Knowledge-at-work

Community of one?

In a recent article, Steve Barth makes the case for mastering ‘mundane’(PKM) tools and techniques before individuals can really contribute to community knowledge practices. Steve recalls that "we can each only perceive our networks from the perspective of our own nodes."

To my way of thinking there is something strange with practicing in a community of one. Here is why:

* Self-elicitation is an endless circle to nowhere

* Real key discoveries / connections / synergies mostly require triggers from outside ourselves

* Personal reflection is a poor substitute for testing & emergence in dialog

* Sense-making is tied to insightful questions, adjustment after feedback and learning from experience.

Getting into a personal huddle, organizing your thoughts and reflecting on the personal past can easily take you away from awareness of real flow and emergence - where it all happens. I'm saying you need to have social mediation (validation, testing, acceptance) before individual 'knowings' becomes knowledge. There are many people who experience very strong individual 'knowings', but society regards their 'knowledge' as ravings and places little value on any personal 'knowing' which is not socially mediated.

The key to knowledge work IMO is community, where you share, create, critique, validate new connections with others. Arranging reflecting and organizing your personal beliefs, perceptions and values without sharing is NOT KM as I see things.

For me, a PKM tool or exercise hardly makes sense as knowledge is emergent in practice and dialog, knowledge is social rather than personal, needs verification and is difficult to capture. At a personal level, practices may be many times more important that tools, e.g. reciprocity, sharing, listening, supporting and coaching others, being well-linked and connected, being in dialog & the flow, inviting critique, engaging in creative abrasion. – not things you can do alone on a desert island or in your individual cube!

Previous PKM thoughts.

More KM and e-learning

The interesting areas of overlap IMO cover social learning, communities of practice and peer to peer learning.

There is a close relationship between e-learning and KM as both domains seek to increase awareness, increment competencies, stimulate innovation and introduce new ideas.

Both areas have tended to focus way too much on the technologies and to move slowly on the cultural issues, both need to find ways to deal with fundamentals such as shared meaning, identity, delivering useful context, discovery and emergence via dialog and self-motivation.

KM and e-learning share this duality around personal vs. group processes, how to find the balance and where to focus attention and energies. In KM, this is articulated as personal knowledge management (PKM) and in e-learning the mantra is self-directed or paced learning (SDL). If you share the view that knowledge is a social construct and all learning requires validation and feedback - you may question the utility of PKM & SDL directions taken to the extreme.

These areas share many practices and tools, think of AARs (after action reviews), lessons learned, case studies, capture & sharing of experience via stories and pattern languages, mentoring. Web conferencing, IM, blogging, Wiki, groupware, best practice repositories, FAQs are examples of technologies that cross the boundaries.

Marc Rosenberg's book - "e-Learning" - currently leads the field in this area IMO.

Sharing understanding

Takes time and commitment to share understanding or knowledge. Takes engagement from both parties, there must be some form of 'fair' exchange and more 'action' than surface interpretation.

In a formal education environment, this motivation is helped by the fees you or the government pay for sharing content and formal assessment. In the wider world, you will have to ask engaging questions to build reciprocity, keep energy levels high, perhaps by adding a little creative abrasion.

What then are some of these barriers?:

1) expert(s) often do not know how to tell what they know - often they do not know what they know, it is tacit

2) experts do not know what you do not know and often they are unaware of what they know that can help until it is surfaced via dialog & inquiry.

3) expert knowledge consists of complex patterns in context, they make an intuitive leap to interventions and solutions after finding & matching patterns based on 'fuzzy' conditions.

4) there must be a common language, not just speaking the same words, but some appreciation for the others mental models, assumptions, values and goals.

5) there must be a clear expression of 'need' and gaps, often non-experts lack the background & structure to express their knowledge and information needs and must be helped to 'see the larger picture'.

Barriers to using explicit knowledge / information to promote shared understanding:

* no joint purpose or mental models
* no shared distinctions, assumptions and meaning
* no engagement in community reflection and feedback
* no opportunity to feel, experience and practice
* no way to learn from failure

May I suggest you read a review article on interpretation or the writings of Douglas Hofstadter. This will give you a feel for the issues of being receptive to different meanings in a textual or visual medium.

Stealing knowledge

Can anyone steal your knowledge?

In my understanding of knowledge, i.e., a complex linkage between context, information, personal frameworks and social mediation; it can never be stolen. Sure you may have your ideas copied, your information and documentation purloined, your opinions replicated without attributation, but it is just not possible to duplicate your 'thought engine', your unique perspective, reverse-engineer your experience, or your ability to make new and more valuable connections.

These abilities / qualities help to set knowledge apart from information and data.

Documentation & knowledge

A oft repeated question / assertion in KM is the link between explicit documentation and knowledge.

The point I'm trying to make, is documentation alone does not = knowledge. To retain knowledge against attrition you have to have a community that can appreciate the context, understand the issues, talk the language, adopt the assumptions, share the tricks, interpret and adapt the explicit stuff to changing external circumstances.

Agree we need to know how to make things and deliver services, but that knowing does not come from documents, it emerges in the dialog around the practice. To capture and preserve the knowledge, - not the data or information, - but the meaning and shared understanding, you need to sustain the community, energize the questions and promote the learning, rather than capturing content or storing the document.

It is around the tacit stuff; what you may feel, observe, intuit and never 'see' or read, the relationships, the mentoring, the validation by talking, by 'being' and through doing, that creates and finally preserves the knowledge. If we loose the 'community', we revert to information and have to bring forth the knowledge in another community to enliven, validate and refresh it.

If you still have doubts read Doug Hofstadter

Knowledge representation - reification and hiding

Knowledge representations are difficult to grasp, subtle in what they empower and hide, essential for sharing, but so useless for transfer of key tacit stuff

Representations both clarify and hide. Reification as text, graphic or video will enhance certain qualities, reduce or dampen others. We have no visible, tangible representation for the largest, most individual and important (tacit) part of our knowledge. Representations are material, they reify or allow ideas and experience to have an independent existence in an externalized form, they help to capture emergent thought. Like a lump of clay, a representation is tangible, it can be pointed to, passed around, played with. It takes thought experimentation one step further, eliciting new ideas.

There is a subtle trade-off at work here: the more natural the representation (e.g. stories, conversations, sketches) the lower the inference power, i.e., the ability to reason, position and manipulate. Yet it exactly these ephemeral, informal, emergent forms that assist and nurture the flow of knowledge. Passing and sharing knowledge through formal representations (e.g. rules, cases, predicate logic) is difficult, brittle and a battle to fit, find and preserve applicable context.

Our quandary is we badly need a representation to scale sharing, serve as a container, preserve emergent ideas and foster collaboration. When a representation crosses boundaries, there is a loss of meaning (reification) and context, which is counter-balanced by an opportunity for new negotiations, different views and altered meaning. This points to the importance of establishing rationale & context in use or practice, an essential non-represented aspect associated with any formalism. All representations are situated in use.

Some examples of representations are:
* Stories
* Boundary objects
* Cases
* Lessons learned
* Topic maps
* RSS feeds
* FAQs
* Patterns and anti-patterns
* Knowledge / learning objects

Representations are both important and a side track for KM work - knowing what you sacrifice when choosing and using any knowledge representation, is a subtle, invisible, often unacknowledged, and yet cardinal competence in any form of knowledge work.

Reification

So what is reification

Another form of reification is creeping into the workplace in the guise of 'process'. The industrial process is being invested with roles, beliefs and rituals that tend to make these abstract objects into super 'knowledge artifacts'.

Consider a supermarket transaction. You are positioned alongside 'pick me up articles' to increase you likelihood (or your children's or spouse's) of an impulse buy. You are offered (or enticed by rebates) to proffer a store card to capture your demographics so the store can enhance their psychographics and sell your purchasing information back to merchants.

Just think of the energy, thought, technology and human investment tied to that single transaction. There is the cashier taking your money, the scanner taking your information, the data warehouse technician crunching your impulses, the store wide analyst pondering your buying rules, the logistics manager ordering replacements, the shelf packer filling the gap, the chain buyer trying to second guess your next visit and co-purchase......

We are witness to the rise of the reified process, the super knowledge artifact, we embed our learnings, infuse it with our ideas, invest it with our time, depend on it for survival, become constrained by our role. We rely on it for our identity and identify with it for our being & meaning.

We praise, curse, abuse, invent, deny, co-evolve and conspire with this complex, highly connected, ethereal thing. We invest energy, identity and being, perform rituals, make meaning, reify and create knowledge.

We make knowledge artifacts!

Thinking k representations

Can we really capture and represent knowledge?

Do (symbolic & artifactual) representations hold meaning and knowledge? I do not believe so - unless the artifact is co-designed and co-created by a community. Even then, the essential meaning must be refreshed by reflective rituals and validated as an ongoing practice.

Consider a wine product
No sherry or wine (artifact) tells us the whole story, the energy in the sunlight, the climates past that shaped the vine, the vintner’s knowledge that made that special color or the oak vat that imparted the flavor. Those are not things that can be captured in chemistry or completely revealed through product analysis or reverse engineering - they are a situated part of the community & ecology of wine making.

Mediating in collaboration
Prototyping, 'strawman' and mock-up activities (reification) allow participants to draw on their experiences and practices more directly than abstract descriptions. Representations mediate the relation between collaborators and their products, between individuals in a group, between the group and their sponsors and between the group and their users / market. Once captured in a representation, there is a resistance that sets in as descriptions are manifest & objectified that tends to balance the affordance offered. It is the multitude & diversity of interpretations that carries the strength of a representation rather than consensus around shared meaning.

Representation as container
Boundary objects (concept maps, ontologies, source documents) serve as a vehicle, container and carrier, for ideas. When a representation crosses community boundaries, there is a loss of meaning and context, which is counter-balanced by an opportunity for new negotiations, different views and reconstructed / emergent meaning. Points to the importance of establishing rationale & context in use or practice, an essential non-represented aspect associated with any formalism. All representations are situated in use. An important aspect of a memory object is its trajectory, i.e. the consequences of later use and the feedback loops.

So then how exactly do you store, capture, preserve and scale knowledge?

KM sub-culture?

There is a whole league of influential KM folks that seem to operate below the Brint radar. Here I'm thinking of on-line players and personal (blog) publishers e.g.

Bint's list of 58 top KM folks

KM bloggers

If your measure is google number, then these folks have far higher rankings and need to be mentioned.

Showing my ignorance, I'm asking exactly who are?:

Szulanski G
Blackler F
Barney J
Huber G
Kogut B
Cohen W
Daft R
Winter S
Stein E (corporate memory guru?)

And where are, or what about??:

Don Cohen,
Wayne Baker,
Phillipe Baumard,
Edwin Hutchins,
Douglas Engelbart,
Susan Leigh Starr,
Johan Ross,
Humberto Maturana,
Francisco Varela,
Douglas Hofstadter,
Edgar Schein,
Nancy Dixon,
Joseph Novak,
Michael McMaster,

Seems the Brint list may be highly selective in terms of KM contributions and influence, favoring traditional authors over internet publishers and information systems people over true knowledge workers
IMO.

What then are your thoughts / opinions?

Knowledge competencies

What skills and abilities are needed to make KM work?

1) Wrestle with the meaning of knowledge until you feel & understand it.

2) Walk your talk with knowledge practices, share, search, structure, make meaning, learn, seek connections, teach & collaborate.

3) Understand the dynamics of knowledge through participation and engagement, validation of claims, practice deep dialog, hold you identity in check, exchange and suspend judgment, help others to understand, build prototypes, make clear distinctions

4) Work with the available tools and systems, compile yellow pages, assist with gathering customer insights, collect and value idea exchange, craft patterns, share insights.

5) Appreciate KM is all about people, their trust, respect, recognition and motivations, lead by example, have empathy, share, give and help.

6) Reflect in community on ways to work with knowledge (representations, inference, connectivity, access, virtual spaces, awareness)