What Are the Different Types of Risk Analysis?

The risk analysis of a project can be carried out at any stage of the project life cycle and is a continuous process. Risk analysis is the primary work of project risk management, and it is an important part of project risk management. These include: risk identification, risk estimation, risk management strategies, risk resolution and risk supervision.

Basic Information

Chinese name

Product size. Practical experience shows that project risk is directly proportional to the size of the product. Well-known product size measurement units are code lines or feature points.

Technology related. There are risks to new technologies that have never been used. This includes new unused hardware, supporting software, and non-traditional development methods that lack standards and specifications. Outdated technology is also a risk. Technical risks are generally difficult to correct.

Development environment. Inadequate, unreliable, and inconvenient to use development tools can reduce development efficiency.

Organization size and personnel experience.

Customer factors. This is manifested in the often contradictory needs of customers, the lack of understanding of the special needs of customers, the lack of understanding of new technologies used in the project, and the difficulty of communication between the two parties.

Investment decision-making on engineering construction projects or production and operation of enterprises

Risk analysis

Consists of three parts

Risk Assessment: Core and Basic

Risk Management

Risk Communication

Comprehensive risk analysis

Among the methods of comprehensive risk assessment, the most common and simplest analysis method is to obtain the weight of the risk factors and the probability of occurrence through the opinions of survey experts, and then obtain the overall risk level of the project. The steps include:

1. Establish a risk survey. After the risk identification is completed, a list of major risks of the investment project is established, and all important risks that the investment project may encounter are listed in the table.

2. Determine risk weight.

3. Determine the probability of each risk occurring. You can use a scale of 1-5, which indicates that the probability is very small, small, medium, large, and large, representing 5 degrees.

4. Calculate the level of each risk factor.

5. Finally, add the levels of all risk factors in the risk survey form to get the comprehensive risk level of the entire project.

Risk analysis simulation technology

1. Conditions of use:

When more than three random variables are entered in the project evaluation, and each input variable may have more than three or even an infinite number of states (such as continuous random variables), the theoretical analysis cannot be used for risk analysis. At this time, Must use Monte Carlo simulation technology.

2.Principle

Random sampling is used to extract the values of a set of input variables and calculate the project evaluation index based on the values of this set of input variables. The sample is calculated a sufficient number of times to obtain the probability distribution of the evaluation index, and the cumulative probability distribution, expected value and variance are calculated Standard deviation, calculate the probability of the project from feasible to infeasible, so as to estimate the risk assumed by the project investment.

3. Monte Carlo simulation program

Determine the evaluation indicators used in risk analysis, such as net present value and internal rate of return.

Determine the input variables that have an important impact on project evaluation indicators.

The probability distribution of the input variables is determined after investigation.

Random numbers are drawn independently for each input variable.

The sampled value of each input variable is converted from the drawn random number.

A set of project evaluation basic data is formed based on the sampled values of the input random variables.

Calculate the evaluation index value based on the sample data to form the basic data.

Repeat steps 4 to 7 until the predetermined number of simulations.

Sort out the probability distributions of the expected values, variances, standard deviations, and expected values of the evaluation indexes obtained from the simulation results, and draw a cumulative probability map.

Calculate the probability that a project will change from feasible to infeasible.

4. Issues to note when applying Monte Carlo simulation

(1) When applying the Monte Carlo simulation method, it is assumed that the input variables are independent of each other, and the degree of decomposition of the input variables will be encountered in the risk analysis.

The finer the input variables are decomposed, the more the input variables are, and the more reliable the simulation results are. Too fine factorization often results in correlations between variables, which can lead to erroneous conclusions. To avoid this problem, the following measures can be taken.

Limit the degree of decomposition of input variables.

Limit the number of uncertain variables. Only the key variables that have a significant impact on the evaluation index are selected in the simulation, and other variables are kept at the expected value.

Further collect relevant information, determine the correlation between variables, and establish functional relationships.

(2) Monte Carlo simulation times.

Theoretically speaking, the more the number of simulations, the more correct it is, but generally it should be between 200 and 500 times.

Risk Analysis Expert Survey

Expert survey method is an analysis method based on the knowledge, experience and intuition of experts to discover the potential risks of a project.

Scope of application: It applies to the entire process of risk analysis.

Note: When using the expert survey method, the experts should have a reasonable scale, and the number of experts should generally be about 10-20. The number of experts depends on the characteristics, scale, complexity, and nature of the project. There are no absolute rules.