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Businesses Make Decisions On A Daily Basis. Term Paper

Businesses make decisions on a daily basis. Some of these decisions affect man people in the organization, where other decisions are minor and only impact a few people. A decision-making procedure based on sound information and data leads to effective conclusions. Today's fast-paced business environment demands the making of informed decisions based on critical thinking skills. It is our thinking that determines the extent to which we think through the implications of the decisions we make. It is our thinking that determines whether we can identify the assumptions we are making, and whether we should questions those assumptions. A number of different decision-making processes have been suggested. Depending on the type of decision faced, some techniques are more appropriate than others. As a supervisor for United Parcel Service, overseeing 40 individuals who must process and drive thousands of packages to the San Diego airport each morning at 6:30am, organization is essential in my operation. A sound decision-making process can help to expedite procedures. One form of decision is knowledge-based Improvement (KBI), which "is based upon the use of discrete-event simulation in combination with artificial intelligence methods. The purpose is not to replace the human decision-maker, but to develop a means for identifying 'good' practice and for sharing experience (a learning experience)" (Robinson et al.). The fundamental idea in knowledge-based industries is that the company appreciates skill and knowledge over time or it loses performance of those individuals. Knowledge improvement embraces the concept that knowledge can make a difference to performance, but that somehow it should be managed better.

Knowledge-based-based improvement, consists of five key stages: 1) Understanding the decision-making process; 2) Data collection; 3) Determining...

al. 915).
The first step is determining the experts' decision-making strategies by clarifying the individual parts of the decision-making process: decision variables, decision options, attribute variables and attribute levels. Having identified the decision components, the next step in determining the decision-making strategies is to collect examples of decisions from each expert. The third strategy can be represented by the use of a separate decision tree for each decision-maker. The next step in the KBI methodology is to assess and compare the performance of each expert. The last stage uses the decision-making strategies of the most efficient experts as starting point to search for an improved strategy. The search could be made informally by combining strategies and by making incremental changes. Alternatively, heuristic search methods could be implemented, in order to seek for improvements (ibid. 916-917).

Once the data is acquired, the company can decide which decision-makers will analyze the information and make final choices. Convergent or critical thinking is utilized to separate the promising few options from the trivial many possibilities and develop action plans to begin implementing the ideas. At Shell company (Stymne et. al.), knowledge communities are brought together to solve or advise on a particularly significant challenge -- for example, turning round a business in difficulty. Community members may be invited or seconded to work on the problem directly. The knowledge management program in BP Amoco has been bolstered by the CEO's drive to create a learning organization (Prokesh 152). The initial approach captured what everybody knows and connected people who know.…

Sources used in this document:
References Cited

Foreman, Charles W.L., "Modeling and Improving Human Decision-Making," from the Management Course for Presidents, 3-4.

Prokesh, S.E. "Unleashing the power of learning: an interview with British Petroleum's John Browne." Harvard Business Review, 75 (September -- October 1997), 146 -- 168.

Robinson, Alifantis, et. al. "Modeling and Improving Human Decision-Making with Simulation." Proceedings of the 2001 Winter Simulation Conference,

B.A. Peters, J.S. Smith, D.J. Medeiros, and M.W. Rohrer, eds.
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