PMI-RMP® Authorised Instructor  ·  25+ Years Experience

PLAN FOR
UNCERTAINTY.
MASTER RISK.
DELIVER PROJECTS
ON TIME.
ON BUDGET.

Quantitative risk analysis, Monte Carlo simulation, and AI-integrated decision making — for project teams that need to make the right call under pressure.

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25+
Years in
risk analysis
3k+
Professionals
trained
5+
Industry
sectors
2
Books
published
P80
Is your project budget at the right confidence level?
PMI-RMP
Authorised PMI Trainer — exam prep and professional practice
AI + QRA
Combining AI with quantitative risk analysis for better decisions
25+
Years Experience
3,000+
Professionals Trained
2
Books Published
5+
Industry Sectors
Organisations we have worked with
Repsol
Volvo
Wärtsilä
SMBC
Técnicas Reunidas
OHL
Lundin Energy
Moeve
SABIC
Stedin
Ramboll
Cinven
Orange
Lesieur
CUNEF
La Salle
Repsol
Volvo
Wärtsilä
SMBC
Técnicas Reunidas
OHL
Lundin Energy
Moeve
SABIC
Stedin
Ramboll
Cinven
Orange
Lesieur
CUNEF
La Salle
What we offer

Four ways to work with us

Training
Training
Practical Risk Management Programmes
2-day instructor-led workshops, live webinars, and tailored on-site training sessions. From PMI-RMP exam prep to advanced Project Risk Management and Monte Carlo models with AI.
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Consulting
Consulting
Quantitative Risk Consulting
Probabilistic cost and schedule models, Decision and NPV analysis, portfolio risk evaluation. Working models your team can build and update to improve decision making.
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Webinars
Webinars
Live Online Sessions
4-hour live webinars on risk identification, Monte Carlo simulation, and using AI in the project risk process. Hands-on sessions with practical exercises from the first minute. Date to be confirmed.
Register Interest →
AVAILABLE NOW
INTELIGENCIA ARTIFICIAL
Y ANÁLISIS DE RIESGOS
Marcombo · 2026 · 296 pages
+ Taylor & Francis English edition forthcoming
Books
Published Works
Spanish edition available now from Marcombo. English edition forthcoming from Taylor & Francis 2026. Includes Monte Carlo templates, AI prompt library, and video explanations.
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The problem

WHY RISK MANAGEMENT IN PROJECTS KEEPS FAILING

01
Single-point estimates disguised as plans
Most project budgets and durations are presented as fixed numbers. They are not — they are guesses. Without probabilistic analysis you are not managing risk, you are ignoring it.
02
Risk registers that nobody reads
A list of risks with colour-coded heat maps is not a risk management system. It is a compliance document. It does not tell you what to do or what the financial exposure actually is.
03
Cognitive bias in every estimate
Optimism bias, anchoring, and the planning fallacy are embedded in every expert estimate. Without structured estimation and expert calibration techniques, your numbers could be systematically wrong.
04
Analysis that never reaches the decision maker
Risk reports are produced and filed away. Meanwhile, executives make decisions based on intuition or assumptions. The problem is not a lack of analysis — it is the gap between analysis and decisions. That gap is where projects lose money.
Manuel Carmona
PMI-RMP Authorised Instructor AI Expert Certificate
About

MANUEL
CARMONA

MBA · PMI-RMP® · Senior Risk Consultant · Published Author

Manuel is a specialist in quantitative risk analysis and decision modelling with over 25 years of experience across energy, construction, utilities, and technology sectors worldwide.

He helps project teams integrate probabilistic methods and AI into cost estimation, scheduling, and strategic planning — enabling smarter, data-driven decisions under uncertainty.

25+ years in quantitative risk analysis across EU, Middle East, and APAC. Former EMEA Consulting Manager at Palisade — risk software specialists. Author of two books on AI and project risk analysis. Trilingual EN / ES / FR.

25+
Years in quantitative risk analysis
3k+
Professionals trained globally
5+
Industry sectors
2
Books published
PMI-RMP® PMI AI Expert MBA Westminster Monte Carlo Decision Analysis English · Spanish · French
Common misconceptions

Four myths that cost projects money

Myth
"We don't have enough data to do quantitative risk analysis."
Reality
You have expert knowledge. Structured elicitation methods convert that knowledge into probability distributions to model uncertainty. You do not need a large dataset to start.
Myth
"Monte Carlo simulation requires specialist software."
Reality
A working DMUU Monte Carlo model can be built in Excel or any AI tool in under two hours. Simulation software is a useful add-on. The methodology is the skill — not the tool.
Myth
"We tried AI — it's too difficult to implement in our projects."
Reality
With the right training and structured prompts, practitioners at every level can use AI models as trusted advisors — reviewing assumptions, challenging estimates, identifying blind spots, and generating clear executive narratives. The barrier is not the technology. It is knowing how to direct it.
Myth
"A 10% contingency covers our risk exposure."
Reality
10% is a convention, not useful unless it is the result of an analysis. Arbitrary contingencies leave organisations systematically underprepared and financially exposed.
STOP GUESSING.
START MODELLING
YOUR PROJECT RISKS.

Every uncertain project deserves a probabilistic model. Let's build one.

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ABOUT YOUR
PROJECT

Whether you need training for your team, a risk model for a complex project, or want to discuss the upcoming webinar — get in touch and we will respond within one business day.

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