Abstract :
Making decisions is certainly the most important task of a manager and it is often a very
difficult one. This paper offers a decision making procedure for solving complex problems step by
step. It presents the decision-analysis process for both public and private decision-making, using
different decision criteria, different types of information, and information of varying quality. It
describes the elements in the analysis of decision alternatives and choices, as well as the goals and
objectives that guide decision-making. The key issues related to a decision-makerʹs preferences
regarding alternatives, criteria for choice, and choice modes, together with the risk assessment
tools are also presented. The domain of decision analysis models falls between two extreme cases.
This depends upon the degree of knowledge we have about the outcome of our actions. One "pole"
on this scale is deterministic. The opposite "pole" is pure uncertainty. Between these two extremes
are problems under risk. The main idea here is that for any given problem, the degree of certainty
varies among managers depending upon how much knowledge each one has about the same
problem. This reflects the recommendation of a different solution by each person. Probability is an
instrument used to measure the likelihood of occurrence for an event. When you use probability to
express your uncertainty, the deterministic side has a probability of 1 (or zero), while the other end
has a flat (all equally probable) probability. The following sections of this paper are arranged as
below. After introduction in section one, Decision Making under Pure Uncertainty are disscussed in
section two. Section 3 and 4, are allocated to decision making under risk and bayesian approach
respectively. Fifth section talks about decision tree and influence diagram and finally the paper will
end with a brief conclusion.
