An Introduction to Knowledge Management
If knowledge is so important to an enterprise then you might see your own career development as the trading of your own knowledge and if this is the case, will this ring in a new form of employment?
Tom Steward puts it nicely by saying that in today’s economy, knowledge is what you buy and sell and you can’t smell or touch it. Fritz Machlup analyzed loads of data for his 1962 book “The Production and Distribution of Knowledge in the United States” and found that from 1900 to 1959 the US labour force grew by 137% but the knowledge producing occupations by 602%. Daniel Bell in his book “The Coming of the Post Industrial Society” from 1973 focussed on scientific knowledge, which could influence production methods.
In terms of the role of technology in knowledge management, Marc Baker of Royal Mail says: Knowledge management is 70% people, 20% process and 10% technology. This falls well in place with a big problem with de-layering, downsizing and generally letting people go, as best said in a quote by George Santayana: Those who cannot remember the past are condemned to repeat it.
Drivers for Knowledge Management include:
\- Wealth from knowledge
\- Knowledge Interdependency
\- Technology
\- Innovation
\- Organizational Learning
\- Human Resources
Managing Knowledge in Practice
There are different kinds of knowledge presented in this part of the course:
\- Expert networks
\- Corporate and people knowledge
\- Intellectual property assets
\- Intangible parts of knowledge: intellectual capital and managing it as a knowledge managing activity
\- Capturing and Re-Using past experiences
\- Embedding knowledge in products, services, brands and processes
\- Producing knowledge
\- Driving knowledge generation for innovation
\- Building and mining knowledge stores
This gives us 9 categories. The problem with mining them for profit is questionable. Can any type of knowledge be thought of as valid and reliable in the long term aka durable, a given needed for sustainable advantage.
Definitions of knowledge management is hard but Xerox has a good example: Knowledge management is the discipline of creating a thriving work and learning environment that fosters the continuous creation, aggregation, use and re-use of both organizational and personal knowledge in the pursuit of new business value.
The cross-boundary part of knowledge management is often forgotten though. Knowledge is often written about in terms of its capability as an asset of producing value aka intellectual capital. This is often seen as evident through the difference of market and book value.
It can also be said that this difference is simply looking at future profit streams which are based on the future market but also on the track record, resources and capabilities of the enterprise, which again amounts to intellectual capital.
Pay attention though that for the sake of balancing assets and liabilities a lot of companies have huge amounts of goodwill in their books. So profits might not be the best comparison. Due to prudence in financial accounting the goodwill should still be less than the difference between book and market value.
Information management (technology) is only a small part of knowledge management. The learning organization is likely a better fit, but it has become something like TQM and will not be covered in great depth here.
Where does all this lead us? This best is very difficult to define!
What is knowledge anyway?
The greek word for knowledge is episteme, leading us to epistomology, the study of or theories about knowledge. In terms of worlds, it is interesting to note that the English language has one word: knowledge. The french have connaitre and savoir. The germans have kennen and wissen. This leads us to a definition: Knowledge is that which is known.
There are a lot of different ways to “know” though and the question arises by whom and if all knowledge is valid and true. Tacit knowledge, a term coined by Polanyi is also possibly impossible to share. At best it will be given from expert to apprentice through watching and trial and error under guidance.
Bishop Berkelly supported the argument that your real world is a projection of your mind and no real world exists (for us) outside of it.
Scientific knowledge is not really truth either but rather gained through positivism, a confirmation of an experiment leading to a scientific law, a “proven” hypothesis. The root here is induction, meaning that you more from special observations to a general idea.
As an example, quantum physics explains to a large degree what happens in the small, but it is still but a theory. Even A leads to Event B a million times does not mean that Event A really leads to Even B (Hume’s problem)
We end up with what Machlup called “not yet falsified” knowledge. So scientific knowledge is not really special or truer.
Polanyi also said something else: We know more than we can tell.
This is the tacit knowledge problem. Gibbons in “The New Production of Knowledge” argues that we now have Mode 1 and Mode 2 knowledge, where Mode 2 is more implicit, stored within us, and gaining importance. Mode 2 is also a bit allied with the idea of the reflective practitioner.
Kuhn argues that science is based on paradigms and as there are no independent facts a paradigm shift is more of a battle between different social groups, with different languages and assumptions. Hence science is not a quest for objective truth.
Data, Information and Knowledge
Peter Drucker said that information is “data endowed with relevance and purpose”. Data is unorganized observations, numbers, words, sounds and images. Information is data arranged and processes into meaningful patterns. Knowledge is information put into productive use, made actionable and given meaning.
You move from Data to Information (Data with Content), to Knowledge (Information with meaning) to Wisdom (knowledge with insight).
Remember though that data for your might be knowledge for somebody else.
How do you make a knowledge typology then:
\- Knowing that
\- Knowing how
\- Knowing who
\- Knowing when
\- Knowing where
\- Knowing why
Quinn orders these into several categories on a personal level.
\- Cognitive knowledge (know what)
\- Advanced skills (Know how)
\- Systems understanding (know why)
\- Self-motivated creativity (care why=
Karl Wiig classified knowledge management as:
\- factual knowledge
\- conceptual knowledge
\- Expectational knowledge
\- Methodological knowledge
The B823 approach and themes
The course moves from an individual to a group/team and on to the organizational and extra-organizational process and context. Then it moves back to how the organization can manage the individual for knowledge. Themes are:
\- Resources and capabilities: The process of knowledge management are those that ensure the capability to create, integrate, transform, apply and communicate knowledge of all kinds to meet existing and emerging needs and develop new opportunities.
\- Knowledge creation and application
\- Reflective practitioner
\- Communication
\- Technology and Knowledge Management
\- Knowledge and Management
\- The importance of context
\- Managing knowledge as a collective enterprise
\- Knowledge and knowing
\- Uncertainty and complexity