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The analytic hierarchy process is a way of making a decision by taking into account a number of factors. These factors are weighted in terms of their importance, in an attempt to strategically make the best decision based on all the information available. The format for the process was developed in the 1970s by educator Thomas Saaty.
The method works by combining mathematical equations and values with the desires of the individuals involved. Each branch of the decision-making process where there is another choice to be made is assigned a numerical value. Once these values are established, they are said to help the individuals involved make the best decision based on mathematical evidence.
Consider the problem of a family of four selecting a breed of dog. Within the agreed-upon size bracket, there might be four choices: an Australian cattle dog, a golden retriever, a German shepherd, and a dalmatian. Making a decision using the analytic hierarchy process requires family members to also determine what qualities they most desire in a dog. For example, they might like a dog that is active, good with children, and intelligent; these qualities are then ranked from most important to least important.
Each dog breed is given a score based on its abilities in each category; a golden retriever would rank high in the children category, while a cattle dog would score low in the children category and high in the active category. Depending on which characteristic the family valued most, it would be able to draw up a table indicating what dog breeds scored the highest in the characteristics most desired. Negative factors can also be added to the scale: two members of the family may not want a dog that sheds, for instance, so a golden retriever would have low desirability for half of the family in this category.
Giving physical characteristics and personality traits of each dog a value that indicates how important they are to the family as well as how high each dog breed scores allows the family to make an educated, informed, and mathematically logical decision when choosing a new dog. This can turn the decision into an objective one based on mathematical data combined with confirmed information on each choice. The analytic hierarchy process also helps the family consider problems or qualities it may not have otherwise thought of.
While the analytic hierarchy process can help make the best choice based on statistics and other data, it is not foolproof. There are always circumstances beyond the control of those making the decision. The family may adopt a golden retriever that doesn't like children or a cattle dog who is happy to lie in front of the fireplace all day, but statistically the analytic hierarchy process presents individuals with the best chance of making the correct decision.