Motley Fool Money - Burn Through Your Queue
Episode Date: November 9, 2023Actors are headed back to work as streamers seek to monetize viewers. (00:20) Bill Barker and Deidre Woollard discuss: - The long-term impact of Hollywood’s strikes. - Linear television’s fading a...d value. - The value of sports entertainment. (17:09) : Tim White and Tim Beyers sit down with Iinformatica Chief Product Officer, Jitesh Ghai to discuss the future of data management.Claim your Stock Advisor discount here: www.fool.com/mfmdiscount Companies discussed: DIS, WBD, NYT, NFLX, SNAP, PINS, INFAHost: Deidre Woollard Guests: Jitesh Ghai, Tim White, Tim Beyers, Bill Barker Producers: Ricky Mulvey, Mary Long Engineers: Dan Boyd, Rick Engdahl Learn more about your ad choices. Visit megaphone.fm/adchoices
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actors are getting back to work, but are the best days of television behind us?
Motley Fool Money starts now.
Welcome to Motley Fool Money.
I'm Deidra Willard here with Motley Fool analyst Bill Barker.
Bill, how are you today?
I'm well. Thanks.
Well, you know who else is well?
I think are the Hollywood actors, our season of strikes, and it has been a season.
It's finally winding down sag after they reached a deal with the studios last night,
which means content engine, it's going to start ramping back.
up again. I saw a report last night and deadline said the strike costs Southern California around
$6.5 billion and 45,000 entertainment jobs. What do you think about the long-term ramifications
of the strikes? One of the things I'm wondering is if companies have learned maybe to be
sort of cleaner about their content and will probably cut costs more. What do you think?
Well, I think you're going to have to wait a little bit until the actual terms are released.
Until they are ratified by the union membership, they're not going to be given to us.
So a more intelligent response to that will have to wait.
But, I mean, that's not the only response that you can have on this show.
Oh, so. The AI was a part of all of this, and a big part, I think, probably the corporate level was thinking gleefully
about how many people to cut out of the equation with AI. And I think that the terms of the contract
came up and sort of at the right time in order to address this before.
AI gets away from the acting community.
So I think they've inserted their negotiations at the right time when it's evident what will be coming, but it's not too late to change the equation before it works dramatically against the actors.
Yeah, definitely a wait-and-see kind of thing, because it's not going to stop AI innovation, but it may – it feels like a stop.
up to me, but we'll see. We don't know yet.
I mean, I think in terms of both of these strikes, both the writer's strike and the actor's
strike, it's given a little bit of a pause and some plans have had more time to marinate
on exactly how much content and how much to spend on it is determined. There's plenty
of content out there. During the strike, I don't know if you noticed it. There's too much
stuff to catch up on in the various cues and recommendations of friends, unless you're an
addict to late-night TV. And that's been back for a couple of months now with the writers
back. But there's enough to watch. They could go on strike for a couple years, I think.
and there would be more than enough to watch during that time, with the exception of the new stuff that you need some feeding of new stuff.
But in comparison to what's already out there, it's a different equation for the viewer than it used to be.
Yeah, it's very different than the last major strike.
I want to move on from that into talking a little bit about earnings, because we had earnings from Disney and Warner Brothers Discovery over the past couple of days,
which kind of give us insight into that connected TV streaming universe.
And one of the things I'm thinking about is that we've got this tale of two ad markets,
because on the one hand, you had strong connected TV and online results, Netflix, alphabet, meta,
even Snap and Pinterest, which was kind of surprising to me.
But on the other hand, you had Warner Brothers Discovery and Disney both saying, you know,
traditional television advertising was a weakness.
So, I'm wondering if the page has been turned here.
And as an investor, is it worth paying attention to TV advertising anymore?
I don't think you'd want to be a long-term investor in TV advertising for anything that isn't streaming.
A single source, like what's on the networks and things like that.
So the advertising model is getting better and being tried.
more ways on the Netflix's and other streaming services.
So it's picking up there, obviously, the amount of time that people spend watching streaming
services grows, and it comes at the expense of the network TV and the cable network.
So, you might get a little bump in an election year with certain channels getting, depending
on how exciting the race is.
I can certainly see a few channels picking up quite a bit, but the rest, I think it's going
to be to the degree that they have sports.
Sports is doing very, very well, and the rest of the entertainment, creativity and dollars
seem to have migrated to streaming services as have the eyeballs.
Yeah, indeed.
Another thing that I think is interesting about the streaming services, with Netflix, we heard it,
with Disney and with Warner Brothers, is that these aren't primarily U.S. businesses right now in
terms of where the subscribers are coming from. It's increasingly becoming a global, global content
businesses, and really starting to see a lot of growth in India where the population is booming
and the middle class is growing. As we think about valuing these businesses, I'm wondering
how to consider the U.S. parts versus the global parts, because traditionally I think of these
businesses as, like, very dependent on what I might be watching. But that is increasingly
not the case.
No, the U.S. is a little bit more than 4% of the global population, obviously much wealthier
than the midpoint for global population. But the population is growing in India.
India is, you know, now the number one country in terms of population. And, of course, they've
They've had vast international business.
You hear about it more when China's feathers get ruffled about some piece of content and what
happens because of that and the ways in which Disney may or may not have changed some of
the things that they've developed over the few years, last few years, because of how important
the Chinese market is to their theatrical releases.
So it's a huge part of the business, the international part.
Other thing that on the Warner Brothers Discovery call that David Laslap, the CEO said,
is that it's international and it's gaming.
So I think this is interesting because you've got Netflix talking about gaming too.
Disney has gaming too.
But then on the other side, you have Nintendo.
They're getting into producing movies, like they're having a live-action Zelda movie.
So it seems like you've got this sort of IP kind of blur happening, probably a little bit because of the whole Barbie thing.
But would you rather see the gaming companies get into movies or the streaming companies get into gaming?
Well, if it's directed at me, I'd rather see the gaming companies get into movies and series, I think, of The Last of Us on HBO Max or just Max as some people now,
seem to call it being a very successful game.
I had no idea it was a game before I was watching it as a series, and it's a limited time.
Whereas the model for taking the IP of Warner Brothers, say the DC superhero characters
and putting them in a live game that you can tune into all the time, and that the business
model is inherently, how much can we get?
kids, to a degree, but older people as well, addicted to playing a game for very, very, very
long periods of time.
And the answer to that is, you can do it.
And that is a very successful stream of money, as most addictive things are.
They can be turned into good cash, whether it's the coffee that I'm about to have another
sip of, or gaming or, you know, sugar.
and various things that people get addicted to.
So in terms of getting more addictive games out there, I don't think that's a net gain for society.
It's a net gain for Warner Brothers to the degree that they can pull it off.
But I think that they also have participated in a good story in game form being brought to a new audience in the Max platform.
and that's a value.
Yeah, and I think there's a difference between the kind of immersive blockbuster games
that come out and people spend, you know, days, weeks, sort of exploring the universe,
like when Take Do Interactive comes out with a big game or something like that,
versus the more sort of like casual, maybe you play it on your phone off and on kind of gaming.
So I think that some of that is about deciding which kind of gaming companies,
that these entertainment companies want to be.
I think Warner Brothers is in the process of developing a few games that are more in the always-on, join, play for hours type of thing.
And that is a potential source of good revenue.
I'm not blaming them for pursuing that, but the question was what I want.
And that's what I want.
More stories that I have no idea about that are on platforms, like the gaming platforms, being
translated into something that I use, which is my remote control.
Exactly.
Well, staying on Warner Brothers Discovery for a moment.
I think David Zaslov is becoming one of my favorite earnings call CEOs, because he's very direct.
He's got that New York accent, that New York energy, said, it's all about cash flow.
Who has it and who does it?
And I think he kind of like wrapped the table at that moment.
So, true or false?
And if so, is that true for entertainment or for all businesses?
There's a stock phrase in law.
If the facts are on your side, you argue the facts.
If the law is on your side, you argue the law.
And if neither are on your side, you argue like hell.
But this is just like, is cash.
cash flow on your side, or is growth on your side? Growth is not on their side. So they're not pointing,
Zazlov is not pointing to, look, the growth is what I want to talk about today, because there's
nothing to talk about. It's, look, let's look at the cash flow. It's maybe not growing. In fact,
it's being paired down quite a bit, I think, based on the most recent quarterly call. But there's
real cash flow there. The multiple that the market is paying on this cash flow,
cash flow is not very high. So that's what you want to argue. If you're directing shareholders
or potential shareholders to something they might like, it's look at the cash flow that we've got
and how little you have to pay to be invested in it. And the fact that growth will have to come
at some point in the future, undetermined at the moment, that's not something to highlight.
Yeah, yeah, absolutely. And this is a company that's also dealing with paying off a lot of
debt and still integrating all of its various pieces together. So it's a little different than
some of the other companies out there. It's still new in some ways.
Well, I think to go back to the question, is this true for all businesses' cash flow?
And I've sort of translated it into a cash flow versus growth. They're both always something
to pay attention to for investors. Neither one of them is independently a reason to buy or
not buy stock.
Yeah.
I want to talk about the value of sports. I don't know how much of a sports fan you are.
There's certainly sports I watch and sports I don't. On Disney's call, Bob Iger, he talked
a lot about the value of ESPN as a standalone product. There's been a lot of discussion about,
would it be sold? Is the NFL going to take a stake? There's all this back and forth on it.
And I was thinking about that and sort of comparing that with the New York Times and the
Athletic and their earnings, because the athletic is having great growth, but still operating
at a loss.
Do you think robust sports content kind of pays for itself?
And would ESPN be spun off?
Would it have value?
Would it be able to pay for itself?
It would have great value.
I think that it's the number one provider of sports.
on streaming and on the cable platforms.
And Disney is positioning it for evaluation as an independent business by breaking out the numbers
of ESPN itself versus the other parts of their streaming and their cable businesses.
So I think that they have benefited from it.
and it might be something that they can spin off in a way that is good for shareholders.
It's married somewhat to the rest of the Disney business, but not all that smoothly, I think,
in terms of what the effect on the parks or on the effect of their other platforms, Disney Plus,
and Hulu, and, you know, why is ESPN need to be a package with those two, if that's not
your cup of tea. So I think that it's going to, my guess would be at some point, it's going to be
separate from Disney, and it's going to go for a great price. I mean, a great price for Disney.
Yeah. Yeah. The package annoys me a little bit, because I recently had to get ESPN Plus,
and I got Disney Plus and Hulu, which I did not have before. And I didn't necessarily want them.
And that's something that Bob Barker talked about on the call, is that, you know, people really,
that there's a growing audience for people who just want ESPN?
Yeah. There are millions upon millions of people that just want to watch sports.
Mostly guys, is my guess. I haven't done a deep dive on that. But not entirely. Not entirely.
Not entirely. Not saying that.
But, you know, I think probably more guys willing to just sit there and watch sports all day and all night.
And at some point, we'll find out how many of those there are and what the price tag for it goes for.
Because I do think that the number of people that pay for ESPN on their cable package
and have no idea how much they are paying for the ESPN portion of the package
and would not otherwise spend that much money to have ESPN as part of their basic cable or premium cable packages is very real.
but Disney would like to hold on to or Disney's future, you know, whoever ends up owning it if somebody
also owns it, would like to keep 100% of that rather than split it with the cable companies.
Absolutely.
Thanks for breaking it down with me today, Bill.
Thank you.
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Tim White and Tim Byers recently met with Informatica chief product officer Jitesh Guy.
They had an in-depth conversation about the history of data management and how AI is changing the game.
Those of you who've been longtime members may remember Informatica and its products,
for ETL, the old extract, transform, and load technology for data integration. It's a new company
and it's a different era and reported some pretty good earnings this week. Lots of efficiencies here
beating some guidance. Chetesh, where are we now with Informatica? What's the latest on the
company and the just reported quarter? Perfect. Well, Tim and Tim, really great to be here with the both
of you and connecting with all the fools worldwide, me included, big fan. To your question,
Informatica this year is 30 years in the making. We were founded 30 years ago, so you're
exactly right. And we've been exclusively focused on data management, enabling digital transformation,
data, and analytics. You can imagine in this very vibrant
and exciting space. There's been many generations of technology. There's been, you know,
what you described as ETL to build data warehouse appliances and data marts for analytics
and reporting. Then there was this whole wave around Hadoop, which was going to change everything
and big data. And, you know, recognizing and learning from all of that and driving simplicity,
the next wave that really came was cloud.
Informatica has been a leader through every one of these technology disruptions.
In fact, Informatica has led in innovation from a data management standpoint in the ETL world,
as well as in the Hadoop world, and now as the cloud data management leader.
Through that, you can imagine we were a perpetual license business model.
We are now a cloud subscription business model.
And you're right, we're powering our customers' digital transformations, and it shows.
We had great earnings.
We beat on all metrics, top line and bottom line.
Our cloud grew 37% against the guidance of 35% year over year to 550 million in Cloud ARR.
and our subscription business grew 17% year over year to 1.08 billion.
So, you know, we're very excited about what we're doing,
and our customers are equally very excited about how we're powering their analytics, data,
and digital journeys.
So, Jatash, one of the things that's happened over the last 10 years,
as you said, transitioning from big data,
is this idea that we have to massage data and get it into a format
that's really easy for folks to consume.
And now it's getting it ready for AI to consume
and getting it in a format that is super easy for AI to consume.
And I think that's a place where Informatica clearly could play a big role.
On the other hand, you have companies like Amazon that are saying,
just throw your data into an S3 bucket and it'll magically get consumed.
You won't have to transform it at all.
We can just work with it directly raw with Redshift and other tools.
What do you think is the truth there?
Do we have to do a lot of massaging or are we going to be able to work with it raw with AI?
Well, so first and foremost, we are a core part of our strategy is to be independent and neutral.
What does independent and neutral mean is we work with all data wherever it sits.
It can sit in AWS. It can sit in Azure. It can be in Google Cloud, Oracle Cloud. It can be on-premises.
It can be in your tenant within a specific hyperscaler. It can be in Snowflake, Databricks, wherever.
We innovate and partner deeply.
We have deep technology partnerships with all of these hyperscalers.
We equally partner and bring joint technologies to market together for our shared customers.
So from that standpoint, why do the AWS is the hyperscalers of the world partner deeply with us?
Because they recognize that while they have warehouses and data,
data lakes and lakehouses, you need trusted data in those warehouses, data lakes, lakehouses
for trusted outcomes, analytics outcomes, reporting outcomes, as well as AI outcomes.
That's where Informatica comes into play. That's what data management is really all about.
Data management, the migraine level problem that data management is solving for our
global 2000 customer base is really helping them be more data.
What does that mean?
Enabling users of all skill sets, technical and not technical,
easily discover and understand wherever data is.
It could be in an S3 bucket, it could be in Redshift,
it could be in Microsoft Fabric or Snowflake or wherever.
Easily help them discover where it could be in an ERP,
in SAP, it could be in Workday or other SAS and PAS services.
Not just discover it, but easily connect process that data.
process that data for whatever purpose, reporting, analytics, AI, regulatory compliance,
ensure it's of the right quality so that it can be trusted for a specific use case.
And oftentimes there's an immense amount of fragmentation within an enterprise of where data is.
Most enterprises have multiple clouds, multiple SaaS, multiple PAS services, et cetera.
And oftentimes they want to bring together a single view of something this.
critical, a single view of a customer. Well, a customer looks different in Salesforce versus
Jira versus service cloud, and we're able to leverage our AI and build a one complete
single view of Tim, of JETESH. And we'll be able to tell you which Tim and what the view is.
And that's what we call a 360 view of a customer or a patient. All of it needs to be governed.
and we deliver governance capabilities to ensure that our customers can democratize all of this data,
be data-driven, enable AI through data management.
That is data management.
That is everything we do to help organizations drive their digital outcomes.
So I'm glad you called it a migraine level problem because that's something that Tim and I talk about all of the time.
I want to see if I understand you correctly here, Jutash, as I think about use cases, the way you've
described it there is there's a couple of key elements here. Informatica is helping you go out
and search all of your data sources. Then it's bringing those data sources together.
And what it sounds like is you're doing some enrichment of that data. You're not just integrating
it. You're bringing it into something that is well understood. You called it a single view of a
customer. And then you may be enriching it for some particular purpose. You said things like
analytics. So am I understanding you correctly? A customer comes to you and says, I've got six data
sources, and I want to be able to run a cost analysis of my most valuable customers. And then
you come in and say, great, okay, what are those six data sources and what are the attributes that we
need to call out in that data. Is that a way to think about how Informatica operates with a customer?
It's a great use case. It's one of many use cases. Got it. Okay. The way I simplify, you described it
perfectly is you know, you look at an enterprise and you'll notice that there's data everywhere. There's
data in spreadsheets. There's data in email systems. There's data in PowerPoints. There's data in databases, and
lakes, there is more fragmentation than ever before.
And what we do is we scan an enterprise and through metadata, which is data that describes
your data estate, we make your enterprise data searchable, discoverable, kind of like a
Google for the enterprise in concept.
So you're looking for customer data.
We'll show you all the SaaS applications databases where we know customer data to be.
And we know it to be there because we're.
we've applied our AI to metadata, our AML Engine Clare, to help organize all of these data sources.
And then you can do any multitude of things.
You can bring data together for customer churn.
And we will help you connect to those sources, bring the data together, process it, and get
it ready for customer churn analytics.
As one example.
We'll bring data together to help you understand your suppliers so that you can manage
your supply chain at Unilever for.
or various materials to build Dove Soap as an example.
We will help you drive deeper customer experience.
Banco, ABC, Brazil is bringing together trusted data,
training their AI and ML models on it 50% faster than they used to do it
because of our productivity.
And these AI and ML models are now enabling them to process credit approval applications,
30% faster than they were previously, a reduction in credit approval times for their customers,
delivering exceptional customer experiences.
At the heart of all of this is data and managing data, processing it, discovering it,
cleansing it, trusting it, and building authoritative views that you can then train AI on,
that you can then run reports and analytics and operate your business on.
Okay.
So one of the things that I heard you say there was that,
that there's an efficiency improvement in how quickly all of this can get processed and how much effort it takes data engineers to get all this pulled together.
And part of that is because of the AI that's built into the current versions of Informatica Cloud.
And I think that that's really interesting.
And I wonder, competing, though, you've got Open AI and other generative AI-based solutions,
which are kind of taking a different approach than Claire your AI has in the past.
Do you think there's a point at which all of this gets swept under the rug and just generative AI magically does it all?
And we get down to like a zero effort.
We can just, you know, sort of point CAD GPT at our data sources and it does everything.
And there's really no need for this sort of quality and other transformations you're doing.
Yeah, great question.
And we truly live in exciting times.
As a technologist, a lot has changed over the last 18, 24 months with large language models.
And we're all actively, as an industry, across the board, whether it's data, analytics, AI,
SaaS businesses, looking at the awesome power of large language models and how we drive productivity for our customer base.
So from that standpoint, super exciting.
Having said that, you know, chat GPT,
built on GPT4 and beyond is really has really been trained on the internet.
Our customers are the enterprise. And so what we uniquely build, what we uniquely bring to our
customers is highly complementary, whether it's Lama 2 or GPT based chat experiences or
or bedrock, AWS-based experiences,
or barred with Google, et cetera, et cetera,
what's unique and complementary that we bring to bear
is we enable our customers to effectively use their enterprise data.
So now you've got, you used ChatGPT as an example.
By the way, we're partnered with all of them, OpenAI,
with Azure, with AWS,
and leveraging some of their AI equally within our data management cloud
as part of Claire.
From a customer standpoint,
really what we're doing is
we're taking the best of chat GPT,
the simple prompt-based experience,
but enabling this prompt chat-based experience
to answer enterprise questions
specific to their organization,
to their customers, to their employees.
That's where enterprise data married
with this,
awesome large language model set of technologies trained on the internet is highly complimentary.
And what we bring to bear is that structured data within the enterprise to enable our
customers to answer really specific smart enterprise data related questions.
That is what we pioneered as Claire back in 2017 and leveraging large language models we've
launched as Claire GPT. It's a simple chat-based experience that lets anybody do data management and get
data insights. Very interesting. So you have brought the chat experience as well as the traditional
sort of large GUI experience that Informatic is known for. Very much so, very much so. We have Claire
co-pilot is something we launched as a data management assistant to help you build data pipelines faster,
to help you build data quality rules, to help you build master data models to drive governance,
compliance, et cetera.
And then on top of that, within our intelligent data management cloud, we've now launched
Claire GPT, which leverages large language models to understand data management intent.
You type in, connect to Salesforce, aggregate all customer opportunities on a monthly basis,
standardized date to month, day, year, and loaded an network.
to Snowflake. That would have taken a data engineer, a data quality steward, a data analyst,
you know, a few hundred hours across a few of them to just coordinate within three sentences,
we'll just do it. 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 Deidrell Willard. Thanks for listening. We'll see you
tomorrow.
