>> Announcer: The Cube presents HPE Discover 2022,
brought to you by HPE.
>> Welcome back to the CUBE's day one coverage
of HPE Discover 2022 live from Las Vegas.
Lisa Martin, here with Dave Vellante.
We've got a couple of guests here with us next,
going to be talking about industry transformation,
please welcome Brad Schlagenhauf, Director
of Global Industry and Sustainability Marketing
and Andy Hochhalter, Senior Director,
Worldwide Industry Sales Programs,
guys from HPE, thanks for joining us.
>> You bet. >> Thank you for having us.
>> Got to to be here.
>> Industry transformation, that's a big term
it's not a new concept, but we see so much going on.
Andy talked to you about industry transformation,
from your perspective, where are customers?
How are they capitalizing to really make data
a true currency?
>> Right, well, underlying all this is is the data
that is becoming so complex.
But at the same time, there's specialization required
in each industry with the different applications
that the industries are running
and our ability to bring that forward and connect
all those things is a big trend going on.
And as we see that developing over time,
we're more connecting those different applications
that are running is becoming more every day,
we're doing more of that.
>> So where do you want to start?
What's your favorite industry to transform?
I mean, financial services got the whole blockchain thing
going on, industry 4.0 and manufacturing,
retail, everybody has an Amazon war room,
energy now with EVs and solar and everything else
and the price of oil, and now you throw in inflation
and supply chain and I mean every industry
is getting disrupted.
I want to make an observation,
you guys tell me what you think.
You know, think about the incumbent industries,
they generally have data at the outskirts,
it's all siloed and they're trying to put it at the core
and that's a big challenge for them,
what are you guys seeing in terms of
who is having success with that?
Do you have examples?
What role do you play?
We have so much to talk about, right?
>> Yeah, let me I'll jump in here.
I mean, I think one of the unique ideas
is all this in industries you mentioned there
are all trying to learn from each other, right?
If you're a financial institution,
you want to understand what retail is doing
because you want to serve your customers better, right?
You want to look at some of these technologies,
how they're being applied,
you look about like sustainability,
the industries are trying to learn how to do that better
from each other.
So there's this notion of industry and transformation
is it's kind of twofold.
It's one, how are these industries almost like
entering new markets?
I mean, you look at all the tech companies out there,
they're all getting in into payments, for example, right?
You know, Google pay app.
So that's just like one example of where you're seeing
kind of that blurring of lines between industries happening.
>> Content, Amazon getting into grocery.
And so in the premises, the data is the enabler,
I mean, right?
For decades, we've seen a stack,
a vertical stack within an industry
where whether it's research and development,
manufacturing, sales, and distribute marketing,
you were in that industry stuck for life,
and now all of a sudden data allows you
to traverse industries.
This dual disruption agenda that you mentioned, right?
>> Yeah, it's really at it's core is because these companies
have the ability to take advantage of that data even more,
and they're trying to serve their customers even better
that's kind of opening up these new doors for them
to do that because that's, you know, and again,
there's so many good examples out there,
automobile manufacturing are looking towards
the gaming industry to how do they design controls,
that kind of stuff is example.
So you see all kinds of that, you mentioned also
that everybody's trying to bring the data to the core.
I don't think that's necessarily true,
I think you heard earlier today in the keynote,
that companies want to be able to take advantage
of the data wherever it is.
If it's the edge and a factory floor,
if it's a patient data sitting somewhere,
you want to handle it where it is,
and there's a cost to doing that, to bring it all together.
>> Yeah, so by the way, I want to clarify,
'cause you're absolutely right.
Data by its very nature is distributed.
When I say core, I mean put it at the core
of their business, that's what I mean by data first,
but your point is really,
we're going to talk about that because it brings
so many other challenges with how you deal with that.
But please jump in Lisa.
>> I was going to ask you Brad,
you talk about the blurred lines between industries.
And talk to us about how is HPE a facilitator
of those industries learning from each other,
you have such breadth in so many different industries
as Dave mentioned, but how are you that enabler,
if you will, of allowing them to be able to have data
be that key?
>> Yeah, I think it just comes through the experience
of working with these customers in these various industries.
And then there's so many times where customers come to us,
they want us brief, and again, they want to learn
for these other industries.
So we're an aggregator of that technology.
We obviously understand the technology with the cloud
or edge or anything we're doing in with data.
So we're using those lessons and just applying
those out there to those industries.
So I think it's just us as an aggregator.
>> How's the customer experience changing?
And we heard from Home Depot this morning,
they were focused on the customer experience
and their associate experience
bringing those together maybe.
>> Well, what we also heard this morning
is the different personas, right?
That are out there looking to transform their business.
And each of those personas is still linked together
by the data, but they want to use it in different ways
with different applications.
And the ability to connect all those things
again, they're learning from each industry.
So what Home Depot learns about their mobile apps,
maybe something that we can deploy in manufacturing
as far as locating things on the floor
and connecting the edge data in, bring it in
and then use that to analyze, use AI models,
to do predictive behavior, preventative maintenance,
all these things are similar uses of connecting the data,
but then applying to the specific industry use case.
And that pivot of that horizontal use of the data
into those specific demands by at the personas
within the different industries is what we're focused on.
>> Yeah, and the technology is like an accelerate here.
So you're looking about like something like 5G, right?
5G is going to accelerate a lot of transformation
in various industries throughout that.
I mean, technology alone is not really
what the customer cares about it,
they care about what do I do with that?
What kind of outcome can I get?
>> I want to ask you Andy, about the customer conversations,
you talked about the personas.
We've been talking about data democratization
for a very long time.
Obviously it's a challenging thing to do,
but how were you seeing customer conversations
change and evolve, especially over the last couple of years
where every LOB has to have access to data
and be a driver of its value.
>> Well, historically HPEs background is in infrastructure
and we've served industries in the data center
for a legacy, right?
But now they're saying it's more, you know,
I've got to talk to more people in my business
as a data center owner, I've got to serve these folks,
understand their business and as a supplier to me,
you need to understand them as well.
And sometimes help me with that conversation and help me see
the things to make those connections that I may not know
as an IT professional.
And how do we challenge the business
to think about different ways of doing things
in the industry?
So how do we think about bringing those connections
from other industries in and uncovering opportunities
or problems, anticipating problems in those deployments
that they may not have seen by their staying
in their swim lane.
>> You know, I'm torn on this topic because on the one hand,
I think about the big data era
and I know of a lot of failures to return the expectations.
And it wasn't a fail fast, took a decade to get there.
And part of the failure domain was to your earlier point,
Brad, everything was sort of shoved into this centralized
location, you have this hyper specialized data team
everybody has to go through them.
But organizations I think are now realizing
like your thoughts on this,
that data has to go out to the lines of business,
it has to be contextualized.
People are now talking about building data products
and monetizing data and that's really,
to me what digital transformation is about.
But generally speaking,
most companies are not great at data,
they have a lot of data, a lot of data lying around,
insights I think we heard in the morning keynote are scarce.
So what's your vision for how this evolves?
>> Yeah, I think from the data perspective that again,
at the core is how do I serve my customer better, right?
So whether that is actual customer data that you want
to serve up personalized offers for,
or make medical decisions for their better patient outcomes.
So if they keep that in mind, then as far as how
it's used by the different lines of business there,
that's where we can help facilitate in many ways.
And that's where cloud becomes a really key technology.
Having that flexibility to move it around as needed,
deliver the workload where the customer needs it,
that sort of idea is where we're going with this I think.
>> Yeah, I'd like to give you an example,
in the FSI industry out here on the floor,
we've got a demo on payment systems, right?
And we've been doing that with our nonstop product
and supporting that in the banking industry
for 10 years or more.
And it's evolved over time to be,
it's a ubiquitous across in the support.
But now we're talking about new regulations
with all the global events that are going on,
crazy stuff that more pressure on the banks
to comply with that worries about money laundering
and fraud prevention.
Well, connecting the data from those payment systems
into the AI modeling that is now being deployed
to do more sophisticated fraud detection
and money laundering detection
and all of those kinds of things.
How you connect those together as an example,
what we're seeing, how we get more insights
by the combination that we can bring together.
>> And the insights is critical, right?
I mean, without it, the data isn't very useful.
>> Right, and I think even these concepts
like swarm learning, right?
Where you're actually trying to aggregate a lot of that data
and provide even a broader data set to learn from
is even more beneficial.
>> I think that when you think about the principles
of this decentralized world,
that it starts with an organization saying,
look, we recognize that we can't shove it all
into a data warehouse or a data hub, or a single data lake.
We're going to have all of those,
and those are just kind of nodes in the mesh,
like it's steel is Uck, the GNI term,
and increasingly data as product that can be monetized.
We're hearing a lot more about this,
and those are organizational considerations.
I mean, HPE can maybe facilitate that
through whiteboard sessions,
but that leads to, in order to democratize data,
I need self-service infrastructure,
and I need data that can be shared and governed.
I don't know about the last one,
but you definitely are number three.
Self-service, infrastructure, simplification,
your version of cloud, how do you see your role
in that little vision that I just laid out?
Do you buy that?
>> You want to take that or?
>> Well, I think because we see the data
in all these different places
and we're trying to be agnostic to where it comes from,
who owns it, it's how do you get it together
and make it useful?
And you don't have to capture it,
you don't have to own it, but you may own some of it,
you may borrow some of it, you may rent some of it,
you may buy it and you may bring it together
and you'll use it for the purpose
and then move on to expand into new things
that you learn from that you may then monetize
in all those different ways.
So we have a role of making that platform in a way that
you can see it in different ways and use it consistently
and repetitively and gain more value of it
and then apply your applications and all those other things
that you do.
But that bringing together agnostically
is a big part of our offering.
>> And am I not correct?
I'm in my thinking on HPE value is providing
that infrastructure to be able to do just that.
That's your swim lane, if you will.
>> It is, but we're being asked to move up the stack
and provide not only the infrastructure, now the platform,
the ability to offer that platform
in our HPE GreenLake offering, where we now can have
cloud-like services on prem.
It doesn't really matter where the data sits
and then plug in the applications
and even manage those applications for the customers.
>> Okay, I see you as IS, and Paas,
which is that up the stack.
The ability to, I want whatever Python or open shift,
I want to build applications now on that.
Interesting the management piece is something
I excluded because an organization may say,
hey, we need help managing this stuff.
But I see that IS and Paas as infrastructure,
you're not getting into applications
where you're getting,
you're not?
>> No, other than letting customers actually build
on top of that, right?
There's a lot of customer, >> You're an enabler.
>> Absolutely, you look at some of the things we're doing
with our ESMO platform and things like that,
we're providing that development platform
in a really streamlined way of pushing applications out.
I mean, little known fact, right?
Is that most banks right now are hiring
more developers right now than finance people.
So all these industries are becoming tech companies
and that's the whole launch of the FinTech Industry
many years ago, and it's continued to evolve.
>> And they want to bring AI,
they want to bring data into their applications
and you, HPE is an enabler of that.
>> Absolutely, yeah, agree.
>> Give us last question as we wrap up here,
give us the vision, like the next five years,
what are some of the industry transformation elements
you are forecasting if you have a crystal ball.
>> Yeah, I think number one,
just an increased focus on
personalization and customization.
You look at personalized offers
when you add location based services,
things like that, combined 5G
and like all this technologies,
you're seeing a lot of that custom manufacturing.
So those kind of trends are going to continue.
We know those are the workloads that we got to
know is coming down the pike and address those.
Secondly, I think AI, right?
AI is going to impact every industry in a big, big way.
You know, like Andy talked about, fraud detection,
manufacturing, robotics, those kind of things.
And then I think lastly, just this more convergence,
of these industries, right?
Tech is just impacting everything in such a big way
and so you're going to see more of that blurring of lines
between industries as they jump into jump out of
their normal swim lanes, right?
>> Between machine learning and AI,
we're going to see efficiencies by doing things better,
with less deviations and driving lower cost,
and we're going to see new capabilities come to the forefront.
And that's going to be consistent across all industries
and it's going to be based on the data.
Both of those require the the data go in
and drive their models.
>> Do you think any industry is more ripe for disruption?
I mean, timeframe wise, you got healthcare,
like I was wondering, how is AI going to help doctors
make better diagnoses already is?
Will AI make the diagnoses?
You know, retail, I mentioned before, energy,
government is changing, entertainment,
media entertainment is,
do you see any industry patterns
where one is being disrupted more than the other?
>> When we talk to customers, every industry
thinks their industry is not going fast enough.
And so I think everybody is just so hyper focused
on what they are involved in and then their domain
that depending on who you talk to
everybody needs to do it faster,
more economically and more efficiently.
>> And they're all being disrupted now,
it's not only have to faster,
but they've got to transform to keep up with the demands
of their customer.
>> Nobody's safe.
>> Yeah, and the technology's just going to continue
to accelerate that, and that's the thing.
And the market's becoming less forgiving as we go,
so people have to react really, really fast
in these markets and especially with all the other changes
going on around us to actually make that impact.
>> I'm liking what's in this crystal ball,
I'm going to have to ask you guys for some consult
after we wrap here.
Thank you so much for joining David and me
talking about industry transformation.
Tremendous amount of transformation so far
and so much to go, it's exciting to watch.
>> Yeah, appreciate it, thank you for having us today.
>> We appreciate it.
For our guests and Dave Vellante,
I'm Lisa Martin, you're watching theCUBE,
the leader in Livetech Coverage.
We'll app back after a short break.
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