KM is unlike most applied science used in business in that it relies on a powerful integrating output element – a person – to clean up and make sense of whatever they are given by KM. Ideas about knowledge handling can be inconsistent, incoherent, function like a placebo, or just be plain wrong. Mix in some marketing┬áhype over a new collaboration tool, and the result can be a real mess. The person whose job it is to use the knowledge will fix all that, often unconsciously. That may not be the best use of their time.

But KM is changing, as machines become more capable of accessing and using knowledge.


Our Capability

We are interested in the kind of KM where machines have access to and make use of knowledge – there is no person cleaning up the output so the threat of GIGO is all too real, requiring far more discipline in what is done in gathering or creating, cleaning, storing and disseminating knowledge. Discipline turns KM into Systems Engineering – the engineering of a complex knowledge system, where many of the components are abstract, and verbal reasoning becomes more important than spatial reasoning.

KM is a lot more than just managing the knowledge held in text. If the textual knowledge can be captured in a semantic system like Orion and made active, it makes sense to add links to other types of knowledge which also can be made active. As the builders of Orion, we are uniquely placed to do that.

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