Risk cost estimation

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Cost Estimation of Industrial Risk in the Bidding Process

E. Cagno, F. Caron, M. Mancini

Department of Mechanical Engineering

Politecnico di Milano

Abstract. Project cost estimation in the bidding process is a critical concern for the competitiveness and profitability of an engineering and contracting company. Estimates which diverge as little as possible from actual costs have to be made on the basis of relatively limited information. Of the macro-items contributing to the overall cost of a plant project, those linked to engineering activities have been growing continuously in percentage terms for a number of years and have thus become the object of considerable interest. Moreover, since these items are difficult to standardise, estimation is particularly difficult. A method able to produce reliable estimates for these activities could certainly be usefully transferred to other project stages. The methodology proposed to formulate a bid estimate for a HAZOP study envisages the joint use of three tools to produce more accurate estimates and improve the quality of decisions through explicit assessment of the risk of over-estimating (or under-estimating) the cost. First, an analytical estimation model based on improved structuring of available information provides more accurate estimates and facilitates the use of IT applications. Second, company knowledge gained in previous projects is structured and maintained in order to ensure continuous improvement in estimation. This information can be used to improve over time the understanding of the determinant values in the model itself, so obtaining increasingly accurate estimates and probability distributions which take account of historical errors. Finally, a simulation technique provides the probability distribution of the overall cost and thus the confidence interval of the estimates.

Keywords: Cost Estimation, Bidding Process, Safety Engineering, HAZOP.

1. Introduction

Project cost estimation in the bidding process is a critical concern for the competitiveness and profitability of an engineering and contracting company as it involves considerable risk. Indeed, with only the limited information available in the tender documents and the partial results of the basic engineering, an estimate must be drawn up which varies as little as possible from the effectively sustained costs. The reason for this is that the industrial goods market is becoming increasingly competitive and the typical contract is now the lump-sum, in which the contractor agrees to supply at a pre-determined price. Since the starting point for this price is the estimate prepared during the bidding, it is evident that this cost estimate is crucial to the competitiveness and profitability of engineering and contracting companies.

Attention must, therefore, be focused on tools which can improve the quality of bidding decisions, so assessing explicitly a company skill in estimating project costs.

Of the macro-items in the overall cost of a plant project, expenditure linked to engineering activities has for some years been accounting for a growing percentage and, consequently, has attracted considerable attention. The estimate of this expenditure is typically based on the following formula:

Ce = (∑i Coi × Hi) + Cc where:

Ce = overall cost of engineering;

Coi = hourly departmental cost for the ith technical unit; Hi = man-hours required by the ith technical unit;

Cc = commission costs typical of any project (e.g. travel, copies, etc.).

Clearly, the most critical element is the man-hours (Hi), as this is ‘brain-intensive’ work which it is difficult to standardise.

Among engineering activities, safety engineering is particularly significant from the point of view of bid risk, as in addition to being typically systemic and inter-functional, it also involves all areas of the plant (from the process and auxiliary units to the materials handling areas) and is thus subject to considerable initial uncertainty (the lack of qualitative and quantitative information in the tender documents causes great difficulties in estimating this type of activity). Moreover, management of safety engineering is much more innovative than other more consolidated activities (e.g. electrical or civil engineering). In the absence of specific tools, it is difficult to exploit previous experience, meaning that initial estimates may not be reliable.

On the other hand, the increasing severity of industrial safety legislation (at least in developed countries) produces continually greater demand for safety engineering services.

In this light, it is clear that an estimation method able to provide reliable estimates of safety engineering work could also be usefully transferred to other project activities.


2 The HAZOP Study (CIA, 1992; Kletz, 1992; Freeman, 1991; Freeman et al. 1992) is a process analysis procedure which seeks to identify systematically the risks, faults and operational problems which may compromise personal or environmental safety, or plant operation. Moreover, it can also assess the consequences of deviation from standard function and propose corrective actions.

The procedure is based on the generation of a series of questions for submission to a multi-disciplinary team with expertise in the process under examination. To this end, a combination of parameters and guide words is applied to all parts of the plant considered potentially dangerous.

In addition to being particularly demanding from the point of view of the man-hours required, HAZOP studies have strong systemic and multi-disciplinary features typical of plant projects, and can thus be seen as small projects in themselves.

It should also be noted that of the deliverables generated by safety engineering, HAZOP studies are of greatest interest to the client, and the latter often participates directly in the meetings at which the analysis is carried out.

2. Guidelines for the proposed methodology

The methodological approach to the formulation of a bid proposed in the present study envisages the joint use of three tools, the effectiveness of which has been tested in a cost estimate for a real-world project i.e. the design and construction of a chemical plant in a developing country.

1. The first tool is an analytical estimation model which by means of greater structuring of information provides more accurate estimates and facilitates the use of information technology applications. HAZOP is structured in individual, elementary activities at different hierarchical levels so as to identify correctly the various cost drivers, i.e. the parameter which determines the expenditure of time and, therefore, of money (Raz and Elnathan, 1998). It should be noted that the model envisages the use of a series of corrective factors which take account of those aspects specific to a given project (e.g. the client type or the level of innovation) which have a significant impact on the time expended. This provides some ‘measure’ in the estimate of this impact, exploiting to the fullest available information and past experience in order to reduce uncertainty.

2. Second, company know-how gained from previous projects is kept in a structured manner so as to ensure continual improvement in estimation. Starting from the proposed model, two distinct areas in which past experience can be exploited have been identified. The first is continual updating of the general parameters in the estimation model, so that it is progressively calibrated and refined on the basis of company experience. The second concerns the probabilistic aspect of the estimate and involves the definition for each parameter in the model of stochastic distributions based on the percentage deviations seen between estimated and actual values. This is very important in that it means that a probabilistic analysis of the overall cost can be carried out taking account of the company estimation skills.

3. Finally, a simulation technique provides a probability distribution of the overall cost, and the estimate therefore explicitly considers the risk of under-estimating (or over-estimating) the cost, so improving the quality of decisions taken in the bid phase. If the simulation technique is applied to the distributions obtained on the basis of past errors, an aggregated probability distribution of overall cost, and thus of overrun, can be obtained, i.e. the probability that the actual cost is above a certain value. This allows objective allocation of contingences (financial reserves to reduce the risk of overrun to the desired level), while ensuring a competitive bid.

3. Description of the methodology

3.1 An analytical model to estimate the cost of hazop studies

HAZOP studies can be undertaken at various stages in the project life-cycle. Table 1 gives a possible classification. All HAZOP studies with the exception of the pre-start-up type use a relatively codified and substantially similar operational logic, so it is possible to develop specific estimation models from a common base.

In the present study, particular attention is paid to the Main HAZOP, as its greater complexity and breadth make it highly representative of all four types.

Table 2 shows the organisational figures typically involved in a HAZOP study.

Note that the HSE Co-ordinator is part of the team, so the hours attributable to this figure are taken globally without being assigned to individual activities. The estimation model therefore does not include the cost of the HSE Co-ordinator.

The model is based on an Activity Based Costing (ABC) approach applied to the project (Raz and Elnathan, 1998). The HAZOP is structured in individual, elementary activities at different hierarchical levels in order to identify correctly the parameters which determine the necessary man-hours.

To this end, the process is broken down first into phases and then into elementary activities, and an activity breakdown structure is defined. Subsequently, precedence diagrams are used to show the dynamic aspect of the process under examination.


Preparation of the HAZOP. Preparation is necessary before the analysis can start. First, a Team Leader is chosen to act as moderator during the meetings. All necessary documents must also be collected. When the Leader has been chosen, a General Schedule (see figure, ‘General Schedule’) for the HAZOP can be drawn up on the basis of availability. Once part of the necessary project documents have been collected (generally the P&ID), the Leader can begin to prepare the meetings. Careful checking of the documents collected (‘Checking and Updating of Documentation’) is necessary to avoid interruptions (which are expensive because of the number of people involved) when the meetings start.

HAZOP. At this point the HAZOP analysis can start. First, the plant and the study to be conducted are presented. Subsequently, all the plant units1 to be analysed are reviewed, both in terms of the process, and the general plant services. Next the nodes into which the individual units have been sub-divided are addressed. Normally, each node is analysed with reference to normal plant operating conditions. In some cases, there is also analysis in different operating conditions, e.g. start-up, shut-down, maintenance. Recording, i.e. systematic registration on a worksheet of what is done, is carried out in parallel with the analysis. Once a unit has been analysed, the worksheets are passed to team members for comment. Any observations are presented to the Team Leader who together with the Secretary updates the worksheets (shown in the figure as ‘Revision of Worksheets’).

Reporting. When the study of the plant has been concluded, a report must be prepared illustrating the work undertaken and the conclusions reached. This report is prepared by the Team Leader, but it must be reviewed by the safety engineer responsible for the project (Process Safety and Reliability Leader) before submission to the client.

Follow-up. Next the follow-up phase begins, in which the recommendations emerging from the HAZOP must be implemented. It is the job of the HSE Service to ensure that those responsible for the various recommendations provide suitable responses within the deadlines. In particular, the recommendations must be assigned and distributed to the competent engineering service. There is then an expediting stage aimed at those responsible for the recommendations in order to ensure that responses are delivered to the HSE Service within the deadlines. At the same time, the HSE Service must implement the recommendations for which it is responsible. Two types of recommendation are issued during a HAZOP study: simple recommendations which prescribe precise modifications to the project and/or exact checks, and complex recommendations directly involving the HSE Service (‘Management of Complex Recommendations’). Once a response has been received or the service has responded to a recommendation, this must be checked for coherence and recorded in the database (‘Updating of database’ 1, 2, 3). The cycle of expediting, management of recommendations and updating of the database is repeated several times (internal cycle in Figure 1). Periodically, a progress report on follow-up activities must be sent to the client. When all necessary actions have been correctly completed, the final Follow-follow-up Report can be released.

The individual, elementary activities into which the above process is divided are grouped at different hierarchical levels to give a Cost Breakdown Structure, i.e. a disaggregation of the overall cost of the HAZOP study into cost items which are more easily estimated and controlled. This facilitates identification of the most appropriate parameters to estimate the time spent on each individual, elementary activity. There are two types of parameter: cost drivers, which explain consumption of man-hours in standard conditions, and corrective factors, which take account of specific features of a given project.

For the two deliverables in a client report (the HAZOP study and the Follow-up), there are two families of activities with different hierarchical structures (cfr. Figure 2).

The first (HAZOP study) includes the Preparation, Analysis and Reporting phases. Starting from the top, the levels are: - HAZOP, comprising all activities managed at aggregate level in support of the HAZOP study;

- Unit, those activities managed at the plant functional unit level;

- Node, all activities necessary during the application of the HAZOP procedure to individual sections of the plant (typically equipment and lines).

As far as the Follow-up phase is concerned, the levels are based on the recommendations which emerge from the HAZOP study, as the aim of the Follow-up is to ensure that these recommendations are correctly implemented in the project (cfr. Figure 2). There are three levels:

- Follow-up, is the most aggregated level and covers reporting activities concerning the means of implementation of all the recommendations;

- Batch recommendations (for each technical service involved), which include activities associated to groups of recommendations for different engineering services;

- Single recommendations, including all activities dealing with the control of the correct implementation of each recommendation.

For each cost driver in the Cost Breakdown Structure, there is a resources absorption co-efficient under standard conditions, expressed as hours/cost driver unit, e.g. hours/P&ID, hours/node, hours/recommendation (cf. Table 3). In this respect, two observations must be made.

In some cases, these are defined as fractions of other cost drivers (e.g. Nx = w × NR, the proportion, w, of recommendations considered complex).


4 Second, it should be underlined that the expected number of recommendations (NR) is not directly estimated on the basis of the tender documents (as the other cost drivers), but using the following formula (NN = number of nodes weighted by complexity):

NR = [(number of recommendations expected/complex node) kdang × kcli × kqual] × NN

To take account of project uniqueness, corrective factors are introduced which reflect the impact of those parameters which cannot be taken as co-efficients, but where interviews have confirmed an undeniable influence on time expended. Specifically, five factors are used (cfr. Table 4).

The values assigned to each corrective factor in the bid phase is determined by expert judgement (high, medium, low) of the possible variations that a factor may cause in terms of time expended on the activities it influences, bearing in mind the weighting of different factors if more than one is influenced.

For each judgement, a value is assigned to the corrective factor, e.g. if the variation caused by a certain parameter (x) is estimated to be a ±10%, then:

x high ⇒ kx = 1.1 x medium ⇒ kx = 1 x low ⇒ kx = 0.9

In this way, the estimate of the sum of each elementary activity (or in certain cases, an aggregated group of elementary activities similar in terms of cost drivers and corrective factors) is more coherent with the nature of the activity itself. For this purpose, five types of formula are used.

If Hi is the envisaged hours for the ith activity , this gives (cfr. Table 5): 1. Hi = Cj × k1 × k2... × kn (e.g. “Follow-up Report”); 2. Hi = Rj × Nx × k1 × k2... × kn (e.g. “Introduction to nodes”); 3. Hi = [Cj(1), Cj(2), ....Cj(n)], for the different ranger of values of Nx

(e.g. “Collection of Documentation” and “Checking and Updating of Documentation”);

4. Hi = y × Hj (e.g. “HAZOP Procedure operations”); 5. Hi = Cj + RJ × Nx × k1 × k2... × kn (e.g. “Preparation by the Leader”). where:

Cj = constants;

RJ = resource absorption co-efficients in hours/(cost driver unit); Nx = estimated values of the cost driver;

kn = corrective factors taking account of specific features of the project;

y = a constant ratio between the hours necessary to carry out an activity and the hours necessary to carry out a different activity (directly estimated)

A final aspect regards the uncertainties present in any estimate. The main areas of uncertainty responsible for variations in time expended in a HAZOP study are identified (cfr. Table 5 and Table 6).

To obtain the cost of a HAZOP study, the time necessary for the various elementary activities must be multiplied by the number of people involved and their cost/hour. Particular attention should be paid to the time of the Team Leader, who may be an external consultant with a different cost/hour (typically much higher if from abroad). The cost to carry out the study is then the sum of the costs of its elementary activities.

3.2 Structured archiving of company know-how

In the present estimation model, two distinct areas giving opportunities to exploit past experience can be identified. a) The general parameters of the model. First, with the experience gained, the HSE Service specialists must continually update the values for the general parameters in the model. Consequently, the values of constants (Ci), absorption co-efficients (Ri), terms for the various corrective factors (ki), ratios (y), ratios used in calculating cost drivers defined as percentages of NR (s, w, z), and the ‘expected number of recommendations per complex node’ must be reviewed regularly. The proposed procedure envisages re-calculation of averages each time a bid is made. The individual responsible for the bid must carefully define the various input values to the model with the aim of generating a good estimate. These parameters are initialised to values obtained through interviews with HAZOP experts using the Delphi method.


The proposed methodology is chosen in the light of the trade-off between effective estimates and complexity of data processing. The idea is to divide in the various formulae everything which expresses an ‘estimate’ in a true sense (i.e. constants, absorption co-efficients and corrective factors) from costs drivers (number of nodes, expected number of recommendations, number of P&ID) which express information that can be obtained from the tender documents. Taking, for example, the first formula used in the model:

Hi = Ri × Nx × k1 × k2 × ... × kn

The actual values of Hi and Nx are easily obtained. With these values, a new parameter can be obtained which takes account of all those terms which are not contained in the tender documents:

αi = Ri × k1 × k2 × ... × kn

The probability distributions of Nx and αI can be defined on the basis of percentage deviations occurring over time. If, for example, the estimated value of α4 in a given project is 2 hours/node, and the past percentage deviations show a particular probability distribution, the distribution of α4 can be defined as in Table 7, Figure 3 and Figure 4.

3.3 Simulation as a risk analysis technique

From the stochastic distributions based on past error, a deterministic estimate of the probability distribution aggregating the variability of the various elementary activities can be obtained (Vose, 1996).

This gives the cumulative distribution function of the actual cost of the project or one of its phases. Completion of this function results in the so-called overrun probability, defined as:


and understood as the probability that the actual cost will be greater than a given value of c.

Having defined the level of acceptable risk (in terms of overrun probability, it is possible to determine the contingency percentage (financial reserves to cover variability in actual cost) to be included in the bid (cfr. Figure 5).

The overrun curve is obtained by a simulation technique using Monte Carlo sampling of the probability distribution given by past error.

A fundamental aspect of the definition of the simulation model is the correlation between the input variables.

A certain number of correlations emerges as a result of the presence of the same variable in various formulae for the calculation of Hi. This is the case, for example, with the cost driver NP which appears in the expressions for H2 (‘Preparation by the Leader’) and H9 (‘Hazop Leader Report’). The sampled value of NP is therefore used in the formulae for H2 and H9.

Where there is no common cost driver, the correlation between the variables is calculated on the basis of historical values using Spearman’s Rank Order Correlation co-efficient (Mood et al., 1988).

For two casual variables, X an Y, this co-efficient is defined as:



ρ = −





1 2

r (X)

r (Y)


i i n 2 i


where ri(.) are the rankings of the various observations and n is the number of available observations for the pair in question. The ranking is the position of a given figure in an ascending sorted list.

With this Rank Order Correlation, Iman and Conover’s technique (1982) can be used to sample various distributions ‘in a correlated manner’.

The simulation has been applied to a real-world case, so as to demonstrate the effectiveness of the risk analysis in the context of the present methodology.

An overrun curve and contingency percentages for different levels of risk are obtained for the cost of a Main HAZOP in a recently built plant.

4. Conclusions

In explicitly assessing a company estimation skill and the relative risk of error, the proposed methodological approach improves cost estimates of a project or one of its phases and thus the decisions on the bid price.

Of the three tools used, the role of the structured archiving of company information is of particular importance. As has been seen, this helps to refine the values of the parameters used (and thus the accuracy of the estimate) in the model, and to define probability distributions which reflect ‘past skill’ in estimation. These distributions are the input for the simulation.

It should be noted that the accurate inputs are a prerequisite for significant results from the simulation. A well-structured archive is therefore imperative to define the probability distributions used in the simulation, which, in turn, is possible using an ad hoc estimation model.


6 Finally, from a quantitative point of view, the systematic updating with experience of the parameters in the model leads to a progressive reduction in error. This means ‘narrower’ distributions as input to the simulation model which will therefore output a denser distribution of overall cost. A reduction in the variance of the distribution of overall cost represents a considerable benefit, as it means reducing bid risk, i.e. allocating lower contingencies to present more competitive bids.

This is particularly true in the case of HAZOP studies. In the case study, the expected value obtained from the simulation is ITL 122.270.800, 10% above the base cost (ITL 111.057.500) given by the deterministic estimate.

The standard deviation of the distribution of the overall cost is 17.5% of the expected cost, so high contingency percentages must be planned. For example, to reduce the probability of overrun to 30%, a contingency of 18.2% of the base cost must be set (cfr. Table 8).

With regards potential future developments of the methodology presented, it is interesting to extend the approach here applied to HAZOP studies to the estimation of other activities, both in Safety Engineering and, more generally, engineering and management.

First, activities which are difficult to estimate because of their complexity must be identified. These are then structured into elementary sub-activities and set at different hierarchical levels. Finally, through knowledge of the operational process, the most suitable cost drivers and corrective factors to estimate the man-hours needed to carry out each individual activity must be defined.

A second source of future developments concerns the structured archiving of company information. Two directions can be taken in this respect.

The first is a refinement of the logic to exploit experience. This involves, for example, memorising not only the percentage deviations use to define the stochastic distributions, but also other project information (e.g. names of people involved in the project, comments on work carried out, etc.), and providing search engines able to identify analogies with previous projects (e.g. same type of plant, same type of client, etc.).

Second, structured archiving of company information could be more widely used in the bid phase. This involves extending this type of methodology not only to the various engineering and management activities, but also to the estimation of materials, transport and construction costs, taking account of the existing links between the various areas in which knowledge can be acquired.


Caron F. and Cagno E., 1997, “Project Risk Analysis”, CUSL, Milano, Italy.

Chemical Industries Association (CIA) Ltd., 1992, A Guide to Hazards and Operability Studies, CIA, UK. Freeman R. A., 1991, Documentation of Hazards and Operability Studies, Plant/Operation Progress.

Freeman R. A., Lee R. and McNamara T. P., 1992, Plan HAZOP Studies with an Expert System, Chemical Engineering Progress. Iman R. L. and Conover W. J., 1982, A Distribution-free approach to Inducing Rank Order Correlation among Input Variables,

Communication in Statistics, B11, 311-334.

Kletz T., 1992, Identifying and Assessing Process Industry Hazard, Institution of Chemical Engineers. Mood M., Graybill F. A. and Boes D. C., 1988, Introduzione alla statistica, Mc Graw Hill.



HAZOP type

Project life-cycle

phase Main features

Coarse Conceptual


Risks are identified so as to focus project design on plant safety when many technical decisions still have to be taken.

Main End of basic


The aim is to ensure that basic engineering develops a project in which safety criteria are respected. The entire plant is analysed in detail.

Package End of basic engineering

Similar to Main, but for packages provided by vendors.

Final End of detailed engineering

Carried out on designs which must be approved for construction. Focused exclusively on modifications after the Main and Package HAZOPs.

Pre-start-up End of construction Not codified in a standard form. Typically, corresponds to a site analysis to verify that the plant respects safety norms.


8 Function

HSE Coordinator Co-ordinator of the workgroup and responsible for all activities concerning safety and environmental protection.

PSR Leader Responsible for reaching fixed safety engineering objectives during the planning phase.

HAZOP Team Leader Responsible for the management of HAZOP meetings, ensuring that the analysis methodology is correctly applied.

Secretary Takes the minutes of the meetings.


Cost driver Symbols Unit of measurement

Number of P&ID NP Hours/P&ID

Number of units NU Hours/unit

Number of non-repeating nodes NO Hours/ non-repeating node

Number of nodes weighted by complexity

NN Hours/complex node

Expected number of recommendations

NR = [(Expected number of

recommendations/complex node) kdang× kcli× kqual] × NN


Expected number of

recommendations for the HSE Service

z2× NR Hours/HSE Service


Expected number of complex recommendations

w3× NR Hours/ complex

recommendation Expected number of

recommendations leading to changes in technical documentation

s4× NR Hours/ recommendation

leading to changes in technical documentation

Table 3: Cost drivers in the model.


z = ratio between the number of recommendations passed to HSE and the total number of recommendations. 3


10 Corrective



kdang Linked to plant danger , i.e. essentially the toxicity/inflammability of fluids treated, and the general process conditions, typically pressure and temperature.

kcli Corresponds to the client type. A client may place more or less emphasis on the problems of safety and thus on the HAZOP analysis with evident effects on the length of the study.

kinn Concerns the project innovation for the contractor. Clearly, past experience generates skills in terms of ‘good planning’ from a safety point of view. This makes the analysis more rapid and reduces the number of recommendations emerging from the analysis and managed during Follow-up.

kteam The size of the team which as stared in organisation manuals affects the efficiency of meetings.

kqual Refers to the quality of the initial base project. If quality is good (because, for example, the process is covered by a licence and other HAZOP studies have already been carried out), there will probably be few recommendations to follow-up.




“Collection of Documentation” and “Checking and Updating Documentation”

HAZOP H1 = C1 if NP = [0 ÷ 50] H1 = C2 if NP = [50 ÷ 100] H1 = C3 if NP >100

• Estimation errors

• Unforeseen events

“Preparation by the Leader” HAZOP H2 = C4 + R1× NP× kdang • Estimation errors • Unforeseen events

• Experience of the Leader


“Introduction to the plant and the HAZOP study”

HAZOP H3 = C5 • Estimation errors • Unforeseen events

• Experience of the Leader

• Client

“Introduction to unit” UNIT H4= R2× NU× kcli • Estimation errors • Unforeseen events

• Experience of the Leader

• Client

“Revision of worksheets” UNIT H5 = x × H7 • Estimation errors • Unforeseen events

• Experience of the Leader

• Client

• Quality team “Introduction to node” NODE H6 = R3× NO× kcli • Estimation errors

• Unforeseen events

• Experience of the Leader

• Client “Node analysis procedure” and


NODE H7 = R4× NN× kinn× kdang× × kcli× kteam(1)

• Estimation errors

• Unforeseen events

• Experience of the Leader

• Client

• Quality team “HAZOP operations procedure” NODE H8 = y × H7 • Estimation errors

• Unforeseen events

• Experience of the Leader

• Client

• Quality team





“HAZOP Leader report” HAZOP H9 = C6 + R5× NP× kdang× kcli • Estimation errors • Experience of the Leader

• Client “Introduction and verification by

the PSR”

HAZOP H10 = C7 • Estimation errors • Unforeseen events


“Follow-up report” FOLLOW-UP H11 = C8× kcli • Estimation errors • Unforeseen events

• Client “Collection of recommendations

and allocation to different services”


H12 = R6× NR • Estimation errors • Unforeseen events “Expediting” BATCH OF


H13 = C9 • Estimation errors • Unforeseen events

• Follow-up co-ordination “Updating of database and check

of recommendations”


H14 = R7× NR • Estimation errors • Unforeseen events

• Follow-up co-ordination

• Quality of project design


H15 = R8× (z × NR) • Estimation errors • Unforeseen events

• Follow-up co-ordination Management of complex



H16= R9× (w × NR) • Estimation errors • Unforeseen events

• Follow-up co-ordination

• Quality of project design

“Check of modified documentation”


H17= R10× (s × NR) • Estimation errors • Unforeseen events

• Quality of project design


x= constant ratio between H5 and H7

y= constant ratio between H8 and H7

z= ratio between the number of recommendations passed to HSE and the total number of recommendations

w= ratio between the number of complex recommendations and the total number of recommendations

s= ratio between the recommendations leading to changes in technical and the total number of recommendations NP= Number of P&ID

NU= Number of units

NO= Number of non-repeating nodes

NN= Number of nodes weighted by complexity

NR= Expected number of recommendations =[(expected

number or recommendations per complex node)×kdang×kcli×kqual] ×NN

kdang= corrective factor taking account of plant criticality

from a safety point of view

kcli= corrective factor taking account of the Client

kqual= corrective factor taking account of project quality from

a safety point of view

kinn= corrective factor taking account of the level of plant


kteam = corrective factor taking account of team size

Hi= hours required for the ith activity

Ci= time constant (ore) for the ith activity

R1= co-efficient for the “Preparation of the Leader”,

expressed in h/P&ID

R2= co-efficient for the “Introduction to unit” expressed

in h/unit

R3= co-efficient for the “ Introduction to node”,

expressed in h/node

R4= co-efficient for the “Node analysis procedure” and

“Recording” expressed in h/complex node R5= co-efficient for the “ HAZOP report Leader ”

expressed in h/P&ID

R6= co-efficient for the “Collection of recommendations

and allocation to different services”, expressed in h/recommendation

R7= co-efficient for the “Updating of database and check

of recommendations”, expressed in h/ recommendation R8= co-efficient for the “ HSE actions” expressed in h/


R9= co-efficient for the “Management of complex

recommendations” expressed in h/ recommendation R10= co-efficient for the “Check of modified

documentation” expressed in h/ recommendation


Sources of variability Comments

Experience and personality of the Leader

Influences the depth of the analysis.

Client Influences the entire study in function of sensitivity to safety. Quality team Influences the time to carry out the analysis.

Co-ordination of Follow-up Determines the speed of Follow-up.

Quality of project design Influences the number of recommendations produced. Unforeseen events Slow-downs and brief interruptions.

Estimation errors Concerns estimation errors in input values.

Unit costs of external Leader Impacts on all activities in which the Leader takes part.


14 ∆∆∆∆αααα4 /αααα4

Historical data

Probability ∆∆∆∆αααα4


From To From To

-50% -30% 0.05 1.0 1.4

-30% -10% 0.15 1.4 1.8

-10% 10% 0.45 1.8 2.2

10% 30% 0.30 2.2 2.6

30% 50% 0.05 2.6 3.0


Probability of overrun

Contingency (% of base cost)

Contingency (in absolute terms)

Coherent value of base cost

5 43,2 47.929.500 158.987.000

10 34,3 38.053.100 149.110.600

15 28,7 31.854400 142.911.900

20 25.5 28.365.600 139.423.100

25 21,1 23.485.300 134.542.800

30 18,2 20.183.100 131.240.600

35 15,5 17.190.200 128.247.700

40 13,1 14.549.400 125.606.900

45 11,0 12.265.700 123.323.200

50 8,9 9.948.900 121.006.400

55 6,9 7.747.000 118.804.500

60 5,0 5.555.400 116.612.900

65 2,9 3.237.900 114.295.400

70 0.08 925.600 111.983.100

75 - - 109.184.800




Selection of Leader

Collection of Documentation

Preparation by Leader


Checking and Updating of Documentation General




Introduction to the plant and the HAZOP Study

Intro-duction to the unit

Intro-duction to the node HAZOP node analysis procedure HAZOP operations procedure Recording Revision of worksheets 1 2 Iterations Iterations



HAZOP Leader report Introduction and Check by the PSR



Collection and allocation of recommend-ations to the various services Expediting Management of complex recommend-ations Updating of database and check of recommendations (2)

Follow-up report

Action by Safety Service

Check of modified- Document-ation

Updating of database and check of recommendations

(3) Updating of database and check of

recommendations (1) E







Collection of documentation

Checking and updating of documentation

Preparation of Leader

Introduction to the plant and HAZOP study

Leader HAZOP report

Introduction and verification by the PSR


Introduction to the unit

Revision of worksheets UNIT Level'

Introduction to nodes

Node analysis procedure

HAZOP operations procedure

Recording NODE Level



Report Follow-up FOLLOW-UP Level

Collection of recommendations and allocation to different services


Safety Service actions

Management of complex recommendations

Updating of database and check of recommendations

Check of modified documentation SINGLE RECOMMENDATION Level




18 0

0,1 0,2 0,3 0,4 0,5

Percentage error



-50 -10 10 30 50


0 0,1 0,2 0,3 0,4 0,5



1 1.8 2 . 2 2 . 6 3

Figure 4: Probability distribution on the basis of past deviations.