Such models are essential to properly manage the major software development outcomes (e.g., cost, schedule, quality) and to build up organizational knowledge.
Some categorizations are orthogonal, i.e., they address different dimensions of interest (e.g., severity vs. technical cause), so combining them results in categories that are not mutually exclusive.
So instead one must choose a set of discrete categories and devise mapping rules to convert the data consistently and coherently into the new categories.
So instead one must choose a set of discrete categories and devise mapping rules to convert the data consistently and coherently into the new categories.
Thus, some sort of mapping must be done to convert the data into a common format
that still preserves as much of the meaning of the original data as possible.
![[PukiWiki]](image/wadanyan.png "[PukiWiki]")
