Knowledge management: A re-assessment and case

Knowledge Management: A Re-Assessment and Case

Fred Phillips, Lois Delcambre, and Mathew Weaver

The authors are building a knowledge management system (KMS) for use by several U.S. federal agencies. Its use must harmonize with multiple agency and disciplinary cultures, and also link with the efforts of at least one international agency. In this paper, we present the KMS project's technological contributions and imple- mentation considerations as a case in knowledge management (KM). We link the public-sector case with our assessment of KM's current status and future prospects. We find the challenges for KM's future are in theory, interactivity, integration, the recognition of cultural differences, and the design of marketing programs that respect these differences.

Introduction

The authors are building a knowledge management system (KMS) for use by several U.S. federal agencies. The system must harmonize with multiple agency and disciplinary cultures, and link with the efforts of at least one international agency. This paper relates our efforts to:

1. Effectively integrate the new KMS with the existing tools and cultures of the federal agencies;

Fred Phillips is Research Professor of Management in Science and Technology at Oregon Health & Science University in Portland and a Senior Fellow of the IC 2 Institute at the University of Texas at Austin. His research focuses on technology management and technology entrepreneurship. He can be reached at <[email protected]>.

Lois Delcambre is professor of Computer Science at Maseeh College of Engineering at Portland State University. Dr. Delcambre's research focuses on object-oriented and other database data models. Her address is <[email protected]>.

Mathew Weaver, a doctoral candidate in Computer Science and Engineering at Oregon Health & Science University's OGI School, developed the Metadata++ software discussed in this paper. With Lois Delcambre, he has been exploring models for terms or keywords that are used in a digital library. He may be reached at [email protected].

Knowledge, Technology, & Policy, Fall 2004-Winter 2005, Vol. 17, No. 3-4, pp. 65-82.

66 Knowledge, Technology, & Policy / Fall 2004-Winter 2005

2. Make the new KMS consistent with the state of the art and expected future trajectory of knowledge management (KM); and

3. Leverage the insights and new technologies developed within our project in order to advance KM's state of the art along that trajectory.

These goals drove us to review the history and literature of KM, re-assessing its assumptions and contributions.

The paper begins with a summary of this re-assessment. We trace the pre- dictions and principles put forth by early KM visionaries. We focus on the kinds of knowledge an organization may deal with; the inter-cultural misunderstandings that may result when the desire for better knowledge management is instantiated in prescriptions, theories, and information systems; and the uses to which an organization can put KM and KMS. We then describe the current research project, presenting it as a "case" in KM. We conclude with comments linking the public-sector case with the re-assessment of knowledge management, and speculate on KM's future.

Designing our public agency KMS, we responded to the re-assessment and the look forward in what we hope is an exemplary way, by means of intensive visits with potential users; using information from focus groups and user visits to design the metadata language features and the units of information in the KMS; gaining an overview familiarity with the scientific and policy pursuits of the users; initially circumscribing the user community and metadata command set; and usability studies.

Re-conceptualizing KM and identifying the obstacles to its further development should lead to more effective software systems and management practices in the future. We find the challenges for KM's future are in theory, interactivity, integration, the recognition of cultural differences, and the design of marketing programs that respect these differences and leverage the various cultures' commonalities.

Knowledge Management

"When you talk to a lot of CEOs and you say knowledge management, they're gone. They don't hear you. Yet it's actually a very practical way of doubling your margins," says Ron Ponder, CEO of Cap Gemini Ernst & Young Telecom Media Networks (Pellet, 2002). Perhaps these executives balk because, in the words of Gupta and Govindarajan (2000), "A gap exists between the rhetoric of knowledge management and how knowledge is actually man- aged in organizations."

We ascribe much of this gap to software vendors who, under pressure to sell "not ready for prime time" KMS packages, have not had time to incorpo- rate the best ideas of corporate strategists, corporate librarians, and academics. Gupta and Govindarajan agree, noting that "regarding KM as synonymous with information management ... can result in the profoundly mistaken belief that the installation of a sophisticated IT (information technology) infrastruc- ture is the be-all and end-all of knowledge management. Effective KM depends not merely on IT platforms" but primarily on the social structure of an

Phillips, Delcambre, and Weaver 67

organization. This structure, according to Gupta and Govindarajan, includes culture, information systems, reward systems, processes, people, and leader- ship.

Given the well-known difficulties of implementing enterprise-wide software, it is not surprising that making KMS comprehensive and ubiquitous in an enterprise has not been easy. Said one executive whom we interviewed for this project, "I personally do not give much credit to some KM authors, mainly because they are touching different parts of an elephant, and claiming they know everything about corporate management through [the lens of] KM."

Not atypically for a new business idea, knowledge management has gone through phases that may be characterized as Trend-Spotting, Pontificating, Commercial Hype, Disillusionment, and (currently) Re-Assessment,: By 1990, it had become evident to leading thinkers that knowledge was a key asset for businesses seeking new markets, new technologies, new organizational forms, and better customer relationships (Drucker, 1998). A spate of articles in the Harvard Business Review outlined the business potential of managing knowledge assets. The next decade made it clear that knowledge comprised a great deal of the value in every new product (Phillips, Ochs et al., 1999); by 1999, Fortune magazine reported that what companies knew was worth an estimated three to four times the value of their capital equipment, inventories, and real estate combined (Stewart, 1994). KM software became a staple in the information systems marketplace. Generally speaking, however, the software was not based on widely appealing principles of epistemology, organizational behavior, system integration, or return on investment. Sales of knowledge management systems (KMS) slowed, and businesses became skeptical about its value.

It seemed to us a good idea, especially in light of our own current project in public-sector KM, to take stock of what has been learned, and chart an ad- justed future course for knowledge management. Some additional statistics from Smart Business magazine (Editors, 2002) will help set the stage:

�9 "96 percent of business people surveyed were frustrated by their companies' information management processes."

�9 "85 percent of a company's knowledge assets aren't in the relational database that runs major enterprise applications."

�9 "Knowledge workers spend 30 percent of their time looking for information."

Since the inception of the knowledge management movement, new discov- eries have shown that there are different kinds of knowledge and intelligence, different cultural "takes" on knowledge and communication, different levels at which KM can be applied, and other corporate information systems with which KMS must be integrated. We discuss each below. It becomes clear that the early visionaries of KM (academics and corporate laboratory executives) had a great impact on the course of developments. It is equally clear that, while prediction errors are expected and in no way detract from the visionaries' contributions, they were wrong or contradictory about many of the pre- dicted details, and were also in error about the place of KM in the ecology of ideas and business practice.


Kinds of Knowledge: Implications for Organizations

One of the most prominent visionaries, Ikujiro Nonaka (1998), remarked that an organization wishing to create market opportunities "depends on tap- ping the tacit and often highly subjective insights, intuitions, and hunches of individual employees .... " The notion of tacit knowledge was vague yet appealing, a perfect candidate for becoming a buzzword. Indeed, "Tacit" became the name of a software company several years later, and the word has been used indiscriminately in articles and advertisements.

Barquin & Associates distinguish tacit knowledge from explicit knowledge, using the language in the captions of Figure 1.

Tacit knowledge, however, is not just in peoples' heads. It is also in their muscles, and in the ways that group cultures spontaneously arise when teams form and work together. In the next section, we will explore some of the other difficulties caused by the concept of tacit knowledge.

Zacks (1997) introduced the idea of "authorized" and "unauthorized" knowledge. Authorized knowledge might include the consultant's study that recommended the location for the company's headquarters. It would be "unauthorized" to know that the company located where it did simply because it's an easy commute for the president. The latter information won't appear on the intranet, but hearing it via gossip helps employees feel like well-informed insiders. Another example: One of the present authors attended a meeting in which a department head said, "Yes, I 've seen the organization chart, but I want a chart of who has the power to do what." It is the rare company, one would imagine, that would put such a chart in its KMS.

It is not difficult, as Krackhardt and Hanson (1993) demonstrate, to build charts of intra-organizational patterns of communication, or even patterns of

FIGURE 1

Kinds of Knowledge

(a) Tacit: In peoples' heads (b) Explicit: Books, videos, paper, databases, etc.

Source: Barquin, Bennet et al. (2001).


trust. Our customs and laws concerning privacy govern the kinds of personal and inter-personal information that we post to the nets and the KMS. These laws differ by culture and by country, but even within U.S. commercial culture, we are still sorting them out. For example, a credit agency's site tells who owes money to whom, but if a creditor posts fraudulent data to the site, the creditor, the agency, and the agency's ISP (Internet Service Provider) may all be liable.

Zacks' (1997) publisher notes, "Nothing fascinates so much as the subver- sive, the contrarian, the suppressed, and the bizarre." Even staid daily newspapers feature some material of this type. 3 It is hard to imagine a user (as our department head illustrates above) being fully enthusiastic about a KMS that does not feature unauthorized information, and perhaps equally hard to stay on the right side of the law when the KMS does include such information.

The concept of unauthorized knowledge helps explain the failure of shrink- wrapped or enterprise software to fulfill the promise of knowledge management. Nonetheless, according to the editors of Smart Business (Editors, 2002), firms are now putting their faith and dollars into further automation developments: software that indexes unstructured documents; software that matches company experts with other employees' problems; and enterprise portals.

Drucker (1998) saw the information-based organization as a fundamental shift to a fourth stage in the evolution of corporation, following the move to professional management and the later shift to a command-and-control mode of corporate management. He remarked that the corporation of the future will resemble a "hospital or university or symphony orchestra ... knowledge-based, an organization composed largely of specialists who direct and discipline their own performance through organized feedback from colleagues, customers, and headquarters."

Drucker contrasts these feedback mechanisms with the earlier corporate model of command-and-control. With hindsight, we can say that the fast companies of the 1990s did resemble these institutions in their need for collegiality and their respect for knowledge. They closely resembled hospitals and performing orchestras in their need for and use of speedy feedback, and in their unforgiving environments, in which mistakes are glaring and costly. They most closely resembled hospitals in their investments in information technology. In contrast, universities remain paragons of collegiality while still react-

TABLE 1

Examples of Four Kinds of Organizational Knowledge

Authorized Unauthorized

Explicit Template tbr an Who owes favors expense report to whom

How to operate the Where, how hard to hit Tacit cranky copy the coffee machine to

machine make the cup appear


ing slowly to external events, and have concentrated IT investment in customer service-related systems rather than internal KM.

Drucker also maintained that "information based organizations ... require clear, simple common objectives that translate into particular actions. At the same time . . . . information based organizations also need concentration on one objective, or at most, on a few." This was a curious assertion, given the multiple constituencies and multiple business lines that hospitals, universities, and symphonies engage. In fact, as reducing all these imperatives to a single objective seemingly must involve monetizing them, the fall of the very information-based Enron illustrates the hazard implicit in Drucker's statement.

Cultural Misunderstandings: The Varieties of Knowledge, Education, and Management Styles

A reviewer (Collins, 2002) paraphrases engineer/memoirist Henry Petroski's description of his childhood job: "Learning how to fold the newspapers and cram them into a canvas bag took him weeks of effort, rendered all the more frustrating in that it was essentially unteachable. No matter how much veteran newsboys tried to show him the folds, Petroski was left with the realization that the only way anyone learned was by doing."

Is newspaper folding "tacit knowledge"? A useful further distinction would be between:

�9 Knowledge that can be articulated but isn't (or isn't yet, possibly because employees do not know how to articulate it), and

�9 Knowledge which cannot be transmitted via symbols--like how to ride a bicycle.

Both are in counterpoint to "explicit" knowledge, which has been articulated in symbols. Table 1 could be expanded accordingly.

This distinction goes to the heart of what the European tradition considers liberal education, as distinguished from vocational training. The ideal of liberal education puts a high value on learning to articulate (in words or math- ematics) things that had been unexpressed or considered inexpressible. Other kinds of knowledge (when acknowledged at all) were called vocational, ath- letic, mystical, or craft.

Nonaka's (1998) seminal knowledge management article urged U.S. companies to adopt the creativity and knowledge-sharing practices of Japanese firms. He tells the story of Matsushita Corp. capturing the "tacit" skill of a baker at the Osaka International Hotel in order to program the Matsushita home bread-making machine. Nonaka uses the word "craft," referring to the baker's skill. While today's U.S. companies engage their employees in creativity, visualization, and meditation training--activities outside the classical Western definitions of knowledge- -Nonaka may have confused matters in 1991 by failing to recognize what Westerners perceived as the boundary between knowledge and craft. 4

Nonaka wrote, "the knowledge-creating company is as much about ideals as it is about ideas. And that fact fuels innovation." Ideals were and are not


alien to U.S. organizations. Almost all include a vision or values statement in their strategic plan. In particular, Collins and Porras (2001) cite Merck, Johnson & Johnson, and Hewlett-Packard for their vision and their dedication to prin- cipled action. The value of Nonaka's idea is that while a strategy statement can put blinders on an organization, it should, instead, "re-create the company and everyone in it in a nonstop process ... of self-renewal."

While Nonaka was incorrect to imply that U.S. companies pay no attention to creativity, he correctly pointed out that principles of creativity are not row tinely applied to organizational design and renewal except in the most inno- vative U.S. companies. An example of the latter might be Nucor, whose successful experience with knowledge management is documented by Gupta and Govidnarajan (2000).

Uses of Knowledge Management

Kleiner and Roth (1998) aptly note, "Managers have few tools with which to capture institutional experience, disseminate its lessons, and translate them into effective action." This is as concise an objective for KM as we could hope for.

They go on to say, "People in organizations act collectively, but they learn individually. That is the central tenet--and frustration---of organizational 1earn- ing today." This, though, isn't true. Argote and Epple (1990) noted that organizations seem to learn (e.g., continuing to reduce the unit cost of manufactured goods) even after skilled people leave the firm. The only possible conclusion is that workers teach each other, and that this teaching and learning is some- times implicit and invisible--tacit, if you will.

Kleiner and Roth advocate the use of "learning histories," collaboratively authored narratives of project successes and failures. They point out that working together on these histories builds trust among members of an organiza- t i o n - b u t also allow project participants' anonymous comments, and it is difficult to see how the latter can build trust.

We can discern at least four levels of application for KM, and seeming contradictions in the early writer's recommendations may be due to confusing the level of application that is addressed. The levels are:

1. Supporting the individual initiatives of constituents; 2. Supporting project collaboration; 3. Creating and sustaining the learning organization; and 4. Automated decision making.

Each of these is explored below.

Individual Initiatives

Libraries muster automated catalogs, inter-library networks, web access, and networked printers to enhance the ability of customers to find and publish information. Universities do this and more (Steinberg, 2002), automating

72 Knowledge, Technology, & Policy I Fall 2004-Winter 2005

course advising and registration, student financial aid, and so on. Universi- ties, however, generally leave the development of their internal knowledge workers (i.e., the faculty) to the traditional mechanisms of learned conferences and journals.

Health care companies provide personal web pages on which patients may track their treatments, diets and prescriptions. Banks put educational items on their password-protected sites, augmenting the account activity data that customers may access for "online banking." The health and banking sites may be linked to the companies' customer relationship management (CRM) databases, providing information that can be used for marketing purposes.

Collaboration

KM may also aid ad hoc projects, with shifting project team membership. Quinn, Anderson et al. (1998) note that at Merrill Lynch, employees readily use ad hoc networks for projects, because their compensation is tied to peer review of team behavior. The Merrill Lynch portals include databases, ana- lytic models, and communicat ion power beyond what employees can easily find elsewhere. While this level of KM application does not attempt to achieve the total "learning organization," it may reveal information that can support other efforts toward building such an organization. Brown (1998) and Quinn, Anderson et al. (1998) show that the success factors for project-level KM are usability studies and user incentives.

Brown maintains corporate research should create not just new product and manufacturing process knowledge, but also new knowledge about the work- ings of the organization. He articulates Xerox's new (as of 1991) principles:

�9 Research on new work practices is as important as research on new products. �9 Innovation is everywhere; the problem is learning from it. �9 Research can't just produce innovation; it must "co-produce" it. �9 The research department's ultimate innovation partner is the customer.

Brown says, "At PARC, we 've only begun to explore the implications of these new principles ... without giving up our strong focus on state-of-the-art information technologies, we are also studying the human and organizational barriers to innovation."

A figure in (Brown, 1998) displays Xerox's procedures for group-collaborative problem solving using these principles. Brown also tells a story about the importance of usability studies in sales of advanced Xerox copiers.

The late 1980s and early 1990s saw many conferences and publications on (pre-WWW) computer support for collaborative projects. See e.g., Ellis and Malmquist (1992) and other articles in Phillips (1992).

Learning Organization

Garvin (1998) tells us what a learning organization is: "A learning organization is an organization skilled at creating, acquiring, and transferring knowl-


edge, and at modifying its behavior to reflect new knowledge and insights." Nonaka describes what a learning organization does: In a knowledge-creating company, "inventing new knowledge is not a specialized activity ... it is a way of behaving, indeed, a way of being, in which everyone is a knowledge worker."

Garvin points out that the directions indicated by Drucker and Nonaka are appealing but that the latter two authors provide no operational guidelines. Garvin thinks the three activities leading to a learning organization are:

1. Meaning (a definition of learning organization that everyone in the organization understands)

2. Management guidelines for practice 3. Measurement. Metrics for assessing performance.

He does not, oddly, mention information systems. Throughout the literature of KMS and learning organizations, it is clear that

users need not only just-in-time access to facts, data, and expert answers, but also just-in-time access to courses and teachers. Both kinds of content com- prise "knowledge transfer."

Automated Decisions?

A possible fourth level of KM is totally automated decision-making, an area fraught with its own epistemological problems. Data mining procedures can find variate relationships in a customer database. These relationships may be ephemeral, as well as undecidable in the sense of Fisherian hypothesis testing, which was the basis for scientific epis temology throughout the twentieth century. Nonetheless, a short-lived and uncertain pattern may be commercially exploitable if a supply-chain command or a direct-mail marketing piece is issued immediately--and the computer may do this without human intervention. For example, "noticing" that for the past few days red widgets have been selling much better in the east, while western buyers are going for the blue ones, the computer can change shipping orders and mani- fests on the fly, better satisfying the market and increasing profit margins. It does not take much whimsy to wonder, when a database detects a variate relationship and there is no one there to apprehend it, whether it makes knowledge.

A Knowledge Management Case Study

A research project currently underway aims to provide access to documents of the U.S. Department of Agriculture's (USDA) Forest Service. The project is funded by the Digital Government Program at the National Science Founda- tion, the goals of which are to partner traditional computer science researchers with "forward-thinking government agencies to explore and develop new information technologies that will improve the way the government serves the American people. ''5

74 Knowledge, Technology, & Policy l Fall 2004-Winter 2005

This project is a knowledge management project in three important ways. First, it provides access to documents which represent both explicit, factual knowledge and judgments. Second, it provides access to that knowledge as it grows. Third, as the system captures knowledge it alerts the searcher that "we know that." An example of this last point: we know that ferns occur on ultramafic soils. And we know that serpentine soils are ultramafic. These relationships are known to the system, enhancing users ' searches for re levant knowledge.

"Agency-approved documents" such as Environmental Assessments, No- tices of Decision, Appeal Decisions, and so forth provide the tangible record of the scientific, intellectual, and administrative work of the Forest Service and related agencies, including the Department of the Interior (USDI) Bureau of Land Management and the USDI Fish and Wildlife Service. The primary purpose of the system we are building is to provide easy access to these documents for natural resource managers in these agencies. Our approach is to use an extensive set of controlled vocabularies containing appropriate, descrip- tive keywords ("terms") for these documents, along with relationships among these terms. The terms and their relationships are represented in a system called Metadata++ (Weaver, Delcambre, and Maier, 2001). Metadata++ is a knowledge base in its own right, and is available to users for browsing, both to find documents of interest and also to learn more about the scientific and other domains relevant to natural resource managers.

Metadata + +

Even more difficult than representing organizational knowledge in machine- readable format is the problem of getting individuals within an organization to agree on what knowledge should be represented. Our project addresses this problem by allowing each agency to use its own knowledge. For example, the USDA Forest Service and the USDI Bureau of Land Management (BLM) use different sets of words to describe roads and highways. Instead of forcing the agencies to agree on a common vocabulary (a difficult task indeed), Metadata++ represents both vocabularies. Because multiple vocabularies are used to represent similar concepts, users can search for documents based on their own knowledge terms.

Metadata++ provides functionality similar to a thesaurus. Words or phrases (called terms) within a vocabulary are related hierarchically. This hierarchy generalizes various relationships, including broader/narrower terms (such as "Wenatchee National Forest" and "Cle Elum Ranger District") and taxonomy. The second type of relationship is synonymy--used to relate similar terms. For example, the common name "White Cedar" is often used in place of the scientific name Chamaecyparis lawsoniana. Synonymy is also used to relate road and highway terms from the different Forest Service and BLM vocabularies.

In addition to hierarchy and synonymy, Metadata++ supports associations between terms. An association represents any functional or observational cor- relation between terms. Suppose that organizational knowledge includes the


FIGURE 2

Terms within a Vocabulary Are Related Hierarchically in Metadata++.

Insects and Diseases ~ Species ~] Insects and Disease Management

- Wildlife

Wildlife Habitat

Wildlife Species

~quatic @iology

~: Wetlands

+ Range

+: Ecology

Ecosystem Management

' Recreat ion

- . Water

+: Water Terms Air

- S o i l

Soil - Orders, Sub-Orders and Great Groups

~i. Soil - Subgroups +ii. Soil - Families "~'i Oregon Soil Families

~ i ,Oregon Soil Series

observation that Western Hemlock trees commonly grow in arid climates and dense soils. Metadata++ captures this observation when the user creates an association between those terms. This association can then be exploited as users search for documents.

By capturing terms and relationships specific to each agency, Metadata++ provides a knowledge framework that is used for finding documents. Instead of a t tempting to represent a single view of organizational knowledge, Metadata++ allows individuals and agencies to add terms, relationships, and documents. The relationships among terms allow users to find documents from multiple agencies without requiring agency-specific knowledge.

Observations

The primary unit for our project, the "agency approved document," is no- table. Documents, whether simple, two-page summaries of the results of a particular treatment regime for riparian vegetation or Environmental Impact Statements consisting of hundreds of pages, have traditionally received little attention 6 within these agencies in terms of their relationship with information technology. They are produced using word processing software and are some- times posted to the Web, but they are not uniformly or systematically made accessible to other natural resource managers. Metadata++ is addressing the problems of how properly to describe these documents (by associating useful metadata) and how to help users find these documents.

These documents are produced as part of the normal flow of work in the Forest Service; the procedures encourage proper documentation of the scien-


tific investigation and the consideration of issues of importance to various constituents. Current USFS procedures also facilitate interaction with the public throughout the process, in various ways. Thus the documents are produced and used through the life of a project but are not necessarily available to other natural resource managers facing similar situations and addressing the same issues. Furthermore, once the project is completed, the supporting documentation is archived and generally not available for re-use, except with some effort and by people who know to look for it. Current practice uses informal means to access relevant documents; Forest Service staff may know about a project and call a colleague to try to get access to documents, for example.

These documents represent the intellectual and scientific contribution of the agency. We know they could be of more value if they were routinely findable. In addition, these formal documents are supported by less formal scientific documents about surveys, inventories and administrative studies, each of which represents invaluable agency knowledge that is usually not passed on to peers.

USFS project work is almost always interdisciplinary, involving wildlife biologists, fish biologists, vegetation specialists, forest management specialists, and so forth. Often the project work involves collaboration among federal, state, and local agencies. This is particularly true in the Adaptive Management Area program, in which the Forest Service, and Bureau of Land Management, and the Fish and Wildlife Service share administrative control over specific areas of land set aside to support adaptive (experimental) management. The Adaptive Management Area program is the focus for our pilot project. As the agency-approved documents are almost always produced collaboratively, our project does not focus on documenting the collaborative process, but rather on making these collaboratively produced documents available to collaborative teams.

Much of the (collaborative) work involves information-intensive tasks. New documents are created that must synthesize and excerpt a large set of related documents, e.g., from earlier or similar projects or from background documents for the particular USFS project. This kind of extraction and manipula- tion of information from a wide variety of base sources provides an opportunity for new research in information technology and may provide new benefits for knowledge management.

The Forest Project in the Context of KM

The forest KMS project (Landis, Banga, et al., 2002) stops short of attempt- ing to re-make the culture of entire organizations, focusing instead on providing researchers and policymakers access to studies and to each other, in an attractive and non-threatening way. Tolle, co-director of the project, believes KM at the project level will not only provide the missing capacity for a shift in culture but will provide the engine to drive this cultural change. Thus, the forest project supports the first two kinds of KM: individual constituents and team projects. We hope it lays the groundwork for eventual emergence of


learning organizations among the agencies involved, though that is not an explicit goal of the project in its current phases.

Members of our team have conducted user surveys and preliminary usability studies (Banga et al., 2002) more intensively than comparable prior projects have done. This activity has captured a great many data on agency culture, terminology, and information needs. Other team members are specialists in organizational behavior and development, better integrating the IT effort with the expected usage culture in the client agencies. Researchers in the agencies will be able to post judgments and commentaries as well as draft and peer- reviewed articles, enriching the information available.

After much debate it was decided not to allow uncontrolled comments from the public to be posted on the forest KMS. Among agency users, gossip and other unauthorized information is neither prohibited nor expressly encour- aged.

The project revealed areas of tacit knowledge, for example, techniques for collecting samples in streams. As researchers find other KMS users with similar interests and pursuits, and become acquainted, we hope the sharing of such tacit knowledge will occur as an indirect result of the system.

In summary, the forest KMS project faces many cross-cultural issues. Users will represent multiple agencies, scientific disciplines, national origins, professional cultures (IT vs. managerial, for example), and institutional (USDA, USDI, academic, congressional policymakers, etc.) cultures. The team has done all that is possible within the project resources to identify, structure (Drake, Koch, and Steckler, 2003) and address these issues. Internationally, the team has maintained liaison with the GFIS (Global Forest Information Service), under development by IUFRO (the International Union of Forest Research Organizations). 7

Connecting Institutional Knowledge and Management Information Systems: Where Knowledge Management Will Go Next

No doubt much has been missed in this survey of the foundations of knowledge management. The literature in 2004 is massive and daunting, much of it just cheerleading for KMS software, the limitations of which we have already noted.

The challenges for KM's future directions are in theory, interactivity, integration, the recognition of cultural differences, the design of marketing programs that respect these differences, and the development of a critical eye that sorts the KM hype.

Cultural Differences

Relevant cultural differences appear across national and regional bound- aries (like those evinced by Nonaka, as well as many and varied other histori- cal views of rational, intuitive, authoritative, etc., knowledge), between philosophers within the Western traditions, and across generations of workers. There is and will continue to be push-back against KMS from those who


have legitimately different cultural and philosophical viewpoints, from those who are skeptical about distance learning, from those whose jobs may be endangered by codifying their knowledge, and from those with other narrow agendas. This argument is to be welcomed, as it forms the dialectic that will create the future of KM. It is also grist for the wiser marketing strategies that will bring the benefits of improved KMS to users of the future.

Reviewing Hubert Dreyfus' On the Internet, Michael Arnone (2002) paraphrases Dreyfus as follows: "One of the premises of distance education on the Internet is that people can learn without being physically present with their teacher or fellow students. That assumption is a modern legacy of the philoso- phy of dualism espoused by the Greek philosopher Plato and the 17 th century French philosopher Ren6 Descartes." Nietzsche and Kierkegaard argued that the body plays a crucial role in learning, providing the "emotional investment and visceral connections that come only from actually being somewhere and doing something." In the twentieth century, Heidegger and Merleau-Ponty agreed with Nietzsche and Kierkegaard (Arnone, 2002). "Ultimately, physi- cal presence and action are the only ways we have to acquire skills, learn what information is relevant, know reality, and have meaningful lives."

Dreyfus is taking the "cyberspace" metaphor too seriously. He should real- ize there are big markets for instructional yoga videos, web sites about salsa dance steps, and books on how to play the piano. Nonetheless, he makes the good points that all knowledge is to some extent body-based, and that com- puterized instruction may not transmit tacit knowledge effectively. There is a constructive role to be played, however, by computer-aided instruction. Brown (1998) agrees: "It's never enough to just tell people about some new insight ... it ... requires creating new communication techniques that actually get people to experience the implications of a new innovation (sic)."

The expert systems to which KMS owe some filial respect often focused on capturing the knowledge of the OLE, the "Oldest Living Engineer." Today and in the near future, we may expect more push-back against knowledge management as baby boomers react against age-related job discrimination and view KMS as a way to replace them cheaply (Powell, 2002). This can be remedied at least in part by portraying KMS not as a cortical dump, but as a network connecting older workers to others who will appreciate their exper- tise and perspective.

Theory

McKellar's (2001) statement that "As local knowledge initiatives are integrated or consolidated, different cultures can collide" is one that we agree with, and that leads to the topic of integration. The many areas of KM discussed in this paper are summarized in Figure 3. The figure highlights the risks of piecemeal implementations, the potential of integration of KMS across organizational functions, and, perhaps, one frame for a theory of KM.

Like expert systems and computer-aided cooperative work, decision support systems (DSS) are part of the pre-WWW lineage of KM. While DSS were less networked and less interactive than KMS, they led to one insight (Phillips,

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1986) that is yet to be applied to KMS, namely, that theory is an essential success factor. There was never a general theory of DSS. Rather, it became evident that, e.g., a marketing DSS was most useful and efficient when queries went through a theory layer. The marketing DSS described in (Phillips, 1986) used the purchase frequency distribution as the fundamental grammati- cal unit for queries; the algebra of discrete distributions became the grammar relating these units. The DSS was therefore intelligible to marketing profes- sionals; queries were guaranteed to be somewhat sensible and meaningful; and detailed programming of unprecedented query types was kept to a mini- mum. 8

Stankosky (2001) remarks that "We still have no theory of knowledge management." One can foresee that, as with DSS, domain-specific theories will prove both feasible and highly useful before a general KM theory emerges. 9 These theories will lead to KMS that:

�9 Deliver knowledge (facts, opinions, courses, analyses and reports, news, etc.) to employees where and when needed, leading to rapid identification and exploita- tion of market opportunities, and reducing inefficiency and duplicated effort.

�9 Provide a coherent but flexible framework for queries. �9 Provide sufficient unauthorized knowledge and "wild card" data to encourage use

of the KMS and to spur creativity among users. �9 Support the fluid formation of communities of practice and mentor relationships,

while allowing a measure of centralized review or control. �9 Support all four levels of KM (individual, team, learning organization, and auto-

mated decision making), providing useful audit trails for automated decisions. �9 Deliver an efficient and enjoyable experience for external customers, and �9 Do all of the above through an interface that is sensible and attractive for users of

diverse national, linguistic, and agency cultures.

The Forest Portal makes a start on these by virtue of the interdisciplinary (Management, Marketing, Computer Science, and Environmental Science and Engineering) composition of the research team. This composition eased tech- nical communication with the user community and allowed the KMS to harmonize with the community's aims and usage patterns.

Marketing and Adoption

McKellar (2001) remarks, with reference to total-enterprise KM, "KM is not a stand-alone project--has to be woven into the very fabric of the organization. So, executives must actively encourage and facilitate knowledge initiatives throughout all the enterprise's units." Top executives do not have time to personally champion every good idea that comes along. More sophisticated marketing would serve these ideas--and the consultants who push them-- better than plaintive pleas like McKellar's.

Szulanski (1996) notes the major barriers to internal knowledge transfer include "the recipients' lack of absorptive capacity, and a [possibly] arduous relationship between the source and the recipient" of the knowledge. This is a challenge for the development even of domain-specific KM theory, because it


means k n o w l e d g e t ransfer act iv i t ies m a y not be repl icable ; they depend on personal i ty types and perhaps even on specif ic individuals . Meanwhi le , KM must rely on the creat ivi ty of individuals, and provide informat ion to support that creativity.

T h e a f o r e - c i t e d Smart Business ar t ic le (Ed i to r s , 2002) quo t e s F r a n c e s Cairncross , m a n a g e m e n t edi tor o f The Economist, who "sugges ts d iscarding as much information as possible by figuring out what you really need to know." We bel ieve , on the contrary, that it is the unexpec ted demand on knowledge that tests the c rea t ive success of the learning organizat ion. Moreover , m a n y gems of knowledge are lost now, and stopping this drain will improve produc- t ivi ty and the quali ty of dec is ion-making .

The technology execut ive we quoted earl ier concluded, " K M is b e c o m i n g a mo t iva t iona l s logan for k n o w l e d g e sharing, IT por ta l r enova t ion , shar ing ideas th rough story tell ing and bra ins to rming , and documenta t ion , " It is the task o f the K M S bui lders , he adds, to p rov ide the inf ras t ruc ture to suppor t these largely social activities. This is our a im in the forest K M S project.

Notes

1. This research was supported by the National Science Foundation under Grant No. 9983518. The authors wish to acknowledge the contributions of "Forest Team" members Balbinder K. Banga, Marianne Koch, Eric Landis, David Maier, Nicole Steckler, Patricia Toccalino, and Timothy Tolle.

2. These stages result in a "humped" or interrupted sales growth curve, typical for products based on advanced technologies (Phillips, 2001). The Gartner Group co-opted this lore, dubbing it the "hype curve."

3. Viz., "The Edge" column in The Oregonian. This daily newspaper column specializes in the bizarre, the gross, and the questionable.

4. Indeed, his example of the design of Honda's Tall Boy city car, in which designers were given free rein to think divergently, is a red herring. Product designers have never relied totally on explicit knowledge, and in fact may be the best practitioners of blending the arts and engineering. Nor does Honda's 1978 "evolution of the automobile" slogan appear (to an American academic) quite as creative as Nonaka makes it out to be. Nonaka praises Honda's team for blending the disparate ideas of mechanical devices and organic evolution, and for responding to an admo- nition "Let's gamble" from top management. "Artificial life" had been a well-established concept for some years (see, e.g., Conway, 1976), and the idea of computer-generated organic form had been published in academic journals. Putting the idea into industrial practice at that time may have been bold, but hardly out-of-the-box. Similarly, viewers of recent television ads know that Volkswagen claims creative use of the "sphere" as a creative metaphor in the bug car, and furthermore Time magazine (5 August 2002) reports Honda is imitating many design elements of the VW Passat.

5. <www.digitalgovernment.org> 6. Much more attention and technology has been devoted to geographic information systems (GIS)

data and scientific datasets, e.g., to provide FGDC (Federal Geographic Data Committee) metadata. See <www.fgdc.gov/metadata/metadata.html>.

7. Although the thesauri can support multi-lingual capability, we are not utilizing that feature at this time.

8. This "theory layer," of course, was not a complete theory of consumer behavior, but rather just the vocabulary and grammar shared by the partial theories that were current at the time and useful for a query system.

9. See <km.gwu.edu/km/index.cfm> for updates on the work of Stankosky's KM research community at George Washington University.


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Knowledge management: A re-assessment and case

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