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Data Liquidity Levers at Caterpillar

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Manage episode 520370513 series 3409705
Content provided by MIT CISR. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by MIT CISR or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Barb Wixom reads MIT CISR's November 2025 research briefing, which she co-authored with Joaquin Rodriguez, Gabriele Piccoli, and Cynthia Beath. See the text version and related content at https://cisr.mit.edu/publication/2025_1101_DataLiquidityLevers_WixomRodriguezPiccoliBeath. Abstract: Organizations with big aspirations for leveraging AI technology increasingly need data assets with high data liquidity (i.e., ease of data asset reuse and recombination) to achieve their aims. This briefing draws on the multiyear journey of global manufacturer Caterpillar to illustrate how companies can successfully execute foundational data liquidity tactics by managing three data domain practice areas we call data liquidity levers. These areas—data architecture, data preparation, and data permissioning—function as levers to increase or limit data liquidity.
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97 episodes

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Manage episode 520370513 series 3409705
Content provided by MIT CISR. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by MIT CISR or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Barb Wixom reads MIT CISR's November 2025 research briefing, which she co-authored with Joaquin Rodriguez, Gabriele Piccoli, and Cynthia Beath. See the text version and related content at https://cisr.mit.edu/publication/2025_1101_DataLiquidityLevers_WixomRodriguezPiccoliBeath. Abstract: Organizations with big aspirations for leveraging AI technology increasingly need data assets with high data liquidity (i.e., ease of data asset reuse and recombination) to achieve their aims. This briefing draws on the multiyear journey of global manufacturer Caterpillar to illustrate how companies can successfully execute foundational data liquidity tactics by managing three data domain practice areas we call data liquidity levers. These areas—data architecture, data preparation, and data permissioning—function as levers to increase or limit data liquidity.
  continue reading

97 episodes

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