Knowledge Management

Knowledge management is strategic information management.

—Don Marchand and F. Horton, Infotrends, 1986

In my profession, Watson, all sorts of odd knowledge becomes useful, and my room is a storehouse of it.

—Sherlock Holmes, The Adventure of the Three Garridebs, 1925

Knowledge management is the art of managing corporate memory, the craft of keeping up the company's filing cabinet. As a strategic form of information management, it represents information technology's latest gambit in its self-transformation from backroom support function to front-office strategist. Deploying enterprise-wide databases for the rapid storage and retrieval of intellectual capital, best practices, and mission-critical information, "knowledge management" captures, classifies, and indexes strategic information for use by all employees. Common everyday examples of knowledge management include staff directories on Web sites, "frequently asked questions" on tech-support Web sites (FAQs as knowledge base), and Amazon.com's pop-up lists of "related books you might be interested in."

Knowledge management is an integrated, systematic approach to identifying, managing, and sharing an enterprise's information assets, including databases, documents, policies and procedures, as well as previously unarticulated expertise and experience held by individual workers.

—U.S. Army Report, 1999

Convergences: Knowledge Objects and Learning Objects

Evolution of Ask-the-Expert Systems

• Artificial Intelligence: Expert Systems, 1980s

• Electronic Performance Support System: Online Help, 1990s

• Knowledge Management Systems: Knowledge Objects, 2000s

At a time when HR departments are transforming themselves from bureaucratic training units into cutting-edge performance consultancies, IT departments, similarly, are shifting from sheer data-entry centers to knowledge strategists. The new roles reflect broader concerns, including a focus on company-centered performance. As training courses are being broken out into small chunks of performance support (learning objects), IT departments are redesigning their databases as "knowledge management systems," and chunking them into what they call "knowledge objects." A grand commingling of HR and IT is taking place at the level of data and information. Their mutual interest is obvious: Learning objects stress reuse of content pieces within curriculums, knowledge objects emphasize reuse within the organization. As databases become knowledge bases and thus a platform for HR's course-ware, both sides will benefit.

Backgrounds: Lessons Learned

Knowledge management has a long history. As early as the 1960s, AT&T's research arm, Bell Labs, had come up with a paper-based prototype for a knowledge management system (see Fastpaths 1999, Jack Gordon). Upon completion of a project, the project leader would write up the "lessons learned" and file these in a central index, a hardcopy database. Before starting a new project, the new project leader would review the database for any relevant past project reports and apply these to the new project. Personal knowledge sharing was also encouraged. In fact, line worker project leaders were encouraged to ask specialists within the company—even Nobel Prize laureates—for help. Through this company-wide knowledge sharing system, Bell Labs was able to maintain a competitive edge in research and development for decades.

Beyond Industrial Age "Warehousing, Mining, and Drilling"

I've come to the conclusion that the most concrete thing in the world is information.

—Edward Fredkin, digital physicist, 1986

The very metaphors tell a story. In the beginning, IT managed data (raw facts, or literally, "what is given"). It moved in a world that still lived in the industrial age, with its metaphors of data "mining, warehousing, and drilling down." In its most recent incarnations, however, IT is decking itself out with more appropriate information-age metaphors—such as knowledge discovery, knowledge sharing, and knowledge management.

Organizational Challenges

The challenge for knowledge management will be less technological than organizational. For knowledge management requires the partnering of different departments. One typical example would be the partnering of a line unit such as sales and marketing (for content) with information technology (for deployment) and with human resources (for information design). Moreover the well-designed and well-maintained knowledge management database requires at least three experts on staff: a content expert, a database designer/programmer, and a learning designer. Such interdepartmental collaboration and cooperation will come about only if these departments leave their egos outside the meeting room door.

A Four-Step Model

Miss Lemon's private thoughts and dreams were entirely concentrated on a new filing system—which she was slowly perfecting in the recesses of her mind.

—Agatha Christie, The Labours of Hercules, 1947

Knowledge management generally follows a four-step process:

1. Gather Existing Documents and Document Undocumented Knowledge. Existing documentation could include HTML, Word, PDF, PowerPoint, or Excel documents plus e-mails and attachments. It could also include white papers, industry reports, corporate libraries, and Web site links, as well as—and this is the most difficult process—the documenting of (orally circulating) best practices, procedures and processes, tips and tricks, and any competitive information.

2. Organize Information. This step is crucial: Here raw information is turned into "knowledge." The first step is to create an outline, taxonomy, or knowledge-map, which classifies document content into categories. This phase can become as technologically complex as one wishes, including the use of a text-search engine deployed for key-word searches (an automated "spider" crawling through all company documents and servers to retrieve information) or the utilization of taxonomy software to categorize documents. And finally, the content must be chunked and grouped and cross-indexed into a multi-level Knowledge Web.

3. Design Interface. An absolutely key phase, for without a userfriendly interface, the new Knowledge Web will not be used, no matter how sophisticated the relational database is.

4. Update System on a Real-Time Basis. In their forecasting process for knowledge management systems, organizations often overlook the sizable expense of this final step, which amounts to a permanent operating expense. Maintenance of the system involves more than a database administrator and tech support for staff. It includes additional staff who will carry out the daily capture, updating, revising, editing, formatting, resorting, and re-linking of the new information that will flow in, making sure this is cross-referenced to the old and ensuring that the navigation system continues to function properly with any new content categories. Content experts must be on staff to qualify the new content, and users to tag it in terms of on-the-job criticality. If compliance or standards documents are involved in the knowledge base, expensive content experts or even lawyers must be allocated to the project and process as well. As we said in the beginning, knowledge management, if more than company phone numbers and FAQs, can be an expensive business.

The Challenge of Capturing Tacit (Undocumented) Knowledge

We know more than we know we know.

—Michael Polanyi, Personal Knowledge, 1958

If a man reaches the top, he's not going to tell you how he really got there.

—Senior executive of large U.S. corporation
(from Vance Packard, The Pyramid Climbers, 1962)

Like any new discipline, knowledge management faces its challenges. Part of its vision, for example, is to capture and disseminate oral or "tacit" knowledge. Tacit knowledge (literally "silent" knowledge) is knowledge that has not yet been written down by the company, and which circulates orally throughout the organization. Such information is colloquially referred to in organizations as tribal knowledge, voodoo, folklore, or just old-fashioned tips and tricks. Whatever it is called, it is transmitted through the media channels of the water cooler and hallway talk, and its content can range from typical shortcuts or rules of thumb (heuristics) to innovative processes and in-house trade secrets. The assumption of knowledge management is that if all this valuable information and know-how can be written down and indexed (metatagged), a powerful new performance support system or knowledge engine will be created.

This is absolutely true. But before performance consultants launch into documenting worker shortcuts and innovations company-wide, a number of troubling questions have to be answered. First, are company employees willing to divulge their tricks of the trade for company-wide distribution on a public database? "Job security," through withholding key information, is a customary strategy in almost all organizations and professions. Not only are positions and promotions in the company at stake, but employees also fear being replaced by cheaper and/or younger labor once they have divulged all their trade secrets and these have been printed out on a mass basis as company job aids. In some assembly-line manufacturing plants where the machines are computerized, management is trying to do an end-run around this problem by setting the computerized assembly-line to automatically record each motion the workers make, so that the time-and-motion workers' best practices are automatically (and sometimes secretly) recorded in a database. Digital Big Brother is watching in some plants.

Other questions also arise. Will incentives be given to employees for capturing and writing down and exposing the silent knowledge in their heads? Will the following be a common request on company bulletin boards: "Informants Needed: Cash Reward for Information Captured Alive"? Will a new department be created to capture, index, and manage the new influx of "silent" data? Who will track and award the bonuses for contributing to the knowledge base? Will employees be given some sort of guarantee that they will not be laid off if they divulge trade secrets? How would this work? Such questions as these need to be addressed if knowledge management is to become a force in the twenty-first century and avoid the pitfalls of earlier techno-utopian ventures. Artificial intelligence's "expert systems" of the 1980s, for instance, were much over-hyped, and notoriously failed at delivering.

The following Fastpaths titles are intended as tools to bring knowledge management down to the level of corporate reality and make it a success.

Fastpaths

He had a horror of destroying documents, especially those which were connected with his past cases, and yet it was only once every year or two that he could muster the energy to docket and arrange them.

—Sherlock Holmes, The Musgrave Ritual, 1893

1949	Claude Shannon and Warren Weaver: The Mathematical Theory of Communication. The revolutionary book that ushered in our awareness of "the information age," a work in which the authors, engineers at AT&T's Bell Laboratories, defined information as "energy."
1958	Michael Polanyi: Personal Knowledge. The book that inaugurates the discussion of "tacit" knowledge.
1962	Fritz Machlup: The Production and Distribution of Knowledge in the United States. First major attempt to describe the emerging "knowledge" worker as opposed to the "industrial" worker. First definition of the "knowledge" industry.
1966	Michael Polanyi: The Tacit Dimension.
1968	Peter Drucker: The Age of Discontinuity. Relying on Machlup, Drucker points out that following World War II the American economy experienced a "discontinuity," a sudden shift from "goods" to "knowledge" as the trade medium.
1973	Daniel Bell: The Coming of Post-Industrial Society. Solidifies Machlup's and Drucker's theory that the United States has indeed moved to an "information" economy (from an industrial economy).
1986	Donald Marchand and F. Horton: Infotrends: Profiting from Your Information Resources. Defines knowledge management as "strategic" information management.
1986	James Beniger: The Control Revolution: Technological and Economic Origins of the Information Society. Traces the information age back to the industrial revolution and discusses the role of information in organisms and societies.
1988	Shoshana Zuboff: In the Age of the Smart Machine: The Future of Work and Power.
1988	Robert Wright: Three Scientists and Their Gods: Looking for Meaning in an Age of Information. In this brilliant book, Wright lays out with great clarity and wit our deepest thinking about the evolution of "information."
1990	Richard Pascale: Managing on the Edge: How the Smartest Companies Use Conflict to Stay Ahead (includes chapter on "the two faces of learning").
1995	Ikujiro Nonaka and H. Takeuchi: The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation.
1997	Thomas Stewart: Intellectual Capital: The New Wealth of Organizations.
1997	Rudy Ruggles (ed.): Knowledge Management Tools.
1998	Thomas Davenport and L. Prusak: Working Knowledge: How Organizations Manage What They Know.
1998	Carla O'Dell and C. Grayson: If Only We Knew What We Know: Transfer of Internal Knowledge and Best Practices.
1999	Jack Gordon: "Intellectual Capital and You," Training (September 1999).
2000	Nancy Dixon: Common Knowledge: How Companies Thrive by Sharing What They Know.
2001	Melissie Rumizen: The Complete Idiot's Guide to Knowledge Management.
2001	Thomas Housel and Arthur Bell: Measuring and Managing Knowledge.
2001	Marc Rosenberg: E-Learning: Strategies for Delivering Knowledge in the Digital Age.
2002	Timothy Aeppel: "On Factory Floors, Top Workers Hide Secrets to Success: Tight-Lipped Old Hands and 'Voodoo Accuracy'," Wall Street Journal (July 1, 2002). Fascinating article on the challenges of capturing tacit knowledge (the "tribal lore" of employees) in the real world.

"The Tree of Knowledge grew nearby."

—Milton, Paradise Lost, 1667

Tapping the brain power of the hive-mind.

—After Mandeville:
The Fable of the Bees, 1730

See also Learning Objects Learning Organization