Knowledge Acquisition
Knowledge acquisition includes the elicitation, collection, analysis, modeling and validation of knowledge for knowledge engineering and knowledge management projects.
Issues in Knowledge Acquisition
Some of the most important issues in knowledge acquisition are as follows:
Most knowledge is in the heads of experts
Experts have vast amounts of knowledge
Experts have a lot of tacit knowledge
They don't know all that they know and use
Tacit knowledge is hard (impossible) to describe
Experts are very busy and valuable people
Each expert doesn't know everything
Knowledge has a "shelf life"
Requirements for KA Techniques
Because of these issues, techniques are required which:
Take experts off the job for short time periods
Allow non-experts to understand the knowledge
Focus on the essential knowledge
Can capture tacit knowledge
Allow knowledge to be collated from different experts
Allow knowledge to be validated and maintained
KA Techniques
Many techniques have been developed to help elicit knowledge from an expert. These are referred to as knowledge elicitation or knowledge acquisition (KA) techniques. The term "KA techniques" is commonly used.
The following list gives a brief introduction to the types of techniques used for acquiring, analyzing and modeling knowledge:
Protocol-generation techniques include various types of interviews (unstructured, semi-structured and structured), reporting techniques (such as self-report and shadowing) and observational techniques
Protocol analysis techniques are used with transcripts of interviews or other text-based information to identify various types of knowledge, such as goals, decisions, relationships and attributes. This acts as a bridge between the use of protocol-based techniques and knowledge modeling techniques.
Hierarchy-generation techniques, such as laddering, are used to build taxonomies or other hierarchical structures such as goal trees and decision networks.
Matrix-based techniques involve the construction of grids indicating such things as problems encountered against possible solutions. Important types include the use of frames for representing the properties of concepts and the repertory grid technique used to elicit, rate, analyze and categories the properties of concepts.
Sorting techniques are used for capturing the way people compare and order concepts, and can lead to the revelation of knowledge about classes, properties and priorities.
Limited-information and constrained-processing tasks are techniques that either limit the time and/or information available to the expert when performing tasks. For instance, the twenty-questions technique provides an efficient way of accessing the key information in a domain in a prioritized order.
Diagram-based techniques include the generation and use of concept maps, state transition networks, event diagrams and process maps. The use of these is particularly important in capturing the "what, how, when, who and why" of tasks and events.
Comparison of KA Techniques
The figure below presents the various techniques described above and shows the types of knowledge they are mainly aimed at eliciting. The vertical axis on the figure represents the dimension from object knowledge to process knowledge, and the horizontal axis represents the dimension from explicit knowledge to tacit knowledge.
Typical Use of KA Techniques
How and when are the many techniques described above used in a knowledge acquisition project? To illustrate the general process, a simple method will be described. This method starts with the use of natural techniques, then moves to using more contrived techniques. It is summarized as follows.
Conduct an initial interview with the expert in order to (a) scope what knowledge is to be acquired, (b) determine what purpose the knowledge is to be put, (c) gain some understanding of key terminology, and (d) build a rapport with the expert. This interview (as with all session with experts) is recorded on either audiotape or videotape.
Transcribe the initial interview and analyze the resulting protocol. Create a concept ladder of the resulting knowledge to provide a broad representation of the knowledge in the domain. Use the ladder to produce a set of questions which cover the essential issues across the domain and which serve the goals of the knowledge acquisition project.
Conduct a semi-structured interview with the expert using the pre-prepared questions to provide structure and focus.
Transcribe the semi-structured interview and analyse the resulting protocol for the knowledge types present. Typically these would be concepts, attributes, values, relationships, tasks and rules.
Represent these knowledge elements using the most appropriate knowledge models, e.g. ladders, grids, network diagrams, hypertext, etc. In addition, document anecdotes, illustrations and explanations in a structured manner using hypertext and template headings.
Use the resulting knowledge models and structured text with contrived techniques such as laddering, think aloud problem-solving, twenty questions and repertory grid to allow the expert to modify and expand on the knowledge already captured.
Repeat the analysis, model building and acquisition sessions until the expert and knowledge engineer are happy that the goals of the project have been realised.
Validate the knowledge acquired with other experts, and make modifications where necessary.
This is a very brief coverage of what happens. It does not assume any previous knowledge has been gathered, nor that any generic knowledge can be applied. In reality, the aim would be to re-use as much previously acquired knowledge as possible. Techniques have been developed to assist this, such as the use of ontologies and problem-solving models. These provide generic knowledge to suggest ideas to the expert such as general classes of objects in the domain and general ways in which tasks are performed. This re-use of knowledge is the essence of making the knowledge acquisition process as efficient and effective as possible. This is an evolving process. Hence, as more knowledge is gathered and abstracted to produce generic knowledge, the whole process becomes more efficient. In practice, knowledge engineers often mix this theory-driven (top-down) approach with a data-driven (bottom-up) approach (discussed later).
Recent Developments
A number of recent developments are continuing to improve the efficiency of the knowledge acquisition process. Four of these developments are examined below.
First, methodologies have been introduced that provide frameworks and generic knowledge to help guide knowledge acquisition activities and ensure the development of each expert system is performed in an efficient manner. A leading methodology is Common KADS. At the heart of Common KADS is the notion that knowledge engineering projects should be model-driven. At the level of project management, Common KADS advises the use of six high-level models: the organization model, the task model, the agent model, the expertise model, the communications model and the design model. To aid development of these models, a number of generic models of problem-solving activities are included. Each of these generic models describe the roles that knowledge play in the tasks, hence provide guidance on what types of knowledge to focus upon. As a project proceeds, Common KADS follows a spiral approach to system development such that phases of reviewing, risk assessment, planning and monitoring are visited and re-visited. This provides for rapid prototyping of the system, such that risk is managed and there is more flexibility in dealing with uncertainty and change.
A second important development is the creation and use of ontologies. Although there is a lack of unanimity in the exact definition of the term ontology, it is generally regarded as a formalised representation of the knowledge in a domain taken from a particular perspective or conceptualisation. The main use of an ontology is to share and communicate knowledge, both between people and between computer systems. A number of generic ontologies have been constructed, each having application across a number of domains which enables the re-use of knowledge. In this way, a project need not start with a blank sheet of paper, but with a number of skeletal frameworks that can act as predefined structures for the knowledge being acquired. As with the problem-solving models of Common KADS, ontologies also provide guidance to the knowledge engineer in the types of knowledge to be investigated.
A third development has been an increasing use of software tools to aid the acquisition process. Software packages, such as PCPACK, contain a number of tools to help the knowledge engineer analyse, structure and store the knowledge required. The use of various modelling tools and a central database of knowledge can provide various representational views of the domain. Software tools can also enforce good knowledge engineering discipline on the user, so that even novice practitioners can be aided to perform knowledge acquisition projects. Software storage and indexing systems can also facilitate the re-use and transfer of knowledge from project to project. More recently, software systems that make use of generic ontologies are under development to provide for automatic analysis and structuring of knowledge.
A fourth recent development is the use of knowledge engineering principles and techniques in contexts other than the development of expert systems. A notable use of the technology in another field is as an aid to knowledge management within organisational contexts. Knowledge management is a strategy whereby the knowledge within an organisation is treated as a key asset to be managed in the most effective way possible. This approach has been a major influence in the past few years as companies recognise the vital need to manage their knowledge assets. A number of principles and techniques from knowledge engineering have been successfully transferred to aid in knowledge management initiatives, such as the construction of web sites for company intranet systems. This is an important precedent for the aim of this thesis to apply practices from knowledge engineering to the realm of personal knowledge.
Monday, December 31, 2007
Friday, December 28, 2007
Intranets as Knowledge Management Systems
Steven L. Telleen, Ph.D. Principal iorg.com
Many people are beginning to see their intranets becoming powerful knowledge management systems. However, as with the early days of any new approach, there is an intuitive acceptance of the phenomenon accompanied by much confusion around the concepts involved. Additionally, in fields like knowledge management and organizational learning, there are existing perceptions and terms that may inhibit as much as help our understanding of the new environment. This is why it is useful to start with the definitions and concepts, since these are the tools we humans use to understand and communicate. Here are some definitional concepts you might find useful in thinking about the subject.
First, "Learning" is a verb. It is the process of finding (or inventing) patterns from chaos. If we start with an ordered understanding we can't learn, because we already "know" the patterns and relationships. Thus, when people complain about the "chaos" and lack of structure in a free-form intranet, think of it not as a problem, but as a fertile base of materials for organizational learning.
Knowledge, on the other hand, is the repository of what we already have learned. It may be explicit, as in books or intranet content, or it may be implicit as in relationships and processes that may not be documented.
Learning and knowledge are not organizational functions. They happen to and through individual people. An organization only "learns" when an individual is able to impart the understanding to or change the behavior of the organization as a whole. Thus a learning organization must encourage and support this type of effect from its individual learners.
If the individual's learning, insights or experience are explicitly captured in a way they can be shared with the rest of the organization, then it becomes part of the organizational knowledge base. Note, that unlike a personal knowledge base, an organizational knowledge base requires explicitly capturing the information for it to be shared.
Knowledge and learning are iterative. When the potential "learner" confronts an unkown (conceptually chaotic) situation, there are three ways in which he can learn.
1. He can search the knowledge base to see if the situation has been encountered before and the answer already is known. If it is, he either learns it from the organizational knowledge base, or recalls it from his own (mental) knowledge base.
2. He can find several "related" but not exact circumstances and derive an answer by recombining pieces of knowledge from the knowledge base, creating new knowledge in the process.
3. He can generate new knowledge, usually by creating action and noting the response. When we do this in a structured way, we call it scientific research. When we do it in a random way, we call it hit and miss or accident. Note that we call the understanding that we get from our failures "wisdom." Wisdom comes from experience, not from an organizational knowledge base.
Note that this is completely analogous to that chemical information system, genetics. The DNA is the stored knowledge base, sexual reproduction is recombination, and mutation is generating accidental knowledge. I suspect that in learning organizations, as in biology, the largest source of learning is recombination.
An intranet relates to learning organizations in the following way. The intranet is not only a powerful communication medium but also a knowledge base. It has advantages over previous digital knowledge bases in that it more easily captures and handles unstructured and implicit knowledge (in contrast, DBMSs require very structured schemas to be effective).
The ways in which we learn can help us understand what kinds of roles, skills, tools and processes we need to develop to help individuals in the organization find the knowledge already available, move the organization to act on their learning, and capture the experiences in the organizational knowledge base with the minimum effort. A separate paper on agents discusses some of the relevant knowledge management and learning roles likely to emerge around intranets.
The oldest human knowledge base is culture. The knowledge is stored as stories and rituals. When looking at intranets as knowledge bases, it might be useful to look at how culture acts as a modifiable (learning) knowledge management system as it interacts with the individuals that make it up.
Many people are beginning to see their intranets becoming powerful knowledge management systems. However, as with the early days of any new approach, there is an intuitive acceptance of the phenomenon accompanied by much confusion around the concepts involved. Additionally, in fields like knowledge management and organizational learning, there are existing perceptions and terms that may inhibit as much as help our understanding of the new environment. This is why it is useful to start with the definitions and concepts, since these are the tools we humans use to understand and communicate. Here are some definitional concepts you might find useful in thinking about the subject.
First, "Learning" is a verb. It is the process of finding (or inventing) patterns from chaos. If we start with an ordered understanding we can't learn, because we already "know" the patterns and relationships. Thus, when people complain about the "chaos" and lack of structure in a free-form intranet, think of it not as a problem, but as a fertile base of materials for organizational learning.
Knowledge, on the other hand, is the repository of what we already have learned. It may be explicit, as in books or intranet content, or it may be implicit as in relationships and processes that may not be documented.
Learning and knowledge are not organizational functions. They happen to and through individual people. An organization only "learns" when an individual is able to impart the understanding to or change the behavior of the organization as a whole. Thus a learning organization must encourage and support this type of effect from its individual learners.
If the individual's learning, insights or experience are explicitly captured in a way they can be shared with the rest of the organization, then it becomes part of the organizational knowledge base. Note, that unlike a personal knowledge base, an organizational knowledge base requires explicitly capturing the information for it to be shared.
Knowledge and learning are iterative. When the potential "learner" confronts an unkown (conceptually chaotic) situation, there are three ways in which he can learn.
1. He can search the knowledge base to see if the situation has been encountered before and the answer already is known. If it is, he either learns it from the organizational knowledge base, or recalls it from his own (mental) knowledge base.
2. He can find several "related" but not exact circumstances and derive an answer by recombining pieces of knowledge from the knowledge base, creating new knowledge in the process.
3. He can generate new knowledge, usually by creating action and noting the response. When we do this in a structured way, we call it scientific research. When we do it in a random way, we call it hit and miss or accident. Note that we call the understanding that we get from our failures "wisdom." Wisdom comes from experience, not from an organizational knowledge base.
Note that this is completely analogous to that chemical information system, genetics. The DNA is the stored knowledge base, sexual reproduction is recombination, and mutation is generating accidental knowledge. I suspect that in learning organizations, as in biology, the largest source of learning is recombination.
An intranet relates to learning organizations in the following way. The intranet is not only a powerful communication medium but also a knowledge base. It has advantages over previous digital knowledge bases in that it more easily captures and handles unstructured and implicit knowledge (in contrast, DBMSs require very structured schemas to be effective).
The ways in which we learn can help us understand what kinds of roles, skills, tools and processes we need to develop to help individuals in the organization find the knowledge already available, move the organization to act on their learning, and capture the experiences in the organizational knowledge base with the minimum effort. A separate paper on agents discusses some of the relevant knowledge management and learning roles likely to emerge around intranets.
The oldest human knowledge base is culture. The knowledge is stored as stories and rituals. When looking at intranets as knowledge bases, it might be useful to look at how culture acts as a modifiable (learning) knowledge management system as it interacts with the individuals that make it up.
Knowledge Management: 5 Big Companies That Got It Right
American companies will spend $73 billion on knowledge management software this year and spending on content, search, portal, and collaboration technologies is expected to increase 16% in 2008, according to a recently-released report from AMR Research.
Knowledge management systems, which facilitate the aggregation and dissemination of a company's collective intelligence, provide numerous benefits, including enabling innovation and improving process efficiency.
But successfully implementing these systems can be a challenge.
While technology advances have eased some of the installation and integration hurdles, Jim Murphy, AMR's knowledge management research director, says companies looking to do wide-scale deployments still face scalability and performance issues. And, as with other information technologies, user adoption presents the biggest test.
Baseline and it sister publication, CIO Insight, have done several knowledge management case studies over the years. Here we invoke five that show how organizations of various shapes and sizes overcame the deployment challenges they faced.
#1: World Bank: Behind the I.T. TransformationAmidst the World Bank's recent management brouhaha, a more significant event went overlooked-the bank's dramatic transformation from a hierarchical source of low-interest loans to a decentralized organization that uses knowledge-management technologies to fight poverty and disease in developing nations.
It wasn't easy. In order to create a working knowledge management system, the bank's information infrastructure and communications network had to be overhauled.
#2: Southern Co.'s I.T. Aids Post-Katrina RecoverySouthern Co., the energy company that produces electricity for much of the Gulf Coast region, was preparing for Hurricane Katrina even before the 2005 storm struck. Southern had taken steps to meet worst-case scenarios, such as building an enterprise content management platform to ensure that engineers could get immediate access to design plans of electrical substations and other power equipment. As a result, the electricity distributor restored service to its Mississippi customers within 12 days of the hurricane, instead of the initially estimated 28.
Setting up the content-management system presented some challenges, including matching data from one legacy system with a second one. The former system was a database with text data related to drawings, but no images; the latter contained drawings without the related text.
#3: Dow Jones Makes Headlines With Content ManagementWith readers flocking to the Internet, newspaper publishers have been forced to invest more dollars in pushing content to their Web sites. For Dow Jones, that presented a series of challenges, including a constant grapple with the content management and delivery tools needed to serve a growing subscriber base.
#4: Shuffle Master Puts its Money on a PortalShuffle Master, the manufacturer of automatic shuffling machines and chip counting products, had been relying on a fragmented sales and order processing infrastructure that was making it difficult for company employees to find integrated and reliable business information. For example, sales forecasts were issued several times each quarter, but were of limited value to salespeople trying to meet their quarterly goals because the numbers were stale by the time they were issued.
The solution they came up with: Build a portal that could pull data on demand from more than 60 databases. The challenge they faced: How do you build a powerful portal on a midsize company's budget?
#5: Pratt & Whitney: Help YourselfPratt & Whitney airline engines are constantly transmitting information about the status of their parts. Down on the ground, data recorders at the manufacturer, which builds and maintains these engines for carriers such as Delta Air Lines and United Airlines, capture this information and compare it to optimum levels in order to ensure the ongoing health of the engines. Streams of data are made available in a flash through a Web portal. But as the manufacturer found out, portals are only effective if they deliver something that users want.
By John McCormick
With U.S. companies spending $73B on knowledge management software, Baseline presents a look back at five companies that successfully deployed knowledge-management systems.
Knowledge management systems, which facilitate the aggregation and dissemination of a company's collective intelligence, provide numerous benefits, including enabling innovation and improving process efficiency.
But successfully implementing these systems can be a challenge.
While technology advances have eased some of the installation and integration hurdles, Jim Murphy, AMR's knowledge management research director, says companies looking to do wide-scale deployments still face scalability and performance issues. And, as with other information technologies, user adoption presents the biggest test.
Baseline and it sister publication, CIO Insight, have done several knowledge management case studies over the years. Here we invoke five that show how organizations of various shapes and sizes overcame the deployment challenges they faced.
#1: World Bank: Behind the I.T. TransformationAmidst the World Bank's recent management brouhaha, a more significant event went overlooked-the bank's dramatic transformation from a hierarchical source of low-interest loans to a decentralized organization that uses knowledge-management technologies to fight poverty and disease in developing nations.
It wasn't easy. In order to create a working knowledge management system, the bank's information infrastructure and communications network had to be overhauled.
#2: Southern Co.'s I.T. Aids Post-Katrina RecoverySouthern Co., the energy company that produces electricity for much of the Gulf Coast region, was preparing for Hurricane Katrina even before the 2005 storm struck. Southern had taken steps to meet worst-case scenarios, such as building an enterprise content management platform to ensure that engineers could get immediate access to design plans of electrical substations and other power equipment. As a result, the electricity distributor restored service to its Mississippi customers within 12 days of the hurricane, instead of the initially estimated 28.
Setting up the content-management system presented some challenges, including matching data from one legacy system with a second one. The former system was a database with text data related to drawings, but no images; the latter contained drawings without the related text.
#3: Dow Jones Makes Headlines With Content ManagementWith readers flocking to the Internet, newspaper publishers have been forced to invest more dollars in pushing content to their Web sites. For Dow Jones, that presented a series of challenges, including a constant grapple with the content management and delivery tools needed to serve a growing subscriber base.
#4: Shuffle Master Puts its Money on a PortalShuffle Master, the manufacturer of automatic shuffling machines and chip counting products, had been relying on a fragmented sales and order processing infrastructure that was making it difficult for company employees to find integrated and reliable business information. For example, sales forecasts were issued several times each quarter, but were of limited value to salespeople trying to meet their quarterly goals because the numbers were stale by the time they were issued.
The solution they came up with: Build a portal that could pull data on demand from more than 60 databases. The challenge they faced: How do you build a powerful portal on a midsize company's budget?
#5: Pratt & Whitney: Help YourselfPratt & Whitney airline engines are constantly transmitting information about the status of their parts. Down on the ground, data recorders at the manufacturer, which builds and maintains these engines for carriers such as Delta Air Lines and United Airlines, capture this information and compare it to optimum levels in order to ensure the ongoing health of the engines. Streams of data are made available in a flash through a Web portal. But as the manufacturer found out, portals are only effective if they deliver something that users want.
By John McCormick
With U.S. companies spending $73B on knowledge management software, Baseline presents a look back at five companies that successfully deployed knowledge-management systems.
Tuesday, December 25, 2007
Knowledge Management and the Zen of Seeing
By Rakesh Bhaskar
The Zen of Seeing
Seeing is an art often taken for granted. We see what we learn or have learned to see. As Henry Moore once said “We think we see, but we don't”. Everyone sees differently. Your brain processes the visual information from the eye and shows facts based on your mental conditioning. Only an individual who knows the Zen of Seeing can see what “isn't there” and what is “actually there”.
Such individuals have constantly worked on removing murky veils of conformity from their eyes, and this has helped them in understanding the true nature of life.
Zen is a Buddhist and a Universal concept, it means self knowledge. It is a self actualizing process wherein the individual takes a steadfast approach in knowing himself and realizes how to look at the true nature of things. It’s an effective tool for change.
A Zen Practitioner knows that the brain dwells on things that we see. A refined way of looking at things can change the way your brain works and this can bring about quality actions.
Knowledge Management (KM) like Zen is an effective tool for change. KM is an essential organizational driver and an invaluable elixir for professional growth.
In Zen, Knowledge is the basis of understanding the framework of life. KM too, is a way of understanding the functioning of knowledge in an organizational framework. Zen works on the ways of understanding the true knowledge of life. KM works on the ways as to how knowledge works in an organization and improves its lifeline.
KM, in fact, is built around the very principles of Zen. Being an effective KM practitioner is a must for anyone working in a technology environment.
Let’s look at the true nature of KM, and see how we can transform ourselves into effective KM practitioners by imbibing the Zen essentials of seeing.
So, how to practice the Zen of Seeing?
It’s the completeness that matters. Look at the completeness.
For example, take the wheel. Only a complete wheel can make things move. An incomplete wheel never moves. Wheel is an existential reality of movement. The spokes or the inner core can change. The diameter and the circumference can change; the inner core idea of rotation can never change. It moves the world.
We can extract the importance in every tool we use and look into the core idea as to what it does and what it can do to me. As we look deeper into things, we find it’s the core idea that really matters, the rest are just bells and whistles.
Everything exists in Space, even Emptiness. Look at both.
We all live in space. We have occupied and earned certain spaces for ourselves in professional lives. The more space we occupy, the more emptiness we create.Sir Isaac Newton once took some sand lying around and said, “What I know is the sand in my hand, and what I do not know is this Universe”.Space is dimensional, it is what we know; recognize the emptiness in you and expand your existential space. It helps you evolve and emerge as better knowledge worker. You can fill the emptiness with whatever you wish. But, more we recognize the emptiness, more the scope for improvement and development. It’s the emptiness that enables us to keep that step forward. So, take a deep look at both the space and the emptiness.
I am alone. I am interdependent. Look at the interdependency.
Nobody works alone. Nature has taught us that it’s interdependency that works. The ecosystems prevalent in nature are self sustaining as they are interdependent; this is equally true in a knowledge-driven environment. The more we interact and collaborate with our peers, the better it is for us. Collaboration enables learning and improves corporate longevity.The existential truth is that interdependency is a nature’s way of empowering a growth cycle. So, look at your interdependencies and focus on building healthier ones.
I emerge from my senses. Look at your senses.
We are constantly using our senses to evolve. You create your identity from your senses. Be aware about what you do, feel, hear, and think. The more you are consciously aware of your senses, the sharper you get. Sensible use of your surroundings and your skills is a must for overall growth. An honest look at your senses on an everyday basis can go a long way in your personal and professional growth.
There is duality in nature. Look at the duality.
There are two fundamental concepts existing in nature, which often oppose each other. We often experience different states of minds, one state trying to prove its worth over the other. We need to develop the sensibility and the sensitivity within us to be aware of these states. Once you recognize these states, you can rationalize them and compare them. Look deeper into the dualities that exist in you and the surroundings. It helps in sharpening your perceptions and actions.
But, what do these five points mentioned above got to do with Knowledge Management?
Zen of Seeing and Knowledge Management
By continually practicing the Zen of seeing, we can definitely remove the murky veils of conformity from our eyes and can help us understand the true nature of Knowledge Management.
Let’s go ahead and see how the points described above can help us become better KM practitioners.
It’s the completeness that matters. Look at the completeness.
The totality of KM moves itself, like the wheel. KM is like a wheel; it’s complete in itself and drives many an organization in reaching its destinations. A wheel realizes its meaning when it’s put to use. KM, like the wheel has to be put into use to realize its full meaning. When in use, it not only helps you reach the required destination with the necessary speed, but also reduces the time needed to reach the same.
Remember: Wheel moves the world, KM moves an Organization.
Everything exists in Space, even Emptiness. Look at both.
Any project you undertake, recognize the emptiness and the space it occupies. How does it affect you? What are you doing to fill the space? Your best ally in filling this space would be KM. An apt KM practitioner can effectively fill the emptiness he encounters in any project he undertakes, as he knows what can help him overcome it. Take a good look at the emptiness that’s occupying you in a project.
Remember: There is space, there is emptiness. KM helps us transcend both.
I am alone. I am interdependent. Look at the interdependency.
Interdependency is the nature of life. We need to interact to enact any act. Evolution of an individual in an organisation happens when he or she identifies and nurtures healthier knowledge interdependencies. Constant interaction and collaboration is one of the facets of KM. The more we collaborate, the more knowledge we create, the more it’s easier for us to work.
Remember: Healthier interdependencies lead to quality collaborations. Quality collaborations lead to quality creation of knowledge.
I emerge from my senses. Look at your senses.
Indulge your senses with KM, your senses will love it! Train your senses to the very mantra of KM; Create, Capture, Collaborate, Reuse. It’s a mantra, which has immediate and long term results for you and to the organisation. A conscious effort from you to intoxicate your senses with the essence of KM can make it sharper and can make you work smarter.
Remember: KM is a perfect drug for your senses. Use it to develop a “Stay sharp, Work smart” attitude.
There is duality in nature. Look at the duality.
The two most powerful states of mind are Concentration and Awareness. A perfect balance of both is vital for peak performance of a knowledge worker. Develop the sensibility and the sensitivity for understanding this duality. Look at both these attributes and be consciously aware of them. Rationalize and Compare the different states of your mind. Know when to focus and know when to be aware. Concentrate on using KM tools and processes in projects, be Aware of building the KM feeling – sharpen your perceptions and broaden your horizons on KM.
Remember: Accept the dual nature of mind. Concentrate, but be aware.
Zen, KM and You
As you would have understood by now, Zen and KM are relative. Both aim to build better humans and help them in realizing the true nature of knowledge. The form and function that KM brings to an individual is magnanimous in terms of the knowledge gained through collaboration and reuse. Understanding the true nature of things is the essence of life. The understanding of true nature gives us clarity and helps us develop positive visions that are pragmatic and worthwhile.
By Rakesh Bhaskar
The Zen of Seeing
Seeing is an art often taken for granted. We see what we learn or have learned to see. As Henry Moore once said “We think we see, but we don't”. Everyone sees differently. Your brain processes the visual information from the eye and shows facts based on your mental conditioning. Only an individual who knows the Zen of Seeing can see what “isn't there” and what is “actually there”.
Such individuals have constantly worked on removing murky veils of conformity from their eyes, and this has helped them in understanding the true nature of life.
Zen is a Buddhist and a Universal concept, it means self knowledge. It is a self actualizing process wherein the individual takes a steadfast approach in knowing himself and realizes how to look at the true nature of things. It’s an effective tool for change.
A Zen Practitioner knows that the brain dwells on things that we see. A refined way of looking at things can change the way your brain works and this can bring about quality actions.
Knowledge Management (KM) like Zen is an effective tool for change. KM is an essential organizational driver and an invaluable elixir for professional growth.
In Zen, Knowledge is the basis of understanding the framework of life. KM too, is a way of understanding the functioning of knowledge in an organizational framework. Zen works on the ways of understanding the true knowledge of life. KM works on the ways as to how knowledge works in an organization and improves its lifeline.
KM, in fact, is built around the very principles of Zen. Being an effective KM practitioner is a must for anyone working in a technology environment.
Let’s look at the true nature of KM, and see how we can transform ourselves into effective KM practitioners by imbibing the Zen essentials of seeing.
So, how to practice the Zen of Seeing?
It’s the completeness that matters. Look at the completeness.
For example, take the wheel. Only a complete wheel can make things move. An incomplete wheel never moves. Wheel is an existential reality of movement. The spokes or the inner core can change. The diameter and the circumference can change; the inner core idea of rotation can never change. It moves the world.
We can extract the importance in every tool we use and look into the core idea as to what it does and what it can do to me. As we look deeper into things, we find it’s the core idea that really matters, the rest are just bells and whistles.
Everything exists in Space, even Emptiness. Look at both.
We all live in space. We have occupied and earned certain spaces for ourselves in professional lives. The more space we occupy, the more emptiness we create.Sir Isaac Newton once took some sand lying around and said, “What I know is the sand in my hand, and what I do not know is this Universe”.Space is dimensional, it is what we know; recognize the emptiness in you and expand your existential space. It helps you evolve and emerge as better knowledge worker. You can fill the emptiness with whatever you wish. But, more we recognize the emptiness, more the scope for improvement and development. It’s the emptiness that enables us to keep that step forward. So, take a deep look at both the space and the emptiness.
I am alone. I am interdependent. Look at the interdependency.
Nobody works alone. Nature has taught us that it’s interdependency that works. The ecosystems prevalent in nature are self sustaining as they are interdependent; this is equally true in a knowledge-driven environment. The more we interact and collaborate with our peers, the better it is for us. Collaboration enables learning and improves corporate longevity.The existential truth is that interdependency is a nature’s way of empowering a growth cycle. So, look at your interdependencies and focus on building healthier ones.
I emerge from my senses. Look at your senses.
We are constantly using our senses to evolve. You create your identity from your senses. Be aware about what you do, feel, hear, and think. The more you are consciously aware of your senses, the sharper you get. Sensible use of your surroundings and your skills is a must for overall growth. An honest look at your senses on an everyday basis can go a long way in your personal and professional growth.
There is duality in nature. Look at the duality.
There are two fundamental concepts existing in nature, which often oppose each other. We often experience different states of minds, one state trying to prove its worth over the other. We need to develop the sensibility and the sensitivity within us to be aware of these states. Once you recognize these states, you can rationalize them and compare them. Look deeper into the dualities that exist in you and the surroundings. It helps in sharpening your perceptions and actions.
But, what do these five points mentioned above got to do with Knowledge Management?
Zen of Seeing and Knowledge Management
By continually practicing the Zen of seeing, we can definitely remove the murky veils of conformity from our eyes and can help us understand the true nature of Knowledge Management.
Let’s go ahead and see how the points described above can help us become better KM practitioners.
It’s the completeness that matters. Look at the completeness.
The totality of KM moves itself, like the wheel. KM is like a wheel; it’s complete in itself and drives many an organization in reaching its destinations. A wheel realizes its meaning when it’s put to use. KM, like the wheel has to be put into use to realize its full meaning. When in use, it not only helps you reach the required destination with the necessary speed, but also reduces the time needed to reach the same.
Remember: Wheel moves the world, KM moves an Organization.
Everything exists in Space, even Emptiness. Look at both.
Any project you undertake, recognize the emptiness and the space it occupies. How does it affect you? What are you doing to fill the space? Your best ally in filling this space would be KM. An apt KM practitioner can effectively fill the emptiness he encounters in any project he undertakes, as he knows what can help him overcome it. Take a good look at the emptiness that’s occupying you in a project.
Remember: There is space, there is emptiness. KM helps us transcend both.
I am alone. I am interdependent. Look at the interdependency.
Interdependency is the nature of life. We need to interact to enact any act. Evolution of an individual in an organisation happens when he or she identifies and nurtures healthier knowledge interdependencies. Constant interaction and collaboration is one of the facets of KM. The more we collaborate, the more knowledge we create, the more it’s easier for us to work.
Remember: Healthier interdependencies lead to quality collaborations. Quality collaborations lead to quality creation of knowledge.
I emerge from my senses. Look at your senses.
Indulge your senses with KM, your senses will love it! Train your senses to the very mantra of KM; Create, Capture, Collaborate, Reuse. It’s a mantra, which has immediate and long term results for you and to the organisation. A conscious effort from you to intoxicate your senses with the essence of KM can make it sharper and can make you work smarter.
Remember: KM is a perfect drug for your senses. Use it to develop a “Stay sharp, Work smart” attitude.
There is duality in nature. Look at the duality.
The two most powerful states of mind are Concentration and Awareness. A perfect balance of both is vital for peak performance of a knowledge worker. Develop the sensibility and the sensitivity for understanding this duality. Look at both these attributes and be consciously aware of them. Rationalize and Compare the different states of your mind. Know when to focus and know when to be aware. Concentrate on using KM tools and processes in projects, be Aware of building the KM feeling – sharpen your perceptions and broaden your horizons on KM.
Remember: Accept the dual nature of mind. Concentrate, but be aware.
Zen, KM and You
As you would have understood by now, Zen and KM are relative. Both aim to build better humans and help them in realizing the true nature of knowledge. The form and function that KM brings to an individual is magnanimous in terms of the knowledge gained through collaboration and reuse. Understanding the true nature of things is the essence of life. The understanding of true nature gives us clarity and helps us develop positive visions that are pragmatic and worthwhile.
Thursday, December 20, 2007
Role of IT in KM system of any organization
1. Do we need IT solution to implement successful KM programs? The answer lies within the organization. First we have to understand what the organization's strategic objectives are or what it wants to be in future. KM is a means not an end. KM will facilitate the process of achieving organizonal objectives. Through Knowledge management the organization will able to leverage its collective knowledge to improve process, develop new products, enhance customer satisfaction or achieve its other business objectives. So we must focus on organizonal culture, strategic objectives and knowledge in the context of the organization before developing a KM solution. 2. Does your IT tool for KM fit here? Ok before answering that let us study a successful company who has leveraged knowledge of its employees to achieve success in globally operated business process. Buckman Laboratories is a leading manufacturer of specialty chemicals for aqueous industrial systems. To answer every question or customer query each employee has the knowledge of 1200 workforce of the company including the CEO Bob Buckman. Bob was behind K'Netix the knowledge network where all employees can login and participate in discussion on various issues. This serves the purpose of global workforce as they are located in distance places and bringing them together regularly is not possible. Here a shared context is created by the use of IT. K'Netix has helped the workforce located in different part of the world to come together and share knowledge, solve each others problem irrespective of time and distance. Today many organization have similar tools known as discussion board or buletin board. 3. Do you think you need a solution like K'Netix ? KM system of one organization can't be copied by others. Even two organizations in similar line of business located in same country have different KM systems to achieve their business objectives. So the sytem must be uniquely designed to full fill the organizations need with full knowledge of organizionation culture and its business imparitives. So it is not necessary that what has worked for Buckman Lab is going to work for any other orgnization. In another type of industry where employees work within a geographically closed location can have a face to face interaction session periodically to create a shared contex. This KM tool is called community of practice or popularly known as COP. So the job of KM managers, CKO or its team is to identify or develop systems to facilitate knowledge sharing and promote innovation to achieve objectives of the organization through Knowledge Management. It is always required to study the organizonaltional culture, objectives, strategies, knowledge gaps before making any decission on the tool to delploy. After a through study at the end it may happen that we end up in a IT solution ( which is best for the organization ) but with out proper analysis one should not jump into implementing IT solutions in the name of KM. This is one of the biggest reasons for faliure of KM program in organizations.
Role of IT in KM system of any organization
1. Do we need IT solution to implement successful KM programs? The answer lies within the organization. First we have to understand what the organization's strategic objectives are or what it wants to be in future. KM is a means not an end. KM will facilitate the process of achieving organizonal objectives. Through Knowledge management the organization will able to leverage its collective knowledge to improve process, develop new products, enhance customer satisfaction or achieve its other business objectives. So we must focus on organizonal culture, strategic objectives and knowledge in the context of the organization before developing a KM solution. 2. Does your IT tool for KM fit here? Ok before answering that let us study a successful company who has leveraged knowledge of its employees to achieve success in globally operated business process. Buckman Laboratories is a leading manufacturer of specialty chemicals for aqueous industrial systems. To answer every question or customer query each employee has the knowledge of 1200 workforce of the company including the CEO Bob Buckman. Bob was behind K'Netix the knowledge network where all employees can login and participate in discussion on various issues. This serves the purpose of global workforce as they are located in distance places and bringing them together regularly is not possible. Here a shared context is created by the use of IT. K'Netix has helped the workforce located in different part of the world to come together and share knowledge, solve each others problem irrespective of time and distance. Today many organization have similar tools known as discussion board or buletin board. 3. Do you think you need a solution like K'Netix ? KM system of one organization can't be copied by others. Even two organizations in similar line of business located in same country have different KM systems to achieve their business objectives. So the sytem must be uniquely designed to full fill the organizations need with full knowledge of organizionation culture and its business imparitives. So it is not necessary that what has worked for Buckman Lab is going to work for any other orgnization. In another type of industry where employees work within a geographically closed location can have a face to face interaction session periodically to create a shared contex. This KM tool is called community of practice or popularly known as COP. So the job of KM managers, CKO or its team is to identify or develop systems to facilitate knowledge sharing and promote innovation to achieve objectives of the organization through Knowledge Management. It is always required to study the organizonaltional culture, objectives, strategies, knowledge gaps before making any decission on the tool to delploy. After a through study at the end it may happen that we end up in a IT solution ( which is best for the organization ) but with out proper analysis one should not jump into implementing IT solutions in the name of KM. This is one of the biggest reasons for faliure of KM program in organizations.
Tuesday, December 18, 2007
Tacit Knowledge
Tacit Knowledge
The concept of tacit knowing comes from scientist and philosopher Michael Polanyi. It is important to understand that he wrote about a process (hence tacit knowing) and not a form of knowledge. However, his phrase has been taken up to name a form of knowledge that is apparently wholly or partly inexplicable.
Definition
By definition, tacit knowledge is knowledge that people carry in their minds and is, therefore, difficult to access. Often, people are not aware of the knowledge they possess or how it can be valuable to others. Tacit knowledge is considered more valuable because it provides context for people, places, ideas, and experiences. Effective transfer of tacit knowledge generally requires extensive personal contact and trust.
Tacit knowledge is not easily shared. One of Polanyi's famous aphorisms is: "We know more than we can tell." Tacit knowledge consists often of habits and culture that we do not recognize in ourselves. In the field of knowledge management the concept of tacit knowledge refers to a knowledge which is only known by an individual and that is difficult to communicate to the rest of an organization. Knowledge that is easy to communicate is called explicit knowledge. The process of transforming tacit knowledge into explicit knowledge is known as codification or articulation.
Properties of tacit knowledge
The tacit aspects of knowledge are those that cannot be codified, but can only be transmitted via training or gained through personal experience. Alternatively, tacit knowledge can be understood to be knowledge that is embedded in a culture (for instance a regional culture, organizational culture or social culture) and is difficult to share with people not embedded in that culture. Tacit knowledge has been described as "know-how" (as opposed to "know-what" [facts], "know-why" [science] and "know-who" [networking]) . It involves learning and skill but not in a way that can be written down. The knowledge of how to ride a bike is an example: one cannot learn to ride a bike by reading a textbook, it takes personal experimentation and practice to gain the necessary skills.
Tacit knowledge has been found to be a crucial input to the innovation process. A society’s ability to innovate depends on its level of tacit knowledge of how to innovate. Polanyi suggested that scientific inquiry could not be reduced to facts, and that the search for new and novel research problems requires tacit knowledge about how to approach an unknown. Further writers have suggested that most laboratory practices, practices that are vital to the successful reproduction of a scientific experiment, are tacit (Collins, 2001). Ikujiro Nonaka and Hirotaka Takeuchi's book The Knowledge Creating Company (1995) brought the concept of tacit knowledge into the realm of corporate innovation. In it, they suggest that Japanese companies are more innovative because they are able to successfully collectivize individual tacit knowledge to the firm. The two researchers give the example of the first Japanese bread maker, whose development was impossible until the engineers interned themselves to one of Japan's leading bakers. During their internship, they were able to learn the tacit movements required to knead dough, and then transfer this knowledge back to the company.
An example of the problems of tacit knowledge is the Bessemer process – Bessemer sold a patent to his advanced steel making process and was sued by the purchasers who couldn't get it to work – in the end Bessemer set up his own steel company which became one of the largest in the world and changed the face of steel making.
Tacit knowledge may seem a simple idea but its implications are large and far reaching. If important knowledge is tacit, then it cannot be effectively spread through an organization. This means that useful knowledge will not be able to reach those who need it without direct, face-to-face contact. It also means that training newcomers in an organization becomes more time consuming, because they must be given time to learn on their own while doing, which reduces overall efficiency. In order to collectivize and spread tacit knowledge, organizations must invest greatly in the human capital of its members.
Failures due to lack of tacit knowledge - the so called "Law of Unintended Consequences"
Main article: Law of unintended consequences
A technical specialist acquires a defined body of formal knowledge during his education, but to be effective he must acquire tacit knowledge and this is done through a sort of apprenticeship. So a civil engineer has to first have a degree, and then several years of experience before he can become chartered. He is then deemed to be an effective practitioner.
By and large this works well, but in a significant number of cases it does not. As an example, irrigation-scheme-induced Bilharzia and Schistosomiasis, a nasty waterborne parasite, can be put down to civil engineers not being aware of the need to build in cheap anti-bilharzia measures - due to a failure of tacit knowledge and the Relevance Paradox.
The civil engineers were victims of the relevance paradox in that they thought they only needed to know about concrete, water flows etc., not how to restrict velocities, preventing the snail species which carried the disease from multiplying.
Charnock, Anne (1980). Taking Bilharzia's out of the irrigation equation. New Civil Engineer, 7 August. Bilharzia caused by poor civil engineering design due to ignorance of cause and prevention.
Knowledge management
There are many implications for organizational learning and knowledge management, including:
The difficulty inherent in tacit knowledge transfer is that subject matter experts and key knowledge holders may not be aware--hence, unable--to articulate, communicate and describe what they know. Thus, tacit knowledge can be a sustainable competitive advantage.
Tacit knowledge is embedded in group and organizational relationships, core values, assumptions and beliefs. It is hard to identify, locate, quantify, map or value.
Tacit knowledge is impossible to transmit through Central media but it can be transmitted by lateral media .
Tacit knowledge is embedded in human capital. This makes it valuable as a strategic advantage over competitors in terms of innovations, trade secrets, ideas and new technologies.
The concept of tacit knowing comes from scientist and philosopher Michael Polanyi. It is important to understand that he wrote about a process (hence tacit knowing) and not a form of knowledge. However, his phrase has been taken up to name a form of knowledge that is apparently wholly or partly inexplicable.
Definition
By definition, tacit knowledge is knowledge that people carry in their minds and is, therefore, difficult to access. Often, people are not aware of the knowledge they possess or how it can be valuable to others. Tacit knowledge is considered more valuable because it provides context for people, places, ideas, and experiences. Effective transfer of tacit knowledge generally requires extensive personal contact and trust.
Tacit knowledge is not easily shared. One of Polanyi's famous aphorisms is: "We know more than we can tell." Tacit knowledge consists often of habits and culture that we do not recognize in ourselves. In the field of knowledge management the concept of tacit knowledge refers to a knowledge which is only known by an individual and that is difficult to communicate to the rest of an organization. Knowledge that is easy to communicate is called explicit knowledge. The process of transforming tacit knowledge into explicit knowledge is known as codification or articulation.
Properties of tacit knowledge
The tacit aspects of knowledge are those that cannot be codified, but can only be transmitted via training or gained through personal experience. Alternatively, tacit knowledge can be understood to be knowledge that is embedded in a culture (for instance a regional culture, organizational culture or social culture) and is difficult to share with people not embedded in that culture. Tacit knowledge has been described as "know-how" (as opposed to "know-what" [facts], "know-why" [science] and "know-who" [networking]) . It involves learning and skill but not in a way that can be written down. The knowledge of how to ride a bike is an example: one cannot learn to ride a bike by reading a textbook, it takes personal experimentation and practice to gain the necessary skills.
Tacit knowledge has been found to be a crucial input to the innovation process. A society’s ability to innovate depends on its level of tacit knowledge of how to innovate. Polanyi suggested that scientific inquiry could not be reduced to facts, and that the search for new and novel research problems requires tacit knowledge about how to approach an unknown. Further writers have suggested that most laboratory practices, practices that are vital to the successful reproduction of a scientific experiment, are tacit (Collins, 2001). Ikujiro Nonaka and Hirotaka Takeuchi's book The Knowledge Creating Company (1995) brought the concept of tacit knowledge into the realm of corporate innovation. In it, they suggest that Japanese companies are more innovative because they are able to successfully collectivize individual tacit knowledge to the firm. The two researchers give the example of the first Japanese bread maker, whose development was impossible until the engineers interned themselves to one of Japan's leading bakers. During their internship, they were able to learn the tacit movements required to knead dough, and then transfer this knowledge back to the company.
An example of the problems of tacit knowledge is the Bessemer process – Bessemer sold a patent to his advanced steel making process and was sued by the purchasers who couldn't get it to work – in the end Bessemer set up his own steel company which became one of the largest in the world and changed the face of steel making.
Tacit knowledge may seem a simple idea but its implications are large and far reaching. If important knowledge is tacit, then it cannot be effectively spread through an organization. This means that useful knowledge will not be able to reach those who need it without direct, face-to-face contact. It also means that training newcomers in an organization becomes more time consuming, because they must be given time to learn on their own while doing, which reduces overall efficiency. In order to collectivize and spread tacit knowledge, organizations must invest greatly in the human capital of its members.
Failures due to lack of tacit knowledge - the so called "Law of Unintended Consequences"
Main article: Law of unintended consequences
A technical specialist acquires a defined body of formal knowledge during his education, but to be effective he must acquire tacit knowledge and this is done through a sort of apprenticeship. So a civil engineer has to first have a degree, and then several years of experience before he can become chartered. He is then deemed to be an effective practitioner.
By and large this works well, but in a significant number of cases it does not. As an example, irrigation-scheme-induced Bilharzia and Schistosomiasis, a nasty waterborne parasite, can be put down to civil engineers not being aware of the need to build in cheap anti-bilharzia measures - due to a failure of tacit knowledge and the Relevance Paradox.
The civil engineers were victims of the relevance paradox in that they thought they only needed to know about concrete, water flows etc., not how to restrict velocities, preventing the snail species which carried the disease from multiplying.
Charnock, Anne (1980). Taking Bilharzia's out of the irrigation equation. New Civil Engineer, 7 August. Bilharzia caused by poor civil engineering design due to ignorance of cause and prevention.
Knowledge management
There are many implications for organizational learning and knowledge management, including:
The difficulty inherent in tacit knowledge transfer is that subject matter experts and key knowledge holders may not be aware--hence, unable--to articulate, communicate and describe what they know. Thus, tacit knowledge can be a sustainable competitive advantage.
Tacit knowledge is embedded in group and organizational relationships, core values, assumptions and beliefs. It is hard to identify, locate, quantify, map or value.
Tacit knowledge is impossible to transmit through Central media but it can be transmitted by lateral media .
Tacit knowledge is embedded in human capital. This makes it valuable as a strategic advantage over competitors in terms of innovations, trade secrets, ideas and new technologies.
Friday, December 7, 2007
Knowlede Management - What & Why ?
What is "knowledge"?
Aren’t we managing knowledge already? Well, no. In fact, most of the time we’re making a really ugly mess of managing information. In practice, the terms information and knowledge are often used interchangeably by business writers.
Let’s choose a simple working definition and get on with it:
Knowledge has two basic definitions of interest. The first pertains to a defined body of information. Depending on the definition, the body of information might consist of facts, opinions, ideas, theories, principles, and models (or other frameworks). Clearly, other categories are possible, too. Subject matter (e.g., chemistry, mathematics, etc.) is just one possibility.
Knowledge also refers to a person’s state of being with respect to some body of information. These states include ignorance, awareness, familiarity, understanding, facility, and so on.
Email from Fred Nickols, Executive Director — Strategic Planning & Management, Educational Testing Service.
There are many thoughtful and thought-provoking definitions of "knowledge" — including the important distinctions Gene Bellinger et al. make in "Data, Information, Knowledge, and Wisdom". Nevertheless, Nickols provides a good, sensible, functional definition, and it is sufficient for our purposes.
Nickols’ two kinds of knowledge parallel Michael Polanyi’s often-quoted distinction between explicit knowledge (sometimes referred to as formal knowledge), which can be articulated in language and transmitted among individuals, and tacit knowledge (also, informal knowledge), personal knowledge rooted in individual experience and involving personal belief, perspective, and values. (Polanyi, Michael. The Tacit Dimension. London: Routledge & Kegan Paul. See also Karl E. Sveiby’s online description, "Tacit Knowledge."
In traditional perceptions of the role of knowledge in business organizations, tacit knowledge is often viewed as the real key to getting things done and creating new value. Not explicit knowledge. Thus we often encounter an emphasis on the "learning organization" and other approaches that stress internalization of information (through experience and action) and generation of new knowledge through managed interaction.
In the opinion of the editors of Knowledge Praxis, quibbles about fine distinctions in the meaning of knowledge are just not very important. (See Rant #1: Thinking objectively about subjective knowing) It doesn’t matter whether a written procedure or a subject matter expert provides a solution to a particular problem, as long as a positive result is achieved. However, observing how knowledge is acquired and how we can apply knowledge — whether tacit or explicit — in order to achieve a positive result that meets business requirements … that’s a different and very important issue.
Why we need knowledge management now
Why do we need to manage knowledge? Ann Macintosh of the Artificial Intelligence Applications Institute (University of Edinburgh) has written a "Position Paper on Knowledge Asset Management" that identifies some of the specific business factors, including:
Marketplaces are increasingly competitive and the rate of innovation is rising.
Reductions in staffing create a need to replace informal knowledge with formal methods.
Competitive pressures reduce the size of the work force that holds valuable business knowledge.
The amount of time available to experience and acquire knowledge has diminished.
Early retirements and increasing mobility of the work force lead to loss of knowledge.
There is a need to manage increasing complexity as small operating companies are trans-national sourcing operations.
Changes in strategic direction may result in the loss of knowledge in a specific area.
To these paraphrases of Ms. Macintosh’s observations we would add:
Most of our work is information based.
Organizations compete on the basis of knowledge.
Products and services are increasingly complex, endowing them with a significant information component.
The need for life-long learning is an inescapable reality.
In brief, knowledge and information have become the medium in which business problems occur. As a result, managing knowledge represents the primary opportunity for achieving substantial savings, significant improvements in human performance, and competitive advantage.
It’s not just a Fortune 500 business problem. Small companies need formal approaches to knowledge management even more, because they don’t have the market leverage, inertia, and resources that big companies do. They have to be much more flexible, more responsive, and more "right" (make better decisions) — because even small mistakes can be fatal to them.
Roadblocks to adoption of knowledge management solutions
There have been many roadblocks to adoption of formal knowledge management activities. In general, managing knowledge has been perceived as an unmanageable kind of problem — an implicitly human, individual activity — that was intractable with traditional management methods and technology.
We tend to treat the activities of knowledge work as necessary, but ill-defined, costs of human resources, and we treat the explicit manifestations of knowledge work as forms of publishing — as byproducts of "real" work.
As a result, the metrics associated with knowledge resources — and our ability to manage those resources in meaningful ways — have not become part of business infrastructure.
But it isn’t necessary to throw up one’s hands in despair. We do know a lot about how people learn. We know more and more about how organizations develop and use knowledge. The body of literature about managing intellectual capital is growing. We have new insights and solutions from a variety of domains and disciplines that can be applied to making knowledge work manageable and measurable. And computer technology — itself a cause of the problem — can provide new tools to make it all work.
We don’t need another "paradigm shift" (Please!), but we do have to accept that the nature of business itself has changed, in at least two important ways:
Knowledge work is fundamentally different in character from physical labor.
The knowledge worker is almost completely immersed in a computing environment. This new reality dramatically alters the methods by which we must manage, learn, represent knowledge, interact, solve problems, and act.
You can’t solve the problems of Information Age business or gain a competitive advantage simply by throwing more information and people at the problems. And you can’t solve knowledge-based problems with approaches borrowed from the product-oriented, print-based economy. Those solutions are reactive and inappropriate.
Applying technology blindly to knowledge-related business problems is a mistake, too, but the computerized business environment provides opportunities and new methods for representing "knowledge" and leveraging its value. It’s not an issue of finding the right computer interface — although that would help, too. We simply have not defined in a rigorous, clear, widely accepted way the fundamental characteristics of "knowledge" in the computing environment. (See "Cooperative development of a classification of knowledge management functions.")
Aren’t we managing knowledge already? Well, no. In fact, most of the time we’re making a really ugly mess of managing information. In practice, the terms information and knowledge are often used interchangeably by business writers.
Let’s choose a simple working definition and get on with it:
Knowledge has two basic definitions of interest. The first pertains to a defined body of information. Depending on the definition, the body of information might consist of facts, opinions, ideas, theories, principles, and models (or other frameworks). Clearly, other categories are possible, too. Subject matter (e.g., chemistry, mathematics, etc.) is just one possibility.
Knowledge also refers to a person’s state of being with respect to some body of information. These states include ignorance, awareness, familiarity, understanding, facility, and so on.
Email from Fred Nickols, Executive Director — Strategic Planning & Management, Educational Testing Service.
There are many thoughtful and thought-provoking definitions of "knowledge" — including the important distinctions Gene Bellinger et al. make in "Data, Information, Knowledge, and Wisdom". Nevertheless, Nickols provides a good, sensible, functional definition, and it is sufficient for our purposes.
Nickols’ two kinds of knowledge parallel Michael Polanyi’s often-quoted distinction between explicit knowledge (sometimes referred to as formal knowledge), which can be articulated in language and transmitted among individuals, and tacit knowledge (also, informal knowledge), personal knowledge rooted in individual experience and involving personal belief, perspective, and values. (Polanyi, Michael. The Tacit Dimension. London: Routledge & Kegan Paul. See also Karl E. Sveiby’s online description, "Tacit Knowledge."
In traditional perceptions of the role of knowledge in business organizations, tacit knowledge is often viewed as the real key to getting things done and creating new value. Not explicit knowledge. Thus we often encounter an emphasis on the "learning organization" and other approaches that stress internalization of information (through experience and action) and generation of new knowledge through managed interaction.
In the opinion of the editors of Knowledge Praxis, quibbles about fine distinctions in the meaning of knowledge are just not very important. (See Rant #1: Thinking objectively about subjective knowing) It doesn’t matter whether a written procedure or a subject matter expert provides a solution to a particular problem, as long as a positive result is achieved. However, observing how knowledge is acquired and how we can apply knowledge — whether tacit or explicit — in order to achieve a positive result that meets business requirements … that’s a different and very important issue.
Why we need knowledge management now
Why do we need to manage knowledge? Ann Macintosh of the Artificial Intelligence Applications Institute (University of Edinburgh) has written a "Position Paper on Knowledge Asset Management" that identifies some of the specific business factors, including:
Marketplaces are increasingly competitive and the rate of innovation is rising.
Reductions in staffing create a need to replace informal knowledge with formal methods.
Competitive pressures reduce the size of the work force that holds valuable business knowledge.
The amount of time available to experience and acquire knowledge has diminished.
Early retirements and increasing mobility of the work force lead to loss of knowledge.
There is a need to manage increasing complexity as small operating companies are trans-national sourcing operations.
Changes in strategic direction may result in the loss of knowledge in a specific area.
To these paraphrases of Ms. Macintosh’s observations we would add:
Most of our work is information based.
Organizations compete on the basis of knowledge.
Products and services are increasingly complex, endowing them with a significant information component.
The need for life-long learning is an inescapable reality.
In brief, knowledge and information have become the medium in which business problems occur. As a result, managing knowledge represents the primary opportunity for achieving substantial savings, significant improvements in human performance, and competitive advantage.
It’s not just a Fortune 500 business problem. Small companies need formal approaches to knowledge management even more, because they don’t have the market leverage, inertia, and resources that big companies do. They have to be much more flexible, more responsive, and more "right" (make better decisions) — because even small mistakes can be fatal to them.
Roadblocks to adoption of knowledge management solutions
There have been many roadblocks to adoption of formal knowledge management activities. In general, managing knowledge has been perceived as an unmanageable kind of problem — an implicitly human, individual activity — that was intractable with traditional management methods and technology.
We tend to treat the activities of knowledge work as necessary, but ill-defined, costs of human resources, and we treat the explicit manifestations of knowledge work as forms of publishing — as byproducts of "real" work.
As a result, the metrics associated with knowledge resources — and our ability to manage those resources in meaningful ways — have not become part of business infrastructure.
But it isn’t necessary to throw up one’s hands in despair. We do know a lot about how people learn. We know more and more about how organizations develop and use knowledge. The body of literature about managing intellectual capital is growing. We have new insights and solutions from a variety of domains and disciplines that can be applied to making knowledge work manageable and measurable. And computer technology — itself a cause of the problem — can provide new tools to make it all work.
We don’t need another "paradigm shift" (Please!), but we do have to accept that the nature of business itself has changed, in at least two important ways:
Knowledge work is fundamentally different in character from physical labor.
The knowledge worker is almost completely immersed in a computing environment. This new reality dramatically alters the methods by which we must manage, learn, represent knowledge, interact, solve problems, and act.
You can’t solve the problems of Information Age business or gain a competitive advantage simply by throwing more information and people at the problems. And you can’t solve knowledge-based problems with approaches borrowed from the product-oriented, print-based economy. Those solutions are reactive and inappropriate.
Applying technology blindly to knowledge-related business problems is a mistake, too, but the computerized business environment provides opportunities and new methods for representing "knowledge" and leveraging its value. It’s not an issue of finding the right computer interface — although that would help, too. We simply have not defined in a rigorous, clear, widely accepted way the fundamental characteristics of "knowledge" in the computing environment. (See "Cooperative development of a classification of knowledge management functions.")
Knowledge Management—Emerging Perspectives
Yes, knowledge management is the hottest subject of the day. The question is: what is this activity called knowledge management, and why is it so important to each and every one of us? The following writings, articles, and links offer some emerging perspectives in response to these questions. As you read on, you can determine whether it all makes any sense or not.
Content
Developing a Context
A Continuum
An Example
Extending the Concept
Knowledge Management: Bah Humbug!
The Value of Knowledge Management
References
Developing a Context
Like water, this rising tide of data can be viewed as an abundant, vital and necessary resource. With enough preparation, we should be able to tap into that reservoir -- and ride the wave -- by utilizing new ways to channel raw data into meaningful information. That information, in turn, can then become the knowledge that leads to wisdom. Les Alberthal[alb95]
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.
An Example
This example uses a bank savings account to show how data, information, knowledge, and wisdom relate to principal, interest rate, and interest.
Data: The numbers 100 or 5%, completely out of context, are just pieces of data. Interest, principal, and interest rate, out of context, are not much more than data as each has multiple meanings which are context dependent.
Information: If I establish a bank savings account as the basis for context, then interest, principal, and interest rate become meaningful in that context with specific interpretations.
Principal is the amount of money, $100, in the savings account.
Interest rate, 5%, is the factor used by the bank to compute interest on the principal.
Knowledge: If I put $100 in my savings account, and the bank pays 5% interest yearly, then at the end of one year the bank will compute the interest of $5 and add it to my principal and I will have $105 in the bank. This pattern represents knowledge, which, when I understand it, allows me to understand how the pattern will evolve over time and the results it will produce. In understanding the pattern, I know, and what I know is knowledge. If I deposit more money in my account, I will earn more interest, while if I withdraw money from my account, I will earn less interest.
Wisdom: Getting wisdom out of this is a bit tricky, and is, in fact, founded in systems principles. The principle is that any action which produces a result which encourages more of the same action produces an emergent characteristic called growth. And, nothing grows forever for sooner or later growth runs into limits.
If one studied all the individual components of this pattern, which represents knowledge, they would never discover the emergent characteristic of growth. Only when the pattern connects, interacts, and evolves over time, does the principle exhibit the characteristic of growth.
Note: If the mechanics of this diagram are unfamiliar, you can find the basis in Systems Thinking Introduction[bel96] .
Now, if this knowledge is valid, why doesn't everyone simply become rich by putting money in a savings account and letting it grow? The answer has to do with the fact that the pattern described above is only a small part of a more elaborate pattern which operates over time. People don't get rich because they either don't put money in a savings account in the first place, or when they do, in time, they find things they need or want more than being rich, so they withdraw money. Withdrawing money depletes the principal and subsequently the interest they earn on that principal. Getting into this any deeper is more of a systems thinking exercise than is appropriate to pursue here.
A Continuum
Note that the sequence data -> information -> knowledge -> wisdom represents an emergent continuum. That is, although data is a discrete entity, the progression to information, to knowledge, and finally to wisdom does not occur in discrete stages of development. One progresses along the continuum as one's understanding develops. Everything is relative, and one can have partial understanding of the relations that represent information, partial understanding of the patterns that represent knowledge, and partial understanding of the principles which are the foundation of wisdom. As the partial understanding stage.
Extending the Concept
We learn by connecting new information to patterns that we already understand. In doing so, we extend the patterns. So, in my effort to make sense of this continuum, I searched for something to connect it to that already made sense. And, I related it to Csikszentmihalyi's interpretation of complexity.
Csikszentmihalyi[csi94] provides a definition of complexity based on the degree to which something is simultaneously differentiated and integrated. His point is that complexity evolves along a corridor and he provides some very interesting examples as to why complexity evolves. The diagram below indicates that what is more highly differentiated and integrated is more complex. While high levels of differentiation without integration promote the complicated, that which is highly integrated, without differentiation, produces mundane. And, it should be rather obvious from personal experience that we tend to avoid the complicated and are uninterested in the mundane. The complexity that exists between these two alternatives is the path we generally find most attractive.
On 4/27/05 Robert Lamb commented that Csikszentmihalyi's labeling could be is bit clearer if "Differentiation" was replaced by "Many Components" and "Integration" was replaced by Highly Interconnected." Robert also commented that "Common Sense" might be another label for "Mundane." If the mundane is something we seem to avoid paying attention to then "Common Sense" might often be a very appropriate label. Thanks Robert.
What I found really interesting was the view that resulted when I dropped this diagram on top of the one at the beginning of this article. It seemed that "Integrated" and "Understanding" immediately correlated to each other. There was also a real awareness that "Context Independence" related to "Differentiated." Overall, the continuum of data to wisdom seemed to correlate exactly to Csikszentmihalyi's model of evolving complexity.
I now end up with a perception that wisdom is sort of simplified complexity.
Knowledge Management: Bah Humbug!
When I first became interested in knowledge as a concept, and then knowledge management, it was because of the connections I made between my system studies and the data, information, knowledge, and wisdom descriptions already stated. Saying that I became interested is a bit of an understatement as I'm generally either not interested or obsessed, and seldom anywhere in between. Then, after a couple months I managed to catch myself, with the help of Mike Davidson[dav96], as to the indirection I was pursuing.
I managed to survive the Formula Fifties, the Sensitive Sixties, the Strategic Seventies, and the Excellent Eighties to exist in the Nanosecond Nineties, and for a time I thought I was headed for the Learning Organizational Oh's of the next decade. The misdirection I was caught up in was a focus on Knowledge Management not as a means, but as an end in itself. Yes, knowledge management is important, and I'll address reasons why shortly. But knowledge management should simply be one of many cooperating means to an end, not the end in itself, unless your job turns out to be corporate knowledge management director or chief knowledge officer. I'm quite sure it will come to this, for in some ways we are predictably consistent.
I associate the cause of my indirection with the many companies I have been associated with in the past. These companies had pursued TQM or reengineering, not in support of what they were trying to accomplish, but as ends in themselves because they simply didn't know what they were really trying to accomplish. And, since they didn't know what they were really trying to accomplish, the misdirection was actually a relief, and pursued with a passion­­it just didn't get them anywhere in particular.
According to Mike Davidson[dav96], and I agree with him, what's really important is:
Mission: What are we trying to accomplish?
Competition: How do we gain a competitive edge?
Performance: How do we deliver the results?
Change: How do we cope with change?
As such, knowledge management, and everything else for that matter, is important only to the extent that it enhances an organization's ability and capacity to deal with, and develop in, these four dimensions.
The Value of Knowledge Management
In an organizational context, data represents facts or values of results, and relations between data and other relations have the capacity to represent information. Patterns of relations of data and information and other patterns have the capacity to represent knowledge. For the representation to be of any utility it must be understood, and when understood the representation is information or knowledge to the one that understands. Yet, what is the real value of information and knowledge, and what does it mean to manage it?
Without associations we have little chance of understanding anything. We understand things based on the associations we are able to discern. If someone says that sales started at $100,000 per quarter and have been rising 20% per quarter for the last four quarters, I am somewhat confident that sales are now about $207,000 per quarter. I am confident because I know what "rising 20% per quarter" means and I can do the math.
Yet, if someone asks what sales are apt to be next quarter, I would have to say, "It depends!" I would have to say this because although I have data and information, I have no knowledge. This is a trap that many fall into, because they don't understand that data doesn't predict trends of data. What predicts trends of data is the activity that is responsible for the data. To be able to estimate the sales for next quarter, I would need information about the competition, market size, extent of market saturation, current backlog, customer satisfaction levels associated with current product delivery, current production capacity, the extent of capacity utilization, and a whole host of other things. When I was able to amass sufficient data and information to form a complete pattern that I understood, I would have knowledge, and would then be somewhat comfortable estimating the sales for next quarter. Anything less would be just fantasy!
In this example what needs to be managed to create value is the data that defines past results, the data and information associated with the organization, it's market, it's customers, and it's competition, and the patterns which relate all these items to enable a reliable level of predictability of the future.What I would refer to as knowledge management would be the capture, retention, and reuse of the foundation for imparting an understanding of how all these pieces fit together and how to convey them meaningfully to some other person.
The value of Knowledge Management relates directly to the effectiveness[bel97a] with which the managed knowledge enables the members of the organization to deal with today's situations and effectively envision and create their future. Without on-demand access to managed knowledge, every situation is addressed based on what the individual or group brings to the situation with them. With on-demand access to managed knowledge, every situation is addressed with the sum total of everything anyone in the organization has ever learned about a situation of a similar nature. Which approach would you perceive would make a more effective organization?[bel97b]
References
Alberthal, Les. Remarks to the Financial Executives Institute, October 23, 1995, Dallas, TX
Bateson, Gregory. Mind and Nature: A Necessary Unity, Bantam, 1988
Bellinger, Gene. Systems Thinking: An Operational Perspective of the Universe
Bellinger, Gene. The Effective Organization
Bellinger, Gene. The Knowledge Centered Organization
Csikszentmihalyi, Miahly. The Evolving-Self: A Psychology for the Third Millennium, Harperperennial Library, 1994.
Davidson, Mike. The Transformation of Management, Butterworth-Heinemann, 1996.
Fleming, Neil. Coping with a Revolution: Will the Internet Change Learning?, Lincoln University, Canterbury, New Zealand
Senge, Peter. The Fifth Discipline: The Art & Practice of the Learning Organization, Doubleday-Currency, 1990.
theWay of Systems * Feedback * MusingsCopyright © 2004 Gene Bellinger
Content
Developing a Context
A Continuum
An Example
Extending the Concept
Knowledge Management: Bah Humbug!
The Value of Knowledge Management
References
Developing a Context
Like water, this rising tide of data can be viewed as an abundant, vital and necessary resource. With enough preparation, we should be able to tap into that reservoir -- and ride the wave -- by utilizing new ways to channel raw data into meaningful information. That information, in turn, can then become the knowledge that leads to wisdom. Les Alberthal[alb95]
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.
An Example
This example uses a bank savings account to show how data, information, knowledge, and wisdom relate to principal, interest rate, and interest.
Data: The numbers 100 or 5%, completely out of context, are just pieces of data. Interest, principal, and interest rate, out of context, are not much more than data as each has multiple meanings which are context dependent.
Information: If I establish a bank savings account as the basis for context, then interest, principal, and interest rate become meaningful in that context with specific interpretations.
Principal is the amount of money, $100, in the savings account.
Interest rate, 5%, is the factor used by the bank to compute interest on the principal.
Knowledge: If I put $100 in my savings account, and the bank pays 5% interest yearly, then at the end of one year the bank will compute the interest of $5 and add it to my principal and I will have $105 in the bank. This pattern represents knowledge, which, when I understand it, allows me to understand how the pattern will evolve over time and the results it will produce. In understanding the pattern, I know, and what I know is knowledge. If I deposit more money in my account, I will earn more interest, while if I withdraw money from my account, I will earn less interest.
Wisdom: Getting wisdom out of this is a bit tricky, and is, in fact, founded in systems principles. The principle is that any action which produces a result which encourages more of the same action produces an emergent characteristic called growth. And, nothing grows forever for sooner or later growth runs into limits.
If one studied all the individual components of this pattern, which represents knowledge, they would never discover the emergent characteristic of growth. Only when the pattern connects, interacts, and evolves over time, does the principle exhibit the characteristic of growth.
Note: If the mechanics of this diagram are unfamiliar, you can find the basis in Systems Thinking Introduction[bel96] .
Now, if this knowledge is valid, why doesn't everyone simply become rich by putting money in a savings account and letting it grow? The answer has to do with the fact that the pattern described above is only a small part of a more elaborate pattern which operates over time. People don't get rich because they either don't put money in a savings account in the first place, or when they do, in time, they find things they need or want more than being rich, so they withdraw money. Withdrawing money depletes the principal and subsequently the interest they earn on that principal. Getting into this any deeper is more of a systems thinking exercise than is appropriate to pursue here.
A Continuum
Note that the sequence data -> information -> knowledge -> wisdom represents an emergent continuum. That is, although data is a discrete entity, the progression to information, to knowledge, and finally to wisdom does not occur in discrete stages of development. One progresses along the continuum as one's understanding develops. Everything is relative, and one can have partial understanding of the relations that represent information, partial understanding of the patterns that represent knowledge, and partial understanding of the principles which are the foundation of wisdom. As the partial understanding stage.
Extending the Concept
We learn by connecting new information to patterns that we already understand. In doing so, we extend the patterns. So, in my effort to make sense of this continuum, I searched for something to connect it to that already made sense. And, I related it to Csikszentmihalyi's interpretation of complexity.
Csikszentmihalyi[csi94] provides a definition of complexity based on the degree to which something is simultaneously differentiated and integrated. His point is that complexity evolves along a corridor and he provides some very interesting examples as to why complexity evolves. The diagram below indicates that what is more highly differentiated and integrated is more complex. While high levels of differentiation without integration promote the complicated, that which is highly integrated, without differentiation, produces mundane. And, it should be rather obvious from personal experience that we tend to avoid the complicated and are uninterested in the mundane. The complexity that exists between these two alternatives is the path we generally find most attractive.
On 4/27/05 Robert Lamb commented that Csikszentmihalyi's labeling could be is bit clearer if "Differentiation" was replaced by "Many Components" and "Integration" was replaced by Highly Interconnected." Robert also commented that "Common Sense" might be another label for "Mundane." If the mundane is something we seem to avoid paying attention to then "Common Sense" might often be a very appropriate label. Thanks Robert.
What I found really interesting was the view that resulted when I dropped this diagram on top of the one at the beginning of this article. It seemed that "Integrated" and "Understanding" immediately correlated to each other. There was also a real awareness that "Context Independence" related to "Differentiated." Overall, the continuum of data to wisdom seemed to correlate exactly to Csikszentmihalyi's model of evolving complexity.
I now end up with a perception that wisdom is sort of simplified complexity.
Knowledge Management: Bah Humbug!
When I first became interested in knowledge as a concept, and then knowledge management, it was because of the connections I made between my system studies and the data, information, knowledge, and wisdom descriptions already stated. Saying that I became interested is a bit of an understatement as I'm generally either not interested or obsessed, and seldom anywhere in between. Then, after a couple months I managed to catch myself, with the help of Mike Davidson[dav96], as to the indirection I was pursuing.
I managed to survive the Formula Fifties, the Sensitive Sixties, the Strategic Seventies, and the Excellent Eighties to exist in the Nanosecond Nineties, and for a time I thought I was headed for the Learning Organizational Oh's of the next decade. The misdirection I was caught up in was a focus on Knowledge Management not as a means, but as an end in itself. Yes, knowledge management is important, and I'll address reasons why shortly. But knowledge management should simply be one of many cooperating means to an end, not the end in itself, unless your job turns out to be corporate knowledge management director or chief knowledge officer. I'm quite sure it will come to this, for in some ways we are predictably consistent.
I associate the cause of my indirection with the many companies I have been associated with in the past. These companies had pursued TQM or reengineering, not in support of what they were trying to accomplish, but as ends in themselves because they simply didn't know what they were really trying to accomplish. And, since they didn't know what they were really trying to accomplish, the misdirection was actually a relief, and pursued with a passion­­it just didn't get them anywhere in particular.
According to Mike Davidson[dav96], and I agree with him, what's really important is:
Mission: What are we trying to accomplish?
Competition: How do we gain a competitive edge?
Performance: How do we deliver the results?
Change: How do we cope with change?
As such, knowledge management, and everything else for that matter, is important only to the extent that it enhances an organization's ability and capacity to deal with, and develop in, these four dimensions.
The Value of Knowledge Management
In an organizational context, data represents facts or values of results, and relations between data and other relations have the capacity to represent information. Patterns of relations of data and information and other patterns have the capacity to represent knowledge. For the representation to be of any utility it must be understood, and when understood the representation is information or knowledge to the one that understands. Yet, what is the real value of information and knowledge, and what does it mean to manage it?
Without associations we have little chance of understanding anything. We understand things based on the associations we are able to discern. If someone says that sales started at $100,000 per quarter and have been rising 20% per quarter for the last four quarters, I am somewhat confident that sales are now about $207,000 per quarter. I am confident because I know what "rising 20% per quarter" means and I can do the math.
Yet, if someone asks what sales are apt to be next quarter, I would have to say, "It depends!" I would have to say this because although I have data and information, I have no knowledge. This is a trap that many fall into, because they don't understand that data doesn't predict trends of data. What predicts trends of data is the activity that is responsible for the data. To be able to estimate the sales for next quarter, I would need information about the competition, market size, extent of market saturation, current backlog, customer satisfaction levels associated with current product delivery, current production capacity, the extent of capacity utilization, and a whole host of other things. When I was able to amass sufficient data and information to form a complete pattern that I understood, I would have knowledge, and would then be somewhat comfortable estimating the sales for next quarter. Anything less would be just fantasy!
In this example what needs to be managed to create value is the data that defines past results, the data and information associated with the organization, it's market, it's customers, and it's competition, and the patterns which relate all these items to enable a reliable level of predictability of the future.What I would refer to as knowledge management would be the capture, retention, and reuse of the foundation for imparting an understanding of how all these pieces fit together and how to convey them meaningfully to some other person.
The value of Knowledge Management relates directly to the effectiveness[bel97a] with which the managed knowledge enables the members of the organization to deal with today's situations and effectively envision and create their future. Without on-demand access to managed knowledge, every situation is addressed based on what the individual or group brings to the situation with them. With on-demand access to managed knowledge, every situation is addressed with the sum total of everything anyone in the organization has ever learned about a situation of a similar nature. Which approach would you perceive would make a more effective organization?[bel97b]
References
Alberthal, Les. Remarks to the Financial Executives Institute, October 23, 1995, Dallas, TX
Bateson, Gregory. Mind and Nature: A Necessary Unity, Bantam, 1988
Bellinger, Gene. Systems Thinking: An Operational Perspective of the Universe
Bellinger, Gene. The Effective Organization
Bellinger, Gene. The Knowledge Centered Organization
Csikszentmihalyi, Miahly. The Evolving-Self: A Psychology for the Third Millennium, Harperperennial Library, 1994.
Davidson, Mike. The Transformation of Management, Butterworth-Heinemann, 1996.
Fleming, Neil. Coping with a Revolution: Will the Internet Change Learning?, Lincoln University, Canterbury, New Zealand
Senge, Peter. The Fifth Discipline: The Art & Practice of the Learning Organization, Doubleday-Currency, 1990.
theWay of Systems * Feedback * MusingsCopyright © 2004 Gene Bellinger
Thursday, December 6, 2007
Intellectual Capital
“The owners of the tools of production determine economic structure”. (Marx, 1912)
From the mid-nineteenth century to some time in the early twentieth century the tools of production were buildings, machines, and materials; and what it required to own them, was money. Therefore those who had the money, the capitalists, wielded the power in industry.
By the mid-1930s business had become much more sophisticated and money had become more accessible. With modern banking and the availability of venture capital, one didn’t need to own the money in order to be able to use it. Because of the increasing sophistication and complexity of businesses, highly expert managers were needed to run them successfully. The tools of production became management skill, and the managers wielded the power. There is a considerable amount of literature on the separation of management and ownership, and the conflict generated by the transition of power from shareholder to executive. (Burnham, 1941; Berle & Means, 1932; Jacobs, 1991; Belasco & Stayer, 1994)
In the late twentieth century it appears that yet another shift is taking place. Businesses are being reengineered, management structures are being flattened, and workers are being empowered. The new emphasis is on knowledge workers. The new tools of production are specialist skills and knowledge - intellectual capital.
“The principle tools of production today are not machinery and equipment, but the ideas and talents of the people. Today, the intellectual capital of the scientist, the machinist, and the programmer is the critical resource, so the possessors of the intellectual tools of production - people - will come to exercise effective power.” (Belasco & Stayer, 1994)
Charles Handy advises:
“In the age of intellectual capital, we need to rethink the constitution of our corporations to give a proper voice to those who really own that capital - the core workers.” (Rapoport, 1994)
Although Marx might not recognise the form he would be satisfied with the result: the tools of production are finally in the hands of the (knowledge) workers.
During the periods when capitalists and managers owned the tools of production, the economic structures determined by them were well documented in a wealth of theory, frameworks and systems. These date as far back as the fifteenth century when Friar Lucas de Borga of Venice published his treatise, which recorded the concept of double-entry bookkeeping, which some believe was already in use by the Romans and Greeks.
In the last century, Weber’s observations on the German Army, and Fayol’s experience of running French coal mines resulted in the command and control theories of management still popular in many businesses today. (Weber, 1947; Fayol, 1931; Belasco & Stayer, 1994) Over the last century thousands of books have been written, business schools have been set up, graduate degree courses have been created, to develop and propagate the theories, frameworks and systems of management and administration based on the needs of the ‘money capital’ and ‘management skill capital’ eras.
In the coming epoch of intellectual capital some of these theories, frameworks and systems are becoming inadequate.
Edmund Jenkins who chairs a task force for the American Institute of Certified Public Accountants says: “The components of cost in a product today are largely R& D, intellectual assets, and services. The old accounting system, which tells us the cost of material and labor, isn’t applicable.” (Stewart, 1994)
Of grave concern to accountants is the “difficulty of measuring and managing the chief ingredient of the new economy: intellectual capital, the intangible assets of skill, knowledge, and information. Accounting for intellectual capital is more than an exercise for the cloistered or the fad-struck. What’s at stake is nothing less than learning how to operate and evaluate a business when knowledge is its chief resource and result.” (Stewart, 1994)
“People should be counted as an asset, not a cost. Their knowledge and competence are the main sources of wealth-generating capacity today.” (Dodds, 1993)
Charles Handy estimates that the intellectual assets of an enterprise are usually worth three to four times tangible book value. (Stewart, 1994)
Pioneer companies are starting to try and measure intellectual capital in order to account for it. However accounting is only one aspect of the business. The modern enterprise needs to do more than merely reflect intellectual capital on the balance sheet, it must develop structures and frameworks, strategies and procedures for capitalising on it. The structures and frameworks offered by Enterprise Architecture qualify as high calibre ordinance in the arsenal of any large, complex enterprise which aims to survive the battles of twenty-first century commerce.
In 1991 Skandia Assurance & Financial Services (1993 premium income $2.2 billion), appointed Lief Edvinsson as the corporate world’s first director of intellectual capital. Edvinsson, who believes that the value of intellectual assets exceeds by many times the value of assets that appear on the balance sheet, identifies two kinds of intellectual capital, human and structural. Human intellectual capital is important as the source of innovation and renewal, but is useless if it cannot be exploited. Exploiting it requires structural intellectual assets, such as software applications, manuals, and other structured know-how - those things which turn individual know-how into the property of a group. Edvinsson believes that for managers and shareholders, structural capital counts most; it remains the property of the enterprise, it puts new ideas to work, it amplifies the value of human capital, and it can be used again and again to create value. (Stewart, 1994)
Enterprise Architecture can be a particularly powerful tool in capturing and capitalising on structural intellectual assets.
The process of accumulating intellectual assets is often referred to as organisational learning .
From the mid-nineteenth century to some time in the early twentieth century the tools of production were buildings, machines, and materials; and what it required to own them, was money. Therefore those who had the money, the capitalists, wielded the power in industry.
By the mid-1930s business had become much more sophisticated and money had become more accessible. With modern banking and the availability of venture capital, one didn’t need to own the money in order to be able to use it. Because of the increasing sophistication and complexity of businesses, highly expert managers were needed to run them successfully. The tools of production became management skill, and the managers wielded the power. There is a considerable amount of literature on the separation of management and ownership, and the conflict generated by the transition of power from shareholder to executive. (Burnham, 1941; Berle & Means, 1932; Jacobs, 1991; Belasco & Stayer, 1994)
In the late twentieth century it appears that yet another shift is taking place. Businesses are being reengineered, management structures are being flattened, and workers are being empowered. The new emphasis is on knowledge workers. The new tools of production are specialist skills and knowledge - intellectual capital.
“The principle tools of production today are not machinery and equipment, but the ideas and talents of the people. Today, the intellectual capital of the scientist, the machinist, and the programmer is the critical resource, so the possessors of the intellectual tools of production - people - will come to exercise effective power.” (Belasco & Stayer, 1994)
Charles Handy advises:
“In the age of intellectual capital, we need to rethink the constitution of our corporations to give a proper voice to those who really own that capital - the core workers.” (Rapoport, 1994)
Although Marx might not recognise the form he would be satisfied with the result: the tools of production are finally in the hands of the (knowledge) workers.
During the periods when capitalists and managers owned the tools of production, the economic structures determined by them were well documented in a wealth of theory, frameworks and systems. These date as far back as the fifteenth century when Friar Lucas de Borga of Venice published his treatise, which recorded the concept of double-entry bookkeeping, which some believe was already in use by the Romans and Greeks.
In the last century, Weber’s observations on the German Army, and Fayol’s experience of running French coal mines resulted in the command and control theories of management still popular in many businesses today. (Weber, 1947; Fayol, 1931; Belasco & Stayer, 1994) Over the last century thousands of books have been written, business schools have been set up, graduate degree courses have been created, to develop and propagate the theories, frameworks and systems of management and administration based on the needs of the ‘money capital’ and ‘management skill capital’ eras.
In the coming epoch of intellectual capital some of these theories, frameworks and systems are becoming inadequate.
Edmund Jenkins who chairs a task force for the American Institute of Certified Public Accountants says: “The components of cost in a product today are largely R& D, intellectual assets, and services. The old accounting system, which tells us the cost of material and labor, isn’t applicable.” (Stewart, 1994)
Of grave concern to accountants is the “difficulty of measuring and managing the chief ingredient of the new economy: intellectual capital, the intangible assets of skill, knowledge, and information. Accounting for intellectual capital is more than an exercise for the cloistered or the fad-struck. What’s at stake is nothing less than learning how to operate and evaluate a business when knowledge is its chief resource and result.” (Stewart, 1994)
“People should be counted as an asset, not a cost. Their knowledge and competence are the main sources of wealth-generating capacity today.” (Dodds, 1993)
Charles Handy estimates that the intellectual assets of an enterprise are usually worth three to four times tangible book value. (Stewart, 1994)
Pioneer companies are starting to try and measure intellectual capital in order to account for it. However accounting is only one aspect of the business. The modern enterprise needs to do more than merely reflect intellectual capital on the balance sheet, it must develop structures and frameworks, strategies and procedures for capitalising on it. The structures and frameworks offered by Enterprise Architecture qualify as high calibre ordinance in the arsenal of any large, complex enterprise which aims to survive the battles of twenty-first century commerce.
In 1991 Skandia Assurance & Financial Services (1993 premium income $2.2 billion), appointed Lief Edvinsson as the corporate world’s first director of intellectual capital. Edvinsson, who believes that the value of intellectual assets exceeds by many times the value of assets that appear on the balance sheet, identifies two kinds of intellectual capital, human and structural. Human intellectual capital is important as the source of innovation and renewal, but is useless if it cannot be exploited. Exploiting it requires structural intellectual assets, such as software applications, manuals, and other structured know-how - those things which turn individual know-how into the property of a group. Edvinsson believes that for managers and shareholders, structural capital counts most; it remains the property of the enterprise, it puts new ideas to work, it amplifies the value of human capital, and it can be used again and again to create value. (Stewart, 1994)
Enterprise Architecture can be a particularly powerful tool in capturing and capitalising on structural intellectual assets.
The process of accumulating intellectual assets is often referred to as organisational learning .
The Seven Myths of Knowledge Management
In the finger-pointing about how U.S. authorities might have gathered enough information to head off the Sept. 11 terrorist attacks, a shocking lack of communication came to light. A few months ahead of the attacks, an FBI agent in Minnesota raised an alarm about Zacarias Moussaoui, thinking his interest in learning how to fly large jets was related to terrorism. At the same time, an FBI agent in Phoenix had noticed that a group of Arabs had enrolled in flight school and thought he could tie the trend to Osama bin Laden. Yet the two agents never knew about each other’s concerns until too late. Without corroborating evidence, both agents’ concerns never went anywhere.
This sort of breakdown in sharing knowledge—which can result from what the CIA calls TMI, or Too Much Information—is so common in the corporate world that businesses will try to solve the problem by investing $12.7 billion in knowledge-management systems in 2005, up from $2.3 billion in 2000, according to research firm IDC (www.idc.com).
This sort of breakdown in sharing knowledge—which can result from what the CIA calls TMI, or Too Much Information—is so common in the corporate world that businesses will try to solve the problem by investing $12.7 billion in knowledge-management systems in 2005, up from $2.3 billion in 2000, according to research firm IDC (www.idc.com).
Yet, even as they spend all this money, many executives have the sense that they’ve been there and done that—with little to show for all the effort they’ve put into knowledge management. Is all that investment being wasted? Or is there some way to do a better job and reap the benefits of the effort?
If you look at how companies approach knowledge management, you can see that the problem is in the execution. Companies commonly make catastrophic mistakes by falling for one of these seven myths:
(1) KNOWLEDGE MANAGEMENT IS ABOUT KNOWLEDGE. "Knowledge” is one of those words that sound great. Who isn’t for more and better knowledge? It’s almost patriotic. But the real question is: knowledge to what end? Companies that deploy knowledge-management systems hoping they will eventually stumble across a purpose for their knowledge—and there are many such companies—may be in for a long wait. The systems must start and end as all business initiatives should, with a focus on delivering top-line growth, improving operations, and increasing profit margins.
(2) KNOWLEDGE MANAGEMENT IS ABOUT THE TECHNOLOGY. Many companies become so focused on building the knowledge-management system that deploying the technology is all they do. And they fail. One large firm I know built the Rolls Royce of knowledge platforms, a true technological tour de force. But everyone was so busy overengineering the system that they gave too little consideration to how it would operate, to what problem the system was supposed to address, and to how it would integrate with the overarching technology strategy. In the end, the system could not keep up with the rapidly changing business, there was little flexibility to adapt to individual users, and every upgrade became a Herculean task.
(3) THE SYSTEM SHOULD BE SO ALL-ENCOMPASSING THAT IT CAN CURE CANCER AND END WORLD HUNGER. In fact, if you set enormous expectations, you’re almost guaranteed to fail to live up to them and may be dismissed as a failure. Instead, realize that you don’t have to solve every information problem in your business on the first day. You should start small, so you can demonstrate successes and develop evangelists for your efforts.
A telecom company I was involved with took the right approach. Pursuing a huge contract at a large banking customer, the telecom company leveraged knowledge-management tools to integrate the efforts of a global sales team. The team was never caught off guard through the long, arduous sales cycle and had the agility to win the deal. Based on the visibility of that success, and on the lessons learned during that initial foray into knowledge management, this telecom company has been able to extend the capability to all of its most significant sales activities.
A telecom company I was involved with took the right approach. Pursuing a huge contract at a large banking customer, the telecom company leveraged knowledge-management tools to integrate the efforts of a global sales team. The team was never caught off guard through the long, arduous sales cycle and had the agility to win the deal. Based on the visibility of that success, and on the lessons learned during that initial foray into knowledge management, this telecom company has been able to extend the capability to all of its most significant sales activities.
One caveat: You need to think big even as you start small. That’s because you need to make sure that the knowledge-management architecture that you begin with will still work as you expand to include other parts of your business.
(4) THE GOAL IS TO CREATE A DOCUMENT REPOSITORY. Certainly, document management can be a priority if employees often have trouble finding critical information or carry out redundant efforts to develop the same information. However, you must focus as much on the value and reliability of the information as on how the information is stored.
The research department of a global firm I know found this out the hard way. It put all its white papers and research reports online but found that few people used them. Then the firm built a way for people to query each other—people no longer just looked up information but could find the scientists who generated the information and ask a precise question. Employees were delighted. They made better decisions, and in less time.
(5) YOU CAN BUY A READY-MADE SYSTEM. Wishful thinking. Knowledge-management systems are as individualized as the businesses that use them. While there are plenty of good tools available commercially, the real issue is how those are all tied together companywide and how they are integrated into your growth, operations, and technology strategies. If your knowledge-management program asks employees to use four search engines, three document-management systems, and six types of collaboration tools, on multiple types of computer systems, you’re dead. Individual parts of your business might argue that they should be able to tackle knowledge management on their own, but you’re almost always better off being consistent throughout your business.
(6) KNOWLEDGE MANAGEMENT IS ABOUT KNOWLEDGE CONTROL. Companies worry excessively that people will put content in the wrong place or that they can’t be trusted with so much information. They add layer upon layer of approvals for contributing information or accessing it—and sap the potential of their systems.
One executive recently told me that his company had instituted an elaborate system for tracking the relationships it has with customers—then made sure that all its salesmen had access to very little of that information, for fear that they might defect to a competitor and take information with them.
In the end, knowledge management isn’t about maintaining a pristine database. It’s about fostering an environment in which people can ask questions like, “Does anybody know...?” Or, “Who can help me...?” This means an open system that encourages building relationships through communities and creating opportunities for personal interaction, across cubicles and across oceans.
One executive recently told me that his company had instituted an elaborate system for tracking the relationships it has with customers—then made sure that all its salesmen had access to very little of that information, for fear that they might defect to a competitor and take information with them.
In the end, knowledge management isn’t about maintaining a pristine database. It’s about fostering an environment in which people can ask questions like, “Does anybody know...?” Or, “Who can help me...?” This means an open system that encourages building relationships through communities and creating opportunities for personal interaction, across cubicles and across oceans.
(7) IF YOU BUILD IT, THEY WILL USE IT. When done right, knowledge management transforms an organization. That isn’t an easy task. Before you deploy your system, you need to consider the concerns people will have about a new way of doing things. You have to consider the attributes of your culture that encourage knowledge sharing and those that encourage hoarding. Most importantly, you have to face up to the fact that senior executives must provide strong leadership.
Believing any one of these myths is fatal. Merely avoiding them will give companies a much better chance of getting the right information to the right people at the right time.
Rosenberg is a senior director with DiamondCluster International Inc. and the firm’s field leader in knowledge management. He can be reached at marc.rosenberg@diamondcluster.com.
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