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If we take this rule at face value, then the next obvious
thing to do is to find ways to be on the positive and productive side of any 80/20
power curve.
It is, therefore, desirable to identify the 20% of your
customers who are creating 80% of the revenues and vice versa. Discovering
this allows you to readily optimize your organization's energy and resources in
order to maximize its returns.
Although this is a popular example of what Decision Support
Systems can be used for, the actual breadth of support applications cover almost
every imaginable aspect of business; from customer support to production logistics
to long-term strategic planning.
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Implementing Decision Support Systems in the past were
not for the weak of heart. Early DS Systems required heavy usage of proprietary
and opaque data integration schemes. These less-than-adequate fixes were completely
dependent on creating a data bridge towards older legacy systems in order to get
access to key core information like customer accounts. Once retrieved, this
core information had to be combined with data flowing in from other systems in order
to provide a higher level of decision knowledge.
Modern DS Systems must do more than just provide various
business-related options for its users. To be effective, they must also have
the capacity to weigh those options along a scale that is aligned with the organization's
mission.
nwis.net has the required depth of technical expertise,
business process experience and value engineering knowledge to successfully design
and implement advanced Decision Support systems.
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