Define baseline uncertainty and scenario deltas
Reference scenarios for planning
| Use case | Time Δ | Cost Δ | Carbon Δ | Safety Δ | Typical data inputs |
|---|---|---|---|---|---|
| Clash detection and model coordination | -3% to -8% | -2% to -6% | -1% to -4% | -2% to -8% | Issue logs, RFI rates, rework hours, BIM coordination cycles. |
| Logistics and crane/hoist simulation | -4% to -10% | -1% to -5% | -2% to -6% | -1% to -5% | Delivery schedules, laydown plans, route constraints, lift plans. |
| Predictive maintenance and equipment analytics | -1% to -5% | -1% to -4% | -1% to -3% | -1% to -4% | Telemetry, downtime logs, utilization, maintenance intervals. |
Triangular distributions and Monte Carlo outcomes
Each baseline metric is entered as min, most likely, and max. The simulator samples these ranges repeatedly, applies scenario deltas, and summarizes the result distribution.
- Triangular sampling: for a metric X with a=min, b=mode, c=max, a random draw produces a plausible value X0.
- Scenario application: for delta d%, X = X0 × (1 + d/100). Negative d reduces X.
- Percentiles: P50 is the median outcome; P80 is a conservative outcome used for buffers.
- Incidents estimate: Incidents = (RIR / 200000) × LaborHours, then apply safety delta.
- ROI: ROI% = ((BaselineCostMean − ScenarioCostMean − Investment) / Investment) × 100.
A practical workflow for scenario evaluation
- Enter baseline min/most-likely/max for duration, cost, carbon, and safety rate.
- Set labor hours to translate safety rate into expected incidents.
- Add your scenario deltas from planned digital twin initiatives.
- Run enough iterations to stabilize the percentiles (start at 5,000).
- Compare P80 duration and P80 cost when planning contingencies.
- Use exports for stakeholder reviews and change control records.
Digital twin scenarios for construction decision support
Digital twins convert schedules, costs, and site constraints into a simulation-ready model that can be tested before work happens. This calculator focuses on scenario evaluation: you define uncertainty for baseline delivery, then apply realistic percentage deltas that represent twin-driven improvements. The output includes means and conservative percentiles (P50 and P80) to support contingency planning.
1) Baseline uncertainty with triangular ranges
The baseline uses three-point estimates: minimum, most likely, and maximum for duration, cost, carbon, and safety rate (RIR per 200,000 hours). These ranges represent market volatility, productivity variation, and supply risk. Triangular distributions are commonly used when historical data is limited but expert judgement is available.
2) Scenario deltas that mirror field interventions
Each scenario adjusts baseline samples with deltas such as -5% time or -4% cost. Typical construction use-cases include clash detection reducing rework, logistics simulation reducing wait time, and predictive maintenance reducing downtime. Keeping deltas within practical limits helps avoid unrealistic ROI claims.
3) Percentiles for planning buffers
Mean results are useful for comparisons, but P80 is often better for commitments. If a scenario reduces P80 duration from 210 to 195 days, planners can adjust float, crane calendars, or procurement dates with higher confidence. Use P50 for internal targets and P80 for risk-aware baselines.
4) Translating safety rate into expected incidents
Safety is modeled by converting RIR to expected incidents using labor hours. For example, an RIR of 1.2 with 320,000 labor hours implies about 1.92 expected recordable incidents. Safety deltas then estimate reduction potential from better access planning, hazard visualization, and sequencing.
5) ROI framing and stakeholder reporting
ROI is calculated from mean cost savings versus the stated twin investment. Exports support change control by documenting assumptions, iterations, and scenario deltas. Update the baseline ranges as the project progresses to keep the digital twin narrative aligned with measured performance.
Common questions
1) What does P80 mean in this report?
P80 is the value that 80% of simulated outcomes are below. It is commonly used as a conservative planning point for schedule and cost buffers when uncertainty is material.
2) Why use triangular distributions instead of normal distributions?
Triangular ranges work well when you only have min, most likely, and max estimates. They are transparent for workshops and avoid false precision when historical data is limited.
3) How should I choose scenario deltas?
Base deltas on measurable mechanisms: rework reduction, reduced waiting, fewer breakdowns, improved routing, or safety planning. Use pilot results, benchmarks, or past project data, and keep values within realistic limits.
4) Do negative deltas always mean improvement?
Yes for this calculator. Negative deltas reduce time, cost, carbon, or incident expectations. Use positive deltas if a scenario introduces complexity or new constraints that increase demand.
5) How is safety converted into incidents?
The tool uses Incidents = (RIR / 200000) × LaborHours, then applies the safety delta. It provides an expected value for comparison, not a guarantee of site performance.
6) Is ROI based on mean or percentile cost?
ROI is calculated using mean cost savings relative to baseline mean cost. If you prefer risk-based ROI, compare P80 costs manually and treat the result as a conservative estimate.
7) How many iterations should I run?
Start with 5,000. Increase to 10,000–20,000 if percentiles change noticeably between runs. Higher iterations reduce noise, but very large values may slow the page on shared hosting.