The past two years have brought a torrent of challenges for the automotive supply chain. Even beyond Covid-19, there have been blocked canals, congested ports, driver shortages and multiple natural disasters that have surprised OEMs and suppliers around the world. The pandemic exacerbated these issues and created new ones, most notably a critically restricted supply of semiconductor chips.
A key culprit is making these challenges worse: outdated software.
“If you’re reacting to a supply chain crisis with old and inflexible software written in the 1990s, it's a bit like playing a game of chess where you can only see some of the pieces,” says Liam Mawe, Global Head of Automotive and Mobility at Palantir Technologies. “Data and analytics in the supply chain should light up the entire chess board and guide decision-makers in the supply chain to make moves with the full available context towards the strategic goals of the company.”
For many business leaders today, it’s becoming increasingly clear that data technology needs to bridge the gap between analytics and operations. Companies like Palantir lead the way by integrating data in common operating platforms designed for operational decision-making. This creates creating environments where supply-chain crises can be managed intelligently with contextual detail or prevented altogether.
This approach is part of a broader push to revolutionize the automotive industry supply chain by introducing new tools harnessing the power of data and AI technology. Two of the key avenues towards making this happen: leveraging enterprise-wide data and the power of artificial intelligence (AI).