Practical writing on QSRA and QCRA — the method, the maths, the P6 workflows, and the tool landscape. No fluff, references included.
Pertmaster became Oracle Primavera Risk Analysis and then quietly faded. What should schedule risk practitioners use now? An honest look at the landscape — and what monthly QSRA actually needs.
Read the guide →QSRA without the jargon: three-point estimates, Monte Carlo over a CPM network, P50 vs P80, and what the APM PRAM Guide and AACE 57R-09 actually ask for.
Read the guide →A practical end-to-end walkthrough: exporting the XER from P6, gating schedule quality, building the risk register, setting three-point ranges, running the Monte Carlo and reading the P80.
Read →All fourteen DCMA schedule assessment checks, explained through a QSRA lens: which ones actually distort a Monte Carlo, which are hygiene, and what to fix before you simulate.
Read →Two parallel paths, each 50/50 to finish on time, give a project only a 25% chance. Merge bias explained with a closed-form example you can verify — and why simulation is the fix.
Read →Latin Hypercube sampling stratifies each distribution so every part of it gets drawn — a stable P80 in a fraction of the iterations plain Monte Carlo needs. Why it works, the honest caveat, and how we ship it by default.
Read →Not every risk is worth mitigating. Expected value of information ranks risks by how much they actually move your committed date — a sharper guide than the tornado chart, straight out of the Monte Carlo you already run.
Read →A single completion date throws away the one thing a sponsor needs — how wrong it might be. The flaw of averages, the value of including uncertainty, and why the distribution is the deliverable.
Read →A perfect simulation a committee won't act on has failed quietly. Lead with the decision, carry the story on three charts, and win trust with transparency — the communication craft of schedule risk.
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