By

Bob Prieto
Senior Vice President
Fluor

Rick Rye
Fluor

Risk is inherent to major capital construction programs.

The initial paper in this Series defined a ten step process to guide consideration of program risks. Collectively, these interrelated processes contribute to successful strategic risk management. These ten steps encompassed:

• Plan for Risk
• Make Realistic Assumptions
• Utilize Outside Expertise
• Understand Risk Elements and Their Impacts
• Assess and Analyze Risks
• Develop Mitigation and Contingency Plans
• Synthesize the Risks
• Integrate Risk Management
• Establish Clear Metrics
• Manage Risk Continuously

This paper focuses on the seventh and eighth of these steps.

Synthesize the Risks

Risk measurement and analysis, at least in the context of this discussion, include using an analysis vehicle for predicting the extent of possible variations and forecasting the worst case and the best-case scenario for the program budget and schedule. The most unpopular element of employing risk analysis techniques is using the worst-case scenarios. By using probabilistic methods in risk analysis, the program manager will have much more information when compared to other methods and helps to make more informed decisions.

There are now technology tools available that help in managing risk information when evaluating and quantifying multiple risk scenarios. The use of these tools allows program managers to create reasonable and often realistic forecasts and to assign the needed resources such as time and money, with confidence.

It is important to note that risk management software, such as @Risk, Monte Carlo and PertMaster, have become widely used in the construction industry and are thought to provide the most scientific results available. These tools cover statistical risk management techniques and probabilistic calculation methods used in business planning and cost estimation applications. Several references have been included that provide in-depth discussion and examples on modeling, simulation, and analysis techniques.

Risk analysis uses statistical methods in order to arrive at a set of confidence limits determined for program objectives of cost and schedule. By using a simulation risk analysis technique, a cumulative probability distribution curve can be constructed to provide the probability of not exceeding a specified cost or schedule duration. The @Risk simulation calculates numerous scenarios by repeatedly picking random values from the input variable distributions and calculating a risk adjusted estimate.

Integrate Risk Management Process

The risk analysis process integrated with program management applications helps to discipline the continuous collection and evaluation of the multiple factors that have an influence to negatively affect the program. It is imperative that a continuous risk analysis methodology become integrated with the day-to-day program management application. The major objectives of an integrated risk management approach are:

• collaborative mitigation planning for risks before they introduce impact
• sharpening the program management foresight of potential risk issues
• enhancing the identification of resources or technical assistance that would benefit in the risk mitigation planning
• facilitating continuous monitoring, analysis and communication of risk issues.

The risk management process should be implemented to do more than just identify the risk and present a mitigation plan. The risk management process should become a definitive and integrative process to ensure program objectives are achieved.