Decision-making

The decision-making process is a central element of the risk management system. It is a discipline in its own right. This stage concerns decisions on implementation of selected risk management strategies and measures. In consultation with all parties concerned, weighed alternatives are selected and decisions are made for their implementation. The decision may involve implementation of measures to reduce or eliminate unacceptable risks. When appropriate, risks ate eliminated, reduced or transferred in the most cost effective manner. When they are justified, risks are retained or accepted. 

In many industries or businesses, because of the wide range of complex factors and conditions, decision-makers at all levels are faced with difficult decisions. The process involves not only consideration of technical factors, but also political, social, economic, and many other factors. Further, the process is complicated by the variety and complexity of choices and the environment in which they are made, multiple and often conflicting objectives, different perspectives on risks, the uncertainty and the sensitivity of decisions. It is, therefore, important to provide decision makers with valid, reliable and sufficient information to ensure tMt they have taken decisions to their best knowledge. 

Preparation and communication of action plans to deal with risks include  

Documentation of strategies, actions, goals, and schedule dates  

Chemical supply chain including transport and transport-related activities planning  

Should I intervene internally or externally Internal support is needed at times when you must clarify goals, facilitate decision making, and emphasize standards of excellence. External support is when you must work in the organization to give the team credibility. External support may be gathering information from other functions so the team can function efficiently. 

According to the psychodynamic approach, learned patterns of family dynamics influence leadership. Insight into one s own personality is thus beneficial. This approach is criticized because it is based on the psychology of the abnormal and focuses primarily on the personalities of leaders and followers. As such, it does not lend itself to traditional training. 

leaders must evaluate the importance of a decision so they can allocate the appropriate resources and time to it. Leaders must consider who will be impacted by the decision, both inside and outside the organization. As leaders progress with a decision, they must weigh all options. There may be obvious solutions, but new information and technology may prove other solutions to be more viable. This is where the brainstorming or Delphi methods may help identify stakeholder concerns and buy-in for the decision from affected parties. 

make the decision. Not everyone, even with a consensus, will back you 100 percent. People fear the consequences of making a bad decision. If you make a bad decision, admit it, make the right decision, and move on. 

If forced to summarize the purposes of study design, experimental methodology, and statistical analysis in one sentence each, the following might be suitable  

Expanding on the last point, numerical representations of biologically important information facilitate answers to questions that arise during the process of new drug development and thus provide the basis for making the best possible decision at that time given the best evidence available at that time. (It is quite appropriate to use later additional information to come to a new decision.) 

The title of this section may be surprising at first. The process of science, one may think, produces clear-cut answers, and scientists pride themselves on the objectivity inherent in their disciplines and, accordingly, on conducting business in an objective manner. Clinical science, clinical research, and clinical practice, however, require a combination of objective information and informed judgment. Since all judgment is subjective, subjectivity is an integral part of clinical science, clinical research, and clinical practice. 

In this context, the word subjective does not carry the potentially negative connotations that may accompany it in other realms. All of us would likely welcome the medical opinion of a very experienced and well-informed clinician when making a decision concerning several possible therapeutic regimens. The opinion offered would be the clinician s best clinical judgment based on the best available evidence at that time. In the context of study design, Piantadosi (2005) made the following comment  

It is a mistake not to recognize the subjectivity that is present, or to design and interpret studies in formulaic ways. We could more appropriately view experimental designs as devices that encapsulate both objective plans along with unavoidable subjectivity (p.131). 

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The main advantage of this approach is that the designer can keep control of the basic decisions and interact with the design as it develops. By sta dng in control of the basic decisions, the intangibles of the design can be included in the decision making. 

However, in the early stages of design, decisions that have important safety implications must be made based on an incomplete picture. Let us explore simple quantitative measures which can be used to assist decision making in the early stages of design. 

Public consultation and participation aims to assure the quality, comprehensiveness and effectiveness of the EIA, as well as to ensure that the public s views are adequately taken into consideration in the decision-making process. 

Decision-making on the project involves a consideration by the relevant authority of the EIS (including consultation responses) together with any material considerations. 

At each stage of a field life cycle raw data has to be converted into information, but for the information to have value it must influence decision making and profitability. 

As will be shown in the next section, the methods discussed so far do not take account of the uncertainties and lateral variations in reservoir parameters. Hence the accuracy of the results is not adequate for decision making. The next section introduces a more comprehensive approach to volumetric estimation. 

The benefit of using the decision tree approach is that it clarifies the decision-making process. The discipline required to construct a logical decision tree may also serve to explain the key decisions and to highlight uncertainties. 

Keywords economic model, shareholder s profit, project cashflow, gross revenue, discounted cashflow, opex, capex, technical cost, tax, royalty, oil price, marker crude, capital allowance, discount rate, profitability indicators, net present value, rate of return, screening, ranking, expected monetary value, exploration decision making. 

The main purpose of AUGUR4.2 expert ISI is the application to zones where some flaws (indications) had been revealed by scheduled manual ultrasonic inspections. Information provided by AUGUR 4.2 is used for decision-making further surveillance of these zones or corrective measures. The procedure of AUGUR 4.2 examination is included into the approved general scheme of ISI [1]... 

This study describes one stage of a soft tool realisation, which facilitate and improve the task of the expert for x-ray image interpretation and decision-making. We are interested by tbe first four stages of this flow chart. 

The 5th Framework Programme must be more flexible, both in its research activities and in the decision-making process. The Commission proposes that a simplified decision-making procedure should apply to research policy, including the use of qualified majority voting rather than unanimity in the Council of Ministers. 

A simple decision-making problem is I measure variable x of a population A and the same variable xof a population B. I get (slightly) different results. Is there areal difference between populations A and B based on the difference in measurements, or am I only seeing different parts of the distributions of identical populations ... 

A similar decision-making problem consists of very many measurements of var iable a on a large sample from population A, followed by a single measurement of the same property a of an individual. The single measurement will not be... 

The first application of the Gaussian distribution is in medical decision making or diagnosis. We wish to determine whether a patient is at risk because of the high cholesterol content of his blood. We need several pieces of input information an expected or normal blood cholesterol, the standard deviation associated with the normal blood cholesterol count, and the blood cholesterol count of the patient. When we apply our analysis, we shall anive at a diagnosis, either yes or no, the patient is at risk or is not at risk. 

But decision making in the real world isn t that simple. Statistical decisions are not absolute. No matter which choice we make, there is a probability of being wrong. The converse probability, that we are right, is called the confidence level. If the probability for error is expressed as a percentage, 100 — (% probability for error) = % confidence level. 

One variation of rule-based systems are fuzzy logic systems. These programs use statistical decision-making processes in which they can account for the fact that a specific piece of data has a certain chance of indicating a particular result. All these probabilities are combined in order predict a final answer. 

However, ia some cases, the answer is not clear. A variety of factors need to be taken iato consideration before a clear choice emerges. Eor example, UOP s Molex and IsoSiv processes are used to separate normal paraffins from non-normals and aromatics ia feedstocks containing C —C2Q hydrocarbons, and both processes use molecular sieve adsorbents. However, Molex operates ia simulated moving-bed mode ia Hquid phase, and IsoSiv operates ia gas phase, with temperature swiag desorption by a displacement fluid. The foUowiag comparison of UOP s Molex and IsoSiv processes iadicates some of the primary factors that are often used ia decision making ... 

Measurement Method Selection. A measurement method should meet sampling strategy requirements to the degree that the data can be used for decision making. This does not mean that it must be the optimum method with respect to all requirements. The range of methods available is limited and it is often necessary to select a method deficient in one or more attributes but which can yield data from which conclusions can be drawn with the desired degree of confidence. Some of the attributes to be considered in selecting a method foUow. 

Decision Process. In many cases, the decision regarding the need for exposure reduction measures is obvious and no formal statistical procedure is necessary. However, as exposure criteria are lowered, and control becomes more difficult, close calls become more common, and a logical decision-making process is needed. A typical process is shown in Eigure 2. Even when decision making is easy it is useful to remember the process and the assumptions involved. Based on an evaluation, decisions are made regarding control. The evaluation and decision steps caimot be separated because the conduct of the evaluation, the strategy, measurement method, and data collection are all a part of the decision process. 

F. J. Rahn and co-workers, M Guide to Nuclear Power Technology A Resource for Decision Making, Wiley-Interscience, New York, 1984. 

A new facihty should be located ia an area that is economically suitable (see Plant location). At the same time, the social, environmental, and aesthetic effects must be considered. These decisions are part of land-use pohcies. As of this writing (1996), there is no national land-use program. However, there are certain laws that cover portions of this decision-making process and some states have such programs. 

Desire to Be Independent Yet Collaborate. Technical professionals are achievement-oriented and derive motivation from the work itself. This often means a need for increased participation in decision-making, as well as a natural skepticism and resistance to rapid changes in direction and tight control by managers. Collaboration and the desire for some form of teamwork also are a part of the professional s nature. 

An important part of the decision-making tool flow chart (see Fig. 1) is the redefinition of the specifications by the sensor customer after the surveying and testing of commercial sensor systems. This process almost always involves a downgrading of the expectations of the sensor customer, but it can also force a reaUstic evaluation of what sensor information really needs to be made available and at what cost. 

G. S. Sebestyen, Decision-Making Processes in Pattern Recognition MacMillan, New York, 1962. 

Hamburg, M. Statistical Analysis for Decision Making, 2d ed., Harcourt, New York (1977). 

Optimization should be viewed as a tool to aid in decision making. Its purpose is to aid in the selection of better values for the decisions that can be made by a person in solving a problem. To formulate an optimization problem, one must resolve three issues. First, one must have a representation of the artifact that can be used to determine how the artifac t performs in response to the decisions one makes. This representation may be a mathematical model or the artifact itself. Second, one must have a way to evaluate the performance—an objective function—which is used to compare alternative solutions. Third, one must have a method to search for the improvement. This section concentrates on the third issue, the methods one might use. The first two items are difficult ones, but discussing them at length is outside the scope of this sec tion. 

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