Managers the world over want to know if things are “in control.” This usually is taken to mean that the process is producing 100-percent conforming product, and to this end an emphasis is placed upon having a good capability or performance index.

During recent visits to Twitter and LinkedIn, I’ve become increasingly shocked by the devolution of the posts to vacuous nonsense.

‘Process Capability: What It Is and How It Helps,” parts one,

With the click of your mouse you can turn a list of values into a bubble plot. No thought or effort is required. Simply sit back and let the software gods do the heavy lifting of transforming your list of numbers into a fancy graph. What could possibly go wrong?

If Fyodor Dostoyevsky had been a mathematician, he might have written a book called Crime and Statistics. However, since “statistics” doesn’t have quite the same ring as “punishment,” it wouldn’t have sold as well.

“People think that if you collect enormous amounts of data you are bound to get the right answer. You are not bound to get the right answer unless you are enormously smart.”

The control chart is at the heart of the very definition of quality. It is central to building, maintaining, and predicting quality into the future. However, control charts today, more often than not, are misused and misunderstood.

This is part three of a three-part series.

Annalise Suzuki, director of technology and engagement at software provider Elysium Inc., spoke to Quality Digest about the importance of model-based definitions (MBD) for data quality, validation, and engineering