predictable surprise max bazerman predictable surprises: michael watkins auditor independence: don...

Predictable SurpriseMax Bazerman

Predictable Surprises: Michael Watkins

Auditor Independence: Don Moore, George, Loewenstein, Kimberly Morgan, and Lloyd Tanlu

Focusing effects in Competitive Contexts: Yoella Bereby-Meyer, Dolly Chugh, Brit Grosskopf, Lorraine Idson, Simone Moran, Avishalom Tor

What is a Predictable Surprise?

Can you think of problem in your organization that if left unattended will get

worse, eventually creating a far bigger problem, yet, the organization ignores the

problem?

This is a predictable surprise!

Airline Security as a Predictable Surprise - A

The U.S. government knew that terrorists were willing to become martyrs for their cause, and that their hatred toward the United States was increasing.  

Terrorists had previously bombed the World Trade Center.  

Terrorists hijacked an Air France airplane and made an aborted attempt to turn the airplane into a missile aimed at the Eiffel Tower.  

Airline Security as a Predictable Surprise - B

Terrorists had also failed in an attempt to simultaneously hijack twelve U.S. commercial airplanes in Asia.  

Dozens of federal reports and Vice President Al Gore's aviation security commission provided comprehensive evidence that the system was full of holes.  

Airline passengers knew how simple it was to board an airplane with items, such as small knives, that could be used as weapons.

The Failure of Auditor Independence As a Predictable Surprise - A

How could Arthur Andersen vouch for the financial health of a company that had been concealing billions of dollars in debt from its shareholders?  

Confronting criminal investigation for its role in the scandal, Andersen threw what some observers described as a “shredding party” of crucial and possibly incriminating documents.  

At the heart of the Enron debacle is a conflict of interest that experts have been warning about for years. In 2000, multiple scholars testified before the SEC that the rapid growth of the Big 5 accounting firms’ consulting divisions have made impartial financial audits almost impossible.  

The Failure of Auditor Independence As a Predictable Surprise - B

Greater separation between the Big 5 firms’ auditing and consulting functions, many advised, was needed to head off disaster; but, faced with vociferous opposition from auditors and industry, including Arthur Andersen CEO Joseph Berardino, the SEC backed down.

 The predictable result: the collapse of Enron, the loss of thousands of employees’ jobs and retirement savings, and a stain on Andersen’s reputation that may never be erased. Until the fundamental problem of auditor conflict-of-interest is addressed by the federal government, we can expect Enron to be just one in a long string of dramatic corporate disasters.

The Failure of Auditor Independence?

•Adelphia

•Global Crossing

•Haliburton

•Tyco

•Xerox

•Worldcom

1) Legrenzi, Girotto, and Johnson Laird (1993)

2) Gilbert, Wilson and colleagues (Gilbert & Wilson, 2000; Wilson, Wheatly, Meyers, Gilbert, & Axsom, 2000)

3) Schkade and Kahneman (1998)

The Failure to Focus

Characteristics of Predictable Surprises

1) A shared trait of predictable surprises is that leaders knew a problem existed and that the problem would not solve itself.

2) Predictable surprises can be expected when organizational members recognize that a problem is getting worse over time.

3) Fixing the problem would incur significant costs in the present, while the benefits of action would be delayed and ambiguous.

4) Decision-makers, organizations, and nations often fail to prepare for predictable surprises because of the natural human tendency to maintain the status quo.

5) A small vocal minority benefits from inaction, and is motivated to subvert the actions of leaders for their own private benefit.

6) Leaders can expect little credit for the prevention of predictable surprises.

Ignoring Predictable Surprises

We Ignore:1) How the problem

will get worse over time.

2) How others will act opportunistically to exploit the problem.

3) How the environment will affect the problem.

4) How other actors interact with the environment.

Status Quo & Inferior Outcomes

Time to Act

Why Don’t We Prevent Predictable Surprises?

1) Cognitive

2) Organizational

3) Political

Further Cognitive Explanations for Predictable Surprises

1) Positive Illusions

2) Egocentrism

3) Discounting the Future (particularly under uncertainty)

4) Ignoring the Decisions of Others, and Not Thinking Ahead

5) The Omission Bias and the Status Quo

6) Don’t Fix It If We Can’t Tell It’s Broken

Ignoring Others and the Rules of the Game

Your Decision

Other’s Decision

Rules of the Game

Outcome

Acquiring a CompanyIn the following exercise you will represent Company A (the acquirer),

which is currently considering acquiring Company T (the target) by means of a tender offer. You plan to tender in cash for 100% of Company T’s shares but are unsure how high a price to offer. The main concern is this: the value of Company T depends directly on the outcome of a major oil exploration project it is currently undertaking. Indeed, the very viability of Company T depends on the exploration outcome. If the project fails, the company under current management will be worth nothing --$0/share. But if the project succeeds, the value of the company under current management could be as high as $100/share. All share values between $0 and $100 are considered equally likely. By all estimates, the company will be worth considerably more in the hands of Company A than under current management. In fact, whatever the ultimate value under current management, the company will be worth fifty percent more under the management of A than under Company T. If the project fails, the company is worth $0/share under either management. If the exploration project generates a $50/share value under current management, the value under Company A is $75/share. Similarly, a $100/share value under Company T implies a $150/share value under Company A, and so on.

Acquiring a CompanyThe board of directors of Company A has asked you to determine the

price they should offer for Company T's shares.  This offer must be made now, before the outcome of the drilling project is known.  From all indications, Company T would be happy to be acquired by Company A, provided it is at a profitable price.  Moreover, Company T wishes to avoid, at all cost, the potential of a takeover bid by any other firm.  You expect Company T to delay a decision on your bid until the results of the project are in, then accept or reject your offer before the news of the drilling results reaches the press.

Thus, you (Company A) will not know the results of the exploration project when submitting your price offer, but Company T will know the results when deciding whether or not to accept your offer.  In addition, Company T will accept any offer by Company A that is greater than the (per share) value of the company under current management. Thus, if you offer $50/share, for instance, Company T will accept if the value of the company to Company T is anything less than $50.

As the representative of Company A, you are deliberating over price offers in the range of $0/share (this is tantamount to making no offer at all) to $150/share.  What price offer per share would you tender for Company T's stock?

$______ per/share

Acquiring a Company

0

5

10

15

20

25

30

35

40

45

50

$0 $10-

15

$20-

25

$30-

35

$40-

45

$50-

55

$60-

65

$70-

75

$80-

85

$90-

95

Responses

Total number of responses: 123

Acquiring a Company

0

10

20

30

40

50

60

1 3 5 7 9 11 13 15 17 19

Mean Bids Across Trials

Monty Hall - alwaysIn a recent study, college students were given the following question:

In this problem, you will be given a choice of boxes X, Y, or Z. One of these three boxes has a valuable prize in it. The other two boxes are empty. After you pick one of the boxes, the computer will definitely open one of the other two boxes, show you that this unchosen box does not have the prize, and offer you to trade your chosen box for the unopened unchosen box. For example, if you chose box X, the computer will open one of the two other boxes (e.g., Y). The computer will then offer you the opportunity to switch your choice from X to Z.

A student who participated in the study picked box Y. The computer then opened box Z, showed the student it was empty, and offered the student to trade box Y (which the student chose) for box X (the remaining unopened, unchosen box).

Please state whether the student should have traded box Y for box X or not, in order to have the best chance of winning the prize.

Yes______ No_______

Monty Hall - selective

In a recent study, college students were given the following question:

In this problem, you will be given a choice of boxes X, Y, or Z. One of these three boxes has a valuable prize in it. The other two boxes are empty. After you pick one of the boxes, the computer may open one of the other two boxes, show you that this unchosen box does not have the prize, and offer you to trade your chosen box for the unopened unchosen box. The computer will make its decision whether to open a box and offer you a switch with the goal of minimizing the likelihood that you get the prize. For example, if you chose box X, the computer will open one of the two other boxes (e.g., Y). The computer will then offer you the opportunity to switch your choice from X to Z.

A student who participated in the study picked box Y. The computer then opened box Z, showed the student it was empty, and offered the student to trade box Y (which the student chose) for box X (the remaining unopened, unchosen box).

Please state whether the student should have traded box Y for box X or not, in order to have the best chance of winning the prize.

Yes______ No_______

Multi-party Ultimatum - minimum

MBA students from a prestigious University read the following problem, and played one of the six roles – A, B, C, D, E, and F:

In this exercise, six people will be randomly assigned to the roles A, B, C, D, E, and F. A will be randomly selected, and given $60 to allot among A, B, C, D, E, and F. The amounts given to B, C, D, E, and F must be equal, but this amount may be different from the amount that A allocates to A (herself/himself). B, C, D, E, and F will be asked to specify the minimum amount that they would accept. If the amount offered by A to each of B, C, D, E, and F is equal to or greater than the smallest amount specified by B, C, D, E, or F, the $60 will be divided as specified by A. If, however, all of the amounts specified by B, C, D, E, and F are larger than the amount offered by A, all six parties will receive $0.

Please specify the allocation from A that would maximize A’s average dollar payoff:A_____ B_____ C _____ D _____ E_____ F_____

Multi-party Ultimatum - maximum

MBA students from a prestigious University read the following problem, and played one of the six roles – A, B, C, D, E, and F:

In this exercise, six people will be randomly assigned to the roles A, B, C, D, E, and F. A will be randomly selected, and given $60 to allot among A, B, C, D, E, and F. The amounts given to B, C, D, E, and F must be equal, but this amount may be different from the amount that A allocates to A (herself/himself). B, C, D, E, and F will be asked to specify the minimum amount that they would accept. If the amount offered by A to each of B, C, D, E, and F is equal to or greater than the largest amount specified by B, C, D, E, or F, the $60 will be divided as specified by A. If, however, any of the amounts specified by B, C, D, E, and F is larger than the amount offered by A, all six parties will receive $0.

Please specify the allocation from A that would maximize A’s average dollar payoff:A_____ B_____ C _____ D _____ E_____ F_____

Task Order

Order A: MAO, DPS, AAC, MM, DPL

Order B: DPS, MAO, AAC, DPL, MM

Order C: MM, DPL, AAC, MAO, DPS

Order D: DPL, MM, AAC, DPS, MAO

Summary of Coding Scheme Code Description

Rules (R) Statements predominantly relating to the rules of the problems.

Rna Statements predominantly relating to the rules of the problems involving a correct analysis of some aspect of the rules.

Rw Statements predominantly relating to the rules of the problems involving a mistake in understanding or analysis.

Rnr Statements predominantly relating to the rules of the problems involving a reiteration of some important component of the rules.

Rm All other statements predominantly relating to the rules of the problems.

Actor (A) Statements predominantly relating to the focal decision maker (actor) and his interaction with the rules.

Ana Statements predominantly relating to the focal decision maker and his interaction with the rules involving a correct analysis of some aspect of

this interaction.

Aw Statements predominantly relating to the focal decision maker and his interaction with the rules involving a mistake in understanding or

analysis of this interaction.

Am All other statements predominantly relating to the focal decision maker and his interaction with the rules.

Other (O) Statements predominantly relating to the other parties and their interaction with the rules.

Ona Statements predominantly relating to the other parties and their interaction with the rules involving a correct analysis of some aspect of this interaction.

Ow Statements predominantly relating to the other parties and their interaction with the rules involving a mistake in understanding or analysis of this interaction.

Om All other statements predominantly relating to the other parties and their interaction with the rules.

Interaction (I) Statements predominantly relating to the interaction between the actor and the other parties (in light of the rules of the problems).

Ina Statements predominantly relating to the interaction between the actor and the other parties involving a correct analysis of some aspect of this interaction (in light of the rules of the problem).

Iw Statements predominantly relating to the interaction between the actor and the other parties involving a mistake in understanding or analysis of this interaction (in light of the rules of the problem).

Im All other statements predominantly relating to the interaction between the actor and the other parties (in light of the rules of the problems).

Miscellaneous (M) All other statements not included in any of the previous categories.

Summary of Coding Scheme

SIMPLIFIED SUMMARY OF CODES

Code Description

Rules (R) Rna: Statements predominantly relating to the rules of the problems involving a correct analysis of some aspect of the rules.

Rw: Statements predominantly relating to the rules of the problems involving a mistake in understanding or analysis.

Actor (A) Ana: Statements predominantly relating to the focal decision maker and his interaction with the rules involving a correct analysis of some aspect of this interaction.

Aw: Statements predominantly relating to the focal decision maker and his interaction with the rules involving a mistake in understanding or analysis

of this interaction.

Other (O) Ona: Statements predominantly relating to the other parties and their interaction with the rules involving a correct analysis of some aspect of this interaction.

Ow: Statements predominantly relating to the other parties and their interaction with the rules involving a mistake in understanding or analysis of this interaction.

Interaction Ina: Statements predominantly relating to the interaction between the actor and the other parties involving a correct analysis of some aspect of this interaction (in light of the rules of the problem).

Iw: Statements predominantly relating to the interaction between the actor and the other parties involving a mistake in understanding or analysis of this interaction (in light of the rules of the problem).

Counts and Percentages of Correct Responses, by Task

Correct Responses

Task

AAC DPL DPSDP-

PairsMAO MM

MH-Pairs

n 7 46 14 6 34 65 20

Percentage 8.5% 56.1% 17.1% 7.3% 41.5% 79.3% 24.4%

Percentage of Participants’ Statements Belonging to Each Code, by Task

AAC DPL DPS DP-Pairs

MAO MM MH-Pairs

(N=82) (N=81)[i] (N=82) (N=81)2 (N=82) (N=82) (N=82)

Rna 0.00% 0.20% 0.20% 0.20% 0.50% 0.30% 0.40%

Rw 1.70% 2.30% 1.40% 1.80% 1.50% 1.80% 1.70%

Rnr 0.20% 2.60% 2.40% 2.50% 1.10% 2.50% 1.80%

Rm 25.60% 23.20% 22.10% 22.70% 21.30% 20.60% 21.00%

Ana 0.10% 0.00% 0.30% 0.20% 2.20% 1.30% 1.70%

Aw 1.80% 0.70% 0.70% 0.70% 0.20% 0.10% 0.10%

Am 8.70% 6.90% 5.50% 6.20% 6.80% 6.40% 6.60%

Ona 0.30% 1.00% 0.30% 0.60% 0.90% 4.90% 2.90%

Ow 0.50% 1.40% 2.20% 1.80% 0.80% 1.10% 0.90%

Om 5.00% 10.30% 10.80% 10.60% 6.30% 9.80% 8.10%

Ina 0.50% 1.50% 0.70% 1.10% 1.00% 6.60% 3.80%

Iw 11.80% 5.70% 9.30% 7.60% 18.80% 10.10% 14.40%

Im 12.40% 14.00% 13.20% 13.60% 9.10% 6.80% 8.00%

M 31.50% 30.10% 31.00% 30.60% 29.60% 27.80% 28.70%

TOTAL 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%

Code Task

Code Show-up Percentages by Task, for Correct v. Incorrect Responses (and 2 statistic)

*:p < .10 **:p < .05 ***:p .01

Logistic Regression Predicting Participants’ Task-by-Task Correct Responses

*:p < .10 **:p < .05 ***:p .01

a In tasks where quasi-complete separation of data points existed, exact conditional regression was used, and we report exact parameter estimates and the score statistic for overall model fit (Agresti, 1996; Hosmer & Lemeshow, 2000).

Counts and Percentages of Correct Responses for Code Show-up Combinations, by Task

Code Show-up

AAC DPL DPS DP-Pairs MAO MM MH-Pairs

Ina OnlyCorrect responses

1/1 13/13 8/8 3/4 2/2 20/20 1/1

Percent correct

100.00% 100.00% 100.00% 75.00% 100.00% 100.00% 100.00%

Both Ina and IwCorrect responses

1/6 4/4 1/3 2/20 4/4 13/16 15/38

Percent correct

16.70% 100.00% 33.30% 9.09% 100.00% 81.30% 39.50%

No Ina, No IwCorrect responses

3/7 14/17 3/4 0/0 7/7 11/13 0/0

Percent correct

42.90% 82.40% 75.00% 0.00% 100.00% 84.60% 0.00%

Iw OnlyCorrect responses

2/68 15/47 2/67 1/55 21/69 21/33 3/43

Percent correct

2.90% 31.90% 3.00% 1.82% 30.40% 63.60% 9.30%

T a s k

Multiple Regression Predicting Participants’ Overall Success Rate

Variable Sum Correct A: 0-3 scale

Sum Correct B: 0-5 scale

Intercept 1.44*** 2.83***

-0.42 -0.380.08 0.1-0.15 -0.16-0.11* -0.01-0.07 -0.080.04 0.15-0.12 -0.130.01 -0.05-0.1 -0.12

-0.03 -0.12-0.11 -0.110.08 0.01-0.09 -0.09

0.25** 0.46***-0.1 -0.12

-0.42*** -0.30***-0.15 -0.1

Rna show-up

Rw show-up

Ana show-up

Aw show-up

Adjusted

R2.25*** .42***

Ona show-up

Ow show-up

Ina show-up

Iw show-up *:p < .10 **:p < .05

***:p < .01

Overcoming Indirect Effects by Means of Analogical Training

Idson, Bereby-Meyer, Chugh, Garcia, Grosskopf, Moran, & Bazerman (2002)In this experiment, participants in the 2 training conditions were first asked to solve 2 versions of the Monty Hall (MH) and Divide the Pie (DP) problems before they were given the Acquiring a Company (AAC) problem.

1. Simultaneous Training Condition:

MH1, MH2, DP1, DP2 AAC

presented presentedsimultaneously simultaneously Give advice, 20 trials, Give

advice

2. Sequential Training Condition:

MH1, MH2, DP1, DP2 AAC

presented presented sequentially sequentially Give advice, 20 trials, Give advice

3. Control Condition:

AAC MH1, MH2, DP1, DP2

presented presented Give advice, 20 trials, Give advice sequentially sequentially

(1/2 of the subjects in each condition received MH, DP in reverse order. No order effects found.)

Percentage of correct responses

Initial AdviceAdvice after

20 Trials

Simultaneous Training

(n = 46)33% 67%

Sequential Training

(n = 39)33% 60%

Control

(n = 51)14% 53%

Organizational Explanations for Predictable Surprises

1) Structural Barriers (collection, processing, and dissemination of information)

2) Dysfunctional Leadership Incentives• No Reward for Fixing the Problem• “Not my responsibility”

Political Explanations of Predictable Surprises and A Very Bad 2001

Campaign Finance Reform

Failure of Auditor Independence

Failure of Airline Security

Enron

9/11

Why Do Accept Special-interest Groups?

Regardless of whether or not they support welfare, most people assume that government welfare funds are given directly to poor people. In truth, the vast majority of welfare in the United States subsidizes corporations – often to engage in activities that have a negative effect on society. For example, the U.S. government subsidizes tobacco farmers, while simultaneously planning to sue cigarette companies for suppressing information about the dangers of nicotine addiction. The government also subsidizes the cutting of national forests, earning mere pennies on the dollar of timber extracted.

Economics: The issue is coordinating three auto makers versus 275,000,000 citizens

Psychology: Why do we care so little?

The Threats to Auditor Independence

• Being hired and fired by the client

• Providing other services for your auditing client

• Taking jobs in the client firm

Have We Solved the Problem of Auditor

Independence?

The Misspecification of the Problem

As is often the case when issues of auditor independence arise, the problem was defined in terms of intentionally corrupt behavior. This framing of the problem implies that it can be solved through moral suasion and/or the threat of sanctions. At the same time, this perspective fails to account for the fundamental biases that lie at the core of the auditing function.

The Failure of the Sarbanes-Oxley Act of 2002

• Auditor Rotation

• Limited Non-Audit Services

• Leaders Cannot Move Between Firms

What Are Some Future Predictable Surprises?

• Government Subsidies

• Global Warming

• Campaign Finance Reform

• Auditor Conflict of Interest

• Frequent Flier Programs

Vision and Courage:Leaders Need Both

9/11: Clinton and Gore had the vision on airline security; they simply failed to have the courage to act.

Auditor Independence: Arthur Levitt had the vision on this problem, but failed to have the courage to stand up to fierce lobbying in Congress.