Freshworks Refresh 2025 | Dan Keyworth, McLaren Racing

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Dan Keyworth

Director, Business Technology

McLaren Racing

play_circle_outline Dan Keyworth's role as director of Business Technology at McLaren Racing.

play_circle_outline Maximizing Performance: The Vital Role of Real-Time Data and Technology in Formula One Racing

play_circle_outline Adapting to Technology: How F1 Teams Evolve Cars and Collaborate for Competitive Success in Racing

play_circle_outline Emphasis on organizational learning from successes and failures in Formula One.

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Dan Keyworth, McLaren Racing

Dan Keyworth

Director, Business Technology McLaren Racing

In this interview from Freshworks Refresh 2025 at Oracle Park, McLaren Racing’s director of business technology, Dan Keyworth, joins theCUBE’s Bob Laliberte to unpack how Formula 1 operates as one of the most technologically advanced sports on the planet. Keyworth explains how his team supports 1,400 people across McLaren Racing, turning real-time data from 150 sensors on the car, CFD-driven digital twins, wind tunnel testing and driver simulators for Lando and Oscar into a continuous feedback loop that delivers engineering changes every 15 minutes and keeps ... Read more

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Dan Keyworth, McLaren Racing

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Bob Laliberte

>> Hello everyone. We're here at Oracle Park in San Francisco for the Freshworks Refresh 25 Event, and I'm very fortunate to be joined by Dan Keyworth, who is the director of Business Technology at McLaren Racing. Welcome, Dan.

Dan Keyworth

>> Oh, thanks for having me, Bob.

Bob Laliberte

>> Yeah, so great event. First things first, you're the director of business technology. What does that mean? What are your roles and responsibilities at McLaren Racing?

Dan Keyworth

>> Well, Formula One has a huge amount of technology that goes into it. I'm responsible for the things that help us do the sharp end of racing. So, everything that you see on a race weekend in the garage, all the way back to how we actually go and design the car, build it, and then take it racing from the factory as well. There's 1400 people across McLaren and we're trying to give them all of the technology capabilities so they can unlock performance, unleash performance onto our race car. So, yeah, everything from the technical side and the racing side of the sport, but also the back office as well, right? We have a people department, we have finance, we have a big commercial department as well. We're a huge commercial engine and all of that demands a huge amount of technology and luckily, I'm responsible for all of it.

Bob Laliberte

>> Excellent. Now it sounds like certainly keeping you busy.

Dan Keyworth

>> Yeah, always.

Bob Laliberte

>> Now, one of the things I wanted to lean into and find out more about is how it contributes to McLaren's success in its continued high performance. I mean, I know I've heard stories, something like 10,000 data points a second coming off of these cars. So, technology is hugely important to be successful, to be able to optimize. What are you doing from an IT perspective to help drive that consistent performance?

Dan Keyworth

>> Yeah, well look, I know we're at a baseball stadium today, but I would argue that Formula One is the most technologically advanced sport on the planet. We're dealing with a huge amount of information all the time. Like you say, we've got 150 sensors on the Formula One car, and that's pulling information in real time, and that allows our engineers in the garage to make real time decisions, but also we collect that data and do lots of really clever stuff with it in order to inform the design life cycle of the car as well, right? We're always developing and unlocking this product that is an F1 car. You probably argue actually we like this rapid prototype, like small medium business. Forget the Formula One side of it. Actually, we're constantly evolving and developing a product to go faster. We say that if you win the first race in Bahrain and you do nothing to your car, you actually come last at the end of the season. That is the relentless innovation and there is a level of gut and intuition that goes into this sport, but data is absolutely everything. And we want people to be not drowning in data, but swimming quite comfortably in it. And all the technology that we give to our 1400 people across the team is in order to go, how do we find those extra milliseconds? How do we move the dial in terms of performance all the time? And whether that's our surface in the information to say, here's an opportunity for improvement, go get it, or giving them the bigger picture that perhaps they wouldn't see in their own isolated area. So, yeah, it plays a huge part and obviously, IT is under the surface of all of that. There's no denying we put ourselves right in the center of the team. We don't service the race team from a distance. We are there shoulder to shoulder all the time, and it plays a hugely strategic importance for our team.

Bob Laliberte

>> Yeah, I like that analogy of, "Hey, if you win the first race and do nothing, you'll come in last." So, you're always evolving. So, it's really about getting the right data at the right time for the right use, either on race day or for tuning the cars prior to race day.

Dan Keyworth

>> Exactly, yeah. We make an engineering change every 15 minutes, so we're constantly tweaking and evolving. We do something at the top end of the design of a car called CFD, which means computational fluid dynamics is a bit of a mouthful, but what that is, is a full digital twin of the Formula One car. And what that allows an aerodynamicist to do is make small tweaks of the front wing to the bodywork, whatever it might be, to see what the flow, how it may change, and how it may evolve through physics. And of course, that's always informative. We look at that data as soon as we do a run and then we go, "Ah, what other little tweak and change do I need to make it better or make it perform in a slightly different way?" This is the closed loop situation that we're getting all the time. We also have a physical wind tunnel, so we put a 60% version of the Formula One car into a wind tunnel, and that's the first physical reference point we get of the car. And of course, we want to correlate that data with CFD and everything else. And then also for Lando and Oscar, we give them a digital representation in the driver simulator. So, even before we go to the race, we set them up in a way that feels like the car they're going to drive on the race weekend, and that's the first time you actually get the human in the loop element, which is the driver feedback. So, the car could be super fast, but the driver might not feel like it's comfortable to drive. So, these again, are another data point that we're just continually helping to evolve and develop our race cars.

Bob Laliberte

>> Yeah, it's certainly fascinating the amount of technology that you used today to be successful in a sport F1, which you said is probably one of the most technology-advanced sports out there right now, certainly from that data collection and refinement and constant tweaking, so that's fantastic. Now, we're here at Freshworks Refresh, so I assume that's for a reason.

Dan Keyworth

>> Yeah. Of course.

Bob Laliberte

>> You've implemented Freshworks for your race operations. I'm wondering if you can maybe give an example of how Freshworks has enabled your organization to stay up and running on a race day when you're trying to make decisions and make tweaks to a car that's going 200 miles an hour plus.

Dan Keyworth

>> And I think the reason we went with Freshworks is really the simplicity offers our organization. We're trying to move at such a pace. We are looking for frictionless services that we can offer to people. The strap line this week is uncomplicate, and that's definitely done that for us, including the time to get up and running when we became before we become partners. This is as we became a customer. We're doing a number of things in the race operation space, everything from proactivity. So, this is how do we trigger custom workflows to do all the things that really matter to ensure that we offer reliability to our racing team. We have this saying the car never stops on track, yeah, and that is across everything that we do. It's not just a mechanic in the garage going, the car's got to be set up in the right way and we need to make sure it's mechanically sound. Everybody has an input into the way that we go racing. So, we're using Freshworks in a way that allows us to proactively get ahead of the race weekend before we call comms check, which is when everything gets locked in and we're ready to go racing. Yeah. So, we're doing all of that in the factory equally, and anyone that works in IT knows that you don't always have a perfect weekend, right?

Bob Laliberte

>> Right.

Dan Keyworth

>> There's always problems that you're either trying to proactively manage or put control around. We talk about containment, which is how do you contain a situation? How do you make sure that you can continue to move forward? So, we're always doing that in real time, and we've created a common way of working across our software teams, across our IT support teams, whether it be track or factory, all to use the same input and workflow for pure efficiency on a race weekend. So, anytime we see an issue, it goes through the same channel, it gets routed to the right person, and we respond before we even see it-

Bob Laliberte

>> Got it....

Dan Keyworth

>> manifest itself as a fundamental problem with the race car.

Bob Laliberte

>> Yeah. And that's hugely important all the time, but especially on a race day, you need to be able to have that proactive support to be able to fix problems before they cause any kind of an outage, which could be disastrous on a race day.

Dan Keyworth

>> Yeah, absolutely. Yeah.

Bob Laliberte

>> Absolutely. So, I know you brought up the uncomplicated piece, which I think is super important because things while not trying to become complicated, just become complicated.

Dan Keyworth

>> Sure.

Bob Laliberte

>> That's probably driven even more so when you've got distributed environments and if you think about a distributed environment, yours is not only distributed, it's also temporal in that you don't have fixed locations distributed around the globe. You've got locations that you go to and then leave, and you're not back there for another year or so. So, obviously that's obviously going to increase the complexity in an organization. So, I'm wondering how do you maintain your IT consistency and reliability when you're trying to deliver services across the globe on temporary basis?

Dan Keyworth

>> Yeah, look, you're right. I think it's a tough thing to do in the first place. And we acknowledge that Formula One is a tough sport and everything that comes with it has a level of toughness as well. The main thing for us, it's all about repeatability, consistency. Something can appear complex in nature, but if you apply simplicity to it, actually you remove the complexity from it, if that makes sense. We go to 24 races a year. We've got 150 people on the road at any one time that we've got to make sure that we're supporting. We have six sets of our garage that we're setting up at any one time. So, my team will fly ahead to the next race and they'll set the garage up from scratch. So, run three and a half kilometers of cabling, create all the desks, all the infrastructure, all the setup, and that allows the team, we take the stress out of it for the Formula One team, so they can really focus on what matters to them, which is going racing. So, if you fly from, let's say, Austin to Mexico, your desk looks exactly the same. Yeah. So, although under the surface what we're doing has some complexity, like we're trying to make it simple for the people that are interacting with it. And the other thing that we always say is like, we, the winner race, yeah, we don't lose, we learn. So, this evolving learning and the evolution of learning is really important to the sport. Because when you work in something that can present so much uncertainty, you want to make sure that you don't apply a loser's mindset every time something goes wrong. You go, "What's the thing that we need to learn from and continually evolve?" And that includes across the IT space, spotting key trends, doing problem management, all the things that are quite traditional in an IT sense, but doing that with real purpose and efficiency to make sure that ultimately we can put two cars on track, we can finish the race and hopefully be on the stand of the podium.

Bob Laliberte

>> Got it, got it. Awesome. So, I mean, really what you're trying to do is make sure you're simplifying your operations as much as you can-

Dan Keyworth

>> Absolutely....

Bob Laliberte

>> in these highly distributed environments. That makes a lot of sense. We can't have a conversation without talking about AI and automation these days. It's ever present. It's really transforming organizations. I'm wondering if you could touch upon how AI is changing, how the work that you're doing at McLaren and the race days, the decision making for your team. Is it all still human interaction looking and interpreting the data, or is AI playing a role both track side and at the factory?

Dan Keyworth

>> Well, look, it's definitely as similar to the race car and the driver. It's this interaction between human and machine and AI is the same in terms of the topic for the last decade, we've been doing what I'd call traditional machine learning neural networks. And of course that generates a huge amount of proprietary information that is important to going racing your car within your team. What we're feeling with the rise of large language models in agentic is actually the barrier of entry to get to that information is far lower than it ever was. And you can now create the AI native citizen developers that can then go, "Hey, this information has existed and we've got this rich, rich source of information. But how do you go and ask in natural language questions? Show me a lap of Q3 in Belgium between Lando and Oscar, and a graph just appears with you with that exact data point." If you go back a few years, it's like, well, the model exists and the output exists, but you've now got to go wrangle that information into a format that makes sense to you. The speed to value is just increasing massively.

Bob Laliberte

>> Got it.

Dan Keyworth

>> We see AI as probably it's another opinion, it's another voice in the room. You still have the human in the loop and the driver intuition. It's still a reference point, it's a data point, but then you've also got the AI model that's saying there is an X probability that this is what's happening right now and this is probably the decision you need to make and therefore, you've got to go and say, "Well, that's grounded in data, and our sport has been predicated in that that and therefore, there's a level of trust that you've got to put in the information."

Bob Laliberte

>> Yeah, no, I think that's hugely important. I know when I talk to a lot of the tech organizations, I like to refer to it as the time to comfort with that technology. There's usually that timeframe when the AI first gives it, and it's like the human doesn't trust it and has to go validate it manually and so forth. But again, over a certain period of time that builds that trust that you talked about, right? They validate that what the AI is telling you is actually helping you and delivering value.

Dan Keyworth

>> Yeah. And we've learned that over the course of time, like trust is everything. We work in a sport of trust. We've got two very talented drivers, but they have to trust the voice in their ear, which is their engineer. And that is a relationship that has been built up over time. And therefore it's the same with anything that we do, whether it's tools, software, any kind of AI models that we are deploying across our organization. All of that takes time to adopt. All that takes time to build a level of trust, and then you realize where its sweet spot is and how it can deliver performance to your organization.

Bob Laliberte

>> Got it, got it. Now, I know next on the agenda is Las Vegas for you guys.

Dan Keyworth

>> Yes.

Bob Laliberte

>> But I'm wondering what's next on the agenda for you with Freshworks? I know they had a number of announcements here, a lot of AI, some vertical agents, things like that. What's been of interest to you? What are you thinking about what will be next for you with Freshworks?

Dan Keyworth

>> Yeah. Well, look, I think this whole giving your team time back to be more creative and add value in other areas, we want to make sure people are bringing every millisecond to the car. I think we were on an early adoption phase of Freddy AI and we've seen some huge amount of benefits from that. And these are now the next evolution of capability. Some which I feel that we've probably inputted into throughout our feedback, through our customer success loop. So, I feel that certainly anything that is repeatable and requires automatic routing to certain teams. I love the new vision technology around things like screenshots and how it interprets. All of these things, they move the dial. We always say, if you are standing still, you're actually going backwards. So, as we evolve our products, it's great to see Freshworks evolving their product. I think they've announced some incredible capabilities today, not only as a partner, but as a customer. Of course, we want to get our hands on it and start getting the value from it.

Bob Laliberte

>> Excellent. Well, I look forward to talking to you again and hearing how all that's working out for you and to everyone else that's out there watching. Thank you for joining us. Again, we're here at Freshworks Refresh 2025 at Oracle Park in San Francisco. I'm here with Dan from McLaren. Thank you so much for joining me.

Dan Keyworth

>> Thanks for having me.

Bob Laliberte

>> All right, have a great day.