![]() ![]() ![]() Ours is a straightforward example, requiring only odd integer scores. Maximum discrimination is achieved using decimal scores, but the additional effort adds value only in the most extraordinary circumstances. If greater discrimination or compromise is required, even numbers (from 2 to 8) can be used. Scores are usually odd numbers, ranging from 1 to 9. Comparisons are “scored” on Saaty’s Pairwise Comparison Scale, shown in Exhibit 2. This begins with pairwise comparisons of the evaluation criteria to quantify the relative importance of each. Once the decision hierarchy has been established, the analysis can begin in earnest. Larger decision matrices require adjustments that are beyond the scope of this discussion. The process followed here is appropriate with as many as ten criteria and alternatives (10 x 10 matrix). The analysis is sufficiently complex to demonstrate the value of AHP, but not so complex as to overwhelm those unfamiliar with it. An analysis with the minimum number of levels, with three evaluation criteria and three alternatives (a “3 x 3 decision matrix”) was chosen for balance. A “blind” process limits the bias affecting the criteria evaluations.Īdditional alternatives could also have been included in the analysis. At this stage, only the potential sources are known it is best if the content of the proposals has not yet been revealed to evaluators. For our example, let’s assume that RFPs (requests for proposal) have been sent to Jones Machinery, Wiley’s Widget Works, and Acme Apparatus Co. Level 3 identifies the alternatives to be considered. However, we will forego the additional complexity in our example, as it may be a bit overwhelming in one’s first exposure to AHP. For example, the cost dimension could have been split into sub-criteria such as purchase price, maintenance cost, and disposal cost. Additional criteria could have been added, as well as additional levels of analysis. In our example, machines will be evaluated on the dimensions of cost, productivity, and service life. Level 2 is populated with the criteria deemed relevant to the decision. The goal of our example is summarized as “Buy Widget Machine.” The long form of this objective statement may be “Choose source for purchase of new production machine for Widget Line #2.” If the objective is understood by all involved, the summary statement is sufficient if there is concern of confusion, use a more detailed statement. Level 1 is the goal, objective, or purpose of the decision. The decision hierarchy for our example, shown in Exhibit 1, consists of three levels. In AHP, the decision scenario is represented by a hierarchy. The first step of the decision-making process, as always, is to define the decision to be made. Do not be discouraged! Though the presentation may seem lengthy, the process is easy to follow and simple to implement, particularly when using a spreadsheet to perform the required calculations. Due, in part, to the simplified mathematics, the process, at first glance, may seem long and tedious. To make this decision-making aid more accessible, AHP will be executed here with tables and basic mathematics in lieu of matrix operations. Before embarking on the Analytic Hierarchy Process example, it is important to note that AHP was originally developed with matrix notation calculations were performed with matrix algebra.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |