Safran Risk Masterclass Series - How Leading E&C Consultancies Perform QSRA - Data Centers Edition - By Doug Oldfield

Safran Risk Masterclass Series

How Leading Engineering & Construction Consultancies Perform QSRA

Data Centers Edition

Leading engineering and construction consultancies around the world use Safran Risk to perform quantitative schedule risk analysis (QSRA) on major projects.

For data center developments, pressure to deliver capacity quickly sits alongside uncertainty around power availability, planning approvals, critical equipment lead times and evolving requirements driven by AI. Understanding how these uncertainties affect delivery dates is essential to setting credible commitments and prioritising mitigation.

In this practical, free webinar, we will demonstrate how to perform a QSRA using Safran Risk, applying the methodology to a realistic data center project. We will move from a deterministic project schedule to a risk-adjusted view by incorporating duration uncertainty, risk events and their potential impact on key milestones, including energization, commissioning and operational handover.

Participants will see how Monte Carlo simulation can be used to estimate the probability of meeting target dates, identify the activities and risks that have the greatest influence on delivery, and determine appropriate levels of schedule contingency. Examples will explore how dependencies between construction, power infrastructure, equipment delivery and integrated systems testing can affect completion, even where individual work packages appear to be on track.

The session will cover the main steps of the QSRA process, including schedule preparation, uncertainty modelling, risk mapping, simulation, interpretation of probability distributions, confidence levels such as P50 and P80, and sensitivity analysis using tornado charts.

By the end of the session, participants will have a practical understanding of how Safran Risk can support more realistic schedules, clearer delivery commitments and better-informed project decisions in the data center sector.