Sensitivity analysis is a key tool to evaluate or forecast the success of a project and make the best financial, corporate, environmental, etc. decisions in time.
Sensitivity analysis is the name given to a study or a technique that focuses on, taking into account output variables of systems or mathematical models, how it is possible to divide and assign uncertainty (which can be associated with issues such as lack or insufficiency). of data , a possible measurement error , etc.) to various sources of uncertainty linked to input variables . Expressed another way, this mathematical resource allows us to quantify how the input data impacts the results (output data) that are obtained.
Experts suggest, in this framework, carrying out simultaneous uncertainty and sensitivity analyzes in order to be able to carry out comparisons and complement the processes.
It is interesting and useful to know what the fundamentals of sensitivity analysis are (learning, in principle, about variables , parameters , uncertainty , analysis modalities), what specialized software is the most useful, what model validation consists of, what methods and approaches there are, what difficulties or obstacles arise most frequently and what are the fields of application of this study. With the intention of providing an informative article that is as complete and enriching as possible, below we will address all of these aspects mentioned.
Types of sensitivity analysis
A wide range of methods, styles and approaches are available for those wishing to perform sensitivity analysis .
Broadly speaking, it is usual to differentiate between a unidirectional sensitivity analysis (the simplest modality since it consists of working with one variable at a time) and a bidirectional sensitivity analysis (proposing the observation of the influence on the output of a pair of variables. that are changed at the same time).
Nor should we overlook the existence of both local sensitivity analysis and global sensitivity analysis (the latter is especially recommended for complex models that present a large number of interactions and variables).
It is even convenient to know that other methodologies and processes have been designed and implemented over the years, such as the cases of spatial sensitivity analysis , non-parametric sensitivity study and parametric sensitivity analysis , to list specific alternatives to indicative way.
Thanks to sensitivity analysis, a banking entity, for example, can adopt measures and strategies to minimize risks and ensure financial stability for the entity and its clients.
Importance and advantages
All sensitivity analysis is key to informed decision making . With it, it is possible to evaluate the impact that uncertainty has on a system or model, as well as revealing the influence that the variations evident in the inputs of a certain model or system can have on a result. It also accounts for the quality and safety of the model.
Through it, it is possible to consider different scenarios and distinguish the critical variables that affect the results, giving the opportunity to act in time by introducing modifications if necessary. This information is vital during the monitoring of a plan or project, since a properly developed and interpreted sensitivity analysis indicates which variables can be attributed a large part of the responsibility regarding the success or failure of an initiative, idea. or aspiration. It is essential, as it emerges from reality, to examine risk management strategies, prepare budgets , analyze investments , guarantee quality control within a company and make financial forecasts .
With a sensitivity analysis, you can measure or evaluate the impact that changes made in certain variables have on a result.
Examples of sensitivity analysis
Sensitivity analysis has an extensive and diverse field of applications that ranges from the financial field to the health sector, without leaving out the environmental field. With minimal knowledge in this regard and mastering the tools of the Excel program (particularly, the function called data table ), to describe an option available to a huge number of people, a sensitivity analysis can be easily done.
The so-called environmental sensitivity analysis , to give an example for reference, is a relevant instrument when planning the installation of a gas network. It is also important to have an environmental sensitivity analysis implemented with Geographic Information Systems (GIS) for optimal decision making and an efficient and rapid protection and mitigation reaction in the event of an oil spill along the entire coastal area of a region, to add another possibility.
For the progress of a company and its long-term sustainability , meanwhile, it is essential that those responsible know the performance of a particular project (or more than one) and what its profitability is. By resorting to a sensitivity analysis, profitable strategies or initiatives are identified and the weakest corporate points are noted, thus being able to make strategic decisions and define steps to follow, knowing and comparing the different possible scenarios, understanding the potential risks and opportunities that arise in these circumstances.
A financial analyst, for his part, usually resorts to a financial sensitivity analysis with the objective of being able to predict what result will surely be obtained when carrying out, under certain conditions, a specific action.