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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

  • Quantitative risk analysis and project governance: Risk Engineering Society Conference, RISK 2023

    Dr Dale Cooper spoke at the Risk Engineering Society Conference, RISK 2023, held in Brisbane Meanjin on 7-8 September 2023. His paper provided a short summary of the role of quantitative analysis of uncertainty in governance and decision making in large projects. It focused on the interaction between quantitative analysis and tollgate decisions at the end of each project phase, including the contribution of quantitative analysis to the decision support package (DSP) used by an investment review committee. It noted the different contributions of distributional outputs, sensitivity outputs and input data about uncertainties to specific parts of the DSP. Finally, it noted that cost and schedule uncertainty may not be the most important factors if the main focus of decisions is on project value.

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  • Correlation in quantitative risk analysis

    Uncertain quantities can be correlated by a dependence on a common source of variation. Modelling these correlations in quantitative risk analysis must be done with great care. Ignoring correlation in quantitative models can generate outcomes that are wrong, sometimes significantly so, and that have the potential to mislead the users of those models. This tutorial note examines correlation, and practical methods of incorporating it in quantitative risk analysis models.

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  • Extreme project schedule over run

    There is often a sense that project schedule risk distributions fail to exhibit the long right-hand tails that experience suggests should show up in a realistic assessment of schedule risk. This paper demonstrates quantitatively that unexpected extensions of time might arise not from unforeseen risks or understated risks, nor from a bias towards optimism or over-confidence, but through a systematic interaction between the risks that are taken into account by conventional schedule risk modelling and firefighting behaviour stimulated by schedule slippage.

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  • Range analysis – summary of good practice

    This tutorial is drawn from Broadleaf’s long experience with project range analysis, also referred to as quantitative risk analysis or probabilistic risk analysis. It describes some key lessons about project range analysis, and what constitutes good practice. The material covers the analysis of both costs and schedules; the same principles apply to both.

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  • Range analysis resources for projects

    Broadleaf has extensive expertise in schedule and cost range analysis for major projects and related analysis for commercial applications. Range analysis is sometimes called probabilistic risk analysis or quantitative risk analysis. We have been conducting such analyses for large clients around the world for many years. This tutorial summarises some of the resources and case studies available on our web site, with a particular focus on material relating to projects.

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  • Schedule uncertainty in linear developments

    Linear developments such as pipe or cable laying, road or rail building, or tunnelling, present challenges not found in other forms of construction. Analysis of the risk to their schedules may require a different approach from that used for the analysis of general construction projects. In some situations, existing schedule modelling tools lack the means to represent the particular features of linear developments. However, these can be addressed, with appropriate expertise, using two modelling tools and exchanging information between them.

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  • Linking and integrating different views of project risk

    Qualitative and quantitative views of project risk are often treated as if they are distinct from one another. It is easier to make sense of uncertainty if that artificial divide is set aside. This paper describes a way to frame processes based on qualitative and quantitative descriptions of uncertainty as an integrated view of project risk management. This can be used to assist in implementing risk management and as an aid to clear communication about project risk.

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  • Quantifying the risk to software project costs

    In principle, software project cost risk has the same characteristics as the cost risk in other types of projects. However, there are good reasons why software projects have a reputation for being prone to over running budgets and schedules. This note outlines some of the factors involved and how they can be used to make realistic assessments of cost risk, achievable targets and contingency requirements.

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  • Simple schedule risk modelling with Safran Risk

    With a view to exploring alternative tools for quantitative project risk assessment, Broadleaf reviewed Safran Risk, a tool for planning and for modelling schedule and cost uncertainty. While Broadleaf does not endorse any specific tools, we use several in our work and discussing their application provides an opportunity to offer insights into quantitative risk assessment and modelling in general.

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  • 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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