On my last post I discussed the difference between data and information, based on Davenport and Prusak (2000) discussions. Following these authors, today I bring their concept of knowledge.
First it is needed to highlight again that knowledge is a very complex matter. Epistemologists spend their lives discussing what means to actually ‘know’ something. Therefore, there is no need to pretend to have a definitive concept. What I, as well as many other authors focusing on knowledge management and innovation, present is a working definition of it.
Knowledge is a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the mind of knowers. In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms (Davenport and Prusak, 2000, p. 5).
As said before and presented again in the concept, knowledge is a complex matter. It manifests only in the human mind but in different aspects such as experience, values, and insights. Knowledge speeds up problem-solving, by transforming past experiences – read from books, articles or company manuals and norms; or lived personally – into insights and solutions. Sometimes knowers not even know how they came up with solutions, seeming to others to be some sort of mystical power, when it is simply embodied knowledge.
Lundvall and Johnson (1994) make some interesting distinction from these different types of knowledge:
- know-what is related to knowledge about facts. Here knowledge is close to what is commonly defined as data, information such as the year when the Second World War ended, or the proportion of water in the human body. This type of knowledge is highly codifiable and available through information systems;
- know-why is related to understanding how things around us work. This is related to scientific knowledge about how the human body reacts to medicines or why society reacts to certain events. Knowledge here is also codifiable through books, articles, reports that can be shared more easily;
- know-how is associated to skills, how to do things. The difference is that the owner of this type of knowledge might not know why things happen like it does, but he knows how to do it anyway. Experience and practice are key issues for building up this kind of knowledge that can be associated to great chefs, for instance, that performs the same cooking recipe better than the average cook. He might not be able to explain why this difference in performance exists. This type of knowledge is tacit in nature and therefore to codify it is complex for the owner; and
- know-who relates to networking and social connections to the people that can influence or support innovation process. Sometimes knowing specialists or decision makers can facilitate connections to necessary inputs for the innovation process. This type of knowledge is also considered tacit since networking requires trust between the parts and trust can not be easily transferred.
Next post I address how knowledge differs from information and data, and the issue of transferability.
DAVENPORT, Thomas; Prusak, Laurence (2000): Working Knowledge: How organizations manage what they know. Boston: Harvard Business School Press.
LUNDVALL, B.A.; Johnson, B. (1994): The Learning Economy. Journal of Industry Studies, Volume I, Number 2.