F1's commitment to innovation is so great that it probably comes as no surprise that other industries can learn a thing or two from the way it operates - particularly how teams use connectivity and data to get a competitive edge. One example is McLaren, which has been sharing its data systems expertise with ConocoPhillips for use on oil rigs. But a bit closer to home, how can companies that have vehicles and people in the field learn from how F1 teams embrace connectivity and data?
Reams of deep data
Every F1 race car now has more than 100 sensors across the vehicle collecting reams of deep data. Installed along a car's chassis, tyres and throughout the engine, they measure the likes of stress and downward force, brake temperature, tyre pressure, fuel use and monitor how the car is cornering. Sensors on the suspension measure the car's speed and how force affects the vehicle.
This data, as well as similar information on the competing teams is shared with the driver and up to 60 engineers and sports scientists. Indeed in a typical F1 team, data is also shared with 100 remote engineers across the globe. Infiniti Red Bull says it takes under 300 milliseconds for data from the farthest track in Australia to reach Infiniti Red Bull's UK team.
How is this data interpreted and actioned? Real-time simulations run possible outcomes of the race. Every piece of information gleaned is analysed and changes are made live and in retrospect to increase the likes of fuel and aerodynamic efficiency. Data is also used to measure impact forces and can give doctors insight into potential damage a driver may have suffered as the result of a crash.
This continuous optimisation of F1 teams and their drivers comes from connected intelligence - information pulled from big, deep data. There is a laser focus on the need to be able to analyse and get better and better. It's learning through data. But you don't have to be a F1 team to benefit from these ideas.
Fleets learning from F1
While mobile companies aren't focused on driving round a track at 220 mph, they do need to optimise routing, driver behaviour and manage assets within their business to get the competitive edge in their marketplace. This means using tech in the form of Mobile Enterprise Management (MEM) software platforms and vehicle-wide sensors to get feedback on driver and vehicle behaviour.
What behaviour can be fed back upon? Driver behaviour can be the likes of harsh braking, acceleration or seat belt use. Vehicle information can be aerodynamics, weight of load, idling, delivery schedules or nuanced information like refrigeration temperature or crane extension.
Having visibility on, and then actioning against this data can change a business. Managers that can see which of their drivers are accelerating too harshly or speeding, can communicate live or in hindsight to drivers to address the issue. Managers that are alerted to inefficient idling or delivery routes can then mitigate against it.
The impact this has on the fuel consumption, efficiency and safety of a vehicle - and the staff who operate them - is significant. Rolled out across a fleet, the effect on the bottom line of a business is vast. And these savings can be invested elsewhere in the organisation.
Tech can also be used to harness another aspect of F1 - driver competition. Modern mobile apps allow gamification to be applied to fleets. This means drivers can compete against others in their team or even nationwide on safety and efficiency measures such as speed limit adherence, braking and acceleration. Through tech and data, the competitive instinct of drivers can be harnessed to drive down fuel costs and improve safety.
There are clearly significant differences between F1 and mobile enterprise management. But managers that are able to learn from the use of tech and harness the competitive spirit fostered within the sport will make great strides in their marketplace through significant bottom line savings.
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