McLaren’s drive with data
In case you’re not familiar with McLaren, it’s a Formula 1 racing company based in Britain that has won 183 races, 12 drivers’ championships, and eight Constructors’ Championships.
I’ve always been fascinated with tech in sports and when I was researching what to write, this synergy caught my attention and I knew this blog was going to be about it …
So here it is!
Firstly, what’s up with data and F1?
There aren't many sports that use technology, but Formula One is one of them. On average, F1 races last about two hours and within this time, it captures billions of data points in the sensors installed in the cars. The key to winning the race is to be faster than everybody else but it’s just not dependent on the driver’s super instincts but many car characteristics like top speed, gear shifts, no. of components, and air drag. All this is recorded by ECU (Electronic Control Units) which then sends this massive volume of live data from all sensors converted into a signal via a data server system called ATLAS (Advanced Telemetry Linked Acquisition System) built by McLaren to a team of engineers and data analysts. They analyse the data in real-time and ensure everything is working fine under the hood and communicate the same to the on-track crew who are in constant touch with the driver.
The interesting thing is earlier, the data team could also tweak the car configuration from their place itself but this two-way telemetry got banned by F1 in 2003
How does McLaren make use of analytics?
McLaren recently partnered with Alteryx, a company which builds data science and analytics products to help them in various ways of managing data and more importantly getting insights out of them. Let’s see a few areas where it’s being used.
- Data Management
Every stakeholder in the company wants to slice and dice the data as per their use and hence it must be stored and managed in a way which makes this process easier. This is one area where they’re using the software — Alteryx helping them combine many sets of data sources for pre-and post-race analysis, along with back-office operational data. Its key strength is in collecting and connecting data sources, as well as allowing multiple sub-teams to modify and tune the results as needed.
- Cost Analysis
One of the first applications of Alteryx was to determine the manufacturing cost of the car, as Formula One now has a $175 million cost cap on each race to keep the playing field level for all teams. This makes understanding the cost structure of the car difficult as it involves several suppliers and proper part ordering is critical for delivering any updates to the circuit at the correct time.
Now with manufacturing, engineering and finance in one place in the software, data can be manipulated making it easier to find the cost of the car.
- Race Analysis
As we learned about the real-time analysis above, the in-depth analysis starts after the race. It involves matching the performance of the car with the simulator to check correlation and find what went wrong, and what can be improved in the performance and thus set up the expectations for the next race. It also involves post-race analysis of competitors to see how they performed during the race and assess if they would have made the same decision
Well, now you see the race is off-track as well. The way teams use data to make choices might mean the difference between winning and losing a race. From predicting when to conduct pit stops to calculating fuel burn and engine health, analytics appears to be the key to victory.
If you enjoyed reading this, I highly recommend watching this video on telemetry in Formula 1.
