Risk Analysis Based Model for Super Projects Pre- Appraisal
Ahad. Nazari, Assistant Professor, Construction Department, Faculty of Architecture and Urban Planning ,
Shahid Beheshti University, Tehran, Iran , Email: a_nazari@sbu.ac.ir , nazari_ahad@yahoo.com
Abstract
This paper addresses the complex problem of determining the viability of inherently risky Super Projects, usually
involving immense capital investment, long term government commitment and long construction and operational period.
Super Projects have complexity in term of political / legal, technical / design and organizational aspects, which make
them more uncertain and uncontrollable compare to conventional projects.
There is a dichotomy of risk as these projects contain inherent global and elemental risks but have to be certain to
succeed if financial investments are to be attracted. This Investment decisions cannot be made by a corporate board
meeting or by a computer- based system but requires a new approach for assessing their viability. In this paper, A
proposed model for assessment of Super Projects based on an understanding of risk and an application of Analytical
Hierarchical Process (AHP) is presented.
Key words: Project Management, Pre-appraisal Phase Decision Making, Super Projects, Risk Analysis ,Investment
Decision making,. ”challenges and opportunities ”, “IPMA World Congress ,Istanbul ,turkey”
1.
Introduction
The World Development Federation (WDF, 2010) has defined Super Projects as “Global mega projects involving a
capital investment of US $ billion or more, or which reflect innovation solutions or technological breakthrough having
world-wide importance. Super projects include the world’s major infrastructure and facility ventures. Often they have a
significant economic impact within countries or region”. WDF (2010) has identified more than 1600 global Super
Project worldwide, which include transportation, energy and water, urban development, environmental, tourism
development and communications projects.
This definition emphasizes particular features of a super project such as large capital investment, the complexity,
innovation or other external factors. A precise definition is difficult but most authors and researchers agree that super
projects tend to be associated with long construction and operation period, complex organizational structures that are
often affected by political factors and legal regulations. These broader, non- project factors are much more significant in
super projects than in conventional projects.
This paper first outlines the problem which needs to be tackled. Then, an approach to develop a decision model for the
assessment of the viability of super projects, using risk analysis and the Analytical Hierarchical Process, (AHP), is
described.
2. Problem Explanation
Risks and uncertainties are associated with all projects and could influence all phases of the projects including feasibility
study, design, planning, biding and tendering, construction and even marketing and operation phase. However, risks
associated with early phase decisions are more significant than others phases. Moreover cost of decision made at the
early phase of the projects would be more crucial than other phases, in term of its impact on the project life cycle costs
and overall viability of the project. Considering these facts, it is strongly recommended to implement risk analysis in the
early phase of the projects.(Chen, et al.,2009) The nature and complexity of the project are key criteria in the level of
risk analysis in projects. So, risk management is more important and significant in complex and large scale projects than
conventional projects. Today, it is widely accepted as a vital tool in the management of such projects and variety of
guidelines have been published, for this purpose (Wood and Ellis, 2003)
As addressed by Caspary (2008), Large capital projects “Super Projects” in addition to the primary risks which affect all
projects, face with secondary risks such as social, environment, political risk which make financers and other
stakeholders more concern about such risks and influence the project viability. Super projects are faced with a
combination of different qualitative and quantitative, controllable and uncontrollable factors. Risk management is
particularly important in these type of projects with large capital investment, new technology and complex legal and
contractual arrangements (Kangari and Riggs,1989) These type of risk can be assessed by traditional and advanced
methods as well, in order to go beyond the narrow project level in assessing these risks.(Caspary ,2008)
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Moreover, the uniqueness of investment projects, large dynamics of internal and external conditions of the host country
with many unknown parameters, make investment decision burdened with risk (Rebiasz,2007),, so risk analysis is known
as a standard supporting tool for investment decision / project appraisal ((Hertz,1968) Deciding whether or not to invest
in development of a super project is a critical decision for investment companies.This type of decisions is characterized
by combination of uncertain and incomplete information. (Finch, et al.,2002). The
he main problem in investment decision
is to apply risk analysis technique
hnique in an appropriate way, considering type of projects, its common risks, the organization
condition, policies, knowledge and strategy. (Hacura, et al.,2002)
With respect the above explanation, the
he necessity and the potential benefits of developing a decision making model to
assess the viability of super projects in the pre
pre-appraisal phase are self evident. Decision making about the validity of
these types of project is too complicated to be made by simple traditional appraisal techniques. At present this is an
expensive, non-standard and ill-structured
structured process with serious consequences associated with an incorrect decision.
Hence new
ew research crossing the boundaries between three areas is needed. The decision making problem is modeled
based on three specific
ecific but usually discrete areas of knowledge: the characteristics of super projects, risk management
methods and decision making models.
3.
Modeling Process
In order to develop a decision making model the author adopted a rational sequence of activities. As an initial step all the
significant characteristics of super projects, which distinguish them from conventional projects were identified, using
previous research findings and an extensive literature survey, (Warnock,1978), (Moolin,1978
Moolin,1978), (Healy,1981),
(Ihsanallah,1978). Analyzing theses characteristics, as sources of risks, common risk factors in super projects which
could occur in the majority of super projects and could have a high likelihood of occurrence and a significant impact on
their outcome were identified.
The mainn groups of common risk factors were found to be: political/legal risk factors, financial risk factors, economic
risk factors, technical risk factors, design risk factors, management risk factors, resources risks and logistics risks, as
presented in figure 1.. In order to identify individual common risk factors the main groups of common risk factors were
broken down. First, a long list of risk factors was created. Based on
n their likelihood of risk occurrence, their impact and
the views of experienced industrialists consulted by questionnaire the preliminary
reliminary list was reduced
re
to thirty-five
common risk factors.
Fig. 1: Common Risk Factors Associated with Super Projects
Political /
Legal
Technical
Management
Financial
Common
Risks in
Super
Projects
Resources
Economic
Logistics
Desigh
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In order to develop the model, different decision making methods were reviewed. According to Chen et al, (2009),
despite the wide application of quantitative methods of risk analysis, it is important to look at subjective issues that may
not be revealed by objective data, this type of risks are more familiar in non conventional projects with political,
legislation, social, environmental, technological and other sources of complexity in decisions with subjective and
expertise knowledge. In this type of projects risk analysis shall include an assorted mix of quantitative techniques as
well as subjective issues (Chen, et al.,2009). As stated by Rebiasz (2007) Subjective assessment of project risk in
appraisal phase is the attention of many researches and real projects due to this fact that quantification of investment
risks is the most difficult task in risk analysis of investment project appraisal
Moreover, decision making in investment projects faces many criteria with different importance, so MCDM methods are
more appropriate than conventional methods.(Chen,et al.,2009) A Multiple- Criteria Decision Analysis facilitates
balance and trade off between different and even opposite criteria. As point out by Caspary (2008), MCDM facilitates
decision process and its outcomes by structuring the decision analysis procedure and applying team work approach.
Considering the advantages of the MCDM method and subjective nature of the problem, a multiple criteria uncertain
decision making problem with data of both objective and subjective nature, the author selected AHP method, developed
by Saaty (1980), as the most appropriate method for this case. It is a multiple criteria decision making method with
possibility to apply to objective as well as subjective problems. It assists decision makers in simplifying complex
problems and in using experts’ judgment to overcome them (Alidi,1996), (Vargas,1990).
The simplicity of building models and the successful application of AHP models to many real problems are important
features of the AHP method (Zahdi,1986), (Liberatore,1987). The AHP method is operated in four steps. Fist: the
problem is downed into interrelated decision elements and the decision hierarchy is structured. Then: based on the
hierarchical structure of the problem a pair- wise comparison of decision elements is undertaken. In the third step the
weightings of the decision elements are calculated. Finally to determine the overall weightings, the estimated weightings
of decision elements are combined. According to the scale of pair- wise comparison in the AHP method a number
between 1 and 9 inclusive is assigned to each pair-wise comparison. Scale 1,3,5,7,9 present the equal importance,
moderate importance, essential importance, and very strong importance of one factor against the other one, respectively.
Scales 2,4,6,8 refer to Intermediate values (Zahdi,1986).
4.
Explanation of the Model
According to the AHP method, in order to develop the model the hierarchical structure of the problem should be
established. As the identified common risk factors do not have equal significance they need to be prioritized. Using the
AHP method and pair- wise comparison of risk factors, the relative impact of common risk factors was determined.
Utilizing questionnaire the necessary data for pair-wise comparison was gathered. Based on the gathered data, the
common risk factors were classified into three priority groups. Political and financial risk factors have the highest
weight, technical, design, and resources risk factors have the moderate weight and management, logistics and economic
risk factors have the lowest weight. Taking into account the priority groups, a multiple stage decision making model was
developed.
According to this model, the viability of the super projects is assessed in tree stages; first the viability of the project from
financial and political aspects is determined. In the case of the acceptability of the project risk, decision making process
will be continued. Otherwise it will be rejected or further investigation or some revision on the political and financial
factors will be proposed. In the second stage of the decision making process, the viability of projects from technical,
design and resources aspects are evaluated. Stage II of the model is implemented in a similar manner to stage I. Stage III
similar again but utilizing the economic, management and logistics aspects.
Each stage of model comprises of confirmation of risk factors, estimation of the relative impact of risk factors, through
the pair-wise comparisons, estimation of the likelihood of risk occurrence, calculation of the degree of project risk and
finally making a decision about moving to the next step and validating the project or stopping the process. In the first
stage of the decision making process that is represented in figure 1, the viability of super projects is assessed against the
political and financial aspects.
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Fig.2:General Structure of the Risk Analysis Based Model for Super Projects Pre- Appraisal
Stage I of Decision Making Process
Stage I
Analysis of the Political Risks
Analysis of the Financial Risks
Political Risks
Financial Risks
No Decision
Yes Decision
Rejection or Revision of the Project
Stage II of Decision Making Process
Analysis of the Design Risks
Analysis of the Technical Risks
Analysis of the Resources Risks
Stage II
Technical Risks
Design Risks
Resources Risks
No Decision
Yes Decision
Stage III of Decision Making Process
Analysis of the Managerial Risks
Analysis of the Economic Risks
Analysis of the Political Risks
Stage III
Economic Risks
Managerial
Risks
No Decision
Yes Decision
The Project Can be Approved
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Political Risks
First the two main groups of risk factors are compared based upon their impact on the project by pair-wise comparisons.
Pair-wise comparison determines how important is political aspect of the project when is compared to the financial
aspect with respect to their impact on the project. According to the scale of pair- wise comparison a number between 1
and 9 inclusive is assigned to each comparison, as explained above.
Considering the hierarchical structure of the model, figure 1,in the assessment of project risk the overall weight of each
risk factor must be taken into account. Combining risk factors’ weights through the hierarchy, the global weight
(composite weights) of each risk factor is calculated. In order to evaluate the project risk, in addition to the estimation of
the risk factors’ weights (impact) their likelihood of occurrence need to be estimated, using three subjective values low,
moderate and high.
5.
Case Study
In order to investigate the realism of the proposed model, using data gathered from a real super project, it was tested on a
major petrochemical plant.(Nazari, 1999) It was a multinational super project based in a host country, another county
partially guaranteeing off-take and involving a construction contractor and a process contractor from two different
countries. The estimated cost of project was about US $1 billion with 3 years duration. The project has been currently
put on hold (in year 200), because of difficulties in arranging the project finance, insufficient guarantees from the off
taking government and changes on their opinions. In order to apply the proposed model to assess the viability of this
super project, the necessary information and knowledge were captured by interview. Data associated with identification
of risk factors, estimation of their impact by pair-wise comparison of risk factors, and an estimation of their likelihood of
occurrence were considered.
Using the Expert Choice Software (EC- TM) (Exper Choics Software, 2010), the gathered data are applied on the
proposed model. According to the first stage’s result, the total weights(impact) of risk factor with high, moderate, or low
likelihood of occurring are 0.725, 0.172 and 0.10 respectively. Consequently, the project is classified as high risk
project. Based on the first stage’s result it would be too risky to validate the project, unless the project is supported by
some external political and financial guarantees. Comparing the model output with the current situation of the project,
which has been put on hold, it can be demonstrated that for this case the proposed decision making model addresses
realistic concerns and produces output that is realistic.
6.
Discussion
This paper has outlined a simply structured, three stage model for providing decision support to the extremely difficult
and important problem of assessing the viability of a super project. The model is generic and can be used for any type of
super project.
Despite the simplicity of the model, it requires complicated and detailed information that has to be collected for each
project separately and the time and cost implications of this should not be overlooked. Experts’ opinions, judgments
and expertise are the main sources of data required for implementation of the proposed model. In order to gather more
reliable data, a range of experts’ opinions and judgments should be taken into account. Furthermore, by using the Expert
Choice software (ECTM) to execute the model, it provides additional facilities which permit the calculation of the
inconsistency ratio of pair-wise comparisons; hence the possible biases and errors on the judgments should be detected
and reduced.
As a demonstration and after eliciting experts’ knowledge and expertise, the proposed model was tested on a real super
project. It was found that despite the complexity of data, based on experts’ knowledge and expertise the necessary data
for the implementation of the proposed model can be elicited. Finally, comparing the current situation of the case study,
with the model’s outputs it was found that the model is able to reflect the real situation of the project. The next step
development would be to prototype the model on a live super project.
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