Subcritical factors

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Classifying variants into successful and unsuccessful ones is very strict. No levels of acceptability exist in between (at least not in this model). Intermediate levels of importance of the factors are supposed (important: the success criterion shows only two values - acceptable success and inacceptable success). As intermediate levels of relevance are granted relationships can be described that otherwise could not.
Critically important factors have to show specific values to turn alternatives into successful variants. Performance depends critically on those dimensions. Subcritically important dimensions must not show specific values to turn a variant successful. At the same time, the combination of the effect of several success-inhibiting values in different subcritically factors finally turns variants into failures. Irrelevant dimensions do not influence reaching the threshold of the target criterion. Arbitrary values can be observed in successful variants.
What makes dimensions critically important? The simpliest case: Only one variant can be observed as being of acceptable success. That can be demonstrated with an example from daily life:

A car usually is equipped with 4 wheels to provide mobility and one spare wheel. The spare wheel can replace each of the other 4 wheels. None of the 4 wheels is critically important for mobility. One alternative is using all of the original 4 wheels. Other alternatives are replacing each of the 4 wheels by the spare wheel. The multitude of alternative turns each of the 4 wheels replacable and less than critically important. As long there is a spare wheel, even with a broken wheel mobility is preserved.

If there is no spare wheel, each of the 4 wheels is critically important. The target criterion mobility critically depends on the function of each wheel as there is no other acceptable alternative.

If there is only one known alternative with acceptable success, there is no need to assign intermediate levels of relevance to each factor. Each dimension is critically important and each value appears ideal in respect to the target criterion. Of much more interest is the case of having several variants with acceptable success. If factors are critically important and acceptable variants show different values, all values of those important factors in the successful alternatives must be ideal values.
Acceptable variants may show one or more values in each dimension. Not every value must be ideal. As soon several values are observed than can be observed in successful variants, this indicates a high importance of the respective factor. Dimensions are considered being important if only specific values can be observed in conjunction with successful variants. Prerequisite and justification is having tested and observed a multitude of different values and that there are values that observed only in conjunction with inacceptable variants.
Ideal values in important factors facilitate goal-adverse values in subcritically important factors without turning them into failures in the beginning. On the opposite, there is little chance for success if ideal values are missed in important factors. There must be very few variants with identical non-ideal values at an important dimension. That is because the more important dimensions are

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the less acceptable variants exist with the same non-ideal value and

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the more of the other dimensions must show ideal values if the important factor shows a non-ideal value.

There are very few acceptable variants with non-ideal values in important dimensions. The more important a factor is the less other successful variants can be observed with the same non-ideal value and the more of the other factors must show ideal values. Otherwise the successful variants would be failures.
Each factor is more or less important. Importance means that values may not be arbitrary to secure success of a variant. Less important factors may show any value. Various values are tolerated. The theoretical extreme is an endless list of successful alternatives: That requires

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at least one dimension showing completely arbitrary values (zero relevance),

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at least one dimension showing endless many different values,

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gathering data would not consume any resources.