The Evolution of Knowledge Management and the Businesses Implications
By Tom Jackson, Loughborough University
Knowledge Management (KM) is currently a buzz-phrase that it starting to occur
more frequently in many publications and conversations, yet it’s a phrase that
has been around for years. In the years leading up to 2002, KM has been going
through phases of maturity (Sveiby, 2001).
1. The first phase was inward-looking, focusing on productivity issues - "How
can we use IT systems to prevent reinventing-the-wheel?" This phase started
around 1992 and created a multitude of project databases, best practices
databases, Lotus Notes installations etc.
2. The second phase was similar but now with a customer focus - "How can we
leverage what we know about our customers to serve them better?" - Data
warehousing was the theme of the day. The trouble with the early installations
is that all they did was to create massive data and text archives of dubious
value. All passive and no interaction!
3. The third phase is where we are now (1999- 2002) and interaction has reached
the surface: Interactive IT web pages, e-business, e-commerce, on-line
transactions etc. This phase has created a lot of enthusiasm, witness the hyped
valuations of the "dot.coms" during 2000.
4. I am now looking forward to a future phase: the realisation that the key to
unlocking the value of Knowledge is People.
A problem that many organisations face is that KM is in danger of being
perceived as so seamlessly entwined with technology that its true critical
success factors will be lost in the pleasing hum of servers, software and pipes.
As organisations label their document management, database or groupware products
"knowledge management solutions," executives can be excused for mistaking the
software for the solution (Hildebrand, 1999). It's not. It is therefore
important for executives to appreciate the philosophy behind knowledge
management to ensure they do not circum to the software trap.
Where did the Knowledge Management come from?
Much of the current literature in knowledge management is based on the writings
of two philosophers Gilbert Ryle and Michael Polanyi. The most dominant concepts
within the current knowledge management literature are the notions of ‘tacit’
and ‘explicit’ knowledge (Nonaka, 1994). The underlying philosophy of these
constructs can be traced back to Gilbert Ryle (1900-1976) and Michael Polanyi.
Ryle’s most important contribution is demonstrating the difference between
‘knowing how’ and ‘knowing that’. Knowing how cannot be defined in terms of
knowing that (Jashapara 2003). For instance, a chef doesn’t recite his recipes
to himself (knowing that) before he can cook according to them (knowing how).
Michael Polanyi comes from a similar behaviourist background as Ryle in his book
The Tacit Dimension and develops the notion of tacit knowledge from a number of
experiments involving hypothetical shock treatments reminiscent of the
stimulus-response model of behaviour (Skinner, 1938). His starting point of
human knowledge is “the fact that we can know more than we can tell”.
Avoiding Information Overload
Knowledge can come in a variety of forms; structured, semi-structured or
unstructured. In order to organise this knowledge, one starts by gathering
knowledge and working out a way to group, index or categorise it in some way.
One could present a schema conceptualising a vocabulary of terms and
relationships to represent the knowledge. This is called a ‘knowledge map’ or an
‘ontology’. If each one of us tried to organise the same knowledge, we may come
up with wide variations depending on our understanding and perspective on the
subject. In an attempt to prevent this situation from occurring, we have
developed ‘ontologies’ to improve our level of information organisation,
management and understanding (Jashapara 2003). Gruber(Gruber 1993) defines
ontology as: “a formal, explicit specification of shared conceptualisation”
Given the continual information overload problem in many organisations, there is
a need to maintain and improve an existing ontology as it changes over time.
Manual maintenance of ontologies can be tedious and time consuming. Hence, a
variety of tools have been developed to assist the ‘ontology editor’ to
semi-automate the tasks. Certain tools exist to acquire new concepts and place
these within the domain ontology and some of these are based on machine learning
techniques. It is notable that Tim Berners-Lee, inventor of the World Wide Web,
believes that the information overload problems on the existing web will lead to
a second generation which he calls a ‘Semantic Web’. This will make explicit the
semantics underlying all resources on the web and create a form of ‘global’
ontology. It is unclear whether this future ‘global’ ontology will be reused to
create local ontologies by standardising concepts and the relations between them
(Jashapara 2003).
Buying Knowledge Management Tools for your Company?
The use and application of knowledge management tools and technology implies
these important questions for managers:
* What KM tools are most appropriate for a given business problem?
* How does one evaluate the cost effectiveness of KM tools?
* How do these technologies help capture and share the valuable tacit knowledge
or ‘know how’ in an organisation?
For any aspiring purchaser of KM systems or technologies, the internet provides
a multitude of vendors promising to transform your business. But where do you
start? How do you understand the complexity of the offering and their
effectiveness with your business problem? In the highly volatile market of
software engineering, it is likely that many of these so called ‘market leaders’
will cease trading in a few years time (Jashapara 2003). As an experiment in
this book, it was found that fourteen ‘market leaders’ in KM tools (quoted in
Mertins et al. 2000) had ceased trading in a two year time frame. So how can we
decipher the offerings of the multitude of technologies in the market place?
As with purchasing hi-fi systems, one can purchase cheap or expensive KM
technologies. Rather than becoming mesmerised by the power of these
technologies, it is important to remain focused on the organisational needs that
are driving the procurement of these technologies and whether an alternative may
suffice. As a rule of thumb, experience shows that no more than one third of a
knowledge management budget should be committed to technology (O'Dell et al.
2000).
In a 1997 Ernst & Young survey, business managers indicated that the most
important types of knowledge that would help them act effectively were (Smith
and Farquhar 2000):
* Knowledge about customers (97%)
* Knowledge about best practice and effective processes (87%)
* Knowledge about competencies and capabilities of their company (86%)
In the same survey, it is noteworthy that 46% of the 431 US and European
executives felt that their organisations were good at generating new knowledge
but only 13% of the respondents agreed that their organisations were good at
transferring existing knowledge (Ruggles 1998). The most common technologies
employed by organisations were:
* Creating an intranet (47%)
* Creating data warehouses (33%)
* Implementing decision support tools (33%)
* Implementing groupware to support collaboration (33%)
The Future
The predominant KM tools used today tend to focus on explicit knowledge and its
re-workings even though the received wisdom acknowledges that it is the tacit
knowledge or ‘know how’ that leads to greater effectiveness in organisations.
The future challenge in this area is to develop tools to enable tacit knowledge
to be made explicit in an easy and effortless manner. One approach may be the
development of multimedia technologies such as digital video that capture and
store an individual’s ‘know how’ for storage, indexing and future retrieval via
a search engine. This would enable a much richer form of communication between
individuals and allow the addition of a diversity of audio-visual signals from
the spoken word to tone of voice and body language.
Hildebrand, Carol (Sept 15, 1999), Does KM=IT?, CIO Enterprise Magazine
O'Dell, C., Hasanali, F., Hunbert, C., Lopez, K., and Raybourn, C. (2000).
Stages of Implentation: A Guide for Your Journey to Knowledge Management,
American Productivity and Quality Centre, Houston, Tex.
Jashapara, A., (2003), Knowledge Management: An Integrated Approach, Harlow
Essex: Prentice Hall (forthcoming).
Mertins, K., Heisig, P., and Vorbeck, J. (2000). Knowledge Management: Best
Practices in Europe, Springer-Verlag, New York.
Polanyi, M. (1967) The Tacit Dimension, Doubleday, New York.
Ruggles, R. (1998). "The state of the notion: knowledge management in practice."
California Management Review, 40(3), 80-9.
Ryle, G. (1949) The Concept of Mind, Hutcheson, London.
Smith, R. G., and Farquhar, A. (2000). "The Road Ahead for Knowledge Management:
An AI Perspective." American Association for Artificial Intelligence, Winter,
17-40.
Sveiby, Karl-Erik, (2001). What is Knowledge Management? http://www.sveiby.com.au/KnowledgeManagement.html