Managers often have hundreds of decisions to make, and they must understand the inherent psychological components of a smart decision in order to avoid potential problems. Avoiding a bad decision is a skill that mangers can learn, develop, and perfect by examining errors that might have been made in the past, controlling cognitive biases, and by gathering proper information on how to make a good decision. Even highly intelligent managers can make bad decisions due to personal biases and pitfalls. Everyone can fall into various traps that lead to imperfect decisions, and there is therefore a great need to understand the specific decision-making biases and pitfalls as well as to avoid them (Hammond, Keeney and Raiffa, 1998). This paper identifies and explains specific biases demonstrated by four different decisions. The paper also describes what leaders should do to avoid these biases in future.
The kind of decision-making bias represented in the first scenario is confirmation bias. Hammond, Keeney and Raiffa (1998) define confirmation bias as a type of cognitive bias where a person makes a decision in favor of information that confirms previous beliefs, whether they are actually true or not. For instance, take it that that a person holds a belief that ladies are more intelligent than men. Whenever such a person meets a lady who performs better than men in any setting, they take it as an evidence to support their pre-existing belief. In the given scenario, the Chief Executive Officer strongly believes that marketing is a bad use of the company’s finances. She makes her decision on favor of data from several years back showing how sales did not go up despite the fact the company spent a lot of money on marketing. According to the Chief Executive Officer, cutting marketing budget will leave her with extra money for use in other activities as the company continues to record high sales.
Surprisingly, the company’s sales start to drop dramatically following the cut in marketing budget. When asked by one of the workers if the cut in marketing budget could be the cause of the drop in sales, the Chief Executive Officer insists that there must be a different problem that is not associated with the cut in marketing budget. The fact that there is a drop in sales following the cut in marketing budget is a clear indication that making a decision in favor of information that confirms previous beliefs is very wrong.
Confirmation bias should be avoided because it affects how people interpret information, and it can lead to disastrous decisions like the one demonstrated in this scenario. Generally, people who become victims of confirmation bias do not want to face the possibility that their beliefs could be wrong. They are faced with the fear that if they consider contrary evidence, they might make decisions that might be even more catastrophic. In order to avoid similar impacts of confirmation bias in future, the Chief Executive Officer should not only seek information that supports her beliefs when making decisions, but she also should gather additional information that describe the same issue in a different way. This will enable her to make proper decisions that take care of both personal beliefs and what exists in reality (Kourdi, 2003).
The type of decision making bias represented in the second scenario is overconfidence bias. According to Bolland and Fletcher (2012), overconfidence bias occurs when people overestimate their knowledge to predict, whether those estimates are true or not. Victims of overconfidence bias misjudge their opinions and think that they should be given the objective parameters of the situation at hand. In the given scenario, the Chief Executive Officer is confident that he will double the company’s market share by purchasing a major rival. There is lack of evidence to prove that the market share will actually expand following the acquisition but the company’s leader insists that he can overcome all challenges that are associated with the merger.
The decision made by the Chief Executive Officer has been influenced by his overconfidence because he has ignored several warnings from other managers explaining how such mergers have failed in the past. He fails to consider the fact that mergers and acquisitions are normally successful if there are close similarities in the cultures of the merging organizations. Even though the Chief Executive Officer is certain that he will succeed with the merger, he might experience problems due to lack of proper preparation and he may get into a dangerous situation that might be very difficult for him to handle (Hammond, Keeney and Raiffa, 1998).
Managers should learn to avoid overconfidence bias because it leads to bad decisions that may lead to closure of their companies. The best way to circumvent impacts of overconfidence bias is to avoid estimating personal knowledge when making decisions that are likely to affect the whole company. In addition, managers should make proper plans and avoid favoring pessimistic scenarios. This way, they will have a chance of judging every difficult situation somehow realistically without making unnecessary assumptions (Hammond, Keeney and Raiffa, 1998).
In the third scenario, the Chief Executive Officer has decided to purchase Factory A because it has a 94 percent rate of success in producing defect-free products because Factory B has a 5 percent defect rate. The kind of decision-making bias represented in this scenario is framing bias. Kourdi (2003)), defines framing bias as a type of cognitive bias that occurs when someone reacts to a given choice depending on the manner in which it is represented. When a positive frame is presented, people react in such a way that they will be able to avoid risks, while when a negative frame is presented, people tend to seek risks. This affects the type of decision made in case a problem occurs. Generally, a person will present better to positively framed information than to negatively framed information (Bolland and Fletcher, 2012).
In the given scenario, the Chief Executive Officer is expected to make a decision on whether to purchase Factory A or Factory B. The owner of Factory A states that 94 percent of products produce at the factory are free of defects. This means that 6 percent of the products have defects. On the other hand, the owner of Factory B states that only 5 percent of products produced at the company have defects. This shows that 95 percent of products produced at the factory are free of defects. Due to the framing given by the owners of the two factories, the Chief Executive Officer has decided to purchase Factory A which has a 94 percent rate of success in producing defect-free products and has left Factory B which has a 5 percent rate of failure in producing defect-free products. By making such a decision, the Chief Executive Officer has responded better to positively framed information than to negatively framed information, which indicates that his decision has been influenced by framing bias (Bolland and Fletcher, 2012).
Framing bias is robust psychological phenomenon that has affected the decisions made by managers in several instances. Managers should be aware of framing bias, its impacts, as well as how to avoid it. Whenever managers come across some form of information, they are advised to remove the framing and try to anticipate the results from as many perspectives as possible. They should be very careful to include all possible relevant information that may be useful to the situation at hand. This is a very good way of dissecting what is really going on and making meaningful comparisons that may protect them from deliberate manipulations by others. Furthermore, the process of analyzing the given information in details without framing it gives managers an opportunity to think about all other possible alternatives. If only the Chief Executive Officer had avoided the framing in the information given by owners of the two companies, he could have understood that Factory B is better than Factory A as far as production of defect-free products is concerned (Hammond, Keeney and Raiffa, 1998).
The kind of decision-making bias represented in the fourth scenario is sunk-cost bias. Decisions that are influenced by sunk-cost bias occur due to rational attachments that people have to costs that cannot be recovered (Kourdi, 2003). Managers fall victims of sunk-cost bias when making decisions because they want to make their investments worth their while. They want to waste additional finances to try and solve a problem that has already consumed huge funds. In the given scenario, the Chief Executive Officer of an automobile company has decided to introduce a new hybrid vehicle using modern technology. The company has spent a lot of money in research and development as well as on advertising. Unfortunately, it is unable to recover the money spent due to low sales of the hybrid vehicle. The Chief Executive Officer insists that he will continue selling the hybrid vehicle at low prices given that a lot of money has been spent on the project. He has failed to consider abandoning the car and focusing on selling other profitable vehicles. The decision made by the Chief Executive Officer has been influenced by sunk-cost bias because it is rationally attached to costs that cannot be recovered (Bolland and Fletcher, 2012).
Sunk-cost bias can negatively affect a company’s operations because it is a way of spending resources on a bad move. Managers can avoid sunk-cost bias in decision-making by focusing on ideas that will result into positive outcomes. They should stop dwelling on issues simply because they made an investment in the first place, but they should immediately start spending money on new resources that will cut on losses (Hammond, Keeney and Raiffa, 1998). The four decision-making biases: confirmation bias, overconfidence bias, framing bias, and sunk-cost bias are all dangerous to a leader because they have equal impacts on a company’s operations. Decisions that are influenced by any kind of decision-making bias will impact how operations in an organization are conducted as well as how a company performs following existence of a given problem. Managers should be aware of all types of decision-making biases as well as how to avoid them in order to prevent severe impacts that may result from making disastrous decisions (Kourdi, 2003).
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