The puzzle of Enterprise Knowledge
The knowledge management jigsaw puzzleThe knowledge management jigsaw puzzle
Lucas McDonnell gives us 51 pieces of the knowledge management puzzle, and he organizes those pieces in alphabetical order. I might want to order them into buckets by color or shape style or something.
Knowledge management just seems inordinately complicated sometimes, doesn’t it? Like there are so many disparate pieces to the puzzle that we’re not even sure what they all are sometimes.
The list ranges from academic areas of study to activities to technologies and beyond. I'll let someone else group these into a topic map of some sort. Some things I'd like to add
•Writing: The skill of writing has become critically important in a world where people collaborate online. This applies in forums, blogging, online communities, and many other places.
•Presentation skills: Similar to writing, the ability to conceptualize and walk through presentations. Being able to create beautiful presentations isn't the point, but it's nice to have.
•Business Intelligence: I find this topic closely related to KM, when the "knowledge" is the application of domain-specific expertise to large collections of data. It's nice to have good tools, but without the domain knowledge, it may not be possible to pull anything useful from the data.
•Collective Organizing: How do we organize the stuff we collect in a way that everyone can find it when needed?
•Personal Organizing: How can we help individuals manage their personal space, so that they can find things when they need them?
•Incentives: How does an organization encourage the right behaviors? (I'm never sure whether I like the idea of incentives or not. The typical implementation never seems to consider unintended consequences.)
•Librarianship: Several of Lucas' topics fall under the disciplines of library science, but I think it should be called out as a separate piece of the puzzle. Or maybe it is an organizing concept for the other topics.
•Information literacy: One of the elements that library science aims to teach to the larger populace. This is the ability to understand information and how the information made it to my desk.
•Human performance: This might be a stretch to include in the KM puzzle. Study and understanding about how and why people perform, and how to improve that performance. (Also Human Performance Technologies)
•Cognitive science: Understanding of how our brains work.
•Experts: We need the people with domain-specific knowledge, along with the generalists and the connectors.
Knowledge management just seems inordinately complicated sometimes, doesn’t it? Like there are so many disparate pieces to the puzzle that we’re not even sure what they all are sometimes.
It strikes me as being a bit like a jigsaw puzzle. The client has many of the pieces on the table already. Some are joined up. Some aren't. Some pieces are missing. The client doesn't really know what the joined up puzzle will look like - they don't know "the picture on the box". But they know they don't have the full picture, as they are not getting the value they expected from KM.
Read more: Knoco stories: Solving the KM jigsaw puzzle
^ TOP
Knowledge Management Technologies
“With the maturation of the Internet, collaboration and knowledge sharing have become a standard way of conducting business, to the point where enabling technologies require functionality to address these activities,” says Steve Cranford, a director in PricewaterhouseCoopers’ Advisory Practice.It does not only allow company to leverage on the power of knowledge but also facilitate the collaboration culture in the organization.
The Microsoft Sharepoint
The SAP Knowledge Management & Collaboration platform (KMC)
The KMC application
Collaboration
Knowledge Management
Repository
the IBM Social Business platform
^ TOP
Enterprise Knowledge Management Framework
A holistic enterprise knowledge management using Zahkman framework as a thinking tool.
KM model
Before attempting to address the question of knowledge management, it's probably appropriate to develop some perspective regarding this stuff called knowledge, which there seems to be such a desire to manage, really is. Consider this observation made by Neil Fleming[fle96] as a basis for thought relating to the following diagram.
A collection of data is not information.
A collection of information is not knowledge.
A collection of knowledge is not wisdom.
A collection of wisdom is not truth.
The idea is that information, knowledge, and wisdom are more than simply collections. Rather, the whole represents more than the sum of its parts and has a synergy of its own.
We begin with data, which is just a meaningless point in space and time, without reference to either space or time. It is like an event out of context, a letter out of context, a word out of context. The key concept here being "out of context." And, since it is out of context, it is without a meaningful relation to anything else. When we encounter a piece of data, if it gets our attention at all, our first action is usually to attempt to find a way to attribute meaning to it. We do this by associating it with other things. If I see the number 5, I can immediately associate it with cardinal numbers and relate it to being greater than 4 and less than 6, whether this was implied by this particular instance or not. If I see a single word, such as "time," there is a tendency to immediately form associations with previous contexts within which I have found "time" to be meaningful. This might be, "being on time," "a stitch in time saves nine," "time never stops," etc. The implication here is that when there is no context, there is little or no meaning. So, we create context but, more often than not, that context is somewhat akin to conjecture, yet it fabricates meaning.
That a collection of data is not information, as Neil indicated, implies that a collection of data for which there is no relation between the pieces of data is not information. The pieces of data may represent information, yet whether or not it is information depends on the understanding of the one perceiving the data. I would also tend to say that it depends on the knowledge of the interpreter, but I'm probably getting ahead of myself, since I haven't defined knowledge. What I will say at this point is that the extent of my understanding of the collection of data is dependent on the associations I am able to discern within the collection. And, the associations I am able to discern are dependent on all the associations I have ever been able to realize in the past. Information is quite simply an understanding of the relationships between pieces of data, or between pieces of data and other information.
While information entails an understanding of the relations between data, it generally does not provide a foundation for why the data is what it is, nor an indication as to how the data is likely to change over time. Information has a tendency to be relatively static in time and linear in nature. Information is a relationship between data and, quite simply, is what it is, with great dependence on context for its meaning and with little implication for the future.
Beyond relation there is pattern[bat88], where pattern is more than simply a relation of relations. Pattern embodies both a consistency and completeness of relations which, to an extent, creates its own context. Pattern also serves as an Archetype[sen90] with both an implied repeatability and predictability.
When a pattern relation exists amidst the data and information, the pattern has the potential to represent knowledge. It only becomes knowledge, however, when one is able to realize and understand the patterns and their implications. The patterns representing knowledge have a tendency to be more self-contextualizing. That is, the pattern tends, to a great extent, to create its own context rather than being context dependent to the same extent that information is. A pattern which represents knowledge also provides, when the pattern is understood, a high level of reliability or predictability as to how the pattern will evolve over time, for patterns are seldom static. Patterns which represent knowledge have a completeness to them that information simply does not contain.
Wisdom arises when one understands the foundational principles responsible for the patterns representing knowledge being what they are. And wisdom, even more so than knowledge, tends to create its own context. I have a preference for referring to these foundational principles as eternal truths, yet I find people have a tendency to be somewhat uncomfortable with this labeling. These foundational principles are universal and completely context independent. Of course, this last statement is sort of a redundant word game, for if the principle was context dependent, then it couldn't be universally true now could it?
So, in summary the following associations can reasonably be made:
Information relates to description, definition, or perspective (what, who, when, where).
Knowledge comprises strategy, practice, method, or approach (how).
Wisdom embodies principle, insight, moral, or archetype (why).
Now that I have categories I can get hold of, maybe I can figure out what can be managed
A important value of EA is to preserve the institutional knowledge. Most of institutional knowledge is deeply embeded in side a few individual in the enterprise. It vaporized with the departure of each individual. EA is the effort to preserve the institutional knowelge for enterprise to continue on their prosperity.
The Enterprise Knowledge Base
Enterprose business intellegence
^ TOP
Seven principle of knowledge management
The Knowledge grave yardThe Enterprise Knowledge skeleton
Organize Enterprise Knowledge based on Enterprise Map
“With the maturation of the Internet, collaboration and knowledge sharing have become a standard way of conducting business, to the point where enabling technologies require functionality to address these activities,” says Steve Cranford, a director in PricewaterhouseCoopers’ Advisory Practice.
It does not only allow company to leverage on the power of knowledge but also facilitate the collaboration culture in the organization.
The Microsoft Sharepoint
^ TOP
Introduction
Knowledge is power. However, Acquiring a knowledge management tool is only the beginning.EA is a holistic approach to manage the enterprise knowledge. It is a type of knowledge management practice tailor to manage the knowledge under the scope of an organization rather than a general knowledge management.
According to Inside Knowledge, Snowden's early work in the field of decision support systems informed his principles of organic knowledge management, using "the natural contours of [an] organisation to allow knowledge to self-organise and self-manage." [4] He describes his three basic rules or principles of knowledge exchange: [9][10]
"Knowledge can only be volunteered; it can't be conscripted."
"People always know more than they can tell, and can tell more than they can write."
"People only know what they need to know when they need to know it."
1. PRESERVE ENTERPRISE KNOWLEDGE
Enterprise Architecture preserve the institutional knowledge for business continuity. It is inevitable of personnel transition in a enterprise. Instead let the institutional knowledge walk away with the transition, EA is effort to preserve the institutional knowledge and maintain enterprise continuity.
Documenting the existing environment is the fundamental of EA. A managed chaos is better than an out of control chaos. Why the effort of documenting existing environment? Starting from a clean sheets for optimization is not a realistic option for most of exiting enterprise, there are many reasons for an enterprise to become the way it is. EA can not bring the business and technology together without knowing the reasons behind the way it is.
Many people have thought that documenting existing environment is trivial because it is exiting and it is all there. It is easy to see a tree but it is not trivial to see the forest. Documenting the existing environment to map out the enterprise is a major effort in EA. It required systematic engineering approach to document the existing environment for the enterprise similar to the national geographical survey to the country.
Documenting existing environment offer a solution to architecture buy-in. It establish a sense of community to the stakeholders toward architecture compliance. The best architecture compliance enforcement is among the stakeholders rather than totally relies on the government. In urban planning, the sense of community and culture have been a major driver for architecture compliance. For example, neighbors in a subdivision keep up with each other to follow the standards and regulation. Existing environment support
Pattern recognition from documenting existing environment offer a solution to the EA “paralysis by analysis”. The effort of Enterprise Resources Planning approach with the concept of generic model have encountered different bottle because of every enterprise has it own culture and one size does not fit all. Documenting the existing environment tells the most of what the stakeholders need. Pattern recognition from the existing environment establish building blocks to best suit the agency’s particular organization, culture, and internal management practices.
The Preserving Institutional Knowledge section elaborate the approach to preserve institutional knowledge.
To adapt the knowledge management approach in managing the Enterprise institutional knowledge. Knowledge management (KM) comprises a range of practices used in an organization to identify, create, represent, distribute and enable adoption of insights and experiences. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organizational processes or practice.
The type of Enterprise Knowledge
According to Inside Knowledge, Snowden's early work in the field of decision support systems informed his principles of organic knowledge management, using "the natural contours of [an] organisation to allow knowledge to self-organise and self-manage." [4] He describes his three basic rules or principles of knowledge exchange: [9][10]
"Knowledge can only be volunteered; it can't be conscripted."
"People always know more than they can tell, and can tell more than they can write."
"People only know what they need to know when they need to know it."
Enterprise Topology to preserve Intitutional knowledge
Enterprise Topology is the effort to preserve institutional knowledge. The challenge is how to transfer the institutional knowledge from each individual. Not all institutional knowledge can be transfer by words like telling a story. Institutional knowledge reside in each individual in the following forms.. .
• . The knowledge can be described in words.
• . The knowledge can be described in picture.
• . The knowledge unable to describe.
. The subconcius knowledge that the individual does not know they know.
In everyday speech and popular writing, however, the term is very commonly encountered. There it will be employed to refer to a supposed 'layer' or 'level' of mentation (or/and perception) located in some sense 'beneath' conscious awareness -- though, again, the notion's dependence upon informal 'folk-psychological' models that remain vague means that the precise nature and properties of this 'underlying' layer are either never made explicit or possess an ad hoc quality. At different times, references to the 'subconscious' as an agency may credit it with various abilities and powers that exceed those possessed by consciousness: the 'subconscious' may apparently remember, perceive and determine things beyond the reach or control of the conscious mind. The idea of the 'subconscious' as a powerful or potent agency has allowed the term to become prominent in the New Age and self-help literatures, in which investigating or controlling its supposed knowledge or power is seen as advantageous. The 'subconscious' may also be supposed to contain (thanks to the influence of the psychoanalytic tradition) any number of primitive or otherwise disavowed instincts, urges, desires and thoughts.
It take some psychological skill to transfer the institutional knowledge from each individual . In the stone soup story, food is very short right after the war. the hungry solders knows very well that they will get starved by asking food directly from the villagers. But they really knows how to get the hidden food out the villagers and make the best soup that villagers can never forget. Enterprise architecture must also know how to excavate institutional knowledge from each individual, it is more than not just a matter of sent out data call and expect people to tell every thing they know. The skill to excavate embedded institutional knowledge from people requires substantial understanding of human nature.
3.1 The limitation of direct inquiry
Most EA approach gather the enterprise knowledge in a direct approach by sending out data call, survey form and conduct site interview in a very direct approach. In the story of stone soup, the solders knows better that they will get starved if they ask food directly from the villagers, people will not even open the door. It is also a common EA experience that people want Enterprise Architecture to go away because of redundant and overwhelm data call and interview from EA initiatives. Frequently, for the people who have the institutional knowledge, answer the survey is not their priority. The data call an inquiry may comes people with limited institutional knowledge.
3.2 Knowledge transfer by knowing human nature
In the Stone Soup story, the solders knows well to use human nature on getting the hidden food from the villagers. They raise the villagers curiosity by setting up as pot of water and declare to make soup with magic stone. With the curious villagers around, they orchestrate the voluntary contribution of their hidden food. The solders knows the human nature of showing off when a person feels that they know better. Enterprise topology take the same approach to transfer the embedded institutional knowledge from each individual.
3.2.1 Knowledge transfer via the human nature of curiosity
Curiosity is a human gift. One cannot help but be in awe when he contemplates the mysteries of eternity, of life, of the marvelous structure of reality. The initial Enterprise Topology raise the stakeholder curiosity with a very high level Enterprise Topology template similar to the pot of water in the stone soup story.
3.2.2 Knowledge transfer via the sensation of solving a puzzle.
Not only the architects want to put together the Enterprise big picture, the Enterprise Topology has also become a sensation to the stakeholders too. The Enterprise Topology become a big puzzle challenge to every one and trigger the knowledge transfer to complete the enterprise and see the true big picture.
3.2.3 Knowledge transfer via the nature of show off
It is a human nature that people want to show that they know better than you. Do not worry making mistake in preparing the initial enterprise topology. Making honest mistake on the enterprise topology give the opportunity for the stakeholder to show off that they knows better. From there on, they begin to to dumping out their hidden institutional knowledge. The caveats is the architects must do their home work so that they do not appears to ignorant.
Enterprise Architecture document management
Enterprise Architecture record keeping
Organic EA suggest to use EA repository and document library to manage the enterprise knowledge.
Knowledge transfer
Enterprise Architecture preserves the institutional knowledge for business continuity. It is inevitable of personnel transition in a enterprise. Instead of letting the institutional knowledge walk away with the transition, EA is the effort to preserve the institutional knowledge and maintain enterprise continuity. This is a large problem in corporations where folks are entrenched for many years (20+) and little effort has been made with documentation.
While many industry pundits emphasize future state EA plans, there is merit with documenting the current state. A managed chaos is better than one that is uncontrolled. The value of current state architecture comes from two areas. First, when corporations face large efforts that perhaps have been mandated often they must review and change every system in their portfolio. The industry I represent, health insurance, is riddled with mandates of this nature. Understanding where things are is essential. Next, when system retirements/replacements are scheduled it is very useful to have current state blueprints, preferably in a repository, that can be queried to determine the impact of such a change. For example, if one is replacing system A, one can query the repository to see what other systems are tied to system A. Finally, current state architectural information is useful for disaster recovery efforts. While the information would need to be stored off-site it is still useful to have the data to answer questions like "if site Q is down what servers, systems, and business units are impacted?".
Many people have thought that documenting existing environment is trivial because it is exiting and it is all there. It is easy to see a tree but it is not trivial to see the forest. Documenting the existing environment to map out the enterprise is a major effort in EA. It required systematic engineering approach to document the existing environment for the enterprise similar to the national geographical survey to the country.
Documenting existing environment offer a solution to architecture buy-in. It establish a sense of community to the stakeholders toward architecture compliance. The best architecture compliance enforcement is among the stakeholders rather than totally relies on the government. In urban planning, the sense of community and culture have been a major driver for architecture compliance. For example, neighbors in a subdivision keep up with each other to follow the standards and regulation. Existing environment support
Pattern recognition from documenting existing environment offer a solution to the EA “paralysis by analysis”. The effort of Enterprise Resources Planning approach with the concept of generic model have encountered different bottle because of every enterprise has it own culture and one size does not fit all. Documenting the existing environment tells the most of what the stakeholders need. Pattern recognition from the existing environment establish building blocks to best suit the agency’s particular organization, culture, and internal management practices.
EA enable every one to known the parts of Enterprise. In an organization, business managers see the big picture to lead the business directions without knowing the parts. Staff members knows the parts but only the parts they have touched.
Enterprise Knowledge Management ^ TOP