Complex
Adaptive System (CAS) is described in Obolensky (2010,) as a dynamic
organization from which teams are formed, performed and terminate as needed.
The true cornerstones that form the foundation of which people, processes and
policies including relevant and adaptive information, communication systems
that are transparent, inclusive with a flexible developmental strategy process.
Morning Star
and St. Luke are two organizations that share similar Complex Adaptive System
(CAS) business strategies.
In the
United States Morning Star, Inc. is heralded as one of the largest tomato
processing organizations in the world. The success strategy that Morning Star
subscribes is to allow employee self-empowerment, self-management including
personalized mission statements. The organization is considered to a very
unusually operated company due to the methods of allowing freedom of its
employees to seek new challenges with an acceptance of ever increasing roles
and responsibilities.
St. Luke is
an organization located in the United Kingdom that boasts 115 employees in an
open informational type sharing in a formal and decentralized manner. The
dynamics of meeting the needs of the stakeholder vs. operating the company
lends to its unusual business model.
Health Care as a Complex Adaptive System is a business model, which requires
leadership rather than power, incentives and inhibitions rather than command
and control. Since many individuals think of “systems” as exemplars that range
from processing plants, utilities and enterprises and the improvement of a
system through decomposition of performance and management into component
elements and subsequently recomposing through integration and design solutions
for each element.
Not all system redesigns and management problems in the health care
world can be solved by hierarchical decomposition.
By
comparison Complex
adaptive systems can be defined in terms of the following characteristics
(Rouse, 2000):
They
are nonlinear and dynamic and do not inherently reach fixed-equilibrium
points. As a result, system behaviors may appear to be random or chaotic.
They
are composed of independent agents whose behavior is based on physical,
psychological, or social rules rather than the demands of system dynamics.
Because
agents’ needs or desires, reflected in their rules, are not homogeneous, their goals
and behaviors are likely to conflict. In response to these conflicts or
competitions, agents tend to adapt to each other’s behaviors.
Agents
are intelligent. As they experiment and gain experience, agents learn
and change their behaviors accordingly. Thus overall system behavior inherently
changes over time.
Adaptation
and learning tend to result in self-organization. Behavior patterns
emerge rather than being designed into the system. The nature of emergent
behaviors may range from valuable innovations to unfortunate accidents.
There is no
single point(s) of control. System behaviors are often unpredictable and
uncontrollable, and no one is “in charge.” Consequently, the behaviors of
complex adaptive systems can usually be more easily influenced than controlled.
References:
Obolensky, N. (2010). Complex
adaptive leadership. Burlington, VT: Gower Publishing Limited. DOI: www.gowerpublishing.com
Rouse, W.B.
2000. Managing complexity: disease control as a complex adaptive system.
Information • Knowledge • Systems Management 2(2): 143–165.
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