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What Formula E racing can teach companies about digital transformation

The demand for innovation makes the sport both a metaphor and microcosm of the pressures facing businesses at large

What Formula E racing can teach companies about digital transformation

Motorsport championships may be won on the track, but they can be lost in the garage, where the failure to perfectly tune a vehicle or prepare the drivers may cost the team—the difference between a top-three podium finish and being in the middle of the pack. Unsurprisingly, racing teams leap at any opportunity to glean data in pursuit of an edge—from simply scoring lap times to wind tunnel testing to the revolution in telemetry that transformed Formula One in the 1970s. This need for innovation has traditionally made the sport both a metaphor and microcosm of the pressures facing businesses writ large.

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Nowhere is this truer than in Formula E, the first all-electric, single-seater world championship. Winning one of its global circuit of hairpin road races means wringing every last electron from its constantly-evolving batteries—but, spend one too many, and your ride is dead on the track. (In Formula E, races have a time limit rather than a predetermined number of laps.) And just as motorsport has traditionally been a testbed for automotive tech such as disc brakes and hybrid powertrains, the energy efficiency practiced by Formula E will be crucial in global decarbonization efforts to stave off the worst effects of climate change. Building a successful, net-zero racing team that wins world championships—while raising awareness of the climate challenge and accelerating solutions—requires using data to make decisions with no time or margin for error.

“Whereas other motorsports will be spread over three or four days, we have one day,” explained Sylvain Filippi, CTO and managing director for Envision Virgin Racing, one of the founding teams in the series. “Data analysis is critical for us because we need to glean as many insights as possible in as little time as possible.” His remarks were part of a freewheeling conversation amongst Filippi, Envision Virgin Racing driver Nick Cassidy, and Genpact chief digital officer Sanjay Srivastava at this year’s Fast Company Innovation Festival.

PREDICTION BASED ON SIMULATION

Every organization “is fundamentally a tech company; they just don’t know it yet,” Srivastava said. But Envision Virgin Racing is an exception to this rule. As an example of how Genpact is building new tools to accelerate Envision Virgin Racing’s race-day analysis, he pointed to the company’s Lap Estimate Optimizer (LEO). Using AI-powered algorithms, LEO has helped predict the number of laps remaining in a race, so the team can make more informed decisions on the consequences of attacking and overtaking on remaining energy—in other words, it helps constantly inform the team so that they can make “the right decisions at the right point in time,” as Srivastava put it.

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For Cassidy, constantly preparing in the simulator for a race is nothing new. Once again, motorsport was an early adopter of what are known in business today as “digital twins“—fine-grained simulations of real-world systems in which potential tweaks or disruptions can be modeled, observed, and tested. In Formula E, “we might qualify for the race in the rain and then race in dry conditions with no information,” Cassidy noted. “But we’ll have learned what we need from the simulator.” By analyzing the data from the drivers’ practice runs in the simulator—on the track and in the races themselves, using Genpact’s Augmented Race Intelligence (ARI) platform—they can work with their engineers to quickly identify where they need to improve. Heading into a race, they can combine the insight from ARI with their racing knowledge and know they’re ready to compete.

When digitally transforming, how can organizations build trust in their tools in a similar fashion? “The digital [part] is actually easy,” Srivastava said. “It’s the transformation that’s hard.” One lesson is to build confidence in what the data is telling you through constant testing and refinement. Another is how to marry machine predictions with your people’s knowledge and experience to augment an organization’s intelligence. “AI is the best prediction engine right now, but you need to apply human judgment to the prediction analytics that come through and action it,” Srivastava added. Insights gleaned from data are useless if they can’t be delivered and absorbed by the right person at the right moment—whether that’s Cassidy during the race or a worker struggling to unsnarl supply chains. “I think that applies to every corporation on earth,” Srivastava said.

CLEAN TECHNOLOGY TRAILBLAZERS

Formula E also provides a model for how to rapidly innovate when it comes to clean technology. In just seven seasons, Filippi noted, the cars, batteries, and powertrain have already evolved through several iterations as automakers race to keep up. “The supply chain for super-high-voltage, super-lightweight, very efficient EVs didn’t exist until Formula E created the demand,” he said. “Only then did the suppliers get in gear.” As part of Envision Virgin Racing’s own commitment to being the first carbon-neutral team in racing, it is building new data-driven tools to measure the total footprint of its operations—including a carbon calculator to help the team make more-informed travel decisions.

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But the key to building a net-zero world is to make it feel cool, not a sacrifice. And if there is one thing motorsport does well, it’s injecting an ineffable sense of glamour into the quotidian act of driving. That’s why the sport has aggressively pursued a new generation of fans in urban centers who are more likely to identify themselves as environmentalists than “petrol heads,” and data analysis has proven essential in reaching them. “We’re seeing so many people who’ve never been to a race before and showing them the latest and greenest technology,” Cassidy said. “That’s pretty cool.” On that point, Envision Virgin Racing and Genpact agree, the data is unequivocal.

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