_______ Are a Good Forum for Regularly Reviewing Updating and Addressing Risks

Suggested Citation:"4 Take a chance Identification and Analysis." National Research Council. 2005. The Owner'southward Role in Project Take a chance Management. Washington, DC: The National Academies Printing. doi: x.17226/11183.

4
Gamble Identification and Analysis

INTRODUCTION

Ensuring that adequate and timely hazard identification is performed is the responsibility of the owner, as the owner is the first participant in the project. The sooner risks are identified, the sooner plans can be fabricated to mitigate or manage them. Assigning the risk identification process to a contractor or an private member of the projection staff is rarely successful and may be considered a way to achieve the appearance of risk identification without actually doing information technology.

It is important, all the same, that all project direction personnel receive specific training in risk management methodology. This training should cover non but risk analysis techniques simply also the managerial skills needed to interpret take a chance assessments. Because the owner may lack the specific expertise and experience to identify all the risks of a projection without help, information technology is the responsibility of DOE's project directors to ensure that all meaning risks are identified by the integrated project team (IPT). The actual identification of risks may be carried out by the owner's representatives, by contractors, and past internal and external consultants or advisors. The risk identification part should non be left to chance but should be explicitly covered in a number of projection documents:

Statement of work (SOW),
Work breakup structure (WBS),
Budget,
Schedule,

Suggested Commendation:"iv Risk Identification and Analysis." National Research Council. 2005. The Owner's Role in Projection Risk Management. Washington, DC: The National Academies Printing. doi: 10.17226/11183.

Acquisition programme, and
Execution plan.

METHODS OF RISK IDENTIFICATION

There are a number of methods in utilise for run a risk identification. Comprehensive databases of the events on past projects are very helpful; however, this knowledge oft lies cached in people'southward minds, and admission to it involves brainstorming sessions past the projection team or a meaning subset of it. In improver to technical expertise and experience, personal contacts and group dynamics are keys to successful run a risk identification.

Projection team participation and contiguous interaction are needed to encourage open communication and trust, which are essential to effective risk identification; without them, team members will be reluctant to enhance their risk concerns in an open forum. While smaller, specialized groups can perform gamble assessment and risk analysis, effective, ongoing run a risk identification requires input from the entire project squad and from others outside it. Take chances identification is one reason early activation of the IPT is essential to projection success.

The run a risk identification process on a project is typically one of brainstorming, and the usual rules of brainstorming use:

The full project team should exist actively involved.
Potential risks should exist identified by all members of the projection team.
No criticism of any suggestion is permitted.
Whatever potential adventure identified by anyone should exist recorded, regardless of whether other members of the group consider it to be significant.
All potential risks identified past brainstorming should be documented and followed up by the IPT.

The objective of risk identification is to place all possible risks, not to eliminate risks from consideration or to develop solutions for mitigating risks—those functions are carried out during the risk assessment and run a risk mitigation steps. Some of the documentation and materials that should be used in risk identification as they become available include these:

Sponsor mission, objectives, and strategy; and project goals to achieve this strategy,
SOW,

Suggested Citation:"4 Risk Identification and Assay." National Research Quango. 2005. The Owner's Office in Projection Risk Management. Washington, DC: The National Academies Press. doi: 10.17226/11183.

Projection justification and cost-effectiveness (projection benefits, present worth, rate of return, etc.),
WBS,
Project performance specifications and technical specifications,
Project schedule and milestones,
Project financing plan,
Project procurement program,
Projection execution plan,
Project benefits projection,
Project cost estimate,
Projection environmental affect argument,
Regulations and congressional reports that may bear upon the project,
News articles virtually how the project is viewed by regulators, politicians, and the public, and
Historical safety performance.

The take a chance identification process needs to exist repeated as these sources of information change and new information becomes bachelor.

There are many ways to approach risk identification. 2 possible approaches are (one) to identify the root causes of risks—that is, identify the undesirable events or things that can go wrong then identify the potential impacts on the project of each such consequence—and (ii) to identify all the essential functions that the project must perform or goals that it must attain to be considered successful and then identify all the possible modes by which these functions might fail to perform. Both approaches can piece of work, but the project squad may find it easier to identify all the factors that are critical to success, and then work backward to place the things that tin go incorrect with each one.

Risk identification should be performed early in the project (starting with preproject planning, even before the preliminary concept is canonical) and should continue until the project is completed. Chance identification is not an exact science and therefore should exist an ongoing process throughout the projection, particularly as it enters a new phase and equally new personnel and contractors bring unlike experiences and viewpoints to take chances identification. For this reason, the DOE projection director should ensure that the project risk management plan provides for periodic updates.

METHODS OF QUALITATIVE RISK ASSESSMENT

The goal of risk identification is not only to avoid omissions but also to avoid the opposite pitfall—of beingness distracted by factors that are not root causes but only symptoms. Treating the symptoms, rather than the root causes, will give the appearance of activity but will not solve the

Suggested Citation:"4 Risk Identification and Assay." National Inquiry Quango. 2005. The Owner's Function in Projection Chance Management. Washington, DC: The National Academies Press. doi: 10.17226/11183.

problem. Unfortunately, identification of symptoms is far easier than identification of root causes. Projection owners should ensure that the take a chance identification process goes across the symptoms. While outside, disinterested reviewers tin sometimes assistance perform this function, the following sections describe methods that tin can exist used past project personnel to place risks and their causes.

Gamble Screening

Following the initial risk identification phase, the projection manager should have a working list of risks that have been identified every bit potentially affecting the project. From this list, the project director should differentiate those that seem minor and do not require farther attending from those that require follow-up, qualitative analysis, quantitative analysis, and active mitigation and management. This process requires some qualitative assessment of the magnitude and seriousness of each identified hazard. Diverse methods that have been developed to appraise failures in physical equipment and systems have too been applied in one grade or another to project risks.

The ordinarily used gamble tool shown in Table 4-1 is a two by two matrix that allows assigning a run a risk to one of four quadrants based on a qualitative assessment of its relative impact (high or depression) and the likelihood of its occurrence (high or depression). Risks in the upper right quadrant

Table 4-1 Take a chance Screening Based on Impact and Probability

Suggested Citation:"four Risk Identification and Analysis." National Research Council. 2005. The Owner's Role in Projection Risk Management. Washington, DC: The National Academies Printing. doi: 10.17226/11183.

demand the about attending. Effectively gradations of impact and likelihood—for instance, very high, loftier, medium, low, and very depression (a five by 5 matrix)—would allow a more nuanced consideration of the attention needed.

Low Impact, Low Probability

Risks that tin be characterized as both low impact and low likelihood of occurrence are essentially negligible and can usually be eliminated from active consideration. The main concern of the owner'due south project director is to monitor these factors sufficiently to decide that the bear upon or likelihood does not increment.

Loftier Impact, Loftier Probability

Risks that are characterized as both high impact and high likelihood of occurrence often crusade a project to be terminated, or to fail if it is continued in spite of the risks. In this situation, the possessor's management must determine if the project should exist terminated or if the projection is so mission critical or the potential benefits are so great that taking the risks is justified. Risk management does not imply that no risks are taken; it means that the risks taken should be calculated risks. For example, an owner may determine to proceed if at that place is a reasonable expectation that enough engineering or management try tin can reduce either the impact or the likelihood of the events, such that the risk can get either low impact, high probability or depression probability, high affect. Oft such a decision is contingent on achieving the necessary risk reductions by some deadline.

Low Bear upon, High Probability

Low-impact, high-probability risks are those largely due to uncertainties nigh a number of elements that may be individually modest risks only that in the aggregate could amount to a meaning gamble. These include uncertainties apropos the actual costs of labor and materials (such as steel), the actual durations of activities, deliveries of equipment, productivity of the workforce, changes due to design development or the possessor's preferences, and other uncertainties that are typically considered to lie within the natural variability of project planning, design, construction, and commencement-up (they do not include catastrophic events or radical design changes). Each of these uncertainties, taken alone, would take fiddling bear upon on the projection. Even so, taken together, there is the possibility that many of the estimates of these factors would prove to be too optimistic, leading

Suggested Commendation:"4 Hazard Identification and Analysis." National Research Council. 2005. The Owner's Office in Project Risk Direction. Washington, DC: The National Academies Press. doi: ten.17226/11183.

to cumulative effects such every bit performance shortfalls, schedule overruns, and cost overruns. Methods for dealing with such risks include

Provision for acceptable contingencies (safety factors) for upkeep and schedule (contingencies are discussed in Chapter 6).
Improvement in the work processes in gild to reduce the uncertainties. Prefabrication of major components to avoid the uncertainties of construction at a job site is one example of changing the normal process to reduce risks (although in this instance the alter may also innovate new risks, such as transportation of the components to the job site; thus the resolution of i risk may give ascension to another).

High Impact, Low Probability

By definition, high-bear on, low-probability events are rare occurrences, and therefore it is very hard to assign probabilities to them based on historical records. Data practice not exist and so subjective estimates of probabilities are necessary. However, the objective is not the scientific determination of accurate probabilities of rare events merely the decision of what management deportment should be taken to monitor, mitigate, and manage the risks. For example, if a sure take chances is identified and management determines that some specific mitigation actions should be taken if the run a risk has a likelihood of more than ane in 100 of occurring, then a precise label of the probability is unnecessary; the but issue is whether it is assessed to be more than 1 in 100 or less than 1 in 100.

Pareto Diagrams

One of the important uses of a good run a risk analysis is to determine where to apply management resources and what to leave alone, as management resources are not unlimited. 1 approach is to break downwardly the uncertainties into manageable parts. Pareto diagrams are 1 fashion to show the sources of uncertainty or impact in descending order. This form of presentation makes explicit those activities that have the greatest effect on the project completion date or cost and that therefore require the greatest management attention. The project director or manager must then determine whether the loftier-ranking events are (ane) truly root causes or (ii) simply work packages or activities that may reflect underlying causes but are themselves symptoms. The resulting analysis tin provide guidance for managers to reduce, mitigate, buffer, or otherwise manage these sources of incertitude.

Suggested Citation:"iv Take a chance Identification and Analysis." National Research Council. 2005. The Owner'south Function in Project Risk Direction. Washington, DC: The National Academies Press. doi: 10.17226/11183.

Every bit a elementary analogy, suppose we are interested in determining which work packages have the greatest effects on the dubiousness in the full price. First, we judge the uncertainty, or variance, in the toll of each individual work package. 2nd, we estimate the correlations or associations between each pair of work packages. Then, by elementary second-moment theory (Benjamin and Cornell, 1970),¹ the sensitivity of the uncertainty in the total project cost with respect to each work bundle is proportional to the combination of the action uncertainties and the correlations between activities. That is, the uncertainty in the full cost is affected not but by the dubiety in each work parcel just also by how much each work parcel affects, and is afflicted by, the others. Equally an elementary instance, the uncertainty in the cost of a structure project may be more sensitive to outdoor activities than to indoor activities because unusually bad weather tin can cause a number of outdoor activities to run over budget and over schedule simultaneously, whereas indoor activities are typically not linked then tightly to the weather. By tabulating these values for all work packages, and sorting them from largest to smallest, we can identify those piece of work packages with the largest sensitivities, which are those to which the project managing director should give the highest priority. If we do this for a project of, say, 20 piece of work packages and sort them co-ordinate to the largest values of the sensitivities, we can and so plot a Pareto diagram, as shown in Effigy iv-1. (The absolute values of the sensitivities accept no importance; the only concern is the relative values.)

Failure Modes and Effects Analysis

In project chance assessment, a failure tin exist any significant event that the sponsor does non want to happen—a budget overrun, a schedule overrun, or a failure to encounter scope, quality, or mission performance objectives. While risks may arise from specific causes, they may also be the result of general ecology conditions that are not express to specific times and places merely are pervasive throughout the project. The objective of failure modes and effects assay is the identification of root or mutual causes, which may impact the project as a whole. Often this identification is facilitated by methodically considering the project office by function,

All probability distributions may be characterized by their moments. Second-moment theory is the use of the 2nd moments of probability distributions—that is, ways, variances, and covariances (or correlation coefficients), instead of total probability distribution functions. Every bit probability distributions are subjective and therefore not capable of precise definition, this guess method tin can greatly simplify many calculations and, more chiefly, provide the risk annotator with insight into the effects of uncertainty on project outcomes.

Suggested Citation:"4 Risk Identification and Analysis." National Research Council. 2005. The Owner'south Role in Projection Risk Management. Washington, DC: The National Academies Press. doi: x.17226/11183.

FIGURE 4-i Pareto diagram.

to effort to avoid omissions. Identification of potential risks that turn out, upon farther assessment, to be negligible is a waste of time; however, failure to identify potential risks that turn out to exist serious is a threat to the project. Therefore, the project managing director should err on the side of caution when identifying possible risks.

Failure modes and furnishings analysis (FMEA) is a discipline or methodology to assist in identifying and assessing risks qualitatively. It is a method for ranking risks for further investigation; however, information technology is not a method for quantifying risks on a probabilistic basis (Breyfogle, 1999). FMEA is typically based on a subjective assessment of the relative magnitudes of the impacts of the run a risk events on the project (often on a scale from 1 to 10), multiplied by the relative likelihood that the adventure issue will occur (also on a scale from 1 to x). In addition, a third parameter may be included to assess the caste of warning that the project will accept regarding the actual occurrence of the gamble event (once again on a scale from 1 to 10). This third parameter may give some management back up by establishing early on warning indicators for specific serious risks, which might not otherwise have been established.

Suggested Citation:"4 Risk Identification and Analysis." National Research Council. 2005. The Owner's Role in Project Risk Direction. Washington, DC: The National Academies Press. doi: 10.17226/11183.

The purpose of assigning these values for all significant risks is merely to rank the risks and to set priorities for subsequent quantitative analysis of the pregnant risks. In the absence of more quantitative factors, such as sensitivity assay, the failure modes, or better, all root causes, can exist used to rank the risks. Ane tin can prepare a Pareto chart that shows the risks ordered by possible affect or by the combination of impact and likelihood of occurrence. So risk mitigation efforts can first accost the failure mode or root cause with the highest impact and work from there.

The three factors—severity, likelihood, and leading indicators—interact. For example, if the projection is the construction of a facility in a flood plain or an area with poor drainage, then a failure mode could be flooding of the work site. Project direction cannot affect the frequency of floods, so risk management must focus on trying to reduce the severity of the impact of a flood. If the control method is to purchase flood insurance and then evacuate personnel and abandon the site if the water rises, so measuring the height of the h2o (the "Nilometer" method) may be a sufficient indicator. If the control method is to reduce the severity of loss by placing sandbags around the perimeter and renting pumps, then measuring the water height may have little impact on the mitigation endeavor; but measuring the rainfall across the watershed may be more than appropriate because it allows time to implement the control. If the command method is to build a cofferdam around the site earlier constructing annihilation else, and then the choice of leading indicator may be irrelevant.

Efforts to mitigate the risks will focus on the impact, likelihood, and detectability of the almost serious hazard or its root causes and will try to reduce these factors until this adventure becomes as low as or lower than the next higher risk. Every bit this process continues, the virtually important risks volition exist reduced until there are a number of risks substantially the same and a number of other risks all lower than the starting time group. The first group volition crave specific direction actions and may crave constant monitoring and attending throughout the project. The second group will be monitored, but with lower priority or frequency. The offset group is considered the critical group, much like the critical-path activities in a network schedule; the second grouping is the noncritical group, which must exist watched primarily to encounter that none of the risks from this grouping become critical.

Information technology should be emphasized that this form of hazard assessment is qualitative and relative, not quantitative and accented. It is primarily for distinguishing betwixt risks that require follow-upward and management, considering of high impact or high likelihood (or both), and risks that do not appear to require follow-up, because of both low impact and low likelihood. It should exist clearly understood that in that location is no quantitative assessment of the overall risk to the total project: The severity factors are not estimated

Suggested Commendation:"4 Run a risk Identification and Analysis." National Research Council. 2005. The Owner's Role in Project Gamble Direction. Washington, DC: The National Academies Printing. doi: x.17226/11183.

in terms of loss of dollars, the likelihoods of occurrence are non probabilities, and there is no cost-benefit analysis of the risks versus the command methods. The analysis but identifies risk priorities in a methodical way to help direct further hazard management activities. It is left to the judgment of the project engineers, designers, and managers to determine the appropriate risk mitigation and control measures to achieve an adequate level of risk. Notation especially that risks with a depression likelihood of occurrence but very loftier severities may crave follow-up and management activity.

Due to changes in project weather condition or perceptions, even risks that announced to accept low affect and loftier likelihood at one time may appear differently at another. Therefore, the possessor's representatives have the responsibility to reevaluate all failure modes and effects periodically to ensure that a risk previously considered negligible has not increased in either touch on or likelihood to a level requiring management attention.

Project Definition Rating Index

The Project Definition Rating Index (PDRI) is an example of an condiment qualitative chance cess tool (CII, 1996, 1999). The PDRI is used in front-end project planning to aid the project team assess project scope definition, place take chances elements, and subsequently develop mitigation plans. Information technology includes detailed descriptions of bug and a weighted checklist of project scope definition elements to jog the memory of project team participants. Information technology provides the means to assess risk at various stages during the front-finish project planning process and to focus efforts on high-gamble areas that need additional definition. The PDRI facilitates the projection team's cess of risks in the project scope, price, and schedule. Each gamble element in the PDRI has a serial of five predetermined weights. In one case the weights for each element are determined they are added to obtain a score for the unabridged project. This score is statistically correlated with project performance to gauge the level of certainty in the project baseline.

METHODS OF QUANTITATIVE Risk ANALYSIS

Later risk factors are assessed qualitatively, it is desirable to quantify those determined by screening activities to be the nearly significant. It cannot exist repeated too often that the purpose of risk assessment is to be meliorate able to mitigate and manage the projection risks—not simply to compute projection risk values. The assessment of risks attributed to elements completely out of project direction command—such as forcefulness majeure, acts of God, political instability, or actions of competitors—may exist necessary to reach an understanding of total projection risk, simply the risk assessment should

Suggested Citation:"four Risk Identification and Analysis." National Research Council. 2005. The Owner's Role in Projection Gamble Direction. Washington, DC: The National Academies Press. doi: ten.17226/11183.

exist viewed as a step toward identifying active measures to manage all risks, even those considered outside the command of project managers, non to support a passive attitude toward risks as inevitable.

Information technology is ofttimes desirable to combine the diverse identified and characterized adventure elements into a unmarried quantitative project risk estimate. Owners may as well be interested in knowing the total risk level of their projects, in gild to compare different projects and to decide the risks in their projection portfolios. (See the discussion of plan risk and project portfolios in Chapter 8.) This judge of overall project risk may exist used every bit input for a determination nigh whether or not to execute a project, as a rational basis for setting a contingency, and to set priorities for risk mitigation.

While probabilistic risk assessment methods are certainly useful in determining contingency amounts to cover various procedure uncertainties, simple computation methods are frequently as good equally, or fifty-fifty better than, complex methods for the applications discussed here. Owner's representatives should be skilful in elementary statistical approaches for computing take chances probabilities, in order to be able to bank check the numbers given to them by consultants and contractors. When addressing probabilistic take a chance cess, project directors should go on in mind that the objective is to mitigate and manage project risks and that quantitative risk assessment is but a part of the process to assistance achieve that objective.

At that place are many available methods and tools for quantitatively combining and assessing risks. Some of the most frequently used methods are discussed briefly below.

Multivariate Statistical Models

Multivariate statistical models for project costs or durations are derived from historical data. Also known every bit regression analysis, statistical models are one of two methods of assay explicitly cited in OMB Circular No. A-94 (OMB, 1992). The models are typically either meridian-down or parametric and do not contain enough particular to validate bottom-up engineering estimates or projection networks.

These methods are objective in that they do not rely on subjective probability distributions elicited from (possibly biased) project advocates. Analysts build linear or nonlinear statistical models based on data from multiple past projects so compare the projection in question to the models. The use of such statistical models is desirable every bit an independent benchmark for evaluating cost, schedule, and other factors for a specific project, but statistically based methods require a large database of projects, and many owners do non perform enough projects or expend the effort to create such databases. Owners who take performed many projects but have non developed usable historical projection databases have an opportu-

Suggested Citation:"four Take a chance Identification and Analysis." National Research Council. 2005. The Owner's Office in Projection Gamble Management. Washington, DC: The National Academies Press. doi: 10.17226/11183.

nity to ameliorate their competence in project and plan management by organizing their own data. Computational methods such as resampling and bootstrapping are too used when data are insufficient for direct statistical methods.

The bootstrap method is a widely used computer-based statistical process originally developed by Efron and Tibshirani (1993) to create a proxy universe through replications of sampling with replacement of the original sample. Bootstrapping is used to estimate conviction levels from express samples simply is not applicable for developing point estimates.

Upshot Copse

Event copse, also known as error trees or probability trees, are commonly used in reliability studies, probabilistic risk assessments (for example, for nuclear ability plants and NASA space probes), and failure modes and effects analyses. The results of the evaluations are the probabilities of diverse outcomes from given faults or failures. Each consequence tree shows a particular event at the summit and the weather condition causing that event, leading to the conclusion of the likelihood of these events. These methods tin can be adapted to projection cost, schedule, and performance adventure assessments.

System Dynamics Models

Projects with tightly coupled activities are non well described by conventional project network models (which prohibit iteration and feedback). Efforts to apply conventional methods to these projects can lead to incorrect conclusions, counterproductive decisions, and projection failures. In contrast, system dynamics models (Forrester, 1969) depict and explicate how project beliefs and performance are driven past the feedback loops, delays, and nonlinear relationships in processes, resources, and management. System dynamics models tin can be used to clarify and test project participants' assumptions as well as to design and test proposed project improvements and managerial policies. Considering arrangement dynamics models are based on dynamic feedback the models can also exist used to evaluate the impacts of various failure modes or root causes, particularly in cases where the root causes can be identified merely the ripple event of their impacts is difficult to estimate with any confidence.

Arrangement dynamics models have been effectively used for project evaluation, planning, and run a risk assessment (Cooper, 1980; Lyneis, Cooper, and Els, 2001; Ford and Sterman, 2003). Although the use of these models is not standard practice for project planning and adventure management, they tin can significantly help owners to improve their understanding of project risks.

Suggested Citation:"iv Chance Identification and Analysis." National Research Quango. 2005. The Possessor's Role in Project Risk Management. Washington, DC: The National Academies Press. doi: ten.17226/11183.

Sensitivity Assay

Sensitivity analysis of the results of any quantitative risk assay is highly desirable. A sensitivity coefficient is a derivative: the change in some upshot with respect to a change in some input. Even if the probability of a particular chance cannot exist adamant precisely, sensitivity analysis can be used to determine which variables have the greatest influence on the risk. Because a primary function of take chances analysis is to break down the problem into essential elements that tin can be addressed past management, sensitivity analysis can be very useful in determining what decisions the manager should make to get the desired results—or to avoid undesired results. In the absence of difficult information, sensitivity analysis can exist very useful in assessing the validity of risk models.

Project Simulations

Project simulations are group enactments or simulations of operations, in which managers and other project participants perform the project activities in a virtual environment before undertaking them on the project. This blazon of simulation may or may not be supported by computers; the accent is not on the calculator models simply rather on the interactions of the participants and the effects of these interactions on projection outcomes. For this reason, project simulations are very skilful for team building earlier a projection actually starts up. They are not inexpensive, but the cost is generally comparable to the costs of the other techniques cited here, and they can be very cost-effective in the long run, compared to the typical approach of jumping into major projects with little or no preparation of the personnel and their working relationships. Engineering and construction contractors have adult project simulation methods (Halpin and Martinez, 1999), and owners can develop their own or specify that their contractors should perform such simulations earlier a project starts, in conjunction with the other preproject planning efforts.

Stochastic Simulation Models

Stochastic simulation models are computerized probabilistic simulations that, for computational solution, typically utilise random number generators to draw variates from probability distributions. Considering the computer simulation is performed with random numbers, these methods are also called Monte Carlo simulations. The objective of the simulation is to find the uncertainties (empirical probability distributions) of some dependent variables based on the assumed uncertainties (subjective probability distributions) of a set of independent variables, when the relation-

Suggested Citation:"4 Adventure Identification and Analysis." National Inquiry Council. 2005. The Owner'due south Function in Project Risk Management. Washington, DC: The National Academies Press. doi: 10.17226/11183.

ships between the dependent and independent variables are also complex for an analytical solution. Thus each iteration (random simulation) may be considered an experiment, and a large number of these experiments gives insights into the probabilities of various outcomes. Monte Carlo simulation is typically used to combine the risks from multiple risk factors and as such is useful to determine whether the full take chances of a project is too corking to allow information technology to go along or to determine the advisable amount of contingency. This technique is the second of the ii methods explicitly cited in OMB Circular No. A-94 (OMB, 1992).

Stochastic simulations differ from multivariate statistical models because they are typically not based on difficult information. They can be useful in the absence of real data in that they are based on subjective assessments of the probability distributions that exercise not crave large databases of previous projection information. An often-cited weakness of this method is that subjective assessments of probability distributions often lack credibility, because they may be influenced by bias. This can be overcome to some degree past a advisedly structured awarding of expert judgment (Keemey and von Winterfeldt, 1991).

As is the instance with all the other figurer methods for quantitative risk analysis discussed here, the validity of the method lies entirely in the validity of the probabilistic models. Monte Carlo simulation is very versatile because information technology can exist practical to virtually any probabilistic model. However, the validity of the results may sometimes be suspect, due to the following factors:

The independent variables may non really exist independent;
The number of iterations in the simulation may be insufficient to produce statistically valid results; or
The probability distributions causeless for the independent variables are subjective and may be biased if they are provided by project proponents.

It is certainly possible to develop project-specific cost models, for example, by using causal parameters that are totally independent. However, many risk analyses are not based on project-specific models but simply adopt the standard applied science condiment cost models, in which the total cost is the sum of work package costs. The simulations simply add up the uncertainties associated with work packages, but they may exist inaccurate because these work packages are non necessarily independent. It is computationally much easier to perform Monte Carlo simulation if the analyst avoids the need to consider interactions betwixt variables past simply assuming that all variables are independent; however, an analysis without consideration of mutual manner failure tin pb to an under-

Suggested Citation:"iv Hazard Identification and Assay." National Inquiry Council. 2005. The Owner'due south Role in Project Risk Management. Washington, DC: The National Academies Printing. doi: ten.17226/11183.

interpretation of total project gamble. In project risk assessment, a common style could be an result or environmental status that would cause many price variables to tend to increment (or decrease) simultaneously. It is widely recognized that a unmarried consequence can cause effects on a number of systems (i.e., the ripple effect). If the event occurs, the costs of these systems volition all increment, whereas if it does not occur, they will remain within the upkeep. Thus these afflicted costs are definitely not statistically independent.

Collaboration between people who are very conversant with the specific risks of the projection and those who are familiar with probabilistic methods is typically required to reduce bias and to produce realistic quantification of projection risks. Project owners should ensure that the probabilistic inputs are as objective and unbiased as possible and that the reasons for choosing specific probability distributions are adequately documented.

As with any method, the use of stochastic simulation requires quality control. The possessor's policies and procedures on Monte Carlo simulation should include cautions to projection directors and managers about the limitations of this method every bit it is usually applied. The projection director is generally not a specialist in Monte Carlo simulation, and does not need to be, only should understand the advantages and limitations of this approach. This is particularly true at present that Monte Carlo simulation is readily available through mutual spreadsheet software and then can be used by people with piffling knowledge of statistics. A project director should know enough to be able to critically evaluate the stochastic simulation results for plausibility and should non have the results only considering they come from a estimator.

It is mutual for Monte Carlo simulations to apply far fewer iterations than the minimum normally required to become statistically valid answers. Simply simulations with insufficient iterations may underestimate the probability in the tails of the distributions, which is where the risks are. (Meet, for instance, Alder, Feldman, and Taggo, 1998.) Therefore, a simulation with fewer random samples may indicate more or less run a risk than one with more iterations. In that location are mathematical formulas (Breyfogle, 1999) that can be used to compute the minimum number of iterations for acceptable conviction limits on the ways or the values in the tails of the distribution. If a consultant or contractor is performing Monte Carlo simulations for risk assessments, information technology would be prudent for the owner's project manager to review the confidence limits on all values computed using Monte Carlo simulation, to ensure that a sufficient number of iterations has been performed.

The use of Monte Carlo and other techniques for mathematically combining the risks of individual work packages into a single project risk number should not obscure the fact that the objective is to manage the risks.

Suggested Citation:"4 Gamble Identification and Analysis." National Inquiry Council. 2005. The Owner's Role in Projection Risk Direction. Washington, DC: The National Academies Press. doi: 10.17226/11183.

As typically used, Monte Carlo simulations tend to be focused on total risk probabilities, not on sensitivity assay, risk prioritization, or assessing possible outcomes from different proposed adventure direction policies.

Condiment Models

Additive models, as the proper name implies, are those in which the combination of take a chance factors is based on unproblematic addition. An example is the summation of cost elements to generate the total projection cost, or the summation of activity durations to generate the full projection duration. These models are relatively simple programs based on the summation of moments, derived from probability theory, to combine risks for dependent as well as independent variables. If the objective is simply to detect the probability distribution of the project price estimate as the sum of a number of work packages or activities, stochastic simulation is unnecessary. 1 reward of simple condiment models is that they are easily understood, and information technology is usually obvious which activities contribute the virtually to the total project incertitude and which exercise non. This method is the basis for the program evaluation and review technique (PERT) for determining dubiousness in project completion times.

In bottom-upward project price estimating, the total cost is only the sum of the costs in the WBS piece of work packages. This is a purely linear relationship. Therefore, estimating the uncertainty in the total toll requires just summing the uncertainties in the private cost accounts, modified by the dependencies between them. Probability theory tells us that we tin can compute the moments of the probability distribution of the total projection cost by summing the moments of the uncertainties in all the individual cost accounts (Burlington and May, 1953; Hald, 1952). The number of moments can be approximated to some finite number. (This is a very common method of approximation in technology—for example, the truncation of a Taylor Series after one term in order to proceeds a linear equation.) The second-moment arroyo (Benjamin and Cornell, 1970) uses the first two moments, i.e., the mean and the variance, and neglects the third (skewness) and higher. The second-moment approach does not deal with full probability distributions simply uses but the means, variances, and covariances (the first two moments) to characterize uncertainties.

This approximation is justified because it is very difficult or fifty-fifty incommunicable to estimate higher moments (skewness, kurtosis, etc.) with any accuracy, even if i were in possession of large historical databases. In most cases of risk assessment, the probability distributions are largely subjective and based on judgment and feel rather than hard data. At that place is little betoken in making highly precise computer calculations on numbers that cannot be estimated accurately anyway.

Suggested Commendation:"4 Risk Identification and Analysis." National Enquiry Council. 2005. The Owner'south Role in Project Take a chance Management. Washington, DC: The National Academies Press. doi: 10.17226/11183.

There are some additional advantages of the 2d-moment approach:

Priorities for risk mitigation tin can be obtained from a Pareto analysis using only the uncertainty in each individual take a chance factor and the correlations between adventure factors.
Sensitivity analyses are easily performed.
As a projection progresses, the estimates of the uncertainties in future cost accounts or activities tin can readily be revised, based on the past performance of the projection itself. This is one of this method'south virtually useful properties. By comparing the actual performance on completed work packages, activities, or milestones with the prior estimated uncertainties, 1 obtains revised estimates of the piece of work packages, activities, or milestones yet to come.

Through second-moment assay, project directors can use the information and experience on the actual project to revise the estimates of the work to go. This approach can exist a valuable tool for plan managers, if each project director is required to report the updated, revised cost at completion, including the confidence bounds on this estimate, for every reporting period. Because this method looks frontwards instead of backward, as virtually other projection direction methods practice (including earned value analysis), unfavorable revisions to either the expected price at completion or the uncertainty in the toll at completion should trigger direction action. Conversely, favorable revisions to either the expected cost at completion or the uncertainty in the cost could let direction reserves to be reallocated to other projects with greater needs. (See Chapter 8 for a discussion of managing risks of project portfolios.)

The second-moment method provides a simple, convenient method for the adjustment of risks, and hence the adjustment of the required contingencies, as a project gain and information are obtained on how well or desperately it is performing. The objective of this approach is to react equally presently as possible to information on recent project performance that tends to confirm or to refute the current estimates. The key command parameter is the estimated toll (or time) at completion. For example, if the best estimate of the cost at completion, updated with the most recent progress data, is higher than the original estimate, and so, bold no scope changes, either the take a chance of overrunning the budget is greater than originally estimated, or program direction corrective action may be needed to bring the project dorsum on target. Conversely, if the updated all-time estimate of the cost at completion is the same as or lower than the original guess, so the required contingency can be decreased. In this approach, the estimates of all time to come piece of work packages are updated as the actual costs for each completed work bundle become bachelor through the cost reporting organization.

Suggested Citation:"4 Take chances Identification and Analysis." National Research Council. 2005. The Possessor'due south Office in Projection Risk Management. Washington, DC: The National Academies Press. doi: ten.17226/11183.

TABLE 4-2 Summary of Take a chance Analysis Tools

Tool	Characteristics
Two-dimensional impact/ probability	Qualitative, simple to use and most frequently used, tin can exist expanded to iii or more dimensions, and can be combined with FMEA
Pareto diagram	Simple qualitative method for prioritizing take chances elements
Failure modes and effects analysis (FMEA)	Qualitative, used for initial screening only, effective in a team environment
Project Definition Rating Index	Qualitative, used in front-end project planning, effective in a team environment
Multivariate statistical model	Quantitative, requires historical database
Event tree	Quantitative, rarely used for risk analysis
Organisation dynamics model	Both qualitative and quantitative, rarely used but effective, requires skilled modelers
Sensitivity analysis	Quantitative, useful regardless of which other procedure used, useful in absence of hard data
Project simulation	Both qualitative and quantitative, useful for squad edifice, expensive to implement
Stochastic simulation	Quantitative, oft used, often misused, so limitations must be fabricated clear
Additive model	Quantitative, can exist adjusted as project progresses

Tabular array iv-2 provides a summary of the qualitative and quantitative methods of risk analysis reviewed in this department.

Determination

Although additive, 2d-moment models lack the computational complexity of stochastic take chances cess techniques, for most practical applications they are more than adequate. From the standpoint of the owner, the purpose of project risk cess is to minimize the impact of doubtfulness on the project. How this is best accomplished will vary with circumstances, simply, in general, simple direct methods have proven them-

Suggested Citation:"iv Run a risk Identification and Analysis." National Research Council. 2005. The Owner's Role in Projection Run a risk Direction. Washington, DC: The National Academies Printing. doi: 10.17226/11183.

selves in practice. This does non discount the value of stochastic models, but their awarding needs to be considered in terms of their contribution to risk direction. Probabilistic simulations are of detail value when data are sparse and the full range of possible adverse events cannot be easily inferred. Provided that a sufficient number of simulations are performed, boundaries for full project take a chance tin can be established. Nevertheless, for the vast majority of projects, it is the committee'southward commonage experience that the simpler models are more useful for generating hazard estimates that can exist used in day-to-day project management.

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Source: https://www.nap.edu/read/11183/chapter/6