sCurve’s Commitment to our Quantitative Process & Tools offers the following.

Generic risk quantification methodologies fail to provide adequate data for identifying the critical risks specific to claims, and fail to capture data consistently over time which could be used to optimize ROI for your projects and business. That is why our quantitative risk analysis team, based in Houston, strives to improve comprehension of risk factors and modelling in the processes we advocate for.

sCurve’s Expert Use of Quantitative Analysis Helps Ensure the Following:

  • Appropriate levels of contingency are set at the outset of a project
  • Risks are quantified and understood at the outset of a project
  • Objective decisions about the level of mitigation can be calculated based on exposure
  • Incremental decisions about key project decisions can be Objectively Quantified
  • Tools Used Consistently show patterns of quantified risk & opportunity over time
  • Prevents under or over commitment of capital based on intuition
  • Auditable results and processes

Quantitative Project Analysis and Quantitative Claim Risk Analysis Models

Quantitative claim risk analysis takes information available at a point in time on your project and assimilates that information into inputs, which when properly used can generate a probabilistic distribution of the possible outcomes of cost and schedule on your project. This modelling is commonly used to help establish contingency levels as a part of the funding amounts or commitments which are used to make commitments in an FID package on large projects.

Typically, sCurve researches the project, reading things like the project execution plan or potentially the E.I.S. (Environmental Impact Statement), the Construction execution plan, the contracting plan, examines the accepted estimate and proposed schedule for the work, and the examines the risk register to gain an understanding of how the risks could impact these elements.

We then discuss the risk, plans, cost, and schedule with team members at length so that we understand how to map the risks to the appropriate cost or schedule elements. The conversations also help us validate that the model is an adequate construct of the execution of the work. We build the model using the schedule as a basis with cost loading done within that schedule to appropriately account for cost impacts which are associated with delays or improvements to the timeline. sCurve then runs some basic tests using extreme input values to ensure the proper function of the model. After ensuring the validity of the model, the outputs are then analyzed and used for making decisions or setting funding levels and schedule goals.

Constructing the model in this way shows us the proportionate effects of a given risk on both dollars and time with respect to the project. This allows us to help make very objective arguments about what it might be worth spending to solve a problem given that we can reasonably assess the scale of the risks impact if it occurs and as unaddressed. We can also run very informative scenario analyses with respect to the delivery of late equipment, or the shortage of skilled manpower, or any number of other key issues on the project.

During the execution of the project, as more information is available to more precisely define the impact of a risk – very accurate predictions can be made with respect to what will happen to key dates and budget tranches. The modelling can also be used to assess the financial and time impact of an opportunity, like cutting 1.5 months from the overall schedule by deciding to ship a large vessel by air freight instead of the traditional ocean freight.

In the hands of a team like sCurve, where we have the expertise to build the tool, and more importantly to run a process to extract and use accurate data, iCRA can be a fantastic tool for optimizing decisions on your project and helping you come in on budget and on time. This work can be used to objectively examine granular decisions during project execution, or to help you set realistic expectations at the beginning of your project.