Red Bull Racing - when remote working gives you wings

Martin Banks Profile picture for user mbanks March 3, 2021
The typical remote worker will travel with a laptop, but Red Bull Racing carries its own data center around the world’s race tracks.

red bull

Running a Formula One GP racing team is a pretty specialist way of making a living, yes? Well, it is certainly complicated, requiring high agility and speed of turnaround across the board. But then, the events of the past year means that the same could be said of every business!

That said, the way that an outfit like the Red Bull Racing Formula One team operates would certainly have been seen as ‘bleeding edge’ before the pandemic and lockdowns became the norm.

Data, of course, is the lifeblood of GP car racing, although in times past, that data was pretty much limited to what a stop-watch could help tell a team. Make an intelligent guess at what was good aerodynamics or the best suspension set-up, then time the car doing laps: quicker equalled good; slower meant throw away and guess again. The notion of the kind of digital twin now possible with simulation tools simply did not exist.

But today engineers can not only measure the real time response of a car against a simulation, using some two hundred sensors on the vehicle, they can mirror and measure the entire manufacturing and management process via sensors scattered across all parts of the business. This allows them to not only simulate the car’s performance accurately, but simulate the factory’s response to any changes that are required.

Zoe Chilton, the Red Bull team’s Head of Partnerships, explains:

We can really identify not just what makes it go faster, but how we make it go faster, and which elements interact with each other as we design them in, to help us see the whole package as a unit and deliver performance in a holistic way. This also applies to our business. So internally, when we think about our internal supply chain or design management process, how we take parts from the drawing board to the track.

F1 is a world where innovation is a Red Bull company mantra - if you follow another team on the drawing board, you will always follow them on the track. This perhaps is one aspect of the business that can be taken too far in other, more prosaic areas. It is an observable fact that, in and around other business sectors, IT included, it is often the company that follows into a new marketplace that actually becomes the market leader, having had the chance to refine the core ideas, while not being committed to the details of the original implementation.

Dashing away with the data center

Over recent years all the GP teams have made increasing use of remote working tools – Citrix in the case of Red Bull – but as the wealth of data being both generated and consumed has increased, the level of that remote working has grown significantly. As well as the key race day players seen on TV – the senior race managers on the pit wall, the pit-crew and, of course, the drivers - the team travels with fifty or more analysts and technicians that are checking the response from every sensor on the cars – in real time - to ensure their optimum running.

Part of the kit that travels to every race is a large number of workstations and specialist technical systems, together with a mobile data center system running all the real time monitoring, analysis and information systems. Citrix is used not only to run this set-up, but also to link back, again in real time, with the supercomputer system back at the Red Bull Milton Keynes HQ. Another team of analysts, technicians and design engineers not only monitors events, but develops and adjusts race strategies – yet again in real time – dependent upon events.

One result of this is the need to design, manufacture and ship new components to the track. Often, the need for these is only discovered at the full-scale track testing that happens on Friday, so they can be used in race qualifying on Saturday afternoon.

Again, perhaps this is a way of working that most businesses would say does not apply to them at all, but in a growing number of areas that is no longer the case. Even in high volume consumer product markets – where `n’ million of the same product are stamped out every week/month/year – consumer pressure is now growing for increased personalisation and localisation of supposedly `standard’ consumer products. This is in addition to the much faster response customers expect to orders placed with their favourite e-commerce website. This is going to be exactly what many businesses in other sectors will now start to face. They will be generating and responding to ever-larger data files at the same pressure currently applied to Red Bull Racing.

Wizard prang sorted in minutes

What is involved here, how it works and what the results can come from it are perhaps best shown in a case study Chilton cites, a saga that began with Red Ball’s star driver, Max Verstappen, crashing the car on the way to the starting grid at last year’s Hungarian Grand Prix.

As well as driving, Verstappen was checking radio communications, running through checklists with analysts and technicians in the pits and back at HQ, checking brakes and gearbox operations, charging up the energy recovery system batteries, and optimising the many variable settings available to the Pit Wall race management team. That team is fed data by the analysts and technicians on site and at HQ, particularly any findings that might compromise a car’s performance. As part of that process, Verstappen was also reporting on his observations of tyre performance, track conditions and the like, which on this occasion was `damp and slippery’.

In the middle of this workload, he and his car parted company with the track and started a relationship with a crash barrier, breaking a steering rod, entirely removing the front wing and damaging the nose cone. The aerodynamics technicians back in the HQ operations room were first to notice the incident from their sensor monitoring before it was seen on TV. They were also able to determine the car was still drivable so, after a rapid full analysis of the incident and damage, the decision was made to direct him to drive the battered vehicle to his grid position rather than the pits.

The reasoning was simple: conducting the repair in the pits would mean having to start the race from the pit lane, placing the car last by some distance, when its start position was seventh on the grid. Chilton goes on:

The trackside team made the judgment call that he should proceed to the grid, even though the car was in pieces. And even though it felt like he couldn't possibly start the race, we thought we'd have a go. So the team managed to replace the whole front end of the car, including the broken suspension and the nose cone. This is a job that would normally take a couple of hours in the garage.

In practice, however, there was just 40 minutes left between the car’s arrival on the grid and the start of the race. Available data on the accident allowed the pit crew to arrive on the grid with all the necessary replacement parts from the spares the team travels with, and all the correct tools to do the job. In the end they completed the task, with the car declared safe to race, some 20 seconds before the klaxon sounded to say the grid had to be cleared. And in the final analysis, the effort proved worthwhile because Verstappen finished the race on the podium, in third place.

My take

This level of fast response may seem extreme, but the ability to evaluate and assess data quickly, make appropriate and timely judgement calls, and act on them with staff properly equipped with the right tools for the job then in hand, is going to be increasingly important to any business that wants its brand to remain `sticky’ to its customers.

When it comes to the increasing uptake of e-commerce, it has to be remembered that while delivery is always important – indeed many consumers now regularly discuss the efficacy (or otherwise) of courier services, regardless of the product being delivered – the vendors’ brand is still made or lost on how they respond to customer requirements, comments and complaints. To do that effectively demands having a rich level of data available on those customers and products and the right level of response available to pull it off the shelf.

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