Accelerating Supply Chain Planning at Jaguar Land Rover From 3 Weeks to 45 Mins

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Presented by

Harry Powell, Director of Data, Jaguar Land Rover

About this talk

A supply chain case study. The automotive supply chain is one of the most complex and global in the world; the average car is made up of some 4,500 parts produced by 100s of suppliers, relying on forecasts issued years in advance. This sessions will show you how, using graph analytics, Jaguar Land Rover (JLR) has reduced query time across their entire supply chain from 3 weeks to just 45 minutes. And how JLR accurately plans in response to supply and demand uncertainties around the Covid-19 pandemic.

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TigerGraph is a platform for advanced analytics and machine learning on connected data. Based on the industry’s first and only distributed native graph database, TigerGraph’s proven technology supports advanced analytics and machine learning applications such as fraud detection, anti-money laundering (AML), entity resolution, customer 360, data operations, digital twin, recommendations, knowledge graph, cybersecurity, supply chain, IoT, and network analysis. This channel showcases TigerGraph's technology and how it helps organisations tap into their data to gain key insights into the business decisions and processes driving innovation, growth and cost optimisation. For more information visit www.tigergraph.com