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Originally published March 19, 2025

Stan Garfield
18 min readMar 20, 2025

This is the 113th article in the Profiles in Knowledge series featuring thought leaders in knowledge management. Michael E.D. (Edward Davison) Koenig is professor emeritus at the College of Information and Computer Science at Long Island University, a long-time participant in and observer of the knowledge management scene, and the author of numerous articles and books. His specialties are Information Retrieval, Distance Learning, History, E-Learning, and Metadata.

Michael is the former and founding dean of the College of Information and Computer Science at Long Island University. His career has included senior management positions in the information industry: Manager of Research Information Services at Pfizer Inc., Director of Development at the Institute for Scientific Information, Vice President, North America at Swets & Zeitlinger, and Vice President Data Management at Tradenet; as well as academic positions: Associate Professor at Columbia University, and Dean and Professor at Dominican University.

His Ph.D. in information science is from Drexel University, his MBA in mathematical methods and computers, and his MA in library and information science are from the University of Chicago, and his undergraduate degree is from Yale University. A Fulbright Scholar in Argentina, he is the author of more than one hundred professional and scholarly publications, and is the co-editor of Knowledge Management for the Information Professional (2000), Knowledge Management Lessons Learned: What Works and What Doesn’t (2003), and Knowledge Management in Practice: Connections and Context (2008), all published by Information Today for the American Society for Information Science and Technology. A member of the editorial board of more than a dozen journals, he is also the past president of the International Society for Scientometrics and Informetrics. In 2005 he was awarded the Jason Farradane Award “in recognition of outstanding work in the information field.”

Background

Profiles

Education

  • Drexel University — PhD, Information Science, 1978–1982
  • University of Chicago
  1. MBA, Mathematical Methods and Computers, 1968–1970
  2. MA, Library/Information Science, 1966–1968
  • Yale University — BA, Physics, Psychology, 1959–1963

Experience

  • Long Island University
  1. Professor Emeritus. 2017 — Present
  2. Professor, 1999–2017
  3. Dean, College of Information and Computer Science, 2001–2006
  • Dominican University — Dean and Professor, 1988–1999
  • Tradenet Inc. — Vice President, Data Management, 1985–1988
  • Columbia University School of Library Service
  1. Adjunct Professor, 1985–1988
  2. Associate Professor, 1980–1985
  • Swets & Zeitlinger — Vice-president, North American Operations, 1978–1980
  • Institute for Scientific Information
  1. Director of development, 1977–1978
  2. Director of library operations, 1974–1977
  • Pfizer Pharmaceuticals — Manager of Information Services, 1970–1974
  • Yale University — Assistant Head, Circulating Sterling Library, 1965–1966
  • US Navy — Communications Officer (Lieutenant Junior Grade), USS Shadwell (LSD-15), 1963–1965

Content

Articles

Intellectual Capital and Knowledge Management

A program to capitalize on intellectual capital is typically described as having six steps:

  1. Define the role of information and knowledge in your business. In some areas, that role and that importance is transcendently obvious — in the pharmaceutical industry for example, where the NDA, the new drug application, the patented new drug is the name of the game. Indeed, Peter Drucker has described information or knowledge as being the pharmaceutical industry’s principal product, with the pill being merely the container for the product. Most contexts will not be so obviously information driven, but when closely examined, the role of information and knowledge is apt to be considerable. For example: almost any technological skills or expertise, or knowledge about customers, what do they need, what do they want, is in fact intellectual capital, although we haven’t typically thought about it that way before.
  2. Assess your competitors’ knowledge assets and their strategies. What differentials are there? What do they do differently? What can you learn from them?
  3. Assess your knowledge assets, your portfolio. Where is that knowledge stored and maintained? Who uses it? Who has access to it? Who else could benefit from access? Some of us in the library community will be having a slight feeling of déja-vu at this point. Yes this is precisely the concept of “information mapping” that Horton and others in the library community have been promoting for years. We’ll return to this point later.
  4. Evaluate your knowledge assets. As in the case of a stock portfolio, ask the questions: are the assets performing? What are your assets worth? How can you leverage and manage their value? Patents are an obvious knowledge asset. Perform a triage on them. Which ones are trivial and no longer worth the legal effort and expense to maintain and renew them? More importantly, which ones may have unexamined applications and are worth investing the time to examine where they might be applied, perhaps to develop new products or perhaps to license to other corporations. Dow Corporation is often cited as an example of a company that has successfully done precisely that.
  5. Invest and take action. Identify gaps and plug them. Create information resources where they are needed. Direct R & D to where it is needed. Look for knowledge and technology to license, where appropriate, before your competitors do.
  6. Reassemble your knowledge portfolio, your info-map, and keep cycling.

The Origins and Development of Knowledge Management

Though it had earlier antecedents, the concept of Knowledge Management (KM), as we now know it, evolved as a concept in the late 1980s. The term originated in the consulting community. It arose from the merger of two factors: the recognition of the importance to an organization of its information and knowledge assets, and from the emergence of the Internet and the almost immediate recognition of the utility of the Internet as an information and knowledge sharing tool, particularly for geographically dispersed organizations. KM has gone through four stages:

  1. An emphasis upon the new technology and upon the development of “best practices” or “lessons learned”.
  2. An increased recognition of human and cultural factors, and upon the development of “communities of practice” to facilitate the sharing of information.
  3. An increased recognition of the importance of designing the systems for retrievability, and the importance of data design and structure, including taxonomy development and utilization.
  4. An emphasis upon extending KM systems beyond the parent organization to include, for example, vendors and suppliers, customers, users, alumni, etc.

KM has exhibited remarkable staying power and growth in a fashion that is dramatically different from all other business enthusiasms of the late 20th century.

ResearchGate

KMWorld (1)

KMWorld (2)

What is KM? Knowledge Management Explained (2018)

The classic one-line definition of Knowledge Management was offered up by Tom Davenport early on: “Knowledge Management is the process of capturing, distributing, and effectively using knowledge.” Probably no better or more succinct single-line definition has appeared since.

What is KM trying to accomplish?

Rich, Deep, and Open Communication

First, KM can very fruitfully be seen as the undertaking to replicate, indeed, to create, the information environment known to be conducive to successful R&D — rich, deep, and open communication and information access — and to deploy it broadly across the firm. It is almost trite now to observe that we are in the post-industrial information age and that we are all information workers. Furthermore, the researcher is, after all, the quintessential information worker. Peter Drucker once commented that the product of the pharmaceutical industry wasn’t pills, it was information. The research domain, and in particular the pharmaceutical industry, has been studied in depth with a focus on identifying the organizational and cultural environmental aspects that lead to successful research. The salient aspect that emerges with overwhelming importance is that of rich, deep, and open communications, not only within the firm, but also with the outside world. The logical conclusion, then, is to attempt to apply those same successful environmental aspects to knowledge workers at large, and that is precisely what KM attempts to do.

Situational Awareness

Second, Situational Awareness is a term only recently, beginning in 2015, used in the context of KM. The term, however, long precedes KM. It first gained some prominence in the cold war era when studies were commissioned by all of the major potential belligerents to try to identify what characteristics made a good fighter pilot. The costs of training a fighter pilot were huge, and if the appropriate characteristics leading to success could be identified, that training could be directed to the most appropriate candidates, and of those trained the most appropriate could be selected for front-line assignment. However, the only solid conclusion of those studies was that the salient characteristic of a good fighter pilot was excellent “situational awareness.” The problem was that no good predictive test for situational awareness could be developed.

The phrase then retreated into relative obscurity until it was resuscitated by Jeff Cooper, a firearms guru, and others in the context of self-defense. How do you defend and protect yourself? The first step is to be alert and to establish good situational awareness. From there the phrase entered the KM vocabulary. The role of KM is to create the capability for the organization to establish excellent situational awareness and consequently to make the right decisions.

What does KM actually consist of?

What are the operational components of a KM system? This is, in a way, the most straightforward way of explaining what KM is — to delineate what the operational components are that constitute what people have in mind when they talk about a KM system.

(1) Content Management

So what is involved in KM? The most obvious is the making of the organization’s data and information available to the members of the organization through dashboards, portals, and with the use of content management systems. Content Management, sometimes known as Enterprise Content Management, is the most immediate and obvious part of KM. For a wonderful graphic snapshot of the content management domain, see Real Story Group’s Vendor Map. This aspect of KM might be described as Librarianship 101, putting your organization’s information and data up online, plus selected external information, and providing the capability to seamlessly shift to searching, more or less, the entire web. The term most often used for this is Enterprise Search. This is now not just a stream within the annual KMWorld Conference but has become an overlapping conference in its own right.

(2) Expertise Location

Since knowledge resides in people, often the best way to acquire the expertise that you need is to talk with an expert. Locating the right expert with the knowledge that you need, though, can be a problem, particularly if, for example, the expert is in another country. The basic function of an expertise locator system is straightforward: it is to identify and locate those persons within an organization who have expertise in a particular area. These systems are now commonly known as expertise location systems. In the early days of KM, the term ‘Yellow Pages” was commonly used, but now that term is fast disappearing from our common vocabulary, and expertise location is, in any case, rather more precise.

There are typically three sources from which to supply data for an expertise locator system: (1) employee resumes, (2) employee self-identification of areas of expertise (typically by being requested to fill out a form online), and (3) algorithmic analysis of electronic communications from and to the employee. The latter approach is typically based on email traffic but can include other social networking communications such as Twitter, Facebook, and LinkedIn. Several commercial software packages to match queries with expertise are available. Most of them have load-balancing schemes so as not to overload any particular expert. Typically, such systems rank the degree of presumed expertise and will shift a query down the expertise ranking when the higher choices appear to be overloaded. Such systems also often have a feature by which the requester can flag the request as a priority, and the system can then match high priority to high expertise rank.

(3) Lessons Learned

Lessons Learned databases are databases that attempt to capture and make accessible knowledge, typically “how to do it” knowledge, that has been operationally obtained and normally would not have been explicitly captured. In the KM context, the emphasis is upon capturing knowledge embedded in personal expertise and making it explicit. The lessons learned concept or practice is one that might 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 most often used was “best practices,” but that phrase was soon replaced with “lessons learned.” The reasons were that “lessons learned” was a broader and more inclusive term and because “best practice” seemed too restrictive and could be interpreted as meaning there was only one best practice in a situation. What might be a best practice in North American culture, for example, might well not be a best practice in another culture. The major international consulting firms were very aware of this and led the movement to substitute the new more appropriate term. “Lessons Learned” became the most common hallmark phrase of early KM development.

The idea of capturing expertise, particularly hard-won expertise, is not a new idea. One antecedent to KM that we have all seen portrayed was the World War II debriefing of pilots after a mission. Gathering military intelligence was the primary purpose, but a clear and recognized secondary purpose was to identify lessons learned, though they were not so named, to pass on to other pilots and instructors. Similarly, the U. S. Navy Submarine Service, after a very embarrassing and lengthy experience of torpedoes that failed to detonate on target, and an even more embarrassing failure to follow up on consistent reports by submarine captains of torpedo detonation failure, instituted a mandatory system of widely disseminated “Captain’s Patrol Reports.” The intent, of course, was to avoid any such fiasco in the future. The Captain’s Patrol Reports, however, were very clearly designed to encourage analytical reporting, with reasoned analyses of the reasons for operational failure and success. It was emphasized that a key purpose of the report was both to make recommendations about strategy for senior officers to mull over, and recommendations about tactics for other skippers and submariners to take advantage of.

The military has become an avid proponent of the lessons learned concept. The phrase the military uses is “After Action Reports.” The concept is very simple: make sure that what has been learned from experience is passed on, and don’t rely on the participant to make a report. There will almost always be too many things immediately demanding that person’s attention after an action. There must be a system whereby someone, typically someone in KM, is assigned the responsibility to do the debriefing, to separate the wheat from the chaff, to create the report, and then to ensure that the lessons learned are captured and disseminated. The experiences in Iraq, Afghanistan, and Syria have made this process almost automatic in the military.

The concept is by no means limited to the military. Larry Prusak maintained that in the corporate world the most common cause of KM implementation failure is that so often the project team is disbanded and the team members almost immediately reassigned elsewhere before there is any debriefing or after-action report assembled. Any organization where work is often centered on projects or teams needs to pay very close attention to this issue and set up an after-action mechanism with clearly delineated responsibility for its implementation.

A particularly instructive example of a “lesson learned” is one recounted by Mark Mazzie, a well-known KM consultant. The story comes from his experience in the KM department at Wyeth Pharmaceuticals. Wyeth had recently introduced a new pharmaceutical agent intended primarily for pediatric use. Wyeth expected it to be a notable success because, unlike its morning, noon, and night competitors, it needed to be administered only once a day, and that would make it much easier for the caregiver to ensure that the child followed the drug regimen, and it would be less onerous for the child. Sales of the drug commenced well but soon flagged. One sales rep (what the pharmaceutical industry used to call detail men), however, by chatting with her customers, discovered the reason for the disappointing sales and also recognized the solution. The problem was that kids objected strenuously to the taste of the drug, and caregivers were reporting to prescribing physicians that they couldn’t get their kid to continue taking the drug, so the old stand-by would be substituted. The simple solution was orange juice, a swig of which quite effectively masked the offensive taste. If the sales rep were to explain to the physician that the therapy should be conveyed to the caregiver as the pill and a glass of orange juice taken simultaneously at breakfast, then there was no dissatisfaction, and sales were fine.

The obvious question that arises is what is there to encourage the sales rep to share this knowledge? The sales rep is compensated based on salary (small), and bonus (large). If she shares the knowledge, she jeopardizes the size of her bonus, which is based on her comparative performance.

This raises the issue, discussed below, that KM is much more than content management. It extends to how does one structures the organizational culture to facilitate and encourage knowledge sharing, and that extends to how one structures the organization’s compensation scheme.

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. Are employees free to submit to the system un-vetted? Who, if anyone, is to decide what constitutes a worthwhile lesson learned? Most successful lessons learned implementations have concluded that such a system needs to be monitored and that there needs to be a vetting and approval mechanism for items that are posted as lessons learned.

How long do items stay in the system? Who decides when an item is no longer salient and timely? Most successful lessons learned systems have an active weeding or stratification process. Without a clearly designed process for weeding, the proportion of new and crisp items inevitably declines, the system begins to look stale, and usage and utility falls. Deletion, of course, is not necessarily loss and destruction. Using carefully designed stratification principles, items removed from the foreground can be archived and moved to the background but still made available. However, this procedure needs to be in place before things start to look stale, and a good taxonomically based retrieval system needs to be created.

These questions need to be carefully thought out and resolved, and the mechanisms designed and put in place, before a lessons-learned system is launched. Inattention can easily lead to failure and the creation of a bad reputation that will tar subsequent efforts.

(4) Communities of Practice (CoPs)

CoPs are groups of individuals with shared interests that come together in person or virtually to tell stories, to share and discuss problems and opportunities, discuss best practices, and talk over lessons learned. Communities of practice emphasize, build upon, and take advantage of the social nature of learning within or across organizations. In small organizations, conversations around the water cooler are often taken for granted, but in larger, geographically distributed organizations, the water cooler needs to become virtual. Similarly, organizations find that when workers relinquish a dedicated company office to work online from home or on the road, the natural knowledge sharing that occurs in social spaces needs to be replicated virtually. In the context of KM, CoPs are generally understood to mean electronically linked communities. Electronic linkage is not essential, of course, but since KM arose in the consulting community from the awareness of the potential of intranets to link geographically dispersed organizations, this orientation is understandable.

A classic example of the deployment of CoPs comes from the World Bank. When James Wolfensohn became president in 1995, he focused on the World Bank’s role in disseminating knowledge about development; he was known to say that the principal product of the World Bank was not loans, but rather the creation of knowledge about how to accomplish development. Consequently, he encouraged the development of CoPs and made that a focus of his attention. One World Bank CoP, for example, was about road construction and maintenance in arid countries and conditions. That CoP was encouraged to include and seek out not only participants and employees from the World Bank and its sponsored projects and from the country where the relevant project was being implemented, but also experts from elsewhere who had expertise in building roads in arid conditions, such as, for example, staff from the Australian Road Research Board and the Arizona Department of Highways. This is also a good example of the point that despite the fact that KM developed first in a very for-profit corporate context, it is applicable far more broadly, such as in the context of government and civil society.

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Knowledge Management: Libraries and Librarians Taking Up the Challenge edited by Hans-Christoph Hobohm — Chapter: Knowledge Management, User Education, and Librarianship

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Stan Garfield
Stan Garfield

Written by Stan Garfield

2.3K Followers
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Knowledge Management Author and Speaker, Founder of SIKM Leaders Community, Community Evangelist, Knowledge Manager https://sites.google.com/site/stangarfield/

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