Risk advisers reviewing an illustrative probability, confidence, and sensitivity analysis in a boardroom

Quantitative risk analysis

Quantify uncertainty. Protect confidence.

Quantitative Risk Analysis (QRA), Quantitative Schedule Risk Analysis (QSRA), and Quantitative Cost Risk Analysis (QCRA) for defensible contingency and delivery decisions.

Decision evidence

See the uncertainty. Explain the choice. Govern the response.

A qualitative screen focuses the conversation; QRA, QSRA, and QCRA then use distributions, dependencies, and scenarios to show how cost, time, and confidence can move.

Illustrative five by five probability and impact matrix with example risk markers and decision zones — Illustrative example — synthetic data, not a forecast or project result.

Illustrative qualitative risk screen
Marker	Likelihood	Impact	Decision zone
R01	Likely	Severe	Escalate now
R02	Almost certain	Major	Escalate now
R04	Possible	Moderate	Treat and monitor
R07	Unlikely	Minor	Manage locally

Illustrative QRA, QSRA, and QCRA workflow from baseline through simulation to live controls — Illustrative example — synthetic data, not a forecast or project result.

Illustrative QCRA cumulative cost curves comparing a baseline and mitigation scenario at P50, P80, and P95 — Illustrative example — synthetic data, not a forecast or project result.

Illustrative total outturn cost (USD millions)
Scenario	P50	P80	P95
Baseline	100.0	108.5	116.2
Mitigation	100.8	105.4	111.0

Illustrative QSRA completion confidence curve showing baseline, P50, and P80 markers with milestone view — Illustrative example — synthetic data, not a forecast or project result.

Illustrative completion confidence (months from approval)
View	Completion	Interpretation
Baseline	32 months	Reference plan
P50	34 months	Median modelled outcome
P80	36 months	80% at or below under assumptions

Illustrative tornado sensitivity chart ranking design, procurement, ground, interface, and market drivers — Illustrative example — synthetic data, not a forecast or project result.

Illustrative sensitivity range (USD millions equivalent)
Driver	Favourable	Adverse
Design maturity	−5.4	+7.8
Procurement lead time	−3.6	+5.9
Ground conditions	−2.9	+4.7
Interface readiness	−2.2	+3.2
Market escalation	−1.4	+2.3

Illustrative executive QRA dashboard connecting cost and schedule confidence to accountable next actions — Illustrative example — synthetic data, not a forecast or project result.

Illustrative executive decision view
Signal	Illustrative value	Decision use
Outturn P50	$108m	Median reference
Outturn P80	$116m	Resilient allowance view
Completion P80	M+36	Schedule confidence
Top driver	Design maturity	Evidence and owner needed

How to read the example

P80 means the modelled value is at or below the threshold in 80% of simulations under the stated assumptions. It is not a guarantee, and the chosen percentile should reflect the decision-maker's risk appetite. Sensitivity ranks influence; it does not remove uncertainty. Every live model should record scope, distributions, correlations, iterations, assumptions, and refresh date.

Quantitative risk analysis

Quantify uncertainty. Protect confidence.

Sponsors, investment committees, programme leaders, lenders, and delivery partners who need uncertainty translated into cost, time, contingency, and confidence ranges.

We start with the decision and work backwards to the evidence, the people, and the controls required to make it defensible. The scope is proportionate to the consequence and designed to remain useful after the engagement.

Common triggers

The baseline is mature enough for a probabilistic view
Contingency or completion confidence is being challenged
A funding, investment, or recovery gate needs quantified scenarios
Cost, schedule, and risk teams are using different assumptions

Where we help

Model scope, assumptions, risk events, opportunities, and dependencies
QRA for integrated cost and schedule exposure
QSRA for completion dates, milestones, and float confidence
QCRA for estimate, contingency, and outturn confidence
Sensitivity, correlation, scenario, and decision-threshold analysis
Executive briefing that explains ranges, drivers, and actions in plain language

Advice should leave a decision behind.

We make assumptions, dependencies, owners, and next actions visible so the work can move into governance and delivery.

What changes

A stronger view of the next move.

The output is not activity for its own sake. It is greater confidence in what to protect, what to challenge, and what to do next.

A transparent basis for contingency and confidence decisions

Visibility of the few drivers that matter most

Scenarios leaders can compare before committing capital or recovery action

A model and narrative that can be refreshed as evidence changes

Frequently asked questions

A clear start to the conversation.

These answers describe how we typically begin. The right scope depends on the decision and context.

What does a typical engagement include?

We agree the decision, evidence, scope, outputs, and governance route at the outset. The work may be a focused review, a workshop-led assessment, or support through an active decision gate.

How quickly can you help?

Timing depends on the decision and the evidence available. Use the contact form to describe the urgency and we will respond with a proportionate next step.

Will the work replace our existing advisers?

Usually not. We work alongside existing teams and advisers, adding an independent view where the decision, record, or accountability needs greater clarity.

Related capabilities

Connected support when the situation crosses disciplines.

Complex decisions rarely stay inside one service line.

Related sectors

Context that sharpens the question.

Sector experience helps us recognise the interfaces and promises around the decision.

Start with the decision

Bring us the question behind the request.

Share the context, timing, and consequence. We will respond with a proportionate next step.

Open the contact form