Victory Fueled by Data

Mercedes-AMG Petronas Formula One Team & TIBCO

Seven-time FIA Formula One™ Constructors' champion Mercedes-AMG Petronas Formula One is at the pinnacle of motorsport. Over its years of partnership with TIBCO, it amassed more than 50 race wins—including Constructors' and Drivers' championships—and operationalized turning data into insight that informs car design, race strategy, and driver performance.

 

Speed of data analysis and adaptability quickly translate into vital information. Data is the competitive advantage, fueling innovation and providing the best solutions for both constructing and racing.

 

Follow the Mercedes-AMG Petronas Formula One Team

Lessons for Every Industry

In Detail: 2021

  • Cost Visualization
  • Predictable Outcomes
Making the Most of Every Dollar

Making the Most of Every Dollar

With new cost cap regulations, extracting the maximum performance per dollar spent has become more important than ever in Formula One™. Cost visualization helps the team better plan budgets, predict changing costs, and maintain regulatory compliance.

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Leveraging Advanced Simulations

Continuous success relies upon calculated preparations for each unique racing situation. To achieve the best racing outcomes, the team simulates millions of racing scenarios and car configurations to devise the best strategies and ensure the best cars are on-track any given race day.

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Leveraging Advanced Simulations

Winning Data-Centric Strategies

In Detail: 2020

  • Data Foundation
  • Constant Adaptations
  • In-the-moment Decisions
Laying a Foundation for Long Term Success

Laying a Foundation for Long Term Success

Formula One™ racing is probably the most competitive, technology-intensive sport in the world. To achieve continuous success and keep competitors at bay, teams must expertly wrangle the volume, variety, and velocity of their data and turn it into a competitive advantage that fuels innovation.

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Innovating for Wins Year After Year

The time between F1™ seasons is short, and often, needed changes to car and strategy are great. Command of the team’s data enables speedy adaptation and innovation of processes, practices, and culture that add up to winning season after season.

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Constant Adaptations
In-the-moment Decisions

Fast Decision-making Race after Race

Data analytics supports the game plan and the minute-by-minute decisions made by the garage, drivers, and other team stakeholders. With every new circuit, unrelenting competitors, and changing weather and track conditions, data analytics and decision-making are crucial.

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Precision-Engineered Excellence

In Detail: 2019

  • Optimal Car Setup
  • Reliability Testing
  • Digital Twins
Optimal Car Setup

Expecting the Unexpected

Data is central to Formula One™. Teams sift through billions of parameter combinations to find the fastest possible setup for that track, that day, that car, that driver. With so many variables and changing conditions, it’s impossible to fully prepare. But here's how Mercedes-AMG Petronas Formula One Team expects the unexpected.

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Continuous Innovation & Collaboration

Here’s how the team uses data to bring insight and build a superior understanding leading to operational excellence and competitive advantage. This story describes its use of aerodynamics testing in a wind tunnel, and dynamometer and hydraulic testing to assess and improve the reliability of components.

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Continuous Innovation & Collaboration
Digital Twins

Digital Twins Throw Down Big Gains

Factors contributing to Formula One™ car performance include design, aerodynamics, configuration, strategy—and the unsung hero—simulator analytics. F1™ teams, like Mercedes-AMG Petronas Formula One, use simulators that mimic the real track experience, a digital twin that maximizes limited on-track testing time.

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Fueling Industries Beyond the Track

Internet of Things

Internet of Things

The modern data-centric economy is exploding with connected devices. Businesses need to integrate them, aggregate the massive flow of disparate data into a cohesive view, analyze, then quickly act on the insights. Learn more about using the Internet of Things like the F1 team.

Digital Twin

Digital Twin

Digital twins are models of physical systems and offer tremendous value. One example is digitally monitoring physical assets and predicting when maintenance is needed to reduce downtime. Learn more about how the F1 team has turned digital twins into a competitive advantage.

Hyperconverged Analytics

Hyperconverged Analytics

TIBCO Hyperconverged Analytics allows an understanding of past and present trends so you can make informed decisions and achieve better outcomes. Learn more about how hyper-converged analytics delivers predictive insights at scale.

F1 Simulation Demonstration

  • Introduction
  • Race Simulation Overview
  • Gameplay & Telemetry Simulation
  • Building Models: Best Variables for Predicting Lap-time Performance
  • Machine Learning Models for Predictive Analytics
  • Conclusion
F1 Demo Introduction
F1 Demo Introduction

This F1 e-racing demonstration shows tools and models that could be applied to any business that uses data to predict outcomes—especially relevant in a climate of constant change. With real-time data telemetry, predictive models, and live dashboards, you can make informed decisions to optimize product and service integrity.

Simulation Gameplay Telemetry
F1 Demo Simulation Gameplay Telemetry and Architecture

A key feature of most racing simulations is the ability to generate telemetry data just like in the real world. In this simulation, 80 data messages per second are captured, processed, and displayed on a dashboard for analysis.

Simulation Gameplay Telemetry
F1 Demo Simulation Gameplay Telemetry and Architecture

Telemetry remotely measures data points and automatically transmits the data to a receiver for monitoring and analysis. TIBCO Spotfire® dashboards are used to optimize and predict performance, discover insights, and explore captured data. Similar use cases could be achieved for a healthcare or insurance provider, a financial institution, or a supply chain. Enjoy a visual overview of the F1 2020 telemetry capture and analysis using TIBCO® Data Science and Spotfire® analytics.

Building the Models
F1 Demo Building the Models

With TIBCO Data Science software, you can discover the most important variables for building models that predict business outcomes. See how workflows can be built to wrangle data and identify feature importance, and note the software’s drag and drop functionality that reduces or eliminates the need for coding.

Learning Models for Predictive Analytics
F1 Demo Machine Learning Models for Predictive Analytics

After identifying model variables using TIBCO Data Science software, the next step is building the model that will predict lap-time performance. We then use statistics to analyze and optimize performance. Spotfire analytics interprets the output, so we gain insight into driver performance. The model can predict significant events, enabling preparation that could mean the difference between winning and losing in racing or other business.

F1 Demo Conclusion
F1 Demo Conclusion

Business leaders are faced with vast amounts of data that, if handled appropriately, can provide insights for better decisions. This demonstration shows simulation analytics techniques used by Mercedes-AMG Petronas Formula One to optimize car performance. Real-time data, visual analytics, and predictive machine learning models provide insight into your business and give you the power to predict the future.

You've seen how Mercedes-AMG Petronas F1 does it - so what can TIBCO make possible for you?

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