[MUSIC PLAYING]
STANY WINKLER: Welcome to our Google Cloud Next 22' session
with Deutsche Borse Group.
Increasing Agility-- How Deutsche Borse Group Runs Core
Finance Processes on S/4HANA Google Cloud.
My name is Stany Winkler and here at Google Cloud
I am Head of SAP Sales Specialist for EMEA North.
As an international exchange organization,
Deutsche Borse Group is aiming at becoming a major reference
for the financial services industry
by moving workloads to the Cloud.
Deutsche Borse Group is actually among the very first
financial institutions to run core finance and treasury
processes in S/4HANA on Google Cloud.
Leveraging Cloud technology has increased automation
and process availability.
Going forward, Deutsche Borse's Cloud journey
includes the integration of Google Analytics
into its entire enterprise analytics roadmap as well.
We're very excited to hear from two experts in their field
sharing their perspectives on the subject.
So I am thrilled to welcome Allison Krill, Chief Technology
Officer of Deutsche Borse Group, and Lars Bolanca, Executive
Vice President and Head of Corporate IT
at Deutsche Borse Group.
Allison and Lars, welcome and over to you.
ALLISON KRILL: Thank you Stany.
So before we get going on our Cloud journey and strategy,
I thought I'd spend a little bit of time
giving you an overview of who we are as Deutsche Borse Group.
So Deutsche Borse Group is an international exchange
organization that provides innovative market
infrastructure.
We serve as a wide variety of the full market chain,
starting with pretrade, which covers index services
as well as selling of our market data to different clients.
We then cover the trading and clearing value chain,
everything from derivatives markets to cache markets,
to energy and FX.
And then lastly, we have post-trading,
which is made up of custody, collateral and liquidity
management, but also our investment fund
services business.
As a very critical part of the financial service value chain,
it's important for us to have state of the art IT
infrastructure, but that has to be highly available.
It has to be trusted.
And that trust also means that we
operate in a very highly regulated environment.
As Deutsche Borse Group, we're around 10,000 individuals
headquartered out of Germany, but we
have staff offices and infrastructure
around the globe supporting the financial markets
infrastructure.
The IT organization is made up of different areas.
We have product teams that service the different business
lines that I've mentioned.
But then we also operate central IT functions
that are focused on corporate IT services,
where Lars will explain a little bit more
about his team and the role and how they're
progressing our Cloud strategy.
But also we have central services
covering infrastructure, security,
and also driving innovation.
And that's where my team is really
taking a lead to drive our Cloud strategy across the group.
So going into our Cloud strategy--
public cloud strategy is a fundamental pillar
as part of our overall business as well as
IT strategy for the group.
We see significant benefits of operating in public cloud,
from agility and being able to dynamically meet
different business demands by scaling
up and down infrastructure, but also improving quality.
We've gotten significant benefits of operating our dev
and simulation environments in the public cloud
and it allows us to, on demand, scale
at different services for our clients
so that they can test different environments within our trading
infrastructure and compare on demand at a 24 by 7 request.
We also have seen sizeable reductions in operating costs
as we standardize our infrastructure and our software
stack.
But really from a business strategy where we see Cloud
driving the most benefit is allowing
us to deliver things in a more dynamic way
and deliver solutions that we couldn't have done previously,
whether it's new blockchain-based services,
delivering digital securities infrastructure
and some new asset classes, but also having environments
around big data, where we can drive greater
analytic solutions and tap into machine learning capabilities.
Our journey on public cloud started in 2016
when we focused very much in a sort of proof of concept
approach, but we made some fundamental pivots
to that early 2017 and into 2018 to mature and also
enable us to scale.
Some of those things that we created
was setting up a Cloud Central of Excellence team
under the CTO area, which allowed
us to standardize on processes, automate processes, but also
standardize on architecture blueprints.
We also, to tackle the very complex regulatory environment
and also criticality and evidencing
how we run in a highly regulated environment
where we're outsourcing certain services,
we set up something called the Collaborative Cloud Audit
Group.
This has been instrumental in bringing together
40 companies, institutions, across the financial services
area and insurance companies, to make sure
that we are driving audits in a way that's
efficient, both from our side, but also from the Cloud
providers that we work with.
It makes much more sense for us to conduct audits together
than having 40 different institutions approaching Google
requesting the same evidence, the same information,
to show regulatory compliance.
And that's been a huge benefit in giving us
kind of the momentum and the power across the industry.
I would say the other thing that we've done successfully
is making sure that we partner with Google
to ensure that we have contracts in place that
meet the regulatory standards and that has also
enabled us to move critical workloads and critical data
into the Cloud as we've progressed on that journey.
The other key thing that we have done that's driven successes
is really developing those strategic partnerships
with the likes of Google that allow
us to co-engineer and tackle some
of the more challenging industry problems,
such as things like how we evidence
and build world class security in a Cloud native way.
So all in all, it's been a sort of interesting successful
journey, one that's made up of constant
learning and improving.
To date, we're on track to have around 35%
of our environment in the public Cloud by the end of the year.
But our ambition goes much further
and we've got a roadmap that we've
defined based on business benefit, innovation,
and value add to get to over 75% over the coming five years.
So with that, I'll hand over to Lars
to walk through specifically how we're
applying the strategy in the corporate IT landscape
and what we've done on SAP.
LARS BOLANCA: Thank you Allison.
And as Allison already mentioned at the beginning
and shared also a bit the outlook on the Cloud journey,
I will now look a bit on how do we do this practically,
so giving the example of corporate IT.
So, how do we run IT for our group functions
and also here, as you rightfully mentioned,
how do we do co-engineering for things where there is
no solution yet in the market.
We try to also be a bit, not only trying to be,
but we are innovate on the innovation side
and try to also explore things that we are learning as we go.
So looking a bit on corporate IT and also our journey--
and it follows exactly the same time schedule
that Allison has been presenting--
we started very early with easy things,
so examples are travel expense or purchasing.
Because it is software as a service, it is Cloud,
it is easy to explain because everyone
understands travel expense.
Everyone understands how to buy a pencil.
And these were services on the other side that also allowed us
as a group to learn how do we do Cloud
in the context of regulation, how
do we do Cloud in the context of our control functions,
and then within corporate IT, how
do we make sure we can run services in the Cloud
with a proper operation setup.
So this was the things we started,
and we then went along with a lot of software
as a service items, speaking HR, speaking client
services and sales, and then also speaking,
let's say, the first versions of running analytics in the Cloud.
The emission level for us as is corporate IT
is to exceed the 35% that we have today.
So we are today running at 55% of corporate IT in the Cloud
already.
Target state is to have everything either software
as a service or running in GCP.
So the idea is, really, that in the end,
except of a minimal footprint, which we cannot move
to the Cloud, everything will be running into the Cloud.
And this would also set an industry standard,
so when speaking to partners and peers,
this is what many companies are striving for, but more looking
into, let's say, a 5 to 10-year roadmap,
rather than a one to two-year roadmap.
If you look at the target picture here specifically,
our setup is everything that is not Software as a Service.
We're running Google in a typical setup,
and Allison was also referring to this,
we are requiring at all times less than two hours.
We are requiring high availability, in general.
We have to think about exit strategies, and so all
these type of things.
And we are doing this for new products like SAP S/4HANA,
but we are also doing this for legacy SAP environments
like our old BW, so Business Warehouse, or our old CRM
system.
So this is something we learn as we go.
The more modern the application, the easier it is to move.
The older it is, the more tricky it is to move,
but these are things we are learning.
What matters a lot for us is regulation and information
security.
And for this, we also have very early
in the context of co-engineering started with Google
to see how can we run an S4 system in Google Cloud with all
the, let's say, security features,
with all the regulatory context that we have.
So starting with the technology side, but also,
looking at contractual frameworks,
looking at what are processes that we need,
and also, what are reportings that we need.
For example, when it comes to who has access to our data,
when does data access happen?
How is our network environment really
a lot around monitoring and control.
So these are things we started very early.
We have set this up today.
And when I get asked last, what have been your key drivers
to move with Google, then I can always outline three topics.
The first one is when we look at scalability,
so a classical example, we use is building grounds.
So we have building grounds once a month.
We have simulation for this building run also once a month.
Each of them is taking two to three days.
And in a classic environment, you
have a multi-terabyte environment, running 24 by 7,
but only being used for five days.
And with Google, we can scale up.
When we need the services, we run them
and then we run down the machines, respectively,
so we really have the full scale of, let's say, flexibility.
The second item is around disaster recovery
and high availability, where we are operating
in a two-region setup.
And when I translate this into an on-premise world,
this would mean you have to build two data centers,
and building two data centers will take you a month to years.
If we speak about setting up regions
within Google out of the box, we are speaking weeks to months,
depending on design and setup requirements.
These are things you can do out of the box,
and this helped us also a lot.
And the last time was really when speaking about automation.
So classically, let's say, infrastructure is a code.
So here we had, really, a lot of learnings on one side,
but also, a lot of fun.
I can really call it as it is.
In the operations team, when they started exploring
and they could do everything themselves.
So normally, when you run on-premise infrastructure,
you have a better team, you have a network team,
you have a data center team, and all of them
have to work hand in hand, and they have different priorities.
If you are running also, the infrastructure as a code,
you basically, run it all.
Of course, you need to have some security and foreign principles
in place, but you do this more or less
with your keyboard and your command line.
So these are the benefits that teams were highlighting,
and I think this is really a huge milestone compared
to an open setup.
If we then look at a bit of sneak preview--
and Stany was also mentioning this at the introduction--
an innovation case that we are doing at the moment
is how can we now integrate best of breed,
so kind of combining a classical SAP business warehouse, which
controls our accounting class, so that you will not convince
them in anything is off.
On the other side, you have a lot of workloads
that historically have been moved into an SAP warehouse,
where you say, there is no reason that they are there.
The past just has been there.
And this is where we now use Google Analytics for things
like data tiering, data mesh, so also,
allowing people decentrally to work on data
and while keeping all data control, on the other side,
also making sure we have flexibility for these teams
and really using things out of the box.
And this is where we have seen, really,
a lot of speed in the organization,
and we are still in a POC phase.
But we are seeing that historically,
building up an SAP business warehouse can take you years,
and the POC we did in three months,
where we used really out-of-the-box services
and people really start liking this.
So this is a bit of a recap on innovation cases we also do.
And with this, Stany, I would hand over back to you.
STANY WINKLER: Thank you, Allison and Lars,
for sharing these valuable insights and your success
stories.
Setting an industry standard, indeed,
and having a little bit of fun while at it
sounds like a wonderful combination.
And to you, our audience, thank you so much for joining us here
at Google Cloud Next '22.
[MUSIC PLAYING]