Essay About Adaptive Systems And Enterprise Application Integration

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Integration laws reflect the reality of
dealing with “complex adaptive systems”
that are characteristic of
Enterprise Application Integration (EAI).
They represent the reality of “what is”
rather than “what could be.” Just like the
laws of physics, they describe many realworld
characteristics.
An effective EAI methodology must be
aligned with the EAI laws. Although challenging
them wont land you in jail, ignoring
them will likely add to the list of failed
integration projects. As you start your new
EAI initiative, remember these five laws:
* The whole is greater than the sum of
its parts. The notion of “process decomposition”
is deeply ingrained in most
modern analysis techniques and methodologies.
It assumes there are natural
boundaries along which to divide a complex
system into smaller components for
integration. This approach comes from
the reductionist perspective, dealing with
one dimension of problem analysis.
While this approach helps tackle complex
problems in short timeframes, it
fails as system complexity increases and
natural boundaries disappear. All the
gains achieved by breaking down the big
problem are lost as the cost of integrating
the small solutions becomes unworkable.
Most methodologies fail to realize that
the essence of an end-to-end system cannot
be captured by studying its individual
components; they fail to assign responsibility
for the holistic solution. Or, if
accountability is clear for the initial construction
of a solution, the solution can
deteriorate if no one is responsible for
sustaining the end-to-end processes.
* Theres no end-state. Organizational
entities split, merge, and morph into new
structures. Political motivations and
boundaries change. Technology evolves
and todays leading edge is obsolete
tomorrow. Any effective EAI methodology
must consider the full life cycle of a
system and be based on best practices that
recognize the adaptive nature of complex
systems. From the start, we must plan for
constant change.
Furthermore, EAI must deal with legacy
systems based on prior generations of
technology. There have been many
waves of application technology over the
years that seem to move in regular
seven-year cycles (e.g., mainframe to
mini