Latest / The Innovation Show / EP 665 Paul Nunes — Motorola, Combinatorial Innovation and the Treasure in the Trash

Transcript

EP 665 Paul Nunes — Motorola, Combinatorial Innovation and the Treasure in the Trash · The Innovation Show

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  innovation has countless examples where it's been critical in the
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  success and sale of products.
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  So I would encourage listeners, as they think about it, you know, when's
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  the last time you thought about your suppliers as your partner in innovation?
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  Because as we move to an increasingly modular and combinatorial innovation
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  world, that supplier innovation is gonna become ever more critical to maintaining
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  continuous innovation, if not breakthrough innovation when you're at the pinnacle of
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  your success, you want to shout it and you want-- and you've got the money to do it.
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  But it's almost the natural precursor to the downfall
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  it's
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  not that we didn't know what to do, it's just that by the time it-- we had
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  to do it, we didn't have the people to do it." Because the key is we
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  fired all those guys, or they all left 'cause they were all bored and that.
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  The constant pressure of technology to deflation, and more naturally deflation
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  'cause it's easier than innovation real innovation, is potentially the,
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  fundamental challenge of strategy today
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  before we start, I want to thank our sponsor, Kyndryl, who runs
• 1:15
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  With a unique blend of AI-powered consulting built on unmatched managed
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  You can find out more about Kyndryl at K-Y-N-D-R-Y-L, kyndryl.com.
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  Today's episode came about through collaboration, conversation,
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  communication, and friendship with my friend Paul Nunes.
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  It is always a pleasure to have you back on the show, my man
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  Always a pleasure.
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  Always a pleasure.
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  Always enjoy our discussions, and it's been too long, so
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  it's good to talk to you again
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  Always too long, man.
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  Always too long.
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  And let's give a bit of context here.
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  Paul and I would share each other articles every so often.
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  He is unbelievable thought leader.
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  And by the way, for those watching us, on the shelves there you have four of
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  his books, Big Bang Disruption, Mass , Affluence, which we'll be covering in
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  the future, Pivot to the Future, and Jumping the S-Curve, which we've covered.
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  But we haven't done Mass Affluence, and we were going to do Mass Af-
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  Affluence, and then he sent me a couple of papers, and one of them was, , a
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  story that I just had to share , because I was working on this article Based
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  on the Concept of a Lazarus Taxon.
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  Now, if anybody remembers the episode we did with Sam Arbesman,
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  Sam was the one who put me onto this.
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  He talked about this, this fish called a ceelocinth . A prehistoric fish
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  that everybody presumed was dead, and a Lazarus taxon is a species that
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  people presume , extinct, that has been living away somewhere else all the
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  time, and that's exactly what company we're gonna talk to you about today.
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  I was thinking Nokia.. But Paul discovered multiple other companies like that,
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  but one of them that he put me onto was Motorola, and we're gonna share
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  that with you today, and then draw on a lot of the concepts Paul teaches
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  in his work, in his books, et cetera.
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  Paul, maybe you'll set us up and, tell us what the hell Aidan's talking about there.
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  I think what we're talking about here is this really interesting
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  aspect of companies that seem to resurrect themself from the dead.
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  Which I think, you know, people know the term Lazarus, right?
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  So Lazarus taxon or taxa is the plural.
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  these are fossils that have disappeared from the record and then reappear,
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  you know, millions of years later.
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  Now, there's not a lot of companies that can claim to reappear millions of
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  years later, but there are a few that do seem to appear 20, even 30, , 50
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  years later and seem to have like, these fish and these other fossils have sort
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  of, you know, reappeared from the dead.
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  so it's always been fascinating to me because it ties interestingly
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  and nicely with jumping the S curve and this idea of jumping the S curve
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  , This idea that have to keep reinventing yourself tier after
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  tier, in order to be a, what we termed in the earliest days with
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  Accenture, a high performance business.
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  So, "What is a high performance business?" "Well, it's certainly not
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  one that's a, a one-off you know, a fly by night or a one-hit wonder.
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  has to have some permanence." But then the question is, well, how
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  much permanence does it need to have really for it to be important?
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  And that really ties into this whole thing is like, well, what
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  is a failed company really?
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  And we can say, you know… So one of the things we talked about then was,
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  well, maybe a failed company is a company that loses more in its afterlife or
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  in its late life than it actually ever made in profit, and that's a really
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  interesting segment of businesses, right?
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  Is those that spend all their profits.
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  you brought that up real recently, and that's another real area we can
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  go down into the real interest, which is this idea of are you doing with the
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  savings from technology and AI, are you putting it into something good?
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  Are you just blasting it?
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  by necessity, are you giving it back to the shareholders?
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  But then there's this idea of, well, what happens when you fail, when you
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  really collapse at the end of a curve?
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  we've talked about that a bunch and we looked at that in, in the books and stuff.
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  And so, you know, Fujifilm was always the great example versus Kodak because
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  Fujifilm was sort of prepared for the end.
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  It was able to reuse a lot of its technologies with other industries
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  that it had already been in such, so it didn't really disappear or fail entirely.
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  But there's another class that seems to be wiped out . but they too tend
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  to r-restore on numerous occasions.
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  So it was really fascinating.
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  So where we had gotten into the discussion, as I had sent you the
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  thing on Motorola, because it had just reoccurred to me that Motorola was in
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  the process of, of this rebirth you know, the short of the story is that
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  it split, I guess it was around 2000 into two businesses of necessity,
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  Motorola Solutions, which took all of the traditional sort of army, I call it
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  walkie-talkie, but it has another name.
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  But but you know, the walkie-talkies and the radios of World War II and
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  all of that, and, for all the first responders, radio gear and all of
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  that was huge business of Motorola's that most people didn't think about.
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  Sort of off in Motorola Solutions, but then there was also Motorola Mobility,
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  and it has its own history which is pretty interesting as well in terms of, you
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  know, absolute collapse sale to Google, mostly for intellectual property rights.
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  We'll talk a bit about that.
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  But then also sold onto Lenovo where it then pioneered a number of new
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  entrants, mostly for the mid consumer market and low-end consumer market.
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  And has really repositioned through some technology tricks, like foldable
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  screens, into a real position of rebirth and renewed positioning.
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  I just found that fascinating and so, and I loved, you know,
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  and you were the one who kind of taught me this term Lazarus taxon.
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  So, that was the origin
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  Brilliant.
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  So l- let's talk about one of the concepts you put me onto that I learned
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  from, I think it was Big Bang, the idea of combinatorial innovation.
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  The, the great example you gave, and I've seen some of your talks before as
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  well, where you talk about, well, you've, you've, your company at the end of your
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  curve, there's, treasure in the trash, if you will, or there's assets in the
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  ashes, where you, you go, "What can I…
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  What, what's still useful from this thing that's, that's no longer in the
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  context that it was very successful, is no longer successful, but, but something,
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  something's useful from it?" And you talk about this at, at the end of life
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  of companies that they can do this, and maybe we'll share that concept.
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  You might give us a couple of examples, because it's a nice segue
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  for what happened with Motorola
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  Yeah.
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  Combinatorial innovation sounds very fancy, and I sort of liked it for
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  that reason, but what it really just means is that a lot of innovation
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  doesn't come from absolute scratch from, you know, pure greenfield.
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  It comes from putting all of the pieces that are available to you on
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  the table and saying, " What else can we do?" Sort of like the Apollo 13
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  solution, which was, you know, what do we actually have in the module?
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  And how do we build this thing, for those who've seen the movie or know the story.
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  But there's an interesting thing that an awful lot of innovation is
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  of a particular nature, which is that it doesn't start from scratch.
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  It simply recombines things.
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  So putting a cell phone and putting a screen into a refrigerator, for example,
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  creating the Internet of things.
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  And so there was the whole thing that, you know, we can use a camera the refrigerator
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  to look at whether or not there's milk left and reorder, and we'll… But
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  this isn't all about reinventing the…
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  I don't have to invent a camera.
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  I don't have to invent a cellular network to transfer that data or a
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  Wi-Fi network to transfer that data.
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  I don't have to, I don't have to invent a lot of stuff.
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  I just have to create some software that kind of pulls this stuff
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  together, and I have to buy some of these parts from other people.
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  in a world of what we term in one of our books, near perfect market information,
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  which is another complicated term, which just basically means I can see everything
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  that everybody's selling on the internet.
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  I've got endless shelf space, and I've got
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  endless
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  ability to now see every part that's out there.
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  And I always used to talk about, you know, even now, recently, I fixed my
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  washing machine, a small digression, because I was able to find the part
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  that was needed online and simply pay for a $10, you know, sort of fake
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  part, not OEM, because it was online.
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  It was on Amazon.
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  know, a part for a, a, an Electrolux washing machine on Amazon.
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  Fix it yourself This is combinatorial innovation in the sense that
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  like, well, what if I wanted to build my own washing machine?
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  I could get 90% of the parts, maybe 100% of the parts off of
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  Amazon, let alone the internet.
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  So what we do is we start to recombine all these pieces.
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  Now for innovation, and so drones is a perfect example.
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  Why did drones become such a big solution or has come- become such a big product?
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  Well, nobody was inventing drones from the very beginning, right?
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  What is a drone?
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  A drone is really a flying camera.
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  It's a gyroscope.
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  It's a… And I was like, "Well, where do I see these products?
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  Where do I see these things?
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  Hmm, who's making a lot of cameras that doesn't need cameras anymore?
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  it's the cell phone industry and needs another place to sell cameras to."
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  who do I know that has gyroscopes and gyroscopic and you know, all these
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  sort of motion detectors, all the gaming industry and the cell phone
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  industry, again, all of these things.
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  So it turns out that all I'm really doing is putting a cell phone
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  on wings with propellers, right?
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  And creating some software to sort of manage that, but that's a drone.
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  And so you can see the speed at which I can design, you know, send
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  to third party, you know, makers, get it into a supply chain and sell it.
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  You know, the speed at which that went from zero to 60, zero to you
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  know, 10 million, 100 million units sold was tremendous, and that's
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  what's going on everywhere else.
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  Now, where it becomes really important, I think, for this idea of Lazarus
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  ta- taxon is When we start to look at failure and we look at like,
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  you know, well, who are the, cats?
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  Who are the bottom feeders?
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  I hate to call them that, but it really is this idea.
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  But you see that it's like to treasures, or we just say the treasure in the trash.
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  I find it fascinating to be thinking about, well, who are the ones, you know,
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  the private equity firms sometimes, who are the ones that are actually going out
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  and sort of saying, "All right, where's the treasure, you know, in the trash?"
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  And I hate to call it that as well because yeah.
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  And then, and how do you extract it?
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  which is fascinating as well.
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  so one of the treasures in the trash, you look at IP you look at talent, look
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  at-- So there's all kinds of categories that we see that you can break down
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  and start to say, okay, you know.
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  And I think one of the great things, if you want to get a feel for it,
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  that I've been doing a bit lately in my own retirement s-semi-retirement,
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  been watching these shows.
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  I'm always fascinated with these people who restore cars, right?
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  Because a, a car restoration in many ways is a perfect example
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  for what has to go on here.
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  You gotta break it down.
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  You gotta take it all the way down to its parts.
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  You know, they're all rusty, some are broken, some can't be replaced.
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  You gotta tear it all down, what you have, and then build it
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  back up in a sequence of steps.
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  Because if you don't clean the metal in a car and get all the rust off
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  and everything else, and you just quickly rebuild it, you're gonna
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  have a nice car, but it's gonna rust out again on you in two years.
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  you really have to do it by step, and you have to do it right, and
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  you have to do it completely.
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  And so some of the research that I see going on, some of the research that I've
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  been conducting for myself and my own thinking, think really ties into a lot
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  of stuff that you've been saying is, we know about that rebuilding process?
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  You know, what do we know about the restoration process of companies?
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  And we don't know, I think, you know, I haven't found, we don't know as much
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  because it's a lot more easy, it's a lot easier for us to study successful
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  companies and, you know, all of the wonderful stories and those, and
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  even those that can jump an S-curve.
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  But we don't really study the companies that have been restored
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  like a great, you know, car or you know, airplane or whatever
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  th- there could be a future for you, man, instead of a show on restoring
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  cars, restoring old washing machines.
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  Yeah.
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  Paul Nunez presents Washing Machine Rebirth, or the Phoenix Washing Machine.
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  Bring it back.
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  Well, I-- it is serious is because there's an, an important other big idea
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  that's buried in that, is the idea of the necessity of modularity, and it ties even
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  into mass affluence and everything else.
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  Everything that's more expensive is human talent.
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  And as we go into a diminishing population, right, as we go into a
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  shrinking and imploding population, and with how hard it is to find people
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  committed to the trades, you can't find people to fix washing machines.
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  So we either have to fix them ourselves, we have to reach into a level of
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  modularity says, "I can fix it myself," because I'm going to just throw out
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  it… You know, there's only ten parts to it, and I take the one that
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  isn't working, and I throw it out.
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  So design for mo-- You know, I know it seems like a bit of a digression,
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  but it is tied in together with that because there's a design for modularity.
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  And to bring it back to Motorola that we're talking about, and I won't profess
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  to know , too much about the details of it, it's pretty clear that the
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  technologies in the phone are built off of chips and chip designs and aspects
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  that were pretty easy to reassemble.
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  And in fact, actually, the move to Android as an operating system
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  the phone was, again, part of the simplicity and repair thing.
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  Motorola couldn't keep up with its own software.
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  Who could?
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  And the cost of that and the people and everything else.
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  So you lose the customization, but you get simplicity and modularity, and you
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  also get, well, all of the phone software refreshes come straight from that.
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  this idea of the necessity of partnering with other companies
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  that not only will provide the parts but provide the resuability
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  that provide the the maintenance of that and the continual upgrade.
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  Because who's going to improve?
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  When you think about it, and this is a really interesting thing that
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  we found in our research about automobiles and stuff and in the
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  study of innovation, which is if you don't have what we call supplier-based
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  innovation, which is, you know, I've got a windshield in automobiles, right?
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  Tempered glass.
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  Well, tempered glass comes out of, you know, makers like Corning.
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  I don't know who invented it.
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  I won't say that.
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  But glass is the glass that's structured, so that it breaks
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  into little pieces instead of really razor-sharp shards, right?
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  Well, whose job is it to invent that?
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  Is it the automaker or is it the glass supplier to the auto?
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  Because there's a glass supplier.
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  And so that ability get all of your component makers on board with
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  making your product better, whether they're simply doing it by making
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  the supply better or whether they're doing it intentionally for you.
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  in fact, in our studies, and this is really important from an innovation
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  standpoint, which is what all this is about you know, at the highest
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  level that we talk about, from an innovation standpoint, there's
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  customer-supplied innovation.
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  The sources, there's nine-- We identified nine sources of innovation, customer
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  innovation, leadership innovation.
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  You know, at the Westin Hotels, it was the CEO who was tired of sleeping in a
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  bad bed, apocryphally, as the story goes, simply came in and said, "You know, I
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  don't care that we're a hotel company, and I don't care whatever. We're gonna
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  make a good bed because I'm tired of sleeping on a bad bed, and I think others
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  are gonna enjoy it too." So, but that's often, you know, this CEO-led innovation.
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  But getting back to the original point, innovation has countless
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  examples where it's been critical in the success and sale of products.
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  So I would encourage listeners, as they think about it, you know, when's
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  the last time you thought about your suppliers as your partner in innovation?
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  Because as we move to an increasingly modular and combinatorial innovation
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  world, that supplier innovation is gonna become ever more critical to
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  maintaining continuous innovation, if not breakthrough innovation
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  I don't wanna come too far off the trail, but you know us, man.
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  We do this all the time.
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  The… By the way, this is like a conversation out loud
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  our conversations we have.
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  Total nerd fest.
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  But one of the things you said there, I wrote about this a couple of weeks ago.
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  You're modular.
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  You have a partner.
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  That partner say it's a windscreen company.
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  And I think this is quite important in the age of AI, is that I have my expertise,
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  you're a supplier to me, but then now you kinda go, "Hmm, we've become pretty good
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  at this. Let's go after, I know we're a windscreen company, but let's actually
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  build the car around the windscreen."
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  And it's kind of what happened with BYD.
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  They were a, an energy company, a battery company, and they built, they go, "You
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  know what? Let's wrap the, let's wrap the battery in a car." And to huge
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  success, because the context changes.
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  And this idea of the partnering and the, the frenemy of the partner.
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  Sometimes the, and we've seen it in the, the innovation literature, that
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  the supplier actually becomes now a competitor and actually steals your
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  lunch, and happens in China quite a bit.
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  I know you've talked about this.
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  Maybe you'll say a word on that.
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  And particularly in an age of AI where, say, for example, I, I know
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  this shouldn't happen, but I am using an enteri- enterprise partner, one
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  of the big companies, an AI partner, and I'm putting my IP into it.
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  And then, and sometimes I'm actually putting in implicit tacit knowledge into
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  the thing, and then the thing's available for everyone else that can then access
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  it, because you're just essentially making the pie of knowledge bigger.
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  So there's a lot in there, but maybe you'll, you'll give us your thoughts.
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  what's really interesting is almost all profitable advantage comes
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  from closed systems of technology.
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  But to close the system only encourages everybody else like Unix and whatever
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  to band against you and create some large open system And the, the, the
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  users of Unix might not make as much money, at least they don't-- they're
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  not held, hostage to your closed system.
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  And it's really the only way to sort of compete.
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  So the history of technology, and I've been fortunate to, you know,
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  to be a small student of it over the years, but the history of technology
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  shows this forever yin and yang of closed system, open system.
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  There's almost no way around it because, again, the the abnormal
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  rents to use, you know, sort of things, the above average rents, the
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  profits come from a closed system.
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  It's much easier to make money in a closed system.
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  So you're always gonna have that sort of tension.
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  I think where there's opportunity in a bunch of places, one is there's
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  finite supply, and we'd even talked about how, you know, Apple i-in the
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  book on Jobs, they talk about sort of cornering the market on camera lenses.
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  We've talked about that that, well, if there's only so many camera lenses,
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  you can only make so many phones.
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  matter if you have all the other parts, doesn't matter.
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  So this idea of, of having proprietary technologies in the ecosystem of parts,
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  there's the two ways of competing.
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  One is, you know…
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  And you have to be the best because it is, it's accelerated to the point of
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  almost instantaneous commoditization.
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  You're only as good as your last version anything because, you
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  know, this interchangeability.
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  So there's that tension, but if it's interchangeable and I find it
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  cheaper or better in the ecosystem, yeah, I'm likely to trade up.
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  this is where I think even AI can't conquer and where there's a lot of things
• 22:48
  like there's an awful lot of human and human relationship in the nature of
• 22:54
  structuring these ecosystem solutions.
• 22:59
  Now, AI will be able to tell you where your opportunity is.
• 23:02
  AI will be able to tell you very quickly, "Hey, much better, cheaper
• 23:06
  options to this part out there."
• 23:09
  But AI may not be able to tell you exactly how reliable really that new
• 23:14
  other vendor is, nor will it be able to tell you exactly what the true
• 23:19
  value of your relationship with this other company is as well, right?
• 23:25
  So I mean, maybe eventually long-term, you know, I don't know, 50, 100 years out,
• 23:29
  but probably not in our lifetimes anyway.
• 23:32
  But so this idea of understanding and building some level of human-based
• 23:38
  connection across a competitive ecosystem, because if it's all just about the
• 23:43
  cheapest parts then it's like, well, might as well just let the computers run, right?
• 23:48
  Which is what everybody sort of thinks is gonna happen with AI.
• 23:51
  It's like, we'll let AI figure out what the best combination of
• 23:54
  parts is and just constantly cancel contracts and start new contracts
• 23:59
  and get me new parts and da, da, da.
• 24:01
  But, you know, you can get this vision of, a great Dr. Seuss thing,
• 24:06
  you know, the Star Belly Sneetches.
• 24:08
  This is pretty random for those who don't have kids, but there's
• 24:11
  a great part of this book of Dr.
• 24:13
  Seuss's, which has all these characters, but they're all running around chasing
• 24:16
  each other's… their tails because they don't know if they want multiple
• 24:19
  stars or fewer stars or all of that.
• 24:22
  So you can imagine the chaos that comes from trying to perfectly
• 24:27
  optimize parts, you know, inventory, say, and your parts usage.
• 24:33
  The other thing relates back, so we can tie it back to the Motorola aspect,
• 24:37
  which is designing to a custom segment, might even be an enormous segment, which
• 24:44
  is the financially limited market or, you know, whatever you wanna call them.
• 24:50
  Now, that requires using more affordable parts, and that's actually where Motorola
• 24:55
  had a, a great advantage because nobody could touch combined, the combinatorial
• 25:01
  solution that Motorola had come together to put a- an approximate hundred and
• 25:06
  eighty to two hundred dollar phone.
• 25:09
  They basically, you know, the, the… And then what they said is that, you
• 25:13
  know, because they don't-- you don't have power and charging capabilities
• 25:18
  all over, and it's great 'cause, like, in Africa, you see, in my travels,
• 25:22
  you, you see these huts, right?
• 25:24
  And they have cell phone-- They have solar panels on them.
• 25:28
  And it's like, "And what's that for?" It's like, "Well, that runs the LED
• 25:32
  lights at night and the phone chargers." And the phone charger, because
• 25:37
  Wow
• 25:38
  you don't have a power grid, you don't have phone chargers.
• 25:44
  So battery-- Where am I going with this?
• 25:46
  Battery life is important.
• 25:49
  It's not important to the mo-- to the f-the first world model,
• 25:52
  whatever you wanna call it, to the, you know, to the affluent world.
• 25:57
  But it's certainly important, you know, battery, l- how long the battery lasts
• 26:01
  is really important to a certain class.
• 26:05
  . Cutting down the design of using the processor at full power all the
• 26:10
  time, but conserving battery for that, designing, building that into
• 26:15
  the hardware design of a phone is actually enough of a differentiation.
• 26:21
  So regardless of the perfect solution idea of AI in a world of
• 26:28
  infinite parts, there's still the opportunity that's honest to say,
• 26:32
  well, where's the market segment?
• 26:34
  Where's the opportunity?
• 26:36
  Where's the combination that actually really peaks on a, a market of size
• 26:44
  and value, that's an opportunity?
• 26:46
  And again, tying it back to where Motorola has, has helped its rebirth
• 26:51
  is by finding that profitable segment in that opportunity.
• 26:56
  And I think that's where a lot of other companies are gonna have to, to think
• 27:00
  It's a great point, man, and y- Christensen talked about it.
• 27:04
  He called it the concept of a non-consumer and this whole… It's your biggest
• 27:09
  customer, the customer who's not actually buying from you today, , this happened
• 27:13
  with General Motors and Ford when Toyota entered the States in the 1950s.
• 27:16
  They look at it and they go, "That's terrible. I can't believe they're trying
• 27:20
  to compete with us." And you're going, "They're not. Be- they're competing with
• 27:24
  somebody who can't afford a car." And I think that concept is so, so important
• 27:28
  that that becomes your biggest customer.
• 27:30
  And actually, there's a whole segment there.
• 27:32
  You reminded me of my son, who's now 16.
• 27:36
  His first phone was a phone, I think it was called the Rugged Phone.
• 27:40
  Like, this phone was a little, basically unbreakable.
• 27:44
  And you're like, "I'm not gonna give my kid an iPhone where he can smash
• 27:47
  it and I have to get the screen changed time and time again. I'll
• 27:49
  buy something that's good enough."
• 27:51
  And I think it's that idea of good enough, and it's really,
• 27:54
  really valuable for this concept.
• 27:56
  But th- this, one, one of the other things you said and we come back to,
• 28:00
  I'm just looking at my notes here, is the, the, the IP question again.
• 28:06
  And I, I just wanna bring that to the, to the fore again because it becomes, , so
• 28:11
  important in the age of AI, where IP is, a lot of people feel is at risk.
• 28:17
  But IP in the concept of selling it, what's useful from
• 28:23
  all the stuff you've built.
• 28:25
  Kodak is another kind of, in a way, a Lazarus taxon, in that they had
• 28:29
  so much, so much IP, and they had so many pa- patents that they're
• 28:34
  still making money from that.
• 28:36
  , Kodak is an excellent part of the story, even long after Kodak had sort
• 28:41
  of failed or disappeared, it was still making billions of dollars, billions
• 28:47
  a B, on IP and licensing deals.
• 28:52
  There is this idea of, you know, what are you creating and what
• 28:56
  are you protecting as your assets?
• 28:59
  I… the relevance of IP, you know, it, it's just a, it's a really big topic in
• 29:04
  the sense of there ways to get around IP?
• 29:08
  Do you design little things, you know, so what is the real
• 29:11
  protectable and what's the lifespan?
• 29:13
  How long does that stuff remain relevant?
• 29:16
  So you can't bet on it forever, but I think it's an enormous
• 29:20
  element and question for those who are going to restore cars.
• 29:24
  You know, if you're gonna restore a business or, or chop shop a, a car, right?
• 29:28
  Because the other option of restoring an, an old
• 29:31
  Washing machine
• 29:33
  an old, well, no, an old car, but the, the, you know, you can
• 29:36
  either, you can either take it…
• 29:38
  But this is even true of, you know, when you talk about restoring cars, right?
• 29:41
  A lot of times there's value.
• 29:44
  There was, just to digress slightly, but there was something like a million-dollar
• 29:49
  Porsche that was found in a garage, and it may be a bit apocryphal.
• 29:53
  But a million-dollar Porsche found in a garage that couldn't be restored,
• 29:57
  but it had so many of the missing original parts for other restored
• 30:04
  Porsches of that year that its value, and so again, you know, talking about
• 30:11
  hidden treasure, was, "Oh, you know, I can never restore this Porsche.
• 30:16
  I don't want it." It's like, no, somebody bid like a million dollars
• 30:19
  for it because they knew they could chop it up into 50,000, $100,000 parts,
• 30:24
  $10,000 parts that would all go to lots of these other cars to be restored.
• 30:30
  And so that's really the nature of where it goes into in that.
• 30:33
  And I think what's interesting to tie it back to technology is, even AI, is It's
• 30:40
  fair that we didn't think a lot about this previously, and this is always when
• 30:44
  I think about thought leadership, it's always important to think about why now,
• 30:49
  If you're gonna have a topic about why now, so I think the reason it-- what
• 30:52
  justifies us talking about this right now is even 10, 20, 30, 50 years ago, we
• 30:59
  would never be able to think about how you could resell all those parts of a
• 31:03
  Porsche 911, you know, '62 Porsche 911.
• 31:08
  Today, you couldn't, you know, 30 years ago, you couldn't really think about,
• 31:12
  well, how am I gonna disassemble a company and all its component AI and
• 31:18
  try and figure out and find who are the companies that are gonna buy that AI?
• 31:22
  Who are the thing?
• 31:23
  now this idea of Disassembling and reselling a company for value is so
• 31:31
  much easier, so much more possible.
• 31:35
  The potentiality, the potential in that is so much higher thanks to technology right?
• 31:42
  I get visibility into who potential buyers are of the IP or products or capabilities.
• 31:49
  And it's not just IP, 'cause the other thing that's really important
• 31:52
  is manufacturing capability, manufacturing capability and processes.
• 31:58
  Then also I think even the talent, and this is something
• 32:01
  that we wrote about 40 years ago.
• 32:05
  Eh, 30 years ago.
• 32:06
  I don't wanna date myself too much, even 30 years ago, there
• 32:10
  was this thought of like, well, what if you had a group working on
• 32:13
  something that failed at a company?
• 32:15
  if you just resold that research group?
• 32:18
  What about this idea?
• 32:19
  And this was one of our, you know, as I used to dabble in sort of sci-fi
• 32:22
  thinking, is that, no, you would actually be moved and sold as an HR not as a…
• 32:29
  We always think of HR, we always think of HR staffing as individuals, right?
• 32:36
  Generally, or as an entire company.
• 32:39
  we never really think about the, the tiering of, well, what if I put four
• 32:44
  or five people together and said… I mean, 'cause everybody knows when you
• 32:48
  hire an executive, you're hoping to hire the four or five other people they
• 32:52
  worked closely with, and you're hoping that these people are gonna jump ship.
• 32:55
  But what if we formalized the process of hiring teams units or divisions
• 33:04
  and cutting them up in these tranches of the humans, just the capabilities
• 33:11
  and the IP and everything else?
• 33:12
  'Cause a lot of times we think, well, they're just workers in a
• 33:15
  factory, so we'll just ship them along with the parts, right?
• 33:19
  But this idea of all the value, and I think that's gonna become increasingly
• 33:23
  interesting, if not important, at least more interesting as an idea as
• 33:28
  we think about, well, what's AI going to do to some of the simple thinking?
• 33:32
  And then what's gonna be the importance when we talk about the importance of
• 33:36
  relationships, but how do we kinda quantify the value of relationships?
• 33:42
  And I'll give you another specific that I was just covering recently that fascinated
• 33:48
  me, was the, the story of Fairchild Semiconductor and the oh, I forget what
• 33:54
  they call them, the, the Traitorous Eight.
• 33:57
  So most people don't know that basically it was oh, and I forget
• 34:00
  the name of the company, I apologize, beforehand, that the eight people that
• 34:05
  started Fairchild Semiconductor came
• 34:08
  Shockley.
• 34:09
  Shockley Semiconductor.
• 34:10
  Yeah, but the eight include like, you know, Noyce and,
• 34:15
  Gordon Moore and of Moore's Law.
• 34:18
  And, and you think about, and it's like, and this is j- it's a
• 34:21
  traditional story, but probably lost to a lot of younger, readers
• 34:25
  and that 'cause it's so historical.
• 34:27
  But it's like, wow, this company but we loved it as an important story of talent
• 34:32
  when you really think of the talent.
• 34:34
  It's like this company had these eight people that were outrageously
• 34:38
  talented, outrageously, and they were allowed to leave together
• 34:42
  because they were dissatisfied and then went off to do these things.
• 34:46
  And that's actually got us a nice tie in that I'll just
• 34:48
  throw out to kind of close that.
• 34:51
  , shockley had all that talent.
• 34:52
  Shockley should be a name we still talk about today.
• 34:57
  another nerdy thing I was doing was I was thinking of doing a series on
• 35:02
  football shirt sponsors that are gone.
• 35:05
  So all these companies that were like, I remember Sharp on the Man United
• 35:10
  football shirt, shirt, and all these companies, and they're just like,
• 35:14
  they're all, all people might remember them is from the old football jerseys.
• 35:18
  But they, they were, they're earning that much money that they
• 35:21
  were sponsors at these teams at a time where it was very expensive
• 35:25
  Bingo.
• 35:26
  Bingo.
• 35:27
  And this is where some might say, and I think I've probably said it and
• 35:31
  others would say it, but is the first sign that they lost the thread, right?
• 35:37
  They lost sight of the ball.
• 35:38
  They took their eye off the ball.
• 35:40
  Because when you're more worried about getting on a, a Manchester shirt
• 35:45
  you are about good quality stuff to customers for good prices and everything
• 35:51
  else, this is the thing of, you know, why is it always the people who put
• 35:56
  their names on buildings that wind up disappearing five years later?
• 35:59
  Not always, not whatever, but like stadiums.
• 36:02
  Why is the stadium sponsorship-- mean, it's the same thing, but
• 36:05
  it's like stadium sponsorship, you know, sort of the last refuge.
• 36:11
  Or it- it's the pinnacle of when you're at the pinnacle of your success,
• 36:16
  you want to shout it and you want-- and you've got the money to do it.
• 36:20
  But it's almost the natural precursor to the downfall because it's like executives
• 36:26
  are worried about who I'm going to impress with the visibility of my name.
• 36:29
  Because people will argue as, you know, you could say, people will argue, "Well,
• 36:33
  no, it's about name recognition and it's, you know, it's about keeping in
• 36:37
  the whatever." the science of it is there is a certain amount of signaling that
• 36:42
  goes on with it in, with advertising, so we can't be unscientific about this.
• 36:46
  It's like, yes, that you can buy a Super Bowl commercial is
• 36:51
  a commercial in and of itself.
• 36:53
  It signals to consumers that you have enough money or enough wherewithal
• 36:58
  or enough backing to be able to afford a million dollars a minute
• 37:02
  or three million, whatever it is now, of Super Bowl advertising.
• 37:09
  But it's also a question of, when you think about the stages of marketing and
• 37:15
  starting with awareness, awareness to understanding, to preference, to purchase.
• 37:23
  You know, do you really need to build awareness?
• 37:26
  Has anybody not heard-- Has anybody in the copier business not heard of Sharp?
• 37:32
  You know, so, so the whole vanity project.
• 37:35
  So I think you raised a great point, but I just wanted to add that little extra
• 37:38
  context of things that we've looked at is, you know, to what extent is that actually
• 37:43
  scientifically a marker of a company that may be at its peak or losing its way?
• 37:49
  So your aver- observation is right on.
• 37:52
  I was thinking about Moneyball and that whole idea of the, the, I, I can't
• 37:56
  remember what it was called, science metrics or something, that the whole,
• 38:00
  the, the science of sport and, you know, what type of player is best for
• 38:03
  a team and all that kind of stuff.
• 38:04
  That marketing in a way has gone there, and you, you can be sure
• 38:09
  that somebody, you know, maybe it's a CEO, this was a dream.
• 38:13
  I, I wanna be a Super Bowl ad or I wanna be on the cover, the, the
• 38:17
  jersey sponsor, et cetera, et cetera
• 38:19
  is no question about that.
• 38:20
  That, I mean, that's I think even in the literature of, know, it's a,
• 38:27
  you know, it's always that there's a huge amount of vanity to it.
• 38:30
  I don't think anybody could argue having your name on a stadium or par- I mean,
• 38:35
  particularly if your name is the name of the company for these, you know, we won't
• 38:42
  name particular names, but you can think of buildings, buildings in San Francisco,
• 38:46
  buildings in, you know, other places.
• 38:50
  Building, your building, your stadium, your
• 38:53
  Sears Tower
• 38:55
  exactly.
• 38:56
  Yeah, the, but I, I just can imagine, right, so somebody on, maybe listeners to
• 39:01
  this show, so you're a, an advanced type of marketer, you're head of innovation.
• 39:07
  You're kind of going, "What I could do if I had that money, how I could use it," and
• 39:11
  it goes back to this concept of if you're making savings through AI efficiencies,
• 39:16
  are you reinvesting it or as, as you told me, are you eating your seed corn?
• 39:21
  Or, you know, not even seed corn.
• 39:23
  Are you, are you using this excess resource that you have for vanity
• 39:27
  projects, or are you actually gonna to grow the next academy of the sports team?
• 39:32
  Because most companies don't, which is actually the last thing I'd love
• 39:35
  you to finish on, because one of the very valuable things is I, I think if
• 39:40
  you're a company, you should map, as you said, your suppliers, your, your
• 39:45
  innovation that's coming from, your capabilities, your talent on S-curves.
• 39:50
  You, it's a whole system of S-curves.
• 39:52
  I often think of those, you know, when you're a kid and you
• 39:54
  make the paper doll and you pull them out, except it's S-curves.
• 39:57
  You pull out a lot of S-curves and you go map every subsystem
• 40:01
  of the company to an S-curve.
• 40:03
  But one of them, as you talk about, one of the disappearing ones, and
• 40:06
  one that people don't realize until it's too late, is the talent curve.
• 40:10
  So oftentimes a new strategy, there's a change in the business environment,
• 40:15
  there's a new strategy needed, but nobody in the company can carry
• 40:18
  that strategy 'cause you don't have the capabilities in the company.
• 40:21
  So there's two sides to this coin.
• 40:22
  One is letting that happen.
• 40:25
  The other is, like you said, relationships is an S-curve.
• 40:28
  So if a lot of the glue that joins your, your industry is based on relationships,
• 40:35
  along comes maybe some type of private equity money, buys your company, and sees,
• 40:40
  kind of go, "What the hell does Paul do?
• 40:42
  What does Nunes do, apart from fix washing machines?" And they go, "Well,
• 40:46
  you know, he knows buttloads of people.
• 40:49
  He knows them well.
• 40:50
  He meets them regularly.
• 40:51
  He meets them for coffees.
• 40:52
  They like him." That's of no value to PE or somebody coming into a company, 'cause
• 40:58
  they actually don't see the value of that thing until it's gone, and, and that's
• 41:03
  often that happens in so many companies.
• 41:05
  I'd love your thoughts on that because I, I can just see it coming, Paul, when
• 41:10
  you have this AI efficiency, and say a company has heavy investment from
• 41:16
  private money, and then you go, "Well, let's get rid of the, all those guys,"
• 41:21
  you know, , the relationship-based, non-transactional sales team.
• 41:25
  What the hell do those guys do?
• 41:26
  Bringing people to Man United games with Sharp on their jersey.
• 41:30
  What are they doing for us?
• 41:31
  And you're going, loads of stuff.
• 41:33
  It's hard to actually articulate it, but actually loads of stuff.
• 41:37
  Not interested, get rid of them.
• 41:39
  It's a great question.
• 41:41
  A great thing to add, 'cause there were two actual unconventional wisdom things
• 41:45
  I did want to raise with you, which will be a perfect way to sort of close.
• 41:49
  And it really is a big point because you know, sort of where to start from that.
• 41:54
  One is that
• 41:57
  Part of what happened down in the old curve, so let's start with the old curve.
• 42:00
  The old curve had the inventor, then you had this rise, and the- during the
• 42:06
  climb, fired all the people that cost too much and that were inventors 'cause they
• 42:11
  were trying to do something different.
• 42:12
  And I always like to use sort of Starbucks.
• 42:14
  Like, once you figure the, the colors, like, you know, I know
• 42:17
  what the counter looks like, I know what the store design looks like.
• 42:19
  All I'm trying to do is stick a lot more of these stores all
• 42:22
  over the place, 'cause the more stores, more revenue, more profit.
• 42:26
  in this wild growth thing.
• 42:27
  And then the thing is that, well, but if I keep hiring managers or I keep
• 42:32
  all my R&D, it's like I don't need R&D 'cause I'm not changing anything.
• 42:35
  'Cause if I change something, I might screw up the business.
• 42:39
  So there also becomes the whole you know, thing against innovation, the
• 42:43
  whole management push against innovation, which says, you know, "Every new thing
• 42:48
  you're recommending to me, it's like, what's the marginal utility of that?
• 42:52
  I shouldn't play with a good thing and a good formula." And so you get the
• 42:56
  Jack Welches that just basically tear out and you get the Six Sigma crowd,
• 42:59
  and we talked a little bit about this.
• 43:01
  get to the top, and this is where all of the s- a ton of the CSOs that
• 43:06
  I talked to over the years, and I know and stuff, they always said
• 43:09
  it's
• 43:09
  not that we didn't know what to do, it's just that by the time it-- we had
• 43:13
  to do it, we didn't have the people to do it." Because the key is we
• 43:16
  fired all those guys, or they all left 'cause they were all bored and that.
• 43:20
  So what we saw in jumping the S curve is that it was critically important
• 43:23
  that you had enough new projects.
• 43:25
  Like, why do you have to start the next curve early?
• 43:28
  Now get this tension.
• 43:29
  If I start the next curve too early, I may be ahead of the technology of the
• 43:33
  next curve, and that's a huge problem.
• 43:35
  And hopefully we'll have another time to talk so we can go into
• 43:39
  this problem of trying to force of technology, which you just can't do.
• 43:44
  You can throw all the money you want at battery technology.
• 43:46
  It hasn't turned into exponential improvement.
• 43:50
  Nobody knows when and if that's gonna happen for real.
• 43:53
  So we can talk about
• 43:53
  , a great case is that actually the Geoffrey Cain book I was telling
• 43:56
  you about about NeXT Computer.
• 43:58
  I mean, Jobs was trying to do that.
• 44:01
  He was trying to jump the curve, and the curve wasn't ready.
• 44:04
  The technology didn't exist for what he, his vision was.
• 44:07
  And actually, he was lucky he got another bite of the cherry
• 44:10
  or the apple as the story went
• 44:13
  This is perfect.
• 44:14
  No, exactly.
• 44:15
  But yeah, but it's real easy, and we can go someday into a lot of the
• 44:19
  stories of these companies that, you know, even GE and Predix and stuff.
• 44:23
  It's like you can throw billions and billions and billions into trying to
• 44:27
  accelerate the technology, not the innovation, which is the use of the
• 44:30
  technology, but if the core technology just won't give up the ghost, just
• 44:35
  won't improve on the timetable that you need it to you can wind up throwing
• 44:40
  a lot of good money after bad or you can bankrupt yourself chasing that.
• 44:44
  goes to the thing, so gets compressed, and then there's a second challenge now,
• 44:50
  which is that technology, and this goes to things that you've been talking about
• 44:53
  recently and is really important, is this idea of what to do with the money.
• 44:56
  Well technology can do two things.
• 44:58
  It can help you innovate, but it can also take costs out of a system, right?
• 45:02
  Most of w- the easy thing, the easiest way to innovate, quote unquote, is to use
• 45:07
  technology to take cost out of a system.
• 45:10
  Taking those costs out, even like AI, right?
• 45:12
  I don't need all these analysts, so I'm gonna fire all these analysts
• 45:15
  and just use the AI answers.
• 45:18
  Well, that's gonna save you cost, but what are you gonna do with that money?
• 45:22
  And the key is, all right, what if I fire all these people, but now I don't
• 45:25
  have these people who've learned anything about my business for later on, so
• 45:29
  maybe I should repurpose those folks.
• 45:33
  But so we get into this compressed nature of where's the money coming from?
• 45:37
  And I'm not sure that in some of the stuff that you've been talking
• 45:40
  about one of the things I did wanna talk about is this idea that
• 45:45
  Technology really lends itself to taking out costs and price deflation.
• 45:50
  So one of the things that we didn't have to fight so badly 'cause it was
• 45:53
  slower, the nature of a technology learning curve, a business learning
• 45:57
  curve that takes out cost, 'cause that's where your profit comes from.
• 46:01
  But if consumers know you're doing that, they want the money.
• 46:06
  So the more consumers are aware of the deflating nature, the, the price
• 46:10
  deflation nature, you're getting-- You as a buyer, again, combinatorial
• 46:13
  innovation, you're getting everything cheaper because all of those suppliers
• 46:18
  are bringing it to you cheaper.
• 46:19
  But the, the problem today is, again, with the near perfect market
• 46:23
  information, the consumer knows this.
• 46:25
  So the consumer is not gonna let Apple raise its price to fifteen hundred or
• 46:31
  two thousand dollars for the new 19 or whatever the iPhone is coming out, right?
• 46:36
  It's gonna be about a thousand dollars or twelve hundred with a little inflation.
• 46:41
  now you're gonna have to tell me how much more stuff you're
• 46:43
  gonna jam into this phone, how much more value you're gonna get.
• 46:47
  But, you know, we forget that even in previous dollars, we used to
• 46:52
  buy PCs at three thousand dollars, you know, a desktop, right?
• 46:57
  When's the last time anybody bought a three thousand dollar
• 46:59
  desktop in terms of a mass market?
• 47:03
  So as a consumer, we are in a an unprecedented and
• 47:07
  wonderful world of deflation.
• 47:11
  But deflation is real, and so this will be a topic for another discussion there.
• 47:15
  But companies need to really think through deflationary pressures.
• 47:20
  China was a great one.
• 47:21
  You know,- I even saw that there are some… just the thing is that
• 47:26
  China might not have been in a hurry for cheaper oil because that
• 47:29
  would accelerate their deflation problems, and real risk in China.
• 47:35
  So anyway, it's a huge thing.
• 47:38
  And so while it sounds simple to just sort of say, "Hey, you've got this money.
• 47:42
  Where to put this money?" The constant pressure of technology to deflation,
• 47:49
  and more naturally deflation 'cause it's easier than innovation real
• 47:54
  innovation, is potentially the, the fundamental challenge of strategy today
• 48:01
  man, we said we'd do 15 minutes.
• 48:05
  It's nearly an hour.
• 48:07
  Coming up on an hour.
• 48:08
  This is what happens all the time.
• 48:09
  We say, "Let's catch up and see what's going on." And
• 48:12
  yeah, it's always a pleasure.
• 48:13
  And Paul, by the way, 'cause you mentioned there, people might be
• 48:16
  wondering what was he talking about that time where you said during your trails.
• 48:19
  So he's been traveling the world.
• 48:21
  How many countries have you done, man?
• 48:23
  How many left?
• 48:24
  Oh, I don't even like to say.
• 48:25
  I've got 130.
• 48:27
  Got another 64 to go.
• 48:29
  amazing, amazing.
• 48:30
  This is on the bucket list.
• 48:31
  And you're getting through it.
• 48:33
  Just back from Papua New Guinea, just off to Turkey.
• 48:36
  So living, living the life, man.
• 48:37
  Living the life.
• 48:38
  One last thing, actually, I, I, I'll say, and it's just 'cause i- it's, I
• 48:42
  think it's quite relevant is, I mentioned about how PE can come in and go, "Okay,
• 48:47
  get rid of those people that we don't need anymore, or we don't feel we need."
• 48:51
  The, the people who created the curve we're on, perhaps, or the people who
• 48:56
  have those ro- those nondescript roles, which is actually often people in, in
• 49:02
  roles I've worked in, and many of the listeners of the show, that will work on
• 49:05
  new concepts, new projects, new ideas, trying to bring new blood to the company.
• 49:10
  But then there's another thing happening, where I've seen this, where
• 49:14
  you have a new what was used to be a third world country, or a country that
• 49:22
  didn't have massive economic prosperity before, and there's a shift in those
• 49:28
  people in senior leadership in those.
• 49:30
  And , it kind of goes to the idea of the DNA changes of the organization.
• 49:36
  And in some countries, the culture might have been very tire- top down
• 49:40
  or hierarchical, and not so much like, you know, let people make mistakes and
• 49:45
  let people learn, et cetera, et cetera.
• 49:47
  It becomes very computer-like, 'cause this is what triggered this memory, was , we're
• 49:53
  talking about AI can't do those things.
• 49:55
  But companies are becoming more scientific, if you will, and less human.
• 50:00
  And in there, there's no space, there's no, no tolerance for white
• 50:04
  space or, or ambiguity, which is where innovation really lives
• 50:09
  well, I think you posit a great theory worth exploring.
• 50:15
  concern might be, or my position would be, not sure that's true.
• 50:20
  I'm not sure we've lost white space.
• 50:22
  I'm not sure that we don't have as much time for thinking and being with people.
• 50:28
  Heck, you know, me, just my nature, it's a long story, but we spend too
• 50:34
  much time talking to each other.
• 50:37
  And, you know, when you think about it, like the meetings, the conferences,
• 50:42
  the whatever, I mean, taking the pulse of what everybody else is
• 50:46
  thinking has become the fundamental job of so many businesses, right?
• 50:52
  But it's not real though, man.
• 50:54
  I don't think it's real.
• 50:55
  I think it's, I think it's, it c- it just
• 50:57
  not real until it gets real.
• 50:59
  But I, I haven't solved that yet.
• 51:00
  I haven't figured out whether or not there is something profound in the nature
• 51:05
  of that or whether it's all garbage.
• 51:09
  Now, what's interesting from the Motorola story is they had to go
• 51:13
  from 20,000 to 3,800 employees just to manage the cost structure.
• 51:21
  And so, you know, so… A- and if you think about when Elon Musk bought
• 51:27
  X or, you know, Twitter, now X, the amount of headcount that was taken,
• 51:34
  he took out a billion dollars or whatever it was, and don't quote
• 51:37
  me on that, of headcount, right?
• 51:40
  And it's like, did it ever stop running?
• 51:43
  Did we ever not-- As a consumer, did you ever notice where that
• 51:47
  billion dollars headcount went?
• 51:51
  that's sort of two sides of the same coin.
• 51:52
  So how people add value, how the relationships with people add value,
• 51:57
  we just don't know that magic.
• 51:59
  I don't think we know why those eight people got together and why those eight
• 52:03
  people were even at Shockley to begin with, but we do know what they do.
• 52:06
  And, you know.
• 52:08
  And I would actually maybe, you know, from the nature of people in relationships, the
• 52:13
  risk is always, 'Cause I think it's great, do you-- have you ever heard of a Learjet?
• 52:18
  , Yeah, from you actually, bro.
• 52:20
  Private,
• 52:20
  Yeah
• 52:21
  jet, right?
• 52:22
  A Learjet.
• 52:23
  Well, guess what Lear did before he created He created eight-track tapes.
• 52:29
  He created the alternator in a car.
• 52:32
  created, with his buddy, the first radio, car radio that was sold to Galvin and
• 52:42
  his brother at Galvin Manufacturing.
• 52:45
  So Motorola grew out of the same guy who created the Learjet Who knew?
• 52:52
  Only to say that we don't know the na- we don't know everything about
• 52:57
  people in HR, but we need the, a- and the nature of sharing ideas,
• 53:02
  working ideas, and the value of that.
• 53:05
  I'm not too worried about it.
• 53:06
  I think people will figure it out.
• 53:08
  I guess I would close with the idea of something saw recently that I
• 53:12
  just felt was so wrong, I wanted to scream it to, to somewhere.
• 53:17
  But somebody said, you know, "Technology is gonna advance beyond the ability
• 53:21
  of people to use it." And I just thought, you know, my 40 years in the
• 53:27
  business says technology has never outstripped people's ability to use it.
• 53:34
  It's fundamentally constrained by people's ability to use it
• 53:41
  and adapt it, and adapt to it.
• 53:43
  Adopt it and adapt to it.
• 53:46
  So fear not, the world is a lot better , than, you know, people say.
• 53:51
  Get excited about it
• 53:53
  Awesome.
• 53:53
  And what I'm gonna do actually is I'm gonna get, if somebody, Paul,
• 53:57
  I, the opinion there I shared with Paul, I love your opinion.
• 54:01
  Email us at admin@theinnovationshow.io or on Substack or LinkedIn.
• 54:07
  Get in touch with me.
• 54:08
  Tell me what you think about that idea of the DNA changing, what Paul's
• 54:11
  point was and my point, and I have a copy of one of Paul's books for you.
• 54:15
  Not Mass Affluence, 'cause I don't have m- multiple copies, but I have loads.
• 54:19
  You can't see.
• 54:20
  I have a top shelf up there and I have loads of Paul's books because
• 54:23
  he will be coming to Ireland soon.
• 54:25
  I'm putting that out there, Paul.
• 54:27
  Bringing him over, and we'll be doing a session together, and it
• 54:30
  will be hopefully next year in 2027.
• 54:33
  Paul, for people who wanna find you, LinkedIn the best place?
• 54:37
  LinkedIn's the best place
• 54:39
  Brilliant.
• 54:39
  Okay, man.
• 54:40
  I wanna thank finally our sponsor, Kyndryl, who runs and reimagines the
• 54:44
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• 54:48
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• 54:52
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• 54:59
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• 55:04
  Paul, anything else before we sign off?
• 55:07
  That's good.
• 55:08
  Great as always to talk to you, man
• 55:10
  Always, always a pleasure, man.
• 55:11
  Enjoy Turkey.
• 55:13
  Don't, don't go, don't go missing on us over there.
• 55:16
  We need you back.
• 55:17
  We've loads more to talk about.
• 55:19
  Paul Nunes, thank you for joining us
• 55:22
  Thanks, Aidan
• 55:23
  Nice one, bro.