IS1060 Introduction
to information systems
38
Another way to categorise information is as being either
descriptive or
probabilistic. An example of descriptive information might be the layout
of a city on a map or the number of items in stock in a warehouse. An
example of probabilistic information would be an economic forecast of the
pound−yen exchange rate in two years’ time or the demand for items from
the warehouse over the next two months. Descriptive information can be
traced back to some
real world thing or phenomenon, but probabilistic
information can only be traced back to an abstract model that may use
some descriptive data.
Information may be of high or low
quality. A good team of economists
(with University of London degrees) will be expected to produce better
forecasts than a bad team (with degrees from other universities). How do
we know which team is good? We need more information –
the universities
they studied at, or better still, their previous record at forecasting.
Is more information better than less information?
Often what we implicitly mean by good information is exactly the right
information, with no wastage; not too much, not too little.
A paper phone
directory (something many of us use less and less) contains many names
and phone numbers, and if they were randomly organised they would be
of little use. So phone directories are organised systematically to enable a
particular number to be found assuming we know the name. In this way
we have potential
access to a lot of information, but can home in quickly
on what we need. In a managerial context, an excess of ill-organised
information is often described as
information overload. This is where
a manager or user receives too much information
and cannot determine
which parts are important or relevant. Computer-based information
systems should be designed based on a good understanding of people’s
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