decision making and problem solving. Determine whether it makes sense to
distinguish between the two.
making can be considered as a deliberation that is figuring out what action
need to be taken in order to maximize the expected benefit. Due to uncertainty
there may be no assure that the result of the action might be the one meant,
and the great one can hope for is to maximise the chance of an ideal outcome.
The process rests on the idea that an excellent decision is one which outcomes
for an excellent decision-making process that considers all essential elements
and is explicit about decision alternatives, preference and uncertainty (Marek
and Roger, 2002).
on D’Zurilla and Chang (1995) “problem solving refers to the rational look for
an answer through the application of problem solving abilities and techniques
which are designed to maximise the chance of locating the “best” or most
adaptive solution for a particular problem”.
making and problem solving are quite similar activities but the foremost
distinction among the two are problem solving is a technique whilst decision
making is a process. Some people consider decision making as the first three
steps in problem solving that is problem definition, problem analysis and
generating possible solution. Others use the terms interchangeably. Another
name of problem solving, is solving a problem. This is means a method in which
a group or a person makes something advantageous out of problem. Meanwhile,
decision making is the process that is carried out typically for the duration
of problem solving. Decision making is the important thing so that a person can
achieve the best conclusion in problem solving. Problem solving is more an
analytical aspects of thinking and also use the intuition in getting the facts.
Meanwhile, decision making is more of a judgement where after a person think
something then the person will take an action. However, decision making and
problem solving need a certain set of abilities for every different to be
is DSS, Business Intelligence, Business Analytics, and Predictive Analytics?
How these concepts are related to each other.
Based on Marek and Roger (2002), “decision
support systems are interactive, computer-based systems that aid users in
judgement and preference activities. It’s provide the information storage and
retrieval however decorate the traditional facts get entry to and retrieval
capabilities for model constructing and model-based totally reasoning. Its
assist framing, modelling and problem solving.
Intelligence (BI) is an umbrella term that combines architectures, tools,
databases, analytical tools, applications and methodologies. It’s most
important goal to enable interactive access (from time to time in real time) to
data, enable manipulation of these data, and to provide business managers and
analysts the capacity to behaviour appropriate evaluation.
application and strategies for collecting, storing, analysing and imparting get
admission to data to assist users make higher and strategies decisions and
additionally referred to as an analytical processing, business intelligence
tools or business intelligence applications, that is business analytics.
analytics is using statistical techniques and data mining to decide what’s
likely to appear inside the future. Business use predictive analytics to
forecast whether customers are probable to interchange to a competitor, what
customers are likely to shop for, how possibly customers are to respond to an
advertising, and whether or not customer is creditworthy. Predictive analytics
also have used in sports team to discover the gamers maximum possibly to make contributions
to a group’s achievement (Efraim et al., 2007).
These concepts are related to each other where Business
Intelligence (BI) uses a data warehouse, whereas decision support systems can
use any data supply consisting of dat warehouse. Most decision support system
(DSS) are constructed to support decision making at once, while most business intelligence
(BI) systems are constructed to provide data that it is believed will cause
progressed decision making. Business intelligence (BI) has an approach to
executive orientation while decision support system (DSS) are commonly oriented
toward analysts. Business intelligence (BI) systems have a tendency to be
evolved with commercially to be had tools, whereas decision support system
(DSS) generally tend to apply more custom programming to cope with issue that
can be unstructured. Decision support system (DSS) methodologies and tools
originated in large part in academia, whereas business intelligence (BI) arose largely
from the software industry. Many business intelligence (BI) tools, such as
information mining and predictive analysis, have turn out to be taken into
consideration, decision support system (DSS) tools are properly. Technically, business
analytics provides a further measurement to business intelligence (BI) models
and answer methods. These are often buried so deep within the tools, however,
that the analyst need not get his or her hands “dirty.” Typically,
the terms are used interchangeably.
it is important to focus on the effectiveness of a decision, not necessarily
the efficiency of making a decision?
The effectiveness of a decision
impacts a corporation for as long as the decision subjects, and as
significantly because the decision scope. The efficiency of creating the
decision influences most effective the decision-making procedure itself. The
different among effectiveness of a decision-making and efficiency in
decision-making enables decision support systems (DSS) analysts understand the
impact of decision support system (DSS) on decision behaviour. Keen and Scott
Morton (1978) present the subsequent reasons of these important concepts,
“Effectiveness in decision making requires us to deal with the manner of
figuring out what have to be carried out at the same time as efficiency in
decision making addresses the way performing a given defined task to be able to
obtain outputs in addition to feasible, relative to a few overall performance
The growing efficiency generally
takes the form of minimizing time, cost or effort to finish a decision making
activity. Effectiveness specializes in what activities must occur, enhancing
the decision method, and improving data used for a decision making,
specifically facts and content material used inside the decision process. A
focal point on effectiveness requires decision-makers to evolve and examine, to
make a responsive adjustment to modifications within the environment for and
within which they make decisions (after Bennett 1983, p.2). “Good” decisions
are extra effective decisions and consequently decision support system (DSS)
must improve content material utilized by a decision maker and improve the