There is no management of knowledge except through a management of information.

Note to reader: this is the 3rd of 5 posts beginning with the post titled, ""No Knowledge but through Information"
“Management” comes from “manage” which derives from the Latin “manus” – hand. ([1] Soucres used for definitions are the on-line services, Merriam-Webster OnLine ( and Wiktionary (
The management practiced by our many of forbearers, those with no staff to order, was necessarily hands on. My grandfather was a dairy farmer. His management of his livestock and his crops was literally “hands on”. The same could be said for my grandmother as she managed the household. Or of the grocer who managed his store in town.
In our time, the expression “hands-on style of management” is not a redundancy nor even meant to be taken literally. Managers who are “hands-on” are more directly involved with their staff and with day-to-day details. Managers who literally manage their staff with the use of their hands risk run the serious risk of being sued for harassment.
But we are still quite literally hands-on in many of our efforts to manage information. We compose an email message with finger presses to the keyboard and then we send the email with a click of the mouse button. Likewise, we use our hands on keyboard and mouse to work with electronic documents and with web pages. We make printouts for an even more direct interaction with our information. Paper forms of information endure (Sellen & Harper, 2002) in large measure for their hands-on affordances. Paper and the means to write on paper with pencil or pen are nearly always at hand. Paper can be folded, torn and thrown away. Writing, sketching or doodling on paper is easy and satisfying. There is a “feel” to paper that we may never achieve with digital forms of information.
Knowledge as “no thing” cannot be managed directly. If we think we have knowledge “at our fingertips” we are most likely touching information in some form instead. This is not to say that knowledge management is not possible. But we do so through its expression in information. There is no management of knowledge except through the management of information.
What are we doing when we manage information? What must we do to manage knowledge? These questions are each considered in turn.

What are we doing when we manage information?
Information as data – as bits – is a resource to be managed. The DAMA International Foundation in a pamphlet provided for download from their web site states that “The basic premise of Data Management (DRM) is that information and data is like any other business resource – and should be managed as such.” (DAMA International Foundation, 2005, p. 5). The pamphlet goes on to say that “the amount must be optimized. In other words, the company should always have enough--but also minimize excess and redundancy” and “resource should be shared and leveraged in as many ways as possible, in order to maximize its value while diminishing its overall costs”
These are sensible steps for a company to take with data, information or any other resource. Steps must be taken, for example, to insure that information is properly maintained. Information should be securely stored. Access to information should be controlled. Its use should be monitored. For information or data, viewed as a resource, considerations apply that aren’t that different from those that might apply to money or laptops or employee time.
But for information as “data in motion” additional considerations arise. Information can be copied and communicated. Information is sent and received with purpose or intention mind. Is information getting to the right people? Is it having a desired effect? Depending upon context, depending upon the recipient, the same information may save valuable time and money or be a waste of it.
One of the neater definitions of management[1] is “the judicious use of means to accomplish an end”. Mary Parker Follett , writing a the turn of the last century defined management (of people) as "the art of getting things done through people". Substitute “information” for people and we have a nice definition for information management – the art of getting things done through information.
An ideal in information management is to have “have the right information (in the right place, in the right form, enough, not too much, etc.) to meet our current need” (Jones, 2007, p. 7). We come closer to this ideal to the extent that we’re able to create and maintain a mapping between information and need.

A simple, stylized mapping between information and need is depicted in Chapter 3 of the book, Keeping Found Things Found"  (see also, excerpt on this site: Only small portions of the mapping have an observable external representation. In a company or as individuals, for example, we maintain folder structure or a tagging scheme which is visible in our filing systems, digital and paper-based. However, much of a mapping has only hypothesized existence in the memories of individuals and perhaps also in the policies, procedures and daily workflows of an organization. Large portions of the mapping are potential and not realized in any form, external or internal. A sort function or a search facility, for example, has the potential to guide from a need to desired information.
With respect to the mapping, we have two basic kinds of information management activity corresponding to the two directions in which the mapping can be traversed: Keeping activities attempt to take us from information encountered to anticipated need. Finding activities attempt to go in the other direction – from need to information.
Finding: From need to information. In their efforts to meet a need, people seek. People search, sort and browse. People scan through a results list or the listing of a folder’s contents in an effort to recognize information items that relate to a need. These activities are all examples of finding activities. Finding is broadly defined to include both acts of new finding where there is no previous memory of having the needed information, and to include acts of re-finding. More broadly still, finding includes efforts to create the needed information as in “finding the right words” or “finding the right ideas.”
Keeping: From information to need. Many events of daily life are roughly the converse of finding events. Instead of having a need for which we seek information, we have information in hand and must determine what, if anything, we need to do with this information. In organizations and as individuals we encounter and generate large amounts of information. Decisions and actions are much the same no matter the information or its source. Is the information at all relevant, or potentially useful? Do we have an anticipated need for this information? What are the costs of not having this information? Some information – tax-relevant information for past years, for example -- must be kept even though the likelihood that a need for this information will arise is very small since the costs of not having this information, should the need arise, are very high (Jones, 2004).
Finding and keeping activities traverse the mapping in complementary directions. Four kinds of information management activity focus on the mapping itself. Elsewhere, I refer to these collectively referred to as meta-level activities or, simply, “m-level” activities (Jones, 2007):
Maintaining and organizing. How to … organize information for repeated use? … safeguard this information against loss? … insure that information is current and correct? .. update formats to keep pace with changes in standards and in supporting tools?.. insure that old information is deleted, archived or otherwise moved out the way? What about versions? What about duplicates and near-duplicates? These are all questions of maintenance and organization.
Managing privacy and the flow of information. Information management aims to insure that the right people have the right information at the right time. But steps must also be taken to insure that other people – the wrong people – don’t also have access to this information. And how to insure that the right people aren’t distracted or overwhelmed the information they receive?
Measuring and evaluating. Choices are made in support of all the activities described so far. Schemes of organization are selected; strategies, policies and procedures are adopted; supporting tools are put in place. We then need to ask, periodically or continuously, “is it (the resulting mapping between information and need) working? Can it work even better? If so, what should change?” These questions depend both upon the measurements we’re able to make and also on the evaluations we must make in cases where measurements (and the underlying objectives these measurements reflect) are in competition with one another.
Making sense of our information. Efforts to make sense are the most “meta” of meta-level activities. “Does it make sense?” The question can be applied to choices made in each of the other meta-level activities. The question has broad application and reaches to deeper levels of understanding concerning ultimate goals and tradeoffs. We might hear ourselves saying something like “I understand what you want to do but it doesn’t make sense”. Choices that make sense with one need in mind, may not make sense when other needs are also considered. Does the mapping make sense? Our information is now totally secure against unauthorized access but we can’t easily access the information either. Does this make sense? We make sense of information. We use our senses. We also “make” and manipulate. Information is a thing to be piled and sorted, arranged and re-arranged. Information is a thing to be touched. Information is in the mapping. Information is also how we represent the needs of a mapping (including goals and constraints). Information, perhaps in the form of graphs, is how we represent a hierarchy of need. Information is how we represent the synergies and conflicts between needs. Information is how we represent the mapping itself. It’s all information.

What must we do to manage knowledge?
To make a variation an old joke, ask any three people involved in “knowledge management” for a definition of same and you’ll likely get three different definitions. Wait a few more minutes and you’ll get three more.
In his blog post, “43 knowledge management definitions - and counting…[3], Ray Sims documents a diversity of definitions for knowledge management. Many of the definitions seem to have little in common with each other save for the repeated use of the word “knowledge”.
One of the better, more forthright, of the definitions comes from the CIO Magazine Tutorial[4]: “Unfortunately, there's no universal definition of knowledge management (KM), just as there's no agreement as to what constitutes knowledge in the first place. For this reason, it's best to think of KM in the broadest context. Succinctly put, KM is the process through which organizations generate value from their intellectual and knowledge-based assets. Most often, generating value from such assets involves codifying what employees, partners and customers know, and sharing that information among employees, departments and even with other companies in an effort to devise best practices.”
The definition notes that “generating value” (from knowledge-based assets) involves information – the “codifying” of what people know and “sharing that information”. We can consider KM to require two essential transformations: From knowledge to information and then, to complete the transfer of knowledge, from information back to knowledge. The first transformation is often referred to as knowledge elicitation. We need a name for the second transformation as well. Call it knowledge instillation.
Knowledge elicitation[5]. Each of us knows a lot about matters big and small. We know, for example, how to spot and move away from erratic, potentially dangerous people on a street or subway platform. We may know (not I) how to use the buttons on a video game controller. Some of this knowledge is relatively easy to express. We know to stay clear of people who are shouting and screaming. But the more knowledge is integrated into our beliefs, our judgments and our actions, the less easy it is for us to give expression to this knowledge. Polanyi (1967) makes the distinction between explicit knowledge – knowledge readily expressed – and tacit knowledge -- knowledge not easily expressed. Polanyi offers, as an aphorism, that “we know more than we can tell”.
We can never tell all of what we know but methods of knowledge elicitation can help us to tell more of what we know. A review of all the various techniques of or with potential application to knowledge elicitation is beyond the scope of this paper. Techniques involve the use of repertory grids (Kelly, 1955), concept maps (Novak, 1998), affinity diagramming (Bondarenko & Janssen, 2005) , interviews – free-form or structured and observations (e.g., as an expert works through a selection of problems or cases) (Hoffman, 1989) . The person whose knowledge is being targeted may be asked to think aloud and a transcription of the recording of this think-aloud may later be subjected to a protocol analysis (Newell & Simon, 1972).
A point to make is that these methods are as much, if not more, about information as about knowledge. Each method involves several forms of information. Included, to be sure, are eponymous forms of information such as concept maps, affinity diagrams and repertory grids. Information in other forms is used to set the stage for a session with the expert . And the results of this session are recorded using other forms. In sessions with an expert underwriter in which I participated, for example, the underwriter worked through, one by one, a paper stack of applications for life insurance, thinking aloud as he did so. His utterances were recorded and later transcribed. Paper -based applications, cassette recordings (this was in the 80’s) and electronic transcription were each used in knowledge elicitation.
Knowledge instillation.”Instillation” comes from “instill” as in “to cause to become part of someone’s nature”. Instillation neatly contrasts with “installation”. Much as we might like to, we can’t simply “install” a new body of knowledge in our brains or in an organization as we might install a new software program on our computers. Knowledge elicitation is only step one. Knowledge instillation is often the more difficult step in the transfer of knowledge. Popular books on knowledge management write of the barriers to transfer and change (e.g., Argyris, 1994). We read of the importance of creating a culture to promote knowledge transfer (e.g., O’Dell, Grayson & Essaides, 1998) and of creating communities for the sharing of knowledge (e.g., Snyder & McDermott, 2002).
Challenges remain even when recipients are willing. Of potential relevance is wealth of education research on methods of teaching and learning (see, for example, Bransford, Brown, & Cocking, 2000). Of direct relevance, for example, is an ongoing debate concerning the extent to which – putting it plainly – people can be taught or need to learn for themselves (see, for example, Duffy, Lowyck, & Jonassen, 1993; Schwartz & Bransford, 1998).
Person-to-person contact remains one of the most effective ways to transfer knowledge. In educational contexts, for example, students working with individual human tutors test at levels of performance as much as two standard deviations higher than students in a conventional classroom (Bloom, 1984). Identifying expertise and locating experts is an area of research in its own right (e.g., McDonald and Ackerman, 2000). Now the Web provides a basis for a transfer of knowledge on a variety of topics ranging from home repair to cancer treatment[6].
We can also recognize that instances KE and KI are commonplace and by no means limited to companies and classrooms. If someone asks you for directions or if you try to teach someone skill that you have and they don’t (e.g., driving a car or driving a golf ball), you are doing KE. You may imagine the route or the way you drive in your “mind’s eye”. Or you may actually do the thing you mean to tell or teach. You may go to the destination or you may take the golf swing – observing your actions as you do so. In these examples, your objective is to render your skill, your knowledge, into forms of information (spoken instructions, hand gestures, reenactments) that can be communicated to someone else. But acts of KE are only a step one. Step two is for the other person to really understand, to “get it”, and not just to nod as if he or she does. The ultimate proof is in the action but by then the costs of failure may be too high. Managers and parents alike often apply techniques to test for transfer such as having the intended recipient repeat the instructions or testing for choice points (“what will you do if..”).


[2] Figure 1 is an illustration done by Elizabeth Boling and is a variation of a figure that first appeared in Jones (2007).


[4], as viewed on January 31, 2009.

[5] The term knowledge elicitation is often used interchangeably with but is to be preferred to the terms “knowledge acquisition” or “knowledge capture”. There is nothing wrong with “capture” as commonly used – as in “I want to capture these good ideas on paper” or “I want to capture this moment in a photograph”. It seems reasonable then to talk about capturing knowledge – as long as we understsand that what is being captured is at best a pale reflection of the knowledge we actually have. The term “knowledge acquisition” is more problematic since it implies that knowledge has actually been transferred to, “acquired by” an someone – if not the targeted recipients then at least an intermediary (e.g., the person interivewing the expert). Nothing of the sort actually happens.
<These terms were used frequently in the 1980’s in connection with efforts to build expert systems. Attempts were made to “acquire” or “capture” the knowledge of human experts for use in computer-based expert systems. However, these terms were not apt then and are even less apt now when knowledge management is more about attempts to facilitate the exchange of knowledge among people. Knowledge was never captured. Knowledge could only be said to have been acquired by an expert system after a time-consuming process of iterative tinkering of rules and representations. Whatever eventually found programmatic expression in the expert system bore only a passing resemblance to the forms of information (transcripts, rules inferred, diagrams, etc.) initially used to represent the results of interviews with the expert.

[6] See, for example,


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