Automated Transcript
Excellent, Bernie, thank you for joining us. I hope you’ve enjoyed the experience. How did you find it?
Yeah, it was good. It was really engaging. I think it’s good to speak to a room with some of the lessons that we have from F1 and try to bring little bits that they can learn or implement, or start to think about in day-to-day life or work.
You unpacked so much in your presentation. If we just shine the light in maybe one area, what would you say is the biggest thing from F1 that transfers into the world of business? What can we learn from it?
I think the biggest thing that most businesses can learn is the analysis. If you can analyze the wins and the failures, analyze what went wrong the last time, analyze your competitors, whatever the case may be, what can you improve? If something’s gone wrong, what procedure can you change? What piece of software can you implement? What change needs to be done to make that better the next time?
You mentioned something really interesting that I missed really came over in your presentation. It almost feels like an over-analysis, but the amount of time it seems that F1 and the teams spend is disproportionately analyzing failure. It’s something I don’t think we do enough of in the real world. How would you get good at that?
I think it is just about perseverance. In F1, in many ways, it’s easier because post-race we have this gap almost satisfied that we can go through what happened the week before. You can’t fail again and again and again, nor can business. You have to improve. You have to get better because your next task is next week. So the quicker you can analyze those things, the better. It is about getting every department, every group, every little team to do their own bit of analysis on their own performance. If you’ve got a good enough team, that’s how you should get the best answers to that analysis. That’s how that team will learn and grow the most.
It feels like being great in the moment is a large part of what distinguishes between success and failure in F1.
Yes, and again, harking back to the analysis, because I’ve spent so much time going through what’s gone wrong in the past, what’s gone right in the past, why certain things have worked or not worked, you’ve got that inbuilt knowledge of what potentially could happen. That’s one aspect that makes those decisions easier. The preparation is everything. We spend a lot of time in the run-up to our decision or our incident, thinking about what would happen if. Although you’ve got a short period of time to make the final decision, you have done at least some of the conversation in advance of that decision. That may feel like a lot of wasted preparation for a lot of people, but that means that when you’re making that final decision, you feel like you’re making it from a position of knowledge rather than just guesswork.
When you actually think about some of the things you’re talking about in terms of marginal gains and what feels like just a plethora of data, could you bring to life exactly how much data you collect in a race weekend and how you sift through that data to find those insights?
I think the difficulty with the data we collect in a race or in any track running is that it’s always imperfect. There are so many more variables. You can never do a straight AaBb task; that just doesn’t exist, particularly in the real world for us, because so much of the environment is changing. A lot of what F1 relies heavily on is being fit to database about data in a good enough way that you can align what’s happening at individual times. You’re not just looking at the difference in lap time; you’re looking at that with all of the other scope in the background. I don’t have the exact number for how many sensors on the car, how much data we collect, but it’s huge. The time you could spend looking at the data far outweighs the time in the session. One of the most difficult things we have is between, let’s say, a P1 and P2. There are only 3 to 4 hours, and that’s not enough time to fully go through all of that. Some of the data sources we have, we have automated ways of, you know, alerts when the temperature is too high or pressures too high. We’ve got people looking at those sorts of things live, and we’ve got certain algorithms we can run to check for anomalies and that sort of thing. But ultimately, it comes down to being very regimented and not looking at one piece of data, one test very isolated from the rest of the system.
When you collect that data and present it, we know one of our key partners is AWS. We do a huge amount of work on unlocking the power of that connect platform, engaging customer experience, and so on. How does that platform come into play in the world of F1?
I think the biggest thing we have is having all of our data accessible easily in a very well-documented way, so that you’re not having to dig to find the answer. The answer is there, available for you, nicely marked up and aligned in a very neat way. That’s very powerful, because as soon as you really need to dig into it to find the piece of data you’re looking for, people will naturally become lazy and not look for that missing piece of information. So it is about having the catalog of data there, available in a very nicely cataloged way.
We’ve talked a little bit about AI and machine learning, which you would clearly expect us to do here today. What does the future look like for those new technologies within F1?
Versions of AI and machine learning, in particular, have been used in F1 for quite a while. From a strategy point of view, we use machine learning. When we look at a strategy on a Friday or Saturday night, we try and predict what we think others may do in certain situations. A lot of that has happened. We also use massive simulations to try and come up with the correct car setup because there are so many variables and where you can go as you’re trying to find the local optimum. The big step forward, I think for me, in AI is going to come when, as a strategist, the game is playing back. You can ask for your move, and it’s going to predict in an intelligent way the moves of others in terms of predicting what the drivers are likely to do. Prediction teams won’t do the correct thing or the most obvious thing but will do something slightly different based on who their strategist is on the pit wall or based on recent analysis of what they’ve done. So to have that proper, you know, chess-style computer game, it’s going to be really interesting from one side.
One of the scenarios earlier, I mentioned the whole concept of saying it’s important to be a geek. It’s important, especially in our industry, to look forward to what’s coming next. The one superpower or skill that you felt was really important was that of curiosity and always remaining curious. Does that resonate with you and why?
100%. For us, we never look at a race and think there’s nothing that could have been done better. We’re always looking at decisions others made, why they made decisions. We’re almost paranoid that they know something or are doing something better than we are doing. So we spend a lot of our time investigating someone not doing something much different from us, but in many ways coming up with what our you know, if we could get it to work like this, what would that look like? I seem to spend most of my F1 life writing lists of things I would like to do if I had more time. Be that a piece of software, a tool, a database, some investigation into how temperatures affect wet weather times, whatever the case may be, I seem to have loads of lists of what the next investigation would be, and you need to keep driving that because it keeps your people interested, they’re working on something new, and it will push the whole team forward.
Being good together is something that’s massively important to us, and it’s really our North Star. What we mean by that is being good together with our customers, but also our internal customers as well. When we think about how we come together as teams and stuff like that, it just feels like that really resonates as well in the world of F1, especially when you think about that world record pit stop. You wouldn’t have done that unless you’ve been good together. What do you think are the key ingredients of being good together?
There are a few things that go into that. We’re forced to be good together. We’re spending 23, 24 races together. So you need to get along. But, in the heated comms on the pit wall, communication is key and often difficult because you’ve got multiple languages going on. You’ve got multiple preconceptions of what might happen. It is about having everyone pretty aligned and open to the opinions of others. One of the things is trusting your experts. If you have someone who is an expert in their field, there’s a voice at your side. Chide the leaders regardless of their hierarchy or seniority in the team, and it is about trying to bring all those ideas together. Comms is so crucial. And then I think one of the biggest is reviewing it honestly. There have been times that I’ve gone through radio comms, I’ve sat and others and realized, oh, it didn’t, I wasn’t quite strong enough in that, or I didn’t quite say whatever it was, the way I meant to, or I can understand how that was misunderstood. How many people look at their Zoom meetings then go, oh, I mean, we should have said that a little bit differently. That’s effectively what we’re doing in F1.
My last question. As part of our new brand image, part of reminding us how good together piece, we have a new family member, and it’s a purple dog. We’re running a competition to name it. So I’m going to ask you what your contribution is to it. What would you name the gamma purple dog?
It’s going to be really off-piste, and I can give the reason for it. I would name it Dave. It was recently we took on, we’ve been fostering guide dogs. And we had a black guide dog called Dave. There is nothing funnier than running through the park going, Dave. There’s this really normal name. So I would name him something like that.
Well, there you go, Dave is the name of the dog. So look, I think he’s just to say thank you very much. We’ve loved having you with us here today. We wish you all the best. Good luck with the book launch. We’re looking forward to getting that in the hands of our customers. And you’re welcome in the gamma family any time. Thank you very much for being with us.
Thank you very much for having us. I look forward to meeting Dave.
