ROMAN Consulting Group
Risk Management
A risk register tells you what could go wrong. A quantitative risk analysis helps you understand what it could mean for cost, schedule, and the decision in front of you. ROMAN Consulting Group provides independent qualitative and quantitative risk analysis for capital projects, helping owners make uncertainty visible early, when there's still time to act on it.
What is Risk Management
Independent risk management is the structured identification, prioritization, and quantification of project uncertainty by a party without a stake in the outcome, so risk insight remains balanced and credible rather than shaped by optimism bias. It begins with qualitative risk assessment, identifying risks, describing causes and effects, and prioritizing exposure, and where the decision warrants it, advances into quantitative analysis that translates that exposure into cost and schedule ranges.
Our Approach
Risk Identification — populating a structured risk register with disciplined descriptions, calibration, and clear ownership, beginning as early as FEL-1
Qualitative Prioritization — using a probability-and-impact framework (per AACE RP 62R-11) to determine which risks matter most and require treatment
Mitigation and Residual Risk — applying treatment strategies (per AACE RP 63R-11) and identifying the exposure that remains after mitigation, the correct input for quantitative modeling
Quantitative Modeling — where the decision justifies it, building an integrated cost and schedule risk model (per AACE RP 57R-09) that connects uncertainty, risk events, and shared drivers into probability-based outcomes rather than single-point targets
Decision-Ready Reporting — communicating results as P-level cost and schedule outcomes, confidence ranges, and key drivers, not additional charts for their own sake
Risk reviews are led by AACE-credentialed practitioners using independent facilitation, so the risks that surface are the ones that actually matter, not the ones that are comfortable to discuss internally. Models are scaled to what the project's data and maturity can actually support; a lighter, transparent scenario analysis is often more useful than an overbuilt model presented with false precision.
Built for Teams Facing a Real Decision Under Uncertainty
Owners and project teams approaching a stage-gate, funding approval, or major estimate update. Organizations whose deterministic cost and schedule targets don't reflect the confidence leadership actually needs. Teams that have a risk register but have never tested what it means in dollars or days.
Case Study
A mid-size owner was preparing a funding request built on a single deterministic cost estimate and a single planned completion date, with no stated confidence level for either. ROMAN facilitated an independent qualitative risk assessment, surfacing several schedule-driven cost exposures the internal team had not connected, extended commissioning support costs tied to a permitting risk that, if realized, would also push completion well past the deterministic date. The resulting integrated quantitative model gave the capital committee a P50 and P80 cost and schedule range instead of a single unqualified number, along with the specific drivers behind the spread, allowing the committee to approve funding with an appropriate contingency rather than a number likely to be exceeded.
Frequently Asked Questions
Q. What is the difference between qualitative and quantitative risk assessment?
A. Qualitative risk assessment identifies and prioritizes risks using descriptive probability and impact ratings. Quantitative risk analysis assigns numerical probabilities and cost or schedule impacts to produce contingency and exposure ranges.
Q. When should risk analysis begin on a capital project?
A. Risk analysis should begin as early as FEL-1, feasibility and concept selection, since front-end decisions carry the most influence over final cost and schedule outcomes.
Q. Does every project need a quantitative risk model?
A. No. The right question isn't whether a project is large enough for quantitative analysis, it's whether the decision is important enough and the project basis mature enough for a quantitative view to improve it. Some situations are better served by a focused scenario analysis than a full integrated model.
