Eai

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 won't 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.

* There's no end-state. Organizational

entities split, merge, and morph into new

structures. Political motivations and

boundaries change. Technology evolves

and today's leading edge is obsolete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