratively on path forward. And I would say
25:56
Speaker 3: that there's lots being said on activist shareholder, but my
26:00
Speaker 3: experience is that they are like any other shareholder who
26:04
Speaker 3: have a logical argument. If you have a counterpoint, you
26:08
Speaker 3: should support this with the facts and data. Or if
26:11
Speaker 3: you support their point, then you have to execute it,
26:15
Speaker 3: and in that case it just becomes much more of
26:18
Speaker 3: not what to do, but how to do it. So
26:20
Speaker 3: our conversation with Aliot, like any of the shareholder, was
26:23
Speaker 3: this is the situation, here are the paths, this is
26:26
Speaker 3: how we are thinking about it. And we benefited from
26:29
Speaker 3: their expertise in capital markets how the shareholders will react,
26:32
Speaker 3: and definitely that helped us to shape our decision in
26:35
Speaker 3: terms of in a certain way, which was very constructive,
26:38
Speaker 3: really really interesting.
26:40
Speaker 2: So we seem to go through these long phases where
26:44
Speaker 2: conglomerates kind of become in style, they become favored. You
26:50
Speaker 2: oversaw fourteen billion dollars in M and A, which sounds
26:54
Speaker 2: like a lot of money, but we know really isn't
26:57
Speaker 2: You know? That's a that's not a mega buying spray.
27:02
Speaker 2: And for long, for the longest time, it seemed like
27:05
Speaker 2: there was a financial advantage to being a conglomerate. At
27:10
Speaker 2: what point does that structure stop being an advantage? Is
27:14
Speaker 2: what is being part throwing all these different pieces under
27:17
Speaker 2: one roof, What does that prevent the company from doing?
27:21
Speaker 3: I think every business model has an era, So I
27:24
Speaker 3: think we have to go back to what created this
27:27
Speaker 3: era of conglomerate or larger companies. It really started from
27:33
Speaker 3: them when the world was started becoming more globalized. After
27:36
Speaker 3: two thousand, China came into wto the world became more
27:39
Speaker 3: global and there was much more global trade, which became
27:44
Speaker 3: the norm on how companies were growing. So all US
27:48
Speaker 3: companies started growing globally. But at the same time they
27:51
Speaker 3: were able to drive a lot of productivity by taking
27:54
Speaker 3: manufacturing into Asia, a lot of you know, man park
27:57
Speaker 3: productivity by doing work in different virtual with a lot
28:00
Speaker 3: of IT skills coming in. So there was a case
28:03
Speaker 3: to make bigger companies bigger because they had the unique
28:08
Speaker 3: know how to drive a lot of productivity and scale
28:11
Speaker 3: at a global scale because they were already present there.
28:14
Speaker 3: And that cycle persisted for almost fifteen years till the
28:18
Speaker 3: time that value was captured, and that value capture became
28:23
Speaker 3: generally known. Therefore, the question started asking to say, is
28:28
Speaker 3: creating this complex company worth it? Or simplification or a
28:31
Speaker 3: sector focus is a better way to do it. So
28:34
Speaker 3: I think there was a reason that proposition really worked
28:37
Speaker 3: well and created a lot of value. Take a case
28:39
Speaker 3: of Honeywell, a shareholder value creation from a time of
28:42
Speaker 3: two thousand to twenty seventeen eighteen, one of the best
28:44
Speaker 3: in class and the entire SMP. So it's not that
28:48
Speaker 3: anything was wrong. We created a tremendous shareholder value. But
28:51
Speaker 3: now this point of saturation comes in and then it
28:54
Speaker 3: really brings you to the point of specialization. If their
28:58
Speaker 3: markets have scale and you can preserve scale while you
29:02
Speaker 3: are specialist, that's best of the both words. And that's
29:05
Speaker 3: what we are doing now to create a scale aerospace company,
29:09
Speaker 3: a scale automation company. We're still very global, we still
29:12
Speaker 3: have very mature processes, but at the same time, you're
29:15
Speaker 3: focused on singular segment. So I guess, like in everything else,
29:19
Speaker 3: you learn through cycles, and this cycle is all about
29:22
Speaker 3: having the mix of scale and specialization. This will persist
29:26
Speaker 3: it something else comes in now where there's a case
29:29
Speaker 3: to do something else, and I feel good about where
29:33
Speaker 3: we are in opposition, and it is going to create
29:35
Speaker 3: much more shareholder value.
29:36
Speaker 2: So twenty years before you started talking about breaking into
29:41
Speaker 2: three pieces, your fellow Dell component General Electric, went through
29:46
Speaker 2: the same process, arguably with not a whole lot of success.
29:52
Speaker 2: They started out fairly richly valued. There wasn't a whole
29:56
Speaker 2: lot of room to grow and cre When you're thinking
30:02
Speaker 2: about breaking into three are you looking at other companies
30:05
Speaker 2: like General Electric and saying what can we learn from
30:08
Speaker 2: what they did right, what they got wrong, what missteps
30:11
Speaker 2: they made.
30:11
Speaker 3: I think the situation for each company is very different
30:14
Speaker 3: because separation cannot create value alone by itself. We have
30:19
Speaker 3: to be convicted that the standalone asset has enough growth
30:22
Speaker 3: potential and invest and asset base which is going to grow,
30:26
Speaker 3: which is going to create value. So I think comparing
30:30
Speaker 3: example you gave versus Honeywell is absolutely very different. Portfolios
30:34
Speaker 3: way very different. I mean, so I would say that
30:37
Speaker 3: our drivers were more around what I talked about. Our
30:41
Speaker 3: stock price are more static, We were more We did
30:46
Speaker 3: not destroy any shareholder value, so our question was how
30:49
Speaker 3: do we create more shareholder value with external factors coming in,
30:52
Speaker 3: growth of aerospace, growth of AI. Is that inflection point
30:56
Speaker 3: for us to make a different decision. So we did
30:58
Speaker 3: it more from a point of strength versus we have
31:01
Speaker 3: some crisis coming in. So sometimes you use your point
31:04
Speaker 3: of strength to make the right decisions. And we did
31:08
Speaker 3: it fast and we did it right. I think every
31:11
Speaker 3: other company came from a different circumstances, but the decision
31:15
Speaker 3: on the outwardy looked very similar. They look like they
31:17
Speaker 3: all did the same thing, but they all came from
31:20
Speaker 3: a different backgrounds and you know, different set of assets
31:26
Speaker 3: when we started looking at it. Some people believe that
31:29
Speaker 3: we got influenced by success of GE. I want to
31:34
Speaker 3: remind that G success came post our decision. That was
31:38
Speaker 3: a process which was occurring. So yeah, you have that's
31:41
Speaker 3: a data point to say they are also doing it.
31:43
Speaker 3: But some of the success we have observed some outstanding
31:45
Speaker 3: work by the G leadership team that really started happening
31:48
Speaker 3: twenty four to twenty five time frame. We were far
31:51
Speaker 3: along the way in our own analysis by that time,
31:53
Speaker 3: so I think those are parallel things happening. So there's
31:57
Speaker 3: no one thing you can attribute to say that this
31:59
Speaker 3: thing influenced. It's a combination of the reason which all
32:01
Speaker 3: come together, and that's what really brings us to where
32:04
Speaker 3: we are today.
32:05
Speaker 2: I like this phrase in your thesis of the current
32:09
Speaker 2: transition from automation to autonomy with artificial intelligence as the
32:15
Speaker 2: dividing line. How far along that process are we as
32:21
Speaker 2: a country are the industrial sector and honeywell, so.
32:27
Speaker 3: I would say that we as a country have an
32:31
Speaker 3: advantage of being the leader in the space of cloud
32:35
Speaker 3: and data science and companies like Honeywell has responsibility to
32:40
Speaker 3: take that know how which the tech sector is creating.
32:42
Speaker 3: Beat Microsoft, beat Google, Beatenvidia and all the very capable
32:48
Speaker 3: tech companies. How do we bring that capability into our
32:51
Speaker 3: sector Because our customer is not going to go and
32:57
Speaker 3: they are not looking to buy a cloud capability or
32:59
Speaker 3: they not looking to buy AI LM. They want to
33:03
Speaker 3: solve a problem. They want to run a business, they
33:05
Speaker 3: want to run an operation, they want to have more uptime,
33:07
Speaker 3: they want to have more profitability. So our job is
33:12
Speaker 3: to take our system to what I mentioned before and
33:15
Speaker 3: add this intelligence layer. And what this intelligence layer is
33:18
Speaker 3: all about. Taking capability from the tech companies, take large
33:21
Speaker 3: language models from the likes of Google and Nvidia, use
33:25
Speaker 3: a cloud power which is there from Amazon and Microsoft,
33:28
Speaker 3: but really build a purpose offering from the industrial sector.
33:32
Speaker 3: And as we are doing that, we are able to
33:34
Speaker 3: create the agentic models for our customers. And that's what
33:38
Speaker 3: they buy from us. The underlying plumbing what we have,
33:41
Speaker 3: they don't want to know it, They don't want to
33:42
Speaker 3: know how this is built. Say yeah, so you're automating
33:45
Speaker 3: this piece of my work. That's great, So I'm going
33:48
Speaker 3: to get more productivity for that how much I should
33:50
Speaker 3: pay you for it? Right, So I would say we
33:52
Speaker 3: are in the state that this is no more hypothesis.
33:57
Speaker 3: We are in the not in the early but we
34:00
Speaker 3: are in the stage of deployment of these capabilities across
34:03
Speaker 3: different customer base. Why it is not taken up at
34:08
Speaker 3: scale is because our customers have to go through a
34:10
Speaker 3: significant change management in their organization because fundamentally the roles
34:15
Speaker 3: of people are changing. Some roles require skills which are
34:20
Speaker 3: less important today and some more new skills are required.
34:24
Speaker 3: And they can't do that overnight. Just because I created
34:26
Speaker 3: a new set of technology. They have to absorb it,
34:29
Speaker 3: they have to ingest it. But we have some fabulous
34:32
Speaker 3: examples on customer useating and scale in different sectors like
34:36
Speaker 3: university systems, quick service restaurants. People are using some of
34:41
Speaker 3: our technologies at a very large scale in refineries, etc.
34:44
Speaker 3: So I would say that if I'm sitting with you
34:48
Speaker 3: it twelve months back, I would have said very modest deployment.
34:51
Speaker 3: Sitting today, I would say I'm very excited on about
34:54
Speaker 3: opportunity we see a year from now. I would argue
34:57
Speaker 3: that the penetration will go up substantially up because there's
35:00
Speaker 3: a real economic value creation from what were really properity.
35:03
Speaker 3: And we as a country are leading because we have
35:07
Speaker 3: the core components of this technology and now we have to,
35:12
Speaker 3: you know, take this cability across the world. When our
35:14
Speaker 3: customers excited, they really like what we are doing.
35:17
Speaker 2: Earlier, you mentioned restaurant automation. What does hauntingwell do for
35:23
Speaker 2: either fast food service or casual dining?
35:26
Speaker 3: They say, think about it. I mean, when you look
35:28
Speaker 3: at a small fast food dining restaurant, there's not much
35:31
Speaker 3: automation in that, but it consumes energy for sure. I mean,
35:35
Speaker 3: let's take a typical McDonald's restaurant as just as an example.
35:39
Speaker 3: There's a kitchen there, there's a fryer, there's a refrigeration.
35:43
Speaker 3: It's is keeping a lot of products there. There's of
35:45
Speaker 3: course lights going on. These assets were never thought as
35:50
Speaker 3: a way to improve energy efficiencies by companies like us.
35:53
Speaker 3: We say we should automate a large hospital. It's massive,
35:56
Speaker 3: there's a lot of opportunity there, or a large building.
35:59
Speaker 3: These assets were never paid attention by us because there
36:02
Speaker 3: was no technology available. But when the cloud technology came in,
36:07
Speaker 3: we are able to connect these assets flawlessly. You know,
36:10
Speaker 3: in a matter of hours, and then you able to
36:13
Speaker 3: use a lot of AI based rules set to understand
36:16
Speaker 3: what should be the energy consumption actual versus what it
36:19
Speaker 3: is today and give that tools to the owner to say,
36:22
Speaker 3: you know, an example, we connected a quick service chain
36:25
Speaker 3: in UK, I think something like five hundred plus of
36:27
Speaker 3: their restaurants into a single operating system and they are
36:31
Speaker 3: observing thirty to forty percent energy reduction. Like anything else,
36:35
Speaker 3: the good old management principle, what do you inspect is
36:38
Speaker 3: what you get. Once these were thinking running off my own,
36:42
Speaker 3: nobody paid attention even though they desired to do something,
36:45
Speaker 3: there was no mechanism. So we created an easy mechanism
36:49
Speaker 3: to make this available to the customer. So all of
36:51
Speaker 3: a sudden they were able to generate a lot more
36:53
Speaker 3: productivity without adding too much of cost. And that's a
36:56
Speaker 3: part of the new tools which is coming in which
36:59
Speaker 3: was not possible, and that gives me a lot of
37:01
Speaker 3: excitement that this is going to be much more level
37:05
Speaker 3: of productivity efficiency which is less talked about. You know,
37:09
Speaker 3: whenever there's AI dialogue, it's jobs going to cut jobs.
37:13
Speaker 3: Nobody talks about economic value creation. It is doing a
37:16
Speaker 3: real value for our customer base, making people more productive.
37:21
Speaker 3: That's the story of the industrial side, which is probably
37:24
Speaker 3: requires more more amplification.
37:26
Speaker 2: So what's the Pewter Drucker quote. You can't manage what
37:29
Speaker 2: you can't measure. So forget five hundred restaurants, what is
37:33
Speaker 2: Starbucks thirty thousand? McDonald's forty thousand.
37:36
Speaker 3: Applies to all of these kind of accid and many
37:38
Speaker 3: people have done this work. So it's not that we
37:40
Speaker 3: have created some new inventions. Some of them have done
37:42
Speaker 3: this kind of discovery, but this effort was not very standardized.
37:46
Speaker 3: It's like a custom made thing somebody will do. Because
37:49
Speaker 3: you are a big company, you can afford it. But
37:51
Speaker 3: when you do it a large scale, there are hundreds
37:54
Speaker 3: of these chains. There are hundreds of retail stores. We're
37:58
Speaker 3: also doing similar work around the big retail store chains,
38:01
Speaker 3: very similar example. So these distributed assets are becoming a
38:06
Speaker 3: way of capturing value at one end of the equation
38:10
Speaker 3: or the other end of the equation. When you have
38:13
Speaker 3: retirals coming and our customers are worried about knowledge going
38:16
Speaker 3: out of the door, they're looking at a mechanism of
38:19
Speaker 3: knowledge capture so they can perform their task. That's also
38:23
Speaker 3: penetrating very rapidly so scenarios are different. Some scenarios are
38:27
Speaker 3: looking at I never paid attention and now I can
38:30
Speaker 3: do it. Some are saying I have less people do
38:32
Speaker 3: something about it. But the capability is fundamentally the same.
38:36
Speaker 3: It's the same capability which solves both the problem.
38:39
Speaker 2: Coming up, we continue our conversation with Vimal Kapor, CEO
38:43
Speaker 2: and chairman of Honeywell, discussing the state of automated technology today.
38:50
Speaker 2: I'm Barry Richults. You're listening to Master's Business on Bloomberg Radio.
39:06
Speaker 2: I'm Barry Ridolts. You're listening to Masters in Business on
39:09
Speaker 2: Bloomberg Radio. My extra special guest this week is vim
39:13
Speaker 2: Al Kapoor. He is CEO and chairman at Honeywell, the
39:17
Speaker 2: company he has worked at for the past thirty seven
39:20
Speaker 2: years since starting there as an engineer. So I'm curious
39:24
Speaker 2: as to how some technologies seem to just take forever
39:29
Speaker 2: to find their way into the real world, you know,
39:33
Speaker 2: if you travel around the world. I remember the first
39:38
Speaker 2: time I saw one of the point of sale handheld
39:42
Speaker 2: units in a restaurant in Europe. I don't know, maybe
39:45
Speaker 2: it was fifteen years ago and I was astonished. Wait,
39:49
Speaker 2: I don't have to request the check. They come, then
39:52
Speaker 2: they have to give him the key, the card, they
39:54
Speaker 2: go away, like I will take a check they come
39:56
Speaker 2: by it. It seems to have taken a decade to
40:00
Speaker 2: make its way here. What are some of the impediments
40:03
Speaker 2: to some of this some of the cutting edge technologies
40:07
Speaker 2: that's obviously using a bunch of tech that already existed.
40:13
Speaker 2: Is this a problem getting adaptation even though it's clearly
40:18
Speaker 2: more productive, more efficient, faster turn of tables, Like I
40:22
Speaker 2: was astonished how long it took for the United States
40:25
Speaker 2: to implement that fure.
40:26
Speaker 3: I think there's a scenario in your example because it's
40:30
Speaker 3: a technology displacement of some old method versus a more
40:34
Speaker 3: new method. But the reason I believe more bullish about
40:38
Speaker 3: it is that we are solving a known problem. And
40:40
Speaker 3: the known problem is word has less people to do
40:43
Speaker 3: a lot of work around skill labor in the industrial world.
40:48
Speaker 3: That's a real problem. So our solution is not trying
40:50
Speaker 3: to find a problem. We are finding we are giving
40:53
Speaker 3: a solution to a known problem. Adoption rates are lower
40:57
Speaker 3: because of the change management issue, But this is the
41:00
Speaker 3: monument of the order of eighteen months, twenty four months,
41:03
Speaker 3: thirty months, that's not a decade, So I remain very
41:06
Speaker 3: optimistic given my experiencing these sectors, the adoption rates are
41:11
Speaker 3: going to be much more quicker because the problem is real.
41:14
Speaker 3: We are not inventing the problem. This problem exists for it.
41:18
Speaker 3: And by the way, this problem is everywhere in the world.
41:21
Speaker 3: This is not a.
41:22
Speaker 2: US problem only skilled labor.
41:24
Speaker 3: Skilled labor. Europe has more population shrinkage than US. Go
41:28
Speaker 3: to Japan and Korea, they have the same problem. China
41:30
Speaker 3: has population shrinkage. So this is a universal issue. This
41:34
Speaker 3: is not invented here. Now we get excited on the
41:38
Speaker 3: job displacement happening with robots and humanoids. That's a small
41:43
Speaker 3: portion of a manufacturing industry that probably is also displacing
41:48
Speaker 3: some tasks which humans are not willing to do, like
41:50
Speaker 3: lifting boxes. Right yeah, I mean, okay, it's not very interesting.
41:55
Speaker 3: But then there are other jobs with other sectors which
41:58
Speaker 3: we address. A physical AI or intelligence layer is going
42:03
Speaker 3: to create a tremendous amount of economic value.
42:05
Speaker 2: So I keep hearing people compare that intelligence layer of
42:10
Speaker 2: artificial intelligence to the Internet. I'm wondering, and you seem
42:15
Speaker 2: very bullish and excited about everything AI can do. Is
42:19
Speaker 2: there a better comparison. Is the Industrial Revolution a better
42:24
Speaker 2: framework for thinking about the impact of AI over the
42:28
Speaker 2: next ten to fifty one hundred years.
42:31
Speaker 3: I think the AI impact will be different in each sector,
42:34
Speaker 3: and I think if we make it too broadbrush, we
42:38
Speaker 3: are losing the bigger picture. But when we are making
42:40
Speaker 3: it specific to a segment, then you're being more precise
42:44
Speaker 3: to say in context of the end markets we serve
42:48
Speaker 3: of the industrial sector. I talked about examples there. It's
42:52
Speaker 3: all about the skill shortage issue, which is very different
42:54
Speaker 3: from if we are using AI for better search engine.
42:58
Speaker 3: If I'm using AI for or making a summary of
43:01
Speaker 3: art talk, which somebody can do, and that's a very
43:04
Speaker 3: different use case, and one can argue is it going
43:06
Speaker 3: to add productivity or not? Or is it going to
43:08
Speaker 3: take away jobs. That's a different scenario from simply not
43:11
Speaker 3: having people to do work. Way different scenario, and I
43:15
Speaker 3: think that makes our case more compelling. The adoption rates
43:19
Speaker 3: are driven by a near real need versus we are
43:22
Speaker 3: trying to create a need which is unknown, and that's
43:24
Speaker 3: not being talked a lot more. A lot more dialogue
43:28
Speaker 3: is around job displacements, but those are more in the
43:31
Speaker 3: jobs which could be automated like finance function or HR function.
43:36
Speaker 3: Maybe to a certain degree it's true, but not to
43:39
Speaker 3: the point. My personal view is that it's going to
43:41
Speaker 3: have the amount of impact which is being talked about.
43:43
Speaker 2: So let's talk about some of the challenges of this
43:47
Speaker 2: technology layer and some of the black hats out there.
43:51
Speaker 2: When Mythos came out, I would imagine a company like
43:54
Speaker 2: Honeywell set up and took notice the idea of of
44:00
Speaker 2: AI taking over industrial controllers, power, water, air conditioning. All
44:05
Speaker 2: that stuff has to be thought of as a genuine threat.
44:09
Speaker 2: Nobody wants rogue thermostats or what have you. How do
44:14
Speaker 2: you look at the threat from a powerful entity like
44:19
Speaker 2: Mythos and how much of an arms race are we
44:23
Speaker 2: in to harden all of our soft underbelly.
44:27
Speaker 3: So I think we have to appreciate the fact that
44:31
Speaker 3: where we are deploying AI, it is substantially different from
44:36
Speaker 3: what we are ginerally talking about in broader public domain.
44:40
Speaker 3: If you think of applying AI in an industrials Let's
44:43
Speaker 3: take a case of a hospital and I want to
44:45
Speaker 3: apply AI into automation system to make it more efficient.
44:48
Speaker 3: The data of that is not in public domain. The
44:51
Speaker 3: data is in Honeymoon system or it's one of our
44:54
Speaker 3: competitor system, So you cannot go to internet and train
44:57
Speaker 3: anything because there's nothing to train on. So that makes
45:01
Speaker 3: data friction as a big problem in industrial sector, which
45:04
Speaker 3: in a way becomes a protection layer for us. But
45:07
Speaker 3: that doesn't mean friction becomes a protection layer. But it
45:09
Speaker 3: doesn't mean we should not do anything about it. So
45:11
Speaker 3: you say, oh, unprotected, it means we should take it
45:14
Speaker 3: seriously to think of potential threats coming in because if
45:17
Speaker 3: the data friction is removed, which is hard to do,
45:20
Speaker 3: but humans are very intelligent, so we have worked very
45:24
Speaker 3: hard to remove the data friction and also use our
45:27
Speaker 3: domain knowledge because interestingly, you cannot solve a horizontal problem
45:34
Speaker 3: in industrial domain. What I mean by that is you
45:37
Speaker 3: do not have a software application like a CRM system
45:40
Speaker 3: or an HR system. The problems of each sectors are
45:44
Speaker 3: very different. If you're a refinery, you're trying to produce
45:47
Speaker 3: more jet fuel and more diesel. If you are a
45:51
Speaker 3: life census manufacturing facility, you're trying to produce drug with
45:54
Speaker 3: minimal quality giveaway. But if you're a data center you
45:57
Speaker 3: want more uptime. Your problems are so different. So we
46:00
Speaker 3: can't create a magic AI application and sell to everybody.
46:04
Speaker 3: We have to be purposeful that where do we use
46:06
Speaker 3: our data and what problem we solve, which only come
46:09
Speaker 3: from years of experience. So those two really become in
46:12
Speaker 3: a way a constraint for a genuary company to come
46:15
Speaker 3: in because of data friction and lack of understanding of domain,
46:20
Speaker 3: which means companies like us which possess both have to
46:23
Speaker 3: solve this problem. And that's why we are very bullish
46:25
Speaker 3: about it to say we're going to do it. We're
46:28
Speaker 3: going to take all the capabilities from tech companies and
46:30
Speaker 3: build new set of capabilities to take our industry from
46:33
Speaker 3: a pure play automation to more towards autonomy. And autonomy
46:36
Speaker 3: doesn't mean humans will disappear. Humans will become more empowered,
46:40
Speaker 3: human will become more capable, and to the extent is
46:44
Speaker 3: some skilled shortages, it'll address that point.
46:48
Speaker 2: So let's talk a little bit about how tumultuous the
46:51
Speaker 2: past twelve months have been in terms of geopolitics. We
46:56
Speaker 2: not only have the war in the Ukraine, but now
47:00
Speaker 2: in Iran we had the on again, off again, on
47:04
Speaker 2: again and most recently off again tariffs. How does this
47:08
Speaker 2: affect how a company like Honeywell thinks about resuring and
47:12
Speaker 2: bringing manufacturing back to the United States, things about supply
47:16
Speaker 2: chain issues. How do you plan in such a tumultuous environment.
47:21
Speaker 3: But it's definitely a challenge for companies. To have more
47:24
Speaker 3: stability is what companies want. So I would say that
47:27
Speaker 3: companies like US have very mature processes to deal with it.
47:32
Speaker 3: So every time this issue occurs, we have some sort
47:35
Speaker 3: of disturbance for depends four weeks, eight weeks, twenty weeks,
47:41
Speaker 3: who knows, depending on the situation. So we have learned
47:44
Speaker 3: how to deal with it. But it doesn't come without
47:46
Speaker 3: a cost. You lose some growth in that window. You
47:48
Speaker 3: may have to incorrect stra cost like it happened in
47:50
Speaker 3: case of tariff, because when tariff got announced, we have
47:53
Speaker 3: no choice but to paid right now whether we can
47:55
Speaker 3: recover it or not as a subsequent decision.
47:57
Speaker 2: Are you one of the many companies that have filed
48:00
Speaker 2: litigation to get.
48:01
Speaker 3: Redated not find any litigation?
48:03
Speaker 2: How big of a hit was?
48:05
Speaker 3: It was not big for us. We were mostly down
48:07
Speaker 3: to the second part of your queshion. We have been
48:10
Speaker 3: doing manufacturing local for local for multiple years, so we
48:14
Speaker 3: made for us in US made for Europe in Europe,
48:18
Speaker 3: made for China in China, so we don't move a
48:20
Speaker 3: lot of stuff around. However, what we cannot control is
48:23
Speaker 3: the global nature of the components we buy. Right if
48:26
Speaker 3: I have to buy.
48:27
Speaker 2: Everything in the supply chain and raw materials.
48:29
Speaker 3: Correct, because we can't make everything. So if a component
48:33
Speaker 3: is made in Korea, like batteries, we have to buy
48:35
Speaker 3: it from there, and if a component is made in
48:38
Speaker 3: China or somewhere else, we have to buy it from there.
48:41
Speaker 3: So that impact is certainly not under our coverage because
48:46
Speaker 3: we don't have an endless capacity to invest in everything
48:49
Speaker 3: but our core manufacturing. We have one hundred and fifty factories,
48:54
Speaker 3: you know, and they're well disabled around the world, and
48:57
Speaker 3: they are well distributed across the world. I mean, so
48:59
Speaker 3: we are, so we don't have this foundational challenge of resharing,
49:04
Speaker 3: but we certainly have to deal with changing environment in
49:07
Speaker 3: which we have to think about more local supply based
49:10
Speaker 3: development aligned to what the expectations are at this point
49:14
Speaker 3: of time.
49:15
Speaker 2: So we've noticed that defense budgets really around the world,
49:19
Speaker 2: not just here in the United States, have been rising,
49:23
Speaker 2: and there certainly has been fairly robust demand for aerospace
49:27
Speaker 2: there's a big upgrade cycle just kind of starting. A
49:30
Speaker 2: lot of the fleets are pretty old. How do you
49:33
Speaker 2: look at this in terms of risk and opportunity? How
49:35
Speaker 2: are you thinking about defense and aerospace?
49:38
Speaker 3: Defense is a big opportunity for our aerospace business. That's
49:41
Speaker 3: about forty percent of aerospace business. So it's certainly the
49:45
Speaker 3: current changes in geobolgical environment and government spending more money
49:49
Speaker 3: is only positive. So it's going to become an even
49:52
Speaker 3: more growth driver for the business compared to what it had.
49:56
Speaker 3: So when we started this thesis two two and a
49:58
Speaker 3: half years back, we did not predict this level of
50:01
Speaker 3: demand in the defense, but now that's really a reality,
50:06
Speaker 3: whether it's in US, whether it's some of our US allies.
50:09
Speaker 3: There's a lot more growth opportunity across the board for
50:12
Speaker 3: different products and services we provide.
50:14
Speaker 2: And then there's been some debate about the future of
50:18
Speaker 2: technology and industry. China seems to be running away in
50:22
Speaker 2: a couple of areas like energy transition and robotics. From
50:27
Speaker 2: where you sit, is the lead going to pass back
50:31
Speaker 2: and forth or is there a clear winner? And that's
50:34
Speaker 2: a potential problem for the United States, both strategically and economically.
50:39
Speaker 3: I think we have to look at what's look ahead.
50:42
Speaker 3: Was just trying to look back and be you know,
50:45
Speaker 3: skeptical about it. We will look ahead the problems which
50:49
Speaker 3: the world is in head of us. We clearly know
50:52
Speaker 3: the US lead in AI, So how do we protect
50:55
Speaker 3: the lead? We clearly have a lead in quantum. It's
50:57
Speaker 3: one of the businesses we own that. How do we
51:00
Speaker 3: keep that scale?
51:01
Speaker 2: You do? I didn't realize what does Honeywell do in
51:04
Speaker 2: the quantum space.
51:05
Speaker 3: So we own a business called Quantinum in which Honeywell
51:07
Speaker 3: has a majority stake. We spun it off as separate
51:09
Speaker 3: company in twenty twenty one. Oh okay, all right, so
51:12
Speaker 3: it's not it's Honeywell investments in that company versus it's
51:16
Speaker 3: not part of Honeywell.
51:17
Speaker 2: I recall I call that way back when that's right, really.
51:21
Speaker 3: Twenty fist correct. So there are technologies in which US
51:25
Speaker 3: have an advantage. US have to rebuild its supply base
51:28
Speaker 3: for some of the critical sectors like semiconductor, like pharmaceutical
51:32
Speaker 3: which are mission critical, and I think that's underway, but
51:36
Speaker 3: we need to have patients that those things take years
51:39
Speaker 3: to happen. There's not a switch to say we want
51:42
Speaker 3: to do it, and those things show up. They can
51:44
Speaker 3: take five, seven, ten years, so I think it's heading
51:46
Speaker 3: in a right direction. We as a country has all
51:49
Speaker 3: the capabilities, we have the capital. We haven't know how,
51:53
Speaker 3: but we have to refurbase some of our skill which
51:56
Speaker 3: we last over a couple of years in few portions
51:58
Speaker 3: of industrial sector. But let's not forget we have very,
52:01
Speaker 3: very capable companies which created the same sector all over
52:04
Speaker 3: the world, so those have not gone away.
52:06
Speaker 2: So resuring is not as challenging as a lot of
52:09
Speaker 2: people make it.
52:10
Speaker 3: It is more thoughtful in terms of which how do
52:13
Speaker 3: you prioritize? All things being equal, reshoring is the right
52:16
Speaker 3: thing to do. But my personal view is we should
52:19
Speaker 3: pick up the top five and say, okay, here are
52:20
Speaker 3: the five we want to go really go after I
52:22
Speaker 3: make it successful, because try to do everything is going
52:25
Speaker 3: to be just extremely difficult in auto a prioritization.
52:28
Speaker 2: So final question before I get to our speed rounds,
52:32
Speaker 2: what do you think when it comes to automation and
52:34
Speaker 2: artificial intelligence? What do you think business people and investors
52:39
Speaker 2: for that matter, really are misunderstanding what little nugget that
52:44
Speaker 2: you've experienced would give them a little more insight and
52:48
Speaker 2: so what the future looks like.
52:49
Speaker 3: I think the point we discussed earlier that the automation
52:54
Speaker 3: gets heavily enabled by AI and really create the intelligence layer,
52:57
Speaker 3: and that opportunity to create it as being under a estimated.
53:01
Speaker 3: I think this opportunity is real because of the skill shortage,
53:03
Speaker 3: because of the knowledge capatures that got created over a
53:07
Speaker 3: period of time. So I truly believe that's something which
53:11
Speaker 3: needs more, more conversation and more emphasis.
53:15
Speaker 2: So I only have you for another three minutes, so
53:17
Speaker 2: let me click through these questions really quickly, starting with
53:22
Speaker 2: tell us about your mentors who helped shape your career.
53:26
Speaker 3: My early managers. I mean, I was lucky to have
53:29
Speaker 3: some very good managers who taught me different things. You know,
53:33
Speaker 3: not to be fearful about whom you are talking to,
53:36
Speaker 3: how do you think about value propositions, how to think
53:39
Speaker 3: global scale. So I think in honeywell, you're blessed to
53:42
Speaker 3: have some very strong leaders in different part of my
53:44
Speaker 3: career in the first fifteen twenty years, which really shape you.
53:47
Speaker 3: Because what shapes you as the first fifteenish years of
53:51
Speaker 3: your life, because once those value system is built in
53:54
Speaker 3: your brain, you kind of live with that and I
53:57
Speaker 3: was benefiting from some very powerful winters intoferent parts of
54:00
Speaker 3: the company.
54:01
Speaker 2: Let's talk about books. What are some of your favorites.
54:03
Speaker 2: What are you reading recently?
54:05
Speaker 3: So books I read variety, both from leadership to sectors
54:09
Speaker 3: specific The recent one of the book I'm reading is
54:13
Speaker 3: The Price from Dan Jurgen. If anybody is interested about
54:16
Speaker 3: oil economy, please do read it. Six months back I
54:19
Speaker 3: started reading Chip War so some of the sectors specific things,
54:23
Speaker 3: but also read about leadership of some of the people
54:26
Speaker 3: I admire. Dave Cody, who was Chairsea of Honeywell for
54:28
Speaker 3: a long time. He has some very fascinating book Winning
54:32
Speaker 3: Now and Winning Later inter and joined our board recently.
54:37
Speaker 3: She has some fascinating leadership books, so I read some
54:39
Speaker 3: of them. I read a lot of books on China.
54:42
Speaker 3: I think it's underestimated the scale of that economy, so
54:46
Speaker 3: I think we just need to There's a book called
54:49
Speaker 3: Words View China's view of the word. Very interesting book.
54:52
Speaker 3: It's like, we have a view about China, what about
54:54
Speaker 3: their view? Have you ever asked them the question why
54:57
Speaker 3: do you do? What do you do? So? I kind
54:59
Speaker 3: of you have very diverse The reading habits of waiting
55:05
Speaker 3: from my business specific to leadership to some of the
55:08
Speaker 3: countries specifics. You have tuggled around a lot.
55:11
Speaker 2: On that and our final two questions, what sort of
55:13
Speaker 2: advice would you give to a recent college graduate interest
55:17
Speaker 2: in the career in either engineering or management.
55:22
Speaker 3: I mean both are fascinating carrier. I would say engineering
55:25
Speaker 3: is a carrier which gives you a lot of options,
55:28
Speaker 3: So do pursue that because it gives you a wide
55:31
Speaker 3: variety of choices. Management is something that people should do
55:36
Speaker 3: who have more willingness to take a risk and have
55:38
Speaker 3: courage to make decisions, because in the end, at some
55:41
Speaker 3: point in your career you will have to do both.
55:44
Speaker 3: And if you think that's not your sphere, that's something
55:47
Speaker 3: you're not good at it, I would rather argue than
55:50
Speaker 3: you choose something really good at versus otherwise you're going
55:53
Speaker 3: to get saturated at some point. But management is an
55:56
Speaker 3: excellent carrier by itself, so both are both are excellent.
56:00
Speaker 2: And our final question, what do you know about the
56:03
Speaker 2: world of automation, engineering and artificial technology today that might
56:10
Speaker 2: have been useful thirty seven years ago when you first
56:13
Speaker 2: started at Honeywa.
56:14
Speaker 3: I don't know. I think I'm always excited about learning
56:17
Speaker 3: new technology all the time. You know, I'm still very
56:21
Speaker 3: curious to read things how they work. I think I
56:25
Speaker 3: will say that staying curious is very important for us
56:29
Speaker 3: as a human being. We should never be satisfied on
56:31
Speaker 3: what we know. We should always ask the question what
56:34
Speaker 3: we do not know, whether it is about a technology
56:37
Speaker 3: or a business process, or for that matter, any fact
56:39
Speaker 3: of life and more. You are curious. More successful you
56:43
Speaker 3: are because you're open minded and you're always willing to learn.
56:46
Speaker 3: And that has been my principle all my life. Always
56:49
Speaker 3: learned something new about anything, and you feel very fulfilled.
56:52
Speaker 2: Huh really really terrific. The mouse thank you so much
56:56
Speaker 2: for thanking generous with your time. We have been speaking
56:59
Speaker 2: with them. Kapor, CEO and chairman of Honeywell. If you
57:04
Speaker 2: enjoy this conversation, well be sure and check out any
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57:11
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