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Appendix A. 4 Tools for identifying & evaluating options

Multi-attribute Utility (MAU) Models


Multi-attribute utility (MAU) models are mathematical tools for evaluating and comparing alternatives to assist in decision making about complex alternatives, especially when groups are involved. They are designed to answer the question, "What's the best choice?" The models allow you to assign scores to alternative choices in a decision situation where the alternatives can be identified and analyzed. They also allow you to explore the consequences of different ways of evaluating the choices. The models are based on the assumption that the apparent desirability of a particular alternative depends on how its attributes are viewed. For example, if you're shopping for a new car, you will prefer one over another based on what you think is important, such as price, reliability, safety ratings, fuel economy, and style.

are open for all to see, it's possible to make any number of changes and review the results. For example, if it appears that some attribute is too important in determining the results, the weights can be adjusted to produce different results.

What are they?

Methods to evaluate alternatives. MAU models give you a way to score, evaluate, and compare possible alternatives. They offer a quantifiable method for choosing options.

Identify valuable attributes. To use a MAU model, you must identify all the attributes needed to evaluate the alternatives. They are assigned a weight that reflects their importance to the decision. You may assign a value of 3, 2, or 1 to each attribute, depending on its importance. Or you may use 100 points and distribute them over the attributes according to their importance.

Score your options. You then give a score to each of the alternatives for each attribute. You may use a scale of 1-10. Each alternative's score for each attribute is then multiplied by the weight of that attribute, and the total is calculated. That total represents the value (or utility) of that alternative, and can be compared to the same calculation for the others. If it is a group process, each member of the group scores the attributes for each alternative and the group's ratings can be totaled or averaged.

Explore potential consequences. A MAU model can be used to further explore the consequences of changing the attributes, their weights, or the scores they received. Since the criteria

are open for all to see, it's possible to make any number of changes and review the results. For example, if it appears that some attribute is too important in determining the results, the weights can be adjusted to produce different results.

What are they good for?

Clear selection criteria. One of the most useful benefits of using a MAU model is that it makes clear to all involved the basis on which the alternatives are being evaluated. This is particularly important in group decision making situations in which many different points of view and decision alternatives have to be reviewed and taken into account.

Some limitations and considerations

Requires group consensus. MAU models are typically used in a group situation. To be effective there, the group must be able to come to consensus on the attributes in the model and on the rough range of weights to be used. Achieving this consensus may be very difficult and time consuming, or even impossible with some groups.

Conflicts often arise. The level of detail and specification necessary in the discussion of attributes and their weights can result in considerable conflict and contention, rather than the move toward consensus.