Articles by Jim L. Smith

Many quality professionals, including statisticians, have remained mired in their rapidly diminishing consultative roles of teaching statistical tools, analyzing data, designing experiments and performing internal consulting duties while having few leadership responsibilities and limited accountability.

I have spent numerous years working in and with all aspects of quality. During my earliest time in industry solving problems was more of a singular focus, but over the years the focus has become more of a team effort.

It’s safe to say that all quality practitioners are familiar with the control charting terms “common cause” and “special cause” variation. However, how many have really thought about their interpretations and associated action plans which could also add to variation? 

When faced with most problems dealing with processes, products, or service, quality professionals typically implement two types of remedial actions which were handed down to us by experts like Dr. Joseph M. Juran, Dr. Frank Gryna, et al. “Control of nonconforming product” and “root cause analysis with corrective action” are two separate and essential processes.

Quality at the source (QATS) has been used well before lean manufacturing became so popular. Many people in the quality function have applied the principles especially at critical work areas to detect nonconforming items and prevent them from moving forward in the process.

It shouldn’t come as a surprise, but even after all these years the ISO9001 quality management system (QMS) requirements still come under attack and mostly from those in the quality profession. I recently read another super critical appraisal of ISO9001 from someone who commented they were on the “front lines.” I’m not sure what front lines they’ve been on, but it’s obviously not the same ones I’ve been on.

The recent implementation of the new quality management system requirements has generated concerns about many issues including documents and standards. 

It’s not enough to just think about it or plan for it, wish or hope or imagine it.

Last month’s column focused on statisticians and their need to transition to leaders. In order to do so, one must understand the difference between managing work/projects and leading others.

I had a discussion recently with someone who, for three decades, had been performing a statistical function at a large manufacturing company. He couldn’t understand why, in spite of excellent job performance reviews, his company had furloughed him indefinitely.