DECISION SUPPORT SYSTEM FRAMEWORK FOR FEASIBILITY
STUDY IN CONSTRUCTION PROJECT
NURJULIANA BT. MOHD NAZARI
A project report submitted in partial fulfillment of the
requirement for the award of the degree of
Master of Science (Construction Management)
Faculty of Civil Engineering
Universiti Teknologi Malaysia
June, 2007
iv
“ To my love ones…
Papa, Mama and Kakak…
To the important people in my life…
Abg. Azreen and Zati…
I appreciate all the love,
understanding and support from
each one of you…”
v
ACKNOWLEDGEMENTS
In writing and completing this research, I am indebted to many individuals and
organizations. Firstly, I would like to thank especially to my committed supervisor,
Dr. Arham Abdullah for the valuable guidance and time spent in advising me
through out the research. I also would like to express my sincere gratitude to Mr.
Nasafian, Mr. Mior Yunus and Mr. Abdul Rashid from the consultants firms, for all
their cooperation in providing valuable information and wisdom for this research. To
Ms. Nurfarhana and Ms. T. Syarifah Atifah, thank you for the tips and explanation
that are really helpful in understanding the computer’s jargons. I have a lot of
support from my friends, among others, Hana, Gui, Aniza, Amalina, Ain, Emma and
Azreen. I thank them all. Last but not least, thank you to other parties that may
involves in any way in helping me to finish this research.
vi
ABSTRACT
The construction projects present a unique situation where each project is different
with different situation and parties. One of the important stage involve in a
construction project is the preparation of the feasibility study. Feasibility study
needs a lot of information and the process to analyze the information is tedious and
time consuming. The decision support system (DSS) is an attempt to simplify the
analyzing process and to reduce the time needed in preparing the study. The aim of
this research is to proposed Decision Support System Framework particularly for
quantity surveying consultants to improve the effectiveness of the decision making
process. The objectives of the study are to identify the current practice of decision
making process in the feasibility study of construction project, to identify the DSS
that is able to improve the decision making process in the feasibility stage and to
develop a Decision Support System Framework for feasibility study. The
information gathered for the first and the second objectives mainly via interviews
and internet sources were used as a guideline to develop the framework. The
framework was developed based on the DSS identified during the second objectives.
The framework of the system provides terminology, concepts and guidelines that are
useful to apply the system. By understanding the factors considered for the study as
the area of application for the DSS, the type of DSS application are able to be
identified, that is the cost estimation DSS. Then, the requirement of the cost
estimation DSS identified that is the Crystal Ball are gathered to complete the
framework. The framework can be use as a guideline to develop the prototype of the
system and as a guide to apply the system.
vii
ABSTRAK
Sesebuah projek pembinaan adalah unik dengan setiap projek melibatkan keadaan
dan pihak yang berbeza-beza. Kajian kemungkinan merupakan salah satu peringkat
yang penting dalam sesebuah projek pembinaan. Kajian kemungkinan memerlukan
banyak maklumat serta proses untuk menganalisa kesemua maklumat tersebut rumit
serta memakan masa. Decision Support System (DSS) adalah satu langkah untuk
memudahkan proses menganalisa serta untuk membantu menjimatkan masa dalam
penyediaan kajian kemungkinan. Matlamat penyelidikan ini adalah untuk
mencadangkan Rangka Kerja Decision Support System khususnya untuk perunding
juruukur bahan untuk meningkatkan keberkesanan proses membuat keputusan.
Objektif penyelidikan ini pula adalah untuk mengenalpasti praktis semasa proses
membuat keputusan dalam penyediaan kajian kemungkinan untuk projek
pembinaan, untuk mengenalpasti DSS yang dapat menambah baik proses membuat
keputusan dalam penyediaan kajian kemungkinan serta untuk membina Rangka
Kerja Decision Support System untuk kajian kemungkinan. Maklumat yang telah
didapati bagi objektif pertama dan kedua yang diperolehi melalui temuduga serta
bahan daripada internet telah digunakan sebagai panduan untuk membina rangka
kerja tersebut. Rangka Kerja tersebut memberikan terma, konsep dan panduan yang
berguna untuk mengaplikasikan sistem ini. Dengan memahami bahawa faktor-faktor
yang terlibat dalam kajian kemungkinan sebagai satu keadaan dimana DSS boleh
diaplikasikan, jenis aplikasi DSS yang sesuai dapat ditentukan iaitu cost estimation
DSS. Kemudian, maklumat mengenai keperluan bagi cost estimation DSS yang telah
dikenalpasti iaitu Crystal Ball dikumpul untuk melengkapkan rangka kerja ini.
Rangka kerja tersebut dapat digunakan sebagai panduan untuk membina prototaip
bagi sistem ini serta sebagai panduan untuk mengaplikasikan sistem ini.
viii
CONTENT
CHAPTER
CHAPTER I
TITLE
PAGE
TITLE
i
SUPERVISOR DECLARATION
ii
STUDENT DECLARATION
iii
DEDICATION
iv
ACKNOWLEDGEMENT
v
ABSTRACT
vi
TABLE OF CONTENT
viii
LIST OF TABLES
xii
LIST OF FIGURES
xiii
LIST OF APPENDIX
xiv
INTRODUCTION
1.1
Introduction
1
1.2
Problem Statement
2
1.3
Background
3
1.4
Aim and Objectives
5
1.5
Scope and Limitation
5
1.6
Importance of Study
5
1.7
Expected Finding
6
1.8
Structure of Research
7
ix
CHAPTER II
LITERATURE REVIEW
2.1
Introduction
9
2.2
Decision Support System
9
2.2.1
Decision Making and Decision
Support System (DSS)
2.2.2
Decision Making In
Construction Management
2.2.3
2.2.6
14
Characteristics of Decision
Support Systems (DSS)
2.2.5
12
Research on Development
Of Decision Support System
2.2.4
11
16
Architecture of Decision
Support System (DSS)
17
Database Management System
18
2.1.6.1 Data Sources
19
2.1.6.2 Data Warehouses and
Software Agents
2.2.7
20
Model Base Management System
21
2.1.8.1 Types of Model
21
2.2.8
User Interface
22
2.2.9
Message Management System
23
2.2.10 Types of Decision Support Systems
24
2.2.11 The Advantages and Disadvantages
of Decision Support System
2.3
28
Feasibility Study
33
2.3.1
Introduction
33
2.3.2
Preparation of Feasibility Study
36
2.3.3
Considerations for Feasibility Study
37
2.3.3.1
Economic Analysis
37
2.3.3.2
Technical Analysis
41
2.3.3.3
Financial Analysis
46
x
CHAPTER III
RESEARCH METHODOLOGY
3.1
Introduction
3.1.1
First Stage: Introduction Of
The Research Field
3.1.2
3.3
CHAPTER IV
52
Third Stage: Analysis And The
Interpretation of Data and Information
3.2
50
Second Stage: Data And
Information Collection
3.1.3
50
53
Research Method
53
3.2.1
Literature Review
53
3.2.2
Document Analysis
54
3.2.3
Semi-Structured Interview
55
Framework Methodology
56
RESULT AND DISCUSSION
4.1
Introduction
57
4.2
Respondent Profile
57
4.2.1
Company A
57
4.2.2
Company B
58
4.2.3
Company C
59
Interview Analysis
59
4.3
4.3.1
Feasibility Study Decision Making
Process and the Factors Considered
66
4.4
DSS Application: Cost Estimation
71
4.5
Suggested Cost Estimation DSS
72
4.5.1
Spreadsheet-Based DSS
74
4.5.2
Crystal Ball
76
4.5.3
Crystal Ball 7 Standard Edition
77
4.5.4
How Does Crystal Ball
Enhance Excel
77
xi
4.5.5
System Requirements
79
4.5.5.1 About Microsoft
.NET Framework
4.6
80
Tools and Function of Crystal Ball
81
4.6.1
Defining an Assumption
82
4.6.2
Defining a Forecast
85
4.6.3
Running a Simulation
86
4.6.4
Using the forecast chart
87
4.6.5
Using the sensitivity Chart
88
4.6.6
Creating a Report
88
4.6.7
Others Features available
89
with Crystal Ball.
CHAPTER V
4.7
The Framework
90
4.8
Conclusion
93
CONCLUSION AND RECOMMENDATION
5.1
Introduction
94
5.2
Conclusion
94
5.3
Problems Encountered During Research
96
5.4
Suggestion on Further Research
97
References and Bibliography
Appendix
98
103
xii
LIST OF TABLES
NO.
TITLE
PAGE
Table 4.0
Semi-structured Interview Questions and Answers
60
Table 4.1
Exclusions of Construction Cost For Estimating
70
Table 4.2
DSS Software and the Description
74
xiii
LIST OF FIGURES
NO.
TITLE
PAGE
Figure 2.0
Feasibility Stage in the Development Process
33
Figure 3.0
Research Methodology
51
Figure 4.0
Decision Making Process of Feasibility Study
67
Figure 4.1
The Usage of Crystal Ball in Industries and their
Applications
76
Figure 4.2
Crystal Ball added tools in Microsoft Excel
78
Figure 4.3
Crystal Ball New Menus Function
79
Figure 4.4
Crystal Ball System Framework
82
Figure 4.5
Distribution Gallery Window
83
Figure 4.6
Define Assumption Window
84
Figure 4.7
Define Forecast Window
85
Figure 4.8
Run Preferences Window
86
Figure 4.9
Forecast Window with Statistics and
Percentile Function
87
Figure 4.10
Sensitivity Window
88
Figure 4.11
Create Report Window
89
Figure 4.12
Decision Support System Framework for
Feasibility Study
92
xiv
LIST OF APPENDIX
NO.
Appendix 1
TITLE
Interview Question
PAGE
103
CHAPTER I
INTRODUCTION
1.1
Introduction
Good decision making is imperative for organizations to survive. In order for good
decision making to occur, the proper steps must be taken to ensure accurate
information used. Decision Support System (DSS) is a computer-based system that
is designed to aid decision makers in making decision that may include multiple
attributes, objectives and goals (Cascante et al, 2002). Good decision making tools
are necessary to make good strategic decisions. The framework of the system will
provides terminology, concepts and guidelines that are useful to apply the system.
A Feasibility Study report is a business plan for a specific development
project. It provides the rationale and the support for that rationale to pursue a
specific development project from the feasibility phase, pre-construction,
construction and occupancy through investment management.
It offers a
comprehensive format that emphasizes the justification of the project relative to the
target market’s needs and wants, and a thorough risk analysis with appropriate
mitigations.
A feasibility report is dynamic and should as often as necessary to
incorporate any changes to assumptions or to incorporate new information. As a
result, all assumptions made and external dependencies specified in the feasibility
study are meticulously documented. The report is prepared in close consultation
2
with the client (in addition to an architect and other construction consultant) since
some of the work included in the report most likely has already been completed by
the client or his consultants, that is, the idea or vision for the project or the market
study.
1.2
Problem Statement
In order to effectively and efficiently practice decision making, decision support
system (DSS) have been used in some of the phases of the decision making process.
Decision support system are systems under the control of one or more decision
makers that provide an organized set of tools to impart structure to portions of the
decision-making situation and to improve the ultimate effectiveness of the decision
outcomes. The construction project present a unique situation to those involved in
managing the construction process (Barton, 1985).
Each project is different from
all others, with different situation involving a large number of different
organizations and individuals, all of whom have different and often conflicting
priorities and objectives.
There are several estimates and predictions must be made which attempt to
forecast the future.
Inevitably the forecasted value will deviate from the actual
outcome, due to a lack of complete information about future events. The feasibility
study is also providing the forecasted value and may involve with uncertainty. The
many contributing factors to the construction problem are referred to collectively as
uncertainty. According to a noted engineering expert and member of the National
Committee of the Chinese People's Political Consultative Conference (CPPCC)
stressed the necessity of strengthening feasibility study of major construction
projects in order to improve their return on investment. As a source of analysis and
recommendations, a feasibility study is an important tool that investors can rely on
to help them make management and development decisions.
3
Where there is uncertainty as to which events might occur, the logic of the
decision process should include the necessary information. Feasibility study needs
a lot of information and the process to analyze the information is very tedious and
consumed a lot of time.
The DSS is an attempt to simplify the analyzing process
and to reduce the time needed in preparing the study.
1.3
Background
A Decision Support System (DSS) is defined as an interactive system that provides
the user with easy access to decision models and data in order to support semistructured and unstructured decision making tasks (Watson et al, 1997). The user is
typically a manager or a staff professional. A key part of the system is the software
interface that makes the system easy to use.
The system contains models that are
used to analyze data. Data are maintained to be used in the analysis. According to
Steven Alter (1977), any application that provides information that supports decision
making is DSS, even systems that only provide access to data. Thus, the absence of
model component does not preclude its classification as a DSS.
Building on the capabilities of Management Information System, DSS are
reoriented to produce information to support specific decision processes. There is a
human/machine interface where these two components of decision processes are
operating interactively to produce quality decisions. The DSS will be using Monte
Carlo simulation that is a sophisticated form of what-if analysis as a model of
decision making. Monte Carlo simulations help to manage risk and simulate
complex systems.
They are best for modeling uncertainty and volatility.
Monte
Carlo simulation allows user to replace point estimates with fuzzy values that reflect
the uncertainty. This helps user to characterize the range of potential outcomes in a
situation and assess the probability of reaching specific targets. Like decision trees,
Monte Carlo simulations result in an expected value that aids in choosing the most
attractive course of action.
They also provide information about the range of
outcome, probability of reaching specific targets, most likely outcomes, etc.
4
The feasibility study processes covers various aspect and among them that
usually being considered are the economic analysis, technical analysis, financial
analysis and the environmental assessment.
The economic analysis will consider
the market or demand analysis that would provide estimates on the benefits or
revenue derived from the project whilst the technical analysis would provide the
physical requirements (site, machinery and equipment, building and construction)
and hence the cost of the project. The next step is the financial analysis that would
compare the benefits or revenue of the project with to its corresponding cost to
determine whether benefits or revenue is more than the cost.
However, the
financial analysis provides only the net benefits attributable to the project but does
not assess the impact of the project on the economy as a whole.
It is also without any doubt that projects would have either a positive or
negative effect on the environment. If the effects are negative (such as air and
water pollution, land erosion, depletion of fish stock, etc.), it would not only
incur costs for any corrective actions but also result in a negative impact on the
quality of life.
With the rapid pace of economic development, the environmental
impact assessment is essential to prevent environmental problems.
It should be
noted that due to the specific characteristics of the different types of projects
(agricultural, industrial, infrastructure, social projects), the techniques outlined in
this research will serve as guides only.
5
1.4
Aim and Objectives
The aim of this research is to proposed Decision Support System framework
particularly for construction consultants that involves in preparing the feasibility
study in order to improve the effectiveness of the decision making process.
The
objectives of the study are listed as follows:-
1. To identify the current practice of decision making process in the feasibility
study of construction project in an organization.
2. To identify the Decision Support System that is able to improve the decision
making process in the feasibility stage.
3. To develop a Decision Support System Framework for feasibility study.
1.5
Scope and Limitation
The research will be limited to the construction consultants firm which involved in
preparing the feasibility study. Since there are several factors considered for the
feasibility study, the factors considered for this research are those that are considered
by consultants whose been interviewed. The extent of knowledge acquisition was
limited by time constraint.
1.6
Importance of Study
The framework of Decision Support System is useful as a guideline to the
professionals to apply the system to enhance the decision making process for the
purpose needed. It is important in the state of the world today that demanded better
decision making by professionals (Jones, 2006). There are believes that decision of
improved quality can still be obtained by improving the process of decision-making.
DSS is a tool to enhance the performance of decision maker/professional as they
6
helped them to gain more knowledge, experience and expertise and consequently
enhance as well as improving the quality and the process of the decision making
(Irtishad, 1990).
The feasibility studies help development owners, investors and lenders make
informed decisions by providing critical information about a specific concept or
project, such as new construction, redevelopment or renovation of an existing
property, or reuse of underutilized or abandoned facilities.
Because a feasibility
study provides specific and organized information about a development project, a
comprehensive feasibility study is a crucial part of the development process.
It
outlines investors, end users, government, community and the developer about a
project’s operations and goals.
The importance of a comprehensive, thoughtful
feasibility study cannot be overemphasized. Much of the project's success hinges
on it.
The DSS is an attempt to aid and support the decision making during the
feasibility stage.
1.7
Expected Finding
The expected findings are being made based on the objectives to be achieved. The
current practice of decision making process involved during the feasibility stage may
considered certain factors as a basis of the decision made. The considered factors
have to be supported by analyzed information that may be prepared in a complex
way. DSS may improved the decision making process in providing more efficient
analyzing approach.
A suitable DSS that are available in the market will be
proposed even the use is not very common in the construction industry.
The
requirement of the framework will be identified and the framework develop are hope
to improve the decision making process during the feasibility study.
7
1.8
Structure of Research
This research is divided into five chapters as follows:-
a) Chapter I : Introduction
This chapter discussed briefly on the introduction to the research topic that are
the decision support system and feasibility study in construction industry. This
chapter furthermore outlined the problem statement, background, aim and
objectives, scope and limitation for this research, the importance of this research
and as well as the expected findings for this research.
b) Chapter II : Literature Review
In this chapter, the literature review is discussed in detail. The discussion focuses
on the two main elements of this research as stated earlier that are the decision
support system and feasibility study in construction industry. The literature is on
the concept and the detail description on the decision support system and the
theory and guideline for the feasibility study.
c) Chapter III : Research Methodology
For this chapter, the research methodology of this research is explained. The
methodology consists of the methodology for the whole research and the
framework methodology. It have outlined in several stages on what need to be
done, how it would be done and what information needed for this research in
order to ensure the achievement of the research objectives.
d) Chapter IV : Result and Discussion
This chapter has presented the result of this research based on the determined
objectives to be achieved. It has clarified on the data and information collection
and their analysis. In achieving the objectives, the findings, that are the current
8
practice of decision making for feasibility study, the suitable DSS for feasibility
study and the DSS framework for the study are explain and discussed.
e) Chapter V : Conclusion and Recommendation
This chapter discussed the conclusion for this whole research, the problem
encountered during the research, recommendation for the result and suggested
some idea for further research.
CHAPTER II
LITERATURE REVIEW
2.1
Introduction
This chapter will discuss on the two important components of this research that are
the decision support system and the feasibility study. The discussion will elaborate
on the theory of the two components with some explanations based on the literature
review.
2.2
Decision Support System
The use of information technology to support decision making and problem solving
continues to advance. Decision Support System (DSS) have evolved significantly
since their early development in the 1970. During the 70s and 80s, the concept of
DSS grew and evolved into full field of research, development and practice. DSS
was both an evolution and a departure from previous types of computer support for
decision making.
Management Information System (MIS) provided scheduled report for welldefined information needs, demand reports for ad hoc information request and the
ability to query a database for specific data.
Operations Research/Management
Science (OR/MS) employed mathematical models to better analyze and understand a
specific problem.
Each was lacking some of the attributes needed to support
decision making such as focus, development methodology, handling of managerial
10
data, use of analytic aids and dialog between user and system.
The DSS have
evolved at the intersection of trends in data processing and management science
modeling to play an important role in the overall mission of information system in
organizations.
The DSS initially defines the nature of computer-based systems to assist
decision makers with ill-structured problems (Watson et al, 1997).
Over the past
two decades, DSS has taken narrower definition while other systems have emerged
to assist specific kind of decision makers, faced with specific kinds of problems.
These so-called ‘support system’ have many concept and principles in common, yet
they vary in the kind of user to be supported, nature of the task, kinds of technology
used, and methodology of development.
They are among the most important and
valuable type of computer based system, because they increase the efficiency and
effectiveness of upper level information workers who tend to be highly paid. Thus,
the ability to build, develop, install and use these systems generates higher
productivity increases and business value than more traditional transaction
processing or reporting system.
Gorry and Scott Morton (1971) have explored the concept of structure in
decision making in their paper.
They developed a matrix which showed the
interaction between the level of management and the amount of structure in the
decision making done at each level. As the level of management increases from the
operating management to executive levels, the decision making process become
semi-structured, then unstructured.
The thrust of their argument was that
management science models were effective for structured decision making, but
decision makers needed tools and technology to assist them in dealing with semistructured or unstructured problems.
11
2.2.1
Decision Making and Decision Support System (DSS)
Decision making is a process that involves a variety of activities, most of them
dealing with the handling of information (Watson et al, 1997).
By understanding
the dynamics of the process, the decision makers can make decision more effectively
and efficiently (Jones, 2006).
It is considered to consist a set of steps or phases
which are carried out in the course of making decision.
The process can be
conceptualized as consisting of intelligence, design and choice phases (Simon 1960).
Intelligence involves the identification of a problem that requires a decision,
and the collection of information relevant to the decision.
Design involves the
creation and evaluation of alternative courses of action. The decision makers may
speculates the possible outcomes based on each of the alternatives.
The possible
outcomes are then reviewed in terms of the organization’s purpose (Holsapple and
Joshi, 2001).
Choice is the selection of a course of action. There may not always be clear
choice.
Several of the alternatives may return similar outcomes or there may be
instances when none of the alternatives seem to satisfy the decision maker. At this
point, the decision maker can either make the choice based on what is presented or
choose to return to one of earlier stages to reformulate new alternatives or additional
information.
According to Jones (2006), there is a fourth phase that is implementation.
Once the alternative has been chosen, the next step is to implement or put the choice
into action.
This may include alerting effected individuals of what is to be done
next or simply reporting which alternative has been selected. The decision making
process actually culminates with implementation.
The difference in nature of decision making have been commonly noted to
include such dimensions as decision structure (structured/unstructured), source of
12
information (internal/external), accuracy of information (deterministic/probabilistic,
present/future) and scope of decision (narrow or broad).
Sprague (1980) defines
DSS as computer-based systems that help decision makers confront ill-structured
problems through direct interaction with data and analysis models.
Each part of this definition has a key concept that contributes to the unique
character of DSS. DSS are computer-based systems which add to the many other
approaches and tools that decision makers can use to assist in decision making tasks.
DSS help decision makers in terms of they often do not deliver an optimum answer.
In fact, they may be no optimum because these are ill-structured problems and
situations so decision must evolve through the interaction of decision makers with
resources such as data and analysis models.
Current DSS can be viewed as
computer-based system that lie at the intersection of two major evolutionary trends
that are data processing which has yielded a significant body of knowledge about
managing data and management science which has generated a significant body of
knowledge about modeling.
2.2.2
Decision Making in Construction Management
The construction project present a unique situation to those involved in managing
the construction process.
Each project is different from all others, and must be
carried out at a different location each time.
The project must be formulated and
executed by integrating the efforts of a large number of different organizations and
individuals, all of whom have different and often conflicting priorities and
objectives (Barton, 1985). The manager of the process must consider and assess
different technologies and alternative combinations of labour and equipment.
Estimate and predictions must be made which attempt to forecast the future.
Inevitably the forecasted value will deviate from the actual outcome, due to a lack of
complete information about future events.
The many contributing factors to the
13
construction problem are referred to collectively as uncertainty. Hypothesis of the
global uncertainty can be subdivided into two major components, namely variability
in the performance of a task, and interference from outside the task which frustrates
its progress.
When making decisions, managers cannot be certain of good outcomes,
because they cannot completely control external events nor have total foresight.
Therefore, management should try to increase the probability of good outcomes by
making good decisions. Where there is uncertainty as to which events might occur,
the logic of the decision process should include that information.
There is a basic need to be able to quantify and assess the impact that
uncertainty can have on a project, and to incorporate this knowledge in the project
brief and the management of the project.
This expanded awareness of the project
gives executive management and the client a more complete view of the project and
a basis for decision making.
It provides a much higher quality of information on
which to base a decision, and allows an assessment of both uncertainty and risk
while incorporating the manager’s own value judgment into the decision.
The use in the simulator model of variability as a component of uncertainty
is based on the factual observation of the construction process. However, neglect of
this factor is often proposed by texts of ‘classical’ network analysis, with statement
such as only occasional construction project will have variances in activity
durations, while observation of the construction operation leads to the conclusion
that it is pervasive and very large.
Variability can be defined as the range and
frequency distribution of possible durations in the execution of a particular task.
As well as an awareness of uncertainty, a manager requires a management
tool to use in quantifying and assessing the impact this uncertainty may have on the
project. The manager must aware of the effect uncertainty may have so that he may
make a rational decision as to what level of risk to accept in the light of the
circumstances at the time.
A management tool incorporating uncertainty will not
14
make decision making easier but it will present more and better information than is
currently available on which to base decision and, therefore, arguably improve the
possibility of a good decision.
The technique which is employed to form a
management tool to use in an uncertain environment, to augment the decision
maker’s intuition and experience, is simulation. Simulation is also referred to as the
Monte Carlo technique.
The implementation of a Decision Support System (DSS) in the construction
industry involves many variables. The nature of the problem to be solved is the key
factor, but the methodological approach to the problem, the DSS technique and the
nature of the data available must be considered. A rigorous content analysis was
conducted by Bastias and Molenaar (2005) on over one-hundred journal articles
spanning over thirty years from the Journal of Construction Engineering and
Management published by the American Society of Civil Engineering (ASCE). Five
different taxonomies were applied to analysis the nature of the problem, decision,
complexity, data-system and tool-technique. The findings show that DSS are mostly
static, unstructured, and model-centric, and that simulation and suggestion
techniques are the most used for the industry. In general, there are many ways of
solving DSS problems in the construction industry, but the decision maker must
strive to find the best solution for each specific problem.
2.2.3
Research on Development of Decision Support System
Several decision support systems have been developed specifically for construction
management (Nadkarni, 2000).
DBID: DSS for Bidding in Construction is an
analogy based decision support system, which assists contractors in preparing
competitive bids for building projects (Moselhi, et. al 1993). This DSS uses neural
networks to help determine the optimum markup for new bids based on past projects
in Canada and the United States.
The neural networks are able to predict, the
uncertainty in the assessment of the contractor of the project risks is accounted for
by a sensitivity analysis performed using the Monte Carlo simulation technique
15
which produces a measure of a probability of winning the bid at any desired level of
markup.
COMPASS, a decision support system designed by Hastak, Halpin and
Vanegas (1996), is used for project cost control strategy and planning. Throughout
the lifecycle of project, a COMPASS methodology assists management in
identifying attributes such as management errors, regulatory approval, and
error/rework that may cause potential project cost escalation. Furthermore, it also
assists management in formulating a cost control strategy for the project.
COMPASS methodology allows constructors to utilize their experience, and past
project performance data, to evaluate the probable escalation in the estimated project
cost and in formulation a cost control strategy.
In 1994, Kahkonen had developed an interactive decision support system for
building construction scheduling.
This DSS provides support for decisions made
during early planning stages and helps define the logic of the plan. This DSS can
also help in managing activity dependencies in the preparation of schedules.
Next is the Activity Duration Decision Support System (ADDSS) that
evaluates the impact of different factors on activity durations. The ADSS employs
fuzzy modus ponens deduction (FMPD) techniques to assess the impacts of duration
factors on activity durations.
These factors, which in the past were interpreted in
linguistic values, are quantified into numerical values using angular fuzzy act theory.
These numerical values are used to modify the activity durations affected by the
cumulative impact of different site, climatic, resource, and management factors. A
scheduler needs to provide information regarding each affecting factor to the
ADDSS.
In return, ADDSS will furnish the scheduler with an assessment of the
optimistic and pessimistic durations of an activity (Wu and Hadipriono 1994).
In 1996, a decision support system was develop to help with decision related
to the preservation of the civil infrastructure.
The DSS provide assistance for
decisions concerned with the three main tasks of infrastructure maintenance and
16
rehabilitation:
symptom
identification.
observation
condition
diagnosis,
and
treatment
The architecture of the system consists of knowledge bases,
database, analysis programs, and various interfaces (Shen and Grivas 1996).
A Decision Support System called DS^2 was developed to assist with
decisions related to the construction of drilled shafts.
DS^2 can reduced
construction cost by providing expert advice that would otherwise be both difficult
and very expensive to obtain. DS^2 is composed of three prototype expert systems
that interface with spreadsheet, database, and graphics packages.
DS^2 uses a
heuristic, rule-based, backward chaining system to analyze geological information,
suggests a construction method, prepares a preliminary cost estimate, and suggests
key specification items (Fisher, et. al 1995).
2.2.4
Characteristics of Decision Support Systems (DSS)
Fundamentally, the main thrust of DSS is on decisions in which there is a sufficient
structure for computer and mathematical models to be of value, but where the
judgment of the manager is essential. The following are the characteristics of DSS
(Nadkarni, 2000):
a) Broad-based approach to supporting decision making-accent on
‘management by perception’. Human/machine interface where human
retains control over the decision making process
b) Support decision making for solving structured, semi-structured and
unstructured problems
c) Utilization of appropriate mathematical and statistical models
d) Query capabilities to obtain information by request (ad-hoc report, ‘whatif scenarios’) – interactive mode
e) Output directed to organization personnel at all levels
17
f) Integrated subsystems
g) Comprehensive data base
h) Easy-to-use approach
i) Adaptive system over time
2.2.5
Architecture of Decision Support System (DSS)
A DSS consist of two major sub-systems that is human decision makers and
computer systems. The function of a human decision maker as an element of DSS
is not to enter data to build a database, but to exercise judgment or intuition
throughout the entire decision making process.
The first step of decision making
process begins with creation of decision support model, using an integrated DSS
program or DSS generator such as Microsoft Excel and Microsoft Access. The user
interface sub-system or dialog generation and management system is the gateway to
both database management system (DBMS) and model-based management system
(MBMS).
Prior to above mentioned sub-systems, Vicki Sauter (1997) discuss the subsystems as four components of DSS as follows:-
1) Database Management System
2) Model-Base Management System
3) User Interface
4) Mail Management System
18
2.2.6
Database Management System
The Database Management System (DBMS) provides access to data as well
as all of the control programs necessary to get those data in the form appropriate for
the analysis under consideration, without the user programming the effort. It should
be sophisticated enough to give users access to the data even when they do not know
where the data are physically located. In addition, the DBMS facilitates the merger
of data from different sources.
Again, the DBMS should be sufficiently
sophisticated to merge the data without explicit instructions from the user regarding
how one accomplishes that task.
In other words, DBMS are a set of computer programs that create and
manage the database, as well as control access to the data stored within it.
The
DBMS can be either an independent program or embedded within a DSS generator
to allow users to create a database file that is to be used as an input to DSS. It is
primarily concerned with managing a large amount of data physical storage such as
hard disks and creating, updating and querying databases in an optimal way.
DBMS is a necessary function primarily useful in the intelligence stage of
decision making process, but not sufficient to support design and choices stages of
decision making process. To adequately support these stages, DSS should be able
to include the following activities: projection, deduction, analysis, creation of
alternatives, comparison of alternatives, optimization and simulation (Sprague and
Carlson, 1982).
In performing these essential tasks, DSS utilizes many types of
management science or operation research.
They include linear programming,
integer programming, network models, goal programming, simulation and statistical
models and spreadsheet modeling. All these model are stored in the model base.
Data base management is an important component of DSS because of the diversity
of the data that is required (Nadkarni, 2000).
19
2.2.6.1 Data Sources
Apart from the DBMS, a sub-component that needs to be considered is the
data sources.
Data play an important role in a DSS.
Data are either accessed
directly by the user or are an input to the models for processing. As the importance
of DSS has grown, it is becoming increasingly critical for the DSS to use all the
important data sources within the organization, and from external sources also.
Indeed the concept of data sources must be expanded to information sources,
moving beyond traditional access to database records, to include document
containing concept, ideas and opinions that are so important to decision making.
To characterize the full scope of information sources relevant to DSS, and to
explore some of its ramifications, it is helpful to consider four types of information.
There are as follows:-
1)
Internal record based information
2)
Internal document based information
3)
External record based information
4)
External document based information
Basically, there is the record based information and document based
information which further divided into internal and external.
The internal record
based information pertains primarily to entities, such as individual employees,
customers, parts or accounting codes. Well-structured data records are use to hold a
set of attributes that describe such entity. The internal document based information
pertains primarily to concept, ideas, thoughts and opinions.
Less structured
documents or messages, with a wide variety of information forms, are used to
describe these.
Whereas the external information based information has focus of intention of
information systems because that is the type of information computer-based
application systems generate and manage easily. External record base information
20
has become more popular recently in the form of public database; end user
themselves have generally handled the procurement of these data, often using
outside time-sharing services.
Until recently, practically no attention has been
given by DSS builders or vendors to document-based information, either internal or
external, as an information resource for DSS.
Those areas have been the
responsibility of either the administrative vice president or corporate library.
2.2.6.2 Data Warehouses and Software Agents
There are one more sub-components that need to be considered for DBMS that is
data warehouses and software agents.
Separate database for decision support
applications are being developed through the creation of data warehouses.
These
are special database that are designed to allow decision makers to do their own
analysis. There are also sometimes referred to as information databases. With the
typical data warehouse, needed data are first extracted from mainframe and other
databases. Prior to be placed in the data warehouse, the data is processed to make
them more usable for decision support. The data are then maintained on a file
server, and special purpose software is often used to support DSS activities better.
Very popular are multi-dimensional databases that provide fast response times for
complex queries against large files. End users then employ yet more specialized
software to do their own decision analysis.
Even though decision makers are better equipped than ever before to analyze
the vast quantities of data stored by organization, this is increasingly being
recognized as not being good enough, because important information is often
available only when actively sought. Important developments may go undetected
because no one was looking for them. In response to these problems, vendors now
offer software agents which continually send queries to databases in order to find
exceptional conditions.
When one is found, it is automatically sent to the
appropriate person, often through e-mail. They reflect an exciting integration of
artificial intelligence capabilities into decision support.
21
2.2.7
Model Base Management System
The Model Base Management System (MBMS) performs a similar task for
the models in the DSS.
It keeps track of all the possible models that might be run
during the analysis, as well as controls for running the models. This might include
the syntax necessary to run the jobs, the format in which the data need to be put
prior to running the model (and to put the data in such a format), and the format in
which the data will be in after the job is run.
The MBMS also links between
models so that the output of one model can be the input into another model.
Further, the MBMS provides context-sensitive assistance to help the user question
the assumptions of the models to determine if they are appropriate for the decision
under consideration.
In simple expressions, MBMS is a set of computer program embedded
within a DSS generator that allows user to create, edit or restructure, update and/or
delete a model. The modeling component gives decision makers the ability to
analyze the problem fully by developing and comparing alternative solutions. Users
may create models and associated database files to make specific decisions.
The
created models and database are stored in the model base and database in the direct
access storage devices such as hard disks.
2.2.7.1 Types of Model
In order to understand the MBMS, the types of models that provide the analysis
capabilities for a DSS need to be addressed. There are many different types of
models and various ways that they can be categorized. Important distinctions can be
made on the basis of their purpose, treatment of randomness and generality of
application.
22
The purpose of a model can be either optimization or description. An
optimization model is one that seeks to identify points of maximizing or
minimization. Next is the descriptive model. It describes the behavior of a system.
In a sense, any model that is a descriptive model if it is a valid representation of
reality. But a descriptive model describes only the system’s behavior; it does not
suggest optimizing conditions.
Regarding randomness, nearly all systems are probabilistic. That is the
behavior of the system cannot be predicted with certainty because a degree of
randomness is present. A probabilistic model attempts to capture the probabilistic
nature of the system by requiring probabilistic data inputs and by generating
probabilistic outputs. Even though most systems are probabilistic, most
mathematical models are deterministic. Deterministic models employ single valued
estimates for the variables in the models and generate single valued outputs.
Deterministic models are more popular than probabilistic ones because they are less
expensive, less difficult, and less time consuming to build and use, and they often
provide satisfactory information to support decision making.
In terms of generality of application, a model can be developed for use with
only one system that is custom-built model, or a model may be applicable to many
systems that are ready-built models. In general, custom-built models describe a
particular system and, consequently, provide a better description than a ready-built
model. However, they are generally more expensive for the organization because
they have to be built ‘from the ground up’.
2.2.8
User Interface
From the user’s viewpoint, the user interface subsystem is the only part of
DSS components with which they have to deal. Therefore, providing an effective
user interface must take several important issues into consideration, including choice
of input and output devices, screen design, use of colors, data and information
23
presentation format and the use of different interface styles. As the name suggested
the user interface represents all the mechanisms whereby information is input to the
system and is output from the system.
users request data and models.
It includes all the input screens by which
In addition, it includes all the output screens by
which users obtain the results. Many users think of the user interface as the real
DSS, because that is the part of the system they see.
Nowadays, the decision support system generator provide the user with a
wide variety of interface modes such as menu based interaction mode, command
language style, question and answers, form interaction, natural language processing
based dialog and graphical user interface (GUI). GUI use icons, buttons, pull-down
menus, bars, boxes extensively and have become the most widely implemented and
versatile type. The interface system allows user to create, update, delete databases
files and decision models via DBMS and MBMS. It also provides a variety of input
and output formats. The formats include multidimensional color graphics, tables and
multiple windows on screen.
2.2.9
Message Management System
Whereas there is general agreement of the existence of the first three
components of a DSS, there is a fourth, relatively new component of a DSS, referred
to as the mail or Message Management System (MMS). This component allows for
the use of electronic mail as another source of data, modeling, or general help in the
decision making process.
Since electronic discussion groups, electronic mail
among workers, and other resources are quickly becoming an important resource to
decision makers, they need to be managed and integrated as do other components of
a DSS if they are to be a resource for decision making.
DSS provides a framework through which decision makers can obtain
necessary assistance for decision making through an easy-to-use menu or command
system. Generally, a DSS will provide help in formulating alternatives, accessing
24
data, developing models and interpreting their result, selecting options, or analyzing
the impacts of a selection.
2.2.10 Types of Decision Support Systems
There are a number of Decision Support Systems. These can be categorized into
five types:
a)
Communications-Driven DSS
This breed of DSS is often called group decision support systems (GDSS).
They are a special type of hybrid DSS that emphasizes the use of
communications and decision models intended to facilitate the solution of
problems by decision makers working together as a group. GDSS supports
electronic communication, scheduling, document sharing and other group
productivity and decision enhancing activities and involves technologies
such as two-way interactive video, bulletin boards, e-mail, etc.
Most communications-driven DSS are targeted at internal teams,
including partners. Its purpose are to help to conduct a meeting, or for users
to collaborate. The most common technology used to deploy the DSS is a
web or client server.
For examples; chats and instant messaging software,
online collaboration and net-meeting systems. Communication-Driven DSS
will exhibit at least one of the following characteristics:
1) Supports coordination and collaboration between two or more
people;
2) Facilitates information sharing;
3) Enables communication between groups of people;
4) Supports group decisions.
25
b)
Data-Driven DSS
Data-driven DSS are a form of support system that focuses on the provision
of internal (and sometimes external) data to aid decision making.
Most
often this will come in the form of a data warehouse that is a database
designed to store data in such a way as to allow for its querying and analysis
by users.
An example of a data-driven DSS would be a Geographic
Information System (GIS), which can be used to visually represent
geographically dependant data using maps.
These DSS has file drawer
systems, data analysis systems, analysis information systems, data
warehousing and emphasizes access to and manipulation of large databases
of structured data.
Most data-driven DSS are targeted at managers, staff and also
product/service suppliers. It is used to query a database or data warehouse
to seek specific answers for specific purposes.
It is deployed via a main
frame system, client/server link, or via the web.
c)
Document-Driven DSS
Document-driven DSS are support systems designed to convert documents
into valuable business data.
While data-driven DSS rely on data that is
already in a standardized format that lends itself to database storage and
analysis, document-driven DSS makes use of data that cannot easily be
standardized and stored.
Document-driven DSS is the newest field of study in Decision
Support Systems.
Examples of document-driven tools can be found in
Internet search engines, designed to sift through vast volumes of unsorted
26
data through the use of keyword searches. The three primary forms of data
used in document driven DSS are:
1) Oral (i.e. transcribed conversations);
2) Written (i.e. reports, memos, e-mail and other correspondence);
3) Video (i.e. TV commercials and news reports).
None of these formats lend themselves easily to standardized database
storage and analysis, so managers require DSS tools to convert them into
data that can be valuable in the decision making process.
These systems help managers retrieve and mange unstructured
documents and web pages by integrating a variety of storage and processing
technologies to provide complete document retrieval and analysis.
It also
access documents such as company policies and procedures, product
specification, catalogs, corporate historical documents, minutes of meetings,
important correspondence, corporate records, etc. and are usually driven by a
task-specific search engine.
Document-driven DSS are more common, targeted at a broad base of user
groups.
The purpose of such a DSS is to search web pages and find
documents on a specific set of keywords or search terms.
The usual
technology used to set up such DSS is via the web or a client/server system.
d)
Knowledge-Driven DSS
Knowledge-driven DSS are systems designed to recommend actions to users.
Typically, knowledge-driven systems are designed to sift through large
volumes of data, identify hidden patterns in that data and present
recommendations based on those patterns.
27
These systems provide recommendation and/or suggestion schemes
which aid the user in selecting an appropriate alternative to a problem at
hand.
Knowledge driven DSS are often referred to as management expert
systems or intelligent decision support systems. They focus on knowledge
and recommends actions to managers based on an analysis of a certain
knowledge base. Moreover, it has special problem solving expertise and are
closely related to data mining i.e. sifting through large amounts of data to
produce contend relationships.
e)
Model-Driven DSS
Model-driven support systems incorporate the ability to manipulate data to
generate statistical and financial reports, as well as simulation models, to aid
decision-makers.
Model-based decision support systems can be extremely
useful in forecasting the effects of changes in business processes, as they can
use past data to answer complex ‘what-if’ questions for decision makers.
Model-driven DSS are complex systems that help to analyze
decisions or choosing between different options.
These are used by
managers and staff members of a business, or people who interact with the
organization, for a number of purposes depending on how the model is set
up.
These DS can be deployed via software/hardware in stand-alone PCs,
client/server systems, or the web.
The underlying model that drives the DSS can come from various
disciplines or areas of specialty and might include accounting models,
financial models, representation models, optimization models, and others. It
uses data and parameters to aid decision makers in analyzing a situation.
These systems usually are not data intensive and consequently are not linked
to very large databases.
28
2.2.11 The Advantages and Disadvantages of Decision Support System
According to the discussion made by Power (2002), the advantages are as follows:
a)
Time Savings
For all categories of decision support systems, research has demonstrated and
substantiated reduced decision cycle time, increased employee productivity
and more timely information for decision making.
The time savings that
have been documented from using computerized decision support are often
substantial.
Researchers have not however always demonstrated that
decision quality remained the same or actually improved.
b)
Enhance Effectiveness
A second category of advantage that has been widely discussed and
examined is improved decision making effectiveness and better decisions.
Decision quality and decision making effectiveness are however hard to
document and measure.
Most research has examined soft measures like
perceived decision quality rather than objective measures.
For example,
Hogue and Watson (1983) reported the most important reason managers
cited for using a DSS was to obtain accurate information. Studies of modeldriven DSS have examined this outcome more than research on other types
of DSS.
c)
Improve Interpersonal Communication
DSS can improve communication and collaboration among decision makers.
In appropriate circumstances, communications-driven and group DSS have
had this impact. Model-driven DSS provide a means for sharing facts and
assumptions.
Data-driven DSS make "one version of the truth" about
company operations available to managers and hence can encourage factbased decision making.
Improved data accessibility is often a major
motivation for building a data-driven DSS.
This advantage has not been
adequately demonstrated for most types of DSS.
29
d)
Competitive Advantage
Vendors frequently cite this advantage for business intelligence systems,
performance management systems, and web-based DSS.
Although it is
possible to gain a competitive advantage from computerized decision
support, this is not a likely outcome.
Vendors routinely sell the same
product to competitors and even help with the installation.
Organizations
are most likely to gain this advantage from novel, high risk, enterprise-wide,
inward facing decision support systems. Measuring this is and will continue
to be difficult.
e)
Cost Reduction.
Some research and especially case studies have documented DSS cost saving
from labor savings in making decisions and from lower infrastructure or
technology costs. This is not always a goal of building DSS.
f)
Increase Decision Maker Satisfaction
The novelty of using computers has and may continue to amaze analysis of
this outcome.
DSS may reduce frustrations of decision makers, create
perceptions that better information is being used and/or create perceptions
that the individual is a ‘better’ decision maker.
Satisfaction is a complex
measure and often researcher measure satisfaction with the DSS rather than
satisfaction with using a DSS in decision making.
Some studies have
compared satisfaction with and without computerized decision aids.
g)
Promote Learning
Learning can occur as a by-product of initial and ongoing use of a DSS.
Two types of learning seem to occur that are learning of new concepts and
the development of a better factual understanding of the business and
decision making environment. Some DSS serve as actual training tools for
new employees. This potential advantage has not been adequately examined.
30
h)
Increase Organizational Control
Data-driven DSS often make business transaction data available for
performance monitoring and ad hoc querying.
Such systems can enhance
management understanding of business operations and managers recognize
that this is useful. What is not always evident is the financial benefit from
increasingly detailed data.
On a more worrying note, some DSS provide
summary data about decisions made, usage of the systems, and
recommendations of the system.
Managers need to be very careful about
how decision-related information is collected and then used for
organizational control purposes.
The discussion of disadvantages builds upon the work of Klein and Methlie (1995)
and Winograd and Flores (1986). The following are the disadvantages:
a)
Overemphasize Decision Making
Implementing
DSS
may
reinforce
the
rational
overemphasize decision processes and decision making.
perspective
and
It is important to
educate managers about the broader context of decision making and the
social, political and emotional factors that impact organizational success. It
is especially important to continue examining when and under what
circumstances DSS should be built and used.
One must continue to ask if
the decision situation is appropriate for using any type of DSS and if a
specific DSS is or remains appropriate to use for making or informing a
specific decision.
b)
Assumption of Relevance
According to Winograd and Flores (1986), “Once a computer system has
been installed it is difficult to avoid the assumption that the things it can deal
with are the most relevant things for the manager's concern.” The danger is
that once DSS become common in organizations, that managers will use
31
them inappropriately.
There is limited evidence that this occurs.
Again
training is the only way to avoid this potential problem.
c)
Transfer of Power
Building DSS, especially knowledge-driven DSS, may be perceived as
transferring decision authority to a software program.
This is more a
concern with decision automation systems than with DSS.
One advocates
building computerized decision support systems to improve decision making
while keeping a human decision maker in the ‘decision loop’.
In general,
the value shows the need for human discretion and innovation in the decision
making process.
d)
Unanticipated Effects
Implementing decision support technologies may have unanticipated
consequences. It is conceivable and it has been demonstrated that some DSS
reduce the skill needed to perform a decision task. Some DSS overload
decision makers with information and actually reduce decision making
effectiveness.
e)
Obscuring Responsibility
The computer doesn't make a ‘bad’ decision, people do. Unfortunately some
people may deflect personal responsibility to a DSS. Managers need to be
continually reminded that the computerized decision support system is an
intermediary between the people who built the system and the people who
use the system. The entire responsibility associated with making a decision
using a DSS resides with people who built and use the system.
f)
False Belief in Objectivity
Managers who use DSS may or may not be more objective in their decision
making. Computer software can encourage more rational action, but
32
managers can also use decision support technologies to rationalize their
actions. It is an overstatement to suggest that people using a DSS are more
objective and rational than managers who are not using computerized
decision support.
g)
Status Reduction
Some managers argue using a DSS will diminish their status and force them
to do clerical work. This perceptual problem can be a disadvantage of
implementing a DSS. Managers and Information System staff who advocate
building and using computerized decision support need to deal with any
status issues that may arise. This perception may or should be less common
now that computer usage is common and accepted in organizations.
h)
Information Overload
Too much information is a major problem for people and many DSS increase
the information load.
Although this can be a problem, DSS can help
managers organize and use information. DSS can actually reduce and
manage the information load of a user.
DSS developers need to try to
measure the information load created by the system and DSS users need to
monitor their perceptions of how much information they are receiving. The
increasing ubiquity of handheld, wireless computing devices may exacerbate
this problem and disadvantage.
33
2.3
Feasibility Study
2.3.1
Introduction
Before deciding to invest in a specific area, an investor wants to be reasonably sure
that he or she will see an adequate return on specific product or services produced
for that environment.
Therefore, before any serious money is committed, an
analysis is usually performed to examine the proposed investment from several
standpoints.
The decision about whether or not to move a project into design
depends on cost of money, schedule, budget and market demand (Gould and Joyce,
2000). If the economics look favorable, the project proceeds. The Feasibility stage
is when the feasibility study is prepared as shown as Figure 2.0.
Figure 2.0 : Feasibility Stage in the Development Process
34
There must be a demand for the specific service or product. An example is
single-family homes.
Generally, in times of expanding business activity, there is
also an increase in the demand for single-family homes.
However, if the area in
question was recently in economic recession, it may be an oversupply of existing
housing and therefore little demand of new homes. Any developer will examine not
only the issue of overall economic activity but also the specific type of project and
specific environmental factors to ensure that homes built will sell.
Then, the cost of actual construction must be taken into account. In time of
economic expansion, cost also increase.
The price of materials such as lumber or
brick may increase because the local supplier has trouble keeping enough to meet an
increased demand.
The supplier may have to buy from other geographic areas
where price are higher.
The cost is pass on to the builder.
There may also be a
shortage skilled labor which means importing labor or using less-skilled labor.
Either way, both costs and risk to the project increase. Such factors could make it
too costly to construct a facility and still realized a reasonable return on investment.
Afterward, the cost of money itself can be a key factor. Most construction
projects use borrowed money. If interest rates are high, then the cost of servicing
the investor’s debt may make the return on investment too low.
The investors may
elect to put their money into another type of investment. Finally, the timing of the
project can be very important. Construction projects often involve long periods of
time between conception and completion.
During this interim period, which can
sometimes be several years, the anticipated market can change radically.
Sometimes, if the investor is lucky, this change can be for better; but just as likely it
can be for the worse.
During the early analysis stage, the owner often consults with architects and
construction professionals. Architects provide early design advice, and construction
professionals offer cost and constructability advice.
Their advice helps an owner
make a more informed decision about the feasibility of the specific project. Cost is
of particular concern since most projects fail from an economic standpoint.
Once
these elements; market need, cost of construction, financing costs and time to market
35
have been analyzed, a decision will be made to go forward or to cancel the
construction of the project.
Until the construction actually begins, a project may have many go/no go
decision points. The decision on feasibility is one of the first major ones, the time
when many, if not most, projects do not go forward. Many are analyzed and found
to fall short when the rate of return is calculated. Investors simply move on to more
lucrative projects.
The feasibility of the project and evaluation of its practicality,
which naturally dependant upon the extent and scope of the particular project will
identify the comprehensive nature of the feasibility studies that are undertaken.
In the basic construction industry, most feasibility projects are considered are
classified as either engineering or economic feasibility studies.
The feasibility
studies of a project should considered and evaluate the following aspects (Tenah,
1985):
1) Alternate courses of action: what are the alternative solution to satisfying
and meeting the need?
2) Engineering and evaluation or analysis of such alternate solutions:
Practical design solutions, cost estimates and basic engineering analysis.
3) Economic evaluation of such alternatives: what is the problem or
possible manner of financing? What are the basic revenues? What
economic impact will the project have?
4) Social analysis of the project: what is the impact upon society or the
community of the project under consideration?
36
5) Political considerations: the political factor may be considered one of the
realities and practicalities of implementation, depending upon different
and opposing political points of view that may change over the period of
time and within the area in which the project is being planned and
analyzed.
2.3.2
Preparation of Feasibility Study
Feasibility Study Phase outlines the process for beginning, conducting, and
completing a feasibility study, a process that ends with the submission of the
Prospectus package for site and design funding. This section describes the process,
deliverables, and keys to success to develop a sound project and site/design funding
request. It explains that the feasibility study is the core of this process, but not the
only ingredient needed for success.
The Feasibility Study plays the most important role in shaping the final
delivered project.
It evaluates alternatives; forms the breadth and scope of the
project and budget; and sets expectations for the team, the customer agency, and the
local community.
The preparation of the feasibility study are depends on the nature of a
project.
For the project, which architect takes the lead role, than the prime
consultant who will be required to develop scope for the feasibility study is the
architect. A team of consultants will be required to undertake the feasibility study.
The feasibility study typically consists of two stages. The first stage is to test and
confirm some of the project assumptions that led to the initial support of the project,
and the second stage to carry out a more detailed evaluation and develop a preferred
retrofit option.
37
An architect should be retained in each stage of the feasibility study to
provide direction in associate’s matters.
A cost consultant or quantity surveyor
shall be required to prepare capital cost estimates in the second stage of the
feasibility study process. According to Sandhu (2006), quantity surveyors prepare
cash flow and feasibility studies and are there in general to assist the architect in the
preparation of tender documents and calling of tenders. A concise report should be
prepared at the end of both the first and second stage of the feasibility study process.
The purpose of the report is to summarize the evaluation, analysis, design and
recommendations from the feasibility study, and to prepare some of the
documentation required for the Project Agreement.
2.3.3
Considerations for Feasibility Study
There are three considerations that will be discussed pertaining to the
preparation of the feasibility study that are the economic analysis, technical analysis
and financial analysis.
2.3.3.1
Economic Analysis
The economic analysis will consider the market research and demand analysis. The
market research should be carried out to establish whether the goods and services to
be provided by a new productive unit required by the community (the demand), and
to estimate the volume which it would wish to acquire at given prices.
There can be no discussion of profitability or of the other aspects of the
feasibility study if there is no demand.
Therefore, the market study includes the
following elements the determination of demand for the project’s output and the
volume, target group and time frame for the demand. This study is equally relevant
to projects which produce ‘marketable’ goods and services (commercial products)
and those which do not, such as schools, hospitals, roads and the like. In the latter
38
case, which are termed broadly as social goods and are supplied ‘free’ (due to the
absence of a market price); it is more difficult to estimate the volume of demand.
This, however, does not mean that a needs analysis can be ignored.
A market research is sometimes conducted prior to a full feasibility study
if this parameter or variable is considered very significant to the success or failure of
the project. It is only after this study that subsequent aspects in the feasibility study
follows. The study seeks to determine the following:
a) The size, nature and growth of total demand for the product;
b) The supply situation and the nature of competition;
c) The description and price of the product to be sold;
d) The different factors affecting the market;
e) The appropriate marketing program for the product
An analysis of demand is important to identify the needs of consumers and
determining whether they are willing and have the capability to pay for a given
product.
The size, nature and growth of total demand for a product may be
determined as follows:
a) Who and where is the market?
Segment the market according to type, manner of use, income
classification, location, age, etc. The manner of segmenting the
market would depend on the type of product being
considered.
b) What is the total domestic demand from the historic point of
view?
c) Is there a foreign market? If so, determine the historical demand.
39
d) Evaluate demand growth patterns in the past and project future
demand by applying appropriate projection methods.
The demand may as well consider with the supply. The supply situation
may be determined who and where are the direct competitors and classify them
according to size, product quality, location, performance and market segment
performance. The type of competition in existence would influence the decision on
production capacity and marketing strategies.
There is also needs to determine
historical domestic supply as comprised by local production and imports. If there is
a foreign market, determine the historical supply patterns in the targeted countries as
comprised by their local production and imports.
Other than that supply growth
patterns and project future supply are evaluated by applying appropriate projection
methods.
Once we have the data on demand and supply situations, the demand and
supply trends are compared and the unsatisfied amount of demand is determined.
If demand appears to be fairly satisfied by supply, we have to consider whether the
factors affecting the market may disrupt the equilibrium so as to cause demand to
grow faster than supply or whether the quantity of the product is such that it may
create additional demand or redirect part of the existing demand in its favor. Then,
the market share is determined by using the proposed production volume as against
the total market size;
In economic theory, price is determined mainly by the demand-supply
situation. An increase in demand with supply constant will hike up prices.
reverse would result in the lowering of prices.
The
There are, however, other factors
which assert some influence on the price. Without any change in demand or supply,
prices may go up if inputs such as raw materials cost rise; or prices may decline if
the government decides to subsidies production.
40
There are certain factors affecting the market that may be quantified or
predicted. Demand may be significantly affected by population growth, income,
changes, taste, rural/urban development, prices of substitute and complementary
products, and marketing techniques such as advertising, promotions and credit
policies. Supply may be influenced by the development of substitute products, the
entry or exit of firms, sources and costs of production, government create policies
and technology availability. Whereas, prices may be affected by production costs,
price controls inflation and price of substitutes.
The final aspects of a economic analysis would consist of a
comprehensive marketing program that determine the types of marketing program
prevalent in the industry and gauge their respective effectiveness.
It is also will
draw up a marketing plan that identifies and defines the target market, the selling
price, the packaging, the distribution network, the sales management mechanism and
promotion activities.
The important components of the marketing program are
product, price, place (distribution) and promotion.
As in other studies, that of the market includes two stages: the collection
of data and the establishment of empirical basis for their elaboration and analysis.
Data collection is part of identifying the needs of consumers and determining
whether they are willing and have the capability to pay for the products.
In
forecasting demand, one takes into consideration not only production and import
figures of the past, but also such other factors as credit availability, income
distribution, population growth, price variations, age composition, degree of
urbanization, taste and preferences and money supply.
Thus, the analysis and
elaboration stage will involve analyzing both macroeconomic variables and
microeconomic variables.
41
2.3.3.2
Technical Analysis
The technical analysis is used to establish whether or not a project is technically
feasible and provide tentative alternatives to achieve the project's objectives.
It is
an attempt to determine how well the technical requirements of the project can be
met, which location would be the most advantageous and what would be the
optimum size of a plant. The technical feasibility analysis should consider various
aspects and alternatives of a project as follows:-
a) Preliminary research and testing
b) Selection of the reduction process
c) Specification of operating and assembly of equipment
d) Location, buildings and site layout
e) Plant layout
f) Supplementary engineering works
g) Efficiency
h) Flexibility of productive capacity
i) Work schedules
j) Size of project
All engineering projects require a certain amount of preliminary tests and
research. These tests cover widely varied matters such as simple strength tests of the
site for the construction of buildings, laboratory or pilot plant tests of the
possibilities of using certain raw materials or processes, the conditions under which
such uses will be possible, experiments with new crops and metallurgical research
into the treatment of ores. The project itself need only contain a clear summary of
the information regarding these tests and research.
In many cases there are no problems regarding the production process or
system, but in others complexities and alternatives arise which should be explained
together with the solutions offered, in relation to the preliminary research.
To
provide clarity and better presentation, the process of selection and description of the
production can be described by the use of simple drawings or flow diagrams.
42
For the selection and specification of equipment, there are two stages in
involves that are the choice of the type, in order to draw up the specifications for the
bids and the selection between the various equipment of the type chosen in order to
decide between the bids. Selection of the type of equipment will be influenced by
the nature of the process, the scale of production and the degree of mechanisation,
all of which are closely inter-connected.
It may often happen, for instance, that a
certain degree of mechanisation is only applicable above a certain production level,
and similarly certain processes lend themselves better to mechanisation than others.
The type of production is thus related to the degree of mechanisation and
automation. The analysis of bids for a given technology or engineering is not only a
question of choosing the lowest bid in direct terms, but
also entails other
considerations such as:
a) Specifications or suitability for the type of raw materials;
b) Minimum risk of obsolescence;
c) Commitments for technical assistance and technology transfer;
d) Alternative plant sizes/design flexibility; and
e) Cost factors and operating conditions.
The technical feasibility analysis of a project depends largely on location,
as substantial differences usually exist in the availability, quality and costs of the
various requirements in an alternative location.
Projects whose technical
requirements could have been well taken care of in one location sometimes fail
because they are established in another place where conditions are less favorable. In
other words, a project situated in a location that is remote from services and supply
sources such as experienced labour force, market, raw materials, utilities and other
requirements would be operating with disadvantages.
In addition, an engineering and buildings project should include estimates
of the size and characteristics of the buildings required for production and site
layout. The problem acquires special interest in the case of manufacturing industry,
43
because the distribution of the industrial buildings has an important bearing on the
handling and flow of raw materials, materials in process of manufacture, and
finished products. Reception areas, stores, central workshops and other installations
must be functionally situated in relation to the main factory building and transport
services.
The other important factor for consideration is future expansions which
mean adequate land with acceptable physical characteristics.
The efficiency of a project such as a manufacturing operation depends to a
great extent on the layout of the plant and equipment, since this can lead to economy
in movement and the flow of material and processes thereby saving time and money.
Some other factors which need attention in plant layout are:
a) Storage space for raw materials and supplies;
b) Space for internal transport;
c) Utilities service systems including waste disposal;
d) Interdepartmental communication;
e) Future expansion flexibility;
f) Environmental considerations.
Projects must often cover additional installations to supply the services
needed for actual production or for the employees/persons who will work on the
project.
Consideration of these supplementary engineering works arises from the
project's technical.
The quality and quantity of the buildings for housing, camps
and welfare services will be more elastic since in this case the criterion will be both
economic and social, and will vary with circumstances. A solution has to be sought
which is reasonable in cost, but which will at the same time provide the minimum
comfort required by the workers and employees.
This association of various
supplementary projects with the principal or central project may be indispensable in
the case of agricultural, mining or industrial projects, which because of their nature
must be situated close to natural resources and far from urban centers.
44
Once the manufacturing method, the size of the plant and the arrangement
of equipment and buildings has been decided, it will be possible to calculate the
volume of each type of input required by the project, both for installation and
operation.
Once the volume has been determined in physical terms, operating and
input costs can be estimated.
Moreover, this volume serves as a useful element of
comparison when appraising the estimated administrative and operating efficiency
of the enterprise.
The volume of input according to the physical processes employed the
quality of the available raw materials and the experience of other plants can be
estimated with the help of preliminary technical research.
In addition to the purely
technical factors, these estimates should also take into account the industry's general
administrative and technical organization and the quality of the labour available.
This may lead to specific recommendations regarding the organization and
administrative structure of the enterprise, training and contracting of advisers.
It
may be also necessary to have laboratories for the technical checking of raw
materials, the-actual production process and final products as part of the quality
control in accordance with the required specifications.
The need for flexibility in productive capacity is at times a result of
seasonal demand; at others, it may depend on temporary limitations in the
availability of raw materials, or a tight financial situation, which means that
production, has to be started on a limited scale in the first stage. Naturally there are
limitations in the approach to these problems, but if the conditions mentioned should
exist, solutions should be sought which will tend to facilitate pleasant growth and
permit flexibility of operation with minimum drawbacks, interference and cost.
The schedule of project implementation from project preparation through
plant start-up and the identification of potential causes of delay are one aspect of
technical study.
There must be realistic schedules which not only include all
activities from engineering design through land purchase/acquisition, construction
and procurement, to testing of equipment and training staff necessary for the
successful completion of the project.
These schedules should be arranged in a
45
coherent sequence.
The estimates of realistic schedules in terms of timing and cost
are drawn up from experience with comparable projects in the same or similar
environment.
The size of a project usually means its production capacity during a normal
operating period. Owing to the need for capacity and provision for operating
flexibility to meet demand fluctuations, the normal output will seldom be 100% of
the installed capacity. Size is sometimes expressed in terms of the number of
persons employed, the capital involved, or some other units. However, whatever
unit of measurement this may be, the optimum size and the best location will be
those which will lead to the most favorable financial result. Some important factors
in considering the size of projects are:
a) The volume of demand to be met;
b) The relationship between size (or scale of production) and the
technique and investment;
c) The relationship between size and location or the geographical
distribution of the market;
d) The problem between size and financing or capital resources for
the project;
e) Administrative experience and capacity.
Once the various aspects are given thoughts, it becomes natural to have a
fair idea as to the overall project costs. Basically, details of capital cost (land,
building, machinery/ equipment), and development cost (such as land clearing,
infrastructure), production cost and maintenance cost should be given due
considerations. Since the technical analysis would cover both engineering and nonengineering aspects of a project, a checklist would definitely help a project officer in
managing his varied tasks, even if a consulting firm has been appointed. The
checklist would include those aspects that have been covered above and. amongst
others, the examination of details such as technical description of the project,
relevant project site characteristics and size, project implementation schedules,
46
technical life of project, salvage values, availability of technical supporting staff and
impact from the project.
2.3.3.3
Financial Analysis
The financial analysis is one of the analysis conducted in a feasibility study and
is normally undertaken after the market and technical analyses. The objective of
the analysis is to determine the financial viability of the project and there are
basically two main types of analysis as follows:-
a) Analysis of projects with ‘measurable benefits’
Benefits that can be valued at market prices. The output of these
projects, if sold in the market, provides the benefits of the project.
b) Analysis of projects with ‘non-measurable benefits’
Benefits that cannot be valued at market prices. These are mainly
social and security projects which are undertaken by the public sector
to provide essential services and therefore cannot be valued at market
prices.
In the case of projects with ‘measurable benefits’ it is important to
determine if the benefits produced by the project justify the cost. This analysis
examines the opportunity cost of capital and determines if the project is a justifiable
investment, especially to the individuals or agencies undertaking the investment. If
it is not justifiable, then it will be financially prudent to consider alternative
investments to maximize the use of capital and other resources.
While in the case of projects with “non-measurable benefits” it is not
possible to make a direct comparison between benefits and costs. The decision to
implement such projects is usually determined through policy and strategy
considerations. The financial analysis, in this
case, examines
the
various
47
alternatives of implementing the project and selects the least cost alternative in
order to optimize the use of capital.
The major analytical tool of financial analysis of projects is the Discounted
Cash Flow (DEF) technique. This method involves basically three steps that are the
preparation of the project cash flow, discounting the net cash flow and derivation of
Net Present Value (NPV) and/or the Internal Rate of Return (IRR) of the project
The essence of financial appraisal is the forecasting of all costs and
benefits over the lifetime of the project. The appraisal is done at prevailing market
prices and the format in which it is set out is often described as a ‘Cash Flow
Statement’. The term cash flow statement is to some extent a misnomer. This is
because what one is really concerned with is the flow of resources involved in the
project, cash being merely a convenient way of measuring the flow.
In fact, the
format is referred to as a ‘Resource Flow Statement’ to avoid confusion with the
‘Sources and Application of Funds’ Statement used by accountants and which is
sometimes referred to as a cash flow statement. The cash flow statement includes
the following costs as follows:
a) Capital Costs
•
Land
•
Buildings (including site preparation and civil works)
•
Plant and equipment (acquisition costs plus
transportation)
•
Vehicles
•
Contingency allowances (physical and price)
b) Operating Costs
•
Raw materials
•
Costs
•
Labour
•
Utilities
48
•
Fuel
•
Transport
•
Repairs and maintenance
c) Pre-operating Expenses
• Expenses incurred before commencement of
operations e.g. pre-feasibility and feasibility studies,
architect's and surveyor's fees.
d) Sunk Costs
•
Use of capital assets from other projects abandoned
projects
e) Working Capital
•
Stocks (of raw materials), spare parts and cash
requirements to pay bills
•
There is no set formula for calculating working capital
requirements. Each project has to be viewed
individually
•
Only the extra requirements over and above the
amounts needed in the previous year are included
•
The value of working capital in the last year as a
benefit to the project when it is liquidated
Then, there are several benefits to be valued for the cash flow. They are as follows:-
a) Sales value
•
If output is sold through normal commercial channels
b) Imputed value (using market price of output)
• If output e.g. on the farm, is not sold but is consumed
by the farm family
49
c) Principle of ‘with’ and ‘without’ project
• When project is not completely new but merely an
addition to an existing activity;
• The entire output of the project cannot be treated as
the benefit of the project;
• Benefit of the project is the change (increase) in output
as a result of the project.
In addition to presenting the costs and benefits in a Cash Flow Statement,
there are other considerations for the cash flow that are the salvage value and the life
of the project. The salvage value is the value of fixed assets at the end of project
when they are sold constitutes a benefit to the project. While the life of project is
based on expected technical life of project's major investment components like in an
irrigation project this would be determined by the expected useful life of the
upstream dam and irrigation canals.
It is also being based on technological
obsolescence such as the industrial projects and projects with a high degree of
mechanisation.
Given the above information, the layout of the project cash flow is not
difficult. In some cases, each year of the project's life is given a separate row and
each heading a separate column.
In other cases, the years are given the columns
and the headings the row. Once the cash flow of benefits and costs for the project
have been determined in the manner indicated earlier, it is necessary to ascertain the
financial feasibility of the project by comparing the costs (which are normally
incurred in the first few years of the project) with the positive net benefits. The net
benefits (or net cash flow) are derived by simply subtracting the total costs from
total benefits for each year of the project.
CHAPTER III
RESEARCH METHODOLOGY
3.1
Introduction
In preparing this research, the research methodology involved several stages to
ensure the achievement of the research objectives. The research methodology was
divided into three stages (Refer Figure 3.0) as follows:-
3.1.1
First Stage: Introduction of the Research Field
The first stage starts form the determination of the research field that is done through
reading several journals.
There are various field of research that has been gone
through and the Decision Support System seems to be a very interesting research
field.
Through the reading, the problem of statement are been identified.
Then,
after further discussion with the supervisor, the aim and objectives are able to be
developed.
The objectives than are used to determined the research title.
Next,
after some thorough readings on journals and books, the scope of the research are
then been identified.
52
3.1.2
Second Stage: Data and Information Collection
This stage is the guideline to acquire the data and the information needed to achieve
the objective of this research.
In this stage, the information needed is determined
base on the objectives established earlier. For the first objective that is to identify
the current practice of decision making process in the feasibility study of
construction project in an organization, the information needed are the current
decision making process in preparing the feasibility studies and the problems that
may occur in the process of preparing it.
The first objectives also require the
information on the usage of DSS in any decision making process in the organization
The second objective is to identify the Decision Support System that is able to
improve the decision making process in the feasibility stage and the information
needed is the factors considered and the DSS type of application that is suitable to
the factors considered. For both the first and the second objectives the sources and
the methodology in acquiring the information is more or less the same.
For both
objectives, several semi-structured interviews will be conducted with construction
consultants that involved in preparing the feasibility study.
Other than that,
literature reviews and document analysis of journals, internet sources and past thesis
will be used to support the data and information obtains from the interviews.
For the third objective, that is to develop a Decision Support System
Framework for feasibility study, the information needed are; the suitable DSS
Software’s features to improve decision making, the components needed to develop
the DSS framework that includes the features, hardware and software and the
process to develop the DSS framework. In order to achieve this objective, literature
review and document analysis on journals, internet sources and past thesis that are
related will be used.
53
3.1.3
Third Stage: Analysis and The Interpretation of Data and Information
During this stage, the analysis and the interpretation of data and information that
have been obtained from the second stage will be conducted.
Based on the
information gathered from the interviews sessions, literature reviews and the
document analysis, the objectives of this research will be determined. Last but not
least, the conclusions and further suggestion related to the research will be made.
3.2
Research method
3.2.1
Literature Review
A literature review report is a combination of information on a topic presented in an
organized formal narrative or a body of text that aims to review the critical points of
current knowledge on a particular topic. It is to document what other professionals
have learned, developed or investigated on a topic of interest to this research.
According to Cooper (1988) "a literature review uses as its database reports
of primary or original scholarship, and does not report new primary scholarship
itself.
The primary reports used in the literature may be verbal, but in the vast
majority of cases reports are written documents. The types of scholarship may be
empirical, theoretical, critical/analytic, or methodological in nature.
Second a
literature review seeks to describe, summarize, evaluate, clarify and/or integrate the
content of primary reports".
Among of the literature sources are the research journals and special reports
in interest discipline. Any study, whatever the scale will occupy reading what other
people have written about the area of interest in this particular research, gathering
information to support or rebut the arguments and writing about their findings. It is
to provide evidence that the researcher has read certain amount of appropriate
54
literature and he also has some awareness of the current state of knowledge on the
subjects.
Most often associated with science-oriented literature, such as a thesis, the
literature review usually precedes a research proposal, methodology and results
section. Its ultimate goal is to bring the reader up to date with current literature on a
topic and forms the basis for another goal, such as the justification for future
research in the area.
3.2.2
Document Analysis
Document analysis is also a type of normative-survey research which deals
with records that already exist. It does not concern with the general importance of
the documents, but only with certain characteristics which can be identified and
counted.
The fact that one works directly from documents does not mean that he
avoids all problems of collecting and selecting data.
In some cases, he may need
only to produce few books from library, but in other cases he may need to collect his
document specimens from afar.
Among the sources of data for document analysis are from records, reports,
printed forms, letters, catalogues, pictures and films.
When using document
sources, one must bear in mind the fact that data appearing in print are not
necessarily trustworthy. Documents used in this research must be subjected to the
same careful types of critics employed by the historian. Not only is the authenticity
of the document important, but the validity of its contents is also crucial in fact.
Document analysis works best when the purpose is to gain insight into an
instructional activity or approach. The purpose of the document analysis are
including describing the prevailing practices or conditions; to discover the relative
importance of, or interest in certain topics or problems; to discover level of difficulty
of presentations in textbook or in other publications; to evaluate bias, prejudice or
55
propaganda in textbook presentation and lastly to explain the possible causal factors
related to some outcome, action or event.
3.2.3
Semi-Structured Interview
Semi-structured interviews are guided conversations where broad questions are
asked, which do not constrain the conversation, and new questions are allowed to
arise as a result of the discussion. This is different from questionnaires and surveys
where there are very structured questions that are not deviated from.
A semi-
structured interview is therefore a relatively informal, relaxed discussion based
around a predetermined topic. It is usually best to conduct such interviews in pairs
with one person doing the interview and one taking detailed notes.
The process of a semi-structured interview involves the interviewer
presenting the context of the study and its objectives to the interviewee. The set of
questions are prepared but open, allowing the interviewees to express opinions
through discussion. The questions are generally simple, with a logical sequence to
help the discussion flow. The interviewer needs to design an interview framework
and analyze the information at the end of each day of interviewing.
The semi-structured interview is the most adequate tool to capture how a
person thinks of a particular domain. Its combination of faith in what the subject
says with the skepticism about what she/he is saying, about the underlying meaning,
induces the interviewer to go on questioning the subject in order to confirm the
hypothesis about his/her beliefs.
It is conducted with a fairly open framework
which allow for focused, conversational, two-way communication.
They can be
used both to give and receive information.
Unlike the questionnaire framework, where detailed questions are
formulating ahead of time, semi structured interviewing starts with more general
questions or topics.
Relevant topics are initially identified and the possible
56
relationship between these topics and the issues such as availability, expense,
effectiveness become the basis for more specific questions which do not need to be
prepared in advance.
3.3
Framework Methodology
The framework will provide the terminology, concept and the guideline that are
useful when building the system. The terminology will describe the terms or jargon
that will involves in the decision support system that will be valuable in
understanding the system. These are obtain during further literature review and
research on the system and software from various sources such as the journals and
the internet. The concept will describe the process of both preparing of the
feasibility study and the decision support system. Whereas the guideline will be in a
flowchart that will explain the decision support system framework. The information
and the objectives achieved in the first and second objectives will be the based to
develop the framework.
CHAPTER IV
RESULT AND DISCUSSION
4.1
Introduction
This chapter will discuss the analysis of the data and information collected from
three interviews sessions with three quantity surveying consultant firm that have
been chosen as a sample for this research. The data and information collected are
verified, edited and then analysed to match the objectives of this research that is to
identify the current practice of decision making process in the feasibility study of
construction project in an organization, to identify the Decision Support System that
is able to improve the decision making process in the feasibility stage and to develop
Decision Support System Framework for feasibility study.
4.2
Respondent Profile
4.2.1
Company A
The first respondent is a quantity surveying firm that will be known as Company A.
The firm was incorporated in 1998 as a corporate body Quantity Surveying
professional practice registered with the Board of Quantity Surveyors and is also
registered with the Ministry of Finance to provide quantity surveying consultancy
services.
The firm has managed to expand and establish itself in this field.
The
58
expansion involved the setting up of branch offices in Johor Bahru and Ipoh together
with an increase in human resources.
The services offered by this firm during the Pre-Contract stage involves the
preparation of the feasibility studies and project cash flow, preliminary estimated
and cost plan, as well as providing advice on tendering procedures.
The stated
services include the followings:a)
A study on the viability and profitability of property developments.
b)
Cost advice of projects (project estimates & cost control).
c)
Advice on size and structure to be built based on estimated cost.
d)
Advice on development economics and budget allocation.
e)
Working together with the designers in finalizing the building to be built
within the budget/estimate.
4.2.2
Company B
The second respondent will be known as Company B. The company is an
International Consultancy practice, specializing in Construction Cost & Contract
Management Consultancy.
It is first established in 1973, the company has
progressed in tandem with the rapid economic growth in Asia and now has fifteen
offices in seven countries.
The services provided related in cost and contract consultancy are as follows:a) Feasibility Studies
b) Development Appraisals
c) Budget Estimates
d) Cost Planning
e) Cost Control and Management
f) Contract Administration
g) Contract and Claims Consultancy
h) Final Accounts
59
i) Contract Procurement
j) Contractual Advice
4.2.3
Company C
The third respondent will be known as Company C.
The firm is a sole
proprietorship company and was established in 1997. They have quite an experience
on the services they offered that covers from Pre-Contract until Post-Contract stage.
During the Pre-Contract stage the services involves the preparation of the feasibility
studies, projected project cash flow, preliminary estimated and cost plan, in addition
to provide advice on tendering procedures. They also provide services on contract
administration, contract and claim management, final account and contract
procurement for Post-Contract stage.
4.3
Interview Analysis
There are three interviews sessions that have been conducted. The questions asked
are based upon the first and second objectives to be achieved in this research. The
information needed as stated in Chapter III (refer Figure 3.0) are the main reference
to the question designed. The questions and answers gathered are as follows:-
60
Table 4.0 : Semi-structured Interview Questions and Answers
No
1.
Question
What is the
current practice
of preparing the
feasibility
study? (the
process)
Company
Answers
A
Generally, the process begin by requesting from client and consultant involved for project brief, preliminary
drawings and other relevant information, conduct a site visit where required, then prepare the feasibility study
report. The report will be prepared based on what type of construction, either for commercial, residential or
others. The report then will seek approval and being amend accordingly until it is acceptable to the client.
B
C
A
2.
Who are the
people involved
in preparing and
approving the
feasibility
study?
The process begin when the client express the needs to prepare the feasibility study. Then, other related
information like drawings, clients’ requirements and time target will be requested from relevant consultant
and the feasibility study report will prepared. It is usually took several time of preparing the report to meet
client’s satisfaction.
This firm usually did the feasibility study for the government project and the feasibility studies prepared are
in the form of Preliminary Detail Abstract (PDA) that is based on Gross Floor Area (GFA). The feasibility
study will be refine several time as per client’s requirement before the final study are accepted.
The people involved are according to the stages along the process of preparing the feasibility study. The
requesting of the needed information and the site visit are the responsibility of the Director, Senior QS and
the General Manager. They also responsible to verify and approved the feasibility study report prepared. The
feasibility study report and all the needed amendments will be prepared by the QS and the Senior QS.
B
To prepare the feasibility study, this firm will formulate a QS team where they will be brief by the
requirements.
C
Each project will be handled by a QS. The project QS will prepare the feasibility study and the Senior QS will
supervised and give approval before being forwarded to client for any comments or further action.
61
Table 4.0 : Semi-structured Interview Questions and Answers (cont’d)
No
3.
4.
5.
Question
What are the
factors
considered in
the feasibility
study?
What are the
analyzing
methods used in
preparing the
feasibility
study?
What are the
problems
occurred during
the preparation
of the feasibility
study?
Company
Answers
A
The practice of this firm, the factors considered is the floor area, site location, development value,
construction cost, specifications, consultant fees, sales revenue, other services, cash flow (if necessary) and
profitability (if necessary).
B
As far as this firm is concern, the factors considered are the construction cost with several exclusions. (Refer
Table 4.1)
C
Since this company uses the PDA as the basis for the feasibility study the factors are according to the
elements considered in the PDA and focus on the construction cost.
A
B
C
A
B
C
Usually used probability-IRR, PV & NPV, clients are more interested in profitability.
Experience is important to do the analyzing because usually the data is not complete and a lot of assumptions
have to be made.
Cost per GFA.
a) Lack of cost data (historical data) especially for international project.
b) Problem in accessibility to site to conduct site visit.
c) Insufficient project brief from client.
Insufficient information from client
Lack of information from client, have to make a lot of assumptions and allowances
62
Table 4.0 : Semi-structured Interview Questions and Answers (cont’d)
No
6.
7.
Question
Company
Is there any
usage of
computer based
system in the
process of
preparing the
feasibility
study? (if any,
please describe)
In your opinion,
is there a need
for computer
based system
aid in preparing
the feasibility
study?
(describe)
A
B
C
8.
We only use the Microsoft Words and Microsoft Excel in preparing the feasibility study. For the local
Other than the Microsoft Words for the report, we use Everest that is one of the estimating software available
in market. We also use Ripac, another software for the measurement works, it is believed to have more
function than we used it for like for preparing an estimate, but it is however under utilized.
We only use the Microsoft Words and Microsoft Excel in preparing the feasibility study.
A
It is hard to say because the local construction industry nowadays is slow in adapting new computer based
system.
B
Yes, but it is hard to implement because the feasibility study involved a lot of parameters and usually the
client are reluctant to give all the information needed because they considered it as their private information.
C
Its all usually depends on the principal of a company, but if the system can improves the current way of
preparing the work, it should be good.
A
Do you have
knowledge on
the Decision
Support System
(DSS)?
Answers
B
C
No.
Yes, heard about it before during studying abroad in United Kingdom.
Yes, heard it during studying before.
63
Table 4.0 : Semi-structured Interview Questions and Answers (cont’d)
No
Question
Company
A
No.
9.
Is there any
usage of the
decision support
system in any
process of work
in your
organization? (if
any, please
describe)
B
No.
C
No.
Answers
a) Lack of budget (initial capital, maintenance fees).
A
b) Time and cost to train workers to adapt to new system.
c) Limited vendor in local market that cause the higher price in purchasing and updating.
In your opinion,
is there any
10 barrier of
implementing
the DSS?
a) Attitudes of workers.
B
b) Will cause more learning and training time.
c) Workers are rushing to achieve client’s dateline and reluctant to use the new system as it may slow
them down.
a) Lack of budget
C
b) The principal way of thinking that reluctant to spend or invest as long as the current job can be done in
the current way of doing things.
64
The first question addresses the current practice of preparing the feasibility
study. The overall process is more or less the same where it starts when the client
express the needs to prepare the study. Then the feasibility study will be prepared,
each with the company’s own practice on which factors to consider. There will be
back and forth on the submission of the feasibility report and the acceptance to
finally fulfill the client’s satisfaction. One of the company interviewed, prepare the
feasibility study in the form of Preliminary Detail Abstract (PDA) that is based on
Gross Floor Area (GFA). It is usually for the government construction project.
The second question is to identify the people who are involved in preparing
and approving the feasibility study. In general the Senior Quantity surveyor and the
quantity surveyor is the main person to conduct the feasibility study and to prepare
the report. The approval will be made by the higher ranking officer like the general
manager or the director of the company.
One of the most important information needed that is the factors considered
in the feasibility study is asked in the third question.
The main factors is the
construction cost and the other factors is the floor area, site location, development
value, specifications, consultant fees, sales revenue, other services, cash flow and
profitability.
The factors then will be analyzed to make recommendation to the client.
Based on the answers to the fourth question, the analyzing method is usually based
on probability and the cost per GFA.
The value of the Internal Rate of Return
(IRR) and Net Present Value (NPV) usually the value that the clients are interested
because they interested to the profitability of the project proposed. The experience
in analyzing is very important because the data usually is not complete and a lot of
assumptions must be made.
The fifth question addresses the problems that are usually faced during the
preparation of the feasibility study. The problem is mainly lacking in information
provided by client. This usually happens because the clients like to keep most
65
needed information as private and confidential.
Other problems are lack of cost
data especially for international project and problem in accessibility to conduct site
visit.
The lack of data and information needed are the reason quantity surveyor
needs to make assumptions and the value of uncertainty is involved. Therefore, the
cost estimation DSS can be helpful in solving this problem.
Next, the sixth question inquires any usage of computer based system in the
process of preparing the feasibility study. The companies mainly use the Microsoft
Words and Microsoft Excel in preparing the study. Other than that, there is also the
usage of Everest in doing the estimating. Then, the company’s representative gives
their opinion in the needs of computer based system aid in preparing the study
through the seventh question. In their opinion they said that, there is the need, but
there are some difficulties to implementing it such as the nature of the construction
industry that is slow in adapting the new computer based system and the
involvement of a lot of parameters in preparing the feasibility study.
Afterward, the eighth question wonder on the knowledge of the company’s
representative on the DSS. Only one of them have no knowledge on the matter ask
and the others have knowledge on DSS. Hence their knowledge is limited to what
they’ve learned and heard during studying before. There is also no usage of the DSS
in any other process of work in their organization. These answers are referred to the
ninth question.
The last question seeks the opinion on the barrier of implementing the DSS
and the answers can be concluded as follows:-
a) Lack of budget (initial capital, maintenance fees)
b) Limited vendor in local market (the higher price in purchasing and
updating)
c) Attitudes of workers
d) Cause more learning and training time
e) The principal way of thinking
66
4.3.1
Feasibility Study Decision Making Process and the Factors Considered
Based on the answers from the interviews session, we are able to get the whole idea
on how the feasibility study are prepared and who are involved during the process.
It can be visualized by referring to the flowchart of the process of preparing the
feasibility study (refer Figure 4.0).
The process of preparation a feasibility study starts when there are request
from the client or any consultant representing a construction project. Then, either
the director, or the general manager or the senior quantity surveyor will request
necessary information like the project brief, preliminary drawings and other relevant
information from the client or the consultant involved.
The project brief will include the information on the type of project
proposed.
It is important because different types of construction project have
different approach of feasibility study but still, the principle is the same. It can be
either for commercial or residential type of project or also different in terms of
project delivery like Built Lease Transfer (BLT), or Built Operate Transfer (BOT),
or Build Lease Operate Transfer (BLOT) , or Private Financing Incentive (PFI) or
the usual Conventional way.
The requested information will subsequently be
reviewed upon received by either of the said person in charge.
The next required steps is to conduct a site visit where required.
The site
visit is only applicable to local project. For international project, only the director’s
approval is required prior to site visit.
The data and information collected during
the site visit shall be recorded in a standard type of record system such as the Site
Visit Checklist.
proposed site.
The site visit will give a clear view of current condition on the
67
START
Request the following information as available from Client /
Consultant:
• Project brief
• Preliminary Drawings
• Other relevant information
Review information receive from Client / Consultant
Conduct site visit where required (Applicable only to local
project. For international project, Director’s approval is
required prior to site visit). Record the site visit data.
Conduct Feasibility Study and prepare the information on
the factors considered.
DSS Application Area
Prepare feasibility study report and submit to managing
director/ director for rectification and approval.
A
68
A
Verify feasibility study report
Make amendments to
feasibility study report
and re-submit
NO
Is feasibility study
report acceptable?
YES
Approved feasibility study report
Issue Feasibility Study report to Client / Consultant and
maintain a copy.
Is Feasibility Study
Report acceptable to
Client / Consultant?
YES
Follow-up with Client / Consultant for decision / action
END
Figure 4.0 : Decision Making Process of Feasibility Study
NO
69
After that, the feasibility study is conducted by considering certain related
factors. In practice, the factors considered are more or less the same but still varied
in each quantity surveying consultant according to their company standard. There
are those who only treat the construction cost as their consideration for feasibility
study and there are those who include other elements as follows:-
a)
Floor area
b)
Site location
c)
Development value
d)
Specification
e)
Consultant fees
f)
Sales revenue
g)
Other information/services
h)
Cash flow (if necessary)
i)
Profitability (if necessary)
There are also some exclusions for some consulting firm in considering the
construction cost as stated in Table 4.1.
70
Table 4.1 : Exclusions Of Construction Cost For Estimating
No.
EXCLUSIONS
1.
Cost of land and associated costs
2.
Professional fees
3.
Supervision cost
4.
5.
Planning and submission fees, documentation fees, survey fees, strata title ad
miscellaneous expenses etc.
General advertisement and promotion expenses including pre-opening
expenses
6.
Statutory contribution and local authorities charges
7.
Management and administration cost
8.
Work outside the site boundary
9.
Quick rent and assessment charges
10.
Fluctuations of cost on building materials and labour
11.
Legal fees and stamp duties
12.
Development tax and income tax
13.
Development charges (if any)
14.
Interest on loan
15.
Any other items not specifically mentioned in this estimate
By considering all the elements as mentioned above, the feasibility study
report are prepared.
The study and the report will be prepared by a quantity
surveyor and being monitored by a senior quantity surveyor. Then, the report will
be submitted to Managing Director or Director for rectification and approval. After
that, the report will be verified to determine whether it is acceptable or otherwise.
Unapproved feasibility study report will be passed back to the quantity surveyor in
charged for amendment and shall be re-submitted for approval.
71
On the other hand, the approved feasibility study report is issues to client or
the consultant with a copy will be kept for reference for the consultant. The copy is
usually will be send in PDF form for security purposes. Then the general manager
or the senior quantity surveyor will seek whether the feasibility study report is
acceptable to the client or the consultant. They also will make a follow-up with the
client or consultant for decision and action.
Based on practice and experience, the report usually are being done several
time or issues to meet the customer requirements. The client usually asks for several
issues to match their planning or decision that is either to proceed, or to postpone, or
to change or to cancel the project. It is usually depends on the outcome and the
recommendation of the feasibility study report.
4.4
DSS Application: Cost Estimation
The interview sessions provides the information for the first and the second
objectives.
By knowing the factors considered in the feasibility study, a DSS
application are being able to be identified to improve the decision making process of
the study. The said application is the cost estimation DSS. From all of the factors
stated earlier, only those that are involves with calculation and estimation will be
suitable to be adapt with the cost estimation DSS. They are as follows:
a)
Floor area
b)
Development value
c)
Construction Cost
d)
Consultant fees
e)
Sales revenue
f)
Cash flow
g)
Profitability
72
Cost estimation DSS are frequently model-driven and spreadsheet-based, but
other types of DSS are developed and marketed for assisting in this task.
Successfully estimating costs is important to the survival and profitability of many
firms in many different industries. The specific model-driven DSS that is developed
should help an estimator input data, apply a detailed quantitative estimating model,
conduct sensitivity and ‘what if’ analyses, and prepare a formal proposal.
According to the U.S. Department of Labor (BLS, 2002), “cost estimators
develop the cost information that business owners or managers need to make a bid
for a contract or to determine if a proposed new product will be profitable”.
In
some businesses, cost estimates are prepared on the back of an envelope or on a
simple ‘bid’ sheet. As the complexity of the estimating task increases computerized
decision support becomes increasingly important.
There were more than 200,000
cost estimators in the United States in 2000, about 50 percent worked in the
construction industry and 20 percent in manufacturing industries. Currently, most
estimators do not use computerized decision support.
This all can change in the future. Cost estimators use a computer database
containing information on costs and conditions of many other similar projects.
Although computers cannot be used for the entire estimating process, they can
relieve estimators of much of the drudgery associated with routine, repetitive, and
time-consuming calculations. Computers also are used to produce all of the
necessary documentation with the help of word-processing and spreadsheet
software, leaving estimators more time to study and analyze projects.
4.5
Suggested Cost Estimation DSS
The identified factors considered during the study will be the guideline in
identifying the decision support system that is able to improve the decision making
process in the feasibility study stage. Based on the interviews, the factors involve
estimation and calculation of several types of cost and values. The estimation and
73
the calculation are usually are done via Microsoft Excel even though the use of other
software such as the Everest cannot be totally denied.
A cost estimation DSS is a software application that helps a person estimate
cost elements. ‘Cost Estimation’ refers to the purpose of the Decision Support
System and does not constrain how the system is implemented. The generic task is
subtle and semi-structured and it can be approached in many ways. Since Microsoft
Excel is the usual tools in preparing the feasibility study in current practice, the
decision support system that have been identified to improve the process of
preparing the study is the Crystal Ball. It is a model-driven and spreadsheet-based
decision support cost estimating application. It is also a tool that supports Microsoft
Excel in enhancing the already provided function of the usual version of the
software.
In suggesting the DSS that is able to improve the decision making process
for the feasibility study, several cost estimation DSS application software have been
reviewed.
Three DSS web based application and three DSS Window based
application were reviewed and analyzed. The web based application is the EMC
software, Fidelity Calculators and Principal Financial.
The Windows based
application is the software that supports Excel that is Crystal Ball by Decisioneering
Inc., Premium Solver Platform by Frontline System, Inc. and @Risk by Palisade
Asia-Pacific.
Based on the review, the three web based application is not suitable for the
feasibility study.
As describe in Table 4.2, the said web based applications cater
more for pharmaceuticals decision making, intelligent document management and
other personal investment. As for the Window based application, Premium Solver
Platform and @Risk are not suitable even though they can perform the same kind of
simulation.
It is because, they are hard to understand and more complicated to
operate compared to Crystal Ball that is more easy to use and user friendly. Crystal
Ball also shows clearly how works and can enhance Microsoft Excel. That are the
reasons in proposing to choose the Crystal Ball as the cost estimation DSS for the
feasibility study.
74
Table 4.2 : DSS Software And The Description
DSS Software
Description
• Pharmaceuticals decision making
EMC
• Intelligent document management
Fidelity Calculators
Principal Financial
• Personal investment (retirement, insurance,
banking, health)
• Personal investment (retirement, insurance,
banking, health)
• Monte Carlo Simulation
• Easy to understand and operate
Crystal Ball
• User friendly
• Clearly shows how it works with Microsoft
Excel
• Monte Carlo Simulation
Premium Solver Platform
• Complicated to operate
• Hard to understand the system
@Risk
• Monte Carlo Simulation
• Hard to understand and operate
4.5.1
Spreadsheet-Based DSS
A Decision Support System that has been or will be implemented using a
spreadsheet package can be termed a spreadsheet-based DSS. A spreadsheet is the
enabling technology for the DSS. A wide variety of DSS can be implemented using
desktop, client-server or Java spreadsheet applications.
In the world of accounting, a spreadsheet spreads or shows all of the costs,
income, taxes, and other financial data on a single sheet of paper for a manager to
look at when making a decision. Also, a spreadsheet is a collection of cells whose
values can be displayed on a computer screen. An electronic spreadsheet organizes
75
data into columns and rows. The data can then be manipulated by a formula to give
an average, maximum or sum. By changing cell definitions and having all cell
values re-evaluated, a user performs ‘what if?’ analysis and observe the effects of
those changes.
Decision support systems built using spreadsheet software are
sometimes called spreadsheet-based DSS.
Are spreadsheet packages DSS generators? Sprague and Carlson (1982)
defined a DSS Generator as a computer software package that provides tools and
capabilities that help a developer quickly and easily build a specific Decision
Support System. Spreadsheet packages qualify as DSS generators because:
a) They have sophisticated data handling and graphic capabilities;
b) They can be used for ‘what if’ analysis;
c) Spreadsheet software can facilitate the building of a DSS.
Model-driven and data-driven DSS are the most common types of DSS one
would consider developing using a spreadsheet package. Spreadsheets seem
especially appropriate for building a DSS with one or more small models.
A
developer would then add buttons, spinners and other tools to support a decision
maker in ‘what if?’ and sensitivity analysis.
A data-driven DSS can also be implemented using a spreadsheet. A large
data set can be downloaded to the DSS application from a DBMS, a web site or a
delimited flat file. Then pivot tables and charts can be developed to help a decision
maker summarize and manipulate the data.
Spreadsheet-based DSS can be created in an end user development
environment or in a multi-user environment. Microsoft Excel is certainly the most
popular spreadsheet application development environment. Add-in packages like
Crystal Ball, is able to increase the capabilities of a spreadsheet and the variety of
models that can be implemented.
76
4.5.2
Crystal Ball
Since 1986, Decisioneering has built its reputation on Crystal Ball® as a line of
simulation, forecasting, and optimization software.
They’ve pioneered the use of
simulation and optimization in everyday decisions and are dedicated to developing
the tools, services and training that individuals and companies need to better
calculate, communicate and diminish their business risks. Their services have been
used in several industries with different kind of application as stated in Figure 4.1.
Figure 4.1 : The Usage of Crystal Ball in Industries and their Applications
( Source : Decisioneering, Inc. (2000-2005), http://www.crystalball.com )
This is time of change for project management, where low-cost software and
improved computing power that enable to better model projects and calculate the
related risks. Crystal Ball can help to assess alternatives, increase the confidence in
planning details, and make more informed decisions despite the uncertainties or lack
of data. It have the capabilities to transform the Microsoft® Excel spreadsheets to
get a credible picture of risk, create accurate predictive models, search for the best
solution and maximize the value. Crystal Ball software is a tool that provides Monte
Carlo simulation to forecasting, optimization and real options analysis.
77
4.5.3
Crystal Ball 7 Standard Edition
Crystal Ball 7 Standard Edition is the easiest way to perform Monte Carlo
simulations in user own spreadsheets. Crystal Ball automatically calculates
thousands of different ‘what if’ cases, saving the inputs and results of each
calculation as individual scenarios. Analysis of these scenarios reveals the range of
possible outcomes, their probability of occurring, which input has the most effect on
model and where ones should focus the efforts.
Crystal Ball is an easy-to-use simulation program that helps you analyze the
risks and uncertainties associated with your Microsoft Excel spreadsheet models.
With Crystal Ball, user will have the potential of answering difficult management
questions in minutes with just a few clicks of the mouse. Up until now, user
probably dealt with risk in the spreadsheet models by selecting the mean or bestguess values for your uncertain variables (e.g. costs, demands, development times,
etc.). With this method, the final report reflects only a single outcome based on your
best ability to interpret the uncertain elements in your model.
Crystal Ball are able to generates multiple outcomes through automate ‘what
if’ analysis in the spreadsheets with Monte Carlo simulation (a technique for
simulating real-world situations involving elements of uncertainty).
It quickly
assigns ranges of values to inputs and automatically calculates thousands of different
outputs and their probabilities.
It then records the results for in-depth analysis or
summarized reporting with Crystal Ball's many reports, charts and tools.
4.5.4
How Does Crystal Ball Enhance Excel
Excel spreadsheet are excellent tools for analysis, but they do have their limits.
That’s why Decisioneering created Crystal Ball, an Excel add-in. One major
limitation of Excel is that only a single value can be assign to a cell. To view other
78
scenarios, one must manually change the value in a cell.
Crystal Ball enhances
Excel by allowing user to:-
1)
Describe the uncertainty for any cell
2)
Calculate the effect of uncertainty on the variable of interest
Figure 4.2 : Crystal Ball added tools in Microsoft Excel
Crystal Ball adds three new menus and a new toolbar to Excel (refer Figure
4.2). The Crystal Ball toolbar follows the modeling process, from left to right. The
first nine buttons help to enhance a new or existing model with Crystal Ball. The
next five buttons control the simulation. The final eight buttons generate charts and
reports and launch the online help. Crystal Ball adds three menus: Define, Run and
Analyze.
79
The Define Menu helps to set up a Crystal ball model. The Run menu helps
to run a simulation and also includes links to additional applications and tools for
Crystal Ball Professional or Premium Edition. The Analyze Menu provides many
options to help in analyzing the results of a simulation and create reports that will
communicate the result of the analysis (Refer Figure 4.3).
Figure 4.3 : Crystal Ball New Menus Function
The capabilities of performing the simulation in shorter time compared to
recent method allows the user and it this case the quantity surveyor consultant to
make the simulation on meetings upon requested by clients. This improves the
overall process of decision making through the feasibility study by eliminating
unnecessary process of refining the study several time that can really saves time.
4.5.5
System Requirements
The system requirements are the requirements needed for Crystal Ball to function in
terms of the operating system, supporting software and the hardware. The system
requirement of the computer where needed the Crystal Ball products are as follows:-
80
a)
Operating system
1) Microsoft Windows 2000 Professional with Service Pack 3,
2) Windows XP Home Edition with Service Pack 2,
3) Windows XP Professional with Service Pack 2,
4) Windows Vista (tested on Windows Vista Business, Home
Premium, Home Basic, and Enterprise editions)
b)
Software
1) Microsoft Excel 2000, 2002 (XP), 2003, or 2007
2) Microsoft Internet Explorer 6.0 or later (web browser)
3) Microsoft .NET Framework 2.0 (or 3.0 with Windows XP
versions or Vista)
4) Adobe Acrobat Reader 6.0 or later
c)
Hardware
1) Personal computer with Pentium-equivalent microprocessor (800
MHz or faster)
2) At least 512 MB of RAM
3) At least 142 MB of free hard disk space for Microsoft .NET
Framework (if not already installed) and 94 MB for Crystal Ball.
(Note: Each of these two components requires approximately
twice the given amount of disk space during installation.)
4) CD-ROM drive
5) Video graphics adapter and monitor with at least 1024x768
resolution
4.5.5.1 About Microsoft .NET Framework
The Microsoft .NET Framework is recent technology from Microsoft for developing
secure and advanced Windows applications. Microsoft .NET Framework 2.0 (or 3.0
for Windows XP or Vista) must be installed to a computer before installing and
81
licensing the Crystal Ball.
Crystal Ball must be locked to one of these supported
versions of Microsoft .NET Framework to run properly.
It is a software component that can be added to or is included with the
Microsoft Windows operating system.
It provides a large body of pre-coded
solutions to common program requirements, and manages the execution of programs
written specifically for the framework.
The .NET Framework is a key Microsoft
offering, and is intended to be used by most new applications created for the
Windows platform. It is first released in 2002, and is included with Windows XP,
Windows XP, Windows Server 2003, and Windows Vista, and can be installed on
older versions of Windows.
4.6
Tools and Function of Crystal Ball
To function as a decision support tools for the feasibility study, Crystal Ball
provides new tools with certain function.
It supports the decision making process
by providing a model-driven system that allows user to explore any consequences.
The system starts with defining an assumption until lastly produces a report.
overall framework of the system illustrated in Figure 4.4.
The
82
Figure 4.4 : Crystal Ball System Framework
4.6.1
Defining an Assumption
The first step in the beginning of using the Crystal Ball is to describe uncertainty in
a single-value cell using Crystal Ball’s probability distributions (referred to as
assumptions). In any spreadsheet model, there are factors or variables that may be
uncertain.
Depending on what types of models, these variables can be anything
from predicted revenues to cost estimates.
Alone, Excel limits the user to a single guess for the value in each cell. The
users are forced to use and average or estimated value for each uncertain variable. In
place of estimated values, Crystal Ball creates probability distributions, or
assumptions. These distributions represent the range and likelihood of the possible
values for a variable. Probability distributions offer users a simple graphical way to
describe the uncertainty around a value in your model.
own shape and parameters.
Each distribution has its
83
In defining an assumption, user needs to determine which of the model
variables are uncertain. The user can ask themselves on how confident they are of
the input value. Is it a guess or an average? If so, then it is an excellent candidate
for an assumption.
To begin with, select the cell with the uncertain values and click the Define
Assumption Button (the first button on the left of the first nine buttons).
Then,
Distribution Gallery window (refer Figure 4.5) will appear. The user can select the
type of distribution provided like the Normal Distribution or the Triangular
Distribution or others. If the user did not sure what type of distribution to choose, a
description of each type of distribution is provided with a single click at each type of
the distribution.
For example, if we choose the Triangular Distribution, the
description stated that, it shows the number of successes when you know the
minimum, maximum and most likely values.
Figure 4.5 : Distribution Gallery Window
84
After that, the Define Assumption window (refer Figure 4.6) will appear.
Crystal Ball takes the assumption name from the text label in cell next to the cell
with the uncertain values that the user chooses earlier. It is important when defining
the assumption, to make sure that they have unique names to differentiate during the
analysis.
In the Define Assumption window, the user can define each of the
parameters; minimum, likeliest and maximum. These parameters define the
uncertainty of the percent on the type of the variables.
Figure 4.6 : Define Assumption Window
After define each of the parameters and click OK button, the assumption cell
is now shaded green. To view an assumption, the user can select the cell and click
the Define Assumption button. Then the user can select a second uncertain variable
and repeat the same step. Maybe this time, the user can choose the normal
distribution. The normal distribution provides the user with the mean and standard
deviation. At this time there are two green assumptions. User can define as many
assumptions as they need in a model.
85
4.6.2
Defining a Forecast.
The next step is to define the output, or Crystal Ball forecast. The user now needs
to tell Crystal Ball which cells to monitor. These output or forecast cells, contain
formulae that are affected by user’s assumption cells. A forecast is the variable of
interest that user are trying to calculate, such as Net Present Value or the Capacity of
Reserves.
The user can define as many forecasts as needed.
When Crystal Ball
runs a simulation, it stores all forecast values. When the simulation ends, user can
analyze these values to understand the level of risk.
To start the forecasting, user need to select the cell with the needed forecast
value and click Define Forecast button (the third button from the left of first nine
buttons).
Then the Define Forecast window (refer Figure 4.7) will appear. User
can enter the Forecast Name with the description of the forecast value.
To avoid
confusion, make sure all forecast have unique names. After that, click OK button
and the cell selected with forecast value is shaded blue.
Figure 4.7 : Define Forecast Window
86
4.6.3
Running a Simulation
Now its time to run the simulation.
Crystal Ball uses Monte Carlo simulation to
dynamically produce alternatives scenarios in the spreadsheet models.
This is
known as ‘What if’ analysis. A simulation is made up of individual trials. To see
the effects of a simple trial, click the Single Step button on the toolbar (the last
button of the next five buttons).
When user requested a single step, Crystal ball
selected and entered a new value for each assumption. Excel then recalculated the
spreadsheet and generated a new forecast value.
The Single Step button can be
used a few more times to see how the spreadsheet inputs (assumptions) and the
outcome (forecast) change with each trial.
simulation.
The changes during the trial are the
To reset the simulation, just use the Reset button (the button on the
right side of the Single Step button).
Figure 4.8 : Run Preferences Window
87
User also can simulate as many time as 1000 number of trial for different
scenarios through the Run Preferences button (the first button of the next five
buttons).
After clicking the Run Preferences button and enter the number of trial
needed (refer figure 4.8), click the Run button (the next button after the Run
Preferences button) to automatically simulate the trials.
4.6.4
Using the forecast chart
The user now can watch how the forecast chart, a histogram of the forecast values,
builds with each new trial. Once the simulation has ended, user can use the forecast
chart to analyze the results.
Then, user can learn more from the statistic view.
Click View from the menu of the Forecast window, and then choose Statistic. This
view will show user the statistics of the simulation results. User can also view the
percentiles by choosing Percentile at View menu (refer Figure 4.9).
Figure 4.9 : Forecast Window with Statistics and Percentile Function
88
4.6.5
Using the sensitivity Chart
Next, Crystal Ball uses the sensitivity chart to see what’s driving this uncertainty.
Based on the explanation before this, there are two assumptions made and the
outcomes generated are the result from contribution of both assumptions. Now user
may need to know does one have a greater impact than the other. To examine the
effect of assumptions, user can use the Sensitivity Chart button (the fifth button on
the final eight buttons). User can see the sensitivity of the assumption to the
outcome through Sensitivity window appeared (refer Figure 4.10).
Figure 4.10 : Sensitivity Window
4.6.6
Creating a Report
The last step is creating a report. The report from a Crystal Ball simulation can be
generated easily by clicking the Create Report button (the third last button on the
final eight buttons). Create Report window (refer Figure 4.11) will appear and user
can choose the type of report needed. There are either report on assumptions,
decision variables, forecasts or even full report. Then, Crystal ball will generate the
final report with all the information requested.
89
Figure 4.11: Create Report Window
4.6.7
Others Features available with Crystal Ball.
1)
Distributing fitting
If user have historical data and want to use them to create
assumptions, users can use the Distribution Fitting option, available
via Fit button in the Distribution Gallery window.
2)
Correlated Assumptions
Many assumption variables, such as inflation and cost, have a direct
relationship that user can define using a correlation coefficient. This
makes for more realistic spreadsheet model. Use the Correlate button
found on any assumption dialog.
3)
Categories of distributions
The distribution gallery organizes distributions in categories, which
are libraries of distribution. The favorite or most-used distributions
90
can be save to a Favorites category or to a new category which can be
created.
4)
Publish and subscribe
Categories of distributions can be shared across the users
organization, with anyone who needs to use these pre-defined
distributions, via the publish and subscribe mechanism.
5)
Precision Control
This feature can provide the confidence of knowing that enough trials
have been run through. This feature can be set in the Define Forecast
window.
6)
Extreme Speed
Extreme speed, powered by PSI Technology, runs simulations up to
100 times faster than Normal speed.
This speed mode can be
dramatically increases the speed to perform the simulations and
optimizations. This tool is in the Run Preferences window.
4.7
The Framework
In the end, the DSS Framework for feasibility study are develop based on the
information on the decision making process and the factors considered in the study.
By understanding the factors as the area of application for the DSS, the type of DSS
application are able to be identified that is the cost estimation DSS.
Then, the
requirement of the cost estimation DSS are gathered to complete the framework.
By referring to Figure 4.12, the framework is divided to four phases. Phase
1 is identifying the process that is the feasibility study process.
Phase 2 is
identifying the area of application that is the estimation and calculation of factors
considered. Next, the third phase is identifying the DSS application that is the cost
91
estimation DSS. The last phase that is Phase 4 is identifying the system required to
support the cost estimation DSS.
The identified cost estimation DSS that is the Crystal Ball will be adapted to
factors considered as stated in the framework. The system requirements are the
requirements needed for Crystal Ball to function in terms of the operating system,
supporting software and the hardware.
92
Phase 1: Identify
Process
Phase 2: Identify Area
of Application
Phase 3: Identify DSS
Application
Feasibility
Study Process
Estimation and Calculation
of Factors Considered
Cost Estimation
DSS
a) Floor area
Phase 4: Identify System
Requirement
System Requirement
• Microsoft Windows 2000 Professional
with Service Pack 3,
• Windows XP Home Edition with
Service Pack 2,
• Windows XP Professional with Service
Pack 2,
• Windows Vista (tested on Windows
Vista Business, Home Premium, Home
Basic, and Enterprise editions)
Operating
System
b) Development value
c) Construction Cost
d) Consultant fees
e) Sales revenue
Crystal Ball
Software
f) Cash flow
g) Profitability
• Microsoft Excel 2000, 2002 (XP), 2003, or 2007
• Microsoft Internet Explorer 6.0 or later (web browser)
• Microsoft .NET Framework 2.0 (or 3.0 with Windows XP versions or
Vista)
• Adobe Acrobat Reader 6.0 or later
Hardware
• Personal computer with Pentium-equivalent
microprocessor (800 MHz or faster)
• At least 512 MB of RAM
• At least 142 MB of free hard disk space for
Microsoft .NET Framework (if not already
installed) and 94 MB for Crystal Ball
• CD-ROM drive
• Video graphics adapter and monitor with at
least 1024x768 resolution
Figure 4.12 : Decision Support System Framework for Feasibility Study
93
4.8
Conclusion
In conclusions, the end result of this research are being develop through several
phases of understanding the two main component of this research that are the DSS
and the feasibility study. It is believed that Crystal ball provides efficient simulation
that are more advanced and can really improved the output of the feasibility study in
terms of more dependable recommendation by the quantity surveying consultant.
In a broader context, cost estimation DSS application are applicable
wherever the calculation and estimation of cost and any values of uncertainty is
needed and does not limited to this stage. By identifying the area of application at
any stage or process, we can determine what type of DSS application is suitable.
CHAPTER V
CONCLUSION AND RECOMMENDATION
5.1
Introduction
This chapter will discuss the conclusion for this research as a whole in achieving all the
objectives determined at the early stage of this research. In addition, there are also the
problem encountered during doing the research, recommendations based on the result
achieved, and several suggestions on further research.
5.2
Conclusion
In the early stage of this research, the discussion and explanation is on the Decision
Support System and the Feasibility Study as the two important components of this
research. The explanation on the DSS covers the background on the system itself, the
relationship between the decision making and the DSS, the decision making in the
construction management as well as on the research on the development of the DSS.
Other than that, there are also the discussion on the characteristics and the four
important components of the system that are the Database Management System, Model
Base Management System, User Interface and the Mail Message Management.
95
Furthermore, the discussion on the types of the DSS and the advantages and
disadvantages of the system were also included.
For the second components of this
research, the explanation covers the background of the feasibility study, the preparation
of the study and the considerations for the feasibility study that includes the economic,
technical and financial analysis.
Next, the methodology to complete this research and to achieve the objectives
determine earlier are being explain. The methodology mainly involves literature
reviews, semi-structured interviews and internet sources. There is also other method
that has been used such as the document analysis. The information needed for each of
the objectives stated earlier is the based to design the methodology of this research. The
design methodology has been helpful as a guide to ensure that this research is conducted
smoothly to minimize any problem faced.
Needed data and information gathered, were then being reviewed and analyze to
suit with the objectives. The information from the interview sessions was the main
important information in achieving the first and the second objectives. The answers
from the interview sessions have been able to fulfill the first and the second objectives
by clearly provides the information on the current practice of preparing the feasibility
study and outlined all the factors considered in the feasibility study. The interview
sessions were conducted with three quantity surveying consultant companies that have
been chosen as a sample for this research. The three companies are among the known
company in this field and have lots of valuable experiences regarding to the topic asked.
For the second objectives also, literature reviews on internet sources are very
helpful in providing the information on the suitable DSS application for the study.
Then, based on the information for the first and the second objectives, the third
objectives were being able to be fulfilled. The previous objectives have all the necessary
information to guide in developing the DSS framework for the feasibility study.
96
The main finding of this research is the DSS Framework for Feasibility Study
that has been develops. The framework consists of the terminology, concepts and the
guideline that are useful in applying the system. The framework can be adapted to any
company that has the intention to implement this system to their appropriate work
process and feels that this system really can enhance the daily working process.
In general, the three objectives of this research have been achieved. The
following results have been able to be identified and developed:-
1) Decision making process of feasibility study
2) Cost Estimation Decision Support System
3) DSS Framework for feasibility study
The framework developed, can be used to build the prototype for this system and at the
end, the actual DSS for Feasibility Study can be develop.
5.3
Problems Encountered During Research
In conducting and finishing this research, there are several problems that have been
faced. Among others, the problem is there are very limited time in collecting and
analyzing the data and information. In this situation good planning and time
management is important to ensure all needed data and information can be gathered in
time provided.
There are also problem in getting the companies chosen to cooperate as
respondents for this research. There are several companies that have turn down the
acquisition on being the respondent. The company policy of private and confidential
also limits this research in obtaining more information. In facing this problem, there is
97
need to have some contacts with the people in the industry. With determination and
some social skill, the relevant companies have agreed to give their cooperation.
Then, there is also problem in suggesting the DSS that is suitable for the
feasibility study because there are so many software that are available in the market and
in choosing the appropriate system, many hours have been spent browsing through the
internet. After many hours spent on choosing the suitable DSS, more hours needed to
really understand the system in order to propose the used of the system. It is very time
consuming process and the time is very limited for this research. This problem also
related to time issue, so planning is really important to ensure that enough time is
allocated for this activity.
5.4
Suggestion on Further Research
Other research related to this aspect can be done by other researcher. As this
research covers only the feasibility stage and specific type of DSS, further research on
the implementation of DSS on other stage in the development of construction project
can be explore. Other than that, the implementation or the potential use of DSS in other
construction consultant can be suggested.
This system is widely used in other industry such as the manufacturing and the
medical industry, so the comparison on the type of application and the usage can be
identified. The information needed can be helpful in improving the current
implementation of DSS in construction industry. Further research also can be done on
the steps that need to be taken to overcome the barrier in implementing the DSS in the
construction industry.
98
References and Bibliography
Allan Ashworth (2005). “Pre-Contract Studies: Development Economics, Tendering
and Estimating.” Oxford : Blackwell Science Ltd.
Arain, F.M. and Low, S.P. (2005). “A Framework for Developing a KnowledgeBased Decision Support System for Management of Variation Orders for
Institutional Buildings.” March.
Barton, P. (1985). “Information Systems in Construction Management; Principles
and Applications.” London: B.T. Batsford Ltd.
Bastias, A. and Molenaar, K. (2005). “Classification and Analysis of Decision
Support Systems for the Construction Industry.” Computing in Civil
Engineering.
Behrooz Noori and Mohammad Hossein Salimi (2005). “A Decision Support
System for Business-to-Business Marketing.” The Journal of Business and
Industrial Marketing, 20, 4/5. 226-236.
Bureau of Labor Statistics (2002-2003), U.S. Department of Labor, Occupational
Outlook Handbook, Cost Estimators, http://www.bls.gov/oco/ocos006.htm
(1 June 2007).
Cascante, L.P., Plaisent, M, Bernard, P. and Maguiraga, L. (2002), “The Impact Of
Expert Decision Support Systems On The Performance Of The New
Emplyees” Information Resources Management Journal, Oct-Dec, 64-78.
Cooper, H. (1998). “Synthesizing Research: A Guide for Literature Reviews.” New
Jersey: Prentice Hall.
Decisioneering, Inc, (2000-2005), Excel spreadsheet risk analysis & forecasting
products, http://www.crystalball.com/product.htm (30 May 2007).
99
DSSResource.COM,
(1995-2006),
Ask
Dan!
about
DSS,
http://www.dssresource.com/faq/index.php (30 May 2007).
EMC
Corporation
(2007),
EMC
Software,
http://software.emc.com/products/software_az/infoscape.htm (30 May 2007).
Fisher, D., ONiel, M. and Contreras, J. (1995), “DS^2: Drilled Shaft Decision
Support System” Journal of Construction Engineering and Management.
I21(1): 86-94.
FMR
Corp.
(1996-2007),
Fidelity
Investments:
401k.COM,
http://401k.fidelity.com/401k/home.htm (30 May 2007).
Frontline System, Inc., About Frontline System & Spreadsheet Optimization,
http://www.solver.com/about.htm (30 May 2007).
Gorry, G.A. and Scott-Morton, M.S. (1971), “A Framework for Management
Information System” Sloan Management Review 12(3): 55-70.
Gould, F.E. and Joyce N.E. (2000). “Construction Project Management.” New
Jersey: Prentice Hall.
Hogue, J.T. and H.J. Watson (1983), “Management’s Role in the Approval and
Administration of Decision Support Systems,” MIS Quarterly, 7(2), June,
15-26.
Holsapple, C.W. and Whinston, A.B. (2001). “Decision Support System:A
Knowledge-based Approach.” Cincinnati: Thomas Learning Custom
Publishing.
Irtishad Ahmad (1995), “Expert Decision Support Systems For The Construction
Industry” ACS Proceedings of the 26th Annual Conference, April, 221-225.
100
Jones, K. (2006), “Knowledge Management As A Foundation For Decision Support
System” The Journal Of Computer Information System, Vol.46, Iss. 4, 116125.
Kahkonen, K. (1994), “ Interactive Decision Support System for Building
Construction Scheduling” Journal of Computing in Civil Engineering. 8(4):
519-534.
Khairuddin Abdul Rashid (2002), “Construction Procurement in Malaysia:
Processes and System: Constraints and Strategies.” Kuala Lumpur: Research
Centre, IIUM.
Klein, M. and Methlie, L. B. (1995). “Knowledge-based Decision Support Systems
with Applications in Business.” United Kingdom : John Wiley & Sons.
Ku Azril Ridzhie Ku Ahmad (2005). “ Cadangan Rekabentuk Rangka Kerja Bagi
Pemilihan Kontraktor Binaan.” Universiti Teknologi Malaysia : Master
Project.
Moore, Nick (1987). “How to do research.” London : The Library Association
Publication.
Moselhi, O., Hegazy, T. and Fazio, P. (1993), “DBIB: Analogy-based Decision
Support System for Bidding in Construction” Journal of Construction
Engineering and Management. I99(3): 466-478.
Nadkarni, C.P. (2000). “Development of Construction Environmentally Informed
Decision Support System.” San Jose State University : Master Project.
Nisbet, J.D and Entwistle, N.J (1970). “Educational Research Methods.” London :
University of London Press.
Nor Azlinda bt. Mohamed Sabli (2003). “Information Exchange in Construction
Industry.” Universiti Teknologi Malaysia : Master Project.
101
Palisade Asia-Pacific Pty. Limited (2007), About Palisade, Risk and Decision
Analysis
Software
–
Palisade
Asia
Pacific,
http://www.palisade.com.au/about/about.asp (30 May 2007).
Power, D. J. (2002). “Decision Support Systems: Concepts and Resources for
Managers.” Westport, CT: Greenwood/Quorum Books.
Principal
Finance
Services,
Inc.
(2007),
Principal.com-For
Business,
http://www.principal.com/biz.htm (30 May 2007).
Reuven Y. Rubinstein (1981), Simulation and the Monte Carlo Method.” United
States of America : John Wiley and Sons Inc.
Seeley, Ivor H. (1997). “Quantity Surveying Practice.” London : Mc Millan Press
Ltd.
Shen, Y.C. and D. Grivas (1996), “Decision Support System For Infrastructure
Preservation,” Journal of Computing Civil Engineering. I0 (1): 40-49.
Sidney M. Levy (2006). “Project Management in Construction .” New York : The
McGraw-Hill Companies.
Simon, H.A. (1960). “The New Science of Management Decision.” New York:
Harper and Row.
Sprague, R.H and Watson, H.J. (1996). “Decision Support System for
Management.” New Jersey : Prentice-Hall Inc.
Sprague, R.H., Jr. (1980), “A Framework For The Development Of Decision
Support System” MIS Quarterly. 4(4):1-26.
Sprague, R.H., Jr. and Carlson, E.D. (1982). “ Building Effective Decision Support
System.” Englewood Cliffs, NJ: Prentice Hall.
102
Tenah, K.A. (1985), “The Construction Management Process”. Virginia: Reston
Publishing Company.
Vicki Sauter (1984). “Decision Support System.” United States of America : John
Wiley and Sons Inc.
Watson, H.J., Houdeshel G. and Rainer, R.K., Jr.(1997). “Building Executive
Information Systems and Other Decision Support Application.” United
States of America : John Wiley and Sons Inc.
Wikimedia
Foundation,
Inc.
(2007),
Wikipedia,
the
free
encyclopedia,
http://enwikipedia.org (1 June 2007).
Winograd, T. and Flores, F. (1986). “Understanding Computers and Cognition.”
Reading, MA: Addison-Wesley.
Wu, W.K., Hadipriono, F. (1994), “Fuzzy Modus Ponens Deduction Technique For
Construction Scheduling” Journal of Construction Engineering and
Management. I20(1): 162-179.
Yow Soon Keong (2006). “The Current Practice and Problems of Contractual
Arrangement In Construction Industry.” Universiti Teknologi Malaysia :
Master Project.
103
APPENDIX I
MSC CONSTRUCTION MANAGEMENT
FACULTY OF CIVIL ENGINEERING
UNIVERSITI TEKNOLOGI MALAYSIA
RESEARCH TITLE:
DECISION SUPPORT SYSTEM FRAMEWORK FOR FEASIBILITY
STUDY IN CONSTRUCTION PROJECT
BY:
NURJULIANA BT. MOHD NAZARI
840508-14-5756 (MA061066)
SUPERVISOR:
DR. ARHAM ABDULLAH
Aim and Objectives
The aim of this research is to proposed Decision Support System framework particularly for
construction consultants that involves in preparing the feasibility study in order to improve the
effectiveness of the decision making process. The objectives of the study are listed as follows:-
1. To identify the current practice of decision making process in the feasibility study of
construction project in an organization.
2. To identify the Decision Support System that is able to improve the decision making
process in the feasibility stage.
3. To develop a Decision Support System Framework for feasibility study.
APPENDIX I
104
Interview Question
1. What is the current practice of preparing the feasibility study? (the process)
2. Who are the people involved in preparing and approving the feasibility study?
3. What are the factors considered in the feasibility study?
4. What are the analyzing methods used in preparing the feasibility study?
5. What are the problems occurred during the preparation of the feasibility study?
6. Is there any usage of computer based system in the process of preparing the
feasibility study? (if any, please describe)
7. In your opinion, is there a need for computer based system aid in preparing the
feasibility study? (describe)
8. Do you have knowledge on the Decision Support System (DSS)?
9. Is there any usage of the decision support system in any other process of work in
your organization? (if any, please describe)
10. In your opinion, is there any barrier of implementing the DSS?