Knowledge Management as an Input
Many Knowledge Management (KM) platforms focus on collecting organizational information, or input: Storing, organizing, and sharing (STOS) information is viewed and practiced as a primary purpose of KM. These functions of STOS are not new and have been previously (and in some practices currently) “performed” by a filing cabinet to store, organize, and share information with office occupants. What many KM platforms have offered us is for large quantities of users to have access to large quantities of information with few, or no, space-time restrictions.
Note that KM platform functionality, to store more information for more users, is a quantitative improvement, as it is based on functional increase/decrease in time, speed, size, etc. — all are quantitative properties. Think of simple examples where the “-ER” is a driving force of progressive technologies: larg-ER TV sets, small-ER mobile devices, fast-ER download, etc. Whereas many of us welcome such changes, and we look forward to exploring the next generation of gadgets, an increase in the quantity of informational input is not a direct indicator of organizational efficiency; conversely, amalgamation of information may have a detrimental effect on organizational productivity.
Knowledge Management: From Input to Output
Progression from managing input to producing and managing output is a qualitative development, as original input (information) is converted into a qualitatively different/new output (problem solving and innovation).
How does an organization bolster its KM value from storing large quantities of information to producing explicit outcomes? Start simple — with definitions. If I tell you that we developed a knowledge management platform and you tell me that your organization is exploring to employ a new KM platform, we may very well be talking about different concepts and functions:
o Do you define “knowledge” (in KM) as information? expertise? problem driven tasks, etc.
o When we say, we want to manage knowledge (as defined above), do we want to collect it? develop it? implement changes, etc.
We cannot assume a uniform interpretation of these abstract notions. Thus, the whole concept of Knowledge Management is frequently miscommunicated and misunderstood. Definitions of concepts “Knowledge” and “Management” are likely to be different for different organizations. And they should be. The key is to define and communicate internally unique organizational knowledge management approach and to clearly communicate this need when looking for a KM platform. Is there a KM platform that can “do it all” and can address any KM need of any organization? Most likely not and most likely there shouldn’t be. Why? For the same reason that there shouldn’t be a vacuum cleaner that performs the functions of a microwave and a dishwasher.
Below we delineate a brief overview of four key KM functions offered by Cinteg. These functions constitute a natural systemic progression of organizational knowledge development from the input of content management to the output of innovation management.
Content Management allows users to perform basic store-organize-share functions, which establish valuable building blocks for further knowledge management practices. Content Management allows organizations to bring in and organize for future distribution and easy access codified organizational knowledge (written policies, procedures, and other internal documentation).
This is a more focused definition and application of KM (as distinguished from content, idea, and innovation management). Knowledge Management is a process of identifying possible integrations between relevant information/content and individual and collective expert knowledge.
Idea Management strives to achieve a meticulous balance between such antipodes as structure and flexibility. Structure establishes the focus for idea development; flexibility provides a safe environment for experimenting with multiple directions.
Once tacit ideas mature into explicit solutions and innovative approaches, the innovation management process supports in organizing and employing solutions to relevant applications. These applications turn into new organizational knowledge, which will become subject to a new cycle of content management.
Note that whereas the above described KM platform is outcomes driven, it does not offer an end-point. Any Complex Adaptive System (and we will address this topic in one of our upcoming KM maxims) sustains its agility via relentless renewal: outdated and futile knowledge elements are discarded; productive KM elements are applied to produce new knowledge.
What is the significance of outcomes driven Knowledge Management and does every organization need it?
Not every organization. It goes back to the questions of purpose of KM. If organizational knowledge is needed and used as a reference for employees to have access to policies, procedures, and other documentation, then input based KM is a better fit. If value of organizational knowledge is measured by usability of current knowledge to produce new knowledge in response to changes in the environment (competition, exploring new market sectors, etc), outcomes-based KM will support the organization in resolving challenges and opportunities of environmental changes.
MindAppster is a new start-up, based in New York and at the forefront of Knowledge Management ideas and applications, including how our understanding of Knowledge Management will affect future business decisions, large and small. MindAppster’s innovative products include Cinteg, the first real Knowledge Management application available for business in iOS and Android downloads. It actively empowers users to capitalize and collaborate on their knowledge.
To book a Knowledge Management consultation, contact email@example.com .