What you actually get,
before you book.
Five rendered deliverables straight from the CPP forensic toolkit. Click any sample to open the full interactive dashboard. Sample data, fictional project, real methodology.
One coherent forensic engagement, five deliverables.
Each sample below was generated from the same demonstration schedule, baselined 01-Apr-2025 and updated to a data date of 01-Jul-2025. The delay events in it are two owner-caused (an authority-having-jurisdiction hold on commissioning, an owner-directed re-sequence of integrated systems testing) and one contractor-caused (punch-list and deficiency re-work). One schedule, five complementary forensic lenses.
Schedule Health Dashboard
Full DCMA 14-Point assessment with pass/fail per criterion, executive summary, key performance metrics, baseline-versus-current comparison, six untruncated exception registers (leads, lags, high float, high duration, valid dates, missed tasks) listing every flagged activity, risk and predictive tiles, and a reproducibility manifest. This run grades F, with 5 of 13 scored criteria passing. C10 is not scored because the XER export carries no resource-assignment table.
View sampleForensic Windows Analysis Dashboard
Observational/dynamic/contemporaneous as-is analysis (AACE 29R-03 §3.3) over one window, baseline to current. Completion shift, party attribution (owner 7 wd, contractor 14 wd, concurrent 0, force majeure 0, nothing unattributed), slip velocity, float burndown, and a cumulative activity slip register with all 261 rows listed.
View sampleCollapsed As-Built / But-For Analysis
Independent dual-method validation per AACE 29R-03 §3.8 (Modeled / Subtractive / Single Base — Collapsed As-Built) of the windows result. Three delay events removed from the as-built network one at a time and then all together, for a cumulative subtractive impact of 20 working days; per-event but-for finish dates with cross-reference back to the MIP 3.3 windows result.
Independent in methodology (windows + collapsed are mathematically distinct approaches); both are computed by CPP's open-source engine — see DAUBERT.md §3 for the same-author crossval caveat.
Monte Carlo Schedule Risk Analysis
5,000-iteration Monte Carlo simulation over triangular duration uncertainty (optimistic 90%, most likely 100%, pessimistic 130%). P10/P25/P50/P75/P80/P85/P90/P95 completion bands measured against the deterministic CPM finish, plus a Pearson-correlation sensitivity tornado. This run has no mitigation scenario loaded, so it reports a single baseline scenario with no mitigated comparison, and no random seed was fixed, which means a re-run would draw a different sample and land on slightly different percentile dates.
View sampleClaim Workbench Dashboard
Mixed-evidence intake from one folder: 7 artifacts, being 2 XER updates and 5 text notes. Produces a chronological evidence ledger, a schedule chain-diff across the two snapshots (655 relationships added, 535 removed, 405 activities added, 327 removed, 1,922 flagged edits in total), a rolling baseline that preserves the 327 original baseline activities and captures as-introduced dates for the 405 added mid-chain, a 14-of-100 trust score, and slip-to-evidence pairings auto-keyed by date and activity code. This folder carries no emails, PDFs or workbooks, so 98.5% of the 264 activity slips pair only with the schedule files under analysis, and the evidence-supported rate is 1.5%, being the slips whose paired document actually names the slipped activity code.
View sampleHave a real claim that needs this treatment?
Twenty-five years of construction-schedule practice, the same toolkit you just clicked through, and a fixed-fee engagement scoped to your matter. Send the file or drop a line.