Story update 11/23/2010: A paragraph was added to the end of this case study to reflect the current state of the company's quality initiatives.

After a meal at a local Chinese restaurant, my fortune cookie said, “If you keep too busy learning the tricks of the trade, you may never learn the trade.” When I think about how this applies to Six Sigma, it seems obvious that far too much Six Sigma training is ded

The economy has become a convenient excuse on which to pin the blame for everything—especially job losses. Well, in the case of quality positions, yes… and no.

For a group of people who claim to practice management by fact, questioning the as-given condition, we in the lean community have a troubling habit of citing and accepting made-up lean enterprise statistics.

I’ve spent most of the past two years living in China where I have learned much on how enterprise is managed over there. Many people have said that this century belongs to Asia. That may be, but they have a lot to learn and change before that happens.

The four questions of data analysis are the questions of description, probability, inference, and homogeneity. Any data analyst needs to know how to organize and use these four questions to be able to obtain meaningful and correct results.

“Lean” has come to mean an integrated, end-to-end process viewpoint that combines the concepts of waste elimination, just-in-time inventory management, built-in quality, and worker involvement supported by a cultural focus on problem solving.

You know how sometimes you think everyone knows a secret that they haven’t let you in on? Well, I had the opposite happen to me the other day. I assumed everyone knew the purpose for measurement system analysis (MSA), a.k.a.

I have just finished rereading Walter A. Shewhart's 1939 book Statistical Method from the Viewpoint of Quality Control (Dover Publications, 1986). Mine is the 1986 edition, which has a foreword by W. Edwards Deming.