DATA, INFORMATION, AND KNOWLEDGE

The terms data, information, and knowledge are often used interchangeably, but have significant and discrete meanings within the knowledge management domain.

Data are specific, objective facts or observations, such as “inventory contains 45 units”. Standing alone, such facts have no intrinsic meaning, but can be easily captured, transmitted, and stored electronically.

Information is defined by Peter Drucker as “data endowed with relevance and purpose”. People can turn data into information by organizing them into some unit of analysis. Deciding on the appropriate unit of analysis involves interpreting the context of the data and summarizing them into a more condensed form. Consensus must be reached on the unit of analysis.

Knowledge is a mix of contextual information, experiences, rules, and values. It is richer and deeper than information and more valuable because someone has thought deeply about that information and added his or her own unique experience, judgment, and wisdom. Knowledge also involves the synthesis of multiple sources of information over time. The amount of human contribution increases along the continuum from data to information to knowledge. The more complex and ill-defined elements of knowledge are difficult if not impossible to capture electronically.

Although knowledge has always been important to the success of an organization, it was presumed that the natural, informal flow of knowledge was sufficient to meet organizational needs. But managing knowledge has become far more complex, the amount of knowledge to manage far greater than ever, and the tools to manage knowledge far more powerful. Managing knowledge provides value to organizations in several ways.

REFERENCES

Strategic Management of Information Systems, 5th Edition International Student Version