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Judgment in Managerial Decision Making 8e

Chapter 8
Fairness and Ethics in Decision Making

Copyright 2013 John Wiley & Sons

1

In-Group Favoritism
Favoring similar others
This may seems harmless, but it has the unintended consequence of indirect discrimination
Indirect discrimination
People are more likely to associate positive characteristics with in-group (groups they belong to) members than with out-group members.
People are more likely to punish unfair behavior when it is directed at demographically similar others than they are for demographically different others
People often regard the favors they do for in-group members as virtuous
In-group favoritism, is equivalent to punishing people for being different from you
yet helping people who are like us is viewed by society as a nice thing to do, while discriminating against those who are different is viewed as unethical

A vast line of literature exists suggesting that we tend to perform favors for similar others.
This tendency to help out people who are like us seems communal and harmless, but it has the unintended consequence of indirect discrimination.
People are less likely to associate positive characteristics with out-group members than with in-group members.
People are less likely to punish unfair behavior when it is directed at demographically different others than they are for demographically different others.
This tendency to indirectly discriminate against out-group members in favor of in-group members has important consequences.
African-Americans are more likely than Caucasians to have their loan applications denied when controlling for a variety of factors. One reason for this may be that predominately white loan officers are more likely to approve loans to unqualified whites who are similar to themselves than to equally unqualified blacks who are different from themselves.
Many schools admit legacies whose parents attended the university. A consequence of this practice is that less qualified applicants from privileged households with Ivy-League educated parents are more likely to be admitted to top universities than even more qualified applicants from less privileged households who lack the connections necessary to be admitted to top institutions.
2

In-Group Favoritism
Consequences
Loans
African-Americans are more likely than Caucasians to have their loan applications denied.
This may be because white loan officers are more likely to approve loans to unqualified whites
Legacy admissions
Less qualified applicants from privileged households with Ivy-League educated parents are more likely to be admitted to top universities than even more qualified applicants from less privileged households who lack the connections necessary to be admitted to top institutions

A vast line of literature exists suggesting that we tend to perform favors for similar others.
This tendency to help out people who are like us seems communal and harmless, but it has the unintended consequence of indirect discrimination.
People are less likely to associate positive characteristics with out-group members than with in-group members.
People are less likely to punish unfair behavior when it is directed at demographically different others than they are for demographically different others.
This tendency to indirectly discriminate against out-group members in favor of in-group members has important consequences.
African-Americans are more likely than Caucasians to have their loan applications denied when controlling for a variety of factors. One reason for this may be that predominately white loan officers are more likely to approve loans to unqualified whites who are similar to themselves than to equally unqualified blacks who are different from themselves.
Many schools admit legacies whose parents attended the university. A consequence of this practice is that less qualified applicants from privileged households with Ivy-League educated parents are more likely to be admitted to top universities than even more qualified applicants from less privileged households who lack the connections necessary to be admitted to top institutions.
3

Implicit Attitudes
Most people think of their attitudes as being within the scope of their conscious awareness and under their control
Unconscious prejudice
A plethora of evidence suggest that when we meet someone, our minds automatically activate stereo- types of the person’s race, sex, and age
We are more likely to respond to aggression after seeing a black face than after seeing a white face.
participants in an experiment work on a boring computer task. Meanwhile, the computers flashed subliminal images of either white or black faces, so quickly that participants were not consciously aware of them.
When the computers “broke down” and the participants were informed that their work had been lost, those who had been shown black faces responded with significantly more aggression than those shown white faces, consistent with the common stereotype of African Americans as aggressive and violent
The automatic activation of stereotypes tends to make whites uncomfortable in interracial interactions.
We require conscious effort that is cognitively taxing in order to suppress our negative racial stereotypes.

Overall, there is a plethora of evidence suggesting that we hold implicit attitudes favoring some demographic groups over others.
We are more likely to respond to aggression after seeing a black face than after seeing a white face.
The automatic activation of stereotypes tends to make whites uncomfortable in interracial interactions.
We require conscious effort that is cognitively taxing in order to suppress our negative racial stereotypes.
The IAT is one tool commonly used to assess implicit attitudes.
It involves categorizing items as quickly as possible. For example, a black face may appear and then you may subsequently have to categorize words by indicating whether they are “good” or “bad”.
For example, the more quickly you accurately associate “good” words to white faces relative to black faces, the greater the extent you are considered to have pro-white implicit attitudes.
Though the IAT seems like a strange way to predict actual behavior, it actually has been demonstrated to predict observable behaviors.
People who tend to associate women with communal traits implicitly tend to consider ambitious women as lacking social skills.
Implicit attitudes are associated with nonverbal behaviors towards different groups of people.
Implicit attitudes tend to predict our spontaneous behaviors while they do not predict more deliberative behaviors very well.
One way that we may reduce our implicit biases that favor particular social groups is by lowering prejudice in society as a whole. For example, one study found that after Barack Obama’s election, people became less prejudiced towards blacks than they were before his election. A reason for this may be that he provides a salient positive exemplar of African-Americans.
4

Implicit Attitudes
The Implicit Associations Test, or IAT
One tool commonly used to assess implicit attitudes
It involves categorizing items as quickly as possible.
For example, a black face may appear and then you may subsequently have to categorize words by indicating whether they are “good” or “bad”.
Conducted in several rounds. In some, test takers must assign good to white faces, and bad to black faces; while in other rounds, the test taker must do the opposite
For example, the more quickly you accurately associate “good” words to white faces relative to black faces, the greater the extent you are considered to have pro-white implicit attitudes

Overall, there is a plethora of evidence suggesting that we hold implicit attitudes favoring some demographic groups over others.
We are more likely to respond to aggression after seeing a black face than after seeing a white face.
The automatic activation of stereotypes tends to make whites uncomfortable in interracial interactions.
We require conscious effort that is cognitively taxing in order to suppress our negative racial stereotypes.
The IAT is one tool commonly used to assess implicit attitudes.
It involves categorizing items as quickly as possible. For example, a black face may appear and then you may subsequently have to categorize words by indicating whether they are “good” or “bad”.
For example, the more quickly you accurately associate “good” words to white faces relative to black faces, the greater the extent you are considered to have pro-white implicit attitudes.
Though the IAT seems like a strange way to predict actual behavior, it actually has been demonstrated to predict observable behaviors.
People who tend to associate women with communal traits implicitly tend to consider ambitious women as lacking social skills.
Implicit attitudes are associated with nonverbal behaviors towards different groups of people.
Implicit attitudes tend to predict our spontaneous behaviors while they do not predict more deliberative behaviors very well.
One way that we may reduce our implicit biases that favor particular social groups is by lowering prejudice in society as a whole. For example, one study found that after Barack Obama’s election, people became less prejudiced towards blacks than they were before his election. A reason for this may be that he provides a salient positive exemplar of African-Americans.
5

Implicit Attitudes
The IAT reveals the relative strength of implicit attitude but not their absolute strength
It cannot reveal whether or not someone is racist, sexist, and so on. Rather, it measures the strength of an individual’s implicit association between two pairs of categories(4 categories in total) , such as White/Black and Good/Bad
For example, if the test reveals that you associate good with white, it does not mean that you love white and hate black. It only means that you love both, but favor the whites a bit more

Overall, there is a plethora of evidence suggesting that we hold implicit attitudes favoring some demographic groups over others.
We are more likely to respond to aggression after seeing a black face than after seeing a white face.
The automatic activation of stereotypes tends to make whites uncomfortable in interracial interactions.
We require conscious effort that is cognitively taxing in order to suppress our negative racial stereotypes.
The IAT is one tool commonly used to assess implicit attitudes.
It involves categorizing items as quickly as possible. For example, a black face may appear and then you may subsequently have to categorize words by indicating whether they are “good” or “bad”.
For example, the more quickly you accurately associate “good” words to white faces relative to black faces, the greater the extent you are considered to have pro-white implicit attitudes.
Though the IAT seems like a strange way to predict actual behavior, it actually has been demonstrated to predict observable behaviors.
People who tend to associate women with communal traits implicitly tend to consider ambitious women as lacking social skills.
Implicit attitudes are associated with nonverbal behaviors towards different groups of people.
Implicit attitudes tend to predict our spontaneous behaviors while they do not predict more deliberative behaviors very well.
One way that we may reduce our implicit biases that favor particular social groups is by lowering prejudice in society as a whole. For example, one study found that after Barack Obama’s election, people became less prejudiced towards blacks than they were before his election. A reason for this may be that he provides a salient positive exemplar of African-Americans.
6

Implicit Attitudes
Implicit attitudes predict actual behavior
Females and social skills
People who tend had strong implicit attitudes connecting women with common traits implicitly (e.g. helpful) tend to consider ambitious women as lacking social skills
Implicit attitudes are associated with nonverbal behaviors towards different groups of people
Implicit attitudes tend to predict our spontaneous behaviors while explicit attitudes predict more deliberative behaviors very well
Lowering prejudice in society could be a solution
For example, after Barack Obama’s election, people became less prejudiced towards blacks than they were before his election. A reason for this may be that he provides a salient positive exemplar of African-Americans

Though the IAT seems like a strange way to predict actual behavior, it actually has been demonstrated to predict observable behaviors.
People who tend to associate women with communal traits implicitly tend to consider ambitious women as lacking social skills.
Implicit attitudes are associated with nonverbal behaviors towards different groups of people.
Implicit attitudes tend to predict our spontaneous behaviors while they do not predict more deliberative behaviors very well.
One way that we may reduce our implicit biases that favor particular social groups is by lowering prejudice in society as a whole. For example, one study found that after Barack Obama’s election, people became less prejudiced towards blacks than they were before his election. A reason for this may be that he provides a salient positive exemplar of African-Americans.
7

Prescription Drug Prices
Imagine that a major pharmaceutical company is the sole marketer of a particular cancer drug. The drug is not profitable, due to high fixed costs and a small market size, yet the patients who do buy the drug depend on it for their survival. The pharmaceutical company currently produces the drug at a total cost of $5/pill and only sells it for $3/pill. A price increase is unlikely to decrease use of the drug, but will impose significant hardship on many users.
How ethical would it be for the company to raise the price of the drug from $3/pill to $9/pill?

Take a moment to consider this scenario.
Most people consider it unethical for the company to raise its prices and impose hardship on those who depend on it.
8

Prescription Drug Prices
Now imagine that, instead of raising the price, the company sold the rights to produce the drug to a smaller, lesser-known pharmaceutical company. At a meeting between the two companies, a young executive from the smaller firm says: “Since our reputation is not as critical as yours, and we are not in the public’s eye, we can raise the price five fold to $15/pill.”
Would selling the manufacturing and marketing rights to the other firm be more or less ethical?

Now, consider this adapted version of the scenario.
In this case, the company is not directly raising the price, but is doing it indirectly by selling production rights to a relatively unknown company.
Additionally, the price will ultimately raise to $7 higher that in the previous scenario.
Despite the higher price, due to the indirect nature of the price increase, people believe that this outcome is more fair than the previous outcome.
However, when people are asked to evaluate this scenario and the prior scenario jointly, they tend to believe that this outcome is more unfair than the previous outcome.
9

Prescription Drug Prices
When evaluating each of these two options individually, participants found it more unethical to raise the drug price to $9 per pill than to sell off the product to another firm
When asked to compare the two options, they found the behavior that led to a $15 per pill price to be more unethical.
People typically observe only one behavior at a time rather than comparing and contrasting two options

Now, consider this adapted version of the scenario.
In this case, the company is not directly raising the price, but is doing it indirectly by selling production rights to a relatively unknown company.
Additionally, the price will ultimately raise to $7 higher that in the previous scenario.
Despite the higher price, due to the indirect nature of the price increase, people believe that this outcome is more fair than the previous outcome.
However, when people are asked to evaluate this scenario and the prior scenario jointly, they tend to believe that this outcome is more unfair than the previous outcome.
10

Indirectly Unethical Behavior
Impression management
Protection of self-perceptions
People who carry out such “indirect unethical behavior” may do so as much to protect their self-perceptions as ethical individuals

As suggested by the prior examples, one important aspect of indirect behavior is that it allows people to manage the impressions that others form of them. A study finding that people are more likely to sacrifice $1 than to allocate the entire pie of money to themselves in a dictator game so that they can prevent their counterpart from knowing that they had received an unequal allocation.
People also go through great lengths to protect their perception of themselves as ethical individuals.
One study found that people will keep themselves ignorant about the economic outcomes of others when they have the opportunity to select an option that is in their economic best interest. This probably allowed participants to feel that any potential harm to others was indirectly caused by them since they did not have a conscious awareness of others’ payoffs.
11

Indirectly Unethical Behavior
Participants in a study played a peculiar dictator game in which half of them had to choose between two options. One option gave them $5 and the other person $5. The second option gave them $6 but gave the other person $1.
Participants in the “baseline” condition had all of this information. 74% of them chose the first option over the second option, giving an equal $5 payment to each player.
By contrast, participants in the “hidden payoff” condition saw that the first option would pay them $5 and that the second option would pay them $6; however, they would have to click on a box to learn what the consequence of their decision would be for the other party.
Half of these participants chose not to click, and chose option 2
Remaining willfully ignorant of the larger consequences of their choices allowed them to choose selfishly

As suggested by the prior examples, one important aspect of indirect behavior is that it allows people to manage the impressions that others form of them. A study finding that people are more likely to sacrifice $1 than to allocate the entire pie of money to themselves in a dictator game so that they can prevent their counterpart from knowing that they had received an unequal allocation.
People also go through great lengths to protect their perception of themselves as ethical individuals.
One study found that people will keep themselves ignorant about the economic outcomes of others when they have the opportunity to select an option that is in their economic best interest. This probably allowed participants to feel that any potential harm to others was indirectly caused by them since they did not have a conscious awareness of others’ payoffs.
12

Indirectly Unethical Behavior
Participants in another study had a choice: either (1) play a standard dictator game in which they could allocate $10 between themselves and another person who would know about the game and their choice, or (2) exit the game silently and receive $9, knowing that the other person would receive nothing and would never even know about the existence of the game.
Roughly one third of participants took the “silent exit” option, a choice that is difficult to justify as rational,
As a self-interested person should play the standard dictator game and simply allocate the entire $10 to himself or herself
The people who chose the $9 silent exit apparently wanted to behave selfishly but felt more comfortable doing so when they could keep their selfishness secret

As suggested by the prior examples, one important aspect of indirect behavior is that it allows people to manage the impressions that others form of them. A study finding that people are more likely to sacrifice $1 than to allocate the entire pie of money to themselves in a dictator game so that they can prevent their counterpart from knowing that they had received an unequal allocation.
People also go through great lengths to protect their perception of themselves as ethical individuals.
One study found that people will keep themselves ignorant about the economic outcomes of others when they have the opportunity to select an option that is in their economic best interest. This probably allowed participants to feel that any potential harm to others was indirectly caused by them since they did not have a conscious awareness of others’ payoffs.
13

Judgment in Managerial Decision Making 8e

Chapter 12
Improving Decision Making

Copyright 2013 John Wiley & Sons

1

Use Decision-Analysis Tools
Linear models
What are they?
A formula that weights and adds up the relevant predictor variables in order to make a quantitative prediction
An example,
A parent asked his boy’s pediatrician to predict how tall his son would grow. The pediatrician offered a simple linear model in response.
She said that a child’s adult height is best predicted with the following computation.
First, average the parents’ heights.
Second, if the child is a boy, add two inches to the parents’ average. If the child is a girl, subtract two inches from the parents’ average

One way to improve decision-making is to use decision-analysis tools.
These tools allow people to guide their decision-making process by converting qualitative preferences into quantitative data that can be converted into expected values and then compared. They typically consider the following:
Weights placed on the importance of different attributes.
The value of each attribute.
The probability of uncertain events occurring.
The objective costs associated with each option.
Linear models facilitate the process of performing a quantitative decisions analysis when there is uncertainty.
These models account for relevant variables that predict future outcomes and combine them in a linear fashion to provide estimates of future outcomes.
They can be used to predict a wide range of things such as:
A child’s adult height given the height of his or her parents and his or her gender.
A baseball player’s future performance given his past performance, age, height, and weight.
A movie studio predicting the potential revenue that will be generated by a movie.
Linear models are effective at improving decisions.
Research in a variety of domains has demonstrated that they make better predictions than “experts”.
More complex models provide limited improvement to simple linear models.
We have inconsistent preferences that are prone to bias while models are consistent and unbiased.
They also are effective at allowing people to gauge the effectiveness of various practices, which helps them learn and fine-tune their managerial strategies.
Despite the demonstrated effectiveness of linear models, people frequently object to their use.
People still believe that brief interviews are more effective at predicting performance than a long history of prior performance and aptitude tests to draw from. Neither of these factors truly give people a sense of an individual’s unique characteristics and the latter requires little effort and provides a lot of unbiased data.
People also believe that it is impossible to model the qualitative preferences and tastes of individuals, but research has demonstrated that linear models are reasonably effective at capturing such qualitative preferences.
One domain in which linear models could improve the decision-making process is admissions decisions.
In a manifestation of what is known as the correspondence bias, graduate school admissions tend to be biased in favor of individuals with high GPAs from lenient institutions because they fail to sufficiently discount the role of lenient grading.
One researcher developed a linear model to make graduate admissions decisions and compared it to the decisions of an admissions committee.
The model was capable of ruling out 55% of applicants who the committee also rejected.
The model also proved more effective at predicting the future ratings of applicants than the committee.
Overall, the effectiveness of this simple model suggests that the implementation of simple models using decision rules to make quick admissions decision can save universities hundreds of millions of dollars in time and resources saved from not having committees review applications.
Decision-analysis tools can also be of assistance in making hiring decisions.
Job interviews predict only 14% of the variability in employee performance. However, people continue to believe in them as an effective diagnostic tool.
Interviewers are biased by the availability of subjective qualities that they associate with effective performance when interviewing potential applicants.
Interviewer affect is influenced by superficial cues associated with a candidate and this influences their perceptions of the candidate.
Individuals who are extroverted, sociable, tall, attractive, and ingratiating are often considered as ones that represent the qualities of effective leaders even though they are far less predictive of performance than less observable traits such as conscientiousness and intelligence.
Managers tend to seek information that confirms the quality of their decision after hiring an applicant, which prevents them from learning. In addition, they never have a sample of performance from those who were interviewed but not hired to use as a comparison group.
Interviews may be difficult to justify based on the time that goes into them and the little predictive validity they have, but if the ratings of interviewers are combined into a linear model with measures of aptitude and past performance, hiring decisions could be improved.
2

Linear Models
Why they lead to superior decisions?
Lead to superior predictions than experts
More complex models produce only marginal improvement above a simple linear framework
Linear model are superior because:
People are much better at selecting and coding information (what variables to put) than they are at integrating the information (using data to make a prediction)
We are inconsistent. Given the same data, we will not always make the same decision
A linear model can be programmed to avoid biases that are known to impair human judgment
Allow organizations to identify the factors that are important in the decisions of its experts, making them valuable tools

One way to improve decision-making is to use decision-analysis tools.
These tools allow people to guide their decision-making process by converting qualitative preferences into quantitative data that can be converted into expected values and then compared. They typically consider the following:
Weights placed on the importance of different attributes.
The value of each attribute.
The probability of uncertain events occurring.
The objective costs associated with each option.
Linear models facilitate the process of performing a quantitative decisions analysis when there is uncertainty.
These models account for relevant variables that predict future outcomes and combine them in a linear fashion to provide estimates of future outcomes.
They can be used to predict a wide range of things such as:
A child’s adult height given the height of his or her parents and his or her gender.
A baseball player’s future performance given his past performance, age, height, and weight.
A movie studio predicting the potential revenue that will be generated by a movie.
Linear models are effective at improving decisions.
Research in a variety of domains has demonstrated that they make better predictions than “experts”.
More complex models provide limited improvement to simple linear models.
We have inconsistent preferences that are prone to bias while models are consistent and unbiased.
They also are effective at allowing people to gauge the effectiveness of various practices, which helps them learn and fine-tune their managerial strategies.
Despite the demonstrated effectiveness of linear models, people frequently object to their use.
People still believe that brief interviews are more effective at predicting performance than a long history of prior performance and aptitude tests to draw from. Neither of these factors truly give people a sense of an individual’s unique characteristics and the latter requires little effort and provides a lot of unbiased data.
People also believe that it is impossible to model the qualitative preferences and tastes of individuals, but research has demonstrated that linear models are reasonably effective at capturing such qualitative preferences.
One domain in which linear models could improve the decision-making process is admissions decisions.
In a manifestation of what is known as the correspondence bias, graduate school admissions tend to be biased in favor of individuals with high GPAs from lenient institutions because they fail to sufficiently discount the role of lenient grading.
One researcher developed a linear model to make graduate admissions decisions and compared it to the decisions of an admissions committee.
The model was capable of ruling out 55% of applicants who the committee also rejected.
The model also proved more effective at predicting the future ratings of applicants than the committee.
Overall, the effectiveness of this simple model suggests that the implementation of simple models using decision rules to make quick admissions decision can save universities hundreds of millions of dollars in time and resources saved from not having committees review applications.
Decision-analysis tools can also be of assistance in making hiring decisions.
Job interviews predict only 14% of the variability in employee performance. However, people continue to believe in them as an effective diagnostic tool.
Interviewers are biased by the availability of subjective qualities that they associate with effective performance when interviewing potential applicants.
Interviewer affect is influenced by superficial cues associated with a candidate and this influences their perceptions of the candidate.
Individuals who are extroverted, sociable, tall, attractive, and ingratiating are often considered as ones that represent the qualities of effective leaders even though they are far less predictive of performance than less observable traits such as conscientiousness and intelligence.
Managers tend to seek information that confirms the quality of their decision after hiring an applicant, which prevents them from learning. In addition, they never have a sample of performance from those who were interviewed but not hired to use as a comparison group.
Interviews may be difficult to justify based on the time that goes into them and the little predictive validity they have, but if the ratings of interviewers are combined into a linear model with measures of aptitude and past performance, hiring decisions could be improved.
3

Linear Models
Why do we resist them?
Some have raised ethical concerns
People still believe that brief interviews are more effective at predicting performance than a long history of prior performance and aptitude tests to draw from.
How could they tell what I’m like?
Neither of these factors (interviews or linear models) truly give people a sense of an individual’s unique characteristics and the latter requires little effort and provides a lot of unbiased data

Despite the demonstrated effectiveness of linear models, people frequently object to their use.
People still believe that brief interviews are more effective at predicting performance than a long history of prior performance and aptitude tests to draw from. Neither of these factors truly give people a sense of an individual’s unique characteristics and the latter requires little effort and provides a lot of unbiased data.
People also believe that it is impossible to model the qualitative preferences and tastes of individuals, but research has demonstrated that linear models are reasonably effective at capturing such qualitative preferences.
One domain in which linear models could improve the decision-making process is admissions decisions.
In a manifestation of what is known as the correspondence bias, graduate school admissions tend to be biased in favor of individuals with high GPAs from lenient institutions because they fail to sufficiently discount the role of lenient grading.
One researcher developed a linear model to make graduate admissions decisions and compared it to the decisions of an admissions committee.
The model was capable of ruling out 55% of applicants who the committee also rejected.
The model also proved more effective at predicting the future ratings of applicants than the committee.
Overall, the effectiveness of this simple model suggests that the implementation of simple models using decision rules to make quick admissions decision can save universities hundreds of millions of dollars in time and resources saved from not having committees review applications.
Decision-analysis tools can also be of assistance in making hiring decisions.
Job interviews predict only 14% of the variability in employee performance. However, people continue to believe in them as an effective diagnostic tool.
Interviewers are biased by the availability of subjective qualities that they associate with effective performance when interviewing potential applicants.
Interviewer affect is influenced by superficial cues associated with a candidate and this influences their perceptions of the candidate.
Individuals who are extroverted, sociable, tall, attractive, and ingratiating are often considered as ones that represent the qualities of effective leaders even though they are far less predictive of performance than less observable traits such as conscientiousness and intelligence.
Managers tend to seek information that confirms the quality of their decision after hiring an applicant, which prevents them from learning. In addition, they never have a sample of performance from those who were interviewed but not hired to use as a comparison group.
Interviews may be difficult to justify based on the time that goes into them and the little predictive validity they have, but if the ratings of interviewers are combined into a linear model with measures of aptitude and past performance, hiring decisions could be improved.
4

Linear Models
Why do we resist them?
Choosing mushmelons for his grandmother’s cake requires judgment, taste, experience, and a lot more that are not possible in the linear model
Research, however, has shown that they can
They rule out intuitions or gut feelings
Requires difficult changes within organizations
What will bank loan officers do when computers make the decisions?
These models still need us to specify the inputs, monitor the outcome, update variables, and so on

Despite the demonstrated effectiveness of linear models, people frequently object to their use.
People still believe that brief interviews are more effective at predicting performance than a long history of prior performance and aptitude tests to draw from. Neither of these factors truly give people a sense of an individual’s unique characteristics and the latter requires little effort and provides a lot of unbiased data.
People also believe that it is impossible to model the qualitative preferences and tastes of individuals, but research has demonstrated that linear models are reasonably effective at capturing such qualitative preferences.
One domain in which linear models could improve the decision-making process is admissions decisions.
In a manifestation of what is known as the correspondence bias, graduate school admissions tend to be biased in favor of individuals with high GPAs from lenient institutions because they fail to sufficiently discount the role of lenient grading.
One researcher developed a linear model to make graduate admissions decisions and compared it to the decisions of an admissions committee.
The model was capable of ruling out 55% of applicants who the committee also rejected.
The model also proved more effective at predicting the future ratings of applicants than the committee.
Overall, the effectiveness of this simple model suggests that the implementation of simple models using decision rules to make quick admissions decision can save universities hundreds of millions of dollars in time and resources saved from not having committees review applications.
Decision-analysis tools can also be of assistance in making hiring decisions.
Job interviews predict only 14% of the variability in employee performance. However, people continue to believe in them as an effective diagnostic tool.
Interviewers are biased by the availability of subjective qualities that they associate with effective performance when interviewing potential applicants.
Interviewer affect is influenced by superficial cues associated with a candidate and this influences their perceptions of the candidate.
Individuals who are extroverted, sociable, tall, attractive, and ingratiating are often considered as ones that represent the qualities of effective leaders even though they are far less predictive of performance than less observable traits such as conscientiousness and intelligence.
Managers tend to seek information that confirms the quality of their decision after hiring an applicant, which prevents them from learning. In addition, they never have a sample of performance from those who were interviewed but not hired to use as a comparison group.
Interviews may be difficult to justify based on the time that goes into them and the little predictive validity they have, but if the ratings of interviewers are combined into a linear model with measures of aptitude and past performance, hiring decisions could be improved.
5

Linear Models
Evidence to better outcomes:
Graduate school admission
Hiring
Graduate school admission
In a manifestation of what is known as the correspondence bias (assuming students’ behavior or GPA corresponds to their innate traits), graduate school admissions tend to be biased in favor of individuals with high GPAs from lenient grading institutions because they fail to sufficiently discount the role of lenient grading and institutions’ quality.
Its easier to make a linear model avoiding this error
One researcher developed a linear model to make graduate admissions decisions relying on three factors:
Graduate school examination scores
Undergraduate GPA
Quality of undergraduate school
Compared to the decisions of an admissions committee, the model was better at predicting future student performance

One domain in which linear models could improve the decision-making process is admissions decisions.
In a manifestation of what is known as the correspondence bias, graduate school admissions tend to be biased in favor of individuals with high GPAs from lenient institutions because they fail to sufficiently discount the role of lenient grading.
One researcher developed a linear model to make graduate admissions decisions and compared it to the decisions of an admissions committee.
The model was capable of ruling out 55% of applicants who the committee also rejected.
The model also proved more effective at predicting the future ratings of applicants than the committee.
Overall, the effectiveness of this simple model suggests that the implementation of simple models using decision rules to make quick admissions decision can save universities hundreds of millions of dollars in time and resources saved from not having committees review applications.
Decision-analysis tools can also be of assistance in making hiring decisions.
Job interviews predict only 14% of the variability in employee performance. However, people continue to believe in them as an effective diagnostic tool.
Interviewers are biased by the availability of subjective qualities that they associate with effective performance when interviewing potential applicants.
Interviewer affect is influenced by superficial cues associated with a candidate and this influences their perceptions of the candidate.
Individuals who are extroverted, sociable, tall, attractive, and ingratiating are often considered as ones that represent the qualities of effective leaders even though they are far less predictive of performance than less observable traits such as conscientiousness and intelligence.
Managers tend to seek information that confirms the quality of their decision after hiring an applicant, which prevents them from learning. In addition, they never have a sample of performance from those who were interviewed but not hired to use as a comparison group.
Interviews may be difficult to justify based on the time that goes into them and the little predictive validity they have, but if the ratings of interviewers are combined into a linear model with measures of aptitude and past performance, hiring decisions could be improved.
6

Linear Models
Decision-analysis tools can also be of assistance in making hiring decisions.
Job interviews predict only 14% of the variability in employee performance. However, people continue to believe in them as an effective diagnostic tool.
Interviewers are biased by the availability of subjective qualities that they associate with effective performance when interviewing potential applicants.
Interviewer affect is influenced by superficial cues associated with a candidate and this influences their perceptions of the candidate.
Individuals who are extroverted, sociable, tall, attractive, and ingratiating are often considered as ones that represent the qualities of effective leaders even though they are far less predictive of performance than less observable traits such as conscientiousness and intelligence.
Managers tend to seek information that confirms the quality of their decision after hiring an applicant, which prevents them from learning. In addition, they never have a sample of performance from those who were interviewed but not hired to use as a comparison group.
Interviews may be difficult to justify based on the time that goes into them and the little predictive validity they have, but if the ratings of interviewers are combined into a linear model with measures of aptitude and past performance, hiring decisions could be improved.

One domain in which linear models could improve the decision-making process is admissions decisions.
In a manifestation of what is known as the correspondence bias, graduate school admissions tend to be biased in favor of individuals with high GPAs from lenient institutions because they fail to sufficiently discount the role of lenient grading.
One researcher developed a linear model to make graduate admissions decisions and compared it to the decisions of an admissions committee.
The model was capable of ruling out 55% of applicants who the committee also rejected.
The model also proved more effective at predicting the future ratings of applicants than the committee.
Overall, the effectiveness of this simple model suggests that the implementation of simple models using decision rules to make quick admissions decision can save universities hundreds of millions of dollars in time and resources saved from not having committees review applications.
Decision-analysis tools can also be of assistance in making hiring decisions.
Job interviews predict only 14% of the variability in employee performance. However, people continue to believe in them as an effective diagnostic tool.
Interviewers are biased by the availability of subjective qualities that they associate with effective performance when interviewing potential applicants.
Interviewer affect is influenced by superficial cues associated with a candidate and this influences their perceptions of the candidate.
Individuals who are extroverted, sociable, tall, attractive, and ingratiating are often considered as ones that represent the qualities of effective leaders even though they are far less predictive of performance than less observable traits such as conscientiousness and intelligence.
Managers tend to seek information that confirms the quality of their decision after hiring an applicant, which prevents them from learning. In addition, they never have a sample of performance from those who were interviewed but not hired to use as a comparison group.
Interviews may be difficult to justify based on the time that goes into them and the little predictive validity they have, but if the ratings of interviewers are combined into a linear model with measures of aptitude and past performance, hiring decisions could be improved.
7

Judgment in Managerial Decision Making 8e

Chapter 12
Improving Decision Making

Copyright 2013 John Wiley & Sons

1

Acquire Expertise
Presumably, experience should allow people to overcome biases, as it allows them to learn from feedback of past decisions
Yet, there is a great deal of evidence indicating that people experience difficulty in learning from past experience
Difficulties in learning from feedback
Accurate and immediate feedback rare
(i) outcomes are commonly delayed and not easily attributable to a particular action; (ii) variability in the environment degrades the reliability of feedback ; (iii) there is often no information about what the outcome would have been if another decision had been taken; and (iv) most important decisions are unique and therefore provide little opportunity for learning
people misremember their forecasts because they anchor to current states of the world and fail to accurately recall their prior predictions

One issue with much of what we have covered throughout this course is that much of the evidence supporting it was derived from experiments conducted on undergraduate students with little to no experience in the tasks that they were being asked to conduct.
Presumably, experience should allow people to overcome biases, as it allows them to learn from feedback.
Though this seems like a reasonable assumption, there is a great deal of evidence that people experience difficulty in learning from past experience.
People who play the “Acquire a Company” problem that we discussed earlier (the one where a rational decision-maker would realize that because a hypothetical target company will have more information about the outcome of an oil exploration project than the acquiring company, the acquiring company should not make an offer to acquire the target company) exhibited no learning after playing the game 20 times and receiving outcome feedback immediately after each game. They continued to make bids in the range of $50-$75 even though not making a bid is the optimal decision.
Negotiators reduce the tendency to overestimate the size of the bargaining zone in their negotiations, but there is no evidence that experience reduces other errors or leads to improved performance.
There are several reasons that are responsible for these difficulties in learning through experience:
Feedback is rarely accurate, immediate, and unambiguous.
Even when feedback does meet these criteria, evidence suggests that people misremember their forecasts because they anchor to current states of the world and fail to accurately recall their prior predictions. This prevents the process of learning to make more accurate forecasts, as people fail to underestimate the extent to which they erred in the first place.
Given that experience alone does not necessarily improve the quality of one’s future decisions, people should focus on acquiring “expertise” rather than experience.
Expertise involves the development of a strategic concept for what constitutes rational decision making in a given situation and for learning to overcome the potential biases that may arise in the situation.
It involves constant monitoring of our decision-making processes.
It also can be taught to others, unlike experience.
2

Acquire Expertise
Given that experience alone does not necessarily improve the quality of one’s future decisions, people should focus on acquiring “expertise” rather than experience.
Expertise involves the development of a strategic concept for what constitutes rational decision making in a given situation and for learning to overcome the potential biases that may arise in the situation.
It involves constant monitoring of our decision-making processes.
It also can be taught to others, unlike experience.

One issue with much of what we have covered throughout this course is that much of the evidence supporting it was derived from experiments conducted on undergraduate students with little to no experience in the tasks that they were being asked to conduct.
Presumably, experience should allow people to overcome biases, as it allows them to learn from feedback.
Though this seems like a reasonable assumption, there is a great deal of evidence that people experience difficulty in learning from past experience.
People who play the “Acquire a Company” problem that we discussed earlier (the one where a rational decision-maker would realize that because a hypothetical target company will have more information about the outcome of an oil exploration project than the acquiring company, the acquiring company should not make an offer to acquire the target company) exhibited no learning after playing the game 20 times and receiving outcome feedback immediately after each game. They continued to make bids in the range of $50-$75 even though not making a bid is the optimal decision.
Negotiators reduce the tendency to overestimate the size of the bargaining zone in their negotiations, but there is no evidence that experience reduces other errors or leads to improved performance.
There are several reasons that are responsible for these difficulties in learning through experience:
Feedback is rarely accurate, immediate, and unambiguous.
Even when feedback does meet these criteria, evidence suggests that people misremember their forecasts because they anchor to current states of the world and fail to accurately recall their prior predictions. This prevents the process of learning to make more accurate forecasts, as people fail to underestimate the extent to which they erred in the first place.
Given that experience alone does not necessarily improve the quality of one’s future decisions, people should focus on acquiring “expertise” rather than experience.
Expertise involves the development of a strategic concept for what constitutes rational decision making in a given situation and for learning to overcome the potential biases that may arise in the situation.
It involves constant monitoring of our decision-making processes.
It also can be taught to others, unlike experience.
3

Acquire Expertise
In the words of Confucius:
“By three methods we may learn wisdom: First, by reflection, which is noblest; Second, by imitation, which is easiest; and third, by experience, which is the bitterest.”

One issue with much of what we have covered throughout this course is that much of the evidence supporting it was derived from experiments conducted on undergraduate students with little to no experience in the tasks that they were being asked to conduct.
Presumably, experience should allow people to overcome biases, as it allows them to learn from feedback.
Though this seems like a reasonable assumption, there is a great deal of evidence that people experience difficulty in learning from past experience.
People who play the “Acquire a Company” problem that we discussed earlier (the one where a rational decision-maker would realize that because a hypothetical target company will have more information about the outcome of an oil exploration project than the acquiring company, the acquiring company should not make an offer to acquire the target company) exhibited no learning after playing the game 20 times and receiving outcome feedback immediately after each game. They continued to make bids in the range of $50-$75 even though not making a bid is the optimal decision.
Negotiators reduce the tendency to overestimate the size of the bargaining zone in their negotiations, but there is no evidence that experience reduces other errors or leads to improved performance.
There are several reasons that are responsible for these difficulties in learning through experience:
Feedback is rarely accurate, immediate, and unambiguous.
Even when feedback does meet these criteria, evidence suggests that people misremember their forecasts because they anchor to current states of the world and fail to accurately recall their prior predictions. This prevents the process of learning to make more accurate forecasts, as people fail to underestimate the extent to which they erred in the first place.
Given that experience alone does not necessarily improve the quality of one’s future decisions, people should focus on acquiring “expertise” rather than experience.
Expertise involves the development of a strategic concept for what constitutes rational decision making in a given situation and for learning to overcome the potential biases that may arise in the situation.
It involves constant monitoring of our decision-making processes.
It also can be taught to others, unlike experience.
4

Debias Your Judgment
Debiasing refers to a procedure for reducing or eliminating biases from the cognitive strategies of the decision maker
To eliminate cognitive biases, people should be:
warned about the possibility of bias,
understand the direction of the bias,
be provided with feedback about their biased decisions,
and undergo an extensive training program oriented at eliminating the bias

In order to eliminate their cognitive biases, people ideally should be warned about the possibility of bias, understand the direction of the bias, be provided with feedback about their biased decisions, and undergo an extensive training program oriented at eliminating the bias.
Though this seems like a reasonable plan, it is often difficult to implement an effective training program.
Research also suggests that training and testing must be closely linked and in close temporal proximity for effective learning to occur. In reality, people typically have to make conceptually similar decisions in different domains and feedback is often distant and ambiguous. This makes learning through training difficult.
Some strategies that reduce bias are:
Considering the opposite of what you are thinking of deciding at a given moment. This has been demonstrated to reduce overconfidence, hindsight bias, and anchoring effects.
Make decisions in groups.
Train in statistical reasoning so you are less subject to errors in probability perception.
Making people accountable for their decisions also tends to eliminate certain biases.
In order to eliminate biases, people must first “unfreeze” their biased behaviors that they have learned over time. This is a difficult task because:
Admitting that a strategy you have been using for years is flawed can be disconcerting.
People who have been successful have likely received positive feedback for using particular decision-making strategies that may actually be flawed. This makes them resistant to negative feedback about their decision-making strategies.
Successful individuals often believe that they are effective decision-makers. Receiving feedback that they are not clashes with their self-concept and may lead to them rejecting the notion that their decision-making is flawed.
The goal of presenting you with problems and examples of real-world behavior throughout this course was to provide you with unambiguous feedback about your own biases. Hopefully this made you more likely to reconsider your decision-making strategies and to become receptive to alternative ways of thinking.
Once you have unfrozen your past strategies, you must change them.
First, you should abstract from examples to adopt a more conceptual view of these biases that is not limited to specific contexts. Your decisions are rarely within the same specific context and without a strong concrete representation of the general pattern of cognitive biases, it will be difficult for you to recognize when you should adopt certain decision-making strategies.
If you can successfully abstract from situational examples of bias, you can better understand the root causes of various judgmental biases.
A final crucial step to change is recognizing that everybody is subject to biases. This should help you from being threatened by the possibility that you are biased. Once you are willing to change, the following procedures can help you successfully implement changes into your decision-making strategies:
Play Devil’s advocate with yourself and consider how your decisions may be flawed. This can help you notice any potential biases that are influencing your decisions. It also can debias your information processing.
Think of ways to test whether alternative viewpoints may be more valid than your own. For example, if you are thinking of investing in a startup that looks like a sure success, the fact that nobody else has invested in the firm yet may be a signal that something you cannot observe is flawed about the company.
Once you have successfully abandoned your current decision-making strategies in favor of ones that are unbiased, you then must make sure that this change persists and that you don’t revert to your old strategies that are flawed.
Continuous practice in implementing new strategies will help make them second-nature.
Reexamining your decision-making at various points in time can also help you make sure that you have not relapsed to your old habits.
5

Debias Your Judgment
Though this seems like a reasonable plan, it is often difficult to implement an effective training program.
Research suggests that training and testing must be closely linked and in close chronological proximity for effective learning to occur.
In reality, people typically have to make conceptually similar decisions in different domains and feedback is often distant and ambiguous. This makes learning through training difficult

In order to eliminate their cognitive biases, people ideally should be warned about the possibility of bias, understand the direction of the bias, be provided with feedback about their biased decisions, and undergo an extensive training program oriented at eliminating the bias.
Though this seems like a reasonable plan, it is often difficult to implement an effective training program.
Research also suggests that training and testing must be closely linked and in close temporal proximity for effective learning to occur. In reality, people typically have to make conceptually similar decisions in different domains and feedback is often distant and ambiguous. This makes learning through training difficult.
Some strategies that reduce bias are:
Considering the opposite of what you are thinking of deciding at a given moment. This has been demonstrated to reduce overconfidence, hindsight bias, and anchoring effects.
Make decisions in groups.
Train in statistical reasoning so you are less subject to errors in probability perception.
Making people accountable for their decisions also tends to eliminate certain biases.
In order to eliminate biases, people must first “unfreeze” their biased behaviors that they have learned over time. This is a difficult task because:
Admitting that a strategy you have been using for years is flawed can be disconcerting.
People who have been successful have likely received positive feedback for using particular decision-making strategies that may actually be flawed. This makes them resistant to negative feedback about their decision-making strategies.
Successful individuals often believe that they are effective decision-makers. Receiving feedback that they are not clashes with their self-concept and may lead to them rejecting the notion that their decision-making is flawed.
The goal of presenting you with problems and examples of real-world behavior throughout this course was to provide you with unambiguous feedback about your own biases. Hopefully this made you more likely to reconsider your decision-making strategies and to become receptive to alternative ways of thinking.
Once you have unfrozen your past strategies, you must change them.
First, you should abstract from examples to adopt a more conceptual view of these biases that is not limited to specific contexts. Your decisions are rarely within the same specific context and without a strong concrete representation of the general pattern of cognitive biases, it will be difficult for you to recognize when you should adopt certain decision-making strategies.
If you can successfully abstract from situational examples of bias, you can better understand the root causes of various judgmental biases.
A final crucial step to change is recognizing that everybody is subject to biases. This should help you from being threatened by the possibility that you are biased. Once you are willing to change, the following procedures can help you successfully implement changes into your decision-making strategies:
Play Devil’s advocate with yourself and consider how your decisions may be flawed. This can help you notice any potential biases that are influencing your decisions. It also can debias your information processing.
Think of ways to test whether alternative viewpoints may be more valid than your own. For example, if you are thinking of investing in a startup that looks like a sure success, the fact that nobody else has invested in the firm yet may be a signal that something you cannot observe is flawed about the company.
Once you have successfully abandoned your current decision-making strategies in favor of ones that are unbiased, you then must make sure that this change persists and that you don’t revert to your old strategies that are flawed.
Continuous practice in implementing new strategies will help make them second-nature.
Reexamining your decision-making at various points in time can also help you make sure that you have not relapsed to your old habits.
6

Debias Your Judgment
Strategies for reducing bias
Consider the opposite
Make decisions in groups
Training in statistical reasoning
Make people accountable

In order to eliminate their cognitive biases, people ideally should be warned about the possibility of bias, understand the direction of the bias, be provided with feedback about their biased decisions, and undergo an extensive training program oriented at eliminating the bias.
Though this seems like a reasonable plan, it is often difficult to implement an effective training program.
Research also suggests that training and testing must be closely linked and in close temporal proximity for effective learning to occur. In reality, people typically have to make conceptually similar decisions in different domains and feedback is often distant and ambiguous. This makes learning through training difficult.
Some strategies that reduce bias are:
Considering the opposite of what you are thinking of deciding at a given moment. This has been demonstrated to reduce overconfidence, hindsight bias, and anchoring effects.
Make decisions in groups.
Train in statistical reasoning so you are less subject to errors in probability perception.
Making people accountable for their decisions also tends to eliminate certain biases.
In order to eliminate biases, people must first “unfreeze” their biased behaviors that they have learned over time. This is a difficult task because:
Admitting that a strategy you have been using for years is flawed can be disconcerting.
People who have been successful have likely received positive feedback for using particular decision-making strategies that may actually be flawed. This makes them resistant to negative feedback about their decision-making strategies.
Successful individuals often believe that they are effective decision-makers. Receiving feedback that they are not clashes with their self-concept and may lead to them rejecting the notion that their decision-making is flawed.
The goal of presenting you with problems and examples of real-world behavior throughout this course was to provide you with unambiguous feedback about your own biases. Hopefully this made you more likely to reconsider your decision-making strategies and to become receptive to alternative ways of thinking.
Once you have unfrozen your past strategies, you must change them.
First, you should abstract from examples to adopt a more conceptual view of these biases that is not limited to specific contexts. Your decisions are rarely within the same specific context and without a strong concrete representation of the general pattern of cognitive biases, it will be difficult for you to recognize when you should adopt certain decision-making strategies.
If you can successfully abstract from situational examples of bias, you can better understand the root causes of various judgmental biases.
A final crucial step to change is recognizing that everybody is subject to biases. This should help you from being threatened by the possibility that you are biased. Once you are willing to change, the following procedures can help you successfully implement changes into your decision-making strategies:
Play Devil’s advocate with yourself and consider how your decisions may be flawed. This can help you notice any potential biases that are influencing your decisions. It also can debias your information processing.
Think of ways to test whether alternative viewpoints may be more valid than your own. For example, if you are thinking of investing in a startup that looks like a sure success, the fact that nobody else has invested in the firm yet may be a signal that something you cannot observe is flawed about the company.
Once you have successfully abandoned your current decision-making strategies in favor of ones that are unbiased, you then must make sure that this change persists and that you don’t revert to your old strategies that are flawed.
Continuous practice in implementing new strategies will help make them second-nature.
Reexamining your decision-making at various points in time can also help you make sure that you have not relapsed to your old habits.
7

Debias Your Judgment; Unfreezing
Many behaviors are ingrained, or part of a standard repertoire, and are therefore quite difficult to change:
Admitting that a strategy you have been using for years is flawed can be disconcerting.
People who have been successful have likely received positive feedback for using particular decision-making strategies that may actually be flawed. People tend to continue behavior that are positively rewarded
Successful individuals often believe that they are effective decision-makers. Receiving feedback that they are not clashes with their self-concept

In order to eliminate biases, people must first “unfreeze” their biased behaviors that they have learned over time. This is a difficult task because:
Admitting that a strategy you have been using for years is flawed can be disconcerting.
People who have been successful have likely received positive feedback for using particular decision-making strategies that may actually be flawed. This makes them resistant to negative feedback about their decision-making strategies.
Successful individuals often believe that they are effective decision-makers. Receiving feedback that they are not clashes with their self-concept and may lead to them rejecting the notion that their decision-making is flawed.
The goal of presenting you with problems and examples of real-world behavior throughout this course was to provide you with unambiguous feedback about your own biases. Hopefully this made you more likely to reconsider your decision-making strategies and to become receptive to alternative ways of thinking.
Once you have unfrozen your past strategies, you must change them.
First, you should abstract from examples to adopt a more conceptual view of these biases that is not limited to specific contexts. Your decisions are rarely within the same specific context and without a strong concrete representation of the general pattern of cognitive biases, it will be difficult for you to recognize when you should adopt certain decision-making strategies.
If you can successfully abstract from situational examples of bias, you can better understand the root causes of various judgmental biases.
A final crucial step to change is recognizing that everybody is subject to biases. This should help you from being threatened by the possibility that you are biased. Once you are willing to change, the following procedures can help you successfully implement changes into your decision-making strategies:
Play Devil’s advocate with yourself and consider how your decisions may be flawed. This can help you notice any potential biases that are influencing your decisions. It also can debias your information processing.
Think of ways to test whether alternative viewpoints may be more valid than your own. For example, if you are thinking of investing in a startup that looks like a sure success, the fact that nobody else has invested in the firm yet may be a signal that something you cannot observe is flawed about the company.
Once you have successfully abandoned your current decision-making strategies in favor of ones that are unbiased, you then must make sure that this change persists and that you don’t revert to your old strategies that are flawed.
Continuous practice in implementing new strategies will help make them second-nature.
Reexamining your decision-making at various points in time can also help you make sure that you have not relapsed to your old habits.
8

Debias Your Judgment; Change
Once you have unfrozen your past strategies, you must change them.
There are three critical steps to changing your decision-making process:
(1) clarification of the existence of specific judgmental deficiencies,
(2) explanation of the roots of these deficiencies, and
(3) reassurance that these deficiencies should not be taken as a threat to your self-esteem
Once you are willing to change, the following procedures can help you successfully implement changes into your decision-making strategies:
Play Devil’s advocate with yourself and consider how your decisions may be flawed. This can help you notice any potential biases that are influencing your decisions. It also can debias your information processing.
Think of ways to test whether alternative viewpoints may be more valid than your own.
For example, if you are thinking of investing in a startup that looks like a sure success, the fact that nobody else has invested in the firm yet may be a signal that something you cannot observe is flawed about the company

Once you have unfrozen your past strategies, you must change them.
First, you should abstract from examples to adopt a more conceptual view of these biases that is not limited to specific contexts. Your decisions are rarely within the same specific context and without a strong concrete representation of the general pattern of cognitive biases, it will be difficult for you to recognize when you should adopt certain decision-making strategies.
If you can successfully abstract from situational examples of bias, you can better understand the root causes of various judgmental biases.
A final crucial step to change is recognizing that everybody is subject to biases. This should help you from being threatened by the possibility that you are biased. Once you are willing to change, the following procedures can help you successfully implement changes into your decision-making strategies:
Play Devil’s advocate with yourself and consider how your decisions may be flawed. This can help you notice any potential biases that are influencing your decisions. It also can debias your information processing.
Think of ways to test whether alternative viewpoints may be more valid than your own. For example, if you are thinking of investing in a startup that looks like a sure success, the fact that nobody else has invested in the firm yet may be a signal that something you cannot observe is flawed about the company.
Once you have successfully abandoned your current decision-making strategies in favor of ones that are unbiased, you then must make sure that this change persists and that you don’t revert to your old strategies that are flawed.
Continuous practice in implementing new strategies will help make them second-nature.
Reexamining your decision-making at various points in time can also help you make sure that you have not relapsed to your old habits.
9

Debias Your Judgment; Refreezing
Once you have successfully abandoned your current decision-making strategies in favor of ones that are unbiased, you then must make sure that this change persists and that you don’t revert to your old strategies that are flawed.
Continuous practice in implementing new strategies will help make them second-nature.
Reexamining your decision-making at various points in time can also help you make sure that you have not relapsed to your old habits.

Once you have successfully abandoned your current decision-making strategies in favor of ones that are unbiased, you then must make sure that this change persists and that you don’t revert to your old strategies that are flawed.
Continuous practice in implementing new strategies will help make them second-nature.
Reexamining your decision-making at various points in time can also help you make sure that you have not relapsed to your old habits.
10