1.1 Theoretical Model of Risk Management Circle
Within this theoretical model and risk management circle, risks can be seen as controllable and assessable. According to the author, Dr. Tilo Nemuth, “risk identification at an early stage and an integrated in-house risk management is therefore an indispensable requirement for a monetarily positive result of a project.” The author uses the following risk management circle as depicted in figure 1, for an overall guideline of a risk management system. “Risk” is also defined in this article as “Risk = probability of risk occuring x impact of risk occurring.”
|Figure 1: Stempowski’s Risk Management Circle.|
1.2 Objectives for Risk Management of Project Cost
a. Project risks must be identified early on in the tender and acquisition phase.
b. Monetary analysis of risk impacts must be conducted.
c. Display of the impact of failures.
d. Improved risk awareness.
e. Filtering of high risk projects and implementation of knock-out-criteria for projects in the early stages of growth.
2 Implementation of Risk Assessment in Estimation Procedure and Tender Process
2.1 Two-stage system and comprehension of Monte Carlo Simulation
In this section, Dr. Nemuth claimed that project risks can be placed into categories for more of a organized process of evaluation. This section also introduces the implementation of a two-stage system meant for the “aggregation of project risks.” The first stage is an analysis of all risks and the second stage is a detailed evaluation of the critical risks found from that first analysis. Emphasis is then placed on a Monte Carlo Simulation due to its superiority when compared to other risk analysis methods and techniques.
With reference to the risk management circle presented earlier, the two-stage process is further explained by the following example illustrated in this article.
Stage 1 = Phase 1 + 2 (identify and analyze the project risks)
Stage 2 = Phase 3 (evaluate the risks with MCS) and preparation for Phase 4 (monitoring)
The results of a Monte Carlo Simulation can be seen as a probability distribution. Below in figure 2 is a probability density, while figure 3 is an example of the results displayed in a cumulative ascending chart.
Figure 2: Probability Density for Monte Carlo Simulation.
Figure 3: An example of the cumulative ascending chart.
The purpose of this article was to illustrate that risks for projects are capable of being analyzed and evaluated. This simulation provides decision makers with a better scope of understanding regarding the risks that are present but also the results as well, whether positive or negative. The Monte Carlo Simulation allows for a more concentrated focus on the critical risks at play. Filtering high risks at an early stage can assist the decision maker with avoiding failure later on.
Source:Nemuth, T. (2008). Practical Use of Monte Carlo Simulation for Risk Management within the International Construction Industry. International Probabilistic Workshop, 1-12.