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 L2L CEO John Davagian joins IEN to explain why the manufacturers who win won’t be the ones with the most data or the most AI. They’ll be the ones who turn that data into insights their people can act on immediately. 

For the past decade, manufacturers have automated systems, added IoT sensors, and built dashboards. Those tools are good at identifying problems, but they don’t say what to do about it, when or how fast.

That execution gap is where time disappears on the shop floor and throughput drops.

In this episode of 5 Minutes with IEN, L2L CEO John Davagian explains how to close it:

• Prioritize clarity over data collection. Operators shouldn’t have to be data analysts. AI should sort through thousands of data points, find the abnormality, and hand the operator the correct solution.
• Judge AI by outcomes, not features. Stop asking where you can deploy AI. Find what's keeping your team from fast, accurate decision-making, and start your AI journey there.
• Three things to ask any AI vendor. How is the recommendation produced? Can your people accept, decline, or override it? How is the result measured so the system keeps learning?
• Address two gaps, not one. Close the execution gap on the plant floor. Then, close the visibility gap between the plant floor and the corner office so leadership can see floor activity turn into productivity and profitability.