Extreme decision making has received considerable attention from both academicians and researchers alike. This phenomenon is observed from a variety of applications, spanning decision making in times of uncertainty, decision making in extreme events and crisis, and decision making in the medical field, among others. The common denominator in all these circumstances is the degree of difficulty in which a decision may be made. Since these situations are marked with high stakes, ambivalence, and lack of information, the author found it worthwhile to look into the process of decision making that transpires behind each.
Extreme Decision Making
How do we cope with extreme decisions? To address this, Janis and Mann (1997) developed a framework for decision making in times of uncertainty, as reflected in their conflict theory. The researchers determined five mechanisms for coping in uncertain circumstances. The first is unconflicted adherence wherein obscure or uncertain information is neglected and the individual nonchalantly makes a decision to carry on with whatever he has been doing. The second pattern of coping is called unconflicted change in which an individual adopts a new course of action that is strongly recommended without qualms. This course of action is usually the most conspicuous, apparent, or more strongly put forth in that particular situation. The next one is defensive avoidance wherein an individual avoids any pressure and hostility from others by putting off the decision, and transferring the burden and liability to another person. The individual also justifies his actions and ignores corrections from other people. The fourth coping mechanism is hypervigilance in which the individual strenuously looks for a means of escaping the uncertain situation and urgently takes on the quickest way out without thinking of the consequences of his actions. This immediate decision is said to result from cognitive confusion, compulsion, and repetitive analysis. Extreme cases of hypervigilance are also known as hysteria or panic. Then lastly, there is concerned vigilance wherein the decision maker rationally seeks for a feasible solution to the problem. In this coping mechanism, the individual is expected to make decisions without haste and with full rationality (Janis & Mann, 1997). The study emphasized the importance of making decisions when facing uncertainty because there is no situation that is perfectly certain.
Decision making in crisis demands swift and effective action. Yet decision making during crisis is a rare phenomenon; thus it may not be possible for individuals to exhibit the expertise needed for decision making in crisis. Moreover, dealing with crisis entails great risks and uncertainties; hence different courses of action may be taken for each peculiar situation (Moxley, 2008). This presentation showed the characteristics of crisis and the effects of crisis in the decision making process of leaders. Moxley (2008) in this presentation entitled Decision Making in Crisis also presented the similarities and differences of traditional and naturalistic decision making. He presented that crisis involves multi-component factors which includes rapidly evolving situations, time pressure, chronic consequences of erroneous decisions, critical physical conditions, performance/command tension and a highly stressful circumstances. It was revealed that crisis reduces a leader’s ability to make the right decisions due to information overload, narrowing of attention and negative psychological and physiological effects. Crisis also makes a leader adopt maladaptive styles such as procrastination and panic. However, Moxley (2008) suggested ways to buffer these effects of crisis. Consulting crisis management teams, attending crisis workshop and adopting systematic decision making process were the suggestions put forth.
The difference between traditional and naturalistic decision making process was emphasized. Traditional also known as analytical decision making process is characterized as a vigilant, systemic process wherein several steps are involved. The first is to define the problem then collect information, followed by weighing the evidence. The fourth step is to search for and compare options and lastly make a reasoned decision. This decision making process is known to offer the best decisions provided there is enough time, information and energy to complete the analysis. However, instances arise when an individual does not have adequate time to make a systematic decision; hence an individual must rely only naturalistic decision making commonly known as intuition or gut feel. As presented by Moxley (2008) this type of decision making is swift and automatic. It is typically characterized by extreme limitations on time, ambiguity and lacking information; changing and conflicting goals; dynamic and constantly changing conditions and ill defined goals and ill designed tasks. The usual scenarios for this are during earthquakes, tornadoes, tsunamis, terrorism, war and fires. The author revealed that traditional and naturalistic decision making does not present a more correct decision making style, but rather asserts that the type of decision making should be matched with the situation and the level of experience and expertise of the decision maker. In conclusion, Moxley (2008) mentioned that effective decision making is a technique which has mechanics to it. Knowing which decision making process will give the best result will give optimal outcomes.
On decision making in ambiguity, a research study conducted by Andrew Reeves (2005) entitled Maritime Military Decision Making in Environments of Extreme Information Ambiguity: An Initial Exploration, claims that the use of both training and collaborative planning may help avert the repercussions of decision making during war situations. To be able to prove his claim Reeves (2005) studied two battles, namely the Battle of Trafalgar and the Battle of Midway. The research study examined two independent variables. These variables are common training and collaborative planning. The first variable according to Reeves (2005) refers to the competencies, schooling, beliefs and performance standards with corresponding experience shared by everyone in the battle space. The latter on the other hand, refers to the exchanging views; optimized use of resources; maximized utilization of information technology; wise real-time planning of the task; personal discussion sessions; and an open discussion of shared objectives for the mission to be actualized with relative ease. The research study proved that there is significant evidence to back up Reeve’s (2005) claim of the two maritime wars. Hence for the maritime battles studied the model appears to be relevant in the interpretation of the events and their outcomes. However, Reeves (2005) suggested that further studies about other battles should be made and other variables such as time constraints and leadership style for increased comprehension of decision making in ambiguity should be incorporated to the study.
Moreover, in a research study entitled Decision Making in the Face of Uncertainty: Attributions of American and Norwegian Officials, researchers Heradstveit and Bonham (1986) assert that when individuals are faced with uncertainties, they are likely to use simple minded thinking or methods by which one makes assessments of probability simpler like judgment heuristics. To prove their claim, Heradstveit and Bonham (1986) examine the decisions and actions made by foreign policy makers in Norway and the United States when faced by ambivalent events during a series of incidents that occurred in northern Norway that had to do with Soviet Union ships. Structured interviews were carried out with both American and Norwegian officials to prove the assertion. Further analysis of the interview suggests that the central beliefs of the Norwegian and American officials influenced the way information was processed hence affecting the decisions made by the said officials. Furthermore, Norwegians attributed their actions to the circumstances of the situation whereas they believe that the Soviets’ action is due to the commendable conditions of the situation. The Americans, on the other hand, regard the actions of the Norwegians to dispositional factors while the Soviets’ actions were based on the traits of the situation that arose. The researchers made recommendations based on the policy implications of the manner of attribution of the decision makers (Heradstveit and Bonham, 1986).
There are decision support systems put forth for extreme events. In the article by John Mo (2006) entitled Decision Support Systems Involving Extreme Events, he described the characteristics of extreme events and their implications on decision support requirements. Extreme events are characterized by Mo (2006) as events with high consequence, under-represented and disenfranchised groups especially those who involve the indigent, who are the ones most affected during the occurrence of these events. Extreme events are also rare, non-repeating, high risk and pose complex and ill structured problems. These extreme events can also potentially create long-term change in the environment or to the people affected. They also affect large numbers of people, large ecosystems and offer little opportunity for learning.
For extreme events, according to Mo (2006), decision making implications may be quite different for every event. The attention of people will be focused on the event and the consequence of decisions could be disastrous. Generally, extreme events are difficult to predict. They often occur with no warning and thus only a limited time for analysis is possible. This lack of structure of extreme events may encourage a naturalistic mode of responding when the analytical mode is more appropriate. In the aftermath of an extreme event, decision makers may face a new challenge in addressing the issues and problems caused by these extreme events. In times of extreme events, the cooperation between government and all the stakeholders is important for implementation of effective decisions.
The medical field is not exempt from risky, difficult decisions. Everyday, medical practitioners face the challenges of making critical decisions to save the lives of patients. Years of medical practice together with the skill to evaluate and asses the situation has helped them make important decisions. This is where decision analysis becomes critical. Decision analysis, according to Kapur (2000), was first developed in the business world and is used to describe the approach of examining difficult decisions.
Decision analysis is a statistical way of determining the best decision that a medical practitioner needs to make. This method includes assigning a probability to each medical outcome. These probabilities represent the best guess of the doctor on the possibility of a certain outcome based on the given data. This principle also involves the concept of utility which is assigned to each outcome. Utility refers to the patient’s preference of an outcome over the other. In order to come up with a decision, the various decision points and their consequences together with their associated probabilities and utilities, are mapped to make a visual presentation of the available decisions. This is also called as decision tree. The option with the highest expected utility based on the combined probabilities and utilities is the best treatment. The best treatment has the highest probability of providing the most optimum outcome for the patient (Kapur 2000).
However, the use of decision analysis in some cases has great risks. In psychiatry for example, decision analysis poses problems due to the poor quality of psychiatric research databases. There are situations where lack of evidence to support the decision and action is present making it risky for the practitioner to make a final stance. It is also difficult to generalize because the values assigned to patients are computed values so it may vary from one individual to another. Despite the problems on decision analysis, this method is still useful in evaluating and proving risk and is particularly helpful in teaching, audit and research (Kapur 2000).
At present, psychiatry is bombarded with questions about the concept of risk and the practice of what is called a high risk strategy. High risk strategy refers to the application of risk assessment method to a population then concentrating efforts to particular areas where high risk of poor outcomes are seen (Rose 1992). There are several advantages to this strategy. One advantage is it is cost effective since only a minority of individuals is used as target population. Another advantage, is that it avoids potential harmful treatments to individuals who do not need it. This strategy also leads to interventions which are specifically made for those individuals who need it. However, there are also disadvantages and serious problems. First, those individuals who belong to the lower risk, higher volume group are excluded even though they represent a larger number of the population. Second, any intervention at the high risk group alone does not significantly contribute to the reduction of occurrence of disease in the population. Lastly, the distinction between high and low risk is arbitrary and vague.
An example of a high risk strategy is the current management of self harm, or popularly known as suicide. This method shows several disadvantages of a high risk strategy (Kapur & House, 1998). First, choosing high risk groups results in the exclusion of a large number of low risk individuals hence affecting the impact of suicide prevention strategies made. Second, the available risk measures are poor at predicting suicidal behavior. Lastly, suicide risk may be continuously distributed in the population wherein the distinction between high and low risk groups is not applicable (Kapur & House, 1998).
In order to compensate for the problems posed by the high risk approach, an alternative method can be used. This method is called a population based strategy involving the entire population in the study rather than targeting a few. This is said to be more powerful because of the number of individuals involved in the study. Population approaches are also said to be radical since they seek to solve underlying causes of phenomenon rather than just external manifestations (Kapur & House, 1998). However, disadvantages and problems are also seen with the use of population approach. This method is said to be very expensive because of the large number of individuals involved in the study. Aside from this, it may not be always compatible with the medical model used in managing health problems. According to Kapur and House (1998) a combination of high risk and population strategies might be more feasible and effective than using one strategy alone. For example, in the case of suicide or deliberate self harm, it could mean that the intervention should be made to all patients like using card listing and contact numbers coupled with clinical methods of risk assessment to identify patients who may benefit from more intensive treatment.
In conclusion, the author has examined the various literature that explain extreme decision making as a phenomenon. Across applications, it has been seen that decision making in situations of ambiguity and crisis remains difficult no matter how scientific and systematic the decision making support systems that are put forth. This is a call for more research on extreme decision making, with the eventual aim of mitigating the risks and averting the repercussions of rushed, irrational decisions.
Janis, I. L. & Mann, L. (1977). Decision making: A psychological analysis of conflict, choice and commitment. Free Press.
Kapur, N. (2000). Decisions in the medical field and the concept of risk. Advances in Psychiatric Treatment, 6, 399-406.
Kapur, N. & House, A. (1998). Against a high risk strategy in the prevention of suicide. Psychiatric Bulletin, 22, 534–536.
Mo, J. (2006). Decision support systems involving extreme events. Retrieved on October 26, 2008 from: http://220.127.116.11/search?q=cache:uM02Cmr1uQQJ:www.dar.csiro.au/css/Aug%2520Workshop%252006/%2706%2520Workshop%2520Presentations/DSSforExtremeEvents1Mo.ppt+extreme+decision+making&hl=tl&ct=clnk&cd=29&gl=ph
Moxley, T. (2008). Decision making in a crisis. Retrieved on October 26, 2008 from: http://www.drieottawa.org/presentations/20080305/20080305_cf_todd_moxley.pdf
Overview of Decision Making. [PDF document]. Retrieved from Lecture Notes Online Web site: http://www.totalqualityassuranceservices.com
Reeves, A. (2005). Maritime military decision making in environments of extreme information ambiguity: an initial exploration. Naval Postgraduate School Monterey: CA Dept of Information Sciences.
Rose, G. (1992). The strategy of preventive medicine. Oxford: Oxford University Press.