### 10-2 Risk Assessment

The next step in the risk management process is risk assessment. This involves sifting through the lists of risks, eliminating inconsequential ones, and categorizing the rest with regard to importance and deserving of attention. Risk Assessment can be done using qualitative or quantitative techniques.

**Scenario Analysis** – This is a very common qualitative technique for risk assessment. It involves determining the likelihood that the risk event will occur and the degree of impact on the project objective. Historical data from previous projects can be used to help with the assessment. Charts showing the probability and impact of each risk are used in this technique. A few examples are attached here. Risk-impact-chart , Risk-impact-chart-II

In addition to the charts, sometimes some firms prefer to calculate a Risk Factor, a number that captures the overall risk of a specific event. The risk factor (RF) is based on the probability (P) and the consequence (C). **RF= P _{f} +C_{f} – P_{f} *C_{f}**

It is also possible to include the ability to detection of the event ( i.e how imminent is the event) into the equation. One approach is to calculate the risk severity matrix as: **Risk Value= Probability X Impact X Detection**.

**Quantitative Techniques**– There are several common quantitative techniques that can be used for risk assessment. These include Decision Trees and expected value, simulation and sensitivity analysis.

A Decision Tree is a technique where the decision making situation (with uncertain events and outcomes) is represented in the form of a tree with nodes and branches. Notes represent events and decision points while branches represent alternatives associated with the nodes. The expected value at the end of a branch (option) is the product of the event probability and the monetary value for that risk event. A simple example is shown here. simplified-Decision-Tree-example

Simulation (Monte Carlo) is using a model to carry out several repetitions of a risk event (scenario) to provide a statistical distribution of the expected outcomes. For example, you can use Monte Carlo simulation to determine the probability of finishing a project by a given date.

Sensitivity Analysis is a method determining the effects of changing one or more variables on an outcome. Microsoft Excel is a tool that can be used to carry out sensitivity analyses. For example, we can use sensitivity analysis to determine the impact changing inflation rates on the viability ( e.g. NPV) of a project that we are considering.