Motley Fool Money - Put The Glasses On!
Episode Date: October 26, 2023(00:21) Asit Sharma and Deidre Woollard discuss: - Why this quarter has been so good for ad revenue and if that might change. - How Meta’s spending on virtual reality could pay off. - If Apple or Me...ta will triumph in the great headset race. (21:40) Tim Beyers talks with author and New York University professor Melissa Schilling about traits shared by the world’s greatest innovators. Claim your Stock Advisor discount here: www.fool.com/mfmdiscount Companies discussed: META, AAPL, NVDA, SNOW, TSLA, AMZN Host: Deidre Woollard Guests: Asit Sharma, Melissa Schilling, Tim Beyers Producer: Ricky Mulvey Engineers: Dan Boyd, Tim Sparks Learn more about your ad choices. Visit megaphone.fm/adchoices
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Ad revenue is back, and that's good news for meta.
Motley Full Money starts now.
Welcome to Motley Full Money.
I'm Dieter Wollard here with Motley Full analyst.
Asa, Arsittgen, good to see you again.
Dieter's so good to see you.
Advertising is back, sort of, I think.
This has been such an interesting week to look at earnings on yesterday's show.
Ricky and Nick, they covered Alphabet.
Strong ad revenue, strong search revenue, strong story.
for YouTube. We've got a similar story today with Meta, Gap advertising revenue up 24% year over
year. I think sometimes we get distracted by all of the other things that Alphabet and Meta do,
but these are still, these are ad businesses. That's where the money is. This is only one quarter,
though. How should we be thinking about this? I'm happy, but I'm a little, I'm cautious. How are
you? I think I'm cautious too, Deidre. I think this quarter reflects.
Businesses that were previously shell-shocked last year have slowly adjusted to the business
environment.
They're spending a little more.
So the caution is being cautiously pulled back.
Businesses have to spend on advertising after all, right, to raise revenues and bring in the profits.
So I think that's good, but we're not out of the woods yet.
As you know, the macro environment is so volatile.
Interest rates are still sky high.
It seemed to be ever climbing.
Inflation is persistent.
Loans are starting up against student loan payments.
So with this uncertain environment for discretionary spending among consumers, I wonder too.
For me, two data points make a trend.
Let's see one more quarter like this among all these players and I might feel a little
more comfortable.
Yeah, I think so too.
The GDP numbers came out today and they came out higher than expected.
But consumers are feeling the pinch.
The savings rate is going down.
So it'll be interesting to see a holiday season.
the impact on that for these companies as well. I mean, when even Snap is getting solid ad revenue,
I start to think, okay, maybe this is something real. I know, right? Even Snap's making money.
Exactly. Must have been a good quarter for advertisers. Well, so we've got the money coming in,
but this is Mark Zuckerberg's year of efficiency, and on the earnings call, he made it clear.
He wants to keep that going. He likes where things have been. And yet, this is, this.
This is the huge ad yet is, of course, reality labs.
They're still spending like crazy on this.
$3.7 billion loss this quarter.
They've said they're going to keep on spending.
It's necessary for them to build out AR and VR.
But at some point, at some point, this has to stop, right?
At some point, you can't just keep spending without any real benefit to it.
You have to stop at some point.
I mean, what, a couple hundred million dollars in revenue?
And then, as you point out, a $3.7 billion loss.
What is working in Mark Zuckerberg's favor, of course, is that tremendous margin that comes
from the advertising business and the fact that in tightening the belt in so many other spaces,
I think he's bought a lot of goodwill among shareholders, making the whole of the business
more efficient, gives him some leeway to continue with the losses, even though they're significant
in this one area. But I think at some point, you'll have to show a better return on all this
investment for shareholders to count it any further.
Yeah. And I think one of the things that the analysts are looking for that came up on the
call was, okay, you're spending all this money. Is this transferable to other areas? Is this
benefiting things? And CFO, Susan Lee, she wasn't really, she didn't quite give them
But the answer I thought they were looking for, she said most of the spends on headcount and
cost rated related to directly to Reality Lab.
So it's pretty clear that what they're doing is directly related to just the AR and VR.
And it's not really going to go over and help the family of apps, which is, of course, where
the money is made.
I think they actually can get some benefit out of that.
And, Deidre, I was surprised, too, at the answer that Susan Lee gave.
So, when you think about reality labs, you and I, and I think most members think of a company
within meta that's trying to build out the metaverse, is trying to build a virtual reality,
immersive environment through the use of the devices, their audiovisual devices, and then,
you know, some augmented reality, which is sort of blending a physical and a virtual environment.
But the things that they're investing in are wide, they're vast.
If you ever have a chance to watch some videos on what exactly goes on and all these
research dollars into reality labs, there's much investment in sort of kinetic experiences.
There's much investment in understanding what happens when the human face smiles or frowns
or raises an eyebrow.
And that has a direct application to the avatar business that Meta is in.
working on avatars, once they get those to a super realistic degree of competency, so you
and I, because we're recording this audio in Zoom.
I'm looking at your pleasant face just now, and I can see you just reacted with a smile.
Now, imagine our avatars that can interpret simultaneously these micro-expressions and really give
this realistic environment to both of us that we are in, like, you.
the synchronous communication environment. You actually don't need a VR experience for that.
You don't even need an AR experience for that. That can conceivably occur over two laptops,
if you can make the avatars very realistic. And some of this investment, you can see how they
just port it over to other places. It doesn't have to exist solely within virtual reality.
I wish he had talked a little bit more about all the money that they've poured into bridging
this divide between physical environments and virtual environments. So, we're just a little bit more.
what if the Metaverse fails. I think there's some yield there. And I've said this before. I'm here on
Motley Full Money. I think business collaboration could be big for meta. Now, whether any of this
gets commercialized or not, truly as anyone's guess, I say if you're pumping in tens of billions
of dollars over a multi-year period, there's got to be something that can translate and give you
some decent revenue out of this.
Yeah, I certainly hope so. And yeah, I want to talk about the business aspect a little bit later. But first, I want to talk about the gear. Meta has not had a great track record with devices. You had Facebook phone. That didn't work. You had the Meta portal that hasn't really, that did not take off. But when we were at the Motley Fool One event earlier this week, our colleague, Kirsten Gera, she said she was looking at the Apple Vision Pro as one of the things that she thinks is going to be
kind of transformative. I think Zuckerberg would prefer that she, of course, say, Meta Quest or the
Rayban smart glasses. But there's this pressure right now to deliver the thing that goes on our face.
And do you think that Apple or Meta is going to be the winner in this space? Obviously,
meta's device is far, far cheaper, and they've had more swings here to make this work. But
it's Apple. How are you thinking about these two?
Man, Deidre, it's Thursday.
What you're throwing such a hard question?
The weekend is like right in my sight.
Okay.
Let's see.
Apple, you know, their device is like seven times more expensive than the meta three.
But it's a beautiful device from what we've seen.
And we know that it's going to deliver an unparalleled experience in some respects.
Until we can actually try it out, I can't say that it's going to be a game changer or not.
But certainly ditching the controller, which used with the meta quest, to something where you can just use hand gestures to control a pointer object like a mouse.
I think that's so Apple delivering this bespoke experience.
I'm sure the form factor is going to be elegant.
It already looks great.
And the experiences are going to be immersive and they're going to be fun.
We already know all this about Apple.
The thing here that strikes me is a little different than other great products they've rolled out
is just the delta of the next best product and this new product.
I mean, it's an even bigger gulf than when the iPhone first came out versus the phones you
could buy in the market.
So I do question the first generation, how much uptake it will have at $3,500 per pair.
But what we will see is sort of a trickle-down effect.
So, Meta will try to pack more features into its next versions.
And Apple will also work on second and third generation devices, where, as they've done
the past, they'll give you some lower price points with fewer features.
At some point, the two of those converge.
So which ultimately wins out.
If I had to bet, I'd have to bet Apple just because of their track record with devices.
And what you point out about Meta stumbles, but I still feel that we shouldn't under us
estimate Meta's ability to make their device more widespread in the marketplace.
Let's go Apple.
Well, and I think it's interesting too that Apple, they thought potentially about doing smart
glasses.
They decided that that wasn't the first wing for them.
We've seen Google Glass.
Meta keeps trying to make this happen.
A snap that we talked about earlier didn't do well with it.
The smart glasses thing, it's still hard for me to figure out that one.
I think I'm more interested in the fully.
immersive headsets as a real changer. But we'll see.
Yeah, the Raybans are sleek.
They are sleek.
Meta partnered with Raybans, parent, and you have actually sort of a fun form factor
for a lot of people. And I do think since the last iterations of smart glasses that hit the
marketplace, there seems to be more acceptance and fewer privacy concerns.
So I wouldn't be surprised to see this sell pretty well.
This is, again, not like a VR or even mixed reality type device.
It's simply smart glasses, but you can take video.
You can communicate with an AI agent through the day if you want.
They look pretty sleek.
Not for me, but I can definitely see a generation of consumers maybe buying up.
And I believe the price point is just like $2.99 entry point, Diedra, somewhere around there.
Yeah, they're not too expensive.
expensive. Yeah. Well, you just mentioned AI agent, and that brings us into talking a little bit about
business, which you've teased earlier, because one of the things that Meta's doing, you've talked
about making the avatars, they're now creating AI for businesses and these agents, these experiences.
So the way they see it is basically every business is going to have an AI for customer interactions.
And we're already talking to bots probably more than we'd like to. But this is supposed to be better.
I have this question. This is one of the things I was really thinking about with this.
So if I'm spending my time with meta to develop my AI agent, maybe I'm putting things into a large language model, I'm really working on this thing.
This is still, I mean, you've got multiple apps. You've got like WhatsApp and Instagram and Facebook, but it's still a walled garden.
Are companies going to have to invest in creating multiple AI avatar experiences across multiple
like customer input points, multiple walled gardens. It all seems like a lot of work for companies
and a lot of money too. A lot of work, a lot of money, and uncertain return. I think companies are
going to pick one model and work with that on one cloud provider or maybe one portal. So Snowflake
offers a portable for training. You can actually work directly with Nvidia, depending on your
industry. But I think that's more of what companies will do, whether it's meta or another company.
They'll choose a training model, a large language model. They'll figure out, okay, with this provider,
my data set's secure, and then they'll experiment. And no one is going to create multiple bots at this
point in time on multiple platforms unless that ROI is there. If it doesn't improve your customer
service, if it actually degrades it because you've got different bots giving different answers,
you're not going to keep investing. So I like that meta is pushing this. And I like that their
large language model is open source. They're sort of kneecapping the idea that other large language
models will be proprietary and businesses will spend only on those. They're sort of using a playbook
that they've used many times before.
That's smart business on their part, but it does further the AI cause.
It makes it easier for people to innovate.
So there's some mercenary goodwill that Meta is creating out there where their particular
large language models is concerned.
But I'm going to push back on that a little bit, just because of the cloud thing.
So because companies, when they were first moving to the cloud, they generally picked one horse.
Now, I've been listening to our friends, Tim White and Tim Byers, talk a little bit about this.
Now we're seeing more multi-cloud where companies are sort of expanding out.
So I'm wondering if over time you start with one AI, but then maybe you have different needs, different purposes, and maybe it becomes multi-AI the same way it becomes multi-cloud as it evolves over time.
I've been talking kind of years in the future.
No, totally.
And actually, Tim Byers and I were having a slight conversation last night.
about multi-clouds and cloud providers cooperating with each other to sell businesses.
So I'm with you there.
What I was talking about is simply the context of, say, a customer-facing bot on a cloud
provider where you're giving your data set to the cloud provider and working with their models.
I don't think in that particular instance, like where it's customer service, many businesses
will want to do that on multiple platforms.
But, gee, within businesses, you could have different divisions who have no idea of what
the other side is doing.
One will be on an Nvidia platform in the future.
One will be using Snowflake to maybe also go to Nvidia.
Some will be on Amazon Web Services and their particular cloud-based AI training ground.
So I do see that for sure.
As businesses get used to working with AI models, they're pretty much.
probably isn't going to be a single winner, one-size solution. But for specific use cases,
that I don't see like you're going to use six different models for one purpose.
Yeah. Yeah, that makes sense. Well, last quarter was just when Threads was starting to pick
up, and there was a lot of talk about it in the earnings call and a lot of excitement. This quarter,
I think they mentioned it maybe twice, maybe three times. So you've got about 100 million
monthly actives who knows how active they really are. But Zuckerberg said it'll take a few years,
but he thinks over time it could be a one billion person public conversation app that is more positive.
Given that they're not really putting that much effort to it, do you think that that's actually
correct? It didn't seem like there was that much enthusiasm for threads, at least this quarter.
I think it's personal with his rival Elon Musk.
I think he wanted to say something about threads just for the community to understand that they're still investing in it.
But more telling was Zuckerberg spent more time talking about consumer-to-business conversations
and how that's really getting monetized.
Specifically, the example he used WhatsApp in India, where he said some 60% of users.
users have used a click-to-message interaction with a business, meaning you see a business
ad and you click to message them because you need something.
I was just in India and I certainly experienced that myself.
That really is going to be a more moneymaker for META is working on where businesses and
consumers are interacting.
I really don't see at this point the potential for threads to be some kind of great monetization
Engine, still the user interface needs work from my experience, like, browsing around,
and I see as we're talking, you seem to be agreeing with me, DeJ. So, yeah, I think that was just
sort of like, and we're still there. Don't think we're not fully invested here. But look,
look where the money is going. It's going into like pumping up that WhatsApp revenue,
ad revenue, which is blossoming, frankly.
Yeah, yeah, the ad revenue and the growth of those business services that we talked about. One thing that
wasn't in the earnings and that they can't really talk about is some of the regulatory concerns
that Metta is facing. This week, you had multiple lawsuits come out from a variety of states
and some joint lawsuits saying company violated consumer protection laws related to how it
markets to children and teens. Neither one of us is a lawyer. We don't know what happens next,
but the thing I'm thinking about is the court of public opinion. Does this make a difference
in how people start to consider using META's products and exposing their children to it
when they turn 13 or even earlier?
I mean, this is a perceptive question, Dider. It's hard to remember now, but before the pandemic,
before all the investment in reality labs, before all this economic upheaval we had,
Meta had the solid advertising business, and it competed with its peers, but
It seemed like whenever retail investors and institutional investors were plugging valuation stuff into their models,
they always valued meta, then Facebook, a little less versus peers with similar models.
It never quite traded at the premium that it should have.
And why was that?
It's because I believe investors were really concerned with their inept handling of privacy,
almost since day one.
And that always seemed to hit their results.
We saw lawsuits being filed in the past.
We saw Meta, then Facebook as an organization, not really being the most stringent in terms
of protecting users' privacy.
And this seems to be sort of an ongoing issue with Meta.
And it might be one reason, among some others, I still don't own shares myself.
And part of that, too, is maybe an unease with the company.
if you really don't value your customers' privacy, is that a company that I just personally want
to invest in?
I've never been able to get over that hump and here it flares up again in some of the lawsuits
that you've mentioned.
So we'll see.
I think that has the potential to be a drag on the valuation in the future.
Right now, all the attention has been on first the plunging of capital into reality
labs and then this memory we had this year that, oh, wow, there's a great.
digital advertising business here and Zuck is cutting cost. So the stock has benefited. But it's sort of like
now what? I mean, what happens from here? And this would play into anyone's valuation thesis,
I think, because it's happened in the past and it's hit that valuation in the past.
Yeah, yeah. So much to consider with this one. Thanks for breaking it down with me,
Osset. So much fun, Deidre. Thanks a lot for having me.
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Earlier this week at a special event for Motley Fool 1 members, Motley Fool analyst Tim Beyers,
interviewed Professor Melissa Schilling, author of the book Quirky, the remarkable story of the
traits of foibles and genius of breakthrough innovators who changed the world. They talked about
the fascinating things she discovered while researching some of the world's greatest thinkers.
Melissa, thank you for being here. I think the mic is hot. Thank you for having me. It is hot.
Yes, right. Let's talk about breakthrough innovation and let's talk about maybe the
most talked about breakthrough innovation right now, which is AI.
So let's start there.
Big picture first.
Which companies to your mind, and based on the research you're doing, are most threatened
by AI, and which one stand to profit the most, do you think, if you could name a couple?
Oh, so you want specific company names?
Well, or types of companies, and if you've got some specific names, I know there are a lot of people
here that would be very interested in that.
Yeah, okay. All right.
So, I mean, obviously, Nvidia, you can't talk about AI without talking about
Nvidia. And I think that that's a really interesting story because I think they sort of accidentally
end up poised in a perfect place to capitalize on AI in that they were developing extraordinary
microprocessors and data processing capability for the video game industry and ended up basically
creating products that are perfectly positioned to now be a dominant player in AI,
and they're doing a lot of the hard, heavy lifting of AI, I think.
Also, any company that's working in cloud is going to be a big benefactor of AI,
because what AI is going to allow us to do is utilize a lot more data, right?
And a lot of companies that will adapt to AI won't have to do it in-house.
They're going to do it via the cloud and via cloud service providers
who are helping them tap the capabilities of AI without having to bring that
capability in-house, which is something else I want to talk about AI, if possible.
Yeah, okay.
So one of the things I think is coolest about AI.
First of what, let me say something that's a trap.
It's a trap to look across industries and think this industry will be decimated, that
industry will be decimated.
I think on average, that's not what we'll see.
What we'll see is that AI is going to change what creates a winner in an industry versus
a loser in an industry.
And by that, I mean, I like to use an analogy.
I'm a big fan of analogies, as I think it makes it really concrete.
But if we think about how spreadsheets affected the accounting profession,
spreadsheets, like spreadsheet programs, like it was Lotus 1, 2, 3 in the beginning,
and now Excel.
They didn't put accountants out of business, right?
Maybe a few accountants who decided, oh, I don't want to work with spreadsheets,
that's not for me.
Those accountants probably ended up being...
I need my ledgers, those accounts.
Those accountants, who want to use a pencil and a big adding machine,
those accountants are probably gone.
But for most accountants, what it did was it enabled them to do more, better, faster, more precise.
So more regular updating, more precise measures, more segment accounting.
And so that's what you want to look for.
Who are the players in an industry who are going to pick up this tool and use it to do bigger,
better, more exciting things?
Who do you think then, so taking that as gospel here for a minute, who do you think then
is the group that's threatened by AI?
the ones that don't want to do more, bigger, better.
Yeah.
You could, in my business, being a professor, analyzing companies, you can spot them structurally sometimes.
They tend to be companies that are older, that have really strong hierarchy and hierarchical norms.
They're a little bit rigid.
Counterintuitively, also, very decentralized companies will have a harder time responding to the shifts that are required by AI.
We tend to think of decentralized companies tend to be promoted as like flexible and facts.
and they're really good at incremental innovation,
but decentralized companies where you don't have a lot of authority
at the center of the company have a harder time making big systemic changes fast.
For a big systemic change fast, it's easier if you can have more centralized control.
So on the one hand, you want some centralized control to be able to make that change quickly,
but you also want to have a company that embraces change,
where there's no sacred cows, there's not a lot of power distance,
distance, everyone has a voice, companies who are being proactive about saying, okay, how do we
disrupt ourselves instead of how do we defend our business?
That's the positioning you want to look for.
Also, frankly, companies that have some slack.
So companies that have had some free cash flow that is leaving them sitting on a bit of capital
where they feel comfortable that they can make bigger, bolder moves.
Because in a company operating on razor-thin margins in an extremely competitive industry, they're
looking a month out, a quarter out, it's very difficult for them to do big changes and to
invest in those, they're going to perceive it as too risky.
So that sounds like, and then we'll pivot to your book here, but that sounds like you
just said industries where the profit margins are thin, you're looking out a quarter, maybe
not five years.
So that sounds like retail, that sounds like consumer products, that sounds like in some
industries that maybe are a little bit more industrial.
You think that's fair?
Well, again, I don't think it will serve us to label a whole industry as going to be a loser
or a winner in AI.
But the structure of the company itself.
The structure.
I think retail is a great example of an industry that will be completely transformed by AI because
it's a data-heavy industry where you can really utilize that data.
I think the ones that adopt AI early and aggressively are going to vastly outperform the ones
that don't.
That makes a lot of sense.
Well, this is interesting, so let's pivot then to break through an
Because you wrote about this in your book, which is fantastic.
I really think everybody should read this, particularly if you are investing in any way.
And in Breakthrough Innovation, this book identifies in a very thoughtful and narrative-driven
way some of the greatest breakthrough innovators in history.
And I'm sure you are very familiar with the name.
So I'll name a couple.
You mentioned Thomas Edison.
You mentioned Albert Einstein.
You mentioned Elon Musk, Steve Jobs.
Marie Curie.
always have to include some women in there. Yes, Marie Curie, which is a fascinating story as well.
How should we be thinking about as investors some of the key traits that you identify here?
I'll focus in on one, which is separateness. So I'd love for you to maybe define that a little bit.
These breakthrough innovators have a view of separateness, and you define it in a very interesting way.
Can you talk a little bit about that?
Yeah, sure. And let me first preface this by saying, before I started this,
project, I was working on a bunch of stuff related to networks, social networks, collaborative
networks among firms.
And so I really had this ex ante expectation that innovators would turn out to be hyper-connected.
They would have these really big, robust, replete, you know, social networks that would enable
them to get lots of ideas.
And so then it was very surprised to actually find that most of the serial breakthrough innovators
in my study were, you couldn't help but call them anything else.
They were separate.
They were socially detached.
Sometimes it was a personality trait, like extreme introversion or antherophobia.
Sometimes it was, in Edison's case, he was deaf.
Sometimes it was periods of depression or sickness, like in the case of Curie or Tesla.
Sometimes it almost looks like Asperger's.
That's where you start, you know, Elon Musk said he has Asperger's.
Einstein clearly had some sort of a little bit of spectrum disorder.
But that separateness that it gave them, that sense that they were different
and that they didn't quite fit in with the social world,
ended up being incredibly liberating because it meant, first, that they weren't socialized to
buy into all the norms that everybody else had bought into.
And norms can be constraining, right?
Paradigms can be constraining.
People who are extremely well indoctrinated or trained in a particular area have a harder time
coming up with a radical innovation than people who haven't been indoctrinated in that way.
So part of it is what you've been exposed to and what you've learned.
If you've learned really well what the field thinks works and doesn't work, that can trap you.
And so in some sense, these people who weren't part of the norm didn't have that trap.
But there's a second side to it.
And that is that a lot of these people were also very rebellious.
And that was part of the separateness.
They had this view that I'm not part of the social world.
Its rules don't apply to me.
And so they were sometimes difficult people or people who didn't care that much what you thought of them.
And so we certainly see that with Marie Curie.
We see it with Albert Einstein.
It was Steve Jobs and the reality distortion field.
Yep, and you see it with Elon Musk.
He does not care what you think about him.
Now, the way that unfolds is multifaceted, shall we say.
So there's some ways in which he comes across as kind of a jerk, right?
Like when he manages, you know, he's not a warm, fuzzy manager at all.
And he has said things on Twitter that he shouldn't have said, in my opinion.
I think that's fair.
Yeah.
And it's because he's a low self-monitor and he doesn't care that much what you
think of him. But that ends up serving him because, you know, most breakthrough ideas, the first
time you see a breakthrough idea, you're generally not going to react favorably to it at all,
because it's going to feel weird. It's going to look jarring. It's called, it's a breakthrough
because it breaks with something. It breaks with your expectations, or it breaks with the way
we do things or what we believe. And so breakthrough innovations tend to be kind of ugly
and unsettling. And people who want the approval of others are going to have a real hard time,
both introducing those and sticking with them in the face of criticism. But if you are someone like
Musk, he believes in his ideas, he doesn't care whether you do. He has confidence that he will
make it work whether you think you can or anyone else can or not. So he sticks with these
ideas even when other people say, that's dumb or that's impossible or what are you thinking. And
it's a kind of, it's almost a disagreeableness, but it's a very beneficial disagreeableness.
I mean, let's transpose this on ourselves and the Motley Fool, but all of us individually,
as investors. So how can we foster a little breakthrough innovation in ourselves, as investors,
as people, as people in the world? How do we do this for ourselves?
So there's probably three things, I think, are most effective that you can do right away.
One is when you have an idea that you think is a breakthrough innovation idea, don't show it to people early.
Don't seek early feedback because it's only two kinds of feedback you'll get.
You'll either get negative feedback or you'll get people blowing smoke up your backside because they want to make you happy.
You probably won't get the useful feedback you were hoping for.
You have to have enough conviction that if you believe it's a really cool idea, pursue it and elaborate it on your own.
wait for a while before you expose it to other people. That's one thing I would do.
Okay. Actually, along with that, I'm actually going to get sneak four in here.
All right, good. Forget about credentializing norms. One of the thing you learn over and over again
when you study breakthrough innovators is that they're very often outsiders. They may not have
had the PhD that you were expecting or the they may not have worked for the company that you
were expecting. Those credentializing norms are also homogenizing norms, right? So be, be
confident in your ability to enter an industry that you aren't trained in, right? If you want to do
something in an industry and you don't have the right degree for that area, don't let that stop you,
and don't make that stop other people. The third one, find your own idealistic mission.
Find those things that you feel like would be worth doing even if nobody pays you for it or
pats you on the head for it, right? Because once you find those, that's going to make you work harder,
think bigger, move faster, that's really, really powerful.
Oh, and then I had a fourth one, and I just forgot what it was.
No, that's okay.
I mean, I think what's interesting in what you just said there is be maybe a bit of stubborn
willingness to pursue the things that are very interesting to you.
If you are, when you're looking at companies right now, or maybe in some of your own work
with startups, is there any kind of identifying characteristic of, say, like a stubborn
willingness to do something that really stands out to you when you do your consulting work,
maybe a company you've run across or a founder you've run across?
You know, when you have a manager, for example, that understands what the big picture is
and is willing to let go of current business to get to that big picture, that's actually
really powerful.
And that probably sounds really big.
I'll give you a great, I'll give you a specific example from a street just down
the company just down the street here, Bloomberg Corporation.
I'll tell you something they were doing wrong and then something they did to turn it around.
Okay.
If that's okay.
Am I allowed to talk about Bloomberg?
Yes, you can.
Okay.
We got five minutes.
We can do it.
It'll be really fast.
So Bloomberg was founded basically because Michael Bloomberg figured out that he could lay these
computer lines between investment companies and get more information faster to people, right?
Instead of having bond runners, you could get the bond prices just beam to you basically
over a computer line.
And so his whole original success and competitive advantage was quantity of data with speed,
those two things.
And what they would produce on their monitors were beautiful, you know, visualizations
and things that had been, you know, data that had been curated and calculated that
humans would perceive with their eyes, right?
Investment bankers would look at that and process that data with their eyes.
That was the whole business model.
And what that meant was that when mobile was just a baby, when smartphones were just
coming up, it was very unattractive to Bloomberg.
A mobile solution was not attractive because it was going to be not as fast,
not as much data on a little bitty screen, right?
Which was just so it wasn't very sexy to the company.
There were not a lot of people who wanted to work in mobile because the metric of performance at Bloomberg had been speed,
speed and data cool algorithms, right?
And that just didn't compute with mobile.
And we did this exercise where we took apart the performance dimensions of their industry and thought about
where the payoff was, where the utility payoff was for each of these dimensions. And they came out
of that realizing, oh my God, we have to go mobile, right? Because mobile is where the room for
more utility was. They'd actually basically maxed out speed from a human perspective, right? I'm like,
I asked them at one point, how fast are humans? You know, if your data's coming even faster,
can investment bankers process that even faster? And I got a lot of blank stairs to that question.
But we had this meeting and a big argument broke out.
They ended up moving 60 people over to the mobile division and invented an award-winning mobile
application that was crucial to the success of the company.
So that willingness to tear down parts of their own business model to move forward is super, super
important.
As always, people on the program may have interests in the stocks they talk about.
And the Motley Fool may have formal recommendations for or against.
so don't buy ourselves stocks based solely on what you hear.
I'm Deidre Wollard.
Thanks for listening.
We'll see you tomorrow.
