>Quality Function Deployment (QFD) links the Voice of the Customer
>(customer wants and needs are at the center of any valid TQM
>effort) to internal metrics a.k.a. performance measures. It is
>these internal metrics and performance measures that are plotted
>on SPC charts. And it is these same metrics that show up in SD
>models.
I agree with Bob's explanation of how these tools can be deployed
throughout an organization in concert with one another. However, what I
have been interested in is how SPC and SD work at the level of individual
mental models. Both tools tend to provide their users with entirely new
ways of perceiving, and therefore improving, their worlds. In other words,
they give you AHAs! of a very similar nature. IMHO, here is why.
Buckminster Fuller said something like (and I paraphrase) "Don't teach me
new ways of thinking. Instead give me a tool that makes me think in new
ways." That is what SPC and SD models do: they provide a tool that forces
us to think in new ways. These tools help us make the shift that Senge
describes as moving from:
events---->patterns of behavior--->underlying structures
Here is how the tools enable the shift...
The key aha of variation/SPControl charting is that until you can
differentiate between common and special cause behavior, you have no way of
distinguishing important (i.e., special cause) events, from unimportant
(i.e., random, or common cause) events. No matter how good it makes you
feel to be a "take charge, action-oriented manager", ANY reactions to
common cause events, no matter how well-intended or logical they may seem,
are likely to be detrimental to process performance.
The impact of this is that when managing a work process, every event is a
problem of equal magnitude until we begin control charting. Using SPC
charts forces us to stop reacting to (common cause) events, and to see
beyond them to the patterns of behavior that emerge over time as we plot
the data. By studying the patterns of behavior using SPC, we learn that
only special causes are events of importance, i.e., problems to solve. All
other variation is inherent in the system itself. Eventually, as the system
becomes stable (i.e., no special causes), further improvement requires
examining the underlying structure of the process itself, which is the
source of all common cause variation. In summary, the progression SPC
charting enables is as follows:
When you: You shift from:
--------------------------- -------------------------------------
- begin keeping SPC charts - events ---> patterns of behavior
- get system in-control - patterns ---> underlying structures
Like SPC charts, which provide a tool and a discipline for seeing beyond
the common cause events in a process, SD models help us see beyond
day-to-day events (like a drop in sales or an inventory shortage) to the
underlying feedback structures that are generating the observed behavior in
complex, dynamic systems. The progression SD modeling enables is:
When you: You shift from:
-------------------------------- -----------------------------------
- plot Behavior Over Time (BOT) - events ---> patterns of behavior
- map, model, simulate - patterns ---> underlying structures
What all this boils down to is captured by Peter Senge at the beginning of
Chapter 7 in The Fifth Discipline: "The bottom line of systems thinking is
leverage--seeing where actions and changes in structures can lead to
significant, enduring improvements...Our nonsystemic ways of thinking are
so damaging specifically because they consistently lead us to focus on
low-leverage changes."
In short, SPC and SD models help us (a) stop reacting to events and
(b) gradually ascend the "ladder of leverage" from events to patterns to
underlying structures. The effect of doing so is twofold:
- we avoid taking counterproductive actions, like blaming actors
within the system for system behavior, or reacting to common
cause events, which is called "tampering" by Deming
- the actions we take instead have greater positive impact
I hope this more clearly describes my interest in SPC/SD linkages than my
previous post. In the spirit of the Learning Org list, I welcome any
additional clarification of my thinking by others on the list.
Bye for now...
_ _____________________________
/ )| Joe Kilbride -- jk@mcs.com |( \
/ / | Kilbride Consulting | \ \
_( (_ | Downers Grove, IL | _) )_
(((\ \>|_/->_____________________<-\_|</ /)))
(\\\\ \_/ / \ \_/ ////)
\ / "I have seen \ /
\ _/ the enemy, \_ /
/ / and he is us." \ \
/ / -- Pogo \ \
PS -- To readers unfamiliar with SPC, my apologies for using terminology
you may be unfamiliar with. If interested and want to learn more, consider
the recommendations below. I personally have found Joiner's book helpful.
Everyone on the Internet who seems to know anything about SPC and variation
swear by the Wheeler books. I'm ordering them myself.
- Brian Joiner's "4th Generation Management" available from Joiner
Associates @ 800/669-8326, or
- Donald J. Wheeler's books including "Understanding Variation" or
"Understanding Statistical Process Control" from SPC Press
@ 800/545-8602
PSS - To Bob Klein: Your reply also mentioned a presentation on SD/TQM
linkages by Fredel and Norm Wada at last years STIA conference in Boston.
As I was unable to attend last year (and will be again this year), was
wondering if you could tell me more about this on the back channel. Thanks
in advance for any help.