Symptoms are observed when a process analysis is performed, whereby the processes are analyzed with the help of a base set of filters.
Example
For example, you inspect your global sales processes of the last year and you find that a disproportionately large number of customer complaints occur in your subsidiary in China compared to the rest of the world. You start a process analysis to find out the cause of this asymmetry. In addition to the filters that define the base set of your observation (here: sales processes, last year’s processes, and country) you specify the dimension value that you want an explanation for (here: complaints). This dimension value is called the symptom. PPM uses your settings to analyze all suitable dimensions for values with strikingly high or low numbers of occurrences in combination with the symptom. The result of the analysis is a table that lists all dimension values together with an estimate of how strongly this value affects the occurrence of the symptomatic value. This table may contain a row showing that complaints very often occur together with the value "PN4711" for the product dimension. The dimension value "PN4711" is called a root cause.
The following criteria can be used as symptoms.
The following criteria are not supported.
Supported dimensions
Variants are analyzed on combined and precise level independently.
Non-supported dimensions