Uncertainty, Risk, Value and Life-Cycle Costing

Introduction

Quantity surveying is not limited to measuring work and multiplying quantities by rates. Construction decisions are made before all relevant information is known, and costs continue long after practical completion. Ground conditions may differ from the site investigation, prices may rise, design requirements may change, maintenance may be greater than expected, and an apparently inexpensive solution may impose high energy or replacement costs. A competent quantity surveyor therefore supports decisions under uncertainty, rather than presenting a single estimate as though it were certain.

This chapter develops four connected capabilities:

• identifying and allocating uncertainty and risk;
• analysing how changes in assumptions affect cost;
• comparing alternatives using value engineering and whole-life costing; and
• communicating financial consequences for informed project decisions.

The emphasis is on disciplined judgement. Mathematical models support professional reasoning, but they do not replace reliable data, appropriate allowances, contractual analysis or consultation with designers, contractors, clients and facility managers.

Learning objectives

By the end of this chapter, a student should be able to:

1. distinguish uncertainty, risk, contingency, allowance and escalation;
2. prepare a qualitative and quantitative risk assessment;
3. use sensitivity analysis, scenario analysis and expected monetary value;
4. explain probability distributions and Monte Carlo simulation in estimating;
5. apply value engineering without reducing required performance;
6. calculate and interpret discounted life-cycle costs;
7. compare options using equivalent annual cost and benefit–cost reasoning; and
8. identify ethical, contractual and governance requirements in cost advice.

1. Uncertainty and risk in construction estimating

1.1 Meaning of uncertainty

Uncertainty exists when the future state of a project, or the value of a variable, is not known with confidence. Examples include the final quantity of rock excavation, the date of a planning approval, future interest rates and the service life of a roof membrane.

Risk is commonly treated as an uncertain event or condition that may affect project objectives. Its effect may be a threat or an opportunity. For example, unexpected contamination is a threat, whereas an early bulk purchase at a favourable price may be an opportunity. In professional risk management, risk is not simply “something that may cost more”; it includes probability, consequence, ownership, response and residual exposure.

A useful distinction is:

• Known cost: sufficiently defined and included in the base estimate.
• Allowance: a provisional amount for an incompletely designed or uncertain item.
• Contingency: an amount or reserve for identified or unidentified uncertainty, depending on the organisation’s policy.
• Escalation: change in prices over time caused by inflation, market movement, exchange rates or resource scarcity.
• Risk allowance: a quantified provision associated with specified risk events or variability.
• Unknown unknown: a condition not reasonably foreseeable at the time of estimating. It cannot be calculated reliably, although organisational reserves and contractual mechanisms may provide resilience.

A contingency is not a substitute for incomplete design, poor measurement or deliberate underpricing. If a risk is already represented in a detailed allowance, adding a second unexamined contingency may double count it.

1.2 Sources of uncertainty

Uncertainty enters estimates through several channels:

The estimator should record the source, estimate basis, confidence level, date, responsible person and required action. This creates an audit trail and allows the estimate to be updated rationally.

2. A framework for risk-informed estimating

A practical risk process has six stages:

1. Establish context: define cost, time, quality, carbon and operational objectives.
2. Identify risks: use workshops, checklists, historical data, site information and design reviews.
3. Analyse risks: assess probability and consequence, first qualitatively and then quantitatively where justified.
4. Plan responses: avoid, reduce, transfer, accept or exploit the risk.
5. Allocate ownership: assign each action and residual risk to an accountable party.
6. Monitor and report: update the risk register as design, procurement and construction information changes.

2.1 Qualitative risk matrix

A risk matrix classifies risks using categories such as low, medium and high probability and impact. It is useful for prioritisation, but it is not a precise probability model. Categories can conceal important differences: a probability of 21% and one of 79% might both be labelled “medium” under a poorly designed matrix. Therefore, a matrix should guide attention, not determine a contingency automatically.

A risk register normally includes:

3. Quantitative methods

3.1 Expected monetary value

For a discrete set of mutually exclusive and collectively exhaustive outcomes, expected monetary value (EMV) is the probability-weighted average:

where pᵢ is the probability of outcome i, Cᵢ is its monetary consequence, and ∑pᵢ = 1. Costs may be represented as positive amounts for expenditure; alternatively, a consistent net-cost convention may be used. The EMV is an average over repeated comparable situations, not a prediction that the project will experience the average outcome.

For a single risk event with probability p and cost impact C:

This is appropriate when probability and impact are reasonably estimated, the event is defined, and the impact is not already included elsewhere. It is less reliable when risks are correlated, probabilities are subjective and uncalibrated, or the event has severe non-financial consequences.

Worked example 1: discrete risk allowance. A project faces three mutually exclusive ground conditions:

• normal excavation: probability 0.60, additional cost $0;
• moderate rock: probability 0.30, additional cost $80,000;
• extensive rock: probability 0.10, additional cost $240,000.

The expected additional cost is:

The $48,000 is a rational expected allowance under the stated assumptions. It does not guarantee adequacy if extensive rock occurs, and a client may choose a larger reserve because affordability and risk tolerance matter.

If an opportunity produces savings, it may be represented as a negative cost. For example, a 40% chance of saving $25,000 has an expected cost effect of −$10,000. Threats and opportunities should be shown separately before being netted, so that an optimistic opportunity does not obscure a serious threat.

3.2 Decision trees

A decision tree represents choices, uncertain events and outcomes in sequence. At a decision node, the decision-maker selects an alternative; at a chance node, nature determines an outcome. Each complete path has a probability and a financial result. The preferred option is not necessarily the one with the highest EMV if the client is risk-averse, has a strict budget ceiling or faces non-monetary consequences.

3.3 Range estimating and three-point estimates

When a quantity or cost is uncertain, an estimator may define an optimistic (a), most likely (m) and pessimistic (b) estimate. A commonly used triangular expected value is:

This treats all values within the range according to a triangular distribution with mode m. A different approximation, often associated with the beta-PERT approach, is:

The PERT approximation gives greater weight to the most likely value. Both are modelling conventions, not laws of nature. They should be used only when a, m and b have a defensible meaning and the estimate is not being presented as statistically measured data.

For a triangular distribution, the range must satisfy a ≤ m ≤ b. The spread indicates uncertainty, but the mean alone does not communicate the risk of exceeding the budget.

3.4 Monte Carlo simulation

Monte Carlo simulation repeatedly samples uncertain input variables from specified probability distributions and calculates the resulting project cost. If the simulation is repeated N times and produces total costs T₁, T₂, …, Tₙ, the simulated mean is:

Percentiles are often more useful than the mean. A P80 cost is the value that 80% of simulated outcomes do not exceed, subject to the quality of the model and interpretation of the percentile. Simulation requires explicit assumptions about distributions, correlations and the relationship between variables. False precision can arise when uncertain inputs are assigned detailed distributions without evidence.

Correlation is particularly important. Steel price and project escalation may move together; excavation quantity and disposal cost may be linked. Treating correlated variables as independent can understate or overstate the range of total cost. Simulation outputs should therefore include assumptions, sensitivity rankings, number of iterations, correlation treatment and model validation.

4. Sensitivity and scenario analysis

4.1 Sensitivity analysis

Sensitivity analysis changes one input, or a controlled group of inputs, while holding others constant to observe the effect on the output. For a cost estimate C and input x, a simple local sensitivity ratio is:

where ∆ denotes a change from the base case. If the unit of x differs from the unit of C, the ratio must be interpreted with those units; it is not automatically a dimensionless percentage.

A percentage sensitivity can be expressed as:

This is useful for comparing variables measured in different units, provided the changes are defined consistently and the relationship is reasonably local. Sensitivity analysis identifies influential assumptions; it does not assign probabilities.

Worked example 2: sensitivity of a concrete package. A package is estimated at 1,200 m³ of concrete at $180/m³ and reinforcement at 150 tonnes at $1,050/tonne. The base package cost is:

If concrete quantity increases by 10%, the additional cost is:

If reinforcement price increases by 10%, the additional cost is:

Under these separate changes, concrete quantity is the more influential assumption. This conclusion applies only to the stated package and changes; interaction effects may exist.

4.2 Scenario analysis

Scenario analysis changes several related assumptions coherently. For example:

• Base scenario: approved design, normal productivity and current market rates;
• Upside scenario: early procurement, favourable ground and stable supply;
• Downside scenario: delayed approval, poor ground and high escalation.

Scenarios are not probability forecasts unless probabilities are explicitly assigned. Their principal value is strategic: they reveal whether a decision remains acceptable under plausible conditions. A scenario should state its assumptions, time horizon, cost boundary and decision implications.

5. Contingency, escalation and estimate maturity

Contingency should be linked to the stage and quality of information. Early concept estimates may require broader ranges because quantities, design and procurement strategy are immature. As design develops, unknown scope should reduce, although new technical risks may be discovered.

A robust estimate separates:

1. base cost for defined scope;
2. design development allowance;
3. identified risk allowance;
4. market or price escalation;
5. client change reserve; and
6. management reserve, where governance permits.

The categories must not overlap. Escalation is time-dependent. If a current price P₀ is expected to increase at annual rate i for t years, compounded escalation is:

where i is expressed as a decimal and t is measured in years. This assumes a constant annual rate and compounding. If different rates apply in different periods, the general form is:

where iₖ is the rate for period k. Escalation should be applied to the relevant cost components and dates, not indiscriminately to a total that includes fixed or already-escalated items.

Worked example 3: escalation. A façade package costs $500,000 at the estimate base date. It is expected to be procured in 18 months, with annual escalation of 4%. Assuming annual compounding:

The result is an estimate, not a guaranteed market price. A supplier quotation, contract index and procurement timing may provide better evidence.

6. Value engineering and value management

6.1 Meaning of value

Value is commonly understood as the relationship between required function and resources used. A simplified expression is:

This ratio is conceptual rather than a complete decision rule. Function includes performance, capacity, safety, quality, appearance, durability, maintainability and compliance. Cost may mean initial cost or whole-life cost. A cheaper component is not better value if it fails required performance or creates excessive operating costs.

Value engineering is a structured, multidisciplinary process applied particularly during design development and procurement. It seeks to achieve required functions at optimum total cost. It is not merely cost cutting, post-award substitution or reduction of quality without functional analysis.

6.2 Functional analysis

The team identifies what an element must do, normally using an active verb and measurable noun, such as “control heat gain,” “support occupancy load” or “convey stormwater.” Functions are classified as basic, secondary, required, desirable or unnecessary. Alternatives are then generated and evaluated against cost, risk, programme, carbon, safety and stakeholder requirements.

A typical value study follows:

1. information phase;
2. function-analysis phase;
3. creative phase, generating alternatives without premature judgement;
4. evaluation phase;
5. development phase, testing selected proposals; and
6. presentation and implementation phase.

The quantity surveyor contributes cost plans, life-cycle calculations, market intelligence, risk analysis and commercial consequences. The designer and specialist suppliers test technical feasibility; the client confirms priorities.

6.3 Value engineering safeguards

A proposal should not be accepted solely because it reduces capital cost. It should demonstrate:

• compliance with codes, standards, planning and fire requirements;
• equal or acceptable functional performance;
• acceptable durability and maintainability;
• no unacceptable health, safety or accessibility consequence;
• realistic supply-chain capacity and warranties;
• impact on programme, interfaces and commissioning;
• whole-life cost and environmental implications; and
• clear responsibility for design and performance.

Ethically, the surveyor must disclose assumptions and avoid presenting a low-cost alternative as equivalent when evidence is incomplete.

7. Whole-life and life-cycle costing

7.1 Scope

Life-cycle costing evaluates costs over a defined analysis period, not only the initial construction price. Depending on the client’s purpose, it may include land-related costs, design, construction, energy, water, cleaning, planned maintenance, repairs, replacement, operation, residual value, demolition and disposal. The boundary must be declared because “whole-life cost” is not identical in every organisation.

Environmental life-cycle assessment and whole-life carbon are related but distinct. A cost model may include energy expenditure without measuring embodied carbon, while a carbon assessment may include impacts that have no direct monetary price. The two analyses can inform one another but should not be conflated.

7.2 Discounted cash flow

Money paid or received at different times is not directly comparable. Present value discounts future cash flows to a base date. For a future cost Cₜ occurring at time t, with constant annual discount rate r:

For several costs:

Here C₀ is the cost at the base date, Cₜ is the cost in period t, r is the discount rate per period, and NPV is the net present value of costs under the chosen sign convention. If costs are entered as positive outflows, the expression gives present cost; if benefits and costs are mixed, signs must be stated.

The discount rate must be consistent with the price basis. A nominal cash-flow model includes expected inflation and uses a nominal discount rate. A real-price model excludes general inflation and uses a real discount rate. The approximate Fisher relationship is:

where rₙ is the nominal rate, rᵣ is the real rate and i is general inflation. Mixing nominal costs with a real discount rate produces distorted results.

If a residual value R is expected at the end of period n, it is normally treated as a benefit or negative cost:

A finite analysis period does not necessarily equal the physical life of the asset. The selected period should reflect client policy, investment horizon, expected occupancy, component replacement cycles and uncertainty.

7.3 Equivalent annual cost

When options have different service lives, comparing their present values alone may be misleading. The equivalent annual cost (EAC) converts a present value into a uniform annual amount over n periods:

The capital-recovery factor in brackets assumes a constant annual discount rate, end-of-period payments and a zero residual value unless residual value has already been included in PV. If residual value is not included, it must be incorporated before applying the factor.

Worked example 4: life-cycle comparison. Two roof systems are considered over a 20-year period at a real discount rate of 3%.

• System A: initial cost $300,000; annual maintenance $8,000; replacement cost $120,000 in year 15.
• System B: initial cost $360,000; annual maintenance $4,000; replacement cost $60,000 in year 15.

The present value of a uniform annual cost A for n years is:

For System A, the annuity factor for 20 years at 3% is approximately 14.877. Thus:

For System B:

System B has the lower present life-cycle cost by approximately $37,838, despite its $60,000 higher initial cost. This conclusion depends on maintenance, replacement timing, discount rate and service-performance assumptions. If the alternatives have equal service lives and satisfy the same functional requirements, present-value comparison is generally direct. If service lives differ, EAC or a common analysis period is preferable.

7.4 Uncertainty in life-cycle costing

Operating and maintenance costs are often more uncertain than initial construction cost. Good practice includes sensitivity tests for:

• energy price and consumption;
• occupancy and operating hours;
• component life and replacement date;
• discount rate;
• maintenance frequency;
• residual value; and
• performance degradation.

A low discount rate increases the present importance of distant costs; a high rate reduces it. Selecting a discount rate solely to make a preferred option appear attractive is improper. The rate should follow the client’s policy, funding context and stated economic assumptions.

8. Option appraisal and decision quality

An option appraisal combines cost with performance and risk. A decision table may include capital cost, present life-cycle cost, programme, safety, carbon, flexibility, resilience and confidence in the evidence. Weighted scoring can support discussion, but weights are value judgements and should be agreed transparently.

A basic benefit–cost ratio is:

Benefits and costs must use the same base date, discount rate, analysis boundary and price basis. A BCR greater than 1 indicates benefits exceed costs under the model, but it does not automatically identify the best option where budgets, distributional effects, risk or statutory duties matter.

The decision-maker should distinguish:

• robustness: performs acceptably across scenarios;
• flexibility: allows later adaptation when information improves;
• reversibility: can be changed without excessive sunk cost; and
• value of information: whether obtaining better information is worth its cost.

For example, additional geotechnical investigation may reduce uncertainty enough to avoid a major contingency or redesign. The investigation should be assessed as an information investment, not merely an overhead.

9. Applied case: illustrative municipal library project

Background

A municipality is planning a 4,000 m² library. The client must choose between two façade systems before the design is frozen. System X has lower initial cost but greater maintenance exposure. System Y costs more initially and has better thermal performance, but the energy saving is uncertain. The analysis period is 25 years, and all amounts are stated in real prices.

Problem

The project team initially recommends System X because it reduces the capital budget by $180,000. The client asks whether that recommendation remains valid when maintenance, energy and replacement are included.

Analysis

The quantity surveyor establishes the following assumptions:

The team checks that both systems meet fire, structural, weatherproofing and acoustic requirements. Energy estimates are reviewed by the building-services engineer rather than accepted solely from a supplier.

Using an annuity factor of approximately 17.413 for 25 years at 3%, the present value of annual costs is estimated as follows:

To avoid overstating precision, the project team calculates the second value carefully:

Thus, System Y has an estimated present-cost advantage of about $349,203. The initial premium is recovered in the model through lower energy, maintenance and replacement costs.

Scenario testing

The team then tests a downside scenario in which the energy saving is only half the predicted amount. System Y’s annual energy cost becomes $89,000 rather than $82,000. The increase in present cost is approximately:

System Y still has a lower estimated present cost, although the margin is reduced. The team also tests a higher discount rate and a delayed replacement. The ranking remains unchanged, but confidence in the energy prediction is lower than confidence in the quoted capital prices.

Approach and outcome

The client selects System Y, subject to performance-based specifications, a mock-up, commissioning requirements and post-occupancy energy monitoring. The risk register records uncertainty in energy performance and assigns it to the design-and-services team. The procurement documents identify warranties, maintenance access and replacement compatibility.

Learning points

1. Initial cost and life-cycle cost answer different questions.
2. A value-engineering proposal must preserve required function.
3. Sensitivity testing identifies assumptions that deserve verification.
4. A model is more credible when its boundary, price basis and discount rate are explicit.
5. Performance obligations and monitoring can convert an uncertain benefit into an accountable commitment.

10. Professional, ethical and technological considerations

Risk and cost advice influences public expenditure, safety and commercial fairness. A surveyor should not manipulate contingencies to meet an arbitrary budget, hide uncertainty through excessive decimal places, or present a supplier’s unverified claim as an established saving. Estimates should identify exclusions, assumptions, data dates and confidence levels. Conflicts of interest, confidential quotations and commercially sensitive risk information require proper governance.

Contract strategy affects risk allocation. A risk should generally be allocated to the party best able to control, price or insure it. Transferring every risk to a contractor does not eliminate it; it may increase tender premiums, disputes or contractor insolvency risk. Contract provisions for provisional sums, fluctuation, latent conditions, design responsibility, insurance and changes should be consistent with the estimate.

Digital estimating, BIM quantity extraction, cost databases and AI-assisted forecasting can improve speed and pattern recognition. They do not guarantee accuracy. Automated quantities may inherit modelling errors; historical data may contain hidden bias; AI-generated rates may lack local market context; and confidential project data may be exposed through unsuitable platforms. Human review, source traceability, version control and validation against measured work remain essential.

Best-practice checklist

Before issuing an uncertainty or option report, the surveyor should confirm that:

• the estimate base date and price basis are stated;
• scope, exclusions and measurement rules are documented;
• risks are separated from design allowances and escalation;
• probability and impact assumptions have an identified source;
• double counting has been checked;
• dependencies and correlations are considered;
• scenarios are coherent and decision-relevant;
• life-cycle boundaries and analysis period are stated;
• the discount rate is appropriate and consistent with inflation treatment;
• technical equivalence has been verified for value proposals;
• non-financial consequences are visible; and
• recommendations are accompanied by sensitivity, confidence and action requirements.

Chapter Summary

Construction cost advice is necessarily conditional because scope, quantities, prices, time and performance are uncertain. Risk management begins with clear risk statements and proceeds through identification, analysis, response, ownership and monitoring. Contingencies should be structured and transparent rather than used to conceal poor definition.

Expected monetary value provides probability-weighted reasoning for discrete outcomes, while three-point estimates and Monte Carlo simulation represent ranges and combined uncertainty. Sensitivity analysis shows which assumptions influence the result; scenario analysis tests coherent combinations of assumptions. Neither method removes uncertainty, and both require defensible inputs.

Value engineering seeks required function at optimum cost and must not be confused with indiscriminate cost cutting. Whole-life costing compares initial, operating, maintenance, replacement and end-of-life costs on a common time basis. Present value, net present value and equivalent annual cost enable options with different payment patterns or lives to be compared. Results depend on the analysis boundary, discount rate, price basis, performance assumptions and risk tolerance.

Professional decisions should therefore combine quantitative analysis with technical verification, stakeholder priorities, contractual understanding, ethical disclosure and governance. The strongest recommendation is usually not the cheapest initial option, but the option whose performance, risk and cost remain acceptable across credible future conditions.

Key Terms

Uncertainty: Lack of complete knowledge about future conditions or variable values.

Risk: An uncertain event or condition that can affect project objectives.

Contingency: A provision for specified or unspecified uncertainty, subject to defined policy.

Allowance: A provisional amount for an incompletely defined item.

Escalation: Increase in prices over time.

Risk register: Structured record of risks, consequences, responses, owners and status.

Expected monetary value: Probability-weighted average monetary outcome.

Decision tree: Model showing decisions, chance events, probabilities and outcomes.

Sensitivity analysis: Examination of output change caused by changing input assumptions.

Scenario analysis: Evaluation of coherent alternative future conditions.

Monte Carlo simulation: Repeated random sampling used to estimate a distribution of outcomes.

Correlation: Statistical association between uncertain variables.

Value engineering: Structured search for required function at optimum total cost.

Function analysis: Identification and evaluation of what a system or component must do.

Life-cycle cost: Cost incurred across defined stages of an asset’s life.

Present value: Value at a base date of a future cash flow after discounting.

Discount rate: Rate used to convert future cash flows to present value.

Equivalent annual cost: Uniform annual amount equivalent to a present value.

Residual value: Value remaining or recovered at the end of the analysis period.

Risk allocation: Assignment of responsibility for managing and bearing risk.

Review Questions

Short Answer Questions

1. Distinguish between an allowance, contingency and escalation.
2. What is the principal difference between sensitivity analysis and scenario analysis?
3. State the expected monetary value formula and define its variables.
4. Why must nominal cash flows be paired with a nominal discount rate?
5. Explain why value engineering is not simply cost cutting.

Long Answer Questions

1. Describe a complete risk-management process for a major building project and explain the role of the quantity surveyor at each stage.
2. Explain how Monte Carlo simulation can be used in cost estimating, including the importance of input distributions, correlations and percentile outputs.
3. Discuss the advantages and limitations of using contingencies in early-stage cost plans.
4. Explain the principles and stages of a value-engineering study, including technical, commercial and ethical safeguards.
5. Compare present-value analysis and equivalent annual cost for options with different service lives.

Analytical / Application Questions

1. A project has a 25% probability of a $160,000 delay cost and a 10% probability of a $400,000 ground-treatment cost. Assuming the events are separately defined and no overlap exists, calculate the combined expected risk cost and identify one limitation of this calculation.
2. Two plant alternatives have different initial, maintenance and replacement costs. Develop a 20-year life-cycle cost model, state an appropriate discount-rate and price-basis assumption, and identify at least three sensitivity tests that should accompany the recommendation.
3. A contractor proposes replacing a specified façade system with a cheaper product. Prepare a value-engineering appraisal framework that tests functional equivalence, life-cycle cost, risk allocation, programme, warranties, carbon and stakeholder acceptance.

Multiple Choice Questions with Answers

Question 1

A project risk has a probability of 0.25 and a cost consequence of $160,000. What is its expected monetary value?

A. $40,000

B. $160,000

C. $640,000

D. $25,000

Correct Answer: A. $40,000

Question 2

Which method changes one input while holding other assumptions constant to identify its influence on an estimate?

A. Scenario analysis

B. Sensitivity analysis

C. Value engineering

D. Risk transfer

Correct Answer: B. Sensitivity analysis

Question 3

Using the PERT approximation, what is the expected value when a = 80, m = 100 and b = 140?

A. 100

B. 103.3

C. 106.7

D. 120

Correct Answer: C. 106.7

Question 4

Which statement about a contingency is most accurate?

A. It guarantees that the final cost will not exceed the budget.

B. It should replace incomplete measurement and design development.

C. It is a transparent provision for defined uncertainty under an organisational policy.

D. It is identical to price escalation.

Correct Answer: C. It is a transparent provision for defined uncertainty under an organisational policy.

Question 5

A future cost C occurring in year t at discount rate r has present value equal to which expression?

A. C × (1 + r)ᵗ

B. C ÷ (1 + r)ᵗ

C. C ÷ (1 − r)ᵗ

D. C × r × t

Correct Answer: B. C ÷ (1 + r)ᵗ

Question 6

Why is equivalent annual cost useful?

A. It eliminates all uncertainty from an estimate.

B. It converts a present value into a comparable uniform annual amount.

C. It measures only initial construction cost.

D. It applies inflation automatically.

Correct Answer: B. It converts a present value into a comparable uniform annual amount.

Question 7

Which action is most consistent with value engineering?

A. Deleting safety systems to meet a budget.

B. Selecting the lowest tender without checking performance.

C. Analysing required function and developing alternatives that preserve performance.

D. Adding an unpriced design change after contract award.

Correct Answer: C. Analysing required function and developing alternatives that preserve performance.

Question 8

In a Monte Carlo cost model, a P80 result generally represents the cost level that:

A. 80% of simulated outcomes do not exceed, subject to model assumptions.

B. is exactly 80% higher than the mean.

C. must occur in every project.

D. has an 80% profit margin.

Correct Answer: A. 80% of simulated outcomes do not exceed, subject to model assumptions.

Question 9

A nominal cash-flow model should normally use which discount rate?

A. A real discount rate with no inflation adjustment

B. A nominal discount rate consistent with included inflation

C. A zero discount rate in all cases

D. The contractor’s markup percentage

Correct Answer: B. A nominal discount rate consistent with included inflation

Question 10

Which practice most directly reduces the risk of double counting in an estimate?

A. Applying one large percentage contingency to every cost item

B. Separating base cost, allowances, identified risks and escalation with defined boundaries

C. Ignoring risks already identified in the design

D. Using more decimal places in the estimate

Correct Answer: B. Separating base cost, allowances, identified risks and escalation with defined boundaries