It’s the “biggest change we’ve seen in the last twenty years.”
That’s a quote from Dan Keyworth during his recent webinar with Alteryx.
He’s the Director of Business Technology for McLaren Racing. And he’s responsible for all the IT systems and tech for McLaren’s Formula One programs, plus the rules of entering e-sports and Extreme E as well.
So, when Formula 1 decided to change the style of cars used in racing, plus added new spending caps and technical regulations during a pandemic with supply chain issues, every decision he and the rest of the McLaren Racing team made came with added pressure.
Now, they have to rethink how they’ve done things, how they can make changes to their processes, and how they can do it quickly — while remaining competitive for 23 races.
All at a time when McLaren Racing’s fan base is growing.
And while Formula 1 racing may be different than selling financial packages or packaged goods, the challenges they faced and the solutions they devised to hit their goals are the same as almost any other company. And they do it taking a top-down approach.
1. McLaren Racing Focuses on the End Goal
For McLaren Racing, the end goal is easy — win.
Not just the next race, but the upcoming races, too.
Knowing their goal helps each part of their team understand what they need to focus on to improve as a whole. And that helps them understand what data to collect.
Every race weekend, McLaren Racing collects around “one and a half terabytes of data” from their car alone.
They have data for pit stops, driver health, car performance, and more.
But knowing their end goal helps them understand what data they’ll need to improve, and, because of that, the data they need to collect.
The Takeaway: Have a clear goal in mind for your business so that all teams and people understand what they need to do to help the company.
2. They Iterate
McLaren Racing uses a design loop to test out potential features and modifications to cars. Sometimes, the features they test won’t be used immediately, but rather further down the road.
In some cases, they use a “digital twin.”
Since they have a limited amount of time to run tests (especially one called a Computational Fluid Dynamics (CFD) test), they have to use the data to tell them what works and what doesn’t. When they have something that works, only then do they start ordering supplies and building the car.
With the supply issues affecting the world, and new spending caps for all teams in their sport, they have to be smart about what materials they order and how they use them.
Not only that, but with less money to hire additional support, they also have to use the data to identify the fastest way to bring items with limited supplies, plus high impact, to production.
The Takeaway: Use your data to guide your time-to-production process for each department.
3. They Adapt to the Data
During a race, McLaren Racing makes engineering changes to their cars every 14 minutes.
By the end of the season, their cars will have changed by nearly 80% from their original model.
It’s because McLaren Racing is always modifying things during the design loop and testing stages. They’re always working on something new to make the car faster and more efficient.
The product people see on TV is often the culmination of several rounds of testing. Features. Optimization. Parts. Design. All of the data is brought together and evaluated for the race.
They stream the data live from the cars and their engineers, who are also drivers, are constantly talking to the drivers about how they feel. They’ll ask questions about driving style, physical setup, the engine, and more.
The Takeaway: It’s okay to change based on what the data tells you, and it can even give you the advantage.
4. They Build a Community
Because everyone’s working towards the same goal, and they’re all using data to drive them, everyone needs to be on the same page with the data.
That means ensuring everyone can access the data they need. It means ensuring everyone can use the data and make sense of it. It means making sure everything is unified and cohesive.
For this, McLaren Racing uses analytics automation with Alteryx.
Their data science team, which often goes through 3,000 lines of code a day loves Alteryx. It gives them a way to speed up certain aspects of their process and then add Python and add-ons on top of it.
It’s also made it easier for the entire organization to get involved. They get people from the Alteryx partner ecosystem to help guide people on how to solve problems themselves in Alteryx.
The Takeaway: Remove data silos and other obstacles stopping your team from being on the same page, and empower them to contribute to the process
5. They Trust the Process
No matter how much data McLaren Racing has, they’re still a team made of people. People who operate on emotion the same way anyone does.
No matter what decisions you make, there’s always something you feel is right.
For McLaren Racing, which makes changes every 14 minutes, the decisions they make need to be fast, and right. Even small mistakes can cost them from making the podium or placing.
While it’s nice to slow down and make decisions, business doesn’t always afford you the luxury of time.
Instead, make the data the gold standard.
The Takeaway: As Keyworth says: “Trust the process, and the data will tell you the rest.”