6
KNOWLEDGE
5. List the different knowledge support technologies that can help users put knowledge into action.
INTRODUCTION
Knowledge management typically addresses one of two general objectives:
knowledge reuse to promote efficiency and innovation to introduce more effec- tive ways of doing things. Knowledge application refers to the actual use of knowledge that has been captured or created and put into the KM cycle (see Figure 6-1).
Knowledge eventually is made accessible to all the knowledge workers in the organization, with an implicit assumption that they will be used. This assump- tion turns out to be a rather large and often unfounded one. If we recall the Nonaka and Takeuchi model from Chapter 3, we can see that having captured, coded, reorganized, and made knowledge available, we are still only in the third quadrant. The knowledge spiral needs to be completed by successful internalization of knowledge. This process of internalization, it should be recalled, consists not only in accessing and understanding the content but in consciously deciding that this is indeed a good—ideally better—way of doing things, and hence the knowledge is applied to a real-world decision or problem.
This is knowledge reuse, the process whereby useful nuggets of knowledge or knowledge objects are made available in a library of such objects. These knowledge objects can be annotated references, components (programs or text), templates, patterns, or other types of containers. For example, consult- ing companies often reuse project proposal templates because they convey the company brand, contain useful reusable objects such as testimonials, company description, and so on. The goal is to reduce the time it takes to complete tasks as well as to help maintain higher standards regarding the quality of the work to be done. The benefits to new employees are enormous as they are able to
F
IGURE6-1
A
N INTEGRATEDKM
CYCLEKnowledge Acquisition and Application
Assess
Contextualize
Update Knowledge Capture and/or Creation
Knowledge Sharing and Dissemination
attain “day one” performance with the help of such a reuse library; that is, they are able to perform at a fairly high level on their first day on the job. The other major benefit is the work that is not done—because it was possible to see that someone else had already done it. The savings involved in not “rein- venting the wheel” can be considerable.
KM aims to support learning organizations that provide all employees with access to corporate memory so that both the individuals and the organization as a whole improve. Corporate memory is often incomplete because it has cap- tured only explicit knowledge. KM also attempts to make accessible the valu- able tacit knowledge, which is added to the corporate memory. While it is possible to reuse tacit knowledge (and this is done all the time during knowledge-sharing interactions), reuse tends to refer to packaged explicit knowledge. Reuse of explicit knowledge affords a longer-term advantage.
Whereas tacit knowledge reuse can benefit the individual who sought the advice of a more experienced colleague, knowledge objects that are accessible through the knowledge repository are accessible to all workers and they remain so for as long as they are useful.
That being said, it is imperative to try to include or at least be able to point to where the tacit knowledge associated with a given knowledge object resides.
It is never possible or even desirable to try to render all knowledge explicit.
If knowledge workers can easily locate and communicate with individuals in the company that are connected to a given knowledge object (e.g., they are familiar with how it is used, they have been trained, etc.), then the ability to apply or to make use of this knowledge is greatly increased. In the example of the proposal writing knowledge object or template, hyperlinks can easily be included not only to good examples of past proposals that were successful (best practices) but also to the individuals involved in their preparation so that they can be contacted for advice, a read-through, or other forms of help.
The essence of problem solving, innovation, creativity, intuitive design, good analysis, and effective project management involves more tacit, rather than explicit, knowledge. By putting tacit knowledge in a principal role and cultivating tacit knowledge environments, KM can play an important role in application development, particularly in reuse. Another aspect of the explicit knowledge problem is the fallacy that documentation (explicit knowledge) equals understanding. We seek understanding in order to successfully reuse a component. However, the larger and more complex the component, the harder it is to gain the required understanding from documentation alone. Under- standing, in this context at least, is a combination of documentation and con- versation—conversation about the component and the context in which that component operates. No writer of documentation can anticipate all the ques- tions a component user may have. Even if this were possible, the resulting documentation would be so extensive and cumbersome that potential users would simply develop their own component rather than wade through the documentation.
Knowledge management systems that focus on gathering, recording, and accessing reams of “knowledge” at the expense of person-to-person interac- tions have proven to be expensive and less than satisfactory. Organizations that fail to understand tacit knowledge will repeat many of the mistakes made with
methodologies such as Computer Assisted Software Engineering (CASE). A common assumption in the past was that all relevant knowledge could be bundled up in nice, neat, easily accessible packages of “best practices” that practitioners could then “repeat.”
When we attack reuse as a knowledge management problem, we begin to ask new questions, or at least look for different avenues for finding solutions to the problem. How do we go about finding the component we need? How do we gain confidence that the component does what we want it to do and does not do strange things that we do not want? What is the distance (orga- nizationally or geographically) between the component developer and users?
Are there other people who have used this component whom we could talk to and learn from? Do we have access to the author of this component?
Have others found this component to be effective? How should we go about testing this component? How easily will this component integrate into our envi- ronment?
Dixon (2000) outlines factors that affect knowledge transfer: characteristics of the receiver (skills, shared language, technical knowledge), the nature of the task (routine, nonroutine), and the type of knowledge being transferred (a continuum from explicit to tacit). The author then identifies five categories of knowledge transfer that she has observed, from Near Transfer (“transferring knowledge from a source team to a receiving team that is doing a similar task in a similar context but in a different location”) to Serial Transfer (“the source team and the receiving team are one and the same”). Dixon then describes techniques that work well for each of these five types of transfer.
The objective of this chapter is not to describe the practices for knowledge transfer in detail, but rather to point out that merely coding a component and scratching out a few lines of documentation will rarely be enough to facilitate knowledge transfer. Other researchers such as Hatami, Galliers, and Huang (2003) found that a key to organizational success in the face of global com- petition is the ability to capture organizational learning, to effectively reuse the knowledge through efficient means, and to synthesize these into more intelli- gent problem recognition, strategic analysis, and choices in strategic directions.
By tapping into their organization’s memory, decision makers can make more intelligent business decisions. This is achieved when individuals access data, information, and knowledge residing in repositories. However, retrieval alone is not enough—knowledge application must follow, and the success of knowl- edge application appears to be a function of the characteristics of the individ- ual, the knowledge content, the purpose of reuse for the particular task at hand, and the organizational context or culture.