What is an Analytic Hierarchy Process ?
The Analytic Hierarchy Process (AHP) is a structured procedure of mathematical operations intended for getting a score among several situations contrasted with each other under certain criteria.
As such, is a powerful tool to use for decision-making when dealing with multiple alternatives of choice judged under several points of view (criteria) simultaneously.
AHP belongs to the Multi-Criteria Decision Methods (MCDM) family where stands out over other members of this group.
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Why using AHP ?
Strategic decisions that involve risky bets and with results that can have repercussions in the long term are presented to decision makers poorly defined under ambiguous, uncertain and often confusing assumptions. Additionally, there are variables that increase considerably in quantity and complexity the more depth the analysis is required. Under these conditions, many of the mathematical techniques that require very limited, precise, and orderly information fail to be properly applied, and decision makers end up rejecting them. Added to the above is the fact that the increasing agility required for commercial and productive actions has an impact on less and less time granted for decision-making, with which decision-makers face decision-making pressured by high complexity of the information and the scarce time to discern.
The AHP is fundamentally presented as a fast technique once the desired values for the model variables have been entered, with parameters easily adjustable to each particular decision scenery, covering an infinite range of possible applications, always using the same process path, with requirements of resources adjustable to each need.
How to use AHP ?
When confronted with a decision, scenarios can be assumed composed of decision units (we name them DU) and decision criteria (we name them DC). A decision unit is something over it is required to take some action (change, move, replace, sell, contract, buy, etc), and a decision criterion is a measurable attribute from a decision unit.
The AHP technique involves determining decision criteria common to several decision units in such a way that further comparison can be established. Thereafter, once DCs for DUs are all set, the AHP technique will require the decision maker to establish, in a two-step process, firstly a numeric comparison among DCs and, secondly, a numeric comparison between DUs subjected to each DC.
An efficient decision-maker will try to catch the most attributes from a decision unit to get the wider possible picture of the scenario. Since evident complications arise from analyzing a huge amount of information simultaneosuly, the AHP technique helps by structuring the available information and setting a logical path for the analysis.
A little bit of history
The first reference can be found in a paper called "An eigenvalue allocation model for prioritization and planning" authored by Thomas L. Saaty and published in 1972 by the University of Pennsylvania. It has been extensively studied and refined since then.
Subsequent developments have deepened the use of comparison scales based on various functions for adapting the method to specific uses. Consistency Index criteria have also been incorporated to supervise the correct application of the comparison scales, trying to reduce the subjectivity of the evaluations.
The current version presented in this application corresponds with the original model proposed by Prof. Saaty, perfectly suitable for general purposes.
Other complementary techniques
Some of the other methods from de MCDM family are:
- Weighted Sum Model
- Weighted Product Model
- ELECTRE
- TOPSIS
- Multi-Attribute Utility Function (MUAT)
- ... and many more.
