What is knowledge? Knowledge is to know!
"What is knowledge?" is a 5,000-year-old question, which is still the subject of much philosophical, psychological, and epistemological research. It is defined as the act of knowing where a person analyzes information, evaluates the situation, and then creates knowledge! Luckily, the discipline of KM found a way to avoid joining this 5,000-year-old debate by adopting two working definitions of knowledge. The first is that knowledge is not information, and the second is that the knowledge of an organization is more than the aggregate knowledge of its individual members. Understanding these two definitions lays the basis for KM.
The Information/Knowledge Interface - Two Sides of a Coin or Two Levels of Consciousness
If information and knowledge are one and the same, then an organization with the best information databases and technology should be the most knowledgeable. Information cannot substitute for knowledge despite the fact that to know is partly to have all the information you can get about something. This is because knowledge, unlike information, cannot stand alone from the knower - the human being. Knowledge is the outcome of the human cognitive abilities to understand, perceive, sense, and evaluate a situation. The human element is what distinguishes knowledge from information. This means the best information databases and technology systems cannot result in knowledge unless and until processed by the human mind. It is the human mind that transforms data and information into applicable knowledge expressed in action or stored in the mind as experience.
The link between information and knowledge is so close that some define knowledge as the next level of abstraction that information is taken to when applied to more specific situations by the human mind.3 Others define knowledge as "information that has been understood, interpreted, and validated in the context of application."9 The relationship between information and knowledge has been studied thoroughly, because if the process by which information is converted into knowledge can be rationally analyzed, then it can be computed. Interestingly, this is the quest of Artificial Intelligence, wherein the goal is to have a computer replicate human thinking. In fact, many attempts have been made to replicate the brain's neurological transfer of information in computing programs without success so far, other than in providing what is called intelligent decision support programs.
However, it seems that until they can install a heart into a computer, no computer will be able to replicate the human brain's ability to know. This is because, as neurological research has shown, information bits transferred by the neurons of the brain are loaded with parcels of emotional charges that trigger memories. When the memory is triggered, the brain accesses reservoirs of past experiences, sometimes unrelated experiences, to judge a certain situation, producing knowledge. Added to that is the human intuitive or psychic ability, which intensifies the depth of human knowledge. The external input of information into one's brain alone is not what produces knowledge, but those combined with internal inputs as well. The relevance of this to KM is that no matter how robust your computational and technological systems are, unless the human aspect of knowledge generation is understood and accommodated, a KM program will not be effective.
While IT is a crucial enabler of communication, and hence sharing and transfer of information and knowledge, it alone cannot capture the depth of tacit human knowledge. Though IT tools facilitate change of behavior, they will not necessarily enable or enhance the knowledge creation process. Trillions of dollars are spent every year on IT with very few returns, and studies of computers in the workplace have shown no increase in efficiency or effectiveness.11 In fact, overre-liance on IT by organizations implementing KM programs was found to be the main reason behind the failure of these programs.12 IT supremacy should not be confused with knowledge, and value, creation. Many organizations declare "We operate at Internet speed, and we have an internal response time of 10 minutes" without realizing that it is not the number of e-mails or user hits that are critical for knowledge creation. A survey by Ernst and Young of 431 U.S. companies in 1997 showed that almost all of the companies restricted their KM initiatives to creating an intranet (47%), creating knowledge repositories (33%), or implementing decision support tools (33%). Only 24% created networks of knowledge workers (a structural/cultural change), and 18% mapped sources of internal expertise (to locate tacit knowledge).13
To enable knowledge creation, the IT system should enable the conversion of tacit into explicit knowledge resources on a continuous basis, in order to retain as many resources as possible when employees leave. To do that, the IT system should accommodate the human/social aspect of knowledge creation. This human/social aspect of KM stems from the nature of organizational learning itself. While individual learning is a cognitive venture, group learning is more of a social activity in which the members interact, share, and challenge each other's interpretation, then act. Through this interaction, new knowledge is created and individual tacit knowledge is transformed into explicit organizational knowledge. The IT system/infrastructure should not only provide the necessary communication tools, but should also be designed to support the knowledge creation cycle of the core business processes of the organization. The IT system should also be based on a clear understanding of how individual knowledge is converged into organizational knowledge and vice versa.
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What is knowledge? Knowledge is to know!