A Conceptual Framework of the Evolution of Knowledge Management

Knowledge Management as a discipline is experiencing a history and evolution since the early 90’s. Knowledge management started off with high expectations of boosting efficiency and effectiveness of business processes, forcing up outcomes and profits to unknown heights by applying ideas of engineering and machine dynamics, and bringing the blessings of information technology to the world of knowledge, information and thinking. Knowledge was assumed to be a kind of object that could be managed like other commodities as well. The slump was quite sharp and sobering. As one writer of knowledge management puts it, there was no other incidence in industrial history, where such a lot of resources was invested into a new development and the outcome was so pathetic – in any other area, efforts would have been cut short much earlier. Yet, the initially blind faith in the new world of the Internet, networking, knowledge reengineering and the like was so dominant, that it took quite some time to rediscover the missing factor: the human – thinking – being got entirely forgotten and omitted among all the machines, database, “knowledge mines” and networks. While certain efforts even tried to substitute this “working animal” (which was considered more as messy, unreliable, slow, risky), it turned out that it can not be rendered obsolete, but that systems, processes and technology actually must sustain and support the thinking being to soar. Knowledge management has been put back into the place it belonged: an auxiliary discipline at the workplace, serving the “worker”.

Quickly it became apparent, that the individual and his/ her knowledge (and thus the “hosting” institution) benefit strongly from the interaction with others – obviously a truth that builds the basis of all forms of learning and teaching. It was acknowledged that in many situations, the interaction with peers had tremendous effects on creativity, lateral thinking, innovation, efficiency and effectiveness. The true potential of knowledge management did not lie in accessing the individual “expert” (in the broad sense of an ingenious, experienced, knowledgeable person) but precisely in helping him/ her to overcome their “isolation”: the idea of community became key.

The most recent expansion of the concept and scope of knowledge management was the one into systemic thinking: the turning point was to accept that it’s actually living systems, that contain and embody knowledge. It was key to recognise that knowledge is not confined to individual brains. In opposition to the initial assumption of knowledge being an object, it was recognised that knowledge has very much a volatile characteristic, rather a process, in constant flow and morphing and that it actually rather appears in the interaction and relationship between individuals and thus is property of a system as a whole. As much as this may appear a rather academic discussion, as much is it a real world issue with concrete practical implications – in fact it was the observation of failing practical concepts lagging behind expectations in terms of impact (eg. the aforementioned “black hole” of the first days of knowledge management) that drove the knowledge management evolution. And as a source of “frustration”, wrong conceptual assumptions were identified – like the one of knowledge having a shelf life like any object, which turned out not to be the case. As Kurt Lewin put it, there is nothing so practical as a good theory – however, if the theory is wrong, then the practices won’t work out.

In other words, the scope, the perspective of knowledge management did constantly jump to broader circles of engagement:

Circles of Engagement in KM

In concrete terms, this evolution has been framed in three generations of knowledge management. Different authors have defined them in different ways. Peter Senge, the chair of the Society of Organisational Learning (SoL), had nicely described the first shift:
„The first generation of knowledge management has come and gone. The second generation, which promises both deeper insights and greater impact, will be less about data and more about the social nature of knowledge, less about ‘capture and retrieval’ and more about innovating and sharing, and ultimately more about know-how rather than know about – the only knowledge that ultimately matters in any pragmatic institution.“

The next shift from the second to the third generation could be described analogous, promising deeper understanding of the holistic functioning of social systems. While our machine-based ideas of society, organisations, communities and other institutions with their mechanistic perspective have largely failed in being helpful and having real impact, the organic perspective is looking more at complex dynamics, that rely on probabilities rather than certainties, on sense-making rather than reductionism, on facilitating interaction and collaboration of social entities and human beings rather than command and control.

The First Age Information for Decision Support
(Prior to 1995: computerisation of major applications)
The Second Age The Humanisation of KM
(The human side of KM was emphasised)
The Third Age The Organic Age of KM
(Complexity theory, understanding of organisations as learning and living, complex entities)

After Ungerer, Herholdt and Uys: Leveraging Knowledge-based Assets, Knowres Publishing 2006

The three generations can be broken down along various lines:

3 Generations of KM

With this shift from generation to generation, knowledge management also closed up more and more with its twin disciplines of change management and system transformation – based on the insight, that in a pragmatic institution, learning on the basis of knowledge sharing must be an inherent part of effective change processes, while each knowledge sharing process must lead to actual change if it does not want to turn out pointless.

System improvement and change management in return have come along way recognizing that the best and most effective way to improve impact in complex social systems is to have all the members (“view holders”) of a system jointly and collaboratively working on it in order to ensure seizing its complexity and diversity. Yet the most effective way is not by addressing the issues (“problems”) as individual parts, but by gaining an understanding of the system and its interactions/ dynamics as a whole and by identifying opportunities, possibilities and potentials.

Weisbord's Learning Curve

Source: Marvin Weisbord (1987): Productive Workplaces, S.260