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Essay / Research Paper Abstract
This 3-page paper provides an explanation of how knowledge can be built out of a lot of information and data. Bibliography lists 2 sources.
Page Count:
3 pages (~225 words per page)
File: AS43_MTknowcrtn.rtf
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Unformatted sample text from the term paper:
an industrial economy, in which the farmers hung up their plows and took to the factories instead to mass produce goods for consumers that increasingly had more leisure time. The
industrial economy gave way to the service economy of the mid-to-late 20th century. These days, were involved in what we know as the knowledge economy. Though employees are still valued
for their skills and personality, it is their knowledge that many business gurus believe will be a competitive advantage for firms in the future.
But what, exactly, is knowledge? Is it bits, bytes and data? Leonard and Swap (2005) point out that knowledge is part of "deep smarts," in other words, the
intuition and judgment, as well as experience that many employees have, and bring to their job. They point out some examples of the "smarts," such as the venture capitalist who
has a "gut instinct" that a candidate who might seem perfect in every way just isnt a good fit with his portfolio, or the shop foreman who "sees" a potential
bottleneck problem on an assembly line and fixes it before it even occurs (Leonard and Swap, 2005). The trick, the authors point out, is ensuring that the knowledge sticks around
even after the employee has left (Leonard and Swap, 2005). The tricky part of knowledge transfer, however, is ensuring that the
right knowledge goes to the right people (Leonard and Swap, 2005). Too much information doesnt do anyone any good. For example, going back to the shop foreman example above, the
CEO of that same company would have little use for the foremans intuition about assembly lines - unless, of course, the CEO is an obsessive micromanager, but thats not what
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