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The rational decision-making model is a structured and sequential approach to decision-making, aimed at seeking precise solutions to well-defined problems using precise methods. The decision maker derives the necessary information by observation, statistical analysis, or modeling, and makes a systematic analysis of such 'hard' quantitative data to choose from the various alternative courses of actions.
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The rational approach to decisions is based on scientifically obtained data that allow informed decision-making, reducing the chances of errors, distortions, assumptions, guesswork, subjectivity, and all major causes for poor or inequitable judgments. Such an information and knowledge based approach promotes consistent and high quality decisions, and reduces the risk and uncertainties associated with decisions.
The rational method infuses the decision-making process with discipline, consistency, and logic. It is a step-by-step approach that requires defining problem, identifying the weighing and decision criteria, listing out the various alternatives, deliberating the present and future consequences of each alternative, and rating each alternative on each criterion. Such a sequential approach allows the decision maker to arrive at the optimal decision.
The methodology caters to addressing complex issues by breaking it down into simple steps, and considering all aspects of the problem with all possible solutions before making a final decision.
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The rational decision making process requires careful consideration and deliberation of data; this takes time, making this method unsuitable for quick-decisions. In the age of fast-paced changes, seizing the opportunity at the spur of the moment plays a big part in success, and the rational model does not live up to this task. Moreover, delay in making and implementing a decision may result in dilution of the perceived benefit of such an alternative, for the benefits may accrue only when taken at that time. As such, this model finds use mostly in making long-term and policy decisions rather than short-term or floor level operational decisions.
Rational decision-making is steeped in conservatism, and errs on the side of caution. Many a time, the company makes it big when managers or leaders follow their gut instincts to take a gamble and seize an opportunity. Similarly, many times success depends on being the pioneer in the field, or the first to launch a new and untested product, which may find wide acceptance. Limiting decisions to analysis of available data may impede such approaches. The unavailability of past tends or information about such new products or opportunities causes rational decision makers to opt for more secure and conventional options.
Rational decisions are more structured and informed, but people making such decisions usually become unpopular, with the rank and file perceiving them as insensitive autocratic leaders. The basis of rationality is profit maximization or bottom line orientation, and interpersonal relations or emotions have no place in what constitutes “rationality.” Reliance on cold facts requires ignoring or paying secondary importance to sensitive human relationships. Over-reliance on the bottom line, with scant regard to human values, slowly but surely erodes the organization of its intellectual capital and resilience, sowing the seeds for its eventual destruction.
The fruits of rational decisions become apparent only in the long run, and the rank and file usually do not get to see immediate or tangible returns or benefits of the decision. This combined with the insensitivity to human emotions causes a negative perception.
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While rational decisions strive to remove subjectivity, assumptions, and uncertainty from the decision-making process, the method itself is based on many assumptions.
The rational model assumes that the decision maker has accurate information and knowledge of the situation, the underlying cause and effect relationships to evaluate various situations, and the necessary tools and competence. This need not always remain the case. Very often the quantity, quality, accuracy, and integrity of information may be found wanting. Moreover, the reliance of scientific data to generate the most optimal choice works well in theory, but human ability has limits to gather, process, and understand all the information needed to optimize a decision outcome. Such defects in information directly translate to a defect in the decision.
This model also assumes that conditions remain stable. The real world always remains in a constant state of flux and, very often, the information needed to make a decision either remains incomplete or keeps constantly changing, forcing the decision makers to improvise.
Ultimately, how people make decisions depends on their culture, conventions, experience, education, and many more factors. The pros and cons of the rational decision-making approach suggests that it finds use as a facilitating tool to aid decision-making and supplement the existing system in certain situations. Imposing it as a decision-making system by uprooting the existing system may become counterproductive.
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- Simon, Herbert, (8 December 1978) A. "Rational Decision Making in Business Organizations." Nobel Memorial Lecture. Carnegie-Mellon University, Pittsburgh, Pennsylvania. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.117.7589&rep=rep1&type=pdf on July 18, 2011.
- Carey, W.P. "Rational versus Holistic: Two Very Different Approaches to Executive Decision Making." Retrieved from http://knowledge.wpcarey.asu.edu/article.cfm?articleid=1281 on July 18, 2011.