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Thanks for this TRANDOC insight.
Assuming some paralelism between military strategy and business strategy, Walmart's positioning on the NHIN Entry Points to medical record management systems using small medical practices and very low pricing strategies bears modeling.
A recent Huffington Post article used the Black Swan concept to explore Walmart's campaign.
In the mid 1980's some interesting work was done on the topic of "Ambiguity and Command" that developed testable computer models of large military campaigns using academics and senior military officers. (They used the terms "Garbage Can Model of Organizational Choice" instead of "Wicked Problems" ;-}
Are there computer models (with some ontology savvy that George H. provided) being used today that allow scenarios for military campaigns and health care technology campaigns against multiple targets?
Cheers,
Bob
2009/3/30 Peter Yim <peter.yim@xxxxxxxx>
Indeed! .. Thanks, Duane.
The Issue-based Information System (IBIS) folks (Horst Rittle, Jeff
Conklin, et al.) have been calling problems typified by what is
identified here as "Interactive complexity" in your earlier message
*Wicked Problems* (as opposed to "Tame Problems").
(Not that I am proposing we include this in the conference discussion,
but) Back in late 2007 and the first half of 2008, we ran a joint
NASA, Ontolog and Federal Knowledge Management Working Group (KMWG)
virtual mini-series called "Ontology in Knowledge Management and
Decision Support (OKMDS)" (which SusanTurnbull, SteveRay and I were
among the co-organizers) - see:
http://ontolog.cim3.net/cgi-bin/wiki.pl?OKMDS
Of particular interest to this conversation the proceedings from
following two sessions:
* 2008_04_17 - Thursday: OKMDS Panel Discussion: "Knowledge Mapping
for Sensemaking" - JeffConklin, SimonBuckinghamShum, EricYeh &
JackPark
- see: http://ontolog.cim3.net/cgi-bin/wiki.pl?ConferenceCall_2008_04_17
... where one can see some of the latest developments in the IBIS
techniques and tools, and the range of work in those areas ... and,
* 2007_12_13 - Thursday: OKMDS - "Making Better Strategic Decisions,
by Asking If It Is Going To Get Better or Worse" - Panel: TedGordon,
PeterYim, AdamCheyer, DeniseBedford, PatCassidy, KenBaclawski,
DuaneNickull & JerryGlenn
- see: http://ontolog.cim3.net/cgi-bin/wiki.pl?ConferenceCall_2007_12_13
... which describes the design of (among other uses) a policy
decision support system (human-machine environment) that I have been
involved in since 2002.
Regards. =ppy
--
---------- Forwarded message ----------
From: Caneva, Duane C. <Duane_C._Caneva@xxxxxxxxxxx>
Date: 2009/3/30
Subject: Re: [mphise-talk] the MPHISE Conference - Day-1 Panel-1
Briefing-4 - preparation
To: "[mphise-talk]" <mphise-talk@xxxxxxxxxxxxxxxx>
I like this as a simple explanation of complexity in systems. It is an
Army document that was used to understand the complexity of developing a
counter-insurgency program for Iraq. The challenge is in understanding
the differences in "structural complexity" and "interactive complexity".
(1) Structural complexity is based upon the number of parts in a system.
The larger the number of independent parts in a system, the greater its
structural complexity.
Structural Complexity. It is possible for a system to have many parts
and therefore great structural complexity, but to exhibit almost no
interactive complexity. Machines function this way. A microchip may have
billions of internal circuits and therefore great structural complexity,
but its responses to a wide range of inputs are entirely predictable. It
is therefore interactively simple. Similarly, an automobile driver knows
when he puts his foot on the accelerator that his vehicle, which is
constructed from thousands of parts, will go faster.
(1) Such systems demonstrate linearity, because they exhibit
proportionality, replication, additivity, and demonstrability of cause
and effect. Proportionality means that a small input leads to a small
output, a larger input to a larger output. Push down lightly on the
accelerator, the car will go slowly, but push down heavily and its speed
will increase. Replication means that the system will respond the same
way to an input under the same conditions. Replication also allows cause
and effect to be demonstrated. Thus, a driver knows that changing the
position of the accelerator causes the speed to change.
(2) Additivity means that the whole is equal to the sum of the parts.5
The additive nature of linear systems legitimizes analysis. Analysis
reduces the system into progressively smaller components in order to
determine the properties of each. In a system that exhibits little
interactive complexity, the properties of the whole system can be
understood based upon the properties of the components. The most
effective way to study such a system is systematically6 and
quantitatively using the analytical problem solving. Unfortunately, the
operational problems confronting commanders at all levels are rarely
linear.
(2) Interactive complexity is based upon the behavior of the parts and
the resulting interactions between them. The greater the freedom of
action of each individual part and the more linkages among the
components, the greater is the system's interactive complexity.
Interactive Complexity. Interactive complexity makes a system more
challenging and unpredictable than structural complexity. These systems
are non-linear because they are not proportional, replicable, or
additive, and the link between cause and effect is ambiguous. They are
inherently unstable, irregular, and inconsistent. The most complex
systems are those that are both structurally and interactively complex.
However, even a structurally simple system can be interactively complex
and therefore unpredictable. Take for example, the highly interactive
dynamics associated with a small group of friends. A system composed of
people is inherently interactively complex because people have great
freedom of action and links to many others in their society.
(1) Reductionism and analysis are not as useful with interactively
complex systems because they lose sight of the dynamics between the
components. The study of interactively complex systems must be systemic7
rather than reductionist, and qualitative rather than quantitative, and
must use different heuristic approaches rather than analytical problem
solving.
5 Thomas Czerwinski, Coping with the Bounds: Speculations on
Nonlinearity in Military Affairs (Washington, D.C.: DoD Command and
Control Research Program, 1997), pp. 8-9.
6 Systematic: A methodical process dependant on an expectation of
prescriptive cause and effect within a closed system.
7 Systemic: A holistic approach that draws from systems theory, aimed at
understanding and influencing change in an open system. Note that system
is derived from a Greek word meaning "to combine." A systemic
understanding means combining components of a system in a context and
establishing the nature of their behavior and relationships. Systemic is
not equivalent to systematic.
(2) Since warfare represents a clash between societies or cultures,
most operational problems are both structurally and interactively
complex. Several features of the current and future operational
environment have magnified the non-linear complexity inherent in all
warfare. War amongst the people has increased the number of linkages
within the operational environment, and made the freely-formed opinions
of large groups of people on all sides-to include neutrals-important to
the outcome. The media carry images and perceptions of the ongoing
operations and each action carries an implicit message. Each Soldier
thus has potential links to the members of a global audience, and
therefore his actions can "directly impact on the outcome of [a] larger
operation."8
(3) The ways that adversaries are organized add to the complexity of the
operational environment. In many cases, the adversaries are
indistinguishable from the rest of the population. Their organizations
and objectives are not just different than the regular armies of states;
they have a completely different logic, one that makes the recognition
of cultural narratives and the study of anthropology, history, and
language essential for a more complete understanding of the nature of
the conflict.
Best,
Duane
Duane C. Caneva, MD, FACEP
Director, Medical Preparedness Policy
White House Homeland Security Council
202-456-2171 (o)
202-503-5439 (c)
202-456-6024 (f)
DCaneva@xxxxxxxxxxx
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