Monte Carlo Simulation Calculator
Advanced project risk analysis using probabilistic modeling and simulation
Understanding Monte Carlo Simulation
Monte Carlo simulation is a computational technique that uses random sampling to model uncertainty and assess project risks. By running thousands of iterations with different scenarios, it provides probabilistic insights into project outcomes.
📊 Probability Analysis
Calculate the probability of meeting deadlines and staying within budget
🎯 Risk Assessment
Identify high-risk areas and quantify potential cost/schedule overruns
âš¡ Decision Support
Make data-driven decisions with confidence intervals and sensitivity analysis
Project Configuration
Task 1
Ready for Simulation
Configure your project tasks and constraints, then run the Monte Carlo simulation
Advanced Monte Carlo Concepts
📈 Distribution Types
Triangular Distribution
Uses optimistic, most likely, and pessimistic estimates. Simple and intuitive for most project scenarios.
Beta Distribution (PERT)
More realistic shape that accounts for skewness. Used in PERT analysis for better accuracy.
Normal Distribution
Symmetric bell curve. Useful when outcomes cluster around a mean value with predictable variance.
🎯 Advanced Features
Correlation Analysis
Model relationships between tasks when risks are correlated, providing more realistic simulations.
Confidence Intervals
Probability-based ranges (80%, 90%, 95%) that help set realistic project targets.
Sensitivity Analysis
Identify which tasks have the greatest impact on project outcomes for focused risk management.
🔬 Best Practices
Quality Input Data
Use realistic three-point estimates based on historical data and expert judgment.
Sufficient Iterations
Minimum 10,000 iterations for statistical significance; increase for complex projects.
Regular Updates
Re-run simulation as project progresses and new information becomes available.
Frequently Asked Questions
How many simulation iterations should I run?
Start with 10,000 iterations for most projects. For critical projects or when using correlation, increase to 50,000 or 100,000 iterations for more accurate results.
What is task correlation and when should I use it?
Task correlation models the relationship between risks across different tasks. Use when tasks share common resources, technologies, or external dependencies that could cause multiple tasks to be affected similarly.
How do I interpret the confidence levels?
The 80th percentile means there's an 80% chance the project will complete within that duration or cost. 95th percentile is more conservative but includes more contingency.
What should I do if the simulation shows high risk?
Review task estimates, identify high-impact risks, consider adding contingency reserves, optimize the critical path, or adjust project scope and constraints.