ANALY TIC S AC ROS S T H E E N T ERP RISE
continually analyze data to verify that previously detected relationships are still valid and to discover new ones. Fortunately,
major discontinuities with data do not happen very often, so change generally happens gradually. Social media sentiment,
however, has a much shorter half-life than
most data.
Using relationships derived from past
data has been repeatedly demonstrated
to work better than assuming that no relationships exist. The relationships that
have been detected are likely correlation
rather than causality. However, these relationships, if detected and acted upon
quickly, may provide at least a temporary
business advantage.
You don’t have to understand analytics technology to derive value from it.
For a long time, many business leaders
expressed the opinion that mathematics should be used by only those who
understood the details of the computations. However, in recent years this view
has been changing, and analytics is being treated like other technologies. You
must learn how to use it effectively, but
it is not necessary to understand the inner workings in order to apply analytics
to business decisions. You have to apply
analytics methods in the context of the
problem that is being solved and make
the results accessible to the end user. But
just as the user of a car navigation system
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does not need to understand the details
of the routing algorithm, the end user of
analytics does not have to understand the
details of the math.
Typically, making the results accessible to the end user involves wrapping the
math in the language and the process of
the end user. Also, the analytics can be
embedded deep inside things so that the
user does not see it, like in supply chain
operations. Analytics should be usable by
anyone, not just those with Ph.D.s in statistics or operations research. Some users will want to understand the algorithms
and inner workings of an analytics model
in order to