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Cost and schedule risk analysis

Material on quantitative risk analysis of costs, schedules and value, often in association with major projects and investments

  • The real risk to your project budget

    This paper examines the structure of cost uncertainty in an estimate and demonstrates how it can be addressed by separating expert judgements from numerical calculations and linking the two together using risk factors that represent uncertainty in major cost drivers. It sets out some principles for deciding what to address by means of expert judgement and what to implement as numerical calculations.

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  • Contingency assessment methods and trends

    This is a webinar delivered for the PMI Risk Community of Practice by Dr Stephen Grey. It explains the historical origins of some common methods for contingency assessment and points out the need to move to those that make more intelligent use of the power we now have available in computers and simulation software.

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  • Project cost contingency

    Project cost contingency setting is an important part of managing risk in projects. This note describes how a contingency is related to a base estimate and project risk as well as outlining how it is utilised during project execution.

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  • Beta PERT origins

    In the decades since PERT was developed, the Beta PERT distribution to which it gave rise has come to have a special place in risk modelling. Many people assume that it must represent a fundamental characteristic of uncertainty in durations and other features of projects. In fact, the rationale for using a Beta distribution is anything but fundamental. The modern Beta PERT is a reverse engineered replica of the distribution chosen for convenience in the 1950s to convert three point estimates into a mean and variance.

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  • Weaknesses of common project cost risk modelling methods

    The widespread use of flawed methods is the result of project scale and complexity having grown more quickly than computing power and availability. Risk-register-based and line-item ranging methods are often inappropriate and time consuming as well as producing unrealistic forecasts. Practices that grew out of a need to deal with project cost uncertainty in a time when the power and availability of computers were, by today’s standards, very limited have become entrenched in common usage long after the constraints that led to them being adopted have disappeared.

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