Decision analysis techniques - Essay Example

Decision Analysis Techniques Decision making is a difficult task, it is not about what decision one should make, but it is about how one should make a decision, and why one should choose a particular option over the other available ones. At an organizational level it is the duty of CEOs and directorial board to make decisions for the whole firm. Decision making becomes tougher with increase in the number of stakeholders (Betsch & Haberstroh, 2014). The greater the number of involved party, the greater is the stress.

Further, decision making becomes tougher, when the available options are greater in number, because the probability of each event to be correct diminishes with increasing number of available options. Two very important elements of decision making are risk assessment and coping with uncertainty, because whenever a person or an organization has to make a decision, it is dependent on the future events (Anderson, Sweeney, Williams, Camm, & Cochran, 2015). No one can be certain about what will happen in the future; however, there is a probability for each to happen, and probability is nothing but a statistical term that suggest that what are the possibilities, and whether it is suitable to take a chance or not.

Risk assessment deals with the analysis of all the possible known events, and the likeliness of their occurrence. Meanwhile, coping with uncertainties is a bit tough, because one does not know what will be the next possible event. In this regards taking an initiative and starting from scratch is prone to uncertainty (Pettigrew, 2014). On the other hand risks are are determined over a period of application, and by collection of data, and during the assessment phase before the decision is finalized, the decision makers use the available data to predict the possible outcome, and choose the most practical option.

Over the years the research in actuarial sciences has led to the development of different techniques and protocols that are capable of determining the likeliness of the occurrence of an event. Some of the most commonly used techniques for predicting the possible consequences for a decision include the Sensitivity Analysis; the Maxmin criterion; the Expected Monetary Value; and the Sensitivity Analysis; Utility Function. Each of these models is designed to minimize the expected degree of loss.

The Maxmin criterion compares best outcome versus the worst, and then calculates the possibility of the occurrence of the events. The Sensitivity analysis calculates the maximum deviation from the expect events, and Utility function determines the attitude of decision making firm. Overall, there are limitations in all of the models mentioned above; however, their use has definitely provided some success, and therefore they are still regularly put into practice when it comes decision making. References Anderson, D.

, Sweeney, D., Williams, T., Camm, J., & Cochran, J. (2015). An introduction to management science: quantitative approaches to decision making. . Cengage Learning. Betsch, T., & Haberstroh, S. (Eds.). (2014). The routines of decision making. Psychology Press. Pettigrew, A. M. (2014). The politics of organizational decision-making. . Routledge.