Know About Quantitative Model in Measuring Risk

Measurement of risk is one crucial step that must be done in risk management. Measurement of risk is generally carried out qualitative and quantitative. Although sometimes there is only a qualitative measurement include only, but for more complete information, of course, also required a quantitative risk measurement.

Now, a method for quantitatively measuring these risks also vary, including major and commonly used are as follows.

Simple Method
This method is a quantitative method of the simplest. Thus, this method of measuring risk based on knowledge of the risks that have occurred historically in the various elements of the project. The higher of the risk factor cause the higher the cost estimates contingency.

Sensitivity Analysis
Each risk has a different impact. Sensitivity analysis allows us to determine risks which have the greatest impact on the sustainability of a project. Sensitivity analysis is done by analyzing the possibility of changing an element, other elements assuming ceteris paribus (no change).

For example, by using a tornado diagram, which is a diagram that illustrates the contribution of a risk to the overall risk model. A tornado diagram is formed by drawing a correlation between variations in the distribution of inputs.

Decision Tree
Decision tree analysis illustrates the diagram which the contents are options to the decision being considered, as well as the implications of choosing alternatives such decisions.

Through the decision tree, then we will be shown the probability of benefits and risks derived from various alternative decisions to be taken. Furthermore, by combining cost-benefit estimate with the probability for each event that occurs, then the later will produce expected monetary value for each decision.

This decision tree allows us to analyze the risks and benefits that may arise, the implications sequel, and the payoff is likely to be obtained.

Simulation
Simulation models typically use Monte Carlo methods, ie, a probabilistic computing with a computer, which uses random number generator to draw samples from probability distributions. The purpose of this simulation itself is to measure the impact of some uncertainty to some quantity (the result), such as the cost or duration of the project.

Monte Carlo is one form of sensitivity analysis, too, only more comprehensive and sophisticated. This simulation requires the implementation of a more complicated, because they have to know certain information about the probability distribution, the mean, standard deviation, and shape distribution. Only, this simulation is preferable to analyze the project because it is more comprehensive and contains more information about the impact of a risk to the cost and duration of the project.

In addition, for the project can also be simulated using the Critical Path Method, especially to cope with project scheduling.