ANP is a multi-criteria decision analysis tool that uses benefits, opportunities, costs, and risks to model sub-elements of a decision. It uses ratio scale measurements and subjective data to rank alternatives in a super matrix, which is subjected to sensitivity analysis. ANP has been used in real-world scenarios, such as a Turkish construction company considering a bid on an overseas project.
Diplomatic and military analysts, civic planners, and corporate executives often have to make decisions that have many, somewhat opaque, parameters. They can use a multi-criteria decision analysis tool known as ANP (Analytic Network Process) to provide assistance. ANP provides more than economic analysis; uses four elementary criteria: benefits (B), opportunities (O), costs (C) and risks (R), from which decision makers can model the sub-elements of a decision. These four elements are reviewed according to weighted priorities and produce rankings of alternatives in a condensed picture of what-if scenarios. These scenarios can then be viewed against the goals to determine the alternative that will facilitate the best results.
The analytical network process initially uses the organization of hierarchical networks of objectives and elements of these objectives. At the same time, evaluations of the influences, feedback connections and interdependencies of each of the four elements and their sub-elements are mapped. In these assessments, benefits and opportunities can be given a valuable balance of considering costs and risks using a (B+O) minus (C+R) approach. These results are further enriched by the use of ratio scale measurements, while making wise comparisons between items.
Ratio scale measurements are developed that assign weight to priorities consisting not only of objective facts, but also of subjective data. Subjective data can be factors such as nodes of societal beliefs and values, political biases and agendas, and both tangible and intangible criteria, each weighted according to their own priority positions. The synthesis of the criteria and the subjective positions of these objectives are what form the basis of the ranking of the alternatives in what is called the super-matrix.
In the application, the balancing of all these elements gives an overview of each what-if scenario and the rankings of the alternatives in the super matrix. Predicting these outcomes using the analytical network process involves both quantitative and qualitative analyzes and deductive and inductive reasoning to predict likely determinants and likely outcomes. The what-if scenarios are subjected in their final analysis to sensitivity analysis, so that any changes in judgment, design or priority inputs can test their stability.
Many real-world examples of applying the analytical network process have been reported in numerous published books and reports. For example, a Turkish construction company reported using analytical network analysis and its BOCR criteria scenarios when considering a bid on an overseas construction project. The company had to consider risks such as a high level of terrorism and different cultural, political and legal environments surrounding the project in the other country. Costs such as the unavailability of certain raw materials that are expected to be imported are further weighed against any benefits or opportunities realized by the project. These were just a few of the many factors that ANP modeled to determine whether the project’s benefits and opportunities would outweigh its costs and risks.
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