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Figure 1. Model of KM contributors
information. O'Dell and Grayson (1998, pp. 18ff)
identify five similar barriers: organizational silos,
reluctance to use ideas developed elsewhere, lack
of common perspectives and terminology, focus-
ing on explicit rather than tacit knowledge, and
a lack of time or other resources. KM initiatives
and systems are intended to help overcome such
barriers. Furthermore, note that the effective use
of a KM system entails additional best practices
involving the KM process.
A variety of techniques can be used to address
these challenges. Creating glossary pages can help
to bridge terminology problems. Initially, it may
help to focus on specific groups or sub-organi-
zations, where people have shared perspectives
and mutual trust. For example, at EnginCom, one
engineering group developed a KM system, and
other related groups found it useful, which led to
broader adoption. Another useful technique is to
identify common document types or actions and
develop corresponding tools, to make it easier
for people to contribute to the KM system. Most
wiki platforms allow users to create templates that
are used for new pages, and some support fields
for multiple-choice, numeric, or other data. For
example, SalesCom defined templates for sales
call reports and for monthly status reports. The
author helped another organization to develop
forms to help people submit and review project
proposals.
Participation is critical to system success.
People must be confident that collaborating and
using the KM system will help them find needed
knowledge. Furthermore, they must be willing
to contribute their own knowledge. However,
“people rarely give away valuable possessions
(including knowledge) without expecting some-
thing in return” (Davenport & Prusak, 2000, p. 26).
Thus, it is important to understand both the roles
and incentives of people who use the system.
In most KM systems, the vast majority of the
content is contributed by a few people, and most
people contribute rarely (if ever), although they
may well use knowledge in the system; this is il-
lustrated in figure 1.According to Nielsen (2006),
in most online communities 1% of participants
contribute most of the content; 9% contribute
occasionally, and 90% read but never contribute,
while for Wikipedia the frequencies are closer
to 0.003%, 0.2%, and 99.8% - i.e., 1000 users
contribute 2/3 of the content. Nielsen observes
that it is impossible to overcome this inequality,
but suggests some ways to encourage broader
participation. A particular KM system probably
has an optimal distribution, even if it cannot be
calculated. If too few people contribute, they may
become overwhelmed, or the system may not be
useful. On the other hand, in some situations a
KM system run by a few knowledgeable or well-
connected brokers might function quite well. At
the other extreme, if too many people contribute,
it may be difficult to find the truly useful knowl-
edge. Some online communities find that modest
barriers result in higher quality (e.g. Taylor, 2007);
this may also be true for KM projects.
There are many ways to encourage participa-
tion, although they can have unexpected draw-
backs. Organizations can hire or assign staff
to create content, in order to help bootstrap the
KM system so that it contains more information.
However, this may lead other users to assume that
contributing content is the sole responsibility of
those assigned staff. Organizations can provide
explicit incentives, although these may decrease
intrinsic motivation, or be manipulated. Often,
a more productive tactic is to find ways for the
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