Express Decision (ED) was designed with the goal of implementing Performance Evaluation Process (PEP) in order to support the decision-maker (DM) in making individual decisions, in which the alternatives derived from the available set are more preferable in situations of uncertainty. The distinctive feature of PEP is that the decision-maker is not required to formulate criteria for assessing outcomes in advance, as is the case with multi-criteria decision-making theories, and these criteria can be applied even unconsciously within the process of decision-making. When supporting an individual, ED uses only those criteria and sub-criteria that exist in any goal-directed decision-making under uncertainty. These two criteria, categorized into positive and negative outcomes, determine the decision-maker’s existing goal, while two sub-criteria, subjective importance (intensity) and subjective possibility (likelihood), are characterized by the uncertainty of the occurrence of an outcome. In this case, intensity is measured on a fuzzy verbal scale, from extremely weak to extremely strong, while likelihood is associated with the range of characteristics from extremely seldom to extremely often.
Performance Evaluation Process, supported by ED, allows to
The preference of each alternative is evaluated by measuring the intensity and likelihood of its positive and negative outcomes. ED uses these four characteristics (positive intensity and positive likelihood; negative intensity and negative likelihood) to determine the positive, negative, and global preference scores of the alternatives. If some characteristics of intensity or likelihood are so uncertain that DM cannot measure them, the alternative should be disaggregated with the use of DM into simpler problems for their further evaluation by the same four-characteristic- scheme. When the alternative is disaggregated to such an extent that all sub-problems can be positively evaluated (i.e. their intensities and likelihoods can be determined), the aggregation process can begin. As a result of aggregation, all positive and all negative preference scores of sub-problems will be combined into global positive and global negative preference scores of the alternative correspondingly. Note: the current version of ED does not yet support the aggregation process, so it should be performed manually.
During the decision-making stage, the alternatives are compared and ranked according to their preference scores, and a decision is made regarding selecting an alternative for execution. An alternative with a sufficient level of preference for execution is selected. A low level of preference can occur when the problem is too complicated or not significant enough. The specification of the goal and the addition of new alternatives make it possible to arrive at an acceptable solution. If both alternatives have a sufficiently high level of preference, but their preference levels are equal or very close to each other, then positive and negative preference levels should both be considered.
In the Personalization tab (next one to the right), you will need to specify an arbitrary set of options (alternatives) from which you hesitate to select the best one. In this tab you will only need to name them, so that later, in the Play tab, you will be able to distinguish them by name. Tabs can be clicked (tapped), or if you are working on a mobile device (phone, tablet, phablet, etc) you can also perform a swipe gesture to the left or to the right to switch tabs as necessary.
During the play phase you will need to think about each option as having its own pros (+) and cons (-), with a corresponding level of intensity and a likelihood of occurrence.
Both levels can be set by dragging corresponding slider handles. The value of each metric can be controlled by observing color of the slider handle as well as a label displayed on the top of the slider. The default value of the label is set to >>> to indicate that selection of intensity and likelihood has yet to be made.
As soon as intensity and likelihood are identified by the decision-maker, the positive, negative, and global preference scores will be determined, and the best option will be highlighted.
The options with undefined characteristics of intensity or/and likelihood should be divided into sub- problems to such a level of outcomes that it can be positively evaluated and then used to compound the particular level of preference for the alternative.