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Risk lifecycle and risk relationships on construction projects
hernational
Journal of Project Management
1994 12 (2) 68-74
Risk management
Risk lifecycle and risk relationships on construction projects H Ren Department of Construction Management RG4 2BU. UK
and Engineering,
University of Reading,
Whiteknights,
Reading
The paper presents a new method of assessing the financial risk in construction projects. In this method, two elements are distinguished: the risk lifecycle and risk relationships between separate project risks. The risk lifecycle consists of two successive distinct periods: concealment and action. Through the risk relationships, the mutual effects and interactions between risks are analysed. An example is used to illustrate the advantages of using the risk lifecycle and risk relationships Keywords:
risk lifecycle:
concealment
and action, risk relationships
The construction industry is renowned as a high-risk industry. Construction projects involve complex, timeconsuming design and construction processes characterized by unforeseen circumstances. As a result, effective risk management has become a major problem that confronts the industry. The success of a project-management exercise depends very much on the efficient and effective management of the risks involved’-3. This paper suggests that an extra depth of knowledge is required for risk-management techniques to assess and predict accurately the consequences to a project of potential financial losses. The addition is the study of the character of the risks themselves. The character is described by the risk lifecycle. Relevant characteristics include time properties, influence relationships between risks, and associated cashflow consequences. The awareness of the need to understand the above characteristics has led to the development of two new concepts: the risk lifecycle, and risk relationships. In this paper, these concepts are incorporated into risk management at a practical level. A theoretical framework is developed, and is then applied to a case study to demonstrate its impact on current risk-management approaches.
A risk’s random features constitute its lifecycle. As Figure 1 shows, any risk generally has a period from the possible existence to the occurrence of the risk event. This period is called the concealment of the risk, and it is the first part of the risk lifecycle. For example, say there is uncertainty about the subsoil ground conditions on a site. If the structural designers have incorrect information, or they are unable to take due account of this uncertainty, the concealment of the subsoil risk is the period from the design of the substructure to the construction of the substructure. Once the risk event occurs, its action lasts for a certain period. This action is the second part of the risk lifecycle, and it is defined as the risk action. During this period, the risk action is embodied by overrun costs, delay, poor quality, and so on over a period of the risk action. These outcomes or consequences are generally referred to as the risk loss. The aim of studying the risk lifecycle is to put a time dimension into risk-analysis theory and application, which can provide users with a powerful time tool for dynamic risk management, thus enhancing risk prediction.
Risk
Start
lifecycle
Risks are associated with all projects in a dynamic environment. They are described by possible events’-3. Their random characteristics mainly embody the following aspects: l l
68
the uncertainty the randomness risk action;
as to the occurrence of the risk; of the start time and the duration of the
l
the randomness risk action.
time
of the risk loss over the period of the
and duration
of risk
Although risk management is a new field, many methods of dealing with risk have been used in the construction industry. However, the current theories of risk neglect the start time and the duration of the risk action, which are a necessary and important part of risk analysis. Take weather forecasting as an example. If we are informed that rain, wind or snow are likely, and to what degree, without the 0263-7863/94/020068-07
0 1994 Butterworth-Heinemann
Ltd
RISK
I_
MANAGEMENT
_b
Risk life cycle
The risk loss
I
Start time of the risk Tie
+-
Concealment
Figure 1
b
Action
Risk lifecycle
times and the duration of risk action, the technique of range estimating is used. This is one of the most effective methods of dealing with the problem of time uncertainty. This method uses three figures, min, ML and max, and a probability distribution4, such as the uniform, triangular, beta and normal distributions. min and mux are the two extreme start times or duration figures under abnormal conditions. ML is the most likely start time or duration under normal conditions.
start times and durations being stated, we are unsure about how to deal with the weather, because of the shortage of such vital information. As in weather forecasting, the start time and duration of the risk action are indispensable components in risk analysis. The advantages can be briefly expressed as follows: If the start time and duration of the risk action are estimated in advance, the scheme of the project can be systematically planned, controlled and managed in order to minimize the associated risk loss. If the cashflow of the risk loss can be predicted in advance, financial management can be carried out in a well thought-out-way.
Cashflow of risk loss For convenience, all the risk losses are transformed into money loss, and there is thus a sole criterion for comparison and decision. Only when the time concept is introduced into the risk loss can it be studied in a dynamic way. The cashflow of the risk loss gives an overall picture of the loss and the time relationship. Decision makers can clearly estimate the magnitude of the risk loss at any point in time. Owing to the variety of features of the risk action, there are many types of cashflow of risk loss. Losses from earthquakes and accidents exhibit a sudden and sharp damage increment within a very short time. Some economic risk actions first have a gradual rise and then fall. The cashflow of the risk loss may be continuous, discrete, and so on. The principle of determining the cashflow of the risk loss depends on the characteristics of the risk action,
The start time of the risk action is defined as the moment at which the risk event begins; it is a discrete time point. The duration of the risk is defined as the period between the start and the disappearance of the risk action. The magnitude of the duration of the risk action depends on its type, feature and existing environment. For example, some physical risk events, e.g. an earthquake, last a very short time, but some economic risks, such as inflation or an economic recession, can be sustained. As Figure 2 shows, the start time and the duration of risk action are the random variables. They vary within ranges with certain kinds of probability distributions. To illustrate the probability distributions of the start ---
l---------* Probability
distribution
of the start time of risk occurrence
/I\ Min
StartTie ML
~
l
i
Max
--------,___T:T---------_,
Probability distribution of the risk duration I I I I
Duration Min ,-__-_--------___~ Figure 2 International
ML
Max
WI
Start time and duration
Journal of Project Management
1994 Volume 12 Number 2
69
RISK MANAGEMENT
and the environment in which it exists. To study the risk lifecycle, one of the requirements is to have an overall estimation of the risk. The characteristics of the risk are described by two time periods: the concealment, and the action. The concealment period includes the start time and the occurrence probability of the risk event. The action period includes the duration and the loss of the risk event. Data and information about a risk lifecycle are given in Table 1.
Relationships
between risks
The characteristics of a risk are decided not only by its own features, but also by the influence of other risks in the system. In fact, risks in a system mutually affect, impede and promote each other. The independent risk seldom exists in reality. This kind of mutual influence among risks in a system is defined as the risk relationship. The study of this relationship can provide the following main benefits. It provides users with an analytical method of logical, inductive and deductive inference, and makes risk decisions possible on the basis of detailed understanding of the relationships between risks. It overcomes the shortcomings of statistical methods, which are too generalized, and, therefore, it enhances accuracy in decision making. Thus, the study of the relationships between risks should play an important role in risk analysis, and it could contribute to adequate risk management.
Basic patterns of risk relationship In reality, the relationships between risks are very complex and varied. If we classify or subclassify or further subclassify these relationships, we can obtain the basic patterns of a risk relationship. The classifications are independence, dependence, parallel and series.
project. This kind of relationship between risk A and risk B is defined as dependence. The graphical representation of a risk is a circle. The size of the circle has no significance, and the circle may assume any form. It may be square, rectangular, or hexagonal, to suit the needs of the model. The connection between risk A and risk B is an arrow that denotes the dependent relationship. In practice, the number of risks that are dependent on risk A can be more than one. As an example, if risk A, a reduction in labour productivity, occurs, it probably leads to the occurrences of risk B,, a delay in the completion of the project, risk B,, an escalation of the cost, risk B,, poor quality, and so on. A graphical representation of the dependence relationship is shown in Figure 3. Parallel In the parallel situation, more than one risk A,, A,, , A, together affect one or more risk B,, B2, . , B,,,. Under the condition in which one or more of A,, A,, , A,, occur, risk(s) B,, B,, . . ,B, probably occur. As an example, there are three risks: bad weather, materials shortages, and inappropriate plant. Once one or more of them have occurred, a delay in the progress of construction probably occurs. The graphical representation of the parallel situation is shown in Figure 4. Series In the series situation, more than one risk A,, A,, , A, together affect one or more risk B,, B,, . , B,. Only if these risks A,, A,, . . , A,, occur all together will risk(s) B,, B,, , B,,, probably occur. As an example, there are three risks. Risk A, is that of bad weather that is an uncertainty in a period. Risk A, is the scheduled planning for the construction of the substructure. If bad weather and the construction of the substructure occur together, then risk B, the overrun time of this project, possibly occurs. This series relationship is shown in Figure 5.
Independence Independence means that characteristics, such as the probability of occurrence, the start time, the duration and the loss of the risk are not affected by any other risks in the system. Correspondingly, this risk does not have any impact on the other risks.
With dependence, the occurrence of risk B is dependent upon the occurrence of risk A. If risk A occurs, then risk B probably occurs. If risk A does not occur, then risk B definitely does not occur. As an example, if risk A, a reduction in labour productivity, occurs, it probably causes the occurrence of risk B, a delay in the completion of the Table 1 Description min
ML
max
Probability
distribution
Start time, date
2/9/93
10/9/93
16/9/93
Uniform
-1
Duration,
1.0
1.4
2.2
Triangular
fSXl0
f6COO
f8000
Shape of risk loss [Probability
70
A
Risk
82
Risk
Bn
Figure 3 Risk
AI
Risk
A2
Risk
An
‘Dependence’ Risk
61
Risk
82
Risk
Bm
of risk
Categories
Loss, f
Risk
BI
0A
0-
Dependence
weeks
Risk B
Risk A
Risk
of occurrence
Beta
& a
m21
n>2 of risk = 0.4.1
Figure 4
‘Parallel’
International Journal
of
Project Management
1994 Volume 12 Number 2
KISK
Risk Al
ro
&
Risk A2
Risk 82
Risk An Figure
5
Risk Bl
Risk Bm ‘Series’
Case study of application relationships
of risk lifecycle and
In this section, a case study, a commercial development in the south of England, was selected from the live projects of a major cost consultancy. This case illustrates the application of the risk lifecycle and relationships to practical risk management. For simplicity, discussion is limited to the construction of the substructure of the project. The major steps of the application are as follows: l
l l l
the list; the the the
identification
of the risks and the creation
of risks and creation of a risk list
The identification of risk and the creation of a risk list are dependent upon many factors, such as past experience, personal tendency, and the possession of information. Therefore, almost no two risk analysts will make the same judgment when they identify risks from the same project. However, in the case study, we made the best possible use of a variety of experienced members of the project team. Their information, skills and judgment were integrated by successive iterations or partial iterations. This finally led to a reasonable identified risk list for the case (see Table 2).
Evaluation
of relationships
between risks
Determining the relationships between risks is the second step of the method. First, we identify the risks which have mutual relationships. Second, we classify, analyse and decide on the basic relationship patterns between these risks. Finally, we use the graphical representations of the Design
stage-)(
1
Table 2 Risk list of case study Number
Risk
1
Inadequate site investigation Uncertainty of subsoil conditions Loss due to unexpected subsoil problems Requirement to redesign and make substantial substructure Bad weather Rearrangement of staff and plant Reorder materials and equipment Loss due to delay in the construction
2 3 4 5 6 7 8
changes
to the
basic relationship pattern to connect them. In respect of this case, the relationship between risk 1 and risk 2 conforms to the ‘series’ model, because these two risks can only occur together. It is most likely that the construction of the substructure faces unexpected subsoil problems. The relationship between risk 4 and risk 5 corresponds to the ‘parallel’ model, because the occurrence of either risk 4 or risk 5 will probably cause a delay. The others have a ‘dependence’ relationship. The relationship diagram of the case is shown in Figure 6.
of a risk
evaluation of the relationship between risks; definition of the ranges of the time and the loss; simulation and the statistical analysis of the results.
Identification
MANAGEMENT
Construction
Definition
of ranges of time and loss
The ranges of the start time and the duration of risk action are mostly influenced by the project scheduled planning, which is carried out using, for example, bar charts or a network. We must pay attention to the logic of the start times between risks. For instance, as shown in Figures 3, 4 and 5, the start time of risk B must be more than or equal to that of risk A. If it is not, there is a logical mistake. In practical terms, it is better to use the interval or difference between the start times of risk B and risk A as the start time of risk B, in order to avoid such mistakes. The magnitude of the duration of a risk is partially determined not only by the duration of the procedure associated with the risk, but also by the management measures for dealing with the risk and the features of the risk. The surveyors used their expertise to select the most appropriate distributions and ranges for the start times and durations of the risks in the risks list in Table 2. Table 3 shows their selections, It should be noted that the start time of risk 3 is zero, because after risk 2 occurs, risk 3 immediately ensues. Table 4 lists their probabilities of occurrence and the ranges of their risk losses. The estimated figures in Tables 3 and 4 have been derived from a of the substructure
,I
I Figure International
6
Journal of Project
Risk-relationship Management
diagram of case study
I994 Volume 12 Number 2
71
RISK
MANAGEMENT
Table 3 Range estimations
of risk start time and duration
Number of risk
Start time, weeks
min 1
-
2 3 4 5 6 7 8
0.5 0.0 0.5 2.5 3.0 4.0 0.0
Duration,
ML
max
0.8 0.0 1.0 3.5 4.5 4.5 0.5
1.0 0.0 1.5 5.0 5.0 5.0 1.0
Distribution
weeks
Distribution
min
ML
max
1.0 1.0 4.0 2.5 1.0 1.0 4.0
1.5 1.5 5.0 3.0 1.5 1.2 5.0
2.0 2.0 6.0 3.5 2.0 1.5 6.0
U T U U T U
T
T U T N U T
[U: uniform distribution, T: triangular distribution. ] Table 4 Estimations
of probability
of occurrence
of risk and risk loss
Number of risk
Probability
I
0.4 0.3 Depends on risks 1 and 2 Depends on risks 1 and 2 0.6 0.9 0.8 Depends on risks 1 and 2, or 5
of ocurrence
Ranges of risk loss
min, f 2 3 4 5 6 7 8
combination of analysis of the project project-management team’s judgment.
Simulation
20 000 30 000 10 000 45 000 40 000
situation
and the
Number of risk occurrence
Probability occurrence
Risk Risk Risk Risk Risk Risk Risk Risk Risk
1200 900 378 378 1200 347 290 1059 198
1200/3000 900/3000 378/3000 37813000 120013000 34713000 29013000
72
1 2 3 4 5 6 7 8a 8b
max, f -
25 000 35 000 14 000 60 000 50 000
-
0.400 0.300 0.126 0.126 0.400 0.116 0.097
(1059+ 198)13000 = 0.419
Uniform Normal
16 000 70 000 60 000
Triangular Uniform Triangular
Figure 8. Figure 8 provides
tribution
detailed information about the disof risk loss as time varies. This is a convenient
Table 6 Simulation
of risk
= = = = = = =
30 000 40 000
As shown in Table 6, the start times of all the risk actions are calculated from the start of the construction of the substructure. The expected values and standard deviations of the start times and the durations are based on each risk action’s occurrence number, which is obtained from the simulation. The risk actions’ expected values of start time and duration in this case are shown in Figure 7, from which we know the risk actions’ expected times of occurring. The function of this diagram is similar to those of bar charts and networks, and it provides a powerful time tool for risk management. For simplicity, before discussion about the cashflow of risk loss, we make the following assumption: once risk events occur, the cashflows of the risk loss always follow the shapes shown in Table 7. The risk cashflows and total compound cashflow of all the risks’ losses are shown in
Number of risk
of risks
Number of risk
of risk loss
-
This case was evaluated by using the Predict software. Predict is a risk-analysis software package that has been developed by Risk Decisions Ltd. It is a worksheet-based modelling tool that relates to uncertainty. The structure of the model is as shown in Figure 6, and the data are from Tables 3 and 4. The number of iterations of the simulation was 3000. The simulation results are shown in Tables 5 and 6. In Tables 5 and 6, the occurrence of risk 8 is caused by the occurrence of two groups of risks. The first group includes risk 5, risk 1 and risk 2. The occurrence of these causes the occurrence of risk 8, and this group is referred to as risk 8a. The second group only includes risk 1 and risk 2. Their occurrence causes the occurrence of risk 8, and this is referred to as risk 8b. Because of the randomness of the start times and the durations of the risk actions, we apply their statistical results, such as the expected value, to the time analysis. of occurrence
ML, f
-
and statistical analysis of results
Table 5 Probabilities
Distribution
Risk Risk Risk Risk Risk Risk Risk Risk Risk
1 2 3 4 5 6 7 8a 8b
results of case study
Start time, weeks
Duration,
weeks
Risk loss, f
EV
Std dev
EV
Std dev
EV
0.761 0.761 1.759 3.737 5.733 6.799 1.759 3.737
Std dev
0.145 0.145 0.345 0.725 0.936 0.558 0.345 0.725
1.508 1.508 4.998 2.992 1.490 1.245 4.998 2.992
0.200 0.200 0.580 0.202 0.163 0.148 0.580 0.202
25 054 34 879 13 315 57 276
1231 7 197
49 899
4 164
2 946 1 688
[ EV: expected value, Std dev: standard deviation. ] International
Journal of Project
Management
1994 Volume 12 Number 2
RISK
-
The constructlon
of the substructure
MANAGEMENT
Pw
‘” 1.51 CD)
x o
n
d
Risk 2 1.51 CD)
n 1.759
Risk 3 4.988
(S) 3.737
4
1.759
2.992
(S)
aa+j
CD) CD)
*_ 5.733
(S)
6.269
CS)
(S)
Risk 5 1.490
1.245
CD)
1 4.988
Risk 7
CD) Risk 8 (a)
1 2.992
CD)
I
Risks’ expected
Risk 6
1
I
Figure 7
CD)
1
Risk 8 (b)
start times and durations
[ 1 time unit = 1 week. S = start time of risk action, D = duration of risk action.]
The construction
4 E.16592 syl
The individual Risk3
I 759(S)
>
j I ; ! > ; 5
151(D)
cash-flow
of risk
loss
f.,3g85
I
+-
Risk 4
4.988(D)
El7872
5.733(S)
Risk 6 L46005
Risk Y
6 289(S)
>
; 4 7
I .245(D)
L4895
i : > ; > J-------------------;J :
l
of the substructure
4.988(D)
2.992(D)
-__---------
0
The probability
of occurrence
is approximately
l/3
0
The probability
of occurrence
is approximately
I /IO
Total
Figure 8
International
Ll5062
3 737(S)
risk
loss cash-flow
of the case
Risk-loss cashflow of case study
Journal of Project Management
1994 Volume 12 Number 2
73
RISK MANAGEMENT
Table 7 Shapes of cashflow
of risk loss
Number of risk
Shape of cashtlow of risk loss
Distribution risk loss
I
-
-
of
Conclusions
2 -71
Oni form
Triangular
6
iiang”Jar
7
Uniform
8
Triangular
tool that is designed to allow decision makers to carry out cost planning and financial management with more confidence. Of all the risks in this case, the identified key risks are risk 1, risk 2 and risk 5, because risks 3, 4, and 6-8 are dependent on risk 1 and risk 2. The large part of the occurrence number of risk 8 is caused by the occurrence of risk 5. The total expected value of the risk loss in pounds sterling caused by risk 1 and risk 2 is 25 054 + 34 879 + 13 315 + 57 276 + 49 899 * 19811257 = 138 384 The total expected value of the risk loss in pounds caused by risk 5 is 49 899 * (1059/1257)
= 42 039
Comparing risk 1 and risk 2 with risk 5, it is obvious that risk 1 and risk 2 carry a greater risk than risk 5, because the loss caused by risk 1 and risk 2 is 3.79 times larger than that caused by risk 5. In fact, risk 1 and risk 2 can be avoided or reduced at the design stage through management effort. However, risk 5 cannot be controlled by man, and therefore the focus of risk management in this case lies in the control of risk 1 and risk 2. Throughout this case study, we can easily distinguish the difference between new and conventional methods, and see
74
the value of analysing the risk lifecycle and relationships. It has also demonstrated how the risk lifecycle and relationships are applied to practical risk management.
This paper has developed a new methodology, the risk lifecycle and relationships5. This is a new way of assessing an aspect of project risks, namely the financial consequences of potential risks. Using it, not only can conventional risk identification, analysis and response be performed, but also the time, and the mutual effects and interactions of risks can be revealed so that decision makers can more realistically assess the consequences of risks in an uncertain environment. It provides an in-depth research method for risk management, and this analytical process could also be written into a computer program to simulate any complicated situation for effective and efficient risk analysis.
References Flanagan, R and Normal, G Risk Management and Construction Blackwell Scientific (1993) Perry, J C and Hayer, R W ‘Construction projects - know the risks’ Chartered Mech. Eng. (Feb 1985) pp 42-45 Perry, J C ‘Risk management - an approach for project managers’ ht. J. Project Manage. Vol 4 No 3 (1986) Johnson, N L and Kotz, S Distributions in Statistics: Continuous Univariate Distributions - Vol 2 Houghton Mifflin, USA (1970) Ren, H ‘Risk management in construction cost and inflation’ PhD Thesis University of Reading, UK (1992) Dr Hong Ren graduated in civil engineering from the Chongqing and Institute of Architecture Engineering, China, in 1982. He was awarded an MSc in construction management from the same university in 1985, and a PhD from the University of Reading, UK, where he is a research fellow, in 1992. His current research interests include the Chinese construction industry and its market.
International
Journal of Project Management
1994 Volume 12 Number 2
Journal of Project Management
1994 12 (2) 68-74
Risk management
Risk lifecycle and risk relationships on construction projects H Ren Department of Construction Management RG4 2BU. UK
and Engineering,
University of Reading,
Whiteknights,
Reading
The paper presents a new method of assessing the financial risk in construction projects. In this method, two elements are distinguished: the risk lifecycle and risk relationships between separate project risks. The risk lifecycle consists of two successive distinct periods: concealment and action. Through the risk relationships, the mutual effects and interactions between risks are analysed. An example is used to illustrate the advantages of using the risk lifecycle and risk relationships Keywords:
risk lifecycle:
concealment
and action, risk relationships
The construction industry is renowned as a high-risk industry. Construction projects involve complex, timeconsuming design and construction processes characterized by unforeseen circumstances. As a result, effective risk management has become a major problem that confronts the industry. The success of a project-management exercise depends very much on the efficient and effective management of the risks involved’-3. This paper suggests that an extra depth of knowledge is required for risk-management techniques to assess and predict accurately the consequences to a project of potential financial losses. The addition is the study of the character of the risks themselves. The character is described by the risk lifecycle. Relevant characteristics include time properties, influence relationships between risks, and associated cashflow consequences. The awareness of the need to understand the above characteristics has led to the development of two new concepts: the risk lifecycle, and risk relationships. In this paper, these concepts are incorporated into risk management at a practical level. A theoretical framework is developed, and is then applied to a case study to demonstrate its impact on current risk-management approaches.
A risk’s random features constitute its lifecycle. As Figure 1 shows, any risk generally has a period from the possible existence to the occurrence of the risk event. This period is called the concealment of the risk, and it is the first part of the risk lifecycle. For example, say there is uncertainty about the subsoil ground conditions on a site. If the structural designers have incorrect information, or they are unable to take due account of this uncertainty, the concealment of the subsoil risk is the period from the design of the substructure to the construction of the substructure. Once the risk event occurs, its action lasts for a certain period. This action is the second part of the risk lifecycle, and it is defined as the risk action. During this period, the risk action is embodied by overrun costs, delay, poor quality, and so on over a period of the risk action. These outcomes or consequences are generally referred to as the risk loss. The aim of studying the risk lifecycle is to put a time dimension into risk-analysis theory and application, which can provide users with a powerful time tool for dynamic risk management, thus enhancing risk prediction.
Risk
Start
lifecycle
Risks are associated with all projects in a dynamic environment. They are described by possible events’-3. Their random characteristics mainly embody the following aspects: l l
68
the uncertainty the randomness risk action;
as to the occurrence of the risk; of the start time and the duration of the
l
the randomness risk action.
time
of the risk loss over the period of the
and duration
of risk
Although risk management is a new field, many methods of dealing with risk have been used in the construction industry. However, the current theories of risk neglect the start time and the duration of the risk action, which are a necessary and important part of risk analysis. Take weather forecasting as an example. If we are informed that rain, wind or snow are likely, and to what degree, without the 0263-7863/94/020068-07
0 1994 Butterworth-Heinemann
Ltd
RISK
I_
MANAGEMENT
_b
Risk life cycle
The risk loss
I
Start time of the risk Tie
+-
Concealment
Figure 1
b
Action
Risk lifecycle
times and the duration of risk action, the technique of range estimating is used. This is one of the most effective methods of dealing with the problem of time uncertainty. This method uses three figures, min, ML and max, and a probability distribution4, such as the uniform, triangular, beta and normal distributions. min and mux are the two extreme start times or duration figures under abnormal conditions. ML is the most likely start time or duration under normal conditions.
start times and durations being stated, we are unsure about how to deal with the weather, because of the shortage of such vital information. As in weather forecasting, the start time and duration of the risk action are indispensable components in risk analysis. The advantages can be briefly expressed as follows: If the start time and duration of the risk action are estimated in advance, the scheme of the project can be systematically planned, controlled and managed in order to minimize the associated risk loss. If the cashflow of the risk loss can be predicted in advance, financial management can be carried out in a well thought-out-way.
Cashflow of risk loss For convenience, all the risk losses are transformed into money loss, and there is thus a sole criterion for comparison and decision. Only when the time concept is introduced into the risk loss can it be studied in a dynamic way. The cashflow of the risk loss gives an overall picture of the loss and the time relationship. Decision makers can clearly estimate the magnitude of the risk loss at any point in time. Owing to the variety of features of the risk action, there are many types of cashflow of risk loss. Losses from earthquakes and accidents exhibit a sudden and sharp damage increment within a very short time. Some economic risk actions first have a gradual rise and then fall. The cashflow of the risk loss may be continuous, discrete, and so on. The principle of determining the cashflow of the risk loss depends on the characteristics of the risk action,
The start time of the risk action is defined as the moment at which the risk event begins; it is a discrete time point. The duration of the risk is defined as the period between the start and the disappearance of the risk action. The magnitude of the duration of the risk action depends on its type, feature and existing environment. For example, some physical risk events, e.g. an earthquake, last a very short time, but some economic risks, such as inflation or an economic recession, can be sustained. As Figure 2 shows, the start time and the duration of risk action are the random variables. They vary within ranges with certain kinds of probability distributions. To illustrate the probability distributions of the start ---
l---------* Probability
distribution
of the start time of risk occurrence
/I\ Min
StartTie ML
~
l
i
Max
--------,___T:T---------_,
Probability distribution of the risk duration I I I I
Duration Min ,-__-_--------___~ Figure 2 International
ML
Max
WI
Start time and duration
Journal of Project Management
1994 Volume 12 Number 2
69
RISK MANAGEMENT
and the environment in which it exists. To study the risk lifecycle, one of the requirements is to have an overall estimation of the risk. The characteristics of the risk are described by two time periods: the concealment, and the action. The concealment period includes the start time and the occurrence probability of the risk event. The action period includes the duration and the loss of the risk event. Data and information about a risk lifecycle are given in Table 1.
Relationships
between risks
The characteristics of a risk are decided not only by its own features, but also by the influence of other risks in the system. In fact, risks in a system mutually affect, impede and promote each other. The independent risk seldom exists in reality. This kind of mutual influence among risks in a system is defined as the risk relationship. The study of this relationship can provide the following main benefits. It provides users with an analytical method of logical, inductive and deductive inference, and makes risk decisions possible on the basis of detailed understanding of the relationships between risks. It overcomes the shortcomings of statistical methods, which are too generalized, and, therefore, it enhances accuracy in decision making. Thus, the study of the relationships between risks should play an important role in risk analysis, and it could contribute to adequate risk management.
Basic patterns of risk relationship In reality, the relationships between risks are very complex and varied. If we classify or subclassify or further subclassify these relationships, we can obtain the basic patterns of a risk relationship. The classifications are independence, dependence, parallel and series.
project. This kind of relationship between risk A and risk B is defined as dependence. The graphical representation of a risk is a circle. The size of the circle has no significance, and the circle may assume any form. It may be square, rectangular, or hexagonal, to suit the needs of the model. The connection between risk A and risk B is an arrow that denotes the dependent relationship. In practice, the number of risks that are dependent on risk A can be more than one. As an example, if risk A, a reduction in labour productivity, occurs, it probably leads to the occurrences of risk B,, a delay in the completion of the project, risk B,, an escalation of the cost, risk B,, poor quality, and so on. A graphical representation of the dependence relationship is shown in Figure 3. Parallel In the parallel situation, more than one risk A,, A,, , A, together affect one or more risk B,, B2, . , B,,,. Under the condition in which one or more of A,, A,, , A,, occur, risk(s) B,, B,, . . ,B, probably occur. As an example, there are three risks: bad weather, materials shortages, and inappropriate plant. Once one or more of them have occurred, a delay in the progress of construction probably occurs. The graphical representation of the parallel situation is shown in Figure 4. Series In the series situation, more than one risk A,, A,, , A, together affect one or more risk B,, B,, . , B,. Only if these risks A,, A,, . . , A,, occur all together will risk(s) B,, B,, , B,,, probably occur. As an example, there are three risks. Risk A, is that of bad weather that is an uncertainty in a period. Risk A, is the scheduled planning for the construction of the substructure. If bad weather and the construction of the substructure occur together, then risk B, the overrun time of this project, possibly occurs. This series relationship is shown in Figure 5.
Independence Independence means that characteristics, such as the probability of occurrence, the start time, the duration and the loss of the risk are not affected by any other risks in the system. Correspondingly, this risk does not have any impact on the other risks.
With dependence, the occurrence of risk B is dependent upon the occurrence of risk A. If risk A occurs, then risk B probably occurs. If risk A does not occur, then risk B definitely does not occur. As an example, if risk A, a reduction in labour productivity, occurs, it probably causes the occurrence of risk B, a delay in the completion of the Table 1 Description min
ML
max
Probability
distribution
Start time, date
2/9/93
10/9/93
16/9/93
Uniform
-1
Duration,
1.0
1.4
2.2
Triangular
fSXl0
f6COO
f8000
Shape of risk loss [Probability
70
A
Risk
82
Risk
Bn
Figure 3 Risk
AI
Risk
A2
Risk
An
‘Dependence’ Risk
61
Risk
82
Risk
Bm
of risk
Categories
Loss, f
Risk
BI
0A
0-
Dependence
weeks
Risk B
Risk A
Risk
of occurrence
Beta
& a
m21
n>2 of risk = 0.4.1
Figure 4
‘Parallel’
International Journal
of
Project Management
1994 Volume 12 Number 2
KISK
Risk Al
ro
&
Risk A2
Risk 82
Risk An Figure
5
Risk Bl
Risk Bm ‘Series’
Case study of application relationships
of risk lifecycle and
In this section, a case study, a commercial development in the south of England, was selected from the live projects of a major cost consultancy. This case illustrates the application of the risk lifecycle and relationships to practical risk management. For simplicity, discussion is limited to the construction of the substructure of the project. The major steps of the application are as follows: l
l l l
the list; the the the
identification
of the risks and the creation
of risks and creation of a risk list
The identification of risk and the creation of a risk list are dependent upon many factors, such as past experience, personal tendency, and the possession of information. Therefore, almost no two risk analysts will make the same judgment when they identify risks from the same project. However, in the case study, we made the best possible use of a variety of experienced members of the project team. Their information, skills and judgment were integrated by successive iterations or partial iterations. This finally led to a reasonable identified risk list for the case (see Table 2).
Evaluation
of relationships
between risks
Determining the relationships between risks is the second step of the method. First, we identify the risks which have mutual relationships. Second, we classify, analyse and decide on the basic relationship patterns between these risks. Finally, we use the graphical representations of the Design
stage-)(
1
Table 2 Risk list of case study Number
Risk
1
Inadequate site investigation Uncertainty of subsoil conditions Loss due to unexpected subsoil problems Requirement to redesign and make substantial substructure Bad weather Rearrangement of staff and plant Reorder materials and equipment Loss due to delay in the construction
2 3 4 5 6 7 8
changes
to the
basic relationship pattern to connect them. In respect of this case, the relationship between risk 1 and risk 2 conforms to the ‘series’ model, because these two risks can only occur together. It is most likely that the construction of the substructure faces unexpected subsoil problems. The relationship between risk 4 and risk 5 corresponds to the ‘parallel’ model, because the occurrence of either risk 4 or risk 5 will probably cause a delay. The others have a ‘dependence’ relationship. The relationship diagram of the case is shown in Figure 6.
of a risk
evaluation of the relationship between risks; definition of the ranges of the time and the loss; simulation and the statistical analysis of the results.
Identification
MANAGEMENT
Construction
Definition
of ranges of time and loss
The ranges of the start time and the duration of risk action are mostly influenced by the project scheduled planning, which is carried out using, for example, bar charts or a network. We must pay attention to the logic of the start times between risks. For instance, as shown in Figures 3, 4 and 5, the start time of risk B must be more than or equal to that of risk A. If it is not, there is a logical mistake. In practical terms, it is better to use the interval or difference between the start times of risk B and risk A as the start time of risk B, in order to avoid such mistakes. The magnitude of the duration of a risk is partially determined not only by the duration of the procedure associated with the risk, but also by the management measures for dealing with the risk and the features of the risk. The surveyors used their expertise to select the most appropriate distributions and ranges for the start times and durations of the risks in the risks list in Table 2. Table 3 shows their selections, It should be noted that the start time of risk 3 is zero, because after risk 2 occurs, risk 3 immediately ensues. Table 4 lists their probabilities of occurrence and the ranges of their risk losses. The estimated figures in Tables 3 and 4 have been derived from a of the substructure
,I
I Figure International
6
Journal of Project
Risk-relationship Management
diagram of case study
I994 Volume 12 Number 2
71
RISK
MANAGEMENT
Table 3 Range estimations
of risk start time and duration
Number of risk
Start time, weeks
min 1
-
2 3 4 5 6 7 8
0.5 0.0 0.5 2.5 3.0 4.0 0.0
Duration,
ML
max
0.8 0.0 1.0 3.5 4.5 4.5 0.5
1.0 0.0 1.5 5.0 5.0 5.0 1.0
Distribution
weeks
Distribution
min
ML
max
1.0 1.0 4.0 2.5 1.0 1.0 4.0
1.5 1.5 5.0 3.0 1.5 1.2 5.0
2.0 2.0 6.0 3.5 2.0 1.5 6.0
U T U U T U
T
T U T N U T
[U: uniform distribution, T: triangular distribution. ] Table 4 Estimations
of probability
of occurrence
of risk and risk loss
Number of risk
Probability
I
0.4 0.3 Depends on risks 1 and 2 Depends on risks 1 and 2 0.6 0.9 0.8 Depends on risks 1 and 2, or 5
of ocurrence
Ranges of risk loss
min, f 2 3 4 5 6 7 8
combination of analysis of the project project-management team’s judgment.
Simulation
20 000 30 000 10 000 45 000 40 000
situation
and the
Number of risk occurrence
Probability occurrence
Risk Risk Risk Risk Risk Risk Risk Risk Risk
1200 900 378 378 1200 347 290 1059 198
1200/3000 900/3000 378/3000 37813000 120013000 34713000 29013000
72
1 2 3 4 5 6 7 8a 8b
max, f -
25 000 35 000 14 000 60 000 50 000
-
0.400 0.300 0.126 0.126 0.400 0.116 0.097
(1059+ 198)13000 = 0.419
Uniform Normal
16 000 70 000 60 000
Triangular Uniform Triangular
Figure 8. Figure 8 provides
tribution
detailed information about the disof risk loss as time varies. This is a convenient
Table 6 Simulation
of risk
= = = = = = =
30 000 40 000
As shown in Table 6, the start times of all the risk actions are calculated from the start of the construction of the substructure. The expected values and standard deviations of the start times and the durations are based on each risk action’s occurrence number, which is obtained from the simulation. The risk actions’ expected values of start time and duration in this case are shown in Figure 7, from which we know the risk actions’ expected times of occurring. The function of this diagram is similar to those of bar charts and networks, and it provides a powerful time tool for risk management. For simplicity, before discussion about the cashflow of risk loss, we make the following assumption: once risk events occur, the cashflows of the risk loss always follow the shapes shown in Table 7. The risk cashflows and total compound cashflow of all the risks’ losses are shown in
Number of risk
of risks
Number of risk
of risk loss
-
This case was evaluated by using the Predict software. Predict is a risk-analysis software package that has been developed by Risk Decisions Ltd. It is a worksheet-based modelling tool that relates to uncertainty. The structure of the model is as shown in Figure 6, and the data are from Tables 3 and 4. The number of iterations of the simulation was 3000. The simulation results are shown in Tables 5 and 6. In Tables 5 and 6, the occurrence of risk 8 is caused by the occurrence of two groups of risks. The first group includes risk 5, risk 1 and risk 2. The occurrence of these causes the occurrence of risk 8, and this group is referred to as risk 8a. The second group only includes risk 1 and risk 2. Their occurrence causes the occurrence of risk 8, and this is referred to as risk 8b. Because of the randomness of the start times and the durations of the risk actions, we apply their statistical results, such as the expected value, to the time analysis. of occurrence
ML, f
-
and statistical analysis of results
Table 5 Probabilities
Distribution
Risk Risk Risk Risk Risk Risk Risk Risk Risk
1 2 3 4 5 6 7 8a 8b
results of case study
Start time, weeks
Duration,
weeks
Risk loss, f
EV
Std dev
EV
Std dev
EV
0.761 0.761 1.759 3.737 5.733 6.799 1.759 3.737
Std dev
0.145 0.145 0.345 0.725 0.936 0.558 0.345 0.725
1.508 1.508 4.998 2.992 1.490 1.245 4.998 2.992
0.200 0.200 0.580 0.202 0.163 0.148 0.580 0.202
25 054 34 879 13 315 57 276
1231 7 197
49 899
4 164
2 946 1 688
[ EV: expected value, Std dev: standard deviation. ] International
Journal of Project
Management
1994 Volume 12 Number 2
RISK
-
The constructlon
of the substructure
MANAGEMENT
Pw
‘” 1.51 CD)
x o
n
d
Risk 2 1.51 CD)
n 1.759
Risk 3 4.988
(S) 3.737
4
1.759
2.992
(S)
aa+j
CD) CD)
*_ 5.733
(S)
6.269
CS)
(S)
Risk 5 1.490
1.245
CD)
1 4.988
Risk 7
CD) Risk 8 (a)
1 2.992
CD)
I
Risks’ expected
Risk 6
1
I
Figure 7
CD)
1
Risk 8 (b)
start times and durations
[ 1 time unit = 1 week. S = start time of risk action, D = duration of risk action.]
The construction
4 E.16592 syl
The individual Risk3
I 759(S)
>
j I ; ! > ; 5
151(D)
cash-flow
of risk
loss
f.,3g85
I
+-
Risk 4
4.988(D)
El7872
5.733(S)
Risk 6 L46005
Risk Y
6 289(S)
>
; 4 7
I .245(D)
L4895
i : > ; > J-------------------;J :
l
of the substructure
4.988(D)
2.992(D)
-__---------
0
The probability
of occurrence
is approximately
l/3
0
The probability
of occurrence
is approximately
I /IO
Total
Figure 8
International
Ll5062
3 737(S)
risk
loss cash-flow
of the case
Risk-loss cashflow of case study
Journal of Project Management
1994 Volume 12 Number 2
73
RISK MANAGEMENT
Table 7 Shapes of cashflow
of risk loss
Number of risk
Shape of cashtlow of risk loss
Distribution risk loss
I
-
-
of
Conclusions
2 -71
Oni form
Triangular
6
iiang”Jar
7
Uniform
8
Triangular
tool that is designed to allow decision makers to carry out cost planning and financial management with more confidence. Of all the risks in this case, the identified key risks are risk 1, risk 2 and risk 5, because risks 3, 4, and 6-8 are dependent on risk 1 and risk 2. The large part of the occurrence number of risk 8 is caused by the occurrence of risk 5. The total expected value of the risk loss in pounds sterling caused by risk 1 and risk 2 is 25 054 + 34 879 + 13 315 + 57 276 + 49 899 * 19811257 = 138 384 The total expected value of the risk loss in pounds caused by risk 5 is 49 899 * (1059/1257)
= 42 039
Comparing risk 1 and risk 2 with risk 5, it is obvious that risk 1 and risk 2 carry a greater risk than risk 5, because the loss caused by risk 1 and risk 2 is 3.79 times larger than that caused by risk 5. In fact, risk 1 and risk 2 can be avoided or reduced at the design stage through management effort. However, risk 5 cannot be controlled by man, and therefore the focus of risk management in this case lies in the control of risk 1 and risk 2. Throughout this case study, we can easily distinguish the difference between new and conventional methods, and see
74
the value of analysing the risk lifecycle and relationships. It has also demonstrated how the risk lifecycle and relationships are applied to practical risk management.
This paper has developed a new methodology, the risk lifecycle and relationships5. This is a new way of assessing an aspect of project risks, namely the financial consequences of potential risks. Using it, not only can conventional risk identification, analysis and response be performed, but also the time, and the mutual effects and interactions of risks can be revealed so that decision makers can more realistically assess the consequences of risks in an uncertain environment. It provides an in-depth research method for risk management, and this analytical process could also be written into a computer program to simulate any complicated situation for effective and efficient risk analysis.
References Flanagan, R and Normal, G Risk Management and Construction Blackwell Scientific (1993) Perry, J C and Hayer, R W ‘Construction projects - know the risks’ Chartered Mech. Eng. (Feb 1985) pp 42-45 Perry, J C ‘Risk management - an approach for project managers’ ht. J. Project Manage. Vol 4 No 3 (1986) Johnson, N L and Kotz, S Distributions in Statistics: Continuous Univariate Distributions - Vol 2 Houghton Mifflin, USA (1970) Ren, H ‘Risk management in construction cost and inflation’ PhD Thesis University of Reading, UK (1992) Dr Hong Ren graduated in civil engineering from the Chongqing and Institute of Architecture Engineering, China, in 1982. He was awarded an MSc in construction management from the same university in 1985, and a PhD from the University of Reading, UK, where he is a research fellow, in 1992. His current research interests include the Chinese construction industry and its market.
International
Journal of Project Management
1994 Volume 12 Number 2