Antoine Le Nel

I think, first of all, everyone thinks there was a huge amount of luck. I think the idea that what King did really well, I think they've tested extensively everything. So it was a volume game, you know, at some point. They understood that super quickly, saying, you need to try as much as you can. At some point, something will pick up. And I think they did that super, super, super well.

And I think then there was this super fast pace. I remember we were launching a game like every quarter, pretty much, we were launching a game. And not all of them were successful, but just like the pace at which we were producing games, releasing the games and so on. I think we did that super, super well.

And I think then there was this super fast pace. I remember we were launching a game like every quarter, pretty much, we were launching a game. And not all of them were successful, but just like the pace at which we were producing games, releasing the games and so on. I think we did that super, super well.

And I think then there was this super fast pace. I remember we were launching a game like every quarter, pretty much, we were launching a game. And not all of them were successful, but just like the pace at which we were producing games, releasing the games and so on. I think we did that super, super well.

The thing you have to get very good at, though, is cutting when you see the data isn't showing signs. How long is enough data or how much data is enough data to know that it wasn't working?

The thing you have to get very good at, though, is cutting when you see the data isn't showing signs. How long is enough data or how much data is enough data to know that it wasn't working?

The thing you have to get very good at, though, is cutting when you see the data isn't showing signs. How long is enough data or how much data is enough data to know that it wasn't working?

I think that's the thing that probably has changed over time at King. I think at the beginning, we were cutting things very quickly. As time went, we started to wait longer and longer. Oh, you know what? Give it another chance. Give it another chance. Give it another chance, you know?

I think that's the thing that probably has changed over time at King. I think at the beginning, we were cutting things very quickly. As time went, we started to wait longer and longer. Oh, you know what? Give it another chance. Give it another chance. Give it another chance, you know?

I think that's the thing that probably has changed over time at King. I think at the beginning, we were cutting things very quickly. As time went, we started to wait longer and longer. Oh, you know what? Give it another chance. Give it another chance. Give it another chance, you know?

That's the whole point on when and that's how you probably can measure the agility of the organization is how quickly you kill projects versus how many more chances you're giving to them.

That's the whole point on when and that's how you probably can measure the agility of the organization is how quickly you kill projects versus how many more chances you're giving to them.

That's the whole point on when and that's how you probably can measure the agility of the organization is how quickly you kill projects versus how many more chances you're giving to them.

So if testing and speed of iteration and testing was something that you did very well, what was something that King really messed up?

So if testing and speed of iteration and testing was something that you did very well, what was something that King really messed up?

So if testing and speed of iteration and testing was something that you did very well, what was something that King really messed up?

It's definitely the most data-driven organization I've ever been in, in the sense that really data was driving the organization. If you take the thing literally, the company was driven by data. I think it was so powerful that at some point we just went way too far in the sense that, for example, when we're launching games, sometimes we're probably looking more at the data than the game itself.

It's definitely the most data-driven organization I've ever been in, in the sense that really data was driving the organization. If you take the thing literally, the company was driven by data. I think it was so powerful that at some point we just went way too far in the sense that, for example, when we're launching games, sometimes we're probably looking more at the data than the game itself.

It's definitely the most data-driven organization I've ever been in, in the sense that really data was driving the organization. If you take the thing literally, the company was driven by data. I think it was so powerful that at some point we just went way too far in the sense that, for example, when we're launching games, sometimes we're probably looking more at the data than the game itself.

You know, it's like you're going to have meetings and then you just look at the numbers and you're like, is that wrong? That's the big difference, for example, with Revolut, I think. We're a lot more product-driven, which means we spend more time looking at the product than looking at the data. Is the data not an input? Exactly, it's an input. It is an input.