So decision execution cycles performed by agents in executing tasks and task pat- terns in business processes are in part sequentially ordered knowledge produc- tion and knowledge integration processes. Figure 7.4 provides an overview of a knowledge life cycle (KLC) model begun in collaboration with Mark McElroy, Edward Swanstrom, Douglas Weidner, and Steve Cavaleri (1999), during meetings sponsored by the Knowledge Management Consortium International (KMCI), and further developed more recently by Mark McElroy and myself. Knowledge production and knowledge integration, abstracted from the planning, monitor- ing, and evaluating phases of decision cycles, are core knowledge processes in the model.
Knowledge production is initiated in response to problems produced by deci- sion cycles in business processes. It produces organizational knowledge (OK). It includes (not shown in the figure) surviving knowledge claims (SKCs), undecided knowledge claims (UKCs), and falsified knowledge claims (FKCs), and informa- tion about the status of these. All of the above are codified, explicit, world 3 objects. Organizational knowledge (OK) is composed of all of the foregoing results
Figure 7.4. The knowledge life cycle (KLC) framework.
of knowledge production. It is part of what is integrated into the enterprise by the knowledge integration process.
The knowledge production process, in combination with previous agent pre- dispositions, also produces beliefs related to the world 3 knowledge claims. These are world 2 objects, predisposing various organizational agents to action. In some instances they are predispositions that correspond to organizational knowledge;
in other instances they are predispositions that reflect awareness of validated or surviving knowledge claims but contradict them, or supplement them, or bear some other conceptual relationship to them. At the individual level these beliefs are in part tacit, since all of them are not expressible linguistically by the individ- uals holding them, or implicit, since some that are neither tacit nor explicit may not have been verbally expressed. Where these beliefs have been validated by the individuals or by other intelligent agents holding them, they constitute world 2 knowledge held by those agents. But they are not organizational knowledge.
Rather they are outputs of the organizational NKMS to the individual agents.
The knowledge integration process takes organizational knowledge and by integrating it within the organization produces the distributed organizational knowledge base (DOKB). Integrating means communicating organizational knowledge content to the organization’s agents with the purpose of making them fully aware of existing organizational knowledge. This also requires making the knowledge available in knowledge stores that agents can use to search for and retrieve knowledge. The result of knowledge integration is that the content of codified organizational knowledge is available in both accessible and distributed knowledge stores and, in addition, is reflected in the predispositions of agents all across the enterprise. The DOKB is the combination of distributed world 3 and world 2 knowledge content.
The DOKB, in its turn, has a major impact on structures incorporating orga- nizational knowledge such as normative business processes, plans, organizational culture, organizational strategy, policies, procedures, and information systems.
Coupled with external sources these structures then feed back to impact behav- ioral business processes through the acting phase of decision cycles, which, in turn, generates new problems to be solved in the planning, monitoring, and eval- uating phases—that is, in the next round of knowledge processing. That is why it is called the knowledge life cycle (KLC) framework).
“Drilling down” into knowledge production (Figure 7.5), the KLC view is that information acquisition and individual and group learning, in the service of problem-solving, impact on knowledge claim formulation, which, in turn, pro- duces codified knowledge claims (CKCs). These, in their turn, are tested in the knowledge validation task cluster, a critical examination of knowledge claims including, but not limited to, empirical testing, which then produces organiza- tional knowledge.
The key task cluster that distinguishes knowledge production from information produc- tion is knowledge claim evaluation (or validation). It is the subprocess of criticism of competing knowledge claims and of comparative testing and assessment of them that transforms knowledge claims from mere information into tested informa- tion, some of which passes organizational tests and therefore becomes, from the organizational point of view, knowledge.
In other words, the difference between information and knowledge is valida- tion. But what is validation? It is testing and evaluation of knowledge claims
(world 3), or testing and evaluation of beliefs (world 2). Testing and evaluation of knowledge claims is public and sharable in the sense that the claims themselves are sharable and the tests and their results are sharable. That is why world 3 knowledge is objective. Testing and evaluation of beliefs is private and personal. It is this difference that makes world 2 knowledge subjective.
Validation is not the same thing as justification. Justification is the process of proving that a knowledge claim is true. Validation never proves anything with certainty. It simply provides (1) a record of how well competing knowledge claims stand up to our tests or (2) personal experience of how well competing beliefs stand up to our tests. Justification of knowledge claims and beliefs is impossible, but validation of them is not.
Since validation is just our process of testing and evaluating knowledge claims or beliefs, the practice of it will vary across individuals, groups, communities, teams, and organizations. A particular entity may use validation practices based on explicit rules or specified criteria to compare knowledge claims, but it need not. Agents are free to change their tests or criteria at any time, to invent new ones, or to apply ad hoc tests and criticisms in validation. That is, validation is a free-for-all; it is just the process by which knowledge claims and beliefs run the gauntlet of our skepticism and our criticism.
Looking at knowledge production from the viewpoint of agents at different levels of organizational interaction and keeping the role of knowledge claim vali- dation in mind, it follows that individual and group learning may involve knowledge production from the perspective of the individual or group. From the perspective of the enterprise, however, what the individuals and groups learn is information, not knowledge. Similarly, information acquired may be knowledge from the perspective of the external parties it is acquired from, but not knowl- edge to the enterprise acquiring it, until it has been validated as such.
Figure 7.5. Knowledge production.
Figure 7.5 also illustrates that knowledge validation has a feedback effect on individual and group learning. This occurs because individuals and groups par- ticipating in knowledge claim validation are affected by their participation in this process. They both produce world 3 organizational knowledge in the form of codified and validated knowledge claims, and also experience change in their own “justified” beliefs (generate world 2 knowledge) as an outcome of that partici- pation.
Drilling down into knowledge integration (Figure 7.6), organizational knowl- edge is integrated across the enterprise by the broadcasting, searching/retrieving, teaching, and sharing task clusters. These generally work in parallel rather than sequentially. And not all are necessary to a specific instance of the KLC. All may be based in personal non-electronic or electronic interactions.
An illustration of the distributed organizational knowledge base is provided in Figure 7.7. Here containers of both world 2 and world 3 knowledge are repre- sented. The knowledge of each type is the content of the validated beliefs held by agents and the validated (or surviving) knowledge claims stored in various media and repositories.
Next, the same containers are viewed as business structures influencing behavior rather than as mere containers of knowledge. As such they provide the external background conditions for agent behavior (see Figure 7.8).
The relationship between structures incorporating organizational knowledge and business process behavior is presented in a somewhat different perspective in Figure 7.9. This figure presents the agent, individual, group, team, or organization as a decision maker executing the transactions that are the atomic components of processes. World 2 knowledge is contained in the goal-directed agent and is com- posed of the memories, values, attitudes, and situational orientations of agents.
World 3 knowledge is contained in the cultural conditions that make up part of Figure 7.6. Knowledge integration.
social ecology. Thus, Figure 7.9 also illustrates the role of world 2 knowledge as an immediate precursor of decisions and transactional behavior in the organiza- tional system, as well as the role of world 3 knowledge as a cultural factor shaping psychological orientations in general and world 2 knowledge in particular.
Figure 7.7. The distributed organizational knowledge base.
Figure 7.8. Business process behavior and containers of knowledge.
Table 7.1 provides a glossary of the major terms used in the KLC model.
Knowledge production and knowledge integration, their subprocesses, and task clusters, etc., like other value networks, are partly composed of decision cycles through which agents execute their roles in these value networks. This means that planning, acting, monitoring, and evaluating also apply to knowl- edge processes and to activity in the KLC. That is, higher-level KLC processes are executed by agents performing KLC decision cycles and engaging in planning, monitoring, and evaluating. The knowledge producing and knowledge integrat- ing activities initiated by KLC decision cycles are KM-level knowledge producing and knowledge integrating task clusters, because they address problems in knowl- edge processing about how to plan, how to monitor, or how to evaluate. These problems are solved by producing and integrating KM-level knowledge.