Summer 2019 - Quality Management Forum
Real-time Quality Management Systems By Tom Pearson
Significant advances over the last 20 years in systems theory, analytics/ artificial intelligence (AI), and real-time applications now enable new real-time quality management systems (RQMS).
Structured Systems Management: The Missing Link for Future Quality Practice By Richard E. Mallory
Almost 50 years ago, Dr. W. Edwards Deming announced that systems management was fundamental to what we can now call quality science1, and he introduced a “system of profound
knowledge” (Deming, 1993, pp. 94–118) as a framework for transformation of our organizational work and our entire economy. He said that “[a]n integral part of the system of profound knowledge is appreciation for a system.” (Deming, 1993, pg 50). But while Deming’s system of profound knowledge got a lot of discussion at the time, most of its contemporary application has been limited to the “profound knowledge of variation,” and to process standardization and process improvement. The most recent frameworks for both are currently described as Lean Six Sigma, Kaizen, or 5S, and all represent what can be called forms of process science. Process science, in turn, has become the mainstay of quality practice, and, in many ways, its sole foundation.
Missing the Target; How Training Needs Assessment Can Help By Sandra Currie-Samson
Organizations today are facing rapid change and disruption. Learning and skill development increase as technology impacts every point of our lives. However, many organizations do not understand what they can do. Nor do they see an urgency to do so. A recent report from Accenture states that “only 3 percent of executives intend to significantly increase investment in training and reskilling programs in the next three years,” but 67 percent of their employees feel “it will be important/very important to learn new skills to work with intelligent technologies in the next three to five years” (Shook & Knickrehm, 2018, p. 9).
Coaches Corner - Advancing Toward the Basics By J.R. McGee
As a Master Black Belt Sensei who has trained and certified 73 other Master Black Belts, I’ve spent a lot of time using, teaching, and playing with the various and sundry tools our methodologies bring to bear. Multi-Variant Regression Analysis, Design of Experiment, ANOVA, Monte Carlo Analysis, and numerous others are powerful, highly useful, challenging, and frankly, a lot of fun to learn and play with to solve large, complex problems.
However, I’m learning that often it’s our simpler tools that solve the toughest problems. And not inconsequentially, I’m seeing that using some of these tools in newer, less traditional ways can be every bit as powerful, and even more challenging.