-: So good morning, Rahul.
Many thanks for being with us today.
-: Well, Lucas, Marc, it's great to be here.
Thanks for having me.
And it's a real pleasure to come here
and chat about data and DDP with you.
-: We as BCG, have developed an approach
which we call DDP.
It's the data and digital platform transformation approach
with which we help those kind of customers
that really want to put data out there
to accelerate their journey.
-: Data's really the foundation
on which AI can drive insights
and differentiated outcomes.
It's really all about helping our customers
take advantage of AI, put it to work,
and use it to drive differentiated outcomes.
-: So creating value for the customer
can be separated in time or place from actually capturing.
If you look, for example, at Amazon Prime,
what were your experiences with this creation
versus capture concept?
-: So the Prime innovation
was creating a subscription fee
that then eliminated shipping costs.
And so this led to people shopping more and more at Amazon,
it made the purchase experience better.
And you're absolutely right,
we're looking to instrument all of the interactions we have
from the emails that customers open, the things they browse,
the things they buy, the shows they watch.
So you have customers seeing value, that drives traffic,
that in turn drives purchases for our suppliers.
And then that growth allows us to get efficiency
in our system while still creating a win-win
for ourselves and our suppliers.
So this concept of DDP,
of focusing on customer value creation,
instrumenting what you're doing
and then using that to drive a win-win
from a value capture perspective
can really set you up for long-term growth
and long-term customer value creation.
-: At BCG, we think that the only way
to realize that combination of value capture
is to do it through a horizontal, layered architecture.
The basic foundational idea of DDP.
What does putting data at the core really mean at Amazon?
-: So having that data available to everyone who needs it
in a safe, secure, well-governed way is absolutely critical.
I think when you have good governance,
you can actually set people free to innovate
because you're confident that only the right people
will see the right data for the right purpose.
And that in turn enables our individual business units
to build their own analytic
and machine learning and AI capabilities,
all operating off the same playbook
and augmenting that with their own business unit data.
Each individual team owns their data,
makes it available through APIs,
and understands who's allowed to use it.
But we also have certain assets that are centralized
to allow us to get that source of truth.
And it's the combination of these
with great governance in between
and the ability to discover data
that lives around the company in this distributed fashion
that allows our teams to go fast
and go independently while still being cohesive
in terms of trying to achieve customer value
and capturing some value for the company.
-: What we've learned is that, in the end,
you would like to mirror this value creation,
value capturing ID also within the tech stack.
So our DDP actually recognizes what we call the layers.
-: You know, the Layered Modular Architecture
is absolutely at the core of how we think about building
and creating these interesting customer experiences.
And so our Amazon business, for example, on Prime Day,
can run trillions of transactions
on some of the databases that we offer.
And we don't need to know the details
of what they're operating on,
we really understand the APIs that they're interacting with
and we focus on their availability and performance and SLEs.
-: So we talk about multidisciplinary teams
organized in organizational platforms,
mirrored to the business.
How does that work within episode?
-: We've had the concept of the two pizza team
for a long time.
The idea comes from the fact that teams
should be relatively small
and so this allows them to be cohesive, to move fast,
and then we imbue those teams
with a very clear ownership mandate, so you own your area.
You have to go to your customers,
understand what they need, make sure you deliver it,
and ask for the resources that you need to deliver that.
-: In order to conclude, please give us
a snapshot on how you see Amazon and AWS evolving
in the coming months and years.
-: It's important to focus on things
that will stay the same.
If you invest in those, you'll always be relevant.
And so on our e-commerce business,
we talk about the need for always having
great selection, great prices.
And on the AWS side, we really want to deliver
top-notch security, operational performance,
great value, and great price performance.
I really am focused on helping our customers
get value for their business
from AI, machine learning, and data.
And so it's really about finding a business outcome
they're looking to drive, and then using AI and data
as a force multiplier to achieve that outcome
quickly and effectively.
It's data that's gonna be the differentiator,
and using ideas like DDP to connect that data
into AI technology is the way we think customers
are gonna be successful, and we're really focused on that.
-: Very inspiring.
Thank you very much, Rahul.
-: Thanks, great to be here.
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