Christian Klein: Yes. So Adam, thanks for the question. I mean to shed further light and give you better insights into the product and tech and the commercials on how we go to market. I mean, first, it’s very important to emphasize. I mean, we have today around about 300 AI use cases. And for example, take Lidl and Kaufland, they actually have massive demand forecast data, over 400 input levels going into the demand forecast. We are taking this data, petabytes of data and analyzing it to predict better demand. And now they can actually have optimized their inventory and their supply chain costs by over 10%, which is massive for a company of the size and scale of Kaufland and Lidl and this is here. And so now we have certain scenarios on cash flow automation and where we actually could actually improve the DSO by 10%.
We have many of these examples. Now with generative AI, and I think we really sit on a data of over 400,000 customers and the material flows, the financial flows, employee customer data. And now we are taking this data, not only with Signavio to benchmark and give business process recommendations. I mean we see it in the first prototypes that we are going to be able to not only that the system can self-learn on this data on how to improve all these workflows. No, no, no, the systems itself will also drive further automation of workflows going forward. They can look into the customization of an ERP, which is huge in on-prem. They can help customers to generate code on the platform to build differentiating capabilities to fasten the time to value.
And last but not least, I just did something yesterday where we said, “Hey, when I have a skill gap here in my company and that in that space, from where did I hire the best skills in the past, in which country, from which university, and the system gives you unbelievable smart recommendations. And this is something what SAP can do. And this is where we’re going to launch further generative AI use cases. They will come with a 30% premium because we believe in the immense value and we see how customers respond to that. And we are going to embed that in every RISE, in every GROW, in every LoB deal going forward. This will not be like, okay, here’s our generative AI portfolio. No, no, this will be embedded because there, we also believe that our sales team and our partners can sell it best when it comes integrated with our application portfolio.
Operator: [Operator Instructions]. And the next question is from the line of Michael J. Briest with UBS Limited.
Michael Briest: Just on the cash flow, actually, Dominik. I noticed that you cut your CapEx outlook for the year by about €50 million. And obviously, you’ve raised the profit target by €50 million, less the free cash flow goal for the year unchanged. It still feels like free cash flow is part of the business that needs maybe more work than other parts. What are you actually doing to improve it? And how linear should we think about the progression to the €7.5 billion in 2025 to be?
Dominik Asam: I mean the key levers on free cash flow are quite obviously, on the profit side first and then the working capital. And of course, also the CapEx and leasing part of it, which should be kept as low as possible. We are, as we speak, starting to initiate pressure on these metrices to improve the cash conversion. I think for the current fiscal year, and we are on a good trajectory. If you just look at the phasing of H1 versus H2, as we’ve seen in prior year, you take that kind of receivable sale into account that kind of at the year-end last year into H1, Q1 to be precise. And this year, you see that we’re actually a little bit ahead of that kind of completion rate. So for this year, we’re fine now. How linear or not, that will be through 2025.
