I generally don’t spend time trying to define knowledge and knowledge management (KM). Such attempts can lead to long, unsatisfying, and ultimately useless debates. And I definitely avoid referring to a continuum of data, information, knowledge (and sometimes wisdom), often represented in the form of a pyramid. I don’t find any value in this.
I use this definition of knowledge management from Ellen Knapp, former Chief Knowledge Officer of Coopers & Lybrand: Knowledge management is the art of transforming information and intellectual assets into enduring value for an organization’s clients and its people.
I add these statements about KM:
- The purpose of knowledge management is to foster the reuse of intellectual capital, enable better decision making, and create the conditions for innovation.
- KM provides people, processes, and technology to help knowledge flow to the right people, at the right time, so they can act more efficiently, effectively, and creatively.
- Knowledge management enables Sharing, Innovating, Reusing, Collaborating, and Learning (SIRCL).
I use this definition of knowledge, often attributed to Peter Drucker: The knowledge that we consider knowledge proves itself in action. What we now mean by knowledge is information in action, information focused on results.
In The Problem with the Data-Information-Knowledge-Wisdom Hierarchy, David Weinberger wrote: The emphasis in all these cases is on knowledge being “actionable” because of the business context, and on knowledge being a refinement of information because that’s how we extracted value from data. That may be a useful way of thinking about the value of information, but it’s pretty far from what knowledge has been during its 2,500-year history. Throughout that period, Plato’s definition has basically held: Knowledge is the set of beliefs that are true and that we are justified in believing. Indeed, we’ve thought that knowledge is not a mere agglomeration of true beliefs but that it reflects the systematic and even organic nature of the universe. The pieces go together and make something true and beautiful. More, knowledge has been the distinctly human project, the exercise of the highest and defining capabilities of humans, a fulfillment of our nature, a transgenerational treasure that it is each person’s duty and honor to enhance.
In The Knowledge in Knowledge Management Fred Nickols defined three other terms often used in knowledge management:
- Explicit knowledge is knowledge that has been articulated and, more often than not, captured in the form of text, tables, diagrams, product specifications and so on.
- Tacit knowledge is knowledge that cannot be articulated. As Michael Polanyi (who coined the term) put it, “We know more than we can tell.”
- Implicit knowledge is knowledge that can be articulated but hasn’t. Its existence is implied by or inferred from observable behavior or performance.
In the next post I will present additional definitions as part of an overall framework.
Knowledge capture includes making entries into databases; examples of this information include personal profiles, repositories, and knowledge bases.
Content captured as part of a KM program includes documents, communications of various types, and training. Details each type, how to capture.
Knowledge capture includes collecting documents, presentations, spreadsheets, records, etc. that can be used for innovation, reuse, and learning.
KM thought leaders; Mary Lee Kennedy is the Executive Director of ARL and led design and implementation of KM strategies at Microsoft