Role of Computational Support in Decision Making- myassignmenthelp

Question: Write about theRole of Computational Support in Decision Making. Answer: According to Mintzberg, (2009), management is a craft that is based on several sciences. One of these sciences is decision making. Mintzberg suggested that there are three path ways to decision making seeing first, thinking first, and doing first. Doing first refers to trial and error. Seeing first refers to research while thinking first refers to a logical analyses of the steps to be taken. Decision theory is important to help leaders in business, government and all other fields understand a decision completely. The job of managers, essentially, is to take decisions that will drive the organization towards is primary goals.(Turban Aronson, 2001) A variety of computational support tools like statistics, data visualization, heuristics, etc. are available to manager to help them make these decisions. Any organization and leader must have a balance between normative decision making i.e. making decisions based on what ought to be, and descriptive decisions (decisions based on what is). A combination of these two approaches to decision making is prescriptive decision making or decision making that exploits the logical consequences of normative studies by a(McFall, 2015) Decision making requires an evaluation or imagination of the consequences that may occur, in case a decision is made.(McFall, 2015)(Simon, 1979) Computational support, in the form of data, metrics, statistical analyses, heuristics etc. help provide some certainty to this evaluation. Data analyses and forecasts may help validate decisions. As mentioned earlier, Mintzberg suggested that decision making is a craft, the accuracy of which depends on the context.(Mintzberg, 2009) Computational support helps provide this context. In addition, data assigns tangible, real numbers to vague, abstract ideas like utility, consumer satisfaction etc. The predictive power of computational science helps understand and visualize the shape and scale of the environment around us, thus, helping predict various variables such as returns, costs etc. at various points in time or at various points on the curve. They help understand all the risks associated with a decision. Thus, computational data helps validate the arm chair theories or intuitive thinking.(Simon, 1979)(Gigerenzer, 2017) Human decisions are complex and must take into account a variety of factors. No human activity takes place in a vacuum where the consumer is able to make free, fair and rational decisions. In fact, the more information that would be available, the greater would be the odds that humans would suffer from bounded rationality. Bounded rationality refers to the tendency to take sub optimal decisions due to mental fatigue that may be experienced due to making decisions based on too many choices. Theories or normative standards make various assumptions such as rationality of consumers but computational support helps verify the extent to which these are true (McFall, 2015)(Simon, 1979) Computational support utilizes the information provided by the information systems of an organization (human information, accumulated data and research) to process it and provides output in the form of comprehensive answers. Computation support does not only help make smart decisions but also help validate the decisions. This improves the confidence in those decisions.(Gigerenzer, 2017) Bibliography Gigerenzer, G. (2017, January 26). How do smart people make smart decisions? Retrieved April 13, 2018, from Youtube.com: https://www.youtube.com/watch?v=-Lg7G8TMe_A McFall, J. P. (2015). Rational, Normative, Descriptive, Prescriptive, or Choice Behavior? The Search for Integrative Metatheory of Decision Making. Behavioral Development Bulletin 20(1) , 45-59. Mintzberg, H. (2009, October 14). LancasterManagement: Henry Mintzberg on Decision Making. Retrieved April 13, 2018, from Youtibe.com: https://www.youtube.com/watch?v=DyvXu3lSSG0 Simon, H. A. (1979). Rational Decision Making in Business Organizations. THE AMERICAN ECONOMIC REVIEW , 494-514. Turban, E., Aronson, J. E. (2001). Decision Support Systems Intelligent Systems: 6th Edition. Upper Saddle River, NJ, USA: Prentice Hall.