Solvix International provides schedule risk analysis services for clients who need a quantified view of programme uncertainty rather than a single deterministic finish date. We review the project schedule, identify major sources of uncertainty, build suitable probability assumptions, and run probabilistic analyses to estimate likely completion outcomes, milestone confidence, and contingency requirements across the programme.
Schedule risk analysis can be applied at tender stage, at baseline acceptance, during delivery, or when recovery options are being compared. It turns a single forecast date into a range of possible outcomes with stated confidence levels.
The value of a schedule risk analysis depends on the quality of the underlying schedule and the risk inputs. A sound analysis is transparent about both and gives results that management can use.
A deterministic schedule gives a single date with no indication of how likely it is. We show the range of likely outcomes and which risks drive it.
The methodology depends on the maturity of the schedule, the depth of project records, the risk environment, and the purpose of the study. In most engagements, Solvix begins by reviewing the schedule structure and the client’s risk assumptions before building a calibrated probabilistic model that can withstand management and stakeholder scrutiny.
A structured PRA workflow for programme uncertainty, scenario testing, and risk-informed completion forecasting.
Review the baseline or current schedule, logic health, key milestones, calendars, constraints, and data reliability before simulation.
Identify uncertainty ranges, discrete events, interface risks, procurement threats, and external drivers that may affect completion.
Assign probability ranges and suitable distributions to activity durations and risk events, based on project data and documented assumptions.
Simulate numerous outcomes to test finish-date volatility, milestone confidence, and the combined effect of uncertainty on the critical path.
Identify which activities, paths, or event families most influence the project finish date and contingency requirement.
Issue P-values, risk histograms, tornado insights, and practical mitigation options for the project team and stakeholders.
The model is only as reliable as the schedule and the risk inputs, so preparation is carried out before any simulation is run.
correct logic gaps, remove unnecessary constraints, and summarise the schedule to a level suitable for analysis.
collect duration ranges and risk events from the project team and the risk register.
map risk events to activities and apply correlation where activities share the same uncertainty.
check that the model behaves as expected before running the full simulation.
review P-values and drivers with the project team and agree mitigation actions.
A good schedule risk analysis does more than produce a probability chart. It should show how uncertainty affects the critical path, which risks matter most, where contingency is likely to be consumed, and which mitigation measures provide the best decision value.
It is a probabilistic assessment that estimates likely project completion outcomes by combining schedule logic with uncertainty ranges and discrete risks, rather than relying only on a single deterministic finish date.
These are confidence levels. For example, a P80 date is a finish date with about an 80 percent probability of being achieved based on the model assumptions used in the analysis.
No. It complements them. A sound deterministic schedule remains essential, but schedule risk analysis adds visibility into how uncertain the finish date really is.
Yes. One of the most useful applications is testing whether proposed mitigations meaningfully improve the probability of meeting a target date.
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