Management of Technology


Management of Technology


It is commonplaces currently to mention that data is that the most important quality to be
managed. however not many of us - significantly not practitioners - invest considerably time
in learning regarding what data extremely is and the way totally different data management is
from info management. significantly IM-focused people or computer code vendors
tend to treat BVI and klick because the same issue. However, the terribly act of managing and
management science itself are often seen, to an oversized extent, because the application of human
knowledge in associate structure context to attain desired outcomes. Thus, managing
knowledge are often outlined terribly narrowly or generally betting on an individual's specific
goals or perspective.
A slender definition of klick is sometimes related to the readying of
information management systems, whereas broad definitions ar typically related to
the softer aspect of management like leadership vogue, structure culture, rewards
and recognition programs, etc. during this article, we are going to argue that despite the growing
focus on info management systems as a key enabler of klick, knowledge
management as associate rising discipline depends on the fusion of the contributions of
many disciplines, as well as philosophy, psychology, sociology, management and
economics that till recently failed to cross methods.

DEFINING info AND data
In order to completely perceive the variations between IM and metric linear unit, it's necessary to
review basic definitions {of information|of data|of data} and knowledge. There has been no shortage of
authors providing their own definitions of those terms. Thus, during this paper, we'll not
present our own definitions, however rather discuss the management implications of
definitions provided by some leading authors. In general, the definitions of knowledge
tend to be way more uniform and fewer complicated than the definitions of information.
Information is typically outlined as:
• "Organized data" (Saint-Onge, 2002);
• "Data dowered with connexion and purpose" (Drucker, 2001);
• "Interpreted data" (Probst et alii, 2002).
These definitions area unit almost like several others that time to the very fact that info
includes human participation within the purposeful organization of information.
Defining data, however, could be a far more complicated task. a technique to tackle
this task is to travel back to the roots of the Greek word knowledge, which implies absolute
truth. That appears broad enough to incorporate several sequent definitions. What is
absolute truth and the way to achieve it, however, are queries plaguing several
generations of philosophers since philosopher and philosopher. we'll not discuss all the
perspectives that a lot of nice thinkers have offered since then, however highlight that 2
main views are place forth regarding however we tend to learn and acquire knowledge: empiricism
and rationalism (Gordon, 2002). The interaction between authors returning from these 2
camps provide North American nation this a lot of accepted understanding regarding data. Namely,
knowledge will solely reside in one's mind and is that the results of human expertise and
reflection supported a collection of beliefs that area unit at an equivalent time individual and collective.
The same complexness is highlighted by a number of the leading authors within the
emerging field of information management. for example, Davenport & Prusak (1998)
define data as a combination of fluid experiences, values, discourse info and
intuition that has a structure to guage and incorporate new experiences and
information. It originates and is applied within the minds of people. this is often almost like
Nonaka & Takeuchi's definition (Nonaka & Takeuchi, 1995): "Knowledge is true and
justified belief.

We might highlight several different definitions, however in our opinion, they might not
add considerably to any instructive  the distinction between info and
knowledge. In general, all authors purpose to the quality of data compared to
information. The key distinction is summarized by the role contend by human
beings. within the case of data, as straightforward because it could seem, people play a
prominent role as creators, carriers, conveyors and users. In distinction, within the case of
information, these same functions will happen "outside" humans and while not their direct
influence.
KEY DIFFENCES BETWEEN info and data
MANAGEMENT
We will analyze the variations between IM and kilometer in line with 5 totally different
dimensions :
• interaction Between info and data
• IM and kilometer Projects: totally different scopes, approaches and mensuration systems
• structure Learning and kilometer
• Broad ideas of kilometer
• protective Intellectual Capital: IM and kilometer views
Interplay Between info and data
From a management perspective the key distinction between info and data
is that info is way additional simply known, organized and distributed.
Knowledge, on the opposite hand, cannot extremely be managed as a result of it resides in one's
mind. Thus, kilometer is actually restricted to making the proper conditions for people to
learn (using info and experiencing the world) and apply their data to the
benefit of the organization. the appliance of one's data will, hopefully, thereby
be translated into relevant info that's shared and used, new merchandise and actions
that create price.
This understanding of data and kilometer will leads one to have faith in the wellknown
"spiral of data creation" projected by Nonaka & Takeuchi (1995).
Although the authors accept as true with Nonaka & Takeuchi's read of however data is
created, we discover it vital to focus on that they are doing not clearly make a case for the various
between info and data. In our opinion they use the term "explicit

knowledge" virtually as a word for the word "information". This interchange, in our
opinion, could have crystal rectifier several practitioners that scan their contribution to quickly to assume
too much in terms of knowledge Management (IM) rather than data
Management (KM).
One of the refined aspects of the 2 distinctive approaches mentioned within the
paragraph higher than is that as data is became info (documents, bestpractices,
databases, etc) a change happens. info isn't an equivalent as
knowledge in an exceedingly totally different state (outside somebody's head). throughout the method of
speaking and writing people don't seem to be simply "downloading" (using the figure of a
typical transfer from the Internet) what they understand. They are, in fact, learning and
transforming what they understand into one thing that's materialized as symbols which
resembles what they understand, however that's inherently totally different from what they understand. As
Polany (1997) once said: "We understand over we are able to tell". once the desired
knowledge is somewhat additional "easily" translated into statute info, we have a tendency to tend not
to notice such a vital distinction (e.g. directions to work a occasional machine).
However, once the desired data is embodied in one's physical skills (e.g. soccer
player) and/or is said to complicated data that needs important expertise and
analysis of the many variables (e.g. family doctor), then the inherent troublesome of changing
knowledge into info becomes additional evident.
A very fascinating perspective that clearly distinguishes klick from IM has been
offered by Von Krogh, Ichijo and Nonaka (2000). These authors engineered upon Nonaka's
initial work and suggests the concept that it's impracticable to manage data.
According to their read, one will solely prepare, and hopefully completely have an effect on the
knowledge creation method through several social control actions and choices. The key
for these authors isn't the readying of refined info technology, but the
facilitation of conversations regionally and progressively among folks in several
locations. Thus, klick is concerning supporting conversations and supporting a humanistic
perspective of labor. it's additionally deeply implanted within the values of the organization since
knowledge in their opinion is additionally true and even belief, hi our opinion, the
perspective offered by these authors highlights another key distinction between IM and
KM: IM is sometimes not involved with the particular method of knowledge-creation or
innovation.
KM systems area unit essentially way more human-centric than IM systems or
initiatives. Thus, klick practitioners should acknowledge that increasing the richness and
quality of the out there info sources and therefore the instructive  capability of staff
is far additional fascinating than merely increasing the amount of knowledge out there.
Information in and of itself will be mindless and digressive while not correct context. Thus, two
of the most issues of klick (and historically not of data management) ought to
be (1) the availability of context for and validation of accessible info and (2)
increasing the connections among individuals (who have knowledge) that may doubtless not
occur while not the assistance of a klick system. With these goals in mind, context regarding the
main info sources (especially unstructured information) is considerably enriched
by as well as further details like (Terra & Gordon, 2002):
• United Nations agency created the information;
• what's the background of the authors;
• wherever and once was it created;
• however long can the data be relevant, valid and accurate;
• United Nations agency valid the information;
• United Nations agency else may well be interested or has similar knowledge;
• wherever was it applied or verified to be useful;
• What different sources of data ar closely related;
• the way to check a number of the ideas (e.g. through templates and simulation).
IM and

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1 comments:


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