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FACULTY WORKING
PAPER NO. 863

Cognitive Bias in Strategic Decision-Making:
Some Conjectures

Charles R. Schwenk

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FACULTY WORKING PAPER NO. 863
College of Commerce and Business Administration
University of Illinois at Urbana-Champaign
April 1982

Cognitive Bias in Strategic
Decision-Making: Some Conjectures

Charles R. Schwenk, Assistant Professor
Department of Business Administration

ABSTRACT

Strategic decision-making can be viewed as a special kind of decision-
making under uncertainty. Researchers in a variety of fields have
identified a number of cognitive or perceptual mechanisms by which
decision makers distort information from the environment to make it
appear simpler and reduce the apparent uncertainty in a decision-making
task. Within this paper, a four-stage model of strategic decision-making
is developed and the possible effects of cognitive biases at each stage
are discussed. Finally, techniques for introducing conflict into strategy
formulation are proposed as ways of counteracting the effects of these
biases.

COGNITIVE BIAS IN STRATEGIC
DECISION- MAKING: SOME CONJECTUKES

Strategic decision-making has been defined as a special kind of ill-
structured problem-solving process and as a special type of decision-
making under uncertainty (Hofer & Schendel, 1978:46). Because of the
importance of strategic decision-making, much effort has been devoted
to developing procedures for improving the effectiveness of the process
by increasing the amount of data considered and the thoroughness with
which it is evaluated (Grant & King, 1979:104-122).

A number of recent articles in the strategic management field have
developed and validated descriptive models of the strategic decision-
making process (Mintzberg, Raisinghanl, & Theoret 1976; Glueck 1976;
Mazzolini, 1981; Hofer & Schendel, 1978). These models involve various
numbers of stages and are generally similar to earlier models of the
organizational decision-making process (Lang, Dittrich, & White, 1978).
The decisional activities at each stage have been examined experimentally
by cognitive psychologists and behavioral decision theorists and numerous
biases have been identified which limit decisional effectiveness. An
understanding of these biases is necessary for the design of effective
strategic decision-making aids.

Theorists in the field of Strategic Management have pointed out
that human cognitive limitations might affect strategic decision-making
(Steiner & Miner, 1977:226-231; Mintzberg, 1973:45-46), basing their
arguments on Simon's notions of "bounded rationality" and "satisficing. "
They have pointed out that strategic decision-makers are subject to
bounded rationality and do not optimize in their decisions but have not

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discussed the specific effects of bounded rationality on decision- makers'
perceptions or the specific decisional behaviors adopted in preference
to optimizing. However, some researchers have discussed the effects of
specific cognitive biases on general managerial decision-making (Taylor,
1975; Hogarth, 19 80) and on the use of forecasts (Hogarth & Makridakis,
1981).

This paper develops conjectures about possible biases in strategic
decision-making by drawing on literature in the fields of cognitive
psychology and behavioral decision theory dealing with problem formu-
lation and decision- making under uncertainty. These biases allow for
some specific predictions about the types of errors to which decision
makers will be subject in various activities or phrases of strategic
decision-making. Such information could be helpful to researchers in
attempting to explain decisionad failures and to practitioners inter-
ested in reducing the effects of these biases through the use of deci-
sion aids. This paper does not, of course, represent an exhaustive
review of the literature in these fields. Rather, attention is focused
on some of the more widely discussed cognitive biases.

Research on these biases has dealt with them individually and has
not focused on the interaction between then. For this reason, and the
fact that most of the research was conducted in laboratory settings
using relatively simple judgement and decision tasks, statements about
the effects of these biases on strategic decision-making must remain
speculative.

In this paper, a general model of the strategic decision-making
process will be synthesized from existing models. Cognitive biases

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which may operate at each stage of the process will then be discussed.
Finally, suggestions for future research on cognitive biases and for
improving strategic decisions will be offered.

A DESCRIPTIVE MODEL OF THE STRATEGIC DECISION- MAKING PROCESS
The strategic management literature contains a number of strategic
decision- making models. Since cognitive biases will be discussed in
terms of their effects on various processes in strategy formulation,
it is necessary to generate a model which represents the essential
features of the most prominent models in the field. Hofer & Schendel
(1978, p. 47) have developed a model which builds on the major ana-
lytical models of Andrews (1965, 1980), Ansoff (1965), and others.
It includes the seven steps of strategy identification, environmental
analysis, resource analysis, gap analysis (problem identification),
generation of strategic alternatives, strategy evaluation, and stra-
tegic choice.

The fact that such processes actually occur in organizational
decision-making has been confirmed by Mintzberg, Raisinghani, &
Theoret (1977). Several of the stages dealt with in Hofer & Schendel's
model are also covered by Mintzberg, et al. However, their model
begins with the identification and diagnosis of a problem. This is
followed by the search for alternatives and information related to the
alternatives. This stage, in turn, is followed by the evaluation and
selection of an alternative. This is an iterative model involving
numerous feedback loops which allow decisional activity to cycle
from later to earlier stages as the strategic problem definition is
progressively refined.

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It may be that the two rcdels actually describe two different but
equally legitimate types of strategic decision-making. Leotiades
(1979:96-102) distinguished between strategy formulation which is part
of a regular strategic planning cycle and strategy formulation which
occurs in response to a particular problem (for example, a need to
make a particular acquisition decision). Ihe former begins with at-
tempts to systematically collect information about the environment and
the company's resources and is best described by Hofer & Schendel's
model. The latter, which begins in response to a particular problem,
is probably best described by Mintzberg's model.

Glueck (1976) proposed a model which included the stages of Appraisal
(including an analysis of environmental opportunities and threats and
company resources). Choice (generation and consideration of alternative
strategies and choice among the alternatives), Implementation, and
Evaluation. Finally, Mazzolini (1981) developed a nodel involving five
major activities based on his own research and literature review. The
five activities included Decision-need identification. Search for
alternatives for action. Investigation of courses of action. Review and
approval, and Implementation.

These models are built on earlier and more general decision-making

models and are consistent with at least the first three stages of

Simon's four-stage description of the management decision-making

process (1960:40-44).

Decision making comprises four principal phases:
finding occasions for making a decision, finding pos-
sible courses of action, choosing among courses of
action, and evaluating past choices.

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The first phase of the decision-niaking process —
searching the environment for conditions calling for
decision — I shall call intelligence activity (bor-
rowing the military ireaning of intelligence). The
second phase — inventing, developing, and analyzing
possible courses of action — I shall call design
activity. The third phase — selecting a particular
course of action from those available — I shall call
choice activity. The fourth phase, assessing past
choices, I shall call re\dew activity.

(Simon, 1960:40-41)

As a basis for the discussion of simplification mechanisms, a
simplified four-stage model of the strategy formulation process has
been developed based on earlier models. The four stages in the present
model are strategic problem identification, strategic alternatives
generation, evaluation and selection, and strategy implementation.
There seems to be a good deal of agreement among researchers in this
field (represented by those whose model we discussed) that at_ least
these basic activities characterize strategic decision-making. How-
ever, this model is not intended to represent the full complexity of
strategic decision-making.

Any model which is representative of the more popular models in
the field would have to include the notion of feedback loops. Thus
in this derived model, decisional activity may cycle from later to
earlier stages as in the Mintzberg et al. model.

Problem identification includes attempts to identify the com-
pany's current implicit and explicit goals, objectives, and strategies
as well as an assessment of the significant opportunities and threats
in the environment, and the company's current resources. Assessment
of opportunities and threats in the environment is a preliminary stage
to gap analysis and often requires forecasting. Problem identification

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also includes a recognition that a problem exists. This presumably
takes the form of a gap between current or projected future perfor-
mance and the explicit and implicit goals and objectives of manage-
ment. The problem is then defined and clarified as causes of the
gap are identified. Alternatives generation involves the identifica-
tion of gap-dosing options and their development to a state of re-
finement in which they can be evaluated against each other. The
evaluation and selection stage involves the screening and evaluation
of alternatives and the selection of the alternative which best solves
the problem defined in the preceding stage. Finally, the implementation
stage involves carrying out the strategy chosen. This model, along
with the Mintzberg et al., Glueck, Hofer & Schendel, and Mazzolini
models, is presented in Table 1.

Insert Table 1 about here

Obviously, all of these stages do not occur in all decisions in
exactly this sequence. In fact, Witte (1972:179) found from examining
233 organizational decision processes that the activities related to
the "stages" of gathering information, developing alternatives, eval-
uating alternatives , and making choices were carried out in approximately
the same proportion to each other throughout the decision process. The
phase theorem (i.e., the theorem that decision-making occurs in dis-
tinct phases or stages) postulates that activities associated with
gathering information should predominate early in a decision process
and that activities related to choice should dominate toward the end
of the decision process. In contrast, Witte found that there was a

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relatively high level of the activities associated with all four
"stages" at the beginning of the decision process, a lull toward the
middle of the process, and a very high level of activity toward the
end of the process. Witte concluded "we believe that human beings
cannot gather information without in some way simultaneously devel-
oping alternatives. They cannot avoid evaluating these alternatives
immediately, and in doing this they are forced to a decision" (Witte,
1972:180).

Therefore, the four activities in the derived model may be seen
simply as decisional processes which may or may not occur as stages.
It may be that the structured process which often characterizes cyclical,
formal strategic planning makes it more likely that the phases will be
executed in this order while in strategy formulation guided by a par-
ticular problem, the activities are less likely to be executed sequen-
tially. Normative work in strategic management suggests that problem
identification should be based on detailed data which reveals gaps be-
tween performance and expectations, numerous strategic alternatives
should be generated, and these should be thoroughly and objectively
evaluated prior to choice (Hofer & Schendel, 1978). However, the
complexity and uncertainty involved in strategic decision-making makes
it unlikely that these normative prescriptions will be carried out.

The next section of the paper will discuss cognitive biases which
may operate to reduce the apparent complexity and uncertainty in a
decision situation and may simultaneously reduce the quality of the
strategic decision.

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COGNITIVE BIASES IN STRATEGIC DECISION-MAKING
Research in cognitive psychology and behavioral decision theory
has identified numerous cognitive biases which may operate in strategic
decision-making. These biases may not operate in all strategic deci-
sions. However, their effect may help to explain failure in strategic
decision-making.

In the next section, the biases identified in cognitive psychology
and behavioral decision theory research have been classified according
to strategic decision-making stage they seem roost likely to affect.

Table 2 represents the stages of the strategy formulation process
and the cognitive biases which may operate at the first three stages.
The biases which operate at each stage will be discussed, as well as
their probable effects on each stage.

Insert Table 2 about here

Some biases nay operate to reduce decisional effectiveness at more
than one of the stages.

Problem Identification

In the strategic decision-making models previously discussed, the
major purpose of information gathering in the beginning of the process
is to identify gaps between objectives and performance. However, such
gaps may indicate either random fluctuations or changes requiring revi-
sions in strategy. Decision-makers* expectations may determine how
such gaps are interpreted or even whether information on such gaps will
be accepted and used. The following have been identified as cognitive
biases which may affect problem identification: prior hypothesis bias.

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adjustment and anchoring, escalating conmitinent, the illusion of con-
trol, reasoning by analogy, salience, and misguided parsimony (see
Table 2).

Prior Hypothesis Bids

Researchers have identified a number of biases which lead decision-
makers to ignore or misinterpret information. Levine (1971), Pruitt
(1961) and Kason (1960) showed that individuals who formed erroneous
beliefs or hypotheses about the relationship between variables tended
to make decisions on the basis of these beliefs despite abundant evi-
dence over numerous trials that they were wrong. Further, they sought
and used information consistent with these hypotheses rather than dis-
confirming information. Jervis (1976:143-181) has also provided num-
erous examples from international relations of peoples' tendency to
accept information which conforms to existing expectations and beliefs.
Under the effects of this bias, decision-makers who wish to believe
that the company's current strategy is working may ignore information
suggesting gaps between performance and expectation. Conversely, those
who wish to believe it is failing may overweight Information on such
gaps.

Adjustment and Anchoring

Tversky & Kahneman (1974) discuss another bias which helps decision-
makers deny gaps. They call this the anchoring bias. In strategic
decision-making individuals must often make initial judgements about
values of variables critical in particular decisions and revise these
judgements as new data comes in. However, the adjustments are typically

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insuf ficient. Final estimates of values are biased toward the initial
values. Individuals involved in the ongoing process of strategy formu-
lation may attend to negative information about the success of present
strategy but they will tend not to make full use of it in revising
their predictions of company performance under the present strategy.
These revisions will be smaller than are justified by the new infor-
mation.

Escalating Commitment

If these initial biases do not come into play, and the gap is
recognized, some research suggests that decision-makers deny the
significance of the gap and the need for the revision of strategy.
That is, once they have recognized the gap, they may define the problem
indicated by the gap as one which does not require a change in strategy.
Staw (1976), Staw & Fox (1977), Staw & Ross (1978), and Fox & Staw
(1979), in laboratory studies using undergraduates as subjects with
simulated investment tasks, demonstrated escalating commitment to a
chosen alternative despite negative feedback. They found that once
an individual commits a significant amount of money to an investment
project, he will tend to allocate more funds to the project if he
receives feedback indicating that the project is failing than if he
receives feedback indicating that the project is succeeding. The
feeling of personal responsibility for the project apparently induces
decision-makers to remain with their chosen project in spite of evi-
dence that it is not paying off. Staw (1976) found a much weaker
tendency to escalate commitment in subjects who had not made the

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initial commitir.ent but were dealing with a commitrQent made by an
earlier decision-maker.

Staw & Fox (1979) showed that when decision-makers face a series
of commitment decisions the escalating commitment effect is strongest
in the early decisions and may not persist over time, which suggests
that decision-makers may decrease their assessment of the probability
of recovering losses with repeated failure. Thus, decision-makers'
perceptions of the causes of failure seem to be important determinants
of escalating commitment. Staw & Ross (1978) examined the effects of
information indicating either exogenous or endogenous causes of failure
and found that subjects invested more resources in a failing project
when information pointed to an exogenous rather than an endogenous
cavise of the setback.

Finally, Fox & Staw (1979) found that escalating commitment was
most likely to occur when decision-makers were vulnerable to job loss
and when there was strong organizational resistance to the chosen
course of action. An excellent review of these studies is found in
Staw (1981). In these studies, it is obvious that the decision-makers
perceive the discrepancy indicating a project's failure since they
allocate more money to projects which appeared to be failing. However,
they did not use this perceived discrepancy to alert them to the need
to change their strategy. Rather, they seemed to interpret the nega-
tive feedback as a signal that they should commit more funds to save
the project.

Other research indicates a possible hypothesis which decision-makers
may adopt to explain a perceived discrepancy in such a way that it appears

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to require no change in strategy. They may explain it as a result of
chance factors rather than a result of a flaw in initial strategy. If
they adopt this interpretation, they are likely to persist in the cur-
rent course of action and escalate conmitment to it. Staw & Ross (1979)
found that subjects committed significantly more funds to a failing
project when the reason for the failure was extrinsic (a chance event
which could not have been foreseen) than when the reason was seen to
be intrinsic.

Illusion of Control

It may be that decision-makers tend to overestimate the role of
chance in their failures. This speculation is supported by the work
of Langer and Roth (1975) which shows that decision-makers tend to
attribute unsuccessful outcomes to chance while attributing successful
outcomes to their own skill.

Lefcourt (1973), Langer (1975) and Larwood & Whittaker (1977)
have conducted research which deals with decision-makers' judgements
about the role of chance in the outcome of a decision and have defined
a bias they call the illusion of control. Among other things, the
illusion of control leads decision-makers to attribute desirable out-
comes to internal factors (such as their ovn skill, intelligence, in-
sight, etc.) but to blame such external factors as luck for failures.
Decision-makers who note gaps between performance and expectation may
tend to attribute these to chance if the gaps tend to reflect badly
on the strategies they were responsible for designing earlier. This
would cause them to resist changing strategies which have led to per-
formance which is below expectation, strategies which are failing.

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Ihis tendency appears to be stronger in individuals who have expe-
rienced a string of successes and may therefore be especially strong
in upper- level managers involved in strategy formulation. Having
risen to the top in their organizations, they would tend to view
themselves as successful decision makers and good managers. This
would increase their tendency to attribute performance gaps to chance
rather than the failure of their strategies. This bias also has a
very strong effect on the evaluation of alternatives, as will be dis-
cussed in the section on alternatives evaluation.

Reasoning by Analogy

Decision-makers may admit that the gap does exist and that it
indicates a need to change current strategy. If this happens, there
is at least one mechanism which helps to determine the manner in which
the problem will be defined. Steinbruner (1974) has called this mech-
anism reasoning by analogy. Reasoning by analogy involves the applica-
tion of analogies and images from one problem situation to another.
In strategic decision-making, it typically involves the application of
analogies from simpler situations to complex strategic problems. This
mechanism helps to reduce the aversive uncertainty perceived in the
environment. Reasoning by analogy has been shown to be effective in
generating creative solutions to problems (Gordon, 1961; Huff, 1980).
However in strategic decisions, which involve a great deal of uncer-
tainty and complexity, the use of simple analogies is likely to mis-
lead the decision-maker into an overly simplistic view of the situa-
tion and an incorrect definition of the problem (Steinbruner, 1974,
p. 115). -

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A major problem with arguments from analogy is that they are sub-
ject to a bias which Tversky & Kahneman (1974) call availability. Ac-
cording to Tversky & Kahneman, decision-makers assess the probability
of an event by the ease with which instances or occurrences can be
brought to mind. In any strategic decision situation there are poten-
tially many analogous situations which may occur to decision-makers.
Which analogy will decision-makers choose? It may be that they will
choose the analogy which most readily comes to mind. Thus for example,
the analogy chosen may be influenced by a decision-maker's functional
specialization. Further, recent experiences may provide the most
readily available analogies.

Salience and Misguided Parsimony

If decision-makers do not use simple analogies to prematurely
define the problem, but rather attempt to locate the real causes of
the present problem, there are two possible biases which wovild make
it less likely that they will be successful. These biases are dis-
cussed by Nisbett & Foss (1980:115-130) under the headings of salience
and misguided parsimony. According to these authors, highly visible
or salient events or variables are most likely to be taken as causes,
leading decision-makers into a post hoc, ergo propter hoc fallacy.
The availability bias will cause these events to be most readily re-
called. Citing research by Pryor and Kriss (1977), and Taylor and
Fiske (1978), they argued that when decision-makers are given verbal
information about events, characteristics of the message can deter-
mine which aspects of the events are seen as causal factors. When
decision-makers observe events directly, accidental features of the

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environment or their own position in it can be important in deter-
mining causal interpretations.

Regarding misguided parsimony, Nisbett & Ross suggest that decision-
makers tend to believe that events have unitary causes. Because of this,
they may fixate on the first plausible cause which occurs to them rather
than seeking the multiple causes. Essentially, this is a satisficing
approach to determining causality. This bias may have been identified
first by John Stewart Mill in his discussion of "the prejudice that a
phenomenon cannot have more than one cause" (1843/1974, p. 763).
Nisbett and Ross also cite a statement by Kanouse which summarizes the
bias:

individuals may be primarily motivated to seek a
single sufficient explanation for any event, rather
than one that is the best of all possible explana-
tions. That is, individuals may exert more cog-
nitive effort in seeking an adequate explanation
when none has yet come to mind than they do in
seeking for further (and possibly better) explana-
tions when an adequate one is already available.
This bias may reflect a tendency to think of uni-
tary events and actions as having unitary (rather
than multiple) causes; individuals may assume, in
effect, that no more than one sufficient explana-
tion is likely to exist for a single phenomenon
(Kanouse, 1972, p. 131).

Alternatives Generation

After the strategic problem has been defined, the next stage in
the normative model involves the generation of strategic alternatives
for dealing with the problem. As Alexander (1979) points out, alter-
natives may either be created or "found" through a search process.
According to normative theory, a large scale search for alternatives
should be undertaken at this point. This search should produce a

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large number of alternatives which are then evaluated in order to
select the best. However, Cyert & March (1963) and Lindblom (1959)
indicate that the search for solutions to organizational problems does
not meet these demands. Rather, very few alternatives are evaluated
in any depth. Alexander (1979) found support for this assertion in
his study of three top-level decisions. He concluded "[the three
decisions'] most salient common feature is the rapid convergence of
options, both in number and in range, before the formal evaluation
process ever began" (1979: 396). In some cases cognitive biases may
lead to a situation in which there is no_ search for alternatives.

Since the biases discussed in this section tend to eliminate the
search for alternatives, they could be considered biases in the eval-
uations stage. However, since alternatives generation is part of
most normative models, these biases are discussed in terms of their
limiting effects on alternatives generation. These biases include:
single outcome calculations, inferences of impossibility, denying
value tradeoffs, and problem sets (see Table 2).

Single Outcome Calculation

Steinbruner (1974) elaborates on Cyert & March's notions of
problemistic search and applies it to individuals as well as organi-
zations with his discussion of single outcome calculations and re-
lated mechanisms identified in behavioral decision theory research.
Rather than attempting to specify all relevant values and goals and
all alternative courses of action as normative decision theory would
suggest, decision-makers may focus on a single one of their goals'or
values and a single alternative course of action for achieving it.

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Steinbruner argues that, contrary to normative models of organiza-
tional decision-making, uncertainty is not resolved in most instances
by probabilistic calculations of the outcomes of alternatives. Rather,
favorable outcomes are inferred for preferred alternatives while un-
favorable outcomes are projected for non-preferred alternatives. Thus
strategic decision-making involves a single-valued problem and a.
single-preferred alternative to which the decision-maker is committed
from the outset of the decision process (1974, pp. 122-123). This is
an extremely powerful simplification bias and is more likely to be
used in highly complex and uncertain decision environments. Since
this bias allows decision-makers to deny the unpleasant value trade-
offs which are always present in a choice between alternatives it
significantly reduces the stress associated with ill-structured
decision-making.

Inferences of Impossibility

Steinbruner suggests that decision-makers deal with non-preferred
alternatives through inferences of impossibility. In contrast to the
suggestions from normative decision theory, Steinbruner points out
that decision-makers may devote a good deal of effort to identifying
the negative aspects of non-preferred alternatives and attempting to
convince themselves that they are not possible to implement (1974:119).
Since this forces premature rejection of alternatives, it may have
disastrous consequences for decision-makers who use it. They will
achieve a premature closure at the possible cost of rejecting the most
feasible alternative.

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Denying Value Tradeoffs

In addition, as both Steinbruner and Jervis point out, decision-
makers over-value their favored alternative by denying value tradeoffs
(Jervis, 1976:128-136). That is, they attempt to interpret facts in
such a way that the favored alternative appears to serve several values
simultaneously and appears to have no costs associated with it. They
attempt to deny that there are tradeoffs and that there are some values
which may not be served by their favored alternative.

Problem Sets

Problem set is another decisioneil bias which has been demonstrated
in laboratory research in cognitive psychology (Anderson & Johnson,
1966; Newell & Simon, 1972). Basically, problem set is demonstrated
when perceiving an object serving one function makes it more difficult
to perceive it as capable of serving some other function or when re-
peated use of one problem-solving strategy makes it more difficult to
develop other strategies (Anderson & Johnson, 1966, p. 851). Though
this bias has only been experimentally demonstrated using relatively
simple and discrete problem-solving tasks, a similar process may be
operating when strategic decision-makers become strongly committed to
a set of assumptions about the nature of their business and appropriate
solutions to its problems. Mason & MLtroff (1981) have identified this
as a persistent problem in corporate strategy formulation.

Evaluation and Selection

The evaluation of strategic alternatives is the phase of the
decision-making process in which the limitations of Simon's "Admin-
istrative Man" are most evident. As Simon (1976) points out, the

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evaluation and selection stage of administrative decision-making falls
short of objective rationality in at least three ways.

(1) Rationality requires a complete knowledge and
anticipation of the consequences that will fol-
low on each choice. In fact, knowledge of
consequences is always fragmentary.

(2) Since these consequences lie in the future,
imagination must supply the lack of experienced
feeling in attaching value to them. But values
can be only imperfectly anticipated.

(3) Rationality requires a choice among all possible
alternative behaviors. In actual behavior, only

a very few of all these possible alternatives ever
come to mind.

(Simon, 1976:81)

The following discussion deals with biases which may affect the
activities of evaluation and selection. These include: representa-
tiveness, the illusion of control, certainty effects, restriction of
evaluation criteria, focus on negative criteria, and devaluation of
partially described alternatives.

Representativeness

Tversky & Hahnemann (1974) have pointed out a number of individual
cognitive biases which may distort judgements. The first they call
the representativeness bias. This causes a decision-maker to over-
estimate the extent to which a situation or sample is representative
of the situation or population to which he wishes to generalize. This
bias may be responsible for the fact that decision-makers tend to view
strategic decisions in terms of simple analogies. It also causes them
to overestimate the extent to which the past is representative of the

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present and the extent to which solutions offered for problems in the
past will be of value in the present problem.

Part of this representativeness bias involves insensitivity to
predictability. In making predictions of the effects of various
courses of action decision-makers do not take into account the extent
to which the evidence for the predictions is reliable, or the extent
to which the criterion is related to the cues which they use to predict
it (Tversky & Kahnemann, 1974:1125),

Decision-makers are also insensitive to sample size in making
predictions. Though a large number of observations are necessary
in order to make generalizations to a population, strategic decision-
makers are often unable to collect data on a large number of past
strategies and are quite willing to generalize from a small data
base. Further, they have too much confidence in their predictions
from small amounts of data, feeling that these data are representative
of the population as a whole. Tversky & Kahnemann call this a belief
in "law of small numbers" (Tversky & Kahnemann, 1974:1125). Nisbett
& Ross (1980:55-59) have suggested that decision-makers are especially
susceptible to the law of small numbers when considering one or a few
very vividly described cases. A single vivid description of a new ven-
ture's failure in a particular industry may influence the decision about
entering the industry more than volumes of statistical data indicating
high success rates in the industry.

Finally, in decision-making tasks which involve high levels of
uncertainty, decision-makers should be aware of this uncertainty and of
their inability to accurately forecast events in the decision environment.

-21-

Their lack of ability to forecast outcomes should make them wary of be-
coming overcommltted to particular courses of action and should encourage
them to develop contingency plans. However, decision-makers tend to be
overly confident in their ability to predict outcomes (Tversky & Kahnemann,
1974:1129) which perpetuates the illusion that they do not need to develop
formal contingency plans. Einhorn & Hogarth (1978) call this over-
confidence the illusion of validity.

Illusion of Control

Langer's illusion of control may also affect decision-makers'
perceptions of the need for contingency plans. They will overestimate
the extent to which the outcomes of a strategy are under their personal
control and may assume that through additional effort they can make
their strategy succeed should problems arise. Langer (1975) conducted
six studies which showed that subjects making a variety of decisions
expressed an expectancy of personal success inappropriately higher than
the objective probability would warrant. They tended to overestimate
the impact of their skill on the outcome or to overestimate their skill.
Larwood & I'Jhittaker (1977) comparing management students' and executives'
performance on a marketing problem found further evidence for the illusion
of control. The management students tended to overestimate their abilities
and the performance of the hypothetical firm of which they were sales
managers. Managers also overestimated performance in this exercise but
showed less tendency to do this if they had experienced unsatisfactory
results in earlier planning experiences.

-22-

Certainty Effects

Another decisional bias which may be related to the desire for
control over the environment is the certainty effect (Kahnemann &
Tversky, 1979; Tversky & Kahnemann, 1981). Kahnemann & Tversky sum-
marize a number of studies which show that people exhibit decisional
biases when they evaluate outcomes which are considered certain against
to outcomes which are merely probable. When given a choice between a
certain outcome with a given expected value and a probablistic outcome
with a slightly higher expected value, decision-makers will often choose
the certain outcome. This result alone might simply be evidence of risk
aversion. However, when given a choice between a certain loss of a small
amount and the probability of a higher expected loss, they will tend to
choose the probabilistic loss. As Kahnemann & Tversky point out (1979:269),
these results are incompatible with the concept of risk aversion which
holds that certainty is always desirable. Rather, it appears that cer-
tainty increases the aversiveness of losses as well as the desirability
of gains.

These results may be explained in terms of the desire for control
over the environment if we asstime that control over the environment
involves the ability to avoid negative outcomes. People will choose
certainty when faced with a potential gain because the certain outcome
minimizes the possibility of a zero gain which is aversive. On the
other hand, when people are faced with a choice of alternatives, one
involving a potential loss and one involving a certain loss, they will
choose the alternative which, though rasre risky, at least gives them
a chance of avoiding the loss. In other words, they are risk averse

-23-

with respect to gains and risk seeking with respect to losses. It is
often possible to formulate a problem as either a choice between los-
ses or a choice between gains. Thus, these authors have shown that
different formulation of a problem, different reference points against
which outcomes are evaluated, may result in different choices.

Criteria Restriction and Negative Forces

Wright (1974) has conducted laboratory research which reveals two
additional biases which come into play under time pressure or stress.
Business undergraduates made a choice among a number of car models based
on a number of cues with time pressure and distractions varied. The re-
sults support the claim that decision-makers restrict the number of cues
they use in evaluating the quality of various alternatives. Further,
they tend to pay most attention to and accentuate negative cues, those
which provide evidence which will lead to the rejection of alternatives.
In strategic decision-making, this could lead to the rejection of alter-
natives which have important positive features but which have perhaps
one negative feature (Wright, 1974:588-559).

Devaluation of Partially Described Alternatives

Finally, Yates, Jagacinski, & Faber (1978) demonstrated a pref-
erence for con^leteness of information which biases decision-makers'
evaluation of alternatives. Among a group of strategic alternatives,
it is likely that the probable consequences of some of the alterna-
tives will be more completely described than others. Yates, et al.
fovmd that decision makers tend to devalue the alternative that is
partially described. Since partially described alternatives involve

-24-

uncertainty for decision-makers, they tend to negatively evaluate
these against alternatives which are better described and therefore,
resolve more uncertainties.

CONJECTURES
The biases discussed in the preceeding sections form the basis
for some conjectures about probable errors in the strategic decision-
making process. These conjectures, which are numbered below, suggest
the specific ways in which strategic decision-making may depart from
normative prescriptions.

Strategic Problem Identification:

1) Decision-makers will tend to perceive fewer gaps than their
data indicate due to the prior hypothesis and adjustment and anchoring
biases (Levine, 1971; Pruitt, 1961; Wason, 1960; Jervis , 1976; Tversky
& Kahnemann, 1974),

2) Decision-makers will minimize the significance of gaps and not
use the gaps as a basis for strategy revision due to the escalating
commitment (Staw, 1976 & 1981; Staw & Fox, 1977; Staw & Ross, 1978;
Fox & Staw, 1979).

3) Decision-makers will tend to attribute unfavorable gaps to
chance due to the illusion of control (Langer, 1975; Langer & Roth,
1974; Lefcourt, 1973; Larwood & Whittaker, 1977).

4) If the significance of a gap is recognized, decision-makers
will tend to define the problem causing the gap through an analogy to
a simpler situation. Recent experience is most likely to provide the
analogy (Steinbrvmer, 1974; Tversky & Kahnemann, 1974),

-25-

5) Because of the effects of salience and misguided parsimony,
decision-makers who do seek the causes of a strategic problem will
tend to identify a single, highly visible cause (Nisbett & Ross, 1980;
Pryor & Kriss, 1977; Taylor & Fiske, 1978; Kanouse, 1972; Wilson &
Nisbett, 1978).

Strategic Alternatives Generation

6) In searching for a solution to a strategic problem, decision-
makers will tend to generate a single alternative rather than several
alternatives due to the effects of the bias toward single outcome cal-
culation (Steinbnmer, 19 74).

7) Decision-makers will tend to deal with non-preferred alterna-
tives by denying that they serve any values better than the preferred
alternative and by overestimating the difficulty in implementing them.
This is due to the biases toward denying value tradeoffs and infer-
ences of impossibility (Steinbruner, 1974),

8) Because of unchallenged assumptions and problem sets, decision-
makers who attempt to generate more than one alternative will tend to
generate very few (Anderson & Johnson, 1966; Newell & Simon, 1972;
Mason & Mitroff, 1981).

Evaluation and Selection

9) Decision-makers will tend to over-estimate the accuracy of
their predictions of the consequences of alternatives because of the
representativeness bias (Tversky & Hahnemann, 1974; Nisbett & Ross,
1980).

-26-

10) Decision-makers will tend to overestimate the importance of
their own actions in assuming the success of strategic alternatives
due to the illusion of control (Langer, 1975; Langer & Roth, 1974;
Lefcourt, 1973; Larwood & I^ittaker, 1977).

11) Because of certainty effects, decision-makers will tend to
choose more certain outcomes when attempting to maximize gain and
riskier alternatives when attempting to minimize loss (Kahnemann &
Tversky, 1979).

12) Decision-makers will exhibit a bias toward restricting the
number of evaluation criteria used and focusing on negative evaluation
criteria (Wright, 1974).

13) Decision-makers will exhibit a preference for alternatives
described in greater detail, even though partially described alterna-
tives may score higher on the decision-maker's evaluation criteria
(Yates et al., 1978).

Though most of these biases were identified in research on indi-
vidual decision-makers, it is assumed that they will also operate in
group and organizational decisions. This assumption is by no means
universally held. Indeed, Nisbett & Ross (1980, pp. 249-254) have
suggested that collective decision-making may be a way of reducing
the effects of some cognitive biases. For this reason, among others,
the preceding statements about the effects of the biases are stated in
the form of conjectures.

However, there is some support for the assumption that these
biases may actually be aggravated by group and organizational processes
which serve to restrict information reaching decision-makers.

-27-

Those responsible for making the top-level strategic decisions
may not be those who collect the information required for the decision.
Organizational structures and processes distort the information reaching
upper-level decision-makers. Crozier (1963:51) summed up the problem
in the following way, "Those who have the necessary information do not
have the power to decide, and those who have the power to decide cannot
get the necessary information." Information passing from "experts" to
top level decision-makers is subject to hierarchical distortion in both
quantity and quality. This much is well-known and intuitively plausible.
However, there is less discussion in the literature about the direction
this bias could be expected to take.

First, since experts may act as mindguards, protecting decision-
makers from potentially threatening information (Janis, 1972; Janis &
Mann, 1977) information threatening to top-level decision-makers or
information which reflected negatively on their past decisions may be
distorted or omitted. Second, information presented by experts is
often presented as part of a proposed solution to a problem or strategy.
In this case, information might be distorted in favor of the proposed
solution.

Carter (1971) documented the effects of the use of experts in
strategy formulation when he attempted to apply Cyert & March's (1963)
organizational decision-making framework to top level corporate deci-
sions. He examined six top level strategic decisions and found that
these decisions differed from the operational decisions described by
Cyert and March in two ways. First, they tended to involve more levels
of the organization and second, they involved people of more vairying

-28-

backgrounds. For these reasons, proposals for solutions to top level
problems were often presented by coalitions to top-level corporate
decision-makers and supported by staff experts' analysis.

Carter suggests that bias will be added to the appraisal of
proposed problem solution by technical or functional staff experts to
the extent that:

a) The success of the project depends on the top-level decision-
makers' acceptance of the staff's representation of the
relevant issues in the problem.

b) There is uncertainty in data relevant to the problem.

c) The top-level decision-makers possess much less knowledge about
the problem than do the staff people.

d) The top-level decision-makers perceive a great deal of un-
certainty in the problem and a need for the expertise of the
staff.

All four of these conditions are likely to hold in strategic decisions.

Further, Carter suggests that the amount of bias added to data
provided for the evaluation of a given decision and the amount and
type of data provided will depend on the following factors:

a) UTiich data are perceived as desired by higher levels of manage-
ment,

b) The amount of data necessary to gain a favorable decision.

c) The ease of developing data.

d) The extent to which the staff people or their departments will
be held accountable for the consequences of decisions which
were based on the data.

-29-

The actions of experts or mindguards may reinforce biases through
the restriction of information necessary to adequately fonmilate the
problem, to generate feasible alternatives, and to evaluate those al-
ternatives,

CONCLUSIONS AND IMPLICATIONS
In this paper, research on selected cognitive biases has been
summarized and conjectures regarding the possible effects of these
biases on strategic decision-making have been developed. In this
final section of the paper, some implications for research and prac-
tice in strategic management will be drawn.

Fesearch Implications

Future research should focus on documenting the presence of these
biases in strategic decision-making and assessing their effects.

Uiere are those who argue that we cannot draw inferences about
executives' performance at real world decision-making from students
and laboratory decision-making tasks (L\igson, Braunstein, & Hall,
1981). They hold that decision-making abilities required to rise to
a position of strategic responsibility and extensive experience with
a variety of complex decisions produce generally high-quality decision-
making performance in executives which is relatively free from bias.
In support of this claim, there is some evidence to show that some
groups of professional decision-makers such as weather forecasters
make good use of statistical information in forecasting do not exhibit
a high degree of decisional bias (Hogarth, 1975, pp. 277-278). However,
these decision-makers were able to learn from their mistakes and improve

-30-

their performance over time because they are required to make numerous
predictions based on clearly identified data and receive continuous
relatively unambiguous feedback soon after they make their predictions
(Hogarth, 1975, p. 278; Nisbett & Koss, 1980, p. 265). It could be
argued that none of these conditions hold in strategic decision-making;
that such decisions occur infrequently and Involve ambiguous data and
possibly a disagreement about which data are relevant. Further, the
feedback about the success of the strategy is often ambiguous since
there may be multiple evaluation criteria applied to the company's
performance, some of which may yield contradictory results and may
not be available for years after the implementation.

These considerations make the existence of these cognitive biases
in organizational decision-making more plausible. Further support for
their existence and effects comes from the fact that several of these
biases have been found to operate in private and public sector
decision-makers (Steinbruner, 19 74; Staw, 1981; Larwood & Whittaker,
1977; Einhom & Hogarth, 1981),

At this point, it is tempting to suggest that researchers attempt
to identify possible examples of each bias in the literature describing
well-known business decision-making failures. Indeed, books such as
Hartley's Marketing Mistakes (1976) and Smith.' s Corporations in Crisis
(1963) offer numeroios potential examples of some of these biases. How-
ever, there is a consideration which suggests that such examples may
be of little value. Since most of the biases have been identified in
laboratory settings very different from businesses, their existence
in strategic decision-making is still to some extent a matter of

-31-

conjecture. This being the case, effort should be made to document
the existence of these biases in managerial decision-making through
more detailed data including interviews with managers or records of
meetings. Records of business decisions such as those found in the
above-mentioned books merely demonstrate behavior on the part of the
managers which appears consistent with the biases and which may (or
may not be) the result of these biases. These reports are insuffi-
cient, by themselves, to demonstrate the biases' existence.

Future research on these potential biases should take two direc-
tions. First, since many have been examined exclusively in laboratory
research, an attempt should be made to document their existence and
effects in field settings. Researchers may be able to identify the
biases in executives' detailed descriptions of problem solving pro-
cesses such as those collected by Mintzberg, et al. (1976), Field
observation of decision processes may also provide insights into the
effects of these biases.

A second approach would involve further laboratory research in-
vestigating these biases in laboratory tasks more representative of
the ill-structured problems encountered in strategic decision-making.
Such concurrent laboratory and field research has been advocated in
the most fruitful approach to research for several questions In
strategic management (Schwenk, 1982).

Implications for Practice

It is necessary to establish that these biases do in fact exist
in strategic decision-making before making strong recommendations to
managers regarding techniques for avoiding them. However, practitioners

-32-

who suspect that any of these biases may be adversely affecting their
decisions have a wide variety of techniques available for reducing
their effects. Schwenk and Thomas (1982) have summarized research
on a number of techniques for reducing cognitive biases, three
examples of which will be discussed here. For improving the collec-
tion and use of information in problem identification a technique
called Strategic Assumption Analysis has been recommended (Emshoff &
Finnel, 1978; Emshoff & Mitroff, 1978; Mason, 1969; Mason & Mitroff,
1981; Mitroff & Emshoff, 1979; Mitroff, Emshoff, & Kilmann, 1979).
This technique involves the structured presentation and analysis of
divergent assumptions about data relevant to a problem.

There are a variety of creativity stimulants which have been
proven useful In stimulating the generation of alternative solutions
(Gordon, 1961; Huff, 1980; Stanford Research Institute, 1969; Warfleld,
1975), The focus of such techniques is typically the suspension of
critical processes and the encouragement of unusual associations.
Finally, for improving the evaluation of alternatives, the use of the
devil's advocate technique has been proposed (Cosier, 1978, 1980;
Cosier & Aplin, 1980; Cosier & Rose, 1977; Cosier, Ruble, & Aplin,
1978; Herbert & Estes, 1977; Janls, 1972; Jervls, 1976; Schwenk &
Cosier, 1980), This technique involves the development of critiques
questioning the wisdom of a preferred alternative and the challenging
of data and analysis supporting this alternative.

Schwenk and Thomas point out that dec is ion- makers must be aware
of the nature of the strategic decison-making process in order to
make effective use of these aids. Since the process is iterative and

-33-
cyclical, techniques designed to improve performance at one stage may
have impacts at other stages as well. For example, decision-makers
using the devil's advocate approach to improve the evaluation of alter-
natives may find that its use leads to the generation of new alter-
natives and identification of new strategic problems. Of course, this
can greatly increase the time and effort involved in reaching a deci-
sion. Thus, the use of any of these decision aids may reduce biases
at all stages of the strategic decision-making process as well as in-
creasing decision time. Practitioners should be aware of this trade-
off relationship in making use of them.

-34-

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M/C/265

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JUN 95 ,

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