AN APPROACH TO IMPROVING EXISTING MEASUREMENT FRAMEWORKS

Software organizations are in need of methods for understanding, struc turing, and improving the data they are collecting. This paper discuss es an approach for use when a large number of diverse metrics are alre ady being collected by a software organization. The approach combines two methods. One looks at an organization's measurement framework in a top-down fashion and the other looks at it in a bottom-up fashion. Th e top-down method, based on the goal-question-metric (GQM) paradigm, i s used to identify the measurement goals of data users. These goals ar e then mapped to the metrics being used by the organization, allowing us to: (1) identify which metrics are and are not useful to the organi zation, and (2) determine whether the goals of data user groups can be satisfied by the data that are being collected by the organization. T he bottom-up method is based on a data mining technique called attribu te focusing (AF). Our method uses this technique to identify useful in formation in the data that the data users were not aware of. We descri be our experience in analyzing data from a software customer satisfact ion survey at IBM to illustrate how the AF technique can be combined w ith the GQM paradigm to improve measurement and data use inside softwa re organizations.