In the late 1990s and early 2000s, the Analytical Hierarchy Process (AHP) became popular among management employees as a quantitative method for issue resolution. The AHP approach was developed after researchers studied the structure of an issue and the genuine challenges that managers confront while trying to solve it. Today we’ll discuss about this in detail context.
The analytic hierarchy process (AHP), sometimes known as the analytical hierarchy process, is a systematic methodology based on mathematics and psychology for organising and evaluating complicated choices. It was created in the 1970s by Thomas L. Saaty, who collaborated with Ernest Forman to create Expert Choice software in 1983.Since then, AHP has been widely investigated and enhanced.
It is a precise method of measuring the weights of choice criteria. Pair-wise comparisons are used to evaluate the relative magnitudes of variables based on individual experts’ experiences. Using a carefully constructed questionnaire, each responder compares the relative value of each pair of elements.
How does Analytical Hierarchy Process Works?
The AHP approach divides the problem into three halves. The issue that has to be fixed is the first portion, and the different solutions that are accessible to fix the problem are the second portion. The criteria used to assess the different solutions are the third and most significant component of the AHP technique.
Although there are multiple criteria, the AHP technique recognizes that the size of each criterion may not be equal. If you have to select between two restaurants, for example, the flavor and the wait time are two things to consider, but they may not be equally important to you.
The flavor of the food may be significantly more essential than the time it takes to prepare it. As a result, if you give flavour 2 points and waiting time 1 point, you’ll be more likely to find a restaurant that meets your needs.
As a result, while weighing various solutions, weights must be assigned to the criteria to guarantee that the proper conclusion is reached. This may seem self-evident. Management scientists, on the other hand, have had difficulty assigning weights until recently. In the preceding example, we assigned weights at random. In addition, the example only contained two conditions. The allocations get increasingly arbitrary as the number of criteria (factors) increases.
What is the Connection Between AHP and Six Sigma?
AHP is a distinct method. It isn’t part of the normal Six Sigma approach. It was really created several years after the Six Sigma approach was created. It has, nonetheless, found widespread use in six sigma initiatives. AHP is used by managers to assign numerical weights to various criteria. These variables might be ones that customers consider when assessing a product, or they may be ones that management considers when assessing alternative alternatives.
The disadvantage of Using AHP
The AHP approach has its own set of problems. The procedure necessitates the use of advanced mathematics. It is built upon the idea of eigen vectors. As a result, conducting AHP calculations on an Excel sheet is a nightmare. However, software tools that can conduct computations have recently been developed. Managers just need to be aware of the AHP process; the calculations are done automatically.
How to use Analytical Hierarchy Process (AHP)?
Despite the fact that the AHP is one of the most sophisticated methodologies available in the field of management science and operations research, its complexity makes it difficult to employ. Thankfully, software tools have been developed to automate the math-intensive component of the process. The user must follow a basic data gathering process, which is then put into the programme to obtain the desired results.
This is the way to achieve the same thing:
Step 1: Define Alternatives
The AHP process starts with the definition of the options to be assessed. These possibilities may be the many criteria to be assessed for solutions. The many aspects of a product might also be the one to weigh in order to better grasp the perception of buyers. A complete list of all the possibilities accessible must be ready at the conclusion of step 1.
Step 2: Define the Problem and Criteria
The next step is the issue. A linked number of sub-problems are an issue under the AHP technique. Therefore, the AHP technique is based on dividing the problem into a hierarchy of minor issues. Criteria for the evaluation of the solutions come in breaking down the subproblem. However, a person might go to deeper inside the problem, like the root cause analysis. A subjective judgement is when the problem is stopped in smaller subproblems.
Example: A company has to pick among stocks, bonds, real property and gold on the best investment choice. The best investment problem will be divided into smaller problems when using the AHP technique, such as downturn protection, maximum appreciation, market liquidity, etc. Each sub-problem may then be divided into smaller issues until the management believes that the required requirements are met.
Step 3: Establish Priority amongst Criteria Using Pairwise Comparison
The AHP technique compares the matrix in pairs. For instance, the company should assess the relative value of safeguarding against downfall vs liquidity. There will then be a comparison of liquidity and appreciation probability on a pair basis, in the next matrix. Managers should put up this data according to end users’ expectations or those who will utilize the procedure.
Step 4: Check Consistency
Most software products that assist with AHP difficulties include this step. For example, if I claim that liquidity is twice as significant as downside protection and that downfall protection is half as significant as the probability of appreciation in the next matrix, the following situation emerges:
Liquidity = 2 (Protection from downfall)
Protection from downfall = ½ (Chance of appreciation)
As a result, Liquidity must have an equal probability of increasing in value.
However, if I have assigned a weight of more or less than 1 in the pairwise comparison of liquidity and possibility of appreciation, then my data is inconsistent. Because conflicting data yields inconsistent results, prevention is preferable to cure.
Step 5: Get the Relative Weights
The software programme will use the data to do a mathematical computation and give relative weights to the criterion. Once the equation with weighted criteria is complete, one may assess the options to choose the best answer for their needs.
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