Program capstone IP2 - Essay Example

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However, it must always be remembered that there may not always be a correct decision among the choices available. There may have been a better choice that wasn’t deliberated on, or the…
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Program capstone IP2
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MEMORANDUM Chief Executive Officer (CEO). Senior Manager. RE: Good decision making. Decent decision making is the act of choosing between two or more progressions of action. However, it must always be remembered that there may not always be a correct decision among the choices available. There may have been a better choice that wasn’t deliberated on, or the right information may not have been available at the time.
Even though there are no “right” or “wrong” assessment criteria, there are better and also poorer ones, or at least more useful and non-useful ones. The characteristics of good evaluation criteria includes Accuracy and Unmistakability, meaning that a clear and accurate relationship exists between the criteria and the real consequences, comprehensive but concise, meaning that they cover the range of relevant consequences but the evaluation framework remains systematic and manageable and there are no redundancies, direct and ends-oriented, meaning they report directly on the consequences of interest and provide enough information that informed value judgments can reasonably be made on the basis of them, measurable and Consistently Applied to allow consistent comparisons across other options. It clearly elaborate the criteria should be able to distinguish the relative degree of impact across other options. The exclusion of the qualitative descriptions of impact may not be there, or impacts that can’t be physically measured in the field.
For good decision making, you should include the following metrics into your framework to minimize the chances of making a bad decision. First perform a condition Analysis, what is motivating the need for a choice, what might occur if no decision is made, who will decision impact either indirectly or indirectly, what data, exploration, or supporting information you have to validate the inclinations driving your decision. Secondly, Focus your Decision to Public Scrutiny and remember there are no decisions which are private. Rather the details surrounding any decision will likely come out. In addition, conduct a Cost/Benefit Analysis, by doing the potential benefits derived from the decision justify the expected costs. Assess the Reward or risk Ratio; what are all the likely rewards, and when compared with all the potential risks are the odds in your favor, or are they stacked against you. Furthermore, Evaluate whether it is the Right thing to do. I.e. standing behind decisions that everyone supports doesn’t particularly require a lot of boldness. On the other hand, standing behind what one believes is the right decision in the face of tremendous controversy is the stuff great leaders are made of. There are many areas where compromise yields important benefits, but your value system, charisma, or your integrity should never be compromised. The other step is making the decision: Perhaps the important issue is, you must have a bias to the action, and be willing to make choice. Furthermore, you must learn to make the best decision possible even if you possess a data set which is not complete. Don’t fall prey to study paralysis, but rather make the best decision possible with the information at hand using some of the methods stated above. Opportunities and not static, and the law of diminishing returns applies to most opportunities in that the longer you wait to seize the opportunity the smaller the return typically is. The last technique to remember is that always have a back-up plan: The genuine assessment of a leader is what happens in the moments following the realization they’ve made the incorrect choice. Great leaders understand all plans are made up of both variables and constants, and that sometimes the variables may not favor you. Smart leaders always have a contingency plan knowing circumstances can sometimes fall beyond the boundaries of reason or control – no “Plan B” equals a flawed plan.
Assumption can be defined as the recognized cause and effect relations, estimations of the existence of a fact from the known existence of other fact. The major assumption made in various organization includes, an assumption made to address data gaps.
The techniques used to develop TEPs requires three types of environmental data for specific chemicals: physical-chemical and environmental process data for fate and modelling exposure, and risk assessment value data for estimations of risk. Since chemicals that are not assigned TEPs are not included in the ranking system, it is imperative to make use of available data as much as possible. The other assumption is modeling total human exposure, human exposures to chemical concentrations resulting from an environmental release were modeled using factors that are representative of an average member of inhabitants, and doesn’t address the risks posed by atypical exposure patterns in some populations.
The importance of making accurate critical assumptions often makes the difference between success and failure of businesses. For the success, the more your assumption becomes accurate, the lower your risk of failure–and the higher your odds of success.
To test the credibility of ”an automobile manufacturers assumption that the demand for SUVs would continue because gas prices would continue to rise “ you will use the efficiency which is achieved by improvement of technology, so that less energy is consumed while getting the same or better results. For this assumption “An airlines assumption that there was a need for an airline that provided no added amenities” you should consider the corporate road warriors and luxury-focused on those traveling for leisure, it’s often comfort, not cost, that rules but in the current economic downturn and spell of blurs, first-class and business-class airline seats may be an endangered species.
Lindblom, C. E. (1972). Strategies for decision making, Urbana: Dept. of Political Science, University of Illinois.
Hacker, M. (1985). Assumptions. New York: Knopf:
Wisniewski, M. (2006). Quantitative methods for decision makers (4th Ed.). Harlow, England: Prentice Hall/Financial Times. Read More
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