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How Alpine's CIO integrated Data Science into the F1 racing team

Data Science
Akin to the famous Plato’s saying "art imitates life," modern automobiles imitate computers. This saying perfectly fits into describing the Formula 1 race cars, which stand as a testament to humans' unimaginable inventions in speed and technology.
How Alpine's CIO integrated Data Science into the F1 racing team

F1 teams regularly rely on collaborations with technology providers to obtain an advantage on the track by using computing, machine learning, and high-performance stats. Many other sports like cricket and football have also greatly benefited from incorporating similar technological studies (pitch analysis, player stats, weather forecasts, etc). Multiple technological applications like this are very valuable for service providers who invent and revolutionize data-based technologies.

F1 is a game of mastery, diligence, shrewdness, patience, and precision. Furthermore, it is a game of many complications and huge financial requirements, and it is largely beloved by fans across the world. While dealing with sports like F1, it is difficult to perfectly estimate the importance of technology. Technology plays an integral role in Formula 1, even at the grassroot level. Each F1 car has 200 sensors, which together produce 1.1 million telemetry data points per second that are relayed to the pits. For example, the F1 Media and Technology Center in Biggin Hill, England, and their race track exchange 160 gigabytes of data each weekend. These massive transactions of data from machines to systems promote the sport with better efficiency. However, it is imperative to understand that each time technology is used in F1, it's Data Science that’s doing the job.

Nathan Sykes, the renowned CIO and Data Science director of mid-field team Alpine also, the F1 renegade, presented the prospect of achieving greater ROI from Data Science with effective track performance. Sykes’s perception of justifying the budget is proportional to the performance and quality of the race. Not just as a professional but also as an ardent fan, Natan Sykes paved the way where Data Science meets the automobile beasts, putting them on track for more entertainment and revenue.

Here’s how the Alpines' CIO integrated Data Science into the F1 racing team to get the best sports experience and profitable business.

IT as the new business system:

IT was always determined to contribute to the building of the business, but it just wasn’t happening. Over the course of 16 years at Renault Sports Racing, Nathan Sykes dealt with many ambitious projects that would pioneer things in the F1 system. However, every time he found a way, a new problem would emerge, thwarting the process of building something profitable. The process would incur huge investments that would go in vain, depriving the data team of resources. Also, while he was leading, data was deemed a back office function.

"Businesses never gave us a specific goal to focus on, in order to contribute to their work. The process was in the blind, teams didn’t know when and where to contribute. As a result, despite their best efforts, IT departments and professions struggled to make a difference," said Nathan Sykes. These concurrent impediments made Nathan Sykes take the big leap, i.e. change the work module and culture into a much more collaborative space where different departments come together to maintain synergy.

Through this optimal inculcation of the new culture, Nathan Sykes managed to grasp the full attention of business to bring IT to the frontline to create a more data-driven and defined environment. He introduced the practice of owning the work. Furthermore, he wireframed the process of securing, analyzing, and discerning potential questions before the IT field started developing anything. This way, there would be no space for errors or inventions that contribute to nothing.

Using technology to the fullest: Racing simulation, better production, disaster management, and racer performance: Alpine F1 leveraged the best out of technology in collaboration with Microsoft. With the intervention of Power Platforms and Dynamic 365, Alpine stood better at taking faster decisions at the factory level. Additionally, effective SaaS like Azure takes care of building cloud infrastructure in cohesion with data consolidation and analysis. Large Surface studio screens, Dynamics 365, and Power BI dashboards assist the team in overseeing the manufacturing process and obtaining a comprehensive view of the production cycle.

Nathan Sykes proudly proclaimed having 10 power app developers armored with power app workflows, brainstorming behind the tracks to improve the process and minimize production errors, ranging from clerical to manufacturing.

When realistically employed and accessed, the software can really bring about a change in the system, as it completely fills the shoes where people are reluctant to step in. People's enthusiasm is often deflated by tasks such as compiling a pile of reports and processing them for designers, among other things. So, conditions like these allow us to bring software to do the job effectively, said Sykes, referring to the Dynamic 365, Power platforms, and so on.

Dealing with data ROI and cost caps: In the past, the Alpine F1 team relied on how the tire performed based on a single qualifying lap to determine "tire degradation" which is a bare minimum range to analyze the precise condition of a car that's competing in a fierce race. Whereas Data Science changed the way professionals perceive the functioning of a tire through its sensors, with better accuracy. Today's advanced tools rectify problems easily with better precision through their sensors.

Speaking of, there are over 200 sensors on a single F1 car that collect over 50 billion data points on the track. This massive collection of data is used by professionals to determine aerodynamics, performance, control, and many other mechanisms.

However, the ROI of Data Science still remains an unexplored realm in today's cost-cap era where teams must spend at least $140 million. Citing the ROI, Sykes believes that costs must be allocated according to the efficiency of the player and the car's performance to increase engagement and the quality of the sport until further discoveries.

Great players never hesitate to pursue what they love! Similarly, if you are in love with Data Science you should not stop yourself from pursuing it. Enroll in AlmaBetter’s Full Stack Data Science Program, which offers the best student-centric curriculum with 100% placement opportunities.

Read our recent blog on “Statistics and Data Science: Importance and how to learn”.

Bala Ganesh
Content Writer

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