Just as baby boomers on the manufacturing plant floor are getting ready to retire, so are the owners.

Imagine that your boss Ethan calls you into his office. He expresses disappointment in your recent performance and lack of commitment. How would you react? Accept the feedback and put in more effort? Would you pout in your office and start looking for a new job?

What tools should data analysts have in their toolbox? It’s a broad question and one with diverging views. So, I am delighted to welcome back a guest blogger who doesn’t shy away from controversy.

One of the key ideas in lean manufacturing is that defects should be detected as early as possible.

This story was originally published by Knowable Magazine.

When my kids, ages 11 and 8, bang through the back door after school, often the first thing out of their mouths is: “Mom! Can we play Prodigy?”

How can industrial and manufacturing enterprises achieve better new product introduction (NPI), a critical element of operational excellence?

In 2006 I was at a presentation by a world leader in quality (WLQ) who has been singing W. Edwards Deming’s praises since the late 1980s and even does the famous red bead experiment as part of some of his plenaries.

A few years ago, I was asked to conduct a workshop, deliver a keynote, and chair a three-day conference on manufacturing process excellence in Europe, produced by the Process Excellence Network (PEX

As a quality professional, you’ve probably heard the famous quote from W. Edwards Deming, “In God we trust; all others bring data.” Thanks to technological advancements in our industry, data exist more abundantly than ever.

In 1500, China’s economy was the strongest in the world. But by the 19th century, the United States, Western Europe, and Japan had leapfrogged over China by churning out goods and services in vast quantities while the former superpower stalled.