Traditional software metrics, such as code coverage, McCabe complexity, etc. address the needs of a software engineer. In contrast, managers of software development organizations face a broader set of issues. For example, an executive responsible for multiple products and releases has to understand the customer views of those products and put in place, appropriate actions across the products that will be of high business value. This paper presents examples of data and metrics associated with service (i.e. product support) for field reported problems and customer critical situations, and customer satisfaction ratings across a comprehensive range of software product attributes. Issues arising in the data integration, analysis, and correlation of these metrics are highlighted. A systematic methodology for statistical analysis of the data that enables management to derive key, actionable drivers of change through the metrics is presented. We also present an outline of a decision support system developed at IBM for tracking and using software metrics to enable executives to make better informed decisions in supporting their products.