Page 288 - Mechanical Engineers' Handbook (Volume 2)

4 Systems Engineering Methodology and Methods 279

uncertainties associated with the outcomes of proposed policies. Most planning, design, and
resource allocation issues will involve a large number of decision-makers who act according
to their varied preferences. Often, these decision-makers will have diverse and conflicting
data available to them and the decision situation will be quite fragmented. Furthermore,
outcomes resulting from actions can often only be adequately characterized by a large num-
ber of incommensurable attributes. Explicit informed comparison of alternatives across these
attributes by many stakeholders in an evaluation and choice-making process is typically most
difficult.
As a consequence of this, people will often search for and use some form of a dominance
structure to enable rejection of alternatives that are perceived to be dominated by one or
more other alternatives. An alternative is said to be ‘‘dominated’’ by another alternative when
the other alternative has attribute scores at least as large as those associated with the dom-
inated alternative and at least one attribute score that is larger. However, biases have been
shown to be systematic and prevalent in most unaided cognitive activities. Decisions and
judgments are influenced by differential weights of information and by a variety of human
information-processing deficiencies, such as base rates, representativeness, availability, ad-
justment, and anchoring. Often it is very difficult to disaggregate values of policy outcomes
from causal relations determining these outcomes. Often correlation is used to infer causality.
Wishful thinking and other forms of selective perception encourage us not to obtain poten-
tially disconfirming information. The resulting confounding of values with facts can lead to
great difficulties in discourse and related decision making.
It is especially important to avoid the large number of potential cognitive biases and
flaws in the process of formulation, analysis, and interpretation for judgment and choice.
These may well occur due to flaws in human information processing associated with the
identification of problem elements, structuring of decision situations, and the probabilistic
and utility assessment portions of the judgmental tasks of evaluation and decision making.
Among the cognitive biases and information-processing flaws that have been identified
are several that affect information formulation or acquisition, information analysis, and in-
terpretation. These and related material are described in Ref. 21 and the references contained
therein. Among these biases, which are not independent, are the following:
1. Adjustment and Anchoring. Often a person finds that difficulty in problem solving
is due not to the lack of data and information but rather to an excess of data and
information. In such situations, the person often resorts to heuristics, which may
reduce the mental efforts required to arrive at a solution. In using the anchoring
and adjustment heuristic when confronted with a large number of data, the person
selects a particular datum, such as the mean, as an initial or starting point or anchor
and then adjusts that value improperly in order to incorporate the rest of these data,
resulting in flawed information analysis.
2. Availability. The decision-maker uses only easily available information and ignores
sources of significant but not easily available information. An event is believed to
occur frequently, that is, with high probability, if it is easy to recall similar events.
3. Base Rate. The likelihood of occurrence of two events is often compared by con-
trasting the number of times the two events occur and ignoring the rate of occur-
rence of each event. This bias often arises when the decision-maker has concrete
experience with one event but only statistical or abstract information on the other.
Generally, abstract information will be ignored at the expense of concrete infor-
mation. A base rate determined primarily from concrete information may be called
a causal base rate, whereas that determined from abstract information is an inci-