Risk Identification, Analysis and Allocation

8/6/2019 Risk Identification, Analysis and Allocation

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Risk identification, analysis and

allocation


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The Project Management Institutes Guide to theProject Management Body of Knowledge (PMBOK)classifies risk in accordance with five categories:

- external, but unpredictable;- external predictable, but uncertain;- internal, non-technical;- technical;

- legal.This classification concentrates on source of risk ratherthan risk effect.

The preferred way of classifying risk events is to beplace an event in one of twenty-five categories asidentified in Figure. By relating an event to both theamount at stake (between negligible and very high) andthe probability (from improbable to almost certain)


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Of the event happening then each event can be

classified as either as low (l), medium (M) or high (H)risk.With this classification, the least important risk is the

one which is of low probability negliance impact, the

least important risk is the one having high probability very high impact; All types of risk need to be identified. Itis only after assessment (quantification) that it can bedetermined whether a risk has the potential of becoming

consequential or inconsequential. This matter ofclassification is only introduced here but will be dealtwith more fully Risk identification below.


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The most serious effects of project risk

are:

Failure to keep within the cost estimate;

Failure to achieve the required completion date;

Failure to achieve the required quality andoperational performance.


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M H H H H

M M H H H

L M M H H

L L M M H

L L L M M

5

4

3

2

1

5 4 3 2 1

improbable

Unlikely

Reasonably foreseeable

likelyAlmost

certain

Very high

high

moderate

slight

negligible


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When serious occur on project cost estimates and timeschedules, the effect on the overall project can be very

damaging. In extreme cases, time and cost overruns caninvalidate the economic case for a project, turning apotentially profitable investment into a loss makingventure. The evidence would indicate that too many

projects overruns both cost and time targets. Betterproject management will produce significantimprovement in meeting predetermined targets. Betterproject management includes identifying measuring and

responding to risks.Targets are sometimes missed because of unforeseen

events that even an experienced project managercannot anticipate. More often it happens because of


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events that are predictable in general, but not inspecific, terms. This will not always lead simply to

a list of potential calamities. Cost may be lessthan anticipated, the weather may be kind,revenues may exceed expectations (risk may bebeneficial but they must always be taken intoaccount), etc.

A reason for the early identification of risk isthat it focuses the attention of the project's

management on the contract strategy. It will alsohighlight those areas where further design,development work and/or clarification may be

needed.


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Selected TechniquesRisk quantification produces estimates expressed interms of ranges not as single figure. The accuracy of therange and the probability improves with clasped time.Quantifying risk can be fairly subjective. Using one ormore of the following techniques can produced anestimate of the degree of uncertainty:

brainstorming;Probability analysis;Expected (monetary) value;

Decision trees;Statistical sums;Monte Carlo analysisSensitivity profiling;


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Brainstorming

Brainstorming is a general technique you will recall its

application in the value process. Brainstorming sessionscan be valuable when analysing a particular problemsand need to be carried out in a way that will maximisetheir effectiveness. If many different disciplines are

involved in quantifying risks it may be better t hold abrainstorming session for each discipline as well as onethat involves all disciplines. The aim should be that allparticipants leave the session/s with a common

perception of the risks and the uncertainties of theproject. A general process that is used for effectivegeneric (not just for risk events) brainstorming is shownin figure.


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Here the problems is identifying/quantifying riskevents. An indication of the rules of running theworkshops and each persons role, alongwith a time

table for the process, needs to be specified up-front. Abrainstorming session normally consists of three stages:information, creation and evaluation.

Information relating to the problem (in this case,project risk) should be distributed to each participant notas lists but in diagrammatic format. Preferably thisshould be done prior to the session start as a means of

common understanding and to give potential participantsthe opportunity to add or modify the information.The next stage is the creation of ideas ( in this case,

risk events) which is usually a combination thought and

plenary (or subgroup) sessions. Using Post-its each


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Rules plus a timetable

plus the project team

INFORMATIONSTAGE

EVALUATION

STAGE

CREATIONSTAGE

PROBLEM


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Probability analysis

Probability analysis specifies a probability

distribution for each variable. The outcome of theanalysis is a range of possible results with theirrespective probabilities that can be used to

assess attitudes and responses to a project andits risk.

For example, lets look at a variable x1 which

has been determined by a group of experts ashaving the range of values as shown in thehistogram in figure. Well assume x is the numberof days it will take to do a certain activity.

Th hi t i d ith th b i (h i t l)


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The histogram is drawn with the abscissa (horizontal)as the variable x and the ordinate (vertical) as N (thenumber of observations), which is referred to as function

of x or f(x) for short. As can be seen, one person thoughtit could be done in 10 days; three persons, 11 days;eight persons, 12 days; six persons, 13 days; and twopersons, 14 days a total of 20 persons contributing to

deriving the data for variable x.Simply by converting the scale of the ordinate by

dividing by 20 (the total number of observations) thehistogram (a) is converted into a probability chart (b)

with the ordinate now being referred to as the probabilityof x or p(x). By connecting the upper points of theprobabilities a probability distribution is formed with anarea under the curve equal to 1. This distribute of x canbe characterised by knowing two things: its centrality


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and its spread. Centrality is measured bydetermining the mean, and the variance. The

square root of the variance is the standarddeviation, which is the more popular way ofdefining spread. The mean and standarddeviation are called the first and secondmoments respectively.In figure the mean (or expected value) is 12.25

days and the standard deviation is 1.31 days.

This indicates that the optimistic result would be10.94 days and the pessimistic result would be13.56 days.

If it is assumed that the distribution would


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Expected (monetary) value

Probability can be used to calculate the expected

outcome of a decision which has a range ofprobabilities and contingent outcomes. Expectedvalue (EV), as a tool for risk quantification, is theproduct of two numbers: risk event probability (anestimate of the probability that a given event willoccur) and risk event value (an estimate of thegain or loss that will be incurred if the risk event

does occur). For example, the duration of anactivity might be quoted as between 8 and 16weeks with the probabilities as shown in table.The expected value for this activity would be

12.40 weeks.


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The result of this form of calculation isgenerally used as input to further analysis (e.g. in

decision trees) since risk events can occurindividually, or in groups, in parallel or insequence. Often because the expected value is

linked to money the term in this case is expectedmonetary value.


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Table. Duration, probability andexpected value

A

Activity time (weeks)

B

Probability

A x B

Expected value

81216

0.200.500.301.00

1.606.004.8012.40


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Decision treesDecision trees form a graphical means of

bringing together information that deals choiceand making a decision. This technique forcesconsideration of the probability of each outcome.Decision trees are drawn from left to right withevent nodes represented by circles and decisionnodes by squares. Arrowed lines between nodesrepresent influences of one node on another. An

event node that precedes another event nodeindicates that the probability associated with thesucceeding event (chance variable) depends onthe outcome of the preceding event (chance

variable). Likewise, a decision node that


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Precedes an event node indicates that the probability ofthe succeeding chance variable depends upon thepreceding decision. An arrow pointing to a decision node

indicates that either the decision is influenced by a priordecision, or on the occurrence, or not, of prior events.

Decision trees are analysed from right to left and thisis best demonstrated by examining figure which shows avery basic decision tree. A supplier (contractor) needs tomake a decision on whether to bid to construct aplanned new airport or a planned new dam across a

river.The information relating to this scenario is that therewill be two bidders for the airport, the potential profit isestimated at 2 million monetary units (mu), and the cost

of preparing the bid will be 0.5 million mu. There will be


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EVd= 1.33 1.0 = 0.33 million mu

DAM bid 1 million mu

Airport bid 0.5 million mu

EVa= 1.0 0.5 = 0.5 million mu

EV= (4.0.33) + (0x0.66) = 1.33 million mu

1 in 3 (p = 0.33)

2 in 3 (p=0.66)

1 in 2 (p=0.5)

1in 2(p=0.5)

EV= (2x0.5) + (0x0.5) = 1 million mu

4 million mu

0

2 million mu

0


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Triangular and beta distributions

Triangular distribution Beta distribution

Mean = (a + m = b) /6Variance = [(b-a) + (m a) (m

b)]/18

Mean = (a + 4m + b) /6Variance = [(b a)/6]

S


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Statistical sumsStatistical sums can be used to sum probability

distribution of cost estimates quantity estimates andsimilar items. By convention, project cost estimates areeither triangular or beta. The method of momentsapproach require estimates of the optimistic, a, most

likely, m and pessimistic, b, cost estimates for eachindividual activity or task within each work package.From this, the tasks mean and variance can be derivedand by summing these outputs the project expected cost

and standard deviations (square root of the projectsvariance) can be determined. One or both of thedistributions in Table can be assumed. Distributions canbe mixed and matched at will.


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Monte Carlo analysis

A risk model is a representation of some attribute of a

system or project for the prediction and control of therisk exposure contribution of that attribute (usually timeor money). Simulation introduces specific values of theinput variables in the model of interest and observes theeffect on the output variables subject to the probabilitythat govern the model. The Monte Carlo method is at theheart of simulation. (contrary to popular belief, the Monte

Carlo method is related to the atom bomb development,not the capital of Monaco.)

The method process is how in Figure. The method isbest explained by an example.


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Tabulate

frequencies &

probabilities

Derive cumulative

probability

distribution

Encode random

number range

Select

random

numbers

Decode

randomnumbers

Derive

statistical

measure

1

2

3

4

5

6


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Taking the observed data from figure, we have timeand frequency creating columns 1 and 2 respectively.

See tableColumns 3 is obtained by dividing the values in

column 2 to 20. Column 4 is obtained by sequentiallysumming the individual probability values in column 3.The upper value within a given range is obtained bymultiplying by 1000 and then subtracting 1 (e.g. foractivity time 12 the cumulative value = 0.6, multiply by

1000 = 600 and subtract 1 = 599).The unparenthesised numbers in Table form a 10 x 10array of three digit random numbers that can begenerated on a personal computer.


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A spider diagram can be constructed using the


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A spider diagram can be constructed using thefollowing sequence:

Estimate the projects total life-cycle using amean (most likely) set of assumptions. Identify the risky variables in the project using a

decision-tree approach.

Select one of these variables and calculate newLCCs using variable values +1%, +5%, +10%,or whatever other increment may be

appropriate; Plot the results on a diagram similar to thetemplate shown in figure;

Repeat the process for the other variables.


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A

B

C

125

120

115

110

105

95

90

85

80

75

20% +15%10%5%5%10%15%- 20%

LCC mu x 1000

Although LCC has been chosen as the dependent


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Although LCC has been chosen as the dependentvariable for this example, other parameters, such asinitial rate of return (IRR), the duration of a project, etc.

could be used.Figure shows three risk parameters: A, B and C. It isfound that as A and B increases, they increase thedependent variable LCC. As C increases, it decreases

the value of the LCC. It can also be seen that thesteeper the plot of a variable (see B) the more sensitiveit is in affecting the dependent variable than other flatterplots of independent risk variable.

As part of the sensitivity analysis illustrated it is usefulto know how likely the cost parameter will vary within aparticular range. Probability analysis using, say, thecentral limit thereon, can determine probability contourssuch as shown in diagram for a 95% probability

(two standard deviations) The 95% probability which is


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(two standard deviations). The 95% probability, which isequivalent to all values within +2 standard deviations,would define the +% effect on the LCC of that variable.

In the hypothetical case shown in figure the plots arecontained within +15% for A, +7.5% for B, and +10% forC. this procedure would be carried out for any number ofindependent variables. This procedure would then, if

required, the extended to other probabilities to create aseries of contours.The shaded area in fig shows the region for the 95%

contour. Within this contour there is 95% probability of

finding the value, or magnitude, of the independent anddependent risk variables for this project.

Sensitivity analysis gives guidance for furtherinvestigations, provide the critical factors and showswhich parameters should be considered.


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Evidence shows that the eight largest parametersin a project will typically cover up to 90% of the

total risk impact. The challenge is finding them.In summary, risk quantification is primarilyconcerned with determining which risk eventswarrant response. It is complicated by a numberof factors including, but not limited to,opportunities and threats that interact inunanticipated ways, a single event that can

cause multiple effects, opportunities from onestakeholder being a threat to another, andmathematical techniques used that can create a

false impression of precision and reliability.

Project budget cost risk a method


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Project budget cost risk a methodTypically a project risk analysis consists of two parts:schedule and cost risk. Schedule risk has been dealtwith in this section. In general, a schedule risk analysisis more difficult to perform than a cost risk analysisbecause of the modelling, resourcing, crashing, etc. that

are features of finding the optimum schedule. A cost riskanalysis should succeed a schedule risk analysisalthough, because of the interrelationship between timeand cost, the cost risk analysis is, in reality, undertaken

in parallel with a schedule risk analysis. A significantpoint to remember is that both project schedule riskanalysis. A significant point to remember is that bothproject schedule and cost risk analyses should be

developed from the WBS.


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Additional estimates are needed to assess what are


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Additional estimates are needed to assess what aretermed the average risk estimate (ARE) and themaximum likely risk estimate (MLRE)

The ARE is the total financial provision most likely tobe required, i.e. there is as much chance of the riskallowance being adequate as not (50:50); it is the sum ofthe BE and the ARE. On the other hand, the MLRE

represents the budget amount on which there is a 90%chance of not being exceeded. It is derived bycalculating the sum of BE, ARE and MLRE.

So how do we calculate the ARE and the MLRE? To do

that, we need to be able to assess the risk allowances.Risk allowances can be two types: fixed and variable. Afixed risk is an item that will be incurred in whole or notat all with an assessed probability. A variable risk is anitem that is a risk relating to a circumstances which can

occur to varying degrees with corresponding varying


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occur to varying degrees with corresponding varyingprobabilities.

What can help in quantifying probability is to have a

ready means of transforming verbal expressions of risk,e.g. if someone is of the view that an item has a lowprobability of happening, what does this actually meanother than what it intimates? Table gives typical verbal

expressions versus equivalent quantified ,measures ofrisk.So, as you can see, if risk item is considered very high

then its probability of happenings is 0.90. If a risk item is

very slow then its probability would be 0.10. A mediumprobability (i.e. it has as much chance of not happeningas happenings) would be perceived as having aprobability of 0.50, and so on. If a verbal expression isbetween two of those given (e.g. if a risk item is

Considered higher than low, but not medium)


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Considered higher than low, but not medium)extrapolation is required.

The key activities in project estimating and budgetingusing risk analysis are:

identify risks; determine whether fixed or variable;

assign probabilities; establish risk allowances calculate the BE, ARE and MLRE.

The foregoing explanation should conveniently help

you to undertake the first three items. The next step, ofassessing the risk allowances, means determining theaverage risk allowances and the maximum likely riskallowances. This is to be determined for both fixed risks

and variable risks.

A range of risk measures


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A range of risk measures

Verbal

expression

Quantified

probability

Verbal

expression

Quantified

probabilityImpossibleVery slow

Lowmedium

0.000.10

0.250.50

HighVery high

certain

0.750.90

1.00

Fixed risks


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Fixed risks

For a fixed risk the average risk allowance is the

product of the maximum risk allowance and theassessed probability, i.e.:Average risk allowance= maximum riskallowance

x probability of occurrenceSo if the project is to establish a new corporatelogo and everything that goes with it (stationary,

etc) and within that project and development of aCD providing information on the company isbeing considered, this is an item that will either

proceed or will be vetoed, i.e. it is fixed risk.


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Variable risks


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VariablerisksFor a variable risk, the average risk allowance is

assessed as that a 0.50 probability of beingexceeded, i.e. it has a value that has an evenchance of being exceeded.

For instance, envelope with the new logo willbe required but whether the range of sizes will berestricted or extensive is not clear (hence,

variable needed but not sure of extent). Letsassume it has estimated that 23,500 mu is theenvelope cost which has a 0.50 chance of beingexceeded.


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The maximum likely risk allowance is the valuethat is assessed as having a 0.10 chance of

being exceeded. Let assume that the estimate is28 500 mu, i.e. the probability is very high ofproviding envelopes for the stated value of

28500mu.The final step is the calculation of BE, ARE andMLRE. As previously stated BE will have beenderived from those many items in a project thatare considered to be certainties. The ARE andMLRE are best established by tabulating the riskitems in a table having the following headings:

1 risk item;


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1 risk item; 2 probability of occurrence; 3 Average risk allowance;

4 maximum likely risk allowance; 5 spread 6 spread squared

The data for the first four columns aredetermined using the approach alreadyexplained. The spread is the difference between

the maximum likely risk allowance and theaverage risk allowance, i.e. column 4 column3. columns 6 is equivalent to determining thevariance in a statistical sum.

ARE = BE + the sum of all risk items in column 3


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MLRE = ARE + (column 6).So this method provides three budget values: the

baseline estimate. By using this, or a similar method, theproject sponsor or client is being provided with a budgetrange against which there are probability assessments.This provides the decision maker on finances with the

means to decide on the acceptable level of risk andaccordingly the budget premium that must be set asidefor risk items.

Finally, it should be remembered that as risk evaluation

is ongoing, certain risk items should be removed fromthe risk list when they can be classified as certainOther previously unidentified items should beincorporated in the risk list as soon as their absence is

noticed.

Risk Control


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Risk ControlRisk control involves executing the risk managementplan in order to respond to risk events over the course of

the project. When changes occur, the basic cycle toidentify, quantify and respond is repeated. It is importantto understand that even the most thorough andcomprehensive analysis cannot identify all risks and

probabilities correctly; control and iteration required.Inputs to risk

The risk management plan;Risk response plan;Project communication;Additional risk identification and analysisProject and its.

Some of the identified risk events will occur,


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Some of the identified risk events will occur,others will not. The ones that do are actual riskevents and the project management team must

recognise such occurrences so that the responsedeveloped can be implemented. As projectperformance is measured and reported, potential

risk events not previously identified may surface.If the risk event was not anticipated, or theeffect is greater than expected, the plannedresponse may not be adequate, and will benecessary to repeat the response developmentprocess ( and perhaps the risk quantificationprocess as well). As anticipated risk events

occur,


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fail to occur, or as risk event effects are

evaluated, estimates of probabilities and value,as well as other aspects of the risk managementplan, should be updated.

Project management has a vital role to play in

risk management. In the work leading up to theapproval of funds, project managers cancontribute to sound economic appraisal by

producing realistic estimates of cost and time thatare based on a clearly defined standard of thequality of work and the operational requirements.

The key elements for success are:


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The key elements for success are: An in-depth study of risk and uncertainty on all

projects; Estimates of cost and time that include specificcontingency allowances;

Proposals of ways of at least reducing theeffects of risk and uncertainty;

The adoption of methods for allocating the

remaining risks to the various parties in a waythat will optimise project performance;

Recognition that risk and reward go hand-in-


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g ghad and that the allocation of a risk to a partyshould be accompanied by motivation for good

management; An open-minded approach to innovative

solutions to problems and a special awareness

of the problems of overseas owners. Regular and, preferably, independent review of

project proposals and conceptual design to

reduce misunderstandings and ensure that thefull spectrum of uncertainties is exposed.


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of the accuracy of a Delphi forecast, it doesrepresent the best forecast available in the form

of a consensus of experts. Delphi has been usedsuccessfully for the formulation of criterion andthe ranking of objectives in some cases and the

method was found appropriate for formulatinggroup judgments in some cases.


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The issues are such that it is preferable to givetime to participants to ponder over the problem

(and over the reactions presented to them insuccessive analysis) before reacting to them.

In many Delphi studies the first round is done


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In many Delphi studies, the first round is doneas an open ended enquiry and questions areunstructured. Based on the response to this,questions are structured and circulated again.The common practice, however is to formulatequestions by researchers. The second method is

adopted here, since issues to be posed to thepanelists were clear.

While designing the questions, the policies to

be tested can be presented and their desirability,impact, and feasibility of occurrence areascertained. Delphi rounds may also include

questions hw reliable the answer is. When this


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(ii) Use a not more than 15% change level to


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( ) grepresent a state of equilibrium. This can bedone with reference to any of the statistics.

(iii) Standard deviation can also be used as ameasure. When the variation in successiverounds reach a level of stability and also when

it is felt that another round is likely to result onlyin a marginal gain as compared to effortsrequired to perform it, (because of declining

participation) the process may be stopped.


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Four questions in this part cover possible switch


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Four questions in this part cover possible switchto public transport due to adoption of certainpolicies on parking and congestion. The otherquestions cover a set of proposals under fourmain groups for eliciting opinion on theirdesirability and feasibility. The subjects covered

are(i) provision of some additional facilities forperforming the journey

(ii) introducing restrictive measures in busyareas;(iii) introduction of new forms of transport and

(iv) methods of financing major transport projects


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A 100 point scale has been used throughout forrecording opinions on policy issues. Rating of 100 the

issues is highly desired and a rating of 0 means theissue is totally not required. In the final analysis thereplies have been grouped in ranges as follows forpurpose of assessing possibility and desirability of the

suggested policies.

0 - 20 Most impossible or Most undesirable21 40 Not possible or Undesirable41 - 60 Possible or Desirable61 - 80 Highly possible or Very desirable81 100 Very highly possible or Most desirable

Panel


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Panel

The panel of experts chosen include middle

level and major senior level educationists whoare dealing with urban and regional transportproblems. They have been selected from

Railways, Highways, Town Planning andTransport departments and educationalinstitutions.

Documents

Risk Identification, Analysis and Allocation