Knowledge-at-work

Finding KM

Chris Macrae asks:

so what is your love for KM about?

My answer:

I suspect there are many who have arrived at KM via this path.
My interest started in 1985 when I first heard of expert systems, embarked on a journey of discovery that I clearly recognize is still very much underway.

Early years
A fascination with the power and promise of capturing expert decision principles and heuristics. Helping others take a major leap forward in their competencies. Thinking all you needed was to apply the 'best' rational thinking and you were for ever made.

Built fragile, brittle, well-bounded decision support systems. Thought I had the kernels of 'true' knowledge captured in the rules, a proven process for (measurement) & continual refinement, a representation that delivered inference and promoted learning. Boy was I ever wrong!

Middle years
A gradual awareness that knowledge was not in the rules (or the frames, cases, predicate logic or mined document repositories), something far more intractible was at work. Engaging in the web, first e-mail then bulletinboards, newsgroups and listservs, then MOOs and MUDs and morphing to web based conferencing. Discovering networking, learning about creative abrasion and the wonder of asynchronous dialog, moving from sharing the good stuff to collaboration and co-creating it.

Current journey
Slowly understanding knowledge is emergent, ephemeral, constructed and largely tacit. Looking for deep dialog that signals new connections, searching for knowledge spaces, community and collaborative writing genre. Falling into and out of exciting conversations across the internet, trying to sample the spaces where advanced knowledge practices are explored, verified, lived and improved upon. More and more aware that learning is a social activity.

http://www.voght.com/cgi-bin/pywiki?PersonalKnowledge

Thinking of knowledge as a complex, fractal ecology of ideas, memes, thoughts and assumptions.

Right now
* interested in design of living glossaries and making language distinctions
* crafting patterns that capture quality solutions and specify the application context
* excited by the diversity of blogging and distributed, syndicated, persistent conversations

http://denham.typepad.com/km/

* searching for social affordances that foster knowledge creation

http://www.voght.com/cgi-bin/pywiki?SocialAffordances

* aware and wary of individual epistemologies that gloss over the role of relationships, downgrade the importance of social capital and downplay empathy and ethnography
* reflecting on just how slippery knowledge is and
* wondering why so few are drawn to this basic quest, see or appreciate the value of working with knowledge vs. information and why KM has lost it's allure.

So may I too ask, what exactly brings you to KM?

Harvesting knowledge - can we really do it?

Why harvesting is the wrong metaphor

Knowledge is not an object, it is ephemeral, emergent, very relationship & context dependent. To get someone to share their 'knowledge' you need to have their trust and they must be motivated to spill the beans. Knowledge is not something that has a separate existence - you cannot grab or contain knowledge - it requires dialog, community, time, testing & verification to develop and evolve.

Many companies are climbing on the continuity management bandwagon, riding the demographics as the boomers begin to retire and there are dire predictions of severe erosion of institutional memory and organizational brain drain. Let's revisit their arguments:

* identify your experts and asses your risk of knowledge loss - really hard to do for tacit knowledge
* have a plan to harvest ahead of retirement and loss from job changes - expensive, risky and gives uncertain results
* capture and package your knowledge assets before it is too late - there are deep issues here
* leverage your knowledge capital - difficult to do without a community
* speed new employee learning and induction via access to collected knowledge - a myth

The difficulties of capturing and depositing 'knowledge' are well documented. Acquiring understanding and meaning depend on context, exposure and continuous dialog. Knowledge is best 'preserved' or stewarded within a community in the form of stories than in a repository in the form of assertions, rules, examples or patterns. Knowledge is emergent, it flows via relationships and dialog, it requires interpretation to be surfaced from information, it needs a shared context to be explicated and validated.

Tools that claim to harvest knowledge are little more than templates with generic questions and following a prescribed process. Knowledge acquisition is hard, takes a long time and requires domain expertise (enculturation) for effective transfer:

* colleagues and staff are wary of giving up their tricks and tips. There must be a suitable culture and climate in place
* most of the really valuable heuristics are tacit in nature - the experts are not aware and then cannot explain how they do it
* true knowledge is not static, it is outdated at the moment of capture as the environment changes
* what adds value and makes the difference is the expert's ability to handle new problems and make novel distinctions - this cannot be captured
* experts rely on a large invisible personal network to keep them aware, to validate their ideas and to surface new solutions - when the expert departs, they take this network with them or at the very least the social capital that enables network cannot be easily regenerated
* something is always lost when you represent the knowledge - there are subtle trade-offs, language substitutions, issues with context specification and it is impossible to record all the connections that make emergent knowledge so rich.

Much of the early work in knowledge acquisition and elicitation was connected with expert systems, but this approach was found to be 'brittle', it required well-bounded static domains and was unable to incorporate learning. A far more promising avenue is to encourage communities of practice where informal and social learning happens and staff gather around a set of issues and capture their joint expertise through doing and being.

Here some knowledge harvesting tools - take a tour for yourself:

* Cerebyte
* Knowledge harvesting
* Knowledge elicitation
* Knowledge acquistion - AKT

Idea management

"Most Knowledge Management work deals with the organization and structure of information, which, when done well, helps improve productivity and reduces rework and mistakes. A company's future, though, is determined by creativity and innovation, and harnessing the resourcefulness of people to create new knowledge."

[Source]

Recently idea management has seen attention and activity as a forward-looking component of KM. A focus on sharing ideas, gathering converts, embellishing, vetting and finding champions, monitoring progress, providing feedback and enabling escalation has helped to move companies from sharing existing expertise to fostering innovation.

Idea management software is but a small jump from well-established implementations for dealing with call center issues and resolving customer problems. Consider:

* A 'noticeboard' to inform the business of ideas received & in motion
* Assigning 'ownership' and establishing attributation
* Gathering interested parties who identify with the meme and wish to contribute to its realization
* Having a space for packaging the raw idea - brainstorming, dialog and publishing
* Finding or appointing a corporate champion to launch the idea, gain funding and steward the project
* Enabling automatic escalation so good ideas do not languish in some backwater or become mired in politics
* Providing periodic feedback to the progenitor(s), recording and acknowledgement of their IP
* Capturing context, rationale, connections (to other ideas) and ROI
* Providing a repository and a system for portfolio management, valuation and legal protect of the firms intellectual assets.

Here are some links to this emergent genre from the KmWiki

BTW please feel free to comment, hack and deposit your ideas.

Knowledge searching

It may be a little passe, but the Johari window in its many re-incarnations, remains a useful reminder when looking at personal or organizational knowledge.

Knowledge assets

There are a number of variations depending on where you are coming from e.g. this next one that considers

Modes of discourse

or this more common 2 x 2 matrix that looks at:

Knowledge and certainty

Translation:
KK = what you know you know
KDK = what you know you don't know
DKK = what you don't know you (already) know
DKDK = what you don't know, you don't know

There sure is something elusive, futuristic and a little scary about contemplating what you don't know, you don't know. This is the provenience of environmental intelligence, awareness, discontinuous change, weak links and left field emergence. The window you need to pay most attention to if you are not to be caught napping - reflection of a very different kind.

KM Frameworks - do they work?

When last did you delve into a lengthy KM framework document? Been following the progress of Standards Australia's efforts? (BTW you have to buy this one). Are you a fan of the Frid framework from the Canadian Institute of Knowledge Management (V3.0)? Perhaps you have worked your way through Hubert Saint-Onge's "Leveraging Knowledge for value creation - a framework to guide the formulation and implementation of a knowledge strategy"? Maybe IBM's CBI Knowledge Management - a real business guide is your forte? You may be a fan of the European KM Forums, many publications? The KMCI's KLC could be the framework you most identify with?

"To date, guides for good KM practices have been developed. Chairman for the British Standards Institution (BSI) and CEN KM Standards Committee, Mr Ronald Young informed the participants of the development of the PAS2001 – Knowledge Management: A Guide to Good Practice. Mr James Thomson, Projects Manager of Standards Australia International (SAI) also shared that a handbook “Knowledge Management: A Framework for Succeeding in the Knowledge Era” has been published by SAI."

"The difference between a successful and unsuccessful organisation is not the processes or the quality standards. The things that make a difference are the ability to make timely decisions and the ability to create the space for innovation. This is actually what knowledge management is about," said Mr Snowden.

Source

Assumptions and prescriptions

What strikes me about all these frameworks is they are almost all the same and they miss the boat as Dave Snowden says. Take a look:

* What is knowledge, what is KM?
* The context and the current drivers
* Why you need a framework, stress alignment with business goals
* Their particular process: some variation of find, capture, validate, distribute, share & feedback
* They all recommend some technology and/or communities of practice
* Follow some well-worn track - lessons learned, best practices, peer assists
* How to track & measure knowledge assets and a focus on various 'capitals'
* The benefits

What they seem to miss:

* No way to identify, deal or work with tacit knowledge
* No appreciation for emergence, intuition or handling exceptions
* Little thought given to cultivating awareness, innovation, creativity and learning from failure
* Few ways to learn socially, collaboratively or in community
* KMs contribution to agility, listening to customers, business intelligence and understanding markets is minimal
* The importance of relationships and personal identity in knowledge flows and exchanges is unrecognized.

Resources:

KMCI's The new knowledge management
Standard Australia's Interim KM standard
BSI Knowledge Management - A Guide to Good Practice

Paradigm change in knowledge management

So what do you think?

Boundary objects and KM

Boundary object (BO), originally introduced by Starr (1989), is a concept to refer to objects that serve an interface between different communities of practice. Boundary objects are an entity shared by several different communities but viewed or used differently by each of them. As Star points out, boundary objects in an organization work because they necessarily contain sufficient detail to be understandable by both parties, however, neither party is required to understand the full context of use by the other - boundary objects serve as point of mediation and negotiation around intent.

Boundary objects are flexible enough to adapt to local needs and have different distinct identities in
different communities, but at the same time robust enough to maintain a common identity across the
boundaries to be a place for shared work. Boundary objects are not necessarily physical artifacts such as
a map between two people: they can be a set of information, conversations, interests, rules, plans,
contracts, or even persons.

It is around BOs that Communities of Practice (CoPs) often gather. BOs are 'used' by members of different communities in very different ways, although the representation is shared. BOs are an important class of knowledge artifacts. They are center stage in the dynamics of knowledge exchange. BOs are also known as CISs (common information spaces).

Examples:

Reports are a classic example of traces as boundary objects that the professionals and other members share. Faxed documents and email massages are also the boundary object among distributed members.

Information spaces, where particpants gather to exchange information, co-ordinate activites and create knowledge are another example of BOs

A library catalog, an order entry process, travel assistance request form, an organizational knowledge map, i.e. one of the products from your knowledge mapping project!

Mapping BOs:

Boundary objects are a very useful way to structure and frame a knowledge mapping project. When you are identifying & tracking BOs be aware of issues around translation, closure, context, shared meaning. It is around BOs that Communities of Practice (CoPs) often gather. BOs are associated with process, meaning, participation, alignment and reification. They are thus center stage in the dynamics of knowledge exchange. Here are some pragmatics:

* Gather the name (this may change from community to community)
* Describe and record the roles, activities, authorities and responsibilities around the BO
* Map the workflow, the path and sequence from node to node
* Look for signoffs, trigger events, deviation heuristics and hand-offs.
* Check for learning points.

Record your findings in the BO register and on the knowledge map.
Having identified the boundary objects, mapped their flow, recorded their particulars in your register, you are now ready to tackle the next knowledge mapping step, mapping people. I recommend starting a knowledge mapping exercise with BOs for the following reasons:

1) It is not a personally sensitive area, gives you time to meet the staff on neutral ground.
2) BOs quickly highlight, bottlenecks, repositories and communities of practice.
3) Prepares the way for the more detailed personal interviews, you already have an understanding of the main objects, i.e., 'what' the staff are working with.

Some of the dynamics that boundary objects help structure

Ecology or library?

When working with knowledge it is more useful to picture an ecology, than to envision a library - think links, relationships & flow rather than collections, classification & objects

The Meaning of Knowledge Ecology

Knowledge Ecology represents a fundamental shift in current thinking, moving away from a knowledge management (KM) focus on "bottom line" challenges of assessing, organizing, leveraging and profiting from knowledge towards a more social or "community" orientated paradigm, utilizing the synergy between technology and human intellect / innovation

Knowledge Ecology (KE) is a metaphor, a perspective, a design approach, an emergent paradigm and a field of study that recognizes the importance of relationships, the diversity of knowledge forms and types, and centrality of community when working with knowledge. It is ecological in the sense that the best models that we have for organizational designs that create, sustain, and foster the growth of knowledge are natural "learning organizations", for example, ecosystems, brains, plant and animal 'communities'.

"Knowledge ecology" (KE) is an interdisciplinary field of management theory and practice, focused on the relational and social aspects of knowledge creation and utilization. Its primary study and domain of action is the design and support of self-organizing knowledge ecosystems, in which information, ideas, and inspiration cross-fertilize and feed on each other.

For more information about KE, please look up the Knowledge Ecology section of CoIL's Knowledge Garden http://www.co-i-l.com/coil/knowledge-garden/kd/index.shtml

The leverage of KE is:

Its focus on culture, social practices and relationships when working with, developing, exchanging or applying knowledge. This focus inherently facilitates behaviors understood to be needed for the development of "learning organizations".

The recognition that knowledge creation, meaning and use are dynamic processes that emerge from interactions between people in communities and social structures. These processes loose a measure of quality, quantity and value when they are captured (turned into information) in objects & structures other than functionally interacting groups & organizations.

The Core Idea of Knowledge Ecology (from CoIL)

Individuals and organizations can intentionally craft developing and evolving webs of relationship in which to embed and preserve the evanescent knowledge that is always inherent (and has always been inherent) in our conscious cooperation together. The preservation of evanescent knowledge is recognized as learning. Organizations that successfully exhibit this behavior are "learning organizations."

Using the leverage of Knowledge Ecology - putting "living systems" thought and "living systems of thought" into practice - the higher purpose we hope to serve is:

To transform existing organizations to model what is possible in a complex, living, learning systems.
To facilitate the emergence of our individual and collective capacity for constructive, creative action in ourselves and the organizations in which we participate.
To manifest our aspirations more effectively than "old paradigm" approaches, actually increasing what is possible and collectively enabling our endeavors to provide the value that our individual potentials only promise.

Through design and practices consistent with this thinking, we can increase the intelligence, the knowledge creation possibilities, the sustainable action capacities which will result in continual increases in knowledge and its application for individuals and for our human institutions.

For a deeper discussion see: Contrasting KE & KM at my KmWiki

I'm keen to hear your thoughts and views on this

Organizing knowledge ?

Getting the perspective right

Far too many times KM efforts focus on information attributes. We slice and dice our explicit knowledge assets to deliver JIT information and believe we have met our knowledge related goals - wrong!

Knowledge, we all know (or maybe feel), is different and distinct from information. It's properties are less stable, more difficult to validate, less easy to identify, more closely tied to intangibles, heavily dependent on context, often unarticulated. Sometimes knowledge is situated, distributed, emergent, latent, ephemeral, dormant, unrecorded, tacit, embedded, found in 'flow' not as a static object, follows relationships rather than residing in any particular location.

When we 'organize' knowledge we also lean heavily toward the view of knowledge as an explicit already existing object, a static slowly-changing thing, something tangible, locatable, we start to focus on ownership, access, indexing, navigation, classification, metrics, value. These qualities make knowledge organization problematic.

Let's start by looking at the range of representation(s) you may be working with:
* Stories
* Patterns
* Distinctions
* Metaphors
* Rules
* Frames
* Schema
* Concepts
* Events
* Beliefs
* Mental models
* Cases
* Good practices
* Lessons learned

Each of these has optimal ways for organization (sequencing, indexing, clustering, classifying, browsing) that in turn depend on the range and intensity of the practices / operations that may be applicable or which are to be performed consider:
* Awareness
* Synthesis
* Reflection
* Sharing / transfer
* Critique
* Learning / making meaning
* Understanding
* Taking decisions
* Clarifying meaning
* Inquiry / searching

In addition these issues may muddy the waters:
* Context
* Application
* Feedback / followup
* Interpretation
* Users / audience buy-in
* Needs
* Time limitations

Could we be looking in the wrong place when we seek to organize knowledge?, we may be asking the wrong questions, adopting a rather poor model or applying an ineffective metaphor.

Perhaps we should seek to understand the flows, characterize the dynamics, map the relationships that foster emergence, find the connections that promise awareness, search for those tacit foundations that nurture knowledge creation, pinpoint mavens, hubs, connectors, and locate learning friendly communities?

Would conducting an inquiry be a better way? Just a thought

Ontologies

What the heck is an ontology???

A (shared) expression of belief, an agreement on the terminology (and sometimes the meaning) for communication and action. Ontologies serve to bound discourse, facilitate communication within & across communities and networks, leverage action by gathering agreement around meaning, values, objects, the way things are and what is 'out there' that is important. Ontologies help to orientate new folks and act as the stores for key learnings & distinctions accumulated through experience. Ontologies have a large influence on identity and help with the tacit transfer of context. Ontologies IMO are destined to become a very influential part of knowledge work as the semantic web evolves.

See this article on ontologies and XML: http://www.semanticweb.org/knowmarkup.html

Ontologies hold promise for:

* Providing a common language for different parties
* Improving communications through sharing meaning and raising social capital
* Increasing alignment and leveraging self-organization via shared understanding
* Providing an enterprise wide schema for intuitive navigation
* Being able to leverage language as a tool
* Helping communities of practice to improve their dialog and make key distinctions
* Sparking innovation, helping to recognize emergent concepts, knowledge gaps and improving relationships

So where do I start?

Look for an existing ontology and see if it will do or if you can adopt it for your work. Think about people before you jump into selecting a tool or a representation. Get buy-in from key users, stakeholders and identify evangelists. Start small, begin with the familiar construct a glossary, identify key terms, focus on immediate issues, map out the domain before you dive into definitions and become mired in language differences. Avoid becoming the word police

Work on terms that carry high value to the group / organization, i.e. emergent concepts that spark awareness, troubling terms that help clarify common communications, important concepts that carry many names or terms that are used in different ways. Strive for emergent consensus rather than imposing taxonomic 'laws', look for areas where standardization will give immediate benefits e.g. XML markup, computer application integrations, multi-agent processes, e.g. outsourced operations or joint-venture projects.

Here is an article on ontology development

Resources:

* Sebastian Paquet
* Ontology at Buffalo State
* KM through ontologies
* Christian Ohlms, McKinsey & Company
* Corporate memory & ontology

Knowledge landscapes

Caution: this post may bring to you to unknown places!

Take a ubiquitous metaphor, transform it to accommodate new meanings, apply reasoning to the emergent framework and see where you wind-up.

a useful knowledge production pattern or a stream of nonsense!

Landscapes with their fitness gradients, their species niches and evolutionary selection, give a whole new meaning to the term knowledge ecology - memes & genes - will talk about this another time.

Knowledge accumulation can be likened to travelling through a landscape. There are hills and peaks to climb (gaining understanding and competence), valleys and plains to cross (mastering unknown or novel environments), a sense of urgency pervades (local competition). We are driven by identity, curiosity and necessity to explore wider and further. Error, poor judgement (miss-reading) and economic disturbance can result in us being forced to descend from comfortable lofty peaks to wander in the lowlands seeking a new hill to master.

FROM FITNESS LANDSCAPES TO KNOWLEDGE LANDSCAPES By David Oliver and Johan Roos, 1999

Examines the relationships between topography and knowledge. I find this to be a useful way to picture the dynamics of knowledge gains and the need to unlearn before gaining expertise in an adjacent or new field.

Knowledge landscapes apply to individuals, groups and organizations, there are the same fractal qualities we observe when moving up-scale from sand grains to rocks to mountains, the same linkages, relationships, competitive games, sources and sinks that characterize personal KM, CoPs and organizational learning. Often we become stuck on a local plateau, unable to find the real mountain top, or face deep ravines we do not have courage to cross in our knowledge 'walks'.

Metaphor and analogy are powerful tools for working with knowledge. Often times it seems to me, our fitness landscape is not only complex, but heaving at the same time in the knowledge world!.