Economic Computation and Economic Cyberneti cs Studies and Research, Issue 2 2016, Vol. 50 [602932]

Economic Computation and Economic Cyberneti cs Studies and Research, Issue 2 /2016, Vol. 50
________________________________________________________________________________

165

Marcel Ioan BOLOS, PhD
University of Oradea
Diana Claudia SABĂU -POPA, PhD
Professor Emil SCARLAT, PhD
Ioana -Alexandra BRADEA, PhD
E-mail: [anonimizat]
Camelia DELCEA, PhD
The Bucharest Academy of Economic Studies

A BUSINESS INTELLIGENCE INSTRUMENT FOR DETECTION
AND MITIGATION OF RISKS RELATED TO PROJECTS
FINANCED FROM STRUCTURAL FUNDS

Abstract: The Structural Funds, in order to produce the intended effects,
must use their specific management tools, for achieving the strategic objectives,
outcome indicators and elements of added value set by each EU member state. The
project portfolios must be managed properly. If risks of a project become
contagious for other projects, we are witnessing a phenomenon that can
compromise the chance that a p rogram financed by Structural Funds to be well
carried out. In this paper it is introduced an algorithm to reduce the project
implementation risk and an IT interface is designed to serve as a control system,
for the permanent measurement and monitoring of the risk indicators, in order to
facilitate decision -making and prediction .
Keywords: IT interface, dashboard, portfolio risk management,
implementation r isk, structural funds .

JEL Classification: C30, G17, O22.

I. Introduc tion:
In recent years Business Intelligence techniques and tools became more and
more attractive, being used almost in all the large companies in the world, for
analysis, measuring, monitoring, control and decision. In order to achieve the
strategic objectives, the management should pre dict all the stable processes and
should control all the unstable processes. In project management, the structural
funds cannot produce the intended effects if aren’t used some specific AI tools,
which determines the achieving of the strategic objectives, using the structural
funds, outcome indicators and elements of added value set by each EU member
state.
The manifestations forms of the risk are different, from the risk of delay in
preparing t he documentation that highlights the economic sustainability of the
project, to the risk arising from delays selecting the suppliers. All these risks have
in common the time required for completion of stages in the life cycle of a project.

Marcel Bolos, Diana Sabau – Popa, Emil Scarlat, Ioana Bradea, Camelia Delcea
_________________________________________________________________
166

Whatever the del ays, they will have a direct impact on the duration of the project
implementation, which is important from the perspective of project budget,
outcome indicators and the achievement of project objectives. [Pirciog ,
Ciuca, Popescu, 2015]
The control Dashboar d fun ctions by the same laws as the D ashboard of a car
or airplane, including tables, graphs, figures, GPS, indicators that reflect the
desired destination and route. So, the Dashboard reflects the evolution and trend of
the key risk indicators and key per formance indicators, by monitoring their
continuous measurement. Dashboard connects the project with management in real
time, providing benefits due to the large number of people who see the results
every day, increasing the quality of decisions.

II. The Dashboard: An IT Interface that monitors the projects
The D ashboard can be considered a management information system , a
business intelligence tool that displays all of the required information on a single
screen, clearly, in order to be understood by ever y user. The Dashboard represents
an IT interface that transforms data into information; is a cognitive tool which
allows to: identify trends, patterns and irregular ities for decisions and control
[Delcea C., Bradea I.A. , Scarlat E. 2013 ].
A Dashboard gives the management the insights: indicates everything the
CEO needs to run the show. The dashboards created with the current software can
display: graphics, trend analysis, forecasts and dynamic drill -down buttons.
The processed data can be retrieved from var ious sources, analyzed from
several perspectives and distributed on the web and on mobile devices. The main
advantage of this methodology is the simplicity of design. Thus, all information is
presented as simple and concise; avoiding unnecessary graphics. The D ashboard
indicates when an action is required and directly provide s any additional
information required to take that action.
For designing and implementing a Dashboard some steps must be followed:
focus on data, know the users, tool selection, use vis ual design concepts, develop
the indicators, develop the levels of data and threshold, create a prototype, display
information on a single screen, ask for feedback and conduct trainings.
The Dashboard monitors the exposure to critical business risks by usi ng key
risk indicators (K RIs), which alerts when the accepted value s of the threshold are
passed . It offers a direction to follow and information regarding the risk event. It is
used as an alarm signal for further actions.

III. Projects financed from structural funds
The projects financed from structural funds have become a ve ry interesting
topic, with medium and long term challenges, due to the fact that the risk
identification and the subsequent implementation of strategies to reduce or even
disposal the risk , are major concerns of specialists and organizations that provide
structural funds management. Furthermore, the structural funds are today , for most
Member States of the European Union , an instrument for : the implementation of

A Bu siness Intelligence Instrument for Detection and Mitigation of Risks Related
to Projects Financed f rom Structural Funds
__________________________________________________________________
167

sustainable develop ment policies to eliminate the regional development disparities ;
promot ing investment s; creating jobs and ensur ing a high standard of living for the
EU citizens .
Structural Funds are attractive for any Member State due to their
particularities; they are not refundable and have no immediate financing cost,
which makes the beneficiaries of funds to lead a fierce battle between them to
access these resources during the calls projects organized by organizations
competent in the field. Compared to re payable funds, in the banking or capital
market, the Structural Funds protect the beneficiaries’ cash-flow during the project
implementation, but also after that, in the post -deployment period, since they not
generate payments to financial institutions and the impact on the projects
sustainability is straightforward.
Often, projects that are not sustainable for fully funding from the mix of own
and borrowed sources , as they cannot generate sufficient cash -flows to repay the
financial liabilities to creditor s, become sustainable by using structural funds
through cost savings that are generate d by the lack of financing costs.
The operational programs remain tools for macro management , which seek
to implement strategic objectives of national and European political strategy , while
projects become specific tools for the operational program that ensure the
implementation of the objectives. Levels of objectives for the two instruments are
different. The general rule is that any operational program includes a p ortfolio of
projects, without the operational program cannot achieve its purpose . [Davidescu,
Paul Vass, Gogonea , Zaharia, 2015 ]
Here comes the interest of specialists in finance and information technology,
because these project portfolios must meet several prerequisites, namely: i) to be
mature projects ready to be implemented, ii) to be sustainable projects or to ensure
economic sustainability on medium and long term, iii) the project beneficiaries
must have the administrative c apacity to implement them.

IV. The project risk
Any project (P), regardless the funding source , is characterized by a life
cycle that can arise from the idea stage and can be ended with the completion of
implementation. Usually the life cycle of a project, important in terms of structural
funds , differ according to type; the infrastructure project has the life cycle between
3-5 years, while the small value projects, the non-infrastructure projects ha ve a
lifecycle that can reach up to 3 years.
On the entire life cycle of a project, the forms of risk are different, and the
interest for early detection becomes increasingly more interesting given that the
risk of any kind may embarrass the successful completio n of the project
implementation [Caglia no A.C., Grima ldi S., Rafele C. 2015] .
So the budget of a project can be distributed over different periods of time,
according to the schedule of cash -flows. In the absence of compliance with these
cash-flows, caused by delays in implementing the various stages of the life cycle of
the project, the consequences can be diverse. The most important consequence is

Marcel Bolos, Diana Sabau – Popa, Emil Scarlat, Ioana Bradea, Camelia Delcea
_________________________________________________________________
168

the loss of budgets allocated to Member States through operational programs. That
is why EU Member States, which provides structural funds management, will pay
special attention to risks a rising from delay in project implementation, which can
compromise the chance of development of the regions concerned to ensure a high
standard of living for citizens. In this context, the implementation risk of a project
becomes essential, having direct co nsequences, not only on the budget allocated to
EU Member States, but also on cash -flow deficits that can lead to a project .[Boloș
M.I, Sabău -Popa D.C., Filip P., Manolescu A., 2015]

V. Measurement techniques for the risk of implementation
In everyday langua ge of specialists, this category of risk is known as
physical progress. Without going into technical details, it is important to note that
from the beneficiary's perspective and from the perspective of finance and
information technology specialists, the implementation risk represents the situation
in which the project during the implementation stage is not completed on time. A
contractual dead line takes many forms: i) interim deadlines, ii) final deadlines.
Whatever their nature, the project may be affected by the implementation risk if
they are not respected [Hydari H. 2015] .
The immediate consequence is that the planned values of the project are not
realized, the project indicators are put in difficulty and what is worse, as we have
noted before, the budgets of structural funds allocated to the EU stated can be lost.
Regarding the implementation risk causes, they are diverse and often have a
technical nature, such as: a reduced technical capacity of suppliers to execute
contracts, lack of technical equipment necessary for the project implementation
etc..
What arouses the curiosity of this category of risk is the quantification
(measurement) met hod. It includes technical and financial elements that have an
impact on th is type of risk. The implementation risk can generate severe losses in
the budget of the EU member countries , where this type of risk is not proper
manage d.
It is important to note that on risk measurement occur s the project
implementation tim e(𝐷𝑖), for which the information is provided from the contracts
with the beneficiaries; and the actual execution time (𝐷𝑟), for which the
information is provided from the contracts with supplie rs. These terms determines
the delay degree of a project, determined as the ratio between the actual execution
time and the planned time (𝑔î=𝐷𝑟
𝐷𝑖×100)of the project .
The degree of delay in project implementation measures the likelihood of
losing a certai n part of the project value, as a consequence of implementation
contract failure. Therefore it is important to quantify the financial dimension of the
implementation risk and for this it can be taken into account the planned value of
the project in the implementation year(𝑝𝑉𝑃), which is also the y ear of analysis for
the project, adjusted with the degree of delay using a relationship of the form:

A Bu siness Intelligence Instrument for Detection and Mitigation of Risks Related
to Projects Financed f rom Structural Funds
__________________________________________________________________
169

𝑅𝑝=𝑝𝑉𝑃(1−𝑔î) (1)
The intensity of the implementation risk can be expressed in a percentage
form, if it is taken into account the project's value (VP), and the progression risk
(𝑅𝑝) according to the following relationship:

𝑅𝑝=𝑉𝑝−𝑝𝑉𝑃(1−𝑔î)
𝑉𝑝×100 (2)
According to this measurement conditions for the implementing risk, it could be
seen that whenever the degree of delay of a project has significant value, the
probability of losing a part of the project budget increases, which may lead to the
classificatio n of projects into three major categories: i) projects with low risk of
budget loss, ii) projects with medium risk of budget loss, iii) projects with high risk
of budget loss.

𝑅𝑝={0≤𝑅𝑝≤30;𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑠𝑤𝑖𝑡 ℎ𝑙𝑜𝑤𝑟𝑖𝑠𝑘𝑜𝑓𝑏𝑢𝑑𝑔𝑒𝑡𝑙𝑜𝑠𝑠
30<𝑅𝑝≤50;𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑠𝑤𝑖𝑡 ℎ𝑚𝑒𝑑𝑖𝑢𝑚𝑟𝑖𝑠𝑘𝑜𝑓𝑏𝑢𝑑𝑔𝑒𝑡𝑙𝑜𝑠𝑠
𝑅𝑝>50;𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑠𝑤𝑖𝑡 ℎℎ𝑖𝑔ℎ𝑟𝑖𝑠𝑘𝑜𝑓𝑏𝑢𝑑𝑔𝑒𝑡𝑙𝑜𝑠𝑠 (3)

If the implementing risk affects one or more projects, it is probable that a
part of the budget alloca ted to EU country to be lost by decom mitment , as
unconsumed budgets by European rules are lost. In this situation , with the
identification of the implementing risk, it is necessary to take further measures to
restore the safety of their implementation and to ensure the achievement of the
planned project s.

VI. The reduction algorithm of the project implementation risk
The informational algorithm is based on specific assumptions for each
project under implementation and on a number of statistical processing
mechanisms specific to portfolio theory. Furthermore, the specific instruments for
Structural Funds assume that the operational program is used nationwide by the
Member States, while projects are part of the operational program. The rule of
structural funds is that the operational program includes several projects(𝑃);
∑𝑃𝑖𝑛
𝑖=1. The projects, that are part of the operational program, have their
particularities as they are non -infrastructure or infrastructure projects.
The reduction algorithm for the project implementation risk aims to establish
the structure of portfolios of projects given a level of implementation risk,
considered reasonable and to establish the portions of the project value that is
affected by risk. The value of projects affected by risk be comes a source of
information and a decision support for the national organizations of EU Member
States, as it indicates the value of the Structural Funds budge t that may be at risk of
losing [Tams S., Hill K., 2015] .
In terms of risk mitigation algorithm, each project (P) , which is part of the
portfolio of projects , will be defined by : the weight that holds on the total of the

Marcel Bolos, Diana Sabau – Popa, Emil Scarlat, Ioana Bradea, Camelia Delcea
_________________________________________________________________
170

project s value(𝑥𝑝), the value of implementation risk (𝑅𝑝)and the dispersion of risk
compared to the average value recorded in the projects portfolio(𝜎𝑝).
The dispersion value of implementation risk from the average is important
to measure its intensity, given that any departure from the average would mean an
increased risk with adverse effects on the project portfolio. That is why, f or the
dispersion measurement is used the standard deviation, adapted to the specific of
the projects:
𝜎𝑝2=∑(𝑅𝑝𝑖−𝑅𝑝̅̅̅̅)2
𝑁−1𝑛
𝑖=1 (4)
Since the measurement value of the implementation risk dispersion towards
medium is measured in (%)2, it is necessary to appeal to a different notion of
statistics for the dispersion measurement from the mean: the variance, that is
quantified after a relatio nship of the form:

𝜎𝑝=√𝜎𝑝2=√∑(𝑅𝑝𝑖−𝑅𝑝̅̅̅̅)2
𝑁−1𝑛
𝑖=1 (5)

According to the above, the project portfolio is formed as part of the operational
program, in which each project will be characterized by: the weight that holds in
the portfolio of projects, the implementation risk value and the risk dispersion from
the mean𝑃(𝑥𝑝,𝑅𝑝,𝜎𝑝). The equations that will be the basis of the reduction
algorithm of the project implementation risk will be written as:

{𝑅𝑝=∑𝑥𝑘𝑅𝑘𝑘
𝑖=1
𝜎𝑝2=∑𝑥𝑘2𝑛
𝑖=1𝑅𝑘2+2∑𝑥𝑘𝑥𝑗𝜎𝑘𝑗𝑛
𝑖=1 (6)

In addition to the above equations, it is known that the project proportion in
the total portfolio is equal to 1, according to an equation of the form:

∑𝑥𝑖=1𝑛
𝑖=1 (7)

In these conditions will be identified the underlying assumptions of the reduction
algorithm for the project implementation risk , while a risk value over 50% can lead
to a risky portfolio that generates losses in EU Member States' budgets .
Rewriting these equations according to the above assumptions, which aim to
reduce: the risk below 50% and the average dispersion towards the medium value
of the implementation risk , using a set of equations o f the form:

{𝑅𝑝=∑𝑥𝑘𝑅𝑘≤50𝑛
𝑘=1
𝜎𝑝2=𝑚𝑖𝑛∑∑𝑥𝑗𝑥𝑘𝑛
𝑘=1𝑛
𝑗=1 𝜎𝑘𝑗
∑𝑥𝑘𝑛
𝑘=1=1 (8)

A Bu siness Intelligence Instrument for Detection and Mitigation of Risks Related
to Projects Financed f rom Structural Funds
__________________________________________________________________
171

To solve the optimization problem formulated above, we will write the
Lagrangean problem, which will be based on the objective minimizing function of
the variance from the average and the constraints for the average value of the
implementation risk. The Lagrangean problem becomes:

𝛼(𝑥𝑝,𝜏1,𝜏2)=𝑚𝑖𝑛∑∑𝑥𝑗𝑛
𝑘=1𝑛
𝑗=1 𝑥𝑘𝜎𝑘𝑗−𝜏1(∑𝑥𝑘𝑅𝑘𝑛
𝑖=1−50)−
𝜏2(∑𝑥𝑘𝑛
𝑘=1−1) (9)

The optimal conditions of the algorithm are obtained at the points where the first
order derivatives for variables and parameters 𝜏1;𝜏2 are zero, as follows:

{ 𝜕𝛼
𝜕𝑥𝑘=0;
𝜕𝛼
𝜕𝜏1=0;
𝜕𝛼
𝜕𝜏2=0; (10)

After some computations we obtain the following optimal conditions for
the informational algorithm, namely:

𝜕𝛼
𝜕𝑥𝑘=∑𝑥𝑗𝜎𝑘𝑗−𝜏1𝑛
𝑗=1 ∑𝑅𝑘𝑛
𝑘=1−𝜏2=0;
𝜕𝛼
𝜕𝜏1=∑𝑥𝑘𝑅𝑘𝑁
𝐾=1−50=0; (11)
𝜕𝛼
𝜕𝜏2=∑𝑥𝑘𝑛
𝑘=1−1=0;

To simplify the calculations, the above system can be written in a matrix of
form:

(𝑥1
𝑥2
.
𝑥𝑘)(𝜎11𝜎12…𝜎1𝑘
𝜎21𝜎22…𝜎2𝑘
……………
𝜎𝑘1𝜎𝑘2…𝜎𝑘𝑘)−𝜏1(𝑅1𝑅2…𝑅𝑘)−𝜏2(11…1)=0 (12)

From equation (11) it can be determined the weight that each project must have in
the total portfolio, according to the weights vector (X), the variance -covariance
matrix (σ), and the projects implementation risks vector (R) as follows:

𝑋×𝜎−𝜏1𝑅−𝜏2𝑒=0 (13)
or
𝑋=𝜏1𝜎−1𝑅+𝜏2𝜎−1𝑒 (14)

Marcel Bolos, Diana Sabau – Popa, Emil Scarlat, Ioana Bradea, Camelia Delcea
_________________________________________________________________
172

It is formed a system of two equations with unknowns (𝜏1)and(𝜏1), which
will take the following form:
{𝜏1𝑅𝑡𝜎−1𝑅+𝜏2𝑒𝑡𝜎−1𝑅=50
𝜏1𝑅𝑡𝜎−1𝑒+𝜏2𝑒𝑡𝜎−1𝑒=1

From solving the system of equations will be obtained the Lagrangean parameters
as:

𝜏1=|50 𝑒𝑡𝜎−1𝑅
1 𝑒𝑡𝜎−1𝑒|
|𝑅𝑡𝜎−1𝑅𝑒𝑡𝜎−1𝑅
𝑅𝑡𝜎−1𝑒𝑒𝑡𝜎−1𝑒|=50(𝑒𝑡𝜎−1𝑒)−𝑒𝑡𝜎−1𝑅
(𝑅𝑡𝜎−1𝑅)(𝑒𝑡𝜎−1𝑒)−(𝑅𝑡𝜎−1𝑒)(𝑒𝑡𝜎−1𝑅)

𝜏2=|𝑅𝑡𝜎−1𝑅 50
𝑅𝑡𝜎−1𝑒 1|
|𝑅𝑡𝜎−1𝑅𝑒𝑡𝜎−1𝑅
𝑅𝑡𝜎−1𝑒𝑒𝑡𝜎−1𝑒|=𝑅𝑡𝜎−1𝑅−50(𝑅𝑡𝜎−1𝑒)
(𝑅𝑡𝜎−1𝑅)(𝑒𝑡𝜎−1𝑒)−(𝑅𝑡𝜎−1𝑒)(𝑒𝑡𝜎−1𝑅)

The values obtained for Lagrangean parameters are replaced in equation (1 4) to
obtain the final structure of the portfolio, which consists of (𝑥1 𝑥2…𝑥𝑛) weights of
the form:

𝑥=1
(𝑅𝑡𝜎−1𝑅)(𝑒𝑡𝜎−1𝑒)−(𝑅𝑡𝜎−1𝑒)(𝑒𝑡𝜎−1𝑅)[(50(𝑒𝑡𝜎−1𝑒)−𝑒𝑡𝜎−1𝑅)𝜎−1𝑅
+(𝑅𝑡𝜎−1𝑅−50(𝑅𝑡𝜎−1𝑒)𝜎−1𝑒)]
To simplify the calculations we will proceed to some additional notation as:

𝑋1=𝑒𝑡𝜎−1𝑒;
𝑋2=𝑅𝑡𝜎−1𝑒=𝑒𝑡𝜎−1𝑅;
𝑋3=𝑅𝑡𝜎−1𝑅;
𝑋4=𝑋1𝑋3−𝑋22;

Accordingly to this, a simplified form of po rtfolio composition (P) will be :

𝑥=1
𝑥4[(50𝑥1−𝑥2)𝜎−1𝑅+(𝑥3−50𝑋2)𝜎−1𝑒] (15)

The structure of projects portfolio (P) is thus influenced by the value of
each project implementation risk, conventionally denoted (𝑅𝑝)and the variance
from the average implementation risk(𝜎𝑝), the obtained results being of the form:

A Bu siness Intelligence Instrument for Detection and Mitigation of Risks Related
to Projects Financed f rom Structural Funds
__________________________________________________________________
173

(𝑥1
𝑥2
.
𝑥𝑛)=(𝑎1
𝑎2
.
𝑎𝑛) (16)

The project value after the calculations is adjusted by implement ation risk
restricted to be less than 50%, denoted by (𝑉𝑝(𝐴𝑝)), which will be computed as the
difference between the initial project value (𝑉𝑝𝑖) and the adjustment value with the
project implementation risk ( (𝐴𝑝)=𝑉𝑃×𝑎𝑘, after a relationship of the form:

𝑉𝑝=𝑉𝑝𝑖−𝐴𝑝 (17)

The new adjusted value of the project will provide information on the
portion of the project that is not affected by risk, when there is a likelihood of
implementation below 50% previously established as a value till the risk of project
budget loss is below 50 %.
The value of the portfolio risk, while there is a project implementation risk
below 50%, can be expressed by the relationship:

𝜎𝑝2=(𝑥1𝑥2…𝑥𝑛)(𝜎11𝜎12…𝜎1𝑛
𝜎21𝜎22…𝜎2𝑛
…………
𝜎𝑘1𝜎𝑘2…𝜎𝑘𝑛)(𝑥1
𝑥2
.
𝑥𝑛) (18)

The weights ( 𝑥1𝑥2…𝑥𝑛) are the recalculated weights for projects in the
portfolio, in terms of a n implementation risk below 50%, determined according to
the relationship (1 5).
This means that each project from the structure of the operational program
will have the value structure d into two components namely: ( (𝑉𝑝(𝐴𝑝)) determined
as the product of the project value and value share in total project projects ( 𝑎𝑘),
obtained by recalculation according to the implementation risk and a project value
at risk(𝑉𝑅𝑘), so that the portfolio of projects can be rewritten according to the
formula:
𝑉𝑃=(𝑎1𝑎2…𝑎𝑘)(𝑉𝑝1
𝑉𝑝2
.
𝑉𝑝𝑘)+(𝑉𝑅𝑘1𝑉𝑅𝑘2…𝑉𝑅𝑘𝑛) (19)
As the share of the value of the projects that are part of the portfolio
affected by risk (𝑉𝑅𝑘) is higher than the value unaffected by risk (or risk below
50%)(𝑉𝑝(𝐴𝑝)), we can say that the Structural Funds budget that is allocated to the
Member State is affected by the project implementation risk and there is a
probability to lose some of the budget by decom mitment risk. In the opposite

Marcel Bolos, Diana Sabau – Popa, Emil Scarlat, Ioana Bradea, Camelia Delcea
_________________________________________________________________
174

situation, the probability of losing resources from the Structural Funds budget is
quite limited, and that operational program management is properly implemented.
A new risk indicator is founded . It is useful for specialists in finance and
information technology, and is called the global implementation risk
indicator(𝑅𝑔𝑖), which provides information on the probability that an operational
program (which includes a portfolio of projects) generates losses from structural
funds of EU Member States, resulting from project implementation.
The overall implementation risk of operational programs may be
determined by the formula :
𝑅𝑔𝑖=∑𝑉𝑅𝑘𝑖𝑛
𝑖=1
∑𝑎𝑖𝑉𝑃𝑖𝑛
𝑖=1×100 (20)

In its simplest form, the overall implementation risk of operational
programs can take values(𝑅𝑔𝑖≥1), which implies that there is a risk of losing
resources from the EU budget allocated to the Member State. If ( 𝑅𝑔𝑖<1), implies
that structural Funds budget has a management that is correctly implemented
without the risk of losing the short -term financial resources.

VII. Decision -making interface for risk management of the national
organisms with responsibilities in the structural funds area

In any project management authority, there is a lot of information, even
computed indicators, but the information that is really needed are not known.
Dashboard has the ability to calculate, communicate and provide the adequate
information, relevant for policy formulation, decision making, and comparing the
results with the strategic objectives . The mechanism through which Dashboards are
used by national project management organism for decision making is re flected in
the following figure:

A Bu siness Intelligence Instrument for Detection and Mitigation of Risks Related
to Projects Financed f rom Structural Funds
__________________________________________________________________
175

Figure 1. The correlation between Dashboard and decision making process

Further, a Dashboard is built in order to monitor the key risk indicators of
the portfolio risk management. The analyzed portfolio consists of 10 projects
financed by the Structural Funds, for which are calculated the main indicators
reflecting th e implementation risk. The projects are implemented in the North –
West of Romania.

Figure 2.The key indicators computed within the reduction algorithm

Some thresholds were established, according to the formulas found in the
reduction algorithm of the project implementation risk. If a threshold was
exceeded, the risk manager automatically receives a message, to undertake urgent

Marcel Bolos, Diana Sabau – Popa, Emil Scarlat, Ioana Bradea, Camelia Delcea
_________________________________________________________________
176

remedial actions. The exceeding of thresholds is indicated by the colors of the risk
semaphore [Bradea I.A. , Sabău -Popa D., Boloș M. 2014] .
When the risk is in the red zone, are recorded significant losses, urgent
actions must be taken to control these los ses. When the risk is in the yellow zone,
the risk manager ha s to take actions in order toprevent the increasing of risk
exposure.

Figure 3.The key indicators computed within the reduction algorithm

For the analyzed portfolio, the initial average risk is 42.3%, being found in
the yellow zone and more worryingly close to the red zone. According to the
conditions of the implementing risk, it could be seen that whenever the average
risk is higher than 30%, the probability of losing a part of the proje ct budget
increases.
Of the 10 projects analyzed, 3 projects have the values for intensity of the
implementation risk over 0.33, reflecting a worsening of the situation, changes in
trend s and an increased exposure to risk, being necessary to take preventiv e
measures.4 projects registered high values for the considered risk, project number
7 having a value equal to 0.89 . It is also worth mentioning that the project number
8 is not expos ed to this risk.
The overall implementation risk of operational programs is determined. The
global risk of implementation takes the value of 0.5015, indicating a great exposure
to this risk, the losses emerging from it being large. Its value provides information
on the probability that the portfolio of projects generates losses from project
implementation .

A Bu siness Intelligence Instrument for Detection and Mitigation of Risks Related
to Projects Financed f rom Structural Funds
__________________________________________________________________
177

Figure 4. The Dashboard for monitoring the risk related to projects financed
from Structural Funds
As it is presented in the figure above, a fter applying the reduction
algorithm for the implementation risk, was identified a new structure of the
portfolio that would reduce the risk (xp). Also, a new adjusted value of the project
is computed, value that will provide informatio n on the portion of the project that
is not affected by risk.
VIII. Concluding remarks:
A portfolio with projects structure, whose implementation risk is below
50%, according to the algorithm assumptions provides the necessary conditions to
ensure a prudent str uctural funds management of EU Member States through
operational programs. Any value higher than 50% can lead to loss on long -term,
unless appropriate measures are taken to reduce this risk. The conclusion is that for
a certain value of projects implementa tion risk and its dispersion from the mean,
will have to be a certain structure of the projects portfolio to ensure that the risk of

Marcel Bolos, Diana Sabau – Popa, Emil Scarlat, Ioana Bradea, Camelia Delcea
_________________________________________________________________
178

budget loss for each project is within the values set as acceptable for the
operational program.
The project portfolios ar e the key of success for using Structural Funds by
EU members, so once they are implemented; there are equal opportunities to be
successful . During project implementation inevitable risks emerge. If risks of a
project become contagious for other projects, we are witnessing a phenomenon that
can compromise the chance that a program financed by Structural Funds to be well
carried out. Therefore the concern of specialists in finance and information
technology should be focused on two ways, namely: i) early ide ntification and
quantification of risk, to ensure an efficient management to save these projects, ii)
establishment of informational risk reduction algorithms related to portfolios of
projects, falling within the stru cture of an operational program.
The permanent monitoring of the implementation risk should be realized
with the help of a Dashboard. Thorough it, the KRIs gives information about the
level and trend of the implementation risk , which may affect the budget for each
project.

REFERENCES

[1] Bradea I.A. , Sabău -Popa D.C., Boloș M.I.(2014), Using Dashboards in Business
Analysis ;Annals of the University of Oradea . Economic Sciences , Tom XXIII, 1st issue,
pp. 851 -856, ISSN: 1582 -5450, ISSN: 1222 -569X ;
[2]Boloș M.I, Sabău -Popa D.C., Filip P., Manolescu A. (2015), Development of a
Fuzzy Logic System to Identify the Risk of Projects Financed from Structural
Funds ; International Journal of Computers Commu nications & Control , 10(4), pp.
480-491,ISSN: 1841 -9836;
[3]Cagliano A.C., Grimaldi S., Rafele C. (2015), Choosing Project Risk
Management Techniques. A Theoretical Framework ; Journal of Risk Research , vol.
18, issue 2, pp. 232 -248, ISSN: 1366 -9877;
[4] Davidescu A., Paul Vass A.M., Gogonea R.M., Zaharia M. (2015), Evaluating
Romanian Eco-InnovationPerformances in European Context ;Sustainability, 7(9),
12723 -12757, ISSN 2071 -1050, http://www.mdpi.com/2071 -1050/7/9/12723/htm ;
[5] Delcea C., Bradea I.A. , Scarlat E. (2013), A Computational Grey Based Model
for Companies Risk Forecasting ; The Journal of Grey System , issue 3, vol. 25, pp. 70 –
83, Londra, ISSN: 0957 -3720 ;
[6] Hydari H. (2015), The Rules of Project Risk Management: Implementation
Guidelines for Major Projects ; Project Management Journal , vol. 46, issue 4, pp. e4,
ISSN: 8756 -9728 ;
[7] Pirciog S., Ciuca V., Popescu M.E .(2015), The Net Impact o f Training
Measuresf rom Active Labour Market Programs i n Romania –
Subjectivea ndObjectiveEvaluation ; ProcediaEconomicsandFinance , vol. 26, pp. 339
– 344;
[8] Tams S., Hill K. (2015), Information Systems Project Management Risk: Does it
Matter for Firm Performance? ; Journal of Organizational and End User Computing ,
vol. 27, issue 4, pp. 43 -60, ISSN: 1546 -2234.