Understanding Decision Biases in DSS Development

The assignment content discusses the concept of decision bias, which refers to the systematic errors in judgment and decision-making processes. The paper identifies several types of biases, including overconfidence, selectivity, success, and test biases, which can affect decision-makers' judgments and lead to suboptimal outcomes. It also presents a debiasing framework that aims to eliminate these biases by identifying their nature, providing feedback, and offering training programs. The content concludes by emphasizing the importance of considering decision biases in the development of decision support systems.

Running head: MANAGEMENT DECISION MAKING
Management Decision Making
Cognitive Biases

MANAGEMENT DECISION MAKING 1
Table of Contents
Executive Summary.........................................................................................................................2
Introduction......................................................................................................................................2
General framework by D Arnott (1978)..........................................................................................2
Arnott’s Biases.................................................................................................................................2
Conclusion.......................................................................................................................................2
References........................................................................................................................................2

MANAGEMENT DECISION MAKING 2
Executive Summary
The decision-making and the decision bias theory is seen not to focus on the choice process but
instead it focusses on the possible persistent and systematic errors in the decision-making
process. The decision biases are considered to be the cognitions which might prejudice the
quality of our decisions. Therefore a DSS development model is uses for incorporating such
decision biases instead of the development focus task. The study focuses on two of the biases
and explains then thoroughly along with a general framework being provided by Dr. Arnott.

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Introduction
In the era of distributed computing, the decision support system is introduced. The support
system is started in 1965 and the record formalization of system, people, ideas and technology
involved in the applied information technology. The technology provides integrated support to
the managers who are working in a sole proprietorship and it helps to take rational decisions for
the management of organizational hierarchies. The history includes the ideas and records of the
past activities which help to guide the future activities. The different reports are prepared
because of different vantage points, reactions and incidents. The problems can be sorted out
through past history solutions but collection of data is very necessary. The information is
collected from the information technology companies, college and universities, and the
companies which are using decision support system. The decision support system is defined as
the area of information system which is prepared to support and improve the decision making
system. The major modifications in the information technology enable the new decision support
movement. In the year 1980, the spreadsheet and financial modeling software had created a
boom in the personal decision support system. The DSS and its functionality has evolved with
the various development cycles where the clients and the system analysts are the active
contributors to the shape, logic and nature the system. Due to ill-structured management
decisions, the DSS developers should try to adopt an evolutionary approach. The DSS and its
environment are seen to be subjected to change and therefore all the system requirements are
likely to change even when specified with accuracy when the project begins. The major
modifications in the information technology enable the new decision support movement. In the

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year 1980, the spreadsheet and financial modeling software had created a boom in the personal
decision support system. (Arnott, D., & Pervan, G., 2005).
The aim of the paper is contribution to the DSS development theory along with its practices by
presented various researches based on the errors in the decision-making process and judgment
being the prime base for the development of the systems.In this present paper we will discuss the
general framework and the research to improve the decision support system. The paper aims to
discuss the various cycles involved in the DSS evolution. The organization of the paper is as
follows: initially a general framework by D Arnott (1978) is discussed along with various biases.
A general framework in this approach has been described and is then used for structuring the
discussion on the two selected biases two biases of Arnotts’s list of theory seven biases is
explained with an example. The biases used in the project paper involve the memory and the
confidence biases. Present approach along with the DSS evolution framework has been reported
and finally the debiasing strategies for the two selected biases have been identified.
General framework by D Arnott (1978)
The general framework involves the sections from the period of 1965 to mid-1990. The threads
of decision support system is linked with the model-oriented decision support system,
multidimensional analysis, expert system, reporting and query tools, business intelligence,
OLAP, executive information system, and group decision support system. All the information is
converged and diverged over the years. In the 1960s, the new information system comes into
usage which is a management decision system. The concept of decision support system comes
from the theoretical studies of organizational decision making which took place at the Carnegie
institute of technology at the late 1950s. The technical work took place at Massachusetts institute

MANAGEMENT DECISION MAKING 5
of technology in the 1960s. The MIT project’s historical information is on interactive computer
system took place at mutlicians.org. In the 1970s, the journal on Management decision system
starts publishing. Such as the various article on decision support system is publishes by Scott
Morton and Colleagues in 1968. The journal on management decision making is publishes by
Ferguson and Jones in 1969. The breaking book on Management decision making is published
by Michael S. Scott Morton’s in the year 1971. The study on the help of computers and
analytical models is conducted by Scott Morton which helps the managers to take crucial
decision of an organization. The Management decision system is used by the production and
marketing managers which help in the planning of production for laundry equipment’s. The
dissertation research is prepared by the Scott, who includes the definition, implementation and
research on the model driven decision support system.
The fundamental process of design is the system development. The problems came at the time
of decision support system analysis is articulated in the design theory which includes the
problem of insufficient knowledge base for the purpose of designing. The strategic nature of
decision support system acts as a guide for the companies which helps the analysts to overcome
with the trial and error problem to create an effective system. The decision support system helps
to reach at the final stage because the requirement can’t be predicted in advance. The system
should be altered so that the changes can be tracked in the problems, environment and user
because these three factors are inherently volatile in nature. The series of development cycle is
included in the functionality of decision support system. The system analyst and consumers are
main contributors in shaping the decision support system. The evolutionary development for the
decision support system is universally applicable. The decision support system project has the
objective to improve the decision making process for the managers who are decision makers of

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an organization. There should be clear understanding about the nature of the target decision task
and the strategy should be clear which supports the decision making process by the system
analysts. The main problem faced by the analysts is the conceptualization of the decision task
which requires the improvement during the repetition of evolutionary development process. The
strategies improvement is supported by the development methods of decision support system.
The decision support system is mainly about the improvement of decision making process. The
analyst should have the considerable knowledge about the decision support system and the
measures to improve the decision making (Arnott, D., 1998). The guidance is a very important
aspect according to the behavioral decision theory which is a theory of cognitive bias. The
general framework includes the method used for the research and designing which includes the
design science research method and frameworks. The theoretical aspect is included in the next
section. Then, taxonomy of cognitive bias is discussed.
The design science approach is used for the research which is the compliment to the natural
science approach. In the design science, the development and evaluation of Information
Technology related facts are discussed which intends to solve the organizational problems. The
controversies are addressed in the development of system and unit of analysis which is evaluated
in an organizational context. The main design process includes various steps such as: problem
awareness, development, suggestions, evaluation and draw a conclusion. Following figure shows
the research process:

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Source:
The decision support system theory has denominated by the process oriented model of decision
making which is linked with the Nobel Laureate. The design science is conceptualized to
improve the decision making at the time of evolutionary development of decision support
system. The integrated component of framework was composed in the Simons model which
defines the decision support system.
Evolutionary theory & DSS
The nature of decision support system can be retrieved from the evolutionary theory. The
evaluation in decision support system is ontogeny but the cross generation change is also
common. The change in generation is a higher version in the language of information system.
The variance between major and minor version is the problem of system analyst and the

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perception of users. The decision support system is made from the design process and the
evaluation of decision support system is done through artificial selection. In the process of
artificial selection the goal of every individual designer is same. The features are selected very
deliberately which helps to promote the goal among the generations. The goal of many decision
support systems is to support the decision making of managers. The bets mechanism of evolution
is adaption. The adaption decision support system occurs in the life of system version. Another
evolutionary agent is speciation which is the creation of one or two species from the common
stock. The decision support system is classified at the genera level which is a type of information
system at the family level (Sage, A.P., 1981). The decision support system taxon consists of
different species of decision support system. The Alter’s classification of decision support
system includes file drawer system, data analysis system, analysis information system,
accounting models, representational models, suggestion models and optimization models.
Present Approach
The decision support system is evolving by an iterative process of system design. Since the
inception of the filed the use has been central to the theory of decision support system. The
evolutive approach is not implemented in a parallel or linear fashion. The completion of each
evolutive cycle gets near to the final state. The evolution cycle should be continues because the
decision support system exist in continues change. The adaptive design framework includes
analysts, system and user. The cycle of adaptive cycle framework flow the information. The
system provides user learning to the user through personalized use and analyst evaluates the
system function and receives the pressure for evaluation. The analysts provide middle out design
to the user and receive the enabling of implementation. The model helps to understand the

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dynamics of decision support system. The approach is called as adaptive design. The decision
support system evaluation is seen as a learning process. (Silver, M.S.,1991)
Sources:
DSS evolution framework
The Decision support system evolution framework includes aetiology, tempo and lineage.
Aetiology is defined as the evolution causes. The lineage defines the position of evolution which
is between the applications or within the application. The tempo defines the evolution pattern
over the time. The lineage can be conceptualized at the application level of the decision task. The
occurrence of lineage can be thought either at the branching lineage or within an application.
Another perspective of decision support system evolution considers aetiology which triggers the
adaptive process and it directly leads to evolution. The factors can be exogenous or endogenous
with the decision making. The aetiology of decision support system includes cognitive and
environmental triggers. The cognitive triggers comprises of system use, peer interaction, analyst
interaction, training courses, consultant interaction and idle thoughts. The environmental triggers
include technology change, personnel change, mergers, industry change and co-evolution.

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According to the review of decision support system research, it is shown that the evolution is
necessary to compete with the constant change in the environment. (Courbon, J-C., Grajew, J. &
Tolovi, J, 1978).
Another Framework of DSS evolution
The framework is developed by combining the different lineages and aetiology yields. The
framework includes four main classes, namely, with cognitive trigger within the application,
with an environment trigger within an application, within a cognitive trigger between
applications, with an environment trigger between applications. The various patterns are
followed during decision support system evolution (Courbon, J-C, 1996).. The framework is
shown in the figure below:
Initiation cycles
The initiation cycle is developing when the need of new decision support system is realized or
major changes are required in an existing application. The need is realized when the decision

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support system require some improvements. If the debiasing strategy is used by the decision
support system then it is an ethical responsibility to tell the nature of strategy to the client. The
following figure shows the model of decision support system development (Fischhoff, B. &
Beyth-Marom, 1983):
Analyzing cycle
The framework of debiasing can be used in the decision diagnosis activity. It is the part of
unfreezing stage of Lewin-Schein model. The work of the analysis is based on the nature of
project. In this process the managers become accustomed and they are ready to consider the
cognitive biases. The step involves in the combined approach includes: prediction of existence
and the nature of potential bias. Then identify the impact and magnitude of bias. Then, considers
the alternative for reducing the bias and finally assure the user about the existence of bias.
Delivery cycle
It includes the parallel application and iteration of designs, user and system construction. The
cycle covers the stage of refreezing in the Lewin-Schein model. The decision support system
model can be used as the feedback and the training purpose.

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Research design
The system development process is the unit of analysis. The case study considers the details of
than a survey in the prediction of nature and important characteristics of the system development
process. The delta consulting is a service provider business firm which comprises of strategic
consulting, training, project management and IT development. The performance is reviewed by
the board of directors and external consultants. The recommendation includes the core activities
of strategic consulting and project management at the existing level. The recommendation
includes the requirement of training by showing the wound up in the training area and the
investigation of strategic alliance with the training specialist provider. The escalation approach is
used to analyze the effect of confirmation bias.
Reflection & Discussion
The first issue is related to the success of delta’s decision support system. It is difficult to
identify the problem in design research studies because after the research intervention it is not
possible. The identification of alternative intervention is conducted to know other intervention
which could be more successful. The success of the project is the main argument of the
managing director. The success is equated with the repetition of usage and satisfaction of the
user. The managing director has offered a bonus to the development team which is regarding the
success of the project. The case study is conducted to evaluate the use of design related facts at
the center of the design science project which uses the decision support system development
methodology which uses the cognitive bias theory as a construct of focusing. The development
process is effective and feasible.

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Arnotts’s Biases
Cognitive Biases
The cognitive biases are defined as the mental behavior which prejudices the quality of a
decision in the significant number of decisions. It is also known as decision biases. The cognitive
biases can be seen as predictable deviations from rationality. The rational choice is based on the
current assets of decision and based on the choice of decision makers. There are various
cognitive biases which are researched by the researchers of decision theory. There are total thirty
seven biases which are arranged by the taxonomy into the category of adjustment, statistical,
confident, presentation, memory and situational biases (Arnott, D., 2006). Memory biases
include the recall and storage of information. Statistical biases include the normal tendency of
humans to process the information which is contrary with the theory of probability. Cognitive
bias includes the increment of confidence in their area of specialization as a decision maker. The
decision maker has to find the new information related to the decision task. The presentation bias
explains that the bias should not be based on the display of information. It acts as the perceiving
of information which a significant bias for the decision is making process. The situation bias
includes how the respondent reacts on the particular situation and its decision which shows the
major bias from the perspective of decision makers. It is not important that every cognitive bias
create a discrete as the classification implies (Anderson, N.H.,1986). The two cognitive bias are
explained below with an example:
1. Memory biases:

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The memory biases are related to the recall as well as storage of any information. These biases
due to their functionality are usually seen to be the deepest level or the lowest level of the
cognitive biases. The memory biases include the following biases:
1. Hindsight:
"In retrospect the degree to which an event would have been predicted is usually overestimated."
For example, when the commentator hears a weird and unfamiliar result of the election he says,
“I had an inclination that he would win”, while turning of cards in a rummy game with our
friends, we usually claim, “I thought so”, when the information system stops due to ongoing
issues in it, the system analysts are seen to say “I already predicted this.” All the situations
mentioned above are the examples of Hindsight bias. Therefore this type of bias helps in
increasing the confidence of the people in their own decision making process and abilities.
However, they hinder him in reducing their ability to learn from the past experiences. In some of
the cases, we can say that this memory bias is related to the other memory biases and Testimony
when the occurrence of an event effects the recollection. The general heuristics given by Tversky
& Kahneman and its action might be responsible for causing Hindsight along with the new
information being highly vivid which results in overcrowding of the previous knowledge and
information or insufficient adjustment from the knowledge being received recently and there are
evidences which are consistent with the outcomes due to being highly accessible in our memory.
2. Imaginability: "An event will be judged more probable if it can be easily imagined."
When the human constructs an abstract model from the piece of their memory it results in
imaginability, For example, if an expedition is formed in order to investigate an unexplored area
then it gets difficult to imagine it and therefore the explore becomes very curious and serious and

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it is likely for the explorer to underestimate the accidents or mishaps that can that place.
Therefore, we can say that imaginability is some function of memory, experience and the
intellect of the person.
3. Recall: "An event or class will appear more numerous or frequent if its instances are
more easily recalled than other equally probable events."
The familiarity, vividness and the salience of an event to be recalled basically depends on the
ease of recall from the memory. When a person is asked about his primary school memories the
person automatically recalls the situation like being bullied by a senior in the schoolyard etc.
This incidence was although easy to recall but it cannot be regarded as a representative of the
school experiences. Various evolutionary reasons have been provided for the Recall bias
however the decision makes might be able to overweigh all the easily reminisced data and
information to towards detriment of new information or relevant and pertinent memories.
4. Search: "An event may seem more frequent due to the effectiveness of the search
strategy."
When a person attempts towards recalling an event or incidence or any other information, the
search is conducted in our mind which can bias the processing of recall. For an instance, when
asked are there higher number of words starting from ‘m’ as compared to the words where ‘m’ is
in the third letter? People might reply that words starting from m but that is not a correct answer.
Throughout their school experiences people experience every word in an alphabetical manner,
for example, a dictionary is listed sequentially for ease of search for the users. Therefore, people
find is easier to recall the words starting from “m”. However, according to the correct linguistic

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rule the consonants are present at the third position rather than being the first position in the
English word.
5. Similarity: The likelihood of an event occurring may be judged by the degree of
similarity with the 21 class it is perceived to belong to."
Anton is a singer. What is Anton like? Is he likely to be highly well-fashioned? Will he be
extrovert and confident? The answers to queries like this are usually subjected to the similarity
bias where a person is stereotypes and same is considered for him. Although in case of Anton,
his class (singer) is given but in a complex decision situation the perception towards the class of
the entity is also subjected to being biased.
6. Testimony: "The inability to recall details of an event may lead to seemingly logical
reconstructions which may be inaccurate."
This bias results from the cues on the basis of the factual information. The recall and testimony is
usually affected by how the question is being structured. When the automobile accidents are
related to the different speed estimates like (Hogarth, 1987): what was the speed of the car when
they got hit, how fast the cars were moving in the situation of collision, hat was the speed of the
car when they smashed into each other etc.
In case of misleading or complex questions being asked, the Testimony bias becomes the
strongest. Along with the Redundancy bias, the Testimony results in increased frequency of the
questioning or the retelling of the evidence.

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2. Confidence biases:
The confidence biases increase the confidence of a person and help the person to become a
decision makers. One of the most important aspect of this biases is the how the new information
is curtailed regarding a decision task.
1. Completeness:
"The perception of an apparently complete or logical data presentation can stop the search for
omissions."

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There are two major forms of the Completeness bias. The first form is the printed or verbal
presentation which is takes a definitive and covers all the consequences and aspects. Whereas
the second form is the display of believable or logical data display.
2. Control: "A poor decision may lead to a good outcome inducing a false feeling of control
over the judgment situation."
When a person understands the level of control, they have a complex issue. The feeling of
control of many clients have been manipulated by their psychotherapists so as to overcome the
various range of pathologies (Dawes, 1988). Therefore it is imperative to control over one’s life
the control is minimal so as to make an important decision and the outcome is thought to be
disastrous. For example, in the MIS departments various strategic plans are developed for
various applications and the management of IT is given to control to seek out the situation.
3. Confirmation: "Often decision makers seek confirmatory evidence and exclude search for
disconfirming information."
This bias is seen to act against one of the basic foundations of the scientific method that the
information which refutes any of the hypothesis is seen to be more valuable as compared to the
information which supports the hypothesis. For example, there is a debate going on between gun
control. Arthur is in support of the gun control and seeks out various new and pieces which
reaffirm the gun ownership and need for its limitations. Whenever he learns about the media
shooting, he interests them in a manner which are supporting his own existing beliefs.
4. Desire: "The probability of desired outcomes may be assessed to be greater than actually
warrants."

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The Desire bias is usually seen to be related to the Control bias but is not relatable to the past
experiences or the decisions made in past but it is usually related to our wishful thinking and the
importance of the outcome to the one who made the decision. The Control bias is more of a
subjective probability and is set higher than the objective probability. The people winning the
lottery, winning football team, getting a particular job are likely to overestimate success even if
they already have or have an access towards information which should abate all their desire. The
desire bias is seen to reduce the quality of the decision.
5. Overconfidence: "The ability to answer difficult or novel questions is often over-estimated."
The bias of overconfidence is a very common judgment pattern. Various experiments have
attempted to measure the degree of the meta-knowledge of the subject. This type of bias is highly
strong for various difficult questions in case when the domain is unknown towards the subject. It
has been seen that less overconfidence is seen in the experts than the naïve subject and even
show no overconfidence. It has been suggested by Russo and Schoemaker (1992),
overconfidence is a highly complex behavior which is usually caused by Confirmation, Recall,
Adjustment, Similarity, Hindsight biases along with motivational and physiological causes.
6. Redundancy: “The more redundant and voluminous the data the more confidence may be
expressed in its accuracy and importance."
When the people are seen to overestimate the occurrence or even the relevance of the data and
even event which is presented to these people in a repeated manner. This effect is used by the
sport coaches by telling their teams and athletes that they are the best and the greatest. This bias
is also seen to arise in a situation where various sources send the same text, might be due to

MANAGEMENT DECISION MAKING 20
some error. This bias is usually seen to arise in case of the high quantity of data being perceived
for presenting to the one making the decision.
7. Selectivity: "Expectation of the nature of an event can bias what information is thought
relevant."
For example, an experiment on selectivity by Bruner & Postman (1949) where they asked all
the people to look at various playing cards and then name those cards but in some cases the
cards were wrongly coloured like black ace of diamond. All the people were seen to
misreport the trick cards. For some people expecting a heart to be red is difficult but for
some people a black heart was impossible. Therefore, the selectivity bias usually excludes
all the data and information which is seen to be inconsistent with the experience of a person.
In some cases the selectivity bias is seen to exclude important information from the whole
process of decision making due to affiliation, education, trade or even profession of the
person.
8. Success: "Often failure is associated with poor luck and success with the abilities of the
decision maker."
Although the success bias is seen to be highly related to the Control bias but is also very
different from it. The situations were poor decision process are seen to have desirable outcomes
are addressed by the Control bias. Whereas the Success bias reflects the common behavior
pattern of making that the person making the decision is likely to have successful decision. But
the cases of failures are also dependent on various external factors like weather, competition,
luck and even timings.

MANAGEMENT DECISION MAKING 21
9. Test: "Some aspects and outcomes of choice cannot be tested, leading to unrealistic
confidence in judgement."
Usually the task and its nature prevents the evaluation of the outcome of any decision. People
are seen to overestimate their capabilities when the outcomes are not being tested. For example,
how good the staff is at the decision making. If it is performing well, it will be congratulated
every now and then. Due to evaluation of the panel’s performance the test bias will arise due to
their rationality and the candidates who were not successful at their interview session would also
be evaluated and assessed. The person who performs adequately in the office might be the
poorest candidate in the interviews. Therefore it can be concluded that the test bias does not
involves the observed relative frequencies but involves observed frequencies in the judgment.

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The debiasing framework is used to eliminate the bias from the decision maker’s cognitive
strategies. The aim of the framework includes the identification of existing and nature of
potential bias. It considers alternative means which helps in eliminating the bias. To evaluate and
monitor the effectiveness of debiasing technique which is selected for removing the bias. The
strategy of perfecting individuals is developed by fischhoff which attract the attention of decision
makers. The strategy explains the support given to an individual at each level which helps to
overcome the errors in an escalation design. Following are the steps involves in the escalation:
1. The warning is given to the decision maker for doing the bias without giving description of
its nature.
2. Explain the nature of bias which includes the direction and strength of bias.
3. The feedback should be given which includes the warning and type of bias with the reaction
of the decision maker to the bias for the target task.
4. The extended programme of training with the coaching, discussion and feedback is given
which helps to overcome the bias effect.
Conclusion
The decision bias theory considers the various possibilities of all the persistent and systematic
errors in almost all the phases of decision-making and judgment. Due to growing concern over
the decision support system and its uses. The basic concept of the decision bias holds a great
position towards the whole DSS and the analysts as it helps them to understand the nature of the
decision being taken and helps them to provide an insight on the DSS. The taxonomy being
developed has helped in making the researches highly accessible and are used a tool for stressing
focus on the biases that affect the decision tasks in the development processes. Additionally,

MANAGEMENT DECISION MAKING 23
various strategies for reducing the negative effects of the decision biases are required for having
an effective design of the DSS. General debiasing is involved so as to make sure that these biases
do not affect the target decision making in the systems development process.

MANAGEMENT DECISION MAKING 24
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