Ecological analogies I find are a useful way to view knowledge. They remind me that knowledge belongs in a complex system, that there are stores, flows and sinks, organizational immune systems that awake if provoked beyond a threshold to restore the old order, that knowledge is emergent, complex, dynamic, distributed, situated and still rather poorly understood.
Knowledge ecology:
puts the focus on relationships, people, social learning, and communities of practice. It ties to balance people, practice and technology by encouraging a holistic view of knowledge patterns using analogies to natural systems. KE is sensitive to the fragility of knowledge and adopts a sustaining, cultivating, crafting midset, seeking to leverage generative, collaborative and social learning.
KE is harder and takes longer to implement, the relationships with easily measured, fast returns are indirect and diffuse, the emphasis is on longer term positioning, growing & improving competence, innovation and awareness.
Knowledge management:
looks to maximize intellectual capital, promote competitive advantage and secure returns through investment in advanced information technologies, implementation of content driven systems and re-engineering of processes to capture lessons learned, best practices and customer contacts. Focus is on measuring intangible capital, working with explicit knowledge (information) and leverage via technology.
Knowledge ecology helps to make me aware that there is always some new twist in and around knowledge, that static content does not tell the real story, that emotions, beliefs, rituals, pleasure and pain are all part of the system.
Ecology tells me to look for knowledge analogies of niche players and generalists, to appreciate the power and wonder of cross-pollinators and the dynamics of gene flow, through knowledge ecology I have been exposed to the people side of knowledge which seems to be most difficult and the most promising perspective.
One of the core issues in both KE and KM as I see things is: How to support and cultivate the emergence of creative and generative learning / knowledge? There do not seem to be any easy answers here. I've been searching for winning practices for quite some time and have experimented with these:
Mind and concept mapping: to help articulate, compare and structure individual mental models in a visual manner. Shared cognitive models help to build alignment, promote clearer communication and allow others to build and contribute.
Pattern language: having a (semi-formal)ritual for the publication and social validation of knowledge claims.
Crafting distinctions: encouraging participants to 'bring forth new worlds using language'. We use analogy, metaphor, schemas to generate 'new' perspectives and situate the groups learning’s, this follows from a view that language creates reality.
Telling stories: to capture context, ethics, values and rich messages in a form that is easy to remember, a kind of local oral history.
Conversations: to assist participants opening up possibilities, sharing relationships, engaging in dialog, reflection and inquiry, allowing them to give 'voice' to their unspoken values, insights and beliefs.
Asking quality questions: in a trusting environment, this along with deep reflection, are the two practices that seem to help most with the emergence of 'new' local knowledge, learning, insights and understanding.
Record insights in an ever evolving 'corporate memory': where all have access and edit rights. We encourage direct annealing of the text to meld a common meaning and produce documents that all can support.
There are other important practices around the selection of a linear asynchronous tool, summarization, critique, having explicit idea generations, roles for the collection of questions, insights and commitments, bootstrapping, systems analysis techniques, LH column, learning histories, pair-wise comparisons and more.
We circle round categorization & classification, building identity and crossing community boundaries, making an effort to distill a local ontology, discover meaning and share understandings.
Here is a comparison of KE & KM practices
What has been your experience?
Why can't KM just manage knowledge rather than IC, competivite advantage, or ROI? Is it because you can't sell it without these things? If so then we aren't manageing knowledge, but rather the secondary effects of knowledge and the processes of those secondary effects.
Language issues:
1. KE means destroying all KE outside that approved by the central core of the corporate executive. This is contrary to any real effort to enhance the KE. Even the niche players are selected externally rather than by natural selection.
2. Best practices are actually only practices. It remains to be seen whether they are BEST practices.
3. Creative and generative learning / knowledge is a problem, because again you are talking about the creativity of the approved core. Generative learning does not result in knowledge. It is a generalized process that creates information and might create knowledge, but it doe not inherently create knowledge.
4. The social validation process can facilitate commuications of patterns, but not all patterns are going to be socially validated just because they are patterns.
5. A local oral history would mean that you can't write it down.
6. Giving voice to their values is insufficent and a power-based manipulation. The only thing that results is "I was heard, I was ignored." Dialogue provides a better mechanism, but dialogue only occurs in the absense of power.
7. If trust is required, then the system will fail. There is no trust in today's business environment. I know that I will never trust an employer again.
8. Annealing, what better way to impose a power expression over any insights.
9. Distill local ontology as practiced today is to make meaning conformant to the will of the central core. This destroys the ability of non-line organizations to do their job. This will kill companies like reengineering did.
Posted by: David Locke | January 26, 2004 at 08:25 PM