In the world of quality and lean, waste is the enemy. We hunt for it in cycle times, inventory buffers, and defects. But occasionally we encounter a form of waste so massive and literal that we fail to see it as a resource.

Data are the backbone of our digital world. From healthcare to finance, and from government agencies to private businesses, organizations everywhere rely on vast amounts of data to function effectively.

As AI makes its way into every corner of work, quality management is no exception.

I want to revisit the notion of information from a cybernetic viewpoint, drawing primarily from Gregory Bateson’s well-known formulation that information is the difference that makes a difference. This definition doesn’t merely redefine information.

During the last couple of decades working in quality, I’ve lost count of how many times I’ve seen the same pattern play out: A strong launch. Tight focus. Great early results. People doing the right things for the right reasons. Controls are followed.

The manufacturing industry is undergoing a transformation driven by rapid technological advancements, changing consumer preferences, and evolving regulatory frameworks.

Performance rarely collapses with fanfare. More often, it flatlines quietly; sales soften, productivity slows, priorities blur, and yet teams run hard without moving the needle.

Quality has always been a defining metric in manufacturing when it comes to industry trust, brand longevity, and customer loyalty. Manufacturers are already expected to abide by stringent regulations.

In 2021, container ships idled for weeks outside the Port of Los Angeles, a stark visual reminder of just how fragile modern supply-chain reliability had become. The backlog sent shockwaves across industries.

T he year 2025 has been rife with uncertainty for industrial automation OEMs and their customers. A cataclysmic shift in U.S.