What
is Knowledge and Knowledge Work?
Knowledge work has two main characteristics:
- It does not produce goods but information.
To be
more concrete: it turns questions into answers.
- It requires people with long experience or
education.
Frequently, large piles of documentation are required.
Let's give some definitions (After all, good
definitions are a cornerstone of Knowledge Management)
First we distinguish competency versus skill:
- A competency is the ability to produce
- A skill (also called capability or capacity)
is the ability to do something, e.g. programming or planning.
Competencies take a perspective from outside the
(black) box, whereas capabilities look from the inside. This distinction is useful for
many reasons:
 | competencies are measurable, because the results
produced can be measured
|
| often people are so-called ‘unconsciously’
competent: they are successful at producing results but do not know exactly how they do
it. Let's look at a universal example:
Most people are competent to get their car parked. But try to describe exactly how you
do this! Do this exercise independently with two or more people. Then, compare the
results. You’ll most probably realise that each has covered relevant points not
mentioned by the other. There is much more to be learned from this exercise however …
Not only people can be competent, but also teams and machines.
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This brings us to a second important distinction:
- Explicit or codified knowledge:
(multimedia) descriptions that can be used in a website
- Tacit knowledge: the
knowledge competent people have, which is not (yet) made explicit. Here too, there are 2
poles:
- Knowledge in mental models:
the competent person knows about his or her knowledge, which is internally expressed in
words, images, sounds, feelings, etc.
- Implicit knowledge: the
competent person has no idea as to how the result is produced, and the knowledge is
implicit in examples of competent behaviour. Some knowledge, by its very nature, remains
implicit: e.g. can you explain from internal experience how you recognise colours? (If you
can, please contact us, because it would be a scientific breakthrough!) We cannot explain
this, but we can give examples of coloured things and the name of the colours. These can
be used to drill the recognition. We call these mental reflexes.
Modelling then, is the
task of extracting tacit knowledge and codifying it in a consistent structure in a
(multimedia) document or training. You can learn this powerful but
difficult skill at the Academy for
Personal Mastery
The documents can be used to support the execution of the knowledge work, or
to support training.
The explicit knowledge can be described in language or indirectly through examples
and exercises.
As most human knowledge is a mixture, models of
knowledge tend to be a mixture too. Take loan decisions for instance: a risk analyst
| can tell you which ratios he calculates, and how he
does it
|
| can tell you whether a certain figure or combination
of figures is ‘rather positive or negative’, but cannot tell you how exactly
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| cannot tell you how he balances all these vague
expressions to a decision, but can give you al lot of examples of decisions.
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If we want software tools that question and advice the users, one has to code
the knowledge models in software
knowledge base.
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