Taking a look back, many have blamed the failure of knowledge management (KM) on the lack of a solid program backed by top management. While these soft issues are normally common factors for failures, there was one primary reason that KM failed in mass. The big mistake was that the knowledge was organized around a taxonomy which was centrally controlled and unresponsive Today there is a combination of new knowledge approaches that will make KM a reality and likely to be backed by management.
The Problems with Taxonomies:
Taxonomies are rigid hierarchies that limit the kind of relations that a topic had to "parent-child" with minor exceptions for multiple inheritances. This required an overseer that ended up being a bottleneck to organizing knowledge. This kept knowledge trapped from being adaptive in realtime and assumed someone had to manage knowledge acquisition. This taxonomy idea came from the classification of genus and species where it was easier to classify kinds of living things and there was no pressure to complete the task. Limited Taxonomies limit Knowledge Management and the early days leveraged them into dead-end streets.
Opportunities with Ontologies:
Ontologies are easy to expand in that they support real-time change and can support a multitude of knowledge relationships to create a multitude of shapes. They can be reviewed later for accuracy and unnecessary redundancies. The use of flexible and fast ontologies combine well with AI in both learning and reasoning modes. Proven and general use ontologies can be easily combined with specific ontologies to solve both general and specific problem domains. Technology and humans alike can follow ontology paths with ease. In fact, ontologies can support taxonomies within themselves.
KM in the early generations got data, information, knowledge, and wisdom structures all wrong. No wonder top management backed away from it especially when it was failing early. Let's not throw out the baby with the bathwater and finally attack knowledge management with the help of AI in all its forms. Big Data is waiting on it and so are a goodly number of business outcomes.