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.

In the past two months we have looked at how three-sigma limits work with skewed data.

If you remember the woodworking, metalworking, and auto shop classes that used to be taught in high school, you already have an idea of what a makerspace is.

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

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.

You’ve set aside Sunday afternoon to bake some cookies, but you discover you have run out of eggs. Your partner in marital bliss has gone out and taken the car.

Today I’m looking at design from a cybernetics viewpoint. My inspirations come from cybernetics and design theorists Ross Ashby, Stafford Beer, Klaus Krippendorff, Paul Pangaro, and Ranulph Glanville.