Nancy Dixon's new book gives 5 knowledge transfer methods that result from the interaction between the intended receiver (similarity of task and context), the nature of the task (how routine & frequent) and the type of knowledge (explicit vs. tacit) being transfered.
Serial transfer: Same team, same task, different settings. After action reviews, learning histories and set meetings, open diaglog, local facilitation.
Near transfer: Explicit knowledge of frequent & routine tasks moved across organizational boundaries. Electronic dissemination, supplemented by personal interaction, 'push', best practices are shared where context is not an issue.
Far transfer: Tacit knowledge is moved by coaching and consulting, same task different context, reciprocal exchange, peers travel to assist.
Strategic transfer: Infrequent and non-routine, complex system, knowledge is gathered by specialists, multiple 'voices' are synthesized mostly in realtime.
Expert transfer: Explicit knowledge is pulled from forums, summarized and recorded in terms of solutions, rules and distinctions. Context is the same but the task differs, e.g. technical questions to 2nd level helpdesks.
Somehow the whole notion of knowledge transfer does not sit too well with me, feels too much like an object is being exchanged rather than an individual or group learning experience! Are we starting to see greater clarity and the emergence of some KM theory here? I'm thinking of Dixon's transfer types, KM models from Don Mezei, Bo Newman and others, knowledge validation practices from KMCI, ontologies and classifications of tool sets, KM strategy options.....
Task characteristics and knowledge sharing:
Nancy uses, how routine the task is, not in the sense of similariry, but how easily the task can be expressed in terms of explicit steps and the frequency. These are important attributes for knowledge transfer (along with an appreciation of key changes in context). I'm not so sure these are the best task characteristics when we look at learning and knowledge sharing, which are important aspects of to consider when looking at transfer in a holistic (ecosystem) perspective. Here I tend to favor the generic task ontology developed by Chandrasekaran and colleagues: e.g. classification, diagnosis, problem solving and others.
Transfer & learning:
There is little attention to reciprocity, dialog and generative knowledge exchanges in Nancy's categories. I get the feeling Nancy favors knowledge transfer as passing objects and only recognizes transfer resulting in greater than the parts in "far transfer" (tacit exchange). Seems in true knowledge sharing there is always some measure of reciprocity, knowledge creation and learning on both sides. One of the most effective ways to share knowledge is to take time to share meanings, surface assumptions through constructing ontologies, practicing deep dialog and crafting distinctions.
I missed FAQs, co-location, yellowpages and boundary spanning between communities as alternative promising ways to share. Knowledge travels via relationships and I think this aspect could have received more attention in the book. Knowledge transfer goes far deeper than just passing information and Nancy's treatment of context and absoption potential was new and through. It is encouraging to see an entire book devoted to this key knowledge practice, think this is an important text, deserving of a place alongside Brown and Duguid's "The social life of information".
Use of simulation and cases, in particular, Time-Revealed Senarios (TRS) are recent advances to assist with knowledge sharing: TRS as used in Wisdom Tools.