Monte Carlo Schedule Risk Analysis — P10/P50/P80/P90
completion-date forecast for a Primavera P6 schedule.
Implements an AACE-style quantitative SRA (the same math as
CPP's browser Tool_11 Portfolio Risk Engine, scripted Python
counterpart). For each iteration, every activity duration is
sampled from the chosen distribution (Triangular, BetaPERT,
Uniform, Lognormal, etc.) parameterized by % of baseline
duration; CPM re-runs and the project finish date is recorded.
After all iterations, P10/P50/P80/P90 completion dates and a
sensitivity tornado (per-activity correlation to project
finish) are reported.
Use this tool when you need probabilistic completion forecasts
or a tornado/sensitivity ranking. For the QRAMM-aligned
five-level maturity badge (AACE 122R-22) on the result,
pipe the response into
``qramm_maturity``.
Args:
xer_path: server-side path to the schedule XER.
xer_content: full text of the schedule XER (alternative for
hosted/remote use). Supply EXACTLY ONE of path/content.
iterations: number of MC iterations (default 5000).
distribution: 'Triangular', 'BetaPERT', 'Uniform',
'Lognormal' (case-insensitive — passed through).
optimistic_pct, most_likely_pct, pessimistic_pct: %
of baseline duration for the distribution params
(defaults: 85 / 100 / 120).
seed: optional fixed seed for reproducibility (0 = system
entropy = non-reproducible).
output_dir: optional output dir; tempdir if "".
Returns:
Full SRA result dict, key paths:
- 'baseline.percentiles': lowercase p-keys
{'p10','p25','p50','p75','p80','p85','p90','p95'},
each {'day', 'date'}. NOTE: keys are lowercase — read
result['baseline']['percentiles']['p80'], not 'P80'.
- 'baseline.config': sim params used
- 'baseline.sensitivity': per-activity tornado rows
- 'risk_register_simulation.percentiles' (only when a
risk_register is supplied): SAME lowercase convention,
{'p10','p50','p80','p90'} each {'day', 'date'}.
- 'project_name', 'data_date', ...
- HTML / DOCX paths if outputs emitted