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T he success parameters for anyproject are in time completion,within a specific budget and withrequisite performance (technical

requirement). The main barriers in achiev-ing these are changes that occur in theproject environment. The problem multi-plies with the size of the project as uncer-tainties in project outcome increases with

size. Large-scale construction projects areexposed to uncertain environmentsbecause of the following factors.

• planning and design complexity;• presence of various interest groups

(project owner, owner’s project group,consultants, contractors, vendors etc.);

• resources (materials, equipment,funds, etc.);

• availability;• climactic environment;

• the economic and political environ-ment; and

• statutory regulations.

Although risk and uncertainty affect allprojects, size can be a major cause of risk.Other risk factors include the complexity of the project, the speed of its construction, itslocation, and its degree of unfamiliarity.

A cross-country petroleum pipelineconstruction project is characterized by thecomplexity of its execution with respect tolack of experience in relation to certaindesign conditions being exceeded.

These conditions can include waterdepth, ground condition, pipeline size etc.

Other conditions include the influ-ence of external factors that are beyondhuman control. External causes can limitresource availability, including the areas of techniques and technology. Various envi-

ronment impacts, government laws andregulations, changes in the economic andpolitical environment, cost and time over-

runs and the unsatisfactory quality of aproject are the general sources of manage-ment disappointment with a pipelineorganization.

A conventional approach to projectmanagement (as shown in figure 1) and aspracticed by the organization studied inthis article is not sufficient. It does notenable the project management team toaccomplish the following.

• establish an adequate relationship

among all phases of the project;• forecast project achievement for building confidence of project team;

• make decisions objectively with thehelp of an available database;

• provide adequate information foreffective project management; and

• establish close cooperation among theproject team members.

The objective of this article is to modela decision support system (DSS) throughrisk analysis for making objective decisions

on project planning, design, engineering,and resource deployment for completing aproject on time, within budget, and in linewith project objectives, organizational poli-cy and the present business scenario.

Proposed Project ModelFigure 2 illustrates the proposed

project model. Project planning, designand detailed engineering should be takenup in sequence as soon as a project getsapproval. Materials procurement and

works contract preparation start concur-rently with completion of design activities.The availability of funds, materials, draw-ings, specifications, contract document,and other utilities are initiated and imple-mented at the work site by contractorsProjects are controlled through effectivemonitoring of various performance param-eters that are fixed during the planningphase. Just after project planning, risk man-agement with respect to time achievementand covering all project phases is carried

Cost Engineering Vol. 44/No. 3 MARCH 2002 13

Project Risk Management: A Combined Analytic HierarchyProcess and Decision Tree Approach

Dr. Prasanta Kumar Dey

TECHNICAL A RTICLE

ABSTRACT : Time, cost and quality achievements on large-scale construction projectsare uncertain because of technological constraints, involvement of many stakeholders,long durations, large capital requirements and improper scope definitions. Projectsthat are exposed to such an uncertain environment can effectively be managed withthe application of risk management throughout the project life cycle. Risk is by naturesubjective. However, managing risk subjectively poses the danger of non-achievementof project goals. Moreover, risk analysis of the overall project also poses the danger of

developing inappropriate responses. This article demonstrates a quantitative approachto construction risk management through an analytic hierarchy process (AHP) anddecision tree analysis. The entire project is classified to form a few work packages. Withthe involvement of project stakeholders, risky work packages are identified. As all therisk factors are identified, their effects are quantified by determining probability (using

AHP) and severity (guess estimate). Various alternative responses are generated, listingthe cost implications of mitigating the quantified risks. The expected monetary valuesare derived for each alternative in a decision tree framework and subsequent probabil-ity analysis helps to make the right decision in managing risks. In this article, the entiremethodology is explained by using a case application of a cross-country petroleumpipeline project in India. The case study demonstrates the project management effec-tiveness of using AHP and DTA.

KEY W ORDS: Risk management, work break down structure, analytic hierarchy process,decision tree analysis, cross-country petroleum pipeline, and time-cost control

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14 Cost Engineering Vol. 44/No. 3 MARCH 2002

out. Risk management with respect tocost achievement should be carriedout before implementing work.

The scope of this article is limitedto establishing risk management afterthe project was approved.

Risk and Risk Management Process

C.B. Chapman and D.F. Cooper,[3] define risk as, “exposure to the pos-sibility of economic or financial loss orgains, physical damage, or injury, ordelay as a consequence of the uncer-tainty associated with pursuing acourse of action.” The task of riskmanagement can be approached sys-tematically by breaking it down intothe following three stages.

• risk identification;• risk analysis; and• risk responses

Rao Tummala and Y.H. Leung,[17] developed a methodology for riskmanagement that looks at risk identifi-cation, measurement, assessment,evaluation, risk control and monitor-

ing. Their methodology was devel-oped for managing the cost risk of anEHV transmission line project.

T.M. Williams [19] examined var-ious project risk managementresearch. He describes various riskidentification and analysis tools beingused by researchers and practitionersand the management structures andprocedures needed to manage risk.

J.R. Turner [18] suggests usingexpert judgment, plan decompositionassumption analysis, decision drivesand brainstorming for effective identi-fication of risk factors for a projectJ.G. Perry and R.W. Hayes [15] pres-ent a checklist of risk that may occurthroughout the life span of any proj-ect. The Delphi technique has been

used by P.K. Dey [7] for identificationof risk factors. Outside the field ofengineering and construction, anapproach for risk identification inproduct innovation has been reportedby Jim Halman and J.A. Keizer [12].

Most of the analyses done so farare centered on analyzing the dura-tion of the project. Management isinterested in two aspects; the total

Figure 1—Conventional Project Management Model

Figure 2—Proposed Project Management Model

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duration and which activities are critical indetermining that duration. Many authorshave presented the distribution of timeduration of activities as classical Beta distri-bution [10]. J. Berny, [1] proposed his owndistributions for practical simulations. P.K.Dey used Monte Carlo simulation for ana-

lyzing project risk of petroleum pipelines[8].

Recently, a number of systematic mod-els have been proposed for use in the risk-evaluation phase of the risk-managementprocess. R. Kangari and L.S. Riggs [13]classified these methods into two cate-

gories: classical models (i.e. probabilityanalysis and Monte Carlo simulation), andconceptual models (i.e. fuzzy-set analysis)They noted that probability models sufferfrom two major limitations. Some modelsrequire detailed quantitative informationwhich is not normally available at the timeof planning, and the applicability of suchmodels to real project risk analysis is limit-ed, because agencies participating in theproject have a problem with making pre-cise decisions. The problems are ill

defined and vague, requiring subjectiveevaluations that classical models cannothandle.

There is a need for a subjectiveapproach to project risk assessment, withobjectivity in the methodology. The analytic hierarchy process (AHP) developed byT.L. Saaty [16] provides a flexible and easi-ly understood way of analyzing projectrisks. It is a multi criteria decision-makingmethodology that allows subjective as wellas objective factors to be considered in

Table 1—Scale of Relative Importance for Pair-Wise Comparison

Intensity Definition Explanation

1 Equal importance Two activities contribute equallyto the object3 Moderate importance Slightly favors one over another5 Essential or strong importance Strongly favors one over another7 Demonstrated importance Dominance of the demonstrated

importance in practice9 Extreme importance Evidence favoring one over

another of highest possible orderof affirmation

2, 4, 6, 8 Intermediate values When compromise is needed

Source: T.L. Saaty, The Analytic Hierarchy Process [16].

Figure 3—Risk Management Flow Chart

Project Plan

Work Breakdown Structure

Implement

Risk Assessment• Identify Risks• Assess Risks• Determine Consequence

scenarios• Determine Control Measure

Review thework package

plan

Yes

Yes

No

No

I s t h

e

r e s i d

u a l

r i s k

t o l e

r a b l

e ?

D o a n y o f t h e

w o r k

p a c k a

g e s

n e e d

a r i s k

a s s e s s

m e n t ?

W o r k p

a c k a g e

1

W o r k

p a c k a

g e 2

W o r k p a

c k a g e 3 e

t c.

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project risk analysis. The AHP allows theactive participation of decision-makers inreaching agreement and it gives managersa rational basis on which to make decisions.

Formulating the decision problem inthe form of a hierarchical structure is thefirst step. In a typical hierarchy, the toplevel reflects the overall objective or focusof the decision problem. The elementsaffecting the decision are represented inintermediate levels. The lowest level com-prises the decision options. Once the hier-

archy has been constructed, the decision-maker begins the prioritization procedureto determine the relative importance of theelements in each level of the hierarchy.The elements in each level are comparedpair wise with respect to their importancein making the decision that is under con-sideration. The verbal scale used in an

AHP enables the decision-maker to incor-porate subjectivity, experience, and knowl-edge in an intuitive and natural way. Afterthe comparison matrices have been creat-

ed, the process moves on to the phase inwhich relative weights are derived for thevarious elements. The relative weights othe elements of each level with respect toan element in the adjacent upper level arecomputed as the components of the nor-malized eigenvector associated with thelargest eigenvalue of their comparisonmatrix. The composite weights of the decision alternatives are then determined byaggregating the weights through the hierar-chy. This is accomplished by following apath from the top of the hierarchy to eachalternative at the lowest level, and multi-plying the weights along each segment ofthe path. The outcome of this aggregationis a normalized vector of the overallweights of the options. The mathematicalbasis for determining the weights has beenestablished by T.L. Saaty [16].

Conventionally, risk analysis is per-formed at the overall project level. The riskanalysis should show the effects of the riskfactors on the project performance in termsof time, cost, and quality goals. Althoughrisk analysis at the project level may be suf-ficient for a small project from the invest-ment-decision and feasibility-study point ofview, the technique has its limitations forlarge projects.

D.F. Cooper [4] suggested that, in therisk-engineering approach, systematic riskevaluation could be performed by subdi-

viding a project into its major elementsand analyzing the risk and uncertainty asso-ciated with each in detail. Moreover, theseverity of risk pertaining to a project variesfrom activity to activity. Some activities aremore responsive to a specific risk than oth-ers. To risk analyze a project, the level ofactivity for which risks are to be analyzedhas to first be determined.

M.A. Mustafa and J.F. Al-Bahar [14]applied the AHP in risk analysis for theassessment of risk in a construction project

Table 2—Comparison Matrixes in Factor Level

Factors Technical Financial Organizational Acts of Clearance Likelihood

Risk & Economic Risk God Risk Risk

Risk

Technical Risk 1 3 4 5 5 0.479

Financial and Economic Risk 1/3 1 2 4 3 0.228

Organizational risk 1/4 1/2 1 2 3 0.146

Acts of God Risk 1/5 1/4 1/2 1 2 0.064

Clearance Risk 1/5 1/3 1/3 1/2 1 0.083

Consistency Ratio: 0.042. acceptable

Table 3—Likelihood of Risk in a Project

Factors Likelihood Sub-factors LikelihoodLP GP

Technical Risk 0.479 Scope change 0.36 0.172Technology selection 0.124 0.059Implementation methodology 0.13 0.062Equipment risk 0.073 0.035Materials risk 0.08 0.038Engineering and design change 0.233 0.112

Financial 0.228 Inflation risk 0.152 0.035& Economical Fund risk 0.383 0.087Risk Changes in local law 0.105 0.024

Changes in Govt. policy 0.105 0.024Improper estimate 0.255 0.058

Organizational 0.146 Capability of owner’s project 0.106 0.015Risk group

Contractor’s capability 0.283 0.041

Vendor’s Capability 0.448 0.065Consultant’s Capability 0.163 0.024

Acts of God 0.064 Calamity Normal 0.44 0.028Calamity abnormal 0.56 0.036

Clearance risk 0.083 Environmental clearance 0.026 0.022Land acquisition 0.461 0.038Explosive clearance 0.133 0.011Other clearances 0.142 0.012

LP—Local percentageGP—Global percentage

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from the evaluation perspective. P.K. Dey,[5] applied AHP for cost risk analysis of aconstruction project

This article adopts AHP for analyzingrisk in the project and uses decision treeanalysis (DTA) for selecting specific riskresponses for specific work packages fromvarious alternatives.

Decision trees use calculations of expected monetary value (EMV) to meas-ure the attractiveness of alternatives. Theyalso use graphical models to display severalrelevant aspects of a decision situation.These graphical models consist of treelikestructures (hence the name) with branchesto represent the possible action-event com-binations. The conditional payoff is writtenat the end of each branch. A tree givesmuch the same information as a matrix,but, in addition, it can be used to depict

multiple-stage decisions. These are a seriesof decisions over time[9].

A decision tree approach does the fol-lowing.

• It logically structures risk managementphilosophy by identifying alternativeresponses in mitigating risk.

• It provides a basis for quantitative riskmanagement.

• It incorporates management percep-tions.

MethodologyThe methodology adopted for risk

management in this article is explained inthe following steps.

• Identifying the work packages for riskanalysis.

• Identifying the factors that affect thetime, cost, and quality achievement ofa specific work package.

• Analyzing the effect by deriving thelikelihood of the occurrences in an

AHP framework.

• Determining severity of failure byguess estimation.

• Driving various alternative responsesfor mitigating the effect of risk factors.

• Estimating cost for each alternative.• Determining the probability and sever

ity of failure of a specific work packageafter a specific response.

• Forming a decision tree.• Deriving expected monetary value

EMV or the cost of risk response inthis case.

Table 3—Likelihood of Risk in a Project (continued)

Sub-factors River X-ing Pipeline Station Other WorkLaying Construction Packages

LP GP LP GP LP GP LP GPScope change 0.17 0.029 0.39 0.067 0.31 0.053 0.13 0.022technology selection 0.29 0.017 0.23 0.014 0.11 0.007 0.37 0.022implementation methodology 0.47 0.029 0.26 0.016 0.17 0.011 0.1 0.006

equipment risk 0.33 0.012 0.21 0.007 0.28 0.010 0.18 0.006materials 0.17 0.007 0.35 0.013 0.26 0.010 0.22 0.008eng.. and design change 0.37 0.041 0.33 0.037 0.13 0.015 0.17 0.019

Inflation 0.25 0.009 0.25 0.009 0.25 0.009 0.25 0.009Fund 0.25 0.022 0.25 0.022 0.25 0.022 0.25 0.022local law 0.18 0.004 0.18 0.004 0.19 0.005 0.25 0.006policy 0.25 0.006 0.25 0.006 0.25 0.006 0.25 0.006estimate 0.43 0.025 0.43 0.025 0.17 0.010 0.08 0.005

Capability of owner’s project 0.33 0.005 0.3 0.005 0.27 0.004 0.1 0.002group Contractors capability 0.37 0.015 0.33 0.014 0.22 0.009 0.08 0.003

Vendors Capability 0.21 0.014 0.29 0.019 0.4 0.026 0.1 0.007

Consultant Capability 0.49 0.012 0.13 0.003 0.15 0.004 0.23 0.005

Calamity Normal 0.41 0.012 0.35 0.010 0.14 0.004 0.1 0.003Calamity abnormal 0.32 0.011 0.47 0.017 0.09 0.003 0.12 0.004

Environmental 0.25 0.005 0.25 0.005 0.25 0.005 0.25 0.005Land acquisition 0.13 0.005 0.51 0.020 0.3 0.011 0.06 0.002Explosive clearance 0.25 0.003 0.28 0.003 0.36 0.004 0.11 0.001Other clearance 0.25 0.003 0.25 0.003 0.15 0.002 0.35 0.004

Overall Likelihood of failure 0.286 0.317 0.229 0.169

Rank 2 1 3 4

LP—Local percentage, GP—Global percentage

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• Selecting the best option through sta-tistical analysis.

ApplicationThe above steps will be explained

through the case of a cross-country petrole-um pipeline project in the western part of

India. The pipeline has a length of 1300km. Its diameter is 22 inches for a length of 1112 km, 18-inches for a length of 218 km,and 10.75 inches for a length of 123-km (abranch line). The pipeline is designed for 5million metric tons per annum (MMTPA)throughput. The project also consists of the

construction of three pump stations, onepumping-cum-delivery station, two scraper

stations, four delivery stations, and two ter-minal stations. The project cost was esti-mated as 600 million in US dollars. Adetailed description of the project is avail-able in Dey’s Planning for Project ControlThrough Risk Analysis, A Case of aPetroleum Pipeline Laying Project [5].

Figure 3 shows a flow chart for riskmanagement. A risk management groupwas formed to do a risk analysis study forthe project in this article. The group con-sisted of one member each from mechani-cal, electrical, civil, tele-communication,instrumentation, finance, and materials ofproject function. They were entrusted withcollecting data, analyzing, interpreting andpreparing recommendations with activeinteractions with the project groups.

Identification of Work PackagesThe total project scope was decom-

posed and classified to form a work breakdown structure (see figure 4). The first levelis project, the second and third levels arework packages, and the forth level is activi-ties of each work package. Based on theimportance of achieving time targets, thefollowing work packages were consideredfor risk management.

• river crossing;

Table 4—Risk Mapping in Project Level

S

everity

High

Medium

Low

Table 5—Probability and Severity of Risk Factors

Risk Factors Probability Severity

Time Costover-run Over-run(in months) (in Millions)US $)

Scope change 0.172 8 90

Engineering and design change 0.112 5 30Technology selection 0.059 6 20

Land acquisition 0.038 4 0

Contractors capability 0.041 6 30

Vendors Capability 0.065 8 30

Calamity abnormal 0.036 12 90

Implementation methodology 0.062 3 0

Fund availability 0.087 2 0

Improper estimate 0.058 2 0

Materials risk 0.038 3 0

• Calamity normal • Land acquisition • Scope change• Technology selection• Engineering and Design change• Contractor’s capability• Vendors capability• Calamity abnormal

• Change in policy • Implementation• Capability of methodology

owner’s project • Fund riskgroup • Improper estimate

• Consultant’s • Materials riskcapability

• Inflation risk• Environmental

clearance• CCE clearance• Other clearances

Low Medium High

Probability

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• pipeline laying;• stations construction; and• telecommunication and SCADA

system

Identification of Risk FactorsThe risk factors and sub-factors were

identified with the involvement of execu-tives working through brainstorming ses-sions. These executives had more than 15years of project work experience. In thebrainstorming session, they were given achecklist of risk that was initially used toidentify risk factors and sub-factors. Theexecutives next used group consensus todevelop a risk structure.

The following are the risk factors andsub-factors of the project used in this arti-cle.

Technical Risk

• scope change;• technology selection;• implementation methodology

selection;• equipment risk;

• materials risk; and• engineering and design change

Acts of God

• normal natural calamities; and• abnormal natural calamities

Financial, Economical and Political Risk

• inflation risk;• fund risk;• changes of local law;

• changes in government policy; and• improper estimation

Organizational Risk

• capability risk of owner’s project group;• contractor’s failure;• vendor’s failure; and• consultant’s failure

Statutory Clearance Risk

• environmental clearance;

• land acquisition;• clearance from chief controller of

explosives (CCE); and• other clearance from government

authorities

Formation of Risk StructureThis article focuses on two dimensions

of risk; its probability and severity. The riskperception, as shown by J.R. Turner [18],has not been considered because of thenature of construction risk. Figure 5 shows

the AHP model for risk analysis. Level 1 isthe goal of determining the riskiness of theproject. Levels 2 and 3 are for factors andsub-factors respectively. Level 4 containsthe alternatives or work packages.

Pair Wise ComparisonThe AHP model was made in an

Expert Choice software package developedby E.H. Forman and T.L. Saaty [11]. Pairwise comparisons were made through exec-utives working on projects in a group deci-

Table 6—The Cost Data (Million US $) for Each Package Against Various Responses

Responses Pipeline River Station Telecommun- Buildinglaying crossing Construction ication & CP & colony

construction

Carrying out detailed survey with the objective 12 6 6 3 3

of minimum scope and design change

Selecting technology and implementation 3 6 4 1.5 1.5

methodology on the basis of owner’s /

consultant’s expertise, availability of

contractors and vendors and lifecycle costing

Executing design and detailed engineering on 1 1 1 1 1

the basis of selected technology and

implementation methodology and detailed

survey

Selecting superior contractors, consultants and 22 16 10 2 2

vendors on the basis past performance

Scheduling project by accommodating 6 - 4 - -

seasonal calamities

Planning contingencies and acquiring 11 2 6 1 1

insurance

Ensuring the availability of all statutory 1 1 1 1 1

clearance before design and detailed

engineering

Total 56 32 32 10 10

Grand total 140

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sion-making process, using the informationfrom Table 1. A questionnaire was madeand distributed individually to the execu-tives so they would not be influenced byeach other. A risk management group ana-lyzed the responses. Table 2 shows a com-parison matrix of the factor level. The out-come of matrix operation shows the likeli-hood of these risks occurring while the

project is being executed.The pair wise comparison in other lev-els also shows the likelihood of occurrence

of risk sub factors. Synthesizing all of therisk factors and sub-factors across hierarchyforms shows the overall likelihood of fail-ure of the work packages. Table 3 shows thedetailed analysis of the AHP model.

Results and Findings From Risk AnalysisStudy

Technical risk is the major factor fortime and cost overrun of a project. Withinthe technical risk category—scope change,

engineering and design change, technolo-gy, and implementation methodologyselection are the major causes of projectfailure. The pipeline laying and stationconstruction work packages are vulnerablefrom scope changes. Technology selectionis vital for the river crossing and telecom-munication packages. Engineering anddesign changes are quite likely for the river

crossing and the pipeline laying work pack-ages. A prior selection of implementationmethodology is crucial for the river cross-

Table 7—The EMV for “Pipeline Laying Project”

Decision Alternatives Cost Probability Effect Expected Value EMV*

(million of failure ** Time Cost Time Cost (million US$)

US$) (months) (million (months) (million

US$) US$)

Do nothing 0 0.317 12 22 3.8 6.97 35.5

Carrying out detailed survey 12 0.158 2 4 0.32 0.64 15

Using superior technology 3 0.158 12 22 1.9 3.5 21

Engaging expert project team 22 0.317 2 4 0.64 1.3 28

Taking all responses as 56 0.05 2 2 0.1 0.1 56.9

indicated in table

*EMV = 0 + 3.8 X 7.5 + 6.97 = 35.5

(Return on investment is 7.5 million US $ per month i.e. 15% of 600 million US $ per annum)

** Basis for probability figuresDecision Alternatives Basis for Probability figures

Do nothing From Table 3

Carrying out detailed survey 50 percent of “do nothing”Using superior technology 50 percent of “do nothing”

Engaging expert project team Same as “do nothing”

Taking all responses as indicated in table Assumption: probability of failure is five percent


of failure Time Cost Time Cost (million US$)

(months) (million (months) (millionUS$) US$)

Do nothing 0 0.286 15 40 4.3 11.44 43.7

Carrying out detailed 12 0.143 15 40 2.15 5.72 33.85

survey and using

superior technology

Engaging expert 16 0.286 8 20 2.3 5.72 39

project team

Taking all responses 32 0.05 2 8 0.1 0.4 33.15

as indicated in table

Table 8—The EMV for “Pipeline Laying Across River”

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ing packages, as improper selection couldcause major time and cost overruns. Theunavailability of pipe materials and delayeddelivery of pumping unit sometimes resultsin a considerable time overrun.

Other major risk categories for projectachievement are financial, economic, and

political risk (F&ER) and organizationalrisk. Among F&ER, fund flow problemsand improper estimates are the major caus-es of concerns. All the packages are equal-ly vulnerable from fund flow problems.However, the river crossing and pipelinelaying packages are prone to problems from

improper estimates because there are moreuncertainties in the design and implemen-tation methodology selection. Althoughthe organizational risk is less vulnerable forthe project under study, consultant andcontractor’s capabilities are of concern tothe management of the project. The rivercrossing work package is the most suscepti-ble to problems from the performance ofconsultants and contractors. The capabili-

ty of the owner’s project group is requiredfor achievement of all the work packages.

Although the project under study isnot that vulnerable from statutory clear-ance risk, care should be taken in gettingenvironmental clearance and explosiveclearance on time for a trouble free imple-mentation.

Normal and abnormal calamities arethe part and parcel of any pipeline projectMany times project executives rate these asunimportant and not likely to occur


of failure Time Cost Time Cost (million US$)

(months) (million (months) (million

US$) US$)

Do nothing 0 0.229 12 24 2.75 5.5 26.2

Carrying out detailed 9 0.115 0.6 12 0.7 1.32 15.06survey and using

superior technology

Engaging expert 10 0.229 2 0.4 0.46 0.92 14.5

project team

Taking all responses 32 0.05 2 4 0.1 0.2 33


Table 9—The EMV for “Station Construction”

Decision Alternatives Cost Probability Effect Expected Value EMV*of failure Time Cost Time Cost (million US$)

(months) (million (months) (million

US$) US$)

Do nothing 0 0.169 2 2 0.34 0.34 3

Carrying out detailed 4.5 0.085 2 2 0.17 0.17 5

survey and using

superior technology

Engaging expert 3 0.169 0.5 1 0.085 0.17 3.8

project team

Taking all responses 10 0.05 0.5 1 0.025 0.05 10.25


Table 10—The EMV for “Telecommunication and SCADA System”

Work package Risk response

pipeline laying Carrying out detailed survey

pipeline laying across river Taking all responses as indicated in tablestation construction Engaging expert project team

telecommunication and SCADA system Do nothing

Total cost for risk responses is 65.65 million US$ which is much lower than 140 mil-lion US$.

Table 11—The Decisions Emerge From the Decision Tree Approach of RiskManagement for Each Work Package

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However, these factors are vulnerable forall work packages and appropriate contin-gency plans are strongly recommended foreach package.

The pipeline laying work package isthe most risky package with a probability of failure of 0.317. The major factors for pos-sible failure are changes in scope, changesin engineering and design, fund availabili-ty, vendors capability, abnormal natural

calamity and land acquisition. The rivercrossing work package with a probability of failure of 0.286 comes next. The main con-tributing factors are scope changes, imple-mentation methodology selection, engi-neering and design change, and improperestimates. The station construction workpackage is vulnerable from scope changesand has a 23 percent probability of failure.

Risk Mapping All the factors were organized as per

their probability and severity (effect ontime and cost) characteristics as indicatedin table 4. The factor scope change hasbeen identified as the most vulnerable forthe project under study as it has a highprobability of occurrence, as well as highseverity. If there is a change in scope of anyof the work packages, there will be consid-

Figure 4—Work Breakdown Structure of “Cross-country Petroleum Pipeline” project

Figure 5—AHP model for determining riskiness of project

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erable implications on design, planning,and implementation of the program. Thesewill cause considerable time and cost over-runs in the project. Factors like land acqui-sition, technology selection, engineeringand design changes, contractor’s capability,vendors capability, and abnormal calamity

are rated as having medium probability, asadequate planning for the project understudy prompts the executives to perceivethese factors as less vulnerable. However,the project will end up experiencing amajor time and cost overrun, if any of theabove factors occur during the project

implementation. Implementation method-ology, fund risk, improper estimate, andmaterials risk are rated as having mediumprobability of occurrence, as well as severi-ty. The other factors are perceived as eitherlow probability or low severity. The factorswhich have low probability and high sever-ity should be handled carefully with thedevelopment of contingency plans.

Overall Impact on ProjectThe factors that are in the zones hav-

ing medium to high probability and severi-ty were considered for further study. Theseverity of the risk factors was calculatedwith independent consideration to theireffect on each work package and on eachphase (planning, design, materials, con-tract preparation and implementation)Project executives were actively involved inthese calculations. Table 5 shows the prob-

ability and severity of all risk factors.The above results were used to derive

the expected time and cost overrun alongwith the respective standard deviationsusing the following formula [2].

Let X be a random variable. The rthmoment of X about zero is defined by

if X is discrete, (equation 1)or

if X is continuous (equation 2)

The first moment about zero is themean or expected value of the random vari-able and is denoted by µ; thus µ’1 = µ =E( X ).

Again, the rth central moment of X orthe rth moment about the mean of X isdefined by

if X is discrete, (equation 3)or

if X is continuous (equation 4)

Do nothing

Detailed survey

All response

Expert project team

Superior technology

-12

-56

-22

-3

P = 0.95

P = 0.842Failure

P = 0.683Failure

P = 0.317No failure

Failure

P = 0.05No failure

P = 0.317No failure

P = 0.842Failure

P = 0.158No failure

P = 0.158No failure

P = 0.683No failure

Time(Months)

Cost(Million US $)

12

2

0

12

0

2

0

0

0

2

0

2

0

4

0

22

0

4

0

22

Figure 6—Decision Tree for Pipeline Laying Work Package

Figure 7—Decision Tree for River Crossing Work Package

Do nothing

Detailed surveyand superiortechnology

All response

Expert project team

-12

-32

-16

P = 0.857Failure

P = 0.714Failure

P = 0.286No failure

Failure

P = 0.05No failure

P = 0.714Failure

P = 0.246No failure

P = 0.143No failure

P = 0.95

Time(Months)

Cost(Million US $)

15

2

0

8

0

15

0

0 0

8

0

20

0

40

0

40

µ ’r = Ε(Χ r ) = Χ r p(x)

xΣ

µ r = Ε(Χ− µ )r = ( x-µ )r p(x xΣ

µ ’r = Ε(Χ r ) = ∫ Χ r f (x)dx

+∝

−∝

µ r = Ε(Χ− µ )r = ∫ ( x-µ )r f(x)dx+∝

−∝

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owner’s/consultant’s expertise, avail-ability of contractors and vendors andlifecycle costing.

• Execute design and detailed engineer-ing on the basis of selected technologyand implementation methodology anda detailed survey.

• Select superior contractors, consult-ants and vendors on the basis of past

performance.• Schedule project by accommodatingseasonal calamities.

• Plan contingencies and acquire insur-ance.

• Ensure the availability of all statutoryclearances before doing design anddetailed engineering work.

Table 6 shows the estimated cost of theabove risk responses for each work package.Sources for the cost data are the detailedfeasibility report and cost estimate for the

project along with looking at other recentlycompleted projects and quotations fromvendors and contractors.

The next step is to form a decision treefor each work package considering theprobability and severity of failure and vari-ous possible responses.

The group arrived at the followingdecision alternatives.

• do nothing;• carrying out detailed survey (or addi-

tional survey work);• using superior technology;• engaging an expert project team; and• taking all responses as indicated in the

tables included with this article.

Figures 6, 7, 8, and 9 show the deci-sion trees for the work packages (pipelinelaying, pipe laying across river, station con-struction, and telecommunication andcathodic protection) of the project understudy. The probability and severity (timeand cost) for each decision alternative are

derived from the risk analysis study of eachpackage and the expert opinions gainedthrough brainstorming.

The expected money values (EMV)are then calculated for each alternativedecision for all the packages. Tables 7-10show the calculations of decision treeapproach of risk management. Table 11shows the decisions emerge from the deci-sion tree approach of risk management.

T his study suggests a project man-agement model with the applica-tion of risk management princi-ples. A decision support system

(DSS) has been developed in an analytichierarchy process (AHP) and decision treeanalysis (DTA) framework. This helps themanagement of projects and helps in mak-ing objective decisions. The DSS identifies

risk factors that are inherent in the project,analyzes their effect on various activities,and derives responses in line with projectobjectives, the organization’s policy, andbusiness opportunities.

Risk is by nature subjective. However, AHP allows one to objectively analyze theeffect of risk on a project by determiningthe probability of its occurrences. Theprobability and severity of each risk factorare determined through the active involve-ment of field experienced persons in aninteractive environment. The information

is collected in a very structured format inline with AHP requirements and processedusing available computer programs.

Additionally, sensitivity utility of AHP pro-vides an opportunity to the risk manage-ment group to observe the nature of modeloutcomes in different alternative decisionsituations. DTA helps in selecting fromamong various decision alternatives. Riskmanagement using a combined AHP andDTA approach provides the following ben-efits.

• Although most of the risk analysismethodologies quantify risk by deter-mining probability and severity of riskfactors, they do not identify responsesobjectively. However, the combined

AHP and DTA approach not onlydetermines probability and severity of risk factors, but also identifies riskresponses for each work package usingan expected monetary value concept.This approach is especially requiredfor large-scale projects because there

are many outcome uncertainties.• It provides an objective basis to man-agement for additional investment inplanning or for engaging superior con-sultants, contractors, and suppliers forspecific work packages or items.

• It defines the roles of project stake-holders in responding to specific riskfactors and it provides a basis of controlto the owner or management.

• It develops an algorithm to model acomputerized decision support system

using an integrated risk managementapproach. It combines identificationof risk factors, analyzes their effects,allows responses through desiredactions and controls these responses inan interactive way by involving allproject stakeholders. Using sensitivityanalysis at each step provides manage-ment with an ongoing bases for deci-

sions.

General benefits can be achieved fromthe application of risk management in anytype of project, including the followingbenefits.

• The issue/problems are clarified andallowed for from the start of the proj-ect.

• Decisions are supported by thoroughanalysis of available data.

• The structure and definition of the

project are continually and objectivelymonitored.

• Contingency planning allows promptcontrolled, and pre-evaluated respons-es to risk issues that materialize.

• There are clearer definitions of thespecific risk associated with a project.

• It builds-up of a statistical profile of thehistorical risk and this allows bettermodeling for future projects.

• It encourages problem solving andprovides innovative solutions to therisk problems within a project.

• It provides a basis for project organizational structure and appropriateresponsibility matrix.

Specific benefits, achieved by applyingrisk management techniques in managingthe study project, include the following.

• Problems encountered while executing a project were identified duringthe planning phase. This helped inmaking suitable responses for effective

project management. Responsesincluded alternative design and engi-neering, engaging superior consult-ants, contractors and vendors.

• Critical activities were identified andappropriate responsibilities were pre-pared for managing these critical activ-ities.

• Use of a risk management methodolo-gy helped complete the project with-out any time or cost overruns.

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