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The pandemic has been a perfect storm for Jaguar Land Rovers core business, including a two-month factory shutdown, a semiconductor shortage, and profound challenges with both supply and demand. But thanks to advanced data analytics, the British multinational automotive company not only weathered this storm, but has done so with more precision and profit than expected.

JLRs 40-person data science and analytics team has developed an innovative forecasting engine atop a mixed proprietary/open source stack to the tune of 100 million in revenue during each of the past three years, with 2 million in profit directly attributed to JLRs data team in 2020 despite a disastrous global pandemic, says Harry Powell, director of data and analytics at JLR.

One of the key parts of our strategy has been implementing graph technology in the business, and weve had some reasonably good results applying it to the supply chain, says Powell, noting that JLRs use of graph database technology from TigerGraph has been critical in reducing the automakers supply chain planning from three weeks to 45 minutes.

JLR now plans to deploy graph database technology to address quality improvement and pricing applications for its automobiles.

As opposed to relational and non-SQL databases, graph databases detect, capture, and leverage connections among data stored or actively in use in business processes in real time, making them superior to relational databases when tackling challenges involving incidental and unpredictable relationships, says Carl Olafson, a research vice president at IDC.

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Jaguar Land Rover gets more from graph analytics - CIO UK