QSRA · Live · V2.5.0

Quantitative Schedule Risk Analysis, end to end.

From input validation through Monte Carlo to the final deliverable — one toolkit, one source of truth, one audit chain.

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Findings tab: 0 blockers, 21 warnings, 1 info on a reference scheme — **Findings · Reference scheme**Every failed check listed with rule ID, severity, source row and the WBS branch it affects.

Process

Four phases. Same data.

Validate

Four input lanes converge on one canonical schema. Quality checks run as you type. Errors point to the source row.

Model

Monte Carlo across three models (M1 DU, M2 Pre‑mit, M3 Post‑mit). 10,000 iterations default. Spearman attribution. Ours to run.

Deliver

S‑curves, tornados, sensitivity analysis, mitigation deltas, decile attribution. Four briefing formats from one run.

Defend

Every output traces to source. Audit‑replay archive lets you re‑run any historic period byte‑identically.

Validate · Input Validator

Quality checks that run as your team works.

No more "let's run the validator at the end and find out everything's wrong." Risk Studio validates as data comes in.

Four input lanes — manual entry, paste‑in, standard template, non‑standard importer.
17 canonical columns. Full or Split impact is mandatory, with inline help on every field.
Distribution validation — Triangular, BetaPERT, Uniform, Discrete. Min ≤ ML ≤ Max enforced.
Correlation matrix checks — symmetry, diagonal = 1, values in [-1, 1], positive semi‑definite via Higham PSD.
Risk‑to‑activity mapping is checked end to end: orphan risks flagged, split weights summed, single and multi mappings validated.

Validator run UI with progress and findings tally — **Validator run · live**Quality checks fire as data lands. Errors trace back to the row, column or activity that caused them.

Real Safran S-curve, reference scheme, M3 post-mitigation — **S-curve · M3 post-mitigation**10,000 iterations on a representative UK infrastructure scheme. Internal MC engine output.

Model · Monte Carlo Engine

The same family of algorithms. Without the round‑trip.

Higham PSD, NORTA, six distributions. We benchmark every Monte Carlo scheme against Safran and share the per-scheme comparison under NDA. Parity validation is ongoing; we publish the benchmark register to procurement teams on request.

Three‑model approach — M1 Duration Uncertainty, M2 Pre‑mitigation Threats, M3 Post‑mitigation Threats.
Higham PSD repair guarantees positive semi‑definite correlation matrices, so sampling stays stable on analyst‑built matrices.
NORTA sampling — correlated random variates with target marginals preserved.
Six distributions — Triangular, BetaPERT, Uniform, Discrete, plus engine extensions.
Spearman rank attribution drives the tornado. It's the right measure for skewed schedule outputs and what the AACE guidance recommends.
Per‑decile attribution — which risks drive the P10 vs the P80. Honest about model granularity.

Deliver · Four formats

One run. Four briefings. Same numbers.

Weblink HTML dashboard hero with KPI tiles — **Weblink HTML**The board‑facing dashboard. Self‑contained, drill‑down, prints to PDF cleanly when someone wants it on paper.

Outputs tab with deliverable tiles — **Outputs tab**Every deliverable is generated automatically and lives next to the run that produced it. Re‑run, re‑generate, never lose the trail.

Excel report and audit log entries with cryptographic chain — **.xlsm · Excel Report (configurable templates)**The team's existing macro‑enabled template, populated automatically. Cells hold literal values so SharePoint and macros‑disabled viewers still display correctly.

Period-over-period scheme movement view — **.pptx · Analyst Briefing**12‑slide deck on period‑over‑period drift. Each slide ships with speaker notes written for a named audience: PM, Planner, Risk Manager, RAM, RRM.

Run yours through the same pipeline.

Send an XER. We'll come back with the four deliverables ready for your next period board — branded to your scheme, traceable to source.

Send an XER →Read the methodology