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<v ->Hi, Ronald.</v>

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Well, thank you very much

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for having us in this beautiful building at Heineken

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and thanks for

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sharing some perspective on Heineken's data and AI journey.

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First, for the very few who don't know Heineken,

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can you tell us a little bit about the company's history?

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<v ->We are a 160-year-old startup,</v>

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still family-controlled, so a proud and independent brewer,

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and I think everybody will know us for the Heineken brand,

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but actually we have over 400 brands

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that we sell in pretty much every country in the world.

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<v ->Why is data</v>

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and AI critical for a consumer goods company like Heineken?

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<v ->I think every CPG has always tried to find the balance</v>

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between experience, a bit of intuition,

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and a bit of market data to take the right decisions.

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But the amount of data nowadays available is just crazy.

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I think it was 2001,

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over 20 years ago, when the word "big data" was

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invented by Garner.

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But the real explosion of data, at least

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for a company like Heineken, came maybe in the last

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decade, last five years.

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And not only when large companies start to do ERP

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with internal data, but with IoT connecting,

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getting data from cash registers,

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getting data from our fridges in the marketplace.

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We have almost 200 billion data elements streaming out

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of our manufacturing footprint,

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out of machines into our own cloud.

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So there's so much data available,

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and now with AI, it is not just data;

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we can create actionable insights.

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<v ->Can you tell us a little bit more about that journey,</v>

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but also about where you have seen the most

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value-creating opportunities?

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<v ->We have a very, very fragmented tech landscape</v>

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still, ripping out an old landscape and replacing it,

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but that takes, well, six, seven, eight years,

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and we do not have the time.

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So we try to find a way to accelerate,

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to fast-track data and AI.

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And the second thing is, it's also about prioritization.

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You need to be deliberate.

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We did a ton of experimentation

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and also with help from BCG, but let's prioritize

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where the key value buckets and where can we scale?

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So what are the five, six big things that we now do

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that we really try to drive hard across Heineken?

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<v ->What would be the top things where you've seen</v>

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disproportionate value creation?

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<v ->Where we see the biggest opportunity</v>

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and that we are pursuing hard is one,

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around revenue management.

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So things like promo AI, how do you optimize your promos,

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get better return on investments,

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and where do you invest?

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Number two for us, very important, is marketing mix,

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actually commercial mix optimization.

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So we spend billions, as you can imagine,

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on all our beautiful brands, which is super complex.

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There's a lot of touch points, a lot of brands,

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a lot of regions or provinces.

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The third big one is around sales execution.

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That is from promo recommendation to routing

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and scripting of our sales reps, helping them

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to have good conversations online and offline.

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And of course also big is manufacturing.

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It is how we optimize machines and packaging lines

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and even complete brewers.

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And that's logical, right?

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It is around sales, it's around marketing,

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it's around revenue, it's around manufacturing.

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That's also where a lot

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of companies have their biggest cost base or revenue base.

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<v ->With generative AI, there's been a very, very big wave</v>

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of interest, investments, a new wave of experimentation.

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What do you see in the let's say medium term

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of your journey when it comes to AI?

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<v ->For us, the Holy Grail will be also</v>

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in the creative side of things.

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The brand building, even films,

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digital assets online, going from maybe 50 assets

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that we can bring today to life on Formula One

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in a weekend to thousands.

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At the same time, I really see a big step

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where GenAI will drive change.

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(bright music)