Replacing estimates with accurate predictions
Our partnership began in late 2018 with a goal to help the team sharpen its performance with data. The work and projects we focus on are driven by the team's objective. "Ultimately, it's all about lap time," says Gil Abrantes, strategy engineer at Envision Racing. "We focus our time on where we can impact it."
Heading into season five, we quickly helped the team address a new challenge. Formula E regulations had just shifted to a timed race of 45 minutes plus one lap, and the key to success lay in a blend of data, AI, racing expertise, and engineering knowledge.
To manage the speed and energy consumption of its battery-powered cars, Envision Racing's engineers had to accurately predict the number of laps in a race.
This is where we stepped in. We built an AI-based scenario engine, the Lap Estimate Optimizer (LEO), to inject greater precision into the team's lap-count intelligence and guide the team's racing strategies that season. LEO's algorithms assessed thousands of potential scenarios that could affect a race, such as overtakes, accidents, or sudden rain or hail, to understand how many laps there would be in a race.
With more precise predictions – especially when there were changing track conditions as there were in Paris when the drivers tackled rain, sunshine, and hail all in one race – engineers and drivers gained the insight they needed to balance car speed and energy consumption for superior performance.
By extracting competitive advantage from data, LEO solidified the partnership between Genpact and the team.