Are You Unknowingly Reacting to the Data Process?Everyday variation lurks in many guises
Mon, 03/16/2015 - 13:17
In my last column, I discussed how even a well-designed study with a statistically significant result doesn’t necessarily mean viability in the real world. Post-study, one must study the manifestations of variation on the result in any environment… Bears Repeating: Given Two Different Numbers...Is it statistically significant? Who cares?
Tue, 02/17/2015 - 12:17
I have evolved to using fewer, simpler tools in my consulting and have never been more effective, as I commented upon in my last column. It made me ponder the relevance of much of what I learned in my master’s statistics program. Thinking of the… A Funny Thing Happened on the Way to Quality ImprovementThe quality vs. transformation disconnect continues
Wed, 01/28/2015 - 00:00
I've been presenting at the Institute for Healthcare Improvement (IHI) annual forum for 21 consecutive years. Maybe the biggest surprise from these two decades has been the awesome power of simply "plotting the dots," i.e., plotting important… The ‘Teach Once’ Fallacy of Cultural ChangeIt’s all your fault!
Tue, 12/16/2014 - 12:52
For those of you who are improvement practitioners, are you satisfied with the organizational results of your efforts? I have a feeling most of you would answer, “Far from it,” and would almost unanimously feel that you could be more effective… Time to Do a Root Cause Analysis......On the obsession with root cause analyses
Tue, 11/18/2014 - 14:55
During my recent travels speaking at conferences and consulting, root cause analysis (RCA) seems to have taken on a life of its own and is now a well-established subindustry in any organization, regardless of its chosen approach to improvement.… Big Data Have ArrivedBut do you know their quality and origin?
Mon, 10/13/2014 - 09:19
There has been an explosion in new technology for acquiring, storing, and processing data. The “big data” movement (and its resulting sub-industry, data mining) is becoming more prevalent and having major effects on how quality professionals and… Statistical Stratification, Part 2The alternative to the ‘simple, obvious, and wrong’ SWAG
Tue, 09/30/2014 - 14:46
My last article demonstrated a common incorrect technique—based in “traditional” statistics—for comparing performances based on percentage rates. This article will use the same data to show what should be done instead.
To quickly review the… Statistical Stratification... of SortsSWAGs remain alive and well
Thu, 09/18/2014 - 15:19
I chatted about u-charts for rates last time, and this column was going to be about p-charts for percentage data. These are the two major charts for dealing with count data and are helpful for stratifying a stable section of process performance.… Statistical Stratification With Count Data, Part 1What is your area of opportunity?
Thu, 09/11/2014 - 12:51
My last column, “Dealing With Count Data and Variation,” showed how a matrix presentation of stratified count data could be quite effective as a common-cause strategy. I’ll use this column to review some key concepts of count data as well as to… Dealing With Count Data and VariationA non-statistical common cause strategy from Joseph Juran
Tue, 08/19/2014 - 15:58
In my last column, I showed the power of process-oriented thinking with a safety scenario. A simple run chart demonstrated that, despite meeting an aggressive 25-percent reduction goal (i.e., 45 accidents during the first year, and 32 the following…
