Revelatory Attributes of Neuronal Group Architecture for Strategic
Knowledge Management
Harold E. Klein, Fox School of Business, Temple University
Additional to the content itself, the organization and representation
of information largely will determine its utility. No single template
can suit all applications or purposes. Obviously, the better defined
these are, especially if the application/purpose has been performed
repeatedly, the clearer and more specific can be the information
requirement. Conversely, the more diffuse the problem specification,
the less likely it is that the requisite information for its solution
can be forthcoming. This is particularly the case when confronted by
a truly "complex" problem such as strategy formation under chaotic
conditions. Here it is not a question of making choices among various
explicit decision alternatives. The question, more often than not, is
how to define the problem in the first place and, after due
consideration, just what might be responsive alternatives.
The notion that information – chunks of cognitive activity – organized
along the lines of biological complex systems is a useful, even
revelatory, architecture has gained currency.
Network analysis, for example, employed in examining organizational
information flows derives directly from biological system
architectures. However, not all such network templates are equally
useful. Among these, neuronal group architecture has been found to
closely pattern several interrelated strategic decision making
activities: knowledge management, scenario planning and network
organization design. Visualizations of strategic problems in and of
themselves employing such a template were found to reveal answers to
key strategic questions. The results of an actual application of this
type of biologically-enacted protocol will be shown.