Key Issues in the New Knowledge Management (KMCI Press)

The model uses an interesting framework: Understanding is therefore identified as the transformational relationship among data, information, knowledge, and wisdom to create an outcome at a higher level. Although this model does not show whether or how one can j j VOL. Redefining the scope of the hierarchy All the definitions and models reviewed have led to a linear hierarchy, where data is the basis for information, which is the basis for knowledge, which is itself the basis for wisdom.

The reverse of the ascent from data to wisdom is also possible, following the same reasoning. Authors can describe it as a pyramid, a hierarchy, or a circle, but it remains linear as there are no feedback loops. The first step for improving these models is to realize that they have neither a starting point nor an ending point.

Knowledge Management Publications from KMCI

In other words, these models need clearer boundaries. From Table II it is obvious that the literature focuses on defining the difference between information and knowledge, but little attention is paid to the definition of data. Data is not found in nature; it does not grow on trees, and it does not fall from the sky for free. Data have to be made out of something. Data are usually described as observations of reality.

Back in prehistoric times, Cro-Magnons used pictographic representation for data while counting animals; later in history, Sumerians applied symbolic representations of data to capture and record grain harvests and other economic data. Hence, data are more that just observations; they are a level of understanding of existence. Existence describes the whole environment that humans can grasp and create data about. Data are a very basic processed outcome of human observation of existence. What is higher than wisdom? Buddhists refer to enlightenment as the awakening of beings.

To awaken is to achieve a level of insight and understanding equal to that of the Buddhas Van Hien Study Group, However, they make a distinction between awakening and supreme enlightenment, as there are many levels of awakening. It is not the intention of this paper to discuss metaphysics; however, it is useful in reaching the full scope of a hierarchy of knowledge. Enlightenment is the highest form of understanding. Therefore, it should be incorporated into a model that purports to represent a complete perspective on the hierarchy of knowledge.

• Bestselling Series!
• Richard Millet, avant, après (French Edition)?
• Top Authors.

The result is illustrated in Figure 3. Indeed, it is suggested in this paper that not having the two constructs of enlightenment and existence means not taking into account the appropriate borders of the knowledge system. Consequently, traditional models such as the knowledge pyramid are closed systems. Because knowledge management would profit from complexity theory McElroy, , a more coherent model of the knowledge system should be open. Existence and Enlightenment are two states of being which provide the boundaries of the knowledge system.

Data, information, knowledge, and wisdom are cognitive constructs lying in between those two states. While this diagram summarizes useful extensions to the traditional hierarchy it still does not embrace all the improvements possible by using ideas from complex systems. In particular, the diagram still shows a linear hierarchy and it does not show any feedback systems. For example, is it possible to create new knowledge by linking new data with previous wisdom? Can new information be created by linking previous knowledge and new knowledge?

• Journeys of the Heart.
• Dolphin Facts for Kids: Book About Common Dolphin Facts for Kids.
• Key Issues in the New Knowledge Management : Mark W. McElroy : .

How can the need of knowledge to create or use data be depicted? All the models presented previously do not help to show the relationships that exist among data, information, knowledge, and wisdom. Linear thinking is holding back the creation of good metaphors to describe the concept of knowledge completely. Firestone and McElroy made an attempt at generating a non-linear model. However, they failed to see that their model was creating another kind of linear hierarchy. What is needed is a model without a linear hierarchy between data, information, knowledge, and wisdom, because - as shown later — they are all made up from the same basic unit.

They are all labels used to structure human understanding of the same construct: The real distinction among them is learning experience and understanding. Redefining the basis of knowledge management Simple mathematical notation can be employed to explain how data, information, knowledge, wisdom, and enlightenment relate to existence. The following is a metaphor to demonstrate this point. Therefore, the system can be described in the following terms: One can also argue that data is made of symbols Ackoff, , but that does not change the result because symbols are still abstractions of existence.

Regardless of the type of concepts applied — such as meaning, judgment, or anything else — they are still all based on the same thing. What is important is the coefficient that differs among them. The distinction among these constructs is a level of abstraction and understanding. Therefore, a, b, c, d, and e all represent transformation through different level of understanding, the factor suggesting an exponential degree of thinking: Data, information, knowledge, wisdom, and enlightenment are transformations of existence. Therefore, the traditional hierarchy is obsolete, as it does not represent the totality of the possibilities.

These equations emphasize that point by showing how data, information, knowledge, and wisdom could be portrayed from a different perspective. However, this is still not sufficient.

Key Issues in the New Knowledge Management

Social interactions are the basis for the existence of data, information, knowledge, and wisdom. Indeed, according to many authors, data, information, and knowledge are linked through social interactions e. The fourth form, wisdom, should be added to this list, and the possibility of cognitive as well as social interaction as a linking mechanism should not be overlooked.

These four forms can interact in non-linear ways as well as along the traditional linear paths. Hence, existence, data, information, knowledge, wisdom, and enlightenment form a feedback system with positive and negative feedback loops. This is a non-linear appraisal consistent with complexity theory, which helps to reveal the nature of the links among data, information, knowledge, and wisdom and helps to understand why the classical hierarchy is not appropriate. The model shows the cognitive system of knowledge and how understanding permits conceptual linking of Existence to Enlightenment.

The E2E model accommodates the classical linear hierarchy of data, information, knowledge, and wisdom, and also incorporates the extension on both ends of the hierarchy from Existence to Enlightenment previously discussed in this paper. Figure 4 illustrates this.

Cognition is the facilitation process through which the system functions; it is the process by which knowledge and understanding are developed. One implication of complexity theory is that a cognitive system of knowledge will emphasize what a system does, not what it is composed of. Note also that existence and enlightenment are two states of being.

Therefore, cognition is involved at the transitional states between existence and enlightenment, but not at the two ends themselves. Indeed, data, information, knowledge, and wisdom are different cognitive constructions intermediate between these two states. Contrary to past understandings of systems of knowledge, the authors claim that there is no hierarchy among data, information, knowledge, and wisdom.

One does not need to obtain them in a specific order. Depending on the situation, one may not even need to have all of them. Hence, one can obtain information directly from an understanding of existence, without having to acquire any data enroute. In the same manner, one can create knowledge from data without having to create information as an intermediary. This is consistent with the premise of complexity theory that systems incorporate non-linear feedback; such transitions across state boundaries similarly take place in the cognitive system. This cognitive system of knowledge is a social construct, the result of the interaction between a cognitive base data, information, knowledge, and wisdom already possessed and its environment through its existence.

The cognitive base provides the history of the cognitive system, which is an important feature of complex adaptive systems Bak, This implies path dependencies and the irreversibility of time, as argued by Prigogine All individuals have cognitive systems embedded in their mental processes. At a higher level, organizations also possess a cognitive system.

Account Options

Indeed, individual cognitive systems are constituent sub-systems of the organizational cognitive system. Again consistent with complexity theory, the cognitive system of knowledge is considered to be scale free as it exhibits self-similarity at different levels of complexity, i. Indeed, the cognitive base will help to create new data, information, knowledge, and wisdom, but it is the feedback engendered by these new data, information, knowledge, and wisdom that will enable cognitive creativity.

Newly developed or acquired knowledge can be used on an existing database to create new data, but can also lead to new information, knowledge, or even wisdom. Understanding is the power that generates new links among data, information, knowledge, and wisdom. New data can resonate with the knowledge base and lead to the creation of new wisdom. New knowledge can interact with old information and create a new understanding, which could mean the creation of new data, information, knowledge, or wisdom.

New data, information, knowledge, and wisdom can therefore emerge from the combination of newly developed or acquired data, information, knowledge, and wisdom and their respective established bases. The exact output depends upon the type of understanding that is generated within the system. Thus, the model shows how different levels of understanding are required to handle the different constructs of data, information, knowledge, and wisdom. The higher the level of understanding that is required, the greater the chance that data, information, knowledge, and wisdom become tacit.

But if there is no hierarchy; and if data, information, knowledge, and wisdom are different levels of abstraction of existence, their definitions should be re-examined to verify whether they are still appropriate. B Data is a basic interpretation of existence. It is a purely descriptive construct that requires a low categorical level of understanding of existence. B Information is viewed as a meaningful interpretation of existence, one that has a purpose. It is a connective understanding of existence.

It requires a higher level of understanding than data, but a lower one than knowledge or wisdom. B Knowledge is here defined as a meaningful and procedural abstraction of existence. It has a purpose and is a procedural understanding of existence. Without knowledge, lower levels of abstraction of existence are not actionable.

Knowledge requires a higher level of understanding than data and information, but a lower level than wisdom. B Wisdom is understood as a meaningful, procedural, and justified abstraction of existence based on experience. It has a purpose, relates to procedures, but it is also based on a coherent judgement of existence justified through experience. Wisdom therefore permits sound action and use of experience. Wisdom requires a higher level of understanding than data, information, and knowledge.

It is important to notice that these definitions do not imply a linear hierarchy. This means that, for example, information is not just data that has been processed in a useful manner. Furthermore, none of the definitions are linked to facts. Indeed, it would add more confusion than precision to the definitions. Of course, data, information, knowledge, and wisdom are thought to be true by the people using them. But one needs to keep in mind that they are fallible. They are held to be true until proven wrong or superseded by something more coherent.

Why is wisdom not connected directly to existence in the model? Wisdom presupposes experience, and experience implies the presence of a cognitive base. Furthermore, as has been discussed earlier, enlightenment is the highest form of understanding. It is not something to have; it is a state of being, such as existence. Therefore, it is separated from the rest in the model.

The idea of meta-knowledge is shown in many models Wiig, ; McElroy, , but this is not extended to meta-data or meta-information. The metas and the reconstitution of knowledge management Meta- has been used in the literature as something referring to itself, e.

According to the Oxford English Dictionary, meta- means connected with a change of position or state, higher, beyond. Knowledge about knowledge is not meta-knowledge; it is just another kind of knowledge. It can be useful knowledge, but it has nothing meta- in itself. Meta-data, -information, -knowledge, and -wisdom, are data, information, knowledge, and wisdom associated with a change of state; they are at a higher state of development, situated beyond respectively normal data, information, knowledge, and wisdom. So what are they exactly? The authors suggest that they are the essential subject that knowledge management should administer.

Kundrecensioner

They are the understanding of the conversion processes. Meta-data is the understanding of how data is transformed into another form, such as information, knowledge, wisdom, or a more complex set of data. Meta-knowledge is the understanding of how knowledge is converted into data, information, wisdom, or a more complex form of knowledge.

However, it is not appropriate to describe the metas as just one form of knowledge as they are holistic constructs of understanding composed of data, information, knowledge, and wisdom about the conversion processes. Product details Format Paperback pages Dimensions x x 18mm Looking for beautiful books? Visit our Beautiful Books page and find lovely books for kids, photography lovers and more.

Key Issues in the New Knowledge Management

What are its issues? Sense-making, complex adaptive systems, and the third age The Cynefin model and its problems Cynefin conclusions Conclusion: What is culture and how does it fit with other factors influencing behavior? Do global properties exist? Culture and knowledge Conclusion: Review Text "This book is essential for academics, managers, and consultants who want to increase innovation, effectiveness and strategic focus in their organizations. The authors adroitly link the often-abstract issues of information processing and knowledge creation with the tangible and crucial management issues of organizational learning, motivation and culture that executives often neglect when formulating a knowledge management strategy.

By relating these concepts in a straightforward, relevant and empowering way, Firestone and McElroy achieve [in this book] what Peter Senge has done for the field of organizational learning. Their carefully conceived structure and highly accessible framework has the capacity not only to inform, but to transform organizations and those who work in them. I highly recommend this book and the others in KMCI's series. Their views, drawn from learned analyses and extensive practice, challenge several widely held conceptions.

Serious KM professionals and students will find these issues both stimulating and refreshing. They are bound to be engaged by the pertinence of the authors' questions and they will either be convinced by their innovative answers or be inspired to find their own. Key Issues in The New Knowledge Management is a critical reading for anyone who envisions a place for themselves on the KM map in the years ahead.