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<v ->So good morning, Rahul.</v>

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Many thanks for being with us today.

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<v ->Well, Lucas, Marc, it's great to be here.</v>

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Thanks for having me.

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And it's a real pleasure to come here

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and chat about data and DDP with you.

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<v ->We as BCG, have developed an approach</v>

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which we call DDP.

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It's the data and digital platform transformation approach

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with which we help those kind of customers

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that really want to put data out there

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to accelerate their journey.

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<v ->Data's really the foundation</v>

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on which AI can drive insights

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and differentiated outcomes.

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It's really all about helping our customers

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take advantage of AI, put it to work,

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and use it to drive differentiated outcomes.

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<v ->So creating value for the customer</v>

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can be separated in time or place from actually capturing.

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If you look, for example, at Amazon Prime,

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what were your experiences with this creation

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versus capture concept?

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<v ->So the Prime innovation</v>

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was creating a subscription fee

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that then eliminated shipping costs.

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And so this led to people shopping more and more at Amazon,

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it made the purchase experience better.

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And you're absolutely right,

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we're looking to instrument all of the interactions we have

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from the emails that customers open, the things they browse,

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the things they buy, the shows they watch.

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So you have customers seeing value, that drives traffic,

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that in turn drives purchases for our suppliers.

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And then that growth allows us to get efficiency

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in our system while still creating a win-win

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for ourselves and our suppliers.

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So this concept of DDP,

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of focusing on customer value creation,

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instrumenting what you're doing

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and then using that to drive a win-win

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from a value capture perspective

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can really set you up for long-term growth

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and long-term customer value creation.

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<v ->At BCG, we think that the only way</v>

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to realize that combination of value capture

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is to do it through a horizontal, layered architecture.

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The basic foundational idea of DDP.

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What does putting data at the core really mean at Amazon?

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<v ->So having that data available to everyone who needs it</v>

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in a safe, secure, well-governed way is absolutely critical.

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I think when you have good governance,

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you can actually set people free to innovate

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because you're confident that only the right people

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will see the right data for the right purpose.

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And that in turn enables our individual business units

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to build their own analytic

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and machine learning and AI capabilities,

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all operating off the same playbook

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and augmenting that with their own business unit data.

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Each individual team owns their data,

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makes it available through APIs,

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and understands who's allowed to use it.

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But we also have certain assets that are centralized

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to allow us to get that source of truth.

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And it's the combination of these

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with great governance in between

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and the ability to discover data

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that lives around the company in this distributed fashion

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that allows our teams to go fast

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and go independently while still being cohesive

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in terms of trying to achieve customer value

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and capturing some value for the company.

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<v ->What we've learned is that, in the end,</v>

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you would like to mirror this value creation,

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value capturing ID also within the tech stack.

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So our DDP actually recognizes what we call the layers.

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<v ->You know, the Layered Modular Architecture</v>

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is absolutely at the core of how we think about building

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and creating these interesting customer experiences.

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And so our Amazon business, for example, on Prime Day,

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can run trillions of transactions

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on some of the databases that we offer.

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And we don't need to know the details

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of what they're operating on,

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we really understand the APIs that they're interacting with

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and we focus on their availability and performance and SLEs.

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<v ->So we talk about multidisciplinary teams</v>

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organized in organizational platforms,

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mirrored to the business.

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How does that work within episode?

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<v ->We've had the concept of the two pizza team</v>

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for a long time.

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The idea comes from the fact that teams

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should be relatively small

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and so this allows them to be cohesive, to move fast,

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and then we imbue those teams

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with a very clear ownership mandate, so you own your area.

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You have to go to your customers,

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understand what they need, make sure you deliver it,

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and ask for the resources that you need to deliver that.

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<v ->In order to conclude, please give us</v>

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a snapshot on how you see Amazon and AWS evolving

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in the coming months and years.

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<v ->It's important to focus on things</v>

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that will stay the same.

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If you invest in those, you'll always be relevant.

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And so on our e-commerce business,

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we talk about the need for always having

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great selection, great prices.

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And on the AWS side, we really want to deliver

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top-notch security, operational performance,

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great value, and great price performance.

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I really am focused on helping our customers

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get value for their business

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from AI, machine learning, and data.

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And so it's really about finding a business outcome

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they're looking to drive, and then using AI and data

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as a force multiplier to achieve that outcome

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quickly and effectively.

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It's data that's gonna be the differentiator,

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and using ideas like DDP to connect that data

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into AI technology is the way we think customers

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are gonna be successful, and we're really focused on that.

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<v ->Very inspiring.</v>

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Thank you very much, Rahul.

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<v ->Thanks, great to be here.</v>

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(lively music)