Chapter 7: KnowledgeManagement in Practice

FINDING INFORMATION AND KNOWLEDGE

Knowledge exists in all organizations, but all knowledge may not be explicit.Knowledge objects or artifacts are entities that represent knowledge existing within organizational members [McInerney, C., 2002]. A long-time employee may have a deep understanding of processes and guidelines, but he or she may never have written them down or compiled them in a document like a procedural manual. As a gatekeeper of know-how about “how things are done,” this worker has the power of knowing, but may also find that it is tedious and annoying having to answer the same questions over and over again. Codifying his or her knowledge in a manual would allow others to read and understand how tasks and projects can proceed to completion.

SHARINGINFORMATIONANDKNOWLEDGE

Teaching and learning activities, such as online universities in industry, mentoring programs, apprenticeships, and training programs all serve as opportunities for individuals to share knowledge. The live interactions that occur in lectures and other kinds of learning sessions can now be captured fairly easily with digital video or audio equipment. Even mobile devices have these capabilities.They can then be indexed and placed on a shared file platform or in an intranet. If indexed appropriately, knowledge workers can find the audio and video and use these things over and over again.

DEVELOPMENTOF KNOWLEDGE

Although individuals can intentionally develop their own knowledge through seeking opportunities to be creative and learn, the development of knowledge is often a social process. Meetings, teleconferences, planning sessions, knowledge cafes, and team think tank sessions all serve to help workers develop knowledge together. The synergies brought about by effective meetings can encourage the development of new knowledge. Allowing individuals to take risks and occasionally make mistakes (and learn from them) can also develop a culture of innovation that fosters the creation of new knowledge through research and experimentation.

KNOWLEDGE AUDIT

The idea of an information auditory much predates KM as we have defined KM here. Accompanying, or more accurately a component of, the Information Resources Management (IRM) movement of the 1970’s was a strong emphasis upon the information or knowledge audit. The foremost exponent of the information or knowledge audit was Forrest (Woody) Horton. He and Burk developed a program called ‘InfoMapper’ [Burk and Horton, 1988] precisely to facilitate the conduct of an information audit. With the development of KM, there ensued a shift to amuch greater emphasis upon knowledge embodied in people. Indeed, Moulton, L. [2008] advocates a three-stage process for a knowledge audit that starts with people and emphasizes knowledge embodied in people.The first stage focuses on people, “their knowledge and expertise and their connections to others” [Moulton, L., 2008, p. 80].The ideal result is a “map” of:

Who is connected to whom, formally and informally?

What are their formal roles and job descriptions, and informal relationships and roles?

Where do expertise, methods, differing views of the organization reside?

What are the successful knowledge sharing engagements and practices?

What are the barriers to information and knowledge transfer?

TAGS,TAXONOMIES,ANDCONTENTMANAGEMENT

The tag and taxonomy stage of KM consists primarily of assembling various information resources in some sort of portal-like environment and making them available to the organization. This can include internally generated information, including lessons learned databases and expertise locators, as well as external information, the open web and also deep web information subscribed to by the organization .With the arrival of extensive email use by virtually all organizations the extent of internal information to be managed has exploded. The obvious consequence of this plethora of data and information from multiple sources is great terminological inconsistency and confusion, and that, in turn, drives the appeal of syndetic data structures and taxonomies that can assist the user in locating information or knowledge and result in better and more effective searching.

LESSONS LEARNEDDATABASES

Lessons Learned databases are databases that attempt to capture and to make accessible knowledge that has been operationally obtained and typicallywould not have been captured in a fixedmedium(to use copyright terminology). In the KMcontext, the emphasis is typically upon capturing knowledge embedded in persons andmaking it explicit. The lessons learned concept or practice is one thatmight be described as having been birthed by KM, as there is very little in the way of a direct antecedent. Early in the KM movement, the phrase typically used was “best practices,” but that phrase was soon replaced with “lessons learned.” The reasons were that “lessons learned” was broader and more inclusive, and because “best practice” seemed too restrictive and could be interpreted as meaning there was only one best practice in a situation. The implementation of a lessons learned system is complex both politically and operationally. Many of the questions surrounding such a system are difficult to answer. Who is to decide what constitutes a worthwhile lesson learned? Are employees free to submit to the system unvetted?Most successful lessons learned implementations have concluded that such a systemneeds to bemonitored and that there needs to be a vetting and approval mechanism before items are mounted as lessons learned

EXPERTISE LOCATION

Expertise location systems are another aspect of KM that certainly predates KM thinking. TheMitre Corporation, for example, developed such a system in 1978. It was based upon creating a database developed from reformatted resumes retrieved from word-processing tapes, and upon the development of a competence area thesaurus to improve retrieval. There are nowthree areaswhich typically supply data for an expertise locator system, employee resumes, employee self identification of areas of expertise, typically by being requested to fill out a form online, or by algorithmic analysis of electronic communications from and to the employee. The latter approach is typically based on email traffic, but it can include other social networking  electronic communications such as Twitter and Facebook.

COMMUNITIESOF PRACTICE (COPS)

Communities of Practice (CoPs) are groups of individuals with shared interests that come together in person or virtually to tell stories, discuss best practices, and talk over lessons learned [Wenger, E., 1998a,Wenger and Snyder, 1999].Communities of practice emphasize the social nature of learning within or across organizations. In the context of KM, CoPs are generally understood to mean electronically linked communities. Electronic linkage is not essential of course, but since KMarose in the consulting community from the awareness of the potential of Intranets to link geographically dispersed organizations, this orientation is understandable and inevitable.

Chapter 5: Knowledge “Acts”

QUESTIONASKINGANDANSWERIN

Question asking and answering is a foundational process by which what people know tacitly becomes expressed, and hence, externalized as knowledge. They reason that IM addresses questions such as ‘Where,’ ‘Who,’ ‘When,’ and ‘What,’ while KM targets problems involving dynamic complexity, addressing solutions to questions such as ‘How’ and ‘Why.’ Quigley and Debons [1999] adopted a similar stance that considers information as texts that primarily answer ‘informative’ questions such as who, when, what, or where while knowledge is considered as texts that answer more ‘explanatory’ or ‘meaning related’ questions such as why or how. Another category of questions, “What-if,” will also fall in the domain of knowledge activity.Since such questions necessitate predicting and prioritizing outcomes, attempts to address such “what-if ” questions will require integrating understanding of “what” with “why” and “how” to arrive at reasonable resolution

POSTINGCONTENTTOREPOSITORIES

Contributing content such as lessons-learned, project experiences, and success stories is another approach to knowledge sharing.The capturing of best practice has often been highlighted as a form of externalized knowledge. On the other hand, professionals may not have the time to hand off a document for submission to an appointed surrogate either. For many professionals who are used to online communication and accessing databases and discussion lists, we could argue that it is quicker and easier for the professionals to make the contribution themselves. The authors point out that the product supports both the construction of knowledge as content, or as the collaborative, negotiated, coconstructed approach to verifying and validating content, essentially accommodating both the content and process views of knowledge construction.The developed content is then madeavailable to others for (re)use, or, for re-combination, to support newinstances of knowledge creation.

(RE)USINGKNOWLEDGE

Since the publication of this seminal work legions of researchers have worked on systems that will help people formulate effective questions that will retrieve relevant information.McMahon et al. [2004], studying teamwork involving engineering design, suggest that both codification and personalization approaches to knowledge reuse are relevant. They recognize the notion of information value, allowing for the matching of information to the knowledge needs of the user. They propose that good representations of both information characteristics and user characteristics are essential.

KNOWLEDGE-BASED DECISION MAKING

Information used in one activity that results in new knowledge will, in turn, be used to guide selection of alternatives in future tasks that involve decision making. Codified rules and routines would be relied on to support evaluation of alternatives and selection of action decisions. Choice of alternatives, and decision outcomes then provide the backdrop upon which sense making, or justification, of decision rationale occurs. Such decision rationale, and its associated sense making can then be codified for (re)use in other contexts, applied to future activities that draw on it to create new instances of knowledge.involve decision making. Codified rules and routines would be relied on to support evaluation of alternatives and selection of action decisions

Chapter 4: Conceptualizing Knowledge Emergence

 GATEKEEPERS, INFORMATION, STARS,AND BOUNDARY SPANNERS

Allen coined the term ‘Gatekeeper’ to describe the information flow stars that he discovered, the heavily connected nodes in the information flow pattern. The reason that he chose that term was that much of the development and project work that he investigated was classified military work, where here seemed to be something of a paradox, how was a team to be successful if it didn’t effectively connect  with the world of information outside the organization? But how did it do that in a classified and communication restricted environment?What he discovered was that theinformation stars, the sociometric stars, were the answer to that paradox; they were the information channels throughwhich external information reached the project team.That rolewas so crucial in the contexts that Allen typically investigated what he termed his sociometric stars “Gatekeepers.” They oversaw and guarded the gates through which external information reached the projects. Indeed, one might say that they were not just the gatekeepers, they themselves were the gates

RESEARCH PRODUCTIVITY AND KNOWLEDGE

The productivity measure was, at base, simply the number of approved new drugs (new drug applications or NDAs) per millions of dollars of R&D budget. This measure, however, was refined by weighting the NDAs in regard to:

1) whether or not the Food and Drug Administration (FDA) judged the drug to be an “important therapeutic advance,”

2) the chemical novelty of the drug, and

3) the filing company’s patent position in regard to the drug, an indicator of where the bulk of the research was done. The study is compelling because of the high face validity of the measure of success, the successful introduction of new pharmaceutical agents, since that is what pharmaceutical companies are about after all, and because of the statistical robustness of the results, a consequence of the fact that the more successful companies were found to be not just twenty or thirty percent more productive than the not so successful companies, they were two or three hundred percent more productive.

LACKOF RECOGNITIONOFTHESE FINDINGS IN THE BUSINESS COMMUNITY

The three most important characteristics are all related to the information environment and information flow – specifically: 1) easy access to information by individuals; 2) free flow of information both into and out of the organizations; 3) rewards for sharing, seeking, and using “new” externally developed information sources. Note the ‘flow in and out’ and the ‘sharing, seeking, and using’. Number six is also information environment related, 6) the encouragement of mobility and interpersonal contacts. Yet in a remarkable oversight, the studies’ authors never remarked on the dramatic win, place, and show finish of information and knowledge factors

COMMUNITY-BASEDMODELS

The Community of Practice (CoP) is not necessarily department-based nor centered in one organization.ACoP can consist of those in chargeof human resources training, for example, in a number of organizations. These HR professionals can share what they’ve learned through experience about effective seminar scheduling and working with speakers. Reading a book about effective HR training is one way to learn, but sharing what experienced trainers know is a whole different level of learning. The Information Systems literature points to an abundance ofKMstrategies in the category of Computer Mediated Communication (CMC). Such systems provide the infrastructure for enabling the interactions needed for a group’s knowledge synergies and interactive activities [Maier, R., 2002] and may include bulletin boards, electronic meeting/conferencing, or online chat.

CONCEPTUALIZINGKNOWLEDGE EMERGENCE

A Group Decision Support System (GDSS) is able to calculate the votes and display them graphically, so that an individual attending the meeting can see if she or he were an outlier on certain issues or to determine where his or her vote stood as compared with peers. Although anonymous, each participant can have a unique code, known only to the participant, and follow voting patterns on the graphic display.These systems work well in a face-to-face situation where immediate feedback can be given and displayed. The GDSS has not migrated easily to theWeb, however, some web-based systems are available and have adapted to an asynchronous situation. Generic Decision Support Systems (DSS) that act more like expert systems with the added feature of suggesting decision options are well suited to the Web, and they are proliferating as the Web becomes the ubiquitous information and communication platform for information storage and retrieval, and for interaction as well.The range ofWeb-basedDSSs vary in quality fromthemundane (e.g., cosmetics or movie choices) to sophisticated tools such as diagnosing illnesses and suggesting appropriate drug therapies.

REPOSITORYMODEL

It is a model that emphasizes the creation of quality knowledge content in online repositories with re-use as a goal.Markus,M. [2001] argues that the purpose and content of knowledge records in repositories often differ depending on who needs the documentation: the content producer, similar others, or dissimilar others. She emphasizes that a great deal of effort is required to produce quality content, and, as such, part of the burden of documenting and packaging knowledge objects can be transferred to intermediaries, saving time and energy of the organization’s staff.