Factors described by categories not numbers

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There are different kinds of factors: Those that are best described using numbers, e.g. numbers of clients, turnover, etc.. When you measure the influence of these factors, it is easy to say what influence from variations of factor input derives.

A car manufacturer compares different models, each with a top speed of X and a fuel consumption of Y.

There are factors which can not be described by numbers.

A radio station plays music of different styles. Each style contributes to the radio stations success in a different way.

Each style is a category which can be compared, identified as being equal or different. But it is difficult to establish a "distance" between styles as it is possible with different top speeds of different cars. As a surrogate, categorial factors often are transferred into numeric factors. The most prominent metric is money:

A company needs to hire a computer specialist. One candidate costs 60,000 a year, another expects 100,000 a year. A third expects 80,000 a year. Following this surrogate metric this candidates overall contribution to company success should be in between those first two candidates.

If metric factors are measured very precisely, different alternatives rarely show the same values. They are different so that the FACTORFINDER-Procedure runs into problems. It is based on comparisons, on stating identity or difference. As almost no values are identical, the analysis will bring no results. A solution could be establishing classes of values within a numeric factor. Classes can be compared like categories as being equal or different at different variants. We should keep in mind that this means loosing information when transfering metric factors into classes. Slight differences between alternatives assigned to one class are ignored and information is lost. Consequently, other instruments of analysis should be preferred when metric factors are evaluated. The FACTORFINDER-Procedure is aimed at categorial factors.
Ignoring the "distance" between different values is a drawback of the FACTORFINDER-Procedure. At the same time, it is an advantage: Other analytical procedures equal small variations of factor-input implicitly with small variations in output. That holds true in many cases but not always. It can be unjustified,

e.g. if a threshold price tag is reached and a small increase in price lets sales figures break down unproportionally.