Timid Choices and Bold Forecasts: A Cognitive …courses.washington.edu/pbafhall/514/514 Readings...Timid Choices and Bold Forecasts: A Cognitive Perspective on Risk Taking Daniel

Timid Choices and Bold Forecasts:A Cognitive Perspective on Risk Taking

Daniel Kahneman • Dan LovalloDeparttnent of Psychology, University of California, Berkeley, California 94720

V^alter A. Haas School of Business Administration, University of California, Berkeley, California 94720

Decision makers have a strong tendency to consider problems as unique. They isolate thecurrent choice from future opportunities and neglect the statistics of the past in evaluating

current plans. Overly cautious attitudes to risk result from a failure to appreciate the effects ofstatistical aggregation in mitigating relative risk. Overly optimistic forecasts result from theadoption of an inside view of the problem, which anchors predictions on plans and scenarios.The conflicting biases are documented in psychological research. Possible implications for de-cision making in organizations are examined.{Decision Making; Risk; Forecasting; Managerial Cognition)

The thesis of this essay is that decision makers are ex-cessively prone to treat problems as unique, neglectingboth the statistics of the past and the multiple oppor-tunities of the future. In part as a result, they are sus-ceptible to two biases, which we label isolation errors:their forecasts of future outcomes are often anchoredon plans and scenarios of success rather than on pastresults, and are therefore overly optimistic; their eval-uations of single risky prospects neglect the possibilitiesof pooling risks and are therefore overly timid. We arguethat the balance of the two isolation errors affects therisk-taking propensities of individuals and organiza-tions.

The cognitive analysis of risk taking that we sketchdiffers from the standard rational model of economicsand also from managers' view of their own activities.The rational model describes business decisions aschoices among gambles with financial outcomes, andassumes that managers' judgments of the odds areBayesian, and that their choices maximize expectedutility. In this model, uncontrollable risks are acknowl-edged and accepted because they are compensated bychances of gain. As March and Shapira (1987) reportedin a well-known essay, managers reject this interpre-tation of their role, preferring to view risk as a challengeto be overcome by the exercise of skill and choice as a

commitment to a goal. Although managers do not denythe possibility of failure, their idealized self-image isnot a gambler but a prudent and determined agent, whois in control of both people and events.

The cognitive analysis accepts choice between gam-bles as a model of decision making, but does not adoptrationality as a maintained hypothesis. The gamblingmetaphor is apt because the consequences of most de-cisions are uncertain, and because each option could inprinciple be described as a probability distribution overoutcomes. However, rather than suppose that decisionmakers are Bayesian forecasters and optimal gamblers,we shall describe them as subject to the conflicting biasesof unjustified optimism and unreasonable risk aversion.It is the optimistic denial of uncontrollable uncertaintythat accounts for managers' views of themselves asprudent risk takers, and for their rejection of gamblingas a model of what they do.

Our essay develops this analysis of forecasting andchoice and explores its implications for organizationaldecisions. The target domain for applications includeschoices about potentially attractive options that decisionmakers consider significant and to which they are willingto devote forecasting and planning resources. Examplesmay be capital investment projects, new products, oracquisitions. For reasons that will become obvious, our

0025-1909/93/3901/0017$01.25Copyright © 1993, The Institute of Management Sdences MANAGEMENT SCIENCE/VOI. 39, No. 1, January 1993 17

KAHNEMAN AND LOVALLOChoices and Forecasts

critique of excessive risk aversion is most likely to applyto decisions of intermediate size: large enough to matterfor the organization, but not so large as to be trulyunique, or potentially fatal. Of course, such decisionscould be perceived as both unique and potentially fatalby the executive v ho makes them. Two other restric-tions on the present treatment should be mentioned atthe outset. First, we do not deal with decisions that theorganization explicitly treats as routinely repeated. Op-portunities for learning and for statistical aggregationexist when closely similar problems are frequently en-countered, especially if the outcomes of decisions arequickly known and provide unequivocal feedback;competent management will ensure that these oppor-tunities are exploited. Second, we do not deal with de-cisions made under severely adverse conditions, whenall options are undesirable. These are situations in whichhigh-risk gambles are often preferred to the acceptanceof sure losses (Kahneman and Tversky 1979a), and inwhich commitments often escalate and sunk costsdominate decisions (Staw and Ross 1989). We restrictthe treatment to choices among options that can beconsidered attractive, although risky. For this class ofprojects we predict that there will be a general tendencyto underestimate actual risks, and a general reluctanceto accept significant risks once they are acknowledged.

Timid ChoicesWe begin by reviewing three hypotheses about indi-vidual preferences for risky prospects.

Risk Aversion. The first hypothesis is a common-place: most people are generally risk averse, normallypreferring a sure thing to a gamble of equal expectedvalue, and a gamble of low variance over a riskier pros-pect. There are two important exceptions to risk aver-sion. First, many people are willing to pay more forlottery tickets than their expected value. Second, studiesof individual choice have shown that managers, likeother people, are risk-seeking in the domain of losses(Bateman and Zeithaml 1989, Fishburn and Kochen-berger 1979, Laughhunn et al. 1980).^ Except for these

' Observed correlations between accounting variability and mean re-turn have also been interpreted as evidence of risk-seeking by un-successful firms (Bowman 1982, Fiegenbaum 1990, Fiegenbaum andThomas 1988), but this interpretation is controversial (Ruefli 1990).

cases, and for the behavior of addictive gamblers, riskaversion is prevalent in choices between favorableprospects with known probabilities. This result has beenconfirmed in numerous studies, including some in whichthe subjects were executives (MacCrimmon and Weh-rung 1986, Swalm 1966).^

The standard interpretation of risk aversion is de-creasing marginal utility of gains. Prospect theory(Kahneman and Tversky 1979a; Tversky and Kahne-man 1986, 1992) introduced two other causes: the cer-tainty effect and loss aversion. The certainty effect is asharp discrepancy between the weights that are attachedto sure gains and to highly probable gains in the eval-uation of prospects. In a recent study of preferences forgambles the decision weight for a probability of 0.95was approximately 0.80 (Tversky and Kahneman 1992).Loss aversion refers to the observation that losses anddisadvantages are weighted more than gains and ad-vantages. Loss aversion affects decision making in nu-merous ways, in riskless as well as in risky contexts. Itfavors inaction over action and the status quo over anyalternatives, because the disadvantages of these alter-natives are evaluated as losses and are thereforeweighted more than their advantages (Kahneman et al.1991, Samuelson and Zeckhauser 1988, Tversky andKahneman 1991). Loss aversion strongly favors theavoidance of risks. The coefficient of loss aversion wasestimated as about 2 in the Tversky-Kahneman exper-iment, and coefficients in the range of 2 to 2.5 havebeen observed in several studies, with both risky andriskless prospects (for reviews, see Kahneman, Knetschand Thaler 1991; Tversky and Kahneman 1991).

Near-Proportionality. A second important gener-alization about risk attitudes is that, to a good first ap-proximation, people are proportionately risk averse: cashequivalents for gambles of increasing size are (not quite)proportional to the stakes. Readers may find it instruc-tive to work out their cash equivalent for a 0.50 chanceto win $100, then $1,000, and up to $100,000. Mostreaders will find that their cash equivalent increases bya factor of less than 1,000 over that range, but mostwill also find that the factor is more than 700. Exact

^ A possible exception is a study by Wehrung (1989), which reportedrisk-neutral preferences for favorable prospects in a sample of exec-utives in oil companies.

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proportionality for wholly positive prospects would im-ply that value is a power function, u(x) = x", where xis the amount of gain (Keeney and Raiffa 1976). In arecent study of preferences for gambles (Tversky andKahneman 1992), a power function provided a goodapproximation to the data over almost two orders ofmagnitude, and the deviations were systematic: cashequivalents increased slightly more slowly than prizes.

Much earlier, Swalm (1966) had compared executiveswhose planning horizons, defined as twice the maxi-mum amount they might recommend be spent in oneyear, ranged from $50,000 to $24,000,000. He measuredtheir utility functions by testing the acceptability ofmixed gambles, and observed that the functions ofmanagers at different levels were quite similar whenexpressed relative to their planning horizons. The pointon which we focus in this article is that there is almostas much risk aversion when stakes are small as whenthey are large. This is unreasonable on two grounds:(i) small gambles do not raise issues of survival or ruin,which provide a rationale for aversion to large risks;(ii) small gambles are usually more common, offeringmore opportunities for the risk-reducing effects of sta-tistical aggregation.

Narrow Decision Frames. The third generalizationis that people tend to consider decision problems oneat a time, often isolating the current problem from otherchoices that may be pending, as well as from futureopportunities to make similar decisions. The followingexample (from Tversky and Kahneman 1986) illustratesan extreme form of narrow framing:

Imagine that you face the following pair of concurrent decisions.First examine both decisions, then indicate the options youprefer.

Decision (i) Choose between:(A) a sure gain of $240 (84%)(B) 25% chance to gain $1000 and 75% chance to gain nothing(16%)

Decision (ii) Choose between:(C) a sure loss of $750 (13%)(D) 75% chance to lose $1000 and 25% chance to lose nothing(87%)

The percentage of respondents choosing each optionis shown in parentheses. As many readers may havediscovered for themselves, the suggestion that the twoproblems should be considered concurrently has no ef-

fect on preferences, which exhibit the common patternof risk aversion when options are favorable, and riskseeking when options are aversive. Most respondentsprefer the conjunction of options A & D over othercombinations of options. These preferences are intu-itively compelling, and there is no obvious reason tosuspect that they could lead to trouble. However, simplearithmetic shows that the conjunction of preferred op-tions A & D is dominated by the conjunction of rejectedoptions B & C. The combined options are as follows:

A & D: 25% chance to win $240 and 75% chance to lose $760,B & C: 25% chance to win $250 and 75% chance to lose $750.

A decision maker who is risk averse in some situationsand risk seeking in others ends up paying a premiumto avoid some risks and a premium to obtain others.Because the outcomes are ultimately combined, thesepayments may be unsound. For a more realistic example,consider two divisions of a company that face separatedecision problems.^ One is in bad posture and faces achoice between a sure loss and a high probability of alarger loss; the other division faces a favorable choice.The natural bent of intuition will favor a risk-seekingsolution for one and a risk-averse choice for the other,but the conjunction could be poor policy. The overallinterests of the company are better served by aggre-gating the problems than by segregating them, and bya policy that is generally more risk-neutral than intuitivepreferences.

People often express different preferences when con-sidering a single play or multiple plays of the samegamble. In a well-known problem devised by Samu-elson (1963), many respondents state that they wouldreject a single play of a gamble in which they haveequal chances to win $200 or to lose $100, but wouldaccept multiple plays of that gamble, especially whenthe compound distribution of outcomes is made explicit(Redelmeier and Tversky 1992). The question ofwhether this pattern of preferences is consistent withutility theory, and with particular utility functions forwealth has been discussed on several occasions (e.g..Lopes 1981, Tversky and Bar-Hillel 1983). The argu-ment that emerges from these discussions can be sum-marized as "If you wish to obey the axioms of utility

' We are endebted to Amos Tversky for this example.

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theory and would accept multiple plays, then it is log-ically inconsistent for you to turn down a single play".We focus on another observation: the near-certainty thatthe individual who is now offered a single play of theSamuelson gamble is not really facing her last oppor-tunity to accept or reject a gamble of positive expectedvalue. This suggests a slightly different argument: "Ifyou would accept multiple plays, then you should acceptthe single one that is offered now, because it is veryprobable that other bets of the same kind will be offeredto you later". A frame that includes future opportunitiesreduces the difference between the two versions ofSamuelson's problem, because a rational individual whois offered a single gamble will adopt a policy for m + 1such gambles, where m is the number of similar op-portunities expected within the planning horizon. Willpeople spontaneously adopt such a broad frame? Aplausible hypothesis, supported by the evidence fornarrow framing in concurrent decisions and by the pat-tern of answers to Samuelson's problems, is that ex-pectations about risky opportunities of the future aresimply ignored when decisions are made.

It is generally recognized that a broad view of decisionproblems is an essential requirement of rational decisionmaking. There are several ways of broadening the de-cision frame. Thus, decision analysts commonly pre-scribe that concurrent choices should be aggregated be-fore a decision is made, and that outcomes should beevaluated in terms of final assets (wealth), rather thanin terms of the gains and losses associated with eachmove. The recommended practice is to include estimatesof future earnings in the assessment of wealth. Althoughthis point has attracted little attention in the decisionliterature, the wealth of an agent or organization there-fore includes future risky choices, and depends on thedecisions that the decision maker anticipates makingwhen these choices arise.* The decision frame shouldbe broadened to include these uncertainties: neglect offuture risky opportunities will lead to decisions that arenot optimal, as evaluated by the agent's own utilityfunction. As we show next, the costs of neglecting future

* Two agents that have the same current holdings and face the sameseries of risky choices do not have the same wealth if they havedifferent attitudes to risk and expect to make different decisions. Forformal discussions of choice in the presence of unresolved uncertainty,see Kreps (1988) and Spence and Zeckhauser (1972).

opportunities are especially severe when options areevaluated in terms of gains and losses, which is whatpeople usually do.

The Costs of IsolationThe present section explores some consequences of in-corporating future choice opportunities into current de-cisions. We start from an idealized utility function whichexplains people's proportional risk preferences for singlegambles. We then compute the preferences that thisfunction implies when the horizon expands to includea portfolio of gambles.

Consider an individual who evaluates outcomes asgains and losses, and who maximizes expected utilityin these terms. This decision maker is risk-averse in thedomain of gains, risk-seeking in the domain of losses,loss-averse, and her risky choices exhibit perfect pro-portionality. She is indifferent between a 0.50 chanceto win $1,000 and a sure gain of $300 (also between0.50 chance to win $10,000 and $3,000 for sure) andshe is also indifferent between the status quo and agamble that offers equal chances to win $250 or to lose$100. The aversion to risk exhibited by this individualis above the median of respondents in laboratory stud-ies, but well within the range of observed values. Forthe sake of simple exposition we ignore all probabilitydistortions and attribute the risk preferences of the in-dividual entirely to the shape of her utility function forgains and losses. The preferences we have assumed im-ply that the individual's utility for gains is described bya power function with an exponent of 0.575 and thatthe function in the domain of losses is the mirror imageof the function for gains, after expansion of the X-axisby a factor of 2.5 (Tversky and Kahneman 1991). Theillustrative function was chosen to highlight our mainconclusion: with proportional risk attitudes, even themost extreme risk aversion on individual problemsquickly vanishes when gambles are considered part ofa portfolio.

The power utility function is decreasingly risk averse,and the decrease is quite rapid. Thus, a proportionatelyrisk averse individual who values a 0.50 chance to win$100 at $30 will value a gamble that offers equal chancesto win either $1,000 or $1,100 at $1,049. This preferenceis intuitively acceptable, indicating again that the powerfunction is a good description of the utility of outcomes

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for single gambles considered in isolation. The powerfunction fits the psychophysical relation of subjectivemagnitude to physical magnitude in many other con-texts (Stevens 1975).

To appreciate the effects of even modest aggregationwith this utility function, assume that the individualowns three independent gambles:

one gamble with a 0.50 chance to win $500,two gambles, each with a 0.50 chance to win $250.

Simple arithmetic yields the compound gamble:

0.125 chance to win $1,000, and 0.25 to win $750, $500, and$250.

If this individual applies the correct probabilities to herutility function, this portfolio will be worth $433 to her.This should be her minimum selling price if she ownsthe gamble, her cash equivalent if she has to choosebetween the portfolio of gambles and cash. In contrast,the sum of the cash equivalents of the gambles consid-ered one at a time is only $300. The certainty premiumthe individual would pay has dropped from 40% to13% of expected value. By the individual's own utilityfunction, the cost of considering these gambles in iso-lation is 27% of their expected value, surely more thanany rational decision maker should be willing to payfor whatever mental economy this isolation achieves.

The power of aggregation to overcome loss aversionis equally impressive. As already noted, our decisionmaker is indifferent between accepting or rejecting agamble that offers a 0.50 chance to win $250 and a 0.50chance to lose $100. However, she would value theopportunity to play two of these gambles at $45, andsix gambles at $304. Note that the average incrementalvalue of adding the third to the sixth gamble is $65,quite close to the EV of $75, although each gamble isworth nothing on its own.

Finally, we note that decisions about single gambleswill no longer appear risk-proportional when gamblesare evaluated in the context of a portfolio, even if theutility function has that property. Suppose the individ-ual now owns a set of eleven gambles:

one gamble with a 0.50 chance to win $1,000,ten gambles, each with a 0.50 chances to win $100.

The expected value of the set is $1,000. If the gambleswere considered one at a time, the sum of their cash

equivalents would be only $600. With proper aggre-gation, however, the selling price for the package shouldbe $934. Now suppose the decision maker considerstrading only one of the gambles. After selling a gamblefor an amount X, she retains a reduced compound gam-ble in which the constant X is added to each outcome.The decision maker, of course, will only sell if the valueof the new gamble is at least equal to the value of theoriginal portfolio. The computed selling price for thelarger gamble is $440, and the selling price for one ofthe smaller gambles is $49. Note that the premium givenup to avoid the risk is 12% of expected value for thelarge gamble, but only 2% for the small one. A rationaldecision maker who applies a proportionately risk averseutility function to aggregate outcomes will set cashequivalents closer to risk neutrality for small gamblesthan for large ones.

As these elementary examples illustrate, the commonattitude of strong (and proportional) aversion to riskand to losses entails a risk policy that quickly approachesneutrality as the portfolio is extended.^ Because possi-bilities of aggregation over future decisions always existfor an ongoing concern, and because the chances foraggregation are likely to be inversely correlated withthe size of the problem, the near-proportionality of riskattitudes for gambles of varying sizes is logically inco-herent, and the extreme risk aversion observed forprospects that are small relative to assets is unreason-able. To rationalize observed preferences one must as-sume that the decision maker approaches each choiceproblem as if it were her last—there seems to be norelevant tomorrow. It is somewhat surprising that thedebate on the rationality of risky decisions has focusedalmost exclusively on the curiosities of the Allais andEllsberg paradoxes, instead of on simpler observations.

' The conclusions of the present section do not critically depend onthe assumption of expected utility theory, that the decision makerweights outcomes by their probabilities. All the calculations reportedabove were repeated using cumulative prospect theory (Tversky andKahneman 1992) with plausible parameters (a = 0.73; b = c = 0.6and a loss aversion coefficient of 2.5). Because extreme outcomes areassigned greater weight in prospect theory than in the expected utilitymodel, the mitigation of risk aversion as the portfolio expands issomewhat slower. Additionally, the risk seeking that prospect theorypredicts for single low-probability positive gambles is replaced by riskaversion for repeated gambles.

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such as the extraordinary myopia implied by extremeand nearly proportional risk aversion.

Risk Taking in Organizations: Implications andSpeculationsThe preceding sections discussed evidence that people,when faced with explicitly probabilistic prospects in ex-perimental situations, tend to frame their decisionproblem narrowly, have near-proportional risk attitudes,and are as a consequence excessively risk averse in smalldecisions, where they ignore the effects of aggregation.Extending these ideas to business decisions is necessarilyspeculative, because the attitudes to risk that are implicitin such decisions are not easily measured. One way toapproach this problem is by asking whether the orga-nizational context in which many business decisions aremade is more likely to enhance or to inhibit risk aver-sion, narrow framing and near-proportionality. We ex-amine this question in the present section.

Risk Aversion. There is little reason to believe thatthe factors that produce risk aversion in the personalevaluation of explicit gambles are neutralized in thecontext of managerial decisions. For example, attemptsto measure the utility that executives attach to gainsand losses of their firm suggest that the principle ofdecreasing marginal values applies to these outcomes(MacCrimmon and Wehrung 1986, Swalm 1966). Theunderweighting of probable gains in comparisons withsure ones, known as the certainty effect, is also unlikelyto vanish in managerial decisions. The experimental ev-idence indicates that the certainty effect is not eliminatedwhen probabilities are vague or ambiguous, as they arein most real-life situations, and the effect may even beenhanced (Curley et al. 1986, Hogarth and Einhorn1990). We suspect that the effect may become evenstronger when a choice becomes a subject of debate, asis commonly the case in managerial decisions: the rhet-oric of prudent decision making favors the certainty ef-fect, because an argument that rests on mere probabilityis always open to doubt.

Perhaps the most important cause of risk aversion isloss aversion, the discrepancy between the weights thatare attached to losses and to gains in evaluating pros-pects. Loss aversion is not mitigated when decisions aremade in an organizational context. On the contrary, theasymmetry between credit and blame may enhance the

asymmetry between gains and losses in the decisionmaker's utilities. The evidence indicates that the pres-sures of accountability and personal responsibility in-crease the status quo bias and other manifestations ofloss aversion. Decision makers become more risk aversewhen they expect their choices to be reviewed by others(Tetlock and Boettger 1991) and they are extremely re-luctant to accept responsibility for even a small increasein the probability of a disaster (Viscusi et al. 1987).Swalm (1966) noted that managers appear to have anexcessive aversion to any outcome that could yield anet loss, citing the example of a manager in a firm de-scribed as "an industrial giant", who would decline topursue a project that has a 50-50 chance of either mak-ing for his company a gain of $300,000 or losing$60,000. Swalm hypothesized that the steep slopes ofutility functions in the domain of losses may be due tocontrol procedures that bias managers against choicesthat might lead to losses. This interpretation seems ap-propriate since "several respondents stated quite clearlythat they were aware that their choices were not in thebest interests of the company, but that they felt themto be in their own best interests as aspiring executives."

We conclude that the forces that produce risk aversionin experimental studies of individual choice may be evenstronger in the managerial context. Note, however, thatwe do not claim that an objective observer would de-scribe managerial decisions as generally risk averse. Thesecond part of this essay will argue that decisions areoften based on optimistic assessments of the chancesof success, and are therefore objectively riskier than thedecision makers perceive them to be. Our hypothesesabout risk in managerial decisions are: (i) in a generallyfavorable context, the threshold for accepting risk willbe high, and acceptable options will be subjectively per-ceived as carrying low risk, (ii) for problems viewed inisolation the willingness to take risks is likely to be ap-proximately constant for decisions that vary greatly insize, and (iii) decisions will be narrowly framed evenwhen they could be viewed as instances of a categoryof similar decisions. As a consequence, we predict (iv)an imbalance in the risks that the organization acceptsin large and in small problems, such that relative riskaversion is lower for the aggregate of small decisionsthan for the aggregate of large decisions. These hy-potheses are restricted to essentially favorable situations.

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which often yield risk aversion in laboratory studies.We specifically exclude situations in vv hich risk seekingis common, such as choices betv een essentially negativeoptions, or choices that involve small chances of largegain.

Narrow Framing. We have suggested that peopletend to make decisions one at a time, and in particularthat they are prone to neglect the relevance of futuredecision opportunities. For both individuals and orga-nizations, the adoption of a broader frame and of aconsistent risk policy depends on two conditions: (i) anability to group together problems that are superficiallydifferent; (ii) an appropriate procedure for evaluatingoutcomes and the quality of performance.

A consistent risk policy can only be maintained if therecurrent problems to which the policy applies are rec-ognized as such. This is sometimes easy: competent or-ganizations will identify obvious recurring questions—for example, whether or not to purchase insurance fora company vehicle—and will adopt policies for suchquestions. The task is more complex when each decisionproblem has many unique features, as might be thecase for acquisitions or new product development. Theexplicit adoption of a broad frame will then require theuse of an abstract language that highlights the importantcommon dimensions of diverse decision problems. For-mal decision analysis provides such a language, in whichoutcomes are expressed in money and uncertainty isquantified as probability. Other abstract languages couldbe used for the same purpose. As practitioners of de-cision analysis well know, however, the use of an ab-stract language conflicts with a natural tendency to de-scribe each problem in its own terms. Abstraction nec-essarily involves a loss of subtlety and specificity, andthe summary descriptions that permit projects to becompared almost always appear superficial and inad-equate.

From the point of the individual executive who facesa succession of decisions, the maintenance of a broaddecision frame also depends on how her performancewill be evaluated, and on the frequency of performancereviews. For a schematic illustration, assume that re-views occur at predictable points in the sequence ofdecisions and outcomes, and that the executive's out-comes are determined by the value of the firm's out-comes since the last review. Suppose the evaluation

function is identical to the utility function introducedin the preceding numerical examples: the credit forgaining 2.5 units and the blame for losing 1 unit justcancel out. With this utility function, a single gamblethat offers equal probabilities to win 2 units or to lose1 unit will not be acceptable if performance is evaluatedon that gamble by itself. The decision will not changeeven if the manager knows that there will be a secondopportunity to play the same gamble. However, if theevaluation of outcomes and the assignment of creditand blame can be deferred until the gamble has beenplayed twice, the probability that the review will benegative drops from 0.50 to 0.25 and the compoundgamble will be accepted. As this example illustrates,reducing the frequency of evaluations can mitigate theinhibiting effects of loss aversion on risk taking, as wellas other manifestations of myopic discounting.

The attitude that "you win a few and you lose a few"could be recommended as an antidote to narrow fram-ing, because it suggests that the outcomes of a set ofseparable decisions should be aggregated before eval-uation. However, the implied tolerance for "losing afew" may conflict with other managerial imperatives,including the setting of high standards and the mainte-nance of tight supervision. By the same token, of course,narrow framing and excessive risk aversion may be un-intended consequences of excessive insistence on mea-surable short-term successes. A plausible hypothesis isthat the adoption of a broad frame of evaluation is mostnatural when the expected rate of success is low foreach attempt, as in drilling for oil or in pharmaceuticaldevelopment.* The procedures of performance evalu-ation that have evolved in these industries could providea useful model for other attempts to maintain consistentrisk policies.

Near Proportionality of Risk Attitudes. Many ex-ecutives in a hierarchical organization have two distinctdecision tasks: they make risky choices on behalf of theorganization, and they supervise several subordinateswho also make decisions. For analytical purposes, theoptions chosen by subordinates can be treated as in-dependent (or imperfectly correlated) gambles, whichusually involve smaller stakes than the decisions madepersonally by the superior. A problem of risk aggre-

' We owe this hypothesis to Richard Thaler.

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gation inevitably arises, and we conjecture that solvingit efficiently may be quite difficult.

To begin, ignore the supervisory function and assumethat all decisions are made independently, with narrowframing. If all decision makers apply the same nearly-proportional risk attitudes (as suggested by Swalm1966), an unbalanced set of choices will be made: Theaggregate of the subordinates' decisions will be morerisk averse than the supervisor's own decisions on largerproblems—which in turn are more risk averse than herglobal utility for the portfolio, rationally evaluated. Aswe saw in an earlier section, the costs of such inconsis-tencies in risk attitudes can be quite high.

Clearly, one of the goals of the executive should beto avoid the potential inefficiency, by applying a con-sistent policy to risky choices and to those she super-vises—and the consistent policy is not one of propor-tional risk aversion. As was seen earlier, a rational ex-ecutive who considers a portfolio consisting of one largegamble (which she chose herself) and ten smaller gam-bles (presumably chosen by subordinates) should beconsiderably more risk averse in valuing the large gam-ble than in valuing any one of the smaller gambles. Thecounter-intuitive implication of this analysis is that, ina generally favorable context, an executive should en-courage subordinates to adopt a higher level of risk-acceptance than the level with which she feels com-fortable. This is necessary to overcome the costly effectsof the (probable) insensitivity of her intuitive prefer-ences to recurrence and aggregation. We suspect thatmany executives will resist this recommendation, whichcontradicts the common belief that accepting risks isboth the duty and the prerogative of higher manage-ment.

For several reasons, narrow framing and near-pro-portionality could be difficult to avoid in a hierarchicalorganization. First, many decisions are both unique andlarge at the level at which they are initially made. Theusual aversion to risk is likely to prevail in such deci-sions, even if from the point of view of the firm theycould be categorized as recurrent and moderately small.Second, it appears unfair for a supervisor to urge ac-ceptance of a risk that a subordinate is inclined to re-ject—especially because the consequences of failure arelikely to be more severe for the subordinate.

In summary, we have drawn on three psychological

principles to derive the prediction that the risk attitudesthat govern decisions of different sizes may not be co-herent. The analysis suggests that there may be toomuch aversion to risk in problems of small or moderatesize. However, the conclusion that greater risk takingshould be encouraged could be premature at this point,because of the suspicion that agents' view of prospectsmay be systematically biased in an optimistic direction.The combination of a risk-neutral attitude and an op-timistic bias could be worse than the combination ofunreasonable risk aversion and unjustified optimism.As the next sections show, there is good reason to be-lieve that such a dilemma indeed exists.

Bold ForecastsOur review of research on individual risk attitudes sug-gests that the substantial degree of risk to which indi-viduals and organizations willingly expose themselvesis unlikely to reflect true acceptance of these risks. Thealternative is that people and organizations often exposethemselves to risk because they misjudge the odds. Wenext consider some of the mechanisms that produce the'bold forecasts' that enable cautious decision makers totake large risks.

Inside and Outside ViewsWe introduce this discussion by a true story, which il-lustrates an important cognitive quirk that tends to pro-duce extreme optinusm in planning.

In 1976 one of us (Daniel Kahneman) was involved in aproject designed to develop a curriculum for the study of judg-ment and decision making under uncertainty for high schoolsin Israel. The project was conducted by a small team of aca-demics and teachers. When the team had been in operationfor about a year, with some significant achievements alreadyto its credit, the discussion at one of the team meetings turnedto the question of how long the project would take. To makethe debate more useful, I asked everyone to indicate on a slipof paper their best estimate of the number of months thatwould be needed to bring the project to a well-defined stageof completion: a complete draft ready for submission to theMinistry of Education. The estimates, including my own, rangedfrom 18 to 30 months. At this point I had the idea of turningto one of our members, a distinguished expert in curriculumdevelopment, asking him a question phrased about as follows:"We are surely not the only team to have tried to develop acurriculum where none existed before. Please try to recall asmany such cases as you can. Think of them as they were in a



stage comparable to ours at present. How long did it take them,from that point, to complete their projects?" After a long silence,something much like the following answer was given, withobvious signs of discomfort: "First, I should say that not allteams that I can think of in a comparable stage ever did com-plete their task. About 40% of them eventually gave up. Ofthe remaining, I cannot think of any that was completed inless than seven years, nor of any that took more than ten". Inresponse to a further question, he answered: "No, I cannotthink of any relevant factor that distinguishes us favorablyfrom the teams I have been thinking about. Indeed, myimpression is that we are slightly below average in terms ofour resources and potential".

This Story illustrates several of the themes that willbe developed ir\ this section.

Two distinct modes of forecasting were applied to thesame problem in this incident. The inside view of theproblem is the one that all participants in the meetingspontaneously adopted. An inside view forecast is gen-erated by focusing on the case at hand, by consideringthe plan and the obstacles to its completion, by con-structing scenarios of future progress, and by extrapo-lating current trends. The outside view is the one thatthe curriculum expert was encouraged to adopt. It es-sentially ignores the details of the case at hand, andinvolves no attempt at detailed forecasting of the futurehistory of the project. Instead, it focuses on the statisticsof a class of cases chosen to be similar in relevant re-spects to the present one. The case at hand is also com-pared to other members of the class, in an attempt toassess its position in the distribution of outcomes forthe class (Kahneman and Tversky 1979b). The distinc-tion between inside and outside views in forecasting isclosely related to the distinction drawn earlier betweennarrow and broad framing of decision problems. Thecritical question in both contexts is whether a particularproblem of forecast or decision is treated as unique, oras an instance of an ensemble of similar problems.

The application of the outside view was particularlysimple in this example, because the relevant class forthe problem was easy to find and to define. Other casesare more ambiguous. What class should be considered,for example, when a firm considers the probable costsof an investment in a new technology in an unfamiliardomain? Is it the class of ventures in new technologiesin the recent history of this firm, or the class of devel-opments most similar to the proposed one, carried out

in other firms? Neither is perfect, and the recommen-dation would be to try both (Kahneman and Tversky1979b). It may also be necessary to choose units ofmeasurement that permit comparisons. The ratio of ac-tual spending to planned expenditure is an example ofa convenient unit that permits meaningful comparisonsacross diverse projects.

The inside and outside views draw on differentsources of information, and apply different rules to itsuse. An inside view forecast draws on knowledge ofthe specifics of the case, the details of the plan thatexists, some ideas about likely obstacles and how theymight be overcome. In an extreme form, the inside viewinvolves an attempt to sketch a representative scenariothat captures the essential elements of the history ofthe future. In contrast, the outside view is essentiallystatistical and comparative, and involves no attempt todivine future history at any level of detail.

It should be obvious that when both methods areapplied with equal intelligence and skill, the outsideview is much more likely to yield a realistic estimate.In general, the future of a long and complex undertakingis simply not foreseeable in detail. The ensemble ofpossible future histories cannot be defined. Even if thiscould be done, the ensemble would in most cases behuge, and the probability of any particular scenarionegligible.^ Although some scenarios are more likely orplausible than others, it is a serious error to assume thatthe outcomes of the most likely scenarios are also themost likely, and that outcomes for which no plausiblescenarios come to mind are impossible. In particular,the scenario of flawless execution of the current planmay be much more probable a priori than any scenariofor a specific sequence of events that would cause theproject to take four times longer than planned. Nev-ertheless, the less favorable outcome could be morelikely overall, because there are so many different waysfor things to go wrong. The main advantage of the out-side approach to forecasting is that it avoids the snaresof scenario thinking (Dawes 1988). The outside viewprovides some protection against forecasts that are not

' For the purposes of this exposition we assume that probabilities existas a fact about the world. Readers who find this position shockingshould transpose the formulation to a more complex one, accordingto their philosophical taste.



even in the ballpark of reasonable possibilities. It is aconservative approach, which will fail to predict extremeand exceptional events, but will do well with commonones. Furthermore, giving up the attempt to predict ex-traordinary events is not a great sacrifice when uncer-tainty is high, because the only way to score 'hits' onsuch events is to predict large numbers of other extraor-dinary events that do not materialize.

This discussion of the statistical merits of the outsideview sets the stage for our main observation, which ispsychological: the inside view is overwhelmingly pre-ferred in intuitive forecasting. The natural way to thinkabout a problem is to bring to bear all one knows aboutit, with special attention to its unique features. The in-tellectual detour into the statistics of related cases isseldom chosen spontaneously. Indeed, the relevance ofthe outside view is sometimes explicitly denied: phy-sicians and lawyers often argue against the applicationof statistical reasoning to particular cases. In these in-stances, the preference for the inside view almost bearsa moral character. The inside view is valued as a seriousattempt to come to grips wdth the complexities of theunique case at hand, and the outside view is rejectedfor relying on crude analogy from superficially similarinstances. This attitude can be costly in the coin of pre-dictive accuracy.

Three other features of the curriculum story shouldbe mentioned. First, the example illustrates the generalrule that consensus on a forecast is not necessarily anindication of its validity: a shared deficiency of reasoningwill also yield consensus. Second, we note that the initialintuitive assessment of our curriculum expert was similarto that of other members of the team. This illustrates amore general observation: statistical knowledge that isknown to the forecaster will not necessarily be used, orindeed retrieved, when a forecast is made by the insideapproach. The literature on the impact of the base ratesof outcomes on intuitive predictions supports this con-clusion. Many studies have dealt with the task of pre-dicting the profession or the training of an individualon the basis of some personal information and relevantstatistical knowledge. For example, most people havesome knowledge of the relative sizes of different de-partments, and could use that knowledge in guessingthe field of a student seen at a graduating ceremony.The experimental evidence indicates that base-rate in-

formation that is explicitly mentioned in the problemhas some effect on predictions, though usually not asmuch as it should have (Griffin and Tversky 1992,Lynch and Ofir 1989: for an alternative view see Gig-erenzer et al. 1988). When only personal informationis explicitly offered, relevant statistical information thatis known to the respondent is largely ignored (Kahne-man and Tversky 1973, Tversky and Kahneman 1983).

The sequel to the story illustrates a third general ob-servation: facing the facts can be intolerably demoral-izing. The participants in the meeting had professionalexpertise in the logic of forecasting, and none even ven-tured to question the relevance of the forecast impliedby our expert's statistics: an even chance of failure, anda completion time of seven to ten years in case of suc-cess. Neither of these outcomes was an acceptable basisfor continuing the project, but no one was willing todraw the embarrassing conclusion that it should bescrapped. So, the forecast was quietly dropped fromactive debate, along with any pretense of long-termplanning, and the project went on along its predictablyunforeseeable path to eventual completion some eightyears later.

The contrast between the inside and outside viewshas been confirmed in systematic research. One relevantset of studies was concerned with the phenomenon ofoverconfidence. There is massive evidence for the con-clusion that people are generally overconfident in theirassignments of probability to their beliefs. Overconfi-dence is measured by recording the proportion of casesin which statements to which an individual assigned aprobability p were actually true. In many studies thisproportion has been found to be far lower than p (seeLichtenstein et al. 1982; for a more recent discussionand some instructive exceptions see Griffin and Tversky1992). Overconfidence is often assessed by presentinggeneral information questions in a multiple-choice for-mat, where the participant chooses the most likely an-swer and assigns a probability to it. A typical result isthat respondents are only correct on about 80% of caseswhen they describe themselves as "99% sure." Peopleare overconfident in evaluating the accuracy of theirbeliefs one at a time. It is interesting, however, thatthere is no evidence of overconfidence bias when re-spondents are asked after the session to estimate thenumber of questions for which they picked the correct



answer. These global estimates are accurate, or some-what pessimistic (Gigerenzer et al. 1991, Griffin andTversky 1992). It is evident that people's assessmentsof their overall accuracy does not control their confi-dence in particular beliefs. Academics are familiar witha related example: finishing our papers almost alwaystakes us longer than we expected. We all know this andoften say so. Why then do we continue to make thesame error? Here again, the outside view does not in-form judgments of particular cases.

In a compelling example of the contrast between in-side and outside views. Cooper et al. (1988) interviewednew entrepreneurs about their chances of success, andalso elicited from them estimates of the base rate ofsuccess for enterprises of the same kind. Self-assessedchances of success were uncorrelated to objective pre-dictors of success such as college education, prior su-pervisory experience and initial capital. They were alsowildly off the mark on average. Over 80% of entrepre-neurs perceived their chances of success as 70% or bet-ter. Fully one-third of them described their success ascertain. On the other hand, the mean chance of successthat these entrepreneurs attributed to a business liketheirs was 59%. Even this estimate is optimistic, thoughit is closer to the truth: the five-year survival rate fornew firms is around 33% (Dun and Bradstreet 1967).

The inside view does not invariably yield optimisticforecasts. Many parents of rebellious teenagers cannotimagine how their offspring would ever become a rea-sonable adult, and are consequently more worried thanthey should be, since they also know that almost allteenagers do eventually grow up. The general point isthat the inside view is susceptible to the fallacies ofscenario thinking and to anchoring of estimates onpresent values or on extrapolations of current trends.The inside view burdens the worried parents with sta-tistically unjustified premonitions of doom. To decisionmakers with a goal and a plan, the same way of thinkingoffers absurdly optimistic forecasts.

The cognitive mechanism we have discussed is notthe only source of optimistic errors. Unrealistic optimismalso has deep motivational roots (Tiger 1979). A recentliterature review (Taylor and Brown 1988) listed threemain forms of a pervasive optimistic bias: (i) unreal-istically positive self-evaluations, (ii) unrealistic opti-mism about future events and plans, and (iii) an illusion

of control. Thus, for almost every positive trait—in-cluding safe driving, a sense of humor, and managerialrisk taking (MacCrimmon and Wehrung 1986)—thereis a large majority of individuals who believe themselvesto be above the median. People also exaggerate theircontrol over events, and the importance of the skillsand resources they possess in ensuring desirable out-comes. Most of us underestimate the likelihood of haz-ards affecting us personally, and entertain the unlikelybelief that Taylor and Brown summarize as "The futurewill be great, especially for me."

Organizational OptimismThere is no reason to believe that entrepreneurs andexecutives are immune to optimistic bias. The prevalenceof delusions of control among managers has been rec-ognized by many authors (among others, Duhaime andSchwenk 1985, March and Shapira 1987, Salancik andMeindl 1984). As we noted earlier, managers commonlyview risk as a challenge to be overcome, and believethat risk can be modified by "managerial wisdom andskill" (Donaldson and Lorsch 1983). The common re-fusal of managers to refuse risk estimates provided tothem as "given" (Shapira 1986) is a clear illustrationof illusion of control.

Do organizations provide effective controls againstthe optimistic bias of individual executives? Are orga-nizational decisions founded on impartial and unbiasedforecasts of consequences? In answering these questions,we must again distinguish problems that are treated asrecurrent, such as forecasts of the sales of existing prod-uct lines, from others that are considered unique. Wehave no reason to doubt the ability of organizations toimpose forecasting discipline and to reduce or eliminateobvious biases in recurrent problems. As in the case ofrisk, however, all significant forecasting problems havefeatures that make them appear unique. It is in theseunique problems that biases of judgment and choice aremost likely to have their effects, for organizations aswell as for individuals. We next discuss some likelycauses of optimistic bias in organizational judgments,some observations of this bias, and the costs and benefitsof unrealistic optimism.

Causes. Forecasts often develop as part of a casethat is made by an individual or group that already has,or is developing a vested interest in the plan, in a context



of competition for the control of organizational re-sources. The debate is often adversarial. The only proj-ects that have a good chance of surviving in this com-petition are those for which highly favorable outcomesare forecast, and this produces a powerful incentive forwould-be promoters to present optimistic numbers. Thestatistical logic that produces the winner's curse in othercontexts (Capen, Clapp and Campbell 1971; Bazermanand Samuelson 1983; Kagel and Levin 1986) applieshere as well: the winning project is more likely thanothers to be associated with optimistic errors (Harrisonand March 1984). This is an effect of regression to themean. Thus, the student who did best in an initial testis also the one for whom the most regression is expectedon a subsequent test. Similarly, the projects that areforecast to have the highest returns are the ones mostlikely to fall short of expectations.

Officially adopted forecasts are also likely to be biasedby their secondary functions as demands, commandsand commitments (Lowe and Shaw 1968, Lawler andRhode 1976, Lawler 1986, Larkey and Smith 1984). Aforecast readily becomes a target, which induces lossaversion for performance that does not match expec-tations, and can also induce satisficing indolence whenthe target is exceeded. The obvious advantages of settinghigh goals is an incentive for higher management toadopt and disseminate optimistic assessments of futureaccomplishments—and possibly to deceive themselvesin the process.

In his analysis of "groupthink," Janis (1982) identifiedother factors that favor organizational optimism. Pes-simism about what the organization can do is readilyinterpreted as disloyalty, and consistent bearers of badnews tend to be shunned. Bad news can be demoral-izing. When pessimistic opinions are suppressed in thismanner, exchanges of views will fail to perform a criticalfunction. The optimistic biases of individual groupmembers can become mutually reinforcing, as unreal-istic views are validated by group approval.

The conclusion of this sketchy analysis is that thereis little reason to believe organizations will avoid theoptimistic bias—except perhaps when the problems areconsidered recurrent and subjected to statistical qualitycontrol. On the contrary, there are reasons to suspectthat many significant decisions made in organizationsare guided by unrealistic forecasts of their consequences.

Observations. The optimistic bias of capital in-vestment projects is a familiar fact of life: the typicalproject finishes late, comes in over budget when it isfinally completed, and fails to achieve its initial goals.Grossly optimistic errors appear to be especially likelyif the project involves new technology or otherwiseplaces the firm in unfamiliar territory. A Rand Corpo-ration study on pioneer process plants in the energyfield demonstrates the magnitude of the problem (Mer-row et al. 1981). Almost all project construction costsexceeded initial estimates by over 20%. The norm wasfor actual construction costs to more than double firstestimates. These conclusions are corroborated by PIMSdata on start-up ventures in a wide range of industries(cited by Davis 1985). More than 80% of the projectsstudied fell short of planned market share.

In an interesting discussion of the causes of failurein capital investment projects, Arnold (1986) states:

Most companies support large capital expenditure programswith a worst case analysis that examines the projects' loss po-tential. But the worst case forecast is almost always too opti-mistic. . . . When managers look at the downside they gen-erally describe a mildly pessimistic future rather than the worstpossible future.

As an antidote against rosy predictions Arnold rec-ommends staying power analysis, a method used bylenders to determine if organizations under severe straincan make payments. In effect, the advice is for managersto adopt an outside view of their own problem.

Mergers and acquisitions provide another illustrationof optimism and of illusions of control. On average,bidding firms do not make a significantly positive return.This striking observation raises the question of why somany takeovers and mergers are initiated. Roll (1986)offers a "hubris hypothesis" to explain why decisionmakers acquiring firms tend to pay too much for theirtargets. Roll cites optimistic estimates of "economies dueto synergy and (any) assessments of weak manage-ment" as the primary causes of managerial hubris. Thebidding firms are prone to overestimate the control theywill have over the merged organization, and to under-estimate the "weak" managers who are currently incharge.

Costs and Benefits. Optimism and the illusion ofcontrol increase risk taking in several ways. In a dis-cussion of the Challenger disaster. Landau and Chis-

28 MANAGEMENT SCIENCE/VOI. 39, No. 1, January 1993


holm (1990) introduced a "law of increasing optimism"as a form of Russian roulette. Drav ing on the samecase, Starbuck and Milliken (1988) noted how quicklyvigilance dissipates with repeated successes. Optimismin a competitive context may take the form of contemptfor the capabilities of opponents (Roll 1986). In a bar-gaining situation, it will support a hard line that raisesthe risk of conflict. Neale and Bazerman (1983) ob-served a related effect in a final-offer arbitration setup,where the arbiter is constrained to choose between thefinal offers made by the contestants. The participantswere asked to state their subjective probability that thefinal offer they presented would be preferred by thearbiter. The average of these probabilities was approx-imately 0.70; with a less sanguine view of the strengthof their case the contestants would surely have mademore concessions. In the context of capital investmentdecisions, optimism and the illusion of control manifestthemselves in unrealistic forecasts and unrealizableplans (Arnold 1986).

Given the high cost of mistakes, it might appear ob-vious that a rational organization should want to baseits decisions on unbiased odds, rather than on predic-tions painted in shades of rose. However, realism hasits costs. In their review of the consequences of optimismand pessimism, Taylor and Brown (1988) reached thedeeply disturbing conclusion that optimistic self-delu-sion is both a diagnostic indication of mental health andwell-being, and a positive causal factor that contributesto successful coping with the challenges of life. Thebenefits of unrealistic optimism in increasing persistencein the face of difficulty have been documented by otherinvestigators (Seligman 1991).

The observation that realism can be pathological andself-defeating raises troubling questions for the man-agement of information and risk in organizations.Surely, no one would want to be governed entirely bywishful fantasies, but is there a point at which truthbecomes destructive and doubt self-fulfilling? Shouldexecutives allow or even encourage unrealistic optimismamong their subordinates? Should they willingly allowthemselves to be caught up in productive enthusiasm,and to ignore discouraging portents? Should there besomeone in the organization whose function it is toachieve forecasts free of optimistic bias, although suchforecasts, if disseminated, would be demoralizing?

Should the orgaruzation maintain two sets of forecastingbooks (as some do, see Bromiley 1986)? Some authorsin the field of strategy have questioned the value ofrealism, at least implicitly. Weick's famous story of thelost platoon that finds its way in the Alps by consultinga map of the Pyrenees indicates more respect for con-fidence and morale than for realistic appraisal. On theother hand. Landau and Chisholm (1990) pour with-ering scorn on the "arrogance of optimism" in organi-zations, and recommend a pessimistic failure-avoidingmanagement strategy to control risk. Before furtherprogress can be made on this difficult issue, it is im-portant to recognize the existence of a genuine dilemmathat will not yield to any simple rule

Concluding RemarksOur analysis has suggested that many failures originatein the highly optimistic judgments of risks and oppor-tunities that we label bold forecasts. In the words ofMarch and Shapira (1987), "managers accept risks, inpart, because they do not expect that they will have tobear them." March and Shapira emphasized the role ofillusions of control in this bias. We have focused onanother mechanism—the adoption of an inside view ofproblems, which leads to anchoring on plans and onthe most available scenarios. We suggest that errors ofintuitive prediction can sometimes be reduced byadopting an outside view, which forecasts the outcomewithout attempting to forecast its history (Kahnemanand Tversky 1979b). This analysis identifies the strongintuitive preference for the inside view as a source ofdifficulties that are both grave and avoidable.

On the issue of risk we presented evidence that de-cision makers tend to deal with choices one at a time,and that their attitudes to risk exhibit risk-aversion andnear-proportionality. The reluctance to take explicit re-sponsibility for possible losses is powerful, and can bevery costly in the aggregate (for a discussion of its socialcosts see Wildavsky 1988). We claimed further thatwhen the stakes are small or moderate relative to assetsthe aversion to risk is incoherent and substantively un-justified. Here again, the preference for treating decisionproblems as unique causes errors that could be avoidedby a broader view.

Our analysis implies that the adoption of an outsideview, in which the problem at hand is treated as an

MANAGEMENT SCIENCE/VO1. 39, No. 1, January 1993 29


instance of a broader category, will generally reduce theoptimistic bias and may facilitate the application of aconsistent risk policy. This happens as a matter of coursein problems of forecasting or decision that the organi-zation recognizes as obviously recurrent or repetitive.However, we have suggested that people are stronglybiased in favor of the inside view, and that they willnormally treat significant decision problems as uniqueeven when information that could support an outsideview is available. The adoption of an outside view insuch cases violates strong intuitions about the relevanceof information. Indeed, the deliberate neglect of thefeatures that make the current problem unique can ap-pear irresponsible. A deliberate effort will therefore berequired to foster the optimal use of outside and insideviews in forecasting, and the maintenance of globallyconsistent risk attitudes in distributed decision systems.

Bold forecasts and timid attitudes to risk tend to haveopposite effects. It would be fortunate if they canceledout precisely to yield optimal behavior in every situation,but there is little reason to expect such a perfect outcome.The conjunction of biases is less disastrous than eitherone would have been on its own, but there ought to bea better way to control choice under risk than pittingtwo mistakes against each other. The prescriptive im-plications of the relation between the biases in forecastand in risk taking is that corrective attempts should dealwith these biases simultaneously. Increasing risk takingcould easily go too far in the presence of optimistic fore-casts, and a successful effort to improve the realism ofassessments could do more harm than good in an or-ganization that relies on unfounded optimism to wardoff paralysis.*

' An earlier version of this paper was presented at a conference onFundamental Issues in Strategy, held at Silverado, CA, in November1990. The preparation of this article was supported by the Center forManagement Research at the University of California, Berkeley, bythe Russell Sage Foundation, and by grants from the Sloan Foundationand from AFOSR, under grant number 88-0206. The ideas presentedhere developed over years of collaboration with Amos Tversky, buthe should not be held responsible for our errors. We thank PhilipBromiley, Colin Camerer, George Loewenstein, Richard Thaler, andAmos Tversky for their many helpful comments.

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Accepted by Gregory W. Fischer; received April 3, 1991. This paper has been with the authors three months for one revision.


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