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Saturday, 04-Jul-2009 11:03:06 EDT

Search for a Unified Theory of Knowledge Management

Science does not yet as yet have full understanding of the universe. However, it is suggested that with increased technology and theoretical advances, it may be only decades before this achieved. Do such advances finally suggest the arrival of a theory of unified understanding of universe, such as a unified theory of knowledge management.?

Science and its findings have often taken the form of observations about the predictability and generalizability of specific phenomena - it is evident in the 'laws,' 'hypotheses,' and 'theorems' of the normal sciences. Such phenomena have assumed that given an in-depth [perceived] understanding of cause-and-effect, one could generalize the 'behavior' of the phenomena and theretofore 'predict' and 'manipulate' such 'behavior'. Most such observations have been based on the 'controlled' environment notion of experimental designs -- more lately followed by allowing for loosening of assumptions of such 'control' in the case of quasi-experimental designs.

However, the problems of predictability and generalizibility have consistently persisted - more importantly in the case of real world "complex problems." For instance, one may ask: Given that:

(a) the earliest developments in the methods [quantitative, qualitative, etc.] and methodologies [logical positivism, critical relativism, interpretivism, etc.] about the scientific approach have come from the discipline of Educational Psychology -- and have been later adopted by various disciplines related to Business;

(b) the findings of science should inform public policy and practice of 'real world' phenomena [see for instance Campbell and Cook]; and,

(c) the guiding premise is that rigorous methods and methodology of the scientific approach should lead to better policy making thus resulting in better results from that policy.

However, given the current state of K-12 "real world" of application of such rigorous and methodological findings evokes incisive criticism and questioning of the deprecating state of affairs -- as evident from the increasing backlash of public opinion against education -- evidenced by cover stories in print and broadcasting media across both sides of the Atlantic.

Looking at the above rationale, the conclusion could be one of the following:

(i) all the rigorous and methodological findings didn't affect policy;
(ii) the findings were substantive, but weren't adopted by policymakers and practitioners;
(iii) the findings were spurious and hence their practice has resulted in different results than what was expected.

Whatever the conclusion, the key challenge of science -- increasingly is to be scientific while being able to account for phenomena that defy predictive and deterministic logic. To be more and more 'scientific' while taking the nature and form of 'art.'

If universe was in a static state, given increased technology and theoretical advances, one would have hoped for achieving better prediction and generalizability of various scientific and business related phenomena. However, given the increasing pace of discontinuous change [that I have talked about in various other contexts], it is increasingly difficult to set up static models of a dynamically discontinuous reality. In other words, many of our scientific models that have focused on 'main effects' -- including many of them used in the world of business, e.g. on Wall Street -- are increasingly constrained by their relatively lesser understanding of dynamic interactions and the increasing level of 'delta' (the noise factor - that cannot be accounted within a predictive and deterministic logic). Based on such increasing dynamic interactions -- as evident from literature on systems theory and organizational theory published since 1960s or so -- we are moving into "interesting times." Such interesting times will defy most of the "predictive and deterministic" nature of traditional information systems, control systems and performance systems and would put increasing premium on "ongoing learning and unlearning" -- while continuously challenging the existing assumptions. This is how the 'convergent' and optimization-oriented focus of traditional systems is increasingly challenged by the dynamically changing and 'hyperturbulent' business environment. This also presents a fertile bed for devising new ways of thinking about business, technology and organizations -- as evidenced by the cyberspace-based emergent phenomena affecting businesses, industries, governments and the global society at large.

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