Abstract
K eyw or ds Learning organizations, Knowledge management, Workplace learning
Abstract
A bstr ac t T his article examines the alignment and t between knowledge management and organizational learning to determine the potential feasibility of integrating the two approaches. T he philosophicalroots of both disciplines are traced to common ground in a philosophyknown as "pragmatism". Early generation forms of knowledge management are critiqued and a new more pragmatic version is proposed -one that is compatible with organizationallearning. A new form of alignment between organizationallearning and knowledge management is proposed.
Introduction
Is it more than mere happenstance that organizational learning and knowledge management share the same purpose -namely, facilitating effective action? Are these two disciplines in some way re ecting different sides of the same coin? This article proposes that these approaches to increasing intellectual capital and human capacity for effective action are complementary and may be integrated into a larger framework. This framework or system is one that would be designed to scienti cally discover the antecedents of effective action. The theme of increasing our capacity for taking effective action is more important today than ever. Organizational failures are most often caused by ineffectiveness, not as a consequence of inef ciency. Effective action is said to have been realized when we have enjoyed success in achieving those outcomes that are most valuable to us. It is unsurprising that both organizational learning (OL) and knowledge management (KM) offer the potential to achieving higher levels of effectiveness. However, what is largely unknown is the effect that follows from integrating these two approaches together into a uni ed system. Historically, these two disciplines have been considered by their respective advocates to be two separate and distinct elds of praxis. However, there are potential synergies between OL and KM that have emerged and offer practical managers a potentially potent way to leverage human intellectual capital for performance.
The e merge nce of know le dge management
Interest in KM has grown dramatically in recent years as more people have become aware of its potential to drive innovation and improve performance. Reports of major cost reductions and performance increases as a result of KM initiatives at companies, such as BP Amoco, have helped KM to gain the Similarly, Blair (2002) sees KM as being "a discipline of identifying, capturing, retrieving, sharing, and evaluating an enterprise's information assets". Finally, O'Dell and Grayson (1998) of the American Productivity and Quality Center de ne knowledge management as "a conscious strategy of getting the right knowledge to the right people at the right time, and helping people share and put information into action in ways that strive to improve organizational performance". These kinds of traditional rst-generation supply side views of KM focus on employing technology and utilizing networks to increase the ow of information, best practices, and some forms of knowledge in organizations. The core business strategy behind such supply-side approaches is one of leveraging existing intellectual assets in organizations by increasing the dispersion of knowledge. Such strategies are severely limited in their potential to effect innovation in organizations and have been the subject of intense criticism in the KM community. Karl Wiig, (2003) one of the founding fathers of the eld of KM recently writes:
The e merge nce of know le dge management
The last decade's Informatics foray into KM have largely been ad-hoc and not been solidly founded on deeper understandings of such fundamentals as cognitive processes of people at work, business functions, or management philosophies and practices.
The e merge nce of know le dge management
Chief among the failures of such rst-generation approaches are the failure to develop a sound conceptual foundation, treating information and knowledge as being indistinguishable, and ignoring the key functions of knowledge creation, knowledge evaluation, and knowledge processing. Clearly, rst-generation KM does not share much in common with organizational learning.
The e merge nce of know le dge management
On the other hand, newer second and third generation KM approaches view organizational learning as being a critical component of knowledge processing activities. For example, Malhotra (2002) de nes KM as: a framework within which the organization views all its processes as knowledge processing, where all business processes involve creation, dissemination, renewal, and application of knowledge toward organizational sustenance and survival.
The e merge nce of know le dge management
Similarly, Firestone and McElroy (2003) de ne knowledge management as being "a management discipline that seeks to enhance knowledge processing". They view knowledge as being the result of learning activities associated with what they term a knowledge life cycle. This life cycle involves individuals in formulating, sharing, and evaluating various knowledge claims about how and why things work in practice. In knowledge management, the learning mechanisms that drive the knowledge life cycle are assumed to be present, but are not described in detail. Does organizational learning commit the same kinds of omissions by avoiding robust explanations of the role of knowledge in its discipline?
The e merge nce of know le dge management
The role for knowle dge in organizational le arning Organizational learning is often viewed as a social process of inquiry that is largely focused on improving interpretations of past experiences, but assumes Leveraging organizational learning that knowledge is an inevitable product of learning activities. When several popular de nitions of the term learning organization are examined, there is no mention of knowledge. Such de nitions emphasize the importance of increasing the organization's capacity for learning in ways that engender effective action, adaptation, and transformation, but do not refer to knowledge as playing a signi cant role. For example, McGill et al. (1992) do not draw distinctions between the notions of learning organization and organizational learning. They de ne organizational learning as "the ability of an organization to gain insight and understanding from experience through experimentation, observation, analysis, and a willingness to examine both successes and failures". For some, the notion of a learning organization is commonly understood as being an ideal that is meant to be approached, rather than to be realized. For example, Senge (1990) envisions a learning organization as being one that is "continually expanding its capacity to create its future". Pedlar et al.
The e merge nce of know le dge management
(1991) see a learning company as being "an organization that facilitates the learning of all its members and continually transforms itself". Finally, Skyrme (2003) de nes learning organizations as being those:
The e merge nce of know le dge management
organizations that have in place systems, mechanisms and processes, that are used to continually enhance their capabilities and those who work with it or for it, to achieve sustainable objectives -for themselves and the communities in which they participate.
The e merge nce of know le dge management
There is little evidence provided here that knowledge is of great importance to efforts directed toward becoming a learning organization.
Finding common ground
Despite this failure to include knowledge as an essential element in how the learning organization is de ned, many in the organizational learning community would assent that knowledge is the natural product of learning, it is simply not its focus. Argyris (1993) points to the connection between learning and knowledge when he notes:
Finding common ground
knowledge that is actionable, regardless of its content, contains causal claims That means that actionable knowledge is produced if the form of if-then propositions that can be stored in and retrieved from the actor's mind under conditions of everyday life He goes on to say:
Finding common ground
Learning occurs when we detect and correct error. Error is any mismatch between what we intend an action to produce and what actually happens when we implement that action . Learning occurs when we take effective action, detect and correct error (Argyris, 1993, p. 3). What he neglects to say is that the type of learning he references is focused on discovering the validity of our beliefs about how and why things work in practice. To Argyris (1993) , actionable knowledge would appear to take the form of a series of causal claims about how or why our actions were effective in yielding the expected result. Interestingly, Firestone and McElroy (2003) write in similar vein about the knowledge life cycle involving efforts to evaluate the truthfulness of knowledge claims, whereas Argyris (1993) speaks of the need to detect and correct errors in causal claims. It is important to note that while not identical, the similarity in these approaches is unmistakable. Is it possible that KM is simply a broader process that encompasses organizational learning or is organizational learning merely a descriptive method that outlines the processes that occur naturally in organizations to produce the knowledge that KM subsequently utilizes?
Finding common ground
Both Argyris' (1993) approach and Firestone and McElroy's (2003) methods share a common interest in creating processes for evaluating the ef cacy of claims. In KM, Firestone and McElroy (2003) identify 24 different types of knowledge claims, including causal claims. They propose that the validity of these claims should be tested by applying success criteria that consider performance factors, such as:
Finding common ground
. identifying improvements in cycle time without degradation in quality (ef ciency);
Finding common ground
. increase in production of surviving knowledge claims that are relevant to the problems motivating the knowledge life cycle (effectiveness);
Finding common ground
. increase in production of surviving knowledge claims that are successful in use (effectiveness); and . increase in production of surviving knowledge claims of suf cient scope to handle problems motivating the knowledge life cycles of the enterprise (effectiveness).
Finding common ground
By contrast, Argyris (1993) proposes several different methods for testing the validity of causal claims. These include:
Finding common ground
. showing causal maps or action maps that illustrate cause-effect linkages to organization members, then asking them to point of which features are incorrect and asking them to explain why they disagree; and . ask managers to make predictions based on their causal claims and then seek to discon rm them.
Finding common ground
The importance of testing the validity and reliability of causal claims is also important in systems thinking and pragmatic philosophy.
Finding common ground
In American pragmatic philosophy, most commonly associated with Charles S. Peirce, William James, and John Dewey, causal claims or knowledge claims are viewed as being importance mirrors of one's beliefs about how and why things work as they do in practice. In pragmatism, determining whether a speci c action works reliably well in practice to yield the expected result is seen as being an important step in determining the validity of not just the actions taken, but also of the beliefs that underlie them. According to Peirce's Pragmatic Maxim, the merits of one's beliefs are best judged by looking at the effectiveness of the effects they produce. According to this perspective, the importance of the feedback one receives about the effectiveness of prior actions Leveraging organizational learning taken is not so much to validate the knowledge used in obtaining these results as it is to clarify one's beliefs about how and why things work as they do in practice. Senge (1990) refers to this process of belief clari cation as "enriching one's mental model". In many respects, this process of testing, evaluating, and validity knowledge claims is strikingly similar to what Forrester (1961) Senge (1990) , and Sterman (2000) , advocate in relation to systems thinking and modeling. As Senge (1990) notes:
Finding common ground
systems thinking forms a rich language for describing a vast array of interrelationships and patterns of change. Ultimately, it simpli es life by helping us see the deeper patterns lying behind the events and details.
Finding common ground
In effect, this view of systems modeling is designed to surface causal claims and connect them into a coherent whole. The validity of systems models can be judged by their ability to provide managers with insights that enable them to predict actual patterns of performance. Alternatively, computer simulations can be used to determine whether a model composed of causal claims produces the expected kinds of behavior. What differs markedly among organizational learning, knowledge management, systems thinking, and pragmatic philosophies is what is done with the information regarding the validity of causal and knowledge claims.
Tre atment of know le dge claims
Since the term causal claim is a subset of knowledge claims, from this point forward causal claims will be included in discussion of knowledge claims unless a distinction between the two becomes necessary. Customarily, validated knowledge claims are equated with knowledge or truth and invalidated, as well non-validated claims are seen as being something other than knowledge. This is a very unproductive schema for categorizing types of knowledge. It is rare that any kind of knowledge is awlessly effective in yielding expected results or truth. More to the point, the vast majority of knowledge is partially or intermittently effective and has not been validated. This does not suggest that it is valueless when it comes to taking effective action. The KMCI life cycle model, Karl Popper's Three Worlds model, and Peircian pragmatism all view knowledge as being largely immature in most cases, and existing as part of a developmental process over time. When seen from an organizational learning perspective, knowledge is satisfactory when there are no longer mismatches detected between the expected results of our actions and the actual outcomes. Speci cally, this inference is drawn from an interpretation of knowledge inherent in Argyris' (1993) double loop learning model. In other words, here valid knowledge is assumed to exist in the absence of errors in achieving desired results. When viewed from Senge's (1990) perspective, effective learning is assumed to enable actors in organizations "to create the results its members truly desire". Again, the standard of high performance in creating knowledge appears to be one of effectivenessspeci cally, effectiveness in creating the most valued outcomes. In the context of the learning organization, there are few formal processes that are normally in place to assure the validity of knowledge, rather valid knowledge is assumed to exist when individuals, teams, or the organization are effective in reliably achieving the results they seek. While such criteria may seem practical on its surface, it is most likely a weakness of organizational learning doctrine that can bene t from others' perspectives, such as KM and pragmatic philosophy.
Tre atment of know le dge claims
In the knowledge life cycle model (KLC) proposed by Firestone and McElroy (2003) , the process of formulating and validating knowledge claims is only one step in an iterative model that is driven by knowledge applications. Such knowledge applications are known in the knowledge integration activities and include sharing the newly evaluated knowledge, teaching it to other organization members, broadcasting it, and searching. Once such knowledge is applied, it restarts the knowledge production process of forming and evaluating claims. This process is akin, in some respects, to a structured form of total quality management for knowledge production. However, most importantly, it addresses the structured application of knowledge to tasks and problem solving.
Tre atment of know le dge claims
By contrast, in philosophical pragmatism, Peirce (1868) argues for not only what Argyris terms as error correction, but also for validation of knowledge by a community of committed inquirers. Such communities most closely resemble what today in KM are known as "communities of practice". Lesser and Prusak (2000) de ne communities of practice as being "collections of individuals bound by informal relationships that share similar work roles and a common context". From the pragmatist perspective, failures among individuals in detecting errors or being able to predict with accuracy the outcomes of our actions is of relatively little importance in establishing the validity of knowledge. Individual readings are prone to the effects of random and non-systemic variation, whereas communities of people who are dedicated to understanding their work are more likely to recognize valid practices and knowledge.
Tre atment of know le dge claims
The knowledge management role that individuals play as members of communities of practice, inquiry and interest, and their role in these communities, is critical to understand organizational learning. By de nition, all such communities are self-directed. A major consulting client proudly announced to one of us that they already had communities of practice and went on to explain how well they had been organized by the rm's management team. While that's very interesting, it doesn't sound much like a community of practice, but rather a task force. Task forces are formal groupings, while communities of practice are emergent. Some such communities are focused primarily on improving current applications, whereas others, known as communities of interest are more inquiry-oriented.
Tre atment of know le dge claims
Leveraging organizational learning
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Communities of interest are groups of people who are curious to know more about certain types of knowledge and are willing to declare their desire to know more, but may not be willing to do more than make the declaration. Such groups often represent the assemblies of people who are new to a eld or who hold a tangential interest in a subject. Philosopher Charles Peirce (1868) de ned the concept of a "community of interest" as he observed:
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The real, then, is that which sooner or later, information and reasoning would nally result in, and which is therefore independent of the vagaries of you and me. Thus, the very origin of the conception of reality essentially involves the notion of COMMUNIT Y, without de nite limits, and capable of de nite increase in knowledge (Peirce, 1868, p. 69).
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In other words, what is true or valid is ultimately decided on by the community who are most interested and experienced in a domain of practice. Communities of interest are necessary for knowledge creation, but not suf cient. On the other hand, communities of practice (CoPs), John Seeley-Brown, Xerox's knowledge and innovation leader, sees such communities as being a small group of people who've worked together over a period of time. Not a team, not a task force, not necessarily an authorized or identi ed group. People in CoPs can perform the same job or collaborate on a shared task or work toegher on a product. They are peers in the execution of real work (Seeley-Brown and Duguid, 2000) . Communities of practice are essential to knowledge creation because all effective knowledge is created as the result of experience. Communities of inquirers, in this sense, the organization's "knowledge managers", perform the key function of knowledge evaluation and validation. Their mission is to determine which acts work reliably well over time. The community of inquirers is usually composed of people that possess much experience and even more desire to understand which forms of knowledge are effective in producing desired results. Ultimately, the perceptions and knowledge claims of the communities of inquirers are shared with both communities of interest and practice. The task of evaluating the potential effectiveness of knowledge in communities is a much more discrete task than is assessing whether learning has occurred.
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It is much easier to evaluate whether knowledge is effective in achieving its aims than it is to discern if learning is taking place because the aims are usually known. In his action-learning framework, Argyris attributes ineffective behavior to the effects of faulty policies and decision rules. In effect, he has de facto de ned knowledge in a way that is narrow, limited, and lacking in exibility. However, most importantly, it has provided a foundation for organizational learning theories that constricts the role of knowledge by de ning it in a narrow and arti cial way. First, it attributes ineffectiveness in achieving goals to failed policies and decision rules. These must be considered as impoverished surrogates for knowledge. Without doubt, there are compelling arguments to be made that knowledge can be de ned as a series of linked decision rules, but there is little effort made to de ne knowledge in a way that is consistent with the philosophical thinking on the subject of our time. Could the reason for this seeming oversight be that knowledge is viewed as the product of learning and has little bearing of the learning process itself? If so, this is a very parochial and non-systemic view. Knowledge both informs learning and is also its product. Second, noted pragmatist, Charles Peirce differed from his protégé, William James, over a critical issue dealing with the purpose of action and learning. Peirce proposed that sole purpose of action is to provoke the response that will tell us whether our beliefs and reasoning are clear. On the contrary, James appears to have misunderstood his mentor Peirce, and argued that effective action merely validates the correctness of our thinking. There is general consensus that Peirce saw effective action as being only a means to the end of making our thinking clear. Peirce does not say that action is thought's purpose, but conversely he argues that the raison d'etre for thinking is to establish patterns of action in the form of habits, beliefs, and rules for action. "Thought in action has for its only possible motive the attainment of thought at rest", that is, effective action tells us about the correctness of our beliefs. Thought comes to rest when beliefs -truths -are chosen that reliably produce effective action. In that organization members are forever noticing external and internal changes raising new thoughts of healthy doubt, Peirce's principle suggests a force that impels organizational learning. While Argyris (1990) addressed the subject of committing errors in reasoning by his proposing the constructs of defensive routines, Model I and II, and the notion of skilled incompetence, his approach still avoids adequately explaining the respective roles of knowledge and beliefs. On the other hand, Senge (1990) comes closer to dealing with this issue when he addresses the question of the purpose of systems archetypes when he observes, "the purpose of systems archetypes is to recondition our perceptions". In a similar vein, he notes that the purpose of modeling is to enrich our mental models.
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It would appear that unlike KM, the prevailing model of the learning organization is one that is ungrounded in a signi cant way. Both KM and organizational learning appear to be in accord with the idea that the goal of these processes is to increase our capacity for taking effective action. However, KM offers us structured processes and technologies for applying knowledge in organizations, whereas OL leaves us with a continuous improvement processthat is, to continually increase capacity to create the most desired results. The problem with this notion is that there is no deliverable, there is no structure, and the clear absence of any means to convey lessons learned. Is the learning organization an elaborate ideal vision without any viable technologies for implementation? Yet, it also offers us some potentially useful tools and concepts for making sense of experience that can be of value to KM. It is arguable that KM and OL have much to learn from each other, even more to offer each other, but the larger question that looms is -can they be integrated?
Leveraging organizational learning
Before answering that question it is necessary to examine just how these two approaches work in practice.
Grounding knowle dge in practice
Effective knowledge processing can bring new understandings of how problems impede performance to bear on the work being done by people in organizations. Such knowledge may help in reframing the way agents in organizations view problems or provide them with new rules for solving problems. Clearly, KM has a more structured and task or problem-speci c focus than OL. KM functions primarily at the level of practice and action, whereas OL often extends well beyond praxis to considering espoused theories, values, and mental models. OL is usually interpreted as being a capacity enhancement strategy that improves how people learn from experience, while also assisting organization members to surface and question the validity of mental models. So how are these seemingly different approaches linked? While any relationship between OL and KM may not seem immediately transparent, there is a very important connection between the two approaches. Effective KM and OL processes depend on action learning processes to ground them in reality.
Grounding knowle dge in practice
Unlike other forms of learning or knowledge discovery that are rooted primarily in the use of reasoning, OL and KM rely on continuous efforts to validate the accuracy of mental models and beliefs through practice and the feedback of results. (Figure 1) That is, achieving desired results is the standard by which the usefulness and validity of knowledge is assessed. From a systems perspective, this may be framed as a cybernetic process in that it is goal seeking and produces balancing loops that bring knowledge into alignment with beliefs, action, and results. Unlike other forms of learning or knowledge discovery that are rooted primarily in the use of reasoning, OL and KM rely on continuous efforts to validate the accuracy of mental models and beliefs through practice and the feedback of results. Such action learning cycles as developed by Kolb et al. Revans (1980) play a central role in both KM and OL. There is a strong tradition of using models of continuous cycles for combining action, learning, and knowledge that can also be found embedded in the writings of systems theorists A. E. Singer, Ackoff, and Churchman. Dewey has pointed to the relevance of action-learning theories to the processes of knowledge creation by noting that sense-making requires the facility for being both active and passive -at different times. That is, people act on the world, but then, they endure the consequences. Knowledge arises as the beliefs that led to the actions are either validated or invalidated by the experience of the consequences. Action learning theories posit that people learn most deeply through the experience of doing -as opposed to learning in other ways, such as classroom lectures, reading books, and the like. This is because the experiencing of consequences to one's actions holds the potentiality to re ne the accuracy of one's beliefs. This type of learning -that is, modifying one's beliefs -is often viewed as being the most profound type of learning that someone can experience. Action learning is a dualistic process. We do something to the world and the world does something back to us. More often than not, managers who are under pressure to perform by invoking well-practiced rote routines without regard to their own beliefs about causality mistakenly nd greater leverage in emphasizing the doing part rather than the sense-making part of the action learning cycle. The action parts of the cycle are doing and experimenting. The sense-making parts are re ecting and hypothesizing. According to this perspective, the essence of learning through experience (work) is to take intentional action, mentally capture what was done, what happened, and in what context, then develop a possible explanation for why things turned out as they did, formulate this explanation as a new hypothesis about how things really work and then experiment by trying new types of actions that are expected to be effective in yielding desired goals if the system really functions as you understand it. The key point to be made here is that action learning is not about learning new data or information from any sources outside of one's experience. Rather, it is essentially about a person's ability to draw new, and potentially unexpected, meaning from their experience. Ideally this happens in such a way that it enables them to rst, change their mind about how things really work causally, develop new knowledge claims about how cause and effect actually function in any given situation, and act differently in accord with new understandings. Accordingly, we may think of managing itself as an act of knowing what to do under a wide array of circumstances and why. Ideally, the cycle of managing is itself completed when, on re ection, there is learning of what works best for the next time.
Grounding knowle dge in practice
In OL, the quality of knowledge claims is improved over time through a variety of processes including dialogue, planning, and collaboration. Organizational learning may be understood as a collective form of action learning that emphasizes the value of social interaction in surfacing and Leveraging organizational learning exploring one's own beliefs, mental models, and as well as mutually shared beliefs. In doing so, OL strategies seek to address a blind spot in individual learning processes -namely, it is exceedingly dif cult to recognize the incoherencies and incompleteness of our own thoughts. Accordingly, OL enables people through social action to effectively provide another form of grounding in reality -namely, the social reality that in KM is associated with communities of practice. From an action learning perspective, people may learn from the feedback resulting from their actions on a given reality, such as a manager lowering prices and seeing the effect on orders, or they may also test the validity of their ideas in the social reality of their community. As Argyris (1993, p. 284) 
notes:
Seeking truth is an ongoing activity -never fully achieved, always approximated. It has always been regarded as the ultimate purpose of research. The major test of how well we are doing in seeking truth (small t) is to formulate statements of truth as hypotheses and then strive to discon rm them, not simply con rm them.
notes:
Interestingly, with KM there is a growing appreciation of Popper's notion that it is equally important to discon rm one's various hypotheses about what works best in practice, as it is to con rm them. Does OL actually share the same paradigm as KM of approaching organizational as a scienti c experiment that over time is designed to reveal what works best?
notes:
Organizational le arning's evolution aw ay from s cie nce Over time, OL appears to have grown away from its roots in what Argyris termed "action science" and action learning. Its focus was on individuals more than teams or groups. Originally, a central feature of OL was that of "variables" and "patterns of causality" as found in the writings of Nobel laureate, Hebert Simon, and Campbell and Stanley (1963) . The essential notion of this early OL research was on the potential that managers could improve the quality of their decision making by using the feedback of unanticipated results to trigger a process that would surface their deeply held beliefs about causality and question their validity. The hoped for response was that, in the face of under-performance, managers would be able to break the reinforcing cycle produced by their habitual patterns of thought, and develop new alternative strategies that were better suited to producing the desired results in that situation. Clearly, this approach focuses on the role of individual managers' capacity to interpret their experiences in the context of an organizational setting, but does not explicitly address the group or cultural dimensions of organizations. Argyris' (1977) early de nition of OL makes this distinction quite clear.
notes:
Organizations learn through individuals acting as agents for them. The individual's learning activities, in turn, are facilitated or inhibited by an ecological system of factors that may be called an organizational learning system (Argyris, 1977) .
notes:
In this system, when agents (usually managers) are able to become aware of the fallibility of their own theories-in-use, they will be less prone to defend and advocate the use of ineffective theories to others. Thus, the effect is to dampen the propagation of non-viable models of practice and to break the cycle that tends of reinforce norms that continue practices that are unlikely to yield desired effects. The major contribution of this pioneering work in OL was found to be its ability to differentiate the cyclical process of learning directly from one's own work experiences from the view of learning that people normally associate with organizations -namely training and education. More importantly, such learning in the organizational milieu was viewed as being directly related to performance. Unlike other forms of learning in organizations, OL was de ned as a means of discovery -to discover what works best. In other words, it became a tool for revealing the antecedents to effective action. It is critical to note that at this point, OL and current new generation views of KM stand on the same ground. OL's pioneers cast action learning in the same light as the American pragmatist philosophers who were interested in knowledge, beliefs, and action. Historically, OL and KM can be connected to the common roots found in the philosophies of pragmatism.
notes:
In pragmatist philosophy, especially the Peircian version, learning, knowledge and action can never be separated from each other. As noted by Potter (1996): Pragmatism is a doctrine of logic. It is a logical method helping us to know what we think and believe. The meaning of our thought is to be interpreted in terms of our willingness to act upon that thought; it is to be interpreted in terms of its conceived consequences.Peirce, then, see as connection between good thinking and good doing
notes:
Here we see that both KM and OL are concerned with the processes that enable our actions to be effective. The philosophical foundation for uniting OL and KM has been discovered in its OL's roots in pragmatism, and now to an increasing degree in Popperian philosophy.
A more pragmatic vie w of knowle dge
In order to understand the critical role that action learning plays in pragmatic knowledge processes it is rst necessary to de ne knowledge in a way that is consistent with both reasoning and action. Many de nitions of knowledge emphasize reasoning to the exclusion of action. Many OL theorists view knowledge as being the capacity for effective action. While this is true, this de nition de nes knowledge vaguely as a capacity. This de nitional vagueness undermines the potential for knowledge to be used in practical ways. A more precise action-oriented view is that "knowledge is a cache of 'scripts' that may potentially be used in a given situation". A script is a program that governs behavior under speci c circumstances. Scripts contain three basic elements that de ne the situation, set performance targets, and direct the required action. Found at the core of all scripts are simple Leveraging organizational learning performance programs or routines. A routine is a prescribed set of actions governed by an operative policy that is used to reach a speci c performance target. Scripts are designed to t each situation, so it is possible for different types of scripts to evolve to t various kinds of circumstances. Because scripts are situational there is a perceptual element to their use. A routine is initiated to t a perceived set of circumstances. Many people would argue that the circumstances are external and should not be included within a script. Such an objectivist view discounts the role played by beliefs in governing people's perceptions. When perception is understood from a more interpretive perspective, perceptions are viewed as being determined by an individual's own internal symbolic representations. In other words, one can only see those things that are familiar to them in some way. Ultimately, perceptions originate in internal capacities for symbol recognition. In fact, situational representations located in a script are the result of the internalization of some prior external phenomena. Finally, performance targets are merely expected results that range from speci c to general in scope (Figure 2 ).
A more pragmatic vie w of knowle dge
According to this view of knowledge, lessons learned through experience enable an individual's cache of scripts to accumulate as new scripts evolve and other ones are modi ed. This is where action learning comes into play. Action learning is the process by which a person or group re ects back on those actions they have taken and their effects, new hypotheses are created to explain why actions taken caused certain effects, and new actionable approaches are designed. In effect, action learning is the process that enables people to modify existing scripts and design new ones. Action learning can be viewed as a reiterative cycle of looking back, analyzing, and then, looking forward. (Figure 3) In effect, what is being re ected on in the action learning cycle is the effectiveness of scripts in producing desired results. The focus of the analysis and hypothesizing phase of the action learning cycle are intended to determine possible reasons that explain why the prior actions were effective or not. Finally, the experimentation phase of the action learning cycle really means experimenting with -designing new scripts.
Pragmatic knowle dge manageme nt
There are many varying de nitions of knowledge -with each offering differing potential for new insights -and serving as the sources of Figure 2 . Action-oriented view of knowledge organizational innovation. Pragmatically, knowledge management is the process of scienti cally discovering the antecedents of effective action and designing systems to enable people to operate core knowledge processes that integrate beliefs, reasoning, and knowledge. A pragmatic view of knowledge proposes that KM should include the following features Reed, 2000, 2001) .
Knowledge is triadic
Knowledge is composed of sets of:
Knowledge is triadic
. ways to recognize recurring or similar situations;
Knowledge is triadic
. scripts or routines for guiding action; and . clear expectations of expected results.
Knowledge is triadic
In other words, knowledge is a system made up of a case, a rule, and an expected result. Together, this system is known as an act. That is, it is a way of acting in a recognized situation to achieve an expected result. If the use of the act was successful in achieving the expected result, then the action taken was effective.
Knowledge is triadic
Knowledge is a storehouse of potentially usable acts Think of knowledge as being like a warehouse that is lled with stock. In this case, it is lled with acts. There are all kinds of acts in this warehouseproven, disproven, and unproven ones -any of which may be called up for use. In this warehouse there are all kinds of knowledge with varying degrees of utility. Some knowledge is old and some is new in this storehouse. Some knowledge is more useful than others -in that it is more effective in reliably producing the expected outcomes. KM tracks the effectiveness of these various T he knowledge storehouse is lled with potentially effective scripts Acts are contingent sets of decision rules. Each decision rule ts a speci c situation and desired outcome. In knowledge, every speci c problem situation contains a decision rule(s) whose use will yield desired outcomes. There are few acts that are guaranteed to work all of the time. Therefore, we say that most acts are potentially effective in produced expected results.
Knowledge is triadic
A cts are created through the use of reasoning Three basic forms of reasoning are deduction, induction, abduction. Logical processes of reasoning are necessary to create acts. Inferential reasoning enables people to progress from assumptions or truths to logical sets of relations that have practical value in guiding action. For example, children engage in reasoning to help understand the world. A child learns at an early age that dogs bark and chase cars while cats meow and run away from cars. At the simplest level, if a child saw an animal that was barking and chasing a car, then, it would deduce that it is a dog. At a higher level, an older child might be able to infer that it must keep its dog on a leash near a street with busy traf c because dogs chase cars and moving cars can be dangerous to dogs. If the situation is a busy street, the desired result is "protect my dog from harm", then the rule is "keep the dog on the leash". Such situation-speci c decision rules are the essence of organizational knowledge.
Experience teaches us which acts work best
People, whether inside organizations or outside of them, are continually trying to determine which acts will work best. The feedback of results from the use of various acts helps people discover which acts are likely to prove useful under similar circumstances. Through experience, our knowledge of which acts to use to achieve certain purposes can be informed. When OL and KM are viewed pragmatically, it provides a strong conceptual link between them that not only unites them, but also ties them to a well-established conceptual grounding. Future research is warranted into ways that the two disciplines can be integrated or used in tandem.
Conclus ion
The conceptual and philosophical roots of knowledge management and organization learning have been examined with an eye toward comparing and contrasting their similarities and differences. The potential for integration or tandem use of these two disciplines was explored. KM has historically been de ned and practiced in a wide variety of ways, many of which have been judged to be largely incompatible with OL. OL has it roots in the early research of Argyris and Schon on what is known as action learning and action science.
Conclus ion
Action learning is predicated on many concepts that have been developed in the tenets of philosophical pragmatism most often associated with Charles Peirce, Willia m James, and John Dewey. T oday, there are newer conceptualizations of KM that are based either on pragmatic concepts, or similar ideas, such as those espoused by Popper, and Notturno.
Conclus ion
Newer versions of KM and OL share much common ground in the notion of action learning cycles, knowledge claims, a focus on effective action, and a recognition of the important role played by mental models and belief systems. Contemporary KM approaches are knowledge-process centric and give equal weight to creating knowledge as much as distributing existing knowledge. Many of the key functions in OL, such as dialogue, team learning, creating a shared vision, and viewing planning as learning are all elements of what KM considers to be knowledge processing. Historically, noted management thinkers, such as C.W. Churchman and Russell Ackoff developed management systems approaches that were also founded on the precepts of philosophical pragmatism. Unsurprisingly, both were students of the philosopher A.E. Singer at the University of Pennsylvania. Singer had been a student of William James and a contemporary of John Dewey. In a conversation with Russell Ackoff in 2002, he recalled that he knew John Dewey well and would meet with him often when he was a doctoral student under Professor Singer.
Conclus ion
Can a management approach or strategy for organizational intervention ever be fully defensible if it rests on a conceptual foundation that is weak or that contains misconstrued philosophies? Undoubtedly, it is desirable to build any form of practice on a strong foundation. By all appearances, there is reason to believe that a convincing argument can be made that there is a suf cient philosophical basis to ground both OL and KM in shared ideology to their mutual bene t. Whether such an approach is feasible in other ways, such as appealing to practitioners and offering strong face value is another question. Yet, without doubt, there is more than adequate reason to engage in further dialogue and to conduct further research into the pragmatic issues surrounding these questions.

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