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>> Hey, welcome back to theCUBE.
It's live coverage of Snowflake Summit 23.
Live in Las Vegas, Caesars Forum,
Lisa Martin and Dave Vellante.
This is the second full day of CUBE coverage of this event.
We've been talking a lot about all the announcements.
We've been talking a lot about industry trends.
We're going to be talking about the telecom industry day.
We got the chance to be at Mobile World Congress
a few months ago immersed in telecom.
It's a very rapidly changing industry that we all depend on.
>> Yeah, it was our first physical event, right?
We had Supercloud in January, then we went to Barcelona.
It was a great event.
A hundred thousand plus people
and seems like a long time ago.
>> It does, I know.
Lots of change in the telecom industry.
One of our alumni is back who was with us
at Mobile World Congress.
Phil Kippen is here in the global head
of the telecom industry for Snowflake
and Kallol Dutta Group Lead
for Data Automation at Spark New Zealand.
Gentlemen, welcome to the program.
>> Thank you, great to be here. >> Thank you.
>> Give us, Phil and Kallol both of your perspectives.
When you look at the telecom industry as a whole
what are some of the data trends in particular
that you're seeing that organizations are facing?
>> I think many service providers are really looking
at what data they have and how to use it.
As simple as that may sound
that's where most of our service providers are at.
But there's also some really innovative pockets of work
going on in all different geos.
And I think, you know, SPARK is obviously one
that's leading the charge here
with some very innovative stuff that's going on there.
We're seeing a lot of customer experience
a lot of marketing.
And then certainly as well now we're starting to see
some network when we look at what use cases and you know,
what our service providers are actually looking for.
So I think it's different depending on which geo you go to.
But there's just a whole lot going on
some early and then some innovators such as Spark as well.
>> Yeah 'cause you got kind of a new telco, old telco.
You're new telco I'm inferring right.
And leaning into the Cloud,
leaning into modern software platforms.
But describe a little bit about the company.
>> Yes, so we are Spark New Zealand.
We are the largest telecom provider in New Zealand
provide mobile broadband managed data.
But we are also a digital company.
We provide cloud services, digital transformation,
data analytics, and you know, if New Zealand
if it is described New Zealand
New Zealand is between Australia and and Antarctica.
So we are sort of compete for talent as well as resources.
And that drives innovation
that constrains drive innovation.
And we had to change.
And we, like three years back
there was a conversation with the leadership
and the board and say, what do you do with data?
Can we make data as a source of competitive advantage?
And that's where our journey started.
And we essentially looked at data and the use cases.
We started in marketing, we picked a one or two use cases
and we then developed this whole lot of capability
to make value out of data.
>> Okay, started marketing to drive sales, right?
Was that kind of, or was it to drive brand?
>> Yeah, good question.
So every telco starts somewhere.
So we started with marketing.
Some start with networks, some start with product.
But it all converges into one
which is improve the customer experience.
Because if you are happy customers
that drives more sales in a simple way.
So we started with marketing, but we essentially
took the problem in terms of
we are sending too many messages to the customers.
Can we be send the right message
to the right customer at the right time?
And for that we had to get the data together.
And we got the data together by unified data platform.
That's what we called our Snowflake instance.
We made Snowflake the heart of our data
and then we put AI and ML capabilities
on that so as to find the right customer
at the right time that drove
the conversions by 17%.
On the same time the marketing cost reduced by 16%.
That was a huge success.
And that laid the foundation for what we are doing now
what we call as data driven everywhere
which is take the data driven operating model
to all parts of the business.
We are doing one in network
where we are essentially doing network planning
with data so that we have the right network
for the right customer
and the experiences optimized for them.
>> Yeah, and that's what they expect, right?
We expect to be, as consumers
we expect to be connected wherever we are.
Doesn't matter for New Zealand, Antarctica, Las Vegas.
And that customer experience is critical
because customers have choice.
They'll churn.
So obviously you made
some huge business impacts with marketing.
>> Kallol: That's right.
>> Driving retention.
Driving conversions.
You said, I imagine sales is like awesome marketing.
Thank you.
But that's also a challenge with organizations
that sales and marketing and connection, disconnection.
Alignment is key there.
I imagine that was one of the benefits
that came out of what you've just started doing
even with the marketing use case.
>> Yes, and I think the marketing was the start.
That started the journey to look at operations
and customer experience benefits.
How do you make the processes frictionless
by finding the opportunity to automate and make it easy
for our customers.
And while we do that, we also had to change
our operating model in terms of how you enable the data
to show up for our customers.
And we essentially partnered with Snowflake to bring in
the data capability across B2B SME network.
And now we are taking that to finance.
>> To finance.
>> So when we were at MWC we, you and I talked about
the disaggregation of the telco stack,
how that's taking a long time, obviously.
Like I started by saying old telco, new telco,
or even long-term telco
but innovative mindset, growth mindset.
Since we've talked, what are you seeing?
Has it moved at all?
>> Yes, actually it has, strangely enough.
It's only been a short period of time.
But what we have seen is we've started to see
a lot of consolidation between the chief data office
and the CIO with the network teams.
And that's big.
I mean, so some of our providers have started to look at
bringing together product and technology.
Others have been looking to bring CDO closer
to the chief data office, closer to the network team.
There is a lot of change going on right now
and it's a big shift for sure.
So it'll take 'em a little bit of time to get through that.
But that's certainly what we're trying to help them with.
We're trying to bring a platform to market, you know,
and help our service providers go into the network teams
and help them become data folks as opposed to just
expecting the chief data office to do it.
And then when they're both speaking the same language
they can collaborate together and make things happen.
>> Do you, Kallol,
are you envisioning developing applications on Snowflake?
So obviously using Snowflake in the Cloud.
Are you using the Cloud in other ways?
Put BSS systems, OSS systems.
Maybe you could give us a sense
as to paint a picture if you would.
>> So when we looked at data, we were building data
in sort of what we call a service model.
Ask me what you want and I'll build it for you.
And we realized that that's not sustainable.
We need to build it in like a product.
So we essentially created a vision,
created a team across it, created measurement KPIs
so that we change from being a cost center
to being a growth center of the business.
And that essentially enabled us to create products.
And one of our most successful product is called BRAIN.
Now what does BRAIN stand for?
It was a product which was named by the squad itself.
It stands for Build Robust AI for Next Best Action.
And we did that essentially
to manage the multiple models
we have to find the right customer at the right time.
And the BRAIN consists of a decisioning engine, it consists
of a data layer but also a measurement layer
to find the uplift we can do with our use cases.
And that has been a really big story for us.
Now, the company has sort of had that
as a core platform to enable that to go across the company
and realize the same vision across multiple areas.
>> Looking at your website
and seeing that Spark is the first large company
in New Zealand to go all in with Agile.
Talk about that and how is Snowflake a facilitator
of that Agile operational model?
>> We were one of the first companies to do whole Agile
in the world.
And with that operating model change,
it meant that our teams get closer to customers
and we broke the boundaries of business units
and organizational friction which creates
in the high hierarchical model.
And that enabled us to create cross-functional teams
which brought the capability across, for example
the data teams, the ID team, the network teams
the business teams to build capability together.
And they were enabled by the unified data layer
which Snowflake built.
And we used the unified data layer
then to have one view of customers, one view of the product,
which then we use to create apps
for people to use and experience across our network.
>> That's a huge cultural change.
>> Absolutely.
>> How did you do that and how was Snowflake a facilitator?
I imagine you, when you talk about service providers
that's something that you have to facilitate.
>> Yeah, yeah.
It's definitely different.
I mean, service providers, you know,
back let's say circa seven years ago saw applications
and the opportunity to develop applications
and bring those applications to the market
and grow their place in the value chain.
It wasn't in their DNA.
So not a lot of them took advantage of that.
And apps came and went.
So when we look at data now it's the next frontier
and we are seeing many service providers take it seriously.
But I think certainly what Spark's done
is incredibly innovative
and they've been able to operationalize
around something that many others haven't been able to.
And I think that will certainly be one of their
sustainable competitive advantages as they move forward.
>> When did you start building BRAIN?
>> It has been a three year journey.
So because we had to not only change our model,
our data was all across the enterprise.
We had a data warehouse, we had a data lake
we had a operational data store,
we had a feature store, you name it, we got it.
But it was all in disparate systems.
So we had to get that all together in Snowflake over time.
We are nearly there, not fully there
but in six months we will be completely on Cloud
or our code stack.
And our plan is to take it to subsidiaries.
And I remember the frank conversation is how being a app
on a product enables us to reuse what we have got
and we will take it into our subsidiaries
so that they don't have to go
to another three years of pain to get there.
The leverage is much faster.
>> Those disparate systems were all on-prem
or was it a combination of on-prem and in Cloud.
>> All way on-prem.
So we had to move them all into Cloud at the same time.
Curate them, aggregate them and make it usable.
>> AWS or?
>> Azure.
>> Azure. Ah.
>> Like I said, that's massive.
Talk about like the buy-in from the C-suite level
that was needed to make that happen.
'Cause that obviously doesn't happen overnight
but it sounds like you made it happen pretty quickly.
>> Fantastic question.
I think if we see there are two major things
which made this successful.
One was the leadership board
and the executive buy-in on this.
They were fully on it from day one and they supported us.
And it is a long term vision because you can't
we do look to give value in a short term,
but it takes three, four years
to go through the whole transformation.
And they were across us.
And that helped us to create a sustainable strategy.
But we also had a light to that.
Another part which was very important
for this success was what we call as start small,
but start deep.
Start small in minimal viable data to start,
but start deep is do one or two use case really well
end to end, show the value
and go to next one rather than spread yourself thin.
And these two were probably the key reasons we are here
talking about BRAIN and the next evolution of that.
>> That's huge because you guys are in the minority
in terms of the digital transformation projects
that are successful.
But you mentioned two of the things
that we were talking about earlier
that are critical for that, the C-suite buy-in and culture.
For sure can't have a successful transformation journey
without those two components.
>> It's fascinating what they've been able to do.
What's even more fascinating to me
is how they're changing the way
that they build their models,
where they extract their data from.
And so building applications is one level of complexity.
You can go up in complexity certainly
as you start building custom capabilities
or user defined functions.
What they've done is they've created a brand new model
that looks at these non-traditional data sources
and starts to pull from those data sources
interesting information about their subscribers
that then they can go and increase
the accuracy of their prediction models
in serving customers ads.
So you've got so much innovation going on in here
all up and down the stack.
And it is, it's been fascinating to watch,
watch them go and they're doing some great stuff
so far today.
>> Eight months from now, you guys both be at MWC?
>> Absolutely. >> Sure.
>> You will?
Yeah, you going to go?
All right, we got the same spot
in between the halls four and five.
>> Phil: Awesome.
All right, theCUBE will be there
so we'll see you there.
>> Outstanding, looking forward to it.
>> Dave: Love to have you back on.
>> Awesome guys, well looking forward to hearing more.
I'm sure that will be tremendous amount of changes
in the telecom industry in just that short period of time.
But we thank you both for sharing the Spark story,
the innovation.
Congratulations on what you've done so far.
This is an awesome story guys.
Thank you.
>> Outstanding. Thanks guys.
Have a good show.
>> All right, thank you.
For our guest and for Dave Vellante, I'm Lisa Martin.
You're watching theCUBE.
Up next, ZoomInfo going to be talking with Capital One
on how they're maximizing the benefits
of B2B data for future successes.
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