Mike Hudack
speaker
274 appearances
2 recordings
2 series
first heard Sep 2024
last heard Dec 2024
Mike Hudack’s voice in public audio — every appearance, attributed to the second.
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Appearances
Yeah. Yeah. There's always an event. There's always a thing. You know, you're constantly modulating the rate that you pay riders in order to ensure that enough show up to meet the demand, you know, the demand spike that you're anticipating.
It turned out to be really easy because when I got there, again, this is a difficult, you know, in this kind of form, I need to be careful about the way that I tell these stories. But it was Uber Eats was in London and Paris and a bunch of other places. And it was a knife fight in the streets. You know, I mean, it was crazy. It was deeply competitive. There was a fight over.
Well, everything, restaurants, riders, customers. And we were not meeting our brand promise. So Deliveroo's brand promise is great food delivered to you quickly. It's delicious, right? It's like high quality restaurant food. And man, we were late 40% of the time. We were opening our demand modulation tool.
So, you know, if you think about the way that you might in a system like that have orders be on time and fulfill your brand promise, there are all sorts of different ways that you can do it. But the way that we were doing it at the time was opening and closing zones in order to control demand. So, you know, if we were too busy, we would close for orders in SKC, South Kensington, Chelsea, right?
And there was actually a team of about a dozen people in a literally windowless room clicking buttons to open and close zones manually. And they were going to jump out a window. They didn't have a window to jump out of because there were no windows in the room they worked in. But if there were a window... They would have gone through it. And customers were pissed off. It was a rough time.
Did you see churn when they were pissed off?
Well, over time, I think we learned a lot about the importance of selection and all sorts of things. And I think Deliveroo Plus really influenced people's behavior in a really dramatic way, where people feel a loyalty and affinity, a sunk cost with the platform, which brings them back. It was a very... unbelievably important product.
But yeah, you know, it was also the first time that there was an alternative in the market. And so the combination of those things was brutal. How important was exclusivity to winning on the supply side of restaurants? You know, I think we thought it was very important.
But to get back to the question of like figuring out what to build there and how product is different, you know, you land in that kind of a situation and you're like, holy shit, like... You know, we need to fix this problem. We need to be able to modulate demand properly. We need to be able to make a promise to the customer which we can actually fulfill.
And at the time, the logistics algorithm was very, very, very simple. We had an amazing data scientist, a neuroscientist who knew how to build a great delivery algorithm, but we didn't have it. And so the first thing we did was just open up a war room.
We had an apartment across the street from the office, and we moved about 10 engineers into that apartment and had them sit down and spend two or three days trying to figure out the highest leverage way to start actually delivering on our brand promise properly.
And the first thing that they did was they built a lateness model, a machine learning model, to correctly estimate how late we were going to be. The theory being that we could then accurately tell people how long their order was going to take, and they could make a decision as to whether or not to place the order, and they wouldn't be pissed at us.
We would say, instead of saying, oh, it's going to be 15 minutes, we'd say, oh, accurately, it's going to be 45. And then we would deliver within the 45 minutes, and they would be happy customers instead of us having said it was 15 minutes. Still delivering 45, they're pissed off.
And so that team just built a very simple kind of regression model to estimate lateness, and that dramatically improved lates very quickly. And most of the work in Deliveroo for a really long time was actually in what we called the delivery organization. We created an organization called Delivery,
And that was core machine learning systems, dispatch systems, rider pay, rider app, all that kind of stuff. And that was, I think, far more important than the consumer app or the restaurant order manager or anything like that. What was the best product decision you made at delivery?
My favorite was I went on a trip to Spain at some point with a bunch of people from the team and we went there and we really learned the importance of selection. We went to Madrid and Madrid is a very long city and there's one, there's one five guys on one end.
And it turns out that people who live on the other end, the way that we designed our system originally, it would dispatch on kind of a neighborhood basis. And so, you know, you probably experience this living in London ordering delivery. You're like, well, why can't I order from this restaurant, which is like three blocks away? Because it's in another zone.
And, you know, that was kind of optimal for London, which is a city or we thought it was optimal for London, which is a city of residential neighborhoods arranged around high streets. And the restaurant is on the high street. You know, Madrid is very different than that. It kind of has like a central business district and there's like a restaurants and then residential that goes out much further.
It turns out that the people in the outskirts of the residential area still want five guys and they actually will tolerate a longer trip and understand that it'll be a little bit soggy and a little bit cold when it arrives because they just want their like bacon, onion cheeseburger. Right.
And we had this like deep seated assumption that, you know, we should only deliver food as far and as long as it is still what we would consider to be high quality. And after a couple of days there with the local team, we realized how wrong we were. And I remember spending the entire trip back, getting to the airport and sitting in a chair by the gate, putting on headphones and writing.
Showing 161–180 of 274 · page 9 of 14
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