Analytical Hierarchy Process


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Analytical Hierarchy Process

Because people choose these three elements: importance, preference and likelihood to evaluate all the possible alternatives to a decision which sometimes is not consistent with every decision situation, the concept of Analytical Hierarchy Process (AHP) was developed by Dr. Thomas Saaty. Dr. Saaty described the AHP as a decision making approach based on the "innate human ability to make sound judgments about small problems"
AHP transforms complex decision problems into simple decisions for both individuals and groups that employees the use of it to make decision. It is accommodative of intuition, compromise, and consensus structure without narrow-mindedness. The main purpose of this paper is to discuss what the AHP is and some other aspects of it.

What is AHP?
Saaty suggested AHP as a process that requires structuring the decision problem to demonstrate key elements and relationships that elicits judgments reflecting feelings or emotions, and whose judgments can be represented by meaningful numbers having ratio properties. In the AHP approach, complex decisions are organized and assessed against all possible alternatives using a hierarchy of multifaceted objectives allowing for a better, easier, and more efficient identification of selection criteria.

How AHP works
AHP is used to first decompose the decision problem into a hierarchy of easily comprehended sub-problems, each of which can be analyzed independently. The elements of the hierarchy can relate to any aspect of the decision problem tangible or intangible, estimated or carefully measured, well or poorly understood.
Once that hierarchy is established, the decision maker systematically examines the various elements, comparing them to each other in pairs. In making the comparisons, the decision maker can use his/her judgments about the elements’ relative meaning and importance, or they can use well refined data about the elements.
AHP converts the judgments to numerical values that are processed, evaluated and compared over the entire range of the decision problem. A numerical weight or priority vector is derived for each element of the hierarchy, allowing diverse and often incommensurable elements to be compared to one another in a rational and consistent way. This capability distinguishes AHP from other decision making techniques.
At the end of the process, numerical priorities are derived for each of the decision alternatives. It is then a simple matter to pick the best alternative, or to rank them in order of relative preference.

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Importance of AHP
AHP is very useful when the decision-making process is complex, for instance, by being unstructured, it has been applied to numerous various fields (government, business, industry, healthcare, and education) and has proven to be a powerful decision-making tool.
In management, it has been successfully employed in resource allocation, forecasting, total quality management, business process re-engineering, quality function deployment and the balanced scoreboard.
In higher education, AHP has been applied in areas to include funding research support requests, deciding on sabbatical proposals, assessing performance and allocating rewards or compensation, choosing students for admission, financial aid, scholarships and awards, and faculty selection.
AHP is best used along with or in support of other decision making methodologies, example, when using a decision tree to analyze alternative choice nodes of a decision tree, as well as to derive priorities for alternatives at the extremities of the decision tree.
More so, because AHP helps capture both subjective and objective evaluation measures, providing a useful mechanism for examining the consistency of the evaluation measures and alternatives suggested by the decision maker thus it reduces biasness in the decision making process.
AHP allows organizations to decrease widespread pitfalls in decision making process, such as lack of focus, planning, involvement or possession, which eventually are costly distractions that can prevent the decision maker from making the right choice.

Benefits
Are good decisions made by mishap or there is an inherent logical principle that the human mind follows when making decision? If there are implicit logical principles that the mind follows are they consistent and complete? There are no clear cut answers to these questions because in decision making humans are inconsistent and incomplete. The cognitive limitation decreases the prospect of analyzing all the alternatives for the decision situation. That is why the benefits of AHP can not be over stress by decision experts.
First the morphological way of systematic modeling the decision includes people to make explicit their unstated knowledge. This leads to people harmonize and organize their different feelings and understanding. An agreed upon structure provides ground for a complete multisided debate.
Second, in the framework of hierarchies and feedback systems, the process permits decision makers to use judgments and observations to deduce relations and strength of relations in the course of interacting forces moving from general to the particular and to make predictions of most likely outcome.
Third, the decision maker is able to incorporate and trade off values and influence with greater accuracy of understanding then they can use language to explain.
The final benefit is the decision maker is able to include judgment that result from intuition and emotion as well as those that result from logic. Reasoning takes a longtime to learn in most people and it is not an easy skill. By representing the strength of judgments numerically and agreeing on a value, decision makers do not need to participate in lengthen urging.

Limitations
Even though AHP is one of the most widely preferred tools used in reducing complex decision to very comprehensible decision analysis, there are limitations in AHP concept.
Decision makers are humans that are inconsistent when making decisions. The human cognitive limitations make it very difficult for humans to evaluate all the available alternatives when making decision. The decision maker uses prior experience or information available to analyze the decision choice as a result limiting the consistency in the decision making process (the volume of information can limit the consistency).
Also, when the decision phase involves taking into account a variety of multiple criteria with evaluation based on a multiple-value choice, AHP splits the overall problem into many evaluations of lesser importance while keeping at the same their part in the global decision. This becomes confusing for the decision maker because they can not evaluate the true importance of the decision alternative.

Conclusion
This is an extensive discussion of AHP as a formal approach which allows decision makers to follow gradual and thorough steps in analyzing complex decisions. The approach decomposes a larger problem into is constituent parts dealing with rational concepts to choose the best alternative. AHP is a great tool that assists decision makers but it does not make the final selection of the best alternative(s) for the decision maker.

References
Ahmed, N., Berg, D., & Simons, G. R. (2006). The Integration of Analytical Hierarchy process and Data Envelopment Analysis In A Multi-Criteria Decision-Making Problem. International Journal of Information Technology & Decision Making, 5(2), 263-276.

Grandzol, J. R. (2005). IR Applications: Improving the Faculty Selection Process in Higher Education: A Case for the Analytic Hierarchy Process. Retrieved Nov. 25, 2007, from http://airweb.org/page.asp?page=295

McCaffrey, J. (2005). . Retrieved Nov. 23, 2007, from http://msdn.microsoft.com/msdnmag/issues/05/06/TestRun/

Yager, R. R. (1999). An extension of the Analytical Hierarchy Process using OWA operators. An Extension of the Analytical Hierarchy Process Using OWA Operators, 7(3), 401-417.


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