We can establish risk management as a continuous process that is performed throughout the project life cycle to increase the probability that a planned project achieves its objectives.
We organize it as a series of following processes that are cyclic and continuously applied at each stage in the project life cycle.
Collaborating closely with project teams and stakeholders, we can assist in establishing of risk management objectives resulting in documented Risk Management Plan with processes, procedures, organization, tools and systems that guide and support effective risk management throughout the project life cycle.
Risk assessment is typically comprised of following three distinct tasks:
To facilitate risk identification, we can assist in development of the knowledge base of the common risk drivers including Risk Breakdown Structure.
We can also facilitate risk workshops with subject matter experts to identify risk drivers and appropriate risk owners who have knowledge and authority to provide correct information for further analysis.
We can insure correct creation and maintenance of Risk Register with clear cause, risk and effect separation and risk types classification.
We can further categorize all identified risks using qualitative methods to rank risks in terms of criticality and significance to the project objectives.
Based on organization’s risk appetite documented in risk management plan we can establish probability and impact scales and risk scoring and rating to enable comparison and prioritization of risks from different areas.
The output of the qualitative risk analysis is typically reported using a matrix where risk impact is plotted against probability.
For each critical or significant risk selected by the team for quantitative risk analysis, we can prepare a probabilistic estimate of its impact. Estimating output is a distribution of possible cost or schedule outcomes at different levels of confidence. The probability distribution is commonly used to derive the confidence level percentage values that support estimation of the appropriate contingency based on organization’s risk appetite documented in the risk management plan. Organization’s willingness to accept risk can be expressed as organization’s desired percentage confidence (percentile or P value) that the project will not overrun its budget or schedule.
In addition to quantification of required contingency, Quantitative Risk Analysis also allows:
One of the following methods or a hybrid of them is commonly employed for Quantitative Risk Analysis:
Parametric Modeling
Simulation Analysis of a Spreadsheet-Based ICSRA model (Expected Value Method)
Simulation Analysis of a CPM-Based ICSRA model
Hybrid Methods
Parametric models are multi-variable regressions analysis of quantified risk drivers versus cost growth or schedule slip outcomes for historical projects.
With parametric modeling, the risk to impact estimating relationship is implicit and the probabilistic outcomes are inherent to the algorithm.
Can only be used for systemic risks that have predictable relationships with outcomes across all projects, those that are inherent to the project system.
Cost and schedule results are integrated because systemic cost and schedule outcomes are correlated.
Directly estimates the cost or schedule impact of each identified critical project-specific risks using three point estimates which portrays the team’s optimistic and pessimistic view, where the most likely value usually aligns with the estimated value. The simulation produce cumulative probability distribution only for total cost and overall completion date.
Cost and schedule results are integrated because project specific risk impacts are based on assumed risk responses that consider cost/schedule trading.
MCS analysis of the full project scope using resource-loaded CPM schedule as a platform enables greater insight into risk impacts to schedule details and reporting on all cost and schedule aspects.
Integration of cost and schedule is made by the total cost loading onto the activities as time-dependent and time-independent.
In simulation modeling, schedule risks drives the cost of time-dependent direct and indirect costs which represents integration in integrated cost and schedule risk analysis.
The simulation produces cumulative probability distributions for both cost and finish date.
Parametric (P) method quantifies the impact of systemic risks while Expected value (EV) method quantifies the impact of critical project-specific risks.
To integrate both results, parametric model output distributions must be included as the first critical risk in the EV MCS tool.
MCS analysis is required to model the EV portion and to integrate the analyses results in overall cost and schedule cumulative probability distribution.
Parametric (P) method quantifies the impact of systemic risks which includes all inherent and other systemic risks and non-critical project specific risks.
CPM-Based ICSRA method quantifies the impact of inherent risks (duration and cost uncertainties) and critical project specific risks.
This two methods overlap with each other and to combine them correctly net systemic risk not overlapping the inherent risk must be quantified and then assign to all time dependent cost in Parametric and CPM-Based ICSRA model.
We can assist risk owners in planning and implementation of the risk response plans, and in monitoring and reporting on both the status of their identified risks and response plan including: