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8
Decision Making
The extent to which teams successfully deal with transitions to crisis
situations depends heavily on the extent to which the right actions are cho-
sen: the process of decision making. Because of the great publicity that
decision making failures often receive, we typically hear more about faulty
decisions than successes in crisis situations. For example, the disaster at
Three Mile Island resulted in part because operators in the control room
made a decision to shut off an emergency feed water pump, having misdiag-
nosed the state of the reactor (Rubinstein and Mason, 1979~. Less publi-
cized because of their less disastrous outcomes were the more appropriate
decisions taken in response to nuclear power emergencies at the L)avls-
Bessie and Brownsville plants.
The flight crew on board the Air Florida Boeing 737 at Washington's
National Airport in 1982 exhibited faulty judgment in their decision to take
off in icy conditions without requesting an immediate deicing (O'Hare and
Roscoe, 1991; Van Dyne, 1982~. The sluggishly handling plane never gained
necessary air speed and crashed into the 14th Street Bridge in Washington,
DC. In contrast, the problem-solving and decision-making sequence fol-
lowed by the flight crew of the United flight 232, which suffered a total
hydraulics failure over Iowa, was testimony to the good judgment of the
team in crisis bringing a totally crippled and nearly uncontrollable jet to
earth (see Chapter 101.
For tank crews, also, the decisions made under combat stress have a
major bearing on the success of the mission and the survivability of the
crew. Does one chose to engage the enemy or not? Is it worth risking
198
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DECISION MAKING
199
exposure by following the shortest path to an urgent destination? Or should
one follow a longer, slower route, maintaining a low-profile, hidden posi-
tion?
In most teams, decision-making responsibilities fall most heavily on the
team leader-the tank commander, the airplane pilot in command, the hos-
pital physician, or the fire chief. These individuals possess the ultimate
responsibility for choosing the appropriate course of action, but other mem-
bers of the team also play a critical role in communicating the information
on which the optimal decision can and should be based.
Analysis of the decision-making case studies mentioned above and of
numerous others reveals that shortcomings in decision making may result
from limitations in a number of the processes necessary to execute a deci-
sion, from initial information gathering to final choice. In particular, it is
possible to partition the process into two overall phases: the acquisition
and maintenance of situation awareness necessary to diagnose or estimate
the most likely state of affairs, and the selection of a course of action.
While each of these phases can themselves be analyzed further, as indicated
in Figure 8.1, it is instructive to consider examples of how faulty decisions
can result from a breakdown of each. The operators at Three Mile Island,
for example, made the right choice of action given their diagnosis of the
state of the plant which, unfortunately, had been faulty. A correct choice
of action was also made by the commanding officer on the U.S.S. Vincennes
(Klein, 1989; Slovic, 1987; U.S. Navy, 1988~. Given the information pro-
vided to him, that the aircraft approaching the ship was probably hostile, his
decision to launch a missile was probably the best one. The tragedy result-
ing when the missile struck a civilian airliner resulted because the identifi-
cation of that aircraft was in error. In contrast, the Air Florida crash did not
result because the crew failed to diagnose the icing conditions, but because
their choice of action was inappropriate given those conditions. In the first
half of this chapter, we treat these two phases of decision making separately
before discussing how both are related specifically to the transition period.
The section concludes by recommending some possible remediations to guard
against decision failures.
HEURISTICS AND BIASES IN HYPOTHESIS FORMATION
A necessary, but not sufficient, precondition for good decision making
is the existence of a correct hypothesis of the most likely state of the world
within which the chosen action will be carried out. Wickens and Flach
(1988) have presented an information processing model or framework of the
hypothesis formation process, shown in Figure 8.1. Within the model, vari-
ous biases and heuristics (Kahneman et al., 1982) are identified that may
create distortions in hypothesis formation and situation awareness. In the
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200
Cues
WORKLOAD TRANSITION
E!
Perception
and Attention '
-
, ~
I ~
,_
Long Term Memory
Working
Memory
Criterion j
tin I
33 Situation
Assessment
(Diagnosis)
t.1
-- - - --I-- - - - - - - - - - - - - - - - - - - - - --t-- - - - - - --I---
~ Hypothesis
Generation
Action ~ |
GenerationJ ~
~ Choice ~Action | ~
_ _ _ _ _ _ _
1 1
Risk Assessment
~ Salience Bias
E] Representativeness Heuristic
@ As-lf Heuristic
1~ Availability Heuristic
E! Confirmation Bias
] Framing Bias
FIGURE 8.1 A model of decision making. Biases and heuristics, denoted by
letters surrounded by a square, are discussed in the text. Source: Wickens and Flach
(1988~. Copyright held by Academic Press. Reprinted by permission.
following, each of these is illustrated as it might be or has been manifest in
an applied setting.
When integrating multiple sources of information to formulate a hy-
pothesis, the salience bias describes the decision maker's tendency to focus
on the most salient (loudest, brightest, most prominent) cue, rather than that
which may be most informative and diagnostic, when these are not the
same. As one example, in the analysis of the incident aboard the U.S.S.
Vincennes when the Iranian airliner was shot down, it was apparent that the
salient writing of the word F14 on a message board in the combat informa-
tion center, following the uncertain hypothesis of the aircraft's identify,
contributed to the ultimate misidentification of the aircraft.
Which hypothesis a decision maker chooses to base his or her actions
on depends very much on which hypothesis is most available in memory,
rather than in fact which may be the most likely in the circumstances. This
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DECISION MAKING
201
is known as the availability heuristic (Tversky and Kahneman, 1974~. Thus,
the tank commander will find most available the enemy's plan of attack for
which he had just been briefed, or which he had encountered in a recent
drill, because these would be easily brought to mind. Analysis of the Vincennes
incident revealed that the misdiagnosis was the result of interpreting the
actions of the radar contact in terms of a predefined script of a hostile
attack (U.S. Navy, 1988~. That is, an easily recallable sequence of events
that would be likely to occur in combat.
Once a tentative hypothesis is formulated, based perhaps on available
memories and salient information sources, two closely related forces join to
increase the likelihood that available hypotheses will prevail and alterna-
tives will not be considered. The anchoring heuristic describes the ten-
dency to stay with a current hypothesis and consider new information that
might shift one's beliefs in favor of a different hypothesis less than ad-
equately (Tversky and Kahneman, 1974; Van Dyne, 1982~. The confirma-
tion bias (Klayman and Ha, 1987; Tolcott et al., 1989) describes the deci
sion makers' tendency to seek new information that supports one's currently
held hypothesis and to ignore (or at least downplay) information that may
support an alternative hypothesis. Both anchoring and the confirmation
bias seem to have been partially responsible for the disaster at the Three
Mile Island nuclear power plant, in which operators focused on the inappro-
priate hypothesis that the water level was high and ignored critical display
information suggesting just the opposite (i.e., that the water level was too
low, which turned out in fact to be the correct hypothesis). It is easy to
envision how the tank commander, with a preconceived hypothesis regard-
ing the nature of enemy intentions, will interpret ambiguous evidence as
consistent with these intentions. Tolcott et al. (1989) have found that such a
bias is present in the performance of Army intelligence analysts.
EXPERTISE IN DIAGNOSIS
The information flow in Figure 8.1 suggests that human decision mak-
ers go through a time-consuming computational process of evaluating and
interpreting evidence, relying heavily on the limited capacity of working
memory. Yet under time pressure and in potential crisis situations, there is
good evidence that expert decision makers-the skilled tank commander,
pilot, or nuclear power plant control room operator may adopt a very
different strategy of hypothesis diagnosis in which they simply match the
available evidence with the most similar experience already stored in long-
term memory (Ebbeson and Koneci, 19811. Klein (1989), for example, has
documented that expert fire crew chiefs, when diagnosing the nature of a
fire upon first arriving at the scene, go through such a pattern match pro-
cess, as do expert (but not novice) tank commanders in simulated battle
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WORKLOAD TRANSITION
games. The viewed scene is simply compared with a series of mental
representations of typical scenes from past experience, to determine which
one is an adequate match. In a study of pilot decision making, Wickens et
al. (1987) and Barnett (1989) inferred that highly experienced pilots (those
with more than 500 flight hours) used a qualitatively different style of pilot
judgment than novices, relying less on working memory and more on direct
retrieval of the appropriate solutions from long-term memory.
In spite of the apparent advantages of this pattern-matching decision
strategy in some contexts, particularly those involving time pressure, the
limits of this approach should be clearly noted as well. On one hand, such a
technique may be applied effectively only in the domain for which expertise
has been developed. Thus, for example, Klein observed that fire chiefs
used pattern-matching diagnosis behavior when they diagnosed the nature
of a fire, but not when they needed to deal with administrative commands
and personnel decisions. On the other hand, although the pattern-matching
technique is more rapid, less resource demanding, and qualitatively differ-
ent, it is not necessarily more accurate than the time-consuming computa-
tional technique used by novices. Indeed, Wickens et al. (1987) found little
difference in the accuracy of judgments made by high-time versus low-time
pilots, only that high-time pilots were more confident in their decisions. As
noted in Chapter 4, Koehler and McKinney (1991) found that inflight diag
noses of expert pilots were no better than those of less experienced pilots,
and actually suffered more when the problems were nonroutine.
In accounting for these failures, it is reasonable to assume that, because
the pattern-matching approach forces a set of environmental cues to match a
stored template in memory, it may be relatively more susceptible to the
biases in hypothesis formulation discussed above (confirmation, anchoring,
and availability). This is because a situation that is generally similar to the
mental representation of past experience, but may be different in some key
respects, could be classified as identical, with those key differences simply
ignored (i.e., anchoring on what is available from past experience). Unfor-
tunately, with the exception of the Wickens et al. (1987) study, few data are
available regarding the relative quality of pattern matching versus computa-
tional decision making in applied environments. Furthermore, the studies
discussed above have defined expertise in terms of years of experience,
rather than (necessarily) a high quality of performance. It will be important
to continue research that examines decision style and quality as a function
of expertise, unconfounded with experience.
CHOICE
Classic decision theory has focused its efforts on ways to integrate the
uncertainty and the value associated with prospective outcomes of decision
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DECISION MAKING
203
alternatives. That is, a given choice is assumed to have a number of pos-
sible outcomes (depending on the uncertain state of the world in which a
choice is made) (see Figure 8.23. The option that is favored is assumed to
maximize some subjective quantity or preferer~ce for the decision maker. It
is often assumed that this quantity is the subjective expected utility, which
is computed as the utility (subjective value) of each possible outcome for
the choice, multiplied by the subjective probability that that outcome will
be observed. There are numerous alternative models that have been applied
to decision making. For example, it might be assumed that decision makers
will minimize losses or will pick the least effortful decision that has some
minimum level of expected gain (Slovic, 19873. However, if one option
_
-
-
~_
-
-
FIGURE 8.2 A hypothetical risky choice. Decision Option A will yield one of
two possible outcomes, depending on whether the state of the world is 1 or 2. These
states are not known for sure, but are estimated (diagnosed) with probabilities Pi
and P2, respectively. If state 1 is in effect, outcome Al, which has utility UAI, will
be obtained. State 2 will yield outcome A2, with utility UA2. In contrast, decision
Option B will yield a certain (nonrisky) outcome with utility UB, no matter which
state is true.
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WORKLOAD TRANSITION
promises more attractive outcomes given some circumstances, but the chances
of those outcomes are lower than those of less appealing outcomes prom-
ised by competing alternatives how should the conflict be resolved?
A critical concept in such analysis is that of risk, typically characteriz-
ing an option for which the two or more possible outcomes associated with
the choice may differ in their probability of occurrence and do differ in
their utility (i.e., cost or benefit). This situation characterizes option A in
the figure. For example, a low-probability outcome may be associated with
dire consequences and a high-probability outcome may be associated with
consequences that are far more benign. In the nuclear power industry, a
decision to keep a reactor on line when it has shown a faintly suspicious
symptom might be such an example. There is a small probability of a major
disaster if the symptom really does herald a failure but a high probability
that nothing is wrong.
How bad such a risky option is perceived to be (its expected negative
utility) will, of course, depend on how large is the perceived probability of
the negative outcome. There are in fact a number of sometimes conflicting
influences on perceived probability that may bias the estimate in different
directions. For example, very rare events are typically overestimated (ex-
plaining why people believe they will win by entering lotteries) (Sheridan
and Farrell, 1974; Wickens, 1984~. This overestimation is particularly likely
to occur when low-probability events are well publicized so that they be-
come available to memory (Slovic, 1987~. Humans have a tendency to be
overconfident of their own likelihood of success to underestimate the probability
that infrequent, bad things will happen to them (as opposed to someone
else) (Bettman et al., 1986~. This is one example of the general bias toward
overconfidence in human diagnosis and choice.
As shown in the figure, risky options are often paired against "sure
thing" options, for which the consequences are reasonably well known:
shut the nuclear reactor down and the power plant will surely suffer some
disruption, but it also will surely avoid disaster. Research by Kahneman
and Tversky (1981, 1984) into the heuristic known as framing suggests that,
when choosing between a risky and a sure thing option, people respond
differently when the outcomes of both options have positive expected utili-
ties, than when both options have outcomes with negative expected utilities.
Teams in crisis usually are confronted with a pair of negative outcomes.
The tank commander might, for example, choose between a safe retreat,
with a sure loss of position but sure preservation of safety, and a risky
advance, win a low probability of encountering fatality-inducing battle conditions.
In analogous circumstances, when the choice is between negatives, Kahneman
and Tversky found that people usually are biased to choose the risky option.
When in contrast, the choice is viewed as one between positive outcomes,
the choice is more likely to be biased toward the sure thing safe option.
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DECISION MAKING
205
The important feature of this framing bias is that the very same decisions
may be framed positively by emphasizing the good characteristics (e.g.,
probability of winning the battle, preserving crew lives) or negatively (e.g.,
probability of losing the battle, encountering fatalities), and the difference
in framing will influence the choice that is made.
As with our discussion of diagnosis, so also with choice: it appears that
expert decision makers do not generally employ a fully analytic strategy.
They do not carefully weigh all the alternatives, outcome utilities, and prob-
abilities before arriving at a choice. Rather, evidence suggests that these
processes, too, are often circumvented by a decision based on direct memory
retrieval. If, in a particular circumstance (evaluated by diagnosis), a choice
has proven successful in the past (yielded a favorable outcome), it will be
chosen again. Any action that has yielded this outcome can be chosen, not
necessarily that with the highest expected utility (Klein, 1989~. Such a
strategy, in which the first alternative that satisfies all relevant attributes is
selected, has been labeled as satisficing (Simon, 19551. This characterizes
the verbal protocols that fire chiefs give when describing the tactics they
choose to fight a fire (Klein, 19893.
Analogous to our treatment of diagnosis, the alternative direct memory
retrieval method of decision making shown by experts is not necessarily
better than the strategy shown by novices, although it is more rapid and
made with less effort. The strategy will lead to the choice of actions that
are familiar and easy to recall. Hence, certain biases toward availability
may be shown. This appears to be an adaptive strategy in times of stress,
when time pressure is intense, as will be the case in most transition situa-
tions. We consider now the potential effects of the transition on decision
quality.
TRANSITION EFFECTS
The influence of the transition process on decision making may be
roughly described from two perspectives: the exchange between pretransition
effort and post-transition performance, and the overall influence of stress on
. . . .
transition decision per ormance.
Pre-Post Exchange
The first section of this chapter has described the extent to which effec-
tive decision making is based on accurate situation awareness. One can
easily imagine that efficient and accurate judgments in a post-transition
period will depend on the fidelity of knowledge gained in the pretransition
period. Three kinds of knowledge and preparation would seem to be of use
here. The first concerns static knowledge of features that are unlikely to
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WORKLOAD TRANSITION
change. For the tank commander, this characterizes knowledge of the geog-
raphy of the area, the acquisition of which was described in the previous
chapter. For the nuclear power crew, this static information is characterized
by long-term knowledge of plant operation as well as the more transient
knowledge of the repair status of the plant which lines are open and which
are closed. For a disaster relief coordinator, it may involve knowledge of
which units and equipment are located where. There is a high payoff in
investing resources into acquiring this static knowledge or situation aware-
ness, since it will be unlikely to change and can then be used as a basis for
fast and effective decision making after the transition.
Second, there is a class of knowledge and information that can be gath-
ered prior to transition that has uncertainty associated with it. Any decision
that will be taken in response to future meteorological conditions, for ex-
ample, must certainly be of this form. So also will a tank commander's
decision based on intelligence about what an enemy might do (Scott and
Wickens, 1983~. In this instance, it would seem important to prepare for
and consider, not only the most likely hypothesis (or state) based on the
available cues, but also those conditions of less, but nonzero, likelihood. In
short, it is valuable to develop a weighted contingency diagnosis in which
crews are prepared for alternate states in proportion to their degree of likeli-
hood. The prepared decision maker should guard against a sharpening of
preparedness only for the most likely state. In this way the team will be
less likely to misidentify and falsely classify a particular situation, suc-
cumbing to the heuristics of anchoring and availability. An important corol-
lary of this strategy is that estimates of uncertainty should be carefully
preserved as situation information or intelligence is relayed from person to
person or unit to unit. It was in part the failure to relay uncertainty infor-
mation up the chain of command that led to the disaster in the U.S.S.
Vincennes incident (U.S. Navy, 1988~.
Third, and most obviously, post-transition decision making can be fa-
cilitated by the rehearsal of and preparation for contingency response plans.
As noted in Chapter 3, greater pretransition preparation will lead to more
efficient post-transition response. But here again, care must be taken to
guard against blind following of a preprogrammed procedure, without monitoring
its ongoing appropriateness and without entertaining a willingness to modify
or abandon the procedure as needed (i.e., to guard against the confirmation
bias) (Woods and Roth, 19879.
Stress Effects
The second relevant transition effect on decision making concerns the
specific effects of post-transition stress on decision-making performance. Given
that many of the stress effects were covered previously in Chapter 4, we
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DECISION MAKING
207
present here only a brief review of how the combined effects of noise, danger,
and time pressure might be expected to amplify decision-making biases.
Communications
Noise will have a clear and direct degrading effect on communica-
tions the exchange of auditory information necessary for effective deci-
sion making. We might also anticipate a specific form of stress bias for the
listener to expect and therefore hear the subjectively most likely message.
Such was a clear factor responsible for the KIM-PAN AM collision on the
runway in the Canary Islands (Bailey, 1989~.
Perceptual Tunneling
Stress is known to induce an attentional focusing on the most subjec-
tively important source of information (Broadbent, 1971~. Where the sub-
jective importance of an information source does not directly correlate with
its true reliability and diagnosticity, major problems could be encountered.
Confirmation Bias
There is at least anecdotal evidence that stress can enhance the confir-
mation bias, reinforcing still further the belief that the hypothesis or action
one has already chosen is correct. This tendency seems to have character-
ized the operators' behaviors at Three Mile Island (Rubinstein and Mason,
1979) and was diagnosed as a contributing cause of a substantial number of
recent accidents in British military aircraft (Chappelow, 19881.
Phonetic Working Memory
It is not difficult to envision how stress, particularly that characterized
by noise, can reduce working memory capacity (Hockey, 1986) and there-
fore the effectiveness of that memory system in storing verbal information
necessary for hypothesis testing and evaluation (Mehle, 1982~. This is
particularly true when the situation is unfamiliar and the operator is less
able to rely on pattern-matching techniques.
Spatial Working Memory
Wickens et al. (1988a, 1988b) found that pilot decisions made under the
combined stress of noise and time pressure were degraded to the extent that
they depended on visualization of the airspace. One might anticipate, there-
fore, similar effects on decisions that require rapid updating or revision of a
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WORKLOAD TRANSITION
mental model of terrain (in the case of the tank commander) or some other
visual-spatial environment (i.e., the structure of a ship, building, or plant on
fire).
Speed-Accuracv Tradeoff
It has been shown that stress induces a shift to fast, but less accurate,
performance on a speed-accuracy tradeoff (Hockey, 1986~. Furthermore,
given that accurate performance on certain kinds of decisions depends on a
time-consuming weighing of various alternatives, it is reasonable to con-
clude that decision performance following transition will be more error
prone, to the extent that it depends on an analytic computational strategy.
Alternatively, it can be predicted that the preferred strategy of decision
making will be likely to shift to one involving direct memory retrieval,
given that the operator has stored the necessary domain-related knowledge
base (Klein, 19891.
Remediation
Decision researchers have long been aware of the failures and limita-
tions of human decision making (Slovic et al., 1977~. More recently, they
have acknowledged the human's very real strengths in this area compared
with the capabilities of many artificial intelligence systems (Klein, 1989~.
To counteract these limitations, four general remediation solutions have
been proposed, any of which might be appropriate for the transition envi-
ronment. Each of these solutions is described below.
Decision Aids
The increasing power and sophistication of computer technology has
made more feasible the development of programs that can assist decision
making. In each phase, there are two alternative approaches. One involves
the development of artificial intelligence/expert system technology in which
potential solutions (diagnoses or recommended choices) are computer-gen-
erated, to be accepted or rejected by the human operator (Madni, 1988;
Rouse et al., 19901. Such techniques would still appear to be somewhat
limited unless the optimum decision rules can be clearly and unambigu-
ously articulated, and the decision problem is quite self-contained (i.e., does
not involve extracting information from unforeseeable sources). For ex-
ample, a decision aid in recommending diagnoses of a failed gunnery com-
puter might be appropriate. One that recommends battlefield tactics would
be far more tenuous, because of the diversity of factors that should go into
such a consideration.
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DECISION MAKING
209
The alternative approach is a decision aid that provides assistance to
the human operator but does not recommend diagnoses or actions. Such an
aid might, for example, list alternative hypotheses for a diagnosis, to safe-
guard against the tunneling produced by availability and anchoring. Corre-
spondingly, it might list alternative courses of action (without recommend-
ing particular ones). A major potential source of benefit here could be
realized in aids that provided an effective and organized display of informa-
tion cues that could assist in hypothesis evaluation and situation awareness
(MacGregor and Slovic, 1986; Scott and Wickens, 1983~. Such a display
aid could present cues in terms of their information value, in such a way
that salience would not distort the overall representation of information. In
general, displays that minimize the need for cognitive transformation be-
tween what is displayed and what is meant, and that organize information in
logical groupings, will aid the decision maker.
Debias Training
An alternative approach to designing aids that will minimize the impact
of bias is to train or teach the operator about these biases and heuristics
directly. Such debias training has been introduced with the belief that, once
a decision maker is aware of the existence of these biases, he or she will be
less likely to fall prey to their influence; however, the consensus in the
literature is that simple awareness of these biases rarely alleviates them
(Fischhoff, 1982~.
Some examples of modest success in debiasing have been observed,
rendering decision making less susceptible to anchoring (Lopes, 1982) and
overconfidence in meteorological forecasting (Murphy et al., 1985~. While
not yet fully validated as an effective technique, it would seem that provid-
ing decision makers with some level of training into the nature of heuristics,
and the understanding of probability would be of considerable value in
many applied contexts.
Domain Training
An alternative form of training to that used in debiasing is direct train
ing in the domain of the decision itself (rather than in the mechanics of the
decision process). Certainly included here would be training in planning
and diagnosis or situation assessment. One issue that is not well resolved is
the extent to which training to deal with events following crisis shout
focus on highly specific (but brittle) procedures following. In the context
of the nuclear power industry, Woods (1988) has voiced some concern about
the dangers of overtraining operators to follow very specific procedures
given a particular failure diagnosis. The concern results when the diag
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WORKLOAD TRANSITION
noses on which the procedure is based is itself uncertain (i.e., a diagnosis of
the most likely candidate, but not a certain candidate, so that others are
plausible). In this case, overtraining on a particular routine or decided
course of action to follow given that hypothesis, may lead the operator to
follow it blindly, without carefully checking as the decision actions are
carried out, to determine whether the routine remains appropriate. As we
have seen, this tendency may be exaggerated in times of stress. In this
regard, some consideration should be given to training the decision maker
to closely monitor the outcomes of the actions following a decision, in
order to ensure that the choice was in fact the correct one, and to be pre-
pared to alter those actions as necessary. Such training could make use of
the realistic, dynamic simulation facilities offered by SIMNET, a team-
oriented tank training facility to be discussed in further detail in Chapter 10.
The issue of the specificity with which emergency procedures following
should be trained is one for which more research is clearly needed. In at
least one domain, programs to train decision makers have demonstrated
valid success. Diehl (1991) has reviewed the effectiveness of air crew
decision training in a variety of aviation programs and has concluded that
such programs substantially reduce the likelihood of erroneous pilot judg-
ments.
Team Cohesion
The final remediation addresses the need to create efficient decision
making teams within which the communication of information necessary
for optimal diagnosis and choice proceeds in a smooth and unambiguous
fashion. Clearly some degree of standardization and redundancy in vocal
communications is necessary. But other critical factors involve the spirit,
coherence, training, and personality of the team members, and in particular
of the team leader. These are issues that are discussed at the end of Chapter
4 and are dealt with again in some depth in Chapter 10; some of them are
also addressed in Druckman and Bjork (1991~.
SUMMARY
The decision making of teams in transition depends jointly on the deci-
sion-making capabilities of the team leader, and on the flow of information
via voice communication from other team members and from well config-
ured visual displays. When this information transmission is effective, it
provides the basis for good situational awareness or diagnosis of the state of
the world that requires a decision. Yet this diagnosis may be hindered or
distorted by a number of biases or heuristics, some of which are amplified
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DECISION MAKING
211
under times of stress. High degrees of expertise may eliminate some of
these problems and produce more rapid decisions.
Diagnosis is often followed by choice, which depends on the accurate
assessment of outcomes, their utility, and their risk. Here again, certain
biases in risk perception have been identified, and here also the decision
process may be facilitated by expertise.
Two categories of transition effects on the decision process may be
identified. On one hand, there are certain actions the operator can take
before the transition that can improve decision quality (or accuracy) after
the transition. On the other hand, the transition itself will induce a level of
stress that is likely to systematically degrade certain aspects of the decision
process.
The limitations of decision making can be remediated by one of four
techniques: computer-based decision aiding, particularly that which em-
phasizes the display and organization of relevant cues, training of self-
awareness of the decision maker's biases, training in the decision domain,
and development of team cohesion.
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Barnett, B.
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Bettman, J.R., J.W. Payne, and R. Staelin
1986 Cognitive considerations in designing effective labels for presenting risk informa-
tion. Journal of Marketing and Public Policy 5:1-28.
Broadbent, D.E.
1971 Decision and Stress. New York: Academic Press.
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Representative terms from entire chapter:
workload transition
