Importance of Sensitivity Analysis
Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system can be divided and allocated to different sources of uncertainty in its inputs. It can also referred to as “what-if” or simulation analysis. It is a way to redirect the outcome of a decision given a certain range of variables. By creating a given set of variables, an analyst can determine how changes in one variable affect the outcome.
Importance of Sensitivity Analysis
- It compels the decision maker to identify the variables which affect the cashflow forecasts.
- It helps investors in understanding the investment project in totality.
- It indicates the critical variables for which additional information may be obtained.
- It equally helps decision maker to consider actions, which may help in strengthening the “weak spots” in the business.
- It helps to expose inappropriate forecasts and thus guides the decision maker to concentrate on relevant variables.
S.A can be used for both personal planning with the variables in mind to the decisions at corporate levels .
Sensitivity analysis works on the simple principle: Change the model and observe the behavior.
Uses of Sensitivity Analysis
- The key application of sensitivity analysis is to indicate the sensitivity of simulation to uncertainties in the input values of the model.
- They help in decision making
- Sensitivity analysis is a method for predicting the outcome of a decision if a situation turns out to be different compared to the key predictions.
- It helps in assessing the riskiness of a strategy.
- Helps in identifying how dependent the output is on a particular input value. Analyses if the dependency in turn helps in assessing the risk associated.
- Helps in taking informed and appropriate decisions
- Aids searching for errors in the model
The parameters that one needs to note while doing the above are:
- A) Experimental design:It includes combination of parameters that are to be varied. This includes a check on which and how many parameters need to vary at a given point in time, assigning values (maximum and minimum levels) before the experiment, study the correlations: positive or negative and accordingly assign values for the combination.
- B) What to vary:The different parameters that can be chosen to vary in the model could be:
a) the number of activities
b) the objective in relation to the risk assumed and the profits expected
c) technical parameters
d) number of constraints and its limit - C) What to observe:
a) the value of the objective as per the strategy
b) value of the decision variables
c) value of the objective function between two strategies adopted
Measurement of sensitivity analysis
Below are mentioned the steps used to conduct sensitivity analysis:
- Firstly the base case output is defined; say the NPV at a particular base case input value (V1) for which the sensitivity is to be measured. All the other inputs of the model are kept constant.
- Then the value of the output at a new value of the input (V2) while keeping other inputs constant is calculated.
- Find the percentage change in the output and the percentage change in the input.
- The sensitivity is calculated by dividing the percentage change in output by the percentage change in input.
This process of testing sensitivity for another input while keeping the rest of inputs constant is repeated until the sensitivity figure for each of the inputs is obtained. The conclusion would be that, the higher the sensitivity figure, the more sensitive the output is to any change in that input and vice versa.
Methods of Sensitivity Analysis
There are different methods to carry out the sensitivity analysis:
- Modeling and simulation techniques
- Scenario management tools through Microsoft excel
There are mainly two approaches to analyzing sensitivity:
- Local Sensitivity Analysis
- Global Sensitivity Analysis
Local sensitivity analysis is derivative based (numerical or analytical). The term local indicates that the derivatives are taken at a single point. This method is apt for simple cost functions, but not feasible for complex models. Models with discontinuities do not always have derivatives. Local sensitivity analysis is a one-at-a-time (OAT) technique that analyzes the impact of one parameter on the cost function at a time, keeping the other parameters fixed.
Global sensitivity analysis is the second approach to sensitivity analysis, often implemented using Monte Carlo techniques. This approach uses a global set of samples to explore the design space.
Using Sensitivity Analysis for decision making
One of the key applications of Sensitivity analysis is in the utilization of models by managers and decision-makers. All the content needed for the decision model can be fully utilized only through the repeated application of sensitivity analysis. It helps decision analysts to understand the uncertainties, pros and cons with the limitations and scope of a decision model.
Most if not all decisions are made under uncertainty. It is the optimal solution in decision making for various parameters that are approximations. One approach to come to conclusion is by replacing all the uncertain parameters with expected values and then carry out sensitivity analysis. It would be a breather for a decision maker if he/she has some indication as to how sensitive, will the choices be, with changes in one or more inputs.
The Importance of Sensitivity Analysis to SMEs in Nigeria, can not be overemphasize as it is one of the tools that help decision makers with more than a solution to a problem. It provides an appropriate insight into the problems associated with the model under reference. Finally the decision maker gets a decent idea about how sensitive is the optimum solution chosen by him to any changes in the input values of one or more parameters.
SOW Professional is a Management Consulting firm in Lagos, Nigeria, we can assist you on how Sensitivity Analysis can help the growth of your business, hence, we look forward to assist you with this process. Please call:
Call us on 07038254989