Explain the different types of decision making environments?
The environment in which decision-making is done and in which decisions are implemented can be described along the following lines:
Certainty: In an environment characterised by certainty, full information is available on all the factors relevant to the problem and its solution. Information is also regarded as reasonably reliable and easy tonget and is not too expensive. In such a setting, the manager can have full knowledge about the future, about the alternatives and their outcomes. He is therefore in a position to choose the best alternative.
Another meaning of the state of certainty is that the manager considers only a few factors which are known and about which information is available. He ignores the other factors as irrelevant for his problem. In other words, he creates a closed system and tries to make his decision in that setting. He simply ‘abstracts away’ from the complexities of the decision situation by making certain assumptions.
Uncertainty: Under conditions of uncertainty, the manager faces a situation in which information is neither available nor reliable. Everything is in a state of flux; several random forces operate in the environment which makes it unpredictable. The variables change fast; their interaction is complex and the manager has no means of getting a grasp of them. The manager cannot have an idea about the outcomes of the alternatives courses of action or their probabilities. Even so, he had to tackle the situation, create some order out of chaos and make his decision by using his judgment and experience.
Risk: In this situation, the manager is in a position to get only some information about his decision situation. But he is not completely sure of the availability or the reliability of information. Though he may be able to develop alternative courses of action, he is less than definite about their outcomes. In other words, the expected results are not deterministic but only probabilistic because the future conditions cannot be predicted with accuracy in the absence of full information.