J. Service Science & Management, 2010, 3, 181-185
doi:10.4236/jssm.2010.32022 Published Online June 2010 (http://www.SciRP.org/journal/jssm)
181
The Research of Risk Management in Two
Non-Independent IT System
Zhe Yin1,2, Yunfei Guo2, Maosheng Lai1*
1Department of Information Management, Peking University, Beijing, China; 2Mathematics Department, Yanbian University, Yanbian,
China.
Received March 30th, 2010; revised April 30th, 2010; accepted May 31st, 2010.
ABSTRACT
Enterprises use IT system in business sector/information management sector and production management sector on
purpose of the operation, which, of course, is inseparable from risk management. Two non-independent risk estimates
functions are hence founded in order to receive the information of risk easily, that is, the cash flow-based evaluation
functions. Applying the logarithmic probability-distribution function in the estimates function as well as giving an ex-
ample by simulating, this essay has explained the affection of the uncertain factors to the enterprise management such
as the business treatment and so on. At last, it has commented the application of the estimates function in the risk man-
agement.
Keywords: IT System, Non-Independent, Risk Management, Logarithmic Probability-Distribution Function
1. Introduction
The role of IT in business activities has been more and
more important; besides, the amount of its investment is
also increasing. The key of operating businesses more
effectively is to base on the operating principles and to
play the role of IT systems. The application of IT sys-
tems can not only apply to business operations and main-
tenance, but also to social services and business competi-
tion [1].
Japanese companies consulting firms Shigeru Inoue [2]
2000, proposed that the key of risk management is enter-
prise risk quantification, so the introduction of IT syst-
ems need to use the reorganization of business structu-
res [3], and through the systematic of business processes
to achieve business strategy and IT systems integration
and quantification of organic. UNISYS Corporation To-
shiaki Otsuka [4] also proposed risk management should
go through the entire IT system development, testing and
operation cycle. When meeting a bad objective environ-
ment, not only should we reconstruct the system, but also
give the risk management throughout the system life cycle.
In order to carry out the risk management of the chan-
ges in the external environment [5], this article deals only
with a risk quantification, to determine the percentage of
operating losses, and to reduce risk through information
sharing. First, the cash flow-based evaluation function
which can reflect the values of IT systems is embodied;
and considered the effects of IT investments and risk
prediction of two non-independent IT systems such as
knowledge management systems and intelligence proc-
essing systems. Knowledge management systems are the
IT systems of the operational management levels, while
intelligent processing systems for of IT systems which
are for the purpose of knowledge discovery, personaliza-
tion-depth study of levels.
This article gives the logarithmic probability distribu-
tion function and proposes specific statistical methods of
quantifying the risk. Ultimately, in order to adapt to so-
cial changes in the external environment, the application
of the evaluation function in the risk management is also
discussed.
2. The Role of Information Sharing
As a manager of IT systems, there is need to analyze
business strategy and decision-making, and to determine
the system operators who will invest in IT systems and
operators who can increase efficiency of the systems
through the application of IT systems. The system re-
sponsible for CIO and the CEO positions of different
operators are unlikely to adopt the same evaluation sys-
tems. In order to fully share information, using the same
assessment system and the introduction of discounted
cash flow method [6] are the preferred methods of eva-
luation function. As the evaluation function, not only can

The Research of Risk Management in Two Non-Independent IT System
182
it reflect their own business performance, but also accu-
rately can it reflect the risks to the business environment.
Therefore, in order to be prepared to risk, it is also nec-
essary to venture into visual (through statistical tables
and charts) besides quantifying, which can achieve a
more intuitive result.
3. The Cash-Flow Considered Evaluation
Function
In order to show the effect of IT systems, we introduce
the evaluation function (the cumulative efficiency), wh-
ich is composed of the IT investment costs, income and
value-added.
1
{()()
()}(,)
T
t
FI CopetCRt
CG tfr tOpbOpi

 

 (1)
where
I: construction costs of IT systems;
Cope(t): maintenance costs of IT systems;
CR(t): reduced costs within the enterprise;
CG(t): increased turnovers according to IT systems con-
struction;
T: lifetime of IT system;
Opb: added value of improving the business environ-
ment;
Opi: reduction effect of business management risk;
(,)
f
rt : function of the current conversion efficiency (r =
risk rate, t = time);
The main idea of constructing evaluation function F is
that the profit is equal to the difference between input
and income. Besides, the risk rate will change with the
change of the time .So F is a dynamic function.
and 1
(,) (1 )t
frt r  (2)
When the purpose of IT investments in the market is to
improve the enterprise’s competitive edge, the system
values is mainly in terms of increasing the value of the
amount of CG(t) and its business environment the added
value of Opb. And when for the management purposes,
the system performance in terms of cost reduction is in
the amount of the value of CR(t). When in order to im-
prove the business environment or to lay a good founda-
tion for business environment, importing IT systems to
reduce costs or improve enterprise efficiency does not
work at all.
The role of IT systems can be changed as the business
environment to reduce Opi (risk reduction) as its neces-
sity. The value of Opb, Opi and t can be used as the ref-
erence variable of the business environment, which can
be quantified by using options and other methods.
4. An Empirical Analysis of Aisk
Quantitative
4.1 Examples and Statistical Methods to
Quantify the Risk
Take medium-scale IT systems as an example, cost of the
project A has been shown in Table 1. Initial develop-
ment costs are 1 million yuan, annual maintenance costs
are 150,000 yuan, the annual loss of initial cost is 30%,
an annual increase of turnover is 20%, and value-added
based on customer satisfaction is 100,000 yuan. Assum-
ing that IT system life are 7 years, the investment benefit
evaluation function (expression (1)) = 1.1253 million
yuan. Cost of the project B is shown in Table 2. There is
no problem from quantity to consider, then how much
will the risks be?
The risk of cumulative incremental value of operating
benefits (expression (1)) can be expressed through the
probability distribution function, according to Pareto dis-
tribution theory, cumulative incremental value of operat-
ing benefits meets the log-normal distribution. Suppose
the best reduced cost per year of project A is 300,000
yuan, the minimum is 50,000 yuan, the maximum is
320,000 yuan, operational efficiency expectations is
200,000 yuan, the standard deviation is 50,000 yuan; he
best reduced cost per year of project B is 200,000 yuan,
the minimum is 65,000 yuan, the maximum is 250,000
yuan, operational efficiency expectations is 150,000 yuan,
the standard deviation is 30,000 yuan, and the correlation
coefficient of the two projects r = −0.2, the cumulative
incremental value of operating benefits meets the log-
normal distribution .
Table 1. Costing table of project A
Initial investment I 1 million yuan
maintenance costs s /year Cope 150,000 yuan
reduced costs within the enterprise /year CR 300,000 yuan
increased turnovers according to IT
systems construction /year CG 200,000 yuan
risk rate r (%) 5%
added value of improving the business
environment Opb 100,000 yuan
Table 2. Costing table of project B
Initial investment Ⅱ 600,000 yuan
maintenance costs s /year Cope 100,000 yuan
reduced costs within the enterprise /year CR 200,000 yuan
increased turnovers according to IT
systems construction /year CG 150,000 yuan
risk rate r (%) 4%
added value of improving the business
environment Opb 60,000 yuan

The Research of Risk Management in Two Non-Independent IT System183
According to expression (1), the 7-year total cumula-
tive increment economic benefits of project A is 60,230
yuan, 160,748 yuan and 177,280 yuan respectively when
the reduced cost of project A is 50,000 yuan, 300,000 yuan
and 320,000 yuan, respectively, and the corresponding
natural logarithm, is, respectively, −1.79558, 2.77725
and 2.875145. The standard deviation of normal distribu-
tion ln (5) = 1.600; the 7-year total cumulative increment
economic benefits of project B is 5,514 yuan, 92,286
yuan and 126,143 yuan respectively when the reduced
cost of project B is 65,000 yuan, 300,000 yuan and
320,000 yuan, respectively, and the corresponding natu-
ral logarithm, is −0.5953, 2.22 and 2.5348, respectively,
The standard deviation of normal distribution ln (3) =
1.100.
The logarithmic of cumulative incremental of economic
benefits of project A in the interval [−1.79558, 2.875145]
meets the normal distribution, and the logarithmic of cu-
mulative incremental of economic benefits of project B
in the interval [−0.5393, 2.5348] also meets the normal
distribution. We need only to find the probability of color
part in (Figures 1 and 2).
From
2 ut/2
()[() /],
1
2
px uu
uedt






  （）
We can obtain
( 1.795580){1(2.1590)}
{1(2.875145)}
{1[(2.1590-1.0795)/1.6]}
{1[(2.875145-1.0795)
pXpX
pX
 

 
 /1.6]}
{10.8686}{10.9582}
=0.0896
 
Similarly, we can obtain


(0.53930) 1.2340.7
0.88880.758
13.8%
pY
 



We can see that the probability that the logarithm of
benefit evaluation function of project A takes a negative
value is 8.96%, that is, the probability of investment
losses is 8.96%; the probability that the logarithm of
benefit evaluation function of project A takes a positive
value is 91.04%, that is not difficult to find the probabil-
ity that investments can yield results is 91.04%; the pro-
bability that the logarithm of benefit evaluation function
of project B takes a negative value is 13.08%, that is, the
probability of investment losses is 13.08%; the probabil-
ity that the logarithm of benefit evaluation function of
project B takes a positive value is 86.92%, that is not
difficult to find the probability that investment can bear
fruit is 86.92%.
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
Probability
-5 0 5
Logarithmic of cumulative incremental
of economic benefits of
p
ro
j
ect A
Figure 1. Normal distribution of project A
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
Probability
-5 0 5
Logarithmic of cumulative incremental of
economic benefits of project B
Figure 2. Normal distribution of project B
Finally, we proceed to study the risk of the two project,
that is the risk situation of
X
Y. The two projects A
and B are relevant, we can see that the pdf (probability
density function) of
Z
XY






2
22
22
22
1
22
XXYY
xab
r
Z
XXYY
px e
r

 


 ,
where




22
,~ ,;,;
XY
X
YNabr 

The Research of Risk Management in Two Non-Independent IT System
184
Proof
Since


22
,~ ,;,;
XY
X
YNabr 


 
2
2
22
22
1
,
21
1
exp21
2
XY
XY XY
pxy
r
r
xaxayb yb
r
 
 




















  
2
2
22
22
1
21
1
exp21
2
Z
XY
XY XY
px
r
r
zazaxzb xzb
rdz
 
 



















Let and vxab uza
We can obtain that



2
2
2
22
2
1
exp21
2
1
21
XY XY
Z
XY
r
uv uv u
ur
px
r
du
 
 









 










Besides

2
2
22
22 2
2
222 2
2
22
XY XY
XXYYXY
XYXY Y
uv uv u
ur
rv
uuv
 
  r




 



22
22
2
2
2
XXYY
XY
XY
YXXYY
r
u
r v
r















22
22
1
2
XXY
vr
rY

 


Let
22
2
2
1
1
XXY
XY
r
tu
r
Y

 





22
2
XY
YXXYY
r v
r







So


2
2
22
2
22
exp 22
22
t
XXYY
Z
XXYY
p
v
r
x
edt
r

 









Since vxab

 and
2
22
t
edt







2
22
22
22
1
22
XXYY
xab
r
Z
XXYY
px e
r

 



So ()1.0795 0.76221.8417EX YEXEY

 
22
2
1.9620.21.61.11.21
1.57
XYXX YY
r 
 



p
( 2.390880)
2.70 1.17
0.9965 0.8770
11.95%
XY


 


4.2 Result Analysis
You can see risks reduce when the two projects relevant
negatively from the above example, without considering
the effects of environmental change, risk reduction OPi.
Future research should take Opi into account. In particu-
lar, with the case of the recent stock market volatility of
the situation, the importance of risk management has
received considerable attention. Risk management can be
divided into the direct decision-making opportunities for
risk management and indirect risk management whose
profit has nothing to do with direct one. Both are closely
linked into enterprise efficiency and business. The pro-
motion of local management capacity can play through
regional or global risk management into operations ac-
tivities. As long as we handle of relations between local
interests the global economic correctly, the objectives
can be achieved by sharing resources, reducing risk, and
the best operation and management purposes.
5. Conclusions
Investment in IT systems is the key to quantifying of the
economic indicators during the application. Since the

The Research of Risk Management in Two Non-Independent IT System
185
top-down management style, is very difficult to forecast
the future assessment of corporate efficiency, this paper
presents the loss probability calculation method of risk
quantification and easily sharing of risk information me-
thod. (Figure 1, Figure 2) can play a function of profit
and loss evaluation of the effectiveness of visualization.
Future research purpose is the establishment of IT inve-
stsment and run-time system, real-time investment eva-
luation system in order to reduce investment risks.
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