Knowledge Management in Theory and Practice

Link the KM frameworks to key KM concepts and the major phases of the KM cycle

Being able to acquire information fast, process it in q high-quality manner, and distributing it efficiently means improving both the organizational and production process within a specified organization. Therefore, knowing the basic KM framework is crucial to understanding how to handle the retrieved information efficiently. Hence, it is crucial to understand how the existing knowledge management frameworks are related to the key KM concepts and the stages of the knowledge management cycle.

• The von Krogh and Roos Model of Organizational Epistemology (transgression from individual tacit to individual explicit knowledge);
• The Nonaka And Takeuchi Knowledge Spiral Model (field building, dialogue, linking explicit knowledge, learning by doing);
• The Choo Sense-making KM Model (from knowledge creation to sense-making to decision making);
• The Wiig Model for Building and Using Knowledge (commute, maintain, vacation, and driving views of the semantic network);
• The Boisot I-Space KM Model (establishing easy data structure for easy distribution);
• Complex Adaptive System Models of KM (used when organizational behavior must be addressed and regulated).

Speaking of the links between the existing KM frameworks and the KM cycle, however, it is worth keeping in mind that the phases of the KM cycle can be defined from different perspectives and, therefore, might be split into different stages. Picking the most general descriptions of the KM cycle phases, one will be able to see the following correlation between the KM phases and the KM frameworks:

• Discovery;
• Acquisition;
• Creation;
• Storage and organization;
• Sharing;
• Application.

It is important to stress that each of the above-mentioned frameworks presupposes making the aforementioned steps.

What is the major advantage of a complex adaptive system approach to a KM model? What are some of the drawbacks?

Though traditional bureaucratic solutions might be rather useful, they mostly presuppose following rather general directions, while the complex adaptive system approach helps view an organization as a system “in a symbiotic relationship with its environment” (Dalkir, 2005, p. 69). Therefore, the basic advantage of the CASA is that it allows us to specify the goals of every member of the organization and, therefore, come up with a detailed plan on how to reach these goals. A major drawback, however, is that CASA presupposes is that each of the organization components is self-organized (Dalkir, 2005, p. 331); therefore, the supervision provided is rather loose, which increases the possibility of making a mistake.

Provide an everyday example of requisite variety. Next, apply this to the management of knowledge in an organization. What are the key elements needed in order to successfully regulate a complex adaptive system? Why?

A “notion that regulation can be measured” (Dalkir, 2005, p. 340), requisite variety presupposes that the measurement tool must also have at least two parameters. For instance, if a voltmeter can measure tension, the voltmeter must have at least two settings of its won, i.e., the on/off button. Applied to organizational management, the given concept presupposes that a complex adaptive system that every organization is must be regulated according to specific parameters by a tool that should have parameters of its own, e.g., several methods of measurement, etc. Since a complex adaptive system involves self-organizing elements, it must be regulated by the tool that incorporates:

• Environmental analysis;
• Organizational intelligence reinforcement;
• Reinforcement of people’s strengths;
• Transformation of inputs into higher-value outputs.

In other words, the tool applied to solve the problem must help undergo the basic KM stages, which are understanding, creating new ideas, solving problems, making decisions, and taking actions. (Dalkir, 2005, p. 70).

What are the three generations of knowledge management to date? What was the primary focus of each?

As Dalkir stresses, the first generation of knowledge management primarily concerns the containers of knowledge; as Dalkir explains, the first generation of knowledge management is practically the solution to the famous if-only-we-knew-what-we-knew dilemma (Dalkir, 2005, p. 19). Helping organize the available knowledge, the first generation of KM, therefore, helps detect and define the knowledge, which is crucial for the first stage of knowledge management. Therefore, the primary focus of the given approach is information.

As for the second generation of knowledge management, there are reasons to believe that the development of the key concept behind it was the response to the people-oriented leadership strategies. Dalkir (2005) defines the second-generation of knowledge management as the approach that “swung to the opposite end of the spectrum to focus on people” (p. 19). However, the given extreme does not seem reasonable enough since it would be more appropriate to provide a balanced approach, which would help take into account both people and data.

According to Dalkir, who, in his turn, quotes Snowden, the third generation knowledge can be regarded as the type of knowledge, which is “devoted to context, narrative, and content management” (Dalkir, 2005, p. 19). The last of the three specified types, but definitely not the least, it allows for defining the existing types of knowledge and, therefore, improving its management process by arranging the available knowledge according to specific nomenclature. Hence, the third generation is concerned neither with people nor with information, but with the means to distribute information among people.

Compare and contrast major KM life-cycle models, including the Zack, Bukowitz and Williams, McElroy, and Wiig life-cycle models

The Bukowitz and Williams KM Cycle

Created to show how a “strategically correct stock of knowledge” (Dalkir, 2005, p. 32) is created, maintained, and deployed within an organization, the Bukowitz and Williams KM Cycle represent the type of knowledge management, which is focused entirely on processing knowledge. According to Dalkir, the specified framework includes the following concepts:

• knowledge repositories (allows to store knowledge without fearing its leakage);
• relationships (working on the successful delivery of information from one employee to another);
• information technologies (deploying technologies to promote more efficient knowledge sharing);
• communications infrastructure (improves the quality of the knowledge sharing process);
• functional skill sets (improving communication skills);
• process know-how (advancing the KM process);
• environmental responsiveness (developing a reciprocity system among the employees);
• organizational intelligence (training the employees’ communication skills);
• external sources (using outside sources to distribute information evenly).

The McElroy KM Cycle

McElroy, in his turn, suggests that the knowledge management cycle is supposed to consist only of unceasing knowledge production (Dalkir, 2005, p. 35). Therefore, it can be concluded that The McElroy KM Cycle presupposes a transformation from tacit organizational knowledge to individual tacit knowledge. The McElroy KM Cycle includes the following elements:

• problem claim;
• knowledge claim.

The Wiig KM Cycle

Unlike the previous knowledge management cycles, the Wiig approach focuses on the production, processing, and use of quality knowledge. Therefore, it can be considered that Wiig KM system is one step ahead of the previous two. The Wiig knowledge management involves the following elements:

• compiled knowledge (routine/standard tasks);
• building knowledge (obtaining and organizing);
• holding knowledge (remembering and archiving) ;
• pooling knowledge (coordinating and retrieving);
• applying knowledge (performing tasks).

All three of the above-mentioned KM cycles have three similar stages, which are:

• Remembering knowledge;
• Accumulating knowledge;
• Embedding knowledge;
• Archiving knowledge (Dalkir, 2005).

Compare and contrast the cognitivist and connectionist approaches to knowledge management. Why is the connectionist approach more suited to the von Krogh KM model? What are the strengths of this approach? What are its weaknesses? Use examples to make your points

Organizational knowledge is viewed in the cognitivist theory as a self-organizing system; moreover, according to Dalkir, in a cognitivist setting, the members of an organization are completely transparent to the facts that come from the outside world. The above-mentioned means that the cognitivist adepts envision the brain as a “machine based on logic and deduction” (Dalkir, 2005, p. 50).

Unlike the cognitivist approach, the connectionist theory of knowledge management does not presuppose that a human brain is an ideal machine; though the theory admits that bran can deduce and make logical conclusions, it is still clear that the connectionist approach incorporates the principle of “errare humanum est.” In other words, the connectionist model makes it clear that a human brain can make mistakes in calculations, which means that it is far from being perfect. Rather holistic than reductionist (Dalkir, 2005, p. 50), the given approach fits the key principles of the von Krogh KM Model since the former presupposes that “there can be no knowledge without a knower” (Dalkir, 2005, p. 51), which suits the von Krogh Model.

The obvious strengths of this approach come from its assumption that people can make mistakes in their calculations and deductions. Therefore, the connectionist model allows us to check for the results of the calculations more efficiently. The key weakness of the given approach, however, is that it denies the existence of knowledge without a person who can learn it, i.e., doubts the objective reality, clearly implying that reality cannot exist without specific agents.

For example, according to the theory, as long as there are people to experience what gravity is, the law of gravity exists as knowledge, yet when people vanish from the face of the Earth, the law of gravity as a concept will supposedly cease to exist. The given idea relates knowledge to communication, which seems wrong once knowledge is viewed as a bunch of facts.

In what ways is the Choo and Weick KM model similar to the Nonaka and Takeuchi KM model? In what ways do the two models differ?

Discussing the existing major theoretical knowledge management models, one must keep in mind that, no matter how diverse these models might be and on what different principles they might base, they will have at least one thing in common, that thing is their goal, i.e,., representing the means of creating, processing, retaining and using knowledge. Apart from the common goal, the Choo and Weick knowledge management models have a number of other common elements. According to Dalkir, the following can be considered the points at which the four above-mentioned models cross:

The similarities concerning knowledge creation, which have been spotted between the two models, however, owe much to the fact that the Choo and Weick Sense-making Model was largely based on the Nonaka and Takeuchi Knowledge Spiral Model and, thus, shares a number of features with the Nonaka and Takeuchi model. In fact, the Choo and Weick concept can be considered an upgraded and improved Nonaka and Takeuchi’s model.

Therefore, it basically shares its positive and negative aspects. However, shaping the Nonaka and Takeuchi model to suit their understanding of knowledge management process, Choo and Weick have added several features that both upgraded the model and at the same time made it more complicated. Though these features cannot be considered redundant, they clearly need further development.

How does the integration of a bounded rationality approach to decision making strengthen this model? Give some examples

Since Choo’s model is known for being based largely on the bounded rationality approach, as Dalkir explains, it will be reasonable to consider the later in detail to understand how exactly bounded rationality factors into Choo’s model. To start with, it is necessary to provide a definition for bounded rationality. According to Dalkir, bounded rationality can be defined as an approach that presupposes the use of the limited informational analysis, as well as the application of evaluation, processing and shortcuts together with the famous “rule of thumb” (Dalkir, 2005, p. 61).

While other approaches make it clear that a human mind is not suitable for solving logical puzzles at all, or, on the contrary, take the concept of a human mind as a problem-solving mechanism to another extreme, the bounded rationality approach offers a golden mean between the two, stating that a human brain might err, yet in most cases, people can be described as rational beings, which means that they are basically capable of solving puzzles and dilemmas.

Therefore, the introduction of bounded rationality into Choo’s model, which can be defined as a process of knowledge making that is triggered by an outside stimulus (Dalkir, 2005, p. 58), helps stress the duality of Choo’s model. Due to the uncertainty that bounded rationality creates, the role of an individual in decision-making process and the ultimate analysis of the ideas is emphasized.

List some of the key triggers that are required in order for the sensemaking KM model approach to be successful

It would be wrong, however to assume that the sense-making knowledge management model can be launched with the help of any triggering mechanism; only several factors can be considered an efficient triggering mechanism for the model to be launched. Among such factors, the following ones should be mentioned as the factors with the longest lasting effect and the most impressive results:

• “Ambiguous behaviors,” i.e., the behaviors contradicting the initial theory;
• “Extreme cases of aggregate uncertainty in decision environments” (Dalkir, 2005, p. 60);
• Behavioral responses that do not correlate with the theoretical postulates;
• Events within an organization, related either to the production process or to the behavioral standards in the company.

It can be considered that the above-mentioned elements make the bulk of the premises for the Choo model to be implemented. However, it is worth keeping in mind that other reasons for the Choo model to be launched may also exist.

What are the major taxonomic approaches to codifying knowledge that has been captured? What sorts of criteria would help you decide which one(s) to use in a given organization? How would you maintain such a taxonomy?

Considered to be the means to transform tacit knowledge to explicit and vice versa, knowledge codification can be approached in numerous ways. Four basic taxonomic approaches provide knowledge codification. Each of the approaches has a set of unique functions and features:

Taking a closer look at the specifics of each element in the taxonomy table above, one can easily choose the most appropriate model for the knowledge management process. To maintain the chosen taxonomy, it will be required to make sure that the organization works properly and that its corporate culture is based on the principles of clarity, communication and knowledge sharing.

List some of the ways in which social network analysis techniques can be used to better understand how knowledge is circulated within an organization

There can be no doubt that social network has become a driving force in interpersonal communication. As a result, social network is widely used for knowledge creation, acquisition, sharing and suing. Hence, it is crucial to learn how social network techniques can be used for the benefit of an organization in terms of knowledge sharing. Social network analysis can be carried out by using the following methods of quantitative research:

• Surveys;
• Questionnaires;
• Interviews.

or any other method of gathering information among a large group of people and providing exact statistical data. It is worth keeping in mind, however, that the given method of research is rather time-consuming, which means that using the information acquired from a survey within a social network is rather risky. After the information has been gathered, there is a strong possibility that the given information has become dated in the process of its collection and analysis. Hence, it is important to employ the latest technological advances to make the process of analysis as fast as possible.

When would you make use of which Bloom taxonomy? Provide examples of some knowledge applications where each of the three taxonomies could provide useful information

Though in the realm of knowledge management, Bloom’s taxonomy is known primarily as the stages of knowledge management process, in fact, the taxonomy is split into three key domains, which are cognitive, affective and psychomotor ones. It seems that cognitive Bloom taxonomy will be the most useful in the situation when brainstorming is required. As for affective Bloom taxonomy, the latter can be applied in order to shape a company’s corporate culture by shaping the existing organizational behavior and introducing new moral values to the company staff.

Despite the complexity of the task, it seems that affective taxonomy still should be applied when some of the members in an organization display corruptness and seem to abuse their power. Finally, the psychomotor taxonomy allows for a better performance of the staff and for the improvement of their skills.

Since it is crucial for an employee to develop professionally, it is important to take tests according to the principles of Bloom’s psychomotor taxonomy to make sure that the employees have perfected their skills or at least maintain the same high level of performance. In addition, the give kind of taxonomy helps reveal possible problems concerning the employees’ qualification, which means that these problems can be solved at their earliest stages.

What are the key components that should be addressed by an organizational KM architecture? Why are these components critical for organizational knowledge application?

Dalkir (2005) states that there are three key levels, which the organizational KM architecture incorporates:

Data layer

The given concept incorporates the entire range of various types of data, which the organization in question has at its disposal.

Process layer

On the process layer level, the links between different types of the aforementioned data are provided.

User interface

The given element helps access the data in the most efficient and fastest way possible, at the same time guaranteeing that unauthorized users or any other third parties will not be able to get hold of the company data. Since the given components provide the conditions for data acquisition, storage and security, they are crucial for organizational knowledge application.

Reference List

Dalkir, K. (2005). Knowledge management in theory and practice. Burlington, MA: Elsevier Butterworth–Heinemann.