PrintSo far, in previous lessons, effect of risk and uncertainty haven’t been considered in our economic evaluations and the analyses were assumed to be of no-risk condition. In this case, the probability of success and achieving anticipated results is assumed to be 100%, but in reality, some degree of uncertainty is involved and this probability is much lower. The economic analyses that don’t include risk and uncertainty are based on “best guess,” and the results aren’t highly accurate and reliable. For example, if a study shows 20% and 25% ROR for project A and B, the manager would probably choose project B over A. But what if the probability of success is 90% for project A and 40% for project B? This example shows how important it is to consider the effect of risk and uncertainty as a component in economic evaluations.
Quantitative methods, along with informal analysis, are used for decision making under risk and uncertainty. Quantitative methods aim to provide the best possible set of information to decision-makers so that they may apply their experience, intuition, and judgment to achieve the final decision; the decision that leads to maximum possible future profit with the highest probability. There are several different approaches that can be used to quantitatively incorporate risk and uncertainty into analyses. These include sensitivity analysis or probabilistic sensitivity analysis to account for uncertainty associated with possible variation in project parameters, and expected value or expected net present value or rate of return analysis to account for risk associated with a finite probability of failure. The use of sensitivity analysis is advocated for most economic analyses and the use of expected value analysis is advisable if a finite probability of project failure exists. Sensitivity analysis is a means of evaluating the effects of uncertainty on investment by determining how investment profitability varies as the parameters are varied that effect economic evaluation results.
Sensitivity analysis can show how results change if the input parameter changes. If we change one input parameter (such as initial investment) and the result (such as NPV of the project) varies significantly in a wide range, then we say the result is sensitive to the specified input parameter. Here, we aim to find the most sensitive variables. The input parameter investigated for sensitivity analysis usually includes initial investment, selling price, operating cost, project life, and salvage value. If probabilities of occurrence are associated with various levels of each investment parameter, sensitivity analysis becomes probabilistic sensitivity analysis.
It may now be evident to you that the term “uncertainty” as used in this lesson refers to possible variation in parameters that effect investment evaluation. “Risk” refers to the evaluation of an investment using a known mechanism that incorporates the probabilities of occurrence for success and failure and/or of different values of each investment parameter. Both uncertainty and risk influence almost all types of investment decisions, but especially investment involving research and development for any industry and exploration for minerals and oil or gas.
Please watch the following video (3:24): Risk, Uncertainty, and Sensitivity Analysis.
PRESENTER: In this video and the next videos, I will explain how to incorporate risk and uncertainty in the economic evaluation of projects for the purpose of investment. I will explain how we can apply the sensitivity analysis techniques to evaluate the project in this case. In previous lessons, in previous videos, we use fixed numbers. All the numbers that we used were deterministic at no risk condition. The probability of achieving an outcome was 100%.
But it is not the case in real life. There is always some level of uncertainty in the anticipated result, especially things that are happening in the future. For example, if an evaluation of two projects, Project A and Project B shows that Project A has a rate of return of 20% and Project B has a rate of return of 25%, assuming they have the same skill and they require the same amount of investment, what would you do as a manager?
You would choose the project with a higher rate of return. So you will choose Project B, which has a higher rate of return. But what if I tell you the probability of success in Project A is 90% and the probability of success in Project B is just 40%? What would be your decision?
Decision-makers use combinations of qualitative and quantitative methods in risk situations. In this video, we are focusing on quantitative methods. Quantitative methods are aiming to provide the best possible information for the decision-maker. And in the end, decision-makers have to use their own experience, intuition, and judgment for the final decision about maximum possible profits in the future with the highest probability.
There are several quantitative methods for incorporating risk and uncertainty. I will explain two of these methods in this video and the following videos. The first one is called sensitivity analysis or probabilistic sensitivity analysis. And the next one is going to be expected value or expected net present value.
Sensitivity analysis is a method that helps us understand the sensitivity of results to the input variables. Here, our result, our evaluation result, is a measure that shows us the profitability of the project, which it is NPV, rate of return, or any other parameter that we learned so far. In a sensitivity analysis, we want to determine how results vary if we change input variables. What would be the magnitude of change in one variable with respect to the change in other variables? Sensitivity analysis helps decision-makers to find the parameters that have the biggest impact on the results.
Italicized sections are from Stermole, F.J., Stermole, J.M. (2014) Economic Evaluation and Investment Decision Methods, 14 edition. Lakewood, Colorado: Investment Evaluations Co.