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DSS News
D. J. Power, Editor
August 29, 2004 -- Vol. 5, No. 18
A Bi-Weekly Publication of DSSResources.COM
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Featured:
* Ask Dan! - How do decision-making models relate to the design and use
of DSS?
* DSS News Releases
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Ask Dan!
by Dan Power
How do decision-making models relate to the design and use of DSS?
This Ask Dan! about decision models was posted by Ecstazy, a student
studying DSS from Australia, on June 12, 2004 in the Free DSS Forum at
DSSResources.COM. He wrote "Hi Dan, How do Decision Making Models (like
Heuristics, Rationality, Garbage Can, etc.) relate to the design and use
of DSS?" Ecstazy explained "I tried to search for a comprehensive
explanation on the webs and books, but most of them don't really
specifically discuss the relationship between those models and the
design/use of DSS ... Please help me out." I tried, but this is a broad
question that could be included on a Ph.D. comprehensive exam. The
question demonstrates the multidisciplinary nature of research and
thinking about computerized decision support. Ideally an answer should
draw upon knowledge of both organizational and behavioral
decision-making theory and research and Decision Support Systems theory,
research and practice. So what's the answer?
A quick response is that descriptive decision-making models help "fit" a
specific Decision Support System to user needs and limitations.
Normative or prescriptive decision-making models help DSS developers
identify opportunities to intervene in decision making activities and
processes and potentially improve decision-making effectiveness and
other metrics of decision-making success. Some of the descriptive and
normative models are at the individual level of analysis and some are at
the organizational level. Exploring both levels of analysis can be
useful in building computerized Decision Support Systems.
A longer answer might begin by mentioning that "models" is a very broad
term. Each decision-making model has a unique history and relevance to
DSS design and potentially to understanding the use of DSS. Let me touch
on some of the specific "models" mentioned:
1) Heuristic models -- Quantitative heuristic models can be used to
build model-driven DSS; a search heuristic model like backward chaining
is used in some rule-based, knowledge-driven DSS. Heuristic is derived
from a Greek word meaning "steersman for a ship". A heuristic is a rule
of thumb or a decision-making guide. Some heuristics are normative
guides and evidence indicates people use heuristics to help make
decisions.
2) Rationality or a rational choice model -- This concept of rationality
may refer to a descriptive model of individual or organizational
behavior, but rationality is also a prescription for decision-making
behavior. When rationality describes behavior, goals and attitudes in a
decision situation, then a DSS is more likely to be used, to be useful
and to influence decision behavior. Many of us strive for rationality in
our decision-making, but a variety of cognitive, environmental and
behavioral decision-making models describe the limitations of
rationality.
3) Garbage can model -- This is a macro-organizational behavior model
(cf. Cohen, March & Olsen, 1972). The garbage can is a descriptive
metaphor for how organizational decisions are made. For those
situations where the methaphor seems appropriate, DSS can be used by
people to bring problems and solutions together and to facilitate
decisions when a decision opportunity is presented. DSS can help manage
the "garbage can" if participants so desire.
The "garbage can" model is often perceived as political or
anti-rational, so let's explore it in more detail. Cohen, March and
Olsen's (1972) model specifies that: Problems identified in
organizations usually require attention. Problems are the result of
performance gaps or an inability to predict the future. Thus, problems
may originate inside or outside the organization. Traditionally, it was
assumed that problems trigger decision processes; if a problem is
sufficiently threatening, this may happen. Usually, however, managers
and other participants go through the "garbage" and look for
interesting, suitable or important "problems" and "solutions". Managers
often "seek" problems.
According to Cohen et al., solutions are ideas that have been identified
to "solve" one or more "problems". Solutions are independent and
distinct from the problems which they might be used to solve. In some
cases, solutions are answers looking for a problem. Participants may
have ideas for solutions; they may be attracted to specific solutions
and volunteer to play the advocate. Choice opportunities or choice
situations are occasions when people in organizations expect to produce
behavior that can be called a decision, a plan or an "initiative".
"Decision opportunities" can be created by internal or external events
and circumstances. Participants (people, decision makers, managers) come
and go in the "garbage can"; the participation of specific decision
makers varies for each problem and each solution. Participation may vary
depending on the time demands of participants or on other situational
factors. Also, participants may have favorite problems or favorite
solutions which they promote and advocate.
Cohen et al. wrote: "An organization is a collection of choices looking
for problems, issues and feelings looking for decision situations in
which they might be aired, solutions looking for issues to which they
might be the answer, and decision makers looking for work (1972, p. 2)."
4) Satisficing -- Another important decision-making model was developed
by Herbert Simon. He described a "satisficing" model of individual
decision making. A satisficing conception of rationality denies that
rational decision makers must always seek the "best" or the "optimal"
means to desired ends. Rather Simon suggested that people choose the
first alternative that is "good enough" or satifies choice criteria or
aspiration levels.
According to Simon, rational man is a satisficer and not an optimizer.
Professor Simon (1976) wrote: "The social sciences suffer from acute
schizophrenia in their treatment of rationality. At one extreme, the
economists attribute to economic man a preposterously omniscient
rationality. Economic man has a complete and consistent system of
preferences that allows him always to choose among the alternatives open
to him; he is always completely aware of what these alternatives are;
there are no limits on the complexity of the computations he can perform
in order to determine what alternatives are best; probability
calculations are neither frightening nor mysterious to him ... At the
other extreme, are those tendencies in social psychology traceable to
Freud that try to reduce all cognition to affect. Thus we show that
coins look larger to poor children than to rich, that pressures of a
social group can persuade a man he sees spots that are not there, that
the process of group problem-solving involves accumulating and
discharging tensions, and so on."
In general, the development of computerized Decision Support Systems
assumes a rational, analytical model of human and organizational
decision-making. If another model better describes the actual behavior
in a situation, for example, a garbage can model, then a DSS may serve a
very different purpose than trying to enhance rationality. In a garbage
can situation, a DSS may help in rationalizing a match between a problem
and a solution.
This Ask Dan! question is perhaps the start of a research paper or the
stimulus for further thought and inquiry by readers. Please add you
comments, thoughts and replies on the DSS Forum at
http://planningskills.com/webboard/index.php .
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References
Cohen, M. D., J. G. March, J. P. Olsen, "A Garbage Can Model of
Organizational Choice," Administrative Science Quarterly, Vol. 17, No.
1. (March 1972), pp. 1-25.
Power, D. J., "Is there a theory of Decision Support Systems?" DSS News,
Vol. 2, No. 12, June 3, 2001.
Simon, H.A., Administrative Behavior, Third edition (New York: The Free
Press, 1976), pp. xxvi-xxvii.
Simon, H.A., "Rational Decision-Making in Business Organizations," 1978
Nobel Lecture,
http://www.nobel.se/economics/laureates/1978/simon-lecture.pdf
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