Predictive Analytics &
Schedule Risk
Know the future before it happens.
Monte Carlo simulation, EAC forecasting, and AI anomaly detection — the complete predictive analytics suite for construction project controls. Stop reporting single-point estimates and start reporting with mathematical confidence.
Monte Carlo Simulation
10,000 iterations · Highway Bridge Construction
Dec 15, 2026
50% confidence
Jan 8, 2027
80% confidence
Jan 28, 2027
90% confidence
$24.5M
BAC
$10.3M
EV
$11.0M
AC
$26.1M
EAC
-$1.6M
VAC
Top Schedule Risk Drivers
Everything included
Monte Carlo Simulation
Runs 10,000 schedule iterations using activity duration uncertainty to produce probability-based completion date forecasts.
P50 / P80 / P90 Forecasts
Three confidence levels for completion dates. Report P80 to clients, use P90 for risk reserves, track P50 as most likely.
EAC Forecasting
Estimate at Completion calculated using multiple methods: CPI-based, composite, and expert judgment — all shown side by side.
ETC Calculation
Estimate to Complete — exactly how much budget remains needed to finish the project from today's data date.
VAC and TCPI
Variance at Completion and To-Complete Performance Index — know whether your budget target is still achievable.
AI Anomaly Detection
Mistral 7B AI scans all activity data and flags unusual patterns — duration spikes, float collapses, cost outliers.
Tornado Diagram
Ranks the top schedule risk drivers by sensitivity. Shows which activities have the most impact on completion date.
EAC Trend Chart
Tracks how your Estimate at Completion has changed over time — shows whether cost forecasts are converging or diverging.
Schedule Risk Register
Automatically generates a risk register from anomaly detection results with recommended mitigation actions.
Why teams choose this
- Stop reporting a single completion date — report with probability and confidence levels that protect you contractually
- Catch cost overruns 6-8 weeks before they appear in financial reports — EAC trends show the direction before it hits
- Use Monte Carlo P80 dates in EOT claims to demonstrate schedule risk quantification to Engineers and adjudicators
- Identify which activities are driving schedule risk before they become critical — tornado diagram makes it visual
- Replace subjective gut-feel forecasting with 10,000-iteration mathematical modelling — defensible in any dispute
- AI anomaly detection catches data quality issues in P6 that humans routinely miss — bad logic, wrong durations, missing actuals
Who uses this
Planning Manager
Uses Monte Carlo P80 date as the reported forecast completion in monthly reports. Protects the programme from single-point estimate liability.
Commercial Manager
Uses EAC trend chart to identify cost growth early and prepare variation claims before the project hits its contingency.
Project Director
Uses the tornado diagram in steering committee presentations to show which risks are being actively managed and what the mitigation impact is.
Start forecasting with confidence
Replace single-point estimates with probability-based forecasts that hold up in client meetings, steering committees, and dispute resolution.