Km transformational Model

Download 79.96 Kb.
Size79.96 Kb.

An Aristotelian Model of Knowledge Transformation to Support Knowledge Management (KM) in Commercial Organizations

Joel A. Kline

English 5364

Dr. Rice

August 5, 2006
An Aristotelian Model of Knowledge Transformation to Support Knowledge Management (KM) in Commercial Organizations
Knowledge Management (KM) is an enterprise initiative designed to capture, distribute, and share information within a commercial organization. Some practitioners and researchers have questioned whether an organization should first build a knowledge model and address the question “what is knowledge” before attempting to manage knowledge (Prusak). Others fear a redefinition of knowledge will occur at the hands of technology (Mittelstrass).

Aristotelian epistemology provides the suitable model for knowledge transformation within a company. His work in Metaphysics and Rhetoric develops empiricism, dialectic, and rhetoric as methods of knowledge creation. His philosophy towards audience leads to an acknowledgement of the role the audience plays in knowledge creation. Aristotelian epistemology accommodates change, which Platonic and earlier philosophies did not. Finally, his conceptual treatment of certainty is a perfect fit for the commercial environment where certainty ranges from definitive to probable (or less).

The essay extends Aristotle’s concepts to develop a set of requirements for building a transformation model and then synthesizes a transformational model.

The model examines three areas of influence on knowledge transformation: dimension, process, and criteria. Building upon work done by exploring the computational and consciousness levels of knowledge (Murray), the model creates a process that is controlled by criteria through several dimensions. The process begins in the form of data and ends with Wisdom.

Information does not create knowledge…a “knower”…create(s) knowledge.

Jürgen Mittelstrass


Since 1994 many commercial organizations have embraced an enterprise level initiative known as Knowledge Management (KM). Before organizations rush to build systems to “manage” knowledge, shouldn’t they define and articulate “what is knowledge?” The simple answer is yes. But subsequent questions make the task much more complex. Questions such as “how does our organization employ a knowledge model” and “how do we structure and process knowledge?” Organizations typically focus on the difficult tasks of building a KM system and populating it with information. They rarely have the expertise (or time) to create a model that explains knowledge creation within the company. This essay forwards an Aristotelian model for knowledge transformation. It marries many of the classic Aristotelian concepts regarding knowledge with the need for applied knowledge in the enterprise.

Buried within the digital infrastructure of most enterprises is a large quantity of data. This data is not knowledge. When properly interpreted, distributed, or connected to other data, it certainly can become knowledge. The opening quote from Mittelstrass and one theme of my proposed model is to illustrate the important role people play in creating knowledge. Thus, one obvious goal of KM is to store information in such a way that users can create knowledge with it. So knowledge management doesn’t really manage knowledge, it manages the building blocks of knowledge (information). KM is a bit of a misnomer, in my opinion. It should be Information Management, because KM makes the necessary bits of information available to construct knowledge. If computers begin the transformation of data to knowledge and humans complete this transformation we should have a model that includes both. Such is the goal of the essay. To explain how data becomes knowledge I use Aristotelian epistemology as the framework. In order to justify Aristotelian epistemology the essay includes a justification section. It subsequently outlines some model requirements and proposes a model. Before examining the model, however, let’s begin with a brief explanation of KM and a short literature review.
Knowledge Management

KM is a relatively new application with roots in IT and Enterprise computing. Most researchers believe the field is legitimate, although some dismiss KM as the creation of consultants in search of the next technology to build for clients (Prusak). KM might have roots in IT but it’s pervasiveness in business since the turn of the century has made its study relevant and important.

Knowledge Management has multiple definitions. KM always involves application within an organization. Consequently, many commercial enterprises and industries define the term differently. Fortunately, there is significant overlap in the accepted definitions of KM. In addition to an organizational application, there are process activities within KM definitions that overlap. These are processes such as: capturing knowledge; structuring knowledge; validating knowledge; sharing knowledge; and re-using knowledge (Shandbolt). Some definitions are so information-centric they don’t mention the involvement of humans. Presumably, the “organization” part of the definition is satisfactory to note the involvement of humans. Human involvement is central to KM, central to knowledge creation, and central to this essay. UK’s Loughborough University has a suitable definition that includes many of the overlapping concepts:

“Knowledge management is the name of a concept in which a company or organization consciously and comprehensively gathers, organizes, shares, and analyzes its knowledge in terms of resources, documents, and people skills” (Loughborough, 2006).

Another definition has value because of its explicit acknowledgement of people in the KM process. The American Health Information Management Association, defines KM as

“Capturing, organizing, and storing knowledge and experiences of individual workers and groups within an organization and making this information available to others in the organization” (AHIMA, 2004).

These definitions and the explanation of the overlapping concepts should clarify KM. As stated in the Introduction, the problem with KM is that the system does not manage knowledge. It manages information. It is through the processes of sharing and distributing information to users (humans) inside the organization that information transforms into knowledge..

Much of the mainstream research in KM is done by Computer Science, Information Technology, and AI disciplines. None of these disciplines is solely equipped to study the complete field and none of these information-centric fields is equipped to study the knowledge from the user (knower) and epistemological perspective. This presents an opportunity for a theory that can be reconciled with epistemology and answers philosophical questions about knowledge. To continue, I will justify why Aristotelian epistemology can form the foundation for such a model.

Justification for a Classical Model

Two reasons support our proposal for some type of model. First, the field of KM has evolved without defining a theoretical view of knowledge or knowledge transformation. Pemberton puts it this way,

“Part of the reason that there is so much commotion about "knowledge" today is that as yet we lack the tools to build a satisfying understanding of this abstract concept beyond the buzz-word level”(58).

It’s essential to have a clear understanding of knowledge as companies store and accumulate data. A clear understanding of knowledge can help individuals and companies structure data and information within an organization. More importantly, our concept of knowledge is going to change over time. Researchers are pushing technologies like the World Wide Web into becoming a knowledge transforming platform with features like Web 2.0 and the Semantic Web. Before companies flood the universe with information or share what they believe constitutes knowledge among society, companies should have a clear definition of knowledge.

The second reason for a developing a transformational model for KM is to prevent technology from re-defining knowledge as a concept without a human component. As information overloads our society and becomes digital it seems plausible that we might lose our relationship as humans to knowledge. Murray claims that the field of KM is information-centric and not concerned with people as knowledge creators. He notes that the transformation from information to knowledge requires people or is “non-computational”. This means that the true essence of KM doesn’t lie in Information Technology, but in people (234). Mittelstrass believes we’re in danger of commoditizing knowledge. His fear is that the commercial and transient perspective of knowledge removes the human element. This drastically affects education and wrecks the connection between information and knowledge. These consequences ultimately will lead to knowledge being removed as the central expression of rationality for mankind (230).

If organizational knowledge is reconciled with philosophical knowledge it might change the way companies treat information. Certainly, if we acknowledge the human element in the creation of knowledge we will guarantee that knowledge remains the rationalization of human expression and information is what is contained inside our computers, televisions, and electronic devices. Specifically, there are some compelling reasons to choose an Aristotelian epistemological model to build a model and preserve knowledge as human. Here are five:

  1. Aristotle was a pioneer in the struggle between absolute versus situational knowledge. He believed that absolute truth could exist when discovered by empiricism. Yet Aristotle also acknowledged situations where knowledge was probable and Rhetoric was a means of discovery or persuasion for this knowledge. Aristotle is a bridge between Plato’s absolute yet transcendental truth and the Sophistic belief that all knowledge is situational. This is a perfect and balanced conceptual model for the commercial organization.

  2. Aristotle’s philosophy is unbound to religious, political, and economic conceptions of knowledge. Aristotle advocates the use of Rhetoric and ethics towards a life of civic service but his philosophy is not built on a deity. Organizational knowledge can’t have a model that’s built on a political economy (i.e. Marxism) or around theology. Practical requirements dictate a model that defines knowledge in terms of the organization and its people.

  3. Things can be known to a certainty and evidence provides insight into the known in Aristotle’s epistemology. Aristotle’s epistemology asks many of the same questions as Plato but provides the structure to find answers. Numerous authors in the practical applications of AI and KM have recognized how Aristotle’s ideas of sense perception fit with commercial organizations. Nonaka and Takeuchi discuss the importance of sense-perception to Aristotle’s concept of knowledge and note how it differs from Plato. “Thus he stressed the importance of observation and the clear verification of individual sensory perception” (23). This clearly provides a better fit for KM in a commercial organization than the things before it (Plato’s Forms) and much of the epistemology after it (like Foucault’s Archaeology of Knowledge).

  4. Aristotelian philosophy contains two important elements for an integrated KM transformation model: change and audience. Aristotle’s acknowledgment of audience is the first step in recognizing that people are knowledge creators. Aristotle also creates the enthymeme, which presumes an audience has some knowledge. In an organization, there is a presumption that people have pre-existing knowledge about their job, industry, or company. In Metaphysics, Aristotle creates taxonomy for knowledge that connects things to their essence. This effectively allows the knowledge structure to deal with change. If we create something new, it’s connected to what makes it unique. This means that knowledge in a commercial organization can be managed based on whatever change occurs, not a static taxonomy that requires a hierarchy for everything new. Jones argues that Aristotle’s epistemology using form and matter made it possible to explain change. Although A changes to B, it still retains some part of A (223). Aristotle made a distinction between change and development. Thus, his epistemology can accommodate what a commercial organization or industry perceives as “changes” to knowledge.

  5. Aristotelian epistemology can begin to accommodate tacit knowledge. Tacit knowledge is complex, but it can be oversimplified to mean the knowledge that we know but cannot articulate. Through Rhetoric, this knowledge has the chance to become clear. Aristotle acknowledged Rhetoric and its ability to discover and persuade for knowledge that is less certain. Rhetoric can provide a means for tacit knowledge to be transferred between people in an organization. It certainly doesn’t mean that Rhetoric can solve the problems posed by researchers of tacit knowledge. Rhetoric provides, however, a starting point.

Literature Review

This essay could easily fill all of its pages as a comparative review of models of knowledge. The essay cannot begin to examine all the epistemological models in Western philosophy or even a complete account of Aristotle’s epistemology. My approach towards the literature is two-fold. First, we need to examine Aristotle’s works to gain an understanding on how knowledge is created. Next, we must explore models of knowledge that were developed after the classical period. We cannot posit that the classical model is the best fit for KM if modern models of knowledge are a better fit or completely refute the classical model.

The most germane writing from Aristotle appears to Rhetoric and Metaphysics. In Metaphysics Aristotle describes wisdom to deal with the causes and principles of things. He distinguishes between things that are better known to us and things that are better known to themselves. He posits that we should begin our study of things better known to us and then arrive at an understanding of things better known to themselves, a concept he terms “first philosophy” (Cohen). The concept of first philosophy (alternatively known as wisdom, being qua being, etc) has implications for developing a model of knowledge where people create knowledge. While a commercial organization might not be concerned with transcendental knowledge of the universe, it would certainly be concerned to know the causes and principles of things. In Rhetoric, Aristotle addresses the creation of knowledge. Unlike Plato, he is much more understanding of the contextual nature of knowledge. For Plato, there was an absolute truth. For the Sophists, all knowledge was situational. Somewhere in between these two extremes lies Aristotelian philosophy; the idea that empiricism, philosophy, and rhetoric could be used to discover knowledge.

Modern theories of knowledge deal in two separate yet important dichotomies: belief versus knowledge and tacit versus explicit. A significant amount of literature is centered on the relationship between belief and knowledge. For example, if we believe something to be true, does that make it knowledge? In Gettier’s seminal work he writes what has come to be known as the Gettier Problem. He provides an example of someone who has the accurate knowledge of an outcome, but was led to that outcome via false belief. How can we explain how false belief becomes knowledge (Gettier)? Original Western philosophy on the relationship between belief and knowledge were framed by Aristotle in terms of certainty (causes and principles, above). Pitt notes that Hume destroyed the Aristotelian model with A Treatise of Human Nature in 1740. Hume was quite the skeptic and questioned whether a cause (to use an Aristotelian concept) could really be determined. Hume’s refutation of Aristotle’s concept of knowledge works for transcendental knowledge and questions about the existence of God (13). Organizations simply aren’t trying to determine these causes or their principles. So the application of Hume to KM is a bit esoteric. While some sense of skepticism is healthy for an organization, there needs to be a model which structures the causes and the principles. Aristotle does this and it applies very well to our KM model of knowledge transformation.

Research on the differences between tacit and explicit knowledge is definitely germane to the proposed model. Polanyi produced one of the seminal works in this area of epistemology, The Tacit Dimension, in 1983. Casselman and Samson note that “Tacit knowledge is the basic fact that we know more than we are able to tell” (3). They also state how many researchers in KM and knowledge oversimplify Polanyi’s The Tacit Dimension by equating Polanyi’s explanation of tacit knowledge as knowledge that is not yet codified. In reality, Polanyi believes there are levels of tacit knowledge and the organizing laws of a higher level cannot be discerned from the laws of a lower level. By indwelling (immersing) in the particulars of a level we emerge to a higher one (2).

Conceptually, I have described Aristotle’s epistemology as it relates to our soon-to-be-discussed model. I have examined refutation to Aristotle in the form of Hume and broached the very important issue of tacit knowledge via Polanyi. Next, we’ll frame this literature review in terms of creating requirements for the development of a model for the transformation of knowledge in an organization.

Requirements for a KM Model of Knowledge

This section argues the elements that a transformational knowledge model for KM should contain. It’s essential to strike the right balance between theory and application when marrying Aristotelian epistemology with KM. As noted in the justification section, Aristotle is one of the few classical philosophers with theories that accommodate change – a necessary component for KM in organizations. Seven requirements, including change, are described below.

  1. Usefulness.
    The first requirement is that the model is useful to an organization or enterprise. If the model fails to provide value, or accurately show how knowledge can be transformed, then it’s simply an exercise in academics. One aspect of usefulness is that the model provides a transfer mechanism. Consider the classical period. Plato was consumed by describing a method to discover absolute truth while Isocrates maintained that education (the transfer of knowledge) is what most benefited society. Although Platonic and Neo-Platonic thought still pervade Western philosophy, it is the principles of Isocrates that are applied (and useful) at the point where educators transfer knowledge to students. To be useful, the model must show a mechanism for transferring knowledge. In addition to transfer, a useful model should provide structure. Poor or lacking structure means that a KM system fails to organize the information that people in the company need to search, distribute, or connect. AI Researcher Shandbolt argues, “To be useful, knowledge must be structured” (Epistemics, 2005).

  2. Involves the User (knower).
    Many knowledge models are completely independent of the user. In an organization (and often in philosophical models) it’s the person that uses information who creates knowledge. We cannot build a knowledge model solely around the user. This would require knowledge to be completely situational and contain no truth. However, what is useful knowledge to one person might not be useful knowledge to another. Some of this will depend on the user’s needs, experience, and knowledge he has already acquired.
    Murray creates a table where mechanisms must be used to transform data to information to knowledge (and ultimately to wisdom) (235). Murray’s argument is that the consciousness of the human (knower) is what transforms information into knowledge. This concept is congruent with the essay’s premise that the audience or the knower has to be involved for knowledge to be transformed from information.
    Many current theories exist on the role of the knower (user) in creating knowledge. For his part, Aristotle only introduced the subject. Even with enthymemes and ethos/pathos/logos he stopped short of acknowledging that people must be present for creation of knowledge. Newer theories show a dichotomy between knowledge and information. Consider this quote from Patrick Wilson,

“...what can be recorded is not knowledge, but only a representation of knowledge. ... Where there is knowledge, there must be a knower; pieces of paper know nothing. ... In telling what knows, information and knowledge are logically distinct; but if we learn by observing rather than reading and listening there is no message and so no information (the semantic content of a message); we acquire information..., but this is not the same as acquiring knowledge“ (2).

It’s interesting that Wilson wrote this quote in a book in 1977, years before most organizations began dealing with information in digital form.

  1. Frame Ethics.
    As we discuss binary bits and applied knowledge it’s easy to ignore ethics. Ultimately, people use the information in a model in an ethical or unethical manner. Our model should frame ethics in such a way that the user is the basis for ethical decisions. Even if knowledge is universal, the choices that the knowledge creator makes are what lead to ethical or unethical consequences.

  2. Reconcile with other models.
    The model should be reconcilable with other models of knowledge. It should be synthetic and comprised of existing and accepted thought. A lack of overlap with existing models might make the model hard to implement and apply. A second aspect of its reconcilability is that it balances theoretical with applied. The model needs theory to underpin, and a model for application. Imagine a corporate strategy session where participants struggle to build a model of knowledge for the company based on Plato’s forms. It would make a humorous comic strip! A company is ultimately searching for truth by searching for pieces of information that need combined with other pieces of information before it becomes knowledge (or truth). That’s the balance between theory and applied.
    The difficulty in reconciling the definitions with other models of knowledge is the problem with truth. Pitt notes that Aristotle’s (and the classicists in general) relationship between knowledge and truth is what led to attack by philosophers and ultimately David Hume’s Treatise of Human Nature (13). After Hume, we are still trying to come up with a model for knowledge that what we say we know has a certain probability. A true and tight integrative fit with expansive knowledge models is beyond the scope of the paper. But we must start. Otherwise, we’re undertaking and exercise that might be futile from the beginning.

  3. Outline a Process
    The model should have a clear transformation process. One important result in this area is to address tacit and explicit knowledge. The means for creation of knowledge is the foundation of the model. As a harbinger, this reason is why I believe an Aristotelian model serves KM. While organizations create some knowledge that is absolute, there is also much knowledge in the commercial environment that is uncertain. The model needs to handle the certain and the uncertain and Aristotle’s epistemology does this. The Aristotelian model also focuses on the means to achieving (creating) the knowledge, as Bizzell and Herzberg note, “For Aristotle, only scientific demonstration and the analysis of formal logic can arrive at absolute truth. Here he agrees with Plato—both would call this kind of truth the only true knowledge—but Plato emphasized its transcendent origins, whereas Aristotle emphasized the empirical means by which it was obtained” (170).

  4. Handle uncertainty and change.
    The model must handle change. One of the significant reasons that Aristotle’s model of knowledge is so appropriate is due to its ability to handle change.
    However, most definitions of knowledge include a probable knowledge or level of certainty (as Aristotle terms it). Business deals with much uncertainty. Unfortunately, our model must take information and synthesize it into what I term partial knowledge. Sometimes, that’s the best we can accomplish in the business environment. The model deals with changes and treats knowledge as changing. Certainly, in the technological some aspects or elements of knowledge are changing.

Let’s turn our attention to employing these requirements into a viable model.

Synthesis of an Aristotelian KM Model

A few assumptions about the model should be noted. The idea for the dimensions and dichotomy between human and computer comes from Miller, who researches primarily on the effect of consciousness between mind and body (Miller, 85). Academics who teach KM generally understand that the initiative is used by commercial enterprise and industry. People associated with KM in academia are often located in Computer Science, Business, Information Technology or other disciplines which have a direct relationship to industry. A need to transform knowledge inside and organization is an important assumption of this paper. Also, the way knowledge gets applied or used is in no way relevant to its initial capture or storage. The model doesn’t account for a company that does a poor job of populating its databases or fails in capturing the necessary volume of data to make KM effective.

The model (Fig. 1) contains three areas that influence the transformation (or creation) of knowledge. The first is dimensions. Dimensions indicated the “who” or “what” that is occurring at a particular level of the knowledge process. The next area is the knowledge creation process (Process). The process moves from an initial point of data to a completed point of wisdom. The last of the three areas of influence is Criteria. Criteria are what must be met for the process to move from one dimension to the next.

The model contains five dimensions: data as computational; information as human; knowledge; action; and wisdom. The first dimension is the computational dimension. This dimension includes data and information. A KM system stores data and information in the computational dimension. The second dimension is the human dimension. Knowledge is only created when humans become involved. Information sitting in a KM system is not truly knowledge (as I have argued earlier), until someone uses it to create knowledge.

Figure 1. Aristotelian Model for Knowledge Creation in Organizations

In the human dimension of the model, people use Aristotle’s three primary methods for discovery to create knowledge. I term these Mechanisms and label them I., II., and III. The discovery process imitates the model of Aristotle for discovery. Three levels of probability exist regarding the certainty of the knowledge. The first certainty of knowledge uses empiric means to prove knowledge. While Aristotle advocated “science”, he really didn’t have the scientific or mathematical background to develop a model. Later empiricists did have mathematic capabilities and this turned empiricism into the scientific method. Pitt notes that Galileo agreed in principle with Aristotle’s view of empiricism. Galileo simply had more knowledge at his disposal for empiric study (13). Combining the scientific method and Aristotle’s ideas of the empiric leads to knowledge. An example of this is scientific research. A pharmaceutical company is employing the empiric mechanism when it devises scientific tests to assess the efficacy of a drug for the FDA approval process,. The pharmaceutical company validates its knowledge that the drug does treat the medical problem effectively using this mechanism. The certainty that the knowledge created is truth is the highest with this mechanism. The next mechanism in the human dimension is logic/dialectic (Fig 1. II.). In this mechanism the user (knower) employs logic or dialectic to create knowledge from information. In my example of the pharmaceutical company, a manager might employ logic and even the use of Aristotle’s enthymeme in understanding the relationship between senior citizens and drug pricing. Consider this syllogism:

Premise I: People on fixed incomes who use pharmaceuticals need drug price stability.

Premise II: Many senior citizens take pharmaceuticals and are on fixed incomes.

Conclusion: senior citizens need drug price stability.

The company can utilize this mechanism to logically deduce knowledge from information. The last mechanism for transformation of knowledge is Rhetoric (Mechanism III.). Both the empiric mechanism and the logic/dialectic mechanism use methods for creating knowledge that yields high probability and certainty. Aristotle saw the need for another method when knowledge wasn’t as certain and he constructed a role for Rhetoric in this capacity. In the KM Model of Knowledge, this mechanism primarily creates knowledge through dialogue. Rhetoric is normally discussed in terms of persuasion and even Aristotle felt that Rhetoric could be used to articulate the probable and persuade. The application of Rhetoric to business in the KM model of knowledge is indicative of Rhetoric’s capacity to stimulate dialogue and conversation, not just persuade. Rhetoric is useful to Aristotle because it not only can persuade men of the truth, but it can be used in “making decisions about matters on which true knowledge is not available” (Bizzell and Herzberg, 170).

Figure 2. Examples of Knowledge Creation by Mechanisms






Knowledge that can be created through the scientific method.

Knowledge that can be created through the process of logical discovery.

Probable knowledge that can be created through Rhetorical discourse.


Results of a scientific test for FDA approval.


P1: People on fixed incomes who use pharmaceuticals need drug price stability

P2: Many Seniors take pharmaceuticals and are on fixed incomes

C: Seniors need drug price stability

Senator Jones has a daughter with a rare blood disease.

Senator Jones would be a good contact for our new drug which treats the rare blood disease.

The company will contact Senator Jones to ask for her assistance.

Knowledge Type



Explicit or Tacit

Inside an organization there is a substantial amount of knowledge that gets created in this manner. Let’s return to our example of a pharmaceutical company. Someone in the government relations department finds out that U.S. Senator Jones has a daughter with a rare blood disease. The employee raises this point at a meeting where researchers explain that the company is developing a drug for the rare disease. Together, the company uses dialogue to create the knowledge that Senator Jones is a prospective supporter of research, promotion, and legislation regarding the new drug. During this dialogue, some company officials might offer advice against appealing to a U.S. Senator in such a personal and private way. Others might say that the connection to the Senator’s daughter is perfectly acceptable. The dialogue and persuasion that occurs in this conversation ultimately leads to the creation of knowledge regarding the company’s possible actions. Refer to Figure 2 for an overview of the three mechanisms and an example for each.

In most philosophical models of knowledge the final result is either wisdom or the certainty that the created knowledge is valid. The penultimate step of simply “knowing” carries little value for business. There must be an action step, where the knowledge that is created is involved in a decision or action that completes the transformation from data to knowledge. So this leads us to the Action Dimension. In the enterprise, someone creates knowledge and uses it to act. What is learned from the action ultimately becomes wisdom. The user can now address that same situation with internal knowledge (wisdom) much more effectively after gaining wisdom the first time . While wisdom is certainly achievable in business, it normally resides in individuals. These individuals take wisdom and utilize it to process the knowledge that has been created from the results (causes) of action. Action facilitates wisdom, the end result of our KM Model of Knowledge process. Without decisions (actions), our KM system would be just an archive of data.

The last set of components in the model is criteria. Criteria are forms which help to move the process to the next dimension. For the computational dimension, the criterion is accessibility. If the information is not accessible, then the knower cannot access it to create knowledge. So accessibility is a criterion that must be completed before the information can move from the computational dimension to the human dimension. In the human dimension the mechanisms and the knower need the certainty criteria to transform knowledge. This is where the knower and Aristotle’s acknowledgement of the audience is so applicable. The third criterion at the knowledge dimension I term “values”. Information values that are systematically defined in Knowledge Management (and IT) are pragmatic features such as timeliness, completeness, and accuracy. Accuracy shouldn’t be confused with knowledge or truth. Accuracy is a value criterion that ensures that information is accurate. Accuracy does not necessarily connote truth, but that the information is accurate regarding its origin and substance. The next criterion helps transform knowledge into action. This criterion is ethics. Without ethics, action can certainly take place. But without ethics it cannot sustain the knowledge of the company or meet the requirements of the Aristotelian model. The final criterion is memory. Memory helps the individual retain the wisdom that was gained by acting upon knowledge. Without memory, the organization is doomed to repeat its mistakes or fail to repeat its successes over and over. Organizational memory and individual memory are two distinct concepts. This criterion refers to individual memory. The collective memory of people and events is what the KM system tries to capture back into the system as data and information to continue the process.


It would seem that much of Aristotle epistemology is valuable to the synthesis of a KM model. He noted in Metaphysics “that all men strive by nature towards knowledge”. Upon closer reflection, it’s clear that the business purpose for knowledge is not exactly the innate quest for knowledge that Aristotle originally conceived. But that shouldn’t prevent us from framing commercial KM in Aristotelian terms. Aristotle worked towards a balance in his writing and thought (such as the golden mean) and this philosophy can be integrated into business. Aristotle’s concepts of audience, change, causes and principle, methods of discovery, and Rhetoric are wholly sufficient to build a useful model for KM knowledge transformation. Whether the model holds up to the scrutiny of the business environment is the next research question.

Additional Study and Research

There are many stones unturned in this model. One could take the opinion that I have essentially redefined knowledge in the business environment by adding the action step. Consequently, further research might define the relationship of knowledge to action in a business environment. Also, a more exhaustive examination of other models of knowledge could be undertaken. More work needs done to explain the transfer of knowledge into an organization. If the KM system contains a significant amount of the organization’s information then how does information get into the KM system? Aristotle’s levels of Theory, Practical, and Productive outlined in Metaphysics might provide a system that describes how theory (often from the academe), phronesis (business knowledge), and productive (internal “how-to” knowledge) are transferred into an organization’s KM system. Finally, research needs done on tacit knowledge. Philosophers and management gurus alike have struggled with how to first articulate and then capture the tacit knowledge that people have in an organization. If the model poses more questions than it answers, it’s still an attempt to produce a KM knowledge transformation model that is useful for commercial organizations.

AHIMA e-HIMTM Work Group on Computer-Assisted Coding. (2004). Delving into Computer-assisted Coding. Journal of AHIMA, 75(10), App G.

Aristotle. (1991). On Rhetoric. Trans. George A. Kennedy. New York: Oxford University Press.

Bizzell, P. and Herzberg, B. (2001) The Rhetorical Tradition. New York: Bedford/St. Martins.

Casselman, R. Mitch and Danny Samson. (2004) Beyond Tacit and Explicit: Four Dimensions of Knowledge, IEEE 38th Annual Hawaii International Conference on System Sciences Conference Proceedings, January 2005.

Cohen, S. M. (2003). Aristotle's Metaphysics. The Stanford Encyclopedia of Philosophy [Online]. Edward N. Zalta (Ed.). Available: [2006, July 18].

Gettier, E.L. (1963). Is Justified True Belief Knowledge? Analysis, 23, 121-23.

Jones, W.T. (1970). A History of Western Philosophy. The Classical Mind. San Diego: Harcourt Brace Jovanovich, Publishers.

Kraut, R. (2005). Aristotle's Ethics. The Stanford Encyclopedia of Philosophy. [Online]. Edward N. Zalta (Ed.). Available:

Loughborough University. Learning Technology Glossary [Online]. Available: [2006, July 23]

Miller, D.W. (2000). Designing a bridge for consciousness: are criteria for a unification of approaches feasible? Advances in mind-body medicine, 16(2), 82-89.

Mittelstrass, J. (2003). Knowledge as a Good: Science, Education, and the Commodification of Knowledge. Trames, 7(4), 227-236.

Murray, A. J. (2000). Knowledge Management and Consciousness. Advances in mind-body medicine, 16(3), 233-238.

Nonaka, I. & Takeuchi, H. (1995). The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. New York: Oxford University Press

Pemberton, J. M. (1998). Knowledge Management (KM) and the Epistemic Tradition. Records Management Quarterly, 32(3), 58-62.

Pitt, J. C. (1996) Philosophical Methodology, Technologies, and the Transformation of Knowledge. Society for Philosophy and Technology, 3, 1-20. Available: [2006, July 20].

Prusak, L. (2001). Where did knowledge management come from? IBM Systems Journal, V 40.4 Available: [2006, July 9]

Rapp, C. (2002). Aristotle's Rhetoric. The Stanford Encyclopedia of Philosophy [Online]. Edward N. Zalta (Ed.). Available: [2006, July 5].

Shandbolt, N. (2005). Structuring Knowledge. Epistemics Corporate Website. Available: [2006, July 15].

Wilson, P. (1977). Public Knowledge, Private Ignorance. Westport, CT: Greenwood Press.

Download 79.96 Kb.

Share with your friends:

The database is protected by copyright © 2023
send message

    Main page