The assessment of risks that threaten a project

Author:Cristina Maria Stoica - Boris Constantin - Marius Alexa
Position:Professor, Ph.D., 'Petre Andrei' University, Iasi - Lecturer, Ph.D., 'Gh. Asachi' Technical University, Iasi - Assistant, Ph.D.Candidate, 'Al.I.Cuza' University, Iasi
Pages:245-261
Cristina Maria Stoica, Boris Constantin, Marius Alexa
245
LESIJ NO. XIX, VOL. 2/2012
THE ASSESSMENT OF RISKS THAT THREATEN A PROJECT
Cristina Maria STOICA
Boris CONSTANTIN
Marius ALEXA
Abstract
A project consists of a number of interrelated tasks whose aim is to produce a specific result.
A project risk analysis consists of analyzing schedule, cost risk, quality of the final product etc. A
cost risk analysis consists of looking at the various costs associated with a project, their uncertainties
and any risks or opportunities that may affect these costs. The distributions of cost are added up in a
risk analysis to determine the uncertainty in the total cost of the project. A schedule risk analysis
looks at the time required to complete the various tasks associated with a project, and the
interrelationship between these tasks. In this paper we want to study the various risks associated with
the project. We start this study with the assumption that a project’s cost and duration are linked
together and also cost elements and schedule durations are correlated. The normal uncertainties in
the cost items are modeled by continuous distributions like the Pert or triangular distribution. For
project schedule modeling the most flexible environment is spreadsheet. We are interested in
building blocks that typically make up a schedule risk analysis (also a cost risk analysis) and then
show how these elements are combined to produce a realistic model. In the same time we want
implement software tools for run Monte Carlo simulations on standard project planning
applications.
Keywords: feedback loops, cascading risks, portfolios of risks, sensitivity analysis, Monte
Carlo simulations, critical path analysis, ModelRisk software
Introduction
A project consists of a number of interrelated tasks, whose aim is to produce a certain result.
Typically, a risk analysis on the achievement of a project implies the analysis of the risk regarding
the plan of the project and its cost. In some cases the analysis may also include other aspects, such as
for instance the quality of the final product. Risk may be defined as the possibility of the emergence
of an event that affects the achievement of technical or cost objectives, or of project terms. The risk is
aleatory, unpredictable, may be favorable, yet most of the times is unfavorable and thus, under these
circumstances the analysis and prevention of risks should be an utmost preoccupation for project
managers.
In this paper one intends to identify the risks that may appear during the executio n of a
project, as well as to identify techniques and methodologies of dealing with these risks. Since the risk
is usually tackled statistically and since the statist ical results are better only if the statistical
distributions used are closer to the distribution of real data, one emphasized here the creation of new
statistical distributions that would fulfill this requirement.
With this aim in view the team leaded by the author of this article created a library of
programs, named DistriRisk which is based on the following four methods of creating new

Professor, Ph.D., ”Petre Andrei” University, Iaşi (email: stoicacristinamaria@yahoo.com)
∗∗ Lecturer, Ph.D., ”Gh. Asachi” Technical University, Iaşi (email: borisconstantin@yahoo.com)
∗∗∗ Assistant, Ph.D.Candidate, ”Al.I.Cuza” University, Iaşi
246 Lex ET Scientia. Economics Series
LESIJ NO. XIX, VOL. 2/2012
distributions: the composition method, the „Rejection Sampling” (RS) method, the „Importance
Resampling” (IR) method and the Metropolis – Hastings (MH) algorithm. Using the random
generation of numbers, one also created a program for the generation of beta distribution, applicable
in the Monte Carlo method. All these new distributions are to be included in the pack of programs
ModelRisk developed by the company VOSE Consulting with its European headquarters in Belgium.
This paper also suggests another way to calculate the cost of a project by applying the central
limit theorem. Since the ordinance of a project is a simulation based on a privileged scenario for each
task, we hereby suggest the use of the Monte-Carlo method, which allows the exploitation of several
ordinances, combining different scenarios for the tasks of the project, an d leading to a probabilistic
analysis of certain information, such as the duration of the project or the probab ility for a task to be
difficult to achieve.
In the future we intend to develop a sampling algorithm based on the Latin hypercube
method, which will provide a sampling method that seems to be random but guarantees the
reproduction of the input distribution with greater efficiency that the one provided by the Monte
Carlo method.
Once this methodology is certified, we will try together with the specialists of the company
VOSE Consulting to tackle the quantitative calculation of risk, as well as the possibility to model it,
so as to evaluate as many projects as possible.
The risks of a project
The risks corresponding to the main stages of a project are the following: the analysis of the
needs, preparing the project and the execution of a project.
The analysis of the needs. There are four categories of risks that should be taken into
account before launching a project: - the risk of competition; - the risk of market (the commercial
situation);- commercial risks (the manufacture of the product, the relation cost / quality); -
technological risks.
The factors that may increase the risk could be the following: - the inexistence or the
incomplete previous research in the field of the project; - a need formulated in a wrong way; -
functions or restrictions unspecified by the user; - functions, whose complexity is inadequately
assessed when analyzing need, one also noticing an under-estimate of the level of difficulty that
requires expensive resources; - non-negotiable functions, imposing thus highly restrictive objectives
from a technical point of view or when it comes to price or terms, choosing some functional
performances without being in fact imposed by the needs; - not knowing norms and regulations
imposed on certain products.
Preparing the project. These analyses and conception considerations exert an important
effect in the stage of the execution of the project. In the second stage the following risks may be
mentioned:
- various flaws and constant hesitations in the first version of the project, to which one may
add an incomplete and less competent technical documentation;
- under-estimating the complexity of the methods and conception procedures (programs,
automatization microcontrollers), which leads to too little time spent for the learn ing of working
techniques;
- difficulties in defining and planning the stages mentioned in the program;
- the wrong assessment of the availability and performance of resources used; generally, there
is the tendency to over - estimate performances and to under-dimension costs, being too optimist in
what regards the terms;

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