A new Manufacturing Dive article puts numbers to a problem many of us see every day: while most manufacturers have a data management strategy, only about 15% actually follow it, even as data volumes double every couple of years.
The article highlights some interesting trends:
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The AI ambition / AI readiness gap is real. Companies are under board-level pressure to show AI returns, so they fund the use case and starve the foundation. The result, as one executive put it, is "garbage in, garbage out" — just faster.
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Spreadsheets are still running the show. A recent survey found roughly 60% of manufacturers manage critical specification data in Excel or Google Sheets, and teams lose hundreds of hours a year to manual spec work.
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The payoff for getting it right is concrete: capturing retiring workers' institutional knowledge before it walks out the door, faster audits in regulated industries, better supply chain forecasting, and predictive maintenance that saves millions in avoided downtime.
The conclusion resonated with me: the winners of the next decade won't be the manufacturers with the flashiest AI; they'll be the ones who treat data as the foundation, not an afterthought.
Full article from Sakshi Udavant at Manufacturing Dive: https://www.manufacturingdive.com/news/manufacturing-needs-data-standardization/824064/
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Still not convinced? Here's further data on the data challenges manufacturers face in the AI era:
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The Achilles Heel of AI: Why Most AI Projects Fail (And How to Fix It)
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AI Is Not Replacing ERPs – It’s Changing the Way They Function With Data Quality at The Core
- What is Operational Data Integrity?
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